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Single‐Neuron Discharges Correlating High‐Frequency Oscillations Dynamics in Epileptogenesis and Epilepsy Development
High-frequency oscillations (HFO) generated by the microscale overexcitation circuits are promising biomarker of the epileptogenesis and epilepsy development.
ABSTRACT
The mechanism of epilepsy is still unclear. We aim to explore the relationship between high-frequency oscillations (HFOs) dynamics and epilepsy, with a focus on deciphering underlying mechanisms at the single-neuron level. Using a rat model of chronic focal cortical epilepsy induced by cobalt-wire implantation, we monitored the seizures and HFO dynamics, as well as the cross-frequency coupling trends between HFOs and theta activities. Additionally, excitatory and inhibitory neurons' discharges were recorded by 16-channel tetrode electrode, with comparisons made between the discharge rates and changes from baselines during different bands of HFOs (ripple:80-200 Hz; fast ripple, FRs:200-500 Hz). All rats (8/8) with cobalt-wire implantation developed spontaneous seizures within 4 to 8 days post-surgery, in contrast to the control group (3/3) with steel-wire insertion remaining seizure-free. HFOs exhibited a progressive increase over time post-surgery in the epilepsy model, while minimal HFOs was observed in the control group. HFOs recorded during the peak-seizure periods showed a propensity to synchronize with the trough of theta activity, coinciding with heightened seizure frequency. A substantial augmentation showed in the discharge rates of both putative excitatory and inhibitory neurons during HFO occurrences. The change ratios between putative excitatory and inhibitory neurons during ripples were smaller than those during FRs. In conclusion, we found that HFO dynamics reflect epileptogenic network formation, with implications for early seizure prediction and therapeutic interventions. Our data provide novel insights at cellular and cross-frequency level into the mechanistic underpinnings of HFO emergence and network reorganization offering potential strategies for targeting pathological network activity in epilepsy.
in Journal of Neuroscience Research on 2025-07-01 05:44:31 UTC.
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Hemispheric-Specific Coupling Improves Modeling of Functional Connectivity Using Wilson-Cowan Dynamics
arXiv:2506.22951v1 Announce Type: new Abstract: Large-scale neural mass models have been widely used to simulate resting-state brain activity from structural connectivity. In this work, we extend a well-established Wilson--Cowan framework by introducing a novel hemispheric-specific coupling scheme that differentiates between intra-hemispheric and inter-hemispheric structural interactions. We apply this model to empirical cortical connectomes and resting-state fMRI data from matched control and schizophrenia groups. Simulated functional connectivity is computed from the band-limited envelope correlations of regional excitatory activity and compared against empirical functional connectivity matrices. Our results show that incorporating hemispheric asymmetries enhances the correlation between simulated and empirical functional connectivity, highlighting the importance of anatomically-informed coupling strategies in improving the biological realism of large-scale brain network models.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Distinct Modes of Functional Neural Organization in Autism: Insights from Dynamical Systems Analysis of Resting-State EEG
arXiv:2506.23013v1 Announce Type: new Abstract: While differences in patterns of functional connectivity and neural synchronization have been reported between individuals on the autism spectrum and neurotypical peers at various age stages, these differences appear to be subtle and may not be captured by typical quantitative measures of EEG. We used the dynamical systems approach to analyze resting-state EEG to investigate fine-grained spatiotemporal organization of brain networks in autistic and neurotypical young adults. While power spectra showed minimal group differences, autistic participants exhibited higher Lyapunov exponents (indicating less stable neural dynamics), weaker phase synchronization, and lower clustering/efficiency of functional networks during eyes-open resting state, suggesting more random and less stably connected neural dynamics in comparison to those of neurotypical peers. Closing the eyes regularized neural dynamics in autistic but not neurotypical participants, with increases in synchrony strength, transient desynchronization patterning, and functional connectivity observed in the autistic group. The results point to the distinct modes of neural dynamics organization that could reflect life-long adaptations to sensory inputs that shape both resting-state neural activity and cognitive processing strategies.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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An Interpretable Transformer-Based Foundation Model for Cross-Procedural Skill Assessment Using Raw fNIRS Signals
arXiv:2506.22476v1 Announce Type: cross Abstract: Objective skill assessment in high-stakes procedural environments requires models that not only decode underlying cognitive and motor processes but also generalize across tasks, individuals, and experimental contexts. While prior work has demonstrated the potential of functional near-infrared spectroscopy (fNIRS) for evaluating cognitive-motor performance, existing approaches are often task-specific, rely on extensive preprocessing, and lack robustness to new procedures or conditions. Here, we introduce an interpretable transformer-based foundation model trained on minimally processed fNIRS signals for cross-procedural skill assessment. Pretrained using self-supervised learning on data from laparoscopic surgical tasks and endotracheal intubation (ETI), the model achieves greater than 88% classification accuracy on all tasks, with Matthews Correlation Coefficient exceeding 0.91 on ETI. It generalizes to a novel emergency airway procedure--cricothyrotomy--using fewer than 30 labeled samples and a lightweight (less than 2k parameter) adapter module, attaining an AUC greater than 87%. Interpretability is achieved via a novel channel attention mechanism--developed specifically for fNIRS--that identifies functionally coherent prefrontal sub-networks validated through ablation studies. Temporal attention patterns align with task-critical phases and capture stress-induced changes in neural variability, offering insight into dynamic cognitive states.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Hierarchical Characterization of Brain Dynamics via State Space-based Vector Quantization
arXiv:2506.22952v1 Announce Type: cross Abstract: Understanding brain dynamics through functional Magnetic Resonance Imaging (fMRI) remains a fundamental challenge in neuroscience, particularly in capturing how the brain transitions between various functional states. Recently, metastability, which refers to temporarily stable brain states, has offered a promising paradigm to quantify complex brain signals into interpretable, discretized representations. In particular, compared to cluster-based machine learning approaches, tokenization approaches leveraging vector quantization have shown promise in representation learning with powerful reconstruction and predictive capabilities. However, most existing methods ignore brain transition dependencies and lack a quantification of brain dynamics into representative and stable embeddings. In this study, we propose a Hierarchical State space-based Tokenization network, termed HST, which quantizes brain states and transitions in a hierarchical structure based on a state space-based model. We introduce a refined clustered Vector-Quantization Variational AutoEncoder (VQ-VAE) that incorporates quantization error feedback and clustering to improve quantization performance while facilitating metastability with representative and stable token representations. We validate our HST on two public fMRI datasets, demonstrating its effectiveness in quantifying the hierarchical dynamics of the brain and its potential in disease diagnosis and reconstruction performance. Our method offers a promising framework for the characterization of brain dynamics, facilitating the analysis of metastability.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
arXiv:2506.23075v1 Announce Type: cross Abstract: Understanding and decoding brain activity from electroencephalography (EEG) signals is a fundamental challenge in neuroscience and AI, with applications in cognition, emotion recognition, diagnosis, and brain-computer interfaces. While recent EEG foundation models advance generalized decoding via unified architectures and large-scale pretraining, they adopt a scale-agnostic dense modeling paradigm inherited from NLP and vision. This design neglects a core property of neural activity: cross-scale spatiotemporal structure. EEG task patterns span a wide range of temporal and spatial scales, from short bursts to slow rhythms, and from localized cortical responses to distributed interactions. Ignoring this diversity leads to suboptimal representations and weak generalization. We propose CSBrain, a Cross-scale Spatiotemporal Brain foundation model for generalized EEG decoding. CSBrain introduces: (i) Cross-scale Spatiotemporal Tokenization (CST), which aggregates multi-scale features from localized temporal windows and anatomical brain regions into compact scale-aware tokens; and (ii) Structured Sparse Attention (SSA), which captures cross-window and cross-region dependencies, enhancing scale diversity while removing spurious correlations. CST and SSA are alternately stacked to progressively integrate multi-scale dependencies. Experiments on 11 EEG tasks across 16 datasets show that CSBrain consistently outperforms task-specific and foundation model baselines. These results establish cross-scale modeling as a key inductive bias and position CSBrain as a robust backbone for future brain-AI research.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Objective-Free Local Learning and Emergent Language Structure in Thinking Machines
arXiv:2506.23293v1 Announce Type: cross Abstract: We present a neuro-symbolic framework for generative language modeling based on local, event-driven emergent learning. At its core is a hierarchical Hopfield memory chain acting as a compositional short-term memory and dynamic tokenizer (retokenizer). Rather than relying on predefined tokens or supervision, the model builds structure from scratch, learning symbol sequences as multi-scale representations. It constructs projection tensors that bind co-occurring features into hierarchical tokens, introducing redundancy (i.e an emergent gauge structure) and enabling compression of local activations into long-range dependencies. Curiously, we find that the retokenizer can filter natural language patterns from noise, generating synthetic languages with coherent internal morphology -- quantifiably the same as human language. Language is learned in a local (Hebbian) fashion, where model constraints dictate allowed emergent structure, and new information is retained in alignment with this structure. The absence of a global objective enables a form of plasticity not found in conventional language models, allowing the system to generalize beyond its initial inference class -- even without explicit data. We demonstrate that briefly activating a new neuron during inference binds distributed multi-scale token features into a symbolic embedding. These emergent embedding neurons act as long-term memory and support a key-value mechanism for compositional inference and generalization. This architecture provides a methodological foundation for studying how symbolic structure can emerge from local neural learning. It offers a new pathway for building scalable, interpretable neuro-symbolic systems -- where tokens, grammar, and reasoning arise as compressed memory traces within a Hopfield hierarchy. This approach advances the development of neuromorphic architectures for generative language models.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Peripheral brain interfacing: Reading high-frequency brain signals from the output of the nervous system
arXiv:2410.20872v2 Announce Type: replace Abstract: Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human-machine interfacing. However, technologies used to directly measure CNS activity are limited by their resolution, sensitivity to interferences, and invasiveness. Advances in muscle recordings and deep learning allow us to decode the spiking activity of spinal motor neurons (MNs) in real time and with high accuracy. MNs represent the motor output layer of the CNS, receiving and sampling signals originating in different regions in the nervous system, and generating the neural commands that control muscles. The input signals to MNs can be estimated from the MN outputs. Here we argue that peripheral neural interfaces using muscle sensors represent a promising, non-invasive approach to estimate some neural activity from the CNS that reaches the MNs but does not directly modulate force production. We also discuss the evidence supporting this concept, and the necessary advances to consolidate and test MN-based CNS interfaces in controlled and real-world settings.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Functional Correspondences in the Human and Marmoset Visual Cortex During Movie Watching: Insights from Correlation, Redundancy, and Synergy
arXiv:2503.15218v3 Announce Type: replace Abstract: The world of beauty is deeply connected to the visual cortex, as perception often begins with vision in both humans and marmosets. In this study, to investigate their functional correspondences, we used 13 healthy human volunteers (9 males and 4 females, aged 22-56 years) and 8 common marmosets (6 males and 2 females, aged 20-42 months). We then measured pairwise and beyond-pairwise correlations, redundancy, and synergy in movie-driven fMRI data across species. First, we consistently observed a high degree of functional similarity in visual processing within and between species, suggesting that integrative processing mechanisms are preserved in both humans and marmosets, despite potential differences in their specific activity patterns. Second, we found that the strongest functional correspondences during movie watching occurred between the human peri-entorhinal and entorhinal cortex (PeEc) and the occipitotemporal high-level visual regions in the marmoset, reflecting a synergistic functional relationship. This suggests that these regions share complementary and integrated patterns of information processing across species. Third, redundancy measures maintained stable high-order hubs, indicating a steady core of shared information processing, while synergy measures revealed a dynamic shift from low- to high-level visual regions as interaction increased, reflecting adaptive integration. This highlights distinct patterns of information processing across the visual hierarchy. Ultimately, our results reveal the marmoset as a compelling model for investigating visual perception, distinguished by its remarkable functional parallels to the human visual cortex.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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The Relationship between Cognition and Computation: "Global-first" Cognition versus Local-first Computation
arXiv:2506.17970v3 Announce Type: replace Abstract: What fundamental research questions are essential for advancing toward brain-inspired AI or AGI capable of performing any intellectual task a human can? We believe the key question today is the relationship between cognition and computation (RCC). For example, the widely discussed question "Will artificial intelligence replace the human mind?" is, in essence and in scientific terms, an issue concerning RCC. We have chosen to classify RCC into four categories: 1. The relationship between the primitives of cognition and the primitives of computation. 2. The relationship between the anatomical structure of neural representation of cognition and the computational architecture of artificial intelligence. 3. The relationship between emergents in cognition and emergents in computation. 4. The relationship between the mathematical foundations of cognition and computation. The cumulative empirical evidence and theoretical analyses led us to formulate the "Global-first" principle, which highlights the contrast between "Global-first" cognition and local-first computation in RCC, offering a specific and well-defined starting point for understanding RCC.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Automatic Depression Assessment using Machine Learning: A Comprehensive Survey
arXiv:2506.18915v2 Announce Type: replace Abstract: Depression is a common mental illness across current human society. Traditional depression assessment relying on inventories and interviews with psychologists frequently suffer from subjective diagnosis results, slow and expensive diagnosis process as well as lack of human resources. Since there is a solid evidence that depression is reflected by various human internal brain activities and external expressive behaviours, early traditional machine learning (ML) and advanced deep learning (DL) models have been widely explored for human behaviour-based automatic depression assessment (ADA) since 2012. However, recent ADA surveys typically only focus on a limited number of human behaviour modalities. Despite being used as a theoretical basis for developing ADA approaches, existing ADA surveys lack a comprehensive review and summary of multi-modal depression-related human behaviours. To bridge this gap, this paper specifically summarises depression-related human behaviours across a range of modalities (e.g. the human brain, verbal language and non-verbal audio/facial/body behaviours). We focus on conducting an up-to-date and comprehensive survey of ML-based ADA approaches for learning depression cues from these behaviours as well as discussing and comparing their distinctive features and limitations. In addition, we also review existing ADA competitions and datasets, identify and discuss the main challenges and opportunities to provide further research directions for future ADA researchers.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Brain-inspired and Self-based Artificial Intelligence
arXiv:2402.18784v2 Announce Type: replace-cross Abstract: The question "Can machines think?" and the Turing Test to assess whether machines could achieve human-level intelligence is one of the roots of AI. With the philosophical argument "I think, therefore I am", this paper challenge the idea of a "thinking machine" supported by current AIs since there is no sense of self in them. Current artificial intelligence is only seemingly intelligent information processing and does not truly understand or be subjectively aware of oneself and perceive the world with the self as human intelligence does. In this paper, we introduce a Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm. This BriSe AI paradigm is dedicated to coordinating various cognitive functions and learning strategies in a self-organized manner to build human-level AI models and robotic applications. Specifically, BriSe AI emphasizes the crucial role of the Self in shaping the future AI, rooted with a practical hierarchical Self framework, including Perception and Learning, Bodily Self, Autonomous Self, Social Self, and Conceptual Self. The hierarchical framework of the Self highlights self-based environment perception, self-bodily modeling, autonomous interaction with the environment, social interaction and collaboration with others, and even more abstract understanding of the Self. Furthermore, the positive mutual promotion and support among multiple levels of Self, as well as between Self and learning, enhance the BriSe AI's conscious understanding of information and flexible adaptation to complex environments, serving as a driving force propelling BriSe AI towards real Artificial General Intelligence.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Statistical Mechanics of Support Vector Regression
arXiv:2412.05439v2 Announce Type: replace-cross Abstract: A key problem in deep learning and computational neuroscience is relating the geometrical properties of neural representations to task performance. Here, we consider this problem for continuous decoding tasks where neural variability may affect task precision. Using methods from statistical mechanics, we study the average-case learning curves for $\varepsilon$-insensitive Support Vector Regression ($\varepsilon$-SVR) and discuss its capacity as a measure of linear decodability. Our analysis reveals a phase transition in training error at a critical load, capturing the interplay between the tolerance parameter $\varepsilon$ and neural variability. We uncover a double-descent phenomenon in the generalization error, showing that $\varepsilon$ acts as a regularizer, both suppressing and shifting these peaks. Theoretical predictions are validated both with toy models and deep neural networks, extending the theory of Support Vector Machines to continuous tasks with inherent neural variability.in arXiv: Quantitative Biology: Neurons and Cognition on 2025-07-01 04:00:00 UTC.
