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arXiv:2411.12091v1 Announce Type: new
Abstract: There is renewed interest in modeling and understanding the nervous system of the nematode $\textit{Caenorhabditis elegans}$ ($\textit{C. elegans}$). This is particularly interesting as this model system provides a path to bridge the gap between structure and function, from nervous system connectivity to physiology. However, the many existing physiology datasets, both recording and stimulation, as well as connectome datasets, are in distinct formats, requiring extra processing steps before modeling or other analysis can commence. Here we present a homogenized dataset of neural activity, including during stimulation, compiled from 11 neuroimaging experiments and from 10 connectome reconstructions. The physiology datasets, collected under varying experimental protocols, all measure neural activity via calcium fluorescence in labeled subsets of the worm's 300 neurons. Our preprocessing pipeline standardizes these datasets by consistently ordering labeled neurons and resampling traces to a common sampling frequency. The resulting dataset includes neural recordings from approximately 900 worms and 250 uniquely labeled neurons. The connectome datasets, collected from electron microscopy (EM) reconstructions, all contain the entire nervous system of the worm, preprocessed into a graph of connections across the neurons. Using our collection of datasets is facilitated through easy data sharing on HuggingFace. We believe that our joint dataset of physiology and connectivity will facilitate modeling, for example in terms of recurrent neural network or transformer architectures, making it easier to check how well models generalize across animals and labs.
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-11-20 05:00:00 UTC.
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arXiv:2411.12145v1 Announce Type: new
Abstract: Traits are patterns of brain signals and behaviors that are stable over time but differ across individuals, whereas states are phasic patterns that vary over time, are influenced by the environment, yet oscillate around the traits. The quality of a social interaction depends on the traits and states of the interacting agents. However, it remains unclear how to decipher both traits and states from the same set of brain signals. To explore the hidden neural traits and states in relation to the behavioral ones during social interactions, we developed a pipeline to extract latent dimensions of the brain from electroencephalogram (EEG) data collected during a team flow task. Our pipeline involved two stages of dimensionality reduction: first, non-negative matrix factorization (NMF), followed by linear discriminant analysis (LDA). This pipeline resulted in an interpretable, seven-dimensional EEG latent space that revealed a trait-state hierarchical structure, with macro-segregation capturing neural traits and micro-segregation capturing neural states. Out of the seven latent dimensions, we found that three that significantly contributed to variations across individuals and task states. Using representational similarity analysis, we mapped the EEG latent space to a skill-cognition space, establishing a connection between hidden neural signatures and social interaction behaviors. Our method demonstrates the feasibility of representing both traits and states within a single model that correlates with changes in social behavior.
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-11-20 05:00:00 UTC.
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arXiv:2207.01581v2 Announce Type: replace-cross
Abstract: There have been several attempts to use deep learning based on brain fMRI signals to classify cognitive impairment diseases. However, deep learning is a hidden black box model that makes it difficult to interpret the process of classification. To address this issue, we propose a novel analytical framework that interprets the classification result from deep learning processes. We first derive the region of interest (ROI) functional connectivity network (FCN) by embedding functions based on their similar signal patterns. Then, using the self-attention equipped deep learning model, we classify diseases based on their FCN. Finally, in order to interpret the classification results, we employ a latent space item-response interaction network model to identify the significant functions that exhibit distinct connectivity patterns when compared to other diseases. The application of this proposed framework to the four types of cognitive impairment shows that our approach is valid for determining the significant ROI functions.
in arXiv: Quantitative Biology: Neurons and Cognition on 2024-11-20 05:00:00 UTC.
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arXiv:2411.12304v1 Announce Type: new
Abstract: We discuss the possibility of world models and active exploration as emergent properties of open-ended behavior optimization in autonomous agents. In discussing the source of the open-endedness of living things, we start from the perspective of biological systems as understood by the mechanistic approach of theoretical biology and artificial life. From this perspective, we discuss the potential of homeostasis in particular as an open-ended objective for autonomous agents and as a general, integrative extrinsic motivation. We then discuss the possibility of implicitly acquiring a world model and active exploration through the internal dynamics of a network, and a hypothetical architecture for this, by combining meta-reinforcement learning, which assumes domain adaptation as a system that achieves robust homeostasis.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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arXiv:2411.12735v1 Announce Type: new
Abstract: Evolving Boolean functions with specific properties is an interesting optimization problem since, depending on the combination of properties and Boolean function size, the problem can range from very simple to (almost) impossible to solve. Moreover, some problems are more interesting as there may be only a few options for generating the required Boolean functions. This paper investigates one such problem: evolving five-valued spectra Boolean functions, which are the functions whose Walsh-Hadamard coefficients can only take five distinct values. We experimented with three solution encodings, two fitness functions, and 12 Boolean function sizes and showed that the tree encoding is superior to other choices, as we can obtain five-valued Boolean functions with high nonlinearity.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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arXiv:2411.12308v1 Announce Type: cross
Abstract: We present the architecture of a fully autonomous, bio-inspired cognitive agent built around a spiking neural network (SNN) implementing the agent's semantic memory. The agent explores its universe and learns concepts of objects/situations and of its own actions in a one-shot manner. While object/situation concepts are unary, action concepts are triples made up of an initial situation, a motor activity, and an outcome. They embody the agent's knowledge of its universe's actions laws. Both kinds of concepts have different degrees of generality. To make decisions the agent queries its semantic memory for the expected outcomes of envisaged actions and chooses the action to take on the basis of these predictions. Our experiments show that the agent handles new situations by appealing to previously learned general concepts and rapidly modifies its concepts to adapt to environment changes.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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arXiv:2411.12603v1 Announce Type: cross
Abstract: Handling sparse and unstructured geometric data, such as point clouds or event-based vision, is a pressing challenge in the field of machine vision. Recently, sequence models such as Transformers and state-space models entered the domain of geometric data. These methods require specialized preprocessing to create a sequential view of a set of points. Furthermore, prior works involving sequence models iterate geometric data with either uniform or learned step sizes, implicitly relying on the model to infer the underlying geometric structure. In this work, we propose to encode geometric structure explicitly into the parameterization of a state-space model. State-space models are based on linear dynamics governed by a one-dimensional variable such as time or a spatial coordinate. We exploit this dynamic variable to inject relative differences of coordinates into the step size of the state-space model. The resulting geometric operation computes interactions between all pairs of N points in O(N) steps. Our model deploys the Mamba selective state-space model with a modified CUDA kernel to efficiently map sparse geometric data to modern hardware. The resulting sequence model, which we call STREAM, achieves competitive results on a range of benchmarks from point-cloud classification to event-based vision and audio classification. STREAM demonstrates a powerful inductive bias for sparse geometric data by improving the PointMamba baseline when trained from scratch on the ModelNet40 and ScanObjectNN point cloud analysis datasets. It further achieves, for the first time, 100% test accuracy on all 11 classes of the DVS128 Gestures dataset.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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arXiv:2309.10987v4 Announce Type: replace
Abstract: In this paper, we propose SpikingNeRF, which aligns the temporal dimension of spiking neural networks (SNNs) with the radiance rays, to seamlessly accommodate SNNs to the reconstruction of neural radiance fields (NeRF). Thus, the computation turns into a spike-based, multiplication-free manner, reducing energy consumption and making high-quality 3D rendering, for the first time, accessible to neuromorphic hardware. In SpikingNeRF, each sampled point on the ray is matched to a particular time step and represented in a hybrid manner where the voxel grids are maintained as well. Based on the voxel grids, sampled points are determined whether to be masked out for faster training and inference. However, this masking operation also incurs irregular temporal length, making it intractable for hardware processors, e.g., GPUs, to conduct parallel training. To address this problem, we develop the temporal padding strategy to tackle the masked samples to maintain regular temporal length, i.e., regular tensors, and further propose the temporal condensing strategy to form a denser data structure for hardware-friendly computation. Experiments on various datasets demonstrate that our method can reduce energy consumption by an average of 70.79\% and obtain comparable synthesis quality with the ANN baseline. Verification on the neuromorphic hardware accelerator also shows that SpikingNeRF can further benefit from neuromorphic computing over the ANN baselines on energy efficiency. Codes and the appendix are in \url{https://github.com/Ikarosy/SpikingNeRF-of-CASIA}.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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arXiv:2411.00803v2 Announce Type: replace
Abstract: In this paper, a dataset of one-dimensional powder diffraction patterns was designed with new strategy to train Convolutional Neural Networks for predicting space groups. The diffraction pattern was calculated based on lattice parameters and Extinction Laws, instead of the traditional approach of generating it from a crystallographic database. This paper demonstrates that the new strategy is more effective than the conventional method. As a result, the model trained on the cubic and tetragonal training set from the newly designed dataset achieves prediction accuracy that matches the theoretical maximums calculated based on Extinction Laws. These results demonstrate that machine learning-based prediction can be both physically reasonable and reliable. Additionally, the model trained on our newly designed dataset shows excellent generalization capability, much better than the one trained on a traditionally designed dataset.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2024-11-20 05:00:00 UTC.
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Background Misconduct in the academic community remains poorly understood among post-graduate dental students (PGDSs) in North Africa. Data on the knowledge of misconduct (KoM) level in this population is lacking. This brief report assessed KoM of Tunisian PGDSs’. Methods A cross-sectional study was conducted at the Faculty of Dental Medicine of Monastir, involving 147 PGDSs registered in 2022. Students were recruited via email invitations and convenience sampling at a medical congress. A French survey with 11 questions on KoM, offering three-choice answers (yes/no/maybe) was administered. Each correct answer received one point, and a total score below six indicated a low-level of KoM. Results The mean±SD KoM score of the 106 students who accepted to participate in the study was 4.4±1.8, indicating a low-level of KoM. The majority of PGDSs (85.85%) demonstrated a low-level of KoM. A comparison between subjective and objective assessments of KoM levels revealed that a significant percentage of PGDSs underestimated their knowledge (62.26% vs. 85.85%, respectively). Conclusion This study identified a low-level of KoM among North-African PGDSs. This emphasizes the need for further efforts to enhance awareness and promote better KoM in this population.
in F1000Research on 2024-11-19 17:13:42 UTC.
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Background Interest in alternative sources of tubers and legumes has increased in recent years because of the constant search for raw materials that provide bioactive compounds with antioxidant potential benefits for consumers. The functionality of new raw materials is sought through physical and/or chemical modifications to develop and innovate new foods. The objective of this study was to characterize taro (TF) (Colocasia esculenta) and sacha inchi (Plukenetia volubilis) flours, obtained by the wet (SIF-WM) and defatted method (SIF-DM), as an alternative for the formulation of new functional foods. Methods The free polyphenols of the different mixtures were analyzed, and the antioxidant properties of the extracts obtained were measured using ABTS.* (2,2′-Azino-bis(3-ethylbenzthiazoline-6-sulfonic acid). The ABTS radical method, which reacts with the phenolic compounds of the food matrix, using Trolox as a standard. The blends were subjected to pasting analysis, flow profile tests, determination of viscoelastic properties (temperature sweep). Characterization of common microorganisms in these foods was performed. Results The highest protein value was obtained in the sacha inchi flour obtained by the defatted method (72.62%). The majority of components in taro were carbohydrates (85.4%). About antioxidant and determination of free polyphenols, taro flour obtained values of 2.71 μmol ET/g and 7.47 mg EAG/g, higher than sacha inchi flours. In the rheological analysis (pasting properties, flow profile, and viscoelasticity), we observed that adding taro flour in different mixtures increases the viscosity peak and a lower breakdown, while there was an increase in setback. Except for defatted sacha flour, the others presented a flow index >1 before heating, showing a dilatant fluid behavior. The presence of taro flour improves gel formation and stability. Staphylococcus aureus and Salmonella were present in the taro flour. Conclusions The flours analyzed represent a raw material with great potential for the development of products such as protein snacks due to the contribution of sacha inchi, with good expansion due to taro starch, and naturally gluten-free for people with celiac disease.
in F1000Research on 2024-11-19 17:11:02 UTC.
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Background One of the main goals of the government is to ensure a development that would enhance the living standard of the people in the society. In this regard, capital expenditure that would promote infrastructure is most desired. However, in Nigeria, the government spends more on administrative cost (recurrent expenditure) than capital expenditure. Under such condition, contributions to economic growth and national development become an illusion. Methods This study employed Augmented Dickey Fuller Test (ADF) with Bound testing procedure, time series data that covers the period from 1990 to 2020 in Nigeria were used. Results The result from the analysis showed that governmental expenditure has a significant effect on the national development of Nigeria. All the variables have a long-run relationship with economic growth (RGDP), according to the ARDL model’s results. If the government poor policies on education, health services, and infrastructure etc. are addressed, in the long-run, Nigeria will achieve monumental development. Conclusion The study adopted indices such as expenditure on Social and Community Services, Economic Services and Administrative Services to reflect the dynamics of government expenditure coupled with the yearly data garnered from the Central Bank of Nigeria spanning from 1990 to 2020.
in F1000Research on 2024-11-19 17:01:32 UTC.
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Rationale The efficacy of vaccination programs, particularly for diseases like HPV, hinges on widespread acceptance and uptake within communities. However, vaccine hesitancy and inadequate healthcare infrastructure pose significant barriers to achieving optimal vaccination coverage in Nigeria. Recognizing the pivotal role of community engagement in overcoming these challenges, this study aims to explore the potential of leveraging the ward health system (WHS) to enhance HPV vaccination acceptance in Nigeria. Objective The primary objective of this study is to assess the impact of community-based approaches facilitated by the WHS on HPV vaccination demand and acceptance in Nigeria. Specifically, the study seeks to evaluate the effectiveness of ward development committees (WDCs) in mobilizing communities, addressing vaccine hesitancy, and fostering positive attitudes towards HPV vaccination. Method A comprehensive search strategy using various scholarly search engines and sources was employed to gather relevant material. Keywords such as “Boosting Community Engagement” and “Leveraging Ward Health System Approach” guided the search process. Methodical content analysis was used to examine the texts, focusing on identifying emerging trends in community engagement related to HPV vaccination. Discourse analysis further explored the linguistic features of scholarly publications to reveal implicit content through critical thinking. This rigorous approach aimed to extract trustworthy data aligning with the study’s goals, providing a robust foundation for enhancing HPV vaccination strategies in Nigeria. Results The results of the study provide comprehensive insights into the effectiveness of community-based interventions facilitated by the WHS in driving HPV vaccination demand and acceptance. Quantitative data offer valuable information on vaccination coverage rates and factors influencing vaccine acceptance, while qualitative findings provide deeper insights into community perceptions and the role of the WHS in addressing vaccine hesitancy. Conclusions Based on the findings, conclusions drawn regarding the effectiveness of leveraging the WHS to enhance HPV vaccination acceptance in Nigeria. The study highlights the importance of community engagement and the potential of the WHS in overcoming barriers to vaccination uptake. Recommendations The study conclude with recommendations for policymakers, healthcare providers, and community leaders on strategies to optimize the role of the WHS in promoting HPV vaccination acceptance. Recommendations include strengthening WDC functionality, enhancing community outreach efforts, and fostering partnerships to support vaccination programs. Significance Statement This study holds significance as it addresses a critical gap in understanding the role of community-based approaches, particularly through the WHS, in promoting HPV vaccination acceptance in Nigeria. By providing evidence-based insights and recommendations, the study aims to inform policy and practice, ultimately assisting Nigeria in achieving universal health coverage and better health outcomes.
in F1000Research on 2024-11-19 17:00:20 UTC.
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Background The growing incidence of chronic diseases such as cancer and the emergence of drug-resistant microorganisms constitute one of the greatest health challenges of the 21st century. Therefore, it is critical to search for new therapeutic alternatives. Moringa oleifera is a plant well known for the properties of its phytocomponents and its role has been analyzed in a variety of fields, from medicine to biotechnology. Methods In this work, the biological activity of Moringa oleifera in human health was explored through a review of 129 original articles published between 2010 and 2021 related to antitumor activity and its potential uses against chronic and infectious diseases. Results Moringa oleifera extracts showed antioxidant, hypoglycemic, antihypertensive and cytoprotective properties at neuronal, hepatic, renal and cardiac levels. Besides, cytotoxic effects, apoptotic and antiploriferative activity against several cancer cell lines has been demonstrated. On the other hand, the antimicrobial potential of M. oleifera was also evidenced, especially against multidrug-resistant strains. Conclusions Hence, it is supported that there is a wide range of clinical entities in which Moringa oleifera exhibits significant biological activity that could contribute to counteracting metabolic, infectious and chronic diseases in a similar or improved way to the drugs traditionally used.
in F1000Research on 2024-11-19 16:01:47 UTC.
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Background The discovery spurred further exploration, leading to the expansion of opal mining into neighboring districts. Numerous cooperative groups, composed of small-scale miners, traditionally explore, develop, and extract significant amounts of rough opal gemstones. This study tries to investigate the challenges and economic impacts of traditional opal mining practice in wollo province of Ethiopia. Methods The study used in this study is primary data collected from rural households, which are living in five districts of north wollo zone, in Amhara regional state. The data was collected using field observation, focus grouped discussion, interview, and questionnaire from sampled households. The study uses both descriptive and econometric methods of data analysis to achieve its objective. Results Among the challenges of traditional opal mining, primitive way of exploring and extraction, limited access to market and low institutional support in terms of training and finance are identified. The probit model reveals that, increased education, access to training, and access to credit positively influence the likelihood of engaging in opal mining. The ESR model shows that, the average treatment effect on the treated (ATT) indicates that participating in opal mining increases monthly income by 31,380 ETB, while the average treatment effect on the untreated (ATU) shows a potential income increase of 31,625 ETB for non-miners if they engaged in mining. Conclusion The study identifies three main categories of challenges faced by traditional opal miners: exploration and extraction issues, market limitations, and regulatory and institutional shortcomings. Exploration and extraction challenges include the lack of modern mining tools and knowledge, as well as difficult terrain, leading to inefficient and hazardous mining practices. Market-related challenges involve limited access to broader markets and lack of value addition, resulting in miners selling raw opals at significantly lower prices compared to polished ones.
in F1000Research on 2024-11-19 14:51:17 UTC.
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by Dan Liu, Francesca Young, Kieran D. Lamb, David L. Robertson, Ke Yuan
Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical properties, and DNA k-mers. In multi-host prediction tasks, EvoMIL achieves median F1 score improvements of 10.8%, 16.2%, and 4.9% in prokaryotic hosts, and 1.7%, 6.6% and 11.5% in eukaryotic hosts. EvoMIL binary classifiers achieve impressive AUC over 0.95 for all prokaryotic hosts and range from roughly 0.8 to 0.9 for eukaryotic hosts. Furthermore, EvoMIL identifies important proteins in the prediction task. We found them capturing key functions in virus-host specificity.
in PLoS Computational Biology on 2024-11-19 14:00:00 UTC.
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by Evandro Konzen, Richard J. Delahay, Dave J. Hodgson, Robbie A. McDonald, Ellen Brooks Pollock, Simon E. F. Spencer, Trevelyan J. McKinley
Bovine tuberculosis (bTB) has significant socio-economic and welfare impacts on the cattle industry in parts of the world. In the United Kingdom and Ireland, disease control is complicated by the presence of infection in wildlife, principally the European badger. Control strategies tend to be applied to whole populations, but better identification of key sources of transmission, whether individuals or groups, could help inform more efficient approaches. Mechanistic transmission models can be used to better understand key epidemiological drivers of disease spread and identify high-risk individuals and groups if they can be adequately fitted to observed data. However, this is a significant challenge, especially within wildlife populations, because monitoring relies on imperfect diagnostic test information, and even under systematic surveillance efforts (such as capture-mark-recapture sampling) epidemiological events are only partially observed.
To this end we develop a stochastic compartmental model of bTB transmission, and fit this to individual-level data from a unique > 40-year longitudinal study of 2,391 badgers using a recently developed individual forward filtering backward sampling algorithm. Modelling challenges are further compounded by spatio-temporal meta-population structures and age-dependent mortality. We develop a novel estimator for the individual effective reproduction number that provides quantitative evidence for the presence of superspreader badgers, despite the population-level effective reproduction number being less than one. We also infer measures of the hidden burden of infection in the host population through time; the relative likelihoods of competing routes of transmission; effective and realised infectious periods; and longitudinal measures of diagnostic test performance. This modelling framework provides an efficient and generalisable way to fit state-space models to individual-level data in wildlife populations, which allows identification of high-risk individuals and exploration of important epidemiological questions about bTB and other wildlife diseases.
in PLoS Computational Biology on 2024-11-19 14:00:00 UTC.
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by Beren Millidge, Yuhang Song, Armin Lak, Mark E. Walton, Rafal Bogacz
Animals can adapt their preferences for different types of reward according to physiological state, such as hunger or thirst. To explain this ability, we employ a simple multi-objective reinforcement learning model that learns multiple values according to different reward dimensions such as food or water. We show that by weighting these learned values according to the current needs, behaviour may be flexibly adapted to present preferences. This model predicts that individual dopamine neurons should encode the errors associated with some reward dimensions more than with others. To provide a preliminary test of this prediction, we reanalysed a small dataset obtained from a single primate in an experiment which to our knowledge is the only published study where the responses of dopamine neurons to stimuli predicting distinct types of rewards were recorded. We observed that in addition to subjective economic value, dopamine neurons encode a gradient of reward dimensions; some neurons respond most to stimuli predicting food rewards while the others respond more to stimuli predicting fluids. We also proposed a possible implementation of the model in the basal ganglia network, and demonstrated how the striatal system can learn values in multiple dimensions, even when dopamine neurons encode mixtures of prediction error from different dimensions. Additionally, the model reproduces the instant generalisation to new physiological states seen in dopamine responses and in behaviour. Our results demonstrate how a simple neural circuit can flexibly guide behaviour according to animals’ needs.
in PLoS Computational Biology on 2024-11-19 14:00:00 UTC.
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by Eloïse C. Déaux, Théophane Piette, Florence Gaunet, Thierry Legou, Luc Arnal, Anne-Lise Giraud
in PLoS Biology on 2024-11-19 14:00:00 UTC.
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by Lanxin Ji, Iris Menu, Amyn Majbri, Tanya Bhatia, Christopher J. Trentacosta, Moriah E. Thomason
Understanding the sequence and timing of brain functional network development at the beginning of human life is critically important from both normative and clinical perspectives. Yet, we presently lack rigorous examination of the longitudinal emergence of human brain functional networks over the birth transition. Leveraging a large, longitudinal perinatal functional magnetic resonance imaging (fMRI) data set, this study models developmental trajectories of brain functional networks spanning 25 to 55 weeks of post-conceptual gestational age (GA). The final sample includes 126 fetal scans (GA = 31.36 ± 3.83 weeks) and 58 infant scans (GA = 48.17 ± 3.73 weeks) from 140 unique subjects. In this study, we document the developmental changes of resting-state functional connectivity (RSFC) over the birth transition, evident at both network and graph levels. We observe that growth patterns are regionally specific, with some areas showing minimal RSFC changes, while others exhibit a dramatic increase at birth. Examples with birth-triggered dramatic change include RSFC within the subcortical network, within the superior frontal network, within the occipital-cerebellum joint network, as well as the cross-hemisphere RSFC between the bilateral sensorimotor networks and between the bilateral temporal network. Our graph analysis further emphasized the subcortical network as the only region of the brain exhibiting a significant increase in local efficiency around birth, while a concomitant gradual increase was found in global efficiency in sensorimotor and parietal-frontal regions throughout the fetal to neonatal period. This work unveils fundamental aspects of early brain development and lays the foundation for future work on the influence of environmental factors on this process.
in PLoS Biology on 2024-11-19 14:00:00 UTC.
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by Charles W. Dickey, Ilya A. Verzhbinsky, Sophie Kajfez, Burke Q. Rosen, Christopher E. Gonzalez, Patrick Y. Chauvel, Sydney S. Cash, Sandipan Pati, Eric Halgren
In the neocortex, ~90 Hz ripples couple to ~12 Hz sleep spindles on the ~1 Hz Down-to-Up state transition during non-rapid eye movement sleep. This conjunction of sleep waves is critical for the consolidation of memories into long-term storage. The widespread co-occurrences of ripples (“co-ripples”) may integrate information across the neocortex and hippocampus to facilitate consolidation. While the thalamus synchronizes spindles and Up states in the cortex for memory, it is not known whether it may also organize co-ripples. Using human intracranial recordings during NREM sleep, we investigated whether cortico-cortical co-ripples and hippocampo-cortical co-ripples are either: (1) driven by directly projected thalamic ripples; or (2) coordinated by propagating thalamic spindles or Up states. We found ripples in the anterior and posterior thalamus, with similar characteristics as hippocampal and cortical ripples, including having a center frequency of ~90 Hz and coupling to local spindles on the Down-to-Up state transition. However, thalamic ripples rarely co-occur or phase-lock with cortical or hippocampal ripples. By contrast, spindles and Up states that propagate from the thalamus strongly coordinate co-ripples in the cortex and hippocampus. Thus, thalamo-cortical spindles and Up states, rather than thalamic ripples, may provide input facilitating spatially distributed co-rippling that integrates information for memory consolidation during sleep in humans.
in PLoS Biology on 2024-11-19 14:00:00 UTC.
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Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2024-11-19 12:01:14 UTC.
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Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2024-11-19 01:10:53 UTC.
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The success of our actions often depends on what others are doing. How does the brain discern predictions of others’ actions when situations are ambiguous? Recent work by Ma and colleagues suggests that the brain solves this problem by entertaining multiple predictions of others’ actions, ranked by their likelihood.
in Trends in Neurosciences: In press on 2024-11-19 00:00:00 UTC.
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How astrocytes in the mediobasal hypothalamus regulate systemic glucose and cholesterol metabolism remains largely unknown. Yin et al. show that astrocytic Tak1 controls glucose and cholesterol metabolism and is required for mitochondrial transfer from astrocytes to POMC neurons, which are vital for Tak1 to exert its metabolic effects.
in Cell Reports: Current Issue on 2024-11-19 00:00:00 UTC.
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Root et al. report that expression of individual granulins, 6 kDa subunits of progranulin (88 kDa), is sufficient to prevent disease-associated phenotypes in aged Grn−/− mice. Granulins ameliorated lysosomal dysfunction, microglial activation, lipid dysregulation, and lipofuscin accumulation in Grn−/− mouse brains, suggesting that granulins are the functional components of progranulin.
in Cell Reports: Current Issue on 2024-11-19 00:00:00 UTC.
