last updated by Venus on April 20, 2021 06:00 PM on behalf of Ankur Sinha.
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in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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Correction to: Journal of Computational Neuroscience
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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The principle of constraint-induced therapy is widely practiced in rehabilitation. In hemiplegic cerebral palsy (CP) with impaired contralateral corticospinal projection due to unilateral injury, function improves after imposing a temporary constraint on limbs from the less affected hemisphere. This type of partially-reversible impairment in motor control by early brain injury bears a resemblance to the experience-dependent plastic acquisition and modification of neuronal response selectivity in the visual cortex. Previously, such mechanism was modeled within the framework of BCM (Bienenstock-Cooper-Munro) theory, a rate-based synaptic modification theory. Here, we demonstrate a minimally complex yet sufficient neural network model which provides a fundamental explanation for inter-hemispheric competition using a simplified spike-based model of information transmission and plasticity. We emulate the restoration of function in hemiplegic CP by simulating the competition between cells of the ipsilateral and contralateral corticospinal tracts. We use a high-speed hardware neural simulation to provide realistic numbers of spikes and realistic magnitudes of synaptic modification. We demonstrate that the phenomenon of constraint-induced partial reversal of hemiplegia can be modeled by simplified neural descending tracts with 2 layers of spiking neurons and synapses with spike-timing-dependent plasticity (STDP). We further demonstrate that persistent hemiplegia following unilateral cortical inactivation or deprivation is predicted by the STDP-based model but is inconsistent with BCM model. Although our model is a highly simplified and limited representation of the corticospinal system, it offers an explanation of how constraint as an intervention can help the system to escape from a suboptimal solution. This is a display of an emergent phenomenon from the synaptic competition.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats—two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out—thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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An important problem in systems neuroscience is to understand how information is communicated among brain regions, and it has been proposed that communication is mediated by neuronal oscillations, such as rhythms in the gamma band. We sought to investigate this idea by using a network model with two components, a source (sending) and a target (receiving) component, both built to resemble local populations in the cerebral cortex. To measure the effectiveness of communication, we used population-level correlations in spike times between the source and target. We found that after correcting for a response time that is independent of initial conditions, spike-time correlations between the source and target are significant, due in large measure to the alignment of firing events in their gamma rhythms. But, we also found that regular oscillations cannot produce the results observed in our model simulations of cortical neurons. Surprisingly, it is the irregularity of gamma rhythms, the absence of internal clocks, together with the malleability of these rhythms and their tendency to align with external pulses — features that are known to be present in gamma rhythms in the real cortex — that produced the results observed. These findings and the mechanistic explanations we offered are our primary results. Our secondary result is a mathematical relationship between correlations and the sizes of the samples used for their calculation. As improving technology enables recording simultaneously from increasing numbers of neurons, this relationship could be useful for interpreting results from experimental recordings.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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The authors find several printing errors in the equations in the final versions on line and in print proof. However, there were no such errors in the submitted proof.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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Excitatory synaptic signaling in cortical circuits is thought to be metabolically expensive. Two fundamental brain functions, learning and memory, are associated with long-term synaptic plasticity, but we know very little about energetics of these slow biophysical processes. This study investigates the energy requirement of information storing in plastic synapses for an extended version of BCM plasticity with a decay term, stochastic noise, and nonlinear dependence of neuron’s firing rate on synaptic current (adaptation). It is shown that synaptic weights in this model exhibit bistability. In order to analyze the system analytically, it is reduced to a simple dynamic mean-field for a population averaged plastic synaptic current. Next, using the concepts of nonequilibrium thermodynamics, we derive the energy rate (entropy production rate) for plastic synapses and a corresponding Fisher information for coding presynaptic input. That energy, which is of chemical origin, is primarily used for battling fluctuations in the synaptic weights and presynaptic firing rates, and it increases steeply with synaptic weights, and more uniformly though nonlinearly with presynaptic firing. At the onset of synaptic bistability, Fisher information and memory lifetime both increase sharply, by a few orders of magnitude, but the plasticity energy rate changes only mildly. This implies that a huge gain in the precision of stored information does not have to cost large amounts of metabolic energy, which suggests that synaptic information is not directly limited by energy consumption. Interestingly, for very weak synaptic noise, such a limit on synaptic coding accuracy is imposed instead by a derivative of the plasticity energy rate with respect to the mean presynaptic firing, and this relationship has a general character that is independent of the plasticity type. An estimate for primate neocortex reveals that a relative metabolic cost of BCM type synaptic plasticity, as a fraction of neuronal cost related to fast synaptic transmission and spiking, can vary from negligible to substantial, depending on the synaptic noise level and presynaptic firing.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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An inverse procedure is developed and tested to recover functional and structural information from global signals of brains activity. The method assumes a leaky-integrate and fire model with excitatory and inhibitory neurons, coupled via a directed network. Neurons are endowed with a heterogenous current value, which sets their associated dynamical regime. By making use of a heterogenous mean-field approximation, the method seeks to reconstructing from global activity patterns the distribution of in-coming degrees, for both excitatory and inhibitory neurons, as well as the distribution of the assigned currents. The proposed inverse scheme is first validated against synthetic data. Then, time-lapse acquisitions of a zebrafish larva recorded with a two-photon light sheet microscope are used as an input to the reconstruction algorithm. A power law distribution of the in-coming connectivity of the excitatory neurons is found. Local degree distributions are also computed by segmenting the whole brain in sub-regions traced from annotated atlas.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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Observations of finely-timed spike relationships in population recordings have been used to support partial reconstruction of neural microcircuit diagrams. In this approach, fine-timescale components of paired spike train interactions are isolated and subsequently attributed to synaptic parameters. Recent perturbation studies strengthen the case for such an inference, yet the complete set of measurements needed to calibrate statistical models is unavailable. To address this gap, we study features of pairwise spiking in a large-scale in vivo dataset where presynaptic neurons were explicitly decoupled from network activity by juxtacellular stimulation. We then construct biophysical models of paired spike trains to reproduce the observed phenomenology of in vivo monosynaptic interactions, including both fine-timescale spike-spike correlations and firing irregularity. A key characteristic of these models is that the paired neurons are coupled by rapidly-fluctuating background inputs. We quantify a monosynapse’s causal effect by comparing the postsynaptic train with its counterfactual, when the monosynapse is removed. Subsequently, we develop statistical techniques for estimating this causal effect from the pre- and post-synaptic spike trains. A particular focus is the justification and application of a nonparametric separation of timescale principle to implement synaptic inference. Using simulated data generated from the biophysical models, we characterize the regimes in which the estimators accurately identify the monosynaptic effect. A secondary goal is to initiate a critical exploration of neurostatistical assumptions in terms of biophysical mechanisms, particularly with regards to the challenging but arguably fundamental issue of fast, unobservable nonstationarities in background dynamics.
in Journal of Computational Neuroscience on May 01, 2021 12:00 AM.
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Publication date: Available online 19 April 2021
Source: Neural Networks
Author(s): Guanjun Li, Shan Liang, Shuai Nie, Wenju Liu, Zhanlei Yang
in Neural Networks on April 20, 2021 06:00 PM.
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in PNAS on April 20, 2021 03:09 PM.
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by Eric A. Chadwick, Takaya Suzuki, Michael G. George, David A. Romero, Cristina Amon, Thomas K. Waddell, Golnaz Karoubi, Aimy Bazylak
In this work, non-invasive high-spatial resolution three-dimensional (3D) X-ray micro-computed tomography (μCT) of healthy mouse lung vasculature is performed. Methodologies are presented for filtering, segmenting, and skeletonizing the collected 3D images. Novel methods for the removal of spurious branch artefacts from the skeletonized 3D image are introduced, and these novel methods involve a combination of distance transform gradients, diameter-length ratios, and the fast marching method (FMM). These new techniques of spurious branch removal result in the consistent removal of spurious branches without compromising the connectivity of the pulmonary circuit. Analysis of the filtered, skeletonized, and segmented 3D images is performed using a newly developed Vessel Network Extraction algorithm to fully characterize the morphology of the mouse pulmonary circuit. The removal of spurious branches from the skeletonized image results in an accurate representation of the pulmonary circuit with significantly less variability in vessel diameter and vessel length in each generation. The branching morphology of a full pulmonary circuit is characterized by the mean diameter per generation and number of vessels per generation. The methods presented in this paper lead to a significant improvement in the characterization of 3D vasculature imaging, allow for automatic separation of arteries and veins, and for the characterization of generations containing capillaries and intrapulmonary arteriovenous anastomoses (IPAVA).in PLoS Computational Biology on April 20, 2021 02:00 PM.
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by Michelle Wille, Jemma L. Geoghegan, Edward C. Holmes
Identifying the animal reservoirs from which zoonotic viruses will likely emerge is central to understanding the determinants of disease emergence. Accordingly, there has been an increase in studies attempting zoonotic “risk assessment.” Herein, we demonstrate that the virological data on which these analyses are conducted are incomplete, biased, and rapidly changing with ongoing virus discovery. Together, these shortcomings suggest that attempts to assess zoonotic risk using available virological data are likely to be inaccurate and largely only identify those host taxa that have been studied most extensively. We suggest that virus surveillance at the human–animal interface may be more productive.in PLoS Biology on April 20, 2021 02:00 PM.
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Author(s): Kevin R. Pilkiewicz and Michael L. Mayo
Establishing formal mathematical analogies between disparate physical systems can be a powerful tool, allowing for the well studied behavior of one system to be directly translated into predictions about the behavior of another that may be harder to probe. In this paper we lay the foundation for suc...
[Phys. Rev. E 103, 042417] Published Tue Apr 20, 2021
in Physical Review E: Biological physics on April 20, 2021 10:00 AM.
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The present pilot study examined to what extent the COVID-19 lockdown affected the behavioral and psychological symptoms of dementia (BPSD) in people with dementia and worsened their family caregivers’ distress. The associations between changes in the BPSD of relatives with dementia (RwD) and in their caregivers’ distress, and sense of social and emotional loneliness, and resilience were also investigated.
Materials and MethodsThirty-five caregivers of RwD attending formal healthcare services before the COVID-19 lockdown volunteered for the study, and were interviewed by phone during the lockdown. Caregivers completed the NeuroPsychiatric Inventory (NPI) to assess their care recipients’ BPSD and their own distress, and two questionnaires assessing their social and emotional loneliness, and their resilience.
ResultsNo clear changes emerged in either the BPSD of the RwD or the caregivers’ distress during lockdown compared with before the pandemic. Caregivers reporting more frequent and severe BPSD in their RwD before the lockdown scored higher on emotional loneliness. Those reporting more frequent and severe BPSD under lockdown, especially men and those taking care of RwD with more advanced dementia, scored higher on both social and emotional loneliness. A significant negative correlation also emerged between caregivers’ resilience and changes in their level of distress due to the lockdown, with female caregivers reporting greater resilience.
DiscussionOur findings offer preliminary insight on the effects of loneliness and resilience, and on the influence of individual characteristics on the experience and consequences of informal caregiving for RwD in times of restrictions imposed by a pandemic.
in Frontiers in Ageing Neuroscience on April 20, 2021 05:02 AM.
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In human vision objects and their parts can be visually recognized from purely spatial or purely temporal information but the mechanisms integrating space and time are poorly understood. Here we show that human visual recognition of objects and actions can be achieved by efficiently combining spatial and motion cues in configurations where each source on its own is insufficient for recognition. This analysis is obtained by identifying minimal videos: these are short and tiny video clips in which objects, parts, and actions can be reliably recognized, but any reduction in either space or time makes them unrecognizable. State-of-the-art deep networks for dynamic visual recognition cannot replicate human behavior in these configurations. This gap between humans and machines points to critical mechanisms in human dynamic vision that are lacking in current models.
in arXiv: Quantitative Biology: Neurons and Cognition on April 20, 2021 01:30 AM.
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We propose a neural model of multi-spin interacting system simulating neurons that interact each other through the surroundings. In such open system approach, we consider the neurons coupled with their surroundings including the axons connecting between neurons and the glial cells which distribute around the neurons. The surrounding environment is physically modeled as a collection of all kinds of vibrational modes. By solving the dynamics of neurons, we analyze the neural collective behavior. The action potential is taken into account for simulating the environmental effect from the surroundings, which mimics the neural firing mechanism. We find that this model can generate random neuron-neuron interactions and is proper to describe the process of information transmission in the nervous system. The physical meaning behind the scene can also be explained.
in arXiv: Quantitative Biology: Neurons and Cognition on April 20, 2021 01:30 AM.
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According to mechanistic theories of working memory (WM), information is retained as persistent spiking activity of cortical neural networks. Yet, how this activity is related to changes in the oscillatory profile observed during WM tasks remains an open issue. We explore joint effects of input gamma-band oscillations and noise on the dynamics of several firing rate models of WM. The considered models have a metastable active regime, i.e. they demonstrate long-lasting transient post-stimulus firing rate elevation. We start from a single excitatory-inhibitory circuit and demonstrate that either gamma-band or noise input could stabilize the active regime, thus supporting WM retention. We then consider a system of two circuits with excitatory intercoupling. We find that fast coupling allows for better stabilization by common noise compared to independent noise and stronger amplification of this effect by in-phase gamma inputs compared to anti-phase inputs. Finally, we consider a multi-circuit system comprised of two clusters, each containing a group of circuits receiving a common noise input and a group of circuits receiving independent noise. Each cluster is associated with its own local gamma generator, so all its circuits receive gamma-band input in the same phase. We find that gamma-band input differentially stabilizes the activity of the "common-noise" groups compared to the "independent-noise" groups. If the inter-cluster connections are fast, this effect is more pronounced when the gamma-band input is delivered to the clusters in the same phase rather than in the anti-phase. Assuming that the common noise comes from a large-scale distributed WM representation, our results demonstrate that local gamma oscillations can stabilize the activity of the corresponding parts of this representation, with stronger effect for fast long-range connections and synchronized gamma oscillations.
in arXiv: Quantitative Biology: Neurons and Cognition on April 20, 2021 01:30 AM.
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Stationarity of the constituents of the body and of its functionalities is a basic requirement for life, being equivalent to survival in first place. Assuming that the resting state activity of the brain serves essential functionalities, stationarity entails that the dynamics of the brain needs to be regulated on a time-averaged basis. The combination of recurrent and driving external inputs must therefore lead to a non-trivial stationary neural activity, a condition which is fulfilled for afferent signals of varying strengths only close to criticality. In this view, the benefits of working vicinity of a second-order phase transition, such as signal enhancements, are not the underlying evolutionary drivers, but side effects of the requirement to keep the brain functional in first place. It is hence more appropriate to use the term 'self-regulated' in this context, instead of 'self-organized'.
in arXiv: Quantitative Biology: Neurons and Cognition on April 20, 2021 01:30 AM.
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Early detection and quantification of tumour growth would help clinicians to prescribe more accurate treatments and provide better surgical planning. However, the multifactorial and heterogeneous nature of lung tumour progression hampers identification of growth patterns. In this study, we present a novel method based on a deep hierarchical generative and probabilistic framework that, according to radiological guidelines, predicts tumour growth, quantifies its size and provides a semantic appearance of the future nodule. Unlike previous deterministic solutions, the generative characteristic of our approach also allows us to estimate the uncertainty in the predictions, especially important for complex and doubtful cases. Results of evaluating this method on an independent test set reported a tumour growth balanced accuracy of 74%, a tumour growth size MAE of 1.77 mm and a tumour segmentation Dice score of 78%. These surpassed the performances of equivalent deterministic and alternative generative solutions (i.e. probabilistic U-Net, Bayesian test dropout and Pix2Pix GAN) confirming the suitability of our approach.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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A core challenge of evolutionary search is the need to balance between exploration of the search space and exploitation of highly fit regions. Quality-diversity search has explicitly walked this tightrope between a population's diversity and its quality. This paper extends a popular quality-diversity search algorithm, MAP-Elites, by treating the selection of parents as a multi-armed bandit problem. Using variations of the upper-confidence bound to select parents from under-explored but potentially rewarding areas of the search space can accelerate the discovery of new regions as well as improve its archive's total quality. The paper tests an indirect measure of quality for parent selection: the survival rate of a parent's offspring. Results show that maintaining a balance between exploration and exploitation leads to the most diverse and high-quality set of solutions in three different testbeds.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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This paper introduces ARCH-Elites, a MAP-Elites implementation that can reconfigure large-scale urban layouts at real-world locations via a pre-trained surrogate model instead of costly simulations. In a series of experiments, we generate novel urban designs for two real-world locations in Boston, Massachusetts. Combining the exploration of a possibility space with real-time performance evaluation creates a powerful new paradigm for architectural generative design that can extract and articulate design intelligence.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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Drawing inspiration from the philosophy of Yi Jing, Yin-Yang pair optimization (YYPO) has been shown to achieve competitive performance in single objective optimizations. Besides, it has the advantage of low time complexity when comparing to other population-based optimization. As a conceptual extension of YYPO, we proposed the novel Yi optimization (YI) algorithm as one of the best non-population-based optimizer. Incorporating both the harmony and reversal concept of Yi Jing, we replace the Yin-Yang pair with a Yi-point, in which we utilize the Levy flight to update the solution and balance both the effort of the exploration and the exploitation in the optimization process. As a conceptual prototype, we examine YI with IEEE CEC 2017 benchmark and compare its performance with a Levy flight-based optimizer CV1.0, the state-of-the-art dynamical Yin-Yang pair optimization in YYPO family and a few classical optimizers. According to the experimental results, YI shows highly competitive performance while keeping the low time complexity. Hence, the results of this work have implications for enhancing meta-heuristic optimizer using the philosophy of Yi Jing, which deserves research attention.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic the early stages of biological visual systems. In particular, it contains a pre-filtering step $\ell^0$ defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). The layer $\ell^0$ shows a rotational symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. The convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the profiles of simple cells in V1. We study the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the learned filters. We also examine the association fields induced by the learned kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connectivity. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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In this paper, we introduce a new approach based on distance fields to exactly impose boundary conditions in physics-informed deep neural networks. The challenges in satisfying Dirichlet boundary conditions in meshfree and particle methods are well-known. This issue is also pertinent in the development of physics informed neural networks (PINN) for the solution of partial differential equations. We introduce geometry-aware trial functions in artifical neural networks to improve the training in deep learning for partial differential equations. To this end, we use concepts from constructive solid geometry (R-functions) and generalized barycentric coordinates (mean value potential fields) to construct $\phi$, an approximate distance function to the boundary of a domain. To exactly impose homogeneous Dirichlet boundary conditions, the trial function is taken as $\phi$ multiplied by the PINN approximation, and its generalization via transfinite interpolation is used to a priori satisfy inhomogeneous Dirichlet (essential), Neumann (natural), and Robin boundary conditions on complex geometries. In doing so, we eliminate modeling error associated with the satisfaction of boundary conditions in a collocation method and ensure that kinematic admissibility is met pointwise in a Ritz method. We present numerical solutions for linear and nonlinear boundary-value problems over domains with affine and curved boundaries. Benchmark problems in 1D for linear elasticity, advection-diffusion, and beam bending; and in 2D for the Poisson equation, biharmonic equation, and the nonlinear Eikonal equation are considered. The approach extends to higher dimensions, and we showcase its use by solving a Poisson problem with homogeneneous Dirichlet boundary conditions over the 4D hypercube. This study provides a pathway for meshfree analysis to be conducted on the exact geometry without domain discretization.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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The current COVID-19 pandemic has shown us that we are still facing unpredictable challenges in our society. The necessary constrain on social interactions affected heavily how we envision and prepare the future of social robots and artificial agents in general. Adapting current affective perception models towards constrained perception based on the hard separation between facial perception and affective understanding would help us to provide robust systems. In this paper, we perform an in-depth analysis of how recognizing affect from persons with masks differs from general facial expression perception. We evaluate how the recently proposed FaceChannel adapts towards recognizing facial expressions from persons with masks. In Our analysis, we evaluate different training and fine-tuning schemes to understand better the impact of masked facial expressions. We also perform specific feature-level visualization to demonstrate how the inherent capabilities of the FaceChannel to learn and combine facial features change when in a constrained social interaction scenario.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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A challenging part of dynamic probabilistic risk assessment for nuclear power plants is the need for large amounts of temporal simulations given various initiating events and branching conditions from which representative feature extraction becomes complicated for subsequent applications. Artificial Intelligence techniques have been shown to be powerful tools in time-dependent sequential data processing to automatically extract and yield complex features from large data. An advanced temporal neural network referred to as the Transformer is used within a supervised learning fashion to model the time-dependent NPP simulation data and to infer whether a given sequence of events leads to core damage or not. The training and testing datasets for the Transformer are obtained by running 10,000 RELAP5-3D NPP blackout simulations with the list of variables obtained from the RAVEN software. Each simulation is classified as "OK" or "CORE DAMAGE" based on the consequence. The results show that the Transformer can learn the characteristics of the sequential data and yield promising performance with approximately 99% classification accuracy on the testing dataset.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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We combine two popular optimization approaches to derive learning algorithms for generative models: variational optimization and evolutionary algorithms. The combination is realized for generative models with discrete latents by using truncated posteriors as the family of variational distributions. The variational parameters of truncated posteriors are sets of latent states. By interpreting these states as genomes of individuals and by using the variational lower bound to define a fitness, we can apply evolutionary algorithms to realize the variational loop. The used variational distributions are very flexible and we show that evolutionary algorithms can effectively and efficiently optimize the variational bound. Furthermore, the variational loop is generally applicable ("black box") with no analytical derivations required. To show general applicability, we apply the approach to three generative models (we use noisy-OR Bayes Nets, Binary Sparse Coding, and Spike-and-Slab Sparse Coding). To demonstrate effectiveness and efficiency of the novel variational approach, we use the standard competitive benchmarks of image denoising and inpainting. The benchmarks allow quantitative comparisons to a wide range of methods including probabilistic approaches, deep deterministic and generative networks, and non-local image processing methods. In the category of "zero-shot" learning (when only the corrupted image is used for training), we observed the evolutionary variational algorithm to significantly improve the state-of-the-art in many benchmark settings. For one well-known inpainting benchmark, we also observed state-of-the-art performance across all categories of algorithms although we only train on the corrupted image. In general, our investigations highlight the importance of research on optimization methods for generative models to achieve performance improvements.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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We check the robustness of a recently proposed dynamical model of associative Pavlovian learning that extends the Rescorla-Wagner (RW) model in a natural way and predicts progressively damped oscillations in the response of the subjects. Using the data of two experiments, we compare the dynamical oscillatory model (DOM) with an oscillatory model made of the superposition of the RW learning curve and oscillations. Not only do data clearly show an oscillatory pattern, but they also favor the DOM over the added oscillation model, thus pointing out that these oscillations are the manifestation of an associative process. The latter is interpreted as the fact that subjects make predictions on trial outcomes more extended in time than in the RW model, but with more uncertainty.
in arXiv: Quantitative Biology: Neurons and Cognition on April 20, 2021 01:30 AM.
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This chapter collects several probabilistic tools that proved to be useful in the analysis of randomized search heuristics. This includes classic material like Markov, Chebyshev and Chernoff inequalities, but also lesser known topics like stochastic domination and coupling or Chernoff bounds for geometrically distributed random variables and for negatively correlated random variables. Most of the results presented here have appeared previously, some, however, only in recent conference publications. While the focus is on collecting tools for the analysis of randomized search heuristics, many of these may be useful as well in the analysis of classic randomized algorithms or discrete random structures.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 20, 2021 01:30 AM.
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Nature Photonics, Published online: 20 April 2021; doi:10.1038/s41566-021-00816-9
Author Correction: MINSTED fluorescence localization and nanoscopyin Nature Photomics on April 20, 2021 12:00 AM.
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Nature Photonics, Published online: 20 April 2021; doi:10.1038/s41566-021-00804-z
Optical acoustic sensors have gained interest for use in photoacoustic imaging systems, but can they dethrone conventional piezoelectric sensors altogether?in Nature Photomics on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22591-5
The authors here study the origin of seismic Love waves induced by ocean waves. The study finds Love waves to originate along steep bathymetry and underlying geological interfaces, particularly sedimentary basins, yielding spatio-temporal information about ocean-land coupling in deep water.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22560-y
Our understanding of the age-related molecular alterations in cancer is still limited. Here, the authors perform a pan-cancer analysis of age-associated genomic, transcriptomic, and epigenetic alterations, linking age-related gene expression changes to age-related DNA methylation alterationsin Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22544-y
The role of epigenetic deregulation in colorectal cancer (CRC) is not fully understood yet. Here the authors use patient-derived organoids, epigenomics and single-cell RNA-seq to reveal that YAP/TAZ are key regulators that bind to active enhancers in CRC and promote tumour survival.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22490-9
Pancreatic ductal adenocarcinoma has a collagen-rich dense extracellular matrix that promotes malignancy of cancer cells. Here, the authors show that fibrillar collagen that is cancer-cell-derived, but not stroma-derived, selectively restrains tumor growth under control of their pC-proteinase, BMP1.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22473-w
Intrinsic mechanical properties of sub-100 nm thin films are markedly difficult to obtain, yet an ever-growing necessity for emerging fields such as soft organic electronics. Here, the authors present a shear motion assisted transfer technique for fabricating free-standing sub-100 nm thin films and measuring their inherent structural–mechanical properties.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22467-8
The regulation of PD-L1 via proteasomal degradation is unclear. Here, the authors show that EGFR inhibition activates GSK3 α to promote PD-L1 phosphorylation, which leads to PD-L1 ubiquitination and proteasome mediated degradation by ARIH1 E3 ligase.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22431-6
The ventromedial hypothalamus regulates systemic glucose metabolism. Here the authors show that cytosolic phospholipase A2 mediated phospholipid metabolism contributes to this regulation in healthy animals but exert deteriorating effects on glucose homeostasis under high-fat-diet feeding.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22365-z
Dysregulation of synovial fibroblasts is thought to be an important step in the pathogenesis of rheumatoid arthritis. Here the authors implicate α2-6 sialylation in this process by studying the glycome of these cells in patients and in a mouse model of inflammatory joint disease.in Nature Communications on April 20, 2021 12:00 AM.
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Nature Communications, Published online: 20 April 2021; doi:10.1038/s41467-021-22354-2
Sleep dysregulation has been linked to dementia, but it is unknown whether sleep duration earlier in life is associated with dementia risk. Here, the authors show higher dementia risk associated with short sleep duration (six hours or less) in a longitudinal study of middle and older age adults.in Nature Communications on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01060-5
First powered flight on another planet opens the door for a new era of explorationin Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01029-4
Unpicking how cancer stem cells divide and spread could help to explain how tumours grow and evade treatments.in Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01028-5
Sharing COVID data? Check these recommendations and guidelinesin Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01027-6
China should track impact of pollution on health and the environmentin Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01026-7
China’s publications: fewer but betterin Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01025-8
Support Myanmar’s embattled scientists and studentsin Nature on April 20, 2021 12:00 AM.
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Nature, Published online: 20 April 2021; doi:10.1038/d41586-021-01020-z
Africa needs reliable energy infrastructure, not rich-world hypocrisy.in Nature on April 20, 2021 12:00 AM.
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The role of the cannabinoid receptor 2 (CNR2) is still poorly described in sensory epithelia. We found strong cnr2 expression in hair cells (HCs) of the inner ear and the lateral line (LL), a superficial sensory structure in fish. Next, we demonstrated that sensory synapses in HCs were severely perturbed in larvae lacking cnr2. Appearance and distribution of presynaptic ribbons and calcium channels (Cav1.3) were profoundly altered in mutant animals. Clustering of membrane-associated guanylate kinase (MAGUK) in post-synaptic densities (PSDs) was also heavily affected, suggesting a role for cnr2 for maintaining the sensory synapse. Furthermore, vesicular trafficking in HCs was strongly perturbed suggesting a retrograde action of the endocannabinoid system (ECs) via cnr2 that was modulating HC mechanotransduction. We found similar perturbations in retinal ribbon synapses. Finally, we showed that larval swimming behaviors after sound and light stimulations were significantly different in mutant animals. Thus, we propose that cnr2 is critical for the processing of sensory information in the developing larva.
in Frontiers in Molecular Neuroscience on April 20, 2021 12:00 AM.
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Stem cell scientists have developed methods for the self-formation of artificial organs, often referred to as organoids. Organoids can be used as model systems for research in multiple biological disciplines. Yoshiki Sasai’s innovation for deriving mammalian retinal tissue from in vitro stem cells has had a large impact on the study of the biology of vision. New developments in retinal organoid technology provide avenues for in vitro models of human retinal diseases, studies of pathological mechanisms, and development of therapies for retinal degeneration, including electronic retinal implants and gene therapy. Moreover, these innovations have played key roles in establishing models for large-scale drug screening, studying the stages of retinal development, and providing a human model for personalized therapeutic approaches, like cell transplants to replace degenerated retinal cells. Here, we first discuss the importance of human retinal organoids to the biomedical sciences. Then, we review various functional features of retinal organoids that have been developed. Finally, we highlight the current limitations of retinal organoid technologies.
in Frontiers in Neuroscience: Neurodegeneration on April 20, 2021 12:00 AM.
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The adult mammalian brain contains distinct neurogenic niches harboring populations of neural stem cells (NSCs) with the capacity to sustain the generation of specific subtypes of neurons during the lifetime. However, their ability to produce new progeny declines with age. The microenvironment of these specialized niches provides multiple cellular and molecular signals that condition NSC behavior and potential. Among the different niche components, vasculature has gained increasing interest over the years due to its undeniable role in NSC regulation and its therapeutic potential for neurogenesis enhancement. NSCs are uniquely positioned to receive both locally secreted factors and adhesion-mediated signals derived from vascular elements. Furthermore, studies of parabiosis indicate that NSCs are also exposed to blood-borne factors, sensing and responding to the systemic circulation. Both structural and functional alterations occur in vasculature with age at the cellular level that can affect the proper extrinsic regulation of NSCs. Additionally, blood exchange experiments in heterochronic parabionts have revealed that age-associated changes in blood composition also contribute to adult neurogenesis impairment in the elderly. Although the mechanisms of vascular- or blood-derived signaling in aging are still not fully understood, a general feature of organismal aging is the accumulation of senescent cells, which act as sources of inflammatory and other detrimental signals that can negatively impact on neighboring cells. This review focuses on the interactions between vascular senescence, circulating pro-senescence factors and the decrease in NSC potential during aging. Understanding the mechanisms of NSC dynamics in the aging brain could lead to new therapeutic approaches, potentially include senolysis, to target age-dependent brain decline.
in Frontiers in Neuroscience: Neurodegeneration on April 20, 2021 12:00 AM.
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To explore the association between lipoprotein-related phospholipase A2 (Lp-PLA2) and the risk of Parkinson’s disease (PD).
MethodsA case-control study involving 58 hospitalized PD patients and 60 healthy controls was carried out. Serum Lp-PLA2 level was detected. According to the disease course and severity, PD patients were subdivided to analyze the clinical value of Lp-PLA2. Relationship between Lp-PLA2 and PD risk was analyzed by logistic regression. Diagnostic value of Lp-PLA2 in PD patients was investigated using receiver’s operator characteristic curves.
ResultsLp-PLA2 level was significantly higher in the PD patients compared with the controls, and was significantly and positively correlated with the Hoehn-Yahr (H&Y) stage. The serum Lp-PLA2 level and H&Y stage of PD patients with a longer disease course were significantly higher than those with a shorter disease course. PD patients with milder conditions had significantly lower serum Lp-PLA2 levels than patients with severe conditions. Multivariable logistic regression analysis indicated higher Lp-PLA2 level was an independent risk factor of PD patients. Moreover, the area under the curve for Lp-PLA2 was 0.703, which was between those of homocysteine and serum amylase A.
