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Laboratory-Based Retrospective Study on ANA Profile Results in Ajman: A Decade of Autoantibody Distribution by Age and Gender [version 1; peer review: awaiting peer review]
Background Antinuclear antibodies (ANA) are vital in diagnosing and monitoring autoimmune diseases, with prevalence affected by demographics and environment. Aim This study analyzed ANA testing trends over a decade in Ajman, UAE, focusing on prevalence, antibody types, and demographics, filling a gap in Middle Eastern longitudinal data. Methods A retrospective, cross-sectional examination of Thumbay Labs ANA profile data from 2015 to 2025 was performed. HEp-2 cell–based indirect immunofluorescence assays were run first, followed by extractable nuclear antigen testing. In addition to age and gender, autoantibody patterns were collected. While descriptive statistics summarized prevalence, chi-square tests examined associations. Logistic regression models estimated independent ANA-positive predictor ORs and 95% CIs. Results Among 2,482 individuals tested (67.6% female), 30.7% demonstrated positivity for at least one ANA-related antibody. Anti-Ro52 (7.9%), anti-SSA/Ro (7.2%), and anti-RNP/Sm (4.3%) were the most frequently detected autoantibodies. Females exhibited significantly higher ANA positivity than males (33.1% vs. 23.1%; p < 0.001). Gender remained an independent predictor in multivariable analysis (OR = 1.42; 95% CI: 1.18–1.72), with females also showing increased odds of anti-Ro52, anti-SSA/Ro, anti-SSB/La, and anti-histone reactivity. Although age demonstrated variability in univariate analyses, it did not independently predict ANA positivity. Conclusions Our study results align with international trends and provide the first decade-long summary of ANA testing patterns in the UAE. The data establish a baseline for autoimmune disease surveillance and highlight the need for clinical–laboratory coordination and prospective studies to understand ANA reactivity in this location further.in F1000Research on 2026-04-22 07:48:54 UTC.
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Developing a Virtual Research Environment in the Parkinson's Progression Markers Initiative: myPPMI
In the 15 years since Parkinson's Progression Markers Initiative (PPMI) launched, research conduct has advanced with broader connectivity, enabling virtual and hybrid methods for recruitment, engagement, education, and data collection. To meet evolving needs, PPMI created “myPPMI,” which has grown from an informational portal to a multi-country, participant-centered, virtual research environment integrating education, screening, e-consent, longitudinal non-motor and motor assessments, and biospecimen referral. Built on a secure, cloud-native architecture with daily analytics and a multi-tier support model, myPPMI enables precision recruitment, real-time eligibility matching, and standardized low-burden data capture across studies. The platform is designed to enable focused data collection from individuals or groups based on the data they have already provided. This strategy provides the tools to establish precise subsets of high interest that could be targeted for further data acquisition. Usability testing and rapid global scaling demonstrate a generalizable, decentralized framework for biomarker-driven, Parkinson's disease research. ANN NEUROL 2026
in Annals of Neurology on 2026-04-22 04:25:39 UTC.
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NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligence
arXiv:2604.18637v1 Announce Type: new Abstract: Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a workshop convened by the National Science Foundation in August 2025, we identify three fundamental capability gaps in current AI: the inability to interact with the physical world, inadequate learning that produces brittle systems, and unsustainable energy and data inefficiency. We describe the neuroscience principles that address each: co-design of body and controller, prediction through interaction, multi-scale learning with neuromodulatory control, hierarchical distributed architectures, and sparse event-driven computation. We present a research roadmap organized around these principles at near, mid, and long-term horizons. We argue that realizing this program requires a new generation of researchers trained across the boundary between neuroscience and engineering, and describe the institutional conditions: interdisciplinary training, hardware access, community standards, and ethics, needed to support them. We conclude that NeuroAI, neuroscience-informed artificial intelligence, has the potential to overcome limitations of current AI while deepening our understanding of biological neural computation.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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Quantum-Like Models of Cognition and Decision Making: Open-Systems and Gorini--Kossakowski--Sudarshan--Lindblad Dynamics
arXiv:2604.18643v1 Announce Type: new Abstract: This paper starts with surveying the evolution of quantum-like models of cognition and decision making, transitioning from static kinematic representations to a robust dynamical framework based on open quantum systems. We provide a comprehensive analysis of the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) master equation's application in cognitive psychology and decision making, illustrating how it models mental state evolution as a dissipative process influenced by an informational environment. We categorize dynamical regimes into Passive and Active Hamiltonians, demonstrating how non-commutation with projections on decision basis serves as a mathematical signature of cognitive agency and Quantum Escape from classical equilibria. The utility of this framework is further explored through its ability to stabilize non-Nash outcomes in strategic games, such as the Prisoner's Dilemma. Building upon this dynamical foundation, we identify ``cognitive beats'' as a signature of the internal struggle between competing ``flows of mind'' deliberated at approximately equal frequencies. Distinct from the damped oscillations of simple interference, these beats emerge from a structural tension between Liouvillian channels that generates a secondary, slow-scale modulation of conviction. This beat envelope dictates the timing of peak readiness and hesitation, providing a mathematical map of the transition between conflicting cognitive states. By resolving these nested time scales, we provide a new spectral diagnostic for the depth of cognitive agency and the complexity of the underlying deliberation process. This paper develops a theoretical framework linking GKSL dynamics with quantum-like cognition and decision-making (QCDM), highlighting how dissipative quantum models can capture features of human thought and decision processes.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens
arXiv:2604.18827v1 Announce Type: new Abstract: Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to modeling brain activity remains unclear. Here we leveraged a dataset of 3.1 million neurons from the visual cortex of 73 mice across 323 sessions, totaling more than 150 billion neural tokens recorded during natural movies, images and parametric stimuli, and behavior. We train multi-modal, multi-task models that support three regimes flexibly at test time: neural prediction, behavioral decoding, neural forecasting, or any combination of the three. OmniMouse achieves state-of-the-art performance, outperforming specialized baselines across nearly all evaluation regimes. We find that performance scales reliably with more data, but gains from increasing model size saturate. This inverts the standard AI scaling story: in language and computer vision, massive datasets make parameter scaling the primary driver of progress, whereas in brain modeling -- even in the mouse visual cortex, a relatively simple system -- models remain data-limited despite vast recordings. The observation of systematic scaling raises the possibility of phase transitions in neural modeling, where larger and richer datasets might unlock qualitatively new capabilities, paralleling the emergent properties seen in large language models. Code available at https://github.com/enigma-brain/omnimouse.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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Modelling time-order effects in haptic perception with a Bayesian dynamical framework
arXiv:2604.19662v1 Announce Type: new Abstract: Perceptual judgments of sequential stimuli are systematically biased by prior expectations and by the temporal structure of sensory input. In haptic discrimination tasks, these effects often manifest as time-order asymmetries, whereby the perceived difference between two stimuli depends on their presentation order. Here, we introduce a dynamical Bayesian model that accounts for these biases by combining noisy sensory measurements with an evolving internal representation of stimulus intensity. The model formalizes perception as an inference process in which prior expectations are updated by incoming stimuli and propagate in time between observations. We test the model on psychophysical data from vibrotactile discrimination experiments, in which participants compare pairs of sequential stimuli with varying intensities. With a small number of parameters, the model quantitatively reproduces both the direction and magnitude of time-order effects across subjects, as well as the observed inter-individual variability. The inferred parameters provide a compact description of perceptual biases in terms of prior expectations and noise characteristics. Beyond fitting the data, the model induces a transformation of stimulus space, leading to a subject-dependent geometry of perceived stimuli. In this transformed space, perceptual judgments exhibit approximate symmetries that are absent in the physical stimulus coordinates. These results suggest that temporal biases in perception can be understood as a consequence of dynamical inference, and that they impose non-trivial geometric constraints on perceptual representations.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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Simulation Based Inference of a Simple Neural Network Structure
arXiv:2604.18599v1 Announce Type: cross Abstract: Neurophysiologists are nowadays able to record from a large number of extracellular electrodes and to extract, from the raw data, the sequences of action potentials or spikes generated by many neurons. Unfortunately these ''many neurons'' still represent only a tiny fraction of the neuronal population that constitutes the network. Using association statistics such as the estimation of the cross-correlation functions, they are trying to infer the structure of the network formed by the recorded neurons. But this inference is compromised by the tremendous under-sampling of the neuronal population. We propose to focus instead on simple spike train statistics, like the empirical spikes frequency, or the interspike interval distribution. Their sampling distributions can be estimated by simulations, and, given a few observed spike train statistics, they provide enough information to infer the structure of the underlying network. We show that, on a ''toy model'', our method gives significantly better results than the sub-network reconstruction method with regards to the inference of the connection probability of the original network.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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Testing quantum-like markers in neural dynamics
arXiv:2508.21490v2 Announce Type: replace Abstract: We propose two experiments for identifying quantum markers in neural data based on quantum variants of well-known equations for neural activity that describe electrical signal propagation on axonal arbors and dendrites. These include (i) testing if power spectra from subthreshold oscillations in neuronal cultures follow the classical Fitzgugh-Nagumo equations or a recently introduced quantum variant of them and (ii) testing if propagation statistics of electrical activity in axons follow the classical diffusive cable equation or a quantum variant of it.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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Non-linear associations of amyloid-$\beta$ with resting-state functional networks and their cognitive relevance in a large community-based cohort of cognitively normal older adults
arXiv:2510.12751v2 Announce Type: replace Abstract: Background: Non-linear alterations in brain network connectivity may represent early neural signatures of Alzheimer's disease (AD) pathology in cognitively normal older adults. Understanding these changes and their cognitive relevance may help clarify early network vulnerability associated with AD pathology. Most prior studies recruited participants from memory clinics, often with subjective memory concerns, limiting generalizability. Methods: We examined 14 large-scale functional brain networks in 968 cognitively normal older adults recruited from the community using resting-state functional MRI, cerebrospinal fluid (CSF) biomarkers (amyloid-$\beta$ 1-42 [A$\beta$], total tau, phosphorylated tau 181), and neuropsychological assessments. Functional networks were identified using group independent component analysis. Results: Inverted U-shaped associations between CSF A$\beta$ and functional connectivity were observed in the precuneus network and ventral default mode network (DMN), but not in the dorsal DMN, indicating network-specific vulnerability to early amyloid pathology. Higher connectivity in A$\beta$-related networks, including dorsal and ventral DMN, precuneus, and posterior salience networks, was associated with better visual memory, visuospatial, and executive performance. No significant relationships were observed between CSF tau and functional connectivity. Conclusions: Using a large, community-based cohort, we demonstrate that non-linear alterations in functional connectivity occur in specific networks even during the asymptomatic phase of AD. Moreover, A$\beta$-related network connectivity is cognitively relevant, highlighting early network vulnerability and its functional consequences in amyloid pathology.in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-22 04:00:00 UTC.
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TurboEvolve: Towards Fast and Robust LLM-Driven Program Evolution
arXiv:2604.18607v1 Announce Type: new Abstract: LLM-driven program evolution can discover high-quality programs, but its cost and run-to-run variance hinder reliable progress. We propose TurboEvolve, a multi-island evolutionary framework that improves sample efficiency and robustness under fixed evaluation budgets. Inspired by the multiple-offspring strategy in evolutionary algorithms, TurboEvolve introduces verbalized Sampling, prompting the LLM to emit K diverse candidates with explicit self-assigned sampling weights, and an online scheduler that adapts K to expand exploration under stagnation and reduce overhead during steady progress. To exploit existing solution pools, we further propose "seed-pool injection," which clusters seeds and assigns them across islands with controlled perturbations and elitist preservation to balance diversity and refinement. Across multiple program-optimization benchmarks, TurboEvolve consistently achieves stronger performance at lower budgets and improves best-known solutions on several tasks.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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SpikeMLLM: Spike-based Multimodal Large Language Models via Modality-Specific Temporal Scales and Temporal Compression
arXiv:2604.18610v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but incur substantial computational overhead and energy consumption during inference, limiting deployment in resource-constrained environments. Spiking Neural Networks (SNNs), with their sparse event-driven computation, offer inherent energy efficiency advantages on neuromorphic hardware, yet extending them to MLLMs faces two key challenges: heterogeneous modalities make uniform spike encoding insufficient, and high-resolution image inputs amplify timestep unfolding overhead. We propose SpikeMLLM, the first spike-based framework for MLLMs, which unifies existing ANN quantization methods in the spiking representation space and incorporates Modality-Specific Temporal Scales (MSTS) guided by Modality Evolution Discrepancy (MED) and Temporally Compressed LIF (TC-LIF) for timestep compression from T=L-1 to T=log2(L)-1. Experiments on four representative MLLMs across diverse multimodal benchmarks show that SpikeMLLM maintains near-lossless performance under aggressive timestep compression (Tv/Tt=3/4), with average gaps of only 0.72% and 1.19% relative to the FP16 baseline on InternVL2-8B and Qwen2VL-72B. We further develop a dedicated RTL accelerator tailored to the spike-driven datapath, observing 9.06x higher throughput and 25.8x better power efficiency relative to an FP16 GPU baseline under a deployment-oriented co-design setting, suggesting the promise of algorithm-hardware co-design for efficient multimodal intelligence.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Neuromorphic Continual Learning for Sequential Deployment of Nuclear Plant Monitoring Systems
arXiv:2604.18611v1 Announce Type: new Abstract: Anomaly detection in nuclear industrial control systems (ICS) requires continuous, energy-efficient monitoring across multiple subsystems that are often deployed at different stages of plant commissioning. When a conventional neural network is sequentially trained to monitor new subsystems, it catastrophically forgets previously learned anomaly patterns, a safety-critical failure mode. We present the first spiking neural network (SNN)-based anomaly detection system with continual learning for nuclear ICS, addressing both challenges simultaneously. Our approach introduces spike-encoded asynchronous sensor fusion, a delta-based encoding that converts heterogeneous sensor streams into sparse spike trains at rates dictated by each sensor's natural dynamics, achieving 92.7% input sparsity. We evaluate five continual learning strategies, including sequential fine-tuning, Elastic Weight Consolidation (EWC), Synaptic Intelligence (SI), experience replay, and a hybrid EWC+Replay approach, on the HAI 21.03 nuclear ICS security dataset across three sequentially deployed subsystems (boiler, turbine, water treatment). The hybrid EWC+Replay method achieves an average F1 score of 0.979 with near-zero average forgetting (AF = 0.000 single seed; 0.035 +/- 0.039 across three seeds), while requiring 12.6x fewer operations (an estimated 2.5x in energy based on published hardware specifications) than an equivalent artificial neural network. The system detects all tested attacks with a mean latency of 0.6 seconds. These results demonstrate that neuromorphic computing offers a viable path toward always-on, energy-efficient, and adaptable safety monitoring for next-generation nuclear facilities.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models
arXiv:2604.18612v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, while recent prompting strategies such as Chain-of-Thought (CoT) have further elevated their performance in handling complex logical problems. Despite these advances, high-quality reasoning remains heavily reliant on manual static prompts and is sensitive to decoding configurations and task distributions, leading to performance fluctuations and limited transferability. Existing automatic prompt optimization methods typically adopt single-agent local search, failing to simultaneously optimize prompts and decoding hyperparameters within a unified framework to achieve stable global improvements. To address this limitation, we propose Agent-GWO, a dynamic prompt optimization framework for complex reasoning. Specifically, we unify prompt templates and decoding hyperparameters as inheritable agent configurations. By leveraging the leader-follower mechanism of the Grey Wolf Optimizer (GWO), we automatically select three leader agents ($\alpha$, $\beta$, and $\delta$) to guide the collaborative updates of the remaining agents, enabling iterative convergence toward robust optimal reasoning configurations that can be seamlessly integrated for inference. Extensive experiments on multiple mathematical and hybrid reasoning benchmarks across diverse LLM backbones show that Agent-GWO consistently improves accuracy and stability over existing prompt optimization methods. The code will be released publicly.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Optimising Urban Flood Resilience
arXiv:2604.18620v1 Announce Type: new Abstract: Due to the increasing frequency and severity of storm events, driven by the escalation of anthropogenic climate change and urban expansion, there is a requirement for increasingly efficient flood risk management strategies. While Blue-Green Infrastructure (BGI) offers a sustainable solution for managing flood risk, optimal implementation is challenging. To help overcome this challenge, this study presents a novel multi-objective optimisation tool that couples a state-of-the-art hydrodynamic model with a bespoke evolutionary algorithm. The use of a fully dynamic hydrodynamic model enables the tool to accurately evaluate the effectiveness of proposed BGI features with respect to property scale flood vulnerability and hazard analysis. This contrasts with alternative approaches which utilise simplified models, which can only reliably predict inundation extents, thus the proposed optimisation tool provides greater certainty regarding the optimality of the solutions. As a hydrodynamic simulation is required to evaluate each candidate solution, the bespoke evolutionary algorithm is specifically designed to minimise the number of simulations required, ensuring the tool is computationally practical. The effectiveness of the tool in this regard is validated via the derivation of exact convergence measures, for a tractable search space, and via comparisons with benchmark algorithms, for an intractable search space. Compared with traditional design practices, the proposed tool offers an automated approach capable of efficiently exploring a wide range of solutions, providing decision-makers with a set of optimal solutions from which they can make informed investment decisions. The presented methods provide a robust framework for optimising a variety of BGI features in complex urban environments.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Scalable Memristive-Friendly Reservoir Computing for Time Series Classification