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Antibodies are powerful tools for the therapy and diagnosis of various diseases. In addition to conventional hybridoma-based screening, recombinant antibody-based screening has become a common choice; however, its application is hampered by two factors: (1) screening starts after Ig gene cloning and recombinant antibody production only, and (2) the antibody is composed of paired chains, heavy and light, commonly expressed by two independent expression vectors. Here, we introduce a method for the rapid screening of recombinant monoclonal antibodies by establishing a Golden Gate-based dual-expression vector and in-vivo expression of membrane-bound antibodies. Using this system, we demonstrate the rapid isolation of influenza cross-reactive antibodies with high affinity from immunized mice within 7 days. This system is particularly useful for isolating therapeutic or diagnostic antibodies, for example during foreseen pandemics.
in eLife on 2024-11-19 00:00:00 UTC.
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The conformational ensemble and function of intrinsically disordered proteins (IDPs) are sensitive to their solution environment. The inherent malleability of disordered proteins, combined with the exposure of their residues, accounts for this sensitivity. One context in which IDPs play important roles that are concomitant with massive changes to the intracellular environment is during desiccation (extreme drying). The ability of organisms to survive desiccation has long been linked to the accumulation of high levels of cosolutes such as trehalose or sucrose as well as the enrichment of IDPs, such as late embryogenesis abundant (LEA) proteins or cytoplasmic abundant heat-soluble (CAHS) proteins. Despite knowing that IDPs play important roles and are co-enriched alongside endogenous, species-specific cosolutes during desiccation, little is known mechanistically about how IDP-cosolute interactions influence desiccation tolerance. Here, we test the notion that the protective function of desiccation-related IDPs is enhanced through conformational changes induced by endogenous cosolutes. We find that desiccation-related IDPs derived from four different organisms spanning two LEA protein families and the CAHS protein family synergize best with endogenous cosolutes during drying to promote desiccation protection. Yet the structural parameters of protective IDPs do not correlate with synergy for either CAHS or LEA proteins. We further demonstrate that for CAHS, but not LEA proteins, synergy is related to self-assembly and the formation of a gel. Our results suggest that functional synergy between IDPs and endogenous cosolutes is a convergent desiccation protection strategy seen among different IDP families and organisms, yet the mechanisms underlying this synergy differ between IDP families.
in eLife on 2024-11-19 00:00:00 UTC.
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When mice run, activity in their primary visual cortex (V1) is strongly modulated. This observation has altered conceptions of a brain region assumed to be a passive image processor. Extensive work has followed to dissect the circuits and functions of running-correlated modulation. However, it remains unclear whether visual processing in primates might similarly change during locomotion. We therefore measured V1 activity in marmosets while they viewed stimuli on a treadmill. In contrast to mouse, running-correlated modulations of marmoset V1 were small and tended to be slightly suppressive. Population-level analyses revealed trial-to-trial fluctuations of shared gain across V1 in both species, but while strongly correlated with running in mice, gain modulations were smaller and more often negatively correlated with running in marmosets. Thus, population-wide fluctuations of V1 may reflect a common feature of mammalian visual cortical function, but important quantitative differences point to distinct consequences for the relation between vision and action in primates versus rodents.
in eLife on 2024-11-19 00:00:00 UTC.
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Bacillus velezensis is a species of Bacillus that has been widely investigated because of its broad-spectrum antimicrobial activity. However, most studies on B. velezensis have focused on the biocontrol of plant diseases, with few reports on antagonizing Salmonella Typhimurium infections. In this investigation, it was discovered that B. velezensis HBXN2020, which was isolated from healthy black pigs, possessed strong anti-stress and broad-spectrum antibacterial activity. Importantly, B. velezensis HBXN2020 did not cause any adverse side effects in mice when administered at various doses (1×107, 1×108, and 1×109 CFU) for 14 days. Supplementing B. velezensis HBXN2020 spores, either as a curative or preventive measure, dramatically reduced the levels of S. Typhimurium ATCC14028 in the mice’s feces, ileum, cecum, and colon, as well as the disease activity index (DAI), in a model of infection caused by this pathogen in mice. Additionally, supplementing B. velezensis HBXN2020 spores significantly regulated cytokine levels (Tnfa, Il1b, Il6, and Il10) and maintained the expression of tight junction proteins and mucin protein. Most importantly, adding B. velezensis HBXN2020 spores to the colonic microbiota improved its stability and increased the amount of beneficial bacteria (Lactobacillus and Akkermansia). All together, B. velezensis HBXN2020 can improve intestinal microbiota stability and barrier integrity and reduce inflammation to help treat infection by S. Typhimurium.
in eLife on 2024-11-19 00:00:00 UTC.
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Abstract
The current reinforcement learning framework focuses exclusively on performance, often at the expense of efficiency. In contrast, biological control achieves remarkable performance while also optimizing computational energy expenditure and decision frequency. We propose a decision-bounded Markov decision process (DB-MDP) that constrains the number of decisions and computational energy available to agents in reinforcement learning environments. Our experiments demonstrate that existing reinforcement learning algorithms struggle within this framework, leading to either failure or suboptimal performance. To address this, we introduce a biologically inspired, temporally layered architecture (TLA), enabling agents to manage computational costs through two layers with distinct timescales and energy requirements. TLA achieves optimal performance in decision-bounded environments and in continuous control environments, matching state-of-the-art performance while using a fraction of the computing cost. Compared to current reinforcement learning algorithms that solely prioritize performance, our approach significantly lowers computational energy expenditure while maintaining performance. These findings establish a benchmark and pave the way for future research on energy and time-aware control.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
Given a directed graph of nodes and edges connecting them, a common problem is to find the shortest path between any two nodes. Here we show that the shortest path distances can be found by a simple matrix inversion: if the edges are given by the adjacency matrix Aij, then with a suitably small value of γ, the shortest path distances are Dij=ceil(logγ[(I-γA)-1]ij).We derive several graph-theoretic bounds on the value of γ and explore its useful range with numerics on different graph types. Even when the distance function is not globally accurate across the entire graph, it still works locally to instruct pursuit of the shortest path. In this mode, it also extends to weighted graphs with positive edge weights. For a wide range of dense graphs, this distance function is computationally faster than the best available alternative. Finally, we show that this method leads naturally to a neural network solution of the all-pairs-shortest-path problem.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
Neural network pruning is a popular approach to reducing the computational costs of training and/or deploying a network and aims to do so while minimizing accuracy loss. Pruning methods that remove individual weights (fine granularity) can remove more total network parameters before reaching a given degree of accuracy loss, while methods that preserve some or all of a network’s structure (coarser granularity, such as pruning channels from a CNN) take better advantage of hardware and software optimized for dense matrix computations. We compare intelligent iterative pruning using several different criteria sampled from the literature against random pruning at initialization across multiple granularities on two different architectures and three image classification tasks. Our work is the first direct and comprehensive investigation of the relationship between granularity and the efficacy of intelligent pruning relative to a random-pruning baseline. We find that the accuracy advantage of intelligent over random pruning decreases dramatically as granularity becomes coarser, with minimal advantage for intelligent pruning at granularity coarse enough to fully preserve network structure. For instance, at pruning rates where random pruning leaves ResNet-20 at 85.0% test accuracy on CIFAR-10 after 30,000 training iterations, intelligent weight pruning with the best-in-context criterion leaves it at about 90.0% accuracy (on par with the unpruned network), kernel pruning leaves it at about 86.5%, and channel pruning leaves it at about 85.5%. Our results suggest that compared to coarse pruning, fine pruning combined with efficient implementation of the resulting networks is a more promising direction for easing the trade-off between high accuracy and low computational cost.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
The sparse coding model posits that the visual system has evolved to efficiently code natural stimuli using a sparse set of features from an overcomplete dictionary. The original sparse coding model suffered from two key limitations; however: (1) computing the neural response to an image patch required minimizing a nonlinear objective function via recurrent dynamics and (2) fitting relied on approximate inference methods that ignored uncertainty. Although subsequent work has developed several methods to overcome these obstacles, we propose a novel solution inspired by the variational autoencoder (VAE) framework. We introduce the sparse coding variational autoencoder (SVAE), which augments the sparse coding model with a probabilistic recognition model parameterized by a deep neural network. This recognition model provides a neurally plausible feedforward implementation for the mapping from image patches to neural activities and enables a principled method for fitting the sparse coding model to data via maximization of the evidence lower bound (ELBO). The SVAE differs from standard VAEs in three key respects: the latent representation is overcomplete (there are more latent dimensions than image pixels), the prior is sparse or heavy-tailed instead of gaussian, and the decoder network is a linear projection instead of a deep network. We fit the SVAE to natural image data under different assumed prior distributions and show that it obtains higher test performance than previous fitting methods. Finally, we examine the response properties of the recognition network and show that it captures important nonlinear properties of neurons in the early visual pathway.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
In recent years, using orthogonal matrices has been shown to be a promising approach to improving recurrent neural networks (RNNs) with training, stability, and convergence, particularly to control gradients. While gated recurrent unit (GRU) and long short-term memory (LSTM) architectures address the vanishing gradient problem by using a variety of gates and memory cells, they are still prone to the exploding gradient problem. In this work, we analyze the gradients in GRU and propose the use of orthogonal matrices to prevent exploding gradient problems and enhance long-term memory. We study where to use orthogonal matrices and propose a Neumann series–based scaled Cayley transformation for training orthogonal matrices in GRU, which we call Neumann-Cayley orthogonal GRU (NC-GRU). We present detailed experiments of our model on several synthetic and real-world tasks, which show that NC-GRU significantly outperforms GRU and several other RNNs.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
Associative learning is a behavioral phenomenon in which individuals develop connections between stimuli or events based on their co-occurrence. Initially studied by Pavlov in his conditioning experiments, the fundamental principles of learning have been expanded on through the discovery of a wide range of learning phenomena. Computational models have been developed based on the concept of minimizing reward prediction errors. The Rescorla-Wagner model, in particular, is a well-known model that has greatly influenced the field of reinforcement learning. However, the simplicity of these models restricts their ability to fully explain the diverse range of behavioral phenomena associated with learning. In this study, we adopt the free energy principle, which suggests that living systems strive to minimize surprise or uncertainty under their internal models of the world. We consider the learning process as the minimization of free energy and investigate its relationship with the Rescorla-Wagner model, focusing on the informational aspects of learning, different types of surprise, and prediction errors based on beliefs and values. Furthermore, we explore how well-known behavioral phenomena such as blocking, overshadowing, and latent inhibition can be modeled within the active inference framework. We accomplish this by using the informational and novelty aspects of attention, which share similar ideas proposed by seemingly contradictory models such as Mackintosh and Pearce-Hall models. Thus, we demonstrate that the free energy principle, as a theoretical framework derived from first principles, can integrate the ideas and models of associative learning proposed based on empirical experiments and serve as a framework for a better understanding of the computational processes behind associative learning in the brain.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Abstract
Spiking neural networks (SNNs) have garnered significant attention owing to their adeptness in processing temporal information, low power consumption, and enhanced biological plausibility. Despite these advantages, the development of efficient and high-performing learning algorithms for SNNs remains a formidable challenge. Techniques such as artificial neural network (ANN)-to-SNN conversion can convert ANNs to SNNs with minimal performance loss, but they necessitate prolonged simulations to approximate rate coding accurately. Conversely, the direct training of SNNs using spike-based backpropagation (BP), such as surrogate gradient approximation, is more flexible and widely adopted. Nevertheless, our research revealed that the shape of the surrogate gradient function profoundly influences the training and inference accuracy of SNNs. Importantly, we identified that the shape of the surrogate gradient function significantly affects the final training accuracy. The shape of the surrogate gradient function is typically manually selected before training and remains static throughout the training process. In this article, we introduce a novel k-based leaky integrate-and-fire (KLIF) spiking neural model. KLIF, featuring a learnable parameter, enables the dynamic adjustment of the height and width of the effective surrogate gradient near threshold during training. Our proposed model undergoes evaluation on static CIFAR-10 and CIFAR-100 data sets, as well as neuromorphic CIFAR10-DVS and DVS128-Gesture data sets. Experimental results demonstrate that KLIF outperforms the leaky Integrate-and-Fire (LIF) model across multiple data sets and network architectures. The superior performance of KLIF positions it as a viable replacement for the essential role of LIF in SNNs across diverse tasks.
in Neural Computation on 2024-11-19 00:00:00 UTC.
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Early infection in life has been implicated in increasing the risk for neurological disorders. Here we performed single-cell sequencing of microglia and monocytes from 6-month-old WT and 5xFAD mice subjected to one dose of LPS (1mg/kg) at postnatal day 9. We successfully mapped disease-associated microglia (DAM) and perivascular macrophages in our data and demonstrated a subpopulation of microglia that adopted a monocyte-like profile, marked by Lyz2, Tmsb10, Lgals1and Lgals3. This unique subset appeared in response to early systemic LPS challenge and AD pathology but diminished in the presence of double stimulus. Different cytokines were altered in the brain and periphery as seen using mesoscale plates. GM-CSF and MIP-1beta levels were altered in an amyloid-beta(A beta)-dependent manner in hippocampus. MIP-1beta and IFN-gamma were altered upon early LPS stimulation. In the periphery, we found MMP-9 was significantly increased in serum samples from 5xFAD mice. Interestingly, early LPS stimulation significantly elevated TNF-alpha in serum from WT and 5xFAD mice, but was reduced in the hippocampus due to A beta pathology. The LPS treatment in 5xFAD mice had a tendency to improve the short-term memory deficit. Taken together, we observed long-lasting effects from early life stress, including activation of inflammation in the periphery and brain through modulation of different signaling cascades.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Anterolateral system (ALS) spinal projection neurons are essential for pain perception. However, these cells are heterogeneous, and there has been extensive debate about the roles of ALS populations in the different pain dimensions. We recently performed single-nucleus RNA sequencing on a developmentally-defined subset of ALS neurons, and identified 5 transcriptomic populations. One of these, ALS4, consists of cells that express Sst, the gene coding for somatostatin, and we reported that these were located in the lateral part of lamina V. Here we use a SstCre mouse line to characterise these cells and define their axonal projections. We find that their axons ascend mainly on the ipsilateral side, giving off collaterals throughout their course in the spinal cord. They target various brainstem nuclei, including the parabrachial internal lateral nucleus, and the posterior triangular and medial dorsal thalamic nuclei. We also show that in the L4 segment Sst is expressed by ~75% of ALS neurons in lateral lamina V and that there are around 120 Sst-positive lateral lamina V cells on each side. Our findings indicate that this is a relatively large population, and based on projection targets we conclude that they are likely to contribute to the affective-motivational dimension of pain.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Osteoarthritis (OA) is a condition affecting synovial joints that has a multifactorial pathogenesis and where pain is the main symptom driving clinical decision making. During OA, a plethora of mediators are released by infiltrating immune cells and resident cells, such fibroblast-like synoviocytes. Although the roles of certain OA-associated disease mediators are well-understood, there are a number of molecules that are dysregulated in OA for which no role has been identified. For example, in dogs and humans with OA, dysregulation of the synovial fluid lipidome occurs and some findings have been replicated by studying the plasma lipidome in a mouse model of osteoarthritis. One upregulated lipid is the sphingomyelin N-palmitoyl-D-erythro-sphingosylphosphorylcholine (d18:1/16:0), also known as SM(d34:1), referred to here as SM. This study investigated the ability SM to cause joint pain and neuronal hyperexcitability in mice. Overnight incubation of sensory neurons with either SM or a structurally related ceramide produced a decrease in rheobase, i.e. hyperexcitability. By contrast, when injected into the knee joint of mice, SM, but not the related ceramide, evoked joint swelling, mechanical hyperalgesia and decreased digging behaviour. Moreover, when studying the excitability of retrograde traced, knee-innervating sensory neurons, only those isolated from SM-injected mice exhibited hyperexcitability. The results generated demonstrate that a dysregulated lipidome can contribute to inflammatory OA pain, further work being necessary to determine the mechanism by which SM exerts its activity.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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This study investigated the interplay between attention and arousal in humans by measuring pupil dilation as a function of task engagement and stimulus relevance. Arousal in response to task-relevant and unexpected irrelevant sounds was measured in healthy young adults during the performance of an auditory detection task, the Competitive Attention Test, and in sensory matched passive conditions. Attention was manipulated using informative and uninformative visual cues. Both relevant and irrelevant sounds elicited a larger increase in pupil dilation in the active compared to the passive condition, revealing a global effect of task engagement on arousal. Additionally, in the active condition, the pupil dilation amplitude during the anticipation and detection of the task-relevant sound was greater following an informative compared to an uninformative cue, while no cue effect was found on the pupil dilation response to distracting sounds. This finding suggests that arousal can be selectively enhanced by attention for task-relevant, but not -irrelevant, events.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Scents could modulate anxiety levels, such as anxiety in a medical office. Here we investigated the impact of two scents on the subjective and physiological anxiety markers in the dental office environment, utilizing self-reported anxiety assessments alongside physiological assessment with electroencephalographic (EEG) and electrocardiographic (ECG) measurements. Lavender was the first tested scent with the previously reported calming effect. African stone was the second stimulus with a musky scent. Twenty healthy participants took part in scent exposure sessions. Anxiety levels were assessed using the State-Trait Anxiety Inventory (STAI), EEG-based theta, alpha, and beta power ratios, and heart rate variability (HRV) indices derived from ECG data. Lavender exposure significantly decreased self-reported anxiety whereas African stone reduced physiological indicators of anxiety. Namely, African stone exposure led to decreased theta and increased alpha power in the parietal-occipital EEG signals. Additionally, decreases were observed in low-frequency (LF) HRV power and total HRV power, reflecting lowered autonomic arousal. These findings support the potential effectiveness for olfactory interventions to aid in anxiety management within clinical environments, but draw attention to the issue of proper evaluation of anxiety. In particular, the difference between the subjective reports and traditional EEG and HRV markers indicates that anxiety involves a complexity of factors, which makes its treatment by scents challenging.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Functionally specific long-range lateral connectivity in layer 2/3 of the primary visual cortex (V1) supports the integration of visual information across visual space and shapes spontaneous, visual and optogenetically driven V1 activity. However, a comprehensive understanding of how these diverse cortical regimes emerge from this underlying cortical circuitry remains elusive. Here we address this gap by showing how the same model assuming moderately iso-orientation biassed long-range cortical connectivity architecture explains diverse phenomena, including (i) range of visually driven phenomena, (ii) modular spontaneous activity, (iii) the propagation of spontaneous cortical waves, and (iv) neural responses to patterned optogenetic stimulation. The model offers testable predictions, including presence of slower and iso-tropic spontaneous wave propagation in layer 4 and non-monotonicity of optogenetically driven cortical response to increasingly larger disk of illumination. We thus offer a holistic framework for studying how cortical circuitry governs information integration across multiple operating regimes.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Oculomotor activity provides critical insights into cognition and health, with growing evidence demonstrating its involvement in various cognitive functions such as attention, memory, and sensory processing. Furthermore, eye movements are emerging as significant indicators of psychopathologies and neurological disorders, including schizophrenia, dementia, depression, and tinnitus. Despite its crucial importance across domains, the role of oculomotion has often been underexplored in neuroimaging studies - largely due to methodological challenges. Eye movements have traditionally been viewed as artefacts in the neural signal, leading to the exclusion of epochs containing them, or correction methods to remove their influence. However, this strategy does not allow us to determine their role in a range of neural effects or mapping between tasks and neural responses. To enable such nuanced investigations in typical function and disease, we introduce what we term "Ocular Response Functions". We used simultaneous magnetoencephalographic and eye-tracking recordings during the resting-state combined with temporal response functions to precisely map the relationship between oculomotion and neural activity. Our approach allows for the temporally and spatially precise prediction of neural activity based on ocular action, and vice versa. We further validate this method in a passive listening task, highlighting its potential for uncovering cognitive insights in experimental settings. By providing a robust framework for examining the interplay between eye movements and neural processes, our method opens new avenues for both research and clinical applications, potentially advancing early detection and intervention strategies for neurological and psychiatric disorders.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Microtubules play a crucial role in neuronal structure and function, with their stability and dynamics regulated by post-translational modifications (PTMs) such as polyglutamylation. In Alzheimer disease (AD), the microtubule-associated protein TAU becomes mislocalized into the somatodendritic compartment (TAU missorting), dissociates from microtubules, aggregates into neurofibrillary tangles, and contributes to microtubule destabilization and neuronal death. Here, we investigated the role of Tubulin-Tyrosine-Ligase-Like proteins (TTLLs) in TAU missorting and microtubule dysregulation using human induced pluripotent stem cell (hiPSC)-derived cortical neurons treated with oligomeric amyloid-beta (oA{beta}) to replicate AD-like conditions. TTLL1, TTLL4, TTLL6 were selectively knocked down (KD) to assess their impact on TAU missorting and microtubule stability. Fluorescence resonance energy transfer (FRET) microscopy was used to examine interactions between TAU and TTLL proteins. We observed TAU missorting, increased tubulin polyglutamylation, decreased microtubule stability, and synaptic declustering in oA{beta}-treated neurons. TTLL1 KD significantly reduced TAU missorting, tubulin polyglutamylation, and synaptic disintegration, while TTLL4 KD showed moderate effects, and TTLL6 KD restored microtubule acetylation. Importantly, TTLL KD did not impair neuritic networks, dendritic complexity, or neuronal activity. FRET microscopy revealed a potential interaction between TAU and TTLL1, but not other TTLLs, suggesting a direct role of TTLL1 in TAU-mediated toxicity. Our findings indicate that targeting TTLL1, either alone or in combination with other TTLLs, may be a promising therapeutic strategy to counteract microtubule and synaptic dysfunction in AD and related neurodegenerative disorders.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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The development of compulsive cue-controlled -incentive- drug-seeking habits, a hallmark of substance use disorder, is predicated on an intrastriatal shift in the locus of control over behaviour from a nucleus accumbens (Nac) core - dorsomedial striatum network to a Nac core - anterior dorsolateral striatum (aDLS) network. Such shift parallels striatal adaptations to chronic drug, including cocaine self-administration, marked by dopamine transporter (DAT) alterations originating in the ventral striatum that spread eventually to encompass the aDLS. Having recently shown that heroin self-administration results in a pan-striatal reduction in astrocytic DAT that precedes the development of aDLS dopamine-dependent incentive heroin-seeking habits we tested the hypothesis that similar adaptations occurr following cocaine exposure. We compared DAT protein levels in whole tissue homogenates, and astrocytes cultured from ventral and dorsal striatal territories of drug naive male Sprague Dawley rats to those of rats with a history of cocaine-taking or an aDLS dopamine-dependent incentive cocaine-seeking habit. Cocaine exposure resulted in a decrease in whole tissue and astrocytic DAT across all territories of the striatum. We further demonstrated that compulsive, i.e., punishment-resistant, incentive cocaine-seeking habits were associated with a reduction in DAT mRNA levels in the Nac shell, but not the Nac core-aDLS incentive habit system. Together with the recent evidence of heroin-induced downregulation of striatal astrocytic DAT, these findings suggest that alterations in astrocytic DAT may represent a common mechanism underlying the development of compulsive incentive drug-seeking habits across drug classes.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Vision first evolved in the water, where light becomes increasingly monochromatic with viewing distance. The presence of spectrally broad ('white') light is therefore the exclusive remit of the visual foreground. However, if and how aquatic visual systems exploit this 'white effect' as an inductive bias, for example to judge distance, remains unknown. By combining two-photon imaging with hyperspectral stimulation, genetic cone-type ablation, and behaviour, we here show that zebrafish suppress neural responses to the visual background by contrasting 'greyscale' and 'colour' circuits that emerge at the first synapse of vision. To do so, zebrafish use an early retinal architecture that fundamentally differs from that of mammals: Rather than combining cone signals to drive the retinal output leading to behaviour, zebrafish vision is built around competing ancestral cone systems: Red/UV versus green/blue. Of these, the non-opponent red and UV cones, which are retained in mammals, are necessary and sufficient for vision. By contrast, the colour opponent green and blue cones, which are lost in mammals, form a net-suppressive 'auxiliary' system that shape the 'core' drive from red and UV cones. Our insights challenge the long-held notions that cones act in concert to drive visual behaviour, and that their spectral diversity primarily serves colour vision. Instead, we posit that vertebrate vision is ancestrally built upon opposing cone systems that emerged to exploit the strong spectral interactions of light with water. This alternative view points at terrestrialisation, not nocturnalisation, as the leading driver for visual circuit reorganisation in mammals.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Loss of function variants of SCN1B are associated with a range of developmental and epileptic encephalopathies (DEEs), including Dravet syndrome. These DEEs feature a wide range of severe neurological disabilities, including changes to social, motor, mood, sleep, and cognitive function which are notoriously difficult to treat, and high rates of early mortality. While the symptomology of SCN1B-associated DEEs indicates broad changes in neural function, most research has focused on epilepsy-related brain structures and function. Mechanistic studies of SCN1B/Scn1b have delineated diverse roles in development and adult maintenance of neural function, via cell adhesion, ion channel regulation, and other intra- and extra-cellular actions. However, use of mouse models is limited as knockout of Scn1b, globally and even in some cell-specific models (e.g., Parvalbumin+ interneuron-specific knockout) in adult mice, leads to severe and progressive epilepsy, health deterioration, and 100% mortality within weeks. Here, we report findings of a novel transgenic mouse line in which Scn1b was specifically deleted in cerebellar Purkinje cells. Unlike most existing models, these mice did not show failure to thrive or early mortality. However, we quantified marked decrements to Purkinje cell physiology as well as motor, social, and cognitive dysfunction. Our data indicate that cerebellar Purkinje cells are an important node for dysfunction and neural disabilities in SCN1B-related DEEs, and combined with previous work identify this as a potentially vital site for understanding mechanisms of DEEs and developing therapies that can treat these disorders holistically.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Unilateral whisker denervation activates plasticity mechanisms and circuit adaptations in adults. Single nucleus RNA sequencing and multiplex fluorescence in situ hybridization revealed differentially expressed genes related to altered glutamate receptor distributions and synaptogenesis in thalamocortical (TC) recipient layer 4 (L4) neurons of the sensory cortex, specifically those receiving input from the intact whiskers after whisker denervation. Electrophysiology detected increased spontaneous excitatory events at L4 neurons, confirming an increase in synaptic connections. Elevated expression levels of Gria2 mRNA and functional GluA2 subunit of AMPA receptors at the TC synapse indicate the presence of stabilized and potentiated TC synapses to L4 excitatory neurons along the intact pathway after unilateral whisker denervation. These adaptations likely underlie the increased cortical activity observed in rodents during intact whisker sensation after unilateral whisker denervation. Our findings provide new insights into the mechanisms by which the adult brain supports recovery after unilateral sensory loss.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Temporal prediction is a crucial mechanism that allows the brain to optimize sensory processing by anticipating event timing. This predictive ability enhances processing efficiency by modulating brain activity through cortical oscillations that periodically influence neuronal excitability . For example, stimuli with predictable timing are processed more accurately. Although it is well-established that predictions are generated across large-scale brain networks, the roles of different cortical regions, particularly the frontal cortices and sensory areas, remain debated. In this study, we investigated the role of frontal cortices in temporal prediction during auditory perception. Cue tones predicted the timing of auditory targets with different levels of certainty (50%, 80%). We recorded electroencephalographic data (EEG) while participants detected the targets. Functional connectivity analyses revealed that the level of predictability modulates the relative contributions of frontal and auditory cortices during both the anticipation and detection of targets: as the certainty of predictions grows, the involvement of frontal brain regions increases. Our findings suggest that the auditory temporal prediction network relies on an integrated system of frontal and sensory regions, which are sensitive to the level of predictability.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Compared to the well-established functions of sympathetic innervation, the role of sensory afferents in adipose tissues remains less understood. Recent work revealed the anatomical and physiological significance of adipose sensory innervation; however, its molecular underpinning remains unclear. Here, using organ-targeted single-cell RNA sequencing, we identified the mechanoreceptor PIEZO2 as one of the most prevalent receptors in fat-innervating dorsal root ganglia (DRG) neurons. We found that selective PIEZO2 deletion in fat-innervating neurons phenocopied the molecular alternations in adipose tissue caused by DRG ablation. Conversely, a gain-of-function PIEZO2 mutant shifted the adipose phenotypes in the opposite direction. These results indicate that PIEZO2 plays a major role in the sensory regulation of adipose tissues. This discovery opens new avenues for exploring mechanosensation in organs not traditionally considered mechanically active, such as the adipose tissues, and therefore sheds light on the broader significance of mechanosensation in regulating organ function and homeostasis.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Understanding and predicting cognitive decline in Alzheimer's disease (AD) is crucial for timely intervention and management. While neuroimaging biomarkers and clinical assessments are valuable individually, their combined predictive power and interaction with demographic and cognitive variables remain underexplored. This study lays the groundwork for comprehensive longitudinal analyses by integrating neuroimaging markers and clinical data to predict cognitive changes over time. Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), feature-driven supervised machine learning techniques were applied to assess cognitive decline predictability. Results showed that while imaging biomarkers alone offered moderate predictive capabilities, including cognitive and demographic factors significantly improved model performance, with the Random-Forest model achieving near-perfect accuracy. The analysis highlighted the leading role of neuroimaging biomarkers as predictors, along with the importance of incorporating cognitive scores and demographic data to enhance predictability. Explainability analyses further revealed that clinical and demographic data could estimate brain imaging metrics, emphasizing the bidirectional nature of these relationships. This study underscores the need for integrating multi-dimensional data in future longitudinal research to capture time-dependent patterns in cognitive decline and guide the development of targeted intervention strategies. We also introduce and provide NeuroLAMA, an open and extensible data engineering and machine-learning system, to support the continued investigation by the community
