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SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
arXiv:2507.08402v1 Announce Type: new Abstract: Intracortical Brain-Computer Interfaces (iBCI) aim to decode behavior from neural population activity, enabling individuals with motor impairments to regain motor functions and communication abilities. A key challenge in long-term iBCI is the nonstationarity of neural recordings, where the composition and tuning profiles of the recorded populations are unstable across recording sessions. Existing methods attempt to address this issue by explicit alignment techniques; however, they rely on fixed neural identities and require test-time labels or parameter updates, limiting their generalization across sessions and imposing additional computational burden during deployment. In this work, we introduce SPINT - a Spatial Permutation-Invariant Neural Transformer framework for behavioral decoding that operates directly on unordered sets of neural units. Central to our approach is a novel context-dependent positional embedding scheme that dynamically infers unit-specific identities, enabling flexible generalization across recording sessions. SPINT supports inference on variable-size populations and allows few-shot, gradient-free adaptation using a small amount of unlabeled data from the test session. To further promote model robustness to population variability, we introduce dynamic channel dropout, a regularization method for iBCI that simulates shifts in population composition during training. We evaluate SPINT on three multi-session datasets from the FALCON Benchmark, covering continuous motor decoding tasks in human and non-human primates. SPINT demonstrates robust cross-session generalization, outperforming existing zero-shot and few-shot unsupervised baselines while eliminating the need for test-time alignment and fine-tuning. Our work contributes an initial step toward a robust and scalable neural decoding framework for long-term iBCI applications.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Transcranial Focused Ultrasound for Identifying the Neural Substrate of Conscious Perception
arXiv:2507.08517v1 Announce Type: new Abstract: Identifying what aspects of brain activity are responsible for conscious perception remains one of the most challenging problems in science. While progress has been made through psychophysical studies employing EEG and fMRI, research would greatly benefit from improved methods for stimulating the brain in healthy human subjects. Traditional techniques for neural stimulation through the skull, including electrical or magnetic stimulation, suffer from coarse spatial resolution and have limited ability to target deep brain structures with high spatial selectivity. Over the past decade, a new tool has emerged known as transcranial focused ultrasound (tFUS), which enables the human brain to be stimulated safely and non-invasively through the skull with millimeter-scale spatial resolution, including cortical as well as deep brain structures. This tool offers an exciting opportunity for breakthroughs in consciousness research. Given the extensive preparation and regulatory approvals associated with tFUS testing, careful experimental planning is essential. Therefore, our goal here is to provide a roadmap for using tFUS in humans for exploring the neural substrate of conscious perception.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Critical dynamics governs deep learning
arXiv:2507.08527v1 Announce Type: new Abstract: Artificial intelligence has advanced rapidly through larger and deeper neural networks, yet fundamental questions remain about how to optimize network dynamics for performance and adaptability. This study shows that deep neural networks (DNNs), like biological brains, perform optimally when operating near a critical phase transition - poised between active and inactive dynamics. Drawing from physics and neuroscience, we demonstrate that criticality provides a unifying principle linking structure, dynamics, and function in DNNs. Analyzing more than 80 state-of-the-art models, we first report that improvements in accuracy over the past decade coincided with an implicit evolution toward more critical dynamics. Architectural and training innovations unknowingly guided networks toward this optimal regime. Second, building on these insights, we develop a training method that explicitly drives networks to criticality, improving robustness and performance. Third, we show that fundamental problems in AI, including loss of performance in deep continual learning, are caused by loss of criticality and that maintaining criticality rescues performance. This work introduces criticality as a fundamental framework for AI development by emphasizing dynamic optimization alongside scale. It bridges artificial intelligence with physics and biological cortical network function inspiring novel self-tuning strategies in DNNs. The findings offer a theoretically grounded path forward in designing efficient, adaptable, and high-performing artificial intelligence systems drawing inspiration from principles observed in biological neural systems.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Distinct neurodynamics of functional brain networks in Alzheimer's disease and frontotemporal dementia as revealed by EEG
arXiv:2507.08728v1 Announce Type: new Abstract: Objective While Alzheimer's disease (AD) and frontotemporal dementia (FTD) show some common memory deficits, these two disorders show partially overlapping complex spatiotemporal patterns of neural dynamics. The objective of this study is to characterize these patterns to better understand the general principles of neurodynamics in these conditions. Methods A comprehensive array of methods to study brain rhythms and functional brain networks are used in the study, from spectral power measures to Lyapunov exponent, phase synchronization, temporal synchrony patterns, and measures of the functional brain connectivity. Furthermore, machine learning techniques for classification are used to augment the methodology. Results Multiple measures (spectral, synchrony, functional network organization) indicate an array of differences between neurodynamics between AD and FTD, and control subjects across different frequency bands. Conclusions These differences taken together in an integrative way suggest that AD neural activity may be less coordinated and less connected across areas, and more random, while FTD shows more coordinated neural activity (except slow frontal activity). Significance AD and FTD may represent opposite changes from normal brain function in terms of the spatiotemporal coordination of neural activity. Deviations from normal in both directions may lead to neurological deficits, which are specific to each of the disorders.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy
arXiv:2412.17820v5 Announce Type: replace Abstract: Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option for patients with drug-resistant seizures. However, accurately predicting surgical outcomes remains a significant challenge. This study introduces a novel biomarker derived from brain connectivity, analyzed using non-Euclidean network geometry, to predict the surgery outcome in TLE. Using structural and diffusion magnetic resonance imaging (MRI) data from 51 patients, we examined differences in structural connectivity networks associated to surgical outcomes. Our approach uniquely utilized hyperbolic embeddings of pre- and post-surgery brain networks, successfully distinguishing patients with favorable outcomes from those with poor outcomes. Notably, the method identified regions in the contralateral hemisphere relative to the epileptogenic zone, whose connectivity patterns emerged as a potential biomarker for favorable surgical outcomes. The prediction model achieves an area under the curve (AUC) of 0.87 and a balanced accuracy of 0.81. These results underscore the predictive capability of our model and its effectiveness in individual outcome forecasting based on structural network changes. Our findings highlight the value of non-Euclidean representation of brain networks in gaining deeper insights into connectivity alterations in epilepsy, and advancing personalized prediction of surgical outcomes in TLE.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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A Turing Test for Artificial Nets devoted to model Human Vision
arXiv:2502.00721v3 Announce Type: replace Abstract: In our invited talk at the AI Evaluation Workshop of the University of Bristol back in June 2022 we argued that, despite claims about successful modeling of the visual brain using ANNs, the problem is far from being solved (even for low-level vision). Open issues include: where should we read from ANNs to reproduce human behavior?, this ad-hoc read-out is part of the brain model or not?, should we use artificial psychophysics or artificial physiology?, artificial experiments should literally match the experiments in humans?. There is a clear need of rigorous procedures for experimental tests for ANNs models of the visual brain, and more generally, to understand ANNs devoted to generic vision tasks. Following our experience in using low-level facts from Visual Neuroscience in Image Processing, we presented the idea of developing a low-level dataset compiling the basic spatio-temporal and chromatic facts that are known to happen in the retina-V1 pathway, and they are not currently available in existing databases such as BrainScore. In our results we checked the behavior of three recently proposed models with similar architecture: (1) A parametric model tuned via Maximum Differentiation [Malo & Simoncelli SPIE 15, Martinez et al. PLOS 18, Martinez et al. Front. Neurosci. 19], (2) A non-parametric model, the PerceptNet, tuned to maximize the correlation with human opinion on subjective distortions [Hepburn et al. IEEE ICIP 20], and (3) A model with the same encoder as PerceptNet, but tuned for segmentation (published later as Hernandez-Camara et al. Patt.Recogn.Lett. 23, Hernandez-Camara et al. Neurocomp. 25). Results on 10 compelling psycho/physio visual facts show that the first model is the one with closer behavior to the humans in terms of receptive fields, but more interestingly, on the nonlinear behavior for spatio-chromatic patterns of a range of luminances and contrasts.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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The role of gain neuromodulation in layer-5 pyramidal neurons
arXiv:2507.03222v2 Announce Type: replace Abstract: Biological and artificial learning systems alike confront the plasticity-stability dilemma. In the brain, neuromodulators such as acetylcholine and noradrenaline relieve this tension by tuning neuronal gain and inhibitory gating, balancing segregation and integration of circuits. Fed by dense cholinergic and noradrenergic projections from the ascending arousal system, layer-5 pyramidal neurons in the cerebral cortex offer a relevant substrate for understanding these dynamics. When distal dendritic signals coincide with back-propagating action potentials, calcium plateaus turn a single somatic spike into a high-gain burst, and interneuron inhibition sculpts the output. These properties make layer-5 cells gain-tunable amplifiers that translate neuromodulatory cues into flexible cortical activity. To capture this mechanism we developed a two-compartment Izhikevich model for pyramidal neurons and single-compartment somatostatin (SOM) and parvalbumin (PV) interneurons, linked by Gaussian connectivity and spike-timing-dependent plasticity (STDP). The soma and apical dendrite are so coupled that somatic spikes back-propagate, while dendritic plateaus can switch the soma from regular firing to bursting by shifting reset and adaptation variables. We show that stronger dendritic drive or tighter coupling raise gain by increasing the likelihood of calcium-triggered somatic bursts. In contrast, dendritic-targeted inhibition suppresses gain, while somatic-targeted inhibition raises the firing threshold of neighboring neurons, thus gating neurons output. Notably, bursting accelerates STDP, supporting rapid synaptic reconfiguration and flexibility. This suggests that brief gain pulses driven by neuromodulators could serve as an adaptive two-timescale optimization mechanism, effectively modulating the synaptic weight updates.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Communities in the Kuramoto Model: Dynamics and Detection via Path Signatures
arXiv:2503.17546v3 Announce Type: replace-cross Abstract: The behavior of multivariate dynamical processes is often governed by underlying structural connections that relate the components of the system. For example, brain activity, which is often measured via time series is determined by an underlying structural graph, where nodes represent neurons or brain regions and edges cortical connectivity. Existing methods for inferring structural connections from observed dynamics, such as correlation-based or spectral techniques, may fail to fully capture complex relationships in high-dimensional time series in an interpretable way. Here, we propose the use of path signatures, a mathematical framework that encodes geometric and temporal properties of continuous paths, to address this problem. Path signatures provide a reparametrization-invariant characterization of dynamical data and can be used to compute the lead matrix, which reveals lead-lag phenomena. We showcase our approach on time series from coupled oscillators in the Kuramoto model defined on a stochastic block model graph, termed the Kuramoto Stochastic Block Model (KSBM). Using mean-field theory and Gaussian approximations, we analytically derive reduced models of KSBM dynamics in different temporal regimes and theoretically characterize the lead matrix in these settings. Leveraging these insights, we propose a novel signature-based community detection algorithm, achieving exact recovery of structural communities from observed time series in multiple KSBM instances. We also explored the performance of our community detection on a stochastic variant of the KSBM as well as on real neuropixels of cortical recordings to demonstrate applicability on real-world data. Our results demonstrate that path signatures provide a novel perspective on analyzing complex neural data and other high-dimensional systems, explicitly exploiting temporal functional relationships to infer underlying structure.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Hyperchaos and complex dynamical regimes in $N$-dimensional neuron lattices
arXiv:2505.03051v2 Announce Type: replace-cross Abstract: We study the dynamics of $N$-dimensional lattices of nonchaotic Rulkov neurons coupled with a flow of electrical current. We consider both nearest-neighbor and next-nearest-neighbor couplings, homogeneous and heterogeneous neurons, and small and large lattices over a wide range of electrical coupling strengths. As the coupling strength is varied, the neurons exhibit a number of complex dynamical regimes, including unsynchronized chaotic spiking, local quasi-bursting, synchronized chaotic bursting, and synchronized hyperchaos. For lattices in higher spatial dimensions, we discover dynamical effects arising from the "destructive interference" of many connected neurons and miniature "phase transitions" from coordinated spiking threshold crossings. In large two- and three-dimensional neuron lattices, we observe emergent dynamics such as local synchronization, quasi-synchronization, and lag synchronization. These results illustrate the rich dynamics that emerge from coupled neurons in multiple spatial dimensions, highlighting how dimensionality, connectivity, and heterogeneity critically shape the collective behavior of neuronal systems.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Scientific Machine Learning of Chaotic Systems Discovers Governing Equations for Neural Populations
arXiv:2507.03631v2 Announce Type: replace-cross Abstract: Discovering governing equations that describe complex chaotic systems remains a fundamental challenge in physics and neuroscience. Here, we introduce the PEM-UDE method, which combines the prediction-error method with universal differential equations to extract interpretable mathematical expressions from chaotic dynamical systems, even with limited or noisy observations. This approach succeeds where traditional techniques fail by smoothing optimization landscapes and removing the chaotic properties during the fitting process without distorting optimal parameters. We demonstrate its efficacy by recovering hidden states in the Rossler system and reconstructing dynamics from noise-corrupted electrical circuit data, where the correct functional form of the dynamics is recovered even when one of the observed time series is corrupted by noise 5x the magnitude of the true signal. We demonstrate that this method is capable of recovering the correct dynamics, whereas direct symbolic regression methods, such as SINDy, fail to do so with the given amount of data and noise. Importantly, when applied to neural populations, our method derives novel governing equations that respect biological constraints such as network sparsity - a constraint necessary for cortical information processing yet not captured in next-generation neural mass models - while preserving microscale neuronal parameters. These equations predict an emergent relationship between connection density and both oscillation frequency and synchrony in neural circuits. We validate these predictions using three intracranial electrode recording datasets from the medial entorhinal cortex, prefrontal cortex, and orbitofrontal cortex. Our work provides a pathway to develop mechanistic, multi-scale brain models that generalize across diverse neural architectures, bridging the gap between single-neuron dynamics and macroscale brain activity.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-14 04:00:00 UTC.