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Neural Langevin Machine: a local asymmetric learning rule can be creative
arXiv:2506.23546v1 Announce Type: cross Abstract: Fixed points of recurrent neural networks can be leveraged to store and generate information. These fixed points can be captured by the Boltzmann-Gibbs measure, which leads to neural Langevin dynamics that can be used for sampling and learning a real dataset. We call this type of generative model neural Langevin machine, which is interpretable due to its analytic form of distribution and is simple to train. Moreover, the learning process is derived as a local asymmetric plasticity rule, bearing biological relevance. Therefore, one can realize a continuous sampling of creative dynamics in a neural network, mimicking an imagination process in brain circuits. This neural Langevin machine may be another promising generative model, at least in its strength in circuit-based sampling and biologically plausible learning rule.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Can "consciousness" be observed from large language model (LLM) internal states? Dissecting LLM representations obtained from Theory of Mind test with Integrated Information Theory and Span Representation analysis
arXiv:2506.22516v1 Announce Type: cross Abstract: Integrated Information Theory (IIT) provides a quantitative framework for explaining consciousness phenomenon, positing that conscious systems comprise elements integrated through causal properties. We apply IIT 3.0 and 4.0 -- the latest iterations of this framework -- to sequences of Large Language Model (LLM) representations, analyzing data derived from existing Theory of Mind (ToM) test results. Our study systematically investigates whether the differences of ToM test performances, when presented in the LLM representations, can be revealed by IIT estimates, i.e., $\Phi^{\max}$ (IIT 3.0), $\Phi$ (IIT 4.0), Conceptual Information (IIT 3.0), and $\Phi$-structure (IIT 4.0). Furthermore, we compare these metrics with the Span Representations independent of any estimate for consciousness. This additional effort aims to differentiate between potential "consciousness" phenomena and inherent separations within LLM representational space. We conduct comprehensive experiments examining variations across LLM transformer layers and linguistic spans from stimuli. Our results suggest that sequences of contemporary Transformer-based LLM representations lack statistically significant indicators of observed "consciousness" phenomena but exhibit intriguing patterns under $\textit{spatio}$-permutational analyses. The Appendix and code are available as Supplementary Materials at: https://doi.org/10.1016/j.nlp.2025.100163.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Towards Efficient and Accurate Spiking Neural Networks via Adaptive Bit Allocation
arXiv:2506.23717v1 Announce Type: new Abstract: Multi-bit spiking neural networks (SNNs) have recently become a heated research spot, pursuing energy-efficient and high-accurate AI. However, with more bits involved, the associated memory and computation demands escalate to the point where the performance improvements become disproportionate. Based on the insight that different layers demonstrate different importance and extra bits could be wasted and interfering, this paper presents an adaptive bit allocation strategy for direct-trained SNNs, achieving fine-grained layer-wise allocation of memory and computation resources. Thus, SNN's efficiency and accuracy can be improved. Specifically, we parametrize the temporal lengths and the bit widths of weights and spikes, and make them learnable and controllable through gradients. To address the challenges caused by changeable bit widths and temporal lengths, we propose the refined spiking neuron, which can handle different temporal lengths, enable the derivation of gradients for temporal lengths, and suit spike quantization better. In addition, we theoretically formulate the step-size mismatch problem of learnable bit widths, which may incur severe quantization errors to SNN, and accordingly propose the step-size renewal mechanism to alleviate this issue. Experiments on various datasets, including the static CIFAR and ImageNet and the dynamic CIFAR-DVS and DVS-GESTURE, demonstrate that our methods can reduce the overall memory and computation cost while achieving higher accuracy. Particularly, our SEWResNet-34 can achieve a 2.69\% accuracy gain and 4.16$\times$ lower bit budgets over the advanced baseline work on ImageNet. This work will be fully open-sourced.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Marker Gene Method : Identifying Stable Solutions in a Dynamic Environment
arXiv:2506.23734v1 Announce Type: new Abstract: Competitive Co-evolutionary Algorithms (CCEAs) are often hampered by complex dynamics like intransitivity and the Red Queen effect, leading to unstable convergence. To counter these challenges, this paper introduces the Marker Gene Method (MGM), a framework that establishes stability by using a 'marker gene' as a dynamic benchmark and an adaptive weighting mechanism to balance exploration and exploitation. We provide rigorous mathematical proofs demonstrating that MGM creates strong attractors near Nash Equilibria within the Strictly Competitive Game framework. Empirically, MGM demonstrates its efficacy across a spectrum of challenges: it stabilizes the canonical Rock-Paper-Scissors game, significantly improves the performance of C-RMOEA/D on ZDT benchmarks, and, when augmented with a Memory Pool (MP) extension, it successfully tames the notoriously pathological Shapley Biased Game. This work presents a theoretically sound and empirically validated framework that substantially enhances the stability and robustness of CCEAs in complex competitive environments.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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More Efficient Real-Valued Gray-Box Optimization through Incremental Distribution Estimation in RV-GOMEA
arXiv:2506.23738v1 Announce Type: new Abstract: The Gene-pool Optimal Mixing EA (GOMEA) family of EAs offers a specific means to exploit problem-specific knowledge through linkage learning, i.e., inter-variable dependency detection, expressed using subsets of variables, that should undergo joint variation. Such knowledge can be exploited if faster fitness evaluations are possible when only a few variables are changed in a solution, enabling large speed-ups. The recent-most version of Real-Valued GOMEA (RV-GOMEA) can learn a conditional linkage model during optimization using fitness-based linkage learning, enabling fine-grained dependency exploitation in learning and sampling a Gaussian distribution. However, while the most efficient Gaussian-based EAs, like NES and CMA-ES, employ incremental learning of the Gaussian distribution rather than performing full re-estimation every generation, the recent-most RV-GOMEA version does not employ such incremental learning. In this paper, we therefore study whether incremental distribution estimation can lead to efficiency enhancements of RV-GOMEA. We consider various benchmark problems with varying degrees of overlapping dependencies. We find that, compared to RV-GOMEA and VKD-CMA-ES, the required number of evaluations to reach high-quality solutions can be reduced by a factor of up to 1.5 if population sizes are tuned problem-specifically, while a reduction by a factor of 2-3 can be achieved with generic population-sizing guidelines.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Unsupervised Sparse Coding-based Spiking Neural Network for Real-time Spike Sorting
arXiv:2506.24041v1 Announce Type: new Abstract: Spike sorting is a crucial step in decoding multichannel extracellular neural signals, enabling the identification of individual neuronal activity. A key challenge in brain-machine interfaces (BMIs) is achieving real-time, low-power spike sorting at the edge while keeping high neural decoding performance. This study introduces the Neuromorphic Sparse Sorter (NSS), a compact two-layer spiking neural network optimized for efficient spike sorting. NSS leverages the Locally Competitive Algorithm (LCA) for sparse coding to extract relevant features from noisy events with reduced computational demands. NSS learns to sort detected spike waveforms in an online fashion and operates entirely unsupervised. To exploit multi-bit spike coding capabilities of neuromorphic platforms like Intel's Loihi 2, a custom neuron model was implemented, enabling flexible power-performance trade-offs via adjustable spike bit-widths. Evaluations on simulated and real-world tetrode signals with biological drift showed NSS outperformed established pipelines such as WaveClus3 and PCA+KMeans. With 2-bit graded spikes, NSS on Loihi 2 outperformed NSS implemented with leaky integrate-and-fire neuron and achieved an F1-score of 77% (+10% improvement) while consuming 8.6mW (+1.65mW) when tested on a drifting recording, with a computational processing time of 0.25ms (+60 us) per inference.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Correlated Mutations for Integer Programming
arXiv:2506.22526v1 Announce Type: cross Abstract: Even with the recent theoretical advancements that dramatically reduced the complexity of Integer Programming (IP), heuristics remain the dominant problem-solvers for this difficult category. This study seeks to establish the groundwork for Integer Evolution Strategies (IESs), a class of randomized search heuristics inherently designed for continuous spaces. IESs already excel in treating IP in practice, but accomplish it via discretization and by applying sophisticated patches to their continuous operators, while persistently using the $\ell_2$-norm as their operation pillar. We lay foundations for discrete search, by adopting the $\ell_1$-norm, accounting for the suitable step-size, and questioning alternative measures to quantify correlations over the integer lattice. We focus on mutation distributions for unbounded integer decision variables. We briefly discuss a couple of candidate discrete probabilities induced by the uniform and binomial distributions, which we show to possess less appealing theoretical properties, and then narrow down to the Truncated Normal (TN) and Double Geometric (DG) distributions. We explore their theoretical properties, including entropy functions, and propose a procedure to generate scalable correlated mutation distributions. Our investigations are accompanied by extensive numerical simulations, which consistently support the claim that the DG distribution is better suited for unbounded integer search. We link our theoretical perspective to empirical evidence indicating that an IES with correlated DG mutations outperformed other strategies over non-separable quadratic IP. We conclude that while the replacement of the default TN distribution by the DG is theoretically justified and practically beneficial, the truly crucial change lies in adopting the $\ell_1$-norm over the $\ell_2$-norm.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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FF-INT8: Efficient Forward-Forward DNN Training on Edge Devices with INT8 Precision
arXiv:2506.22771v1 Announce Type: cross Abstract: Backpropagation has been the cornerstone of neural network training for decades, yet its inefficiencies in time and energy consumption limit its suitability for resource-constrained edge devices. While low-precision neural network quantization has been extensively researched to speed up model inference, its application in training has been less explored. Recently, the Forward-Forward (FF) algorithm has emerged as a promising alternative to backpropagation, replacing the backward pass with an additional forward pass. By avoiding the need to store intermediate activations for backpropagation, FF can reduce memory footprint, making it well-suited for embedded devices. This paper presents an INT8 quantized training approach that leverages FF's layer-by-layer strategy to stabilize gradient quantization. Furthermore, we propose a novel "look-ahead" scheme to address limitations of FF and improve model accuracy. Experiments conducted on NVIDIA Jetson Orin Nano board demonstrate 4.6% faster training, 8.3% energy savings, and 27.0% reduction in memory usage, while maintaining competitive accuracy compared to the state-of-the-art.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
arXiv:2506.23165v1 Announce Type: cross Abstract: Safety is an essential requirement for reinforcement learning systems. The newly emerging framework of robust constrained Markov decision processes allows learning policies that satisfy long-term constraints while providing guarantees under epistemic uncertainty. This paper presents mirror descent policy optimisation for robust constrained Markov decision processes (RCMDPs), making use of policy gradient techniques to optimise both the policy (as a maximiser) and the transition kernel (as an adversarial minimiser) on the Lagrangian representing a constrained MDP. In the oracle-based RCMDP setting, we obtain an $\mathcal{O}\left(\frac{1}{T}\right)$ convergence rate for the squared distance as a Bregman divergence, and an $\mathcal{O}\left(e^{-T}\right)$ convergence rate for entropy-regularised objectives. In the sample-based RCMDP setting, we obtain an $\tilde{\mathcal{O}}\left(\frac{1}{T^{1/3}}\right)$ convergence rate. Experiments confirm the benefits of mirror descent policy optimisation in constrained and unconstrained optimisation, and significant improvements are observed in robustness tests when compared to baseline policy optimisation algorithms.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Benchmarking Spiking Neural Network Learning Methods with Varying Locality
arXiv:2402.01782v2 Announce Type: replace Abstract: Spiking Neural Networks (SNNs), providing more realistic neuronal dynamics, have been shown to achieve performance comparable to Artificial Neural Networks (ANNs) in several machine learning tasks. Information is processed as spikes within SNNs in an event-based mechanism that significantly reduces energy consumption. However, training SNNs is challenging due to the non-differentiable nature of the spiking mechanism. Traditional approaches, such as Backpropagation Through Time (BPTT), have shown effectiveness but come with additional computational and memory costs and are biologically implausible. In contrast, recent works propose alternative learning methods with varying degrees of locality, demonstrating success in classification tasks. In this work, we show that these methods share similarities during the training process, while they present a trade-off between biological plausibility and performance. Further, given the implicitly recurrent nature of SNNs, this research investigates the influence of the addition of explicit recurrence to SNNs. We experimentally prove that the addition of explicit recurrent weights enhances the robustness of SNNs. We also investigate the performance of local learning methods under gradient and non-gradient-based adversarial attacks.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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TMN: A Lightweight Neuron Model for Efficient Nonlinear Spike Representation
arXiv:2408.17245v3 Announce Type: replace Abstract: Spike trains serve as the primary medium for information transmission in Spiking Neural Networks, playing a crucial role in determining system efficiency. Existing encoding schemes based on spike counts or timing often face severe limitations under low-timestep constraints, while more expressive alternatives typically involve complex neuronal dynamics or system designs, which hinder scalability and practical deployment. To address these challenges, we propose the Ternary Momentum Neuron (TMN), a novel neuron model featuring two key innovations: (1) a lightweight momentum mechanism that realizes exponential input weighting by doubling the membrane potential before integration, and (2) a ternary predictive spiking scheme which employs symmetric sub-thresholds $\pm\frac{1}{2}v_{th}$ to enable early spiking and correct over-firing. Extensive experiments across diverse tasks and network architectures demonstrate that the proposed approach achieves high-precision encoding with significantly fewer timesteps, providing a scalable and hardware-aware solution for next-generation SNN computing.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Connecting phases of matter to the flatness of the loss landscape in analog variational quantum algorithms
arXiv:2506.13865v2 Announce Type: replace-cross Abstract: Variational quantum algorithms (VQAs) promise near-term quantum advantage, yet parametrized quantum states commonly built from the digital gate-based approach often suffer from scalability issues such as barren plateaus, where the loss landscape becomes flat. We study an analog VQA ans\"atze composed of $M$ quenches of a disordered Ising chain, whose dynamics is native to several quantum simulation platforms. By tuning the disorder strength we place each quench in either a thermalized phase or a many-body-localized (MBL) phase and analyse (i) the ans\"atze's expressivity and (ii) the scaling of loss variance. Numerics shows that both phases reach maximal expressivity at large $M$, but barren plateaus emerge at far smaller $M$ in the thermalized phase than in the MBL phase. Exploiting this gap, we propose an MBL initialisation strategy: initialise the ans\"atze in the MBL regime at intermediate quench $M$, enabling an initial trainability while retaining sufficient expressivity for subsequent optimization. The results link quantum phases of matter and VQA trainability, and provide practical guidelines for scaling analog-hardware VQAs.in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-07-01 04:00:00 UTC.
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Mechanisms Involved in Corticotropin-Releasing Factor-Induced Excitation of Entorhinal Neurons and Facilitation of Glutamate Release at the Perforant Pathway
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2025-07-01 01:31:49 UTC.
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Experience-induced NPAS4 reduces dendritic inhibition from CCK+ inhibitory neurons and enhances plasticity.
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2025-07-01 01:31:05 UTC.
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The effects of medial gastrocnemius muscle fatigue on regional modulation of the ankle plantarflexors during standing external perturbations
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2025-07-01 01:30:49 UTC.
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Turmoil at US science academy as Trump cuts force layoffs
Nature, Published online: 01 July 2025; doi:10.1038/d41586-025-01939-7
Efforts by leaders of the US national academies to adjust to the new political reality have spurred member concerns about capitulation and censorship.in Nature on 2025-07-01 00:00:00 UTC.
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Uncovering memorization effect in the presence of spurious correlations
Nature Communications, Published online: 01 July 2025; doi:10.1038/s41467-025-61531-5
Spurious feature reliance is a challenge in achieving balanced performance in machine learning models. Here, the authors demonstrate that a small subset of neurons are responsible for memorizing spurious correlations and show that this concentrated memorization contributes to imbalanced performance.in Nature Communications on 2025-07-01 00:00:00 UTC.
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Protein kinase A is a dependent factor and therapeutic target in mouse models of fibrous dysplasia
Nature Communications, Published online: 01 July 2025; doi:10.1038/s41467-025-61402-z
This study shows that protein kinase A (PKA) drives bone lesions in fibrous dysplasia and that targeting it in mouse models reduces disease severity, highlighting PKA as a promising therapeutic target for fibrous dysplasia.in Nature Communications on 2025-07-01 00:00:00 UTC.
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Suppression of gut colonization by multidrug-resistant Escherichia coli clinical isolates through cooperative niche exclusion
Nature Communications, Published online: 01 July 2025; doi:10.1038/s41467-025-61327-7
In this work, authors explore the potential of strain-specific commensal E. coli in their ability to inhibit multi-drug resistant Enterobacterales via nutrient competition. Their findings highlight the potential of rationally designed metabolically complementary probiotics for targeted gut decolonization of antibiotic-resistant bacteria.in Nature Communications on 2025-07-01 00:00:00 UTC.
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GPerturb: Gaussian process modelling of single-cell perturbation data
Nature Communications, Published online: 01 July 2025; doi:10.1038/s41467-025-61165-7
Single-cell CRISPR screens enable high-throughput analysis of how genetic changes affect individual cells. Here, authors present GPerturb, a method that accurately detects and quantifies gene-level effects of perturbations, with uncertainty estimates, revealing complex biological interactions.in Nature Communications on 2025-07-01 00:00:00 UTC.
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PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cell
Scientific Data, Published online: 01 July 2025; doi:10.1038/s41597-025-05452-4
PW-BALFC, a clinical dataset for detection and instance segmentation of bronchoalveolar lavage fluid cellin Nature scientific data on 2025-07-01 00:00:00 UTC.
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A neuromorphic model of active vision shows how spatiotemporal encoding in lobula neurons can aid pattern recognition in bees
Bees’ remarkable visual learning abilities make them ideal for studying active information acquisition and representation. Here, we develop a biologically inspired model to examine how flight behaviours during visual scanning shape neural representation in the insect brain, exploring the interplay between scanning behaviour, neural connectivity, and visual encoding efficiency. Incorporating non-associative learning—adaptive changes without reinforcement—and exposing the model to sequential natural images during scanning, we obtain results that closely match neurobiological observations. Active scanning and non-associative learning dynamically shape neural activity, optimising information flow and representation. Lobula neurons, crucial for visual integration, self-organise into orientation-selective cells with sparse, decorrelated responses to orthogonal bar movements. They encode a range of orientations, biased by input speed and contrast, suggesting co-evolution with scanning behaviour to enhance visual representation and support efficient coding. To assess the significance of this spatiotemporal coding, we extend the model with circuitry analogous to the mushroom body, a region linked to associative learning. The model demonstrates robust performance in pattern recognition, implying a similar encoding mechanism in insects. Integrating behavioural, neurobiological, and computational insights, this study highlights how spatiotemporal coding in the lobula efficiently compresses visual features, offering broader insights into active vision strategies and bio-inspired automation.in eLife on 2025-07-01 00:00:00 UTC.
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Translation, reliability, and validation of the Dutch Safe Use of Mobility Aid Checklist (SUMAC-NL) for walker use in people living with dementia [version 3; peer review: 1 approved, 1 approved with reservations]
Background People with dementia have a yearly risk of falling of 60 to 80 percent. Therefore, a walker is often recommended. However, the use of a walker in people with dementia is associated with a threefold increased odds of falls compared to their healthy peers who walk with a walker. Assessing walking skills with a walker can improve the quality of advice on its use. Therefore, a tool to assess functional walking skills with a walker is needed. The SUMAC was developed to fill this gap. So far, there is no Dutch instrument available that can assess functional walking skills with a walker in people with dementia. Methods Reliability was evaluated by scoring videos of people with dementia (n = 9) using a walker performing the SUMAC-NL. ICC was used to assess inter-rater and test-retest reliability. An expert panel (n = 8) evaluated the content validity using the content validity index (CVI) and the content validity ratio (CVR). Results Inter-rater reliability of the SUMAC-NL was statistically significant for the physical function (PF) domain (ICC = 0.94, 95%CI (0.84, 0.98, p < 0.001) and for the interaction with equipment (EQ) domain (ICC = 0.79, 95%CI (0.49 – 0.95), p < 0.001). Test-retest reliability was statistically significant for both the PF domain (ICC = 0.95, 95%CI (0.89, 0.99), p < 0.001) and EQ domain (ICC = 0.92, 95%CI (0.82, 0.98), p < 0.001). The SUMAC-NL shows content validity with a CVI >0.79 for both domains and a CVR of 0.53 on the PF domain and 0.78 on the EQ domain. Conclusions The SUMAC-NL shows good to excellent reliability and content validity for both the PF and the EQ domain. The SUMAC-NL seems to be a promising tool to assess walking with a walker in people with dementia in the Netherlands.in F1000Research on 2025-06-30 15:03:16 UTC.
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Culture as a Determinant of Health and Well-being: Expanding the Concept of Cultural Capital [version 1; peer review: awaiting peer review]
Abstract Introduction Cultural capital, conceptualized by Bourdieu, is a form of individual capital facilitating social mobility. Although local culture has been recognized as important in global health interventions, epidemiology, which is a key discipline evaluating such interventions, lacks conceptual frameworks and tools to measure cultural capital. This paper aims to identify challenges in adapting Bourdieu’s theory of cultural capital to public health and epidemiology, and to provide proposals to address them. Methods A theory adaptation approach, drawing on insights from public health, epidemiology, cultural anthropology, and related fields. Results and Discussion We identify five key challenges: 1. the epistemological divergence between Bourdieu’s focus on power structures and public health’s focus on health promotion; 2. the need to consider intervention-oriented cultural capital concept; 3. the need to assess cultural capital at the collective level; 4. the need for cultural capital concept that encompasses human nature beyond the social space; and 5. the unclear and inconsistent definitions of culture across research fields. For each challenge, we propose corresponding conceptual frameworks to facilitate the integration of cultural capital into public health and epidemiological research. Finally, we discuss the collective and existential properties of cultural and other forms of capital, arguing the liberating and constraining effects of capital (e.g., the risks of stereotyping specific subpopulations). Conclusion This study represents an initial step toward establishing cultural epidemiology as a field that quantitatively assesses the role of culture in shaping health and well-being. Future empirical research is needed to operationalize and apply these frameworks.in F1000Research on 2025-06-30 15:00:33 UTC.
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H- and m-channel overexpression promotes seizure-like events by impairing the ability of inhibitory neurons to process correlated inputs
by Scott Rich, Taufik A. Valiante, Jérémie Lefebvre
Channelopathies affecting the hyperpolarization-activated cyclic nucleotide gated (HCN or h-) channel and the Kv7 voltage gated m-type potassium (m-) channel present a paradox in epilepsy research: despite experimental evidence that both over- and underexpression of these channels can be epileptogenic, channel overexpression does not appear to increase the excitatory-inhibitory (E-I) balance as caused by channel underexpression. We here derive a viable mechanism for ictogenesis driven by h- and m-channel overexpression from analysis of an in silico spiking neuronal microcircuit exhibiting spontaneous seizure-like events (SLEs). Such SLEs are dependent upon sufficiently strong gain in two adaptation terms phenomenologically modeling these channels’ effects: voltage homeostasis (h-current) and spike-frequency adaptation (m-current). Excessive gain of these adaptation terms translates high levels of input correlation into population-level deviations from baseline activity, promoting a sequence of network-level events that collectively provoke an SLE. Importantly, these changes do not cause increased excitability in isolated neurons, nor does this cascade require a change in the amplitude of external input to the circuit, suggesting an ictogenic pathway independent of classical changes to the E-I balance. The viability of this mechanism for SLE onset is strengthened by the host of experimentally-characterized features of seizure produced in this model reliant upon the presence of these adaptation terms, including the irregular initiation and termination of SLEs and time-varying peak frequency of oscillations during such events (i.e., chirps). Moreover, the cell-type dependent effects of changes in these adaptation terms, as delineated in our analyses, represent experimentally-testable predictions for future study of h- and m-channelopathies. These computational results provide vital new insights into the epileptogenic nature of h- and m-channel overexpression currently absent in the experimental literature.in PLoS Computational Biology on 2025-06-30 14:00:00 UTC.