arXiv:2604.19343v1 Announce Type: new Abstract: Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physical substrate. This unique characteristic enables efficient, fast, and adaptive computing, particularly well suited for deep learning applications. Among recent developments, the memristive-friendly echo state network (MF-ESN) has emerged as a promising approach that combines memristive-inspired dynamics with the training simplicity of reservoir computing, where only the readout layer is learned. Building on this framework, we propose memristive-friendly parallelized reservoirs (MARS), a simplified yet more effective architecture that enables efficient scalable parallel computation and deeper model composition through novel subtractive skip connections. This design yields two key advantages: substantial training speedups of up to 21x over the inherently lightweight echo state network baseline and significantly improved predictive performance. Moreover, MARS demonstrates what is possible with parallel memristive-friendly reservoir computing: on several long sequence benchmarks our compact gradient-free models substantially outperform strong gradient-based sequence models such as LRU, S5, and Mamba, while reducing full training time from minutes or hours down seconds or even only a few hundred milliseconds. Our work positions parallel memristive-friendly computing as a promising route towards scalable neuromorphic learning systems that combine high predictive capability with radically improved computational efficiency, while providing a clear pathway to energy-efficient, low-latency implementations on emerging memristive and in-memory hardware.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Large Language Models Exhibit Normative Conformity
arXiv:2604.19301v1 Announce Type: cross Abstract: The conformity bias exhibited by large language models (LLMs) can pose a significant challenge to decision-making in LLM-based multi-agent systems (LLM-MAS). While many prior studies have treated "conformity" simply as a matter of opinion change, this study introduces the social psychological distinction between informational conformity and normative conformity in order to understand LLM conformity at the mechanism level. Specifically, we design new tasks to distinguish between informational conformity, in which participants in a discussion are motivated to make accurate judgments, and normative conformity, in which participants are motivated to avoid conflict or gain acceptance within a group. We then conduct experiments based on these task settings. The experimental results show that, among the six LLMs evaluated, up to five exhibited tendencies toward not only informational conformity but also normative conformity. Furthermore, intriguingly, we demonstrate that by manipulating subtle aspects of the social context, it may be possible to control the target toward which a particular LLM directs its normative conformity. These findings suggest that decision-making in LLM-MAS may be vulnerable to manipulation by a small number of malicious users. In addition, through analysis of internal vectors associated with informational and normative conformity, we suggest that although both behaviors appear externally as the same form of "conformity," they may in fact be driven by distinct internal mechanisms. Taken together, these results may serve as an initial milestone toward understanding how "norms" are implemented in LLMs and how they influence group dynamics.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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What Makes an LLM a Good Optimizer? A Trajectory Analysis of LLM-Guided Evolutionary Search
arXiv:2604.19440v1 Announce Type: cross Abstract: Recent work has demonstrated the promise of orchestrating large language models (LLMs) within evolutionary and agentic optimization systems. However, the mechanisms driving these optimization gains remain poorly understood. In this work, we present a large-scale study of LLM-guided evolutionary search, collecting optimization trajectories for 15 LLMs across 8 tasks. Although zero-shot problem-solving ability correlates with final optimization outcomes, it explains only part of the variance: models with similar initial capability often induce dramatically different search trajectories and outcomes. By analyzing these trajectories, we find that strong LLM optimizers behave as local refiners, producing frequent incremental improvements while progressively localizing the search in semantic space. Conversely, weaker optimizers exhibit large semantic drift, with sporadic breakthroughs followed by stagnation. Notably, various measures of solution novelty do not predict final performance; novelty is beneficial only when the search remains sufficiently localized around high-performing regions of the solution space. Our results highlight the importance of trajectory analysis for understanding and improving LLM-based optimization systems and provide actionable insights for their design and training.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Learning Evolution via Optimization Knowledge Adaptation
arXiv:2501.02200v2 Announce Type: replace Abstract: The iterative search process of evolutionary algorithms (EAs) encapsulates optimization knowledge within historical populations and fitness evaluations. Effective utilization of this knowledge is crucial for facilitating knowledge transfer and online adaptation. However, current research typically addresses these goals in isolation and faces distinct limitations: evolutionary sequential transfer optimization often suffers from incomplete utilization of prior knowledge, while adaptive strategies, utilizing real-time knowledge, are limited to tailoring specific evolutionary operators. To simultaneously achieve these two capabilities, we introduce the Optimization Knowledge Adaptation Evolutionary Model (OKAEM), a unified learnable evolutionary framework capable of adaptively updating parameters based on available optimization knowledge. By parameterizing evolutionary operators via attention mechanisms, OKAEM enables learnable update rules that facilitate the utilization of optimization knowledge via two phases: pre-training to integrate extensive prior knowledge for efficient transfer, and adaptive optimization to dynamically update parameters based on real-time knowledge. Experimental results confirm that OKAEM significantly outperforms state-of-the-art sequential transfer methods across 12 transfer scenarios via pre-training, and surpasses advanced learnable EAs solely through its self-tuning mechanism in prior-free settings. Beyond demonstrating practical utility in prompt tuning for vision-language models, ablation studies validate the necessity of the learnable components, while visualization analyses reveal the model's capacity to autonomously discover interpretable evolutionary principles. The code can be accessed at https://gitee.com/Anonymity_Paper/code-of-okaem.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Pareto Optimization with Robust Evaluation for Noisy Subset Selection
arXiv:2501.06813v2 Announce Type: replace Abstract: Subset selection is a fundamental problem in combinatorial optimization, which has a wide range of applications such as influence maximization and sparse regression. The goal is to select a subset of limited size from a ground set in order to maximize a given objective function. However, the evaluation of the objective function in real-world scenarios is often noisy. Previous algorithms, including the greedy algorithm and multi-objective evolutionary algorithms POSS and PONSS, either struggle in noisy environments or consume excessive computational resources. In this paper, we focus on the noisy subset selection problem with a cardinality constraint, where the evaluation of a subset is noisy. We propose a novel approach based on Pareto Optimization with Robust Evaluation for noisy subset selection (PORE), which maximizes a robust evaluation function and minimizes the subset size simultaneously. PORE can efficiently identify well-structured solutions and handle computational resources, addressing the limitations observed in PONSS. Our experiments, conducted on real-world datasets for influence maximization and sparse regression, demonstrate that PORE significantly outperforms previous methods, including the classical greedy algorithm, POSS, and PONSS. Further validation through ablation studies confirms the effectiveness of our robust evaluation function.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models
arXiv:2601.00679v2 Announce Type: replace Abstract: Large Language Models (LLMs) have been emerging as prominent AI models for solving many natural language tasks due to their high performance (e.g., accuracy) and capabilities in generating high-quality responses to the given inputs. However, their large computational cost, huge memory footprints, and high processing power/energy make it challenging for their embedded deployments. Amid several tinyLLMs, recent works have proposed spike-driven language models (SLMs) for significantly reducing the processing power/energy of LLMs. However, their memory footprints still remain too large for low-cost and resource-constrained embedded devices. Manual quantization approach may effectively compress SLM memory footprints, but it requires a huge design time and compute power to find the quantization setting for each network, hence making this approach not-scalable for handling different networks, performance requirements, and memory budgets. To bridge this gap, we propose QSLM, a novel framework that performs automated quantization for compressing pre-trained SLMs, while meeting the performance and memory constraints. To achieve this, QSLM first identifies the hierarchy of the given network architecture and the sensitivity of network layers under quantization, then employs a tiered quantization strategy (e.g., global-, block-, and module-level quantization) while leveraging a multi-objective performance-and-memory trade-off function to select the final quantization setting. Experimental results indicate that our QSLM reduces memory footprint by up to 86.5%, reduces power consumption by up to 20%, maintains high performance across different tasks (i.e., by up to 84.4% accuracy of sentiment classification on the SST-2 dataset and perplexity score of 23.2 for text generation on the WikiText-2 dataset) close to the original non-quantized model while meeting the performance and memory constraints.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Diversifying Toxicity Search in Large Language Models Through Speciation
arXiv:2601.20981v2 Announce Type: replace Abstract: Evolutionary prompt search is a practical black-box approach for red teaming large language models, however existing methods often collapse onto a small family of high-performing prompts, limiting coverage of distinct failure modes. We present a speciated quality-diversity extension of \textit{ToxSearch} that maintains multiple high-toxicity prompt niches in parallel rather than optimizing a single best prompt. \textit{ToxSearch-S} introduces unsupervised prompt speciation via a search methodology that maintains capacity-limited species with exemplar leaders, a reserve pool for emerging niches, and species-aware parent selection that trades off within-niche exploitation and cross-niche exploration. Preliminary results show \textit{ToxSearch-S} reaching higher peak toxicity ($\approx 0.73$ vs.\ $\approx 0.47$) with a heavier tail (top-10 median $0.66$ vs.\ $0.45$) than the baseline. Speciation also yields broader semantic coverage under a topics-as-species analysis (higher effective topic diversity and larger unique topic coverage). Finally, species formed are well-separated in embedding space (mean separation ratio $\approx 1.93$) and exhibit distinct toxicity distributions, indicating that speciation partitions the adversarial space into behaviorally differentiated niches rather than superficial lexical variants.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Energy-Aware Metaheuristics
arXiv:2602.06595v4 Announce Type: replace Abstract: This paper presents a principled framework for designing energy-aware metaheuristics that operate under fixed energy budgets. We introduce a unified operator-level model that quantifies both numerical gain and energy usage, and define a robust Expected Improvement per Joule (EI/J) score that guides adaptive selection among operator variants during the search. The resulting energy-aware solvers dynamically choose between operators to self-control exploration and exploitation, aiming to maximize fitness gain under limited energy. We instantiate this framework with three representative metaheuristics - steady-state GA, PSO, and ILS - each equipped with both lightweight and heavy operator variants. Experiments on three heterogeneous combinatorial problems (Knapsack, NK-landscapes, and Error-Correcting Codes) show that the energy-aware variants consistently reach comparable fitness while requiring substantially less energy than their non-energy-aware baselines. EI/J values stabilize early and yield clear operator-selection patterns, with each solver reliably self-identifying the most improvement-per-Joule - efficient operator across problems.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Benchmarking Swarm Optimization Algorithms for Parameter Initialization in the Quantum Approximate Optimization Algorithm
arXiv:2506.06790v3 Announce Type: replace-cross Abstract: The Quantum Approximate Optimization Algorithm (QAOA) is a prominent variational algorithm for solving combinatorial optimization problems such as the Max Cut problem. A key challenge in QAOA is the efficient identification of variational parameters ({\gamma}, \{beta}) that yield high-quality solutions. In this work, we investigate swarm optimization methods as robust strategies for exploring the QAOA parameter space. We evaluate Particle Swarm Optimization (PSO), Fully Informed Particle Swarm Optimization (FIPSO), Quantum Particle Swarm Optimization (QPSO), and an Adam-assisted FIPSO variant on weighted MaxCut instances across multiple system sizes, circuit depths, and noise regimes, including shot noise. Our results show that these methods achieve lower approximation gaps and more stable convergence compared to standard optimizers such as Adam, COBYLA, and SPSA. In particular, we observe that swarm methods maintain superior performance under noisy and shot limited conditions. These findings suggest that population based search is effective for navigating the complex QAOA landscape and is a promising approach for parameter optimization in near-term quantum algorithms.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Symbolic Quantile Regression for the Interpretable Prediction of Conditional Quantiles
arXiv:2508.08080v2 Announce Type: replace-cross Abstract: Symbolic Regression (SR) is a well-established framework for generating interpretable or white-box predictive models. Although SR has been successfully applied to create interpretable estimates of the average of the outcome, it is currently not well understood how it can be used to estimate the relationship between variables at other points in the distribution of the target variable. Such estimates of e.g. the median or an extreme value provide a fuller picture of how predictive variables affect the outcome and are necessary in high-stakes, safety-critical application domains. This study introduces Symbolic Quantile Regression (SQR), an approach to predict conditional quantiles with SR. In an extensive evaluation, we find that SQR outperforms transparent models and performs comparably to a strong black-box baseline without compromising transparency. We also show how SQR can be used to explain differences in the target distribution by comparing models that predict extreme and central outcomes in an airline fuel usage case study. We conclude that SQR is suitable for predicting conditional quantiles and understanding interesting feature influences at varying quantiles.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Optimized Architectures for Kolmogorov-Arnold Networks
arXiv:2512.12448v2 Announce Type: replace-cross Abstract: Efforts to improve Kolmogorov--Arnold networks (KANs) with architectural enhancements have been stymied by the complexity those enhancements bring, undermining the interpretability that makes KANs attractive in the first place. Here we study overprovisioned architectures combined with sparsification, deep supervision, and depth selection, to learn compact, interpretable KANs without sacrificing accuracy. Crucially, we focus on differentiable mechanisms under a principled minimum description length objective, jointly optimizing activations, structure, and depth end-to-end. Experiments across function approximation benchmarks, dynamical systems forecasting, and real-world prediction tasks demonstrate that sparsification alone is insufficient, but the combination with depth selection achieves competitive or superior accuracy while discovering substantially smaller models. The result is a principled path toward models that are both more expressive and more interpretable, addressing a key tension in scientific machine learning.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware
arXiv:2601.16118v2 Announce Type: replace-cross Abstract: Executing Spiking Neural Networks (SNNs) on neuromorphic hardware poses the problem of mapping neurons to cores. SNNs operate by propagating spikes between neurons that form a graph through synapses. Neuromorphic hardware mimics them through a network-on-chip, transmitting spikes, and a mesh of cores, each managing several neurons. Its operational cost is tied to spike movement and active cores. A mapping comprises two tasks: partitioning the SNN's graph to fit inside cores and placement of each partition on the hardware mesh. Both are NP-hard problems, and as SNNs and hardware scale towards billions of neurons, they become increasingly difficult to tackle effectively. In this work, we propose to raise the abstraction of SNNs from graphs to hypergraphs, redesigning mapping techniques accordingly. The resulting model faithfully captures the replication of spikes inside cores by exposing the notion of hyperedge co-membership between neurons. We further show that the overlap and locality of hyperedges strongly correlate with high-quality mappings, making these properties instrumental in devising mapping algorithms. By exploiting them directly, grouping neurons through shared hyperedges, communication traffic and hardware resource usage can be reduced be yond what just contracting individual connections attains. To substantiate this insight, we consider several partitioning and placement algorithms, some newly devised, others adapted from literature, and compare them over progressively larger and bio-plausible SNNs. Our results show that hypergraph based techniques can achieve better mappings than the state-of-the-art at several execution time regimes. Based on these observations, we identify a promising selection of algorithms to achieve effective mappings at any scale.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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An Imbalanced Dataset with Multiple Feature Representations for Studying Quality Control of Next-Generation Sequencing
arXiv:2604.04981v2 Announce Type: replace-cross Abstract: Next-generation sequencing (NGS) is a key technique for studying the DNA and RNA of organisms. However, identifying quality problems in NGS data across different experimental settings remains challenging. To develop automated quality-control tools, researchers require datasets with features that capture the characteristics of quality problems. Existing NGS repositories, however, offer only a limited number of quality-related features. To address this gap, we propose a dataset derived from 37,491 NGS samples with two types of quality-related feature representations. The first type consists of 34 features derived from quality control tools (QC-34 features). The second type has a variable number of features ranging from eight to 1,183. These features were derived from read counts in problematic genomic regions identified by the ENCODE blocklist (BL features). All features describe the same human and mouse samples from five genomic assays, allowing direct comparison of feature representations. The proposed dataset includes a binary quality label, derived from automated quality control and domain experts. Among all samples, $3.2\%$ are of low quality. Supervised machine learning algorithms accurately predicted quality labels from the features, confirming the relevance of the provided feature representations. The proposed feature representations enable researchers to study how different feature types (QC-34 vs. BL features) and granularities (varying number of BL features) affect the detection of quality problems.in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-22 04:00:00 UTC.