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Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry
arXiv:2503.18114v2 Announce Type: replace-cross Abstract: Integrating task-relevant information into neural representations is a fundamental ability of both biological and artificial intelligence systems. Recent theories have categorized learning into two regimes: the rich regime, where neural networks actively learn task-relevant features, and the lazy regime, where networks behave like random feature models. Yet this simple lazy-rich dichotomy overlooks a diverse underlying taxonomy of feature learning, shaped by differences in learning algorithms, network architectures, and data properties. To address this gap, we introduce an analysis framework to study feature learning via the geometry of neural representations. Rather than inspecting individual learned features, we characterize how task-relevant representational manifolds evolve throughout the learning process. We show, in both theoretical and empirical settings, that as networks learn features, task-relevant manifolds untangle, with changes in manifold geometry revealing distinct learning stages and strategies beyond the lazy-rich dichotomy. This framework provides novel insights into feature learning across neuroscience and machine learning, shedding light on structural inductive biases in neural circuits and the mechanisms underlying out-of-distribution generalization.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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NeurOptimisation: The Spiking Way to Evolve
arXiv:2507.08320v1 Announce Type: new Abstract: The increasing energy footprint of artificial intelligence systems urges alternative computational models that are both efficient and scalable. Neuromorphic Computing (NC) addresses this challenge by empowering event-driven algorithms that operate with minimal power requirements through biologically inspired spiking dynamics. We present the NeurOptimiser, a fully spike-based optimisation framework that materialises the neuromorphic-based metaheuristic paradigm through a decentralised NC system. The proposed approach comprises a population of Neuromorphic Heuristic Units (NHUs), each combining spiking neuron dynamics with spike-triggered perturbation heuristics to evolve candidate solutions asynchronously. The NeurOptimiser's coordination arises through native spiking mechanisms that support activity propagation, local information sharing, and global state updates without external orchestration. We implement this framework on Intel's Lava platform, targeting the Loihi 2 chip, and evaluate it on the noiseless BBOB suite up to 40 dimensions. We deploy several NeurOptimisers using different configurations, mainly considering dynamic systems such as linear and Izhikevich models for spiking neural dynamics, and fixed and Differential Evolution mutation rules for spike-triggered heuristics. Although these configurations are implemented as a proof of concept, we document and outline further extensions and improvements to the framework implementation. Results show that the proposed approach exhibits structured population dynamics, consistent convergence, and milliwatt-level power feasibility. They also position spike-native MHs as a viable path toward real-time, low-energy, and decentralised optimisation.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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Enhancing Parameter Control Policies with State Information
arXiv:2507.08368v1 Announce Type: new Abstract: Parameter control and dynamic algorithm configuration study how to dynamically choose suitable configurations of a parametrized algorithm during the optimization process. Despite being an intensively researched topic in evolutionary computation, optimal control policies are known only for very few cases, limiting the development of automated approaches to achieve them. With this work we propose four new benchmarks for which we derive optimal or close-to-optimal control policies. More precisely, we consider the optimization of the \LeadingOnes function via RLS$_{k}$, a local search algorithm allowing for a dynamic choice of the mutation strength $k$. The benchmarks differ in which information the algorithm can exploit to set its parameters and to select offspring. In existing running time results, the exploitable information is typically limited to the quality of the current-best solution. In this work, we consider how additional information about the current state of the algorithm can help to make better choices of parameters, and how these choices affect the performance. Namely, we allow the algorithm to use information about the current \OneMax value, and we find that it allows much better parameter choices, especially in marginal states. Although those states are rarely visited by the algorithm, such policies yield a notable speed-up in terms of expected runtime. This makes the proposed benchmarks a challenging, but promising testing ground for analysis of parameter control methods in rich state spaces and of their ability to find optimal policies by catching the performance improvements yielded by correct parameter choices.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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Rethinking Spatio-Temporal Anomaly Detection: A Vision for Causality-Driven Cybersecurity
arXiv:2507.08177v1 Announce Type: cross Abstract: As cyber-physical systems grow increasingly interconnected and spatially distributed, ensuring their resilience against evolving cyberattacks has become a critical priority. Spatio-Temporal Anomaly detection plays an important role in ensuring system security and operational integrity. However, current data-driven approaches, largely driven by black-box deep learning, face challenges in interpretability, adaptability to distribution shifts, and robustness under evolving system dynamics. In this paper, we advocate for a causal learning perspective to advance anomaly detection in spatially distributed infrastructures that grounds detection in structural cause-effect relationships. We identify and formalize three key directions: causal graph profiling, multi-view fusion, and continual causal graph learning, each offering distinct advantages in uncovering dynamic cause-effect structures across time and space. Drawing on real-world insights from systems such as water treatment infrastructures, we illustrate how causal models provide early warning signals and root cause attribution, addressing the limitations of black-box detectors. Looking ahead, we outline the future research agenda centered on multi-modality, generative AI-driven, and scalable adaptive causal frameworks. Our objective is to lay a new research trajectory toward scalable, adaptive, explainable, and spatially grounded anomaly detection systems. We hope to inspire a paradigm shift in cybersecurity research, promoting causality-driven approaches to address evolving threats in interconnected infrastructures.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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Massively parallel and universal approximation of nonlinear functions using diffractive processors
arXiv:2507.08253v1 Announce Type: cross Abstract: Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront, e.g., via a spatial light modulator (SLM), and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions, all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering multi-variate and complex-valued functions. We also numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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TS-SNN: Temporal Shift Module for Spiking Neural Networks
arXiv:2505.04165v5 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) are increasingly recognized for their biological plausibility and energy efficiency, positioning them as strong alternatives to Artificial Neural Networks (ANNs) in neuromorphic computing applications. SNNs inherently process temporal information by leveraging the precise timing of spikes, but balancing temporal feature utilization with low energy consumption remains a challenge. In this work, we introduce Temporal Shift module for Spiking Neural Networks (TS-SNN), which incorporates a novel Temporal Shift (TS) module to integrate past, present, and future spike features within a single timestep via a simple yet effective shift operation. A residual combination method prevents information loss by integrating shifted and original features. The TS module is lightweight, requiring only one additional learnable parameter, and can be seamlessly integrated into existing architectures with minimal additional computational cost. TS-SNN achieves state-of-the-art performance on benchmarks like CIFAR-10 (96.72\%), CIFAR-100 (80.28\%), and ImageNet (70.61\%) with fewer timesteps, while maintaining low energy consumption. This work marks a significant step forward in developing efficient and accurate SNN architectures.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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Improvement of Spiking Neural Network with Bit Planes and Color Models
arXiv:2410.08229v3 Announce Type: replace-cross Abstract: Spiking neural network (SNN) has emerged as a promising paradigm in computational neuroscience and artificial intelligence, offering advantages such as low energy consumption and small memory footprint. However, their practical adoption is constrained by several challenges, prominently among them being performance optimization. In this study, we present a novel approach to enhance the performance of SNN for images through a new coding method that exploits bit plane representation. Our proposed technique is designed to improve the accuracy of SNN without increasing model size. Also, we investigate the impacts of color models of the proposed coding process. Through extensive experimental validation, we demonstrate the effectiveness of our coding strategy in achieving performance gain across multiple datasets. To the best of our knowledge, this is the first research that considers bit planes and color models in the context of SNN. By leveraging the unique characteristics of bit planes, we hope to unlock new potentials in SNNs performance, potentially paving the way for more efficient and effective SNNs models in future researches and applications.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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On the Principles of ReLU Networks with One Hidden Layer
arXiv:2411.06728v2 Announce Type: replace-cross Abstract: A neural network with one hidden layer or a two-layer network (regardless of the input layer) is the simplest feedforward neural network, whose mechanism may be the basis of more general network architectures. However, even to this type of simple architecture, it is also a ``black box''; that is, it remains unclear how to interpret the mechanism of its solutions obtained by the back-propagation algorithm and how to control the training process through a deterministic way. This paper systematically studies the first problem by constructing universal function-approximation solutions. It is shown that, both theoretically and experimentally, the training solution for the one-dimensional input could be completely understood, and that for a higher-dimensional input can also be well interpreted to some extent. Those results pave the way for thoroughly revealing the black box of two-layer ReLU networks and advance the understanding of deep ReLU networks.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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What should a neuron aim for? Designing local objective functions based on information theory
arXiv:2412.02482v4 Announce Type: replace-cross Abstract: In modern deep neural networks, the learning dynamics of the individual neurons is often obscure, as the networks are trained via global optimization. Conversely, biological systems build on self-organized, local learning, achieving robustness and efficiency with limited global information. We here show how self-organization between individual artificial neurons can be achieved by designing abstract bio-inspired local learning goals. These goals are parameterized using a recent extension of information theory, Partial Information Decomposition (PID), which decomposes the information that a set of information sources holds about an outcome into unique, redundant and synergistic contributions. Our framework enables neurons to locally shape the integration of information from various input classes, i.e. feedforward, feedback, and lateral, by selecting which of the three inputs should contribute uniquely, redundantly or synergistically to the output. This selection is expressed as a weighted sum of PID terms, which, for a given problem, can be directly derived from intuitive reasoning or via numerical optimization, offering a window into understanding task-relevant local information processing. Achieving neuron-level interpretability while enabling strong performance using local learning, our work advances a principled information-theoretic foundation for local learning strategies.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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Bandit-Based Prompt Design Strategy Selection Improves Prompt Optimizers
arXiv:2503.01163v2 Announce Type: replace-cross Abstract: Prompt optimization aims to search for effective prompts that enhance the performance of large language models (LLMs). Although existing prompt optimization methods have discovered effective prompts, they often differ from sophisticated prompts carefully designed by human experts. Prompt design strategies, representing best practices for improving prompt performance, can be key to improving prompt optimization. Recently, a method termed the Autonomous Prompt Engineering Toolbox (APET) has incorporated various prompt design strategies into the prompt optimization process. In APET, the LLM is needed to implicitly select and apply the appropriate strategies because prompt design strategies can have negative effects. This implicit selection may be suboptimal due to the limited optimization capabilities of LLMs. This paper introduces Optimizing Prompts with sTrategy Selection (OPTS), which implements explicit selection mechanisms for prompt design. We propose three mechanisms, including a Thompson sampling-based approach, and integrate them into EvoPrompt, a well-known prompt optimizer. Experiments optimizing prompts for two LLMs, Llama-3-8B-Instruct and GPT-4o mini, were conducted using BIG-Bench Hard. Our results show that the selection of prompt design strategies improves the performance of EvoPrompt, and the Thompson sampling-based mechanism achieves the best overall results. Our experimental code is provided at https://github.com/shiralab/OPTS .in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-14 04:00:00 UTC.
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KIF5A downregulation in spinal muscular atrophy links axonal regeneration defects with ALS
Spinal muscular atrophy (SMA) is a devastating neuromuscular disorder caused by mutations in the Survival Motor Neuron 1 (SMN1) gene, leading to decreased SMN levels and motor neuron dysfunction. SMN-restoring therapies offer clinical benefit, but the downstream molecular consequences of SMN reduction remain incompletely understood. Here, we demonstrate that SMN deficiency results in downregulation of KIF5A in human neurons and in a mouse model of SMA. We provide evidence that reduced SMN levels impair axon regeneration, which is rescued by KIF5A overexpression and that the RNA-binding protein SMN functions to stabilize KIF5A mRNA. These findings provide evidence of a molecular link between SMA and ALS pathophysiology, highlighting KIF5A as a new SMN target. Our findings suggest SMN-independent interventions targeting KIF5A could represent a complementary therapeutic approach for SMA and other motor neuron diseases.in bioRxiv: Neuroscience on 2025-07-13 00:00:00 UTC.
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Impact of sex and glial tau expression on heat shock protein induction in a Drosophila model of tauopathy
Heat shock proteins (Hsps) are central components of the cellular stress response and serve as the first line of defense against protein misfolding and aggregation. Disruption of this proteostasis network is a hallmark of neurodegenerative diseases, including tauopathies -- a class of neurodegenerative diseases characterized by intracellular tau accumulation in neuronal and glial cells. Although specific Hsps are enriched in glial cells, and some have been shown to directly bind tau and influence its aggregation, the broader interplay between Hsps and tau remains poorly understood. In particular, it is unclear whether tau expression affects the heat shock response, and whether this interaction is modulated in a sex-specific fashion. Here, we used a Drosophila model of tauopathy to examine both inducible and constitutive Hsp expression in response to heat stress in the context of glial tau expression. We found that Hsp expression displays sexually dimorphic expression patterns at basal levels and in response to heat stress. Moreover, tau expression in glia disrupts the normal induction of specific heat shock proteins following heat stress. This work provides new insight into how tau interacts with the cellular stress response, and highlights sex-specific differences in Hsp regulation. Understanding these molecular connections is crucial to understanding how the presence of tau in glial cells influences the stress response, and potentially contributes to tauopathy pathogenesis.in bioRxiv: Neuroscience on 2025-07-13 00:00:00 UTC.
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High-Throughput Tracking of Freely Moving Drosophila Reveals Variations in Aggression and Courtship Behaviors
Aggression is a nearly universal behavior used to secure food, territory, and mates across species, including the fruit fly Drosophila melanogaster. In fruit flies, both sexes display aggression through stereotypical motor patterns. This, along with their sophisticated genetic and molecular toolkit, makes Drosophila melanogaster an excellent model for studying aggression. While male- and female-specific aggressive motor programs have been qualitatively described, automated systems for quantifying these behaviors in freely moving flies remain limited in their ability to combine high-resolution analysis with high throughput. Here, we pair a high-resolution, high-throughput imaging system (the Kestrel) with DeepLabCut pose estimation to create a pipeline that tracks multiple freely moving fly pairs and quantifies social dynamics with high fidelity. We validated body-part tracking using published benchmarks. The platform reliably reproduced a known phenotype: heightened female aggression following thermogenetic activation of cholinergic pC1 neurons in female brain. It also detected increased unilateral wing extension, a courtship display inversely related to aggression, between two males upon activating a previously uncharacterized ~40-neuron group in the male brain. Pose-based analysis revealed locomotive differences between experimental and control groups, and subtle, genotype-specific variations in head butts and UWEs. This workflow enables high-throughput screening and mechanistic dissection of social behaviors.in bioRxiv: Neuroscience on 2025-07-13 00:00:00 UTC.
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Autophagy-driven Presynaptic Reorganization as a Molecular Signature of Brain Resilience.
Neural circuits must remain functionally stable while responding flexibly to changing demands, stressors, and aging-related decline. While this balance is thought to be maintained through plasticity programs that integrate molecular, metabolic, and activity-dependent signals to reconfigure synapses structurally and functionally, direct mechanistic models of how such adaptations are orchestrated remain scarce. Here, we show that targeted impairment of autophagy in the Drosophila mushroom body (MB), a key sleep-regulatory and integrative center in the fly brain, triggers a brain-wide remodeling at presynaptic active zones (AZ). Quantitative proteomics revealed a specific upregulation of AZ scaffold proteins (including BRP, RIM, and Unc13A), accompanied by reduced levels of calcium channel subunits and increased Shaker-type potassium channels. These changes occurred largely independent of transcription and highlight a coordinated, excitability-tuning response centered on the AZ. Behaviorally, MB-specific autophagy impairment increased sleep and modestly extended lifespan. These adaptations resembled a previously described resilience program termed PreScale, which promotes restorative sleep homeostasis in response to sleep deprivation and early, still reversible brain aging. Conversely, overexpression of Atg5 in the MB delayed the onset of PreScale. Notably, autophagic disruption confined to MB neurons also caused widespread, non-cell autonomous accumulation of Ref(2)P and ATG8a-positive aggregates across the brain, revealing systemic propagation of proteostatic stress. Together, our findings identify MB autophagy as a key regulator of synaptic architecture and sleep-associated resilience. Such early acting programs may actively preserve circuit function and behavioral output by regulating synaptic plasticity, and define a genetically tractable model for how local stress signals can orchestrate brain-wide adaptation via post-transcriptional synaptic reprogramming.in bioRxiv: Neuroscience on 2025-07-13 00:00:00 UTC.
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Correction to: Large-scale parameters framework with large convolutional kernel for encoding visual fMRI activity information
This is a correction to: Shuxiao Ma, Linyuan Wang, Senbao Hou, Chi Zhang, Bin Yan, Large-scale parameters framework with large convolutional kernel for encoding visual fMRI activity information, Cerebral Cortex, Volume 34, Issue 7, July 2024, bhae257, https://doi.org/10.1093/cercor/bhae257.in Cerebral Cortex on 2025-07-13 00:00:00 UTC.
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Piano Training Induces Dynamic Neuroplasticity of Bimanual Coordination but Not Auditory Processing in Young Adults
Twenty-six weeks of piano training result in adaptations in the activation of the motor but not the auditory networks. The changes in brain activation in the motor system are task-demand dependent, and cannot be fully explained by a single model of brain plasticity.
ABSTRACT
Piano training enables the study of the interplay between the auditory and motor domains in the acquisition of complex skill. Here, we uniquely combine longitudinal and cross-sectional designs to show how the motor and auditory brain systems respond in novice pianists over a 6-month training period. In the auditory domain, we found no differences in brain activation between novice pianists and a passive control group. In a specially designed piano task on an MRI-compatible keyboard, we demonstrate that the time course of neuroplastic reorganization in the cortical and subcortical regions reflects the shift from spatial attention to automated movements, but depends on task demands related to bimanual coordination. Importantly, no single model of brain plasticity can fully explain the observed dynamic time courses of functional changes. Finally, we demonstrate that the increased activation in the dorsal premotor and parietal cortices in novice pianists compared to skilled musicians while performing the motor task vanishes within the first 6 months of training. These results present converging evidence that the dynamic musical-training-related plasticity is highly contextual, and underscore the importance of ecological designs in research on skill acquisition.
in Journal of Neuroscience Research on 2025-07-12 08:04:25 UTC.
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Mapping Postictal Aphasia through Signal Complexity: A Stereo‐Electroencephalography Study
Objective
The postictal period provides an opportunity to investigate the pathophysiology underlying aphasia and recovery following epileptic seizures. This study examines postictal aphasia in stereo-electroencephalography (SEEG)-explored patients to identify brain regions associated with task-specific language deficits using signal complexity analysis.
Methods
We evaluated video-SEEG-recorded focal seizures with and without postictal aphasia in patients with SEEG-confirmed hemispheric language dominance. SEEG traces were analyzed using permutation entropy (PE), with the postictal period quantified by a PE-based metric, the Postictal Alteration Time (PAT). Brain region PAT was correlated with language function recovery (eg, repetition). Electro-clinical recuperation was also assessed within the dorsal-ventral language stream framework. Additionally, a bedside testing battery was developed to evaluate postictal aphasia severity and task-specific deficits.
Results
A total of 322 seizures from 98 patients were analyzed. Seizures with postictal aphasia had longer PAT than those without. Task-specific language recovery correlated with regional PAT (eg, naming – middle temporal gyrus). Moreover, the dorsal stream recovered faster than the ventral stream. Additionally, the Postictal Aphasia Scale (PAS) was developed, evaluating naming, reading, repetition, and comprehension (verbal and written) and automatic speech. Higher PAS scores (indicating milder deficits) correlated with faster regional complexity recovery. At 5 and 10 minutes postictally, PAS revealed a global aphasia pattern, with comprehension deficits gradually resolving. By 15 minutes, aphasia was primarily production-related, particularly affecting naming.
Interpretation
This study provides new insights into the pathophysiology of postictal aphasia and introduces PAS as a tool for assessing postictal aphasia severity and domain-specific deficits, aiding surgical planning and rehabilitation. ANN NEUROL 2025
in Annals of Neurology on 2025-07-12 04:39:44 UTC.
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Sex Differences in Associations of Lewy Body Disease with Alzheimer's Disease and Cognitive Decline
Objective
To investigate how sex and age at menopause influence the interplay between Alzheimer's disease (AD) and Lewy body disease (LBD) neuropathologies, and their associations with cognitive decline.
Methods
We analyzed data from: (1) three Rush Alzheimer's Disease Center cohorts (i.e., the Religious Orders Study, Rush Memory and Aging Project, and Minority Aging Research Study), and (2) the National Alzheimer's Coordinating Center Neuropathology Data Set. Neuropathological evaluation assessed LBD (neocortical/limbic-type vs none) and AD, including neuritic plaques (β-amyloid plaques surrounded by dystrophic neurites) and neurofibrillary tangles. In each dataset, we tested interactive associations between LBD and sex on neuritic plaques, neurofibrillary tangles, and cognitive decline. Additionally, in the Rush dataset, we tested whether age at spontaneous menopause modified the associations of LBD with neuritic plaques, neurofibrillary tangles, and cognitive decline in women.