ConclusionTo our knowledge, this is the first study to show that increased level of Lp-PLA2 is associated with the risk of PD. Lp-PLA2 may be used for early detection of PD, and provides an effective intervention target for clinical treatment of PD.
in Frontiers in Neuroscience: Neurodegeneration on April 20, 2021 12:00 AM.
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Voxel-wise group analysis is presented as a novel feature selection (FS) technique for a deep learning (DL) approach to brain imaging data classification. The method, based on a voxel-wise two-sample t-test and denoted as t-masking, is integrated into the learning procedure as a data-driven FS strategy. t-Masking has been introduced in a convolutional neural network (CNN) for the test bench of binary classification of very-mild Alzheimer’s disease vs. normal control, using a structural magnetic resonance imaging dataset of 180 subjects. To better characterize the t-masking impact on CNN classification performance, six different experimental configurations were designed. Moreover, the performances of the presented FS method were compared to those of similar machine learning (ML) models that relied on different FS approaches. Overall, our results show an enhancement of about 6% in performance when t-masking was applied. Moreover, the reported performance enhancement was higher with respect to similar FS-based ML models. In addition, evaluation of the impact of t-masking on various selection rates has been provided, serving as a useful characterization for future insights. The proposed approach is also highly generalizable to other DL architectures, neuroimaging modalities, and brain pathologies.
in Frontiers in Neuroscience: Brain Imaging Methods on April 20, 2021 12:00 AM.
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Adolescence has been linked to an enhanced tolerance of uncertainty and risky behavior and is possibly connected to an increased response toward rewards. However, previous research has produced inconsistent findings. To investigate whether these findings are due to different reward probabilities used in the experimental design, we extended a monetary incentive delay (MID) task by including three different reward probabilities. Using functional magnetic resonance imaging, 25 healthy adolescents and 22 adults were studied during anticipation of rewards in the VS. Differently colored cue stimuli indicated either a monetary or verbal trial and symbolized different reward probabilities, to which the participants were blinded. Results demonstrated faster reaction times for lower reward probabilities (33%) in both age groups. Adolescents were slower through all conditions and had less activation on a neural level. Imaging results showed a three-way interaction between age group x condition x reward probability with differences in percent signal change between adolescents and adults for the high reward probabilities (66%, 88%) while adolescents demonstrated differences for the lowest (33%). Therefore, previous inconsistent findings could be due to different reward probabilities, which makes examining these crucial for a better understanding of adolescent and adult behavior.
in Frontiers in Human Neuroscience on April 20, 2021 12:00 AM.
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Stroke continues to be a leading cause of disability. Basic neurorehabilitation research is necessary to inform the neuropathophysiology of impaired motor control, and to develop targeted interventions with potential to remediate disability post-stroke. Despite knowledge gained from basic research studies, the effectiveness of research-based interventions for reducing motor impairment has been no greater than standard of practice interventions. In this perspective, we offer suggestions for overcoming translational barriers integral to experimental design, to augment traditional protocols, and re-route the rehabilitation trajectory toward recovery and away from compensation. First, we suggest that researchers consider modifying task practice schedules to focus on key aspects of movement quality, while minimizing the appearance of compensatory behaviors. Second, we suggest that researchers supplement primary outcome measures with secondary measures that capture emerging maladaptive compensations at other segments or joints. Third, we offer suggestions about how to maximize participant engagement, self-direction, and motivation, by embedding the task into a meaningful context, a strategy more likely to enable goal-action coupling, associated with improved neuro-motor control and learning. Finally, we remind the reader that motor impairment post-stroke is a multidimensional problem that involves central and peripheral sensorimotor systems, likely influenced by chronicity of stroke. Thus, stroke chronicity should be given special consideration for both participant recruitment and subsequent data analyses. We hope that future research endeavors will consider these suggestions in the design of the next generation of intervention studies in neurorehabilitation, to improve translation of research advances to improved participation and quality of life for stroke survivors.
in Frontiers in Human Neuroscience on April 20, 2021 12:00 AM.
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Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex–subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.
in Frontiers in Human Neuroscience on April 20, 2021 12:00 AM.
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Despite that it is commonly accepted that migraine is a disorder of the nervous system with a prominent genetic basis, it is comorbid with a plethora of medical conditions. Several studies have found bidirectional comorbidity between migraine and different disorders including neurological, psychiatric, cardio- and cerebrovascular, gastrointestinal, metaboloendocrine, and immunological conditions. Each of these has its own genetic load and shares some common characteristics with migraine. The bidirectional mechanisms that are likely to underlie this extensive comorbidity between migraine and other diseases are manifold. Comorbid pathologies can induce and promote thalamocortical network dysexcitability, multi-organ transient or persistent pro-inflammatory state, and disproportionate energetic needs in a variable combination, which in turn may be causative mechanisms of the activation of an ample defensive system with includes the trigeminovascular system in conjunction with the neuroendocrine hypothalamic system. This strategy is designed to maintain brain homeostasis by regulating homeostatic needs, such as normal subcortico-cortical excitability, energy balance, osmoregulation, and emotional response. In this light, the treatment of migraine should always involves a multidisciplinary approach, aimed at identifying and, if necessary, eliminating possible risk and comorbidity factors.
in Frontiers in Human Neuroscience on April 20, 2021 12:00 AM.
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In the nervous system synaptic input arrives chiefly on dendrites and their type and distribution have been assumed pivotal in signal integration. We have developed an immunohistochemistry (IH)-correlated electron microscopy (EM) method – the “mirror” technique – by which synaptic input to entire dendrites of neurochemically identified interneurons (INs) can be mapped due preserving high-fidelity tissue ultrastructure. Hence, this approach allows quantitative assessment of morphometric parameters of synaptic inputs along the whole length of dendrites originating from the parent soma. The method exploits the fact that adjoining sections have truncated or cut cell bodies which appear on the common surfaces in a mirror fashion. In one of the sections the histochemical marker of the GABAergic subtype, calbindin was revealed in cell bodies whereas in the other section the remaining part of the very same cell bodies were subjected to serial section EM to trace and reconstruct the synaptology of entire dendrites. Here, we provide exemplary data on the synaptic coverage of two dendrites belonging to the same calbindin-D28K immunopositive IN and determine the spatial distribution of asymmetric and symmetric synapses, surface area and volume of the presynaptic boutons, morphometric parameters of synaptic vesicles, and area extent of the active zones.
in Frontiers in Neuroanatomy on April 20, 2021 12:00 AM.
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Background: Family caregivers of patients with dementia are at high risk of stress and burden, and quarantine due to the coronavirus disease 2019 (COVID-19) pandemic may have increased the risk of psychological disturbances in this population. The current study was carried out during the national lockdown declared in March 2020 by the Italian government as a containment measure of the first wave of the coronavirus pandemic and is the first nationwide survey on the impact of COVID-19 lockdown on the mental health of dementia informal caregivers.
Methods: Eighty-seven dementia centers evenly distributed on the Italian territory enrolled 4,710 caregiver–patient pairs. Caregivers underwent a telephone interview assessing classical symptoms of caregiver stress and concern for the consequences of COVID-19 infection on patient’s health. We calculated prevalence of symptoms and regressed them on various potential stress risk factors: caregivers’ sociodemographic characteristics and lifestyle, patients’ clinical features, and lockdown-related elements, like discontinuity in medical care.
Results: Approximately 90% of caregivers reported at least one symptom of stress, and nearly 30% reported four or more symptoms. The most prevalent symptoms were concern for consequences of COVID-19 on patient’s health (75%) and anxiety (46%). The main risk factors for stress were identified as a conflicting relationship with the patient and discontinuity in assistance, but caregiver’s female sex, younger age, lower education, and cohabitation with the patient also had an impact. Availability of help from institutions or private individuals showed a protective effect against sense of abandonment but a detrimental effect on concern about the risk for the patient to contract COVID-19. The only protective factor was mild dementia severity, which was associated with a lower risk of feeling isolated and abandoned; type of dementia, on the other hand, did not affect stress risk.
Conclusion: Our results demonstrate the large prevalence of stress in family caregivers of patients with dementia during the COVID-19 pandemic and have identified both caregivers and situations at a higher risk of stress, which should be taken into account in the planning of interventions in support of quarantined families and patients.
in Frontiers in Ageing Neuroscience on April 20, 2021 12:00 AM.
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It is difficult to differentiate between Parkinson's disease and multiple system atrophy parkinsonian subtype (MSA-P) because of the overlap of their signs and symptoms. Enormous efforts have been made to develop positron emission tomography (PET) imaging to differentiate these diseases. This study aimed to investigate the co-registration analysis of 18F-fluorodopa and 18F-flurodeoxyglucose PET images to visualize the difference between Parkinson's disease and MSA-P. We enrolled 29 Parkinson's disease patients, 28 MSA-P patients, and 10 healthy controls, who underwent both 18F-fluorodopa and 18F-flurodeoxyglucose PET scans. Patients with Parkinson's disease and MSA-P exhibited reduced bilateral striatal 18F-fluorodopa uptake (p < 0.05, vs. healthy controls). Both regional specific uptake ratio analysis and statistical parametric mapping analysis of 18F-flurodeoxyglucose PET revealed hypometabolism in the bilateral putamen of MSA-P patients and hypermetabolism in the bilateral putamen of Parkinson's disease patients. There was a significant positive correlation between 18F-flurodeoxyglucose uptake and 18F-fluorodopa uptake in the contralateral posterior putamen of MSA-P patients (rs = 0.558, p = 0.002). Both 18F-flurodeoxyglucose and 18F-fluorodopa PET images showed that the striatum was rabbit-shaped in the healthy control group segmentation analysis. A defective rabbit-shaped striatum was observed in the 18F-fluorodopa PET image of patients with Parkinson's disease and MSA-P. In the segmentation analysis of 18F-flurodeoxyglucose PET image, an intact rabbit-shaped striatum was observed in Parkinson's disease patients, whereas a defective rabbit-shaped striatum was observed in MSA-P patients. These findings suggest that there were significant differences in the co-registration analysis of 18F-flurodeoxyglucose and 18F-fluorodopa PET images, which could be used in the individual analysis to differentiate Parkinson's disease from MSA-P.
in Frontiers in Ageing Neuroscience on April 20, 2021 12:00 AM.
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The risk of recurrent stroke following a minor stroke or transient ischemic attack (TIA) is high, when inflammation might play an important role. We aimed to evaluate the value of neutrophil to lymphocyte ratio (NLR) in predicting composite cardiovascular events in patients with minor stroke and TIA.
MethodsConsecutive patients with acute minor stroke or TIA admitted within 24 h of symptoms onset during a 5-year period in a prospective stroke registry were analyzed. We calculated the NLR dividing absolute neutrophil count by absolute lymphocyte count tested within 24 h of admission. NLR ≥4th quartile was defined as high NLR. A composite outcome was defined as stroke, acute coronary syndrome or vascular death within 1 year. We investigated associations between NLR and the composite outcome in univariate and multivariate analyses, among all patients and in those aged over 60 years (i.e., older patients).
ResultsOverall, 841 patients (median age 68 years; 60.4% males) were recruited. No significant independent association was found between NLR and the composite outcome in multivariate analysis in the overall cohort. Among the 612 older patients (median age 73 years; 59.2% males), the median NLR was 2.76 (interquartile range 1.96−4.00) and 148 (24.2%) patients had high NLR. The composite outcome occurred in 77 (12.6%) older patients, who were more likely to have a high NLR (39.0% versus 22.1%; p = 0.001) than those without a composite outcome. In multivariate logistic regression, high NLR (adjusted odds ratio 2.00; 95% confidence interval 1.07−3.75; p = 0.031) was independently associated with the composite outcome in older patients.
ConclusionIn older (aged ≥60 years) patients with acute minor stroke or TIA, a higher NLR, a marker of systemic inflammation that can be easily obtained in routine blood tests, is an independent predictor of subsequent cardiovascular events.
in Frontiers in Ageing Neuroscience on April 20, 2021 12:00 AM.
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This study screened potential fluid biomarkers and developed a prediction model based on the easily obtained information at initial inspection to identify ataxia patients more likely to have multiple system atrophy-cerebellar type (MSA-C).
MethodsWe established a retrospective cohort with 125 ataxia patients from southwest China between April 2018 and June 2020. Demographic and laboratory variables obtained at the time of hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression to construct a diagnosis score. The receiver operating characteristic (ROC) and decision curve analyses were performed to assess the accuracy and net benefit of the model. Also, independent validation using 25 additional ataxia patients was carried out to verify the model efficiency. Then the model was translated into a visual and operable web application using the R studio and Shiny package.
ResultsFrom 47 indicators, five variables were selected and integrated into the prediction model, including the age of onset (AO), direct bilirubin (DBIL), aspartate aminotransferase (AST), eGFR, and synuclein-alpha. The prediction model exhibited an area under the curve (AUC) of 0.929 for the training cohort and an AUC of 0.917 for the testing cohort. The decision curve analysis (DCA) plot displayed a good net benefit for this model, and external validation confirmed its reliability. The model also was translated into a web application that is freely available to the public.
ConclusionThe prediction model that was developed based on laboratory and demographic variables obtained from ataxia patients at admission to the hospital might help improve the ability to differentiate MSA-C from spinocerebellar ataxia clinically.
in Frontiers in Ageing Neuroscience on April 20, 2021 12:00 AM.
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in eLife on April 20, 2021 12:00 AM.
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Publication date: Available online 18 April 2021
Source: Neural Networks
Author(s): Chengdai Huang, Juan Wang, Xiaoping Chen, Jinde Cao
in Neural Networks on April 19, 2021 06:00 PM.
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Publication date: Available online 18 April 2021
Source: Neural Networks
Author(s): Shuchen Wu, Xiaodi Li, Yanhui Ding
in Neural Networks on April 19, 2021 06:00 PM.
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in Annals of Neurology on April 19, 2021 02:36 PM.
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by Yao Jiang, Hui-Fang Liu, Rong Liu
The binding affinities of protein-nucleic acid interactions could be altered due to missense mutations occurring in DNA- or RNA-binding proteins, therefore resulting in various diseases. Unfortunately, a systematic comparison and prediction of the effects of mutations on protein-DNA and protein-RNA interactions (these two mutation classes are termed MPDs and MPRs, respectively) is still lacking. Here, we demonstrated that these two classes of mutations could generate similar or different tendencies for binding free energy changes in terms of the properties of mutated residues. We then developed regression algorithms separately for MPDs and MPRs by introducing novel geometric partition-based energy features and interface-based structural features. Through feature selection and ensemble learning, similar computational frameworks that integrated energy- and nonenergy-based models were established to estimate the binding affinity changes resulting from MPDs and MPRs, but the selected features for the final models were different and therefore reflected the specificity of these two mutation classes. Furthermore, the proposed methodology was extended to the identification of mutations that significantly decreased the binding affinities. Extensive validations indicated that our algorithm generally performed better than the state-of-the-art methods on both the regression and classification tasks. The webserver and software are freely available at http://liulab.hzau.edu.cn/PEMPNI and https://github.com/hzau-liulab/PEMPNI.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by James H. Joly, Brandon T. L. Chew, Nicholas A. Graham
The metabolic reprogramming of cancer cells creates metabolic vulnerabilities that can be therapeutically targeted. However, our understanding of metabolic dependencies and the pathway crosstalk that creates these vulnerabilities in cancer cells remains incomplete. Here, by integrating gene expression data with genetic loss-of-function and pharmacological screening data from hundreds of cancer cell lines, we identified metabolic vulnerabilities at the level of pathways rather than individual genes. This approach revealed that metabolic pathway dependencies are highly context-specific such that cancer cells are vulnerable to inhibition of one metabolic pathway only when activity of another metabolic pathway is altered. Notably, we also found that the no single metabolic pathway was universally essential, suggesting that cancer cells are not invariably dependent on any metabolic pathway. In addition, we confirmed that cell culture medium is a major confounding factor for the analysis of metabolic pathway vulnerabilities. Nevertheless, we found robust associations between metabolic pathway activity and sensitivity to clinically approved drugs that were independent of cell culture medium. Lastly, we used parallel integration of pharmacological and genetic dependency data to confidently identify metabolic pathway vulnerabilities. Taken together, this study serves as a comprehensive characterization of the landscape of metabolic pathway vulnerabilities in cancer cell lines.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by Rohan N. Shah, Alexander J. Ruthenburg
Next-generation sequencing (NGS) has transformed molecular biology and contributed to many seminal insights into genomic regulation and function. Apart from whole-genome sequencing, an NGS workflow involves alignment of the sequencing reads to the genome of study, after which the resulting alignments can be used for downstream analyses. However, alignment is complicated by the repetitive sequences; many reads align to more than one genomic locus, with 15–30% of the genome not being uniquely mappable by short-read NGS. This problem is typically addressed by discarding reads that do not uniquely map to the genome, but this practice can lead to systematic distortion of the data. Previous studies that developed methods for handling ambiguously mapped reads were often of limited applicability or were computationally intensive, hindering their broader usage. In this work, we present SmartMap: an algorithm that augments industry-standard aligners to enable usage of ambiguously mapped reads by assigning weights to each alignment with Bayesian analysis of the read distribution and alignment quality. SmartMap is computationally efficient, utilizing far fewer weighting iterations than previously thought necessary to process alignments and, as such, analyzing more than a billion alignments of NGS reads in approximately one hour on a desktop PC. By applying SmartMap to peak-type NGS data, including MNase-seq, ChIP-seq, and ATAC-seq in three organisms, we can increase read depth by up to 53% and increase the mapped proportion of the genome by up to 18% compared to analyses utilizing only uniquely mapped reads. We further show that SmartMap enables the analysis of more than 140,000 repetitive elements that could not be analyzed by traditional ChIP-seq workflows, and we utilize this method to gain insight into the epigenetic regulation of different classes of repetitive elements. These data emphasize both the dangers of discarding ambiguously mapped reads and their power for driving biological discovery.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by Alex Baranski, Idan Milo, Shirley Greenbaum, John-Paul Oliveria, Dunja Mrdjen, Michael Angelo, Leeat Keren
Mass Based Imaging (MBI) technologies such as Multiplexed Ion Beam Imaging by time of flight (MIBI-TOF) and Imaging Mass Cytometry (IMC) allow for the simultaneous measurement of the expression levels of 40 or more proteins in biological tissue, providing insight into cellular phenotypes and organization in situ. Imaging artifacts, resulting from the sample, assay or instrumentation complicate downstream analyses and require correction by domain experts. Here, we present MBI Analysis User Interface (MAUI), a series of graphical user interfaces that facilitate this data pre-processing, including the removal of channel crosstalk, noise and antibody aggregates. Our software streamlines these steps and accelerates processing by enabling real-time and interactive parameter tuning across multiple images.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by Benjamin Deneu, Maximilien Servajean, Pierre Bonnet, Christophe Botella, François Munoz, Alexis Joly
Convolutional Neural Networks (CNNs) are statistical models suited for learning complex visual patterns. In the context of Species Distribution Models (SDM) and in line with predictions of landscape ecology and island biogeography, CNN could grasp how local landscape structure affects prediction of species occurrence in SDMs. The prediction can thus reflect the signatures of entangled ecological processes. Although previous machine-learning based SDMs can learn complex influences of environmental predictors, they cannot acknowledge the influence of environmental structure in local landscapes (hence denoted “punctual models”). In this study, we applied CNNs to a large dataset of plant occurrences in France (GBIF), on a large taxonomical scale, to predict ranked relative probability of species (by joint learning) to any geographical position. We examined the way local environmental landscapes improve prediction by performing alternative CNN models deprived of information on landscape heterogeneity and structure (“ablation experiments”). We found that the landscape structure around location crucially contributed to improve predictive performance of CNN-SDMs. CNN models can classify the predicted distributions of many species, as other joint modelling approaches, but they further prove efficient in identifying the influence of local environmental landscapes. CNN can then represent signatures of spatially structured environmental drivers. The prediction gain is noticeable for rare species, which open promising perspectives for biodiversity monitoring and conservation strategies. Therefore, the approach is of both theoretical and practical interest. We discuss the way to test hypotheses on the patterns learnt by CNN, which should be essential for further interpretation of the ecological processes at play.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by Tsuyoshi Ikegami, Gowrishankar Ganesh, Tricia L. Gibo, Toshinori Yoshioka, Rieko Osu, Mitsuo Kawato
Humans have the amazing ability to learn the dynamics of the body and environment to develop motor skills. Traditional motor studies using arm reaching paradigms have viewed this ability as the process of ‘internal model adaptation’. However, the behaviors have not been fully explored in the case when reaches fail to attain the intended target. Here we examined human reaching under two force fields types; one that induces failures (i.e., target errors), and the other that does not. Our results show the presence of a distinct failure-driven adaptation process that enables quick task success after failures, and before completion of internal model adaptation, but that can result in persistent changes to the undisturbed trajectory. These behaviors can be explained by considering a hierarchical interaction between internal model adaptation and the failure-driven adaptation of reach direction. Our findings suggest that movement failure is negotiated using hierarchical motor adaptations by humans.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by David P. Shorten, Richard E. Spinney, Joseph T. Lizier
Transfer entropy (TE) is a widely used measure of directed information flows in a number of domains including neuroscience. Many real-world time series for which we are interested in information flows come in the form of (near) instantaneous events occurring over time. Examples include the spiking of biological neurons, trades on stock markets and posts to social media, amongst myriad other systems involving events in continuous time throughout the natural and social sciences. However, there exist severe limitations to the current approach to TE estimation on such event-based data via discretising the time series into time bins: it is not consistent, has high bias, converges slowly and cannot simultaneously capture relationships that occur with very fine time precision as well as those that occur over long time intervals. Building on recent work which derived a theoretical framework for TE in continuous time, we present an estimation framework for TE on event-based data and develop a k-nearest-neighbours estimator within this framework. This estimator is provably consistent, has favourable bias properties and converges orders of magnitude more quickly than the current state-of-the-art in discrete-time estimation on synthetic examples. We demonstrate failures of the traditionally-used source-time-shift method for null surrogate generation. In order to overcome these failures, we develop a local permutation scheme for generating surrogate time series conforming to the appropriate null hypothesis in order to test for the statistical significance of the TE and, as such, test for the conditional independence between the history of one point process and the updates of another. Our approach is shown to be capable of correctly rejecting or accepting the null hypothesis of conditional independence even in the presence of strong pairwise time-directed correlations. This capacity to accurately test for conditional independence is further demonstrated on models of a spiking neural circuit inspired by the pyloric circuit of the crustacean stomatogastric ganglion, succeeding where previous related estimators have failed.in PLoS Computational Biology on April 19, 2021 02:00 PM.
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by Jelke J. Fros, Imke Visser, Bing Tang, Kexin Yan, Eri Nakayama, Tessa M. Visser, Constantianus J. M. Koenraadt, Monique M. van Oers, Gorben P. Pijlman, Andreas Suhrbier, Peter Simmonds
Most vertebrate RNA viruses show pervasive suppression of CpG and UpA dinucleotides, closely resembling the dinucleotide composition of host cell transcriptomes. In contrast, CpG suppression is absent in both invertebrate mRNA and RNA viruses that exclusively infect arthropods. Arthropod-borne (arbo) viruses are transmitted between vertebrate hosts by invertebrate vectors and thus encounter potentially conflicting evolutionary pressures in the different cytoplasmic environments. Using a newly developed Zika virus (ZIKV) model, we have investigated how demands for CpG suppression in vertebrate cells can be reconciled with potentially quite different compositional requirements in invertebrates and how this affects ZIKV replication and transmission. Mutant viruses with synonymously elevated CpG or UpA dinucleotide frequencies showed attenuated replication in vertebrate cell lines, which was rescued by knockout of the zinc-finger antiviral protein (ZAP). Conversely, in mosquito cells, ZIKV mutants with elevated CpG dinucleotide frequencies showed substantially enhanced replication compared to wild type. Host-driven effects on virus replication attenuation and enhancement were even more apparent in mouse and mosquito models. Infections with CpG- or UpA-high ZIKV mutants in mice did not cause typical ZIKV-induced tissue damage and completely protected mice during subsequent challenge with wild-type virus, which demonstrates their potential as live-attenuated vaccines. In contrast, the CpG-high mutants displayed enhanced replication in Aedes aegypti mosquitoes and a larger proportion of mosquitoes carried infectious virus in their saliva. These findings show that mosquito cells are also capable of discriminating RNA based on dinucleotide composition. However, the evolutionary pressure on the CpG dinucleotides of viral genomes in arthropod vectors directly opposes the pressure present in vertebrate host cells, which provides evidence that an adaptive compromise is required for arbovirus transmission. This suggests that the genome composition of arbo flaviviruses is crucial to maintain the balance between high-level replication in the vertebrate host and persistent replication in the mosquito vector.in PLoS Biology on April 19, 2021 02:00 PM.
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by Sylvie Manuse, Yue Shan, Silvia J. Canas-Duarte, Somenath Bakshi, Wei-Sheng Sun, Hirotada Mori, Johan Paulsson, Kim Lewis
Persisters represent a small subpopulation of non- or slow-growing bacterial cells that are tolerant to killing by antibiotics. Despite their prominent role in the recalcitrance of chronic infections to antibiotic therapy, the mechanism of their formation has remained elusive. We show that sorted cells of Escherichia coli with low levels of energy-generating enzymes are better able to survive antibiotic killing. Using microfluidics time-lapse microscopy and a fluorescent reporter for in vivo ATP measurements, we find that a subpopulation of cells with a low level of ATP survives killing by ampicillin. We propose that these low ATP cells are formed stochastically as a result of fluctuations in the abundance of energy-generating components. These findings point to a general “low energy” mechanism of persister formation.in PLoS Biology on April 19, 2021 02:00 PM.
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by Abigail Leavitt LaBella, Dana A. Opulente, Jacob L. Steenwyk, Chris Todd Hittinger, Antonis Rokas
Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter—species that have yet to be cultured in the lab or have only been identified by genomic material.in PLoS Biology on April 19, 2021 02:00 PM.
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by Christiaan H. Vinkers, Herm J. Lamberink, Joeri K. Tijdink, Pauline Heus, Lex Bouter, Paul Glasziou, David Moher, Johanna A. Damen, Lotty Hooft, Willem M. Otte
Many randomized controlled trials (RCTs) are biased and difficult to reproduce due to methodological flaws and poor reporting. There is increasing attention for responsible research practices and implementation of reporting guidelines, but whether these efforts have improved the methodological quality of RCTs (e.g., lower risk of bias) is unknown. We, therefore, mapped risk-of-bias trends over time in RCT publications in relation to journal and author characteristics. Meta-information of 176,620 RCTs published between 1966 and 2018 was extracted. The risk-of-bias probability (random sequence generation, allocation concealment, blinding of patients/personnel, and blinding of outcome assessment) was assessed using a risk-of-bias machine learning tool. This tool was simultaneously validated using 63,327 human risk-of-bias assessments obtained from 17,394 RCTs evaluated in the Cochrane Database of Systematic Reviews (CDSR). Moreover, RCT registration and CONSORT Statement reporting were assessed using automated searches. Publication characteristics included the number of authors, journal impact factor (JIF), and medical discipline. The annual number of published RCTs substantially increased over 4 decades, accompanied by increases in authors (5.2 to 7.8) and institutions (2.9 to 4.8). The risk of bias remained present in most RCTs but decreased over time for allocation concealment (63% to 51%), random sequence generation (57% to 36%), and blinding of outcome assessment (58% to 52%). Trial registration (37% to 47%) and the use of the CONSORT Statement (1% to 20%) also rapidly increased. In journals with a higher impact factor (>10), the risk of bias was consistently lower with higher levels of RCT registration and the use of the CONSORT Statement. Automated risk-of-bias predictions had accuracies above 70% for allocation concealment (70.7%), random sequence generation (72.1%), and blinding of patients/personnel (79.8%), but not for blinding of outcome assessment (62.7%). In conclusion, the likelihood of bias in RCTs has generally decreased over the last decades. This optimistic trend may be driven by increased knowledge augmented by mandatory trial registration and more stringent reporting guidelines and journal requirements. Nevertheless, relatively high probabilities of bias remain, particularly in journals with lower impact factors. This emphasizes that further improvement of RCT registration, conduct, and reporting is still urgently needed.in PLoS Biology on April 19, 2021 02:00 PM.
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by Nora Linscheid, Alberto Santos, Pi Camilla Poulsen, Robert W. Mills, Kirstine Calloe, Ulrike Leurs, Johan Z. Ye, Christian Stolte, Morten B. Thomsen, Bo H. Bentzen, Pia R. Lundegaard, Morten S. Olesen, Lars J. Jensen, Jesper V. Olsen, Alicia Lundby
Delineating human cardiac pathologies and their basic molecular mechanisms relies on research conducted in model organisms. Yet translating findings from preclinical models to humans present a significant challenge, in part due to differences in cardiac protein expression between humans and model organisms. Proteins immediately determine cellular function, yet their large-scale investigation in hearts has lagged behind those of genes and transcripts. Here, we set out to bridge this knowledge gap: By analyzing protein profiles in humans and commonly used model organisms across cardiac chambers, we determine their commonalities and regional differences. We analyzed cardiac tissue from each chamber of human, pig, horse, rat, mouse, and zebrafish in biological replicates. Using mass spectrometry–based proteomics workflows, we measured and evaluated the abundance of approximately 7,000 proteins in each species. The resulting knowledgebase of cardiac protein signatures is accessible through an online database: atlas.cardiacproteomics.com. Our combined analysis allows for quantitative evaluation of protein abundances across cardiac chambers, as well as comparisons of cardiac protein profiles across model organisms. Up to a quarter of proteins with differential abundances between atria and ventricles showed opposite chamber-specific enrichment between species; these included numerous proteins implicated in cardiac disease. The generated proteomics resource facilitates translational prospects of cardiac studies from model organisms to humans by comparisons of disease-linked protein networks across species.in PLoS Biology on April 19, 2021 02:00 PM.
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Author(s): Anang Kumar Singh, P. S. Burada, and Anushree Roy
Various electronic devices, which we commonly use, radiate microwaves. Such external perturbation influences the functionality of biomolecules. In an ultralow field, the cumulative response of a molecule is expected only over a time scale of hours. To study the structural dynamics of biomolecules ov...
[Phys. Rev. E 103, 042416] Published Mon Apr 19, 2021
in Physical Review E: Biological physics on April 19, 2021 10:00 AM.
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Author(s): Osmar Freitas, Lindi M. Wahl, and Paulo R. A. Campos
Deterministic and stochastic evolutionary processes drive adaptation in natural populations. The strength of each component process is determined by the population size: deterministic components prevail in very large populations, while stochastic components are the driving mechanisms in small ones. ...
[Phys. Rev. E 103, 042415] Published Mon Apr 19, 2021
in Physical Review E: Biological physics on April 19, 2021 10:00 AM.
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Machine Learning (ML) is becoming increasingly important in daily life. In this context, Artificial Neural Networks (ANNs) are a popular approach within ML methods to realize an artificial intelligence. Usually, the topology of ANNs is predetermined. However, there are problems where it is difficult to find a suitable topology. Therefore, Topology and Weight Evolving Artificial Neural Network (TWEANN) algorithms have been developed that can find ANN topologies and weights using genetic algorithms. A well-known downside for large-scale problems is that TWEANN algorithms often evolve inefficient ANNs and require long runtimes.