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Feedback parameters for a closed-loop multiple-input multiple-output model of the upper limb
by Ian Syndergaard, Daniel B. Free, Dario Farina, Steven K. Charles
Both closed-loop models and multi-input multi-output (MIMO) models of the neuromusculoskeletal system of the upper limb are important for simulating and understanding motor control. Yet no large-scale linear neuromusculoskeletal models of the upper limb that are both closed-loop and MIMO have been developed. The primary difficulty in creating such models is choosing appropriate feedback parameters (such as feedback gains and delays), as such a collection of parameters is not available in the literature. The purpose of this work is to 1) present a method for developing MIMO models of short-loop afferent feedback and 2) offer estimates of average feedback parameter values and ranges based on the currently available literature. To this end, we combined measurements of feedback-related parameters available in 26 prior studies with known properties of system stability and behavior. As a result, we present estimated feedback gains and delays for a linear model of the upper limb with inputs into the 13 major superficial muscles and outputs to the 7 main joint degrees of freedom from the shoulder to the wrist. This model includes homonymous feedback mediated by Golgi tendon organs and both homonymous and heteronymous feedback mediated by muscle spindles. As a partial validation of muscle-spindle feedback gains, we compared the sign of the estimated gains to known differences in excess central delay between excitatory and inhibitory connections. The comparison proved correct in all 39 muscle pairs for which we had both estimated a feedback gain and found a measured excess central delay value in the literature. Furthermore, as a partial validation of delay times, we compared estimated delay times to measured innervation lengths. We found a strong fit for efferent delays (R = 0.88) and a moderate fit for afferent delays (R = 0.65). In addition, we demonstrate the effect of feedback on model behavior and present brief comparisons between this behavior and experimentally observed behaviors of the human upper limb with and without feedback.in PLoS Computational Biology on 2025-06-30 14:00:00 UTC.
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Investigate channel rectifications and neural dynamics by an electrodiffusive Gauss-Nernst-Planck approach
by Zichao Liu, Yinyun Li
Electrodiffusion plays a crucial role in modulating ion channel conductivity and neural firing dynamics within the nervous system. However, the relationship among ion electrodiffusion, concentration changes, as well as channel conductivity and neuronal discharge behaviors is not quite clear. In this work, we introduce a novel Gauss-Nernst-Planck (GNP) approach to investigate how electrodiffusive dynamics influence ion channel rectification and neural activity. We have analytically demonstrated how the membrane conductance changes along with voltage and ion concentrations due to the electrodiffusive dynamics, bridging the gap between the permeability-based Goldman-Hodgkin-Katz (GHK) model and conductance-based models. We characterize the rectification properties of GABAA, AMPA and leaky channels by estimating their single-channel permeabilities and conductance. By integrating these rectifying channels into neurodynamic models, our GNP neurodynamic model reveals how electrodiffusive dynamics fundamentally shape neural firing by modulating membrane conductance and the interplay between passive and active ion transport-mechanisms, which exhibits difference from conventional conductance-based neurodynamic models especially when ion concentration accumulates to high levels. Furthermore, we have explored how the electrodiffusive dynamics influence the pathological neural events by modulating the stability of neurodynamic system. This study provides a fundamental mechanistic understanding of electrodiffusion regulation in neural activity and establishes a robust framework for future research in neurophysiology.in PLoS Computational Biology on 2025-06-30 14:00:00 UTC.
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A scientific future shared with AI
by Renee Hoch, Joanna Clarke
Artificial intelligence (AI) tools now exist to aid almost every aspect of the research process, from hypothesis generation and data analysis to manuscript drafting and publication. What does the future hold for researchers and publishers as AI use continues to increase? AI tools now exist to aid almost every aspect of the research process, from hypothesis generation and data analysis to manuscript drafting and publication. This Editorial examines what the future might hold for researchers and publishers as AI use continues to increase.in PLoS Biology on 2025-06-30 14:00:00 UTC.
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Gnb5 is a negative regulator of the BACE1-mediated Aβ generation and ameliorates cognitive deficits in a mouse model of Alzheimer’s disease
by Shaokun Chen, Jiechao Zhou, Shuzhong Wang, Erqu Chen, Kai Zhuang, Raozhou Lin, Chensi Liang, Dan Can, Huifang Li, Jing Li, Jie Zhang
β-Amyloid (Aβ) is generated from the amyloid precursor protein (APP) through sequential cleavage by β-site APP-cleaving enzyme 1 (BACE1) and γ-secretase, where BACE1 acting as the rate-limiting enzyme. Elevated BACE1 levels in the brains of Alzheimer’s disease (AD) patients implicate that dysregulated BACE1 expression is crucial to AD pathogenesis. However, the underlying regulatory mechanisms remain unclear. Here, we identified that the G protein subunit β5 gene (Gnb5), a component of the G protein-coupled receptor (GPCR) signaling pathway, is significantly downregulated in both human AD patients and AD mouse models. Conditional knockout of Gnb5 in excitatory neurons resulted in cognitive impairments, whereas adeno-associated virus (AAV)-mediated overexpression of Gnb5 in the hippocampus ameliorated cognitive deficits and reduced Aβ deposition in 5xFAD mice. Mechanistically, we demonstrated that Gnb5 interacts with BACE1, modulating its expression and potentially influencing Aβ generation. We further identify the first tryptophan–aspartate domain (WD domain) of Gnb5 and the Ser81 residue as crucial for this regulation. Expression of this WD domain alone is sufficient to reduce Aβ deposition in 5xFAD mice, whereas a point mutation at Ser81 (S81L) abolishes this effect. Overall, our findings establish Gnb5 as a negative regulator of the BACE1-APP processing axis and unveil mechanistic insights into its role in Aβ-mediated AD pathogenesis.in PLoS Biology on 2025-06-30 14:00:00 UTC.
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The evolution of separate sexes in waterhemp is associated with surprising chromosomal diversity and complexity
by Julia M. Kreiner, Jacob S. Montgomery, Marco Todesco, Natalia Bercovich, Yunchen Gong, Cassandra Elphinstone, Patrick J. Tranel, Loren H. Rieseberg, Stephen I. Wright
The evolution of separate sexes is hypothesized to occur through distinct pathways involving few large-effect or many small-effect alleles. However, we lack empirical evidence for how these different genetic architectures shape the transition from quantitative variation in sex expression to distinct male and female phenotypes. To explore these processes, we leveraged the recent transition of Amaranthus tuberculatus to dioecy within a predominantly monoecious genus, along with a sex-phenotyped population genomic dataset, and six newly generated chromosome-level haplotype phased assemblies. We identify a ~3 Mb region strongly associated with sex through complementary SNP genotype and sequence-depth-based analyses. Comparative genomics of these proto-sex chromosomes within the species and across the Amaranthus genus demonstrates remarkable variability in their structure and genic content, including numerous polymorphic inversions. No such inversion underlies the extended linkage we observe associated with sex determination. Instead, we identify a complex presence/absence polymorphism reflecting substantial Y-haplotype variation—structured by ancestry, geography, and habitat—but only partially explaining phenotyped sex. Just over 10% of sexed individuals show phenotype-genotype mismatch in the sex-linked region, and along with observation of leakiness in the phenotypic expression of sex, suggest additional modifiers of sex and dynamic gene content within and between the proto-X and Y. Together, this work reveals a complex genetic architecture of sex determination in A. tuberculatus characterized by the maintenance of substantial haplotype diversity, and variation in the expression of sex.in PLoS Biology on 2025-06-30 14:00:00 UTC.
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Transcutaneous stimulation of the cervical spinal cord facilitates motoneuron firing and improves hand-motor function after spinal cord injury
Journal of Neurophysiology, Volume 134, Issue 1, Page 128-143, July 2025.
in Journal of Neurophysiology on 2025-06-30 12:51:30 UTC.
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Effects of short-term dual action-simulation training combined with transcranial magnetic stimulation on corticospinal excitation and finger motor performance
Journal of Neurophysiology, Volume 134, Issue 1, Page 144-161, July 2025.
in Journal of Neurophysiology on 2025-06-30 12:51:28 UTC.
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Increased coactivation during clinical tests of spasticity is associated with increased coactivation during reactive standing balance control in cerebral palsy
Journal of Neurophysiology, Volume 134, Issue 1, Page 118-127, July 2025.
in Journal of Neurophysiology on 2025-06-30 12:51:27 UTC.
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Toward Natural Limb Function: A New Era in Prosthetic Innovation
The past decade has witnessed groundbreaking clinical implementation of neuroprosthetic limbs driven by signals from peripheral targets (eg, nerves and muscle) and the brain to restore limb function for individuals with limb loss or impairment. In this review, we highlight recent key clinical trials in peripheral neuroprosthetic interfaces directly with nerve, residual muscle, and reinnervated muscle. We then highlight the key advances in brain interfaces, including clinical trials using electroencephalography, electrocorticography, and intracortical electrodes to control neuroprosthetics. Finally, we explore the future of neuroprosthetic control where both peripheral and brain interfaces can be combined to improve neuroprosthetic performance. ANN NEUROL 2025
in Annals of Neurology on 2025-06-30 12:14:26 UTC.
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Satellite glial cells: Shaping peripheral input into the brain-body axis?
Satellite glial cells (SGCs) envelop sensory and sympathetic ganglion neuronal somas. In this review, Meriau et al. discuss the mechanisms underlying SGCs’ modulation of neuronal functions in health and disease and their potential to shape peripheral input to the brain.in Neuron: In press on 2025-06-30 00:00:00 UTC.
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A unifying mechanism for presynaptic homeostatic plasticity at mammalian peripheral and central synapses
Chipman and colleagues identify Sema3a-PlexinA4-ITGB1 as a unifying, trans-synaptic signaling mechanism for presynaptic homeostatic plasticity (PHP) at both the cholinergic mouse NMJ and glutamatergic synapses in the adult mouse hippocampus. Hippocampal signaling is necessary for cross-modal inhibitory plasticity and links PHP to a functional and ultrastructural re-organization of synaptic vesicle pools.in Neuron: In press on 2025-06-30 00:00:00 UTC.
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Distinct dendritic integration strategies control dynamics of inhibition in the neocortex
Morabito et al. observed that different neocortical interneuron (IN) populations display distinct dendritic properties by varying synaptic receptor composition and input location. These IN-specific dendritic properties enhance synaptic efficiency but are tailored to different temporal processing modes. In the visual cortex, this mechanism supports the distinct dynamics of PV- and SST-INs.in Neuron: In press on 2025-06-30 00:00:00 UTC.
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Maternal obesity impairs fetal brown adipogenesis by attenuating fetal FGF21 signaling
Hua et al. demonstrate that maternal obesity impairs fetal brown adipogenesis by attenuating fetal FGF21 signaling. Meanwhile, postnatal FGF21 supplementation could counteract the adverse effects of maternal obesity on fetal BAT development.in Cell Reports: Current Issue on 2025-06-30 00:00:00 UTC.
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Gut microbiota-bile acid crosstalk contributes to calcium oxalate nephropathy through Hsp90α-mediated ferroptosis
Liu et al. report that the decrease of F. prausnitzii in CaOx renal stone formers is accompanied by the increase of DCA, a secondary bile acid that impairs microbial oxalate catabolism. DCA promotes CaOx crystal deposition via HSP90α-mediated ferroptosis and crystal adhesion, revealing bile acid signaling as a potential therapeutic target.in Cell Reports: Current Issue on 2025-06-30 00:00:00 UTC.
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Natural nappers: monitoring the sleeping patterns of wild orangutans
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02047-2
How being near to other orangutans affects the duration of sleep.in Nature on 2025-06-30 00:00:00 UTC.
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I pioneered my country’s newborn health-screening programme
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02035-6
Clinical geneticist Carmencita Padilla advocates for expanded access to neonatal screening in the Philippines and around the world.in Nature on 2025-06-30 00:00:00 UTC.
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If you’re a US researcher, now is the time to establish a plan B
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-01953-9
The scale of funding cuts in the United States means that countless scientists will lose their jobs. It would be naive not to start thinking about alternative career paths.in Nature on 2025-06-30 00:00:00 UTC.
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’We couldn’t live without it’: the UCSC Genome Browser turns 25
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02034-7
After a quarter of a century, the website remains an essential tool for navigating the genome and understanding its structure, function and clinical impact.in Nature on 2025-06-30 00:00:00 UTC.
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Obesity drugs made in China could power next wave of treatments
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-01987-z
Drugs currently being tested target complications associated with obesity such as heart disease, fatty liver disease and type 2 diabetes.in Nature on 2025-06-30 00:00:00 UTC.
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Stare into a whale’s colossal eye — June’s best science images
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-01957-5
The month’s sharpest science shots — selected by Nature’s photo team.in Nature on 2025-06-30 00:00:00 UTC.
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Trump team axes contracts with publishing giant Springer Nature
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02080-1
The action comes as high-ranking US officials criticize top journals as ‘woke’ and ‘corrupt’.in Nature on 2025-06-30 00:00:00 UTC.
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Ageing is linked to inflammation — but only in the industrialized world
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02085-w
Inflammation, thought to be a driver of age-related disease, does not worsen with age in some Indigenous communities.in Nature on 2025-06-30 00:00:00 UTC.
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What do dolphins talk about? One biologist is trying to listen in
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02033-8
A marine ecologist’s 40-year struggle to understand how animals signal to one another.in Nature on 2025-06-30 00:00:00 UTC.
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Deciphering how dog roses with an odd chromosome copy number sexually reproduce
Nature, Published online: 30 June 2025; doi:10.1038/d41586-025-02048-1
Most sexually reproducing species have an even chromosome copy number, but the dog rose does not. What explains its unusual pattern of chromosome inheritance?in Nature on 2025-06-30 00:00:00 UTC.
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Human CLOCK enhances neocortical function
Nature Neuroscience, Published online: 30 June 2025; doi:10.1038/s41593-025-01993-4
Regulation of gene expression is a facet of human brain specialization. Here, the authors show that human-like expression of the CLOCK gene in the mouse neocortex enhances cognitive flexibility and neural connectivity, suggesting an evolutionary gain of function that may have contributed to human cognitive specialization.in Nature Neuroscience on 2025-06-30 00:00:00 UTC.
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Author Correction: Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural network
Nature Communications, Published online: 30 June 2025; doi:10.1038/s41467-025-61374-0
Author Correction: Single-shot reconstruction of three-dimensional morphology of biological cells in digital holographic microscopy using a physics-driven neural networkin Nature Communications on 2025-06-30 00:00:00 UTC.
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Author Correction: Targeting the disrupted Hippo signaling to prevent neoplastic renal epithelial cell immune evasion
Nature Communications, Published online: 30 June 2025; doi:10.1038/s41467-025-61430-9
Author Correction: Targeting the disrupted Hippo signaling to prevent neoplastic renal epithelial cell immune evasionin Nature Communications on 2025-06-30 00:00:00 UTC.
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Author Correction: Electric vehicle battery chemistry affects supply chain disruption vulnerabilities
Nature Communications, Published online: 30 June 2025; doi:10.1038/s41467-025-61370-4
Author Correction: Electric vehicle battery chemistry affects supply chain disruption vulnerabilitiesin Nature Communications on 2025-06-30 00:00:00 UTC.
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Author Correction: Carbon fibre production using an ecofriendly water-soluble precursor
Nature Communications, Published online: 30 June 2025; doi:10.1038/s41467-025-61365-1
Author Correction: Carbon fibre production using an ecofriendly water-soluble precursorin Nature Communications on 2025-06-30 00:00:00 UTC.
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Correction: High Resolution Water Quality Dataset of Chinese Lakes and Reservoirs from 2000 to 2023
Scientific Data, Published online: 30 June 2025; doi:10.1038/s41597-025-05431-9
Correction: High Resolution Water Quality Dataset of Chinese Lakes and Reservoirs from 2000 to 2023in Nature scientific data on 2025-06-30 00:00:00 UTC.
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Expanding automated multiconformer ligand modeling to macrocycles and fragments
Small molecule ligands exhibit a diverse range of conformations in solution. Upon binding to a target protein, this conformational diversity is reduced. However, ligands can retain some degree of conformational flexibility even when bound to a receptor. In the Protein Data Bank, a small number of ligands have been modeled with distinct alternative conformations that are supported by macromolecular X-ray crystallography density maps. However, the vast majority of structural models are fit to a single-ligand conformation, potentially ignoring the underlying conformational heterogeneity present in the sample. We previously developed qFit-ligand to sample diverse ligand conformations and to select a parsimonious ensemble consistent with the density. While this approach indicated that many ligands populate alternative conformations, limitations in our sampling procedures often resulted in non-physical conformations and could not model complex ligands like macrocycles. Here, we introduce several improvements to qFit-ligand, including integrating RDKit for stochastic conformational sampling. This new sampling method greatly enriches low-energy conformations of small molecules and macrocycles. We further extended qFit-ligand to identify alternative conformations in PanDDA-modified density maps from high-throughput X-ray fragment screening experiments, as well as single-particle cryo-electron microscopy density maps. The new version of qFit-ligand improves fit to electron density and reduces torsional strain relative to deposited single-conformer models and our prior version of qFit-ligand. These advances enhance the analysis of residual conformational heterogeneity present in ligand-bound structures, which can provide important insights for the rational design of therapeutic agents.in eLife on 2025-06-30 00:00:00 UTC.
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Effects of experiencing the COVID-19 pandemic on optimistically biased belief updating
Optimistically biased belief updating is essential for mental health and resilience in adversity. Here, we asked how experiencing the COVID-19 pandemic affected optimism biases in updating beliefs about the future. One hundred and twenty-three participants estimated the risk of experiencing adverse future life events in the face of belief-disconfirming evidence either outside the pandemic (n=58) or during the pandemic (n=65). While belief updating was optimistically biased and Reinforcement-learning-like outside the pandemic, the bias faded, and belief updating became more rational Bayesian-like during the pandemic. This malleability of anticipating the future during the COVID-19 pandemic was further underpinned by a lower integration of positive belief-disconfirming information, fewer but stronger negative estimations, and more confidence in base rates. The findings offer a window into the putative cognitive mechanisms of belief updating during the COVID-19 pandemic, driven more by quantifying the uncertainty of the future than by the motivational salience of optimistic outlooks.in eLife on 2025-06-30 00:00:00 UTC.
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Expansion-assisted selective plane illumination microscopy for nanoscale imaging of centimeter-scale tissues
Recent advances in tissue processing, labeling, and fluorescence microscopy are providing unprecedented views of the structure of cells and tissues at sub-diffraction resolutions and near single molecule sensitivity, driving discoveries in diverse fields of biology, including neuroscience. Biological tissue is organized over scales of nanometers to centimeters. Harnessing molecular imaging across intact, three-dimensional samples on this scale requires new types of microscopes with larger fields of view and working distance, as well as higher throughput. We present a new expansion-assisted selective plane illumination microscope (ExA-SPIM) with aberration-free 1.5 µm×1.5 µm×3 µm optical resolution over a large field of view (10.6×8.0 mm2) and working distance (35 mm) at speeds up to 946 megavoxels/s. Combined with new tissue clearing and expansion methods, the microscope allows imaging centimeter-scale samples with 375 nm lateral and 750 nm axial resolution (4× expansion), including entire mouse brains, with high contrast and without sectioning. We illustrate ExA-SPIM by reconstructing individual neurons across the mouse brain, imaging cortico-spinal neurons in the macaque motor cortex, and visualizing axons in human white matter.in eLife on 2025-06-30 00:00:00 UTC.
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Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism
m6A is the most widespread mRNA modification and is primarily implicated in controlling mRNA stability. Fundamental questions pertaining to m6A are the extent to which it is dynamically modulated within cells and across stimuli, and the forces underlying such modulation. Prior work has focused on investigating active mechanisms governing m6A levels, such as recruitment of m6A writers or erasers leading to either ‘global’ or ‘site-specific’ modulation. Here, we propose that changes in m6A levels across subcellular compartments and biological trajectories may result from passive changes in gene-level mRNA metabolism. To predict the intricate interdependencies between m6A levels, mRNA localization, and mRNA decay, we establish a differential model ‘m6ADyn’ encompassing mRNA transcription, methylation, export, and m6A-dependent and -independent degradation. We validate the predictions of m6ADyn in the context of intracellular m6A dynamics, where m6ADyn predicts associations between relative mRNA localization and m6A levels, which we experimentally confirm. We further explore m6ADyn predictions pertaining to changes in m6A levels upon controlled perturbations of mRNA metabolism, which we also experimentally confirm. Finally, we demonstrate the relevance of m6ADyn in the context of cellular heat stress response, where genes subjected to altered mRNA product and export also display predictable changes in m6A levels, consistent with m6ADyn predictions. Our findings establish a framework for dissecting m6A dynamics and suggest the role of passive dynamics in shaping m6A levels in mammalian systems.in eLife on 2025-06-30 00:00:00 UTC.