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Youth Labour Market Participation in Africa: A Cross-National Analysis of Employment, Unemployment, Sectoral Distribution, and Educational Attainment Among the 15–35 Age Cohort, 2026 [version 1; peer review: awaiting peer review]
Background Africa hosts the world’s largest youth cohort, yet its labour markets remain characterised by structural imbalances, agricultural dependence, gender inequalities, and educational credential mismatches. This study provides a comprehensive, cross-national analysis of youth labour market participation across all 53 African Union member states in 2026, disaggregated by sex, age group, economic sector, and educational attainment. Methods A cross-sectional descriptive-correlational analysis was conducted using International Labour Organisation (ILO) harmonised modelled estimates for the 15–35 age cohort. Youth unemployment rates (YUR), labour force participation rates (LFPR), and notinemployment,educationortraining (NEET) rates were computed by country, sub-region, sex, age group, and education level. Pearson’s correlation coefficient tested the association between YUR and NEET rate at country level. Results Of 545.1 million African youth aged 15–35, 311.5 million (57.1%) were employed, 23.1 million (4.2%) unemployed, 81.7 million (15.0%) inactive, and 128.8 million (23.6%) in education. The continental YUR was 6.91%; North Africa recorded 11.09% versus 6.40% in sub-Saharan Africa. Country-level YUR ranged from 0.4% (Niger) to 37.4% (Eswatini). The NEET rate reached 19.23% (104.8 million youth). Agriculture dominated employment (45.9%). Female YUR(7.56%) exceeded male YUR(6.40%). Upper secondary and tertiary graduates accounted for 52.7% of unemployment. A strong positive correlation existed between YUR and NEET rate (r = 0.720, p = < 0.001). Conclusions African youth labour markets exhibit pronounced heterogeneity, structural informality, and credential–employment mismatches. Targeted policies addressing structural transformation, skills alignment, gender equity, and social protection are urgently required.in F1000Research on 2026-04-22 03:50:51 UTC.
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Measuring Professional Competency in School Counselors: Development and Rasch Validation of a Multidimensional Instrument [version 1; peer review: awaiting peer review]
Background The measurement of professional competency in school counseling remains methodologically constrained by fragmented domain assessment and heavy reliance on classical test theory approaches. There is a critical need for an empirically calibrated instrument that integrates regulatory competency standards with expanded theoretical domains while ensuring measurement precision and structural coherence. This study developed and validated a multidimensional instrument of professional competency for school counselors using Rasch analysis. Methods A cross-sectional instrumental design was implemented. The instrument was constructed across seven domains: assessment, development of guidance and counseling program, implementation of guidance and counseling services, evaluation of guidance and counseling program, supervision of pre-service counselor training, continuous professional development, and collaborative engagement in co-curricular programs. Seventy-one items were rated on a five-point Likert scale. Data from 93 practicing school counselors were analyzed using the Rasch Rating Scale Model. Analyses included the evaluation of category functioning, item and person fit statistics, reliability and separation indices, and principal component analysis of residuals (PCAR) to assess construct dimensionality. Results The Rasch model demonstrated acceptable item fit and ordered rating scale thresholds. The raw variance explained by measures was 53.4%, with 6.7% unexplained variance in the first contrast, indicating a dominant latent construct despite the multidomain theoretical structure. Item difficulty estimates ranged from −1.68 to +1.71 logits, forming a hierarchical continuum from foundational service practices to advanced supervisory and professional roles. Reliability and separation indices indicated stable item calibration and adequate differentiation among levels of professional competency. Conclusions The findings support the structural validity, hierarchical calibration, and measurement precision of the instrument within a unified Rasch framework. The instrument provides a methodologically robust basis for professional assessment, supervision, and competency-based development in school counseling contexts, with significant potential for further validation across diverse educational systems.in F1000Research on 2026-04-22 03:40:40 UTC.
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Transcription factor cooperativity at a GATA3 tandem DNA sequence determines oncogenic enhancer-mediated activation
(Cell Reports 44, 115705; May 27, 2025)in Cell Reports: Current Issue on 2026-04-22 00:00:00 UTC.
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Zinc-redox crosstalk regulates proteostasis in the endoplasmic reticulum
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-72250-w
This study demonstrates a close interplay between zinc and redox homeostasis in the ER. Aberrant zinc elevation disrupts ERp44-mediated protein quality control and impairs oxidative folding of key membrane receptors, including EGFR and Notch.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Engineered local polarization disorder unlocks record efficiency in antiferroelectric capacitors
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-72274-2
The authors introduce controlled compositional heterogeneity to broaden polarization vector distributions while preserving the antiferroelectric modulation in PbZrO3-based ceramics. They reduce polarization hysteresis while maintaining high polarization strength.in Nature Communications on 2026-04-22 00:00:00 UTC.
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S-atom dislocation-induced room-temperature ferroelectricity in two-dimensional α-MnS semiconductor
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-71802-4
A room-temperature ferroelectricity with out-of-plane polarization is disclosed in chemical vapor deposition synthesized two-dimensional α-MnS, which exhibits large tunneling electroresistance, high endurance, and long retention time.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Ambient-compatible precursor engineering for efficient perovskite photovoltaics
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-72159-4
Perovskite solar cells face efficiency losses in ambient air because their precursors are highly moisture- and oxygen-sensitive. Liu et al. use an ionic-liquid additive to stabilize precursor chemistry, enabling robust processing and high-performance devices.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Released palmitic acid–mediated TLR4/NF-κB activation enhances the virulence of Bordetella pertussis MT28 lineage
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-72213-1
A macrolide resistant Bordetella pertussis lineage (MT28) carrying a high-virulence allele (ptxP3) has been reported as a predominant lineage in China. Here, the authors show that MT28 has enhanced colonization and inflammatory characteristics.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Symbiotic phosphate transporter dynamics in rice expose functional plasticity of the arbuscules
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-71496-8
This study uncovers the previously-hidden dynamics of nutrient exchange structures central to the symbiosis between plants and arbuscular mycorrhizal fungi, revealing highly variable development, lifespans and phosphate transport capacities.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Loss of DNA methyltransferase 3a enhances Caspase-8 transcription and promotes cardiomyocyte pyroptosis during myocardial infarction
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-71941-8
Caspase-8 plays a key role in initiating pyroptosis, but its contribution to myocardial infarction has remained unclear. Here, the authors show that ischemia-induced degradation of Dnmt3a leads to demethylation and upregulation of Caspase-8, amplifying Gsdmd cleavage and driving cardiomyocyte death.in Nature Communications on 2026-04-22 00:00:00 UTC.
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Host insulin hijacking by a nematode receptor mediates developmental plasticity and sex ratio shifts
Nature Communications, Published online: 22 April 2026; doi:10.1038/s41467-026-72333-8
The barber’s pole worm, a blood-feeding nematode, exploits host insulin via their IGFR/DAF-2 receptor to drive infection, reproduction, and female-biased development, revealing a target for controlling transmission.in Nature Communications on 2026-04-22 00:00:00 UTC.
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A Virtual Reality Dataset to Support Hand Action Observation in Rehabilitation and Motor Learning Studies
Scientific Data, Published online: 22 April 2026; doi:10.1038/s41597-026-07252-w
A Virtual Reality Dataset to Support Hand Action Observation in Rehabilitation and Motor Learning Studiesin Nature scientific data on 2026-04-22 00:00:00 UTC.
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Comparative analysis of milk and brain fatty acids reveals human-specific signatures in brain development
Communications Biology, Published online: 22 April 2026; doi:10.1038/s42003-025-09401-0
Comparative lipidomics of milk and brain across mammals reveals conserved and human-specific fatty acid signatures that link early nutrition to neurodevelopment.in Nature communications biology on 2026-04-22 00:00:00 UTC.
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Chromosome fusion enhances dependency on Rif1 for entanglement resolution during meiosis in S. pombe
Communications Biology, Published online: 22 April 2026; doi:10.1038/s42003-026-10093-3
Chromosome fusion in fission yeast increases meiotic DNA entanglements and heightens dependence on mechanisms that promote their resolution, highlighting potential cellular adaptations to karyotype change.in Nature communications biology on 2026-04-22 00:00:00 UTC.
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Cell-type-aware transcriptome-wide association studies identify 91 independent risk genes for Alzheimer’s disease dementia
Communications Biology, Published online: 22 April 2026; doi:10.1038/s42003-026-10030-4
Cell-type-aware TWAS of Alzheimer’s disease dementia identifies 91 independent risk genes across six brain cell types, with proteomic support and network links connecting novel candidates to well-established AD genes.in Nature communications biology on 2026-04-22 00:00:00 UTC.
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Insights into unique anatomical structures of the ascidian Halocynthia papillosa obtained by multimodal imaging
Communications Biology, Published online: 22 April 2026; doi:10.1038/s42003-026-10102-5
Multimodal imaging of Halocynthia papillosa reveals features of the central nervous system, oral tentacles, and tunic structure. The findings highlight the value of advanced imaging for studying functional anatomy in non-model marine invertebrates.in Nature communications biology on 2026-04-22 00:00:00 UTC.
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Colony demographics shape nest construction in Camponotus fellah ants
The ant nest serves as the skeleton of the ant superorganism. Similar to a skeleton, the nest expands as the colony grows and requires repair after catastrophic events. We experimentally compared nest excavation in colonies seeded from a single mated queen and allowed to grow for 6 months to excavation triggered by a catastrophic event in colonies with fixed demographics, where the age of each worker, including the queen, is known. The areas excavated by equal group sizes differed significantly between these conditions: heterogeneous populations in naturally growing colonies as well as cohorts of young ants dig larger areas than old ant cohorts. Moreover, we find that younger ants tend to dig slanted tunnels while older ants dig straight down. This is a novel form of age polyethism, where an ant’s age dictates not only her likelihood to engage in a task but also the way she performs the task. We further present a quantitative model that predicts that under normal growth, digging is predominantly performed by the younger ants, while after a catastrophe, all ants dig to restore lost nest volume. The fact that the nests of naturally growing colonies exhibit slanted tunnels strengthens this prediction. Finally, our results indicate how a colony’s demographic and physical history are sketched into the current structure of its nest.in eLife on 2026-04-22 00:00:00 UTC.
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A quantitative in vivo CRISPR-imaging platform identifies regulators of hyperplastic and hypertrophic adipose morphology in zebrafish
Adipose tissues exhibit a remarkable capacity to expand, regress, and remodel in response to energy status. The cellular mechanisms underlying adipose remodelling are central to metabolic health. Hypertrophic remodelling – characterised by the enlargement of existing adipocytes – is associated with insulin resistance, type 2 diabetes, and cardiovascular disease. In contrast, hyperplastic remodelling – in which new adipocytes are generated – is linked to improved metabolic outcomes. Despite its clinical importance, the regulation of hypertrophic and hyperplastic adipose morphology remains poorly understood. Here, we integrate human transcriptomic data with a quantitative CRISPR-imaging platform in zebrafish to identify regulators of adipose morphology. We developed an image-based phenotyping pipeline that captures lipid droplet size, number, and spatial patterning, and applied generalised additive modelling to quantify hyperplastic versus hypertrophic morphology signatures. Using this platform, we conducted an F0 CRISPR screen targeting 25 candidate genes and identified three that induced hypertrophic morphology (txnipa, mmp14b, and foxp1b) and an additional candidate that altered total adiposity (kazna). For functional validation, we generated stable loss-of-function alleles for both zebrafish foxp1 paralogues. Spatial analysis along the anterior-posterior axis revealed that foxp1b mutants display developmental hypertrophy but profoundly blunted adaptive responses to high-fat diet (~68% reduction across all spatial zones), while foxp1a mutants show normal baseline morphology but disrupted spatial patterning of diet-induced hypertrophy. Together, these findings establish a scalable CRISPR-imaging platform for in vivo genetic screening of adipose morphology and reveal distinct roles for Foxp1 paralogues in developmental patterning and adaptive responses to dietary challenge in adipose tissue.in eLife on 2026-04-22 00:00:00 UTC.
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Domain-general demands that deactivate multiple-demand regions
AbstractActivation of multiple-demand regions during diverse difficult tasks has led to the recognition of domain-general demands that arise during any difficult task. Our tasks, however, are temporally structured episodes made of multiple components that are controlled as a single unit toward an overarching goal. Their numerous component control processes are organized through a goal-directed program instated at the episode’s onset. Difficult task episodes that require complex control processes also require a complex program to organize and coordinate them over time. Across four different fMRI experiments with different task designs and contents, we found that instituting these programs at the beginning of extended episodes involves a categorically different domain-general demand from that needed during their subsequent execution. This demand deactivated widespread regions, including the very same multiple-demand regions that activate during the execution of difficult tasks. The distinction between the demands related to program instatement versus those related to control during execution extended to psychophysiological signatures. In a fifth experiment, pupil diameter—typically increasing with control processes—decreased when more demanding programs were being instated. Instating overarching programs at the beginning of extended tasks thus constitutes a unique cognitive demand, distinct from the control processes engaged during task performance.in Cerebral Cortex on 2026-04-22 00:00:00 UTC.
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BOLD response delays represent local cortical processing
AbstractA number of studies showed that stimulus or task conditions can alter the shape of the hemodynamic response (HR). Contrary to variations across brains and brain regions, vascular factors alone cannot account for within-voxel HR waveform variations. Instead, different neuron types may contribute differently to shaping the HR, suggesting that beyond detecting neural activations, measurements of stimulus- or task-specific HRs could inform on the nature of underlying neural processes. To assess this hypothesis, we measured HR apparent delays to oriented visual stimuli with 1 mm and 1-s resolution Blood Oxygenation Level Dependent (BOLD) functional MRI (fMRI) in healthy humans. As expected, decoding V1 patterns of HR amplitudes allowed robust cross-validated predictions of stimulus conditions, ie two orthogonal gratings and an overlay of the two. More interestingly, this was also true using patterns of HR delays alone, and predictions using both delay and amplitude information outperformed those using amplitude alone. Finally, while all stimuli evoked similar V1-averaged HR amplitudes, the overlay stimulus’ HR waveform lagged ~180 ms behind that of grating stimuli. We interpret this increased HR delay as reflecting different neural computations, here more cross-orientation suppression with overlay stimuli, and conclude that neurally relevant information can be obtained from the HR waveform in addition to its commonly used amplitude.in Cerebral Cortex on 2026-04-22 00:00:00 UTC.