To address this issue, we propose a new TWEANN algorithm called Artificial Life Form (ALF) with the following technical advancements: (1) speciation via structural and semantic similarity to form better candidate solutions, (2) dynamic adaptation of the observed candidate solutions for better convergence properties, and (3) integration of solution quality into genetic reproduction to increase the probability of optimization success. Experiments on large-scale ML problems confirm that these approaches allow the fast solving of these problems and lead to efficient evolved ANNs.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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We wish to explore the contribution that asocial and social learning might play as a mechanism for self-adaptation in the search for variable-length structures by an evolutionary algorithm. An extremely challenging, yet simple to understand problem landscape is adopted where the probability of randomly finding a solution is approximately one in a trillion. A number of learning mechanisms operating on variable-length structures are implemented and their performance analysed. The social learning setup, which combines forms of both social and asocial learning in combination with evolution is found to be most performant, while the setups exclusively adopting evolution are incapable of finding solutions.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Graph theory has been extensively used to investigate brain network topology and its changes in disease cohorts. However, many graph theoretic analysis-based brain network studies focused on the shortest paths or, more generally, cost-efficiency. In this work, we use two new concepts, connectedness and 2-connectedness, to measure different global properties compared to the previously widely adopted ones.
in arXiv: Quantitative Biology: Neurons and Cognition on April 19, 2021 01:30 AM.
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In this study, we analyze behaviours of the well-known CMA-ES by extracting the time-series features on its dynamic strategy parameters. An extensive experiment was conducted on twelve CMA-ES variants and 24 test problems taken from the BBOB (Black-Box Optimization Bench-marking) testbed, where we used two different cutoff times to stop those variants. We utilized the tsfresh package for extracting the features and performed the feature selection procedure using the Boruta algorithm, resulting in 32 features to distinguish either CMA-ES variants or the problems. After measuring the number of predefined targets reached by those variants, we contrive to predict those measured values on each test problem using the feature. From our analysis, we saw that the features can classify the CMA-ES variants, or the function groups decently, and show a potential for predicting the performance of those variants. We conducted a hierarchical clustering analysis on the test problems and noticed a drastic change in the clustering outcome when comparing the longer cutoff time to the shorter one, indicating a huge change in search behaviour of the algorithm. In general, we found that with longer time series, the predictive power of the time series features increase.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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We propose a novel surrogate-assisted Evolutionary Algorithm for solving expensive combinatorial optimization problems. We integrate a surrogate model, which is used for fitness value estimation, into a state-of-the-art P3-like variant of the Gene-Pool Optimal Mixing Algorithm (GOMEA) and adapt the resulting algorithm for solving non-binary combinatorial problems. We test the proposed algorithm on an ensemble learning problem. Ensembling several models is a common Machine Learning technique to achieve better performance. We consider ensembles of several models trained on disjoint subsets of a dataset. Finding the best dataset partitioning is naturally a combinatorial non-binary optimization problem. Fitness function evaluations can be extremely expensive if complex models, such as Deep Neural Networks, are used as learners in an ensemble. Therefore, the number of fitness function evaluations is typically limited, necessitating expensive optimization techniques. In our experiments we use five classification datasets from the OpenML-CC18 benchmark and Support-vector Machines as learners in an ensemble. The proposed algorithm demonstrates better performance than alternative approaches, including Bayesian optimization algorithms. It manages to find better solutions using just several thousand fitness function evaluations for an ensemble learning problem with up to 500 variables.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Generalization to out-of-distribution (OOD) circumstances after training remains a challenge for artificial agents. To improve the robustness displayed by plastic Hebbian neural networks, we evolve a set of Hebbian learning rules, where multiple connections are assigned to a single rule. Inspired by the biological phenomenon of the genomic bottleneck, we show that by allowing multiple connections in the network to share the same local learning rule, it is possible to drastically reduce the number of trainable parameters, while obtaining a more robust agent. During evolution, by iteratively using simple K-Means clustering to combine rules, our Evolve and Merge approach is able to reduce the number of trainable parameters from 61,440 to 1,920, while at the same time improving robustness, all without increasing the number of generations used. While optimization of the agents is done on a standard quadruped robot morphology, we evaluate the agents' performances on slight morphology modifications in a total of 30 unseen morphologies. Our results add to the discussion on generalization, overfitting and OOD adaptation. To create agents that can adapt to a wider array of unexpected situations, Hebbian learning combined with a regularising "genomic bottleneck" could be a promising research direction.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Criticality has been conjectured as an integral part of neuronal network dynamics. Operating at a critical threshold requires precise parameter tuning and a corresponding mechanism remains an open question. Recent studies have suggested that topological features observed in brain networks give rise to a Griffiths phase, leading to power-laws in brain activity dynamics and the operational benefits of criticality in an extended parameter region. Motivated by growing evidence of neural correlates of different states of consciousness, we investigate how topological changes affect the expression of a Griffiths phase. We analyze the activity decay in modular networks using a Susceptible-Infected-Susceptible propagation model and find that we can control the extension of the Griffiths phase by altering intra- and intermodular connectivity. We find that by adjusting system parameters, we can counteract changes in critical behavior and maintain a stable critical region despite changes in network topology. Our results give insight into how structural network properties affect the emergence of a Griffiths phase and how its features are linked to established topological network metrics. We discuss how those findings can contribute to understand the observed changes in functional brain networks. Finally, we indicate how our results could be useful in the study of disease spreading.
in arXiv: Quantitative Biology: Neurons and Cognition on April 19, 2021 01:30 AM.
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This work proposes to use evolutionary computation as a pathway to allow a new perspective on the modeling of energy expenditure and recovery of an individual athlete during exercise. We revisit a theoretical concept called the "three component hydraulic model" which is designed to simulate metabolic systems during exercise and which is able to address recently highlighted shortcomings of currently applied performance models. This hydraulic model has not been entirely validated on individual athletes because it depends on physiological measures that cannot be acquired in the required precision or quantity. This paper introduces a generalized interpretation and formalization of the three component hydraulic model that removes its ties to concrete metabolic measures and allows to use evolutionary computation to fit its parameters to an athlete.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Recent advances in quantum computing have drawn considerable attention to building realistic application for and using quantum computers. However, designing a suitable quantum circuit architecture requires expert knowledge. For example, it is non-trivial to design a quantum gate sequence for generating a particular quantum state with as fewer gates as possible. We propose a quantum architecture search framework with the power of deep reinforcement learning (DRL) to address this challenge. In the proposed framework, the DRL agent can only access the Pauli-$X$, $Y$, $Z$ expectation values and a predefined set of quantum operations for learning the target quantum state, and is optimized by the advantage actor-critic (A2C) and proximal policy optimization (PPO) algorithms. We demonstrate a successful generation of quantum gate sequences for multi-qubit GHZ states without encoding any knowledge of quantum physics in the agent. The design of our framework is rather general and can be employed with other DRL architectures or optimization methods to study gate synthesis and compilation for many quantum states.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Association Rule Mining is a machine learning method for discovering the interesting relations between the attributes in a huge transaction database. Typically, algorithms for Association Rule Mining generate a huge number of association rules, from which it is hard to extract structured knowledge and present this automatically in a form that would be suitable for the user. Recently, an information cartography has been proposed for creating structured summaries of information and visualizing with methodology called "metro maps". This was applied to several problem domains, where pattern mining was necessary. The aim of this study is to develop a method for automatic creation of metro maps of information obtained by Association Rule Mining and, thus, spread its applicability to the other machine learning methods. Although the proposed method consists of multiple steps, its core presents metro map construction that is defined in the study as an optimization problem, which is solved using an evolutionary algorithm. Finally, this was applied to four well-known UCI Machine Learning datasets and one sport dataset. Visualizing the resulted metro maps not only justifies that this is a suitable tool for presenting structured knowledge hidden in data, but also that they can tell stories to users.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 19, 2021 01:30 AM.
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Nature Neuroscience, Published online: 19 April 2021; doi:10.1038/s41593-021-00852-2
In new research, Smith et al. identify thousands of novel genetic associations with human brain structure and function, including those on the X chromosome, by analyzing ~4,000 MRI-derived traits measured in almost 40,000 individuals from the UK Biobank resource.in Nature Neuroscience on April 19, 2021 12:00 AM.
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Nature Neuroscience, Published online: 19 April 2021; doi:10.1038/s41593-021-00841-5
Liu et al. present a flexible, insertable and transparent microelectrode (FITM) array termed Neuro-FITM. Multimodal recordings with Neuro-FITM reveal diverse and selective large-scale cortical activation patterns associated with hippocampal sharp-wave ripples.in Nature Neuroscience on April 19, 2021 12:00 AM.
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Nature Neuroscience, Published online: 19 April 2021; doi:10.1038/s41593-021-00840-6
The flow of information in the brain is regulated over space and time. The authors show that mice can adaptively filter stimuli originating in the sensory cortex. The stimuli are gated by attractor dynamics in the frontal cortex, revealing a mechanism of gating of neural information.in Nature Neuroscience on April 19, 2021 12:00 AM.
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Nature Neuroscience, Published online: 19 April 2021; doi:10.1038/s41593-021-00833-5
The act of remembering information or planning actions in short term memory can often be robust to distracting or conflicting information. Finkelstein et al. reveal the neural computations behind this robustness against distractors using a combination of optogenetics, behavior, neural recordings and neural network modelling.in Nature Neuroscience on April 19, 2021 12:00 AM.
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Nature Neuroscience, Published online: 19 April 2021; doi:10.1038/s41593-021-00826-4
The Elliott and Smith teams used imaging and genetics data from 40,000 volunteers in the UK Biobank healthcare study, discovering new genetic influences over brain structure and function, which are of relevance to both rare and common diseases.in Nature Neuroscience on April 19, 2021 12:00 AM.
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Nature Methods, Published online: 19 April 2021; doi:10.1038/s41592-021-01123-5
With protein structure prediction recently getting a seismic boost in accuracy, hopes are also up to better predict unstructured protein regions that can adopt diverse conformations. CAID, a community effort to revive systematic benchmarking, should help.in Nature Methods on April 19, 2021 12:00 AM.
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Nature Methods, Published online: 19 April 2021; doi:10.1038/s41592-021-01117-3
Results are presented from the first Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment, a community-based blind test to determine the state of the art in predicting intrinsically disordered regions in proteins.in Nature Methods on April 19, 2021 12:00 AM.
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Nature Methods, Published online: 19 April 2021; doi:10.1038/s41592-021-01110-w
A new approach tracks animal movements in 3D from multiple camera views using volumetric triangulation, reconciling occlusions and ambiguities present in any one camera view.in Nature Methods on April 19, 2021 12:00 AM.
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Nature Methods, Published online: 19 April 2021; doi:10.1038/s41592-021-01106-6
DANNCE enables robust 3D tracking of animals’ limbs and other features in naturalistic environments by making use of a deep learning approach that incorporates geometric reasoning. DANNCE is demonstrated on behavioral sequences from rodents, marmosets, and chickadees.in Nature Methods on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/s41586-021-03530-2
Adjuvanting a subunit COVID-19 vaccine to induce protective immunityin Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/s41586-021-03321-9
Author Correction: Slower decay of landfalling hurricanes in a warming worldin Nature on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22939-x
Author Correction: Discovering the genes mediating the interactions between chronic respiratory diseases in the human interactomein Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22657-4
Stratification has a considerable influence on lake ecology, but there is little understanding of past or future changes in its seasonality. Here, the authors use modelling and empirical data to determine that between 1901–2099, climate change causes stratification to start earlier and end later.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22646-7
Tracking the evolution of non-equilibrium phases requires measurements over a wide range of timescales. Here, using a combination of femtosecond spectroscopy and scanning tunneling microscopy, the authors map out a temporal phase diagram of metastable states in a charge-ordered material 1T-TaS2.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22581-7
The global agrarian transition is characterized by a rise in large-scale land acquisitions (LSLAs), whose energy impacts are unknown. Here, the authors assess how LSLAs change land use, finding that they necessitate greater investment in energy to meet demands, and greater greenhouse gas emissions.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22572-8
The endoplasmic reticulum-localized adaptor STING regulates the innate immune response through its ability to sense DNA damage. Here the authors reveal that STING functions as a regulator of cellular ROS homeostasis and tumor cell susceptibility to reactive oxygen dependent, DNA damaging agents.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22488-3
Stimulus feature maps are found in primary visual cortex of many species. Here the authors show color maps in trichromatic primates containing segregated ensembles of neurons with distinct chromatic signatures that associate with cortical modules known as blobs.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22485-6
The detailed mechanisms of action of bactericidal antibiotics remain unclear. Here, Wong et al. show that these antibiotics induce cytoplasmic condensation through membrane damage and outflow of cytoplasmic contents, as well as accumulation of reactive metabolic by-products and lipid peroxidation, as part of their lethality.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22399-3
Alzheimer’s disease (AD) is typically associated with hippocampal and cortical pathology, although hippocampal sparing and limbic predominant forms exist. The authors use transcriptomic analysis and neuropathology to identify genes associated with selective hippocampal vulnerability in AD.in Nature Communications on April 19, 2021 12:00 AM.
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Nature Communications, Published online: 19 April 2021; doi:10.1038/s41467-021-22268-z
There is frequently a trade-off between plant immunity and growth. Here the authors show that the epigenetic control of CCA1, encoding a core component of the circadian oscillator, simultaneously promotes heterosis for both defense and growth in hybrids under pathogen invasion.in Nature Communications on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-01056-1
What scientists want to know about COVID vaccines and blood clots, the first flight on Mars and why a scientific career isn’t a pipeline, it’s a braided river.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-01045-4
University of Cape Town risks losing ‘irreplaceable’ historical material on anthropology, ecology and politics.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-01044-5
Mind your language; take your time; practice makes perfect. Three experts share their advice.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-01030-x
Instrument engineer Cristina Sans Coll flies the polar skies to help measure climate change.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-01024-9
How data restrictions shaped nuclear discovery, energy research and more.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-00979-z
Mutations of the NOD2 gene are risk factors for Crohn’s disease. Many aspects of how they contribute to the condition are unknown. The discovery of cell populations that are involved suggests new therapeutic options.in Nature on April 19, 2021 12:00 AM.
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Nature, Published online: 19 April 2021; doi:10.1038/d41586-021-00909-z
NASA’s Ingenuity helicopter successfully hovered for 40 seconds in Mars’s thin atmosphere.in Nature on April 19, 2021 12:00 AM.
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in Journal of Neurology on April 19, 2021 12:00 AM.
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in Experimental Brain Research on April 19, 2021 12:00 AM.
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in Journal of Molecular Neuroscience on April 19, 2021 12:00 AM.
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The present study aimed to detect the effect of tenascin C (TNC) on cell function and chemosensitivity to paclitaxel and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) signaling in glioma cells.
Human glioma cells U87, LN-229, T98G and U251 and normal human astrocytes were obtained, in which TNC expression was detected. The U87 cells and U251 cells were chosen and infected with lentivirus of control overexpression, TNC overexpression, control knockdown, and TNC knockdown for functional experiments. Rescue experiments were then performed to evaluate the effect of PI3K/AKT activator 740 Y-P on cell function and chemosensitivity to paclitaxel in TNC knockdown U251 cells. TNC mRNA and protein expression was elevated in glioma cells, including U87, LN-229, U251 and T98G cells, compared to normal human astrocytes. In U87 and U251 cells, TNC promoted proliferation while inhibiting apoptosis. In addition, TNC upregulated PI3K and p-AKT protein expression in U87 and U251 cells. As for chemosensitivity, TNC increased relative viability in U251 cells treated with 400 ng/mL and 800 ng/mL paclitaxel. In terms of stemness, TNC increased the sphere number per 1000 cells, CD44+CD133+ cell percentage and 1/stem cell frequency (assessed by extreme limiting dilution analysis) in U251 cells. In rescue experiments, 740 Y-P reduced the effect of TNC on proliferation, apoptosis, chemosensitivity to paclitaxel, and stemness in U251 cells.
TNC acts as an oncogenic factor by promoting cancer cell proliferation and stemness while inhibiting apoptosis and chemosensitivity to paclitaxel in glioma via modulation of PI3K/AKT signaling.
in Journal of Molecular Neuroscience on April 19, 2021 12:00 AM.
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Electroencephalography (EEG) significantly contributes to the neuroprognostication after resuscitation from cardiac arrest. Recent studies suggest that the prognostic value of EEG is highest for continuous recording within the first days after cardiac arrest. Early continuous EEG, however, is not available in all hospitals. In this observational study, we sought to evaluate the predictive value of a ‘late’ EEG recording 5–14 days after cardiac arrest without sedatives.
We retrospectively analyzed EEG data in consecutive adult patients treated at the medical intensive care units (ICU) of the Charité—Universitätsmedizin Berlin. Outcome was assessed as cerebral performance category (CPC) at discharge from ICU, with an unfavorable outcome being defined as CPC 4 and 5.
In 187 patients, a ‘late’ EEG recording was performed. Of these patients, 127 were without continuous administration of sedative agents for at least 24 h before the EEG recording. In this patient group, a continuously suppressed background activity < 10 µV predicted an unfavorable outcome with a sensitivity of 31% (95% confidence interval (CI) 20–45) and a specificity of 99% (95% CI 91–100). In patients with suppressed background activity and generalized periodic discharges, sensitivity was 15% (95% CI 7–27) and specificity was 100% (95% CI 94–100). GPDs on unsuppressed background activity were associated with a sensitivity of 42% (95% CI 29–46) and a specificity of 92% (95% CI 82–97).
A ‘late’ EEG performed 5 to 14 days after resuscitation from cardiac arrest can aide in prognosticating functional outcome. A suppressed EEG background activity in this time period indicates poor outcome.
in Journal of Neurology on April 19, 2021 12:00 AM.
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in Journal of Neurology on April 19, 2021 12:00 AM.
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Pain influences both attention and motor behavior. We used a dual-task interference paradigm to investigate (1) alterations in attentional performance, (2) the ability to switch task prioritization, and (3) the effect of attentional demand on trunk coordination during narrow-based walking in and out of a painful episode in individuals with recurrent low back pain (LBP). We tested twenty young adults with LBP both in and out of a painful episode and compared them to twenty matched back-healthy individuals. Participants simultaneously performed a narrow step width matching task and an arithmetic task, with and without instructions to prioritize either task. A motion capture system was used to record kinematic data, and frontal plane trunk coordination was analyzed using vector coding on the thorax and pelvis angles. Single-task performance, dual-task effect, dual-task performance variability, task prioritization switch, and trunk coordination were analyzed using paired t tests or repeated measures two-way ANOVAs. Results indicated that active pain has a detrimental effect on attentional processes, indicated by poorer single-task performance and increased dual-task performance variability for individuals with recurrent LBP. Individuals with LBP, regardless of pain status, were able to switch task prioritization to a similar degree as their back-healthy counterparts. Compared to the control group, individuals with recurrent LBP exhibited a less in-phase, more pelvis-dominated trunk coordination during narrow-based walking, independent of pain status and regardless of attentional manipulations. Thus, altered trunk coordination in persons with LBP appears to be habitual, automatic, and persists beyond symptom duration.
in Experimental Brain Research on April 19, 2021 12:00 AM.
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Previous studies have reported (i) freezing-like posturographic correlates in response to painful as compared to non-painful scenes vision (Lelard et al., Front Hum Neurosci 7:4, 2013) and (ii) an increase of this response during the mental simulation as compared to the passive viewing of the painful scenes (Lelard et al., Front Psychol 8:2012, 2017). The main objective of the present study was to explore the modulation of posturographic correlates of painful scenes vision by the level of depicted pain and the influence of mental simulation on this modulation. Thirty-six participants (36.3 ± 11.4 years old) were included in this study. During the experiment, participants had to stand on a posturographic platform. Three types of static visual stimuli were randomly depicting different pain-level situations: no-pain, low-pain, high-pain. In a first run, participants watched these stimuli passively (passive condition); in a second run, they were asked to “imagine that they were personally experiencing the situations they were about to see” (mental simulation condition). For each picture, subjective ratings were recorded for displeasure and desire to avoid at the end of the posturographic session. Results support an approach-type behavior in response to high-pain stimuli in the passive condition which becomes a withdrawal-type behavior in the mental simulation condition. Moreover, this withdrawal-type behavior is modulated by the level of depicted pain and this modulation does not appear for the subjective data. As a conclusion, these results are in accordance with those of previous studies showing the modulation of posturographic correlates of pain perception by mental simulation and report, for the first time, modulation of this effect by the level of depicted pain. The dichotomy of this modulatory effect between subjective and objective data is discussed as well as the finding of an approach-type behavior towards painful stimuli when passively viewing them becoming a withdrawal-type behavior when mental simulation is applied to the same stimuli.
in Experimental Brain Research on April 19, 2021 12:00 AM.
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The ability to perform individual finger movements, highly important in daily activities, involves visual monitoring and proprioception. We investigated the influence of vision on the spatial and temporal control of independent finger movements, for the dominant and non-dominant hand and in relation to sex. Twenty-six healthy middle-aged to old adults (M age = 61 years; range 46–79 years; females n = 13) participated. Participants performed cyclic flexion–extension movements at the metacarpophalangeal joint of one finger at a time while keeping the other fingers as still as possible. Movements were recorded using 3D optoelectronic motion technique (120 Hz). The movement trajectory distance; speed peaks (movement smoothness); Individuation Index (II; the degree a finger can move in isolation from the other fingers) and Stationarity Index (SI; how still a finger remains while the other fingers move) were extracted. The main findings were: (1) vision only improved the II and SI marginally; (2) longer trajectories were evident in the no-vision condition for the fingers of the dominant hand in the female group; (3) longer trajectories were specifically evident for the middle and ring fingers within the female group; (4) females had marginally higher II and SI compared with males; and (5) females had fewer speed peaks than males, particularly for the ring finger. Our results suggest that visual monitoring of finger movements marginally improves performance of our non-manipulative finger movement task. A consistent finding was that females showed greater independent finger control compared with males.
in Experimental Brain Research on April 19, 2021 12:00 AM.
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We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.
in Frontiers in Human Neuroscience on April 19, 2021 12:00 AM.
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in Frontiers in Ageing Neuroscience on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in eLife on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 19, 2021 12:00 AM.
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Publication date: Available online 17 April 2021
Source: Neural Networks
Author(s): Zuowei Shen, Haizhao Yang, Shijun Zhang
in Neural Networks on April 18, 2021 06:00 PM.
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in Annals of Neurology on April 18, 2021 09:24 AM.
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in Annals of Neurology on April 18, 2021 09:18 AM.
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Prior studies have reported an association between visual evoked potentials (VEPs) and cognitive performance in people with multiple sclerosis (PwMS), but the specific mechanisms that account for this relationship remain unclear. We examined the relationship between VEP latency and cognitive performance in a large sample of PwMS, hypothesizing that VEP latency indexes not only visual system functioning but also general neural efficiency. Standardized performance index scores were obtained for the domains of memory, executive function, visual-spatial processing, verbal function, attention, information processing speed, and motor skills, as well as global cognitive performance (NeuroTrax battery). VEP P100 component latency was obtained using a standard checkerboard pattern-reversal paradigm. Prolonged VEP latency was significantly associated with poorer performance in multiple cognitive domains, and with the number of cognitive domains in which performance was ≥ 1 SD below the normative mean. Relationships between VEP latency and cognitive performance were significant for information processing speed, executive function, attention, motor skills, and global cognitive performance after controlling for disease duration, visual acuity, and inter-ocular latency differences. This study provides evidence that VEP latency delays index general neural inefficiency that is associated with cognitive disturbances in PwMS.
in Journal of Neurology on April 18, 2021 12:00 AM.
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Hand use is a widespread act in many vertebrate lineages and subserves behaviors including locomotion, predation, feeding, nest construction, and grooming. In order to determine whether hand use is similarly used in social behavior, the present paper describes hand use in the social play of rats. In the course of rough and tumble play sessions, rats are found to make as many as twenty different movements a minute with each hand for the purposes of manipulating a partner into a subordinate position or defending against a partner’s attack. The hand movements comprise signaling movements of touching, offensive manipulating of a partner to control a play engagement, and defensive hand movements directed toward blocking, pushing and pulling to parry an attack. For signaling, attack and defense, hand movements have a structure that is similar to the structure of hand movements used for other purposes including eating, but in their contact points on an opponent, they are tailored for partner control. Given the time devoted to play by rats, play likely features the social rat behavior with the most extensive use of hand movements. This extensive use of hand movements for social play is discussed in relation to the ubiquity of hand use in adaptive behavior, the evolution of hand use in the play of mammals, and in relation to extending the multifunctional theory of the purposes of play to include the education of skilled hand movements for various adult functions including as feeding.
in Experimental Brain Research on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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in bioRxiv: Neuroscience on April 18, 2021 12:00 AM.
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Publication date: Available online 16 April 2021
Source: Neural Networks
Author(s): Yanping Chen, Weizhe Yang, Kai Wang, Yongbin Qin, Ruizhang Huang, Qinghua Zheng
in Neural Networks on April 17, 2021 06:00 PM.
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Publication date: Available online 16 April 2021
Source: Neural Networks
Author(s): Nana Fan, Xin Li, Zikun Zhou, Qiao Liu, Zhenyu He
in Neural Networks on April 17, 2021 06:00 PM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 11:19 AM.
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in Journal of Comparative Neurology on April 17, 2021 09:01 AM.
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Nature, Published online: 17 April 2021; doi:10.1038/s41586-021-03383-9
Author Correction: Synthesis and breakdown of universal metabolic precursors promoted by ironin Nature on April 17, 2021 12:00 AM.
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Dysregulation of the oxidant-antioxidant system contributes to the pathogenesis of cerebral stroke (CS). Epigenetic changes of redox homeostasis genes, such as glutamate-cysteine ligase (GCLM), glutathione-S-transferase-P1 (GSTP1), thioredoxin reductase 1 (TXNRD1), and myeloperoxidase (MPO), may be biomarkers of CS. In this study, we assessed the association of DNA methylation levels of these genes with CS and clinical features of CS. We quantitatively analyzed DNA methylation patterns in the promoter or regulatory regions of 4 genes (GCLM, GSTP1, TXNRD1, and MPO) in peripheral blood leukocytes of 59 patients with CS in the acute phase and in 83 relatively healthy individuals (controls) without cardiovascular and cerebrovascular diseases. We found that in both groups, the methylation level of CpG sites in genes TXNRD1 and GSTP1 was ≤ 5%. Lower methylation levels were registered at a CpG site (chr1:94,374,293, GRCh37 [hg19]) in GCLM in patients with ischemic stroke compared with the control group (9% [7%; 11.6%] (median and interquartile range) versus 14.7% [10.4%; 23%], respectively, p < 0.05). In the leukocytes of patients with CS, the methylation level of CpG sites in the analyzed region of MPO (chr17:56,356,470, GRCh3 [hg19]) on average was significantly lower (23.5% [19.3%; 26.7%]) than that in the control group (35.6% [30.4%; 42.6%], p < 0.05). We also found increased methylation of MPO in smokers with CS (27.2% [23.5%; 31.1%]) compared with nonsmokers with CS (21.7% [18.1%; 24.8%]). Thus, hypomethylation of CpG sites in GCLM and MPO in blood leukocytes is associated with CS in the acute phase.
in Journal of Molecular Neuroscience on April 17, 2021 12:00 AM.
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The long-duration response (LDR) to L-dopa is a sustained benefit deriving from chronic administration of therapy to patients with Parkinson’s disease (PD). Almost all patients with early PD may develop the LDR to L-dopa, even if some patients could not at given dosages of the drug. Aim of this exploratory study is to investigate whether a neuroanatomical substrate may underlie the development of the of LDR using structural magnetic resonance imaging (MRI) and voxel-based morphometry (VBM) analysis.
Twenty-four drug-naïve PD patients were enrolled and underwent a baseline 3D T1-weighted structural brain MRI. Then, a treatment with 250/25 mg of L-dopa/carbidopa every 24 h was started and, after 2 weeks, LDR was evaluated by movement time recordings.
After 2 weeks of continuative therapy, 15 patients (62.5%) showed a sustained LDR (LDR +), while nine patients (37.5%) did not develop a sustained LDR (LDR −). VBM analysis on MRI executed before treatment showed changes of gray matter in precentral and middle frontal gyri in patients subsequently developing a sustained LDR with respect to those patients who will not achieve LDR.
Parkinsonian patients who will develop a LDR to L-dopa may present, before starting treatment, peculiar structural conditions in cortical areas involved in motor control. Our exploratory study suggests that some cortical structural changes may predispose individual patients for developing the LDR to L-dopa.
in Journal of Neurology on April 17, 2021 12:00 AM.
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To define the neuropsychological and neuroimaging characteristics of classical infratentorial superficial siderosis (iSS), a rare but disabling disorder defined by hemosiderin deposition affecting the superficial layers of the cerebellum, brainstem and spinal cord, usually associated with a slowly progressive neurological syndrome of deafness, ataxia and myelopathy.
We present the detailed neuropsychological and neuroimaging findings in 16 patients with iSS (mean age 57 years; 6 female).
Cognitive impairment was present in 8/16 (50%) of patients: executive dysfunction was the most prevalent (44%), followed by impairment of visual recognition memory (27%); other cognitive domains were largely spared. Disease symptom duration was significantly correlated with the number of cognitive domains impaired (r = 0.59, p = 0.011). Mood disorders were also common (anxiety 62%, depression 38%, both 69%) but not associated with disease symptom duration. MRI findings revealed siderosis was not only in infratentorial brain regions, but also in characteristic widespread symmetrical supratentorial brain regions, independent of disease duration and degree of cognitive impairment. The presence of small vessel disease markers was very low and did not account for the cognitive impairment observed.
Neuropsychological disturbances are common in iSS and need to be routinely investigated. The lack of association between the anatomical extent of hemosiderin and cognitive impairment or disease duration suggests that hemosiderin itself is not directly neurotoxic. Additional biomarkers of iSS disease severity and progression are needed for future research and clinical trials.
in Journal of Neurology on April 17, 2021 12:00 AM.
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Evidence for the influence of unaware signals on behaviour has been reported in both patient groups and healthy observers using the Redundant Signal Effect (RSE). The RSE refers to faster manual reaction times to the onset of multiple simultaneously presented target than those to a single stimulus. These findings are robust and apply to unimodal and multi-modal sensory inputs. A number of studies on neurologically impaired cases have demonstrated that RSE can be found even in the absence of conscious experience of the redundant signals. Here, we investigated behavioural changes associated with awareness in healthy observers by using Continuous Flash Suppression to render observers unaware of redundant targets. Across three experiments, we found an association between reaction times to the onset of a consciously perceived target and the reported level of visual awareness of the redundant target, with higher awareness being associated with faster reaction times. However, in the absence of any awareness of the redundant target, we found no evidence for speeded reaction times and even weak evidence for an inhibitory effect (slowing down of reaction times) on response to the seen target. These findings reveal marked differences between healthy observers and blindsight patients in how aware and unaware information from different locations is integrated in the RSE.
in Experimental Brain Research on April 17, 2021 12:00 AM.
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in BMC Neuroscience on April 17, 2021 12:00 AM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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in Annals of Neurology on April 16, 2021 07:54 PM.