Results
In the Rush dataset, we included 1,277 women and 579 men. In the National Alzheimer's Coordinating Center dataset, we included 3,283 women and 3,563 men. Across both datasets, men were more likely to have LBD, whereas women showed greater neuritic plaque and neurofibrillary tangle burdens. Sex modified the associations of LBD with neurofibrillary tangles (but not neuritic plaques), whereby LBD was more strongly associated with greater neurofibrillary tangle burden in women than men. Men showed faster LBD-related cognitive decline, whereas women showed faster neurofibrillary tangle-related decline, after adjusting for copathologies (neuritic plaques, neurofibrillary tangles, and LBD, as appropriate). In women, earlier age at menopause exacerbated the associations of LBD with neurofibrillary tangle burden and episodic memory decline.
Interpretation
Sex may influence AD and LBD neuropathologies, highlighting the need for precision approaches to dementia prevention and intervention. ANN NEUROL 2025
in Annals of Neurology on 2025-07-12 04:29:46 UTC.
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Propagating Motor Cortical Dynamics Facilitate Movement Initiation
(Neuron 106, 526–536.e1–e4; May 6, 2020)in Neuron: In press on 2025-07-12 00:00:00 UTC.
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LRRTM2 Functions as a Neurexin Ligand in Promoting Excitatory Synapse Formation
(Neuron 64, 791–798; December 24, 2009)in Neuron: In press on 2025-07-12 00:00:00 UTC.
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Oxidative stress and Kras mutation in Mist1+ cells act in a double-hit manner to drive gastric tumorigenesis
Chen et al. show that Mist1+ cells resist oxidative stress by upregulating Bnip3/Tmed6, with sustained ROS activating YAP to drive cell proliferationwhile synergizing with Kras mutation in a “double-hit” mechanism to promote tumorigenesis.in Cell Reports: Current Issue on 2025-07-12 00:00:00 UTC.
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Multimodal CRISPR screens uncover DDX39B as a global repressor of A-to-I RNA editing
Wei, Li, Lei et al. develop CREDITS and scCREDIT-seq, two complementary CRISPR-based platforms for systematic discovery of A-to-I RNA editing regulators. They identify DDX39B as a global repressor via dsRNA regulation and demonstrate its utility in enhancing RNA editing technologies and anti-HDV therapeutic strategies.in Cell Reports: Current Issue on 2025-07-12 00:00:00 UTC.
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TNF-α-NF-κB activation through pathological α-Synuclein disrupts the BBB and exacerbates axonopathy
Pathological α-Synuclein reveals vascular damage through the endothelial cells’ response. Jeon et al. show that the endothelial TNF-NF-κB pathway is a mechanistic target to mediate synucleinopathy-induced BBB degeneration via GAN deep learning techniques and biological experiments. They demonstrate that regulation of endothelial TNF pathways can modulate synucleinopathy-induced axonal damages.in Cell Reports: Current Issue on 2025-07-12 00:00:00 UTC.
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Interplay between large low-recombining regions and pseudo-overdominance in a plant genome
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61529-z
Pseudo-overdominance describes haplotypic combinations of recessive deleterious alleles complement each other and result in enhanced fitness in heterozygotes compared to homozygotes. Here, the authors show the role of pseudo-overdominance in maintaining genetic diversity in populations of cultivated pearl millet.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Dynamic atomic-scale electron avalanche breakdown in solid dielectrics
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61866-z
Here the authors propose an atomic-scale electron avalanche breakdown model to investigate the dynamic behaviors of excited electrons under extremely high electric fields in various dielectrics ranging from simple oxides to perovskites.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61579-3
Activity recognition in live-cell imaging is laborious. Here, authors present, IVEA, a fully automated AI ImageJ plugin, that efficiently detects and classifies exocytosis events, from synaptic transmission to single-vesicle fusion, across cell types and imaging setups.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Dislocation-assisted electron and hole transport in GaN epitaxial layers
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61510-w
Researchers show that two kinds of crystal dislocations in gallium nitride act as distinct path for electrons and holes. The discovery explains leakage and switching losses in GaN power devices and points to defect-guided design strategies.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Host albumin redirects Candida albicans metabolism to engage an alternative pathogenicity pathway
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61701-5
Candida albicans normally relies on specific pathogenicity mechanisms to cause tissue damage. This study reveals that when sensing host albumin, C. albicans, even avirulent strains, can trigger an alternative pathogenicity pathway via transcriptional and metabolic reprogramming.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-60051-6
Researchers used artificial intelligence to mine global venom proteomes and discovered novel peptides with antimicrobial activity. Several candidates showed efficacy against drug-resistant bacteria in laboratory and animal tests.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Bioinspired Sulfo oxygen bridges optimize interfacial water structure for enhanced hydrogen oxidation and evolution reactions
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61871-2
The hydrogen economy offers a promising route to reduce fossil fuel use, but efficient hydrogen cycling remains challenging. Here, the authors report a bioinspired sulfo-oxygen bridge that optimizes the interfacial water structure to boost hydrogen oxidation and evolution reactions.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Dual path biphasic column for highly selective and ultrafast organic solvent membrane extraction
Nature Communications, Published online: 12 July 2025; doi:10.1038/s41467-025-61777-z
Organic solvent nanofiltration is important for chemical and pharmaceutical industries, though it is challenging to design a membrane for efficient separations. Here, the authors design a column using micron-sized water droplets covered by ion-ligand complexes for efficient separations.in Nature Communications on 2025-07-12 00:00:00 UTC.
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Single-nucleus profiling of the left ventricle of the mouse heart after chronic stress
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05556-x
Single-nucleus profiling of the left ventricle of the mouse heart after chronic stressin Nature scientific data on 2025-07-12 00:00:00 UTC.
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Near-complete reference genome assembly of Hoya carnosa
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05587-4
Near-complete reference genome assembly of Hoya carnosain Nature scientific data on 2025-07-12 00:00:00 UTC.
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Variation of winter wheat phenology dataset in Huang Huai Hai Plain of China from 1981 to 2021
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05368-z
Variation of winter wheat phenology dataset in Huang Huai Hai Plain of China from 1981 to 2021in Nature scientific data on 2025-07-12 00:00:00 UTC.
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A Cross-Species Brain Magnetic Resonance Imaging and Histology Database of Vertebrates
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05540-5
A Cross-Species Brain Magnetic Resonance Imaging and Histology Database of Vertebratesin Nature scientific data on 2025-07-12 00:00:00 UTC.
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A nationwide dataset of stable isotopes in meteoric and terrestrial water across Peru
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05413-x
A nationwide dataset of stable isotopes in meteoric and terrestrial water across Peruin Nature scientific data on 2025-07-12 00:00:00 UTC.
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A Topsoil Salinity Observatory for Arable Lands in Coastal Southwest Bangladesh
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05447-1
A Topsoil Salinity Observatory for Arable Lands in Coastal Southwest Bangladeshin Nature scientific data on 2025-07-12 00:00:00 UTC.
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A combined naturalistic driving, clinical, and neurobehavioral data set for investigating aging and dementia
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05554-z
A combined naturalistic driving, clinical, and neurobehavioral data set for investigating aging and dementiain Nature scientific data on 2025-07-12 00:00:00 UTC.
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SmellyCode++: Multi-Label Dataset for Code Smell Detection
Scientific Data, Published online: 12 July 2025; doi:10.1038/s41597-025-05465-z
SmellyCode++: Multi-Label Dataset for Code Smell Detectionin Nature scientific data on 2025-07-12 00:00:00 UTC.
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Intricate interactions between fine-scale genetic structure, lifestyle, and dietary habits in the Japanese population
Communications Biology, Published online: 12 July 2025; doi:10.1038/s42003-025-08479-w
Advanced genetic clustering analysis reveals the intricate interplay between Japan’s genetic structure and lifestyle and dietary habits, introducing a new framework in genetic epidemiology that integrates both genetic and environmental factors.in Nature communications biology on 2025-07-12 00:00:00 UTC.
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Differences in brain activity during sentence repetition in people who stutter: a combined analysis of four fMRI studies
Our understanding of the neural correlates of developmental stuttering benefits from the use of functional MRI (fMRI) during speech production. Despite two decades of research, however, we have reached little consensus. In the current study, we analysed pooled fMRI data from four different studies that used the same sentence reading task and methodological approach. The combined sample included 56 adolescents and adults who stutter and 53 demographically matched typically fluent controls. A sparse-sampling design was used in each study, in which participants spoke during the silent period between measurements of brain activity. Sentence reading evoked activity in both groups across frontal and temporal regions bilaterally. At statistical thresholds corrected for family-wise error, there were no significant group differences. An uncorrected threshold was applied to explore group differences in areas previously identified in earlier fMRI studies on stuttering. People who stutter (PWS) showed greater activity compared with controls in right frontal pole, right anterior insula extending to frontal operculum, left planum temporale, and midbrain, at the level of red nucleus. In contrast, PWS showed lower activity in left superior frontal sulcus, subgenual medial prefrontal cortex, right anterior temporal lobe, and portions of inferior parietal lobe bilaterally including the angular gyrus on the left. Despite pooling data across multiple studies to achieve a relatively large sample, group differences in regions involved in speech-motor control only emerged at an uncorrected voxel-wise threshold. Some of these findings align with previous fMRI studies, such as increased activity in the right anterior insular cortex.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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ALS-Linked FUS and SOD1 Mutations Elevate MCM2 in Human Motor Neurons
Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterised by progressive motor neuron loss. In typically post-mitotic neurons, abnormal reactivation of cell cycle regulators and DNA replication licensing factors is observed in ALS pathogenesis. Emerging evidence links components of the minichromosome maintenance (MCM) complex, notably MCM2, to replication stress and genomic instability, implying a mechanistic role in ALS pathogenesis. Objective: To determine whether ALS-associated mutations in FUS and SOD1 influence MCM2 expression and localisation in human induced pluripotent stem cell (hiPSC)-derived spinal motor neurons (MNs). Methods: We differentiated isogenic hiPSC lines carrying FUS P525L-GFP and R495QfsX527, a SOD1 mutant line, and matched wild-type controls into spinal MNs ([≥]28 days in vitro). QRT-PCR quantified MCM2 mRNA levels ({Delta}{Delta}Ct method; n=3 biological replicates, technical triplicates). Protein expression was assessed by Western blot densitometry (n=3). Subcellular distribution of MCM2 in FUS mutants was evaluated by immunofluorescence (pilot, N=1; [≥]50 cells quantified). Results: FUS P525L MNs exhibited a modest, non-significant increase in MCM2 mRNA (1.3-fold vs. WT; p=0.1319) but a significant 1.8-fold elevation in MCM2 protein levels (p=0.034). The R495QfsX527 line showed a comparable trend at the transcript level (1.2-fold; p > 0.05) and a 1.6-fold increase in protein (p = 0.041). SOD1 mutant MNs demonstrated a pronounced 2.3-fold MCM2 protein upregulation (p=0.008). Immunofluorescence in FUS mutant MNs revealed no significant nuclear-to-cytoplasmic shift in MCM2 localisation, indicating that elevated MCM2 levels are not driven by subcellular mislocalization. Conclusion: ALS-linked FUS and SOD1 mutations upregulate MCM2 protein in human spinal MNs, suggesting post-transcriptional or stability-driven regulation. The absence of relocalisation in FUS mutants shows that this impact is caused by overexpression rather than mislocalisation. MCM2 may be a biomarker of disease-associated replication stress. Future studies will explore whether MCM2 overexpression exacerbates DNA damage or serves as a compensatory response, clarifying its role in ALS pathogenesis.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Bioenergetic and Protein Processing Imbalances Synergize in iPSC-Dopamine neurons from Individuals with Idiopathic Parkinsons Disease
Patient induced pluripotent stem cell (iPSC)-based models represent a powerful human system to gain insights into the etiopathology of Parkinsons disease (PD). Here, we study several iPSC-derived dopamine neuron (iPSC-DAN) lines, from individuals with idiopathic PD, which is the most common form of PD. Specifically, using iPSC-DAN differentiated for 50-55 days, we performed an in-depth analysis of different bioenergetic pathways and cellular quality control mechanisms in the cells. Our results showed wide ranging impairments in oxidative phosphorylation (OXPHOS), glycolysis and creatine kinase pathways in the PD dopamine (DA) neurons. Specifically, the PD neurons exhibited reduced oxygen consumption rates (OCR) at baseline and after challenges with mitochondrial inhibitors, as well as decreased glycolytic reserves measured via ECAR. This translated to lower OCR:ECAR ratios signifying more reliance on glycolysis vs OXPHOS in the PD cells. Moreover, a mislocalization of creatine kinase B to mitochondria was seen in the PD cells. These energetic changes synergized with the enhanced expression of mitochondrial fission proteins, disrupted mitophagy and oxidative stress. Additionally, the PD neurons contained more monomeric, phosphorylated and aggregated forms of alpha synuclein and displayed reduced viability. Ultrastructural examination through immuno-electron microscopy showed more alpha synuclein gold particles directly associated with mitochondria and packing autophagic vesicles. In essence, these data capture a web of key changes in human iPSC-DAN from idiopathic PD subjects associated with neuronal degeneration.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Individual differences in learning and decision-making: the role of COMT Val158Met polymorphism in transitive inference
Understanding the ordinal relationships between items requires constructing a rank order supporting decision-making between options. This process depends on the ability to learn reciprocal relationships and to select the best option available when making a choice. In such forms of decision-making, the prefrontal cortex (PFC) plays a crucial role in encoding the relative value of alternatives as a decision is formed. Higher-order cognitive abilities are influenced by genetic factors that affect dopamine availability in the PFC, potentially contributing to individual differences. Here, we examined the performance of 83 participants in a transitive inference task (TI), grouped by genotype based on the Val158Met single-nucleotide polymorphism in the Catechol-O-Methyltransferase (COMT) gene. The task included a learning phase in which participants acquired the reciprocal relationships among a set of hierarchically ranked items (A>B>C>D>E>F), followed by a test phase in which they were required to compare all possible item pairs and select the higher-ranked one. While genotype did not significantly influence test-phase performance, it did affect learning efficiency. Specifically, Val homozygotes took a longer learning procedure than both heterozygotes and Met homozygotes during the learning phase. Drift diffusion modelling (DDM) revealed that task performance was explained by the efficiency of evidence accumulation, which was lower in Val homozygotes, accounting for their poorer performance not only during initial learning but also when required to switch to a reversed hierarchical structure (A -
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Cellular basis for cortical network aging in primates
Large-scale brain networks are vulnerable to change with aging and become dysregulated. How these networks are altered at the cellular level remains unclear owing to challenges of bridging data across scales. Here, we integrate in vivo cortical similarity networks with whole brain spatial transcriptomics to characterize the aging brain in a lifespan cohort of macaques (N=64, ages 1-26 years). Deep-layer excitatory neurons and oligodendrocytes emerged as dominant correlates of cortical similarity, linking infragranular cell type composition to macroscopic network structure. Age-related declines in network strength were most pronounced in transmodal networks, including default mode and limbic, and aligned with regions enriched in inhibitory and glial cell types. Parvalbumin-enriched chandelier cells showed the strongest association with regional vulnerability, suggesting a role in network disconnection. Cell-type enrichment was conserved across species, with both human and macaque transcriptomic data aligning with the cortical functional hierarchy. These findings uncover a cellular basis for cortical network aging and highlight the value of imaging-transcriptomic integration across scales.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Multiplicative couplings facilitate rapid learning and information gating in recurrent neural networks
The brain consists of reciprocal connectivity and loops between recurrent neural networks (RNNs) and feedforward neural networks (FNNs). However, how their interactions facilitate learning remains unknown. Here we propose a multiplicative RNN-FNN coupling mechanism and report remarkable computational strengths in learning. The multiplicative interaction imposes a Hebbian-weight amplification onto synaptic-neuronal coupling, enabling context-dependent gating and rapid switching. We demonstrate that multiplicative coupling-driven synaptic plasticity achieves 2-100 folds of speed improvement in supervised, reinforcement and unsupervised learning settings, boosting memory capacity, model robustness and generalization of RNNs. We further demonstrate the efficacy and biological plausibility of multiplicative gating in modeling multiregional circuits, including a prefrontal cortex-mediodorsal thalamus network for context-dependent decision making, a cortico-thalamic-cortical network for working memory and attention, and an entorhinal cortex-hippocampus network for visuospatial navigation and sequence replay. Take together, our results offer insights into multi-plasticity, attractor dynamics and computation of recurrent neural circuits and profound neuroscience-inspired applications.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Perineuronal Net and Inhibitory Synapse Remodeling on Striatal Fast-spiking Interneurons by Chronic Alcohol Exposure
Alcohol use disorder is characterized by persistent drinking in the face of negative consequences. Such inflexible drinking requires dorsolateral striatum fast-spiking interneurons, which comprise roughly 1% of all striatal neurons. How chronic ethanol exposure affects fast-spiking interneuron physiology is poorly understood. We discover in mice that chronic ethanol exposure induced a dramatic loss of GABAergic, but not glutamatergic, synapses onto dorsolateral striatum fast-spiking interneuron somata and proximal dendrites where perineuronal nets, a subdivision of the extracellular matrix, are enriched. We found that chronic ethanol exposure degraded these perineuronal nets and that enzymatically degrading perineuronal nets similarly reduced GABAergic transmission onto dorsolateral striatum fast-spiking interneurons. Modeling the effect of alcohol, we find that silencing extrinsic GABAergic projections to the dorsolateral striatum increased voluntary ethanol consumption. Taken together, these data suggest chronic alcohol exposure remodels perineuronal nets and inhibitory synapses on fast-spiking interneurons to facilitate alcohol drinking.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Spatially resolved mapping of monoacylglycerol lipase activity in the brain
Visualizing signaling systems in the brain with high spatial resolution is critical to understand brain function and to develop therapeutics. Especially enzymes are often regulated on the post-translational level, resulting in a disconnect between protein levels and activity. Conventional antibody-based methods have limitations, including potential cross reactivity and the inability of antibodies to discriminate between active and inactive enzyme states. Monoacylglycerol lipase (MAGL), an enzyme degrading the neuroprotective endocannabinoid 2-arachidonoylglycerol, is the target of inhibitors currently in clinical trials for the treatment of several neurological disorders. To support translational and (pre)clinical studies and fully realize the therapeutic opportunities of MAGL inhibitors, it is essential to map the spatial distribution of MAGL activity throughout the brain in both health and disease. Here, we introduce selective fluorescent activity-based probes for MAGL enabling direct visualization of its enzymatic activity in lysates, cultured cells and tissue sections. We show that oxidative stress, which inactivates MAGL through the oxidation of regulatory cysteines, reduces probe labeling , thereby validating the probes activity-dependence. Extending this approach, we developed an activity-based histology protocol to visualize MAGL activity in fresh-frozen mouse and human brain tissues. This approach revealed robust MAGL activity in astrocytes and presynaptic terminals within the mouse hippocampus, and further allows detection of MAGL activity in the human cerebral cortex. Collectively, these findings establish selective activity-based probes as powerful tools mapping MAGL activity with high spatial resolution across mammalian brain tissue.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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The Functional Epididymal Amyloid Cystatin-Related Epididymal Spermatogenic (CRES) is a Component of the Mammalian Brain Extracellular Matrix