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI framework for parametric spherical deconvolution of diffusion MRI data of the brain. We demonstrate its utility for estimating white matter fibre orientations, mapping uncertainty of voxel-based estimates and performing probabilistic tractography by spatially propagating fibre orientation uncertainty. We conduct an extensive comparison against established Bayesian methods based on Markov-Chain Monte-Carlo (MCMC) and find that: a) in-silico training can lead to calibrated SBI networks with accurate parameter estimates and uncertainty mapping for both single and multi-shell diffusion MRI, b) SBI allows amortised inference of the posterior distribution of model parameters given unseen observations, which is orders of magnitude faster than MCMC, c) SBI-based tractography yields reconstructions that have a high level of agreement with their MCMC-based counterparts, equal to or higher than scan-rescan reproducibility of estimates. We further demonstrate how SBI design considerations (such as dealing with noise, defining priors and handling model selection) can affect performance, allowing us to identify optimal practices. Taken together, our results show that SBI provides a powerful alternative to classical Bayesian inference approaches for fast and accurate model estimation and uncertainty mapping in MRI.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Our ability to identify faces is thought to depend on high-level visual processing in the brain. Nonetheless, studies of face recognition have generally relied on 2D face photographs where low-level strategies relying on texture and appearance cues can be employed to adequately support high face identification performance. Here, we designed a fine face discrimination task under 3D pose and lighting variation that was purely based on shape, a task which challenged state-of-the-art artificial vision systems compared to object recognition tasks. In contrast, humans performed this shape based face task at comparable levels to their object recognition performance. We then tested one of the smallest simian primates on this human-level, machine-difficult visual task, the common marmoset -- a small, New World monkey. Marmosets successfully discriminated between face identities across 3D viewing conditions based purely on face shape. Their face recognition performance was on par with their object recognition performance and exhibited face-specific behavioral signatures similar to humans, including lower performance for inverted faces, faces lit from below, and contrast reversed faces. These results demonstrate that a high-level visual behavior, invariant face recognition based purely on geometry and not additional texture and appearance cues, is shared across simian primates from among the smallest to the most advanced, consistent with the presence of common underlying high-level visual brain areas across simian primates.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Analysis of brain volumes across mammalian taxonomic groups reveal a pattern of complementary and inverse covariation between major brain components, including a robust negative covariation between the limbic system and neocortex. To understand the computational basis of this covariation, we investigated the multidimensional representational space of task-optimized machine learning systems. We found that a smooth mapping of this space onto a two-dimensional surface leads to a characteristic layout depending on the structure of its information source. Visual, somatosensory and auditory systems develop ordered spatiotopic maps where units draw information from localized regions of the sensory input. Olfactory and relational memory systems, in contrast, develop fractured maps with distributed patterns of information convergence. Evolutionary optimization of multimodal systems result in inverse covariation between spatiotopic and disordered system components that compete for representational space. These results suggest that the observed pattern of covariation of brain components reflect an essential computational duality in brain evolution.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Background: Intuitively, emotional states guide not only the actions we take, but also our confidence in those actions. This sets the stage for subjective confidence about the best action to take to diverge from the actual likelihood and, clinically, may give rise to over-confidence and risky behaviours during episodes of elevated mood and the reverse during depressive episodes. Whilst computational models have been proposed to explain how emotional states recursively bias perception of action outcomes, these models have not been extended to capture the impacts of mood on confidence. Here we propose a computational model that formalises confidence and its relationship with learning from outcomes and emotional states. Methods: We collected data both in a laboratory context (n=35) and in pre-registered online replication (n=106; https://osf.io/ygc4t). Participants completed a two-armed bandit task, with learning blocks before and after a mood manipulation in which participants unexpectedly received (positive mood induction) or lost (negative mood induction) a relatively large sum of money. Participants periodically reported their decision confidence throughout the task. We examined the extent to which the mood manipulation biased their confidence, predicting that positive and negative moods would lead to over- and under- confidence, respectively. We further predicted that this effect would be stronger in participants with greater propensity towards strong and changeable moods, measured by the Hypomanic Personality Scale. Moreover, we formalized a computational model in which confidence emerges as the difference between the perceived likelihood of reward for the available options. In this model, mood indirectly biases confidence through recursively biased learning of the reward likelihoods for the available options and not from simply shifting overall confidence up or down. Results: In both experiments, we confirmed that moods impacted confidence in the hypothesised direction; absent of any differences in participants' objective performance, average confidence was higher following positive mood induction, and lower following negative mood induction. This effect was larger in participants with higher levels of trait hypomania. Intriguingly, we found that the effect of mood on confidence emerged in concert with learning. Indeed, whilst the shift in mood was greatest immediately post-mood manipulation and returned to baseline by the end of the learning block, the effect of mood on confidence gradually accumulated over learning trials, peaking at the end of the block. These dynamics were captured by simulations of a 'Moody Likelihood' model. Empirically, this model simultaneously accounted for the effects of mood on choices, mood states and confidence through a mood bias parameter. Conclusion: We present a unified model in which moods recursively bias reward learning and, consequently, confidence in decision making. Moods fundamentally bias the accumulation of reward likelihood, rather than directly biasing decision confidence. Clinically, these findings have implications for understanding two core symptoms of mood disorder, suggesting that both perturbed mood and confidence about goal-directed behaviour arise from a common bias during reward learning.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Tau protein plays a central role in many neuropathies. The trajectory by which tau spreads through neural networks is disease-specific but the events driving progression are unknown. This is due in part to the challenge of characterizing tau aggregates in situ. We address that challenge using in situ micro-x-ray diffraction (micro XRD) and micro-X-ray fluorescence (XRF) to examine tau lesions in the brain of a 79-year-old male with dementia. Neuropathological examination revealed classical forms of tau in the hippocampal formation: extensive Pick bodies in the granular layer; modest numbers of neurofibrillary tangles and dystrophic neurites in the CA4 and hilus. Micro XRD indicated that Pick bodies are low in fibril content, whereas neurofibrillary lesions within adjacent tissue exhibit far greater density of fibrillar tau. XRF demonstrated elevated levels of zinc, calcium and phosphorous in all tau-containing lesions whereas sulfur deposition was greatest in lesions exhibiting high fibrillar content. Correlation of lesion morphology with anatomical localization, tau fibrillation and differential elemental accumulation suggests tau fibrils generate biochemically distinct microenvironments that influence lesion morphology, tau seed formation and spreading.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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The neuronal RNA-binding protein (RBP) family nELAVL regulates key neuronal processes by binding directly to target RNA transcripts. In this study, we demonstrate that ELAVL3 is the predominant nELAVL paralog expressed in D1 and D2 medium spiny neurons of the striatum. To investigate its function, we developed ELAVL3 cTag-crosslinking and immunoprecipitation (CLIP) to generate RBP-RNA interaction maps from these neurons. By integrating data from ELAVL3-cTag and Elavl3 knockout mice, we identified distinct regulatory effects of ELAVL3 on alternative splicing of its target transcripts. Notably, ELAVL3 modulates splicing of transcripts encoding proteins critical for glutamate and dopamine receptor signaling. These findings underscore the role of ELAVL3 in RNA-mediated regulation of molecular pathways essential for medium spiny neuron function in the striatum.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Caenorhabditis elegans exhibits complex head exploratory behavior in natural environments. We quantified these movements and examined the motor circuits responsible for their intricate dynamics. Using variational mode decomposition, we distinguished between fast casts and slow bends. Slow bends backpropagate along the body, whereas fast casts show phase-specific timing and influence directional bias during forward movement. Combinatorial ablations of three types of cholinergic motor neurons, coupled with dynamical systems analysis of subsequent behaviors, revealed their distinct and overlapping roles. RMD contribute to head casts; SMD maintain bending states; SMB and SMD enable slow rhythmic bending and head-body coupling; RMD, SMD, and SMB together constitute the head central pattern generator (CPG) that drives forward locomotion. We propose a computational model with dual-timescale proprioceptive feedback to reproduce fast casts and slow bends and demonstrate how phase-specific head casts enhance roaming efficiency by optimizing movement speed. These findings highlight how different excitatory motor neurons control distinct and complementary aspects of head bending dynamics while working synergistically to maximize locomotion efficiency.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Brain age is a powerful marker of general brain health. Furthermore, brain age models are trained on large datasets, thus giving them a potential advantage in predicting specific outcomes - much like the success of finetuning large language models for specific applications. However, it is also well-accepted in machine learning that models trained to directly predict specific outcomes (i.e., direct models) often perform better than those trained on surrogate outcomes. Therefore, despite their much larger training data, it is unclear whether brain age models outperform direct models in predicting specific brain health outcomes. Here, we compare large-scale brain age models and direct models for predicting specific health outcomes in the context of Alzheimer's Disease (AD) dementia. Using anatomical T1 scans from three continents (N = 1,848), we find that direct models outperform brain age models without finetuning. Finetuned brain age models yielded similar performance as direct models, but importantly, did not outperform direct models although the brain age models were pretrained on 1000 times more data than the direct models: N = 53,542 vs N = 50. Overall, our results do not discount brain age as a useful marker of general brain health. However, in this era of large-scale brain age models, our results suggest that small-scale, targeted approaches for extracting specific brain health markers still hold significant value.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Cellular senescence is a major contributor to aging-related degenerative diseases, including Alzheimer's disease (AD). However, much less is known about the key cell types and pathways driving mechanisms of senescence in the brain. We hypothesized that dysregulated cholesterol metabolism is central to cellular senescence in AD. We analyzed whole transcriptomic data and utilized single-cell RNA seq integration techniques to unveil the convoluted cell-type-specific and sub-cell-type-state-specific senescence pathologies in AD using both ROSMAP and Sea-AD datasets. We identified that microglia are central components to AD-associated senescence phenotypes in ROSMAP snRNA-seq data (982,384 nuclei from postmortem prefrontal cortex of 239 AD and 188 non-AD) among non-neuron cell types. We identified that homeostatic, inflammatory, phagocytic, lipid processing and neuronal surveillance microglia states were associated with AD-associated senescence in ROSMAP (152,459 microglia nuclei from six regions of brain tissue of 138 early AD, 79 late AD and 226 control subjects) and in Sea-AD (82,486 microglia nuclei of 42 dementia, 42 no dementia and 5 reference subjects) via integrative analysis, which preserves the meaningful biological information of microglia cell states across the datasets. We assessed top senescence-associated bioprocesses including mitochondrial, apoptosis, oxidative stress, ER stress, endosomes, and lysosomes systems. Specifically, we found that senescent microglia have altered cholesterol-related bioprocesses and dysregulated cholesterol. We discovered three gene co-expression modules representing the specific cholesterol-related senescence transcriptomic signatures in postmortem brains. To validate these findings, the activation of specific cholesterol associated senescence transcriptomic signatures was assessed using integrative analysis of snRNA-seq data from iMGs (microglia induced from iPSCs) exposed to myelin, Abeta, and synaptosomes (56,454 microglia across two replicates of untreated and four treated groups). In vivo cholesterol-associated senescence transcriptomic signatures were preserved and altered after treatment with AD pathological substrates in iMGs. This study provides the first evidence that dysregulation of cholesterol metabolism in microglia is a major driver of senescence pathologies in AD. Targeting cholesterol pathways in senescent microglia is an attractive strategy to slow down AD progression.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Generative network models (GNMs) have been proposed to identify the mechanisms/constraints that shape the organisation of the connectome. These models most commonly parameterise the formation of inter-regional axonal connections using a trade-off between connection cost and some measure of topological complexity or functional value. Despite its simplicity, GNMs can generate synthetic networks that capture many topological properties of empirical brain networks. However, current models often fail to capture the spatial embedding-i.e., the topography-of many such properties, such as the anatomical location of network hubs. In this study, we investigate a diverse array of generative network model formulations and find that none can accurately capture empirical patterns of long-range connectivity. We demonstrate that the spatial embedding of long-range connections is critical in defining hub locations and that it is precisely these connections that are poorly captured by extant models. We further show how standard metrics used for model optimisation and evaluation fail to capture the true correspondence between synthetic and empirical brain networks. Overall, our findings demonstrate common failure modes of GNMs, identify why these models do not fully capture brain network organisation, and suggest ways the field can move forward to address these challenges.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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The neural code remains undiscovered and understanding synaptic input integration under in vivo-like conditions is just the initial step toward unraveling it. Synaptic signals generate fast dendritic spikes through two main modes of temporal summation: coincidence detection and integration. In coincidence detection, dendrites fire only when multiple incoming signals arrive in rapid succession, whereas integration involves summation of postsynaptic potentials over longer periods with minimal membrane leakage. This process is influenced by ionic properties, especially as the membrane potential approaches the firing threshold, where inactivating currents play a critical role. However, the modulation of temporal summation by these currents under in vivo-like conditions has not been thoroughly studied. In our research, we used computer simulations to investigate how three inactivating currents - A-type potassium, T-type calcium, and transient sodium - affect temporal summation. We found that calcium and sodium currents promote integrative behavior in dendrites, while potassium currents enhance their ability to act as coincidence detectors. By adjusting the levels of these currents in dendrites, neurons can flexibly switch between integration and coincidence detection modes, providing them with a versatile mechanism for complex tasks like multiplexing. This flexibility could be key to understanding how neural circuits process information in real time.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Motor axon regeneration after traumatic nerve injuries is a slow process that adversely influences patient outcomes because muscle reinnervation delays result in irreversible muscle atrophy and suboptimal axon regeneration. This advocates for investigating methods to accelerate motor axon growth. Electrical nerve stimulation and exercise both enhance motor axon regeneration in rodents and patients, but these interventions cannot always be easily implemented. A roadblock to uncover novel therapeutic approaches based on the effects of activity is the lack of understanding of the synaptic drives responsible for activity-mediated facilitation of axon regeneration. We hypothesized that the relevant excitatory inputs facilitating axon regrowth originate in GABA/glycine synapses which become depolarizing after downregulation of the potassium chloride cotransporter 2 in motoneurons following axotomy. To test this, we injected tetanus toxin (TeTx) in the tibialis anterior (TA) muscle of mice to block the release of GABA/glycine specifically on TA motoneurons. Thereafter, we axotomized all sciatic motoneurons by nerve crush and analyzed the time-courses of muscle reinnervation in TeTx-treated (TA) and untreated (lateral gastrocnemius, LG) motoneurons. Muscle reinnervation was slower in TA motoneurons with blocked GABA/glycine synapses, as measured by recovery of M-responses and anatomical reinnervation of neuromuscular junctions. Post-hoc immunohistochemistry confirmed the removal of the vesicular associated membrane proteins 1 and 2 by TeTx activity, specifically from inhibitory synapses. These proteins are necessary for exocytotic release of neurotransmitters. Therefore, we conclude that GABA/glycine neurotransmission on regenerating motoneurons facilitates axon growth and muscle reinnervation and discuss possible interventions to modulate these inputs on regenerating motoneurons.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Migraine is a prevalent and disabling brain disorder characterized by recurrent headache attacks alternating with pain-free periods. Patients with migraine exhibit altered brain activation in response to experimental nociceptive stimuli compared to healthy controls, suggesting impaired pain inhibition mechanisms. However, the relevance of these alterations to the underlying pathophysiology of migraine attacks remains unclear. To explore this relationship, we propose a novel pain imagery paradigm aimed to induce brain activation patterns associated with migraine attacks specifically during pain-free. The task required patients to alternate between imagining a severe migraine attack and being headache free, while healthy controls imagined severe physical head pain (e.g., toothache) and pain relief. We collected fMRI data from 14 episodic migraine without aura patients in the interictal phase and 15 healthy controls performing this task. Both patients and controls activated pain-related brain areas during imagery of pain relative to pain relief. Moreover, controls also activated the medial pain system associated with pain inhibition and attentional modulation of pain via top-down pathways. In contrast, patients significantly deactivated these areas, namely the anterior cingulate cortex and dorsolateral prefrontal cortex. Collectively, our findings indicate altered functioning of pain networks in migraine patients, suggesting a disease-related dysregulation of pain inhibition. Eventually, the proposed attack imagery paradigm may provide a promising alternative to studies of pain mechanisms in migraine research.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Understanding the relationship between brain structure and function is a central goal in neuroscience. While post-mortem studies using microscopic techniques have provided detailed insights into the brain's cytoarchitectonic and myeloarchitectonic patterns, linking these structural findings to functional outcomes remains challenging. Magnetic resonance imaging (MRI) has emerged as a powerful non-invasive tool for studying both structure and function, but discrepancies in spatial resolution between structural and functional imaging, especially in layer-fMRI, complicate the interpretation of functional results. In this study, we explore how visual cortical hierarchy relates to microscopic and mesoscopic laminar features. Focusing on visual areas that span progressive hierarchical levels, V1, V2, V3, and hMT+, we apply a multimodal approach combining post-mortem histology, post-mortem and in-vivo quantitative MRI (qMRI), and resting-state layer-fMRI. Using the open-access post-mortem AHEAD dataset, which integrates histological and qMRI contrasts from the same brain samples, we bridge microscopic observations with qMRI data. In parallel, we incorporate high-resolution qR2* MRI and resting-state layer-fMRI from the same participant, allowing for a comparative analysis of laminar profiles across cortical depth. For computing laminar profiles, we developed an analysis pipeline that bridges histology images, mesoscopic qMRI, and layer-fMRI. Our findings highlight parvalbumin laminar profiles (reflecting interneuron parvalbumin density) as the most discriminative feature for differentiating brain areas. Additionally, we report laminar quantitative T2* (as 1/R2*) profiles from post-mortem and in-vivo data, together with T2*-weighted resting-state layer-fMRI, all of which exhibit a similar overall shape across modalities. Using our methodological framework, a similar laminar characterization can be extended to study other brain regions. Generative models for layer fMRI will benefit from incorporating these new empirical microstructural (parvalbumin) and physical quantitative (qR2*) data, leading to more area-specific and accurate models.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Feature selectivity, the ability of neurons to respond preferentially to specific stimulus configurations, is a fundamental building block of cortical functions. Various mechanisms have been proposed to explain its origins, differing primarily in their assumptions about the connectivity between neurons. Some models attribute selectivity to structured, tuning-dependent feedforward or recurrent connections, whereas others suggest it can emerge within randomly connected networks when interactions are sufficiently strong. This range of plausible explanations makes it challenging to identify the core mechanisms of feature selectivity in the cortex. We developed a novel, data-driven approach to construct mechanistic models by utilizing connectomic data-synaptic wiring diagrams obtained through electron microscopy-to minimize preconceived assumptions about the underlying connectivity. With this approach, leveraging the MICrONS dataset, we investigate the mechanisms governing selectivity to oriented visual stimuli in layer 2/3 of mouse primary visual cortex. We show that connectome-constrained network models replicate experimental neural responses and point to connectivity heterogeneity as the dominant factor shaping selectivity, with structured recurrent and feedforward connections having a noticeable but secondary effect in its amplification. These findings provide novel insights on the mechanisms underlying feature selectivity in cortex and highlight the potential of connectome-based models for exploring the mechanistic basis of cortical functions.
in bioRxiv: Neuroscience on 2024-11-19 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1155: Longitudinal Insights into the Mental Health of Healthcare Workers: Emotional Shifts During Two Years of the COVID-19 Crisis
Brain Sciences doi: 10.3390/brainsci14111155
Authors:
Maia Stanisławska-Kubiak
Grażyna Teusz
Michał Ziarko
Ewa Mojs
Objective: Numerous studies have highlighted the prevalence of mental health disorders among healthcare professionals during the COVID-19 pandemic, with varying indications of emotional strain. This study compares the psychological functioning of healthcare workers at the onset of the pandemic and two years later, offering a comprehensive assessment of their emotional and mental health status in the evolving context of COVID-19. Methods: This longitudinal analysis examined the relationship between stress, emotional processing, and their positive/negative impacts on medical personnel working in Polish hospitals and outpatient clinics in 2020 (n = 285) and 2022 (n = 252). The study employed the Toronto Alexithymia Scale-20 (TAS-20), Cohen’s Perceived Stress Scale (PSS-10), Mini-COPE, Acceptance of Illness Scale (AIS), Emotional Processing Scale (EPS), STAI, and PANAS to assess psychological responses and coping mechanisms. Results: Findings revealed a significant increase in denial, substance use, self-blame, negative mood, and impaired psychological and somatic functioning, alongside heightened symptoms of depression and anxiety. Conversely, a marked decrease in planning, positive reinterpretation, acceptance, religious coping, and seeking social support (both emotional and instrumental) was observed over the two-year period. Conclusion: The prolonged nature of the COVID-19 pandemic has profoundly affected the psychological resilience of healthcare professionals, eroding critical emotional resources necessary for maintaining interpersonal relationships and mental well-being. These results underscore the need for targeted interventions to support the mental health of medical staff in the ongoing crisis.
in Brain Sciences on 2024-11-19 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1154: Window Coverage and Liquid Biopsy in the First-Line Therapy of Severe Sudden Sensorineural Hearing Loss
Brain Sciences doi: 10.3390/brainsci14111154
Authors:
Alexander Kilgue
Rayoung Kim
Lars-Uwe Scholtz
Conrad Riemann
Christoph J. Pfeiffer
Matthias Schürmann
Ingo Todt
Introduction: Based on clinical practice guidelines, the application of corticosteroids as a first-line therapy is common. Although sudden sensorineural hearing loss (SSHL) etiology is primarily idiopathic, hearing loss can result from a perilymphatic fistula (PLF). Recent findings show evidence of a specific rate of PLF based on a cochlin-tomoprotein (CTP) detection test. Based on this rate of PLF treatment, the concepts of SSNHL need to be re-evaluated. The present study aimed to evaluate CTP in SSNHL patients and compare pre-surgical and post-surgical pure tone hearing thresholds after round and oval window sealing as first-line treatment. Material and Methods: A total of 30 patients with unilateral SSNHL with a pure tone average (PTA) (4 Freq. of 60 dB or more were enrolled in a prospective study. All patients underwent tympanoscopy for middle ear exploration as a first-line treatment. After intraoperative observation of a possible PLF, all patients obtained middle ear lavage to gain CTP samples for following ELISA-based CTP detection tests. All patients received round window and oval window sealing with fascia. PTA hearing thresholds were analyzed post-surgically 3 weeks after treatment based on 4-frequency bone conduction (BC). Results: The average preoperative pure tone BC threshold was 97.7 dB compared with the 69 dB postoperative BC threshold. Mean BC improved by 20.3 dB after middle ear exploration and window sealing. A total of 56% (17 of 30) of patients recovered at least 10 dB. The middle ear cochlin-tomoprotein detection rate was 70% positive. Conclusions: The combination of early tympanoscopy and inner ear-specific cochlin-tomoprotein as a detection tool for suspected PLF showed evidence of PLF as a key causative in SSNHL.
in Brain Sciences on 2024-11-19 00:00:00 UTC.