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Evolution of lateralized gustation in nematodes
Animals with small nervous systems have a limited number of sensory neurons that must encode information from a changing environment. This problem is particularly exacerbated in nematodes that populate a wide variety of distinct ecological niches but only have a few sensory neurons available to encode multiple modalities. How does sensory diversity prevail within this constraint in neuron number? To identify the genetic basis for patterning different nervous systems, we demonstrate that sensory neurons in Pristionchus pacificus respond to various salt sensory cues in a manner that is partially distinct from that of the distantly related nematode Caenorhabditis elegans. Previously we showed that P. pacificus likely lacked bilateral asymmetry (Hong et al., 2019). Here, we show that by visualizing neuronal activity patterns, contrary to previous expectations based on its genome sequence, the salt responses of P. pacificus are encoded in a left/right asymmetric manner in the bilateral ASE neuron pair. Our study illustrates patterns of evolutionary stability and change in the gustatory system of nematodes.in eLife on 2025-06-30 00:00:00 UTC.
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Tissue-specific responses to TFAM and mtDNA copy number manipulation in prematurely ageing mice
Somatic mitochondrial DNA (mtDNA) mutations are implicated as important drivers of ageing and age-related diseases. Their pathological effect can be counteracted by increasing the absolute amount of wild-type mtDNA via moderately upregulating TFAM, a protein important for mtDNA packaging and expression. However, strong TFAM overexpression can also have detrimental effects as it results in mtDNA hypercompaction and subsequent impairment of mtDNA gene expression. Here, we have experimentally addressed the propensity of moderate TFAM modulation to improve the premature ageing phenotypes of mtDNA mutator mice, carrying random mtDNA mutations. Surprisingly, we detect tissue-specific endogenous compensatory mechanisms acting in mtDNA mutator mice, which largely affect the outcome of TFAM modulation. Accordingly, moderate overexpression of TFAM can have negative and beneficial effects in different tissues of mtDNA mutator mice. We see a similar behavior for TFAM reduction, which improves brown adipocyte tissue homeostasis, while other tissues are unaffected. Our findings highlight that the regulation of mtDNA copy number and gene expression is complex and causes tissue-specific effects that should be considered when modulating TFAM levels. Additionally, we suggest that TFAM is not the sole determinant of mtDNA copy number in situations where oxidative phosphorylation (OXPHOS) is compromised, but other important players must be involved.in eLife on 2025-06-30 00:00:00 UTC.
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Sex chromosome gene expression associated with vocal learning following hormonal manipulation in female zebra finches
Zebra finches are sexually dimorphic vocal learners. Males learn to sing by imitating mature conspecifics, but females do not. Absence of song in females is associated with partial atrophy and apparent repression of several vocal learning brain regions during development. However, atrophy can be prevented, and vocal learning retained in females when given early pharmacological estrogen treatment. To screen for candidate drivers of this sexual dimorphism, we performed an unbiased transcriptomic analysis of song learning nuclei specializations relative to the surrounding regions from either sex, treated with vehicle or estrogen until 30 days of age when divergence between the sexes becomes anatomically apparent. Analyses of transcriptomes by RNA sequencing identified song nuclei-specialized gene expressed modules associated with sex and estrogen manipulation. Female HVC and Area X gene modules were specialized by estrogen supplementation, exhibiting a subset of the transcriptomic specializations observed in males. Female robust nucleus of the arcopallium (RA) and lateral magnocellular nucleus of the anterior nidopallium (LMAN) specialized modules were less dependent on estrogen. The estrogen-induced gene modules in females were enriched for anatomical development functions and strongly correlated to the expression of several Z sex chromosome genes. We present a hypothesis where reduced dosage and expression of these Z chromosome genes suppress the full development of the song system and thus song learning behavior, which is partially rescued by estrogen treatment.in eLife on 2025-06-30 00:00:00 UTC.
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Modifying gene expression through passive forces
The mRNA metabolism passively shapes the levels of an mRNA modification called m6A within a steady-state cell and upon stress.in eLife on 2025-06-30 00:00:00 UTC.
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Dual-specific autophosphorylation of kinase IKK2 enables phosphorylation of substrate IκBα through a phosphoenzyme intermediate
Rapid and high-fidelity phosphorylation of serine residues at positions 32 and 36 of IκBα by IKK2/β, a highly conserved prototypical Ser/Thr kinase in vertebrates, is critical for canonical NF-κB activation. Here, we report that human IKK2 not only phosphorylates substrate serine residues and autophosphorylates its own activation loop, but also autophosphorylates at a tyrosine residue proximal to the active site and is, therefore, a dual-specificity kinase. We observed that mutation of Y169, an autophosphorylatable tyrosine located at the DFG +1 (DLG in IKK1/α and 2) position, to phenylalanine renders IKK2 incapable of catalyzing phosphorylation at S32 within its IκBα substrate. We also observed that mutation of the phylogenetically conserved ATP-contacting residue K44 in IKK2 to methionine converts IKK2 to an enzyme that no longer catalyzes specific phosphorylation of IκBα at S32 or S36, but rather directs phosphorylation of IκBα at other residues. Lastly, we report evidence of a phospho-relay from autophosphorylated IKK2 to IκBα in the presence of ADP. These observations suggest an unusual evolution of IKK2, in which autophosphorylation of tyrosine(s) in the activation loop and the conserved ATP-contacting K44 residue provide its signal-responsive substrate specificity and ensure fidelity during NF-κB activation.in eLife on 2025-06-30 00:00:00 UTC.
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CD131 contributes to ulcerative colitis pathogenesis by promoting macrophage infiltration
-/-in eLife on 2025-06-30 00:00:00 UTC.
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Power Pixels: a turnkey pipeline for processing of Neuropixel recordings
There are many open-source tools available for the processing of neuronal data acquired using Neuropixels probes. Each of these tools, focuses on a part of the process from raw data to single neuron activity. For example, SpikeInterface is an incredibly useful Python module for pre-processing and spike sorting of individual recordings. However, there are more steps in between raw data and spikes, such as synchronization of spike times between probes and histological reconstruction of probe insertions. Therefore, we developed Power Pixels, combining the functionality of several packages into one integrated pipeline, which may be run in any lab workflow. It includes pre-processing, spike sorting, neuron-level quality control metrics, synchronization between multiple probes, compression of raw data, and ephys-to-histology alignment. Integrating all these steps into one pipeline greatly simplifies Neuropixels data processing, especially for novel users who might struggle to find their way around all the available code and tools.in bioRxiv: Neuroscience on 2025-06-30 00:00:00 UTC.
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Longitudinal Imaging of Experimental Intracerebral Hemorrhage Pathology with Iodine-enhanced Micro-CT
Background Iodine-enhanced micro-computed tomography (Micro-CT) enables high-resolution three-dimensional imaging of brain architecture. This study aimed to characterize both acute and chronic pathological changes following intracerebral hemorrhage (ICH) using iodine-enhanced micro-CT. Method Experimental ICH was induced in 8- to 10-week-old C57BL/6 mice (n = 76) via stereotaxic injection of either 0.075 U collagenase IV or 30 l autologous blood. Iodine-enhanced micro-CT imaging was performed at 4 hours, 1, 3, and 7 days after intracerebral hemorrhage post-ICH to evaluate hematoma formation and erythrolysis. Chronic alterations, including ventriculomegaly and ipsilateral lesion, were assessed at 28 days post-ICH. In parallel, MRI was conducted at 1, 7, and 28 days following autologous blood injection, followed by micro-CT, to facilitate cross-modality quantitative analysis. Lesion volumes were compared between imaging modalities over time. Results Micro-CT enabled quantification of hematoma volume and erythrolysis in ICH models. Hematomas extended along perivascular pathways toward the cerebral surface in both collagenase- and autologous blood- induced ICH models. At 28 days post-ICH, micro-CT detected ventriculomegaly and hypodense lesions without concurrent expansion of the choroid plexus. Lesion volume measurements derived from micro-CT correlated with those from MRI, enabling quantitatively assessment of iron deposition and hematoma size alterations after ICH. Conclusion Iodine-enhanced micro-CT provides a robust and high-resolution imaging platform for evaluating hematoma evolution, hemolysis, ventricular enlargement, and chronic brain lesions in experimental ICH. When integrated with MRI, these multimodal imaging approaches enhance the characterization of both hematoma volume and iron deposition following ICH.in bioRxiv: Neuroscience on 2025-06-30 00:00:00 UTC.
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Luminal Vascular Dysfunction Drives Rapid Blood Brain Barrier Injury in Hyperglycemic Stroke: Key Roles for Luminal Glycocalyx and Complement
Background: Acute hyperglycemia affects approximately 40% of stroke patients and is associated with worse outcomes. The underlying mechanisms linking this metabolic stress to stroke-induced brain injury remains unclear, and effective therapies are lacking. Methods: In a mouse model of acute hyperglycemic stroke, luminal disruption, blood-brain barrier (BBB) leakage, neurological deficit, motor function, and mortality were evaluated. Vascular luminal glycocalyx and complement activation were assessed by immunostaining, with glycocalyx loss confirmed by electron microscopy. Complement C3's causal role was tested using C3 knockout mice and site-targeted inhibition with CR2-Crry. To enhance translational relevance, post-mortem human stroke and control brains were immunostained to assess the association between endothelial glycocalyx loss and vascular complement activation. In a separate stroke patient cohort, soluble complement activation products were measured in pre-thrombectomy plasma, and their predictive value for modified Rankin Scale (mRS) outcomes evaluated using elastic net regression. Results: Hyperglycemic stroke mice exhibited accelerated and more severe BBB breakdown, greater functional deficits, and higher mortality than normoglycemic controls, mirroring clinical observations. Acute hyperglycemia triggered rapid vascular luminal injury characterized by loss of endothelial luminal glycocalyx, luminal IgM/IgG deposition, and vascular complement C3 activation, leading to BBB disruption. This vascular luminal injury was corroborated in human stroke brain tissue. These luminal changes persisted despite glucose normalization and were exacerbated by reperfusion, driving injury into the brain parenchyma. Genetic and pharmacological approaches confirmed vascular complement activation as a causal driver of severe BBB disruption and poor outcomes. Importantly, site-targeted pharmacological inhibition of complement after reperfusion preserved BBB integrity and improved outcomes, defining a time-specific, luminal-directed strategy as a promising adjunct to thrombectomy. Notably, soluble complement activation markers in pre-thrombectomy stroke plasma predicted clinical outcomes, highlighting their potential as pre-intervention markers for patient stratification and tailored therapy. Conclusion: This study reframes acute hyperglycemic stroke as a vascular luminal disorder, establishing a novel Metabolic-Complement-Vascular (MCV) axis linking metabolic stress to endothelial luminal glycocalyx loss, vascular complement activation, and BBB breakdown in both mice and humans. This new mechanistic understanding transforms the therapeutic landscape of hyperglycemic stroke, offering a potential time-defined, luminal-focused adjunct therapy alongside thrombectomy.in bioRxiv: Neuroscience on 2025-06-30 00:00:00 UTC.
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Sephin1 alleviates white matter injury by protecting oligodendrocyte after intracerebral hemorrhage
Background: White matter injury (WMI) caused by intracerebral hemorrhage (ICH) is a major neuropathological feature closely associated with neurological impairments such as motor and sensory dysfunction. Oligodendrocytes (OLs), which are responsible for repairing WMI, also suffer severe death resulting from the compression of hematoma and secondary neuroinflammation after ICH. Sephin1, a selective inhibitor of PPP1R15A, has been shown to reduce general protein synthesis and protect OLs by prolonging the integrated stress response (ISR). We aimed to evaluate the effectiveness of Sephin1 in protecting OLs in experimental ICH mice and primary OLs and microglia co-cultures. Methods: We first determined the performance of ICH mice treated with Sephin1 or vehicle in multiple behavioral tests. To investigate dynamic changes in the number of OLs surrounding the hematoma after ICH, we labeled and tracked apoptotic, proliferating, and mature OLs using immunofluorescence staining. Results: Sephin1 treatment improved long-term neurological function after ICH, which was accompanied by a significant alleviation of WMI in the perihematomal region. Our data indicated that Sephin1 dramatically increased the population of OLs in the perihematomal region after ICH by inhibiting OL apoptosis and promoting OL proliferation. Moreover, Sephin1 treatment attenuated neuroinflammation after ICH by inhibiting microglial polarization to the M1 phenotype. In vitro, a co-culture model of primary OLs and microglia demonstrated that Sephin1 preserved the viability of OLs under pro-inflammatory conditions. Conclusions: Our observations suggest that Sephin1 is a promising therapeutic drug to preserve the OLs and alleviate WMI around the hematoma in ICH, highlighting its translational potential to improve long-term neurological recovery in hemorrhagic stroke.in bioRxiv: Neuroscience on 2025-06-30 00:00:00 UTC.
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Switches in Orientation Coding by Mouse Primary Visual Cortex Neurons Depend on Stimulus Predictability.
How the brain processes a stimulus depends on contextual factors, such as whether it is predictable or surprising. While this process has been partially characterized using EEG and fMRI, and invasive cellular approaches, the microcircuit mechanisms responsible for comparing sensory input and expectations remain poorly understood. Here, we combined layer-resolved recordings of single-unit activity and local field potentials (LFP) in mouse primary visual cortex (V1) with a visual oddball paradigm using oriented gratings. Both event-related potentials and firing rates exhibited distinct temporal components across cortical layers and trial types. We identified robust stimulus-specific adaptation (SSA), mismatch negativity (MMN), and deviant detection (DD) contrast at both early and late epochs. Surprisingly, a substantial subset of excitatory neurons exhibited complete reversals of orientation preference ('preference switches') between standard and deviant trials, rather than only changes in selectivity. These preference-switching cells were primarily observed in layers 2/3 and 5/6 and contributed as much information to stimulus decoding as stably tuned neurons. Our findings demonstrate that context-dependent flexibility in feature preference is an integral part of predictive coding in V1 and challenge the notion of fixed stimulus representations at the single-neuron level.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Intrinsic mechanisms contributing to the biophysical signature of mouse gamma motoneurons
Precise motor control relies on continuous sensory feedback from muscles, a process in which gamma motoneurons play a key role. These specialized spinal neurons innervate intrafusal muscle fibres, modulating their sensitivity to stretch and maintaining proprioceptive signalling during movement. Gamma motoneurons are characterized by a distinct biophysical profile, including low recruitment thresholds and high firing rates that enable rapid activation of intrafusal fibres at contraction onset. Despite their importance, the intrinsic mechanisms that underlie these properties remain poorly understood. In this study, we analysed published and unpublished data to identify a population of low-threshold, high-gain motoneurons with features consistent with gamma motoneurons, emerging during the third postnatal week in mice. Their low recruitment threshold was linked to lower membrane capacitance, higher input resistance, a more hyperpolarized activation of persistent inward currents (PICs), and a narrower axon initial segment. In contrast, higher firing rates were associated not with PIC amplitude but with shorter action potential durations and smaller medium afterhyperpolarizations. Notably, 92% of putative gamma motoneurons exhibited a sodium pump-mediated ultra-slow afterhyperpolarization (usAHP), which was absent in slow alpha motoneurons. This difference could not be attributed to h-current activity or expression of the alpha 3 subunit of the sodium-potassium ATPase. These findings reveal key intrinsic properties that support the unique excitability of gamma motoneurons, offering new insight into their contribution to motor control. This work provides a foundation for future studies into their development, regulation, and involvement in neuromuscular disorders.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Spatial Reorganization of Object Representations in High-Level Visual Cortex Distinguishes Working Memory from Perception
The human visual system balances veridical object visual perception with flexible object visual working memory (VWM), both relying on high-level visual regions. However, how these competing demands shape spatial representations remains unclear. Here, we ask whether VWM inherits the spatial constraints observed in the lateral occipital complex (LOC) during perception, or instead reorganizes these representations to meet mnemonic demands. Using matched bilateral presentation paradigms and fMRI-based decoding, we systematically compared spatial representations during perception and VWM. This approach revealed a striking dissociation: during perception, object information is largely confined to the contralateral LOC, whereas during VWM, robust ipsilateral representations emerge--even when both hemifields must be remembered. Vertex-ablation analyses revealed that VWM engages 70-90% of ipsilateral LOC territories, far exceeding those recruited during unilateral perception. Neither increased attentional span nor top-down feedback from association areas fully explained this expansion; rather, ipsilateral LOC patterns closely mirrored contralateral sensory representations, implicating interhemispheric coordination in VWM. Together, these findings demonstrate that object VWM flexibly recruits distributed high-level visual cortex, with spatial reorganization distinguishing mnemonic flexibility from perceptual fidelity.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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IP3-mediated Ca2+ transfer from ER to mitochondria stimulates ATP synthesis in primary hippocampal neurons
During electrical activity, Ca2+ enhances mitochondrial ATP production, helping to replenish the energy consumed during this process. Most Ca2+ enters the cell via ligand- or voltage-gated channels on the neuronal membrane, where it stimulates the release of additional Ca2+ from the endoplasmic reticulum (ER). Although the influence of cytosolic Ca2+ on neuronal metabolism has been widely investigated, relatively few studies have explored the contribution of ER Ca2+ release in this context. Therefore, we investigated how activity-driven Ca2+ crosstalk between the ER and mitochondria influences the regulation of mitochondrial ATP production. We show that in primary hippocampal neurons derived from rat pups of either sex, depletion of ER Ca2+ led to a reduction in mitochondrial Ca2+ levels during both resting and stimulated states, while exerting only a minimal impact on cytosolic Ca2+ levels. Additionally, impaired ER-mitochondria Ca2+ transfer led to a reduction in mitochondrial ATP production. Similar effects were observed when inositol-3-phosphate receptors (IP3Rs), but not ryanodine receptors (RyRs), were pharmacologically inhibited. Together, our findings show that, in hippocampal neurons, Ca2+ is transferred from the ER to mitochondria through IP3 receptors, and this Ca2+ crosstalk in turn enhances mitochondrial ATP production in response to neuronal activity.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Early postnatal CA3 hyperexcitability drives hippocampal development and epileptogenesis in SCN2A developmental and epileptic encephalopathy
Developmental and epileptic encephalopathies caused by pathogenic variants in SCN2A (SCN2A-DEE), encoding the voltage-gated sodium channel Nav1.2, present with early-life seizures, developmental delay, and increased mortality. Using a novel Scn2a p.A263V gain-of-function (GOF) mouse model, we demonstrate gene-dose and background-dependent phenotypes ranging from self-limited neonatal seizures to chronic epilepsy with high mortality. In vivo electrophysiology revealed hippocampal seizures as early as postnatal day 2.5, with CA3-driven gamma oscillations preceding seizure onset. CA3 and CA1 pyramidal neurons exhibited transient hyperexcitability during early postnatal development, resolving by P24-30. Single-cell RNA sequencing uncovered gene dose-dependent accelerated maturation of hippocampal networks, peaking at P7, alongside widespread transcriptional changes in excitatory and inhibitory neurons. In adulthood, persistent hippocampal network alterations emerged, marked by reduced mid-gamma oscillations and theta-gamma coupling. Our findings establish hippocampal CA3 hyperexcitability as an early driver of epileptogenesis in SCN2A-DEE and highlight it as a potential therapeutic target to mitigate disease progression.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Interleaved Replay of Novel and Familiar Memory Traces During Slow-Wave Sleep Prevents Catastrophic Forgetting
Humans and animals can learn continuously, acquiring new knowledge and integrating it into a pool of lifelong memories. Memory replay during sleep has been proposed as a powerful mechanism contributing to interference-free new learning. In contrast, artificial neural networks suffer from a problem called catastrophic forgetting, where new training damages existing memories. This issue can be mitigated by interleaving training on new tasks with past data; however, whether the brain employs this strategy remains unknown. In this work, we show that slow-wave sleep (SWS) employs an interleaved replay of familiar cortical and novel hippocampal memory traces within individual Up states of the slow oscillation (SO), allowing new memories to be embedded into the existing pool of cortical memories without interference. Using a combination of biophysical modeling and analyses of single-unit activity from the mouse retrosplenial cortex - for a mouse trained first in a highly familiar environment and then in a novel one - we found that hippocampal ripples arriving near the Down-to-Up or Up-to-Down transitions of the sleep SO can entrain novel memory replay, while the middle phase of the Up state tends to replay familiar cortical memories. This strategy ensures the consolidation of novel cortical memory traces into long-term storage while minimizing damage to familiar ones. This study presents a novel framework for how replay of familiar and novel memory traces is organized during SWS to enable continual learning.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Altered Brain Energy Metabolism in the APPPS1 Alzheimer's Model during anesthesia: Integration of Experimental Data and In Silico Modeling