CRES is the defining member of a reproductive subgroup of family 2 cystatins of cysteine protease inhibitors. We previously showed that CRES and other subgroup members are part of a highly plastic amyloid-containing extracellular matrix (ECM) with host defense functions in the mouse epididymal lumen. Based on parallels between the epididymis and the brain, we hypothesized that CRES and CRES amyloids might also function within the brain including the ECM. Here we show that CRES is produced by hippocampal neurons and astrocytes in the male and female mouse and human brain. Further, approximately 50% of hippocampal astrocytes from aged mice, like the aged human donor samples, had significantly reduced levels of CRES compared to younger mice, suggesting an age-related decline in CRES could contribute to altered brain function. Immunofluorescence experiments showed CRES colocalized with the ECM markers phosphacan and wisteria floribunda agglutinin indicating that CRES is part of the ECM. CRES monomer and high molecular weight SDS-resistant forms were found in insoluble fractions of the hippocampus, cortex, cerebellum, and midbrain and bound to the protein aggregation disease (PAD) ligand, which preferentially binds amyloids but not protein monomers, suggesting a population of CRES exists in the brain as an amyloid structure. Collectively, our studies demonstrate that CRES/CRES amyloid is present in the mammalian brain and may contribute to ECM structure and function.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Dynamic Modulation of Beta-Band Oscillations in the LGN and Their Role in Visual Processing
Neuronal oscillations are a ubiquitous feature of thalamocortical networks and can be dynamically modulated across processing states, enabling thalamocortical communication to flexibly adapt to varying environmental and behavioral demands. The lateral geniculate nucleus (LGN), like all thalamic nuclei, engages in reciprocal synaptic interactions with the cortex, relaying retinal information to and receiving feedback input from primary visual cortex (V1). While retinal excitation is the primary driver of LGN activity, retinal synapses represent a minority of the total synaptic input onto LGN neurons, allowing for both retinogeniculate and geniculocortical signals to be influenced by nonretinal sources. To gain a holistic view of network processing in the geniculocortical pathway, we performed simultaneous extracellular recordings from the LGN and V1 of behaving macaque monkeys, measuring local field potentials (LFPs) and spiking activity. These recordings revealed prominent beta-band oscillations coherent between the LGN and V1 that influenced spike timing in the LGN and were statistically consistent with a feedforward process from the LGN to V1. These thalamocortical oscillations were suppressed by visual stimulation, spatial attention, and behavioral arousal, strongly suggesting that these oscillations are not a feature of active visual processing. Instead, they appear analogous to occipital lobe, alpha oscillations recorded in humans and may represent a signature of signal suppression that occurs during periods of low engagement or active distractor suppression.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Loss of FMRP in microglia promotes degeneration of parvalbumin neurons and audiogenic seizures via progranulin insufficiency
Fragile X syndrome (FXS) results from loss of FMR1-encoded FMRP and is associated with reduced density of parvalbumin (PV) neurons; however, the mechanism underlying this abnormality remains unknown. Here we report that microglial FMRP regulates PV neuron density through lysosomal function. Mice with Fmr1 deletion in microglia exhibited audiogenic seizures (AGS) and decreased PV neuron density in the cortex and AGS-associated inferior colliculus (IC). FMRP increased the expression of lysosomal genes in microglia, including the progranulin-encoding Grn gene. Its loss in microglia led to impaired lysosomal function and increased apoptosis in microglia and PV neurons. Furthermore, PV neuron density in the IC was reduced similarly in male Grn+/-, Fmr1-/y, and Grn+/-;Fmr1-/y mice, and AAV8-mediated overexpression of progranulin rescued AGS and PV neuron loss in Fmr1-/y mice. This indicates that progranulin insufficiency is a determinant for PV neuron loss in FXS and elevating progranulin is a therapeutic strategy for FXS.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Retinal waves reveal axial biases in modular patterns of cortical activity that predict future orientation preferences
Spontaneous activity before sensory onset is thought to guide the formation of functional neural circuits. In visual cortex, spontaneous activity prior to experience exhibits modular patterns that resemble future visually evoked orientation selective responses. However, the factors at this early stage that build the initial network interactions that support the orientation tuning of modular responses at eye opening remain unknown. Here we provide the first evidence that retinal waves could play an important role by shaping the modular biases in patterns of intracortical connectivity and lay the foundation for orientation selective responses. We demonstrate that slow propagating waves in developing cortex that are dependent on retinal activity recruit specific modular patterns during their movement across the cortical surface, resulting in strikingly elongated patterns of modular coactivity that predict visually-evoked orientation responses at eye opening. Thus axial biases in spontaneous patterns of co-activity are present before the onset of visual experience and could serve as the seed for the developmental emergence of modular orientation representations.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Characterization of astrocyte density in the Pitt-Hopkins Syndrome mouse model of ASD
Transcription factor 4 (TCF4) is a proneural basic helix-loop-helix transcription factor that plays a critical role in brain development and is associated with a variety of psychiatric disorders including autism spectrum disorder (ASD), major depressive disorder, and schizophrenia. Autosomal dominant mutations in TCF4 result in a profound neurodevelopmental disorder called Pitt-Hopkins Syndrome (PTHS). Germline TCF4 loss-of-function (LOF) studies using human and mouse models have identified dysregulation in neural cell proliferation, genesis, and specification which lead to disruption in neuronal, astroglial and oligodendroglial lineages. In this study, we focused on the role of TCF4 in the genesis of the astrocyte lineage, specifically in the context of modeling PTHS. We show that germline heterozygous mutations in Tcf4 had no effect on the expression of astrocyte marker genes in primary astrocyte cultures and whole brain lysates. Immunohistochemical (IHC) analysis of pan- and subclass-specific astrocyte markers showed Tcf4 mutation had no effect on the proportions of astrocytes in the dorsal cortex and corpus callosum. Lastly, we tracked ventrally-derived astrocytes using an Nkx2.1 reporter mouse and observed that germline Tcf4 LOF did not result in misallocation of ventrally-derived astrocytes into the dorsal cortex, a phenotype previously observed when both Tcf4 alleles were conditionally deleted in the Nkx2.1 lineage. These data indicate that germline heterozygous TCF4 LOF, which models PTHS, does not appear to affect the astrocyte lineage at the cell population level.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Norepinephrine acts through radial astrocytes in the developing optic tectum to enhance threat detection and escape behavior
The ability to switch behavioral states is essential for animals to adapt and survive. We investigated how norepinephrine (NE) activation of radial astrocytes alters visual processing in the optic tectum (OT) of developing Xenopus laevis. NE activates calcium transients in radial astrocytes through 1-adrenergic receptors. NE and radial astrocyte activation shifted OT response selectivity to preferentially respond to looming stimuli, associated with predation threat. NE-mediated astrocytic release of ATP/adenosine reduced excitatory transmission by retinal ganglion cell axons, without affecting inhibitory transmission in the OT. Blockade of adenosine receptors prevented both decreased neurotransmission and the selectivity shift. Chemogenetic activation of tectal radial astrocytes reproduced NE's effects and enhanced behavioral detection of looming stimuli in freely swimming animals. NE signaling via radial astrocytes enhances network signal-to-noise for detecting threatening stimuli, with important implications for sensory processing and behavior.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Somatosensory Realignment Following Single and Dual Force Field Adaptation
Evidence that adaptive motor learning coincides with a realignment of somatosensory perception has led to hypotheses that a shared mechanism underlies both processes, predicting similar properties. However, studies of somatosensory realignment with visuomotor adaptation have shown mixed support, possibly due to a confounding coactivation of sensory prediction errors and multisensory integration. While the former is thought to drive adaptation, both processes may contribute to somatosensory realignment. Here, we examined somatosensory realignment following force field adaptation, which is not confounded by multisensory integration. Across two experiments, we tested whether somatosensory realignment mimics three properties of adaptation in this paradigm. Our first experiment examined the specificity of somatosensory realignment to the perceptions of movement or static position and the generalization to reach directions adjacent to the one performed during the adaptation task. The results showed that force field adaptation coincided with a selective realignment of somatosensory perception of movement in the direction of the perturbing force that did not correlate with the magnitude of adaptation or generalize beyond the reach direction of the adaptation task. In a second experiment, we tested whether context-dependent dual adaptation to opposing force field perturbations coincides with a context-dependent dual realignment of somatosensory perception. The results showed no evidence of context-dependent somatosensory realignment after dual adaptation. Our results indicate that somatosensory realignment does not show the same properties as force field adaptation; however, it displays some coherence with the nature of the perturbation. Overall, our data suggest that somatosensory realignment and adaptation likely stem from distinct mechanisms.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Domain-General Brain Networks Support Language Development
Understanding the neural basis of verbal intelligence across development requires disentangling the contributions of domain-general and language-selective brain systems. Although language is often considered a domain-specific function, complex language tasks also engage domain-general networks, such as the Default-Mode (DM) and Multiple-Demand (MD) systems. Yet how these systems contribute to the maturation of verbal competence remains poorly understood. Here, we examined this question using gray matter volume measures in an accelerated longitudinal dataset of children and adolescents from Beijing (N = 170), using the Verbal Comprehension Index (VCI) from the Wechsler Intelligence Scale as a benchmark for verbal abilities. We observed that individual differences in VCI were more strongly associated with structural maturation of domain general networks (DM and MD) than with the language-selective network, and that these effects varied with age. Targeted validation in an independent cohort from Chongqing (N = 150) confirmed significant contributions of domain-general networks in adolescence (13-15 years), highlighting the robustness of these developmental effects. These findings suggest that domain-general cortical systems play a critical and previously underappreciated role in the emergence of verbal intelligence during adolescence, with implications for understanding how large-scale brain networks support the development of abstract verbal reasoning.in bioRxiv: Neuroscience on 2025-07-12 00:00:00 UTC.
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Electroencephalography-based diagnosis of schizophrenia using machine learning
AbstractSchizophrenia is a mental disorder with a high social burden. Identification of quantitative biomarkers has the potential to facilitate the diagnosis process. This study aims to explore a routine to gain such biomarkers using quantitative analysis of electroencephalography (EEG) data. Previous studies suggest that EEG data can be used to differentiate schizophrenia patients from healthy subjects. Various EEG features were used for such diagnostics using machine learning (ML) algorithms, but selecting the optimal EEG features and the classifiers is still insufficient. We propose an automatic selection of ML parameters using the Waikato Environment for Knowledge Analysis software. Using Waikato Environment for Knowledge Analysis’s “Supervised Attribute Selection” tool, we identified attributes that allow the identification of schizophrenia patients with a high accuracy of 93%. The attributes identified were EEG signals enriched for alpha and gamma frequencies from specific brain areas (frontal right, central, parietal, and occipital). This proposed strategy can effectively identify schizophrenia patients with high accuracy. It could be used as an ML tool to support diagnosis and potentially provide insights into the underlying disease mechanism of schizophrenia.in Cerebral Cortex on 2025-07-12 00:00:00 UTC.
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Altered resting-state brain entropy by repetitive transcranial magnetic stimulation across the human cortex
AbstractRepetitive transcranial magnetic stimulation (rTMS) is a non-invasive neuromodulation technique used to treat neuropsychiatric disorders. Despite its efficacy, its neuro-mechanisms remain unclear. Brain entropy (BEN), a measure of the irregularity and complexity of brain activity, has been shown to reflect the effects of high-frequency rTMS (HF-rTMS). However, it remains unknown whether BEN is sensitive to low-frequency rTMS (LF-rTMS), as well as to target-specific effects.Eighteen healthy adult participants underwent continuous theta burst stimulation (cTBS) over the left dorsolateral prefrontal cortex (L-DLPFC), and 23 healthy adult participants underwent LF-rTMS targeting the L-DLPFC, left temporoparietal junction (L-TPJ), and left occipital cortex (L-OCC). Magnetic resonance imaging scans were performed pre- and post-stimulation, and BEN maps were calculated from the preprocessed functional images.Results showed that cTBS over L-DLPFC increased BEN in the medial orbitofrontal cortex (MOFC), while L-DLPFC LF-rTMS increased BEN in the MOFC, subgenual anterior cingulate cortex, and putamen. LF-rTMS at the L-TPJ increased BEN in the right TPJ, while LF-rTMS at the L-OCC decreased BEN in the posterior cingulate cortex. These findings demonstrate BEN remains sensitive to LF-rTMS and exhibits target-specific effects. Furthermore, this work advances BEN as a promising biomarker for rTMS effects beyond motor cortex paradigms.in Cerebral Cortex on 2025-07-12 00:00:00 UTC.
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Ten simple rules for success as a trainee-led outreach organization in computational biology education
by Jennifer Blanc, Margaret C. Steiner, Lauren E. Blake, Elizabeth Gibbons, Mariadaria K. Ianni-Ravn, Roxroy C. Morgan, Suzanna Parkinson, Christian Porras, Ethan Zhong
in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Ten simple rules for developing a training program
by Leanna B. Blevins, Amy M. Harrigan, Kevin A. Janes, Jason A. Papin
in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Perceptual clustering in auditory streaming
by Nathanael Larigaldie, Tim Yates, Ulrik R. Beierholm
Perception is dependent on the ability to separate stimuli from different objects and causes in order to perform inference and further processing. We have models of how the human brain can perform such causal inference for simple binary stimuli (e.g., auditory and visual), but the complexity of the models increases dramatically with more than two stimuli. To characterize human perception with more complex stimuli, we developed a Bayesian inference model that takes into account a potentially unlimited number of stimulus sources: it is general enough to factor in any discrete sequential cues from any modality. Because the model employs a non-parametric prior, increased signal complexity does not necessitate the addition of more parameters. The model not only predicts the number of possible sources, but also specifies the source with which each signal is associated. As a test case, we demonstrate that such a model can explain several phenomena in the auditory stream perception literature, that it provides an excellent fit to experimental data, and that it makes novel predictions that we experimentally confirm. These findings have implications not just for human auditory temporal perception, but for a wide range of perceptual phenomena across unisensory and multisensory stimuli.in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Time-series modeling of epidemics in complex populations: Detecting changes in incidence volatility over time
by Rachael Aber, Yanming Di, Benjamin D. Dalziel
Trends in infectious disease incidence provide important information about epidemic dynamics and prospects for control. Higher-frequency variation around incidence trends can shed light on the processes driving epidemics in complex populations, as transmission heterogeneity, shifting landscapes of susceptibility, and fluctuations in reporting can impact the volatility of observed case counts. However, measures of temporal volatility in incidence, and how volatility changes over time, are often overlooked in population-level analyses of incidence data, which typically focus on moving averages. Here we present a statistical framework to quantify temporal changes in incidence dispersion and to detect rapid shifts in the dispersion parameter, which may signal new epidemic phases. We apply the method to COVID-19 incidence data in 144 United States (US) counties from January 1st, 2020 to March 23rd, 2023. Theory predicts that dispersion should be inversely proportional to incidence, however our method reveals pronounced temporal trends in dispersion that are not explained by incidence alone, but which are replicated across counties. In particular, dispersion increased around the major surge in cases in 2022, and highly overdispersed patterns became more frequent later in the time series. These increases potentially indicate transmission heterogeneity, changes in the susceptibility landscape, or that there were changes in reporting. Shifts in dispersion can also indicate shifts in epidemic phase, so our method provides a way for public health officials to anticipate and manage changes in epidemic regime and the drivers of transmission.in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Neural network approaches, including use of topological data analysis, enhance classification of human induced pluripotent stem cell colonies by treatment condition
by Alexander Ruys de Perez, Paul E. Anderson, Elena S. Dimitrova, Melissa L. Kemp
Understanding how stem cells organize to form early tissue layers remains an important open question in developmental biology. Helpful in understanding this process are biomarkers or features that signal when a significant transition or decision occurs. We show such features from the spatial layout of the cells in a colony are sufficient to train neural networks to classify stem cell colonies according to differentiation protocol treatments each colony has received. We use topological data analysis to derive input information about the cells’ positions to a four-layer feedforward neural network. We find that despite the simplicity of this approach, such a network has performance similar to the traditional image classifier ResNet. We also find that network performance may reveal the time window during which differentiation occurs across multiple conditions.in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Allocating limited surveillance effort for outbreak detection of endemic foot and mouth disease
by Ariel Greiner, José L. Herrera-Diestra, Michael Tildesley, Katriona Shea, Matthew Ferrari
Foot and Mouth Disease (FMD) affects cloven-hoofed animals globally and has become a major economic burden for many countries around the world. Countries that have had recent FMD outbreaks are prohibited from exporting most meat products; this has major economic consequences for farmers in those countries, particularly farmers that experience outbreaks or are near outbreaks. Reducing the number of FMD outbreaks in countries where the disease is endemic is an important challenge that could drastically improve the livelihoods of millions of people. As a result, significant effort is expended on surveillance; but there is a concern that uninformative surveillance strategies may waste resources that could be better used on control management. Rapid detection through sentinel surveillance may be a useful tool to reduce the scale and burden of outbreaks. In this study, we use an extensive outbreak and cattle shipment network dataset from the Republic of Türkiye to retrospectively test three possible strategies for sentinel surveillance allocation in countries with endemic FMD and minimal existing FMD surveillance infrastructure that differ in their data requirements: ranging from low to high data needs, we allocate limited surveillance to [1] farms that frequently send and receive shipments of animals (Network Connectivity), [2] farms near other farms with past outbreaks (Spatial Proximity) and [3] farms that receive many shipments from other farms with past outbreaks (Network Proximity). We determine that all of these surveillance methods find a similar number of outbreaks – 2-4.5 times more outbreaks than were detected by surveying farms at random. On average across surveillance efforts, the Network Proximity and Network Connectivity methods each find a similar number of outbreaks and the Spatial Proximity method always finds the fewest outbreaks. Since the Network Proximity method does not outperform the other methods, these results indicate that incorporating both cattle shipment data and outbreak data provides only marginal benefit over the less data-intensive surveillance allocation methods for this objective. We also find that these methods all find more outbreaks when outbreaks are rare. This is encouraging, as early detection is critical for outbreak management. Overall, since the Spatial Proximity and Network Connectivity methods find a similar proportion of outbreaks, and are less data-intensive than the Network Proximity method, countries with endemic FMD whose resources are constrained could prioritize allocating sentinels based on whichever of those two methods requires less additional data collection.in PLoS Computational Biology on 2025-07-11 14:00:00 UTC.