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The study of ideological asymmetries in empathy has consistently yielded inconclusive findings. Yet, until recently these inconsistencies relied exclusively on self-reports, which are known to be prone to biases and inaccuracies when evaluating empathy levels. Very recently, we reported ideological asymmetries in cognitive-affective empathy while relying on neuroimaging for the first time to address this question. In the present investigation which sampled a large cohort of human individuals from two distant countries and neuroimaging sites, we re-examine this question, but this time from the perspective of empathy to physical pain. The results are unambiguous at the neural and behavioral levels and showcase no asymmetry. This finding raises a novel premise: the question of whether empathy is ideologically asymmetrical depends on the targeted component of empathy (e.g., physical pain vs cognitive-affective) and requires explicit but also unobtrusive techniques for the measure of empathy. Moreover, the findings shed new light on another line of research investigating ideological (a)symmetries in physiological responses to vicarious pain, disgust, and threat.
in eNeuro on 2024-11-18 17:30:00 UTC.
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Impulsive individuals excessively discount the value of delayed rewards, and this is thought to reflect deficits in brain regions critical for impulse control such as the anterior cingulate cortex (ACC). Delay discounting (DD) is an established measure of cognitive impulsivity, referring to the devaluation of rewards delayed in time. This study used male Wistar rats performing a DD task to test the hypothesis that neural activity states in ACC ensembles encode strategies that guide decision-making. Optogenetic silencing of ACC neurons exclusively increased impulsive choices at the 8 s delay by increasing the number of consecutive low-value, immediate choices. In contrast to shorter delays where animals preferred the delay option, no immediate or delay preference was detected at 8 s. These data suggest that ACC was critical for decisions requiring more deliberation between choice options. To address the role of ACC in this process, large-scale multiple single-unit recordings were performed and revealed that 4 and 8 s delays were associated with procedural versus deliberative neural encoding mechanisms, respectively. The 4 and 8 s delay differed in encoding of strategy corresponding to immediate and delay run termination. Specifically, neural ensemble states at 4 s were relatively stable throughout the choice but exhibited temporal evolution in state space during the choice epoch that resembled ramping during the 8 s delay. Collectively, these findings indicate that ensemble states in ACC facilitate strategies that guide decision-making, and impulsivity increases with disruptions of deliberative encoding mechanisms.
in eNeuro on 2024-11-18 17:30:00 UTC.
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In this paper, we apply the concept of bipolar fuzzy sets to pseudo-UP ideals in pseudo-UP algebras. We prove that the intersection of two bipolar fuzzy pseudo-UP ideals is also a bipolar fuzzy pseudo-UP ideal, while the union of two such ideals does not always result in a bipolar fuzzy pseudo-UP ideal. Additionally, we discuss the concepts of bipolar fuzzy pseudo-UP ideals under homomorphism and explore several related properties. The homomorphic image and inverse image of bipolar fuzzy pseudo-UP ideals in a pseudo-UP algebra are also examined in detail. Furthermore, we study the notion of a bipolar fuzzy pseudo-UP ideal under the Cartesian product of pseudo-UP algebra. The Cartesian product of any two bipolar fuzzy pseudo-UP ideals is also the bipolar fuzzy pseudo-UP ideal of pseudo-UP algebra, and then some related results are obtained. MSC: 03G25, 06D30.
in F1000Research on 2024-11-18 16:55:31 UTC.
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The varied geography (Bekele, 1996) and rapid economic growth of Ethiopia (World Bank, 2020) might have impact its air pollution patterns, with topography, elevation, and climate variability (Lemma Gonfa, 1996) playing significant roles. Environmental challenges, including deforestation and climate change, also affect air quality. This study offers a systematic review of air pollution research in Ethiopia, providing a thorough analysis of its health, environmental, and economic impacts, regional variations, and policy suggestions. It addresses both indoor and outdoor air pollution, assessing their wide-ranging effects. Data were gathered through an extensive search of peer-reviewed articles, policies, and guidelines using Google Scholar and reputable sources, following PRISMA guidelines. The review highlights critical sources of air pollution in Ethiopia, including indoor biomass fuel combustion and outdoor emissions from traffic and industries. Indoor air pollution, particularly from traditional biomass fuels like wood and dung, affects rural and peri-urban areas, leading to high levels of particulate matter and carbon monoxide. Outdoor pollution, driven by urbanization, industrial expansion, and vehicle emissions, worsens health issues and environmental damage. The study identifies severe health consequences, such as respiratory infections and cardiovascular diseases, with air pollution contributing to premature deaths and rising healthcare costs. Economic analysis highlights the significant costs related to healthcare, lost productivity, and infrastructure damage. Environmental impacts include harm to plant health, soil degradation, and contributions to climate change. Despite initiatives to improve air quality monitoring and regulation, challenges persist due to outdated policies, limited infrastructure, and insufficient data. The study emphasizes the need for more comprehensive research and regulations to tackle air pollution crisis.
in F1000Research on 2024-11-18 16:35:20 UTC.
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Background COVID-19 disease has spread rapidly worldwide, causing high mortality. Accessible biomarkers capable of early identification of patients at risk of severe form are needed in clinical practice. The aim of the study was to determine the biological markers that predict a critical condition. Methods Retrospective study including patients with confirmed COVID-19 hospitalized between September 2020 and June 2021. The primary endpoint was progression to critical status within 7 days from admission. We defined two groups: Critical group: Patients who developed a critical condition or died or transferred to the ICU before or at 7th day. Non-critical group: Patients who remained in non-critical respiratory status until 7th day or discharged before or at 7th day. Results Our study included 456 patients, with a sex ratio of 1.32 and an average age of 62 years. At the 7th day of hospitalization, 115 (25.2%) patients were in the critical group and 341 (74.8%) patients were in the non-critical group. The univariate logistic regression indicated that laboratory findings between non-critical and critical groups showed that C-reactive protein (CRP) (p=0.047), D-Dimer (p=0.011), creatinine (0.026), creatine kinase (p=0.039), lactate dehydrogenase (p=0.04), and troponin (p=0.001) were all higher among patients in critical group. However, lymphocyte (p<0.001) and platelet (p<0.001) counts were significantly lower among the critical group. Multivariate logistic regression model, identified four independent risk factors: lymphopenia (OR=2.771, 95%CI=1.482-5.181, p=0.001), Neutrophil to Lymphocyte Ratio (NLR) (OR=2.286, 95%CI=1.461-3.578, p<0.001), thrombocytopenia (OR=1.944, 95%CI=1.092-3.459, p=0.024), and CRP>71.5 (OR=1.598, 95% CI=1.042-2.45, p=0.032) were associated to critical group. Conclusions Our results show the predictive value of lymphopenia, thrombocytopenia, high NLR and CRP levels to evaluate the prognosis of COVID-19 pneumonia. A prognostic score could be proposed for guiding clinical care and improving patient outcomes.
in F1000Research on 2024-11-18 16:28:12 UTC.
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Background The Indian government is committed to addressing various manifestations of malnutrition, including overweight and obesity, inorder to improve individual health and well-being. The scoping review aims to map existing national policy instruments (programmes, schemes, regulations and guidelines) addressing overweight and obesity in India and analysing them for Social and Behaviour Change Communication (SBCC) strategies. Methods Systematic identification and selection of policy instruments using ‘Arksey and O’Malley’ framework was conducted from central government ministry websites, between March and June 2023. These instruments focused on nutrition and/or physical activity, targeting specific demographic groups like pregnant women, lactating mothers, children (0-5 years and 5-9 years), or adolescents (10-19 years); excluding those focusing on specific diseases like micronutrient deficiencies, wasting, and stunting. Based on search strategy six policy instruments were included and analysed for SBCC strategies. Results While many policy instruments incorporated SBCC plans; the ‘National Programme for Prevention of Non-Communicable Diseases (NP-NCD)’ stands out as a significant policy initiative specifically targeting the prevention of overweight and obesity within the broader context of Non-Communicable Diseases. It adopts a comprehensive approach addressing key drivers contributing to overweight/obesity across multiple levels of behavioural influence i.e., individual, interpersonal, community and organisation for health promotion. However, there’s need to strengthen SBCC strategies related to prevention and management of obesity, especially screening and counselling, to cover all age groups with a particular focus on adolescents and youth. SBCC strategies can also be incorporated into India’s Integrated Nutrition Support Programme (POSHAN 2.0) and/or Reproductive, Maternal, New-born, Child, Adolescent Health and Nutrition (RMNCAH+N) under the National Health Mission. Conclusion This paper underscores the necessity for comprehensive strategies to address multifaceted origins of overweight and obesity. The NP-NCD stands out as a noteworthy initiative, and there is considerable potential for other programmes to emulate SBCC strategies to bolster their overall effectiveness. Note : *Policy instruments throughout the paper have been used to cover programmes, schemes, regulations and guidelines.
in F1000Research on 2024-11-18 16:09:36 UTC.
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Background The demand for online education promotion platforms has increased. In addition, the digital library system is one of the many systems that support teaching and learning. However, most digital library systems store books in the form of libraries that were developed or purchased exclusively by the library, without connecting data with different agencies in the same system. Methods A hybrid recommender system model for digital libraries, developed from multiple online publishers, has created a prototype digital library system that connects various important knowledge sources from multiple digital libraries and online publishers to create an index and recommend e-books. The developed system utilizes an API-based linking process to connect various important sources of knowledge from multiple data sources such as e-books on education from educational institutions, e-books from government agencies, and e-books from religious organizations are stored separately. Then, a hybrid recommender system suitable for users was developed using Collaborative Filtering (CF) model together with Content-Based Filtering. This research proposed the hybrid recommender system model, which took into account the factors of book category, reading habits of users, and sources of information. The evaluation of the experiments involved soliciting feedback from system users and comparing the results with conventional recommendation methods. Results A comparison of NDCG scores, and Precision scores were conducted for Hybrid Score 50:50, Hybrid Score 20:80, Hybrid Score 80:20, CF-score and CB-score. The experimental result was found that the Hybrid Score 80:20 method had the highest average NDCG score. Conclusions Using a hybrid recommender system model that combines 80% Collaborative Filtering, and 20% Content-Based Filtering can improve the recommender method, leading to better referral efficiency and greater overall efficiency compared to traditional approaches.
in F1000Research on 2024-11-18 16:03:48 UTC.
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Background Multiple medical conditions arising from reduced physical and physiological functioning, including cognitive decline, manifest in older persons. This study aims to examine the relationship between cognitive function and associated risk factors in older persons living in long-term care facilities in Indonesia. Methods This study involved 350 elderly individuals residing in long-term care institutions. A cross-sectional design utilizing an analytical survey methodology was implemented. Data were gathered via interviews employing a demographic questionnaire and the Montreal Cognitive Assessment (MoCA). Statistical analysis was conducted using SPSS (version 23). Results Univariate analysis demonstrated significant correlations between cognitive performance and gender, ethnicity, level of education, medical history, subjective memory issues, smoking habits, alcohol consumption, dietary intake of fruits and vegetables, and employment history (p < 0.05). Higher education (OR = 0.69, 95% CI: 0.56–0.84) and reduced subjective memory complaints (OR = 0.29, 95% CI: 0.20–0.44) correlated positively with enhanced cognitive function, but alcohol intake (OR = 6.79, 95% CI: 2.42–19.1) correlated with impaired cognitive function. Conclusions the level of education, subjective memory complaints, and alcohol intake are substantially correlated with cognitive performance in older persons residing in long-term care facilities. Evaluating demographic characteristics in elderly individuals can assist healthcare professionals in the early detection of cognitive impairment, facilitating prompt interventions in long-term care environments.
in F1000Research on 2024-11-18 15:24:54 UTC.
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by Fei Cai, Yuehua Wei, Daniel Kirchhofer, Andrew Chang, Yingnan Zhang
Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However, naturally occurring disulfide-constrained peptides (DCPs) and de novo designed Hyperstable Constrained Peptides (HCPs) exhibiting highly stable and drug-like scaffolds, making them attractive therapeutic modalities. Previously, we established a robust platform for discovering peptide therapeutics by utilizing multiple DCPs as scaffolds. However, we realized that those libraries could be further improved by considering the foldability of peptide scaffolds for library design. We hypothesized that specific sequence patterns within the peptide scaffolds played a crucial role in spontaneous folding into a stable topology, and thus, these sequences should not be subject to randomization in the original library design. Therefore, we developed a method for designing highly diverse DCP libraries while preserving the inherent foldability of each scaffold. To achieve this, we first generated a large-scale dataset from yeast surface display (YSD) combined with shotgun alanine scan experiments to train a machine-learning (ML) model based on techniques used for natural language understanding. Then we validated the ML model with experiments, showing that it is able to not only predict the foldability of peptides with high accuracy across a broad range of sequences but also pinpoint residues critical for foldability. Using the insights gained from the alanine scanning experiment as well as prediction model, we designed a new peptide library based on a de novo-designed HCP, which was optimized for enhanced folding efficiency. Subsequent panning trials using this library yielded promising hits having good folding properties. In summary, this work advances peptide or small protein domain library design practices. These findings could pave the way for the efficient development of peptide-based therapeutics in the future.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Chao Wang, Quan Zou
Protein phosphorylation is essential in various signal transduction and cellular processes. To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. In this study, a novel tool called MFPSP is developed for phosphorylation site prediction in multi-fungal species. The amino acids sequence features were derived from physicochemical and distributed information, and an offspring competition-based genetic algorithm was applied for choosing the most effective feature subset. The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. Feature contribution and interaction exploration indicating the proposed model is efficient in uncovering concealed patterns within sequence. We anticipate MFPSP to serve as a valuable bioinformatics tool and benefiting practical experiments by pre-screening potential phosphorylation sites and enhancing our functional understanding of phosphorylation modifications in fungi. The source code and datasets are accessible at https://github.com/AI4HKB/MFPSP/.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Qiangwei Peng, Xiaojie Qiu, Tiejun Li
The time-resolved scRNA-seq (tscRNA-seq) provides the possibility to infer physically meaningful kinetic parameters, e.g., the transcription, splicing or RNA degradation rate constants with correct magnitudes, and RNA velocities by incorporating temporal information. Previous approaches utilizing the deterministic dynamics and steady-state assumption on gene expression states are insufficient to achieve favorable results for the data involving transient process. We present a dynamical approach, Storm (Stochastic models of RNA metabolic-labeling), to overcome these limitations by solving stochastic differential equations of gene expression dynamics. The derivation reveals that the new mRNA sequencing data obeys different types of cell-specific Poisson distributions when jointly considering both biological and cell-specific technical noise. Storm deals with measured counts data directly and extends the RNA velocity methodology based on metabolic labeling scRNA-seq data to transient stochastic systems. Furthermore, we relax the constant parameter assumption over genes/cells to obtain gene-cell-specific transcription/splicing rates and gene-specific degradation rates, thus revealing time-dependent and cell-state-specific transcriptional regulations. Storm will facilitate the study of the statistical properties of tscRNA-seq data, eventually advancing our understanding of the dynamic transcription regulation during development and disease.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Aaron R. Allred, Caroline R. Austin, Lanna Klausing, Nicholas Boggess, Torin K. Clark
Galvanic vestibular stimulation (GVS) is an emergent tool for stimulating the vestibular system, offering the potential to manipulate or enhance processes relying on vestibular-mediated central pathways. However, the extent of GVS’s influence on the perception of self-orientation pathways is not understood, particularly in the presence of physical motions. Here, we quantify roll tilt perception impacted by GVS during passive whole-body roll tilts in humans (N = 11). We find that GVS systematically amplifies and attenuates perceptions of roll tilt during physical tilt, dependent on the GVS waveform. Subsequently, we develop a novel computational model that predicts 6DoF self-motion and self-orientation perceptions for any GVS waveform and motion by modeling the vestibular afferent neuron dynamics modulated by GVS in conjunction with an observer central processing model. This effort provides a means to systematically alter spatial orientation perceptions using GVS during concurrent physical motion, and we find that irregular afferent dynamics alone best describe resultant perceptions.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Salah Bazzi, Stephan Stansfield, Neville Hogan, Dagmar Sternad
Humans are skillful at manipulating objects that possess nonlinear underactuated dynamics, such as clothes or containers filled with liquids. Several studies suggested that humans implement a predictive model-based strategy to control such objects. However, these studies only considered unconstrained reaching without any object involved or, at most, linear mass-spring systems with relatively simple dynamics. It is not clear what internal model humans develop of more complex objects, and what level of granularity is represented. To answer these questions, this study examined a task where participants physically interacted with a nonlinear underactuated system mimicking a cup of sloshing coffee: a cup with a ball rolling inside. The cup and ball were simulated in a virtual environment and subjects interacted with the system via a haptic robotic interface. Participants were instructed to move the system and arrive at a target region with both cup and ball at rest, ’zeroing out’ residual oscillations of the ball. This challenging task affords a solution known as ‘input shaping’, whereby a series of pulses moves the dynamic object to the target leaving no residual oscillations. Since the timing and amplitude of these pulses depend on the controller’s internal model of the object, input shaping served as a tool to identify the subjects’ internal representation of the cup-and-ball. Five simulations with different internal models were compared against the human data. Results showed that the features in the data were correctly predicted by a simple internal model that represented the cup-and-ball as a single rigid mass coupled to the hand impedance. These findings provide evidence that humans use simplified internal models along with mechanical impedance to manipulate complex objects.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Anna K. Leinheiser, Colleen C. Mitchell, Ethan Rooke, Stefan Strack, Chad E. Grueter
Mitochondrial hyperfission in response to cellular insult is associated with reduced energy production and programmed cell death. Thus, there is a critical need to understand the molecular mechanisms coordinating and regulating the complex process of mitochondrial fission. We develop a nonlinear dynamical systems model of dynamin related protein one (Drp1)-dependent mitochondrial fission and use it to identify parameters which can regulate the total fission rate (TFR) as a function of time. The TFR defined from a nondimensionalization of the model undergoes a Hopf bifurcation with bifurcation parameter μ = k + M k - where M is the total concentration of mitochondrial fission factor (Mff) and k+ and k− are the association and dissociation rate constants between oligomers on the outer mitochondrial membrane. The variable μ can be thought of as the maximum build rate over the disassembling rate of oligomers. Though the nondimensionalization of the system results in four dimensionless parameters, we found the TFR and the cumulative total fission (TF) depend strongly on only one, μ. Interestingly, the cumulative TF does not monotonically increase as μ increases. Instead it increases with μ to a certain point and then begins to decrease as μ continues to increase. This non-monotone dependence on μ suggests interventions targeting k+, k−, or M may have a non-intuitive impact on the fission mechanism. Thus understanding the impact of regulatory parameters, such as μ, may assist future therapeutic target selection.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Baptiste Ruiz, Arnaud Belcour, Samuel Blanquart, Sylvie Buffet-Bataillon, Isabelle Le Huërou-Luron, Anne Siegel, Yann Le Cunff
The composition of the gut microbiota is a known factor in various diseases and has proven to be a strong basis for automatic classification of disease state. A need for a better understanding of microbiota data on the functional scale has since been voiced, as it would enhance these approaches’ biological interpretability. In this paper, we have developed a computational pipeline for integrating the functional annotation of the gut microbiota into an automatic classification process and facilitating downstream interpretation of its results. The process takes as input taxonomic composition data, which can be built from 16S or whole genome sequencing, and links each component to its functional annotations through interrogation of the UniProt database. A functional profile of the gut microbiota is built from this basis. Both profiles, microbial and functional, are used to train Random Forest classifiers to discern unhealthy from control samples. SPARTA ensures full reproducibility and exploration of inherent variability by extending state-of-the-art methods in three dimensions: increased number of trained random forests, selection of important variables with an iterative process, repetition of full selection process from different seeds. This process shows that the translation of the microbiota into functional profiles gives non-significantly different performances when compared to microbial profiles on 5 of 6 datasets. This approach’s main contribution however stems from its interpretability rather than its performance: through repetition, it also outputs a robust subset of discriminant variables. These selections were shown to be more consistent than those obtained by a state-of-the-art method, and their contents were validated through a manual bibliographic research. The interconnections between selected taxa and functional annotations were also analyzed and revealed that important annotations emerge from the cumulated influence of non-selected taxa.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Jørgen Ankill, Zhi Zhao, Xavier Tekpli, Elin H. Kure, Vessela N. Kristensen, Anthony Mathelier, Thomas Fleischer
Aberrant DNA methylation contributes to gene expression deregulation in cancer. However, these alterations’ precise regulatory role and clinical implications are still not fully understood. In this study, we performed expression-methylation Quantitative Trait Loci (emQTL) analysis to identify deregulated cancer-driving transcriptional networks linked to CpG demethylation pan-cancer. By analyzing 33 cancer types from The Cancer Genome Atlas, we identified and confirmed significant correlations between CpG methylation and gene expression (emQTL) in cis and trans, both across and within cancer types. Bipartite network analysis of the emQTL revealed groups of CpGs and genes related to important biological processes involved in carcinogenesis including proliferation, metabolism and hormone-signaling. These bipartite communities were characterized by loss of enhancer methylation in specific transcription factor binding regions (TFBRs) and the CpGs were topologically linked to upregulated genes through chromatin loops. Penalized Cox regression analysis showed a significant prognostic impact of the pan-cancer emQTL in many cancer types. Taken together, our integrative pan-cancer analysis reveals a common architecture where hallmark cancer-driving functions are affected by the loss of enhancer methylation and may be epigenetically regulated.
in PLoS Computational Biology on 2024-11-18 14:00:00 UTC.
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by Emma M. Glass, Lillian R. Dillard, Glynis L. Kolling, Andrew S. Warren, Jason A. Papin
Bacterial pathogens pose a major risk to human health, leading to tens of millions of deaths annually and significant global economic losses. While bacterial infections are typically treated with antibiotic regimens, there has been a rapid emergence of antimicrobial resistant (AMR) bacterial strains due to antibiotic overuse. Because of this, treatment of infections with traditional antimicrobials has become increasingly difficult, necessitating the development of innovative approaches for deeply understanding pathogen function. To combat issues presented by broad- spectrum antibiotics, the idea of narrow-spectrum antibiotics has been previously proposed and explored. Rather than interrupting universal bacterial cellular processes, narrow-spectrum antibiotics work by targeting specific functions or essential genes in certain species or subgroups of bacteria. Here, we generate a collection of genome-scale metabolic network reconstructions (GENREs) of pathogens through an automated computational pipeline. We used these GENREs to identify subgroups of pathogens that share unique metabolic phenotypes and determined that pathogen physiological niche plays a role in the development of unique metabolic function. For example, we identified several unique metabolic phenotypes specific to stomach pathogens. We identified essential genes unique to stomach pathogens in silico and a corresponding inhibitory compound for a uniquely essential gene. We then validated our in silico predictions with an in vitro microbial growth assay. We demonstrated that the inhibition of a uniquely essential gene, thyX, inhibited growth of stomach-specific pathogens exclusively, indicating possible physiological location-specific targeting. This pioneering computational approach could lead to the identification of unique metabolic signatures to inform future targeted, physiological location-specific, antimicrobial therapies, reducing the need for broad-spectrum antibiotics.
in PLoS Biology on 2024-11-18 14:00:00 UTC.
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by Jingdi Li, Nele Guttmann, Georgia C. Drew, Tobias E. Hector, Justyna Wolinska, Kayla C. King
Climate change is causing extreme heating events and leading to more infectious disease outbreaks, putting species persistence at risk. The extent to which warming temperatures and infection may together impair host health is unclear. Using a meta-analysis of >190 effect sizes representing 101 ectothermic animal host–pathogen systems, we demonstrate that warming significantly increased the mortality of hosts infected by bacterial pathogens. Pathogens that have been evolutionarily established within the host species showed higher virulence under warmer temperatures, too. Conversely, the effect of warming on novel infections—from pathogens without a shared evolutionary history with the host species—were more pronounced with larger differences between compared temperatures. We found that compared to established infections, novel infections were more deadly at lower/baseline temperatures. Moreover, we revealed that the virulence of fungal pathogens increased only when temperatures were shifted upwards towards the pathogen thermal optimum. The magnitude of all these significant effects was not impacted by host life-stage, immune complexity, pathogen inoculation methods, or exposure time. Overall, our findings reveal distinct patterns in changes of pathogen virulence during warming. We highlight the importance of pathogen taxa, thermal optima, and evolutionary history in determining the impact of global change on infection outcomes.
in PLoS Biology on 2024-11-18 14:00:00 UTC.
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by Olena Kim, Yuji Okamoto, Walter A. Kaufmann, Nils Brose, Ryuichi Shigemoto, Peter Jonas
It is widely believed that information storage in neuronal circuits involves nanoscopic structural changes at synapses, resulting in the formation of synaptic engrams. However, direct evidence for this hypothesis is lacking. To test this conjecture, we combined chemical potentiation, functional analysis by paired pre-postsynaptic recordings, and structural analysis by electron microscopy (EM) and freeze-fracture replica labeling (FRL) at the rodent hippocampal mossy fiber synapse, a key synapse in the trisynaptic circuit of the hippocampus. Biophysical analysis of synaptic transmission revealed that forskolin-induced chemical potentiation increased the readily releasable vesicle pool size and vesicular release probability by 146% and 49%, respectively. Structural analysis of mossy fiber synapses by EM and FRL demonstrated an increase in the number of vesicles close to the plasma membrane and the number of clusters of the priming protein Munc13-1, indicating an increase in the number of both docked and primed vesicles. Furthermore, FRL analysis revealed a significant reduction of the distance between Munc13-1 and CaV2.1 Ca2+ channels, suggesting reconfiguration of the channel-vesicle coupling nanotopography. Our results indicate that presynaptic plasticity is associated with structural reorganization of active zones. We propose that changes in potential nanoscopic organization at synaptic vesicle release sites may be correlates of learning and memory at a plastic central synapse.
in PLoS Biology on 2024-11-18 14:00:00 UTC.