Background: Synaptic transmission and network activity rely on high ATP turnover. Impairments in cerebral energy metabolism are increasingly recognized as central in aging and Alzheimer's disease (AD) pathogenesis. Elderly patients and patients with AD are also at elevated risk for perioperative neurological complications, including post-operative delirium and further cognitive deterioration. However, the interaction between metabolic vulnerability and anesthetic exposure remains incompletely understood. Methods: We investigated cortical metabolic responses and potassium homeostasis in acute brain slices from wild-type (WT) and AD-like APPPS1 transgenic mice, which were either exposed to isoflurane or left untreated. Glia cells were assessed by staining microglia and astrocytes. Measurements of the cerebral metabolic rate of oxygen (CMRO2), extracellular potassium dynamics, and proteomic profiling were integrated with computational modeling to assess oxidative metabolism and anesthetic effects under different conditions. Results: APPPS1 mice exhibited reduced CMRO2 and attenuated neuronal activity compared to age-matched WT controls, showing sex-specific differences. Proteomic analysis revealed the downregulation of key mitochondrial and glycolytic enzymes, indicating an impaired ATP-generating capacity. Exposure to isoflurane further suppressed CMRO2, with a more pronounced effect in the APPPS1 brain tissue, while glia cells exhibited no acute changes. Additionally, isoflurane exacerbated deficits in extracellular potassium ([K]) clearance, highlighting impaired ion homeostasis under anesthetic challenge. Conclusions: Our findings demonstrate that AD-like pathology in APPPS1 mice is associated with a significant decline in oxidative metabolism and ATP availability. These deficits are exacerbated by anesthetic exposure, contributing to impaired potassium regulation. This suggests that diminished metabolic flexibility may underlie increased anesthetic vulnerability and postoperative complications in AD.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Non-equilibrium Thermodynamics Modulate TRPV1 Channel Activation via Tissue Entropy Production
Inflammatory processes involve complex interactions between molecular signaling and biophysical mechanisms, yet the thermodynamic consequences of such processes remain underexplored. Here, we present a theoretical multiscale model that demonstrates how elevated entropy production in inflamed tissue environments modulates the activation threshold of TRPV1 thermosensitive ion channels. Our framework integrates axonal electrophysiology based on the Hodgkin-Huxley formalism, thermodynamic heat transfer with explicit entropy generation, and a dynamic model of TRPV1 channel gating. Simulations reveal that increased entropy production leads to a downward shift in the activation temperature of TRPV1 channels, driven by cumulative non-equilibrium thermodynamic effects. This result provides a mechanistic explanation for the enhanced excitability of sensory axons in inflamed tissue and highlights entropy production as a fundamental physical variable influencing ion channel behavior. The study contributes a novel perspective on the coupling between thermodynamics and sensory transduction at the cellular level.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Forgetting in Drosophila consists of an increase in uncertainty rather than a stochastic loss of memory
While forgetting has been studied extensively in various organisms, its precise nature has often been unclear. Here, we used behavioral experiments in Drosophila to determine that a significant aspect of forgetting consists of a decrease in the ability of a memory to induce an appropriate behavior. We tested flies for memory retention at various times after training and then separately retested both flies that chose correctly and those that chose incorrectly. Although the ability to choose correctly decreased over time, we could not measure any differences in memory between flies that initially chose correctly and those that chose incorrectly upon retest. This suggests that forgetting is unlikely to consist of a spontaneous loss of a memory but instead consists of a decrease in the probability of flies that remember choosing the correct behavioral response. Thus, although flies maintain memory over time, there is an increase in uncertainty associated with this memory. We find that forgetting of long-term memories and accelerated forgetting in old flies occur in a similar manner.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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TRPML3 regulates neuronal gene expression in an in vitro model of autophagy and may act as a genetic marker of familial neurodegenerative disorders
Autophagy is a conserved pro-survival pathway for delivering misfolded proteins and damaged organelles to lysosomes for degradation and protein homeostasis. Anomaly in autophagy leads to aberrant protein aggregation in neuronal cells, which is a common etiology of neurodegenerative disorders. Endo-lysosomal cation channel TRPML3 (Transient Receptor Potential Mucolipin-3) has been shown to induce autophagy in cell line models. However, the mechanism of TRPML3 mediated autophagy induction and the underlying gene expression changes are not clearly understood. Here, by using Ca2+- and electrical-current measurements, RNA sequencing and RT PCR studies, we explored the cellular function of TRPML3 and the global transcriptomic profile in a cell-based serum starvation model of autophagy. We report that serum starvation leads to downregulation of neuronal developmental genes during autophagy induction. TRPML3 overexpression further amplifies the effect of starvation in downregulating neuronal gene expression. But, when nutrition is not a limiting condition, TRPML3 overexpression upregulated neuronal genes including those responsible for axon guidance, synaptogenesis, and dendritic arborization. TRPML3 mediated neuronal gene expression changes were, presumably, due to transcription factors (TF) TFEB, FOXO1 and neuron-specific TFs such as SOX2, and ETV5. To further validate the role of TRPML3 in neuronal gene regulation, we performed meta-analysis of publicly available RNAseq datasets on neurodegenerative disorders which provided insight into the heterogeneity in the molecular mechanisms of autophagy and corroborated the TFEB-mediated autophagy induction and neuronal gene expression in TRPML3 overexpression condition. Based on our results, we propose that TRPML3 may act as a potential genetic marker for familial neurodegenerative disorders.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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The Vomeronasal System of Talpa occidentalis: A Combined Histological, Immunohistochemical, and Lectin-Binding Approach
The vomeronasal system (VNS) is critical for detecting pheromonal cues that modulate sociosexual behaviors. Despite its central role in chemical communication, our understanding of its anatomical and functional variability across mammals remains incomplete. This study provides the first detailed characterization of the VNS in the Iberian mole (Talpa occidentalis), a fossorial species endemic to the Iberian Peninsula. We performed a morphofunctional and neurochemical analysis of the vomeronasal organ (VNO) and the accessory olfactory bulb (AOB) using histology, immunohistochemistry, and lectin histochemistry. The VNO in T. occidentalis exhibited an unusual circular lumen lined by a uniform sensory epithelium, lacking the dual epithelial organization seen in most species. The vomeronasal cartilage was limited in extent and did not form the typical J-shaped structure. Importantly, no evidence of a vomeronasal pump was found, suggesting alternative mechanisms for semiochemical entry, likely facilitated by the anatomical position of the organ and continuous receptor distribution. Immunohistochemical analysis revealed strong expression of Gai2 and Gg8 in sensory neurons, with weaker Ga0 expression, suggesting predominance of V1R-type signal transduction. The AOB, though small, exhibited clear lamination and specific marker localization (Gai2, OMP, CR, MAP2), indicating robust functional organization. Lectin binding revealed specific glycosylation patterns in the glomerular layer, with STL and LEA marking synaptic regions. These findings uncover unprecedented anatomical and molecular features in the VNS of T. occidentalis, positioning this species as a valuable model for studying vomeronasal diversity and evolution among Laurasiatherian mammals.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Identification of Small Molecule Dimethyoxyphenyl Piperazine Inhibitors of Alpha-Synuclein Fibril Growth
Alpha-synuclein (asyn) fibril accumulation is the defining feature of Parkinson disease and is a target for disease-modifying treatments. One therapeutic strategy to reduce fibril accumulation is inhibition of asyn fibril growth. We developed a sensitive fluorescence-based fibril growth assay to screen for small molecule inhibitors. After validating the inhibition assay using a previously identified inhibitor, epigallocatechin-3-gallate, we identified compound 1 as a lead for inhibition of fibril growth. We analysed structure-activity relationships with analogs of 1 to optimize inhibition potency. Our results identified two dimethoxyphenyl piperazine analogs with more potent inhibition of in-vitro assembled fibrils. These analogs also inhibited the growth of asyn fibrils amplified from Lewy Body Disease brain tissue, further validating the inhibitor screening assay. Molecular docking studies indicate that these compounds can bind to the fibril ends, suggesting a potential capping mechanism through which these compounds inhibit the sequential association of monomeric asyn required for fibril growth.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Identifying out-of-voxel echoes in edited MRS with phase cycle inversion
Purpose To identify the origin of out-of-voxel (OOV) signals based on the coherence transfer pathway (CTP) formalism using signal phase conferred by the acquisition phase cycling scheme. Knowing the CTP driving OOV artifacts enables optimization of crusher gradients to improve their suppression without additional data acquisition. Theory and Methods A phase cycle systematically changes the phase of RF pulses across the transients of an experiment, encoding phase shifts into the data that can be used to suppress unwanted CTPs. We present a new approach, phase cycle inversion (PCI), which removes the receiver phase originally applied to the stored transients, replacing it with new receiver phases, matching the phase evolutions associated with each unwanted CTP, to identify the OOV signals. We demonstrated the efficacy of PCI using the MEGA-edited PRESS sequence in simulations, phantom and in vivo experiments. Based on these findings, the crusher gradient scheme was optimized. Results The simulation results demonstrated that PCI can fully separate signals originating from different CTPs using a complete phase cycling scheme. PCI effectively identified the CTP responsible for OOV signals in phantom experiments and in vivo, though with reduced specificity in vivo due to phase instabilities. Re-optimization of the gradient scheme based on the identified OOV-associated CTP to suppress these signals, resulted in cleaner spectra in six volunteers. Conclusion PCI can be broadly applied across pulse sequences and voxel locations, making it a flexible and generalizable approach for diagnosing the CTP origin of OOV signals.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Stretching of the insect mechanoreceptor evokes mechano-electrical transduction in auditory chordotonal neurons
Insect proprioception, vibration and sound detection rely on the scolopidium--a mechanosensory unit enclosing the sensory cilium of chordotonal organ neurons. The cilium contains mechanosensitive ion channels, and is enclosed by a scolopale cell with its tip embedded in a cap. Despite knowledge of the scolopidium's structure in multiple insects, the mechanism by which mechanical force elicits the transduction current remains speculative. We examined scolopidia in the auditory Muller's organ of the desert locust and present a comprehensive three-dimensional ultrastructure of a scolopidium using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM). Next, we characterised sound-evoked motions of Muller's organ and the scolopidium using Optical Coherence Tomography (OCT) and high-speed light microscopy. We further measured transduction currents via patch clamp electrophysiology during mechanical stimulation of individual scolopidia. By combining ultrastructure, sound-evoked motions, and transduction current recordings, our finding suggests that the scolopidium is activated best by stretch along the ciliary axis.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Triceps Surae Muscle Ia Proprioceptive Weighting During Quiet Stance with Vision Occlusion
Visual, vestibular, proprioceptive and cutaneous sensory information is important for posture control during quiet stance. When the reliability of one source of sensory information used to detect self-motion for posture control is reduced, there may be a reweighting of inputs within and/or across the remaining sensory systems determining self-motion for postural control. Muscle vibration, which creates an illusion of muscle stretch and a compensatory movement to shorten the vibrated muscle, may be used to determine the weighting of muscle spindle Ia proprioception for posture control. The objective of this study was to determine the effect of vision occlusion on triceps surae muscle Ia proprioceptive weighting for postural control during quiet stance, utilizing 80 Hz muscle vibration and a quantitative measure of the bodys anterior to posterior ground center of pressure response to triceps surae muscle vibration in freely standing subjects. Subjects (N = 41; mean(standard deviation), 19.6(2.0) years) were examined as they stood with eyes open or eyes closed. Ground center of pressure was measured during quiet standing with, and without, bilateral vibration of the triceps surae muscles. The mean backward center of pressure shift induced by triceps surae vibration was significantly greater during the eyes closed condition compared to eyes open (eyes closed: -4.93(1.62) centimeters; eyes open: -3.21(1.33) centimeters; p = 6.85E-10; Cohens d = 1.29). Thirty-seven subjects increased, and two subjects decreased, their vibration induced center of pressure backward shift in the eyes closed condition compared to eyes open, although the magnitude of the change varied. Results support the idea that for most subjects, during an eyes closed stance there is an increased triceps surae muscle Ia proprioceptive weighting for postural control, due to the need for posture control to depend more on non-visual feedback.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Prior knowledge influences the neural mechanisms supporting memory-based inference
Memory-based inference allows individuals to integrate information acquired across separate episodes to support novel decisions and reasoning. Although prior knowledge, such as schemas, is known to influence learning and memory, its impact on the neural mechanisms underlying inference remains unclear. In this study, we investigated how schema congruency affects the encoding and retrieval of overlapping events and how these processes contribute to memory-based inference. Thirty-nine participants encoded AB associations, consisting of picture-word pairs presented on either schema-congruent or schema-incongruent backgrounds. These were followed by BC associations involving the same word paired with a new picture on a neutral background. At test, participants were asked to infer the indirect AC association. While overall inference accuracy did not differ as a function of schema congruency, behavioral and neural data revealed distinct mechanisms. Inference for schema-incongruent events depended on accurate retrieval of both AB and BC associations, whereas schema-congruent inferences did not. To investigate the neural processes involved, we trained hierarchical multivariate pattern classifiers on EEG data to detect schema and context reinstatement during task performance. For schema-congruent events, successful inference was predicted by schema reinstatement during BC encoding, consistent with integrating overlapping information into a unified memory trace. In contrast, successful inference for schema-incongruent events was predicted by context reinstatement during AC retrieval, reflecting a reliance on flexible recombination of separate memory representations. These findings demonstrate that schema congruency modulates the neural basis of memory-based inference. Congruent events are integrated during encoding, whereas incongruent events rely on retrieval-based inference. Keywords: memory integration, schema, congruency, context, MVPA, EEGin bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Heterogeneity and variability in short term synaptic plasticity and implications for signal transformation
There are many sources of heterogeneity in the CA1 network, including plasticity, connectivity and cell properties, yet the extent and functional consequences of this diversity remains poorly understood. We used patterned optogenetic stimulation of CA3 pyramidal neurons and whole-cell patch clamp recordings from CA1 pyramidal neurons in acute mouse hippocampal slices, to characterize the contributions of different forms of heterogeneity to information flow. We found pronounced heterogeneity in synaptic responses and short-term plasticity (STP), influenced by the neurotransmitter identity, input pattern, and size of the activated presynaptic ensemble. Inhibitory synapses exhibited greater diversity in both response variability and depression profiles than excitatory synapses. We incorporated these readings in a molecule-to-network multiscale model of the CA3->CA1 circuit. The reference model shows strong decorrelation of autocorrelated input, but removal of STP makes the decorrelation frequency dependent. Removal of stochasticity and heterogeneity in connections makes the output periodic. Thus heterogeneity, short-term plasticity, and stochasticity each have distinct effects on cellular information transmission.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Inhibition of nonsense-mediated decay in TDP-43 deficient neurons reveals novel cryptic exons
TAR DNA-binding protein 43 kDa (TDP-43) is an essential splicing repressor whose loss of function underlies the pathophysiology of amyotrophic lateral sclerosis and frontotemporal dementia (ALS-FTD). Nuclear clearance of TDP-43 disrupts its function and leads to the inclusion of aberrant cryptic exons. These cryptic exons frequently introduce premature termination codons resulting in the degradation of affected transcripts through nonsense-mediated mRNA decay (NMD). Conventional RNA sequencing approaches thus may fail to detect cryptic exons that are efficiently degraded by NMD, precluding identification of potential therapeutic targets. We generated a comprehensive set of neuronal targets of TDP-43 in human iPSC-derived i3Neurons (i3N) by combining TDP-43 knockdown with inhibition of multiple factors essential for NMD, revealing novel cryptic targets. We then restored expression of selected NMD targets in TDP-43 deficient i3Ns and determined which genes improved neuronal viability. Our findings highlight the role of NMD in masking cryptic splicing events and identify novel potential therapeutic targets for TDP-43-related neurodegenerative disorders.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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SORLA upregulation suppresses global pathological effects in aged tauopathy mouse brain
A role for the trafficking receptor SORLA in reducing A{beta} levels has been well-established, however, relatively little is known with respect to whether and how SORLA can potentially affect tau pathology in vivo. Here, we show that transgenic SORLA upregulation (SORLA TG) can reverse pathological effects in aged PS19 (P301S tau) mouse brain, including tau phosphorylation and seeding, ventricle dilation, synapse loss, LTP impairment and glial hyperactivation. Proteomic analysis indicates reversion of PS19 profiles in PS19/SORLA TG hippocampus, including pathological changes in synapse-related proteins as well as key drivers of synaptic dysfunction such as Apoe and C1q. snRNA-seq analysis reveals suppression of PS19- signatures with SORLA upregulation, including proinflammatory induction of Plxnb1/Plxnb2 in glia. Tau seeding and aggregation, neuroinflammation, as well as PlxnB1/B2 induction are exacerbated in PS19 hippocampus with SORLA deletion. These results implicate a global role for SORLA in neuroprotection from tau toxicity in PS19 mouse brain.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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A systematic protocol to identify 'clinical controls' for pediatric neuroimaging research from clinically acquired brain MRIs
Progress at the intersection of artificial intelligence and pediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and generalizable models. Retrospective analysis of clinical brain magnetic resonance imaging (MRI) scans offers a promising avenue to augment prospective research datasets, leveraging the extensive repositories of scans routinely acquired by hospital systems in the course of clinical care. Here, we present a systematic protocol for identifying scans with limited imaging pathology through machine-assisted manual review of radiology reports. The protocol employs a standardized grading scheme developed with expert neuroradiologists and implemented by non-clinician graders. Categorizing scans based on the presence or absence of significant pathology and image quality concerns, facilitates the repurposing of clinical brain MRI data for brain research. Such an approach has the potential to harness vast clinical imaging archives exemplified by over 250,000 brain MRIs at the Childrens Hospital of Philadelphia to address demographic biases in research participation, to increase sample size, and to improve replicability in neurodevelopmental imaging research. Ultimately, this protocol aims to enable scalable, reliable identification of clinical control brain MRIs, supporting large-scale, generalizable neuroimaging studies of typical brain development and neurogenetic conditions.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Dietary restriction promotes neuronal resilience via ADIOL
The steroid hormone 5-androstene-3{beta},17{beta}-diol (ADIOL) was discovered in humans nearly a century ago, yet its physiological roles remain poorly defined. Here, we show that fasting and caloric restriction, two forms of dietary restriction, induce transcriptional upregulation of genes encoding CYP11A1, CYP17A1, and 17{beta}-hydroxysteroid dehydrogenase family enzymes, promoting ADIOL biosynthesis. ADIOL, in turn, acts on the nervous system to reduce levels of kynurenic acid, a neuroactive metabolite linked to cognitive decline and neurodegeneration. This effect requires NHR-91, the C. elegans homolog of estrogen receptor {beta}, specifically in the RIM neuron, a key site of kynurenic acid production. Consistent with the known benefits of fasting and caloric restriction on healthspan, enhancing ADIOL signaling improves multiple healthspan indicators during aging. Conversely, animals deficient in ADIOL signaling exhibit reduced healthspan under normal conditions and in genetic models of caloric restriction, underscoring the functional significance of this pathway. Furthermore, ADIOL suppresses cellular stresses induced by the Alzheimer's-associated APOE4 variant, highlighting its potential as a neuroprotective agent. Notably, ADIOL does not significantly impact lifespan, indicating that its healthspan benefits are not simply a byproduct of lifespan extension. Together, these findings establish a physiological role for ADIOL in mediating the neuroprotective and pro-healthspan effects of fasting and caloric restriction and suggest that boosting ADIOL signaling may help narrow the gap between lifespan and healthspan. This positions ADIOL as a promising mimetic of dietary restriction effects on healthspan that could be used as a therapeutic strategy for age-related neurodegenerative conditions.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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The effects of gait speed on the responses to immediate and prolonged exposure to mediolateral optic flow perturbation in healthy young adults
Background: Optic flow is vital for locomotor control and is often perturbed to study the impact of optic flow on balance control. However, it remains unclear whether gait speed influences responses to such perturbations. This study aims to examine the effects of gait speed on gait parameters following immediate and prolonged exposure to mediolateral optic flow perturbations. Methods: Twenty-one young adults (23.43 +/- 4.19 years) walked on an instrumented treadmill, including 3 phases: baseline (3 min), perturbation with mediolateral optic flow (8 min), and post-perturbation (3 min). Trials were conducted at 0.6, 1.2, and 1.8 m/s. Ground reaction forces and 3D motion data were collected to calculate mediolateral margin of stability (MoS), mean step length (SL), step width (SW) and their variabilities. Three repeated-measures ANOVAs (Speed by Phase) were used to compare: baseline vs. early perturbation, early vs. late perturbation, and baseline vs. post-perturbation. Results: The responses to immediate and prolonged exposure to optic flow perturbation were speed dependent. Walking at slow speeds induced greater immediate responses in mediolateral gait parameters (SW and mediolateral MoS, both p < 0.001) compared to walking at faster speeds. During the perturbation phase, the adaptations were larger at faster vs. slower speeds for gait parameters in the direction of movement (SL, p = 0.007). Conclusion: Immediate responses and adaptations to mediolateral optic flow perturbations are speed-dependent and larger at slower gait speeds. The responses to prolonged perturbation are interpreted as step-to-step adaptations that may inform future interventions and studies on gait speed selection.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Cortical dissociation of spatial reference frames during place navigation