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Structural elucidation of the haptoglobin–hemoglobin clearance mechanism by macrophage scavenger receptor CD163
by Ching-Shin Huang, Hui Wang, Joshua B. R. White, Oksana Degtjarik, Cindy Huynh, Kristoffer Brannstrom, Mark T. Horn, Stephen P. Muench, William S. Somers, Javier Chaparro-Riggers, Laura Lin, Lidia Mosyak
Intravascular hemolysis releases hemoglobin into the bloodstream, which can damage vascular and renal tissues due to its oxidative nature. Circulating haptoglobin acts as a primary defense by binding to free hemoglobin, forming a haptoglobin–hemoglobin (HpHb) complex that is then recognized and cleared by the CD163 scavenger receptor on macrophages. While the function and structure of HpHb complex are mostly well-defined, the molecular mechanism underlying its interaction with CD163 remains unclear. Here we report the cryo-electron microscopy structures of human CD163 in its unliganded state and in its complex with HpHb. These structures reveal that CD163 functions as a trimer, forming a composite binding site at its center for one protomer of the dimeric HpHb, resulting in a 3:1 binding stoichiometry. In the unliganded state, CD163 can also form a trimer, but in an autoinhibitory configuration that occludes the ligand binding site. Widespread electrostatic interactions mediated by calcium ions are pivotal in both pre-ligand and ligand-bound receptor assemblies. This calcium-dependent mechanism enables CD163/HpHb complexes to assemble and, once internalized, disassemble into individual components upon reaching the endosome, where low calcium and lower pH conditions prevail. Collectively, this study elucidates the molecular mechanism by which CD163-mediated endocytosis efficiently clears different isoforms of HpHb.in PLoS Biology on 2025-07-11 14:00:00 UTC.
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H3K4me2 marks the enhancer: Enhancer logic in the zebrafish embryo
by Noura Maziak, Juan M. Vaquerizas
At a key point in development, the embryo activates its genome: a shift that is largely coordinated by maternally derived factors. A new study in PLOS Biology identifies H3K4me2-marked enhancers in zebrafish that function independently and mirror the gamete state. At a key point in development, the embryo activates its genome: a shift that is largely coordinated by maternally derived factors. A new study in PLOS Biology identifies H3K4me2-marked enhancers in zebrafish that function independently and mirror the gamete state.in PLoS Biology on 2025-07-11 14:00:00 UTC.
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Neural activity patterns stabilize during wakefulness and conscious experience
by Simon van Gaal
Several neuronal markers have been proposed to differentiate the global brain states that underly states of consciousness. A new pre-registered study in PLOS Biology compares neural markers of loss of consciousness in flies when awake, asleep, and anesthetized. Which neuronal markers can differentiate global brain states that underly states of consciousness? This Primer explores the findings of a new study published in PLOS Biology, which compares neural markers of loss of consciousness in flies when awake, asleep and anesthetized.in PLoS Biology on 2025-07-11 14:00:00 UTC.
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Cilia in the brain display region-dependent oscillations of length and orientation
by Roudabeh Vakil Monfared, Sherif Abdelkarim, Pieter Derdeyn, Kiki Chen, Hanting Wu, Kenneth Leong, Tiffany Chang, Justine Lee, Sara Versales, Surya M. Nauli, Kevin Beier, Pierre Baldi, Amal Alachkar
In this study, we conducted high-throughput spatiotemporal analysis of primary cilia length and orientation across 22 mouse brain regions. We developed automated image analysis algorithms, which enabled us to examine over 10 million individual cilia, generating the largest spatiotemporal atlas of cilia. We found that cilia length and orientation display substantial variations across different brain regions and exhibit fluctuations over a 24-h period, with region-specific peaks during light-dark phases. Our analysis revealed unique orientation patterns of cilia, suggesting that cilia orientation within the brain is not random but follows specific patterns. Using BioCycle, we identified rhythmic fluctuations in cilia length across five brain regions: the nucleus accumbens core, somatosensory cortex, and the dorsomedial, ventromedial, and arcuate hypothalamic nuclei. Our findings present novel insights into the brain cilia dynamics, and highlight the need for further investigation into cilia’s role in the brain’s response to environmental changes and regulation of oscillatory physiological processes.in PLoS Biology on 2025-07-11 14:00:00 UTC.
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Heavy Metal Contamination: Sources, Health Impacts, and Sustainable Mitigation Strategies with Insights from Nigerian Case Studies [version 4; peer review: 3 approved with reservations]
Heavy metal contamination has gradually become a highly significant global issue due to its continual existence in the environment and bioaccumulation in the ecosystems, posing deleterious risks to human health. The major objectives of the review is to investigate the sources, pathways, and toxicological impacts of heavy metals such as cadmium, lead, mercury, and arsenic, elucidating their health consequences and plausible mitigation strategies. Furthermore, the review explores the dual origins of heavy metal contamination; natural geological processes and anthropogenic activities such as industrial emissions, mining, and agricultural practices. These heavy metals seep into soil, water, and food chains, leading to bioaccumulation, bio-magnification and causing significant health risks, including cardiovascular diseases, neurological disorders, and reproductive toxicity. Additionally, the addition of indigenous case studies from Nigeria, such as lead poisoning in Zamfara State and contamination in the Great Kwa River of Cross Rivers State underscores the disproportionate impact of heavy metal pollution in developing nations. The key findings from this review via the selected case studies revealed the socio-economic and environmental dimensions of the issue, providing a contextual understanding of region-specific vulnerabilities and health outcomes. To address these problems, the review evaluates already existing mitigation strategies, including chelation therapy and phytoremediation, while proposing sustainable, cost-effective solutions for reducing exposure and mitigating impacts. It emphasizes the importance of integrative approaches involving policy, community engagement, and technological innovations to fight heavy metal contamination effectively. In conclusion, this review contributes to the understanding of heavy metal toxicity, giving and showcasing very much important insights into the sources and health implications of contamination. By integrating theoretical perspectives with practical solutions, this review provides a robust framework for informing policy makers and advancing sustainable environmental management practices.in F1000Research on 2025-07-11 13:02:09 UTC.
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Digital literacy in the use of digital platforms in public administration in the Lambayeque Region [version 1; peer review: awaiting peer review]
Background Nowadays, digital literacy plays a key role in improving public management, especially in the most vulnerable communities. In this regard, we aim to understand how the knowledge and use of digital tools impact the work life of the vulnerable population in Lambayeque, facilitating their access to digital platforms and, in turn, improving their interaction with public services. The research aimed to analyze how the implementation of digital literacy improved the use of digital platforms in public administration among the vulnerable working population of the Lambayeque Region during the year 2023. Methods To achieve this, an applied approach with a descriptive-propositional scope was adopted. Additionally, a non-experimental and cross-sectional design was employed, considering a population of 1,356 inhabitants of Lambayeque, from which 673 were selected using a statistical formula. Results The results evidenced a positive relationship between digital literacy and the use of digital platforms. It was observed that the majority of respondents had a high level of digital literacy, which favored efficiency in the use of these tools within public administration. However, it was also identified that a sector of the population still presented a medium level, highlighting the need to strengthen the development of digital skills. Furthermore, the findings coincided with previous research that emphasized the importance of digital literacy in various sectors, such as commerce, small and medium enterprises, and financial inclusion. Conclusions Consequently, it was concluded that training in digital literacy was key to the adoption of new technologies and the utilization of digital services, thereby promoting a more active and empowered citizenship in the digital environment.in F1000Research on 2025-07-11 13:00:34 UTC.
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Digital Leadership in Education: A Bibliometric Analysis of Research Trends from 2010 to 2024 [version 1; peer review: awaiting peer review]
The Fourth Industrial Revolution (4IR), the COVID-19 pandemic, and the rapidly digitising educational system due to advances in artificial intelligence (AI) have made a change in leadership imperative. A key framework for improving organisational effectiveness in handling these changes is digital leadership. It combines technological competencies with traditional leadership. Even with increased scholarly interest, there remains a gap in the thorough analysis of the field’s intellectual framework, thematic evolution, and collaborative dynamics. This study addresses this gap by conducting a bibliometric analysis of digital leadership research in education from 2010 to 2024, employing RStudio to map publication trends, influential sources, author productivity, conceptual themes, and social structures. Data from 338 Scopus-indexed documents reveal a significant rise in publications post-2010, peaking in 2023, with core journals such as Education and Information Technologies and Cogent Education dominating the field. Prolific authors like Karakose T., Altinay F., and Z. underscore the centrality of collaborative research, while thematic mapping identifies key clusters: digital competence, virtual leadership, and institutional innovation. Thematic evolution highlights a post-pandemic pivot toward digital transformation and AI integration, though niche areas like K-12 digital leadership remain underdeveloped. Social network analysis reveals fragmented yet growing global collaborations, with the United States, Turkey, and the United Kingdom as dominant hubs, while disparities persist in Global South participation. The study’s implications emphasize the need for interdisciplinary research, equitable global partnerships, and policy frameworks that prioritize digital leadership training for educators. Practitioners are encouraged to implement adaptive strategies to leverage emerging technologies, ensuring sustainable learning outcomes. This analysis provides a foundation for future research and practice in digital leadership by delineating the field’s conceptual and social networks, thereby bridging the divides between theory, policy, and institutional practice.in F1000Research on 2025-07-11 12:59:15 UTC.
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Confirmatory Factor Analysis and Propensity to Cheat Scale Validation in the Ethiopian Public Higher Education Institutions [version 3; peer review: 2 approved with reservations, 2 not approved]
Background This study aimed to validate a comprehensive and psychometrically sound instrument—the Propensity to Cheat Scale (PCS)—designed to measure undergraduate students’ propensity toward academic dishonesty in Ethiopian universities. Based on Ajzen’s Theory of Planned Behavior, the PCS was validated to assess students’ attitudes, subjective norms, and perceived behavioral control related to various forms of cheating, including cheating on tests and examinations, cheating on assignments, cheating on research work (plagiarism), and theft and mutilation of library materials. Methods The present study employed an explanatory research design using a questionnaire based on the Propensity to Cheat Scale (PCS). The questionnaire was administered to 500 university students (male = 367 [73.4%]; female = 133 [26.6%]) selected from three Ethiopian public universities between November and January 2022. In order to measure the underlying variables of propensity towards cheating, a factor model is developed using exploratory factor analysis (EFA), and confirmatory factor analysis was employed to validate the students’ perceived PTC. The internal consistency of the PTC scale was assessed using reliability analysis, and validity evaluations were conducted to confirm the scale’s discriminant and convergent validity. Results Confirmatory factor analysis (CFA) results revealed a good fit to the data, and the internal consistency of the PCS was found to be strong, providing a reliable measure of students’ propensity for cheating. Validity evaluations, including discriminant validity and convergent validity, confirmed the validity of the scale. The average variance extracted (AVE) and composite reliability values also supported the scale’s convergent validity. The multidimensional concept of the PTC was supported by a four-factor solution consisting of 26 reliable and valid items. Conclusion The findings of the study demonstrate that the scale has also provided sufficient evidence of convergent and discriminant validity. By establishing discriminant and convergent validity, as well as reliability, through different validation procedures, the study has provided strong evidence for the effectiveness of the PCS as an instrument for determining whether university students are likely to engage in cheating behavior.in F1000Research on 2025-07-11 12:49:49 UTC.
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From simple lab tasks to the virtual court: Bayesian integration in tennis
Journal of Neurophysiology, Volume 134, Issue 1, Page 303-313, July 2025.
in Journal of Neurophysiology on 2025-07-11 12:22:20 UTC.
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Muscle function and electromyography: (almost) 70 years since Doty and Bosma (1956)
Journal of Neurophysiology, Volume 134, Issue 1, Page 337-346, July 2025.
in Journal of Neurophysiology on 2025-07-11 12:22:18 UTC.
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Unified measures quantifying intensity and similarity of pain and somatosensory percepts
Journal of Neurophysiology, Volume 134, Issue 1, Page 292-302, July 2025.
in Journal of Neurophysiology on 2025-07-11 12:22:17 UTC.
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Complementary functional profiles of mismatch responses mediated by adaptation and deviance detection point to two distinct auditory short-term memory systems
Journal of Neurophysiology, Volume 134, Issue 1, Page 314-336, July 2025.
in Journal of Neurophysiology on 2025-07-11 12:22:15 UTC.
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Patients perspectives on an interprofessional care model in healthcare for patients with immune-mediated inflammatory diseases: A qualitative study [version 1; peer review: awaiting peer review]
Background Managing immune-mediated inflammatory diseases(IMIDs) is complex for patients and healthcare professionals. Research indicates healthcare fragmentation due to mono-disciplinary approaches that address numerous comorbid conditions. While acknowledged as critical to IMIDs care, the joint coordination and management of somatic disorders, psychological disorders, and socioeconomic factors receive limited attention in current clinical practices. Research calls for more interprofessional approaches addressing IMIDs patients’ needs. Therefore, this study explored patients’ experiences participating in an interprofessional patient-centred complex IMIDs intervention to inform future development. Materials & Methods The study was based on semi-structured interviews with 11 participants. We used Thematic Analysis to analyse data. Results We identified three overarching themes: Bringing well-known actors into a new concept, Expanding interprofessional care, and Bridging interprofessional care. From the patients’ perspective, integrating expertise from well-known professionals and a broader spectrum of professionals was critical to addressing their complex IMIDs needs and avoiding fragmentation. Moreover, coordination administered by care coordinators was vital to their experiences of success. Conclusions This study presents a two-fold conceptualisation of interprofessional care to inform future IMIDs intervention development. Our results underscore the importance of individualising and tailoring treatment through patient-centred care to help patients improve their IMIDs and self-management skills.in F1000Research on 2025-07-11 11:23:57 UTC.
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LitSieve: An integrated literature search and triage tool for biocuration [version 1; peer review: awaiting peer review]
Biomedical databases are an important part of the scientific infrastructure for organising and synergising research outputs. Many of these databases abstract content from the rapidly expanding scientific literature. Therefore, database curators require effective literature search methods in order to capture research relevant to their domain. This article describes LitSieve, a literature search tool with filtering based on text mined annotations, and flexible article organisation features. It allows users to define filters based on biomedical entities like genes, diseases and species to include or exclude particular articles within their results. By combining a search query with a filter, curators are able to identify articles relevant to the database which they are curating. LitSieve uses APIs provided by Europe PMC, from which abstracts, article full text and text mined annotations are drawn. LitSieve is available at https://www.ebi.ac.uk/europepmc/litsieve/in F1000Research on 2025-07-11 11:03:14 UTC.