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Effects of sensorimotor delays and muscle force capacity limits on the performance of feedforward and feedback control in animals of different sizes
by Sayed Naseel Mohamed Thangal, Heather L. More, C. David Remy, J. Maxwell Donelan
Animals rely on feedforward and feedback control for perturbation responses. When comparing terrestrial mammals of different sizes, we generally find that several features that affect perturbation responses change—larger animals have longer sensorimotor time delays, heavier body segments, and proportionally weaker muscles. We used simple computational models to study how control of fast perturbation responses is constrained by two limitations—sensorimotor delays and muscle force capacity—as a function of animal size. We developed two tasks representing common perturbation response scenarios in animal locomotion: a distributed mass pendulum approximating swing limb repositioning (swing task), and an inverted pendulum approximating whole body posture recovery (posture task). First, we used a normalized feedback control system to show how feedback response times can either be limited by the force generation capacity of muscles (force-limited), or by sensorimotor delays which constrain the maximum feedback gains that can be used to produce stable responses (delay-limited). Next, we used more detailed scaled models which represent the full size range of terrestrial mammals and parameterized the sensorimotor delays, maximum muscle forces, and inertial properties using scaling relationships from literature. Across animal size and in both tasks, we found that feedback control was primarily delay-limited—the fastest responses used a fraction of the available muscle force capacity. We compared feedback control to the fastest feedforward control strategy, and found that feedforward control response times were about four times faster than feedback control in the smallest animals, and around two times faster in the largest animals. For rapid perturbation responses, feedback control appears ineffective for terrestrial mammals of all sizes, as our simulated fastest response times exceeded available movement times. Thus, feedforward control strategies—including anticipatory adjustments, ballistic motor programs, and exploitation of intrinsic musculoskeletal dynamics—may be essential for reacting quickly to sudden and large perturbations in terrestrial mammals.in PLoS Computational Biology on 2026-04-21 14:00:00 UTC.
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The selfish ribosome
by Mart Krupovic, Eugene V. Koonin
The ribosome is responsible for protein synthesis in all cells, and is the cell’s largest energy consumer. We propose that the ribosome originated as a mutualistic symbiont of an RNA-dependent RNA polymerase ribozyme, supplying peptides that enhanced replication. As life transitioned from the RNA to the RNA–protein world, autonomous replicators became irreversibly addicted to the ribosome for producing replication proteins. Subsequent evolution is construed as a ribosomal takeover, whereby the ribosome evolved to consume most of the cell’s resources, while other cellular componentry ensured the propagation of the ribosome, while being fully dependent on it. Under this perspective, the ribosome is a complex symbiont of the cell with pronounced selfish properties.in PLoS Biology on 2026-04-21 14:00:00 UTC.
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Genomic and functional adaptations in the guanylate-binding protein 5 highlight specificities of bat antiviral innate immunity
by Amandine Le Corf, Sarah Maesen, Amandine Chantharath, Clara Loyer, Juan Manuel Vazquez, M. Elise Lauterbur, Veronika Krchlikova, Lucas Sareoua, Genavieve Gray-Sandoval, Andrea Cimarelli, Carine Rey, Peter H. Sudmant, David Enard, Lucie Etienne
Bats are asymptomatic reservoirs of several zoonotic viruses. This may result from long-term co-evolution between viruses and bats, that have led to host adaptations contributing to an effective balance between strong antiviral responses with innate immune tolerance. To better understand these virus-host interactions, we combined comparative transcriptomics, phylogenomics and functional assays to characterize the evolution of bat innate immune antiviral factors. First, we stimulated the type I interferon immune pathway in Myotis yumanensis primary cells and identified guanylate-binding protein 5 (GBP5) as the most differentially expressed interferon-stimulated gene (ISG). Phylogenomic analyses showed that bat GBP5 has been under strong episodic positive selection, with numerous rapidly evolving sites and species-specific gene duplications, suggesting past evolutionary arms races. Functional tests on GBP5 orthologs from 10 bat species covering the >60 million years of Chiroptera evolution revealed species- and virus-specific restrictions against RNA viruses (retrovirus HIV, and rhabdoviruses European bat lyssavirus and VSV), which are typical signatures of adaptations to past viral epidemics. Interestingly, we also observed a lineage-specific loss of the GBP5 prenylation motif in the common ancestor of Pipistrellus and Eptesicus bats. Importantly, resurrection of the prenylation motif in Eptesicus fuscus GBP5 in corresponding bat cells was associated with different GBP5 subcellular localization and loss of anti-rhabdoviral functions, suggesting specific adaptation to ancient viral epidemics ~22 million years ago. Altogether, our results highlight adaptations that contribute to bat specific immunity and provide insights into the functional evolution of antiviral effector GBP5.in PLoS Biology on 2026-04-21 14:00:00 UTC.
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The Basal Ganglia Upside Down: Non-Canonical Direct and Indirect Pathways Emerging from Striosomes Modulate Dopamine Release and Motor Behavior
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-21 12:39:55 UTC.
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Revisiting the explicit-implicit additivity assumption in visuomotor adaptation
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-21 12:20:20 UTC.
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Partnering With Participant Advisors on the Parkinson's Progression Markers Initiative
Partnership with participants on study protocols and conduct informs study design, provides novel insights, and speeds enrollment and outcomes. The Parkinson's Progression Markers Initiative (PPMI) solicits volunteer inputs through a Community Advisory Board, in-person events, and communication with site teams and centralized study services. Participant inputs have shaped PPMI procedures and protocols including (i) the myPPMI online platform, (ii) return of research information, (iii) lumbar puncture education, (iv) engaging representative populations, and (v) travel procedures. The study's methods for engaging participants and its modifications arising from those conversations provide a model for those seeking to design accessible and impactful studies. ANN NEUROL 2026
in Annals of Neurology on 2026-04-21 12:01:44 UTC.
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Dopaminergic modulation of low- and high spontaneous rate-type I auditory nerve fiber activity
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-21 11:40:13 UTC.
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Traditional Remedy Sagwa as a Risk Factor for Severe Morbidity and Mortality in Iraqi Infants with Acute Diarrhea. A Case–Control Study [version 2; peer review: 1 approved with reservations]
Background Using herbal medicine and supplements in treatment of pediatric diarrhea is used by around 80% of people worldwide. Sagwa is popularly used mainly in rural areas in Iraq. Potential toxicity may include neurotoxic, hepatotoxic, nephrotoxic and cardiotoxic effects. Its potential toxicity includes neurotoxic, hepatotoxic, nephrotoxic, and cardiotoxic effects. Aim This study was carried out to determine the morbidity and mortality linked to Sagwa use in acute gastroenteritis in infants with contributing factors. Patients and Methods A prospective case-control study in Al-Fallujah, Iraq from July 1st, 2022, to Jan 1st, 2023. Infants with acute diarrhea were enrolled and classified based on Sagwa exposure status (exposed vs non-exposed). The cases were infants who had received Sagwa prior to hospital presentation, while controls were age- and sex-matched without Sagwa exposure. The data of patients included: the number of times of having Sagwa, the duration between exposure and hospital admission, duration of hospital stay, the grandmother responsibility, the severity of dehydration, the presence of renal failure, the need for dialysis, convulsion, coma and death. Results The study included 50 cases and 50 controls. No significant differences in age and sex were observed but there was a significant association with rural residence, not educated mothers, grandma responsibility, severe dehydration, convulsions, and death. No significant differences were observed considering renal failure, dialysis and coma. Combining oral and scalp administration was significantly associated with convulsions and renal failure. Conclusion Sagwa use in infants with diarrhea associated with increased morbidity and mortality. Public health interventions targeting caregivers are essential to reduce this preventable risk.in F1000Research on 2026-04-21 11:31:28 UTC.
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Enterprise Architecture in Higher Education for Digital Transformation: An Integrative Review for Fragile Contexts with Application to Yemen [version 2; peer review: 1 approved with reservations]
Background Enterprise Architecture (EA) is a crucial facilitator for the digital transformation of organizations; however, its implementation in the higher education sector of fragile states is still insufficiently studied. This gap makes it harder for policymakers and higher education leaders in countries like Yemen to carry out structured, sector-wide modernization. Methods This study utilizes a systematic integrative review methodology, adhering to PRISMA principles. We synthesized and analyzed 30 peer-reviewed articles and high-credibility reports published between 2010 and June 2025 to identify transferable EA frameworks, governance models, and implementation strategies pertinent to resource-constrained contexts in higher education. Results Our analysis confirms that the TOGAF framework is the most widely used, but it also indicates that successful public sector implementations depend on hybrid adaptations and federated governance models to attain a balance between central policy and institutional autonomy. The most important things that lead to success are strong executive sponsorship and a phased, pilot-led implementation. The primary problems are lack of resources and resistance from within the organization. The results also show a clear link between EA outcomes, such as improved efficiency and resilience, and the main goals of the Sustainable Development Goals (SDGs). Conclusions This review expands EA theory into the inadequately explored area of public administration in fragile contexts. In practice, it provides Yemen with a new, evidence-based, phased implementation pathway. This pathway affords higher education sector leaders a real policy and management tool to help them build strong and useful digital ecosystems in tough places.in F1000Research on 2026-04-21 10:40:37 UTC.
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Climate Change Impacts on Soil Erosion in a Tropical Watershed: Insights from SINGV Regional Climate Modelling and RUSLE [version 1; peer review: awaiting peer review]
Abstract* Background Soil erosion is a major environmental challenge in tropical watersheds, where intense rainfall, complex topography, and land-use dynamics accelerate land degradation. Climate change is expected to intensify these processes by altering precipitation patterns and increasing rainfall erosivity. Methods This study assesses the impact of climate change on soil erosion in the Biyonga sub-watershed, Indonesia, by integrating bias-corrected regional climate model projections with the Revised Universal Soil Loss Equation (RUSLE). Climate model performance was evaluated against observed rainfall data, and corrected precipitation was used to estimate baseline and future erosion under SSP245 and SSP585 scenarios. Results The results indicate an increase in soil erosion of approximately 6.12–8.83 t ha−1 yr−1 under future climate scenarios. Mean erosion rates are projected to reach 46.33–49.03 t ha−1 yr−1, with higher values under SSP585. Steep upstream areas emerge as dominant erosion hotspots, strongly influenced by high slope length and steepness (LS) factors. Moderate erosion (Class II) remains the dominant category, covering about 54–56% of the watershed, while more than half of the area shows increasing erosion trends. Conclusions Climate change is projected to amplify existing erosion patterns rather than fundamentally alter their spatial distribution. Integrating climate projections with spatial erosion modelling provides valuable insights for identifying vulnerable areas and supports adaptive watershed management in tropical environments.in F1000Research on 2026-04-21 07:21:14 UTC.
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Cell-type-resolved transcriptomic landscape of human focal cortical dysplasia
Proceedings of the National Academy of Sciences, Volume 123, Issue 17, April 2026.
SignificanceFocal cortical dysplasia (FCD) is a major cause of drug-resistant epilepsy, yet its biological heterogeneity remains poorly defined. We profiled 487,286 nuclei from paired lesional and perilesional cortices across FCD I-III to generate a cell-...in PNAS on 2026-04-21 07:00:00 UTC.
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Flexible integration of natural stimuli by auditory cortical neurons
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-21 05:22:22 UTC.
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Impact of tongue exercise on hypoglossal axis survival, structure, and output in a rodent model of hypoglossal motor neuron degeneration
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-21 02:50:16 UTC.
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Genome-wide analysis reveals ligand-dependent allostery in RARα:RXR-mediated transcriptional regulation
This study uncovers the genome-wide consequences of allostery within the nuclear hormone receptor family. Using receptor-specific agonists of the RARα:RXR heterodimer, distinct DNA-binding profiles and gene expression patterns are identified. Additionally, distinct doubly liganded receptors activate unique gene networks, demonstrating how ligand identity directs genome-wide regulatory outcomes.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Requirements for development of T helper 1 and T follicular helper cells from a common precursor
CD4+ T cells coordinate cellular and humoral immunity by differentiating into T helper 1 and T follicular helper cells. By tracing polyclonal CD4+ T cells in vivo, Bosma et al. identify a common Th1/Tfh precursor with a hybrid gene program that gives rise to both lineages in response to distinct cellular interactions.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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SIRT6-mediated immunometabolic reprogramming of macrophages drives neutrophilic asthma via LDHA-dependent glycolysis
Su et al. show that SIRT6 deacetylates LDHA at K261 to drive glycolysis and lactate production in macrophages. Lactate subsequently induces H4K12 lactylation, upregulating Cxcl1/2 transcription and promoting neutrophil infiltration. Genetic and pharmacological SIRT6 inhibition suppress neutrophilic airway inflammation, highlighting SIRT6 as a therapeutic target for neutrophilic asthma.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Increased yolk lipid mobilization promotes zebrafish post-segmentation growth via an Hnf4-lipoprotein axis
Sun et al. quantify yolk protein and lipid mobilization during early zebrafish development. Protein catabolism begins early, whereas lipid delivery increases during post-segmentation growth. Zygotic hnf4a/b induction in the yolk syncytial layer is associated with activation of a late lipid-utilization program, and disrupting this program compromises normal growth.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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TgSEC14-LTP1 is a vacuole-secreted SEC14/CRAL-TRIO-like protein required for host DAG flux and PC homeostasis in T. gondii
Cruz-Miron et al. identify TgSEC14-LTP1, a SEC14/CRAL-TRIO-like protein in the parasitophorous vacuole lumen with a hydrophobic-lipid-binding cavity. Conditional depletion reveals its essential role in parasite growth by regulating host-to-parasite diacylglycerol and phosphatidylcholine flux and maintaining lipid homeostasis, leading to reduced parasite size, defective cytokinesis, and delayed egress.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Extensive individual and microorganism-specific circadian oscillations of the upper respiratory tract microbiome
Sun et al. demonstrate that the upper respiratory tract microbiome exhibits extensive circadian oscillations linked to host identity and microbial traits. They reveal how these temporal dynamics drive false positives in microbiome analyses and provide practical sampling strategies to improve the accuracy and reproducibility of human microbiome research.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Vip+ vagal neurons control allergen-induced responses
Zhu et al. show that Vip+ vagal sensory neurons control allergen-induced airway hyperreactivity and type 2 inflammation. NGFR signaling is required for Vip+-mediated airway hyperreactivity. Vip+ neurons relay peripheral allergen signals to the brainstem, defining a lung-brain neuroimmune circuit that contributes to asthma pathogenesis.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Midbrain endocannabinoids actuate dopamine-based action selection
Dopamine signals guide adaptive responses to reward- and threat-predictive cues, yet the mechanisms shaping these rapid dynamics remain unclear. Luján et al. identify midbrain endocannabinoid signaling onto pallidal inputs as a temporally precise disinhibitory mechanism that enables striatal dopamine release to support adaptive action selection in response to salient cues.in Cell Reports: Current Issue on 2026-04-21 00:00:00 UTC.
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Yellow glass shows insect wings at their best
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-00915-z
An experiment to preserve the vivid colour of insect wings in displays and a disagreement about peer review in technology, in our weekly dip into Nature’s archive.in Nature on 2026-04-21 00:00:00 UTC.
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AI doom warnings are getting louder. Are they realistic?