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by Takumi Sase, Keiichi Kitajo
Metastability in the brain is thought to be a mechanism involved in dynamic organization of cognitive and behavioral functions across multiple spatiotemporal scales. However, it is not clear how such organization is realized in underlying neural oscillations in a high-dimensional state space. It was shown that macroscopic oscillations often form phase-phase coupling (PPC) and phase-amplitude coupling (PAC) which result in synchronization and amplitude modulation, respectively, even without external stimuli. These oscillations can also make spontaneous transitions across synchronous states at rest. Using resting-state electroencephalographic signals and the autism-spectrum quotient scores acquired from healthy humans, we show experimental evidence that the PAC combined with PPC allows amplitude modulation to be transient, and that the metastable dynamics with this transient modulation is associated with autistic-like traits. In individuals with a longer attention span, such dynamics tended to show fewer transitions between states by forming delta-alpha PAC. We identified these states as two-dimensional metastable states that could share consistent patterns across individuals. Our findings suggest that the human brain dynamically organizes inter-individual differences in a hierarchy of macroscopic oscillations with multiple timescales by utilizing metastability.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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by Kaiwen Shi, Tao Liu, Hanjiang Fu, Wuju Li, Xiaofei Zheng
Transcript stability is associated with many biological processes, and the factors affecting mRNA stability have been extensively studied. However, little is known about the features related to human long noncoding RNA (lncRNA) stability. By inhibiting transcription and collecting samples in 10 time points, genome-wide RNA-seq studies was performed in human lung adenocarcinoma cells (A549) and RNA half-life datasets were constructed. The following observations were obtained. First, the half-life distributions of both lncRNAs and messanger RNAs (mRNAs) with one exon (lnc-human1 and m-human1) were significantly different from those of both lncRNAs and mRNAs with more than one exon (lnc-human2 and m-human2). Furthermore, some factors such as full-length transcript secondary structures played a contrary role in lnc-human1 and m-human2. Second, through the half-life comparisons of nucleus- and cytoplasm-specific and common lncRNAs and mRNAs, lncRNAs (mRNAs) in the nucleus were found to be less stable than those in the cytoplasm, which was derived from transcripts themselves rather than cellular location. Third, kmers-based protein−RNA or RNA−RNA interactions promoted lncRNA stability from lnc-human1 and decreased mRNA stability from m-human2 with high probability. Finally, through applying deep learning−based regression, a non-linear relationship was found to exist between the half-lives of lncRNAs (mRNAs) and related factors. The present study established lncRNA and mRNA half-life regulation networks in the A549 cell line and shed new light on the degradation behaviors of both lncRNAs and mRNAs.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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by Christophe Menichelli, Vincent Guitard, Rafael M. Martins, Sophie Lèbre, Jose-Juan Lopez-Rubio, Charles-Henri Lecellier, Laurent Bréhélin
Long regulatory elements (LREs), such as CpG islands, polydA:dT tracts or AU-rich elements, are thought to play key roles in gene regulation but, as opposed to conventional binding sites of transcription factors, few methods have been proposed to formally and automatically characterize them. We present here a computational approach named DExTER (Domain Exploration To Explain gene Regulation) dedicated to the identification of candidate LREs (cLREs) and apply it to the analysis of the genomes of P. falciparum and other eukaryotes. Our analyses show that all tested genomes contain several cLREs that are somewhat conserved along evolution, and that gene expression can be predicted with surprising accuracy on the basis of these long regions only. Regulation by cLREs exhibits very different behaviours depending on species and conditions. In P. falciparum and other Apicomplexan organisms as well as in Dictyostelium discoideum, the process appears highly dynamic, with different cLREs involved at different phases of the life cycle. For multicellular organisms, the same cLREs are involved in all tissues, but a dynamic behavior is observed along embryonic development stages. In P. falciparum, whose genome is known to be strongly depleted of transcription factors, cLREs are predictive of expression with an accuracy above 70%, and our analyses show that they are associated with both transcriptional and post-transcriptional regulation signals. Moreover, we assessed the biological relevance of one LRE discovered by DExTER in P. falciparum using an in vivo reporter assay. The source code (python) of DExTER is available at https://gite.lirmm.fr/menichelli/DExTER.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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by Vladislav Uzunangelov, Christopher K. Wong, Joshua M. Stuart
Advancements in sequencing have led to the proliferation of multi-omic profiles of human cells under different conditions and perturbations. In addition, many databases have amassed information about pathways and gene “signatures”—patterns of gene expression associated with specific cellular and phenotypic contexts. An important current challenge in systems biology is to leverage such knowledge about gene coordination to maximize the predictive power and generalization of models applied to high-throughput datasets. However, few such integrative approaches exist that also provide interpretable results quantifying the importance of individual genes and pathways to model accuracy. We introduce AKLIMATE, a first kernel-based stacked learner that seamlessly incorporates multi-omics feature data with prior information in the form of pathways for either regression or classification tasks. AKLIMATE uses a novel multiple-kernel learning framework where individual kernels capture the prediction propensities recorded in random forests, each built from a specific pathway gene set that integrates all omics data for its member genes. AKLIMATE has comparable or improved performance relative to state-of-the-art methods on diverse phenotype learning tasks, including predicting microsatellite instability in endometrial and colorectal cancer, survival in breast cancer, and cell line response to gene knockdowns. We show how AKLIMATE is able to connect feature data across data platforms through their common pathways to identify examples of several known and novel contributors of cancer and synthetic lethality.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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by Jean-Charles Walter, Thibaut Lepage, Jérôme Dorignac, Frédéric Geniet, Andrea Parmeggiani, John Palmeri, Jean-Yves Bouet, Ivan Junier
ParABS, the most widespread bacterial DNA segregation system, is composed of a centromeric sequence, parS, and two proteins, the ParA ATPase and the ParB DNA binding proteins. Hundreds of ParB proteins assemble dynamically to form nucleoprotein parS-anchored complexes that serve as substrates for ParA molecules to catalyze positioning and segregation events. The exact nature of this ParBS complex has remained elusive, what we address here by revisiting the Stochastic Binding model (SBM) introduced to explain the non-specific binding profile of ParB in the vicinity of parS. In the SBM, DNA loops stochastically bring loci inside a sharp cluster of ParB. However, previous SBM versions did not include the negative supercoiling of bacterial DNA, leading to use unphysically small DNA persistences to explain the ParB binding profiles. In addition, recent super-resolution microscopy experiments have revealed a ParB cluster that is significantly smaller than previous estimations and suggest that it results from a liquid-liquid like phase separation. Here, by simulating the folding of long (≥ 30 kb) supercoiled DNA molecules calibrated with realistic DNA parameters and by considering different possibilities for the physics of the ParB cluster assembly, we show that the SBM can quantitatively explain the ChIP-seq ParB binding profiles without any fitting parameter, aside from the supercoiling density of DNA, which, remarkably, is in accord with independent measurements. We also predict that ParB assembly results from a non-equilibrium, stationary balance between an influx of produced proteins and an outflux of excess proteins, i.e., ParB clusters behave like liquid-like protein condensates with unconventional “leaky” boundaries.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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by Diego Vidaurre
An important question in neuroscience is whether or not we can interpret spontaneous variations in the pattern of correlation between brain areas, which we refer to as functional connectivity or FC, as an index of dynamic neuronal communication in fMRI. That is, can we measure time-varying FC reliably? And, if so, can FC reflect information transfer between brain regions at relatively fast-time scales? Answering these questions in practice requires dealing with the statistical challenge of having high-dimensional data and a comparatively lower number of time points or volumes. A common strategy is to use PCA to reduce the dimensionality of the data, and then apply some model, such as the hidden Markov model (HMM) or a mixture model of Gaussian distributions, to find a set of distinct FC patterns or states. The distinct spatial properties of these FC states together with the time-resolved switching between them offer a flexible description of time-varying FC. In this work, I show that in this context PCA can suffer from systematic biases and loss of sensitivity for the purposes of finding time-varying FC. To get around these issues, I propose a novel variety of the HMM, named HMM-PCA, where the states are themselves PCA decompositions. Since PCA is based on the data covariance, the state-specific PCA decompositions reflect distinct patterns of FC. I show, theoretically and empirically, that fusing dimensionality reduction and time-varying FC estimation in one single step can avoid these problems and outperform alternative approaches, facilitating the quantification of transient communication in the brain.in PLoS Computational Biology on April 16, 2021 02:00 PM.
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Publication date: Available online 16 April 2021
Source: Neural Networks
Author(s): Yihong Wang, Xuying Xu, Rubin Wang
in Neural Networks on April 16, 2021 01:00 PM.
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Publication date: August 2021
Source: Current Opinion in Neurobiology, Volume 69
Author(s): Mariela F. Trinchero, Damiana Giacomini, Alejandro F. Schinder
in Current Opinion in Neurobiology on April 16, 2021 01:00 PM.
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Publication date: August 2021
Source: Current Opinion in Neurobiology, Volume 69
Author(s): Clarissa Waites, Xiaoyi Qu, Francesca Bartolini
in Current Opinion in Neurobiology on April 16, 2021 01:00 PM.
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Author(s): Silas Alben
We study the efficiency of sliding locomotion for three-link bodies with prescribed joint angle motions. The bodies move with no inertia, under dry (Coulomb) friction that is anisotropic (different in the directions normal and tangent to the links) and directional (different in the forward and backw...
[Phys. Rev. E 103, 042414] Published Fri Apr 16, 2021
in Physical Review E: Biological physics on April 16, 2021 10:00 AM.
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in Annals of Neurology on April 16, 2021 02:58 AM.
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Recent enhancements in neuroscience, like the development of new and powerful recording techniques of the brain activity combined with the increasing anatomical knowledge provided by atlases and the growing understanding of neuromodulation principles, allow studying the brain at a whole new level, paving the way to the creation of extremely detailed effective network models directly from observed data. Leveraging the advantages of this integrated approach, we propose a method to infer models capable of reproducing the complex spatio-temporal dynamics of the slow waves observed in the experimental recordings of the cortical hemisphere of a mouse under anesthesia. To reliably claim the good match between data and simulations, we implemented a versatile ensemble of analysis tools, applicable to both experimental and simulated data and capable to identify and quantify the spatio-temporal propagation of waves across the cortex. In order to reproduce the observed slow wave dynamics, we introduced an inference procedure composed of two steps: the inner and the outer loop. In the inner loop, the parameters of a mean-field model are optimized by likelihood maximization, exploiting the anatomical knowledge to define connectivity priors. The outer loop explores "external" parameters, seeking for an optimal match between the simulation outcome and the data, relying on observables (speed, directions, and frequency of the waves) apt for the characterization of cortical slow waves; the outer loop includes a periodic neuro-modulation for better reproduction of the experimental recordings. We show that our model is capable to reproduce most of the features of the non-stationary and non-linear dynamics displayed by the biological network. Also, the proposed method allows to infer which are the relevant modifications of parameters when the brain state changes, e.g. according to anesthesia levels.
in arXiv: Quantitative Biology: Neurons and Cognition on April 16, 2021 01:30 AM.
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Recent years have seen the proliferation of disinformation and misinformation online, thanks to the freedom of expression on the Internet and to the rise of social media. Two solutions were proposed to address the problem: (i) manual fact-checking, which is accurate and credible, but slow and non-scalable, and (ii) automatic fact-checking, which is fast and scalable, but lacks explainability and credibility. With the accumulation of enough manually fact-checked claims, a middle-ground approach has emerged: checking whether a given claim has previously been fact-checked. This can be made automatically, and thus fast, while also offering credibility and explainability, thanks to the human fact-checking and explanations in the associated fact-checking article. This is a relatively new and understudied research direction, and here we focus on claims made in a political debate, where context really matters. Thus, we study the impact of modeling the context of the claim: both on the source side, i.e., in the debate, as well as on the target side, i.e., in the fact-checking explanation document. We do this by modeling the local context, the global context, as well as by means of co-reference resolution, and reasoning over the target text using Transformer-XH. The experimental results show that each of these represents a valuable information source, but that modeling the source-side context is more important, and can yield 10+ points of absolute improvement.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 16, 2021 01:30 AM.
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Benchmark suites, i.e. a collection of benchmark functions, are widely used in the comparison of black-box optimization algorithms. Over the years, research has identified many desired qualities for benchmark suites, such as diverse topology, different difficulties, scalability, representativeness of real-world problems among others. However, while the topology characteristics have been subjected to previous studies, there is no study that has statistically evaluated the difficulty level of benchmark functions, how well they discriminate optimization algorithms and how suitable is a benchmark suite for algorithm comparison. In this paper, we propose the use of an item response theory (IRT) model, the Bayesian two-parameter logistic model for multiple attempts, to statistically evaluate these aspects with respect to the empirical success rate of algorithms. With this model, we can assess the difficulty level of each benchmark, how well they discriminate different algorithms, the ability score of an algorithm, and how much information the benchmark suite adds in the estimation of the ability scores. We demonstrate the use of this model in two well-known benchmark suites, the Black-Box Optimization Benchmark (BBOB) for continuous optimization and the Pseudo Boolean Optimization (PBO) for discrete optimization. We found that most benchmark functions of BBOB suite have high difficulty levels (compared to the optimization algorithms) and low discrimination. For the PBO, most functions have good discrimination parameters but are often considered too easy. We discuss potential uses of IRT in benchmarking, including its use to improve the design of benchmark suites, to measure multiple aspects of the algorithms, and to design adaptive suites.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 16, 2021 01:30 AM.
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Simulating and imitating the neuronal network of humans or mammals is a popular topic that has been explored for many years in the fields of pattern recognition and computer vision. Inspired by neuronal conduction characteristics in the primary visual cortex of cats, pulse-coupled neural networks (PCNNs) can exhibit synchronous oscillation behavior, which can process digital images without training. However, according to the study of single cells in the cat primary visual cortex, when a neuron is stimulated by an external periodic signal, the interspike-interval (ISI) distributions represent a multimodal distribution. This phenomenon cannot be explained by all PCNN models. By analyzing the working mechanism of the PCNN, we present a novel neuron model of the primary visual cortex consisting of a continuous-coupled neural network (CCNN). Our model inherited the threshold exponential decay and synchronous pulse oscillation property of the original PCNN model, and it can exhibit chaotic behavior consistent with the testing results of cat primary visual cortex neurons. Therefore, our CCNN model is closer to real visual neural networks. For image segmentation tasks, the algorithm based on CCNN model has better performance than the state-of-art of visual cortex neural network model. The strength of our approach is that it helps neurophysiologists further understand how the primary visual cortex works and can be used to quantitatively predict the temporal-spatial behavior of real neural networks. CCNN may also inspire engineers to create brain-inspired deep learning networks for artificial intelligence purposes.
in arXiv: Computer Science: Neural and Evolutionary Computing on April 16, 2021 01:30 AM.
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Brain-computer interfaces (BCIs) have shown promising results in restoring motor function to individuals with spinal cord injury. These systems have traditionally focused on the restoration of upper extremity function; however, the lower extremities have received relatively little attention. Early feasibility studies used noninvasive electroencephalogram (EEG)-based BCIs to restore walking function to people with paraplegia. However, the limited spatiotemporal resolution of EEG signals restricted the application of these BCIs to elementary gait tasks, such as the initiation and termination of walking. To restore more complex gait functions, BCIs must accurately decode additional degrees of freedom from brain signals. In this study, we used subdurally recorded electrocorticogram (ECoG) signals from able-bodied subjects to design a decoder capable of predicting the walking state and step rate information. We recorded ECoG signals from the motor cortices of two individuals as they walked on a treadmill at different speeds. Our offline analysis demonstrated that the state information could be decoded from >16 minutes of ECoG data with an unprecedented accuracy of 99.8%. Additionally, using a Bayesian filter approach, we achieved an average correlation coefficient between the decoded and true step rates of 0.934. When combined, these decoders may yield decoding accuracies sufficient to safely operate present-day walking prostheses.
in arXiv: Quantitative Biology: Neurons and Cognition on April 16, 2021 01:30 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/s41586-021-03271-2
Author Correction: Rebuilding marine lifein Nature on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22640-z
Tanycytes contribute to the regulation of multiple hypothalamic functions. Here the authors investigate the regenerative and tumorigenic potential of adult Rax+ tanycytes in the median eminence in the context of the stem cell niche in mice.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22638-7
Chemoresistance is one of the main challenges for cancer therapy success. Here, the authors show that dual-specificity phosphatase 16 (DUSP16) expression is associated with chemoresistance in several types of cancer through impairing mitochondria-associated apoptosis.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22589-z
Conventional T cell subsets are selected in the thymus by peptide bearing MHC expressed by cortical epithelial cells, in contrast cortical thymocytes express non-peptide bearing MHC molecules including CD1d and MR1 and select iNKT and MAIT cell populations respectively. Here, the authors generate a novel inducible MHC class-I trasnactivator murine system and suggest the absence of peptide-MHC on thymocytes is involved in the selection of non-peptide specific lymphocytes.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22584-4
Ocean warming and changing circulation as a result of climate change are driving down oxygen levels and threatening ecosystems. Here the author shows that though immediate cessation of anthropogenic CO2 emissions would halt upper ocean oxygen loss, it would continue in the deep ocean for 100 s of years.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22577-3
It is challenging to extract structural information from EM density maps at intermediate or low resolutions. Here, the authors present Emap2sec+, a program for detecting nucleotides and protein secondary structures in EM density maps at 5 to 10 Å resolution.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22520-6
Compared to electromagnetic waves, the wavelength of spin waves is significantly shorter at gigahertz frequencies, enabling the miniaturisation of wave-based devices. Here, the authors present a magnonic Fabry-Pérot resonator allowing for nanoscale and reconfigurable manipulation of spin waves.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-22341-7
Defective viral genomes (DVGs) can interfere with virus replication and provide a potential approach to control infection. Here, Rezelj et al. use a combined experimental evolution and computational approach to identify DVG sequences that optimally interfere with Zika virus infection and show antiviral activity in mice and mosquitoes.in Nature Communications on April 16, 2021 12:00 AM.
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Nature Communications, Published online: 16 April 2021; doi:10.1038/s41467-021-21973-z
For widespread technological application of nonlinear photonic integrated circuits, ultralow optical losses and high fabrication throughput are required. Here, the authors present a CMOS fabrication technique that realizes integrate photonic microresonators on waver-level with mean quality factors exceeding 30 million and 1 dB/m optical losses.in Nature Communications on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-01041-8
Researchers estimate the T. rex population over the 2 million or so years they existed. Plus, the first monkey–human embryos reignite the chimaera debate, and how to curb the spread of COVID-19 vaccine disinformation.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-01036-5
Scientists are investigating rare blood clots to ask if they could be linked to the Johnson & Johnson and Oxford-AstraZeneca coronavirus vaccinesin Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-01035-6
The US National Institutes of Health will remove limits on government scientists and cancel a controversial grant-reviewing ethics panel.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-01000-3
President Joe Biden is preparing to announce the country’s commitment to slashing emissions, but political obstacles remain.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-00998-w
As safety concerns delay the use of two COVID-19 vaccines, Nature looks at the questions that scientists want answered.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-00997-x
Researchers are applying strategies honed during the 2020 US presidential election to track anti-vax propaganda.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-00995-z
A glacier on Mont Blanc provides a decades-long record of the use of bromine, which corrodes the ozone layer.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-00994-0
A vast radio observatory on Earth detects signals similar to those generated by the aurora on Jupiter.in Nature on April 16, 2021 12:00 AM.
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Nature, Published online: 16 April 2021; doi:10.1038/d41586-021-00963-7
Once in the Americas, foxgloves swiftly evolved under pressure by pollinating hummingbirds.in Nature on April 16, 2021 12:00 AM.
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in Journal of Neurology on April 16, 2021 12:00 AM.
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The visuomotor processes involved in grasping a 2-D target are known to be fundamentally different than those involved in grasping a 3-D object, and this has led to concerns regarding the generalizability of 2-D grasping research. This study directly compared participants’ fixation positions and digit placement during interaction with either physical square objects or 2-D virtual versions of these objects. Participants were instructed to either simply grasp the stimulus or grasp and slide it to another location. Participants’ digit placement and fixation positions did not significantly differ as a function of stimulus type when grasping in the center of the display. However, gaze and grasp positions shifted toward the near side of non-central virtual stimuli, while consistently remaining close to the horizontal midline of the physical stimulus. Participants placed their digits at less stable locations when grasping the virtual stimulus in comparison to the physical stimulus on the right side of the display, but this difference disappeared when grasping in the center and on the left. Similar outward shifts in digit placement and lowered fixations were observed when sliding both stimulus types, suggesting participants incorporated similar adjustments in grasp selection in anticipation of manipulation in both Physical and Virtual stimulus conditions. These results suggest that while fixation position and grasp point selection differed between stimulus type as a function of stimulus position, certain eye-hand coordinated behaviours were maintained when grasping both physical and virtual stimuli.
in Experimental Brain Research on April 16, 2021 12:00 AM.
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Face recognition is an essential activity of social living, common to many primate species. Underlying processes in the brain have been investigated using various techniques and compared between species. Functional imaging studies have shown face-selective cortical regions and their degree of correspondence across species. However, the temporal dynamics of face processing, particularly processing speed, are likely different between them. Across sensory modalities activation of primary sensory cortices in macaque monkeys occurs at about 3/5 the latency of corresponding activation in humans, though this human simian difference may diminish or disappear in higher cortical regions. We recorded scalp event-related potentials (ERPs) to presentation of faces in macaques and estimated the peak latency of ERP components. Comparisons of latencies between macaques and humans indicated that the 3:5 ratio is preserved in higher cognitive regions of face processing between those species.
in Frontiers in Systems Neuroscience on April 16, 2021 12:00 AM.
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Two-photon Ca2+ imaging is a leading technique for recording neuronal activities in vivo with cellular or subcellular resolution. However, during experiments, the images often suffer from corruption due to complex noises. Therefore, the analysis of Ca2+ imaging data requires preprocessing steps, such as denoising, to extract biologically relevant information. We present an approach that facilitates imaging data restoration through image denoising performed by a neural network combining spatiotemporal filtering and model blind learning. Tests with synthetic and real two-photon Ca2+ imaging datasets demonstrate that the proposed approach enables efficient restoration of imaging data. In addition, we demonstrate that the proposed approach outperforms the current state-of-the-art methods by evaluating the qualities of the denoising performance of the models quantitatively. Therefore, our method provides an invaluable tool for denoising two-photon Ca2+ imaging data by model blind spatiotemporal processing.
in Frontiers in Neuroscience: Brain Imaging Methods on April 16, 2021 12:00 AM.
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An increase in blood brain barrier permeability commonly precedes neuro-inflammation and cognitive impairment in models of dementia. Common methods to estimate capillary permeability have potential confounders, or require laborious and subjective semi-manual analysis.
New methodHere we used snap frozen mouse and rat brain sections that were double-immunofluorescent labeled for immunoglobulin G (IgG; plasma protein) and laminin-α4 (capillary basement membrane). A Machine Learning Image Analysis program (Zeiss ZEN Intellisis) was trained to recognize and segment laminin-α4 to equivocally identify blood vessels in large sets of images. An IgG subclass based on a threshold intensity was segmented and quantitated only in extravascular regions. The residual parenchymal IgG fluorescence is indicative of blood-to-brain extravasation of IgG and was accurately quantitated.
ResultsAutomated machine-learning and threshold based segmentation of only parenchymal IgG extravasation accentuates otherwise indistinct capillary permeability, particularly frequent in minor BBB leakage. Comparison with Existing Methods: Large datasets can be processed and analyzed quickly and robustly to provide an overview of vascular permeability throughout the brain. All human bias or ambiguity involved in classifying and measuring leakage is removed.
ConclusionHere we describe a fast and precise method of visualizing and quantitating BBB permeability in mouse and rat brain tissue, while avoiding the confounding influence of unphysiological conditions such as perfusion and eliminating any human related bias from analysis.
in Frontiers in Neuroscience: Brain Imaging Methods on April 16, 2021 12:00 AM.
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The central nervous system uses feedback processes that occur at multiple time scales to control interactions with the environment. The long-latency response (LLR) is the fastest process that directly involves cortical areas, with a motoneuron response measurable 50 ms following an imposed limb displacement. Several behavioral factors concerning perturbation mechanics and the active role of muscles prior or during the perturbation can modulate the long-latency response amplitude (LLRa) in the upper limbs, but the interactions among many of these factors had not been systematically studied before. We conducted a behavioral study on thirteen healthy individuals to determine the effect and interaction of four behavioral factors – background muscle torque, perturbation direction, perturbation velocity, and task instruction – on the LLRa evoked from the flexor carpi radialis (FCR) and extensor carpi ulnaris (ECU) muscles after velocity-controlled wrist displacements. The effects of the four factors were quantified using both a 0D statistical analysis on the average perturbation-evoked EMG signal in the period corresponding to an LLR, and using a timeseries analysis of EMG signals. All factors significantly modulated LLRa, and their combination nonlinearly contributed to modulating the LLRa. Specifically, all the three-way interaction terms that could be computed without including the interaction between instruction and velocity significantly modulated the LLR. Analysis of the three-way interaction terms of the 0D model indicated that for the ECU muscle, the LLRa evoked when subjects are asked to maintain their muscle activation in response to the perturbations was greater than the one observed when subjects yielded to the perturbations (p < 0.001), but this effect was not measured for muscles undergoing shortening or in absence of background muscle activation. Moreover, higher perturbation velocity increased the LLRa evoked from the stretched muscle in presence of a background torque (p < 0.001), but no effects of velocity were measured in absence of background torque. Also, our analysis identified significant modulations of LLRa in muscles shortened by the perturbation, including an interaction between torque and velocity, and an effect of both torque and velocity. The time-series analysis indicated the significance of additional transient effects in the LLR region for muscles undergoing shortening.
in Frontiers in Human Neuroscience on April 16, 2021 12:00 AM.
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Cross-sectional studies indicate that normal aging is accompanied by decreases in brain structure. Longitudinal studies, however, are relatively rare and inconsistent regarding their outcomes. Particularly the heterogeneity of methods, sample characteristics and the high inter-individual variability in older adults prevent the deduction of general trends. Therefore, the current study aimed to compare longitudinal age-related changes in brain structure (measured through cortical thickness) in two large independent samples of healthy older adults (n = 161 each); the Longitudinal Healthy Aging Brain (LHAB) database project at the University of Zurich, Switzerland, and 1000BRAINS at the Research Center Juelich, Germany. Annual percentage changes in the two samples revealed stable to slight decreases in cortical thickness over time. After correction for major covariates, i.e., baseline age, sex, education, and image quality, sample differences were only marginally present. Results suggest that general trends across time might be generalizable over independent samples, assuming the same methodology is used, and similar sample characteristics are present.
in Frontiers in Human Neuroscience on April 16, 2021 12:00 AM.
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Purpose: We aimed to find out the distributed functional connectome of white matter in patients with functional dyspepsia (FD).
Methods: 20 patients with FD and 24 age- and gender-matched healthy controls were included into the study. The functional connectome of white matter and graph theory were used to these participants. Two-sample t-test was used for the detection the abnormal graph properties in FD. Pearson correlation was used for the relationship between properties and the clinical and neuropshychological information.
Results: Patients with FD and healthy controls showed small-world properties in functional connectome of white matter. Compared with healthy controls, the FD group showed decreased global properties (Cp, S, Eglobal, and Elocal). Four pairs of fiber bundles that are connected to the frontal lobe, insula, and thalamus were affected in the FD group. Duration and Pittsburgh Sleep Quality Index positively correlated with the betweenness centrality of white matter regions of interest.
Conclusion: FD patients turned to a non-optimized functional organization of WM brain network. Frontal lobe, insula, and thalamus were key regions in brain information exchange of FD. It provided some novel imaging evidences for the mechanism of FD.
in Frontiers in Human Neuroscience on April 16, 2021 12:00 AM.
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Monocular deprivation (MD) of vision during early postnatal life induces amblyopia, and most neurons in the primary visual cortex lose their responses to the closed eye. Anatomically, the somata of neurons in the closed-eye recipient layer of the lateral geniculate nucleus (LGN) shrink and their axons projecting to the visual cortex retract. Although it has been difficult to restore visual acuity after maturation, recent studies in rodents and cats showed that a period of exposure to complete darkness could promote recovery from amblyopia induced by prior MD. However, in cats, which have an organization of central visual pathways similar to humans, the effect of dark rearing only improves monocular vision and does not restore binocular depth perception. To determine whether dark rearing can completely restore the visual pathway, we examined its effect on the three major concomitants of MD in individual visual neurons, eye preference of visual cortical neurons and soma size and axon morphology of LGN neurons. Dark rearing improved the recovery of visual cortical responses to the closed eye compared with the recovery under binocular conditions. However, geniculocortical axons serving the closed eye remained retracted after dark rearing, whereas reopening the closed eye restored the soma size of LGN neurons. These results indicate that dark rearing incompletely restores the visual pathway, and thus exerts a limited restorative effect on visual function.
in Frontiers in Neural Circuits on April 16, 2021 12:00 AM.
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Visual information is conveyed from the eye to the brain through the axons of retinal ganglion cells (RGCs) that course through the optic nerve and synapse onto neurons in multiple subcortical visual relay areas. RGCs cannot regenerate their axons once they are damaged, similar to most mature neurons in the central nervous system (CNS), and soon undergo cell death. These phenomena of neurodegeneration and regenerative failure are widely viewed as being determined by cell-intrinsic mechanisms within RGCs or to be influenced by the extracellular environment, including glial or inflammatory cells. However, a new concept is emerging that the death or survival of RGCs and their ability to regenerate axons are also influenced by the complex circuitry of the retina and that the activation of a multicellular signaling cascade involving changes in inhibitory interneurons – the amacrine cells (AC) – contributes to the fate of RGCs. Here, we review our current understanding of the role that interneurons play in cell survival and axon regeneration after optic nerve injury.
in Frontiers in Cellular Neuroscience on April 16, 2021 12:00 AM.
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Alzheimer’s disease (AD) is a common neurodegenerative disorder that places a heavy burden on patients and society. Hippocampal neuronal loss is a hallmark of AD progression. Therefore, understanding the mechanism underlying hippocampal neuronal death would be of great importance for the diagnosis and treatment of AD. This study aimed to explore the molecular mechanism via which nuclear factor kappa β (NF-κB) promotes hippocampal neuronal oxidative stress and pyroptosis in AD. We collected serum samples from 101 healthy elderly people and 112 patients with AD at the Affiliated Hospital of Kunming University of Science and Technology between January 2017 and January 2020. Commercially available human hippocampal neurons (HHNs) were used to establish an AD model (AD-HHN) following Aβ25–35 treatment. The mRNA expression levels of NF-κB and pyroptosis markers [NLR family pyrin domain-containing 3, caspase-1, interleukin (IL)-1β, and interleukin-18] mRNA and the expression level of miR-146a-5p in the serum samples of patients with AD and AD-HHNs were determined by quantitative reverse transcription polymerase chain reaction. Oxidative stress indices (reactive oxygen species, malondialdehyde, nicotinamide adenine dinucleotide phosphate, superoxide dismutase, glutathione, and catalase) were measured by Enzyme-Linked Immunosorbent Assay (ELISA). The expression of proteins [NF-κB, TP53-induced glycolysis and apoptosis regulator (TIGAR), and pyroptosis markers] was tested by western blotting. The relationship between miR-146a-5p and TIGAR was investigated using a dual luciferase reporter gene assay. We found that NF-κB and miR-146a-5p were highly expressed, while TIGAR was low expressed in patients with AD and AD-HHNs. In addition, there was a significant positive correlation between the expression levels of NF-κB and miR-146a-5p, but a negative correlation between NF-κB mRNA and TIGAR mRNA in patients with AD, as well as miR-146a-5p and TIGAR mRNA in patients with AD. In AD-HNNs, miR-146a-5p targeted and downregulated the expression of TIGAR. Knockdown of NF-κB or overexpression of TIGAR markedly attenuated oxidative stress and pyroptosis in AD-HHNs, while concurrent overexpression of miR-146a-5p inhibited these effects. In conclusion, NF-κB-induced upregulation of miR-146a-5p promoted oxidative stress and pyroptosis in AD-HNNs by targeting TIGAR.
in Frontiers in Cellular Neuroscience on April 16, 2021 12:00 AM.