Animals rely on both sensory perception and memory when navigating relative to learned allocentric locations. Incoming sensory stimuli, which arrive from an egocentric perspective, must be integrated into an allocentric reference frame to allow neural computations that direct an animal toward a learned goal. This egocentric-allocentric spatial transformation has been proposed to involve projections from the rodent postrhinal cortex (POR), which receives strong visual input, to the medial entorhinal cortex (MEC), which contains allocentric spatial cell types such as grid and border cells. A major step toward understanding this transformation is to identify how POR and MEC spatial representations differ during place navigation, which is currently unknown. To answer this question, we recorded single neurons from POR and MEC as rats engaged in a navigation task that required them to repeatedly visit a learned uncued allocentric location in an open field arena to receive a randomly scattered food reward. While neurons in both regions displayed strong tuning to the spatial structure of the environment, neither showed bias toward the goal location despite strongly biased behavior. Critically, when local visual landmarks were manipulated to place the visual scene in conflict with the learned location, POR neurons adjusted their tuning preferences to follow the visual landmarks, while MEC neurons remained in register with the true global reference frame. These findings reveal a strong dissociation between POR and MEC spatial reference frames during place navigation and raise questions regarding the mechanisms underlying integration of POR egocentric signals into the MEC allocentric spatial map.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Motor Learning Outside the Body: Broad Skill Generalisation with an Extra Robotic Limb
Our ability to transfer motor skills across tools and contexts is what makes modern technology usable. The success of motor augmentation devices, such as supernumerary robotic limbs, hinges on users' capacity for generalised motor performance. We trained participants over seven days to use an extra robotic thumb (Third Thumb, Dani Clode Design), worn on the right hand and controlled via the toes. We tested whether motor learning was confined to the specific tasks and body parts involved in controlling and interacting with the Third Thumb, or whether it could generalise beyond them. Participants showed broad skill generalisation across tasks, body postures, and even when either the Third Thumb or the controller was reassigned to a different body part, suggesting the development of abstract, body-independent motor representations. Training also reduced cognitive demands and increased the sense of agency over the device. However, participants still preferred using their biological hand over the Third Thumb when given the option, suggesting that factors beyond motor skill generalisation, cognitive effort, and embodiment must be addressed to support the real-world adoption of such technologies.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Long-Term Effects of Adolescent 5F-MDMB-PICA Intravenous self-administration: Neurobehavioral Consequences and medial Prefrontal Cortex Dysfunction in Adult Mice
Background: Synthetic Cannabinoids Receptor Agonists (SCRAs) are the largest group of new psychoactive substances monitored worldwide. 5F-MDMB-PICA is a recent SCRA classified as a potent full agonist at CB1/CB2 receptors able to activate the mesolimbic dopamine (DA) transmission in adolescent but not in adult mice. Here, we have studied its reinforcing effects in adolescent mice and characterized the neurochemical and behavioral effects induced in the same animals in adulthood. Methods: We utilized an intravenous self-administration (IVSA) protocol in adolescent (PND 40-56) CD-1 male mice. In adulthood (PND 66-78), we conducted several behavioral and neurobiological assessments including: Sucrose Preference Test (SPT); Resident Intruder Test (RIT); Olfactory Reactivity Test (ORT); brain microdialysis to quantify DA levels in the medial Prefrontal Cortex (mPFC); and fiber photometry analysis using the GCaMP calcium sensor to monitor excitatory neural dynamics in the mPFC after exposure to an aversive odorant. Results: We found that 5F-MDMB-PICA, administered through IVSA in adolescent mice, produced an inverted U-shaped dose-response curve. The dose of 2.5 g/kg/25ul elicited behavior consistent with drug seeking. Adult mice exposed to 5F-MDMB-PICA during adolescence exhibited significant behavioral and neurochemical changes in adulthood compared to control mice. These behaviors included increased aggression, reduced social interaction, an anhedonic state, and an abolishment of mPFC DA response to an aversive odorant, as measured by in vivo brain microdialysis. Moreover, fiber photometry analysis of excitatory neuronal activity in the mPFC showed diminished calcium activity in response to the same aversive odorant in 5F-MDMB-PICA-exposed mice compared to controls. Conclusions: Notably, this study is the first to demonstrate that adolescent mice can acquire and sustain IVSA of 5F-MDMB-PICA. Furthermore, it highlights the long-term behavioral and neurochemical changes associated with adolescent exposure to 5F-MDMB-PICA, underscoring the potential detrimental effects of its use during this critical developmental period.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Simultaneous recording of spikes and calcium signals in odor-evoked responses of Drosophila antennal neurons
Most insects, including agricultural pests and disease vectors, rely on olfaction for key innate behaviors. Consequently, there is growing interest in studying insect olfaction to gain insights into odor-driven behavior and to support efforts in vector control. Calcium imaging using GCaMP fluorescence is widely used to identify olfactory receptor neurons (ORNs) responsive to ethologically relevant odors. However, accurate interpretation of GCaMP signals in the antenna requires understanding both response uniformity within an ORN population and how calcium signals relate to spike activity. To address this, we optimized a dual-modality recording method combining single-sensillum electrophysiology and widefield imaging for Drosophila ORNs. Calcium imaging showed that homotypic ab2A neurons exhibit similar odor sensitivity, consistent with spike recordings, indicating that a single ORN's response can reliably represent its homotypic counterparts. Furthermore, concurrent dual recordings revealed that peak calcium responses are linearly correlated with spike activity, regardless of imaging site (soma or dendrites), GCaMP variant, odorant, or fly age. These findings validate the use of somatic calcium signals as a reliable proxy for spike activity in fly ORNs and provide a foundation for future large-scale surveys of spike vs. calcium response relationships across diverse ORN types.in bioRxiv: Neuroscience on 2025-06-29 00:00:00 UTC.
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Lanthionine Ketimine Ethyl Ester Induces Proliferation and Maturation and Regulates Calcium Flux in Primary Mouse Oligodendrocyte Progenitor Cells
LKE increased OPC proliferation and maturation. LKE reduced Ca responses to ATP and glutamate, and increased responses to KCl. Similar effects occurred with a peptide that disrupts Collapsin Response Mediator Protein 2 interactions with NMDARs and VGCCs.
ABSTRACT
Previous studies have shown that lanthionine ketimine ethyl ester (LKE), a semi-synthetic derivative of the endogenous amino acid lanthionine, can induce proliferation and maturation of oligodendrocyte progenitor cells (OPCs) in vivo. In the current study, we examined the effects of LKE on Ca2+ influx in primary mouse OPCs, as intracellular Ca2+ can regulate those processes. Treatment with LKE stimulated proliferation of OPCs and increased the number of Olig2+, CC1+, and PLP+ cells. LKE also reduced cell death (caspase-3 expressing cells). Measurements of Ca2+ flux showed that LKE increased basal Ca2+ levels, reduced Ca2+ influx following stimulation with glutamate or ATP, and increased Ca2+ flux because of depolarization with KCl. Reduced Ca2+ responses were also observed following treatment with a peptide that disrupts interactions of collapsin response mediated protein 2 (CRMP2), a primary target of LKE. These findings demonstrate regulation of Ca2+ levels in OPCs by LKE and suggest that these actions may be mediated, in part, by CRMP2. LKE or related analogs could therefore be of benefit for the treatment of multiple sclerosis as well as other demyelinating conditions.
in Journal of Neuroscience Research on 2025-06-28 06:13:36 UTC.
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Issue Information
in Journal of Neuroscience Research on 2025-06-28 05:52:52 UTC.
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Author Correction: Distinct virome compositions and lack of viral diversification indicate that viral spillover is a dead-end between the western honey bee and the common eastern bumblebee
Communications Biology, Published online: 28 June 2025; doi:10.1038/s42003-025-08415-y
Author Correction: Distinct virome compositions and lack of viral diversification indicate that viral spillover is a dead-end between the western honey bee and the common eastern bumblebeein Nature communications biology on 2025-06-28 00:00:00 UTC.
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Prevalence and determinants of heterosexual anal and oral sex practice among young people in Ethiopia: systematic review and Meta-analysis [version 1; peer review: awaiting peer review]
Introduction Young people in developing nations are particularly affected by HIV infection, which primarily spreads through sexual contact, including anal, oral, and vaginal sex. Heterosexual couples engage in female anal sex, a receptive sexual behavior in which the penis is placed in the female partner’s anus. Anal intercourse has a higher risk of HIV transmission than vaginal intercourse, especially when there is appropriately low condom use, and the majority of couples are unaware of the risk of HIV transmission during anal intercourse. PROSPERO Registration number CRD42024629445 Objectives of the review To determine the pooled prevalence and determinants of heterosexual anal and oral sex practices among young Ethiopian people. Methods This systematic review of peer reviews published in English up to January 31, 2025, measures heterosexual anal and oral sex practices and contributing factors among young people in Ethiopia. STATA version 17 software was used to analyze the pooled prevalence and determinants of heterosexual anal and oral sex practices among young people in Ethiopia. Result Female young people were 2.45 times more likely to engage in heterosexual anal sex practice 95%CI, OR 4.05[1.57-3.33]. Young people who were living alone were 2.50 more likely involved in heterosexual anal sex practice with 95% CI, OR 2.50[1.60-3.40]).Those young people who live alone were 1.91 more likely engaged in heterosexual oral sex practice with 95% CI, OR 1.91[1.7-2.12]. Young people whose intimate partners engaged in heterosexual oral sex practice were 5.13 times more likely to engage in heterosexual oral sex practice in Ethiopia. Conclusions The pooled prevalence of heterosexual oral and anal sex practices in Ethiopia is high. Living alone and female sex were associated with heterosexual anal sex practices, while intimate partner engagement in oral heterosexual sex practice was associated with heterosexual oral sex practice among young people in Ethiopia.in F1000Research on 2025-06-27 14:33:02 UTC.
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Mapping the Intellectual Landscape of Employee Performance Research: A Bibliometric and Mapping Analysis (2020–2025) [version 1; peer review: awaiting peer review]
Purpose This study aims to identify research trends and map the academic structure in the field of employee performance over the past five years. Given the increasing complexity of organizations and post-pandemic work dynamics, bibliometric mapping is necessary to understand the evolution of themes, the contributions of key literature, and the future directions of knowledge development. Design/Methodology/Approach A total of 2,044 articles published between 2020 and 2025 are collected from the Scopus database. The article selection process adheres to the PRISMA 2020 guidelines to ensure transparency and methodological rigor. Analysis is conducted using Bibliometrix R and VOSviewer, employing performance analysis and science mapping techniques. Visualization results include trending topics, a word cloud, the most globally cited documents, and network visualizations identifying the primary thematic clusters within the literature. Findings The findings indicate that research topics are shifting from general issues toward contemporary themes such as digital leadership, work well-being, and organizational adaptation to global changes. Seven primary clusters are identified, reflecting a multidisciplinary approach encompassing structural, psychological, and contextual dimensions. Additionally, articles with high normalized citation scores demonstrate that significant contributions come from practical and cross-sectoral studies. Originality/value The novelty of this study lies in mapping the intellectual structure and research trends of employee performance using Bibliometrix R and VOSviewer, focusing on the post-pandemic period (2020-2025). It uniquely employs trending topics and normalized citation analysis to identify emerging themes and influential publications in contemporary research.in F1000Research on 2025-06-27 14:31:34 UTC.
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Personalized Care in the UAE : A Study on Precision Medicine Awareness and Accessibility among the general population [version 1; peer review: awaiting peer review]
Background Precision medicine is an emerging approach that tailors treatments based on an individual’s genetic profile. The UAE has made significant strides in this field through initiatives like the National Genomics Strategy and the Emirati Genome Program. However, public awareness and engagement remain key challenges. Purpose This study assesses awareness, acceptance, and utilization of precision medicine among UAE residents. Methods A cross-sectional online survey was conducted using a snowball sampling method, The survey collected demographic data, health status, knowledge, and experiences with precision medicine. Descriptive statistics and chi-square tests were used to analyze associations. Results Most participants (94.3%) were under 50 years old, 62.5% were female, and 60.0% held a bachelor’s degree. Awareness of precision medicine was moderate (55.3%), with higher familiarity among females and students. While 40% believed its main benefit was optimizing drug effectiveness, 38.5% viewed it as crucial for preventing adverse drug reactions. Family and friends (29.5%) were the primary sources of information, yet 25.5% had never heard of precision medicine. Awareness of insurance coverage was low, with 59.0% uncertain about their policy. Genetic testing participation was associated with education level (p < 0.05). Acceptance of precision medicine was higher among individuals with chronic illnesses (p = 0.004). Familiarity scores varied significantly by occupation (p < 0.001) and income (p = 0.004), with higher-income individuals showing greater awareness. Males had a broader range of practice scores (p = 0.003), and individuals with chronic conditions were more aware of precision medicine (p = 0.023). Conclusion Despite advancements, public engagement with precision medicine remains limited. Targeted educational initiatives, improved accessibility, and increased awareness of insurance coverage may enhance adoption and utilization.in F1000Research on 2025-06-27 14:28:57 UTC.
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Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology
by Yuxi Long, Bruce R. Donald
Accurate binding affinity prediction (BAP) is crucial to structure-based drug design. We present PATH+, a novel, generalizable machine learning algorithm for BAP that exploits recent advances in computational topology. Compared to current binding affinity prediction algorithms, PATH+ shows similar or better accuracy and is more generalizable across orthogonal datasets. PATH+ is not only one of the most accurate algorithms for BAP, it is also the first algorithm that is inherently interpretable. Interpretability is a key factor of trust for an algorithm and alongside generalizability, allows PATH+ to be trusted in critical applications, such as inhibitor design. We visualized the features captured by PATH+ for two clinically relevant protein-ligand complexes and find that PATH+ captures binding-relevant structural mutations that are corroborated by biochemical data. Our work also sheds light on the features captured by current computational topology BAP algorithms that contributed to their high performance, which have been poorly understood. PATH+ also offers an improvement of 𝒪(m+n)3 in computational complexity and is empirically over 10 times faster than the dominant (uninterpretable) computational topology algorithm for BAP. Based on insights from PATH+, we built PATH−, a scoring function for differentiating between binders and non-binders that has outstanding accuracy against 11 current algorithms for BAP. In summary, we report progress in a novel combination of interpretability, speed, and accuracy that should further empower topological screening of large virtual inhibitor libraries to protein targets, and allow binding affinity predictions to be understood and trusted. The source code for PATH+ and PATH− are released open-source as part of the osprey protein design software package.in PLoS Computational Biology on 2025-06-27 14:00:00 UTC.
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OrgaCCC: Orthogonal graph autoencoders for constructing cell-cell communication networks on spatial transcriptomics data
by Xixuan Feng, Shuqin Zhang, Limin Li
Cell-cell communication (CCC) is a fundamental biological process essential for maintaining the functionality of multicellular organisms. It allows cells to coordinate their activities, sustain tissue homeostasis, and adapt to environmental changes. However, understanding the mechanisms underlying intercellular communication remains challenging. The rapid advancements in spatial transcriptomics (ST) have enabled the analysis of CCC within its spatial context. Despite the development of several computational methods for inferring CCCs from ST data, most rely on literature-curated gene or protein interaction lists, which are often inadequate due to the restricted gene coverage. In this work, we propose OrgaCCC, an orthogonal graph autoencoders approach for cell-cell communication inference based on deep generative models. OrgaCCC leverages the information of gene expression profiles, spatial locations and ligand-receptor relationships. It captures both cell/spot and gene features using two orthogonally coupled variational graph autoencoders across cell/spot and gene dimensions and combines them by maximizing the similarity between their reconstructed cell/spot features. Numerical experiments on five ST datasets demonstrate the superiority of OrgaCCC compared with state-of-the-art methods in CCC inference at the cell-type level, cell/spot level, and ligand-receptor level, in terms of inference accuracy and reliability.in PLoS Computational Biology on 2025-06-27 14:00:00 UTC.
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Resolving the conformational ensemble of a membrane protein by integrating small-angle scattering with AlphaFold
by Samuel Eriksson Lidbrink, Rebecca J. Howard, Nandan Haloi, Erik Lindahl
The function of a protein is enabled by its conformational landscape. For non-rigid proteins, a complete characterization of this landscape requires understanding the protein’s structure in all functional states, the stability of these states under target conditions, and the transition pathways between them. Several strategies have recently been developed to drive the machine learning algorithm AlphaFold2 (AF) to sample multiple conformations, but it is more challenging to a priori predict what states are stabilized in particular conditions and how the transition occurs. Here, we combine AF sampling with small-angle scattering curves to obtain a weighted conformational ensemble of functional states under target environmental conditions. We apply this to the pentameric ion channel GLIC using small-angle neutron scattering (SANS) curves, and identify apparent closed and open states. By comparing experimental SANS data under resting and activating conditions, we can quantify the subpopulation of closed channels that open upon activation, matching both experiments and extensive simulation sampling using Markov state models. The predicted closed and open states closely resemble crystal structures determined under resting and activating conditions respectively, and project to predicted basins in free energy landscapes calculated from the Markov state models. Further, without using any structural information, the AF sampling also correctly captures intermediate conformations and projects onto the transition pathway resolved in the extensive sampling. This combination of machine learning algorithms and low-dimensional experimental data appears to provide an efficient way to predict not only stable conformations but also accurately sample the transition pathways several orders of magnitude faster than simulation-based sampling.in PLoS Computational Biology on 2025-06-27 14:00:00 UTC.
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scRepertoire 2: Enhanced and efficient toolkit for single-cell immune profiling
by Qile Yang, Ksenia R. Safina, Kieu Diem Quynh Nguyen, Zewen Kelvin Tuong, Nicholas Borcherding
Single-cell adaptive immune receptor repertoire sequencing (scAIRR-seq) and single-cell RNA sequencing (scRNA-seq) provide a transformative approach to profiling immune responses at unprecedented resolution across diverse pathophysiologic contexts. This work presents scRepertoire 2, a substantial update to our R package for analyzing and visualizing single-cell immune receptor data. This new version introduces an array of features designed to enhance both the depth and breadth of immune receptor analysis, including improved workflows for clonotype tracking, repertoire diversity metrics, and novel visualization modules that facilitate longitudinal and comparative studies. Additionally, scRepertoire 2 offers seamless integration with contemporary single-cell analysis frameworks like Seurat and SingleCellExperiment, allowing users to conduct end-to-end single-cell immune profiling with transcriptomic data. Performance optimizations in scRepertoire 2 resulted in a 85.1% increase in speed and a 91.9% reduction in memory usage from the first version over the range repertoire size tested in benchmarking, addressing the demands of the ever-increasing size and scale of single-cell studies. This release marks an advancement in single cell immunogenomics, equipping researchers with a robust toolset to uncover immune dynamics in health and disease.in PLoS Computational Biology on 2025-06-27 14:00:00 UTC.
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Human attention-guided visual perception is governed by rhythmic oscillations and aperiodic timescales
by Isabel Raposo, Ian C. Fiebelkorn, Jack J. Lin, Josef Parvizi, Sabine Kastner, Robert T. Knight, Assaf Breska, Randolph F. Helfrich
Attention samples visual space sequentially to enhance behaviorally relevant sensory representations. While traditionally conceptualized as a static continuous spotlight, contemporary models of attention highlight its discrete nature. But which neural mechanisms govern the temporally precise allocation of attention? Periodic brain activity as exemplified by neuronal oscillations as well as aperiodic temporal structure in the form of intrinsic neural timescales have been proposed to orchestrate the attentional sampling process in space and time. However, both mechanisms have been largely studied in isolation. To date, it remains unclear whether periodic and aperiodic temporal structure reflect distinct neural mechanisms. Here, we combined computational simulations with a multimodal approach encompassing five experiments, and three different variants of classic spatial attention paradigms, to differentiate aperiodic from oscillatory-based sampling. Converging evidence across behavior as well as scalp and intracranial electroencephalography (EEG) revealed that periodic and aperiodic temporal regularities can theoretically and experimentally be distinguished. Our results extend the rhythmic sampling framework of attention by demonstrating that aperiodic neural timescales predict behavior in a spatially-, context-, and demand-dependent manner. Aperiodic timescales increased from sensory to association cortex, decreased during sensory processing or action execution, and were prolonged with increasing behavioral demands. These results reveal that multiple, concurrent temporal regularities govern attentional sampling.in PLoS Biology on 2025-06-27 14:00:00 UTC.