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01257-6
Researchers are increasingly sounding the alarm that artificial intelligence could end humanity. But such doomsday warnings carry their own risks.in Nature on 2026-04-21 00:00:00 UTC.
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Personalized CRISPR therapies could soon reach thousands — here’s how
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01243-y
A fresh approach to trialling treatments for rare genetic diseases could make their production an economically viable prospect at last.in Nature on 2026-04-21 00:00:00 UTC.
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Triple-decker solar cells reach efficiency milestone
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01149-9
A promising solar-cell architecture, in which two layers of perovskite semiconductors are stacked on silicon, is making strides towards achieving its full potential.in Nature on 2026-04-21 00:00:00 UTC.
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US speeds research into mind-altering drugs — including mysterious ‘ibogaine’
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01286-1
Some researchers are delighted at an executive order to streamline investigations of psychedelics but also warn that caution is needed.in Nature on 2026-04-21 00:00:00 UTC.
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Forty years after Chornobyl, more nuclear disasters are inevitable — plan for them
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01255-8
Civil nuclear technology comes with unlikely but dangerous risks that shouldn’t be overlooked.in Nature on 2026-04-21 00:00:00 UTC.
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Vaccines mean malaria deaths should be falling — not rising
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01253-w
The tools exist to end this killer disease. It is the money and the will that are lacking.in Nature on 2026-04-21 00:00:00 UTC.
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How big is Big G? Mystery deepens after ten-year effort to measure gravity’s strength
Nature, Published online: 21 April 2026; doi:10.1038/d41586-026-01284-3
Physicists have spent the past decade trying to pin down the elusive fundamental constant, to no avail.in Nature on 2026-04-21 00:00:00 UTC.
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Genomic approaches for understanding the evolution of the human brain
Nature Neuroscience, Published online: 21 April 2026; doi:10.1038/s41593-026-02277-1
This Review describes how an approach that starts from genetic changes under selection during human evolution and integrates comparative and functional studies can reveal adaptive phenotypes across different evolutionary timescales.in Nature Neuroscience on 2026-04-21 00:00:00 UTC.
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Constituent-constrained word prediction during language comprehension
Nature Neuroscience, Published online: 21 April 2026; doi:10.1038/s41593-026-02272-6
Zou et al. reveal a key difference between human brains and large language models (LLMs). While LLMs are optimized to predict the next word, the human brain modulates prediction efficiency by strategically grouping words into phrases.in Nature Neuroscience on 2026-04-21 00:00:00 UTC.
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Incoherent dielectric tensor tomography for quantitative three-dimensional measurement of biaxial anisotropy
Nature Photonics, Published online: 21 April 2026; doi:10.1038/s41566-026-01897-0
The internal structure of biological samples and polycrystalline materials is visualized using incoherent dielectric tensor tomography. Through angular and polarization modulation, the method detects submicrometre optical anisotropic features—such as biaxial symmetry—that are not accessible with the coherent counterpart.in Nature Photomics on 2026-04-21 00:00:00 UTC.
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Multifactor authentication in extracellular vesicle analysis: methods and approaches to address the heterogeneity problem
Nature Methods, Published online: 21 April 2026; doi:10.1038/s41592-026-03068-z
This Perspective introduces the concept of multifactor authentication for extracellular vesicle (EV) analysis as an effective tool to resolve the heterogeneity problem that often confounds mechanistic understanding of EV biology.in Nature Methods on 2026-04-21 00:00:00 UTC.
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NirFAP680: a highly bright and stable large Stokes shift near-infrared fluorogen-activating protein
Nature Methods, Published online: 21 April 2026; doi:10.1038/s41592-026-03061-6
NirFAP680 is a near-infrared fluorogen-activating protein that has an order of magnitude greater cellular brightness and superior photostability compared to currently available NIR FAPs and fluorescent proteins in both single- and two-photon excitation and allows robust imaging of proteins in live cells and in vivo.in Nature Methods on 2026-04-21 00:00:00 UTC.
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Laser-induced nucleation of magnetic hopfions
Nature Physics, Published online: 21 April 2026; doi:10.1038/s41567-026-03236-0
The creation of stable and isolated magnetic hopfions—three-dimensional topological solitons—has remained experimentally challenging. Now the laser-induced nucleation of hopfions has been achieved in a chiral magnet.in Nature Physics on 2026-04-21 00:00:00 UTC.
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Two-electron quantum walks for probing entanglement and decoherence in an electron microscope
Nature Physics, Published online: 21 April 2026; doi:10.1038/s41567-026-03254-y
Entanglement between particles offers insights into quantum behaviour, but methods for studying it in free-electron systems are lacking. Now a two-electron quantum walk is used to probe decoherence of free electrons inside an electron microscope.in Nature Physics on 2026-04-21 00:00:00 UTC.
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An Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europe
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07176-5
An Open Dataset for the Acoustic Monitoring of Nocturnal Migratory Birds in Europein Nature scientific data on 2026-04-21 00:00:00 UTC.
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An AI-Augmented Dataset of Multi-Prototype Electric Vehicle Charging Load Profiles in China
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07273-5
An AI-Augmented Dataset of Multi-Prototype Electric Vehicle Charging Load Profiles in Chinain Nature scientific data on 2026-04-21 00:00:00 UTC.
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Dataset for studying deformation in 3D patient-specific pulmonary artery anatomies
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07257-5
Dataset for studying deformation in 3D patient-specific pulmonary artery anatomiesin Nature scientific data on 2026-04-21 00:00:00 UTC.
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The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videos
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07215-1
The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videosin Nature scientific data on 2026-04-21 00:00:00 UTC.
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A telomere-to-telomere genome assembly of Chinese water deer (Hydropotes inermis)
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07286-0
A telomere-to-telomere genome assembly of Chinese water deer (Hydropotes inermis)in Nature scientific data on 2026-04-21 00:00:00 UTC.
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Decoding a Microbial Community for Healthy Kelp: 403 MAGs from the World’s Largest Kelp Farming Region
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07250-y
Decoding a Microbial Community for Healthy Kelp: 403 MAGs from the World’s Largest Kelp Farming Regionin Nature scientific data on 2026-04-21 00:00:00 UTC.
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Chromosome-level genome assembly of the sponge Halisarca dujardinii
Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07161-y
Chromosome-level genome assembly of the sponge Halisarca dujardiniiin Nature scientific data on 2026-04-21 00:00:00 UTC.
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Retraction Note: circGIGYF1 inhibits stemness and metastasis in colorectal cancer by promoting WWP2-HOXD13 interaction to regulate β-catenin signalling
Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10115-0
Retraction Note: circGIGYF1 inhibits stemness and metastasis in colorectal cancer by promoting WWP2-HOXD13 interaction to regulate β-catenin signallingin Nature communications biology on 2026-04-21 00:00:00 UTC.
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The transcription factor Rlm1 couples the MAPK Slt2/ERK1 pathway to the IRE1-driven unfolded protein response
Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10090-6
A crosstalk between the MAPK Slt2/ERK1 and IRE1-mediated UPR signaling pathway is uncovered in Saccharomyces cerevisiae.in Nature communications biology on 2026-04-21 00:00:00 UTC.
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A single-cell transcriptomic atlas identifies key progenitor populations driving postnatal horn bud development in goats (Capra hircus)
Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10068-4
Single-cell analysis of goat horn buds reveals a day 7 developmental switch in which ZEB2+ progenitor mesenchymal cells initiate osteogenesis while keratinocytes drive sheath mineralization, defining coordinated dermal–epidermal programs of ruminant headgear formation.in Nature communications biology on 2026-04-21 00:00:00 UTC.
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Sabinineoside B alleviates metabolic dysfunction-associated steatotic liver disease by targeting PPAR α
Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10082-6
The novel phenanthrene alkaloid glycoside Sabinineoside B ameliorates metabolic dysfunction-associated fatty liver disease induced by a high-fat diet through the regulation of lipid metabolism via targeting PPAR α.in Nature communications biology on 2026-04-21 00:00:00 UTC.
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Modeling the hallucinatory effects of classical psychedelics in terms of replay-dependent plasticity mechanisms
Classical psychedelics induce complex visual hallucinations in humans, generating percepts that are coherent at a low level, but which have surreal, dream-like qualities at a high level. While there are many hypotheses as to how classical psychedelics could induce these effects, there are no concrete mechanistic models that capture the variety of observed effects in humans, while remaining consistent with the known pharmacological effects of classical psychedelics on neural circuits. In this work, we propose the ‘oneirogen hypothesis,’ which posits that the perceptual effects of classical psychedelics are a result of their pharmacological actions inducing neural activity states that truly are more similar to dream-like states. We simulate classical psychedelics’ effects via manipulating neural network models trained on perceptual tasks with the Wake-Sleep algorithm. This established machine learning algorithm leverages two activity phases: a perceptual phase (wake) where sensory inputs are encoded, and a generative phase (dream) where the network internally generates activity consistent with stimulus-evoked responses. We simulate the action of psychedelics by partially shifting the model to the ‘Sleep’ state, which entails a greater influence of top-down connections, in line with the impact of psychedelics on apical dendrites. The effects resulting from this manipulation capture a number of experimentally observed phenomena, including the emergence of hallucinations, increases in stimulus-conditioned variability, and large increases in synaptic plasticity. We further provide a number of testable predictions which could be used to validate or invalidate our oneirogen hypothesis.in eLife on 2026-04-21 00:00:00 UTC.
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Prior cocaine use disrupts identification of hidden states by single units and neural ensembles in orbitofrontal cortex
The orbitofrontal cortex (OFC) is critical to identifying task structure and to generalizing appropriately across task states with similar underlying or hidden causes. This capability is at the heart of OFCs proposed role in a network responsible for cognitive mapping, and its loss can explain many deficits associated with OFC damage or inactivation. Substance use disorder is defined by behaviors that share much in common with these deficits, such as an inability to modify learned behaviors in the face of new information about undesired consequences. One explanation for this similarity would be if addictive drugs impacted the ability of OFC to recognize underlying similarities, hidden states, that allow information learned in one setting to be used in another. To explore this possibility, we trained rats to self-administer cocaine and then recorded single-unit activity in lateral OFC as these rats performed in an odor sequence task consisting of unique and shared positions. In well-trained controls, we observed chance decoding of sequence at shared positions and near chance decoding even at unique positions, reflecting the irrelevance of distinguishing these positions in the task. By contrast, in cocaine-experienced rats, decoding remained significantly elevated, particularly at the positions that had superficial sensory differences that were collapsed in controls across learning. These neural differences were accompanied by increases in behavioral variability at these positions. A tensor component analysis showed that this effect of reduced generalization after cocaine use also extended across positions in the sequences. These results show that prior cocaine use disrupts the normal identification of hidden states by OFC.in eLife on 2026-04-21 00:00:00 UTC.
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Orderly mitosis shapes interphase genome architecture
Genomes assume a complex 3D architecture in the interphase cell nucleus. Yet the molecular mechanisms that determine global genome architecture are only poorly understood. To identify mechanisms of higher-order genome organization, we performed high-throughput imaging-based CRISPR knockout screens targeting 1064 genes encoding nuclear proteins in multiple human cell lines. We assessed changes in the distribution of centromeres at single-cell resolution as surrogate markers for global genome organization. The screens revealed multiple major regulators of spatial distribution of centromeres, including components of the nucleolus, kinetochore, cohesins, condensins, and the nuclear pore complex. Alterations in centromere distribution required progression through the cell cycle and acute depletion of mitotic factors with distinct functions altered centromere distribution in the subsequent interphase. These results identify molecular determinants of spatial centromere organization, and they show that orderly progression through mitosis shapes interphase genome architecture.in eLife on 2026-04-21 00:00:00 UTC.
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Single-cell co-mapping reveals relationship between chromatin state and gene expression in early zebrafish development
Establishing a cell type-specific chromatin landscape is crucial for the maintenance of cell identity during embryonic development. However, our knowledge of how this landscape is set during vertebrate embryogenesis has been limited, due to the lack of methods to jointly detect chromatin modifications and gene expression in the same cell. Here we present a multimodal measurement of full-length transcriptome and histone modifications in individual cells during early embryonic development in zebrafish. We show that before the formation of germ layers, the chromatin and transcription states of cells are uncoupled and become progressively connected during gastrulation and somitogenesis. Silencing of developmental genes is achieved by local spreading of repressive chromatin together with cell type-specific demethylation. Combining transcription factor (TF) expression and chromatin states within an interpretable machine learning model, we classify TFs as lineage-specific activators and repressors and identify a subset of TFs that are epigenetically regulated. Altogether, our data resolves the dynamic relationship between chromatin and transcription during early vertebrate development and clarifies how these two layers interact to establish cell identity.in eLife on 2026-04-21 00:00:00 UTC.
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Brain-wide mapping of layer-specific functional connectivity in the human cortex at 3T using draining-vein-suppressed fMRI
Layer-dependent functional magnetic resonance imaging (fMRI) is a promising yet challenging approach for investigating layer-specific functional connectivity (FC). Achieving a brain-wide mapping of layer-specific FC requires several technical advancements, including sub-millimeter spatial resolution, sufficient temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein contamination. In this study, we addressed these limitations by integrating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence to suppress vascular signals from the vessels with fast-flowing velocity. The extravascular contamination from pial veins was mitigated using a GE-EPI sequence at 3T rather than 7T, combined with phase regression methods. Additionally, we incorporated advanced techniques, including simultaneous multi-slice (SMS) acceleration and NOise Reduction with DIstribution Corrected principal component analysis (NORDIC PCA) denoising, to improve temporal resolution, spatial coverage, and signal sensitivity. This resulted in a VN fMRI sequence with 0.9 mm isotropic spatial resolution, a repetition time (TR) of 4 s, and brain-wide coverage. The VN gradient strength was determined based on results from a button-pressing task. Using resting-state data, we validated layer-specific FC through seed-based analyses, identifying distinct connectivity patterns in the superficial and deep layers of the primary motor cortex (M1), with significant inter-layer differences. Further analyses with a seed in the primary sensory cortex (S1) demonstrated the reliability of the method. Brain-wide layer-dependent FC analyses yielded results consistent with prior literature, reinforcing the efficacy of VN fMRI in resolving layer-specific functional connectivity. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.in eLife on 2026-04-21 00:00:00 UTC.
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Antibiotic potentiation and inhibition of cross-resistance in pathogens associated with cystic fibrosis
Critical Gram-negative pathogens, like Pseudomonas, Stenotrophomonas, and Burkholderia, are now resistant to most antibiotics. Complex resistance profiles, together with synergistic interactions between these organisms, increase the likelihood of treatment failure in distinct infection settings, for example in the lungs of cystic fibrosis (CF) patients. Here, we discover that cell envelope protein homeostasis pathways underpin both antibiotic resistance and cross-protection in CF-associated bacteria. We find that inhibition of oxidative protein folding inactivates multiple species-specific resistance proteins. Using this strategy, we sensitize multidrug-resistant Pseudomonas aeruginosa to β-lactam antibiotics and demonstrate promise of new treatment avenues for the recalcitrant emerging pathogen Stenotrophomonas maltophilia. The same approach also inhibits cross-protection between resistant S. maltophilia and susceptible P. aeruginosa, allowing eradication of both commonly co-occurring CF-associated organisms. Our results provide the basis for the development of next-generation strategies that target antibiotic resistance, while also impairing specific interbacterial interactions that enhance the severity of polymicrobial infections.in eLife on 2026-04-21 00:00:00 UTC.