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by Farhan Mohammad, Yishan Mai, Joses Ho, Xianyuan Zhang, Stanislav Ott, James Charles Stewart, Adam Claridge-Chang
The brain must guide immediate responses to beneficial and harmful stimuli while simultaneously writing memories for future reference. While both immediate actions and reinforcement learning are instructed by dopamine, how dopaminergic systems maintain coherence between these 2 reward functions is unknown. Through optogenetic activation experiments, we showed that the dopamine neurons that inform olfactory memory in Drosophila have a distinct, parallel function driving attraction and aversion (valence). Sensory neurons required for olfactory memory were dispensable to dopaminergic valence. A broadly projecting set of dopaminergic cells had valence that was dependent on dopamine, glutamate, and octopamine. Similarly, a more restricted dopaminergic cluster with attractive valence was reliant on dopamine and glutamate; flies avoided opto-inhibition of this narrow subset, indicating the role of this cluster in controlling ongoing behavior. Dopamine valence was distinct from output-neuron opto-valence in locomotor pattern, strength, and polarity. Overall, our data suggest that dopamine’s acute effect on valence provides a mechanism by which a dopaminergic system can coherently write memories to influence future responses while guiding immediate attraction and aversion.
in PLoS Biology on 2024-11-18 14:00:00 UTC.
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As post-hoc analyses show, interactive marketing in the new media age has served as a fragmented technique for transitioning from traditional modes of operation to dynamic and customized environments that blur the lines between brands and consumers. Several research papers have been published on interactive marketing, the impact of social media engagement, and brand loyalty. However, they remain fragmented because most produce different results based on different samples at various stages of business development. Nonetheless, there are no systematic reviews that combine all these findings into a comprehensive framework. However, many interactive marketing studies focus on short-term outcomes and do not take into account long-term effects such as brand equity and customer lifetime value. Selected articles were understudied with the requirement of a rigorous review process, which includes a thorough examination of the relevant literature. The implementation of this process is expected to result in the absence of a room for subjective judgment, as all selected studies were carefully evaluated using predetermined criteria. It was determined that the use of these technologies allows brands to interact with their customers in novel and creative ways, resulting in more engaging and dynamic experiences. That is, evaluating the effectiveness of marketing initiatives is critical to understanding their impact.
in F1000Research on 2024-11-18 12:36:00 UTC.
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Background Conventional multi-port laparoscopic cholecystectomy (CMLC) has become the current ‘gold standard’ technique in gallbladder disease. Single-incision laparoscopic cholecystectomy (SILC) has gained attention due to its benefits in improving patient cosmetic results and pain reduction. We aim to assess the latest evidence on the feasibility, safety and surgical outcomes of SILC and CMLC. Methods We conducted searches for randomized controlled trials (RCTs) in PubMed, PubMed Central (PMC), and Europe PMC between December 2011 and 2021. The latest search was conducted in January 2022. We analyzed several outcomes, including perioperative complications, estimated blood loss, operation time, conversion to open surgery, hospital stay, pain score, cosmesis, and days of return to work. Cochrane Risk of Bias (RoB) 2.0 tool was used to evaluate quality of studies. Mantel-Haenszel’s formula and Inverse Variance method were conducted to synthesize results. This study was accomplished in accordance with the PRISMA guidelines. Results A total of 37 studies were eligible, with a total of 2,129 and 2,392 patients who underwent SILC and CMLC. Our study demonstrated a superiority of SILC for the visual analog score (VAS) at six hours post-operation [mean difference (MD) -0.58 (95% CI -1.11, -0.05), p=0.03], cosmesis one-month post-operation [standard MD 2.12 (95% CI 1.10, 3.13), p<0.0001], and cosmesis six months post-operation [standard MD 0.53 (95% CI 0.06, 0.99), p<0.0001]. Meanwhile, SILC showed a longer operation time [MD 10.45 (95% CI 6.74, 14.17), p<0.00001]. In terms of VAS at four time points (4, 8, 12, and 24 hours), perioperative complications, estimated blood loss, conversion to open surgery, hospital stay and days to return to work, SILC did not differ from CMLC. Conclusions SILC is a safe, feasible and favorable procedure in terms of pain reduction and cosmetic results. The option between both procedures is based on surgeon preferences. Registration: PROSPERO (CRD42022306532; 23 February 2022).
in F1000Research on 2024-11-18 12:03:54 UTC.
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Background The cestode Hymenolepis diminuta is a cosmopolitan parasite, which in the adult stage is usually found in the small intestine of rats and accidentally in humans. Case report We describe the finding of eggs of this parasite in an asymptomatic 3-year-old child. The child had extremely high IgE values of 1,376 IU/ml. After receiving treatment with Albendazole suspension 400mg/20mL, on the 10th day post-treatment, he showed no H. diminuta eggs in his fecal matter Conclusions Detailed morphological review of Hymenolepis nana-like eggs is recommended to distinguish them from H. diminuta eggs.
in F1000Research on 2024-11-18 11:44:07 UTC.
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Systematic reviews of health economic evaluations play a crucial role in informing evidence-based healthcare decisions, yet they lack standardized reporting guidelines. A project has been initiated that aims to extend the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for systematic reviews of health economic evaluations (PRISMA-EconEval). This scoping review forms a foundation for the PRISMA-EconEval project, aiming to identify, map, and extract candidate reporting items from the methodological literature. The scoping review will follow the PRISMA Extension for Scoping Reviews (PRISMA-ScR) Checklist and involve comprehensive searches in databases such as PubMed MEDLINE, Embase, and Web of Science, covering the period from 2015 to 2024. Supplementary searching, reference checking and citation searching will target grey literature, overlooked studies and evidence prior to 2015. Inclusion criteria will focus on methodological papers that provide frameworks or recommendations for reporting systematic reviews of health economic evaluations and enhanced case studies that critically discuss methods and reporting structures. The extracted data will be coded and analyzed to produce an initial list of candidate reporting items, structured according to conventional sections of a systematic review (e.g., title, abstract, methods, results). This initial list will be used in the subsequent stages of the project and disseminated through a peer-reviewed publication and presentations at international conferences. The outcome of this scoping review will significantly contribute to the development of a comprehensive PRISMA-EconEval reporting guideline, aimed at enhancing the transparency, consistency, and quality of systematic reviews of health economic evaluations, and provide an essential tool for authors, editors, peer-reviewers, and stakeholders.
in F1000Research on 2024-11-18 11:41:42 UTC.
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Wearable sensors have become integral tools for monitoring biomechanical and physiologic aspects of athletic training and performance. A prominent trend in fitness technology, wearable devices now measure a variety of health characteristics, including movement and posture, physiologic measures (eg, heart rate and energy expenditure), and fluid and electrolyte losses, to understand an athlete’s physiologic responses during activity. Sleep has proven integral to athletic performance, and sleep monitoring wearable devices (eg, watches, rings, and headbands) use various measures, such as actigraphy and pulse oximetry, to analyze sleep quality. Young athletes benefit from wearable devices during training sessions, where multimodal data are collected and analyzed to assess performance. Wearable devices are also useful for resistance training, biofeedback, and electrical muscle stimulation, providing athletes with tools to optimize their training regimens. Moreover, these devices play a crucial role in athlete safety by monitoring cardiac physiology, head impacts, and muscle rehabilitation after injury. We provide a comprehensive review of current wearable technology and its application in youth athletics, describe where and how these sensors are used to help enhance physiologic, biomechanical, and performance parameters, and discuss future directions for wearable devices to advance sports science and athlete management.
in F1000Research on 2024-11-18 11:35:33 UTC.
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Background Temporomandibular disorders (TMD) are diseases of the stomatognathic system characterized by various signs and symptoms. TMD treatment must be multidisciplinary because its causes are multifactorial. Noninvasive conservative treatment strategies should be carried out before considering invasive treatment options that may lead to irreparable damage. Physical therapy is an effective noninvasive therapy for managing the signs and symptoms of TMD. To date, the most effective therapeutic approach for managing TMD pain remains controversial. Therefore, this study aimed to evaluate the most effective physical therapy for pain management, symptom control, and quality of life improvement in patients with TMD. Methods Data search was performed using the PubMed, SCOPUS, and Web of Sciences databases. The results are reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement for systematic reviews. Interventions based on physical therapy, including physical exercise, manual therapy, myofacial muscle manipulation, and postural therapy, with pain relief, increased mouth opening, or improved quality of life as primary outcomes, were examined. Results Twenty eligible articles were analyzed. Most interventions demonstrated statistically significant improvements as measured by the study outcomes. Conclusions Most types of physical therapy demonstrated positive effects on patients with TMD. Furthermore, physical therapy for both cervical and regional TMJ manipulation can be an alternative long-term treatment for TMD.
in F1000Research on 2024-11-18 11:32:58 UTC.
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Background Low Back Pain (LBP) is the most common musculoskeletal disorder in the world. Medical students, particularly those who use computers for study purposes, are more vulnerable to LBP due to prolonged sitting times and improper sitting posture during lectures. However, prior research showed that the prevalence of LBP among medical students appeared lower when they were enrolled during online pandemic learning. Hence, this research is performed to determine the correlation between the duration of sitting and sitting posture on the incidence of LBP among medical students in Universitas Sumatera Utara, Indonesia. Methods A cross-sectional study with an analytical descriptive design was conducted in September 2023 among randomly selected 147 medical students at Universitas Sumatera Utara, Indonesia. The inclusion criteria of the research sample are students with BMI< 23 kg/m2 while the exclusion criteria are students who have abnormalities and a history of trauma or spinal fractures. Data was obtained from filling out questionnaires of The Pain and Distress Scale (PAD) and Body Awareness of Postural Habit in Young People (BAPHY). A Chi-square test and logistic regression were used to analyze data with a p-value < 0.05 was regarded as statistically significant. Results The study’s findings revealed that 40.1% of students reported having LBP problems, 72.1% reported sitting for more than seven hours each day, and 33.3% reported having a bad sitting posture. Chi-square analysis revealed a significant correlation between sitting duration and posture on complaints of lower back pain (RR = 1.69, p = 0.041 and RR = 1.69, p = 0.009). At a risk of 2,438 times, sitting posture is the main factor contributing to LBP among medical students at Universitas Sumatera Utara, Indonesia. Conclusions This research showed a significant correlation between duration and sitting posture on the incidence of low back pain.
in F1000Research on 2024-11-18 11:30:34 UTC.
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Background of the study This research examines how psychological and social biases affect individual investors’ investing decisions. Investor sentiment significantly influences financial markets, frequently causing stock prices to deviate from their intrinsic values. In rising economies such as India, where retail investors are significantly affected by psychological factors, comprehending these attitudes is crucial. Methods This study analyses data from a comprehensive questionnaire that was conducted throughout the nation and included 552 retail investors. The investigation employed structural equation modelling (SEM) to identify the elements that influence the decision-making of individuals who invest in the Indian stock market. Findings The research offers insight on the influence that investor attitude has on investment decision-making as well as the factors that precede it. The study demonstrates that investors make financial decisions based on sentiment. In addition to assessing the efficacy of the Indian financial market, this study sought to ascertain the rationality of investors’ choices by exploring the factors that influence their decision-making process. Conclusion The outcome of the study shows that information seeking, anchoring, herding, representativeness, and overconfidence all have a big impact on investors. Moreover, the study has proven investors’ irrationality and stock market inefficiency. The findings may be employed to further examine the trading practices of international investors and encourage further study in the field of behavioural finance.
in F1000Research on 2024-11-18 11:27:25 UTC.
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Abstract The global energy sector is a primary contributor to greenhouse gas (GHG) emissions, predominantly through fossil fuel combustion for electricity, heating, and transportation (IEA, 2021). This study systematically reviews Ethiopia’s energy sector mitigation approaches, focusing on renewable energy strategies and energy efficiency initiatives. While Ethiopia has made significant progress in hydropower, accounting for over 90% of its electricity generation, challenges remain in diversifying its energy mix to include geothermal and wind energy (Ethiopian Ministry of Water, Irrigation, and Energy (2019) and African Development Bank, 2020). The Climate Resilient Green Economy (CRGE) strategy sets ambitious targets for achieving carbon neutrality by 2030, challenges remain in diversifying its energy mix to include geothermal and wind energy (Benti, Woldegiyorgis, et al., 2023 and Federal Democratic Republic of Ethiopia, 2011), yet its implementation faces barriers, including financial constraints, technological gaps, and weak institutional capacity (Silitonga et al., 2020). The study highlights the potential of Ethiopia’s vast renewable energy resources, such as geothermal and wind, to enhance energy security and foster economic growth through job creation. Despite the hurdles, opportunities exist for scaling up mitigation efforts, particularly through public-private partnerships and improved policy frameworks. This review underscores the importance of addressing barriers to achieve a sustainable energy transition in Ethiopia, contributing to local and global climate mitigation goals. Thus, the policymakers should boost investments in solar, wind, and geothermal energy, reduce reliance on hydropower through incentives, and establish an inter-agency task force for policy alignment. And also, exploring green bonds and fostering human capital development through training and partnerships are essential. A strong monitoring and evaluation framework is crucial for tracking progress towards energy sustainability goals.
in F1000Research on 2024-11-18 11:24:22 UTC.
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Background Third molar extraction is one of the most common oral surgical procedures globally. This study assessed patients’ knowledge of third molar extraction procedures. Methods A self-administered questionnaire was administered to patients (N=384) of the dental hospital at Imam Abdulrahman bin Faisal University in the eastern province. The questionnaire covered demographic data, knowledge of third molar extraction, and patients’ perception questions. SPSS Version 24 was used for statistical analysis. Chi-square and Fisher’s Exact test were used. P-values less than or equal to 0.05 were considered statistically significant. Results According to the demographical characteristics of the patient who received 3rd molar removal surgery. As per the history of the extraction, 45% had previous 3rd molar extraction experience, whereas 55% had no previous dental surgical experience. There was no significant difference between the groups with the knowledge about the extraction (p-0.187). Patients with no previous history were more aware of the correct time for 3rd molar extraction at 27% vs 19%, respectively (P=0.046*). Patients with a previous history of third molar extraction showed significant results of knowledge in terms of taking medication prior to 3rd molar surgical procedure. Conclusion The patient with previous experience with third molar extraction showed low misconceptions. However, further studies should consider increasing the knowledge and correcting the patients’ perceptions.
in F1000Research on 2024-11-18 11:22:07 UTC.
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Background Various problems, such as a shortage of teachers, especially in certain outlying and underdeveloped provinces, unequal distribution of teachers, low teacher competency, and mismatch between educational qualifications and scientific fields, as well as the demands of increasingly dynamic developments in science and technology, resulting in the need for professional development for elementary school teachers to improve teacher professionalism in Indonesia. These background as a basis for the government to create teacher professional education program for elementary school teachers continuously. It is hoped that it will be able to answer the educational problems facing the Indonesian nation. This research explores the opinions of elementary school teachers who have participated in teacher professional development activities through the in-service teacher professional education program. Methods We collected data through a written survey of 24 elementary school teachers, as well as article documents relevant to the research topic. Data were analyzed using thematic analysis. Result The research produced two main themes: increasing teacher competencies and sustainable teacher development programs. Increasing teacher competency related to social competence, pedagogical competence and professional competence. The sustainable teacher development program is related to the guaranteeing the instructional quality of post-program and multi-sectoral collaboration Conclusion Developing teacher professionalism through teacher professional education program in elementary schools in Indonesia positively impacts teachers’ becoming professional teachers. Teacher professional education program is an indication of improving teacher professionalism, especially in developing teaching skills, improving the quality of instruction, teacher motivation and individual development in dealing with various problems in instruction in the classroom, especially in elementary schools, so that the instructional objectives that have been set can be achieved. The professionalism of elementary school teachers will improve if there are sustainable programs such as mentoring programs from the government, universities and parties that focus on improving the quality of education in Indonesia
in F1000Research on 2024-11-18 11:03:07 UTC.
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Objective
Cerebral small vessel diseases (SVDs) are associated with cerebrovascular dysfunction, such as increased blood–brain barrier leakage (permeability surface area product), vascular pulsatility, and decreased cerebrovascular reactivity (CVR). No studies assessed all 3 functions concurrently. We assessed 3 key vascular functions in sporadic and genetic SVD to determine associations with SVD severity, subtype, and interrelations.
Methods
In this prospective, cross-sectional, multicenter INVESTIGATE-SVDs study, we acquired brain magnetic resonance imaging in patients with sporadic SVD/cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), including structural, quantitative microstructural, permeability surface area product, blood plasma volume fraction, vascular pulsatility, and CVR (in response to CO2) scans. We determined vascular function and white matter hyperintensity (WMH) associations, using covariate-adjusted linear regression; normal-appearing white matter and WMH differences, interrelationships between vascular functions, using linear mixed models; and major sources of variance using principal component analyses.
Results
We recruited 77 patients (45 sporadic/32 CADASIL) at 3 sites. In adjusted analyses, patients with worse WMH had lower CVR (B = −1.78, 95% CI −3.30, −0.27) and blood plasma volume fraction (B = −0.594, 95% CI −0.987, −0.202). CVR was worse in WMH than normal-appearing white matter (eg, CVR: B = −0.048, 95% CI −0.079, −0.017). Adjusting for WMH severity, SVD subtype had minimal influence on vascular function (eg, CVR in CADASIL vs sporadic: B = 0.0169, 95% CI −0.0247, 0.0584). Different vascular function mechanisms were not generally interrelated (eg, permeability surface area product~CVR: B = −0.85, 95% CI −4.72, 3.02). Principal component analyses identified WMH volume/quantitative microstructural metrics explained most variance in CADASIL and arterial pulsatility in sporadic SVD, but similar main variance sources.
Interpretation
Vascular function was worse with higher WMH, and in WMH than normal-appearing white matter. Sporadic SVD-CADASIL differences largely reflect disease severity. Limited vascular function interrelations may suggest disease stage-specific differences. ANN NEUROL 2024
in Annals of Neurology on 2024-11-18 10:08:47 UTC.
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Author(s): Nandhu Krishna Babu, M. Sreepadmanabh, Sayantan Dutta, and Tapomoy Bhattacharjee
Wound healing is a complex biological process critical for maintaining an organism's structural integrity and tissue repair following an infection or injury. Recent studies have unveiled the mechanisms involving the coordination of biochemical and mechanical responses in the tissue in wound healing.…
[Phys. Rev. E 110, 054411] Published Mon Nov 18, 2024
in Physical Review E: Biological physics on 2024-11-18 10:00:00 UTC.
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Author(s): D. A. Herrera-Martí
RNA viruses have high mutation rates due the the lack of error correction mechanisms, which may lead the viral population to a state of “error catastrophe” in which genetic information is lost. In this paper, the author exploits the analogy between the error catastrophe transition and the ferromagnetic-to-paramagnetic transition to shed light on the complex, rugged fitness landscapes of RNA interactions.
[Phys. Rev. E 110, 054412] Published Mon Nov 18, 2024
in Physical Review E: Biological physics on 2024-11-18 10:00:00 UTC.
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Objective
Mitochondrial dysfunction is one of the earliest pathological events observed in amyotrophic lateral sclerosis (ALS). The aim of this study is to evaluate the therapeutic efficacy of 2,4-dinitrophenol (DNP), a mild mitochondrial uncoupler, in an ALS mouse model to provide preclinical proof-of-concept evidence of using DNP as a potential therapeutic drug for ALS.
Methods
hSOD1G93A mice were treated with 0.5–1.0 mg/kg DNP through daily oral gavage from presymptomatic stage or disease onset until 18 weeks old. Longitudinal behavioral studies were performed weekly or biweekly from 6 to 18 weeks old. In situ muscle contraction measurements in extensor digitorum longus muscles were conducted to evaluate the preservation of contractile force and motor unit numbers in hSOD1G93A mice following DNP treatment. Muscle innervation and inflammatory markers were assessed using immunostaining. Extent of protein oxidation and activation of Akt pathway were also examined.
Results
DNP delayed disease onset; improved motor coordination and muscle performance in vivo; preserved muscle contractile function, neuromuscular junction morphology, and muscle innervation; and reduced inflammation and protein oxidation at 18 weeks old in hSOD1G93A mice. Strikingly, symptomatic hSOD1G93A mice exhibited a period of recovery in running ability at 20 cm/s several weeks after 2,4-dinitrophenol treatment started at disease onset, offering the first observation in disease phenotype reversal using a small molecule.
Interpretation
Our results strongly support that micro-dose DNP may be used as a potential novel treatment for ALS patients, with a possibility for recovery, when used at optimal doses and time of intervention. ANN NEUROL 2024
in Annals of Neurology on 2024-11-18 09:58:55 UTC.
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•The laminar organization of the monkey perirhinal and parahippocampal cortices supports the view that high-order association cortices are characterized by relatively large superficial layers, with larger neurons and a lower neuronal density.
•Species differences in the relative size and number of neurons in these areas indicate a greater relative development of the entorhinal cortex in the rat and of the perirhinal and parahippocampal cortices in primates.
ABSTRACT
The perirhinal and parahippocampal cortices are key components of the medial temporal lobe memory system. Despite their essential roles in mnemonic and perceptual functions, there is limited quantitative information regarding their structural characteristics. Here, we implemented design-based stereological techniques to provide estimates of neuron number, neuronal soma size, and volume of the different layers and subdivisions of the perirhinal and parahippocampal cortices in adult macaque monkeys (Macaca mulatta, 5–9 years of age). We found that areas 36r and 36c of the perirhinal cortex and areas TF and TH of the parahippocampal cortex exhibit relatively large superficial layers, which are characteristic of the laminar organization of higher order associational cortices. In contrast, area 35 of the perirhinal cortex exhibits relatively large deep layers. Although neuronal soma size varies between subdivisions and layers, neurons are generally larger in the perirhinal cortex than in the parahippocampal cortex and even larger in the entorhinal cortex. These morphological characteristics are consistent with the hierarchical organization of these cortices within the medial temporal lobe. Comparing data in rats, monkeys, and humans, we found species differences in the relative size of these structures, showing that the perirhinal and parahippocampal cortices have expanded in parallel to the cerebral cortex and may play a greater role in the integration of information in the neocortical–hippocampal loop in primates. Altogether, these normative data provide an essential reference to extrapolate findings from experimental studies in animals and create realistic models of the medial temporal lobe memory system.
in Journal of Comparative Neurology on 2024-11-18 07:40:27 UTC.
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Imperfect mimicry may be due to trade-offs between accuracy and vital biological function. Using microCT to compare the CNS of ant-mimicking jumping spiders (A), with a non-mimic (B), we found that mimics had relatively smaller CNS than non-mimics, supporting a trade-off function between mimic accuracy and neural anatomy.
ABSTRACT
In Batesian mimicry, mimetic traits are not always as convincing as predicted by theory—in fact, inaccurate mimicry with only a superficial model resemblance is common and taxonomically widespread. The “selection trade-offs hypothesis” proposes a life-history trade-off between accurate mimetic traits and one or more vital biological functions. Here, using an accurate myrmecomorphic (ant-mimicking) jumping spider species, Myrmarachne smaragdina, we investigate how myrmecomorphic modifications to the body shape impact the internal anatomy in a way that could be functionally limiting. Specifically, via x-ray micro-computed tomography (microCT), we quantify how the spider's constricted prosoma, which emulates the head and thorax of ants, impacts the size of the central nervous system (CNS) and the venom glands. Although, relative to their whole-body mass, we found no significant difference in venom gland volume, the CNS of the ant-mimicking jumping spider was significantly smaller when compared with a relatively closely related non-mimic jumping spider, indicating that some trade-off between mimic accuracy and size of neural anatomy, as articulated by the “selection trade-offs hypothesis,” is a possibility. Our explorative evidence enables and encourages broader investigation of how variable mimic accuracy impacts the neuroanatomy in ant mimics as a direct test of the “selection trade-offs hypothesis.”
in Journal of Comparative Neurology on 2024-11-18 07:39:47 UTC.
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Kato and Bruno show that, despite responding to sounds, rodent primary somatosensory cortex (S1) encodes neither the identity of pure auditory stimuli nor simultaneous auditory-tactile stimulus pairs. Moreover, this insensitivity to auditory and audio-tactile stimulus identity remains unchanged even following prolonged passive exposure to audio-tactile correlations and reward-reinforced behavioral training with audio-tactile stimuli.
in Neuron: In press on 2024-11-18 00:00:00 UTC.
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Wu et al. demonstrate how neutrophils, located within the protective layers of the brain, respond to social threats and modulate psychological processes. This process is governed by testosterone in a context-dependent manner and is executed by neutrophil-mediated meningeal immunity, which impedes threat-related neural activity via IFN-γ-GABAergic signaling axis.
in Neuron: In press on 2024-11-18 00:00:00 UTC.
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Peroxisome proliferator-activated receptor gamma (PPARγ) is a nuclear receptor transcription factor that regulates gene expression programs in response to ligand binding. Endogenous and synthetic ligands, including covalent antagonist inhibitors GW9662 and T0070907, are thought to compete for the orthosteric pocket in the ligand-binding domain (LBD). However, we previously showed that synthetic PPARγ ligands can cooperatively cobind with and reposition a bound endogenous orthosteric ligand to an alternate site, synergistically regulating PPARγ structure and function (Shang et al., 2018). Here, we reveal the structural mechanism of cobinding between a synthetic covalent antagonist inhibitor with other synthetic ligands. Biochemical and NMR data show that covalent inhibitors weaken—but do not prevent—the binding of other ligands via an allosteric mechanism, rather than direct ligand clashing, by shifting the LBD ensemble toward a transcriptionally repressive conformation, which structurally clashes with orthosteric ligand binding. Crystal structures reveal different cobinding mechanisms including alternate site binding to unexpectedly adopting an orthosteric binding mode by altering the covalent inhibitor binding pose. Our findings highlight the significant flexibility of the PPARγ orthosteric pocket, its ability to accommodate multiple ligands, and demonstrate that GW9662 and T0070907 should not be used as chemical tools to inhibit ligand binding to PPARγ.
in eLife on 2024-11-18 00:00:00 UTC.
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Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell class-specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger on hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.
in eLife on 2024-11-18 00:00:00 UTC.