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The Vagal Trigone, often referred to as Ala Cinerea, is a triangular-shaped area of the floor of the fourth ventricle that is strictly involved in the network of chardiochronotropic, baroceptive, respiratory, and gastrointestinal control systems of the medulla oblongata. While it is frequently identified as the superficial landmark for the underlying Dorsal Motor Nucleus of the Vagus, this correspondence is not univocal in anatomical literature and is often oversimplified in neuroanatomy textbooks and neurosurgical atlases. As the structure represents an important landmark for neurosurgical procedures involving the floor of the fourth ventricle, accurate morphological characterization is required to avoid unwanted side effects (e.g., bradychardia, hypertension) during neuorphysiological monitoring and cranial nerve nuclei stimulation in intraoperative settings. The aim of this study was to address the anatomo-topographical relationships of the Vagal Trigone with the underlying nuclei. For this purpose, we have conducted an anatomo-microscopical examination of serial sections deriving from 54 Human Brainstems followed by 3D reconstruction and rendering of the specimens. Our findings indicate that the Vagal Trigone corresponds only partially with the Dorsal Motor Nucleus of the Vagus, while most of its axial profile is occupied by the dorsal regions of the Solitary Tract Nucleus. Furthermore, basing on literature and our findings we speculate that the neuroblasts of the Dorsal Motor Nucleus of the Vagus undergo neurobiotaxic migration induced by the neuroblasts of the dorsolaterally located solitary tract nucleus, giving rise to the Ala Cinerea, a topographically defined area for parasympathetic visceral control.
in Frontiers in Neuroanatomy on April 16, 2021 12:00 AM.
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Exercise has multiple beneficial effects on health including decreasing the risk of neurodegenerative diseases. Such effects are thought to be mediated (at least in part) by myokines, a collection of cytokines and other small proteins released from skeletal muscles. As an endocrine organ, skeletal muscle synthesizes and secretes a wide range of myokines which contribute to different functions in different organs, including the brain. One such myokine is the recently discovered protein Irisin, which is secreted into circulation from skeletal muscle during exercise from its membrane bound precursor Fibronectin type III domain-containing protein 5 (FNDC5). Irisin contributes to metabolic processes such as glucose homeostasis and browning of white adipose tissue. Irisin also crosses the blood brain barrier and initiates a neuroprotective genetic program in the hippocampus that culminates with increased expression of brain derived neurotrophic factor (BDNF). Furthermore, exercise and FNDC5/Irisin have been shown to have several neuroprotective effects against injuries in ischemia and neurodegenerative disease models, including Alzheimer’s disease. In addition, Irisin has anxiolytic and antidepressant effects. In this review we present and summarize recent findings on the multiple effects of Irisin on neural function, including signaling pathways and mechanisms involved. We also discuss how exercise can positively influence brain function and mental health via the “skeletal muscle-brain axis.” While there are still many unanswered questions, we put forward the idea that Irisin is a potentially essential mediator of the skeletal muscle-brain crosstalk.
in Frontiers in Ageing Neuroscience on April 16, 2021 12:00 AM.
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Postoperative cognitive dysfunction increases mortality and morbidity in perioperative patients and has become a major concern for patients and caregivers. Previous studies demonstrated that synaptic plasticity is closely related to cognitive function, anesthesia and surgery inhibit synaptic function. In central nervous system, autophagy is vital to synaptic plasticity, homeostasis of synapticproteins, synapse elimination, spine pruning, proper axon guidance, and when dysregulated, is associated with behavioral and memory functions disorders. The mammalian target of rapamycin (mTOR) negatively regulates the process of autophagy. This study aimed to explore whether rapamycin can ameliorate anesthesia/surgery-induced cognitive deficits by inhibiting mTOR, activating autophagy and rising synaptic plasticity-related proteins in the hippocampus. Aged C57BL/6J mice were used to establish POCD models with exploratory laparotomy under isoflurane anesthesia. The Morris Water Maze (MWM) was used to measure reference memory after anesthesia and surgery. The levels of mTOR phosphorylation (p-mTOR), Beclin-1 and LC3-II were examined on postoperative days 1, 3 and 7 by western blotting. The levels of synaptophysin (SYN) and postsynaptic density protein 95 (PSD-95) in the hippocampus were also examined by western blotting. Here we showed that anesthesia/surgery impaired reference memory and induced the activation of mTOR, decreased the expression of autophagy-related proteins such as Beclin-1 and LC3-II. A corresponding decline in the expression of neuronal/synaptic, plasticity-related proteins such as SYN and PSD-95 was also observed. Pretreating mice with rapamycin inhibited the activation of mTOR and restored autophagy function, also increased the expression of SYN and PSD-95. Furthermore, anesthesia/surgery-induced learning and memory deficits were also reversed by rapamycin pretreatment. In conclusion, anesthesia/surgery induced mTOR hyperactivation and autophagy impairments, and then reduced the levels of SYN and PSD-95 in the hippocampus. An mTOR inhibitor, rapamycin, ameliorated anesthesia/surgery-related cognitive impairments by inhibiting the mTOR activity, inducing activation of autophagy, enhancing SYN and PSD-95 expression.
in Frontiers in Ageing Neuroscience on April 16, 2021 12:00 AM.
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To develop and validate a prediction nomogram based on motoric cognitive risk syndrome for cognitive impairment in healthy older adults.
MethodsUsing two longitudinal cohorts of participants (aged ≥ 60 years) with 4-year follow-up, we developed (n = 1,177) and validated (n = 2,076) a prediction nomogram. LASSO (least absolute shrinkage and selection operator) regression model and multivariable Cox regression analysis were used for variable selection and for developing the prediction model, respectively. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness.
ResultsThe individualized prediction nomogram was assessed based on the following: motoric cognitive risk syndrome, education, gender, baseline cognition, and age. The model showed good discrimination [Harrell’s concordance index (C-index) of 0.814; 95% confidence interval, 0.782–0.835] and good calibration. Comparable results were also seen in the validation cohort, which includes good discrimination (C-index, 0.772; 95% confidence interval, 0.776–0.818) and good calibration. Decision curve analysis demonstrated that the prediction nomogram was clinically useful.
ConclusionThis prediction nomogram provides a practical tool with all necessary predictors, which are accessible to practitioners. It can be used to estimate the risk of cognitive impairment in healthy older adults.
in Frontiers in Ageing Neuroscience on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in eLife on April 16, 2021 12:00 AM.
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in Behavioural and Brain Functions on April 16, 2021 12:00 AM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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in Hippocampus on April 15, 2021 04:42 PM.
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by Cristobal Rodero, Marina Strocchi, Maciej Marciniak, Stefano Longobardi, John Whitaker, Mark D. O’Neill, Karli Gillette, Christoph Augustin, Gernot Plank, Edward J. Vigmond, Pablo Lamata, Steven A. Niederer
Cardiac anatomy plays a crucial role in determining cardiac function. However, there is a poor understanding of how specific and localised anatomical changes affect different cardiac functional outputs. In this work, we test the hypothesis that in a statistical shape model (SSM), the modes that are most relevant for describing anatomy are also most important for determining the output of cardiac electromechanics simulations. We made patient-specific four-chamber heart meshes (n = 20) from cardiac CT images in asymptomatic subjects and created a SSM from 19 cases. Nine modes captured 90% of the anatomical variation in the SSM. Functional simulation outputs correlated best with modes 2, 3 and 9 on average (R = 0.49 ± 0.17, 0.37 ± 0.23 and 0.34 ± 0.17 respectively). We performed a global sensitivity analysis to identify the different modes responsible for different simulated electrical and mechanical measures of cardiac function. Modes 2 and 9 were the most important for determining simulated left ventricular mechanics and pressure-derived phenotypes. Mode 2 explained 28.56 ± 16.48% and 25.5 ± 20.85, and mode 9 explained 12.1 ± 8.74% and 13.54 ± 16.91% of the variances of mechanics and pressure-derived phenotypes, respectively. Electrophysiological biomarkers were explained by the interaction of 3 ± 1 modes. In the healthy adult human heart, shape modes that explain large portions of anatomical variance do not explain equivalent levels of electromechanical functional variation. As a result, in cardiac models, representing patient anatomy using a limited number of modes of anatomical variation can cause a loss in accuracy of simulated electromechanical function.in PLoS Computational Biology on April 15, 2021 02:00 PM.
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by Claudio Bassot, Arne Elofsson
Repeat proteins are abundant in eukaryotic proteomes. They are involved in many eukaryotic specific functions, including signalling. For many of these proteins, the structure is not known, as they are difficult to crystallise. Today, using direct coupling analysis and deep learning it is often possible to predict a protein’s structure. However, the unique sequence features present in repeat proteins have been a challenge to use direct coupling analysis for predicting contacts. Here, we show that deep learning-based methods (trRosetta, DeepMetaPsicov (DMP) and PconsC4) overcomes this problem and can predict intra- and inter-unit contacts in repeat proteins. In a benchmark dataset of 815 repeat proteins, about 90% can be correctly modelled. Further, among 48 PFAM families lacking a protein structure, we produce models of forty-one families with estimated high accuracy.in PLoS Computational Biology on April 15, 2021 02:00 PM.
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by Aref Pariz, Ingo Fischer, Alireza Valizadeh, Claudio Mirasso
Brain networks exhibit very variable and dynamical functional connectivity and flexible configurations of information exchange despite their overall fixed structure. Brain oscillations are hypothesized to underlie time-dependent functional connectivity by periodically changing the excitability of neural populations. In this paper, we investigate the role of the connection delay and the detuning between the natural frequencies of neural populations in the transmission of signals. Based on numerical simulations and analytical arguments, we show that the amount of information transfer between two oscillating neural populations could be determined by their connection delay and the mismatch in their oscillation frequencies. Our results highlight the role of the collective phase response curve of the oscillating neural populations for the efficacy of signal transmission and the quality of the information transfer in brain networks.in PLoS Computational Biology on April 15, 2021 02:00 PM.
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in Annals of Neurology on April 15, 2021 11:10 AM.
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Author(s): Kayla C. Sapp, Andrew H. Beaven, and Alexander J. Sodt
To what spatial extent does a single lipid affect the mechanical properties of the membrane that surrounds it? The lipid composition of a membrane determines its mechanical properties. The shapes available to the membrane depend on its compositional material properties, and therefore, the lipid envi...
[Phys. Rev. E 103, 042413] Published Thu Apr 15, 2021
in Physical Review E: Biological physics on April 15, 2021 10:00 AM.
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Author(s): Jacopo Teneggi, Xin Chen, Alan Balu, Connor Barrett, Giulia Grisolia, Umberto Lucia, and Rhonda Dzakpasu
The brain demands a significant fraction of the energy budget in an organism; in humans, it accounts for 2% of the body mass, but utilizes 20% of the total energy metabolized. This is due to the large load required for information processing; spiking demands from neurons are high but are a key compo...
[Phys. Rev. E 103, 042412] Published Thu Apr 15, 2021
in Physical Review E: Biological physics on April 15, 2021 10:00 AM.
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Author(s): N. Gorbushin and L. Truskinovsky
Peristalsis by actively generated waves of muscle contraction is one of the most fundamental ways of producing motion in living systems. We show that peristalsis can be modeled by a train of rectangular-shaped solitary waves of localized activity propagating through otherwise passive matter. Our ana...
[Phys. Rev. E 103, 042411] Published Thu Apr 15, 2021
in Physical Review E: Biological physics on April 15, 2021 10:00 AM.
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in Journal of Comparative Neurology on April 15, 2021 07:30 AM.
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in Annals of Neurology on April 15, 2021 03:24 AM.
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Nature Neuroscience, Published online: 15 April 2021; doi:10.1038/s41593-021-00837-1
Xu et al. developed and characterized a new animal model of maternal immune activation based on a parasite mimetic. They show that immune and behavioral abnormalities in adult offspring are reversed by adoptive transfer of regulatory T cells.in Nature Neuroscience on April 15, 2021 12:00 AM.
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Nature Neuroscience, Published online: 15 April 2021; doi:10.1038/s41593-021-00835-3
Julian and Doeller show that trial-by-trial modulation of map-like representations in the human hippocampal–entorhinal system predicts contextual memory retrieval during virtual reality navigation independent of visual experience.in Nature Neuroscience on April 15, 2021 12:00 AM.
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Nature Methods, Published online: 15 April 2021; doi:10.1038/s41592-021-01108-4
Phasor S-FLIM combines novel electronics for multichannel fluorescence lifetime acquisition and a phasor-based unmixing algorithm for real-time analysis of reliable spectral lifetime imaging data, enabling new biological observations.in Nature Methods on April 15, 2021 12:00 AM.
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Nature Methods, Published online: 15 April 2021; doi:10.1038/s41592-021-01107-5
PCprophet combines complex-level scoring and machine learning to predict novel protein complexes from protein cofractionation mass spectrometry data and to perform differential analysis across experimental conditions.in Nature Methods on April 15, 2021 12:00 AM.
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Nature Reviews Neuroscience, Published online: 15 April 2021; doi:10.1038/s41583-021-00448-6
Neuroscience can explain cognition by considering single neurons and their connections (a ‘Sherringtonian’ view) or by considering neural spaces constructed by populations of neurons (a ‘Hopfieldian’ view). In this Perspective, Barack and Krakauer argue that the Hopfieldian view has the conceptual resources to explain cognition more fully the Sherringtonian view.in Nature Reviews on April 15, 2021 12:00 AM.
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Nature Physics, Published online: 15 April 2021; doi:10.1038/s41567-021-01219-x
A two-fold rotational symmetry is observed in the superconducting state of NbSe2. This is strikingly different from the three-fold symmetry of the lattice, and suggests that a mixed conventional and unconventional order parameter exists in this material.in Nature Physics on April 15, 2021 12:00 AM.
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Nature Physics, Published online: 15 April 2021; doi:10.1038/s41567-021-01217-z
The two-dimensional electron gas at an oxide interface is patterned to form a channel with a periodic potential imposed on top. This replicates the textbook Kronig–Penney model and leads to fractionalization of electron bands in the channel.in Nature Physics on April 15, 2021 12:00 AM.
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Nature Photonics, Published online: 15 April 2021; doi:10.1038/s41566-021-00792-0
An on-chip, sub-optical-cycle sampling technique for measuring arbitrary electric fields of few-femtojoule near-infrared optical pulses in ambient conditions is demonstrated, offering an improvement of roughly six orders of magnitude in energy sensitivity compared with those previous works in the near-infrared.in Nature Photomics on April 15, 2021 12:00 AM.
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Nature Communications, Published online: 15 April 2021; doi:10.1038/s41467-021-22820-x
Publisher Correction: A single-dose mRNA vaccine provides a long-term protection for hACE2 transgenic mice from SARS-CoV-2in Nature Communications on April 15, 2021 12:00 AM.
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Nature Communications, Published online: 15 April 2021; doi:10.1038/s41467-021-22791-z
Author Correction: A model for the fragmentation kinetics of crumpled thin sheetsin Nature Communications on April 15, 2021 12:00 AM.
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Nature Communications, Published online: 15 April 2021; doi:10.1038/s41467-021-22565-7
Selenoproteins containing selenium have a variety of physiological functions including redox homeostasis and thyroid hormone metabolism. Here, the authors show that RANKL-dependent repression of selenoprotein W regulates cell fusion during osteoclast differentiation and bone remodelling in mice.in Nature Communications on April 15, 2021 12:00 AM.
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Nature Communications, Published online: 15 April 2021; doi:10.1038/s41467-021-22532-2
Oligodendrocyte precursor cell (OPC) proliferation and differentiation is greater in white matter than gray matter. Here, the authors show regulation of OPC proliferation in white matter involved trans-activation of PDGFRα on OPCs via Nrp1 expressed by adjacent microglia.in Nature Communications on April 15, 2021 12:00 AM.
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Nature, Published online: 15 April 2021; doi:10.1038/d41586-021-01017-8
SARS-CoV-2 variants and the future of the pandemic, the tough problem of space junk and India’s COVID-vaccine crunch is putting global supplies at risk.in Nature on April 15, 2021 12:00 AM.
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Nature, Published online: 15 April 2021; doi:10.1038/d41586-021-01001-2
The chimaeras lived up to 19 days — but some scientists question the need for such research.in Nature on April 15, 2021 12:00 AM.
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Nature, Published online: 15 April 2021; doi:10.1038/d41586-021-00996-y
How an explosion of coronavirus cases in India is putting global vaccine supplies at risk.in Nature on April 15, 2021 12:00 AM.
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in The Cerebellum on April 15, 2021 12:00 AM.
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Emerging evidence suggests that the cerebellum may contribute to variety of cognitive capacities, including social cognition. Nonverbal learning disability (NVLD) is characterized by visual-spatial and social impairment. Recent functional neuroimaging studies have shown that children with NVLD have altered cerebellar resting-state functional connectivity, which is associated with various symptom domains. However, little is known about cerebellar white matter microstructure in NVLD and whether it contributes to social deficits. Twenty-seven children (12 with NVLD, 15 typically developing (TD)) contributed useable diffusion tensor imaging data. Tract-based spatial statistics (TBSS) were used to quantify fractional anisotropy (FA) in the cerebellar peduncles. Parents completed the Child Behavior Checklist, providing a measure of social difficulty. Children with NVLD had greater fractional anisotropy in the left and right inferior cerebellar peduncle. Furthermore, right inferior cerebellar peduncle FA was associated with social impairment as measured by the Child Behavior Checklist Social Problems subscale. Finally, the association between NVLD diagnosis and greater social impairment was mediated by right inferior cerebellar peduncle FA. These findings provide additional evidence that the cerebellum contributes both to social cognition and to the pathophysiology of NVLD.
in The Cerebellum on April 15, 2021 12:00 AM.
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Hashimoto’s encephalopathy with serum anti-NH2-terminal of α-enolase (NAE) antibodies occasionally displays clinical symptoms such as cerebellar ataxia and parkinsonism. We studied the frequency of anti-NAE antibodies in patients with Parkinson-plus syndrome.
We examined the positive rates of anti-NAE antibodies in 47 patients with multiple system atrophy (MSA), 29 patients with Parkinson’s disease (PD), eight patients with corticobasal syndrome (CBS), and 18 patients with progressive supranuclear palsy (PSP) using conventional immunoblot analysis.
Positive anti-NAE antibody rates of 31.9%, 10.3%, 50.0%, and 11.1% were reported in the MSA, PD, CBS, and PSP patients, respectively. The duration from onset to a wheelchair-bound state in seropositive MSA patients tended to be shorter than that in seronegative MSA patients.
Anti-NAE antibodies are detected in some patients clinically diagnosed with MSA and CBS. Although its pathophysiological significance remains uncertain, serum anti-NAE antibodies might represent a prognostic marker in the clinical course of MSA.
in Journal of Neurology on April 15, 2021 12:00 AM.
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A quantitative evaluation of motility is crucial for studies employing experimental animals. Here, we describe the development of an in-cage motility monitoring method for new world monkeys using off-the-shelf components, and demonstrate its capability for long-term operation (e.g., a year). Based on this novel system, we characterized the motility of the common marmoset over different time scales (seconds, hours, days, and weeks). Monitoring of seven young animals belonging to two different age groups (sub-adult and young-adult) over a 231-day period revealed: (1) strictly diurnal activity (97.3% of movement during daytime), (2) short-cycle (∼20 s) transition in activity, and (3) bimodal diurnal activity including a “siesta” break. Additionally, while the mean duration of short-cycle activity, net daily activity, and diurnal activity changed over the course of development, 24-h periodicity remained constant. Finally, the method allowed for detection of progressive motility deterioration in a transgenic marmoset. Motility measurement offers a convenient way to characterize developmental and pathological changes in animals, as well as an economical and labor-free means for long-term evaluation in a wide range of basic and translational studies.
in Frontiers in Systems Neuroscience on April 15, 2021 12:00 AM.
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For more than two decades, there has been converging evidence for an essential role of the cerebellum in non-motor functions. The cerebellum is not only important in learning and sensorimotor processes, some growing evidences show its implication in conditional learning and reward, which allows building our expectations about behavioral outcomes. More recent work has demonstrated that the cerebellum is also required for the sense of agency, a cognitive process that allows recognizing an action as our own, suggesting that the cerebellum might serve as an interface between sensorimotor function and cognition. A unifying model that would explain the role of the cerebellum across these processes has not been fully established. Nonetheless, an important heritage was given by the field of motor control: the forward model theory. This theory stipulates that movements are controlled based on the constant interactions between our organism and its environment through feedforward and feedback loops. Feedforward loops predict what is going to happen, while feedback loops confront the prediction with what happened so that we can react accordingly. From an anatomical point of view, the cerebellum is at an ideal location at the interface between the motor and sensory systems, as it is connected to cerebral, striatal, and spinal entities via parallel loops, so that it can link sensory and motor systems with cognitive processes. Recent findings showing that the cerebellum participates in building the sense of agency as a predictive and comparator system will be reviewed together with past work on motor control within the context of the forward model theory.
in Frontiers in Systems Neuroscience on April 15, 2021 12:00 AM.
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The history of neural activity determines the synaptic plasticity mechanisms employed in the brain. Previous studies report a rapid reduction in the strength of excitatory synapses onto layer 2/3 (L2/3) pyramidal neurons of the primary visual cortex (V1) following two days of dark exposure and subsequent re-exposure to light. The abrupt increase in visually driven activity is predicted to drive homeostatic plasticity, however, the parameters of neural activity that trigger these changes are unknown. To determine this, we first recorded spike trains in vivo from V1 layer 4 (L4) of dark exposed (DE) mice of both sexes that were re-exposed to light through homogeneous or patterned visual stimulation. We found that delivering the spike patterns recorded in vivo to L4 of V1 slices was sufficient to reduce the amplitude of miniature excitatory postsynaptic currents (mEPSCs) of V1 L2/3 neurons in DE mice, but not in slices obtained from normal reared (NR) controls. Unexpectedly, the same stimulation pattern produced an up-regulation of mEPSC amplitudes in V1 L2/3 neurons from mice that received 2 h of light re-exposure (LE). A Poisson spike train exhibiting the same average frequency as the patterns recorded in vivo was equally effective at depressing mEPSC amplitudes in L2/3 neurons in V1 slices prepared from DE mice. Collectively, our results suggest that the history of visual experience modifies the responses of V1 neurons to stimulation and that rapid homeostatic depression of excitatory synapses can be driven by non-patterned input activity.
in Frontiers in Synaptic Neuroscience on April 15, 2021 12:00 AM.
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Synaptic active zone (AZ) contains multiple specialized release sites for vesicle fusion. The utilization of release sites is regulated to determine spatiotemporal organization of the two main forms of synchronous release, uni-vesicular (UVR) and multi-vesicular (MVR). We previously found that the vesicle-associated molecular motor myosin V regulates temporal utilization of release sites by controlling vesicle anchoring at release sites in an activity-dependent manner. Here we show that acute inhibition of myosin V shifts preferential location of vesicle docking away from AZ center toward periphery, and results in a corresponding spatial shift in utilization of release sites during UVR. Similarly, inhibition of myosin V also reduces preferential utilization of central release sites during MVR, leading to more spatially distributed and temporally uniform MVR that occurs farther away from the AZ center. Using a modeling approach, we provide a conceptual framework that unites spatial and temporal functions of myosin V in vesicle release by controlling the gradient of release site release probability across the AZ, which in turn determines the spatiotemporal organization of both UVR and MVR. Thus myosin V regulates both temporal and spatial utilization of release sites during two main forms of synchronous release.
in Frontiers in Synaptic Neuroscience on April 15, 2021 12:00 AM.
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Blast-mediated traumatic brain injuries (bTBI) cause long-lasting physical, cognitive, and psychological disorders, including persistent visual impairment. No known therapies are currently utilized in humans to lessen the lingering and often serious symptoms. With TBI mortality decreasing due to advancements in medical and protective technologies, there is growing interest in understanding the pathology of visual dysfunction after bTBI. However, this is complicated by numerous variables, e.g., injury location, severity, and head and body shielding. This review summarizes the visual outcomes observed by various, current experimental rodent models of bTBI, and identifies data showing that bTBI activates inflammatory and apoptotic signaling leading to visual dysfunction. Pharmacologic treatments blocking inflammation and cell death pathways reported to alleviate visual deficits in post-bTBI animal models are discussed. Notably, techniques for assessing bTBI outcomes across exposure paradigms differed widely, so we urge future studies to compare multiple models of blast injury, to allow data to be directly compared.
in Frontiers in Molecular Neuroscience on April 15, 2021 12:00 AM.
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Neurons have high metabolic demands that are almost exclusively met by glucose supplied from the bloodstream. Glucose is utilized in complex metabolic interactions between neurons and glia cells, described by the astrocyte-neuron lactate shuttle (ANLS) hypothesis. The neural retina faces similar energy demands to the rest of the brain, with additional high anabolic needs to support continuous renewal of photoreceptor outer segments. This demand is met by a fascinating variation of the ANLS in which photoreceptors are the central part of a metabolic landscape, using glucose and supplying surrounding cells with metabolic intermediates. In this review we summarize recent evidence on how neurons, in particular photoreceptors, meet their energy and biosynthetic requirements by comprising a metabolic landscape of interdependent cells.
in Frontiers in Molecular Neuroscience on April 15, 2021 12:00 AM.
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Protein–protein interaction networks and signaling complexes are essential for normal brain function and are often dysregulated in neurological disorders. Nevertheless, unraveling neuron- and synapse-specific proteins interaction networks has remained a technical challenge. New techniques, however, have allowed for high-resolution and high-throughput analyses, enabling quantification and characterization of various neuronal protein populations. Over the last decade, mass spectrometry (MS) has surfaced as the primary method for analyzing multiple protein samples in tandem, allowing for the precise quantification of proteomic data. Moreover, the development of sophisticated protein-labeling techniques has given MS a high temporal and spatial resolution, facilitating the analysis of various neuronal substructures, cell types, and subcellular compartments. Recent studies have leveraged these novel techniques to reveal the proteomic underpinnings of well-characterized neuronal processes, such as axon guidance, long-term potentiation, and homeostatic plasticity. Translational MS studies have facilitated a better understanding of complex neurological disorders, such as Alzheimer’s disease (AD), Schizophrenia (SCZ), and Autism Spectrum Disorder (ASD). Proteomic investigation of these diseases has not only given researchers new insight into disease mechanisms but has also been used to validate disease models and identify new targets for research.
in Frontiers in Molecular Neuroscience on April 15, 2021 12:00 AM.
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Neurotrophin brain-derived neurotrophic factor (BDNF) and neurotransmitter serotonin (5-HT) regulate each other and have been implicated in several neuronal mechanisms, including neuroplasticity. We have investigated the effects of BDNF on serotonergic neurons by deleting BDNF receptor TrkB from serotonergic neurons in the adult brain. The transgenic mice show increased 5-HT and Tph2 levels with abnormal behavioral phenotype. In spite of increased food intake, the transgenic mice are significantly leaner than their wildtype littermates, which may be due to increased metabolic activity. Consistent with increased 5-HT, the proliferation of hippocampal progenitors is significantly increased, however, long-term survival of newborn cells is unchanged. Our data indicates that BDNF-TrkB signaling regulates the functional phenotype of 5-HT neurons with long-term behavioral consequences.
in Frontiers in Molecular Neuroscience on April 15, 2021 12:00 AM.
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Recent decades have witnessed an increasing number of large to very large imaging studies, prominently in the field of neurodegenerative diseases. The datasets collected during these studies form essential resources for the research aiming at new biomarkers. Collecting, hosting, managing, processing, or reviewing those datasets is typically achieved through a local neuroinformatics infrastructure. In particular for organizations with their own imaging equipment, setting up such a system is still a hard task, and relying on cloud-based solutions, albeit promising, is not always possible. This paper proposes a practical model guided by core principles including user involvement, lightweight footprint, modularity, reusability, and facilitated data sharing. This model is based on the experience from an 8-year-old research center managing cohort research programs on Alzheimer’s disease. Such a model gave rise to an ecosystem of tools aiming at improved quality control through seamless automatic processes combined with a variety of code libraries, command line tools, graphical user interfaces, and instant messaging applets. The present ecosystem was shaped around XNAT and is composed of independently reusable modules that are freely available on GitLab/GitHub. This paradigm is scalable to the general community of researchers working with large neuroimaging datasets.
in Frontiers in Neuroscience: Brain Imaging Methods on April 15, 2021 12:00 AM.
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The vital role of reward in guiding visual attention has been supported by previous literatures. Here, we examined the motivational impact of monetary reward feedback stimuli on visual attention selection using an event-related potential (ERP) component called stimulus-preceding negativity (SPN) and a standard contextual cueing (CC) paradigm. It has been proposed that SPN reflects affective and motivational processing. We focused on whether incidentally learned context knowledge could be affected by reward. Both behavior and brain data demonstrated that contexts followed by reward feedback not only gave rise to faster implicit learning but also obtained a larger CC effect.
in Frontiers in Human Neuroscience on April 15, 2021 12:00 AM.
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This study aimed to investigate whether oxygenated hemoglobin (oxy-Hb) generated during a motor imagery (MI) task is associated with the motor learning level of the task.
MethodsWe included 16 right-handed healthy participants who were trained to perform a ball rotation (BR) task. Hemodynamic brain activity was measured using near-infrared spectroscopy to monitor changes in oxy-Hb concentration during the BR MI task. The experimental protocol used a block design, and measurements were performed three times before and after the initial training of the BR task as well as after the final training. The BR count during training was also measured. Furthermore, subjective vividness of MI was evaluated three times after NIRS measurement using the Visual Analog Scale (VAS).
ResultsThe results showed that the number of BRs increased significantly with training (P < 0.001). VAS scores also improved with training (P < 0.001). Furthermore, oxy-Hb concentration and the region of interest (ROI) showed a main effect (P = 0.001). An interaction was confirmed (P < 0.001), and it was ascertained that the change in oxy-Hb concentrations due to training was different for each ROI. The most significant predictor of subjective MI vividness was supplementary motor area (SMA) oxy-Hb concentration (coefficient = 0.365).
DiscussionHemodynamic brain activity during MI tasks may be correlated with task motor learning levels, since significant changes in oxy-Hb concentrations were observed following initial and final training in the SMA. In particular, hemodynamic brain activity in the SMA was suggested to reflect the MI vividness of participants.
in Frontiers in Human Neuroscience on April 15, 2021 12:00 AM.