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PPIscreenML is a method for structure-based screening of protein-protein interactions using AlphaFold
Protein-protein interactions underlie nearly all cellular processes. With the advent of protein structure prediction methods such as AlphaFold2 (AF2), models of specific protein pairs can be built extremely accurately in most cases. However, determining the relevance of a given protein pair remains an open question. It is presently unclear how to use best structure-based tools to infer whether a pair of candidate proteins indeed interacts with one another: ideally, one might even use such information to screen among candidate pairings to build up protein interaction networks. Whereas methods for evaluating quality of modeled protein complexes have been co-opted for determining which pairings interact (e.g. pDockQ and iPTM), there have been no rigorously benchmarked methods for this task. Here, we introduce PPIscreenML, a classification model trained to distinguish AF2 models of interacting protein pairs from AF2 models of compelling decoy pairings. We find that PPIscreenML outperforms methods such as pDockQ and iPTM for this task, and further that PPIscreenML exhibits impressive performance when identifying which ligand/receptor pairings engage one another across the structurally conserved tumor necrosis factor superfamily (TNFSF). Analysis of benchmark results using complexes not seen in PPIscreenML development strongly suggests that the model generalizes beyond training data, making it broadly applicable for identifying new protein complexes based on structural models built with AF2.in eLife on 2026-04-21 00:00:00 UTC.
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Architecture shapes event boundaries: Theta dynamics of event segmentation during spatial transitions
Human experience unfolds continuously, yet it is remembered and understood as a sequence of discrete events. How the brain segments this stream of experience, particularly under naturalistic conditions, remains poorly understood. Here we investigate the neural dynamics associated with event boundaries during active navigation through architectural transitions. Using mobile electroencephalography combined with virtual reality, we analyzed data from participants freely walking between rooms and repeatedly crossing doorways. Time-frequency analysis of source-localized neural activity revealed a robust increase in theta-band power (4-8 Hz) over temporo-occipital and parietal regions approximately 300-450 ms after passing through a doorway. This effect was consistent across participants and independent component clusters, indicating a reliable neural signature of architectural transitions. We interpret this theta response within frameworks of event segmentation and Bayesian inference, suggesting that doorways trigger a transient reconfiguration of distributed neural networks when ongoing predictions can no longer be maintained and a new event model must be inferred. By preserving the natural coupling between perception, movement, and environmental structure, our findings demonstrate that architecture provides meaningful boundaries that shape brain dynamics and the organization of experience. More broadly, this work highlights the power of naturalistic experimentation and positions architectural space as an active medium for investigating how the brain structures events.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Neural correlates of licking behavior modulated by target position in the striatal matrix compartment
The striatum is a major cortical input site of the basal ganglia and plays a critical role in the control of orofacial movements such as licking. However, how striatal activity relates to the spatial features of licking behavior remains unclear. In this study, we examined whether neural activity in the striatal matrix and striosomal compartments is associated with the spatial position of a licking target during an operant task. Head-fixed mice performed a licking task in which the target positions were varied across three spatial dimensions. Using fiber photometry in Calb1-IRES-Cre and Pdyn-IRES-Cre mice, we recorded calcium signals from matrix and striosomal neurons. Associations between neural activity, target position, and behavioral variables were quantified using linear mixed-effects modeling with cross-validation. Matrix activity prior to licking onset was primarily associated with the dorsal-ventral target position and reaction time. During licking, matrix activity was modulated by anterior-posterior and medial-lateral positions, independent of reaction time and lick count. In contrast, striosomal activity during licking was predominantly associated with the dorsal-ventral position. These findings demonstrate that neural matrix activity is systematically associated with spatial features of licking behavior, with distinct contributions before and during movement. Our results suggest that striatal matrix circuits provide task-relevant spatial signals for the control of orofacial actions.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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QNPtoVox: A methods pipeline for mapping 2D quantitative neuropathology to 3D MNI voxel space.
Quantitative neuropathology has advanced through whole-slide imaging and digital histology platforms. Yet, these measurements rarely align with neuroimaging coordinate frameworks that may be useful for spatial modeling and other applications. QNPtoVox, short for quantitative neuropathology to voxels, is a reproducible, modular pipeline that transforms quantitative metrics generated by digital pathology software (HALO) into voxel-based maps registered to a standard common coordinate (MNI) template. The workflow integrates digital histopathology, gross tissue photography, ex-vivo MRI, and nonlinear registration to generate spatially standardized 3D pathology representations. This Methods article provides a complete procedural description, including required materials, step-wise instructions, operator-dependent checkpoints, expected outputs, reproducibility evaluation, and troubleshooting. QNPtoVox enables voxel-level integration of neuropathology with neuroimaging tools, unlocking existing histopathology datasets for computational modeling and cross-cohort harmonization.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Neuronal precursor cell persistence in Ganglioglioma is associated with ECM remodeling and immune cell infiltration
Background: Gangliogliomas (GGs) are low-grade glioneuronal tumors that frequently present with drug-resistant epilepsy. Although their indolent course contrasts with their high epileptogenic potential, the oncogenic mechanisms sustaining neuronal precursor-like populations within the tumor microenvironment remain poorly defined. Methods: We performed spatial transcriptomic profiling on eight histologically confirmed GGs and matched healthy cortex to map the cellular and molecular architecture of the tumor microenvironment. Integrated analysis with weighted gene correlation network analysis (WGCNA) defined recurrent oncogenic programs and spatially resolved tumor-stroma interactions. Results: Eight conserved gene modules emerged, encompassing physiological cortical, reactive glial, and oncopathological programs. The latter captured extracellular matrix (ECM) remodeling, vascular-immune signaling, and persistence of immature, proliferative neuronal-like states. Spatial modeling revealed that these oncopathological programs form structured niches at the tumor-brain interface, where radial glia-derived neuronal-like tumor cells coexist with immune and stromal elements engaged in ECM turnover and cytokine signaling. Conclusions: Ganglioglioma represents a hybrid glioneuronal neoplasm in which developmental neuronal programs are co-opted by tumor-associated stromal and immune cues. This convergence establishes a permissive oncogenic niche that sustains precursor-like tumor cells and provides a mechanistic basis for both the tumor's benign growth and its intrinsic epileptogenicity.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Plagl2 unlocks the latent regenerative potential of Müller glia in the adult mouse retina
Muller glia (MG) in the adult mammalian retina have long been recognized as a potential endogenous source for the regeneration of lost retinal neurons. However, existing MG reprogramming strategies yield an incomplete regenerative response by favoring either proliferation or neurogenic differentiation. Here, we show that the zinc-finger transcription factor Plagl2, which has been demonstrated to rejuvenate aged neural stem cells, was sufficient to reprogram adult mouse MG into a progenitor-like state with coupled proliferative and neurogenic competence. Using histology, time-lapse imaging, and single-cell transcriptomics, we found that Plagl2 drove regulated rounds of MG cell cycle re-entry, while N-methyl-D-aspartate-induced retinal injury further promoted the acquisition of neurogenic competence toward inner nuclear layer neuronal identities. These findings identify Plagl2 as a novel rejuvenator of mammalian MG and support the general principle that reprogramming modules can be redeployed across cell types, offering new avenues for unlocking regenerative potential in otherwise non-regenerative tissues.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Pseudouridylation of rRNA by specific snoRNA disrupts ribosomal machinery and consequently affects metabolism, longevity and neurodegeneration
In our society, ageing, longevity, and neurodegenerative diseases are major concerns of public health. Recently, in Drosophila, we have identified a new cluster of three snoRNAs, including jouvence, and showed that each of them affect longevity and neurodegeneration. As these snoRNAs are required in the epithelium of the gut, these results point-out a causal relationship between the epithelium of the gut and the neurodegenerative lesions through the metabolic parameters, indicating a gut-brain axis. Here, we demonstrate that each snoRNA pseudouridylates a specific site on ribosomal-RNA, which consequently affects the amount of ribosomes as well as the translational efficacy. Moreover, using TRAP experiment assay, we also show that these lacks of pseudouridylations modify the translation of specific genes involved in lipid metabolism. Consequently, these lead to a chronic deregulation of trigycerides and sterols levels, whose correlate to an increase of neurogenerative lesions in old flies, as well as to a modification of longevity.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Emotion regulation or dual task? Dissociation of neural and behavioral measures
Cognitive reappraisal, the deliberate reinterpretation of emotional events, is widely considered an effective emotion regulation strategy, and modulation of the late positive potential (LPP) during negative affect reduction has become the primary electrophysiological evidence for volitional emotional control. Experimental instructions, however, impose dual-task demands that free viewing does not, confounding reappraisal with cognitive load. By including instructions to increase emotional responses to pictures (enhance) as well as instructions to decrease (suppress), different predictions are generated. If the LPP reflects regulation, then, compared to free viewing, suppress instructions should decrease LPP amplitude, and enhance instructions should increase LPP amplitude. If modulation instead reflects cognitive load, both instructions should reduce the LPP equally, as both impose an additional cognitive task. In a sample of 107 participants, subjective ratings confirmed that regulation instructions modulated reported emotional intensity in the expected directions (Enhance > View > Suppress), but that both enhance and suppress instructions reduced LPP amplitude compared to free viewing, with Bayesian model comparisons providing strong evidence against direction-specific regulation and in favor of cognitive load. Whole-scalp multivariate pattern analysis confirmed that no instruction-related neural signal exists at any scalp location or latency within the first second after stimulus onset. These data indicate that LPP modulation following both instruction types reflects dual-task cognitive load rather than volitional emotional control.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Minimal social context decouples affective response modalities
Emotions often occur within social interactions where affective cues are accessible or inferable by others. This raises questions regarding how and to which degree social context modulates subjective, physiological and behavioural affective responses, as well as their coherence, questions which remain points of tension in emotion research. To investigate this, we measured subjective affective ratings, autonomic sympathetic and parasympathetic activity, and facial behaviour while participants completed an emotion-induction task. In the social-context condition (but not control), participants believed that their video feed was accessible to a potential future interaction partner. Results show that even such "minimal social context" selectively and differentially modulated affective response modalities, characterised by both intensification of autonomic responses and dampening of overt facial and subjective affect. Multivariate dimensionality analysis further identified a cross-modal affective dimension Interestingly, social context reduced participants' coupling with this shared affective response structure, indicating weaker cross-modal coherence. These findings suggest that emotional responding relies on a flexible, rather than rigid, configuration of affective features, likely recruited to meet the socioemotional demands of a given context. This has important implications for understanding the structure and function of emotion, as well as typical and atypical socioemotional responding.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Facing pain is effortful: key role of the supplementary motor area and anterior midcingulate cortex
Pain captures attention and interferes with executive and motor processes but task performance may be preserved at the cost of more effort. In a preregistered fMRI study, 40 participants performed a visuomotor force-matching task at two force levels under individually calibrated painful or non-painful thermal stimulation, while reporting the intensity of perceived effort. Maintaining task performance under pain was associated with increased perceived effort and recruited brain regions involved in pain modulation and cognitive control. Region-of-interest analysis showed perceived effort was consistently linked to decreased anterior midcingulate cortex activity, whereas supplementary motor area contributions varied depending on its role in motor execution or pain processing. Across experimental condition, motor, pain-modulatory and cognitive-control regions were associated with effort perception. Independently of condition, effort perception was modulated by ventromedial prefrontal cortex and ventral striatum. These findings indicate that effort perception reflects brain activity within areas involved in motor, executive and valuation processes.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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BridgeBP: A Toolbox for Bridging Brain Parcellations and Standardizing Structural Connectivity Matrices
Brain network analysis has emerged as a critical framework for understanding the complex organization and function of the human brain, underpinning insights into cognition, behavior, and neuropsychiatric conditions. Central to this approach is the parcellation of the brain into discrete regions, which simplifies high-dimensional connectome data and facilitates the investigation of network architectures. However, the proliferation of brain parcellation schemes introduces significant challenges: different parcellations often yield varying network sizes and measures, complicating cross-study comparisons and the reproducibility of findings. Moreover, most connectome construction pipelines are rigid, typically outputting connectivity matrices from only one or a few parcellation schemes, which limits flexibility. In this paper, we address these issues by introducing BridgeBP, a novel toolbox designed to bridge brain parcellations by leveraging continuous brain connectivity concepts. BridgeBP transforms structural connectivity matrices derived from one parcellation scheme into matrices corresponding to more than 40 alternative schemes, standardizing analyses and enhancing the robustness of network studies. Through extensive evaluations, we demonstrate that BridgeBP enables consistent network comparisons across diverse parcellation frameworks, paving the way for more reproducible and generalizable insights in brain connectome research.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Protocadherin 9 promotes cell survival of different bipolar subtypes in the developing mouse retina
Neural circuit assembly relies on different neuronal subtypes coming together to form a functional circuit. The question of how the appropriate number of each subtype is integrated into an emerging circuit remains relatively unknown. To answer this question, we used the mouse retina to uncover the molecular mechanisms responsible for neuron subtype integration in a developing circuit. In the mammalian retina, bipolar neurons are a class of interneurons that relay visual information from photoreceptors to ganglion cells. Extensive studies have shown there are 15 distinct bipolar subtypes: 6 types of OFF cone bipolars, 8 types of ON cone bipolars, and 1 type of rod bipolar. During retinal development, bipolar neurons are born in excess and through programmed cell death, a precise number of each subtype remains to give rise to the retinal circuit. Although this process has been well-described, little is known about the key molecules responsible for bipolar subtype integration in the developing retina. Our work uncovered a new role for the autism-associated risk gene, Protocadherin 9 (Pcdh9) in bipolar subtype integration. Deletion of Pcdh9 using a floxed allele leads to loss of OFF and ON cone bipolars; however, disruption in the extracellular binding of Pcdh9 leads to selective loss of ON cone bipolars but not rod bipolars. Moreover, we found this later function of Pcdh9 is mediated by homophilic interactions between ON cone bipolars and their known synaptic partners. Taken together, our work revealed a new role for Pcdh9 in bipolar subtype integration during retinal development.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Sensorimotor training lightens the perceived weight of body augmentation devices