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Case Report: Duodenal duplication: A case report of a rare gastrointestinal anomaly [version 1; peer review: awaiting peer review]
Introduction and Importance Gastrointestinal duplications are rare congenital anomalies, occurring in about 1 in 25,000 births, with duodenal duplications making up 2% to 7% of cases. Typically diagnosed in childhood, they pose diagnostic challenges in adults. Case Presentation We present a case of a 14-year-old boy with mild epigastric pain, whose imaging revealed a large inter-duodeno-pancreatic cystic mass displacing nearby structures. Surgical exploration identified a cystic formation in the second part of the duodenum with a small communication to the duodenal lumen. A subtotal resection and cysto-duodenostomy were performed, leading to an uneventful postoperative recovery. Clinical Discussion Duplication cysts, or alimentary tract duplications, are rare congenital lesions, typically found in the distal ileum but infrequently in the duodenum. Diagnosed mainly in early childhood, they may occasionally present in adulthood, manifesting as abdominal mass, obstruction, or discomfort; in some cases, they mimic choledochal cysts, complicating diagnosis. Surgical removal is the standard treatment, focusing on ensuring proper drainage while preserving biliary and pancreatic ducts. Conclusion Duodenal duplication is a rare, challenging diagnosis in adolescents; this case offers guidance for timely identification and treatment. It aims to support healthcare providers in achieving timely diagnosis and effective management in similar cases.in F1000Research on 2025-06-27 10:04:38 UTC.
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Modeling of neuronal hyperexcitability modulated by Aβ-mediated astrocyte dysfunction
Author(s): YuPeng Li, XiaoLi Yang, Hao Yang, and Jürgen Kurths
Neuronal hyperexcitability is a key feature in the early stages of Alzheimer's disease (AD). However, the underlying mechanisms have not been fully elucidated, particularly the impact of amyloid β-peptide (Aβ)-mediated astrocyte dysfunction on neuronal hyperexcitability. Building upon recent experim…
[Phys. Rev. E 111, 064419] Published Fri Jun 27, 2025
in Physical Review E: Biological physics on 2025-06-27 10:00:00 UTC.
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FXR agonist in post-liver transplantation patients: a randomized open-labeled study. [version 2; peer review: 2 approved with reservations]
Abstract Liver diseases cause nearly 2 million deaths worldwide each year, with approximately 1 million deaths from cirrhosis complications and another 1 million from viral hepatitis and liver cancer, according to WHO estimates. Liver transplantation (LT) remains the primary curative option, boasting success rates of 85% in the first year and 75% at five years post-transplant. Despite high costs, LT is considered cost-effective, especially for younger patients with active work years remaining. However, post-transplant complications, particularly intrahepatic cholestasis, present notable challenges. This complication arises from factors such as ischemia-reperfusion injury, infections, immunological rejection, and surgical complications, all contributing to impaired bile flow and liver damage. Current medical therapies for post-LT cholestasis are limited, with ursodeoxycholic acid (UDCA) frequently used, despite questionable efficacy. Obeticholic acid (OCA), a potent Farnesoid X Receptor (FXR) agonist approved by the FDA for treating primary biliary cholangitis (PBC), has shown potential benefits in reducing elevated cholestatic liver enzymes. Given its significant effects on liver health, OCA may offer therapeutic value in managing post-transplant cholestasis and improving graft survival. This randomized controlled trial (RCT) aims to evaluate OCA’s efficacy compared to UDCA in reducing cholestatic injury and enhancing graft function post-LT. The primary outcomes will focus on a 15% reduction in alkaline phosphatase and gamma-glutamyl transferase levels at 3, 6, and 12 months from baseline one month. Secondary outcomes include molecular markers, biliary complications, graft rejection, quality of life, and cost-effectiveness. Results are anticipated to demonstrate that OCA could improve graft survival, reduce complications, and enhance quality of life, potentially setting a new standard in post-LT care if found beneficial.in F1000Research on 2025-06-27 09:22:18 UTC.
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Clonal Hematopoiesis of Indeterminate Potential Associated with Covert Cerebral Changes
Objective
Clonal hematopoiesis of indeterminate potential (CHIP) is an emerging risk factor for cardio-cerebrovascular diseases. This study aimed to investigate CHIP's association with cerebrovascular or glymphatic changes in a community-based population.
Methods
This study examined Chinese community cohort participants. CHIP mutations were identified through whole-exome sequencing. Intracranial arterial stenosis, silent brain infarcts, cerebral small vessel disease markers, and diffusion along the perivascular space index were identified by magnetic resonance imaging. The correlation between CHIP and neuroimaging outcomes was investigated through univariate and multivariate logistic/linear regression. The multivariate regression model was adjusted for cerebrovascular disease risk factors, including age, sex, body mass index, smoking status, hypertension, diabetes, and hyperlipidemia.
Results
In total, 18.2% (224 out of 1,229) participants were identified as carriers of CHIP mutations. The prevalence of CHIP generally increases with age (p = 0.009). After adjusting for vascular risk factors using multivariate regression, CHIP mutations were found to be significantly associated with increased odds of large magnetic resonance imaging-defined infarcts (>15 mm; OR 3.20; 95% CI 1.18 to 8.43; p = 0.018), inversely associated with diffusion along the perivascular space (β = −0.02; 95% CI −0.04 to 0; p = 0.034), and showed a borderline association with intracranial arterial stenosis (OR 1.52; 95% CI 0.99 to 2.30; p = 0.053). Notably, no statistically significant correlations were observed between CHIP and cerebral small vessel disease markers or brain atrophy measures.
Interpretation
CHIP was significantly associated with glymphatic dysfunction and large infarcts, and marginally associated with intracranial arterial stenosis. Further research is needed to elucidate the pathophysiology linking CHIP to cerebral covert changes. ANN NEUROL 2025
in Annals of Neurology on 2025-06-27 08:50:25 UTC.
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Three-dimensional markerless motion capture of multiple freely behaving monkeys toward automated characterization of social behavior
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Phase 2/3 study evaluating safety, immunogenicity, and noninferiority of single booster dose of AVX/COVID-12 vaccine
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Unusual charge density wave introduced by the Janus structure in monolayer vanadium dichalcogenides
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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VIRMA-mediated m6A modification regulates forebrain formation through modulating ribosome biogenesis
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Tumor-targeting nanocarriers amplified immunotherapy of cold tumors by STING activation and inhibiting immune evasion
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Unveiling the multifunctional use of ochre in the Middle Stone Age: Specialized ochre retouchers from Blombos Cave
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Micrometer-scale-thick quantum-dot LEDs with notably enhanced stability and ultrahigh brightness
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Vertical land motion in Greater New Orleans: Insights into underlying drivers and impact to flood protection infrastructure
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Hepatic NMNAT1 is required to defend against alcohol-associated fatty liver disease
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Past intrusion of Circumpolar Deep Water in the Ross Sea: Impacts on the ancient Ross Ice Shelf
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Global health risks lurking in livestock resistome
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Impact of diurnal temperature and relative humidity hysteresis on atmospheric dryness in changing climates
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Upgrading biocrude oil into sustainable aviation fuel using zeolite-supported iron-molybdenum carbide nanocatalysts
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Quantum sensing of broadband spin dynamics and magnon transport in antiferromagnets
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Automorphy as a self-organizing DPP-dependent process that translates patterns into mechanical programs during Drosophila embryogenesis
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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A PIF-SAUR module safeguards hypocotyl elongation from ABA inhibition in the dark
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Flexible multichannel muscle impedance sensors for collaborative human-machine interfaces
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Mixed surfactants for stabilizing and controlling water transport in double emulsions
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Feedback transcription regulation between OsNAC3 and OsDREB1A promotes postgermination growth in rice
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Supramolecular hydrogel actuators with reprogrammable magnetic orientation by locally mediated viscoelasticity and pinning force
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Pathways of blue carbon export from kelp and seagrass beds along the Atlantic coast of Nova Scotia
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Data-driven approach for potential iron-based half-Heusler thermoelectrics with chemical bonding characteristics
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Sequestration of ribosome biogenesis factors in HSV-1 nuclear aggregates revealed by spatially resolved thermal profiling
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Anisotropic strain relaxation-induced directional ultrafast carrier dynamics in RuO2 films
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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A machine-learning–powered spectral-dominant multimodal soft wearable system for long-term and early-stage diagnosis of plant stresses
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Metabolic regulation of visual acuity
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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All-inorganic metafabric scintillators for conformally flexible and wearable x-ray detection and imaging
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Engineered CD4 TCR T cells with conserved high-affinity TCRs targeting NY-ESO-1 for advanced cellular therapies in cancer
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Revealing neurovascular coupling at a high spatial and temporal resolution in the living human retina
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Strain relaxation in halide perovskites via 2D/3D perovskite heterojunction formation
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Large-scale experimental assessment of variant effects on the structure and function of the citrate transporter SLC13A5
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Dorsal raphe nucleus controls motivation-state transitions in monkeys
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Erratum for the Research Article “Structure and dynamics determine G protein coupling specificity at a class A GPCR” by M. Casiraghi et al.
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Erratum for the Research Article “ATM-phosphorylated SPOP contributes to 53BP1 exclusion from chromatin during DNA replication” by D. Wang et al.
Science Advances, Volume 11, Issue 26, June 2025.
in Science Advances on 2025-06-27 07:00:00 UTC.
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Neuromodulation of the Cingulate Cortex for Pain
The Neuroscientist, Ahead of Print.
The subgenual (sACC) and pregenual (pACC) anterior cingulate and anterior midcingulate (aMCC) cortices are structurally and functionally distinct subregions of the cingulate cortex with critical roles in pain processing. These regions may be promising ...in The Neuroscientist on 2025-06-27 06:55:10 UTC.
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Risk optimization during ongoing movement: insights from movement and gaze behavior in throwing
Journal of Neurophysiology, Volume 134, Issue 1, Page 94-106, July 2025.
in Journal of Neurophysiology on 2025-06-27 03:21:28 UTC.
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Systemic calcitonin gene-related peptide modifies auditory and vestibular end organ electrical potentials, and increases sensory hypersensitivities
Journal of Neurophysiology, Volume 134, Issue 1, Page 107-117, July 2025.
in Journal of Neurophysiology on 2025-06-27 03:21:27 UTC.
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VISTA immune checkpoint blunts radiotherapy-induced antitumor immune response
Nambiar et al. showed that radiotherapy induces VISTA+ immunosuppressive myeloid cells, limiting antitumor immunity. Genetic deletion or antibody-mediated blockade of VISTA synergizes with radiotherapy to enhance T cell responses and myeloid repolarization, improving tumor control across models and supporting VISTA as a promising combination partner for radiotherapy treatment regimen.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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SSB cooperates with METTL16-mediated m6A RNA methylation to promote chemoresistance in colorectal cancer cells
Li et al. show that the SSB/La protein binds to METTL16 and thus promotes METTL16 bindings to RNA and m6A RNA methylation. The SSB/METTL16/RNA axis promotes colorectal cancer cell proliferation, survival, and chemoresistance.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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Cingulin is an RNA-binding protein promoting pancreatic cancer through enhancing importin 7-mediated phospho-ERK nuclear translocation
Su et al. demonstrate that CGN is a novel non-canonical RNA-binding protein. They identify that CGN binds and stabilizes the mRNAs of AXL and importin-7 (IPO7), driving MAPK/ERK activation and pERK nuclear translocation, which in turn promotes the malignant phenotype of PDAC.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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A live-cell biosensor of in vivo receptor tyrosine kinase activity reveals feedback regulation of a developmental gradient
Ho et al. report in vivo biosensors of endogenous receptor tyrosine kinase activity in Drosophila called pYtags. Using pYtags to characterize Torso activity during embryonic terminal patterning, they find that a dynamic domain of Torso activity is tuned by negative feedback to produce a longer-range stable gradient of ERK.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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Phenotypic screens for SIRPA expression reveal RAB21 as a general regulator of macrophage surface identity
Through CRISPR screening, Granda Farias et al. find results consistent with cis CD47-SIRPA interactions relying on QPCTL and that RAB21/Rab21 inactivation reduces macrophage model surface SIRPA/Sirpa expression. Through surface proteomics, they show that Rab21 inactivation modulates expression of macrophage receptors, e.g., Fc gamma receptors impacting phagocytosis of cells and particles.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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VCPIP1 potentiates innate immune responses by non-catalytically reducing the ubiquitination of IRAK1/2
Liyan Lou et al. identified the deubiquitinating enzyme VCPIP1 as a potential therapeutic target for sepsis. They found that VCPIP1 enhanced innate immune activity by stabilizing IRAK1/2. Ablation of VCPIP1 reduces IRAK1/2 levels and thereby impairs inflammatory responses, resulting in attenuated sepsis.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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Lymph node fibroblast phenotypes and immune crosstalk regulated by podoplanin activity
Makris et al. show that podoplanin regulates the transcription profile of lymph node fibroblasts. Podoplanin deletion drives inflammation, disrupts lymph node architecture, and attenuates stromal/immune cell crosstalk. This study shows the significance of the podoplanin/CLEC-2 signaling axis beyond controlling cellular mechanics and actomyosin contractility.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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SUV39H1-dependent methyl-degron is a critical regulator of skeletal homeostasis
Li et al. show that SUV39H1 inhibits female MSC osteogenesis and bone formation by activating the NF-κB cascade in an H3K9me3-independent manner. SUV39H1 deposits lysine methylation at the IκBα degron, which signals UACA binding and provokes IκBα destabilization. The SUV39H1-IκBα-UACA-NF-κB axis is a critical regulator of bone homeostasis.in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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TGF-β Determines the Pro-migratory Potential of bFGF Signaling in Medulloblastoma
(Cell Reports 23, 3798–3812.e1–e8; June 26, 2018)in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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TGF-β Determines the Pro-migratory Potential of bFGF Signaling in Medulloblastoma
(Cell Reports 23, 3798–3812.e1–e8; June 26, 2018)in Cell Reports: Current Issue on 2025-06-27 00:00:00 UTC.
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Exclusive: NIH still screens grants in process a judge ruled illegal
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-02024-9
Directives by the Trump administration are still being applied to grant materials despite court order.in Nature on 2025-06-27 00:00:00 UTC.
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Arrests of scientists over smuggled samples add to US border anxiety
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-01958-4
Nature talks to legal and other specialists about the cases and what to watch out for when transporting lab materials.in Nature on 2025-06-27 00:00:00 UTC.
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Can AI build a virtual cell? Scientists race to model life’s smallest unit
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-02011-0
Several groups hope to develop artificial-intelligence models that can predict how cells behave.in Nature on 2025-06-27 00:00:00 UTC.
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First independent survey of deaths in Gaza reports more than 80,000 fatalities
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-02009-8
Results align with other efforts to count the number of people killed amid the ongoing conflict.in Nature on 2025-06-27 00:00:00 UTC.
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Daily briefing: The oldest rocks on Earth
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-02082-z
Rocks on Hudson Bay, Canada are the only piece of Earth’s crust known to have survived from the planet’s earliest eon. Plus, sea slugs steal photosynthetic equipment from algae to use as an energy source and how artificial-intelligence research is used to bolster surveillance.in Nature on 2025-06-27 00:00:00 UTC.
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Niède Guidon obituary: Brazilian archaeologist who upended ideas on early human migration
Nature, Published online: 27 June 2025; doi:10.1038/d41586-025-02029-4
Researcher used carbon dating to provide evidence that humans had arrived in Brazil much earlier than previously thought.in Nature on 2025-06-27 00:00:00 UTC.
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Emergent photonics for cardiovascular health
Nature Photonics, Published online: 27 June 2025; doi:10.1038/s41566-025-01714-0
The broad applications of emerging photonic technologies, such as photoacoustic imaging, optical wearable sensors, point-of-care testing and optogenetic control, in cardiovascular disease care are reviewed, together with the challenges of integrating these innovations into clinical practice.in Nature Photomics on 2025-06-27 00:00:00 UTC.
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An experimental proxy of water displaceability for ligand discovery
Nature Methods, Published online: 27 June 2025; doi:10.1038/s41592-025-02724-0
ColdBrew is a machine learning-based method that predicts the probability of cryogenic crystallographic waters to be present at room temperature, which links to their relative energies and displaceability by ligands.in Nature Methods on 2025-06-27 00:00:00 UTC.
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Super-resolution microscopy for structural biology
Nature Methods, Published online: 27 June 2025; doi:10.1038/s41592-025-02731-1
This Perspective introduces a framework for defining, measuring and reporting resolution in super-resolution microscopy and details the current state of the art in using fluorescence microscopy for structural biology at the ångström scale.in Nature Methods on 2025-06-27 00:00:00 UTC.
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Atoms revolt against tweezer-imposed order
Nature Physics, Published online: 27 June 2025; doi:10.1038/s41567-025-02946-1
The combination of optical tweezer arrays with high-finesse cavities opens the door to the study of mesoscopic finite-size effects in the critical dynamics and optomechanical response of atomic ensembles.in Nature Physics on 2025-06-27 00:00:00 UTC.
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Dynamic phase transition in 1T-TaS2 via a thermal quench
Nature Physics, Published online: 27 June 2025; doi:10.1038/s41567-025-02938-1
The photoinduced hidden metallic state in 1T-TaS2 has so far been stabilized only at cryogenic temperatures. Now it is shown that accessing an additional mixed-phase long-lived metastable state can stabilize the hidden phase at higher temperatures.in Nature Physics on 2025-06-27 00:00:00 UTC.
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Structural insights into ligand recognition and G protein preferences across histamine receptors
Communications Biology, Published online: 27 June 2025; doi:10.1038/s42003-025-08363-7
This study presents cryo-EM structures of H4R–Gi and H1R–Gi/Gs complexes, revealing distinct histamine recognition, activation mechanisms, and a critical determinant of G protein selectivity in H1R and H4R.in Nature communications biology on 2025-06-27 00:00:00 UTC.
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Neurons throughout the brain embed robust signatures of their anatomical location into spike trains
Neurons in the brain are known to encode diverse information through their spiking activity, primarily reflecting external stimuli and internal states. However, whether individual neurons also embed information about their own anatomical location within their spike patterns remains largely unexplored. Here, we show that machine learning models can predict a neuron’s anatomical location across multiple brain regions and structures based solely on its spiking activity. Analyzing high-density recordings from thousands of neurons in awake, behaving mice, we demonstrate that anatomical location can be reliably decoded from neuronal activity across various stimulus conditions, including drifting gratings, naturalistic movies, and spontaneous activity. Crucially, anatomical signatures generalize across animals and even across different research laboratories, suggesting a fundamental principle of neural organization. Examination of trained classifiers reveals that anatomical information is enriched in specific interspike intervals as well as responses to stimuli. Within the visual isocortex, anatomical embedding is robust at the level of layers and primary versus secondary but does not robustly separate individual secondary structures. In contrast, structures within the hippocampus and thalamus are robustly separable based on their spike patterns. Our findings reveal a generalizable dimension of the neural code, where anatomical information is multiplexed with the encoding of external stimuli and internal states. This discovery provides new insights into the relationship between brain structure and function, with broad implications for neurodevelopment, multimodal integration, and the interpretation of large-scale neuronal recordings. Computational approximations of anatomy have the potential to support in vivo electrode localization.in eLife on 2025-06-27 00:00:00 UTC.
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Structural characterization and dynamics of AdhE ultrastructures from Clostridium thermocellum show a containment strategy for toxic intermediates
Clostridium thermocellum, a cellulolytic thermophilic anaerobe, is considered by many to be a prime candidate for the realization of consolidated bioprocessing (CBP) and is known as an industry standard for biofuel production. C. thermocellum is among the best biomass degraders identified to date in nature and produces ethanol as one of its main products. Many studies have helped increase ethanol titers in this microbe; however, ethanol production using C. thermocellum is still not economically viable. Therefore, a better understanding of its ethanol synthesis pathway is required. The main pathway for ethanol production in C. thermocellum involves the bifunctional aldehyde-alcohol dehydrogenase (AdhE). To better understand the function of the C. thermocellum AdhE, we used cryo-electron microscopy (cryo-EM) to obtain a 3.28 Å structure of the AdhE complex. This high-resolution structure, in combination with molecular dynamics simulations, provides insight into the substrate channeling of the toxic intermediate acetaldehyde, indicates the potential role of C. thermocellum AdhE to regulate activity and cofactor pools, and establishes a basis for future engineering studies. The containment strategy found in this enzyme offers a template that could be replicated in other systems where toxic intermediates need to be sequestered to increase the production of valuable biochemicals.in eLife on 2025-06-27 00:00:00 UTC.