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Dynamic interactions between large-scale brain networks underpin human cognitive processes, but their electrophysiological mechanisms remain elusive. The triple network model, encompassing the salience network (SN), default mode network (DMN), and frontoparietal network (FPN), provides a framework for understanding these interactions. We analyzed intracranial electroencephalography (EEG) recordings from 177 participants across four diverse episodic memory experiments, each involving encoding as well as recall phases. Phase transfer entropy analysis revealed consistently higher directed information flow from the anterior insula (AI), a key SN node, to both DMN and FPN nodes. This directed influence was significantly stronger during memory tasks compared to resting state, highlighting the AI’s task-specific role in coordinating large-scale network interactions. This pattern persisted across externally driven memory encoding and internally governed free recall. Control analyses using the inferior frontal gyrus (IFG) showed an inverse pattern, with DMN and FPN exerting higher influence on IFG, underscoring the AI’s unique role. We observed task-specific suppression of high-gamma power in the posterior cingulate cortex/precuneus node of the DMN during memory encoding, but not recall. Crucially, these results were replicated across all four experiments spanning verbal and spatial memory domains with high Bayes replication factors. Our findings advance understanding of how coordinated neural network interactions support memory processes, highlighting the AI’s critical role in orchestrating large-scale brain network dynamics during both memory encoding and retrieval. By elucidating the electrophysiological basis of triple network interactions in episodic memory, our study provides insights into neural circuit dynamics underlying memory function and offer a framework for investigating network disruptions in memory-related disorders.
in eLife on 2024-11-18 00:00:00 UTC.
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Significant technical challenges exist when measuring synaptic connections between neurons in living brain tissue. The patch clamping technique, when used to probe for synaptic connections, is manually laborious and time-consuming. To improve its efficiency, we pursued another approach: instead of retracting all patch clamping electrodes after each recording attempt, we cleaned just one of them and reused it to obtain another recording while maintaining the others. With one new patch clamp recording attempt, many new connections can be probed. By placing one pipette in front of the others in this way, one can ‘walk’ across the mouse brain slice, termed ‘patch-walking.’ We performed 136 patch clamp attempts for two pipettes, achieving 71 successful whole cell recordings (52.2%). Of these, we probed 29 pairs (i.e. 58 bidirectional probed connections) averaging 91 μm intersomatic distance, finding three connections. Patch-walking yields 80–92% more probed connections, for experiments with 10–100 cells than the traditional synaptic connection searching method.
in eLife on 2024-11-18 00:00:00 UTC.
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Many proteins have been recently shown to undergo a process of phase separation that leads to the formation of biomolecular condensates. Intriguingly, it has been observed that some of these proteins form dense droplets of sizeable dimensions already below the critical concentration, which is the concentration at which phase separation occurs. To understand this phenomenon, which is not readily compatible with classical nucleation theory, we investigated the properties of the droplet size distributions as a function of protein concentration. We found that these distributions can be described by a scale-invariant log-normal function with an average that increases progressively as the concentration approaches the critical concentration from below. The results of this scaling analysis suggest the existence of a universal behaviour independent of the sequences and structures of the proteins undergoing phase separation. While we refrain from proposing a theoretical model here, we suggest that any model of protein phase separation should predict the scaling exponents that we reported here from the fitting of experimental measurements of droplet size distributions. Furthermore, based on these observations, we show that it is possible to use the scale invariance to estimate the critical concentration for protein phase separation.
in eLife on 2024-11-18 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1153: Neuroticism Overestimated? Neuroticism Versus Hypertonia, Pain and Rehabilitation Outcomes in Post-Spinal Cord Injury Patients Rehabilitated Conventionally and with Robotic-Assisted Gait Training
Brain Sciences doi: 10.3390/brainsci14111153
Authors:
Alicja Widuch-Spodyniuk
Beata Tarnacka
Bogumił Korczyński
Aleksandra Borkowska
Background: The aim of the present study was to analyse the association between neuroticism (one of the Big Five personality traits) and the most common secondary sensorimotor complications occurring in patients after spinal cord injury (SCI), i.e., muscle spasticity (hypertonia) and pain, and to investigate the associations between neuroticism and the effects of conventional rehabilitation (dynamic parapodium) and those using robotic-assisted gait training (RAGT) in this group of patients. In addition, the association of neuroticism with self-efficacy, personal beliefs about pain control, and adopted coping strategies among SCI patients was analysed. These data can be used as a reference for designing effective forms of therapy and support dedicated to this group of patients. Methods and procedures: Quantitative analysis included 110 patients after SCI. The participants were divided by simple randomisation into a rehabilitation group with RAGT and a rehabilitation group with dynamic parapodium therapy (DPT). The following survey instruments were used for data collection: Revised NEO Personality Inventory (NEO-PI-R); Ashworth Scale; the Spinal Cord Independence Measure III (SCIM III); the Walking Index for Spinal Cord Injury II (WISCI-II); the American Spinal Injury Association Impairment Scale (AIS); the Pain Coping Strategies Questionnaire&mdash;CSQ; and the Beliefs about Pain Control Questionnaire&mdash;BPCQ. Outcomes and results: analyses showed a positive association between neuroticism and spastic tension (rho = 0.39; p &lt; 0.001). Conclusions and implications: the study showed that a high level of neuroticism correlates with a higher level of spasticity, but no such correlation was observed for pain. Additionally, the study did not show a significant correlation between neuroticism and rehabilitation outcome depending on the rehabilitation modality (RAGT vs. DPT). The results underline the importance of carrying out a psychological diagnosis of patients to provide therapeutic support in the rehabilitation process.
in Brain Sciences on 2024-11-18 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1152: The Influence of Music Reading on Spatial Working Memory and Self-Assessment Accuracy
Brain Sciences doi: 10.3390/brainsci14111152
Authors:
Michel A. Cara
Background/Objectives: Previous research has suggested that Western musicians, who generally demonstrate proficiency in reading musical scores, exhibit superior performance in visuospatial working memory tasks compared to non-musicians. Evidence indicates brain activation in regions such as the left inferior parietal lobe and the right posterior fusiform gyrus during music reading, which are associated with visuospatial processing. This study aimed to explore how musical training influences spatial working memory and to examine the relationship between self-assessment accuracy and cognitive performance. Methods: A visuospatial working memory test, the Corsi block-tapping test (CBT), was administered to 70 participants, including 35 musicians with experience in music reading and 35 non-musicians. CBT performances were compared between groups, controlling for sex and age differences using analysis of covariance. Participants were also asked to self-assess their visuospatial capabilities. Results: Musicians performed significantly better than non-musicians in the CBT and demonstrated greater metacognitive accuracy in evaluating their visuospatial memory capacities. A total of 46.34% of musicians who claimed good performance on the CBT did in fact perform well, in comparison with 14.63% of non-musicians. Sex influenced the outcomes of spatial working memory, while age did not significantly affect performance. Conclusions: This self-awareness of visuospatial capabilities reflects a form of metacompetence, encompassing reflective thinking and the ability to assess one&rsquo;s cognitive skills. Furthermore, while differences in spatial working memory between musicians and non-musicians appear to be related to executive functions associated with general music practice, further investigation is needed to explore other potential influences beyond musical experience.
in Brain Sciences on 2024-11-17 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1151: The Effectiveness of Motor Imagery in Balance and Functional Status of Older People with Early-Stage Dementia
Brain Sciences doi: 10.3390/brainsci14111151
Authors:
Anna Christakou
Christina Bouzineki
Marousa Pavlou
George Stranjalis
Vasiliki Sakellari
Background/Objectives: Dementia involves the loss of cognitive abilities and impairs functional abilities in daily life. In motor imagery (MI) techniques, motor acts are mentally rehearsed without any overt body movements. The purpose of the randomized controlled trial was to examine the effects of MI on the motor function of older adults with dementia. Methods: Overall, 160 participants (43 men, 117 women, MMSE M = 23.20, SD = 0.15) from an Athens Day Care Center of the Alzheimer Association were randomized to (a) the MI and exercise group (experimental group) (n = 55), (b) the only exercise group (1st control group) (n = 52) and (c) the neither MI nor exercise group (2nd control group) (n = 53). The exercise session comprised 24 physiotherapy exercise sessions, lasting 45 min each, twice a week for 12 weeks. The exercises were selected from the Otago Exercise Program. Three assessments were performed: (a) one week prior to the program, (b) at one and a half months and (c) after the program. The experimental group performed a 30-minute MI with exercise program content after the end of every physiotherapy exercise session. The Multidirectional Reach Test, Five Times Sit-to-Stand Test (FTSST), Timed Up and Go test (TUG), Functional Gait Assessment (FGA) and Berg Balance Scale (BBS) were used to assess participants&rsquo; balance and functional status. Results: In the intention to treat analysis (18 participants dropped out), the 3 &times; 3 repeated measures ANOVA indicated statistically significant results between the three groups on (a) the TUG (F = 3.06, df (2), p = 0.04), (b) the FTSST (F = 3.00, df (2), p = 0.05), (c) the forward direction test (F = 4.14 df (2), p = 0.02), the lateral right and the lateral left direction tests (F = 3.90, df (2), p = 0.02 and F = 7.87, df (2), p = 0.00, respectively), and (d) the FGA (F = 4.35, df (2), p = 0.01). The Friedman test showed significant statistical significant differences among the three groups for BBS (X2 = 7.62, df = 2, p = 0.22), and an effect size of partial &eta;2 coefficient for F-tests was found. Post hoc comparisons using a Bonferroni test for ANOVA and Wilcoxon test for Friedman indicated that the mean scores for the experimental group and the 1st control were significantly better than the 2rd control group in many dependent variables. Conclusions: The study showed a positive effect of MI on balance and the functional status of older adults with early stages of dementia with possible beneficial effects on maintaining independence and reducing physical decline.
in Brain Sciences on 2024-11-17 00:00:00 UTC.
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Objective
To identify biochemical changes in individuals at higher risk of developing amyotrophic lateral sclerosis (ALS) or frontotemporal dementia (FTD) via C9orf72 hexanucleotide repeat expansion (HRE) heterozygosity.
Methods
Cross-sectional observational study of 48 asymptomatic C9orf72 HRE carriers, 39 asymptomatic non-carrier controls, 19 people with sporadic ALS, 10 with C9orf72 ALS, 14 with sporadic FTD, and 10 with C9orf72 FTD. Relative abundance of 30 pre-defined cerebrospinal fluid biomarkers of ALS and FTD were compared in asymptomatic C9orf72 HRE carriers and age-matched non-carrier controls. Differential abundance of these proteins was quantified using data independent acquisition mass spectrometry or electro chemiluminescent assay for neurofilament light chain. Unbiased analysis of the entire cerebrospinal fluid proteome was then carried out.
Results
Ubiquitin carboxyl-hydrolase isozyme L1 levels were higher in asymptomatic C9orf72 HRE carriers compared with age-matched non-carriers (log2fold change 0.20, FDR-adjusted p-value = 0.034), whereas neurofilament light chain levels did not significantly differ. Ubiquitin carboxyl-hydrolase isozyme L1 levels remained elevated after matching of groups by neurofilament levels (p = 0.011), and after adjusting for age, sex, and neurofilament levels. A significant difference was also observed when restricting analysis to younger participants (<37) matched by neurofilament level (p = 0.007).
Interpretation
Elevated cerebrospinal fluid ubiquitin carboxyl-hydrolase isozyme L1 levels in C9orf72 HRE carriers can occur in the absence of increased neurofilament levels, potentially reflecting either compensatory or pathogenic mechanisms preceding rapid neuronal loss. This brings forward the window on changes associated with the C9orf72 HRE carrier state, with potential to inform understanding of penetrance and approaches to prevention. ANN NEUROL 2024
in Annals of Neurology on 2024-11-16 10:44:48 UTC.
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Parkinson patients with mild cognitive impairment do not only show established motor (e.g., tremor and rigor) and nonmotor (e.g., depression and global cognitive impairment) symptoms. They also show deficits in some basic numerical functions: (non-) symbolic magnitude comparison and number line estimation In contrast, auditory and written transcoding skills were preserved.
ABSTRACT
Neurodegenerative diseases such as Parkinson's disease (PD) have a huge impact on patients, caregivers, and the health care system. Until now, diagnosis of mild cognitive impairments in PD has been established based on domain-general functions such as executive functions, attention, or working memory. However, specific numerical deficits observed in clinical practice have not yet been systematically investigated. PD-immanent deterioration of domain-general functions and domain-specific numerical areas suggests mechanisms of both primary and secondary dyscalculia. The current study systematically investigated basic number processing performance in PD patients for the first time, targeting domain-specific cognitive representations of numerosity and the influence of domain-general factors. The overall sample consisted of patients with a diagnosis of PD, according to consensus guidelines, and healthy controls. PD patients were stratified into patients with normal cognition (PD-NC) or mild cognitive impairment (level I-PD-MCI based on cognitive screening). Basic number processing was assessed using transcoding, number line estimation, and (non-) symbolic number magnitude comparison tasks. Discriminant analysis was employed to assess whether basic number processing tasks can differentiate between a healthy control group and both PD groups. All participants were subjected to a comprehensive numerical and a neuropsychological test battery, as well as sociodemographic and clinical measures. Results indicate a profile of preserved (verbal representation) and impaired (magnitude representation, place × value activation) function in PD-MCI, hinting at basal ganglia dysfunction affecting numerical cognition in PD. Numerical deficits could not be explained by domain-general cognitive impairments, so that future research needs to incorporate domain-specific tasks of sufficient difficulty.
in Journal of Neuroscience Research on 2024-11-16 08:04:23 UTC.
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in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
Psychiatric disorders are multifactorial conditions without clear biomarkers, influenced by genetic, environmental, and developmental factors. Understanding these disorders requires identifying specific endophenotypes that help break down their complexity. Here, we undertake an in-depth analysis of one such endophenotype, namely imbalanced approach-avoidance conflict (AAC), reviewing its significant dependency on the hippocampus. Imbalanced AAC is a transdiagnostic endophenotype, being a feature of many psychiatric conditions in humans. However, it is predominantly examined in preclinical research through paradigms that subject rodents to conflict-laden scenarios. This review offers an original perspective by discussing the AAC through three distinct lights: optogenetic modulation of the AAC, which updates our understanding of the hippocampal contribution to behavioral inhibition; the impact of environmental stress, which exacerbates conflict and strengthens the stress-psychopathology axis; and inherent epigenetic aspects, which uncover crucial molecular underpinnings of environmental (mal) adaptation. By integrating these perspectives, in this review we aim to underline a cross-species causal nexus between heightened hippocampal activity and avoidance behavior. In addition, we suggest a rationale to explore epigenetic pharmacology as a potential strategy to tackle AAC-related psychopathology. This review assumes greater significance when viewed through the lens of advancing AAC-centric diagnostics in human subjects. Unlike traditional questionnaires, which struggle to accurately measure individual differences in AAC-related dimensions, new approaches using virtual reality and computer games show promise in better focusing the magnitude of AAC contribution to psychopathology.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
The discovery of adult-born granule cells (aDGCs) in the dentate gyrus of the hippocampus has raised questions regarding how they develop, incorporate into the hippocampal circuitry, and contribute to learning and memory. Here, we used patch-clamp electrophysiology to investigate the intrinsic and synaptic excitability of mouse aDGCs as they matured, enabled by using a tamoxifen-induced genetic label to birth date the aDGCs at different animal ages. Importantly, we also undertook immunofluorescence studies of the expression of the immediate early gene Egr1 and compared these findings with the electrophysiology data in the same animals. We examined two groups of animals, with aDGC birthdating when the mice were 2 months and at 7–9 months of age. In both groups, cells 4 weeks old had lower thresholds for current-evoked action potentials than older cells but fired fewer spikes during long current pulses and responded more poorly to synaptic activation. aDGCs born in both 2 and 7–9-month-old mice matured in their intrinsic excitability and synaptic properties from 4–12 weeks postgenesis, but this occurred more slowly for the older age animals. Interestingly, this pattern of intrinsic excitability changes did not correlate with the pattern of Egr1 expression. Instead, the development of Egr1 expression was correlated with the frequency of spontaneous excitatory postsynaptic currents. These results suggest that in order for aDGCs to fully participate in hippocampal circuitry, as indicated by Egr1 expression, they must have developed enough synaptic input, in spite of the greater input resistance and reduced firing threshold that characterizes young aDGCs.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
Extensive research has been focused in the past century on structural, physiological, and molecular attributes of the hippocampus. This interest was created by the unique involvement of the hippocampus in cognitive and affective functions of the brain. Functional analysis revealed that the hippocampus has divergent properties along its axial dimension to the extent that the dorsal sector (dorsal hippocampus, DH) has different connections with the rest of the brain than those of the ventral sector (VH). Still, longitudinal pathways connect the DH with the VH and dampen the functional differences between the sectors. To be able to identify the intrinsic functional difference between the DH and VH, we produced dissociated monolayer cultures from prenatal DH and VH and examined their properties at 10–20 days after plating by imaging the spontaneous activity of the network using Fluo-2 AM, a calcium indicator. Surprisingly, while DH and VH sectors produced dissociated cultures with similar morphological attributes, VH cultures were more active spontaneously than DH cultures. Furthermore, when stimulated to produce action potentials, VH neurons triggered network bursts in postsynaptic neurons more often than DH cultures. Finally, in both DH and VH cultures, electrical stimulation of single cells produced network bursts in response to a burst of action potentials rather than to single spikes. These experiments indicate that even in dissociated cultures, neurons of the VH are more excitable and sensitive to electrical stimulation than DH; hence, they are more likely to generate network bursts and epileptic seizures, as suggested for in vivo brains.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
Topographical projection patterns from the entorhinal cortex to area CA1 of the hippocampus have led to a hypothesis that proximal CA1 (pCA1, closer to CA2) is spatially more selective than distal CA1 (dCA1, closer to the subiculum). While earlier studies have shown evidence supporting this hypothesis, we recently showed that this difference does not hold true under all experimental conditions. In a complex environment with distinct local texture cues on a circular track and global visual cues, pCA1 and dCA1 display comparable spatial selectivity. Correlated with the spatial selectivity differences, the earlier studies also showed differences in theta phase coding dynamics between pCA1 and dCA1 neurons. Here we show that there are no differences in theta phase coding dynamics between neurons in these two regions under the experimental conditions where pCA1 and dCA1 neurons are equally spatially selective. These findings challenge the established notion of dCA1 being inherently less spatially selective and theta modulated than pCA1 and suggest further experiments to understand theta-mediated activation of the CA1 sub-networks to represent space.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
The hippocampus (HC) is recognized for its pivotal role in memory-related plasticity and facilitating adaptive behavioral responses to reward shifts. However, the nature of its involvement in the response to reward downshifts remains to be determined. To bridge this knowledge gap, we explored the HC's function through a series of experiments in various tasks involving reward downshifts and using several neural manipulations in rats. In Experiment 1, complete excitotoxic lesions of the HC impaired choice performance in a modified T-maze after reducing the quantity of sugar pellet rewards. In Experiment 2, chemogenetic inhibition of the dorsal HC (dHC) disrupted anticipatory behavior following a food-pellet reward reduction. Experiments 3–5 impaired HC function by using peripheral lipopolysaccharide (LPS) administration. This treatment, which induces peripheral inflammation affecting HC function, significantly increased cytokine levels in the dHC (Experiment 3) and impaired anticipatory choice behavior (Experiment 4). None of these dorsal hippocampal manipulations affected consummatory responses in animals experiencing sucrose downshifts. Accordingly, we found no evidence of increased neural activation in either the dorsal or ventral HC, as measured by c-Fos expression, after a sucrose downshift task involving consummatory suppression (Experiment 6). The results highlight the HC's pivotal role in adaptively modulating anticipatory behavior in response to a variety of situations involving frustrative nonreward, while having no effect on adjustments on consummatory behavior. The data supporting this conclusion were obtained under heterogeneous experimental conditions derived from a multi-laboratory collaboration, ensuring the robustness and high reproducibility of our findings. Spatial orientation, memory update, choice of reward signals of different values, and anticipatory versus consummatory adjustments to reward downshift are discussed as potential mechanisms that could account for the specific effects observed from HC manipulations.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
The hippocampus is important for social behavior and exhibits unusual structural plasticity in the form of continued production of new granule neurons throughout adulthood, but it is unclear how adult neurogenesis contributes to social interactions. In the present study, we suppressed neurogenesis using a pharmacogenetic mouse model and examined social investigation and aggression in adult male mice to investigate the role of hippocampal adult-born neurons in the expression of aggressive behavior. In simultaneous choice tests with stimulus mice placed in corrals, mice with complete suppression of adult neurogenesis in adulthood (TK mice) exhibited normal social investigation behaviors, indicating that new neurons are not required for social interest, social memory, or detection of and response to social olfactory signals. However, mice with suppressed neurogenesis displayed decreased offensive and defensive aggression in a resident-intruder paradigm, and less resistance in a social dominance test, relative to neurogenesis-intact controls, when paired with weight and strain-matched (CD-1) mice. During aggression tests, TK mice were frequently attacked by the CD-1 intruder mice, which never occurred with WTs, and normal CD-1 male mice investigated TK mice less than controls when corralled in the social investigation test. Importantly, TK mice showed normal aggression toward prey (crickets) and smaller, nonaggressive (olfactory bulbectomized) C57BL/6J intruders, suggesting that mice lacking adult neurogenesis do not avoid aggressive social interactions if they are much larger than their opponent and will clearly win. Taken together, our findings show that adult hippocampal neurogenesis plays an important role in the instigation of intermale aggression, possibly by weighting a cost–benefit analysis against confrontation in cases where the outcome of the fight is not clear.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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ABSTRACT
The supramammillary nucleus (SuM) in the hypothalamus, in conjunction with the hippocampus (HPC), has been implicated through theta oscillations in various brain functions ranging from locomotion to learning and memory. While the indispensable role of the SuM in HPC theta generation in anesthetized animals is well-characterized, the SuM is not always necessary for HPC theta in awake animals. This raises questions on the precise behavioral relevance of SuM theta activity and its interaction with HPC theta activity. We used simultaneously recorded SuM and HPC local field potentials (LFPs) in a one-day water maze (WM) learning paradigm in rats (n = 8), to show that theta activities recorded from the SuM itself were not positively correlated with locomotor (swimming) speed nor acceleration, but the individual relationship between acceleration and SuM theta frequency is correlated with WM learning rates. In contrast, we found that SuM-HPC theta phase coherence is strongly correlated with swimming speed and acceleration, but these do not relate to WM learning. SuM-HPC-directed coherence analysis demonstrated no swimming kinetics nor learning rate associations, but revealed that periods of high SuM-HPC theta phase coherence are driven by the SuM at relatively low (~6.2 Hz) frequencies. Additionally, we demonstrate that the SuM and the HPC also engage in non-random, non-coherent phase coupling modes where either structure preferentially displays a ± 2 Hz difference with the other. Our data indicate SuM theta LFPs do not appear to be related to either speed coding or spatial learning in swimming rats and display non-random out-of-phase theta frequency coupling with the HPC.
in Hippocampus on 2024-11-16 04:40:25 UTC.
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Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2024-11-16 02:23:01 UTC.
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Brain Sciences, Vol. 14, Pages 1150: Effects of Sarcosine (N-methylglycine) on NMDA (N-methyl-D-aspartate) Receptor Hypofunction Induced by MK801: In Vivo Calcium Imaging in the CA1 Region of the Dorsal Hippocampus
Brain Sciences doi: 10.3390/brainsci14111150
Authors:
Yi-Tse Hsiao
Ching-Yuan Chang
Ting-Yen Lee
Wan-Ting Liao
Wen-Sung Lai
Fang-Chia Chang
Background: Hypofunction of the glutamate system in the brain is one of the pathophysiological hypotheses for schizophrenia. Accumulating animal and clinical studies show that sarcosine (N-methylglycine), a glycine transporter-1 inhibitor, is effective in ameliorating the negative and cognitive symptoms of schizophrenia. The aims of the present study were to observe the effects of sarcosine on neuronal activity in the dorsal CA1 (dCA1) hippocampal neurons within an NMDA receptor hypofunction model induced by MK801. Methods: We applied in vivo calcium imaging to observe the dynamics of fluorescence from the dCA1 hippocampal neurons when the mice were exploring in an open field. Using this tool, we directly measured and compared neuronal properties between sarcosine-treated and untreated mice. At the same time, the physiological function of the neurons was also quantified by measuring their place fields. Results: Our data demonstrated that MK-801 (0.2 mg/kg) diminished the fluorescence intensity of dCA1 neurons that had been genetically modified with a calcium indicator. MK-801 also significantly increased the correlation coefficient between the fluorescence dynamics of pairs of cells, a feature that may be linked to the symptom of disorganization in human patients with schizophrenia. The spatial correlations of place fields in the mice were impaired by MK-801 as well. Injected sarcosine (500 mg or 1000 mg/kg) significantly alleviated the abovementioned abnormalities. Conclusions: Our data provide evidence to support the use of sarcosine to alleviate symptoms of schizophrenia, especially hippocampus-related functions.
in Brain Sciences on 2024-11-16 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1149: Sensitivity of Spiking Neural Networks Due to Input Perturbation
Brain Sciences doi: 10.3390/brainsci14111149
Authors:
Haoran Zhu
Xiaoqin Zeng
Yang Zou
Jinfeng Zhou
Background: To investigate the behavior of spiking neural networks (SNNs), the sensitivity of input perturbation serves as an effective metric for assessing the influence on the network output. However, existing methods fall short in evaluating the sensitivity of SNNs featuring biologically plausible leaky integrate-and-fire (LIF) neurons due to the intricate neuronal dynamics during the feedforward process. Methods: This paper first defines the sensitivity of a temporal-coded spiking neuron (SN) as the deviation between the perturbed and unperturbed output under a given input perturbation with respect to overall inputs. Then, the sensitivity algorithm of an entire SNN is derived iteratively from the sensitivity of each individual neuron. Instead of using the actual firing time, the desired firing time is employed to derive a more precise analytical expression of the sensitivity. Moreover, the expectation of the membrane potential difference is utilized to quantify the magnitude of the input deviation. Results/Conclusions: The theoretical results achieved with the proposed algorithm are in reasonable agreement with the simulation results obtained with extensive input data. The sensitivity also varies monotonically with changes in other parameters, except for the number of time steps, providing valuable insights for choosing appropriate values to construct the network. Nevertheless, the sensitivity exhibits a piecewise decreasing tendency with respect to the number of time steps, with the length and starting point of each piece contingent upon the specific parameter values of the neuron.
in Brain Sciences on 2024-11-16 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1148: Visual Cortical Function Changes After Perceptual Learning with Dichoptic Attention Tasks in Adults with Amblyopia: A Case Study Evaluated Using fMRI
Brain Sciences doi: 10.3390/brainsci14111148
Authors:
Chuan Hou
Zhangziyi Zhou
Ismet Joan Uner
Spero C. Nicholas
Background: Amblyopia is a neurodevelopmental disorder of vision, commonly caused by strabismus or anisometropia during early childhood. While studies demonstrated that perceptual learning improves visual acuity and stereopsis in adults with amblyopia, accompanying changes in visual cortical function remain unclear. Methods: We measured functional magnetic resonance imaging (fMRI) responses before and after perceptual learning in seven adults with amblyopia. Our learning tasks involved dichoptic high-attention-demand tasks that avoided V1 function-related tasks and required high-level cortical functions (e.g., intraparietal sulcus) to train the amblyopic eye. Results: Perceptual learning induced low-level visual cortical function changes, which were strongly associated with the etiology of amblyopia and visual function improvements. Anisometropic amblyopes showed functional improvements across all regions of interest (ROIs: V1, V2, V3, V3A, and hV4), along with improvements in visual acuity and stereoacuity. In contrast, strabismic amblyopes showed robust improvements in visual cortical functions only in individuals who experienced significant gains in visual acuity and stereoacuity. Notably, improvements in V1 functions were significantly correlated with the magnitude of visual acuity and stereoacuity improvements when combining both anisometropic and strabismic amblyopes. Conclusions: Our findings provide evidence that learning occurs in both high-level and low-level cortical processes. Our study suggests that early intervention to correct eye alignment (e.g., strabismus surgery) is critical for restoring both visual and cortical functions in strabismic amblyopia.
in Brain Sciences on 2024-11-16 00:00:00 UTC.