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Striatal dopamine transporters (DAT) powerfully regulate dopamine signaling, and can contribute risk to degeneration in Parkinson’s disease (PD). DATs can interact with the neuronal protein α-synuclein, which is associated with the etiology and molecular pathology of idiopathic and familial PD. Here, we tested whether DAT function in governing dopamine (DA) uptake and release is modified in a human-α-synuclein-overexpressing (SNCA-OVX) transgenic mouse model of early PD. Using fast-scan cyclic voltammetry (FCV) in ex vivo acute striatal slices to detect DA release, and biochemical assays, we show that several aspects of DAT function are promoted in SNCA-OVX mice. Compared to background control α-synuclein-null mice (Snca-null), the SNCA-OVX mice have elevated DA uptake rates, and more pronounced effects of DAT inhibitors on evoked extracellular DA concentrations ([DA]o) and on short-term plasticity (STP) in DA release, indicating DATs play a greater role in limiting DA release and in driving STP. We found that DAT membrane levels and radioligand binding sites correlated with α-synuclein level. Furthermore, DAT function in Snca-null and SNCA-OVX mice could also be promoted by applying cholesterol, and using Tof-SIMS we found genotype-differences in striatal lipids, with lower striatal cholesterol in SNCA-OVX mice. An inhibitor of cholesterol efflux transporter ABCA1 or a cholesterol chelator in SNCA-OVX mice reduced the effects of DAT-inhibitors on evoked [DA]o. Together these data indicate that human α-synuclein in a mouse model of PD promotes striatal DAT function, in a manner supported by extracellular cholesterol, suggesting converging biology of α-synuclein and cholesterol that regulates DAT function and could impact DA function and PD pathophysiology.
in Frontiers in Cellular Neuroscience on April 15, 2021 12:00 AM.
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Alzheimer’s disease (AD) is a type of neurodegenerative disease that is associated with the accumulation of amyloid plaques. Increasing non-amyloidogenic processing and/or manipulating amyloid precursor protein signaling could reduce AD amyloid pathology and cognitive impairment. D-penicillamine (D-Pen) is a water-soluble metal chelator and can reduce the aggregation of amyloid-β (Aβ) with metals in vitro. However, the potential mechanism of D-Pen for treating neurodegenerative disorders remains unexplored. In here, a novel type of chitosan-based hydrogel to carry D-Pen was designed and the D-Pen-CS/β-glycerophosphate hydrogel were characterized by scanning electron microscopy and HPLC. Behavior tests investigated the learning and memory levels of APP/PS1 mice treated through the D-Pen hydrogel nasal delivery. In vivo and in vitro findings showed that nasal delivery of D-Pen-CS/β-GP hydrogel had properly chelated metal ions that reduced Aβ deposition. Furthermore, D-Pen mainly regulated A disintegrin and metalloprotease 10 (ADAM10) expression via melatonin receptor 1 (MTNR1α) and the downstream PKA/ERK/CREB pathway. The present data demonstrated D-Pen significantly improved the cognitive ability of APP/PS1 mice and reduced Aβ generation through activating ADAM10 and accelerating non-amyloidogenic processing. Hence, these findings indicate the potential of D-Pen as a promising agent for treating AD.
in Frontiers in Ageing Neuroscience on April 15, 2021 12:00 AM.
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Low-intensity transcranial ultrasound stimulation (TUS) is a non-invasive neuromodulation technique with high spatial resolution and feasible penetration depth. To date, the mechanisms of TUS modulated neural oscillations are not fully understood. This study designed a very low acoustic intensity (AI) TUS system that produces considerably reduced AI Ultrasound pulses (ISPTA < 0.5 W/cm2) when compared to previous methods used to measure regional neural oscillation patterns under different TUS parameters.
MethodsWe recorded the local field potential (LFP) of five brain nuclei under TUS with three groups of simulating parameters. Spectrum estimation, time-frequency analysis (TFA), and relative power analysis methods have been applied to investigate neural oscillation patterns under different stimulation parameters.
ResultsUnder PRF, 500 Hz and 1 kHz TUS, high-amplitude LFP activity with the auto-rhythmic pattern appeared in selected nuclei when ISPTA exceeded 12 mW/cm2. With TFA, high-frequency energy (slow gamma and high gamma) was significantly increased during the auto-rhythmic patterns. We observed an initial plateau in nuclei response when ISPTA reached 16.4 mW/cm2 for RPF 500 Hz and 20.8 mW/cm2 for RPF 1 kHz. The number of responding nuclei started decreasing while ISPTA continued increasing. Under 1.5 kHz TUS, no auto-rhythmic patterns have been observed, but slow frequency power was increased during TUS. TUS inhibited most of the frequency band and generated obvious slow waves (theta and delta band) when stimulated at RPF = 1.5 kHz, ISPTA = 8.8 mW/cm2.
ConclusionThese results demonstrate that very low intensity Transcranial Ultrasound Stimulation (VLTUS) exerts significant neuromodulator effects under specific parameters in rat models and may be a valid tool to study neuronal physiology.
in Frontiers in Ageing Neuroscience on April 15, 2021 12:00 AM.
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Background: The impact of exercise on cognition in older adults with hypertension and subjective cognitive decline (SCD) is unclear.
Objectives: We determined the influence of high-intensity interval training (HIIT) combined with mind-motor training on cognition and systolic blood pressure (BP) in older adults with hypertension and SCD.
Methods: We randomized 128 community-dwelling older adults [age mean (SD): 71.1 (6.7), 47.7% females] with history of hypertension and SCD to either HIIT or a moderate-intensity continuous training (MCT) group. Both groups received 15 min of mind-motor training followed by 45 min of either HIIT or MCT. Participants exercised in total 60 min/day, 3 days/week for 6 months. We assessed changes in global cognitive functioning (GCF), Trail-Making Test (TMT), systolic and diastolic BP, and cardiorespiratory fitness.
Results: Participants in both groups improved diastolic BP [F(1, 87.32) = 4.392, p = 0.039], with greatest effect within the HIIT group [estimated mean change (95% CI): −2.64 mmHg, (−4.79 to −0.48), p = 0.017], but no between-group differences were noted (p = 0.17). Both groups also improved cardiorespiratory fitness [F(1, 69) = 34.795, p < 0.001], and TMT A [F(1, 81.51) = 26.871, p < 0.001] and B [F(1, 79.49) = 23.107, p < 0.001]. There were, however, no within- or between-group differences in GCF and systolic BP at follow-up.
Conclusion: Despite improvements in cardiorespiratory fitness, exercise of high- or moderate-intensity, combined with mind-motor training, did not improve GCF or systolic BP in individuals with hypertension and SCD.
Clinical Trial Registration:ClinicalTrials.gov (NCT03545958).
in Frontiers in Ageing Neuroscience on April 15, 2021 12:00 AM.
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There is growing evidence that testosterone may be implicated in the pathogenesis of Alzheimer’s disease (AD). We aimed to examine the relationship between plasma total testosterone levels and change in brain glucose metabolism over time among non-demented older people.
MethodsThe association of plasma total testosterone levels with change in brain glucose metabolism among non-demented older people was investigated cross-sectionally and longitudinally. Given a significant difference in levels of plasma total testosterone between gender, we performed our analysis in a sex-stratified way. At baseline, 228 non-demented older people were included: 152 males and 76 females.
ResultsIn the cross-sectional analysis, no significant relationship between plasma total testosterone levels and brain glucose metabolism was found in males or females. In the longitudinal analysis, we found a significant association of plasma total testosterone levels with change in brain glucose metabolism over time in males, but not in females. More specifically, in males, higher levels of total testosterone in plasma at baseline were associated with slower decline in brain glucose metabolism.
ConclusionWe found that higher levels of total testosterone in plasma at baseline were associated with slower decline in brain glucose metabolism in males without dementia, indicating that testosterone may have beneficial effects on brain function.
in Frontiers in Ageing Neuroscience on April 15, 2021 12:00 AM.
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Publication date: August 2021
Source: Current Opinion in Neurobiology, Volume 69
Author(s): Fabrice Ango, Nicholas Biron Gallo, Linda Van Aelst
in Current Opinion in Neurobiology on April 14, 2021 06:00 PM.
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in Journal of Comparative Neurology on April 14, 2021 05:36 PM.
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by Changjia Cai, Johannes Friedrich, Amrita Singh, M. Hossein Eybposh, Eftychios A. Pnevmatikakis, Kaspar Podgorski, Andrea Giovannucci
Voltage imaging enables monitoring neural activity at sub-millisecond and sub-cellular scale, unlocking the study of subthreshold activity, synchrony, and network dynamics with unprecedented spatio-temporal resolution. However, high data rates (>800MB/s) and low signal-to-noise ratios create bottlenecks for analyzing such datasets. Here we present VolPy, an automated and scalable pipeline to pre-process voltage imaging datasets. VolPy features motion correction, memory mapping, automated segmentation, denoising and spike extraction, all built on a highly parallelizable, modular, and extensible framework optimized for memory and speed. To aid automated segmentation, we introduce a corpus of 24 manually annotated datasets from different preparations, brain areas and voltage indicators. We benchmark VolPy against ground truth segmentation, simulations and electrophysiology recordings, and we compare its performance with existing algorithms in detecting spikes. Our results indicate that VolPy’s performance in spike extraction and scalability are state-of-the-art.in PLoS Computational Biology on April 14, 2021 02:00 PM.
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by Benjamin R. Pittman-Polletta, Yangyang Wang, David A. Stanley, Charles E. Schroeder, Miles A. Whittington, Nancy J. Kopell
Current hypotheses suggest that speech segmentation—the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing—is executed by a hierarchy of oscillators in auditory cortex. Theta (∼3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ∼1 Hz), requires “flexible” theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech.in PLoS Computational Biology on April 14, 2021 02:00 PM.
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Author(s): Lucas Goiriz and Guillermo Rodrigo
Thermodynamic descriptions are powerful tools to formally study complex gene expression programs evolved in living cells on the basis of macromolecular interactions. While transcriptional regulations are often modeled in the equilibrium, other interactions that occur in the cell follow a more comple...
[Phys. Rev. E 103, 042410] Published Wed Apr 14, 2021
in Physical Review E: Biological physics on April 14, 2021 10:00 AM.
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Author(s): Taigang Liu, Ting Yu, Shuhao Zhang, Yujie Wang, and Wenbing Zhang
Double stranded DNA can adopt different forms, the so-called A-, B-, and Z-DNA, which play different biological roles. In this work, the thermodynamic and the kinetic parameters for the base-pair closing and opening in A-DNA and B-DNA were calculated by all-atom molecular dynamics simulations at dif...
[Phys. Rev. E 103, 042409] Published Wed Apr 14, 2021
in Physical Review E: Biological physics on April 14, 2021 10:00 AM.
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Cervical discogenic pain (CDP) is mainly induced by cervical disc degeneration. However, how CDP modulates the functional interactions within the pain network remains unclear. In the current study, we studied the changed resting-state functional connectivities of pain network with 40 CDP patients and 40 age-, gender-matched healthy controls. We first defined the pain network with the seeds of the posterior insula (PI). Then, whole brain and seed-to-target functional connectivity analyses were performed to identify the differences in functional connectivity between CDP and healthy controls. Finally, correlation analyses were applied to reveal the associations between functional connectivities and clinical measures. Whole-brain functional connectivity analyses of PI identified increased functional connectivity between PI and thalamus (THA) and decreased functional connectivity between PI and middle cingulate cortex (MCC) in CDP patients. Functional connectivity analyses within the pain network further revealed increased functional connectivities between bilateral PI and bilateral THA, and decreased functional connectivities between left PI and MCC, between left postcentral gyrus (PoCG) and MCC in CDP patients. Moreover, we found that the functional connectivities between right PI and left THA, between left PoCG and MCC were negatively and positively correlated with the visual analog scale, respectively. Our findings provide direct evidence of how CDP modulates the pain network, which may facilitate understanding of the neural basis of CDP.
in Frontiers in Neuroscience: Brain Imaging Methods on April 14, 2021 12:00 AM.
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Background: Although low-intensity transcranial ultrasound stimulation (LI-TUS) has received more recognition for its neuromodulation potential, there remains a crucial knowledge gap regarding the neuromodulatory effects of LI-TUS and its potential for translation as a therapeutic tool in humans.
Objective: In this review, we summarized the findings reported by recently published studies regarding the effect of LI-TUS on neuromodulation in both animals and humans. We also aim to identify challenges and opportunities for the translation process.
Methods: A literature search of PubMed, Medline, EMBASE, and Web of Science was performed from January 2019 to June 2020 with the following keywords and Boolean operators: [transcranial ultrasound OR transcranial focused ultrasound OR ultrasound stimulation] AND [neuromodulation]. The methodological quality of the animal studies was assessed by the SYRCLE's risk of bias tool, and the quality of human studies was evaluated by the PEDro score and the NIH quality assessment tool.
Results: After applying the inclusion and exclusion criteria, a total of 26 manuscripts (24 animal studies and two human studies) out of 508 reports were included in this systematic review. Although both inhibitory (10 studies) and excitatory (16 studies) effects of LI-TUS were observed in animal studies, only inhibitory effects have been reported in primates (five studies) and human subjects (two studies). The ultrasonic parameters used in animal and human studies are different. The SYRCLE quality score ranged from 25 to 43%, with a majority of the low scores related to performance and detection bias. The two human studies received high PEDro scores (9/10).
Conclusion: LI-TUS appears to be capable of targeting both superficial and deep cerebral structures to modulate cognitive or motor behavior in both animals and humans. Further human studies are needed to more precisely define the effective modulation parameters and thereby translate this brain modulatory tool into the clinic.
in Frontiers in Neuroscience: Neural Technology on April 14, 2021 12:00 AM.
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Functional human brain mapping is commonly performed during invasive monitoring with intracranial electroencephalographic (iEEG) electrodes prior to resective surgery for drug resistant epilepsy. The current gold standard, electrocortical stimulation mapping (ESM), is time consuming, sometimes elicits pain, and often induces after discharges or seizures. Moreover, there is a risk of overestimating eloquent areas due to propagation of the effects of stimulation to a broader network of language cortex. Passive iEEG spatial-temporal functional mapping (STFM) has recently emerged as a potential alternative to ESM. However, investigators have observed less correspondence between STFM and ESM maps of language than between their maps of motor function. We hypothesized that incongruities between ESM and STFM of language function may arise due to propagation of the effects of ESM to cortical areas having strong effective connectivity with the site of stimulation. We evaluated five patients who underwent invasive monitoring for seizure localization, whose language areas were identified using ESM. All patients performed a battery of language tasks during passive iEEG recordings. To estimate the effective connectivity of stimulation sites with a broader network of task-activated cortical sites, we measured cortico-cortical evoked potentials (CCEPs) elicited across all recording sites by single-pulse electrical stimulation at sites where ESM was performed at other times. With the combination of high gamma power as well as CCEPs results, we trained a logistic regression model to predict ESM results at individual electrode pairs. The average accuracy of the classifier using both STFM and CCEPs results combined was 87.7%, significantly higher than the one using STFM alone (71.8%), indicating that the correspondence between STFM and ESM results is greater when effective connectivity between ESM stimulation sites and task-activated sites is taken into consideration. These findings, though based on a small number of subjects to date, provide preliminary support for the hypothesis that incongruities between ESM and STFM may arise in part from propagation of stimulation effects to a broader network of cortical language sites activated by language tasks, and suggest that more studies, with larger numbers of patients, are needed to understand the utility of both mapping techniques in clinical practice.
in Frontiers in Human Neuroscience on April 14, 2021 12:00 AM.
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This paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface (BCI), which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguished by frequency and spatial information. The classification algorithm was developed by introducing filters for frequency bands selection and conducting optimization with common spatial pattern (CSP) on the tactile evoked EEG signals. It features a combination of spatial and frequency information, with the spatial information distinguishing the sites of stimuli and frequency information identifying target stimuli and disturbances. We investigated both electrical stimuli and vibration stimuli, in which only one target site was stimulated in each block. The results demonstrated an average accuracy of 94.88% for electrical stimuli and 95.21% for vibration stimuli, respectively.
in Frontiers in Human Neuroscience on April 14, 2021 12:00 AM.
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Mismatch brain responses to unpredicted rare stimuli are suggested to be a neural indicator of prediction error, but this has rarely been studied in the somatosensory modality. Here, we investigated how the brain responds to unpredictable and predictable rare events. Magnetoencephalography responses were measured in adults frequently presented with somatosensory stimuli (FRE) that were occasionally replaced by two consecutively presented rare stimuli [unpredictable rare stimulus (UR) and predictable rare stimulus (PR); p = 0.1 for each]. The FRE and PR were electrical stimulations administered to either the little finger or the forefinger in a counterbalanced manner between the two conditions. The UR was a simultaneous electrical stimulation to both the forefinger and the little finger (for a smaller subgroup, the UR and FRE were counterbalanced for the stimulus properties). The grand-averaged responses were characterized by two main components: one at 30–100 ms (M55) and the other at 130–230 ms (M150) latency. Source-level analysis was conducted for the primary somatosensory cortex (SI) and the secondary somatosensory cortex (SII). The M55 responses were larger for the UR and PR than for the FRE in both the SI and the SII areas and were larger for the UR than for the PR. For M150, both investigated areas showed increased activity for the UR and the PR compared to the FRE. Interestingly, although the UR was larger in stimulus energy (stimulation of two fingers at the same time) and had a larger prediction error potential than the PR, the M150 responses to these two rare stimuli did not differ in source strength in either the SI or the SII area. The results suggest that M55, but not M150, can possibly be associated with prediction error signals. These findings highlight the need for disentangling prediction error and rareness-related effects in future studies investigating prediction error signals.
in Frontiers in Human Neuroscience on April 14, 2021 12:00 AM.
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Working memory is essential for daily life skills like reading comprehension, reasoning, and problem-solving. Healthy aging of the brain goes along with working memory decline that can affect older people’s independence in everyday life. Interventions in the form of cognitive training are a promising tool for delaying age-related working memory decline, yet the underlying structural plasticity of white matter is hardly studied.
MethodsWe conducted a longitudinal diffusion tensor imaging study to investigate the effects of an intensive four-week adaptive working memory training on white matter integrity quantified by global and tract-wise mean diffusivity. We compared diffusivity measures of fiber tracts that are associated with working memory of 32 young and 20 older participants that were randomly assigned to a working memory training group or an active control group.
ResultsThe behavioral analysis showed an increase in working memory performance after the four-week adaptive working memory training. The neuroanatomical analysis revealed a decrease in mean diffusivity in the working memory training group after the training intervention in the right inferior longitudinal fasciculus for the older adults. There was also a decrease in mean diffusivity in the working memory training group in the right superior longitudinal fasciculus for the older and young participants after the intervention.
ConclusionThis study shows that older people can benefit from working memory training by improving their working memory performance that is also reflected in terms of improved white matter integrity in the superior longitudinal fasciculus and the inferior longitudinal fasciculus, where the first is an essential component of the frontoparietal network known to be essential in working memory.
in Frontiers in Human Neuroscience on April 14, 2021 12:00 AM.
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The brain is a non-linear dynamical system with a self-restoration process, which protects itself from external damage but is often a bottleneck for clinical treatment. To treat the brain to induce the desired functionality, formulation of a self-restoration process is necessary for optimal brain control. This study proposes a computational model for the brain's self-restoration process following the free-energy and degeneracy principles. Based on this model, a computational framework for brain control is established. We posited that the pre-treatment brain circuit has long been configured in response to the environmental (the other neural populations') demands on the circuit. Since the demands persist even after treatment, the treated circuit's response to the demand may gradually approximate the pre-treatment functionality. In this framework, an energy landscape of regional activities, estimated from resting-state endogenous activities by a pairwise maximum entropy model, is used to represent the pre-treatment functionality. The approximation of the pre-treatment functionality occurs via reconfiguration of interactions among neural populations within the treated circuit. To establish the current framework's construct validity, we conducted various simulations. The simulations suggested that brain control should include the self-restoration process, without which the treatment was not optimal. We also presented simulations for optimizing repetitive treatments and optimal timing of the treatment. These results suggest a plausibility of the current framework in controlling the non-linear dynamical brain with a self-restoration process.
in Frontiers in Computational Neuroscience on April 14, 2021 12:00 AM.
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The CA1, an important subregion of the hippocampus, is anatomically and functionally heterogeneous in the dorsal and ventral hippocampus. Here, to dissect the distinctions between the dorsal (dCA1) and ventral CA1 (vCA1) in anatomical connections, we systematically analyzed the direct inputs to dCA1 and vCA1 projection neurons (PNs) with the rabies virus-mediated retrograde trans-monosynaptic tracing system in Thy1-Cre mice. Our mapping results revealed that the input proportions and distributions of dCA1 and vCA1 PNs varied significantly. Inside the hippocampal region, dCA1 and vCA1 PNs shared the same upstream brain regions, but with distinctive distribution patterns along the rostrocaudal axis. The intrahippocampal inputs to the dCA1 and vCA1 exhibited opposite trends, decreasing and increasing gradually along the dorsoventral axis, respectively. For extrahippocampal inputs, dCA1 and vCA1 shared some monosynaptic projections from certain regions such as pallidum, striatum, hypothalamus, and thalamus. However, vCA1, not dCA1, received innervations from the subregions of olfactory areas and amygdala nuclei. Characterization of the direct input networks of dCA1 and vCA1 PNs may provide a structural basis to understand the differential functions of dCA1 and vCA1.
in Frontiers in Neural Circuits on April 14, 2021 12:00 AM.
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in Frontiers in Cellular Neuroscience on April 14, 2021 12:00 AM.
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Neural crest development involves a series of dynamic, carefully coordinated events that result in human disease when not properly orchestrated. Cranial neural crest cells acquire unique multipotent developmental potential upon specification to generate a broad variety of cell types. Studies of early mammalian neural crest and nervous system development often use the Cre-loxP system to lineage trace and mark cells for further investigation. Here, we carefully profile the activity of two common neural crest Cre-drivers at the end of neurulation in mice. RNA sequencing of labeled cells at E9.5 reveals that Wnt1-Cre2 marks cells with neuronal characteristics consistent with neuroepithelial expression, whereas Sox10-Cre predominantly labels the migratory neural crest. We used single-cell mRNA and single-cell ATAC sequencing to profile the expression of Wnt1 and Sox10 and identify transcription factors that may regulate the expression of Wnt1-Cre2 in the neuroepithelium and Sox10-Cre in the migratory neural crest. Our data identify cellular heterogeneity during cranial neural crest development and identify specific populations labeled by two Cre-drivers in the developing nervous system.
in Frontiers in Cellular Neuroscience on April 14, 2021 12:00 AM.
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Alzheimer’s disease (AD) is one of the most frequently diagnosed neurodegenerative disorders worldwide and poses a major challenge for both affected individuals and their caregivers. AD is a progressive neurological disorder associated with high rates of brain atrophy. Despite its durable influence on human health, understanding AD has been complicated by its enigmatic and multifactorial nature. Neurofibrillary tangles and the deposition of amyloid-beta (Aβ) protein are typical pathological features and fundamental causes of cognitive impairment in AD patients. Dysbiosis of oral and gut microbiota has been reported to induce and accelerate the formation of Aβ plaques and neurofibrillary tangles. For instance, some oral microbes can spread to the brain through cranial nerves or cellular infections, which has been suggested to increase the risk of developing AD. Importantly, the interaction between intestinal microbiota and brain cells has been recognized as influencing the development of AD as well as other neurodegenerative diseases. In particular, the metabolites produced by certain intestinal microorganisms can affect the activity of microglia and further mediate neuroinflammation, which is a leading cause of neuronal necrosis and AD pathogenesis. Which pathogens and associated pathways are involved in the development and progression of AD remains to be elucidated; however, it is well-known that gut microbiota and their metabolites can affect the brain by both direct and indirect means. Understanding the specific mechanisms involved in the interaction between these pathogens and the nervous system is vital for the early intervention in AD. In this review, we aim to comprehensively discuss the possible mechanistic pathways underlying the oral-brain, the gut-brain and the oral-gut-brain associations.
in Frontiers in Cellular Neuroscience on April 14, 2021 12:00 AM.
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Stem cell transplantation offers promise in the treatment of ischemic stroke. Here we utilized systematic review, meta-analysis, and meta-regression to study the biological effect of stem cell treatments in animal models of ischemic stroke. A total of 98 eligible publications were included by searching PubMed, EMBASE, and Web of Science from inception to August 1, 2020. There are about 141 comparisons, involving 5,200 animals, that examined the effect of stem cell transplantation on neurological function and infarct volume as primary outcome measures in animal models for stroke. Stem cell-based therapy can improve both neurological function (effect size, −3.37; 95% confidence interval, −3.83 to −2.90) and infarct volume (effect size, −11.37; 95% confidence interval, −12.89 to −9.85) compared with controls. These results suggest that stem cell therapy could improve neurological function deficits and infarct volume, exerting potential neuroprotective effect for experimental ischemic stroke, but further clinical studies are still needed.
in Frontiers in Cellular Neuroscience on April 14, 2021 12:00 AM.
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It is widely thought that brain repair does not occur, but myelin regeneration provides clear evidence to the contrary. Spontaneous remyelination may occur after injury or in multiple sclerosis (MS). However, the efficiency of remyelination varies considerably between MS patients and between the lesions of each patient. Myelin repair is essential for optimal functional recovery, so a profound understanding of the cells and mechanisms involved in this process is required for the development of new therapeutic strategies. In this review, we describe how animal models and modern cell tracing and imaging methods have helped to identify the cell types involved in myelin regeneration. In addition to the oligodendrocyte progenitor cells identified in the 1990s as the principal source of remyelinating cells in the central nervous system (CNS), other cell populations, including subventricular zone-derived neural progenitors, Schwann cells, and even spared mature oligodendrocytes, have more recently emerged as potential contributors to CNS remyelination. We will also highlight the conditions known to limit endogenous repair, such as aging, chronic inflammation, and the production of extracellular matrix proteins, and the role of astrocytes and microglia in these processes. Finally, we will present the discrepancies between observations in humans and in rodents, discussing the relationship of findings in experimental models to myelin repair in humans. These considerations are particularly important from a therapeutic standpoint.
in Frontiers in Cellular Neuroscience on April 14, 2021 12:00 AM.
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The ubiquitin proteasome system (UPS) and FOXOs transcription factors play a pivotal role in cellular clearance and minimizing the accumulation of Aβ in neurodegeneration (ND). In African Americans (AAs) with mild cognitive impairment (MCI), the role of components of UPS and FOXOs; and whether they are amenable to exercise effects is unknown. We hypothesized that exercise can enhance cellular clearance systems during aging and ND by increasing expressions of FBXO32 and FOXO1. To test this hypothesis, we used TaqMan gene expression analysis in peripheral blood (PB) to investigate the component of UPS and FOXOs; and provide mechanistic insight at baseline, during exercise, and in both genders. At baseline, levels of FBXO32 were higher in women than in men. In our attempt to discern gender-specific exercise-related changes, we observed that levels of FBXO32 increased in men but not in women. Similarly, levels of FOXO1 increased in men only. These data suggest that a graded dose of FBXO32 and FOXO1 may be beneficial when PB cells carrying FBXO32 and FOXO1 summon into the brain in response to Alzheimer’s disease (AD) perturbation (docking station PB cells). Our observation is consistent with emerging studies that exercise allows the trafficking of blood factors. Given the significance of FBXO32 and FOXO1 to ND and associated muscle integrity, our findings may explain, at least in part, the benefits of exercise on memory, associated gait, and balance perturbation acknowledged to herald the emergence of MCI.
in Frontiers in Ageing Neuroscience on April 14, 2021 12:00 AM.
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Frailty is a dynamic clinical condition characterized by the reduction of interconnections among different psychobiological domains, which leads to a homeostatic vulnerability. The association between physical frailty and cognitive dysfunctions is a possible predictor of poor prognosis in patients with neurodegenerative disorders. However, this construct has not been fully analyzed by a multidimensional neuropsychogeriatric assessment matched with multimodal neuroimaging methods in patients with behavioral variant frontotemporal dementia (bvFTD). We have investigated cognitive dysfunctions and frailty status, assessed by both a neuropsychological evaluation and the Multidimensional Prognostic Index (MPI), in a sample of 18 bvFTD patients and compared to matched healthy controls. Gray matter (GM) volume (as assessed by voxel-based morphometry) and metabolism (on 18fluorodeoxyglucose positron emission tomography) were first separately compared between groups, then voxelwise compared and correlated to each other within patients. Linear regression of the MPI was performed on those voxels presenting a significant correlation between altered GM volume and metabolism. The neuropsychological assessment reflected the diagnoses and the functional–anatomical alterations documented by neuroimaging analyses. In particular, the majority of patients presented significant executive dysfunction and mood changes in terms of apathy, depression, and anxiety. In the overall MPI score, the patients fell in the lower range (indicating an early frailty status). On imaging, they exhibited a bilateral decrease of GM density and hypometabolism involving the frontal pole, the anterior opercular region, and the anterior cingulate cortex. Greater atrophy than hypometabolism was observed in the bilateral orbitofrontal cortex, the triangular part of the inferior frontal gyrus, and the ventral striatum, whereas the contrary was detected in the bilateral dorsal anterior cingulate cortex and pre-supplementary motor area. MPI scores significantly correlated only with the co-occurrence of a decrease of GM density and hypometabolism in the right anterior insular cortex, but not with the separate pathological phenomena. Our results show a correlation between a specific pattern of co-occurring GM atrophy and hypometabolism with early frailty in bvFTD patients. These aspects, combined with executive dysfunction and mood changes, may lead to an increased risk of poor prognosis, highlighting a potentially critical and precocious role of the insula in the pathogenesis of frailty.
in Frontiers in Ageing Neuroscience on April 14, 2021 12:00 AM.
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An easily scoring system to predict the risk of cognitive impairment after minor ischemic stroke has not been available. We aimed to develop and externally validate a nomogram for predicting the probability of post-stroke cognitive impairment (PSCI) among hospitalized population with minor stroke. Moreover, the association of Trimethylamine N-oxide (TMAO) with PSCI is also investigated. We prospectively conducted a developed cohort on collected data in stroke center from June 2017 to February 2018, as well as an external validation cohort between June 2018 and February 2019. The main outcome is cognitive impairment defined as <22 Montreal Cognition Assessment (MoCA) score points 6 – 12 months following a minor stroke onset. Based on multivariate logistic models, the nomogram model was generated. Plasma TMAO levels were assessed at admission using liquid chromatography tandem mass spectrometry. A total of 228 participants completed the follow-up data for generating the nomogram. After multivariate logistic regression, seven variables remained independent predictors of PSCI to compose the nomogram included age, female, Fazekas score, educational level, number of intracranial atherosclerotic stenosis (ICAS), HbA1c, and cortical infarction. The area under the receiver-operating characteristic (AUC-ROC) curve of model was 0.829, C index was good (0.810), and the AUC-ROC of the model applied in validation cohort was 0.812. Plasma TMAO levels were higher in patients with cognitive impairment than in them without cognitive dysfunction (median 4.56 vs. 3.22 μmol/L; p ≤ 0.001). In conclusion, this scoring system is the first nomogram developed and validated in a stroke center cohort for individualized prediction of cognitive impairment after minor stroke. Higher plasma TMAO level at admission suggests a potential marker of PSCI.
in Frontiers in Ageing Neuroscience on April 14, 2021 12:00 AM.
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The objective of this study was to determine which factors influence brain iron concentrations in deep gray matter in elderly individuals and how these factors influence regional brain iron concentrations.
MethodsA total of 105 elderly individuals were enrolled in this study. All participants underwent detailed magnetic resonance imaging (MRI) examinations from October 2018 to August 2019. Among them, 44 individuals had undergone a previous MRI examination from July 2010 to August 2011. Quantitative susceptibility mapping (QSM) was utilized as an indirect quantitative marker of brain iron, and the susceptibility values of deep gray matter structures were obtained. Univariate analysis and multiple linear regression analysis were used to investigate 11 possible determinants for cerebral iron deposition.