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Disruptions in primary visual cortex physiology and function in a mouse model of Timothy syndrome
AbstractTimothy syndrome (TS) is a rare genetic disorder caused by mutations in the CACNA1C gene, which encodes the L-type calcium channel α1 CaV1.2 subunit. While it is expressed throughout the body, the most serious symptoms are cardiac and neurological. Classical TS type 1 (TS1) and TS type 2 (TS2) mutations cause prolonged action potentials (APs) in cardiomyocytes and in induced neurons derived from pluripotent stem cells taken from TS patients, but the effects of TS mutations on neuronal function in vivo are not fully understood. TS is frequently associated with autistic traits, which in turn have been linked to altered sensory processing. Using the TS2-neo mouse model, we analyzed the effects of TS2 mutation on the visual system. We observed a widening of APs of pyramidal cells in ex vivo patch clamp recordings and an increase in the density of parvalbumin-positive cells in the primary visual cortex. Neurons from TS2-neo mice recorded extracellularly in vivo were less likely to respond to visual stimuli of low spatial frequency, but more likely to respond to visual stimuli of mid-to-high spatial frequency, compared to those from wild-type mice. These results point to a basic processing abnormality in the visual cortex of TS2-neo mice.in Cerebral Cortex on 2025-06-27 00:00:00 UTC.
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The neural basis of sensorimotor expertise: investigating the role of theta oscillations and the superior parietal lobule using repetitive transcranial magnetic stimulation (rTMS)
AbstractThe study investigates the neural mechanisms underlying sensorimotor integration in motor experts (athletes in fast-paced sports), focusing on their enhanced ability to predict and adapt to dynamic movement patterns within the scope of the action emulation framework. Two experiments were conducted to examine these mechanisms. The first experiment compared experts and novices in a continuous tracking task, revealing that athletes displayed superior tracking performance, particularly on predictable trajectory segments. Electroencephalography (EEG) analysis identified distinct theta band oscillations between the groups. The source localization highlighted the superior parietal lobule (SPL) as a critical region associated with experts’ enhanced motor prediction capabilities. The second experiment employed repetitive transcranial magnetic stimulation (rTMS) to inhibit SPL activity and explore its causal role in motor expertise. Results indicated that rTMS disrupted specific neural oscillations but did not significantly alter behavioral performance, suggesting compensatory mechanisms in functionally connected regions. Differences in theta and beta oscillations between experts and novices’ post-stimulation highlight the adaptive neural plasticity underlying motor expertise. These findings contribute to our understanding of sensorimotor integration in expertise, reinforcing the role of feedforward modeling and predictive processing. This work advances our understanding of the neural substrates underlying high-level sensorimotor expertise.in Cerebral Cortex on 2025-06-27 00:00:00 UTC.
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Distinct neurochemical predictors for different phases of decision-making learning
AbstractFast and accurate sensory–motor mapping is characteristic of successful interaction with our environment and decision-making. Learning is crucial for the development of decision-making processes and has been linked to the balance of excitatory (glutamate) and inhibitory (γ-aminobutyric acid [GABA]) neurochemicals in the cortex. However, learning is not a unitary phenomenon and occurs across time. How neurochemical concentrations are involved, and the role of interventions like transcranial direct current stimulation (tDCS) remains unclear. The efficacy of tDCS to modulate learning has been linked to baseline concentrations of GABA and glutamate, and stimulation may influence neurochemical concentrations. Here, we assessed how neurochemical balance is associated with tDCS modulations to early- and later-phase sensory–motor learning using in vivo 7T ultra-high field magnetic resonance spectroscopy of the right motor cortex (M1), right intraparietal sulcus (IPS), and left prefrontal cortex. A single-dual task paradigm assessed performance immediately post (early learning) and 20 min post (later learning) offline cathodal stimulation to the left prefrontal cortex. tDCS modulations to learning were associated with neurochemical balance in right IPS during early learning, which shifted to right M1 for later learning. These findings elucidate the neurochemical mechanisms at play as sensory–response mappings shift from executive to motoric operations.in Cerebral Cortex on 2025-06-27 00:00:00 UTC.
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Interference Underlies Attenuation upon Relearning in Sensorimotor Adaptation
Savings refers to the gain in performance upon relearning. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit adaptation, a process that uses errors to recalibrate the sensorimotor map, is attenuated upon relearning (
Avraham et al., 2021 ). Here, we test the hypothesis that this attenuation is due to interference arising from the different relationship between the movement and the feedback during washout. Removing the perturbation at the start of the washout block typically results in a salient error signal in the opposite direction to that observed during learning. We first replicated the finding that implicit adaptation is attenuated following a washout period that introduces salient opposite errors. When we eliminated feedback during washout, relearning was no longer attenuated, consistent with the interference hypothesis. Next, we created a scenario in which the perceived errors during washout were not salient, falling within the range of motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended initial experience with veridical feedback and found that this was sufficient to attenuate adaptation during the first learning block. This effect was context specific and did not generalize to other movements. Taken together, the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.in eNeuro on 2025-06-26 16:30:28 UTC.
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Release of Extracellular Matrix Components after Human Traumatic Brain Injury
Animal studies and human tissue experiments have demonstrated that traumatic brain injury (TBI) causes damage to the extracellular matrix (ECM). To test the hypothesis that TBI causes disruption of sulfated glycosaminoglycan (sGAG) in the ECM, we measured levels of sGAG in the cerebrospinal fluid (CSF), blood, and urine, in patients with severe TBI in the acute postinjury period. Samples of CSF, blood, and urine were obtained within 72 h of injury in patients who received external ventricular drains as part of their treatment of severe TBI. Levels of chondroitin and heparan sGAGs were measured, along with their disaccharide constituents. Demographic information, presence of polytrauma, brain injury load, and distance of radiologically visible parenchymal injury from the ventricle were analyzed for correlation with total subtype sGAG levels. Levels were measured in 14 patients ranging in age from 17 to 90 years. CSF sGAG levels were variable among patients, with higher sGAG levels in plasma compared with CSF. Patients with polytrauma had nonsignificantly higher blood sGAG compared with patients with isolated head injury. Subcategories of CSF sGAG levels correlated with distance from the ventricle of parenchymal injury but not with brain injury load. This study is the first to measure sGAG levels in ventricular CSF and the first to analyze levels in TBI. These data demonstrate the elevation locally of intracranial sGAGs after severe TBI and suggest rapid local metabolism of these breakdown products. The consequences of ECM breakdown may provide unique therapeutic and preventive avenues to mitigate postinjury sequelae.
in eNeuro on 2025-06-26 16:30:28 UTC.
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Allosteric modulation of proton binding confers Cl- activation and glutamate selectivity to vesicular glutamate transporters
by Bart Borghans, Daniel Kortzak, Piersilvio Longo, Bettina Kolen, Jan-Philipp Machtens, Christoph Fahlke
Vesicular glutamate transporters (VGLUTs) fill synaptic vesicles with glutamate and remove luminal Cl- via an additional anion channel mode. Both of these transport functions are stimulated by luminal acidification, luminal-positive membrane potential, and luminal Cl-. We studied VGLUT1 transporter/channel activation using a combination of heterologous expression, cellular electrophysiology, fast solution exchange, and mathematical modeling. Cl- channel gating can be described with a kinetic scheme that includes two protonation sites and distinct opening, closing, and Cl--binding rates for each protonation state. Cl- binding promotes channel opening by modifying the pKa values of the protonation sites and rates of pore opening and closure. VGLUT1 transports glutamate and aspartate at distinct stoichiometries: H+-glutamate exchange at 1:1 stoichiometry and aspartate uniport. Neurotransmitter transport with variable stoichiometry can be described with an alternating access model that assumes that transporters without substrate translocate in the doubly protonated state to the inward-facing conformation and return with the bound amino acid substrate as either singly or doubly protonated. Glutamate, but not aspartate, promotes the release of one proton from inward-facing VGLUT1, resulting in preferential H+-coupled glutamate exchange. Cl- stimulates glutamate transport by making the glutamate-binding site accessible to cytoplasmic glutamate and by facilitating transitions to the inward-facing conformation after outward substrate release. We conclude that allosteric modification of transporter protonation by Cl- is crucial for both VGLUT1 transport functions.in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.
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Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk
by Jiaqi Hu, Yixuan Ye, Chi Zhang, Yunfeng Ruan, Pradeep Natarajan, Hongyu Zhao
BackgroundPolygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions.
MethodsUsing summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB).
ResultsWe decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS.
ConclusionOur findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.
in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.
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AI-first structural identification of pathogenic protein target interfaces
by Mihkel Saluri, Michael Landreh, Patrick Bryant
The risk of pandemics is increasing as global population growth and interconnectedness accelerate. Understanding the structural basis of protein-protein interactions between pathogens and hosts is critical for elucidating pathogenic mechanisms and guiding treatment or vaccine development. Despite 21,064 experimentally supported human-pathogen interactions in the HPIDB, only 52 have resolved structures in the PDB, representing just 0.2%. Advances in protein complex structure prediction, such as AlphaFold, now enable highly accurate modelling of heterodimeric complexes, though their application to host-pathogen interactions, which have distinct evolutionary dynamics, remains underexplored. Here, we investigate the structural protein-protein interaction network between humans and ten pathogens, predicting structures for 9,452 interactions, only 10 of which have known structures. We identify 30 interactions with an expected TM-score ≥0.9, tripling the structural coverage in these networks. A detailed analysis of the Francisella tularensis dihydroprolyl dehydrogenase (IPD) complex with human immunoglobulin kappa constant (IGKC) using homology modelling and native mass spectrometry confirms a predicted 1:2:1 heterotetramer, suggesting potential roles in immune evasion. These findings highlight the transformative potential of structure prediction for rapidly advancing vaccine and drug development against novel pathogenic targets.in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.
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On the usage of artificial intelligence in leprosy care: A systematic literature review
by Hilson Gomes Vilar de Andrade, Elisson da Silva Rocha, Kayo H. de Carvalho Monteiro, Cleber Matos de Morais, Danielle Christine Moura dos Santos, Dimas Cassimiro Nascimento, Raphael A. Dourado, Theo Lynn, Patricia Takako Endo
Leprosy, or Hansen’s disease, is a Neglected Tropical Disease (NTD) caused by Mycobacterium leprae that mainly affects the skin and peripheral nerves, causing neuropathy to varying degrees. It can result in physical disabilities and functional loss and is particularly prevalent amongst the most vulnerable populations in tropical and subtropical regions worldwide. The persistent stigma and social exclusion associated with leprosy complicate eradication efforts exacerbate the wider challenges faced by NTDs in sourcing the necessary resources and attention for control and elimination. The introduction of Multidrug Therapy (MDT) significantly lowers the global disease burden. Despite this breakthrough in the treatment of leprosy, over 200,000 new leprosy cases are reported annually across more than 120 countries, emphasizing the need for ongoing detection and management efforts. Artificial Intelligence (AI) has the potential to transform leprosy care by accelerating early detection, improving accurate diagnosis, and enabling predictive modeling to improve the quality for those affected. The potential of AI to provide information to assist healthcare professionals in interventions that reduce the risk of disability, and consequently stigma, particularly in endemic regions, presents a promising path to reducing the incidence of leprosy and improving integration social status of patients. This systematic literature review (SLR) examines the state of the art in research on the use of AI for leprosy care. From an initial 657 works from six scientific databases (ACM Digital Library, IEEE Xplore, PubMed, Scopus, Science Direct and Springer), only 30 relevant works were identified, after analysis of three independent reviewers. We have excluded works due duplication, couldn’t be retrieved and quality assessment. Results show that current research is focused primarily on the identification of symptoms using image based classification using three main techniques, neural networks, convolutional neural networks, and support vector machines; a small number of studies focus on other thematic areas of leprosy care. A comprehensive systematic approach to research on the application of AI to leprosy care can make a meaningful contribution to a leprosy-free world and help deliver on the promise of the Sustainable Development Goals (SDG).in PLoS Computational Biology on 2025-06-26 14:00:00 UTC.
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N2 sleep promotes the occurrence of ‘aha’ moments in a perceptual insight task
by Anika T. Löwe, Marit Petzka, Maria M. Tzegka, Nicolas W. Schuck
Humans sometimes have an insight that leads to a sudden and drastic performance improvement on the task they are working on. The precise origins of such insights are unknown. Some evidence has shown that sleep facilitates insights, while other work has not found such a relationship. One recent suggestion that could explain this mixed evidence is that different sleep stages have differential effects on insight. In addition, computational work has suggested that neural variability and regularisation play a role in increasing the likelihood of insight. To investigate the link between insight and different sleep stages as well as regularisation, we conducted a preregistered study in which N=90 participants performed a perceptual insight task before and after a 20 minute daytime nap. Sleep EEG data showed that N2 sleep, but not N1 sleep, increases the likelihood of insight after a nap, suggesting a specific role of deeper sleep. Exploratory analyses of EEG power spectra showed that spectral slopes could predict insight beyond sleep stages, which is broadly in line with theoretical suggestions of a link between insight and regularisation. In combination, our findings point towards a role of N2 sleep and aperiodic, but not oscillatory, neural activity for insight.in PLoS Biology on 2025-06-26 14:00:00 UTC.
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Reply to “Enhancing the Evaluation of IVT in DOAC‐Treated Stroke Patients: Addressing Methodological Considerations for Future Research”
in Annals of Neurology on 2025-06-26 12:04:23 UTC.
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Enhancing the Evaluation of IVT in DOAC‐Treated Stroke Patients: Addressing Methodological Considerations for Future Research
in Annals of Neurology on 2025-06-26 12:00:03 UTC.
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The Role of Electroencephalography in Predicting Post‐Stroke Seizures and an Updated Prognostic Model (SeLECT‐EEG)
Objective
Seizures negatively impact stroke outcomes, highlighting the need for reliable predictors of post-stroke epilepsy. Although acute symptomatic seizures are a known risk factor, most stroke survivors who develop epilepsy do not experience them. Early electroencephalography (EEG) findings may enhance risk prediction, particularly in patients without acute symptomatic seizures, aiding in patient management and counseling.
Methods
We conducted a multicenter cohort study using data from 1,105 stroke survivors (mean age 71 years, 54% male) with neuroimaging-confirmed ischemic stroke who underwent EEG within 7 days post-stroke. Electrographic biomarkers, including epileptiform activity and regional slowing, were analyzed for their association with post-stroke epilepsy using Cox proportional hazards regression and Fine–Gray subdistribution hazard models, adjusted for differences in EEG timing and patient characteristics.
Results
Post-stroke epilepsy developed in 119 patients (11%), whereas 233 (21%) had acute symptomatic seizures. The 5-year epilepsy risk was 42% (95% confidence interval [CI]: 30–49%) in patients with epileptiform activity versus 13% (95% CI: 9–16%) in those without. Regional slowing doubled the 5-year epilepsy risk (23%, 95% CI: 17–30% vs 11%, 95% CI: 7–16%). Epileptiform activity (subdistribution hazard ratio: 2.3, 95% CI: 1.5–3.4, p < 0.001) and regional slowing (subdistribution hazard ratio: 1.7, 95% CI: 1.1–2.7, p = 0.02) were independently associated with post-stroke epilepsy. A novel prognostic model, SeLECT-EEG (concordance statistic: 0.75, 95% CI: 0.71–0.80), outperformed the previous standard (SeLECT2.0; 0.71, 95% CI: 0.65–0.76, p < 0.001).
Interpretation
Electrographic biomarkers improve post-stroke epilepsy prediction beyond clinical risk factors. The SeLECT-EEG model enhances early risk stratification, particularly in patients without acute symptomatic seizures, informing management strategies and patient counseling. ANN NEUROL 2025
in Annals of Neurology on 2025-06-26 10:24:08 UTC.
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Dynamic landscapes and statistical limits on growth during cell fate specification
Author(s): Gautam Reddy
Motivated by developmental processes in biology, this study extends a classical optimal transport framework to processes that include growth. One key result presented here is the derivation of an analog of the Benamou-Brenier theorem, which identifies the conditions under which the transport map is described by stochastic dynamics on a potential landscape. The author exploits a mathematical connection between stochastic control theory, optimal transport and nonequilibrium thermodynamics. The framework can be used to find a potential landscape that describes the map from any (non-degenerate) initial distribution over cell states (of arbitrary dimensionality) to any target distribution in a finite time.
[Phys. Rev. E 111, 064418] Published Thu Jun 26, 2025
in Physical Review E: Biological physics on 2025-06-26 10:00:00 UTC.
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Enhancing global clinical trial transparency for better health outcomes for all [version 1; peer review: awaiting peer review]
Background In 2022, WHO’s World Health Assembly adopted resolution WHA75.8, emphasizing the critical role of clinical trials in generating high-quality evidence and promoting equitable access to health interventions globally. In response, rapid landscape reviews were conducted to assess global clinical trial regulations, capacities, and funding distribution. Methods The analysis synthesized regulatory frameworks from 94 countries, institutional capacity data from the WHO International Clinical Trial Registry Platform (ICTRP), and funding data from World RePORT for trials registered between 2018-2022. Gaps in data availability and quality were assessed. Results Most countries reference international ethical guidelines, with universal requirements for ethics approval and informed consent. However, only 66% mandate public trial registration, and 40% require results reporting, with stark disparities between high- and low-income countries. High-income countries host over half of global trials; low-income countries contribute less than 1% despite high disease burden. Clinical trials sponsored by non-commercial entities are particularly scarce in low- and middle-income countries. Funding remains concentrated in the Americas and European regions, primarily driven by major funders such as the National Institutes of Health in the United States of America and European Commission. Significant data accessibility challenges persist due to incomplete registry records, inconsistent standards, lack of harmonized identifiers, and limited bulk data access. Recommendations Urgent actions include reinforcing international standards for trial registries, harmonizing data fields, improving registry interoperability, leveraging unique identifiers, enhancing multilingual accessibility, auditing data quality, pooling analytical resources, promoting open data policies, and investing in registry infrastructure and trained personnel. Conclusion Addressing data gaps and inequities in clinical trial ecosystems requires concerted action by global stakeholders. Improved data transparency and interoperability are essential to guide equitable research investments, foster coordination, and strengthen clinical trial capacity worldwide.in F1000Research on 2025-06-26 08:55:00 UTC.
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μ‐Opioid Receptor Dynamics in the Parameningeal Tissue During Migraine Attacks
Objective
The possible impact of meningeal μ-opioid receptor (μOR) binding in migraine remains unknown. This study investigated μOR availability in the cranial parameninges involved in migraine initiation via nociceptor activation.
Methods
We used positron emission tomography with [11C] carfentanil, and measured μOR availability in meninges and adjacent skull bone (parameningeal tissue [PMT]) under resting and sustained thermal pain threshold stress challenge conditions. μOR availability was compared between individuals with migraine in interictal and ictal phases and healthy controls. Furthermore, we examined the relationship between μOR availability and headache intensity, as well as the potential influence of sex on this measure.
Results
A total of 36 patients with interictal episodic migraine (8 also assessed ictally), 7 patients with ictal chronic migraine, and 22 healthy controls were included in the analysis. Both the episodic migraine and chronic migraine groups showed lower μOR availability in the parietal PMT than healthy controls during the ictal resting phase. No significant differences were observed during the interictal phase. Exploratory analyses on the effects of sex indicated that both healthy women and migraine patients of both sexes showed lower μOR availability in the frontal PMT compared with healthy men in the ictal sustained thermal pain threshold stress condition. Furthermore, the interictal μOR availability in the frontal PMT was negatively associated with headache intensity in the preceding month.
Interpretation
The observed variability in PMT μOR availability across the different cortical regions and migraine episodes, along with its association with pain intensity, underscores the critical role of extracerebral mechanisms in migraine pathophysiology. ANN NEUROL 2025
in Annals of Neurology on 2025-06-26 07:00:00 UTC.
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