A distinctive feature of bodily experience is its transparency. During skilled action, our limbs recede from awareness and function as the medium of interaction rather than perceptual objects. This is reflected in systematic perceptual biases: humans reliably underestimate the weight of their own hands, potentially reflecting predictive motor processes that modulate self-generated sensory signals. Wearable technologies may test the limits of this perceptual transparency. Exoskeletons and other augmentative devices attach directly to the body, adding mass that must be integrated into sensorimotor control; yet little is known about how such devices are experienced as they become integrated into the sensorimotor system. Here, we tested whether training with finger-extending exoskeletons alters their perceived weight and whether such changes depend on active use. We developed a Bayesian analytic framework combining individual psychometric modelling with a regression-based decomposition of perceived weight, to partition contributions of the biological hand and attached exoskeletal device. Thirty-four right-handed adults completed a weight-perception task before and after 20 minutes of training with either finger-extending or non-augmenting control devices. Participants compared the perceived weight of their right hand, with or without the exoskeleton, to reference weights suspended from the opposite wrist. Before training, the weight of both the biological hand and the exoskeleton were underestimated to a similar degree (~25-30%), suggesting rapid perceptual integration following attachment. Training selectively increased attenuation of the perceived weight of the finger-extending exoskeleton, with no corresponding change for the biological hand and little evidence for a general training effect. These findings support a two-stage embodiment process in which passive attachment initiates perceptual updating, while sensorimotor training consolidates integration through functional interaction with the device. Perceived weight thus provides a behavioral marker of embodiment, offering insight into how the sensorimotor system integrates wearable augmentative technologies.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Brain-heart interactions predict brain activity recovery after systemic anoxia
Background: Global cerebral anoxia is a leading cause of death and resuscitated patients often remained persistently affected by neurological deficits. While previous studies suggest that brain-heart electrophysiological interactions may predict severity and prognosis after hypoxic brain injury coma, little is known about the brain-heart dynamics at near-death. Gaining insight into these mechanisms is crucial for developing targeted interventions in critical conditions. Results: Using a rodent model of reversible systemic anoxia (n=29, male and female rats), we investigated whether brain-heart interactions during the asphyxia onset could predict the return of brain electrical activities after resuscitation. Electrophysiological recordings confirmed that cerebral activity declines following asphyxia, coinciding with increased heart rate variability. Notably, the strong coupling between cardiac parasympathetic activity and high-frequency brain activity in the somatosensory cortex and hippocampus serves as a key predictor of a favorable outcome. Conclusion: Our study underscores the involvement of the brain-heart axis mechanisms in the physiology of dying and the potential prognostic significance of these mechanisms, paving the way for translational research into critical care, based on new characterizations of cardiac reflexes and brain-heart interactions.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Evaluation of Neuronal Activation Thresholds for Low-Frequency Electromagnetic Exposure Using Morphologically Realistic Neuron Models
International guidelines for low-frequency electromagnetic field exposure (LF EMF) are primarily intended to prevent substantiated adverse effects. In the frameworks, limits on internal electric fields are linked to external exposure levels through computational dosimetry. However, the relationship between internal electric fields and these adverse effects remains incompletely understood. In particular, current approaches often overlook the morphological complexity and diversity of cortical neurons, which may limit the realism of neuronal activation estimates used to support these assessments. This study evaluates LF EMF-induced neural activation using 25 morphologically realistic neuron models spanning all cortical layers, embedded within 11 detailed human head models. The internal electric fields were simulated for uniform magnetic field exposures (100 Hz-100 kHz) along the three anatomical directions, and excitation thresholds were computed using a multi-scale framework combining voxel-based dosimetry with biophysical neuron simulations. A real-world exposure scenario involving a child near an acousto-magnetic article-surveillance deactivator was also analyzed. Thresholds varied across cell type, morphology, cortical location, subject anatomy, frequency, and exposure direction, with L2/3 pyramidal, L4 basket, and L5 thick-tufted pyramidal cells showing the lowest thresholds. Despite this variability, all simulated thresholds were conservative with respect to the basic restrictions and dosimetric reference limits set by IEEE ICES and ICNIRP. The smallest margin occurred at 100 kHz, where the threshold remained a factor of 2.8 above the corresponding limit. These findings indicate that current LF EMF exposure limits remain conservative when evaluated using highly detailed, morphology-based CNS activation models.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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cis-gamma-Amino-L-proline peptides as chemical probes of amyloidogenic processing in neurons and APP/PS1 mice
Alzheimer's disease (AD) is characterized by the accumulation of amyloid-beta (Abeta) peptides, which are a key factor in its pathogenesis. In this study, we present the design and evaluation of gamma-amino-L-proline peptides as metabolically stable, cell-penetrating molecules that can modulate amyloidogenic processing. We screened a library of gamma-peptides in primary neuronal cultures to determine their effects on endogenous Abeta1-42 production, cytotoxicity, and beta-secretase (BACE1) activity. Comparative analysis of structurally related analogues enabled the identification of molecular features associated with Abeta-lowering activity, establishing a qualitative structure-activity relationship. Peptide 33 (P33) emerged as a lead candidate, selectively reducing BACE1 activity without significantly inhibiting the homologous enzyme, BACE2. In vitro blood-brain barrier (BBB) assays revealed that P33 exhibits favorable transendothelial permeability. Intraperitoneal administration of P33 in APP/PS1 mice decreased Abeta levels, reduced amyloid plaque burden, and improved performance in a behavioral recognition task without inducing cytotoxicity or systemic toxicity. These results define cis-gamma-amino-L-proline peptides as a bioorganically distinct and modular scaffold for the development of intracellular modulators of Abeta production.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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The tongue-brain axis mediates a hidden amino acid appetite
Selecting a diet containing all essential amino acids (EAAs) is critical for health. Following EAA deprivation, animals can select a nutritiously complete food source; however, the underlying mechanisms in vertebrates remain unclear. In mice, we show that leucine deficiency activates hypothalamic agouti-related protein (AgRP) neurons, which project to the paraventricular thalamus (PVT) via gamma-aminobutyric acid and are required for EAA deficiency-induced leucine appetite in mice. Furthermore, the peripheral tongue amino acid sensor general control nonderepressive 2 (GCN2) mediates acute EAA appetite via AgRP neurons. Together, these findings identify a tongue-AgRP-PVT circuit underlying EAA appetite, which is important for the rapid and accurate selection of essential nutrients.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Lateral hypothalamic melanin-concentrating hormone neuron dynamics in rats during sensory stimulation and sugar sweetened alcoholic cocktail drinking
There is a dearth of information on how different cocktails sweetened with different sugars impact brain activity. Glucose enters the brain faster and in greater concentration than fructose and directly affects neuronal activity of melanin-concentrating hormone (MCH) neurons. MCH signaling promotes both glucose drinking and alcohol intake by integrating central and sensory inputs, but it is currently unknown how MCH neuronal activity relates to sweetened cocktail drinking. This study sought to investigate the relationship between MCH activity and sugar-sweetened alcoholic cocktail drinking. We also sought to compare MCH neuronal responses to the sugar solutions without alcohol as well as their response to sensory stimuli. In female and male rats, we used fiber photometry to monitor MCH neurons in response to sensory stimuli and during drinking of 10% glucose, 10% fructose, and glucose or fructose cocktails with 1.25% or 10% alcohol. We found that MCH activity rises in response to a variety of sensory stimuli and peaks before the start of drinking for all cocktails, before returning to baseline near the start of drinking. The cocktail type impacted the dynamics of MCH activity, where increased alcohol concentration resulted in earlier MCH activity for fructose but not glucose cocktails. Finally, we found that peak MCH activity during drinking is correlated with approach behavior for all sugar and cocktail types. These findings suggest that glucose and alcohol may interact to directly influence MCH activity. Further, MCH neurons may regulate cocktail drinking in response to sugar type and alcohol concentration.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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tVTA controls dual dopaminergic inputs to the external Globus Pallidus
Midbrain dopamine (DA) neurons critically regulate basal ganglia function through their widespread projections. While the nigrostriatal pathway is well characterized and represents the dominant source of DA in the basal ganglia, other nuclei such as the external Globus Pallidus (GPe) also receive dopaminergic innervation, yet no consensus exists about its precise anatomical origin. In addition, the GABAergic tail of the ventral tegmental area (tVTA) provides a major inhibitory input to midbrain DA neurons, but its influence over DA pathways to the GPe remains unknown. In the rat, we combined retrograde tracing, immunohistochemistry, and ex vivo electrophysiology to identify distinct populations of DA neurons in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) that project to the GPe and display distinct electrophysiological properties. Using optogenetics and electrophysiology, we also demonstrate that these GPe-projecting DA neurons receive powerful inhibitory input from the tVTA. Together, our findings define both the origin and inhibitory control of dopaminergic innervation to the GPe, revealing a previously unrecognized disynaptic circuit (tVTA->DA->GPe) that refines our understanding of basal ganglia circuit function.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Feedback to deep layers in human V1 during perceptual filling-in
Visual surface perception is a fundamental aspect of vision, yet its neural implementation remains poorly understood. Troxler's perceptual filling-in paradigm provides a tractable illusion for studying surface perception, in which a peripheral figure becomes perceptually assimilated into the surrounding background after a period of sustained fixation. Although neural correlates of this phenomenon have been reported in early visual cortex, the underlying mechanisms, particularly the contribution of feedback signaling, remain unresolved. Here we use ultra-high-field (7T) layer-fMRI to investigate perceptual filling-in in the human visual cortex. While experimentally controlling perceptual filling-in, we measured GE-BOLD responses in ten participants. Analyses across cortical depth in the independently localized figure representation in primary visual cortex (V1) revealed neural correlates of filling-in in deep cortical layers, which are associated with feedback input. These findings provide evidence that perceptual filling-in and visual surface perception in general are supported by feedback signals to early visual cortex.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Red fluorescent labeling of myelin by membrane-targeted tdTomato in transgenic mouse lines
Myelin is a highly complex membranous structure wrapped around axons by oligodendrocytes or Schwann cells in the central and peripheral nervous system, respectively. Fluorescent labeling is widely used to study the structure and dynamics of myelin. Combining structural with functional imaging requires labeling of myelin with red fluorescence, as many functional sensors, including Ca2+ indicators and genetically encoded metabolite sensors, fluoresce in the green spectral range. However, in vivo tools enabling red fluorescent labeling of myelinating cells and their myelin sheaths remain limited. Here, we generated a set of seven transgenic mouse lines expressing a membrane-targeted variant of the red fluorescent protein tdTomato in myelinating oligodendrocytes and Schwann cells throughout the nervous system. The mouse lines provide a variety of expression patterns ranging from wide-spread labeling of myelin to a rather sparse expression, the latter enabling visualization of individual oligodendrocytes and their associated myelin sheaths. In the peripheral nervous system, the pattern of fluorescence in sciatic nerves indicates predominant localization of tdTomato to non-compact myelin compartments including the inner and outer tongues, paranodal loops and Schmidt-Lanterman incisures. In summary, our work provides a set of novel mouse lines with myelin labeled by red fluorescence, which are compatible with diverse imaging modalities in the green spectral range enabling integrated structural and functional imaging.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Loss of autism-associated gene wac alters social behavior and identifies cho-1 as a modulator of cholinergic signaling in C. elegans
WAC is an autism-associated gene involved in neurodevelopment. However, the effects of reduced WAC function on behavior and synaptic regulation in vivo remain unclear. Taking cues from the previous studies on the wac gene and the C. elegans model of ASD, we elucidated the effects of wac gene deletion on food-leaving behavior, a known parameter linked to ASD associated genes along with the cholinergic pathway. wac-deficient worms exhibited curtailed food-leaving behavior. Notably, observed phenotype was similar to that exhibited by nematodes with mutation in ASD related gene, neuroligin. In addition, wac-deficient worms showed impaired growth, reduced pharyngeal pumping, and lifespan. To examine potential synaptic mechanisms, we analyzed expression of genes related to cholinergic signaling across all developmental stages (L1 to L4) through young adult (YA). Stage-specific transcriptional changes were observed, with increased expression of ace-1 and acr-3 at L1, acr-3 at L3, and acr-3, cha-1, lev-1, and lev-10 at L4. The transcriptomic alteration was most prominent at YA stage, exhibiting upregulation of ace-1, cha-1, cho-1, lev-1, lev-10, unc-17, unc-29, unc-38, and unc-50. To identify a specific suppressor of upmodulated Ach signaling, RNAi of the upregulated genes was performed. Cho-1 was identified as a specific suppressor of elevated Ach signaling. cho-1 encodes a high-affinity choline transporter responsible for choline uptake in the presynapse. These studies identify the molecular mechanisms pertaining to up-modulation of cholinergic signaling in wac mutant worms.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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On the location of a "central retina" in mice
The retinal topography of mammals reflects significant influences of the visual environment. In diurnal species, local specializations, such as the visual streak (VS) for panoramic vision and the area centralis or fovea for binocular vision, play a key role in optimizing visual perception and species viability. While the location of these sites is typically considered the retinal center, the definition of a 'central retina' is less clear in nocturnal species. In mice, the most frequently used model in ophthalmologic research, the location of a central retina is hardly discernible in retinal images, neither in retinal structure (OCT sections) nor in vascular organization (SLO and angiography). In this study, we compare the murine retina with that of a diurnal rodent, the Mongolian gerbil (MG). We found that the S-opsin transitional zone (OTZ), a region characterized by the change from S- to M-opsin dominance along the dorsoventral opsin gradient in mice, has a similar relative position in the retina to the VS in the Mongolian gerbil, suggesting an evolutionary positional homology between these regions. Further, since the S-opsin-dominant region is optimized for visualizing the sky and the M-opsin-dominant region for visualizing the ground, the OTZ in between, much like the VS, naturally points toward the horizon. We therefore propose considering the OTZ as the position of a 'central retinal area' in mice. Determining the anatomical-physiological center is particularly important to obtain meaningful relative measures such as averages across different retinal areas, as the common referencing to the optic nerve head (ONH) in mice does not take into account retinal organization and the eccentric position of the functional center.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Temporal Dissociation of Syntactic Disambiguation and Memory Retrieval during Sentence Processing: Naturalistic MEG Evidence from Interpretable Models
Human sentence comprehension proceeds word-by-word, with prior research proposing two central sources of cognitive demand during incremental processing: forward-looking disambiguation of the incoming information stream, and backward-looking retrieval of information associated with previous words from working memory. Recent work has shown that Transformer-based language models successfully generate predictions about sentence processing load in human psycho- and neurolinguistic data by operationalizing disambiguation cost as next-token surprisal, and memory retrieval cost as normalized attention entropy (NAE). Such models, however, remain difficult to interpret as it is not well understood what factors play causally into the decision to assign a cost value to a given word in such artificial neural networks. Here, we present interpretable and cognitively grounded models of disambiguation and memory retrieval and evaluate their neural alignment and spatio-temporal correlates using human magnetoencephalography responses to naturalistic narrative speech. Multivariate temporal response function modeling demonstrates firstly that these human-bias-informed models fare equally well in accounting for observed human language processing data as their Transformer counterparts. This same modeling framework then suggests that surprisal and NAE temporally dissociate in the cortical language network -- surprisal being predictive of bilateral superior temporal gyrus and supramarginal gyrus activation ~300-500 ms, and NAE being predictive of activity in the same regions, but later ~750-850 ms. By demonstrating that interpretable neurocomputational models can achieve meaningful brain alignment while maintaining explanatory transparency, this work offers a methodological blueprint for bridging the gap between algorithmic theory and neural implementation.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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APOE is a presynaptic protein that accumulates with age and modulates neurotransmitter release
The synaptic vesicle (SV) cycle is the fastest membrane trafficking and protein sorting process in biology. It underlies neuronal communication and cognition, yet synaptic function declines during normal aging, increasing vulnerability to neurologic disease. How the SV cycle is maintained across the lifespan of a complex organism remains unclear. Here, we used wild-type mice (C57BL/6J) to define the age- and sex-stratified molecular landscape of SVs and identified apolipoprotein E (APOE) as an abundant presynaptic protein further enriched in aged female samples. Super-resolution imaging, cell-type selective expression, and protease protection assays demonstrate that APOE originates from astroglia and associates with the cytosolic face of SVs. Using iGluSnFR and pHluorin optophysiology, we find that both decreased and increased APOE levels impair neurotransmission during stimulus trains. Together, these findings place APOE at the synapse and establish it as a cell-nonautonomous regulator of the SV cycle.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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GPU-Accelerated Optimization Investigates Synaptic Reorganization Underlying Pathological Beta Oscillations in a Basal Ganglia Network Model