ResultsOur results showed no sex- or hemisphere-related differences in susceptibility values in any of the regions studied. Aging was significantly correlated with increased insusceptibility values in almost all analyzed brain regions (except for the thalamus) when we compared the susceptibility values at the two time points. In a cross-sectional analysis, the relationship between gray matter nucleus susceptibility values and age was conducted using Pearson’s linear regression. Aging was significantly correlated with the susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN), with the Put having the strongest correlations. In multiple linear regression models, associations with increased susceptibility values were found in the CN, Put, red nucleus, and dentate nucleus for individuals with a history of type 2 diabetes mellitus (T2DM). However, the patients with hypertension showed significantly reduced susceptibility values in the red nucleus and dentate nucleus. Our data suggested that smokers had increased susceptibility values in the thalamus. No significant associations were found for individuals with a history of hypercholesterolemia and Apolipoprotein E4 carrier status.
ConclusionOur data revealed that aging, T2DM, and smoking could increase iron deposition in some deep gray matter structures. However, hypertension had the opposite effects in the red nuclei and dentate nuclei. Brain iron metabolism could be influenced by many factors in different modes. In future studies, we should strictly control for confounding factors.
in Frontiers in Ageing Neuroscience on April 14, 2021 12:00 AM.
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in Journal of Neuroscience Research on April 13, 2021 04:24 PM.
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in F1000Research on April 13, 2021 03:15 PM.
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by Sascha Frühholz, Joris Dietziker, Matthias Staib, Wiebke Trost
Across many species, scream calls signal the affective significance of events to other agents. Scream calls were often thought to be of generic alarming and fearful nature, to signal potential threats, with instantaneous, involuntary, and accurate recognition by perceivers. However, scream calls are more diverse in their affective signaling nature than being limited to fearfully alarming a threat, and thus the broader sociobiological relevance of various scream types is unclear. Here we used 4 different psychoacoustic, perceptual decision-making, and neuroimaging experiments in humans to demonstrate the existence of at least 6 psychoacoustically distinctive types of scream calls of both alarming and non-alarming nature, rather than there being only screams caused by fear or aggression. Second, based on perceptual and processing sensitivity measures for decision-making during scream recognition, we found that alarm screams (with some exceptions) were overall discriminated the worst, were responded to the slowest, and were associated with a lower perceptual sensitivity for their recognition compared with non-alarm screams. Third, the neural processing of alarm compared with non-alarm screams during an implicit processing task elicited only minimal neural signal and connectivity in perceivers, contrary to the frequent assumption of a threat processing bias of the primate neural system. These findings show that scream calls are more diverse in their signaling and communicative nature in humans than previously assumed, and, in contrast to a commonly observed threat processing bias in perceptual discriminations and neural processes, we found that especially non-alarm screams, and positive screams in particular, seem to have higher efficiency in speeded discriminations and the implicit neural processing of various scream types in humans.in PLoS Biology on April 13, 2021 02:00 PM.
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in Annals of Neurology on April 13, 2021 12:59 PM.
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in Annals of Neurology on April 13, 2021 12:57 PM.
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in F1000Research on April 13, 2021 06:56 AM.
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in Journal of Neuroscience Research on April 13, 2021 05:20 AM.
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in Journal of Neuroscience Research on April 13, 2021 05:14 AM.
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Olfactory perception is a complicated process involving multiple cortical and subcortical regions, of which the underlying brain dynamics are still not adequately mapped. Even in the definition of the olfactory primary cortex, there is a large degree of variation in parcellation templates used for investigating olfaction in neuroimaging studies. This complicates comparison between human olfactory neuroimaging studies. The present study aims to validate an olfactory parcellation template derived from both functional and anatomical data that applies structural connectivity (SC) to ensure robust connectivity to key secondary olfactory regions. Furthermore, exploratory analyses investigate if different olfactory parameters are associated with differences in the strength of connectivity of this structural olfactory fingerprint. By combining diffusion data with an anatomical atlas and advanced probabilistic tractography, we found that the olfactory parcellation had a robust SC network to key secondary olfactory regions. Furthermore, the study indicates that higher ratings of olfactory significance were associated with increased intra- and inter-hemispheric SC of the primary olfactory cortex. Taken together, these results suggest that the patterns of SC between the primary olfactory cortex and key secondary olfactory regions has potential to be used for investigating the nature of olfactory significance, hence strengthening the theory that individual differences in olfactory behaviour are encoded in the structural network fingerprint of the olfactory cortex.
in Frontiers in Systems Neuroscience on April 13, 2021 12:00 AM.
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The aging process and age-related diseases such as Alzheimer’s disease (AD), are very heterogeneous and multifactorial, making it challenging to diagnose the disease based solely on genetic, behavioral tests, or clinical history. It is yet to be explained what ophthalmological tests relate specifically to aging and AD. To this end, we have selected the common degu (Octodon degus) as a model for aging which develops AD-like signs to conduct ophthalmological screening methods that could be clinical markers of aging and AD. We investigated ocular health using ophthalmoscopy, fundus photography, intraocular pressure (IOP), and pupillary light reflex (PLR). The results showed significant presence of cataracts in adult degus and IOP was also found to increase significantly with advancing age. Age had a significant effect on the maximum pupil constriction but other pupil parameters changed in an age-independent manner (PIPR retention index, resting pupil size, constriction velocity, redilation plateau). We concluded that degus have underlying factors at play that regulate PLR and may be connected to sympathetic, parasympathetic, and melanopsin retinal ganglion cell (ipRGC) deterioration. This study provides the basis for the use of ocular tests as screening methods for the aging process and monitoring of neurodegeneration in non-invasive ways.
in Frontiers in Integrative Neuroscience on April 13, 2021 12:00 AM.
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The locus coeruleus noradrenergic (LC-NA) system is studied for its role in various neurological and psychiatric disorders such as epilepsy and Major Depression Dissorder. Chemogenetics is a powerful technique for specific manipulation of the LC to investigate its functioning. Local injection of AAV2/7 viral vectors has limitations with regards to efficiency and specificity of the transduction, potentially due to low tropism of AAV2/7 for LC neurons. In this study we used a canine adenovirus type 2 (CAV2) vector with different volumes and viral particle numbers to achieve high and selective expression of hM3Dq, an excitatory Designer Receptor Exclusively Activated by Designer Drugs (DREADD), for chemogenetic modulation of LC neurons.
MethodsAdult male Sprague-Dawley rats were injected in the LC with different absolute numbers of CAV2-PRSx8-hM3Dq-mCherry physical particles (0.1E9, 1E9, 5E9,10E9, or 20E9 pp) using different volumes (LowV = 3 nl × 300 nl, MediumV = 3 × 600 nl, HighV = 3 × 1200 nl). Two weeks post-injection, double-labeling immunohistochemistry for dopamine β hydroxylase (DBH) and mCherry was performed to determine hM3Dq expression and its specificity for LC neurons. The size of the transduced LC was compared to the contralateral LC to identify signs of toxicity.
ResultsAdministration of Medium volume (3 × 600 nl) and 1E9 particles resulted in high expression levels with 87.3 ± 9.8% of LC neurons expressing hM3Dq, but low specificity with 36.2 ± 17.3% of hM3Dq expression in non-LC neurons. The most diluted conditions (Low volume_0.1E pp and Medium Volume_0.1E pp) presented similar high transduction of LC neurons (70.9 ± 12.7 and 77.2 ± 9.8%) with lower aspecificity (5.5 ± 3.5 and 4.0 ± 1.9%, respectively). Signs of toxicity were observed in all undiluted conditions as evidenced by a decreased size of the transduced LC.
ConclusionThis study identified optimal conditions (Low and Medium Volume with 0.1E9 particles of CAV2-PRSx8-hM3Dq-mCherry) for safe and specific transduction of LC neurons with excitatory DREADDs to study the role of the LC-NA system in health and disease.
in Frontiers in Neuroscience: Neural Technology on April 13, 2021 12:00 AM.
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The severity of neurocognitive impairment increases with prematurity. However, its mechanisms remain poorly understood. Our aim was firstly to identify multiparametric magnetic resonance imaging (MRI) markers that differ according to the degree of prematurity, and secondly to evaluate the impact of clinical complications on these markers.
Materials and MethodsWe prospectively enrolled preterm infants who were divided into two groups according to their degree of prematurity: extremely preterm (<28 weeks’ gestational age) and very preterm (28–32 weeks’ gestational age). They underwent a multiparametric brain MRI scan at term-equivalent age including morphological, diffusion tensor and arterial spin labeling (ASL) perfusion sequences. We quantified overall and regional volumes, diffusion parameters, and cerebral blood flow (CBF). We then compared the parameters for the two groups. We also assessed the effects of clinical data and potential MRI morphological abnormalities on those parameters.
ResultsThirty-four preterm infants were included. Extremely preterm infants (n = 13) had significantly higher frontal relative volumes (p = 0.04), frontal GM relative volumes (p = 0.03), and regional CBF than very preterm infants, but they had lower brainstem and insular relative volumes (respectively p = 0.008 and 0.04). Preterm infants with WM lesions on MRI had significantly lower overall GM CBF (13.3 ± 2 ml/100 g/min versus 17.7 ± 2.5, < ml/100 g/min p = 0.03).
ConclusionMagnetic resonance imaging brain scans performed at term-equivalent age in preterm infants provide quantitative imaging parameters that differ with respect to the degree of prematurity, related to brain maturation.
in Frontiers in Neuroscience: Brain Imaging Methods on April 13, 2021 12:00 AM.
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Herein, we propose a real-time stable control gait switching method for the exoskeleton rehabilitation robot. Exoskeleton rehabilitation robots have been extensively developed during the past decade and are able to offer valuable motor ability to paraplegics. However, achieving stable states of the human-exoskeleton system while conserving wearer strength remains challenging. The constant switching of gaits during walking may affect the center of gravity, resulting in imbalance of human–exoskeleton system. In this study, it was determined that forming an equilateral triangle with two crutch-supporting points and a supporting leg has a positive impact on walking stability and ergonomic interaction. First, the gaits planning and stability analysis based on human kinematics model and zero moment point method for the lower limb exoskeleton are demonstrated. Second, a neural interface based on surface electromyography (sEMG), which realizes the intention recognition and muscle fatigue estimation, is constructed. Third, the stability of human–exoskeleton system and ergonomic effects are tested through different gaits with planned and unplanned gait switching strategy on the SIAT lower limb rehabilitation exoskeleton. The intention recognition based on long short-term memory (LSTM) model can achieve an accuracy of nearly 99%. The experimental results verified the feasibility and efficiency of the proposed gait switching method for enhancing stability and ergonomic effects of lower limb rehabilitation exoskeleton.
in Frontiers in Neuroscience: Neural Technology on April 13, 2021 12:00 AM.
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A number of studies in recent years have explored whole-brain dynamic connectivity using pairwise approaches. There has been less focus on trying to analyze brain dynamics in higher dimensions over time.
MethodsWe introduce a new approach that analyzes time series trajectories to identify high traffic nodes in a high dimensional space. First, functional magnetic resonance imaging (fMRI) data are decomposed using spatial ICA to a set of maps and their associated time series. Next, density is calculated for each time point and high-density points are clustered to identify a small set of high traffic nodes. We validated our method using simulations and then implemented it on a real data set.
ResultsWe present a novel approach that captures dynamics within a high dimensional space and also does not use any windowing in contrast to many existing approaches. The approach enables one to characterize and study the time series in a potentially high dimensional space, rather than looking at each component pair separately. Our results show that schizophrenia patients have a lower dynamism compared to healthy controls. In addition, we find patients spend more time in nodes associated with the default mode network and less time in components strongly correlated with auditory and sensorimotor regions. Interestingly, we also found that subjects oscillate between state pairs that show opposite spatial maps, suggesting an oscillatory pattern.
ConclusionOur proposed method provides a novel approach to analyze the data in its native high dimensional space and can possibly provide new information that is undetectable using other methods.
in Frontiers in Neuroscience: Brain Imaging Methods on April 13, 2021 12:00 AM.
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Neurotransmitter transporters limit spillover between synapses and maintain the extracellular neurotransmitter concentration at low yet physiologically meaningful levels. They also exert a key role in providing precursors for neurotransmitter biosynthesis. In many cases, neurons and astrocytes contain a large intracellular pool of transporters that can be redistributed and stabilized in the plasma membrane following activation of different signaling pathways. This means that the uptake capacity of the brain neuropil for different neurotransmitters can be dynamically regulated over the course of minutes, as an indirect consequence of changes in neuronal activity, blood flow, cell-to-cell interactions, etc. Here we discuss recent advances in the mechanisms that control the cell membrane trafficking and biophysical properties of transporters for the excitatory, inhibitory and modulatory neurotransmitters glutamate, GABA, and dopamine.
in Frontiers in Cellular Neuroscience on April 13, 2021 12:00 AM.
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Objective: To examine whether prefrontal electroencephalography (EEG) can be used for screening dementia.
Methods: We estimated the global cognitive decline using the results of Mini-Mental Status Examination (MMSE), measurements of brain activity from resting-state EEG, responses elicited by auditory stimulation [sensory event-related potential (ERP)], and selective attention tasks (selective-attention ERP) from 122 elderly participants (dementia, 35; control, 87). We investigated that the association between MMSE and each EEG/ERP variable by using Pearson’s correlation coefficient and performing univariate linear regression analysis. Kernel density estimation was used to examine the distribution of each EEG/ERP variable in the dementia and non-dementia groups. Both Univariate and multiple logistic regression analyses with the estimated odds ratios were conducted to assess the associations between the EEG/ERP variables and dementia prevalence. To develop the predictive models, five-fold cross-validation was applied to multiple classification algorithms.
Results: Most prefrontal EEG/ERP variables, previously known to be associated with cognitive decline, show correlations with the MMSE score (strongest correlation has |r| = 0.68). Although variables such as the frontal asymmetry of the resting-state EEG are not well correlated with the MMSE score, they indicate risk factors for dementia. The selective-attention ERP and resting-state EEG variables outperform the MMSE scores in dementia prediction (areas under the receiver operating characteristic curve of 0.891, 0.824, and 0.803, respectively). In addition, combining EEG/ERP variables and MMSE scores improves the model predictive performance, whereas adding demographic risk factors do not improve the prediction accuracy.
Conclusion: Prefrontal EEG markers outperform MMSE scores in predicting dementia, and additional prediction accuracy is expected when combining them with MMSE scores.
Significance: Prefrontal EEG is effective for screening dementia when used independently or in combination with MMSE.
in Frontiers in Ageing Neuroscience on April 13, 2021 12:00 AM.
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Purpose: Imaging of the choroid may detect the microvascular changes associated with early-onset dementia (EOD) and may represent an indicator for detection of the disease. We aimed to analyze the in vivo choriocapillaris (CC) flow density in EOD patients using optical coherence tomography angiography (OCTA) and evaluate the association with its clinical measures.
Methods: This cross-sectional study used the OCTA to image and analyze the choriocapillaris (CC) of 25 EOD patients and 20 healthy controls. Choriocapillaris flow density in the 3 mm area and 6 mm area was measured by an inbuilt algorithm in the OCT tool. Brain volume using magnetic resonance imaging and cognitive assessment was done and recorded.
Results: Significantly reduced capillary flow density of the choriocapillaris was seen in EOD patients when compared to healthy controls in the 3.0 mm (P = 0.001) and 6.0 mm (P < 0.001) area respectively. Montreal Cognitive Assessment (MoCA) scores in EOD patients positively correlated with choriocapillaris flow density in the 3 mm area (Rho = 0.466, P = 0.021). Disease duration of EOD patients also negatively correlated with choriocapillaris density in the 3 mm area (Rho = −0.497, P = 0.008).
Discussion: Our report suggests that choriocapillaris damage may be a potential indicator of early-onset dementia. Microvascular impairment may be involved in the early phase of dementia without aging playing a role in its impairment.
Clinical Trial Registration: www.ClinicalTrials.gov, ChiCTR2000041386.
in Frontiers in Ageing Neuroscience on April 13, 2021 12:00 AM.
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Intracerebral hemorrhage (ICH) is the most fatal subtype of stroke with high disability and high mortality rates, and there is no effective treatment. The predilection site of ICH is in the area of the basal ganglia and internal capsule (IC), where exist abundant white matter (WM) fiber tracts, such as the corticospinal tract (CST) in the IC. Proximal or distal white matter injury (WMI) caused by intracerebral parenchymal hemorrhage is closely associated with poor prognosis after ICH, especially motor and sensory dysfunction. The pathophysiological mechanisms involved in WMI are quite complex and still far from clear. In recent years, the neuroprotection and repairment capacity of mesenchymal stem cells (MSCs) has been widely investigated after ICH. MSCs exert many unique biological effects, including self-recovery by producing growth factors and cytokines, regenerative repair, immunomodulation, and neuroprotection against oxidative stress, providing a promising cellular therapeutic approach for the treatment of WMI. Taken together, our goal is to discuss the characteristics of WMI following ICH, including the mechanism and potential promising therapeutic targets of MSCs, aiming at providing new clues for future therapeutic strategies.
in Frontiers in Ageing Neuroscience on April 13, 2021 12:00 AM.
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Currently there is a shortage of biomarkers for stroke, one of the leading causes of death and disability in aging populations. Retinal vessels offer a unique and accessible “window” to study the microvasculature in vivo. However, the relationship between the retinal microvasculature and stroke is not entirely clear. To investigate the retinal microvascular characteristics in stroke, we recruited patients with stroke and age-matched control subjects from a tertiary hospital in China. The macular vessel density (VD) in the superficial capillary plexus (SCP) and deep capillary plexus (DCP), foveal avascular zone (FAZ) metrics, and optical coherence tomography angiography (OCTA) measured optic disc VD were recorded for analysis. A total of 189 patients with stroke and 195 control subjects were included. After adjusting for sex, visual acuity, systolic and diastolic blood pressure, a history of smoking, levels of hemoglobulin (HbA1c), cholesterol, and high-density lipoprotein (HDL), the macular VD of SCP and DCP in all sectors was decreased in patients with stroke. In the stroke group, the VD around the FAZ and the VD of the optic disk were lower. Logistic regression found the parafovea-superior-hemi VD of DCP > 54.53% [odds ratio (OR): 0.169] as a protective factor of stroke. Using the integration of all OCTA parameters and traditional risk factors, the area under the receiver operating characteristic (AUC) curve of distinguishing patients with stroke was 0.962, with a sensitivity of 0.944 and a specificity of 0.871. Our study demonstrates that the retinal VD is decreased in patients with stroke independently of the traditional risk factors of stroke, which may shed light on the monitoring of stroke using the retinal microvascular parameters.
in Frontiers in Ageing Neuroscience on April 13, 2021 12:00 AM.
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Background: There has been an increasing interest in studying electroencephalogram (EEG) as a biomarker of Alzheimer’s disease but the association between EEG signals and patients’ neuropsychiatric symptoms remains unclear. We studied EEG signals of patients with Alzheimer’s disease to explore the associations between patients’ neuropsychiatric symptoms and clusters of patients based on their EEG powers.
Methods: A total of 69 patients with mild Alzheimer’s disease (the Clinical Dementia Rating = 1) were enrolled and their EEG signals from 19 channels/electrodes were recorded in three sessions for each patient. The EEG power was calculated by Fourier transform for the four frequency bands (beta: 13–40 Hz, alpha: 8–13 Hz, theta: 4–8 Hz, and delta: <4 Hz). We performed K-means cluster analysis to classify the 69 patients into two distinct groups by the log-transformed EEG powers (4 frequency bands × 19 channels) for the three EEG sessions. In each session, both clusters were compared with each other to assess the differences in their behavioral/psychological symptoms in terms of the Neuropsychiatric Inventory (NPI) score.
Results: While EEG band powers were highly consistent across all three sessions before clustering, EEG band powers were different between the two clusters in each session, especially for the delta waves. The delta band powers differed significantly between the two clusters in most channels across the three sessions. Patients’ demographics and cognitive function were not different between both clusters. However, their behavioral/psychological symptoms were different between the two clusters classified based on EEG powers. A higher NPI score was associated with the clustering of higher EEG powers.
Conclusion: The present study suggests that EEG power correlates to behavioral and psychological symptoms among patients with mild Alzheimer’s disease. The clustering approach of EEG signals may provide a novel and cost-effective method to differentiate the severity of neuropsychiatric symptoms and/or predict the prognosis for Alzheimer’s patients.
in Frontiers in Ageing Neuroscience on April 13, 2021 12:00 AM.
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in Journal of Neuroscience Research on April 12, 2021 08:49 PM.
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in F1000Research on April 12, 2021 04:07 PM.
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in F1000Research on April 12, 2021 03:08 PM.
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in Hippocampus on April 12, 2021 02:59 PM.
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in F1000Research on April 12, 2021 02:48 PM.
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in F1000Research on April 12, 2021 02:11 PM.
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by Steffen Lange, Benjamin M. Friedrich
Sperm of marine invertebrates have to find eggs cells in the ocean. Turbulent flows mix sperm and egg cells up to the millimeter scale; below this, active swimming and chemotaxis become important. Previous work addressed either turbulent mixing or chemotaxis in still water. Here, we present a general theory of sperm chemotaxis inside the smallest eddies of turbulent flow, where signaling molecules released by egg cells are spread into thin concentration filaments. Sperm cells ‘surf’ along these filaments towards the egg. External flows make filaments longer, but also thinner. These opposing effects set an optimal flow strength. The optimum predicted by our theory matches flow measurements in shallow coastal waters. Our theory quantitatively agrees with two previous fertilization experiments in Taylor-Couette chambers and provides a mechanistic understanding of these early experiments. ‘Surfing along concentration filaments’ could be a paradigm for navigation in complex environments in the presence of turbulent flow.in PLoS Computational Biology on April 12, 2021 02:00 PM.
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by Maria Kleshnina, Sabrina S. Streipert, Jerzy A. Filar, Krishnendu Chatterjee
A game of rock-paper-scissors is an interesting example of an interaction where none of the pure strategies strictly dominates all others, leading to a cyclic pattern. In this work, we consider an unstable version of rock-paper-scissors dynamics and allow individuals to make behavioural mistakes during the strategy execution. We show that such an assumption can break a cyclic relationship leading to a stable equilibrium emerging with only one strategy surviving. We consider two cases: completely random mistakes when individuals have no bias towards any strategy and a general form of mistakes. Then, we determine conditions for a strategy to dominate all other strategies. However, given that individuals who adopt a dominating strategy are still prone to behavioural mistakes in the observed behaviour, we may still observe extinct strategies. That is, behavioural mistakes in strategy execution stabilise evolutionary dynamics leading to an evolutionary stable and, potentially, mixed co-existence equilibrium.in PLoS Computational Biology on April 12, 2021 02:00 PM.
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by Rui Pang, Ke Xing, Longyu Yuan, Zhikun Liang, Meng Chen, Xiangzhao Yue, Yi Dong, Yan Ling, Xionglei He, Xianchun Li, Wenqing Zhang
Chemical insecticides have been heavily employed as the most effective measure for control of agricultural and medical pests, but evolution of resistance by pests threatens the sustainability of this approach. Resistance-conferring mutations sometimes impose fitness costs, which may drive subsequent evolution of compensatory modifier mutations alleviating the costs of resistance. However, how modifier mutations evolve and function to overcome the fitness cost of resistance still remains unknown. Here we show that overexpression of P450s not only confers imidacloprid resistance in the brown planthopper, Nilaparvata lugens, the most voracious pest of rice, but also leads to elevated production of reactive oxygen species (ROS) through metabolism of imidacloprid and host plant compounds. The inevitable production of ROS incurs a fitness cost to the pest, which drives the increase or fixation of the compensatory modifier allele T65549 within the promoter region of N. lugens peroxiredoxin (NlPrx) in the pest populations. T65549 allele in turn upregulates the expression of NlPrx and thus increases resistant individuals’ ability to clear the cost-incurring ROS of any source. The frequent involvement of P450s in insecticide resistance and their capacity to produce ROS while metabolizing their substrates suggest that peroxiredoxin or other ROS-scavenging genes may be among the common modifier genes for alleviating the fitness cost of insecticide resistance.in PLoS Biology on April 12, 2021 02:00 PM.
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by Julius Kostan, Miha Pavšič, Vid Puž, Thomas C. Schwarz, Friedel Drepper, Sibylle Molt, Melissa Ann Graewert, Claudia Schreiner, Sara Sajko, Peter F. M. van der Ven, Adekunle Onipe, Dmitri I. Svergun, Bettina Warscheid, Robert Konrat, Dieter O. Fürst, Brigita Lenarčič, Kristina Djinović-Carugo
Sarcomeres, the basic contractile units of striated muscle cells, contain arrays of thin (actin) and thick (myosin) filaments that slide past each other during contraction. The Ig-like domain-containing protein myotilin provides structural integrity to Z-discs—the boundaries between adjacent sarcomeres. Myotilin binds to Z-disc components, including F-actin and α-actinin-2, but the molecular mechanism of binding and implications of these interactions on Z-disc integrity are still elusive. To illuminate them, we used a combination of small-angle X-ray scattering, cross-linking mass spectrometry, and biochemical and molecular biophysics approaches. We discovered that myotilin displays conformational ensembles in solution. We generated a structural model of the F-actin:myotilin complex that revealed how myotilin interacts with and stabilizes F-actin via its Ig-like domains and flanking regions. Mutant myotilin designed with impaired F-actin binding showed increased dynamics in cells. Structural analyses and competition assays uncovered that myotilin displaces tropomyosin from F-actin. Our findings suggest a novel role of myotilin as a co-organizer of Z-disc assembly and advance our mechanistic understanding of myotilin’s structural role in Z-discs.in PLoS Biology on April 12, 2021 02:00 PM.
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in F1000Research on April 12, 2021 01:43 PM.
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in F1000Research on April 12, 2021 01:26 PM.
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in Annals of Neurology on April 12, 2021 12:54 PM.
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in F1000Research on April 12, 2021 12:41 PM.
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in F1000Research on April 12, 2021 12:37 PM.
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in F1000Research on April 12, 2021 12:27 PM.
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Author(s): Enrico Skoruppa, Aderik Voorspoels, Jocelyne Vreede, and Enrico Carlon
We investigate the influence of nonlocal couplings on the torsional and bending elasticities of DNA. Such couplings have been observed in the past by several simulation studies. Here, we use a description of DNA conformations based on the variables tilt, roll, and twist. Our analysis of both coarse-...
[Phys. Rev. E 103, 042408] Published Mon Apr 12, 2021
in Physical Review E: Biological physics on April 12, 2021 10:00 AM.
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Author(s): Lei Gu and Ruqian Wu
Despite the recognition of the layered structure and evident criticality in the cortex, how the specification of input, output, and computational layers affects the self-organized criticality has not been much explored. By constructing heterogeneous structures with a well-accepted model of leaky neu...
[Phys. Rev. E 103, 042407] Published Mon Apr 12, 2021
in Physical Review E: Biological physics on April 12, 2021 10:00 AM.
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in F1000Research on April 12, 2021 08:20 AM.
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in Journal of Comparative Neurology on April 12, 2021 08:10 AM.
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in Journal of Comparative Neurology on April 12, 2021 07:53 AM.
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in F1000Research on April 12, 2021 07:52 AM.
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Nature Neuroscience, Published online: 12 April 2021; doi:10.1038/s41593-021-00832-6
Wingo et al. integrate depression GWAS results with human brain proteomes to perform proteome-wide association studies followed by Mendelian randomization. They identify 25 proteins as potential causal mediators of depression, of which 20 are new.in Nature Neuroscience on April 12, 2021 12:00 AM.
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Nature Neuroscience, Published online: 12 April 2021; doi:10.1038/s41593-021-00831-7
McNamee et al. develop a theory of entorhinal–hippocampal processing. Distributed entorhinal input drives hippocampal activity between distinct statistical and dynamical regimes of activity, thereby unifying several empirical observations.in Nature Neuroscience on April 12, 2021 12:00 AM.
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Nature Reviews Neuroscience, Published online: 12 April 2021; doi:10.1038/s41583-021-00454-8
The impairment of brain fluid homeostasis is a feature of various conditions, highlighting the need to better understand brain water transport for drug development. Here, Nanna MacAulay reviews the molecular mechanisms underlying transmembrane water movement in neurons and glia and across brain barriers, emphasizing the part played by water cotransporters in this process.in Nature Reviews on April 12, 2021 12:00 AM.
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Nature Physics, Published online: 12 April 2021; doi:10.1038/s41567-021-01216-0
Transport and thermodynamic measurements on strongly correlated Kondo metal YbB12 reveal the coexistence of charged and charge-neutral fermions in the material and the crucial role played by the latter in the quantum oscillations of resistivity.in Nature Physics on April 12, 2021 12:00 AM.
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Nature Physics, Published online: 12 April 2021; doi:10.1038/s41567-021-01215-1
A computational framework draws analogy with foams to offer a comprehensive picture of how cell behaviours influence fluidization in embryonic tissues, highlighting the role of tension fluctuations in regulating tissue rigidity.in Nature Physics on April 12, 2021 12:00 AM.
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Nature Physics, Published online: 12 April 2021; doi:10.1038/s41567-021-01198-z
Measurements of the proton’s spin structure in experiments scattering a polarized electron beam off polarized protons in regions of low momentum transfer squared test predictions from chiral effective field theory of the strong interaction.in Nature Physics on April 12, 2021 12:00 AM.
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Nature Photonics, Published online: 12 April 2021; doi:10.1038/s41566-021-00796-w
Linear diffractive structures are by themselves passive systems but researchers here exploit the non-linearity of a photodetector to realize a reconfigurable diffractive ‘processing’ unit. High-speed image and video recognition is demonstrated.in Nature Photomics on April 12, 2021 12:00 AM.