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by Fabian Santiago, Amandeep Kaur, Shannon Bride, Dougald Monroe, Karin Leiderman, Suzanne Sindi
Blood coagulation is a vital physiological process involving a complex network of biochemical reactions, which converge to form a blood clot that repairs vascular injury. This process unfolds in three phases: initiation, amplification, and propagation, ultimately leading to thrombin formation. Coagulation begins when tissue factor (TF) is exposed on an injured vessel’s wall. The first step is when activated factor VII (VIIa) in the plasma binds to TF, forming complex TF:VIIa, which activates factor X. Activated factor X (Xa) is necessary for coagulation, so the regulation of its activation is crucial. Tissue Factor Pathway Inhibitor (TFPI) is a critical regulator of the initiation phase as it inhibits the activation of factor X. While previous studies have proposed two pathways—direct and indirect binding—for TFPI’s inhibitory role, the specific biochemical reactions and their rates remain ambiguous. Many existing mathematical models only assume an indirect pathway, which may be less effective under physiological flow conditions. In this study, we revisit datasets from two experiments focused on activated factor X formation in the presence of TFPI. We employ an adaptive Metropolis method for parameter estimation to reinvestigate a previously proposed biochemical scheme and corresponding rates for both inhibition pathways. Our findings show that both pathways are essential to replicate the static experimental results. Previous studies have suggested that flow itself makes a significant contribution to the inhibition of factor X activation. We added flow to this model with our estimated parameters to determine the contribution of the two inhibition pathways under these conditions. We found that direct binding of TFPI is necessary for inhibition under flow. The indirect pathway has a weaker inhibitory effect due to removal of solution phase inhibitory complexes by flow.
in PLoS Computational Biology on 2024-11-15 14:00:00 UTC.
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by Rachel A. Harrison
After dispersal, what cues trigger social learning in immigrants? A new study in wild-caught great tits in PLOS Biology suggests that changes in the physical environment, rather than the social environment, are key in prompting social learning by immigrants.
After dispersal, what cues trigger social learning in immigrants? This Primer explores a new PLOS Biology study in wild-caught great tits which suggests that changes in the physical environment, rather than the social environment, are key in prompting social learning by immigrants.
in PLoS Biology on 2024-11-15 14:00:00 UTC.
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by Aidan Foo, Laura E. Brettell, Holly L. Nichols, 2022 UW-Madison Capstone in Microbiology Students , Miguel Medina Muñoz, Jessica A. Lysne, Vishaal Dhokiya, Ananya F. Hoque, Doug E. Brackney, Eric P. Caragata, Michael L. Hutchinson, Marcelo Jacobs-Lorena, David J. Lampe, Edwige Martin, Claire Valiente Moro, Michael Povelones, Sarah M. Short, Blaire Steven, Jiannong Xu, Timothy D. Paustian, Michelle R. Rondon, Grant L. Hughes, Kerri L. Coon, Eva Heinz
Mosquitoes transmit medically important human pathogens, including viruses like dengue virus and parasites such as Plasmodium spp., the causative agent of malaria. Mosquito microbiomes are critically important for the ability of mosquitoes to transmit disease-causing agents. However, while large collections of bacterial isolates and genomic data exist for vertebrate microbiomes, the vast majority of work in mosquitoes to date is based on 16S rRNA gene amplicon data that provides limited taxonomic resolution and no functional information. To address this gap and facilitate future studies using experimental microbiome manipulations, we generated a bacterial Mosquito-Associated Isolate Collection (MosAIC) consisting of 392 bacterial isolates with extensive metadata and high-quality draft genome assemblies that are publicly available, both isolates and sequence data, for use by the scientific community. MosAIC encompasses 142 species spanning 29 bacterial families, with members of the Enterobacteriaceae comprising 40% of the collection. Phylogenomic analysis of 3 genera, Enterobacter, Serratia, and Elizabethkingia, reveal lineages of mosquito-associated bacteria isolated from different mosquito species in multiple laboratories. Investigation into species’ pangenomes further reveals clusters of genes specific to these lineages, which are of interest for future work to test for functions connected to mosquito host association. Altogether, we describe the generation of a physical collection of mosquito-associated bacterial isolates, their genomic data, and analyses of selected groups in context of genome data from closely related isolates, providing a unique, highly valuable resource for research on bacterial colonisation and adaptation within mosquito hosts. Future efforts will expand the collection to include broader geographic and host species representation, especially from individuals collected from field populations, as well as other mosquito-associated microbes, including fungi, archaea, and protozoa.
in PLoS Biology on 2024-11-15 14:00:00 UTC.
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Background/Objective Weight stigma has significant psychological and social implications, yet studies on perspective-taking as an intervention strategy remain scarce. This study aimed to investigate the effect of perspective-taking on weight stigma among Chinese university students and examine the potential mediating role of common ingroup identity. Methods A randomized controlled experiment with 202 Chinese university students (experimental group, perspective-taking group: n = 102; control group: n = 100) was conducted. Weight stigma was measured pre- and post-intervention using the Anti-Fat Attitudes Test. The study employed a 2 × 2 mixed design with ANCOVA and mediation analysis. Results The experimental group showed significantly lower post-test weight stigma when controlling for pre-test scores (F(1, 199) = 25.69, p < .001). Perspective-taking engagement was significantly higher in the experimental group (t = 3.13, p = .002). Common ingroup identity negatively correlated with post-test weight stigma (r = -.28, p < .001) but did not significantly mediate the perspective-taking and weight stigma reduction relationship. Conclusion Perspective-taking effectively reduces weight stigma among Chinese university students, contributing to stigma reduction strategies in university settings. Further research on underlying mechanisms is warranted.
in F1000Research on 2024-11-15 10:24:37 UTC.
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Background This paper examines the impact of financial inclusion on bank stability within Ethiopian context, using panel data from 17 commercial banks over the period 2015-2023. Given the scarcity of research focused on the relationship between financial inclusion and bank stability in Ethiopia, this paper seeks to address a crucial gap by analyzing both conventional and digital aspects of financial inclusion in relation with bank stability. Methods A two-stage principal component analysis (PCA) was conducted to construct a composite financial inclusion index, integrating 10 conventional and 5 digital indicators. The study applied a two-step robust system generalized method of moments (GMM) to examine the effects of financial inclusion on bank stability, complemented by Granger causality testing to examine the directionality of this relationship. Results The result reveals a significant positive effect of financial inclusion on bank stability and Granger causality tests confirms a bi-directional relationship between financial inclusion and stability, indicating that improvements in financial inclusion foster greater stability and vice versa. Our results also highlight that while bank efficiency and GDP growth rate positively effect stability, total assets and income diversification exhibit detrimental effects. Conclusions It is essential to capitalize policy synergies to promote bank stability and to enhance financial inclusion through conventional and digital channels, while carefully managing the implications of risks associated with income diversification and asset distribution. Ensuring inclusive financial system is vital for maintaining bank stability, thus positioning it as a key priority for financial institutions.
in F1000Research on 2024-11-15 10:21:26 UTC.
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Background Forensic age estimation is not difficult when the body is found in good condition, but in cases of severe decomposition or damage, such as burnt or separated body parts, then the analysis can only be done with bones and teeth. There has been abundant research and development in the field of related biochemistry over the years. Various molecular changes occur in hard tissues and long-lived proteins, such as those in bones and teeth during the physiological process of aging. Aspartic acid racemization and DNA methylation are still the most frequently used age estimation methods because of their advantages in accuracy. Method This study aimed to compare the accuracy of DNA methylation and aspartic acid racemization methods for age estimation. Journal articles were searched in the electronic databases PubMed, Scopus, and Semantic Scholar of 2017-2022 according to PRISMA guidelines. Result Twelve journal articles were eligible for review. The DNA methylation method is quite simple to use because of commercially available methylation kits. Furthermore, the results can be obtained relatively quickly without requiring many samples, and the method is less sensitive to thermal and other damage than the aspartic acid racemization method. Conclusion The aspartic acid racemization method for age estimation has high accuracy, especially in determining age at death. However, temperature and the condition of the teeth affect the racemization of aspartic acid. Given that DNA methylation is generally stable in a wide range of temperatures, it provides a better approach to determining the chronological age even from charred remains.
in F1000Research on 2024-11-15 10:18:56 UTC.
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Elizabethkingia meningoseptica is an uncommon nosocomial pathogen that causes meningitis, pneumonia, and sepsis in neonates and in immunocompromised individuals. It exhibits resistance to many commonly employed first-line antibiotics used to treat gram-negative pathogens. Herein, we present three cases of late-onset sepsis with multi-drug resistant (MDR) Elizabethkingia meningoseptica in high-risk neonates. Case 1 was a one-day-old preterm low-birth-weight infant who presented with respiratory distress syndrome and septic shock. The patient was intubated and administered empirical broad-spectrum antibiotics and antifungal agents. Blood culture grew Candida krusei, hence Amphotericin B was initiated. Repeat blood culture on day 27 showed gram-negative bacilli, identified as Elizabethkingia meningoseptica by MALDI-TOF . Antibiotic susceptibility testing (AST) revealed resistance to Piperacillin/Tazobactam, but sensitivity to Vancomycin, Levofloxacin, and Minocycline. IV Vancomycin was administered, which resulted in clinical improvement and negative blood culture results. Case 2 was an eleven-day-old preterm, low-birth-weight baby who presented with fever. Initial investigations revealed normal complete blood counts (CBC) parameters and elevated CRP levels. Blood and CSF cultures isolated Elizabethkingia meningoseptica with a similar AST pattern. Intravenous Ciprofloxacin was initiated with clinical improvement and negative follow-up blood cultures. Case 3 was a one-day-old preterm baby, appropriate-to-gestational age, presenting with respiratory distress syndrome. The infant was intubated and started on inotropic support and intravenous antibiotics. Blood cultures on day 4 showed Elizabethkingia meningoseptica and Vancomycin was started. Follow-up cultures on days 6 and 14 grew Acinetobacter baumannii. A combination of Levofloxacin and Colistin was added, and blood cultures were negative after seven days, with clinical improvement. Elizabethkingia meningoseptica is a significant cause of hospital-acquired infections, especially in Neonatal Intensive Care Unit (NICU), leading to outbreaks. Clinicians must have a high degree of suspicion of E. meningoseptica for gram-negative bacilli causing sepsis and meningitis in high-risk patients. Recent technological advances have enabled accurate speciation to guide therapy and reduce morbidity and mortality rates.
in F1000Research on 2024-11-15 10:16:51 UTC.
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Science, Volume 386, Issue 6723, November 2024.
in Science on 2024-11-15 08:00:00 UTC.
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Science, Volume 386, Issue 6723, November 2024.
in Science on 2024-11-15 08:00:00 UTC.
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Science, Volume 386, Issue 6723, November 2024.
in Science on 2024-11-15 08:00:00 UTC.
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Science, Volume 386, Issue 6723, November 2024.
in Science on 2024-11-15 08:00:00 UTC.
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Science, Volume 386, Issue 6723, November 2024.
in Science on 2024-11-15 08:00:00 UTC.
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Science Advances, Volume 10, Issue 46, November 2024.
in Science Advances on 2024-11-15 08:00:00 UTC.
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Science Advances, Volume 10, Issue 46, November 2024.
in Science Advances on 2024-11-15 08:00:00 UTC.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
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Science Advances, Volume 10, Issue 46, November 2024.
in Science Advances on 2024-11-15 08:00:00 UTC.
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in Journal of Comparative Neurology on 2024-11-15 07:42:57 UTC.
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Objective
Hippocampal sclerosis (HS), the most common pathology associated with temporal lobe epilepsy (TLE), is not always visible on magnetic resonance imaging (MRI), causing surgical delays and reduced postsurgical seizure-freedom. We developed an open-source software to characterize and localize HS to aid the presurgical evaluation of children and adults with suspected TLE.
Methods
We included a multicenter cohort of 365 participants (154 HS; 90 disease controls; 121 healthy controls). HippUnfold was used to extract morphological surface-based features and volumes of the hippocampus from T1-weighted MRI scans. We characterized pathological hippocampi in patients by comparing them to normative growth charts and analyzing within-subject feature asymmetries. Feature asymmetry scores were used to train a logistic regression classifier to detect and lateralize HS. The classifier was validated on an independent multicenter cohort of 275 patients with HS and 161 healthy and disease controls.
Results
HS was characterized by decreased volume, thickness, and gyrification alongside increased mean and intrinsic curvature. The classifier detected 90.1% of unilateral HS patients and lateralized lesions in 97.4%. In patients with MRI-negative histopathologically-confirmed HS, the classifier detected 79.2% (19/24) and lateralized 91.7% (22/24). The model achieved similar performances on the independent cohort, demonstrating its ability to generalize to new data. Individual patient reports contextualize a patient's hippocampal features in relation to normative growth trajectories, visualise feature asymmetries, and report classifier predictions.
Interpretation
Automated and Interpretable Detection of Hippocampal Sclerosis (AID-HS) is an open-source pipeline for detecting and lateralizing HS and outputting clinically-relevant reports. ANN NEUROL 2024
in Annals of Neurology on 2024-11-15 06:14:52 UTC.
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Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.
in eLife on 2024-11-15 00:00:00 UTC.
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Systems consolidation theories propose two mechanisms that enable the behavioral integration of related memories: coordinated reactivation between hippocampus and cortex, and the emergence of cortical traces that reflect overlap across memories. However, there is limited empirical evidence that links these mechanisms to the emergence of behavioral integration over time. In two experiments, participants implicitly encoded sequences of objects with overlapping structure. Assessment of behavioral integration showed that response times during a recognition task reflected behavioral priming between objects that never occurred together in time but belonged to overlapping sequences. This priming was consolidation-dependent and only emerged for sequences learned 24 hr prior to the test. Critically, behavioral integration was related to changes in neural pattern similarity in the medial prefrontal cortex and increases in post-learning rest connectivity between the posterior hippocampus and lateral occipital cortex. These findings suggest that memories with a shared predictive structure become behaviorally integrated through a consolidation-related restructuring of the learned sequences, providing insight into the relationship between different consolidation mechanisms that support behavioral integration.
in eLife on 2024-11-15 00:00:00 UTC.
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Astrocytes derive from different lineages and play a critical role in neuropathic pain after spinal cord injury (SCI). Whether selectively eliminating these main origins of astrocytes in lumbar enlargement could attenuate SCI-induced neuropathic pain remains unclear. Through transgenic mice injected with an adeno-associated virus vector and diphtheria toxin, astrocytes in lumbar enlargement were lineage traced, targeted, and selectively eliminated. Pain-related behaviors were measured with an electronic von Frey apparatus and a cold/hot plate after SCI. RNA sequencing, bioinformatics analysis, molecular experiment, and immunohistochemistry were used to explore the potential mechanisms after astrocyte elimination. Lineage tracing revealed that the resident astrocytes but not ependymal cells were the main origins of astrocytes-induced neuropathic pain. SCI-induced mice to obtain significant pain symptoms and astrocyte activation in lumbar enlargement. Selective resident astrocyte elimination in lumbar enlargement could attenuate neuropathic pain and activate microglia. Interestingly, the type I interferons (IFNs) signal was significantly activated after astrocytes elimination, and the most activated Gene Ontology terms and pathways were associated with the type I IFNs signal which was mainly activated in microglia and further verified in vitro and in vivo. Furthermore, different concentrations of interferon and Stimulator of interferon genes (STING) agonist could activate the type I IFNs signal in microglia. These results elucidate that selectively eliminating resident astrocytes attenuated neuropathic pain associated with type I IFNs signal activation in microglia. Targeting type I IFNs signals is proven to be an effective strategy for neuropathic pain treatment after SCI.
in eLife on 2024-11-15 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1147: The Impact of Probiotics on Clinical Symptoms and Peripheral Cytokines Levels in Parkinson’s Disease: Preliminary In Vivo Data
Brain Sciences doi: 10.3390/brainsci14111147
Authors:
Luca Magistrelli
Elena Contaldi
Annalisa Visciglia
Giovanni Deusebio
Marco Pane
Angela Amoruso
Introduction. Previous studies have shown that probiotics have positive effects on both motor and non-motor symptoms in Parkinson&rsquo;s disease (PD). Additionally, in preclinical settings, probiotics have demonstrated the ability to counteract neuronal loss and alpha-synuclein aggregation, important pathological hallmarks of PD. Notably, preliminary in vitro studies have revealed the immunomodulatory properties of probiotics. This study aims to evaluate the impact of probiotics on symptoms and peripheral cytokines levels in PD patients compared to placebo. Methods. Patients were enrolled and blindly randomized to receive either active probiotics (comprising Bifidobacterium animalis subsp. lactis BS01 LMG P-21384, Bifidobacterium longum BL03 DSM 16603, Bifidobacterium adolescentis BA02 DSM 18351, Fructo-oligosaccharides and Maltodextrin-Group A) or placebo (Maltodextrin-Group B). Clinical evaluations and plasma levels cytokines (TNF-&alpha;, IFN-&gamma;, IL-6, and TGF-&beta;) were also assessed at enrollment and after 12 weeks. Anti-parkinsonian therapy remained stable throughout the study. Results. Forty PD patients were recruited. After 12 weeks, Group A showed significant improvement in motor symptoms (UPDRS III: 13.89 &plusmn; 4.08 vs. 12.74 &plusmn; 4.57, p = 0.028) and non-motor symptoms (NMSS: 34.32 &plusmn; 21.41 vs. 30.11 &plusmn; 19.89, p = 0.041), with notable improvement in the gastrointestinal sub-item (3.79 &plusmn; 4.14 vs. 1.89 &plusmn; 2.54, p = 0.021). A reduction of IFN-&gamma; levels was observed in both groups, but group A also showed a significant decrease in IL-6 and a slight increase in the anti-inflammatory cytokine TGF-&beta;. Conclusions. Our data suggest that probiotics may modulate peripheral cytokines levels and improve clinical symptoms in PD patients. Probiotics may, therefore, represent a valuable adjunctive therapy to conventional anti-parkinsonian drugs.
in Brain Sciences on 2024-11-15 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1145: New Pharmacological Insight into Etanercept and Pregabalin in Allodynia and Nociception: Behavioral Studies in a Murine Neuropathic Pain Model
Brain Sciences doi: 10.3390/brainsci14111145
Authors:
Loulwah Alothman
Emad Alhadlaq
Asma Alhussain
Alwaleed Alabdulkarim
Youssef Sari
Shakir D. AlSharari
Background/Objectives: Neuropathic pain is challenging to treat, often resistant to current therapies, and associated with significant side effects. Pregabalin, an anticonvulsant that modulates calcium channels, is effective but can impair mental and motor functions, especially in older patients. To improve patient outcomes, reducing the doses of pregabalin and combining it with other drugs targeting different neuropathic pain mechanisms may be beneficial. TNF-&alpha; blockers such as etanercept have shown potential in addressing neuropathic pain by affecting sodium channels, synaptic transmission, and neuroinflammation. This study evaluates the efficacy and safety of combining low doses of etanercept and pregabalin in allodynia and nociceptive tests. Materials and Methods: Male C57/BL6 mice underwent chronic constriction injury (CCI) of the sciatic nerve to induce neuropathic pain. They were divided into seven groups: sham control, CCI control, low and high doses of pregabalin, low and high doses of etanercept, and a combination of low doses of both drugs. Behavioral tests, including von Frey, hot-plate, and rotarod tests, were used to assess pain responses and motor activity. Results: The results indicated that a high dose of pregabalin significantly reduced mechanical allodynia and thermal hyperalgesia but impaired motor function. Conversely, low doses of etanercept alone had no significant effect. However, the combination of low doses of etanercept (20 mg/kg) and pregabalin (5 mg/kg) effectively alleviated pain without compromising locomotor activity. Conclusions: These results suggest a novel therapeutic strategy for neuropathic pain, enhancing analgesic efficacy while minimizing adverse effects.
in Brain Sciences on 2024-11-15 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1146: High Expression of GABAA Receptor β Subunit Genes Is Associated with Longer Overall Survival in Medulloblastoma
Brain Sciences doi: 10.3390/brainsci14111146
Authors:
Jander M. Monteiro
Matheus Dalmolin
Marcelo A. C. Fernandes
Jaqueline I. R. Ramos
Carmen A. P. M. Ribas
Fernando I. Tabushi
Rafael Roesler
Gustavo R. Isolan
Background/Objectives: Most of the rapid inhibitory neurotransmission in the brain is mediated through activation of the &gamma;-aminobutyric acid (GABA) type A (GABAA) receptor, which is a ligand-gated ion channel. GABAA receptor activation via GABA binding allows for an intracellular influx of Cl&minus; ions, thus inducing cellular hyperpolarization. Each GABAA receptor consists of a combination of five subunits, and several subunits have been proposed as biomarkers and therapeutic targets in cancer. Here, we show the expression of genes encoding &beta; subunits of the GABAA receptor, namely GABRB1, GABRB2, and GABRB3, across the four different molecular subgroups of medulloblastoma (MB), which is the most common malignant pediatric brain tumor. We also show the associations of GABAA receptor &beta; subunits with MB patients&rsquo; overall survival (OS). Methods: The expression of genes encoding GABAA receptor &beta; subunits was analyzed using a previously described dataset comprising 763 MB tumor samples. Patients were classified into high- and low-gene-expression groups, and the Kaplan&ndash;Meier estimate was used to examine the relationship between gene expression levels and patient OS. Results: High GABRB1 expression was associated with better OS within each of the four molecular subgroups. The GABRB2 gene showed higher transcript levels in Group 3 MB compared to all other subgroups, and high expression was associated with better prognosis in Group 3 tumors. GABRB3 expression was significantly higher in Group 3 and Group 4 MB, and high expression of GABRB3 genes was associated with longer OS in the sonic hedgehog (SHH) subgroup. The high expression of GABRB1, GABRB2, and GABRB3 is associated with longer patient OS in a subgroup-specific manner. Conclusions: These results indicate a role for GABAA receptors containing &beta; subunits in influencing MB progression.
in Brain Sciences on 2024-11-15 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1144: The Role of Cognitive Reserve in Post-Stroke Rehabilitation Outcomes: A Systematic Review
Brain Sciences doi: 10.3390/brainsci14111144
Authors:
Debora Bertoni
Stefania Bruni
Donatella Saviola
Antonio De Tanti
Cosimo Costantino
Background/Objectives: Stroke remains a major cause of disability and death, with survivors facing significant physical, cognitive, and emotional challenges. Rehabilitation is crucial for recovery, but outcomes can vary widely. Cognitive reserve (CR) has emerged as a factor influencing these outcomes. This systematic review evaluates the role of CR in post-stroke rehabilitation, examining whether higher CR is associated with better outcomes. Methods: A systematic search of PubMed, Google Scholar, Scopus, and Cochrane Library databases was conducted for studies published between 2004 and 2024. Studies examining social-behavior CR proxies (e.g., education, bilingualism) and their impact on post-stroke outcomes were included. Data were analyzed using descriptive statistics. The study quality was assessed using the Methodological Index for NOn-Randomized Studies (MINORS) scale. Results: Among 3851 articles screened, 27 met the inclusion criteria. Higher education levels, bilingualism, and engagement in cognitively stimulating activities were associated with better cognitive outcomes and functional recovery. Lower socioeconomic status (SES) correlated with poorer outcomes. Early rehabilitation and dynamic CR proxies showed stronger associations with cognitive recovery than static ones. Conclusions: CR may predict post-stroke rehabilitation outcomes, with education, bilingualism, and active engagement in cognitive activities showing potential benefits. Future research should explore CR&rsquo;s role alongside factors like lesion location and severity in enhancing recovery.
in Brain Sciences on 2024-11-15 00:00:00 UTC.