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Predicting interface residues for protein polymers based on module division
Author(s): Shuhong Yu, Zicheng Xie, Jiudong Wang, and Xinqi Gong
In the field of computational biology, AlphaFold has facilitated remarkable progress in predicting protein structures. However, for some multimeric complexes, the accuracy of its predictions still needs improvement. Enhancing the prediction of binding sites in protein oligomers contributes to the pr…
[Phys. Rev. E 112, 014403] Published Fri Jul 11, 2025
in Physical Review E: Biological physics on 2025-07-11 10:00:00 UTC.
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The Brain of the African Wild Dog. V. The Somatosensory System and Vestibular Nuclear Complex
Lateral view of the African wild dog brain showing the location of the somatosensory cortical areas in relation to the parietal multisensory region (PP), occipital visual cortical areas (17, 18, 19, 21, SS, T), and temporal auditory cortical areas (AAF, AI AII). These broad relations of the sensory cortex reflect that observed in many other mammals.
ABSTRACT
Social behaviors in the African wild dog (Lycaon pictus) commonly involve a range of tactile aspects, including biting, pushing, embracing, mounting, face and muzzle licking, nose–chin and muzzle contact, paw placement, play fighting, and wrestling, supported by the vestibular system. We employed an array of architectural and immunohistochemical stains to provide a qualitative description of the somatosensory and vestibular systems in the brain of one representative African wild dog individual. The appearance of both systems does not appear to differ from that reported in other Carnivora. The six nuclei forming the vestibular system, and their relationship to each other and the incoming vestibular branch of the eighth cranial nerve, appear like those observed in many mammalian species. The location and appearance of the dorsal column nuclei, the trigeminal sensory column, the colliculi, somatosensory nuclei of the dorsal thalamus, and the five somatosensory cortical areas observed in the African wild dog are like those observed in the domestic dog and other Carnivora. This study of the somatosensory and vestibular systems of the African wild dog completes our series of studies describing the major sensory systems in the African wild dog brain. It appears reasonable to conclude that, at the systems level of analysis, no overt specializations of any of the sensory systems are present. Thus, the neural underpinnings of the complex sociality of the African wild dog may be supported by nonsensory neural systems, such as motor, neuromodulatory, limbic, or cognitive systems, or levels of organization like receptor expression patterns or connectivity.
in Journal of Comparative Neurology on 2025-07-11 08:05:03 UTC.
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Cognitive Performance in Early Neuronal Synuclein Disease with Hyposmia but without Motor Disability: Association with Dopamine Deficiency and Isolated Rapid Eye Movement Sleep Behavior Disorder
Objective
To determine the impact of dopamine deficiency and isolated rapid eye movement (REM) sleep behavior disorder (iRBD) on cognitive performance in early neuronal α-synuclein disease (NSD) with hyposmia but without motor disability.
Methods
Using Parkinson's Progression Markers Initiative baseline data, cognitive performance was assessed with a cognitive summary score (CSS) derived from robust healthy control (HC) norms. Performance was examined for participants with hyposmia in early NSD-Integrated Staging System (NSD-ISS), either stage 2A (cerebrospinal fluid α-synuclein seed amplification assay [SAA]+, dopamine transporter scan [DaTscan]−) or 2B (SAA+, DaTscan+).
Results
Participants were stage 2A (n = 101), stage 2B (N = 227), and HCs (n = 158). Although stage 2 had intact Montreal Cognitive Assessment scores (mean [SD] = 27.0 [2.3]), stage 2A had a numerically worse CSS (z-score mean difference = 0.05, p = NS; effect size = 0.09) and stage 2B a statistically worse CSS (z-score mean difference = 0.23, p < 0.05; effect size = 0.40) compared with HCs. In stage 2A, hyposmia alone was associated with normal cognition, but those with comorbid iRBD had significantly worse cognition (z-score mean difference = 0.33, p < 0.05, effect size =0.50). In stage 2B, hyposmia alone had abnormal cognition (z-score mean difference = 0.18, p = 0.0078, effect size = 0.29), and superimposed iRBD had a statistically significant additive effect.
Interpretation
Using a novel CSS, we demonstrated that hyposmia is associated with cognitive deficits in prodromal NSD without motor disability, particularly when comorbid dopamine system impairment or comorbid iRBD is present. Therefore, it is critical to include and assess cognition at all stages when studying synuclein disease, even in the absence of motor disability. ANN NEUROL 2025
in Annals of Neurology on 2025-07-11 07:24:20 UTC.
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Domain engineering in ferroelectric nematics for nonlinear optical modulation
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Structural and genetic determinants of zebrafish functional brain networks
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Proteins with cognition-associated structural changes in a rat model of aging exhibit reduced refolding capacity
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Discovering high-entropy electrocatalysts through a batch-alloy targeting approach
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Dynamically covalent lipid nanoparticles mediate CRISPR-Cas9 genome editing against choroidal neovascularization in mice
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Cold-air outbreaks in the continental US: Connections with stratospheric variations
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Kilometric sea level changes during the Messinian salinity crisis caused by river erosion and climate
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Stripe rust fungi hijack a host transcriptional repressor to induce TaSWEET14d for enhanced sugar uptake in wheat
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Decoding sexual dimorphism of the sex-shared nervous system at single-neuron resolution
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Constraining biorecalcitrance of carboxyl-rich alicyclic molecules in the ocean
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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BRD4770 protects against DOX-induced cardiotoxicity by inhibiting apoptosis and ferroptosis
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Cypin regulates K63-linked polyubiquitination to shape synaptic content
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Exogenous activation of the adhesion GPCR ADGRD1/GPR133 protects against bone loss by negatively regulating osteoclastogenesis
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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G proteins of the G12 family expressed by POMC neurons regulate key metabolic functions
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Transition of cellular senescence to pyroptosis mediates recurrence of small cell lung cancer after chemotherapy
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Picoeukaryote-based biohybrid microrobots for active delivery in the kidney
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Wearing bacteriophages individually with an adhesive drug-loadable nanohelmet for treating ocular infections
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Parallel evolution of salinity tolerance in Arabidopsis thaliana accessions from Cape Verde Islands
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Change-of-mind neuroeconomic decision-making is modulated by LINC00473 in medial prefrontal cortex in a sex-dependent manner
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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UFMylation maintains tumor suppressor pVHL stability by activating the deubiquitinase BAP1
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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PD-1 and ICOS are coexpressed in T follicular helper cells but define three stages of maturation of T follicular regulatory cells
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Complex I inhibition combined with TLR activation in the breast tumor microenvironment educates cytotoxic neutrophils
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Anabolic indices of matrix proteins identify regenerative small RNA intrinsic to human cartilage
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Electrified dry reforming of methane on Ni-La2O3–loaded activated carbon: A net CO2-negative reaction
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Slab underthrusting is the primary control on flat-slab size
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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A salt-driven mechanism for precise chirality sorting of carbon nanotubes
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Structures and receptor binding activities of merbecovirus spike proteins reveal key signatures for human DPP4 adaptation
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Terrestrial temperature history reveals Late Miocene rapid uplift of the northern Tibetan Plateau
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Atlantification drives recent strengthening of the Arctic overturning circulation
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Polymer encapsulation via initiated chemical vapor deposition (iCVD) to enhance stability of Ti3C2Tx MXene-based formaldehyde sensors
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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A narrow range of transcript-error rates across the Tree of Life
Science Advances, Volume 11, Issue 28, July 2025.
in Science Advances on 2025-07-11 07:00:00 UTC.
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Life without microglia
Microglia are involved in many aspects of postnatal brain development and neuronal plasticity. This article questions some of the assumptions inherent in current experimental models used to analyze microglial ontogeny and function which likely underestimate the contributions of blood monocytes to brain homeostasis. It summarizes evidence from animal models of congenital microglial deficiency that postnatal neuronal development and synaptic refinement do not require the presence of microglia. Instead, the absence of microglia is associated with accelerated progression in disease models and age-dependent neuropathology in humans, implying that the major essential function of microglia is to protect against neuronal injury.in Trends in Neurosciences: In press on 2025-07-11 00:00:00 UTC.
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Shaping the synapse through neuronal activity-regulated miRNAs
The brain’s ability to adapt and support learning relies on experience-dependent synaptic plasticity, where connections between neurons are strengthened or weakened in response to activity. Recent research in mammalian systems reveals microRNAs (miRNAs) as crucial regulators of this process, offering a new perspective on how neurons achieve timely, localized control of protein synthesis. Neuronal activity influences every stage of the miRNA life cycle, from transcription to transport, maturation, and decay. Transcriptional regulation enables neuron-wide structural adaptations, while synapse-specific transport and maturation ensure localized protein synthesis. Though incompletely understood, activity-regulated miRNA decay allows for reversible modulation of gene expression. These discoveries highlight miRNAs as an essential layer of regulation, bridging neuronal activity with molecular changes that support learning and memory.in Trends in Neurosciences: In press on 2025-07-11 00:00:00 UTC.
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Human stem cell-derived GABAergic interneuron development reveals early emergence of subtype diversity and gradual electrochemical maturation
Bershteyn et al. describe the long-term properties of a human stem cell-derived GABAergic interneuron cell therapy candidate undergoing clinical evaluation for drug-resistant epilepsy. Following transplantation into the brains of healthy or epileptic mice, grafted cells demonstrate exceptional purity, differentiation into authentic subtypes, integration with host circuitry, and gradual electrophysiological maturation.in Neuron: In press on 2025-07-11 00:00:00 UTC.
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CAR-T cells containing CD28 versus 4-1BB co-stimulatory domains show distinct metabolic profiles in patients
Cook et al. investigate the metabolic profile of DLBCL patient-derived CAR-T cells ex vivo. Comparing Axi-cel (CD28-co-stimulated) and Tisa-cel (4-1BB-co-stimulated) products, they find divergent metabolic profiles in CAR-T cells. However, in patients responding to therapy, CAR-T cells were metabolically similar between the two products.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Effects of aging on gene expression networks in the Drosophila genetic reference panel
Tan et al. compared gene expression of young and 3-week-old flies from the Drosophila Genetic Reference Panel. Aging caused widespread sex- and genotype-specific transcriptional changes but global robustness of co-expression modules. Some networks lost connectivity and reduced genetic control of gene expression with age and were associated with organismal senescence.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Spike-specific IgG4 generated post BNT162b2 mRNA vaccination is inhibitory when directly competing with functional IgG subclasses
Tam et al. identified SARS-CoV-2 exposure histories that favor development of Spike-specific IgG4 responses. Although IgG4 monoclonal antibodies have reduced effector-function activity, in the context of a polyclonal response, IgG4 is only inhibitory when directly competing with functional antibody subclasses that bind overlapping epitopes.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Modulation of B cell receptor activation by antibody competition
Antibodies from prior exposure to influenza viruses affect immune responses during subsequent encounters. He et al. establish an in vitro system that mimics B cell extraction of viral antigens and use it to study principles of epitope masking, demonstrating a dynamic competition between soluble antibodies and B cell receptors.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Lon dysfunction-mediated collateral sensitivity drives effective antibiotic combination therapies against tigecycline-resistant pathogens
The global dissemination of antibiotic resistance calls for innovative strategies. Yu et al. unveil collateral sensitivity-guided antibiotic combination therapies to combat tigecycline-resistant bacteria, highlighting how Lon dysfunction disrupts membrane homeostasis and causes bacterial death upon nitrofurantoin treatment.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Fha initiates the inside-out assembly of the type VI secretion system
Pei et al. uncover an inside-out mechanism for building the type VI secretion system (T6SS) in bacteria, demonstrating that the conserved protein Fha forms condensates through liquid-liquid phase separation to recruit essential components and drive assembly.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Histone marks enable formation of immiscible phase-separated chromatin compartments
Sun et al. investigate two biochemically similar epigenetic systems, H3K9me3-chromodomain and H3K27me3-chromodomain, and demonstrate how they utilize liquid-liquid phase separation to form immiscible condensates both in vitro and in cellulo. Essentially, the high degree of cooperativity associated with switch-like phase separation enables a clear distinction between “seemingly promiscuous” biochemical systems.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Modulation of aggression by social novelty recognition memory in the hippocampal CA2 region
Villegas and Siegelbaum report that the dorsal CA2 region of the hippocampus acts to selectively increase aggression toward novel compared with familiar individuals. Calcium imaging from mice during aggressive behavior shows that dCA2 neurons encode aggression more strongly during attacks of novel compared with familiar intruders.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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Fe-deficiency-induced chlorosis 1 is essential for chloroplast iron transport and homeostasis under continuous light conditions in Arabidopsis
Zhang et al. demonstrate that FIC1 plays a dual role in facilitating iron uptake into chloroplasts and regulating iron homoeostasis across tissues under continuous light conditions. These mechanisms promote iron translocation from developed leaves to newly developing leaves, thereby meeting the high iron demand for optimal chloroplast function.in Cell Reports: Current Issue on 2025-07-11 00:00:00 UTC.
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SLC7A11 protects amoeboid-disseminating cancer cells from oxidative stress
Graziani et al. show that SLC7A11 increases during melanoma disease progression. SLC7A11 promotes Myosin II-driven amoeboid invasive behavior while shielding amoeboid cancer cells from oxidative stress. Blocking SLC7A11 function represents a potential strategy to prevent metastatic spread.in Cell Reports: In press on 2025-07-11 00:00:00 UTC.
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Author Correction: Adhesive anti-fibrotic interfaces on diverse organs
Nature, Published online: 11 July 2025; doi:10.1038/s41586-025-09311-5
Author Correction: Adhesive anti-fibrotic interfaces on diverse organsin Nature on 2025-07-11 00:00:00 UTC.
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Three weeks in a hide to spot one elusive bear: the life of a wildlife film-maker
Nature, Published online: 11 July 2025; doi:10.1038/d41586-025-02195-5
Vianet Djenguet joins us to talk about working with conservation researchers in the documentary series The Wild Ones.in Nature on 2025-07-11 00:00:00 UTC.
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Lonely spacecraft can navigate the stars
Nature, Published online: 11 July 2025; doi:10.1038/d41586-025-02108-6
NASA’s New Horizons probe, which hurtled past Pluto in 2015, demonstrates that it can sail through interstellar space using its onboard camera.in Nature on 2025-07-11 00:00:00 UTC.
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Mini hearts, lungs and livers made in lab now grow their own blood vessels
Nature, Published online: 11 July 2025; doi:10.1038/d41586-025-02183-9
These sophisticated models will be used for human-development studies and drug testing.in Nature on 2025-07-11 00:00:00 UTC.
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Scientists hide messages in papers to game AI peer review
Nature, Published online: 11 July 2025; doi:10.1038/d41586-025-02172-y
Some studies containing instructions in white text or small font — visible only to machines — will be withdrawn from preprint servers.in Nature on 2025-07-11 00:00:00 UTC.
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Intertwined orders in a quantum material
Nature Physics, Published online: 11 July 2025; doi:10.1038/s41567-025-02942-5
Symmetry-protected topological orders are often in competition with electronic correlations that tend to induce orders with broken symmetry. Now, a quantum material is shown to exhibit correlation-driven tuneable excitonic instabilities intertwined with symmetry-protected topological orders.in Nature Physics on 2025-07-11 00:00:00 UTC.
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Measurement of phonon angular momentum
Nature Physics, Published online: 11 July 2025; doi:10.1038/s41567-025-02952-3
Theory predicts that phonons—quanta of lattice vibrations—can carry finite angular momentum and thus influence physical properties of materials. Now phonons with angular momentum have been seen in tellurium with a chiral crystal structure.in Nature Physics on 2025-07-11 00:00:00 UTC.
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Topological excitonic insulator with tunable momentum order
Nature Physics, Published online: 11 July 2025; doi:10.1038/s41567-025-02917-6
Experimental systems in which non-trivial topology is driven by spontaneous symmetry breaking are rare. Now, topological gaps resulting from two excitonic condensates have been demonstrated in a three-dimensional material.in Nature Physics on 2025-07-11 00:00:00 UTC.
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Changes in cortical beta power predict motor control flexibility, not vigor
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08465-2
This study demonstrates that motor cortical beta power modulations predict motor control flexibility rather than vigor. Using neurofeedback and motor tasks, the authors show that beta power downregulation improves task performance in a context-dependent manner.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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Fortilin deficiency induces anti-atherosclerotic phenotypes in macrophages and protects hypercholesterolemic mice against atherosclerosis
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08425-w
Fortilin promotes atherogenesis by enhancing macrophage survival, proliferation, and lipid uptake while suppressing their transdifferentiation into vascular smooth muscle cells, leading to increased foam cell accumulation and reduced plaque stability.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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TRIM33 loss reduces androgen receptor transcriptional output and H2BK120 ubiquitination
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08449-2
The authors study the role of TRIM33 in androgen receptor (AR) transcriptional activity. They show that TRIM33 and AR co-occupy most of their genomic binding sites and TRIM33 loss altered expression of a subset of AR-responsive genes.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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Altering the biophysical properties of ERC1/ELKS–driven condensates interferes with cell motility
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08470-5
Biochemical and functional analysis with deletion mutants shows that altering the properties of biomolecular condensates driven by the ERC1/ELKS scaffold protein interferes with tumor cell motility.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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Human and artificial visual systems share a computational principle for transforming binocular disparity into depth representation
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08474-1
fMRI and deep neural networks reveal hierarchical transformation of binocular disparity from ambiguous cross-correlation to more refined cross-matching representations.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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βTrCP facilitates MRN complex localization on chromatin to enhance DNA repair
Communications Biology, Published online: 11 July 2025; doi:10.1038/s42003-025-08462-5
βTrCP-mediated regulation of the MRN complex reveals a GSK3-dependent mechanism that enhances chromatin recruitment of the complex via MRE11, thereby promoting efficient DNA damage repair and contributing to genomic stability.in Nature communications biology on 2025-07-11 00:00:00 UTC.