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Aggregation of α-synuclein (αSyn) into proteinaceous deposits is a pathological hallmark of a range of neurodegenerative diseases including Parkinson’s disease (PD). Numerous lines of evidence indicate that the accumulation of toxic oligomeric and prefibrillar αSyn species may underpin the cellular toxicity and spread of pathology between cells. Therefore, aggregation of αSyn is considered a priority target for drug development, as aggregation inhibitors are expected to reduce αSyn toxicity and serve as therapeutic agents. Here, we used the budding yeast S. cerevisiae as a platform for the identification of short peptides that inhibit αSyn aggregation and toxicity. A library consisting of approximately one million peptide variants was utilized in two high-throughput screening approaches for isolation of library representatives that reduce αSyn-associated toxicity and aggregation. Seven peptides were isolated that were able to suppress specifically αSyn toxicity and aggregation in living cells. Expression of the peptides in yeast reduced the accumulation of αSyn-induced reactive oxygen species and increased cell viability. Next, the peptides were chemically synthesized and probed for their ability to modulate αSyn aggregation in vitro. Two synthetic peptides, K84s and K102s, of 25 and 19 amino acids, respectively, significantly inhibited αSyn oligomerization and aggregation at sub-stoichiometric molar ratios. Importantly, K84s reduced αSyn aggregation in human cells. These peptides represent promising αSyn aggregation antagonists for the development of future therapeutic interventions.
in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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Hypoxic-ischemia (HI) is a major cause of acquired visual impairment in children from developed countries. Previous studies have shown that systemic administration of 7,8-dihydroxyavone (DHF), a selective tropomyosin receptor kinase B (TrkB) agonist, provides long-term neuroprotection against HI injury in an immature retina. However, the target genes and the mechanisms of the neuroprotective effects of TrkB signaling are not known. In the present study, we induced an HI retinal injury through unilateral common carotid artery ligation followed by 8% oxygen for 2 h in P7 rat pups. DHF was administered intraperitoneally 2 h before and 18 h after the HI injury. A polymerase chain reaction (PCR) array was used to identify the target genes upregulated after the DHF treatment, which was then confirmed with quantitative real-time reverse transcriptase PCR and a western blot. Effects of the downstream mediator of DHF were assessed using an intravitreal injection of neutralizing antibody 4 h after DHF administration (24 h after HI). Meanwhile, the target protein was injected into the vitreous 24 h after HI to validate its protective effect when exogenously supplemented. We found that systemic DHF treatment after HI significantly increased the expression of the artemin (ARTN) gene and protein at P8 and P10, respectively. The neuroprotective effects of DHF were inhibited after the ARTN protein blockade, with an increase in neuroinflammation and astrogliosis. ARTN treatment showed long-term protection against HI injury at both the histopathological and functional levels. The neuroprotective effects of ARTN were related to a decrease in microglial activation at P17 and attenuation of astrogliosis at P29. ARTN enhances phosphorylation of RET, ERK, and JNK, but not AKT or p38 in the immature retina. Altogether, these results suggest that the neuroprotective effect of a TrkB agonist is partially exerted through a mechanism that involves ARTN because the protective effect is ameliorated by ARTN sequestration. ARTN treatment after HI injury protects the immature retina by attenuating late neuroinflammation and astrogliosis in the immature retina relating to the ARTN/RET/JNK/ERK signaling pathway. ARTN may be a strategy by which to provide long-term protection in the immature retina against HI injury.
in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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The cerebellum harbors a circadian clock that can be shifted by scheduled mealtime and participates in behavioral anticipation of food access. Large-scale two-dimensional difference gel electrophoresis (2D-DIGE) combined with mass spectrometry was used to identify day–night variations in the cerebellar proteome of mice fed either during daytime or nighttime. Experimental conditions led to modified expression of 89 cerebellar proteins contained in 63 protein spots. Five and 33 spots were changed respectively by time-of-day or feeding conditions. Strikingly, several proteins of the heat-shock protein family (i.e., Hsp90aa1, 90ab1, 90b1, and Hspa2, 4, 5, 8, 9) were down-regulated in the cerebellum of daytime food-restricted mice. This was also the case for brain fatty acid protein (Fabp7) and enzymes involved in oxidative phosphorylation (Ndufs1) or folate metabolism (Aldh1l1). In contrast, aldolase C (Aldoc or zebrin II) and pyruvate carboxylase (Pc), two enzymes involved in carbohydrate metabolism, and vesicle-fusing ATPase (Nsf) were up-regulated during daytime restricted feeding, possibly reflecting increased neuronal activity. Significant feeding × time-of-day interactions were found for changes in the intensity of 20 spots. Guanine nucleotide-binding protein G(o) subunit alpha (Gnao1) was more expressed in the cerebellum before food access. Neuronal calcium-sensor proteins [i.e., parvalbumin (Pvalb) and visinin-like protein 1 (Vsnl1)] were inversely regulated in daytime food-restricted mice, compared to control mice fed at night. Furthermore, expression of three enzymes modulating the circadian clockwork, namely heterogeneous nuclear ribonucleoprotein K (Hnrnpk), serine/threonine-protein phosphatases 1 (Ppp1cc and Ppp1cb subunits) and 5 (Ppp5), was differentially altered by daytime restricted feeding. Besides cerebellar proteins affected only by feeding conditions or daily cues, specific changes in in protein abundance before food access may be related to behavioral anticipation of food access and/or feeding-induced shift of the cerebellar clockwork.
in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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Altered function or presence of inhibitory neurons is documented in autism spectrum disorders (ASD), but the mechanism underlying this alternation is poorly understood. One major subtype of inhibitory neurons altered is the parvalbumin (PV)-containing neurons with reduced density and intensity in ASD patients and model mice. A subpopulation of PV+ neurons expresses perineuronal nets (PNN). To better understand whether the relationship between PV and PNN is altered in ASD, we measured quantitatively the intensities of PV and PNN in single PV+ neurons in the prelimbic prefrontal cortex (PrL-PFC) of a valproic acid (VPA) model of ASD at different ages. We found a decreased PV intensity but increased PNN intensity in VPA mice. The relationship between PV and PNN intensities is altered in VPA mice, likely due to an “abnormal” subpopulation of neurons with an altered PV-PNN relationship. Furthermore, reducing PNN level using in vivo injection of chondroitinase ABC corrects the PV expression in adult VPA mice. We suggest that the interaction between PV and PNN is disrupted in PV+ neurons in VPA mice which may contribute to the pathology in ASD.
in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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Alzheimer’s disease (AD) is the most common cause of dementia in the aging population. Evidence implicates elevated soluble oligomeric Aβ as one of the primary triggers during the prodromic phase leading to AD, effected largely via hyperphosphorylation of the microtubule-associated protein tau. At low, physiological levels (pM-nM), however, oligomeric Aβ has been found to regulate synaptic plasticity as a neuromodulator. Through mutational analysis, we found a core hexapeptide sequence within the N-terminal domain of Aβ (N-Aβcore) accounting for its physiological activity, and subsequently found that the N-Aβcore peptide is neuroprotective. Here, we characterized the neuroprotective potential of the N-Aβcore against dysfunction of synaptic plasticity assessed in ex vivo hippocampal slices from 5xFAD APP/PS1 mice, specifically hippocampal long-term potentiation (LTP) and long-term depression (LTD). The N-Aβcore was shown to reverse impairment in synaptic plasticity in hippocampal slices from 5xFAD APP/PS1 model mice, both for LTP and LTD. The reversal by the N-Aβcore correlated with alleviation of downregulation of hippocampal AMPA-type glutamate receptors in preparations from 5xFAD mice. The action of the N-Aβcore depended upon a critical di-histidine sequence and involved the phosphoinositide-3 (PI3) kinase pathway via mTOR (mammalian target of rapamycin). Together, the present findings indicate that the non-toxic N-Aβcore hexapeptide is not only neuroprotective at the cellular level but is able to reverse synaptic dysfunction in AD-like models, specifically alterations in synaptic plasticity.
in Frontiers in Molecular Neuroscience on April 12, 2021 12:00 AM.
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Neural interfacing devices using penetrating microelectrode arrays have emerged as an important tool in both neuroscience research and medical applications. These implantable microelectrode arrays enable communication between man-made devices and the nervous system by detecting and/or evoking neuronal activities. Recent years have seen rapid development of electrodes fabricated using flexible, ultrathin carbon-based microfibers. Compared to electrodes fabricated using rigid materials and larger cross-sections, these microfiber electrodes have been shown to reduce foreign body responses after implantation, with improved signal-to-noise ratio for neural recording and enhanced resolution for neural stimulation. Here, we review recent progress of carbon-based microfiber electrodes in terms of material composition and fabrication technology. The remaining challenges and future directions for development of these arrays will also be discussed. Overall, these microfiber electrodes are expected to improve the longevity and reliability of neural interfacing devices.
in Frontiers in Neuroscience: Neural Technology on April 12, 2021 12:00 AM.
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In neurodegenerative diseases, neurodegeneration has been related to several mitochondrial dynamics imbalances such as excessive fragmentation of mitochondria, impaired mitophagy, and blocked mitochondria mitochondrial transport in axons. Mitochondria are dynamic organelles, and essential for energy conversion, neuron survival, and cell death. As mitochondrial dynamics have a significant influence on homeostasis, in this review, we mainly discuss the role of mitochondrial dynamics in several neurodegenerative diseases. There is evidence that several mitochondrial dynamics-associated proteins, as well as related pathways, have roles in the pathological process of neurodegenerative diseases with an impact on mitochondrial functions and metabolism. However, specific pathological mechanisms need to be better understood in order to propose new therapeutic strategies targeting mitochondrial dynamics that have shown promise in recent studies.
in Frontiers in Neuroscience: Neurodegeneration on April 12, 2021 12:00 AM.
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Deep convolutional neural networks (DCNNs) are widely utilized for the semantic segmentation of dense nerve tissues from light and electron microscopy (EM) image data; the goal of this technique is to achieve efficient and accurate three-dimensional reconstruction of the vasculature and neural networks in the brain. The success of these tasks heavily depends on the amount, and especially the quality, of the human-annotated labels fed into DCNNs. However, it is often difficult to acquire the gold standard of human-annotated labels for dense nerve tissues; human annotations inevitably contain discrepancies or even errors, which substantially impact the performance of DCNNs. Thus, a novel boosting framework consisting of a DCNN for multilabel semantic segmentation with a customized Dice-logarithmic loss function, a fusion module combining the annotated labels and the corresponding predictions from the DCNN, and a boosting algorithm to sequentially update the sample weights during network training iterations was proposed to systematically improve the quality of the annotated labels; this framework eventually resulted in improved segmentation task performance. The microoptical sectioning tomography (MOST) dataset was then employed to assess the effectiveness of the proposed framework. The result indicated that the framework, even trained with a dataset including some poor-quality human-annotated labels, achieved state-of-the-art performance in the segmentation of somata and vessels in the mouse brain. Thus, the proposed technique of artificial intelligence could advance neuroscience research.
in Frontiers in Neuroscience: Brain Imaging Methods on April 12, 2021 12:00 AM.
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This study aims to investigate the agreement of three software packages in measuring baseline ischemic core volume (ICV) and penumbra volume (PV), and determine their predictive values for unfavorable clinical outcome in patients with endovascular thrombectomy (EVT).
MethodsPatients with acute ischemic stroke who underwent computed tomographic perfusion (CTP) were recruited. Baseline CTP measurements including ICV and PV were calculated by three software packages of IntelliSpace Portal (ISP), Rapid Processing of Perfusion and Diffusion (RAPID), and fast-processing of ischemic stroke (F-STROKE). All patients received EVT, and the modified Rankin scale (mRS) at 90 days after EVT was assessed to determine the clinical outcomes (favorable: mRS = 0–2; unfavorable: mRS = 3–6). The agreement of CTP measurements among three software packages was determined using intraclass correlation coefficient (ICC). The associations between CTP measurements and unfavorable clinical outcome were analyzed using logistic regression. Receiver operating characteristic curves were conducted to calculate the area under the curve (AUC) of CTP measurements in predicting unfavorable clinical outcome.
ResultsOf 223 recruited patients (68.2 ± 11.3 years old; 145 males), 17.0% had unfavorable clinical outcome after EVT. Excellent agreement between F-STROKE and RAPID was found in measuring ICV (ICC 0.965; 95% CI 0.956–0.973) and PV (ICC 0.966; 95% CI 0.956–0.973). ICVs measured by three software packages were significantly associated with unfavorable clinical outcome before (odds ratios 1.012–1.018, all P < 0.01) and after (odds ratios 1.003–1.014, all P < 0.05) adjusted for confounding factors (age, gender, TOAST classification, and NIHSS on admission). In predicting unfavorable clinical outcome, ICV measured by F-STROKE showed similar performance to that measured by RAPID (AUC 0.701 vs. 0.717) but higher performance than that measured by ISP (AUC 0.629).
ConclusionsThe software of F-STROKE has excellent agreement with the widely used analysis tool of RAPID in measuring ICV and PV. The ischemic core volume measured by both F-STROKE and RAPID is a stronger predictor for unfavorable clinical outcome after EVT compared to ISP.
in Frontiers in Neuroscience: Brain Imaging Methods on April 12, 2021 12:00 AM.
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To evaluate the prevalence and treatment patterns of speech and language disorders in Germany.
MethodsA retrospective analysis of data collected from 32% of the German population, insured by the statutory German health insurance (AOK, Local Health Care Funds). We used The International Statistical Classification of Diseases and Related Health Problems, 10th revision, German Modification (ICD-10 GM) codes for stuttering (F98.5), cluttering (F98.6), and developmental disorders of speech and language (F80) to identify prevalent and newly diagnosed cases each year. Prescription and speech therapy reimbursement data were used to evaluate treatment patterns.
ResultsIn 2017, 27,977 patients of all ages were diagnosed with stuttering (21,045 males, 75% and 6,932 females, 25%). Stuttering prevalence peaks at age 5 years (boys, 0.89% and girls, 0.40%). Cluttering was diagnosed in 1,800 patients of all ages (1,287 males, 71.5% and 513 females, 28.5%). Developmental disorders of speech and language were identified in 555,774 AOK-insurants (61.2% males and 38.8% females). Treatment data indicate a substantial proportion newly diagnosed stuttering individuals receive treatment (up to 45% of 6-year-old patients), with slightly fewer than 20 sessions per year, on average. We confirmed a previous study showing increased rates of atopic disorders and neurological and psychiatric comorbidities in individuals with stuttering, cluttering, and developmental disorders of speech and language.
ConclusionThis is the first nationwide study using health insurance data to analyze the prevalence and newly diagnosed cases of a speech and language disorder. Prevalence and gender ratio data were consistent with the international literature. The crude prevalence of developmental disorders of speech and language increased from 2015 to 2018, whereas the crude prevalence for stuttering remained stable. For cluttering, the numbers were too low to draw reliable conclusions. Proportional treatment allocation for stuttering peaked at 6 years of age, which is the school entrance year, and is later than the prevalence peak of stuttering.
in Frontiers in Human Neuroscience on April 12, 2021 12:00 AM.
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Purpose: The cognitive effects of total sleep deprivation (TSD) on the brain remain poorly understood. Electroencephalography (EEG) is a very useful tool for detecting spontaneous brain activity in the resting state. Quasi-stable electrical distributions, known as microstates, carry useful information about the dynamics of large-scale brain networks. In this study, microstate analysis was used to study changes in brain activity after 24 h of total sleep deprivation.
Participants and Methods: Twenty-seven healthy volunteers were recruited and underwent EEG scans before and after 24 h of TSD. Microstate analysis was applied, and six microstate classes (A–F) were identified. Topographies and temporal parameters of the microstates were compared between the rested wakefulness (RW) and TSD conditions.
Results: Microstate class A (a right-anterior to left-posterior orientation of the mapped field) showed lower global explained variance (GEV), frequency of occurrence, and time coverage in TSD than RW, whereas microstate class D (a fronto-central extreme location of the mapped field) displayed higher GEV, frequency of occurrence, and time coverage in TSD compared to RW. Moreover, subjective sleepiness was significantly negatively correlated with the microstate parameters of class A and positively correlated with the microstate parameters of class D. Transition analysis revealed that class B exhibited a higher probability of transition than did classes D and F in TSD compared to RW.
Conclusion: The observation suggests alterations of the dynamic brain-state properties of TSD in healthy young male subjects, which may serve as system-level neural underpinnings for cognitive declines in sleep-deprived subjects.
in Frontiers in Human Neuroscience on April 12, 2021 12:00 AM.
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Experimental studies support the notion of spike-based neuronal information processing in the brain, with neural circuits exhibiting a wide range of temporally-based coding strategies to rapidly and efficiently represent sensory stimuli. Accordingly, it would be desirable to apply spike-based computation to tackling real-world challenges, and in particular transferring such theory to neuromorphic systems for low-power embedded applications. Motivated by this, we propose a new supervised learning method that can train multilayer spiking neural networks to solve classification problems based on a rapid, first-to-spike decoding strategy. The proposed learning rule supports multiple spikes fired by stochastic hidden neurons, and yet is stable by relying on first-spike responses generated by a deterministic output layer. In addition to this, we also explore several distinct, spike-based encoding strategies in order to form compact representations of presented input data. We demonstrate the classification performance of the learning rule as applied to several benchmark datasets, including MNIST. The learning rule is capable of generalizing from the data, and is successful even when used with constrained network architectures containing few input and hidden layer neurons. Furthermore, we highlight a novel encoding strategy, termed “scanline encoding,” that can transform image data into compact spatiotemporal patterns for subsequent network processing. Designing constrained, but optimized, network structures and performing input dimensionality reduction has strong implications for neuromorphic applications.
in Frontiers in Computational Neuroscience on April 12, 2021 12:00 AM.
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Oligodendrocytes exert a profound influence on neural circuits by accelerating action potential conduction, altering excitability, and providing metabolic support. As oligodendrogenesis continues in the adult brain and is essential for myelin repair, uncovering the factors that control their dynamics is necessary to understand the consequences of adaptive myelination and develop new strategies to enhance remyelination in diseases such as multiple sclerosis. Unfortunately, few methods exist for analysis of oligodendrocyte dynamics, and even fewer are suitable for in vivo investigation. Here, we describe the development of a fully automated cell tracking pipeline using convolutional neural networks (Oligo-Track) that provides rapid volumetric segmentation and tracking of thousands of cells over weeks in vivo. This system reliably replicated human analysis, outperformed traditional analytic approaches, and extracted injury and repair dynamics at multiple cortical depths, establishing that oligodendrogenesis after cuprizone-mediated demyelination is suppressed in deeper cortical layers. Volumetric data provided by this analysis revealed that oligodendrocyte soma size progressively decreases after their generation, and declines further prior to death, providing a means to predict cell age and eventual cell death from individual time points. This new CNN-based analysis pipeline offers a rapid, robust method to quantitatively analyze oligodendrocyte dynamics in vivo, which will aid in understanding how changes in these myelinating cells influence circuit function and recovery from injury and disease.
in Frontiers in Cellular Neuroscience on April 12, 2021 12:00 AM.
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Amyloid-based neurodegenerative diseases such as prion, Alzheimer's, and Parkinson's diseases have distinct etiologies and clinical manifestations, but they share common pathological events. These diseases are caused by abnormally folded proteins (pathogenic prions PrPSc in prion diseases, β-amyloids/Aβ and Tau in Alzheimer's disease, α-synuclein in Parkinson's disease) that display β-sheet-enriched structures, propagate and accumulate in the nervous central system, and trigger neuronal death. In prion diseases, PrPSc-induced corruption of the physiological functions exerted by normal cellular prion proteins (PrPC) present at the cell surface of neurons is at the root of neuronal death. For a decade, PrPC emerges as a common cell surface receptor for other amyloids such as Aβ and α-synuclein, which relays, at least in part, their toxicity. In lipid-rafts of the plasma membrane, PrPC exerts a signaling function and controls a set of effectors involved in neuronal homeostasis, among which are the RhoA-associated coiled-coil containing kinases (ROCKs). Here we review (i) how PrPC controls ROCKs, (ii) how PrPC-ROCK coupling contributes to neuronal homeostasis, and (iii) how the deregulation of the PrPC-ROCK connection in amyloid-based neurodegenerative diseases triggers a loss of neuronal polarity, affects neurotransmitter-associated functions, contributes to the endoplasmic reticulum stress cascade, renders diseased neurons highly sensitive to neuroinflammation, and amplifies the production of neurotoxic amyloids.
in Frontiers in Cellular Neuroscience on April 12, 2021 12:00 AM.
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in Frontiers in Cellular Neuroscience on April 12, 2021 12:00 AM.
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TDP-43 is a nuclear protein involved in pivotal processes, extensively studied for its implication in neurodegenerative disorders. TDP-43 cytosolic inclusions are a common neuropathologic hallmark in amyotrophic lateral sclerosis (ALS) and related diseases, and it is now established that TDP-43 misfolding and aggregation play a key role in their etiopathology. TDP-43 neurotoxic mechanisms are not yet clarified, but the identification of proteins able to modulate TDP-43-mediated damage may be promising therapeutic targets for TDP-43 proteinopathies. Here we show by the use of refined yeast models that the nucleolar protein nucleolin (NCL) acts as a potent suppressor of TDP-43 toxicity, restoring cell viability. We provide evidence that NCL co-expression is able to alleviate TDP-43-induced damage also in human cells, further supporting its beneficial effects in a more consistent pathophysiological context. Presented data suggest that NCL could promote TDP-43 nuclear retention, reducing the formation of toxic cytosolic TDP-43 inclusions.
in Frontiers in Cellular Neuroscience on April 12, 2021 12:00 AM.
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The role of gut-brain axis in the pathogenesis of Parkinson’s disease (PD) have become a research hotspot, appropriate animal model to study gut-brain axis in PD is yet to be confirmed. Our study employed a classical PD mice model achieved by chronic MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) injection to study concurrent changes of dopaminergic neurons in the midbrain and the colon of mice. Our results showed such a PD model exhibited apparent locomotor deficits but not gastrointestinal dysfunction. Tyrosine hydroxylase expressions and dopamine content reduced greatly in the substantia nigra pars compacta (SNpc) or striatum, but increased in the colon of PD mice. Mechanism investigation indicated autophagy activity and apoptosis were stimulated in the SNpc, but inhibited in the colon of PD mice. Interplay of gut microbiota (GM) and autophagy in response to chronic MPTP injection led to GM dysbiosis and defective autophagy in mice colon. Meanwhile, fecal short chain fatty acids (SCFAs), acetate and propionate in particular, declined greatly in PD mice, which could be attributed to the decreased bacteria abundance of phylum Bacteroidetes, but increased abundance of phylum Firmicutes. GM dysbiosis derived fecal SCFAs might be one of the mediators of downregulated autophagy in the colon of PD mice. In conclusion, colonic dopaminergic neurons changed in the opposition direction with those in the midbrain via GM dysbiosis-mediated autophagy inhibition followed by suppressed apoptosis in response to chronic MPTP injection. Such a chronic PD mice model might not be an ideal model to study role of gut-brain axis in PD progression.
in Frontiers in Ageing Neuroscience on April 12, 2021 12:00 AM.
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Background: Alzheimer's Disease (AD) impairs the ability to carry out daily activities, reduces independence and quality of life and increases caregiver burden. Our understanding of functional decline has traditionally relied on reports by family and caregivers, which are subjective and vulnerable to recall bias. The Internet of Things (IoT) and wearable sensor technologies promise to provide objective, affordable, and reliable means for monitoring and understanding function. However, human factors for its acceptance are relatively unexplored.
Objective: The Public Involvement (PI) activity presented in this paper aims to capture the preferences, priorities and concerns of people with AD and their caregivers for using monitoring wearables. Their feedback will drive device selection for clinical research, starting with the study of the RADAR-AD project.
Method: The PI activity involved the Patient Advisory Board (PAB) of the RADAR-AD project, comprised of people with dementia across Europe and their caregivers (11 and 10, respectively). A set of four devices that optimally represent various combinations of aspects and features from the variety of currently available wearables (e.g., weight, size, comfort, battery life, screen types, water-resistance, and metrics) was presented and experienced hands-on. Afterwards, sets of cards were used to rate and rank devices and features and freely discuss preferences.
Results: Overall, the PAB was willing to accept and incorporate devices into their daily lives. For the presented devices, the aspects most important to them included comfort, convenience and affordability. For devices in general, the features they prioritized were appearance/style, battery life and water resistance, followed by price, having an emergency button and a screen with metrics. The metrics valuable to them included activity levels and heart rate, followed by respiration rate, sleep quality and distance. Some concerns were the potential complexity, forgetting to charge the device, the potential stigma and data privacy.
Conclusions: The PI activity explored the preferences, priorities and concerns of the PAB, a group of people with dementia and caregivers across Europe, regarding devices for monitoring function and decline, after a hands-on experience and explanation. They highlighted some expected aspects, metrics and features (e.g., comfort and convenience), but also some less expected (e.g., screen with metrics).
in Frontiers in Ageing Neuroscience on April 12, 2021 12:00 AM.
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Older adults typically perform worse on spatial navigation tasks, although whether this is due to degradation of memory or an impairment in using specific strategies has yet to be determined. An issue with some past studies is that older adults are tested on desktop-based virtual reality: a technology many report lacking familiarity with. Even when controlling for familiarity, these paradigms reduce the information-rich, three-dimensional experience of navigating to a simple two-dimensional task that utilizes a mouse and keyboard (or joystick) as means for ambulation. Here, we utilize a wireless head-mounted display and free ambulation to create a fully immersive virtual Morris water maze in which we compare the navigation of older and younger adults. Older and younger adults learned the locations of hidden targets from same and different start points. Across different conditions tested, older adults remembered target locations less precisely compared to younger adults. Importantly, however, they performed comparably from the same viewpoint as a switched viewpoint, suggesting that they could generalize their memory for the location of a hidden target given a new point of view. When we implicitly moved one of the distal cues to determine whether older adults used an allocentric (multiple landmarks) or beaconing (single landmark) strategy to remember the hidden target, both older and younger adults showed comparable degrees of reliance on allocentric and beacon cues. These findings support the hypothesis that while older adults have less precise spatial memories, they maintain the ability to utilize various strategies when navigating.
in Frontiers in Ageing Neuroscience on April 12, 2021 12:00 AM.
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Objectives: The purpose of this study was to evaluate the feasibility and whether synthetic MRI can benefit diagnosis of Alzheimer’s disease (AD).
Materials and Methods: Eighteen patients and eighteen age-matched normal controls (NCs) underwent MR examination. The mini-mental state examination (MMSE) scores were obtained from all patients. The whole brain volumetric characteristics, T1, T2, and proton density (PD) values of different cortical and subcortical regions were obtained. The volumetric characteristics and brain regional relaxation values between AD patients and NCs were compared using independent-samples t-test. The correlations between these quantitative parameters and MMSE score were assessed by the Pearson correlation in AD patients.
Results: Although the larger volume of cerebrospinal fluid (CSF), lower brain parenchymal volume (BPV), and the ratio of brain parenchymal volume to intracranial volume (BPV/ICV) were found in AD patients compared with NCs, there were no significant differences (p > 0.05). T1 values of right insula cortex and T2 values of left hippocampus and right insula cortex were significantly higher in AD patients than in NCs, but T1 values of left caudate showed a reverse trend (p < 0.05). As the MMSE score decreased in AD patients, the BPV and BPV/ICV decreased, while the volume of CSF and T1 values of bilateral insula cortex and bilateral hippocampus as well as T2 values of bilateral hippocampus increased (p < 0.05).
Conclusion: Synthetic MRI not only provides more information to differentiate AD patients from normal controls, but also reflects the disease severity of AD.
in Frontiers in Ageing Neuroscience on April 12, 2021 12:00 AM.
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Objective: Olfactory impairment (OI) refers to decreased (hyposmia) or absent (anosmia) ability to smell. We sought to estimate the prevalence and correlates of OI among rural-dwelling Chinese older adults.
Methods: This population-based cross-sectional analysis included 4,514 participants (age ≥65 years; 56.7% women) from the Multidomain Interventions to Delay Dementia and Disability in Rural China (MIND-China). The 16-item Sniffin' Sticks identification test (SSIT) was used to assess olfactory function. Olfactory impairment was defined as the SSIT score ≤10, hyposmia as SSIT score of 8–10, and anosmia as SSIT score <8. Multivariable logistic regression models were used to examine factors associated with OI.
Results: The overall prevalence was 67.7% for OI, 35.3% for hyposmia, and 32.5% for anosmia. The prevalence increased with age for OI and anosmia, but not for hyposmia. The multivariable-adjusted odds ratio (OR) of OI was 2.10 (95% CI 1.69–2.61) for illiteracy and 1.41 (1.18–1.70) for elementary school (vs. middle school or above), 1.30 (1.01–1.67) for current smoking (vs. never smoking), 0.86 (0.74–0.99) for overweight and 0.73 (0.61–0.87) for obesity (vs. normal weight), 4.21 (2.23–7.94) for dementia, 1.68 (1.23–2.30) for head injury, and 1.44 (1.14–1.83) for sinonasal disease. Illiteracy in combination with either male sex or diabetes was significantly associated with an over two-fold increased OR of OI (p for interactions <0.05).
Conclusion: Olfactory impairment is highly prevalent that affects over two-thirds of rural-dwelling older adults in China. OI is correlated with illiteracy, current smoking, dementia, head injury, and sinonasal disease, but negatively associated with overweight or obesity. Olfactory impairment as a potential clinical marker of neurodegenerative disorders among older adults deserves further investigation.
in Frontiers in Ageing Neuroscience on April 12, 2021 12:00 AM.
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Publication date: Available online 10 April 2021
Source: Neural Networks
Author(s): Yongjian Zhong, Bo Du, Chang Xu
in Neural Networks on April 11, 2021 06:00 PM.
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Publication date: Available online 10 April 2021
Source: Neural Networks
Author(s): Zeyu Zhao, Wei-Qiang Zhang
in Neural Networks on April 11, 2021 06:00 PM.
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Publication date: June 2021
Source: Current Opinion in Neurobiology, Volume 68
Author(s): Ann M. Clemens, Michael Brecht
in Current Opinion in Neurobiology on April 10, 2021 01:00 PM.
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Publication date: Available online 9 April 2021
Source: Neural Networks
Author(s): Daoguang Yang, Hamid Reza Karimi, Kangkang Sun
in Neural Networks on April 10, 2021 01:00 PM.
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Publication date: Available online 8 April 2021
Source: Neural Networks
Author(s): Fanghai Zhang, Tingwen Huang, Qiujie Wu, Zhigang Zeng
in Neural Networks on April 09, 2021 06:00 PM.
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Publication date: September 2021
Source: Neural Networks, Volume 141
Author(s): Zhenyuan Guo, Jingxuan Ci, Jun Wang
in Neural Networks on April 09, 2021 06:00 PM.
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in Annals of Neurology on April 09, 2021 04:04 PM.
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in F1000Research on April 09, 2021 04:02 PM.
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in Hippocampus on April 09, 2021 03:44 PM.
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in Hippocampus on April 09, 2021 03:38 PM.
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in Annals of Neurology on April 09, 2021 02:38 PM.
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by Linnea Österberg, Iván Domenzain, Julia Münch, Jens Nielsen, Stefan Hohmann, Marija Cvijovic
The interplay between nutrient-induced signaling and metabolism plays an important role in maintaining homeostasis and its malfunction has been implicated in many different human diseases such as obesity, type 2 diabetes, cancer, and neurological disorders. Therefore, unraveling the role of nutrients as signaling molecules and metabolites together with their interconnectivity may provide a deeper understanding of how these conditions occur. Both signaling and metabolism have been extensively studied using various systems biology approaches. However, they are mainly studied individually and in addition, current models lack both the complexity of the dynamics and the effects of the crosstalk in the signaling system. To gain a better understanding of the interconnectivity between nutrient signaling and metabolism in yeast cells, we developed a hybrid model, combining a Boolean module, describing the main pathways of glucose and nitrogen signaling, and an enzyme-constrained model accounting for the central carbon metabolism of Saccharomyces cerevisiae, using a regulatory network as a link. The resulting hybrid model was able to capture a diverse utalization of isoenzymes and to our knowledge outperforms constraint-based models in the prediction of individual enzymes for both respiratory and mixed metabolism. The model showed that during fermentation, enzyme utilization has a major contribution in governing protein allocation, while in low glucose conditions robustness and control are prioritized. In addition, the model was capable of reproducing the regulatory effects that are associated with the Crabtree effect and glucose repression, as well as regulatory effects associated with lifespan increase during caloric restriction. Overall, we show that our hybrid model provides a comprehensive framework for the study of the non-trivial effects of the interplay between signaling and metabolism, suggesting connections between the Snf1 signaling pathways and processes that have been related to chronological lifespan of yeast cells.in PLoS Computational Biology on April 09, 2021 02:00 PM.
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by Piyush Nanda, Amit Ghosh
The COVID-19 pandemic is posing an unprecedented threat to the whole world. In this regard, it is absolutely imperative to understand the mechanism of metabolic reprogramming of host human cells by SARS-CoV-2. A better understanding of the metabolic alterations would aid in design of better therapeutics to deal with COVID-19 pandemic. We developed an integrated genome-scale metabolic model of normal human bronchial epithelial cells (NHBE) in