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Brain Sciences, Vol. 14, Pages 1143: Spontaneous Intracranial Hypotension and Dural Ectasia in Marfan Syndrome: An Illustrative Case Successfully Treated with Steroid Therapy and Literature Review
Brain Sciences doi: 10.3390/brainsci14111143
Authors:
Francesco Signorelli
Omar Ktari
Ludovico Agostini
Giorgio Ducoli
Fabio Zeoli
Massimiliano Visocchi
Background: Spontaneous intracranial hypotension (SIH) is a rare and frequently misdiagnosed disorder characterized by a low volume of cerebrospinal fluid (CSF) caused by the leakage of CSF through the spinal dural membrane. Patients with Marfan Syndrome (MS) and other connective tissue disorders are at an increased risk for dural ectasia, which may predispose them to spontaneous CSF leaks due to the structural weakness of their dural membranes. The management of SIH in MS patients is debated. Conservative measures, an epidural blood patch (EBP), and surgical treatments are the options generally provided. Methods: Herein, we report on the case of a 52-year-old female affected by MS, genetically confirmed, with a two-month history of sudden-onset, &ldquo;thunderclap&rdquo; headache, worsened in an upright position and horizontal diplopia. A Computed Tomography (CT) scan of the brain showed a bilateral chronic subdural hematoma, slit ventricles, and a caudal descent of the brainstem without overt tonsillar herniation. The Magnetic Resonance Imaging (MRI) scan of the whole spine revealed dural ectasia in the lumbosacral area and presacral perineural cyst without extradural CSF collection. The case was successfully managed with bed rest and high-dose corticosteroid therapy. Then, we discuss the pertinent literature, consisting of 25 papers dealing with the treatment of SIH in patients affected by MS. Results: The literature review yielded 25 papers dealing with SIH management in patients with MS, including 28 patients overall; 21 patients underwent EBP, of whom 7 patients had multiple procedures. Overall, in 23 cases (82%), the symptoms improved. In three cases, the patients were managed conservatively with bed rest. In three of these cases, there was an improvement. In one case, the surgical fenestration of two lumbar intradural spinal meningeal cysts was performed and the patient improved after the procedure. Our patient underwent 15 days of steroid therapy (dexamethasone iv 12 mg/day for 7 days, then reduced to 4 mg/day) and intravenous hydration (Ringer lactate 1500 mL/day). In ten days, the symptoms disappeared. At the 6-month follow-up, the patient was in good clinical condition, and a CT scan showed an almost complete regression of the bilateral subdural hematoma. Conclusions: The management of SIH in MS patients is still challenging. Patients with connective tissue disorders such as MS are at an increased risk for SIH. Few studies have assessed the management of these patients and different strategies. Our case and the available literature provide further data for this type of case.
in Brain Sciences on 2024-11-15 00:00:00 UTC.
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Background Atopic dermatitis (AD) is a chronic inflammatory skin condition characterized by pruritus and skin barrier dysfunction. This study aims to evaluate the therapeutic potential of Pelargonium graveolens (Geraniaceae) in managing AD symptoms through its essential oil. Methods The chemical composition of Pelargonium graveolens flower essential oil (PFEO) was analyzed using gas chromatography-mass spectrometry (GC-MS). Its antimicrobial, antioxidant, and anti-inflammatory properties were assessed, along with the inhibitory effects of PFEO on key enzymes involved in skin repair: tyrosinase, elastase, and collagenase. An in vivo evaluation of a gel formulation containing PFEO was also conducted to assess its anti-inflammatory and analgesic efficacy. Results GC-MS analysis identified major compounds in PFEO, including Geraniol (22.83%), beta-citronellol (19.51%), naphthalenemethanol (15.36%), and Geranyl tiglate (9.38%), with minor constituents such as linalool (3.81%) and neryl formate (1.31%). PFEO exhibited bacteriostatic activity against various bacterial and fungal strains, including Pseudomonas aeruginosa, Staphylococcus aureus, Methicillin-Resistant Staphylococcus aureus (MRSA), Bacillus anthracis, Streptococcus pyogenes, Staphylococcus epidermidis, Candida albicans, and Malassezia spp. The essential oil also demonstrated significant antioxidant properties and inhibited key enzymes linked to skin alterations in AD. Conclusions PFEO shows promising therapeutic potential for managing symptoms of atopic dermatitis due to its antimicrobial, antioxidant, and anti-inflammatory properties, as well as its analgesic effects. The findings support further exploration of PFEO as a natural alternative in the treatment of AD.
in F1000Research on 2024-11-14 17:57:35 UTC.
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Background Cytoscape is an open-source software to visualize and analyze networks. However, large networks, such as protein interaction networks, are still difficult to analyze as a whole. Methods Here, we propose Clust&See3.0, a novel version of a Cytoscape app that has been developed to identify, visualize and manipulate network clusters and modules. It is now enriched with functionalities allowing custom annotations of nodes and computation of their statistical enrichments. Results As the wealth of multi-omics data is growing, such functionalities are highly valuable for a better understanding of biological module composition, as illustrated by the presented use case. Conclusions In summary, the originality of Clust&See3.0 lies in providing users with a complete tool for network clusters analyses: from cluster identification, visualization, node and cluster annotations to annotation statistical analyses.
in F1000Research on 2024-11-14 17:43:17 UTC.
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Background This study aims to contribute to a better understanding of the impact of the financial technologies (fintech) era on the performance in the banking sector, measured through non-performing loans (NPL) and their coverage by provisions for NPL. It is a question of knowing whether banking investment in fintech makes it possible to better evaluate the granting of credits, and therefore makes it possible to reduce overdue credits. Methods To this end, the method used consists of using a regression analysis and a Pearson correlation applied to the financial data of Moroccan banks observed during two distinct periods, namely 2007-2014, considered pre-fintech, and the period 2015-2022, considered as the fintech period. Results With the emergence of the fintech era, the Moroccan banking situation improved slightly compared to the pre-fintech period: bad debts did not increase despite the significant increase in net banking income and the size of banking assets during the fintech era. Conclusions The implementation of fintech has improved customer relationship management, credit risk analysis and loan monitoring services, which ultimately reduces non-performing loans and improves the coverage of non-performing loans by provisions. The main implication of the results allows us to deduce that the implementation of fintech makes it possible to have a positive impact on overdue credits, and they are also likely to serve as a lever for the inclusion of those excluded from banking services.
in F1000Research on 2024-11-14 17:40:03 UTC.
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Visual working memory (VWM) requires precise feature binding. Previous studies have revealed a close relationship between the posterior parietal cortex (PPC) and feature binding during VWM; this study further examined their causal relationship through three transcranial direct current stimulation (tDCS) experiments. In Experiment 1 (N = 57), participants underwent three sessions of tDCS separately, including PPC stimulation, occipital cortex stimulation, and sham stimulation, and completed delayed estimation tasks for orientations before and after stimulation. Results showed that tDCS over PPC selectively prolonged recall response time (RT) and increased the probability of nontarget responses (a.k.a. failure of feature binding, pNT). In Experiment 2 (N = 29), combining metacognition estimation, we further investigated whether the effects of PPC stimulation were attributed to misbinding (i.e., participants self-reported "remembered" in nontarget responses) or informed guessing trials (participants self-reported "forgotten" in nontarget responses). We replicated the main findings in Experiment 1 and observed greater tDCS effects of PPC on RT in informed guessing trials while there are comparable effects on pNT in these two types of trials. In Experiment 3 (N = 28), we then examined whether the tDCS effects over PPC specifically influenced the memory retrieval process by using a change detection task. We found that PPC stimulation did not influence the recognition RT or accuracy. Together, this study provided direct causal evidence supporting the specific involvement of PPC in feature binding during VWM retrieval, from both aspects of speed and response preference, expanding our understanding of the neural basis of feature binding in VWM.
in eNeuro on 2024-11-14 17:30:23 UTC.
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Neurodevelopmental abnormalities are considered to be one of the important causes of schizophrenia. The offspring of methylazoxymethanol acetate (MAM)–exposed mice are recognized for the dysregulation of neurodevelopment and are well-characterized with schizophrenia-like phenotypes. However, the inhibition-related properties of the medial prefrontal cortex (mPFC) and hippocampus throughout adolescence and adulthood have not been systematically elucidated. In this study, both 10 and 15 mg/kg MAM-exposed mice exhibited schizophrenia-related phenotypes in both adolescence and adulthood, including spontaneous locomotion hyperactivity and deficits in prepulse inhibition. We observed that there was an obvious parvalbumin (PV) loss in the mPFC and hippocampus of MAM-exposed mice, extending from adolescence to adulthood. Moreover, the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) in pyramidal neurons at mPFC and hippocampus was significantly dampened in the 10 and 15 mg/kg MAM-exposed mice. Furthermore, the firing rate of putative pyramidal neurons in mPFC and hippocampus was increased, while that of putative inhibitory neurons was decreased during both adolescence and adulthood. In conclusion, PV loss in mPFC and hippocampus of MAM-exposed mice may contribute to the impaired inhibitory function leading to the attenuation of inhibition in the brain both in vitro and in vivo.
in eNeuro on 2024-11-14 17:30:23 UTC.
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in eNeuro on 2024-11-14 17:30:23 UTC.
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in eNeuro on 2024-11-14 17:30:23 UTC.
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Background Sustaining a ‘fit-for-purpose’ health workforce requires a better understanding of the health care worker cadres that are affected during pandemics and their outcomes. In hospitalized health care workers with confirmed COVID-19 between March 2020 and May 2023 in Liberia, we determined the hospitalization and case fatality rates, type of health care worker cadres affected, their demographic and clinical characteristics and hospital exit outcomes. Methods This was a cohort study using routine data extracted from hospitalization forms for health care workers in 24 designated COVID-19 treatment facilities. Results Of the 424 health care workers with COVID-19, hospitalization rates progressively declined between 2020 and 2023, (P<0.001) with the highest rates in 2020 (24/1,000 health care workers) and 2021 (14/1,000 health care workers). Case fatality was 2% in both 2020 and 2021 with no deaths thereafter. Among those hospitalized, the highest proportions were nursing cadres with 191(45%), physicians with 63 (15%) and laboratory technicians with 42 (10%). The most frequent reported site for COVID-19 infection was the health facility (326, 89%). COVID-19 vaccination coverage in health care workers was 20%. The majority (91%) of hospitalizations were for mild symptomatic infections. Even in referral centres (n-52), 18 (35%) were for mild infections. Of the 424 who were hospitalized, 412 (97%) recovered, 9 (2%) died and 3 (1%) either left against medical advice or absconded. Of the nine deaths, none were vaccinated, seven had moderate-to-severe disease but were not referred to specialized COVID-19 treatment centers. Conclusions The hospitalized health care workers for COVID-19 were predominantly clinical and laboratory personnel who were mostly unvaccinated, and health facilities were hot-spots for contracting infections. The triage and referral system was weak with unnecessary hospitalization of mild infections. This study provides useful insights for outbreak preparedness including priority vaccination and improving health care worker safety in Liberia.
in F1000Research on 2024-11-14 16:59:59 UTC.
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Background Table tennis presented a unique and accessible sport for people of all ages, particularly seniors compared to other sports. Methods This study utilized a quantitative with 136 Table tennis players those who registered for attending in the Thailand Master Table tennis Championships 2024 which hosted in January 2024 at Chiangmai. The questionnaire based on the measurement quality of life, WHOQOL Thai version, and analyzed using Descriptive statistics, Pearson Correlation. Results Pearson correlation coefficients between the scores of the quality of life in four dimensions and the overall score revealed significant correlations (p < 0.01) with all dimensions, including physical health, psychological health, social relationships, and environmental health. Conclusions Playing Table tennis for senior in the tournament level helped to improve the quality of life in all domains.
in F1000Research on 2024-11-14 15:21:20 UTC.
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Background Chronic limb-threatening ischemia (CLTI) is the most advanced stage of peripheral artery disease (PAD) and has poor clinical outcomes. Recently, stimulating arteriogenesis has been proposed to improve clinical outcomes. Several studies have shown that miRNAs have beneficial effects on limb ischemia related to arteriogenesis. This study aimed to review the roles of therapeutic miRNAs in the arteriogenesis of limb ischemia. Methods A systematic search was conducted through July 2021 using the PubMed, Scopus, and ScienceDirect databases. Two authors independently assessed studies that investigated the role of miRNAs in the arteriogenesis of limb ischemia, both in vivo and in clinical studies. Results All selected studies were in vivo studies, with a total of 36 articles and 28 types of miRNAs. miRNAs potentially regulate arteriogenesis by targeting different targets. The following miRNAs were upregulated to enhance arteriogenesis: miRNA-126-3p, -93, -675, -143-3p, -130a, -210, -146b, -21, -let-7g, -132/212, -150, and 155. Meanwhile, microRNAs needed to be downregulated, namely: miRNA-939-5p, -503, -199a-5p, -146a, -92a, -14q32 microRNA gene cluster, -15a/16, -100, -133a, -139-5p, -223, -352, -615-5p, -15b/5p, -124-3p, and 29a. MiRNA-126 was the most studied miRNA, and SPRED1 was the most common target of microRNA. However, the included studies showed high heterogeneity in terms of inducing hindlimb ischemia, the timing of administration, and the method used for evaluating arteriogenesis. Moreover, most studies presented unclear or high-risk bias. Conclusion MicroRNA application in a preclinical model of hindlimb ischemia has beneficial effects on arteriogenesis. This result indicates that miRNAs might be potentially beneficial in patients with CLTI. Registration The review protocol was registered with PROSPERO under registration number CRD42024484988.
in F1000Research on 2024-11-14 15:17:25 UTC.
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Background Central serous chorioretinopathy (CSCR) is a common retinal condition with an increased risk of recurrence. Traditional approaches have made choroidal visualization challenging, but recent advances in optical coherence tomography (OCT) innovation have permitted the collection of more accurate choroidal visualizations. This study aimed to measure choroidal thickness in eyes with active CSCR as well as in the unaffected opposite eyes of these same individuals. Methods This research was conducted at the ophthalmology division in Ghazi Al-Hariri Hospital from the 1st of October 2019 until the 31st of March 2020. A total of 49 people, corresponding to 65 eyes, were included in the study. Among these participants, 16 individuals presented with central serous chorioretinopathy (CSCR), affecting a total of 32 eyes. The CSCR individuals were further split into two groups: “Group A” consisted of 20 eyes with active CSCR, and “Group B” encompassed the remaining 12 unaffected opposite eyes. Additionally, the right eyes of 33 individuals who were age and gender-matched served as controls assigned as “Group C”. Results The choroid exhibited a substantial rise in thickness across each of the nine sectors in group A as compared to group C. Similarly, group B showed a significant increase in choroidal thickness in relation to group C. The mean subfoveal choroidal thickness (SFCT) was measured as follows: 474.55μm, 437.5μm, and 292.03μm among groups A, B, and C, correspondingly. These differences were identified as clinically significant for both A vs. C and B vs. C. Conclusions This study’s findings indicate a thickening of the choroid in both eyes exhibiting active CSCR, as well as in the unaffected opposite eyes of those with the disease.
in F1000Research on 2024-11-14 15:15:00 UTC.
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Introduction Low and middle-income countries account for the largest proportion of women’s deaths as a result of pregnancy or childbirth-related complications. The sub-Saharan region is the most affected with approximately 70% (202 000) of maternal deaths between 2000 and 2020. These deaths could have been prevented if expectant mothers were prepared for childbirth. Birth preparedness is perceived as a better strategy that helps attain a substantial reduction in maternal mortality. This is achieved by attending early antenatal classes, receiving skilled care during childbirth, and care and support right after birth. The latest survey on antenatal class attendance conducted in South Africa provides an estimated 30.8% of expectant mothers in public healthcare facilities. Methods This study employed a qualitative approach to collect data, as a result, one focus group discussion with five (N=5) participants and two others with six (N=6) participants each (n=6X2=12) and twenty individual interviews were conducted. The study sought to explore and describe the knowledge and attitudes of healthcare professionals regarding the birth preparedness of women in labour at selected hospitals in Durban KwaZulu-Natal. Results Expectant mothers were unprepared for both labour and postnatal care. The unprepared expectant mothers were uncooperative and made the task of midwives difficult to the extent of endangering the life of their expected newborn babies and their own. Factors such as finance, heterogeneity, staff shortage, language barrier, lack of family support, lack of interest, cultural beliefs, and confusion caused by various sources of information were responsible for birth unpreparedness. Conclusion The synergy between expectant mothers and midwives appears to be an important factor in achieving better birth preparedness.
in F1000Research on 2024-11-14 15:13:17 UTC.
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Digital and financial literacy are changing the landscape of the globe in terms of its approach to development. These two literacies also help to achieve women’s empowerment and, consequently, the sustainable development goals (SDGs) more quickly. This systematic literature review looks at the two literacies and their effects, focusing on women’s participation and showing how digital literacy not only increases women’s access to knowledge and connectivity but is also a door to women’s entrepreneurship and financial independence. Likewise, financial literacy, when coupled with digital skills, can be a breakthrough to the traditional socioeconomic barrier – poverty – by assisting women in making informed economic decisions, increasing their financial independence and resilience in the face of a global crisis. Empirical realities that still hinder women’s education, such as cultural norms, infrastructural deficiencies and educational gaps, still exist. However, the paper points out that to have a more equal world based on the SDGs, the double literacy strategy for women’s empowerment should not be negotiable.
in F1000Research on 2024-11-14 15:11:00 UTC.
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Background Studies have shown that perceived self-efficacy can influence teachers’ emotional state, thoughts and behaviours, and students’ learning. It’s also an important referential of professional satisfaction. In turn, teaching methodologies influence motor learning, as well as psychological, cognitive and social learning, with different impacts on human development and learning retention, levels of intrinsic motivation and continuity of practice in order to support a healthy lifestyle. Research on aquatic educators and teaching methodologies is scarce and at the same time necessary according to the view that aquatic literacy is an integral part of physical literacy and the only possibility of being more able to interact with this environment. Methods In this study we used an online questionnaire, aimed at aquatic professionals, which was answered voluntarily and anonymously to measure the prevalence of the use of different teaching methodologies, the comprehensive aquatic method and the perception of teacher self-efficacy. It has been deposited and can be consulted at https://doi.org/10.6084/m9.figshare.27316242.v1. Results All methods can generate a feeling of self-efficacy in teachers despite having different results, with the methodologies that involve students more actively (cognitivist and constructivist) being those that generate a greater feeling of self-efficacy in teachers. MAC is a method that is more closely related to methodologies focused on active student participation and, consequently, it is a method that generates a high perception of self-efficacy in teachers. Conclusions Levels of self-efficacy influence professional satisfaction, teacher physical, mental and emotional health, as well as student learning. Is recommended that aquatic professionals give prevalence to the cognitivist and constructivist teaching methodologies being MAC a privileged methodological approach for promoting active lifestyle habits throughout life.
in F1000Research on 2024-11-14 15:09:27 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Amyotrophic lateral sclerosis (ALS) is a relentless, fatal neurodegenerative disease. The progressive loss of voluntary muscle function, diagnostic delays, lack of effective treatments, and challenges accessing multidisciplinary care and resources have tremendous impact on quality of life. The congressionally directed ALS committee of the National Academies of Science, Engineering, and Medicine, in their 2024 report “Living with ALS,” recommends critical actions for specific United States stakeholders to make ALS a livable disease over the next decade. This review summarizes the context and recommendations of the report. Advocacy efforts are critical to make these recommendations a reality for the ALS community. ANN NEUROL 2024;96:1035–1039
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Slowly expanding lesions (SELs) in adults with multiple sclerosis (MS) indicate a progressive pathological process. Whether SELs are present in pediatric-onset MS (POMS) or myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is unknown. We studied 19 children with POMS and 14 with MOGAD (median age 14.3 and 9.4 years, respectively) recruited to the Canadian Pediatric Demyelinating Disease Study with: (1) ≥3 research scans 12 months apart; and (2) ≥1 T2-lesions on the earliest scan. A total of 70 SELs from 16 POMS participants and 1 SEL in the MOGAD group were detected. SELs are an early feature of POMS and essentially not a feature of MOGAD. ANN NEUROL 2024;96:1086–1091
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Cryptogenic new-onset refractory status epilepticus (cNORSE) is a devastating condition with unclear pathogenesis. Here, we analyzed the genetic underprints of 31 cNORSE patients from an autoimmune encephalitis observational cohort through whole-genome sequencing. Compared to their controls, cNORSE patients exhibited elevated polygenic risk scores (PRS) for traits associated with autoimmune diseases. The individual PRS against these diseases were correlated with specific clinical phenotypes of cNORSE. The variants were enriched in genes expressed in the central nervous system and lymphocytes. These results suggest a shared genetic framework between cNORSE and other autoimmune/autoinflammatory diseases, and its involvement in the disease pathogenesis. ANN NEUROL 2024;96:1201–1208
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Objective
Hexanucleotide repeat expansions in the C9orf72 gene are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). A large body of evidence implicates dipeptide repeats (DPRs) proteins as one of the main drivers of neuronal injury in cell and animal models.
Methods
A pure repeat-associated non-AUG (RAN) translation zebrafish model of C9orf72-ALS/FTD was generated. Embryonic and adult transgenic zebrafish lysates were investigated for the presence of RAN-translated DPR species and adult-onset motor deficits. Using C9orf72 cell models as well as embryonic C9orf72-ALS/FTD zebrafish, hypothermic-therapeutic temperature management (TTM) was explored as a potential therapeutic option for C9orf72-ALS/FTD.
Results
Here, we describe a pure RAN translation zebrafish model of C9orf72-ALS/FTD that exhibits significant RAN-translated DPR pathology and progressive motor decline. We further demonstrate that hypothermic-TTM results in a profound reduction in DPR species in C9orf72-ALS/FTD cell models as well as embryonic C9orf72-ALS/FTD zebrafish.
Interpretation
The transgenic model detailed in this paper provides a medium throughput in vivo research tool to further investigate the role of RAN-translation in C9orf72-ALS/FTD and further understand the mechanisms that underpin neuroprotective strategies. Hypothermic-TTM presents a viable therapeutic avenue to explore in the context of C9orf72-ALS/FTD. ANN NEUROL 2024;96:1058–1069
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Objective
Neurofilament light chains (NfL) and phosphorylated neurofilament heavy chains (pNfH), established as diagnostic and prognostic biomarkers in hospital-based amyotrophic lateral sclerosis (ALS) cohorts, are now surrogate markers in clinical trials. This study extends their evaluation to a population level, with the aim of advancing their full establishment and assessing the transferability of biomarker findings from controlled cohorts to real-world ALS populations.
Methods
We measured serum NfL and pNfH levels in all ALS patients (n = 790) and general population controls (n = 570) with available baseline samples participating in the epidemiological ALS Registry Swabia, providing platform-specific (ELLA™) reference data and Z-scores for controls, as well as reference data, disease-specific Z-scores and longitudinal data in ALS. We evaluated the diagnostic and prognostic utility of neurofilaments and quantified the impact of ALS-related factors and non-ALS confounders.
Results
Neurofilaments showed high diagnostic and prognostic utility at the population level, with NfL superior to pNfH. The novel concept of a population-based ALS Z-score significantly improved the prognostic utility compared to absolute raw values. Both biomarkers increased more strongly with age in controls than in ALS, and age adjustment improved diagnostic accuracy. Our data show that disease progression rates, ALS phenotype, body mass index (BMI), and renal function need to be considered when interpreting neurofilament levels; longitudinal neurofilament levels were generally stable in individual patients, especially when adjusted for age and baseline levels.
Interpretation
Population-based assessment enhances the utility of particularly serum NfL as a diagnostic and prognostic biomarker in ALS and improves the translation of findings from controlled cohorts to real-world populations. ANN NEUROL 2024;96:1040–1057
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Objective
Periventricular nodular heterotopia (PVNH) is the most common neuronal heterotopia, frequently resulting in pharmaco-resistant epilepsy. Here, we characterize variables that predict good epilepsy outcomes following surgical intervention using stereo-electroencephalography (SEEG) -informed magnetic resonance-guided laser interstitial thermal therapy (MRgLITT).
Methods
A retrospective review of consecutive cases from a single high-volume epilepsy referral center identified patients who underwent SEEG evaluation for PVNH to characterize the intervention and outcomes.
Results
Thirty-nine patients underwent SEEG-guided MRgLITT of the seizure onset zone (SoZ) in PVNH and associated epileptic tissue. PVNH and polymicrogyria (PMG) were densely sampled with a mean of 16.5 (SD = 2)/209.4 (SD = 36.9) SEEG probes/recording contacts per patient. Ablation principally targeted just the PVNH and cortex that was abnormal on imaging was ablated (5 patients) only if implicated in the SoZ. Volumetric analyses revealed a high percentage of PVNH SoZ ablation (96.6%, SD = 5.3%) in unilateral and bilateral (92.9%, SD = 7.2%) cases. Mean follow-up duration was 31.4 months (SD = 20.9). Seizure freedom (ILAE 1) was excellent: unilateral PVNH without other imaging abnormalities, 80%; PVNH with mesial temporal sclerosis (MTS) or PMG, 63%; bilateral PVNH, 50%. SoZ ablation percentage significantly impacted surgical outcomes (p < 0.001).
Interpretation
PVNH plays a central role in seizure genesis as revealed by dense recordings and selective targeting by LITT. MRgLITT represents a transformative technological advance in PVNH-associated epilepsy with seizure control outcomes consistent with those seen in focal lesional epilepsies. In localized unilateral cases and otherwise normal imaging, PVNH ablation without invasive recordings may be considered, and this approach deserves to be explored further. ANN NEUROL 2024;96:1174–1184
in Annals of Neurology on 2024-11-14 14:07:31 UTC.
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Objectives
Spinocerebellar ataxia 27B due to GAA repeat expansions in the fibroblast growth factor 14 (FGF14) gene has recently been recognized as a common cause of late-onset hereditary cerebellar ataxia. Here we present the first report of this disease in the US population, characterizing its clinical manifestations, disease progression, pathological abnormalities, and response to 4-aminopyridine in a cohort of 102 patients bearing GAA repeat expansions.
Methods
We compiled a series of patients with SCA27B, recruited from 5 academic centers across the United States. Clinical manifestations and patient demographics were collected retrospectively from clinical records in an unblinded approach using a standardized form. Post-mortem analysis was done on 4 brains of patients with genetically confirmed SCA27B.
Results
In our cohort of 102 patients with SCA27B, we found that SCA27B was a late-onset (57 ± 12.5 years) slowly progressive ataxia with an episodic component in 51% of patients. Balance and gait impairment were almost always present at disease onset. The principal finding on post-mortem examination of 4 brain specimens was loss of Purkinje neurons that was most severe in the vermis most particularly in the anterior vermis. Similar to European populations, a high percent of patients 21/28 (75%) reported a positive treatment response with 4-aminopyridine.
Interpretation
Our study further estimates prevalence and further expands the clinical, imaging and pathological features of SCA27B, while looking at treatment response, disease progression, and survival in patients with this disease. Testing for SCA27B should be considered in all undiagnosed ataxia patients, especially those with episodic onset. ANN NEUROL 2024;96:1092–1103
in Annals of Neurology on 2024-11-14 14:07:31 UTC.