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Ultraslow serotonin oscillations in the hippocampus delineate substates across NREM and waking
Beyond the vast array of functional roles attributed to serotonin (5-HT) in the brain, changes in 5-HT levels have been shown to accompany changes in behavioral states, including WAKE, NREM, and REM sleep. Whether 5-HT dynamics at shorter time scales can be seen to delineate substates within these larger brain states remains an open question. Here, we performed simultaneous recordings of extracellular 5-HT using a recently developed G-Protein-Coupled Receptor-Activation-Based 5-HT sensor (GRAB5-HT3.0) and local field potential in the hippocampal CA1 of mice, which revealed the presence of prominent ultraslow (<0.05 Hz) 5-HT oscillations both during NREM and WAKE states. Interestingly, the phase of these ultraslow 5-HT oscillations was found to distinguish substates both within and across larger behavioral states. Hippocampal ripples occurred preferentially on the falling phase of ultraslow 5-HT oscillations during both NREM and WAKE, with higher power ripples concentrating near the peak specifically during NREM. By contrast, hippocampal–cortical coherence was strongest, and microarousals and intracranial EMG peaks were most prevalent during the rising phase in both wake and NREM. Overall, ultraslow 5-HT oscillations delineate substates within the larger behavioral states of NREM and WAKE, thus potentially temporally segregating internal memory consolidation processes from arousal-related functions.in eLife on 2025-07-11 00:00:00 UTC.
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Acquisition of auditory discrimination mediated by different processes through two distinct circuits linked to the lateral striatum
The striatum, the central hub of cortico-basal ganglia loops, contains functionally heterogeneous subregions distinguished by the topographic patterns of structural connectivity. These subregions mediate various processes of procedural learning. However, it remains unclear when and how striatal subregions engage in the acquisition of sensory stimulus-based decision-making. A neuroimaging of regional brain activity shows that the anterior dorsolateral striatum (aDLS) and posterior ventrolateral striatum (pVLS) in rats are activated in a different temporal pattern during the acquisition phase of auditory discrimination. Chronic and transient pharmacologic manipulations show that the aDLS promotes the behavioral strategy driven by the stimulus-response association while suppressing that by the response-outcome association, and that the pVLS contributes to forming and maintaining the stimulus-response strategy. Electrophysiological recording indicates that subpopulations of aDLS neurons predominantly represent the outcome of specific behaviors at the initial period of discrimination learning, and that pVLS subpopulations encode the beginning and ending of each behavior according to the progress of learning. In addition, other subpopulations of striatal neurons indicate sustained activation after obtaining reward with distinct patterns reflecting the stimulus-response associations. Our findings demonstrate that aDLS and pVLS neurons integrate the new learning of auditory discrimination in spatiotemporally and functionally different manners.in eLife on 2025-07-11 00:00:00 UTC.
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The microbiome interacts with the circadian clock and dietary composition to regulate metabolite cycling in the Drosophila gut
The gut microbiome plays a key role in the maintenance of host metabolic homeostasis and health. Most metabolic processes cycle with a 24-hour rhythm, but the extent to which the microbiome influences metabolite cycling under different conditions, such as variations in dietary composition, remains largely unknown. In this study, we utilized high temporal resolution metabolite profiling of the Drosophila gut to investigate the role of the microbiome in metabolite cycling. We find that the microbiome increases the number of oscillating metabolites despite the previous finding that it dampens transcript cycling in the gut. Time-restricted feeding also promotes metabolite cycling and does so to a larger extent in germ-free flies, thereby increasing cycling in these flies to levels comparable to those in microbiome-containing flies. Enhancement of cycling by the microbiome depends upon a circadian clock, which also maintains phase in the face of changes in the microbiome. Interestingly, a high protein diet increases microbiome-dependent metabolite cycling, while a high sugar diet suppresses it. Gene Ontology identifies amino acid metabolism as the metabolic pathway most affected by changes in the gut microbiome, the circadian clock, and timed feeding, suggesting that it is subject to regulation by multiple inputs. Collectively, our observations highlight a key role of the gut microbiome in host metabolite cycling and reveal a complex interaction with internal and external factors.in eLife on 2025-07-11 00:00:00 UTC.
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Synaptic properties of layer 6 auditory corticothalamic inputs in normal hearing and noise-induced hearing loss
Layer 6 corticothalamic neurons (CTs) provide strong feedback input that is crucial to perception and cognition in normal and pathological states; however, the synaptic properties of this input remain largely unknown, especially in pathology. Here, we examined the synaptic properties of CT axon terminals in the medial geniculate body (MGB), the auditory thalamus, in normal hearing mice and in a mouse model of noise-induced hearing loss. In normal hearing mice, we found that the synaptic strength of CTs to the core-type ventral subdivision of the auditory thalamus (MGv), which mainly conveys rapid sensory information, is stronger than the synaptic strength of CTs to the matrix-type dorsal subdivision of the auditory thalamus (MGd), which likely conveys higher-order internal state information. This is due to increased functional release sites (n) in CT[->]MGv compared to CT[->]MGd synapses. After noise trauma, we observed enhanced short-term facilitation in CT[->]MGd but not CT[->]MGv synapses. Our findings reveal a previously unknown mechanism of short-term synaptic plasticity after noise-induced hearing loss via which CTs enhance the throughput of matrix-type thalamus, likely to improve perceptual recovery via higher-order contextual modulation.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Memorization of novel patterns in working memory in a model based on dendritic bistability
Working memory can hold many types of information and is crucial for cognition. Commonly, models of working memory maintain information such as hues or words by forming memory attractors through structured connectivities. However, real-world information can be novel, making it infeasible to use pre-trained attractors. In addition, most models-with or without attractors-have focused on maintaining binary categories instead of continuous information in each neuron. In the present study, we investigate how the brain might maintain working memory representations of arbitrary novel patterns with graded values. We propose an unstructured network model in which each neuron has multiple bistable dendrites. Each dendrite effectively implements fast Hebbian plasticity due to dendritic dynamics and dendrite-soma interactions. This network can maintain novel graded patterns under various perturbations without fine tuning of parameters. Through analytical characterization of network dynamics during the encoding and memory periods, we identify different conditions that yield either perfect memories or several types of memory errors. We also demonstrate memory robustness under various conditions and resilience to temporal inhibitory perturbations. Thus, this architecture provides robust and analytically tractable storage of novel graded patterns in working memory.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Genetic inactivation of the Translin/Trax RNase activity alters small RNAs including miRNAs, disrupts gene expression and impairs distinct forms of hippocampal synaptic plasticity and memory
Neurons utilize RNA interference in the reversible translational repression of synaptically localized mRNAs, enabling rapid translation in response to synaptic activity. Two evolutionarily conserved proteins, Translin and Trax, form an RNase complex which processes miRNAs, tRNAs and siRNAs. To determine the specific role of the RNase activity of this complex in brain function, we employed a mouse line harboring a point mutation in Trax (E126A) that renders the Translin/Trax RNase inactive. At the molecular level, we found alterations in the levels of multiple small RNAs including miRNAs, tsRNAs and substantial downregulation of gene expression at the mRNA level in the hippocampus of TraxE126A mice. At the synaptic level, TraxE126A mice exhibit deficits in specific forms of long-term hippocampal synaptic plasticity. At the behavioral level, TraxE126A mice display impaired long-term spatial memory and altered open-field and acoustic-startle behavior. These studies reveal the functional role of Translin/Trax RNase in the mammalian brain.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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AAV-based temporal APOE4-to-APOE2 replacement reveals rebound adaptation and RAB24-mediated Aβ and cholesterol dysregulation
APOE-targeted gene therapy offers a promising strategy for modifying Alzheimer's disease (AD) risk, yet the temporal dynamics and context-dependent effects of APOE isoform modulation remain poorly defined. Here, we developed a rapid AAV-based platform enabling inducible in vivo replacement of APOE4 with APOE2. In 5xFAD mice, sustained APOE4 expression exacerbated cognitive decline, A{beta} deposition (parenchymal and vascular), and glial activation, whereas long-term APOE2 expression--with concurrent APOE4 silencing--significantly reversed these pathological features and rescued cognitive function. In contrast, short-term APOE2 replacement conferred no benefit and unexpectedly worsened behavioral and pathological outcomes. Transcriptomic profiling revealed that APOE4-associated gene signatures were broadly reversed by long-term APOE2 expression, but paradoxically aggravated by short-term replacement. Among these, RAB24--a regulator of autophagic trafficking--was upregulated by APOE4 and short-term APOE2 but suppressed by long-term APOE2. RAB24 elevation impaired A{beta} clearance and cholesterol homeostasis via lysosomal retention in primary astrocytes and neurons. Together, these findings uncover a rebound-adaptation mechanism that shapes APOE2 therapeutic outcomes, identify RAB24 as a modifiable node in A{beta} and cholesterol metabolism, and establish a temporally controlled gene therapy platform to inform the design of future APOE-targeted interventions in AD.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Light stimulation system for measuring pupillary light responses based on Maxwellian view optical system using a retina presentation type viewfinder
Purpose: To evaluate the feasibility of applying a retinal projection viewfinder based on the Maxwellian view (MV) optical system for measuring post-illumination pupil response (PIPR) by comparing its performance with a typical LED-based optical system. Methods: Twenty-two healthy participants underwent pupillometry using both the MV-based viewfinder and a typical LED-based system. Monochromatic red and blue light stimuli were presented for durations of 1 and 10 seconds. Pupil responses, including maximum constriction, PIPR amplitude after 6 seconds from the light offset, area under the curve (AUC) values of PIPR, and sustained slopes, were analyzed using a linear mixed-effects model to assess the differences between the two systems. Results: The MV-based viewfinder significantly enhanced net PIPR amplitude (p < 0.05) and sustained slope (p < 0.01) during 10-second light stimulation compared to the LED system, demonstrating its capability to effectively measure ipRGC-driven responses. In contrast, no significant differences were observed in the net AUC values. These results highlight that the MV-based viewfinder enables effective PIPR measurements by delivering constant and controlled light stimulation directly to the retina, minimizing the effects of dynamic pupil constriction during light stimulation. Conclusions: The MV-based viewfinder showed feasibility as an effective method for measuring PIPR without requiring pharmacological dilation and technical knowledge to build the MV system. This innovative approach has significant potential for clinical and research applications in pupillometry. Translational Relevance: Our methodology provides practical solutions for dilation-free effective measurement of PIPR, accelerating its translation from experimental tool to routine clinical diagnostic.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Deep mapping of the endomembrane system of cerebellar Purkinje neurons
Neuronal function relies on the precise spatial organization of intracellular membrane-bounded organelles involved in anabolism and Ca2+ sequestration, such as the Golgi apparatus, mitochondria and the endoplasmic reticulum (ER), along with structures involved in catabolism, such as lysosomes. Despite their known roles in energy supply, calcium homeostasis, and proteostasis, our understanding of how the anabolism-linked organelles are structurally arranged within neurons remains incomplete. Due to the tremendous complexity in the morphologies and fine structural features and interwoven nature of these intracellular organelles, particularly the ER, our understanding of their structural organization is limited, particularly, with regard to quantitative assessments of their sites of interaction and accurate measures of their volumetric proportions inside of a single large neuron. To approach this challenge, we used serial block-face scanning electron microscopy (SBEM) to generate large-scale 3D EM volumes and electron tomography on high-pressure frozen tissue of the rodent cerebellum, including the largest cells in the vertebrate brain, the cerebellar Purkinje neuron as well as the most abundant cell type in the vertebrate brain, the much smaller cerebellar granule neuron. We reconstructed the neuronal ultrastructure of these different cell types, focusing on the ER, mitochondria and membrane contact sites, to then characterize intracellular motifs and organization principles in detail, providing a first full map to quantitatively describe a neuronal endoarchitectome. At the gross level organization, we found that the intracellular composite of organelles are cell type specific features, with specific differences between Purkinje neurons and Granule cells. At the level of fine structure, we mapped ultrastructural domains within Purkinje neurons where ER and mitochondria associate directly. In addition to cell type specific differences, we observed significant subcellular regional variation, particularly within the axon initial segment (AIS) of Purkinje neurons, where we identified ultrastructural domains with sharply contrasting distributions of ER and mitochondria. These findings suggest a finely tuned spatial organization of organelles that may underpin the distinct functional demands along the axon. We expect that our subcellular map, along with the methods developed to obtain these maps, will facilitate future studies in health, aging and disease to characterize defined features, by developing a framework for quantitative analysis of the neuronal ultrastructure.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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REVS: A New Open-Source Platform for High-Resolution Analysis of Rodent Wheel Running Behavior
Background Rodent wheel running is widely used in neuroscience and preclinical research to assess locomotor function, recovery post-trauma or disease, circadian rhythms, and exercise physiology. However, most existing wheel-running systems offer limited metrics, lack flexibility in hardware, or require costly proprietary software, reducing their usefulness for detailed behavioral phenotyping, especially in models of injury or rehabilitation. New method We developed REVS (Revolution Evaluation and Visualization Software), a low-cost, open-source hardware and software platform for analyzing and visualizing rodent wheel running behavior. REVS captures wheel revolutions using Hall effect sensors and computes 13 day-level behavioral metrics along with detailed bout-level data. Users can interactively explore high-resolution temporal features and export data in Open Data Commons (ODC)-compatible formats. REVS supports customizable wheel types, facilitating use in animals with motor and/or sensory impairments. Results We validated REVS using a mouse model of partial spinal cord injury, where fine motor control is compromised. REVS detected impairments in 10 of 13 behavioral metrics post-injury, with varied recovery trajectories across measures. Principal component analysis revealed that recovery was closely linked to bout quality and intensity, rather than timing. Comparison with existing methods Unlike commercial and open-source systems, REVS offers more detailed metrics, customizable wheel compatibility, seamless blending with common vivarium hardware, integrated data visualizations, and ODC-compatible data export. It also supports flexible analysis across individuals and groups. Conclusions REVS provides a powerful, scalable tool for granular behavioral phenotyping in rodent studies, enhancing reproducibility and revealing insights into subtle locomotor changes associated with injury, recovery, and intervention.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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A novel, evolutionarily conserved inhibitory circuit selectively regulates dentate gyrus mossy cell function.
The mammalian dentate gyrus contributes to mnemonic function by parsing similar events and places. The disparate activity patterns of mossy cells and granule cells is believed to enable this function yet the mechanisms that drive this circuit dynamic remain elusive. We identified a novel inhibitory interneuron subtype, characterized by VGluT3 expression, with overwhelming target selectivity for mossy cells while also revealing that CCK, PV, SOM and VIP interneurons preferentially innervate granule cells. Leveraging pharmacology and novel enhancer viruses, we find that this target-specific inhibitory innervation pattern is evolutionarily conserved in non-human primates and humans. In addition, in vivo chemogenetic manipulation of VGluT3+ interneurons selectively alters the activity and functional properties of mossy cells. These findings establish that mossy cells and granule cells have unique, evolutionarily conserved inhibitory innervation patterns and suggest selective inhibitory circuits may be necessary to maintain DG circuit dynamics and enable pattern separation across species.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Conditions for replay of neuronal assemblies
From cortical synfire chains to hippocampal replay, the idea that neural populations can be activated sequentially with precise spike timing is thought to be essential for several brain functions. It has been shown that neuronal sequences with weak feedforward connectivity can be replayed due to amplification via intra-assembly recurrent connections. However, this phenomenon was thought to depend on inhibitory feedback, but its mechanisms were still unclear. Here, we arrive at a minimal spiking model that shows that feedback inhibition is not needed for this amplification to occur. We then introduce a population model of membrane-potential distributions that explains the spiking network behavior, and we analytically describe how different connectivity structures determine replay speed, with weaker feedforward connectivity generating slower pulses that can be sustained by recurrent connections. These pulses can only propagate if neuronal leak currents are slow enough with respect to the pulse speed. Together, our simulations and analytical results predict the conditions for replay of neuronal assemblies.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Alpha and theta activity during reward anticipation are modulated by implicit expectations about sequential risk
Reward anticipation potentially guides sequential decision making, yet its underlying neural dynamics remain unclear. In this study, we investigated how risk levels and uncertainty modulate oscillatory brain activity during reward anticipation. EEG was recorded while participants (N = 44) performed a modified version of the Balloon Analogue Risk Task where balloon burst probabilities changed throughout the task, promoting uncertainty. We analyzed induced spectral power time-locked to three risk levels: early no-risk pumps, final successful pumps (preceding a cash out), and unsuccessful pumps (preceding a balloon burst). Time-frequency decomposition using Morlet wavelets revealed a parieto-occipital alpha power increase following early no-risk pumps, interpreted as disengagement from deliberative processing when anticipating sure rewards. In contrast, centroparietal alpha and frontocentral theta power decreased most prominently following final successful pumps, suggesting heightened attentional and expectancy-related processes in response to high reward potential. The results indicate that alpha and theta dynamics are sensitive to risk levels and reward expectations. These findings provide novel insights into the oscillatory mechanisms of reward anticipation in uncertain decision environments.in bioRxiv: Neuroscience on 2025-07-11 00:00:00 UTC.
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Knockout of Bmal1 in dopaminergic neurons induces ADHD-like symptoms via hyperactive dopamine signaling in male mice
The central circadian clock coordinates daily oscillations in physiology, metabolism and behavior. Disruptions to core circadian clock genes not only perturb sleep-wake rhythms but also contribute to psychiatr...in Behavioural and Brain Functions on 2025-07-11 00:00:00 UTC.
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Morphological and Molecular Distinctions of Parallel Processing Streams Reveal Two Koniocellular Pathways in the Tree Shrew DLGN
In the mammalian visual system, three functionally distinct parallel processing streams extend from the retina to the visual thalamus and then to the visual cortex: magnocellular (M), parvocellular (P), and koniocellular (K). Tree shrews (Tupaia belangeri), a preprimate species, provide an advantageous model to study the K pathway in isolation because, while M and P pathways remain mixed in Lamina 1 (L1), L2, L4, and L5 of the lateral geniculate nucleus (LGN), L3 and L6 receive strictly K-input from the contralateral eye. Additionally, K-input laminae selectively receive glutamatergic axons from the superior colliculus. To reveal how cellular and synaptic properties of K geniculate laminae may differ from M/P laminae and how tectal input may shape the K relay to the cortex, we studied the morphology and connectivity of retinal and tectal terminals in pathway-specific laminae. While confirming that K laminae relay cells contain calbindin, we also found its expression in GABAergic cells across all laminae. No cell-type or lamina specificity was observed for parvalbumin. Ultrastructurally, retinal terminals are morphologically distinct in M/P versus K laminae. Tectogeniculate axons in L3 and L6 resemble retinal terminals in their morphology and synaptic targets, while corticogeniculate terminals are sparse in L6. VGluT2, the molecular marker for large-sized driver terminals, is expressed prominently in one of the three tectal cell types that project to LGN. Morphological differences in synaptic circuitry between L3 and L6 provide further evidence that two geniculate K laminae are differentially innervated to relay distinct sets of information to the cortex.
in eNeuro on 2025-07-10 16:30:29 UTC.
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Anatomical-electrical coupling of cardiac axes: Definitions and population variability for advancing personalised ECG interpretation
by Mohammad Kayyali, Ana Mincholé, Shuang Qian, Alistair Young, Devran Ugurlu, Elliot Fairweather, Steven Niederer, John Whitaker, Martin Bishop, Pablo Lamata
Electrocardiogram (ECG) recordings are affected by the heart’s three-dimensional orientation within the thorax, i.e., the anatomical axis. Various cardiac conditions can cause the anatomical axis to shift and/or alter the pattern of electrical activation, leading to changes in the electrical axis. Nevertheless, there remains a lack of a formal, population-level study of the interplay between the cardiac anatomical and electrical axes and the factors that affect them. In this context, this study aimed to: (1) propose standardised definitions for the cardiac anatomical and electrical axes, (2) characterise their population-wide interplay in healthy conditions, (3) evaluate the impact of hypertension on their distribution and (4) identify associations with phenotypical and disease characteristics. Using cardiac magnetic resonance images and 12-lead ECGs from ~39,000 UK Biobank participants, patient-specific, paired biventricular geometries and vectorcardiograms were constructed. Five anatomical and four electrical axis definitions were computed, with the optimal pair of definitions selected based on their mutual alignment in 3D space within 28,000 healthy subjects. Accordingly, the anatomical axis was defined as the vector from the apex to the spatial centre of the four valves, and the electrical axis as the direction of the maximum QRS dipole. Mean angular separation in 3D, ΔAE3D, was 145.0° ± 16.8° in the healthy cohort. The electrical axes exhibited a much larger variability, and strong evidence of anatomical-electrical coupling was identified. Increasing BMI notably affected the anatomical axis, rotating the heart more horizontally—a pattern mirrored by the electrical axis. Both axes were also significantly influenced by sex and, to a lesser extent, age. The axes were then studied in the sub-cohort of ~3,500 UK BioBank participants with primary hypertension, where a similar rotational pattern as that with increasing BMI was revealed. Finally, phenome-wide association studies in the 39,000 participants reveal associations between the axes angular metrics and phenotypes signalling an increased afterload, and an association to hypertension among other clinical conditions. These findings underscore the complex anatomical-electrical interplay and highlight the potential of cardiac axes biomarkers for an improved clinical ECG interpretation and disease characterisation.in PLoS Computational Biology on 2025-07-10 14:00:00 UTC.
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Nondisruptive inducible labeling of ER-membrane contact sites using the Lamin B receptor
by Laura Downie, Nuria Ferrandiz, Elizabeth Courthold, Megan Jones, Stephen J. Royle
Membrane contact sites (MCSs) are areas of close proximity between organelles that allow the exchange of material, among other roles. The endoplasmic reticulum (ER) has MCSs with a variety of organelles in the cell. MCSs are dynamic, responding to changes in cell state, and are, therefore, best visualized through inducible labeling methods. However, existing methods typically distort ER-MCSs, by expanding contacts or creating artificial ones. Here, we describe a new method for inducible labeling of ER-MCSs using the Lamin B receptor (LBR) and a generic anchor protein on the partner organelle. Termed LaBeRling, this versatile, one-to-many approach allows labeling of different types of ER-MCSs (mitochondria, plasma membrane, lysosomes, early endosomes, lipid droplets, and Golgi), on-demand, in interphase or mitotic human cells. LaBeRling is nondisruptive and does not change ER-MCSs in terms of the contact number, extent or distance measured; as determined by light microscopy or a deep-learning volume electron microscopy approach. We applied this method to study the changes in ER-MCSs during mitosis and to label novel ER-Golgi contact sites at different mitotic stages in live cells.in PLoS Biology on 2025-07-10 14:00:00 UTC.
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H3K4me2 distinguishes a distinct class of enhancers during the maternal-to-zygotic transition
by Matthew D. Hurton, Jennifer M. Miller, Miler T. Lee
After egg fertilization, an initially silent embryonic genome is transcriptionally activated during the maternal-to-zygotic transition. In zebrafish, maternal vertebrate pluripotency factors Nanog, Pou5f3 (OCT4 homolog), and Sox19b (SOX2 homolog) (NPS) play essential roles in orchestrating embryonic genome activation, acting as “pioneers” that open condensed chromatin and mediate acquisition of activating histone modifications. However, some embryonic gene transcription still occurs in the absence of these factors, suggesting the existence of other mechanisms regulating genome activation. To identify chromatin signatures of these unknown pathways, we profiled the histone modification landscape of zebrafish embryos using CUT&RUN. Our regulatory map revealed two subclasses of enhancers distinguished by presence or absence of H3K4me2. Enhancers lacking H3K4me2 tend to require NPS factors for de novo activation, while enhancers bearing H3K4me2 are epigenetically bookmarked by DNA hypomethylation to recapitulate gamete activity in the embryo, independent of NPS pioneering. Thus, parallel enhancer activation pathways combine to induce transcriptional reprogramming to pluripotency in the early embryo.in PLoS Biology on 2025-07-10 14:00:00 UTC.
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Wakefulness can be distinguished from general anesthesia and sleep in flies using a massive library of univariate time series analyses
by Angus Leung, Ahmed Mahmoud, Travis Jeans, Ben D. Fulcher, Bruno van Swinderen, Naotsugu Tsuchiya
The neural mechanisms of consciousness remain elusive. Previous studies on both human and non-human animals, through manipulation of level of conscious arousal, have reported that specific time-series features correlate with level of consciousness, such as spectral power in certain frequency bands. However, such features often lack principled, theoretical justifications as to why they should be related with level of consciousness. This raises two significant issues: firstly, many other types of times-series features which could also reflect conscious level have been ignored due to researcher biases toward specific analyses; and secondly, it is unclear how to interpret identified features to understand the neural activity underlying consciousness, especially when they are identified from recordings which summate activity across large areas such as electroencephalographic recordings. To address the first concern, here we propose a new approach: in the absence of any theoretical priors, we should be maximally agnostic and treat as many known features as feasible as equally promising candidates. To apply this approach, we use highly comparative time-series analysis (hctsa), a toolbox which provides over 7,700 different univariate time-series features originating from different research fields. To address the second issue, we employ hctsa to high-quality neural recordings from a relatively simple brain, the fly brain (Drosophila melanogaster), extracting features from local field potentials during wakefulness, general anesthesia, and sleep. At Stage 1 of this registered report, we constructed a classifier for each feature, for discriminating wakefulness and anesthesia in a discovery group of flies (N = 13). At Stage 2, we assessed their performances on four independent groups of evaluation flies, from which recordings were made during anesthesia and sleep, and which were originally blinded to the data analysis team (N = 49). We found only 47 time-series features, applied to recordings obtained from the center of the fly brain, to also significantly classify wake from anesthesia or sleep in all 4 of these evaluation datasets. Most of these were related to autocorrelation, and they indicated that signals during wakefulness remained correlated to their past for a longer timescale than during anesthesia and sleep. Meanwhile, time-series features related to well-known potential markers of consciousness, such as those related to complexity or spectral power, failed to generalize across all the flies. However, many of these complexity and spectral features have a consistent direction of effect due to anesthesia or sleep across flies, suggesting that even slight variations in experiment setup can reduce generalizability of classifiers. These results caution the current state of frequent discoveries of new potential consciousness markers, which may not generalize across datasets, and point to autocorrelation as a class of dynamical properties which does.in PLoS Biology on 2025-07-10 14:00:00 UTC.
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Estimation of Paddy Crop Water Usage in Indian Conditions Using Ensemble Learning [version 1; peer review: awaiting peer review]
Background In the Indian coastal state of Odisha, agriculture remains the primary livelihood, particularly paddy cultivation. However, traditional farming practices often result in inefficient resource use, particularly water. Given the state’s varied climatic zones and soil types, there is a pressing need for sustainable solutions. Precision agriculture, which utilizes advanced information technologies for decision-making, offers a pathway to enhance productivity while minimizing resource wastage. Methods This study applied machine learning (ML) and ensemble regression techniques to predict water usage for paddy cultivation in Odisha. The models were trained on a comprehensive dataset integrating remote sensing data, satellite imagery, historical weather records, soil profiles, and field-level observations. Various regression algorithms were used in ensemble combinations to enhance predictive accuracy and model robustness. Soil moisture, climatic conditions, and crop health indicators were continuously monitored using sensor-based and image-derived data. Results The ensemble regression models demonstrated high predictive accuracy, with performance metrics exceeding 90% in forecasting optimal water usage. These predictions enabled precise water management tailored to specific agro-climatic zones within Odisha. Furthermore, the models effectively supported crop recommendation strategies based on soil and environmental parameters, ensuring optimal resource allocation. Conclusions The integration of ML and ensemble regression in precision agriculture significantly improves water use efficiency and supports data-driven farming in coastal Odisha. By enabling accurate predictions of water needs and crop suitability, these technologies contribute to maximizing yield, conserving natural resources, and fostering long-term sustainability. The findings emphasize the potential for scalable, technology-driven solutions to modernize traditional agricultural practices in resource-constrained environments.in F1000Research on 2025-07-10 10:42:22 UTC.
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The importance of early biomarkers in the identification of neurodegenerative disorders [version 1; peer review: awaiting peer review]
In this datanote we presented the data of 31 iRBD (idiopathic Rapid eye movement (REM) sleep Behaviour Disorder) patients studied throughout three years to assess their eventual phenoconversion to Parkinson’s disease and other established neurodegenerative conditions. iRBD is a prodromal condition involved in the development of neurological pathologies such as Parkinson’s disease. In a previous study we evaluated transcription factor mRNA levels in CD4+ T cells as predictive biomarkers of phenoconversion in iRBD. We demonstrated that among the transcription factors mRNA levels analysed, STAT1, GATA3 and FOXP3 mRNA levels in CD4+ T cells may be used to predict phenoconversion.in F1000Research on 2025-07-10 10:40:43 UTC.
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Evaluating the Efficiency of Areke Distillation Process Using the Traditional Method of Distillation and Double Pipe Distillation: A Traditional Ethiopian Beverage [version 1; peer review: awaiting peer review]
Background Areke is a popular traditional distilled beverage in semi-urban and rural areas in Ethiopia. Traditional areke distillation uses an open fire system which consumes a lot of firewood and produces a large amount of indoor air pollution. Methods The areke distiller apparatus (heat exchanger, condenser, energy-efficient stoves, storage tanks, and local areke extraction apparatus) was manufactured by technicians (welders). Different types of grains (wheat, millet, lupine, barley, and maize) were purchased at the neighborhood market. The traditional method of areke fermentation was prepared by an experienced woman brewer using a combination of ingredients using appropriate steps and procedures. The efficacy of a traditional stove, a modified stove, and a combination of a modified stove and double pipe were evaluated. The amount of ethanol was estimated by measuring the refractive index and specific gravity. Sensory evaluation of areke samples was evaluated by 10 consumer sensory panelists. Result The greatest ethanol concentration of the areke (53.75 ± 0.01 (% v/v)) was obtained from millet E (dagusa E) in double pipe distillation (E). The maize E (bekolo E) of overall acceptance had the greatest score (4.5 ± 0.01) compared to other areke sensory parameters. The alcoholic strength of lupine E ( gibeto E) was scored excellent (5.0 ± 0.01) compared to other areke sensory parameters. All of the judges agreed that traditional and double pipe areke consumption was acceptable. The combination of double pipe distillation and modified stove resulted in a 50% ± 0.15 reduction in the average amount of firewood used. The traditional open fire stove consumed more firewood (5.1 kg ± 0.1) than the combination of double pipe distillation and modified stove (2.5 kg ± 0.01). Conclusion These results indicate that the combination of double pipe distillation with modified stove had a better performance compared to the traditional Areke distillation.in F1000Research on 2025-07-10 10:36:09 UTC.
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Glycogen supports glycolytic plasticity in neurons
Proceedings of the National Academy of Sciences, Volume 122, Issue 28, July 2025.
SignificanceIt has long been assumed that glycogen in the brain is primarily a glial energy reserve, with limited direct relevance to neurons. Yet, recent studies have demonstrated a role for glycogen in neuronal function. Here, we extend these findings, ...in PNAS on 2025-07-10 07:00:00 UTC.
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Human neuron subtype programming via single-cell transcriptome-coupled patterning screens
Science, Volume 389, Issue 6756, July 2025.
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A single theory for the evolution of sex chromosomes and the two rules of speciation
Science, Volume 389, Issue 6756, July 2025.
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Microglia replacement halts the progression of microgliopathy in mice and humans
Science, Volume 389, Issue 6756, July 2025.
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Cryo-EM structure of human telomerase dimer reveals H/ACA RNP-mediated dimerization
Science, Volume 389, Issue 6756, July 2025.
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Tissue-integrated bionic knee restores versatile legged movement after amputation
Science, Volume 389, Issue 6756, July 2025.
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Glymphatic dysfunction in Alzheimer’s disease: A critical appraisal
Science, Volume 389, Issue 6756, July 2025.
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Cities as transformative agents for global sustainability
Science, Volume 389, Issue 6756, July 2025.
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The boundless energy, and ego, of Luis Alvarez
Science, Volume 389, Issue 6756, Page 133-133, July 2025.
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Following in our footsteps
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Macrophage-derived oncostatin M repairs the lung epithelial barrier during inflammatory damage
Science, Volume 389, Issue 6756, Page 169-175, July 2025.
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ROS transfer at peroxisome-mitochondria contact regulates mitochondrial redox
Science, Volume 389, Issue 6756, Page 157-162, July 2025.
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Discrete spatiotemporal encoding of striatal dopamine transmission
Science, Volume 389, Issue 6756, Page 200-206, July 2025.
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Single- and multithread rivers originate from (im)balance between lateral erosion and accretion
Science, Volume 389, Issue 6756, Page 146-150, July 2025.
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Origins and diversity of Greenland’s Qimmit revealed with genomes of ancient and modern sled dogs
Science, Volume 389, Issue 6756, Page 163-168, July 2025.
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Overturning circulation structures the microbial functional seascape of the South Pacific
Science, Volume 389, Issue 6756, Page 176-182, July 2025.
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Harnessing carbene polarity: Unified catalytic access to donor, neutral, and acceptor carbenes
Science, Volume 389, Issue 6756, Page 183-189, July 2025.
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The forearc seismic belt: A fluid pathway constraining down-dip megathrust earthquake rupture
Science, Volume 389, Issue 6756, Page 190-194, July 2025.
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Compartmentalization reduces conflict in multipartner plant-insect symbioses
Science, Volume 389, Issue 6756, Page 151-156, July 2025.
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A fish out of water
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In Other Journals
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Organelles share the load
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Integrated prostheses restore dynamic movement
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Electronically diverse carbenes
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Replacing microglia to treat a brain disease
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China’s antismog push faces challenges
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PEPFAR disruptions could cause HIV resurgence
Science, Volume 389, Issue 6756, Page 135-135, July 2025.
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State law threatens Brazil’s high grasslands
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U.S. scientific workforce is set to shrink sharply
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