Objective. Pathological beta-band oscillations (13 to 30 Hz) in the subthalamic nucleus (STN) are a hallmark of Parkinson's disease and a primary target for deep brain stimulation therapy, yet the specific pattern of synaptic reorganization that drives their emergence remains incompletely understood. We developed a GPU-accelerated computational framework to systematically investigate combinations of synaptic changes across basal ganglia pathways that produce Parkinsonian beta oscillations while satisfying literature-based electrophysiology constraints. Approach. We implemented a biophysically detailed spiking network model of the STN, external globus pallidus (GPe), and internal globus pallidus (GPi) in JAX (a high-performance numerical computing Python library), achieving a 490-fold speedup over conventional CPU-based simulation. Using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) we optimized 10 network parameters across two stages: first establishing a healthy baseline matching primate electrophysiology data, then searching within biologically motivated bounds for synaptic modifications that reproduce Parkinsonian firing rates and beta power. Fixed in-degree connectivity ensured optimized parameters produced scale-invariant dynamics from 450 to 45000 neurons. All simulations ran on a single cloud GPU instance at 84 cents per hour. Main Results. The optimizer converged on a coordinated pattern of synaptic reorganization dominated by asymmetric changes within the STN-GPe reciprocal loop: STN to GPe excitation increased 2.21-fold while GPe to STN inhibition collapsed to 0.11-fold of its healthy value. STN to GPi and GPe to GPi pathways changed minimally (1.06-fold and 1.45-fold respectively). This configuration transformed asynchronous firing (beta: 0.4 percent of spectral power) into synchronized bursting with prominent beta oscillations (49.4 percent), with firing rate changes matching experimental observations. Network dynamics were invariant across a 100-fold range of network sizes (firing rate deviation less than 2.4 Hz; all metrics p less than 0.001 across 10 random seeds at 45000 neurons). We implemented a simplified deep brain stimulation model for validation purposes, which achieved complete beta suppression (49.4 percent to 0.0 percent) and restored GPi output to healthy levels. Significance. These results suggest that pathological beta oscillations emerge from a specific pattern of synaptic reorganization, namely the reduction of GPe inhibitory feedback to STN. The GPU-accelerated optimization framework, running on commodity cloud infrastructure, demonstrates an accessible platform for parameter exploration in neural circuit models and a foundation for generating synthetic training data for adaptive deep brain stimulation algorithms.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Preserved brain function and reversible cognitive adaptation duringendurance exercise
Endurance exercise imposes extreme metabolic demands on the adult human brain, raising the question of how core brain function is preserved under physiological challenge. We previously showed that marathon running induces reversible reductions in myelin within specific white-matter tracts, suggesting adaptive structural change under metabolic stress. Here, we asked whether this process is functionally tolerated. Neurophysiological recordings revealed maintained conduction latencies across motor, somatosensory, visual, and auditory pathways within 48 hours after race completion, indicating intact axonal signal transmission despite reduced myelin content. Cognitive testing revealed selective and transient modulation of higher-order processing, including attenuated practice-related gains in processing speed and short-lived increases in interference, whereas visuomotor speed and executive flexibility were preserved. All cognitive measures normalized one month after the race, supporting an adaptive framework linking myelin change with preserved brain function under extreme metabolic stress.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Tau pSer396 and pSer404 Define Distinct Epitope Regions Linked to Different Antibody Functions
Hyperphosphorylated tau is a central pathological feature of Alzheimer's disease and related tauopathies, and antibodies targeting the pSer396/pSer404 epitope region represent a promising therapeutic strategy. However, direct comparisons of pSer396- and pSer404-selective antibodies and the impact of humanization on their functional properties remain limited. We generated two new monoclonal antibodies (mAbs), 9E (pSer404-specific) and G10 (pSer396-specific), and evaluated them alongside 4E6 (pSer404) and PHF-1 (pSer396) in murine and partially humanized chimeric formats. Antibodies were assessed in mixed cortical cultures using extracellular (PHF + Ab) and intracellular (PHF [->] Ab) paradigms. Efficacy in preventing tau-induced toxicity and seeding differed substantially among antibodies and was variably altered by chimerization, despite identical variable regions. Antibodies targeting pSer404 were more effective than those targeting pSer396, and antibodies that preferentially bound soluble pathological tau species in competition ELISA were consistently more efficacious, whereas neuronal uptake was comparable across variants. To define structural determinants of phospho-epitope recognition, we determined the crystal structures of the Fab regions of 9E, G10, and PHF-1, and additionally solved the co-crystal structure of Fab PHF-1 in complex with a pSer396 tau peptide at 2.55 [A] resolution. The PHF-1 complex reveals a heavy-chain-dominant binding mode in which pSer396 is anchored within an electropositive pocket and Tyr394 adopts a flipped conformation that stabilizes a {beta}-strand-like motif, consistent with a phosphorylation-dependent conformational switch. These findings demonstrate that epitope selectivity, aggregate preference, structural binding mode, and Fc context collectively govern antibody efficacy, and that humanization can substantially alter therapeutic properties.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Regulation of itch-induced scratching by nucleus accumbens dopamine receptor-expressing neurons
Scratching provides transient relief from itch, yet the neural circuit mechanisms that transform scratching into itch relief remain poorly understood. Midbrain dopaminergic neurons and their downstream targets in the lateral shell of the nucleus accumbens (NAc LaSh) are implicated in itch - scratch processing. Previous studies show that pharmacological manipulation of dopamine D1 and D2 receptors in the NAc LaSh alters scratching behavior, but the specific contributions of D1R- and D2R-expressing neurons during acute and chronic itch remain unclear. Here, we show that NAc LaShD1R and D2R neurons bidirectionally regulate scratching behavior across itch states. NAc LaShD1R neurons' activity promotes scratching bouts, whereas NAc LaShD2R neurons preferentially facilitate scratch termination. Anterograde viral tracing revealed distinct brain-wide projection patterns of NAc LaShD1R and D2R neurons, which we functionally tested using projection-specific optogenetic manipulations. We found that NAc LaShD2R neurons terminate scratching by inhibiting neurons in the lateral parabrachial nucleus (LPBN), a key hub for itch processing. Furthermore, dopamine levels in the NAc LaSh were elevated during chronic itch compared with acute itch, suggesting enhanced dopaminergic signaling contributes to persistent scratching. Together, these findings identify circuit mechanisms linking reward pathways to itch regulation.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Association between chronotype and dual-task gait cost across distinct cognitive domains in healthy young adults
Chronotype reflects individual circadian preference for timing of sleep, wakefulness, and peak performance and has been linked to variability in prefrontal cognitive function across the day. Whether chronotype independently relates to dual-task gait cost (DTC) and whether this relationship differs by cognitive task domain is unclear. Sixty-nine healthy young adults (37 female; mean age 21.3 years) completed the Morningness-Eveningness Questionnaire (MEQ). Spatiotemporal gait parameters were recorded with three-dimensional motion capture during single-task walking and three dual-task conditions: backward word spelling (5LWB; phonological), serial subtraction by seven (SS7; arithmetic), and reverse month recitation (RMR; sequential). DTC was calculated for eight gait parameters. Condition differences were assessed with nonparametric tests and post-hoc comparisons. Multiple linear regression, adjusting for age, sex, BMI, and baseline gait velocity, tested the independent association between MEQ score and mean velocity DTC; exploratory Spearman correlations examined other parameters. SS7 produced the largest mean velocity DTC (-12.76%), significantly greater than 5LWB (-7.95%; p = 0.002) and RMR (-9.57%; p = 0.021). MEQ score independently predicted mean velocity DTC in 5LWB ({beta} = -0.51, p < 0.001, R{superscript 2} = 0.269) and RMR ({beta} = -0.55, p = 0.004, R{superscript 2} = 0.222), indicating greater morningness associated with better gait-speed preservation under cognitive load; the SS7 association was not significant ({beta} = -0.33, p = 0.071). Exploratory correlations showed MEQ-DTC associations across 7/8 parameters in 5LWB, 4/8 in RMR, and 3/8 in SS7. Chronotype is independently associated with dual-task gait cost in a task-domain-specific manner, with stronger effects for phonological and sequential tasks than for arithmetic processing. The SS7 condition yielded the largest interference but weakest chronotype modulation, suggesting arithmetic dual-task disruption may be less sensitive to circadian arousal. Fixed testing time and cross-sectional design warrant within-subject, multi-timepoint studies to confirm chronotype effects separate from time-of-day confounds.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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A novel reporter mouse for astrocyte-derived extracellular vesicles reveals trafficking of cargo to neuronal mitochondria
Extracellular vesicles (EVs) mediate intercellular transfer of lipids, proteins, and nucleic acids between nearly all cell types. We previously showed that astrocyte-derived EVs modulate neuronal mitochondria in vitro, but whether endogenous astrocytic EVs are trafficked to neuronal mitochondria in vivo remained unknown. To address this, we generated an EV reporter mouse, Aldh1l1-Cre; CD9-tGFPfl/fl, in which astrocyte-secreted EVs are labeled with a CD9-turboGFP fusion protein (CD9-tGFP). Astrocyte-specific expression of CD9-tGFP was verified in brain tissue and isolated EVs, comprising 13.2 +/- 1.6% of total brain EVs. In primary glial cultures, CD9-tGFP was restricted to astrocytes, localizing to vesicular compartments and cell protrusions (filopodia and cilia), with 89.3 +/- 2.2% of astrocyte-derived EVs carrying the label. These EVs were enriched with the sphingolipid ceramide, consistent with its co-distribution with CD9-tGFP in astrocytic cell protrusions. In the cortex, hippocampus, and cerebellum, CD9-tGFP was predominantly detected in astrocytic processes co-labeled with GLAST1 and GFAP, forming contacts with laminin-positive capillaries and parvalbumin-positive neurons. CD9-tGFP-labeled EVs were detected inside capillaries and neurons, and super-resolution STED microscopy revealed partial overlap with neuronal mitochondria. Live-cell spinning disk confocal imaging and AI-assisted proximity analysis confirmed uptake of CD9-tGFP EVs by neuronal cells and trafficking of their cargo to mitochondria in vitro. Biochemical isolation of synaptic and non-synaptic mitochondria confirmed EV-derived cargo on mitochondria in vivo, with 3-fold higher association of CD9-tGFP with synaptic than non-synaptic mitochondria. Together, these findings validate the Aldh1l1-Cre; CD9-tGFPfl/fl reporter mouse as a powerful tool for tracking astrocyte-derived EVs in vivo and provide direct evidence that their cargo is preferentially trafficked to synaptic mitochondria.in bioRxiv: Neuroscience on 2026-04-21 00:00:00 UTC.
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Deficits in Forelimb Reach Learning in a Mouse Model of Fragile X Syndrome
Fragile X syndrome is a leading cause of intellectual disability and autism spectrum disorder, for which therapies are limited. A mouse model of fragile X syndrome, the Fmr1 knock-out (KO) mouse, has been particularly valuable for interrogating the molecular, cellular, and circuit mechanisms that underlie the neurological deficits seen in this syndrome. Key deficits in fragile X syndrome include impairments in social behaviors, cognition, and motor learning. Given the difficulties in extrapolating complex human behaviors to mouse models, motor behaviors are a particularly tractable form of learning to study in the mouse. We investigated a form of forelimb reach learning in both male and female Fmr1 KO mice, quantifying different parameters of the task using both manual analysis and DeepLabCut-based tracking of reach trajectories. While Fmr1 KO mice show impaired learning overall, our results showed that the presence or absence of a cue that signals reward alleviated some of the deficits. In addition to a single metric of success in learning, we determined the specific parameters of the motor behavior that were responsible for that success or failure. Our findings provide an essential framework for linking specific behavioral impairments in motor learning to the cellular and circuit mechanisms that support them.
in eNeuro on 2026-04-20 16:30:30 UTC.
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Environmental Enrichment Attenuates Fentanyl-Seeking Behavior and Protects against Stress-Induced Reinstatement in Both Male and Female Rats
Environmental enrichment (EE) reduces vulnerability to multiple drugs of abuse, yet its impact on fentanyl use and relapse-like behavior remains unclear. Here, we tested whether long-term, nonsocial, object-based EE alters fentanyl self-administration, extinction, and stress-induced reinstatement in male and female rats. Rats were individually housed in either standard nonenriched (NE) conditions or in EE cages containing a rotating set of novel objects beginning at least 3 d prior to self-administration. EE did not impact acquisition of fentanyl self-administration but reduced fentanyl intake during maintenance of self-administration and reduced the persistence of drug-seeking in extinction. Following extinction, yohimbine robustly reinstated drug-seeking behavior in NE rats but reinstatement in EE rats was markedly attenuated, indicating reduced sensitivity to stress-induced relapse triggers. Circulating corticosterone levels were lower in EE rats across the experiment and were positively correlated with reinstatement responding, suggesting that enrichment's protective effects may be mediated in part by reduced hypothalamic-pituitary-adrenal (HPA) axis activation. These findings demonstrate that object-based EE, even in the absence of social enrichment, is sufficient to blunt fentanyl use, facilitate extinction, and constrain stress-induced reinstatement. The results highlight the role of environmental context and stress regulation in fentanyl vulnerability and suggest that enrichment-inspired, nonsocial interventions may offer a scalable strategy to reduce opioid use and relapse risk.
in eNeuro on 2026-04-20 16:30:30 UTC.
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A Multi-Network Approach Identifies Proteins Related to Dendritic Spines in Alzheimers Disease
Proteomic studies have generated robust assessments of protein abundance changes in Alzheimer's disease (AD); however, identifying how the protein abundance changes affect specific biological processes remains a challenge. To address these hurdles, we used a multi-network computational analysis approach that integrated dendritic spine morphometry data with mass spectrometry-based proteomics from the same individuals. The samples exhibited a range of AD neuropathology and were categorized into three groups: controls, asymptomatic AD, and AD cases. Multiplex tandem mass tag mass spectrometry proteomic data (N = 8,212 proteins) was generated on Brodmann area 46 (BA46) dorsolateral prefrontal cortex (DLPFC) human samples (N = 41, 23 males and 18 females), from which dendritic spine morphometry analysis existed. To integrate the multi-scale data types, two computational network analysis methods were performed, including weighted coexpression network analysis (WGCNA) and SpeakEasy2 (SE2). Both WGCNA and SE2 revealed that the mitochondria protein modules were decreased in AsymAD and AD cases compared with controls, whereas the DNA repair modules were increased in AsymAD and AD compared with controls. Synaptic protein modules that correlated to multiple spine morphology traits were identified in both WGCNA and SE2. Pearson’s correlation analyses identified over a dozen individual proteins linked to multiple dendritic spine density and morphology traits. Collectively, these findings demonstrate how integration of spine morphometry data with proteomics can contextualize proteins for functional validation and identify synaptic alterations in AD progression.
in eNeuro on 2026-04-20 16:30:30 UTC.
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Inducible CreERT2 Mouse Lines for Characterization of Retinal Bipolar Cell Subtypes
Bipolar cells relay visual signals from photoreceptors to ganglion cells. In the mouse retina, 15 bipolar cell subtypes have been identified and are classified as ON or OFF bipolar cells based on their responses to light or as rod or cone bipolar cells based on their photoreceptor connectivity. Despite this diversity, the distinct structural and functional roles of bipolar cell subtypes in visual information processing remain poorly understood, largely due to lack of tools and models for their characterization. In this study, we generated inducible Cre mouse lines driven by the promoters of Vsx1, Lhx3, and Lhx4 and crossed them with ChR2EYFP reporter mice to trace lineage and characterize bipolar cell subtypes in postnatal and adult mouse retinas. Following tamoxifen induction in adult male and female mice, ChR2EYFP expression was detected in type 2, 6, and 7 bipolar cells in the Vsx1CreERT2 line; type 1b, 2, and 6 bipolar cells in the Lhx3CreERT2 line; and type 2, 3, 4, and 5 bipolar cells in the Lhx4CreERT2 line. In addition, Lhx4CreERT2 activity was observed in cone photoreceptor cells. ChR2EYFP expression was also detected in other ON and OFF cone bipolar cells, as well as rod bipolar cells, when tamoxifen induction was performed in the postnatal mice. These inducible Cre lines enable genetic manipulation in retinal bipolar cell subtypes at different developmental time points and serve as tools for elucidation of the mechanisms that control bipolar cell subtype development and function.
in eNeuro on 2026-04-20 16:30:30 UTC.
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A standardized workflow for kinetic metabolic model curation and dissemination
by Margaret Cook, Stella Anastasakis, Adel Heydarabadipour, Janis Shin, Diego Alba Burbano, James M. Carothers, Herbert M. Sauro
Kinetic metabolic models provide invaluable insights into cellular metabolism, supporting applications in synthetic biology, metabolic engineering, and systems biology. However, reproducibility and utility of these models hinge on clear and rigorous documentation, standardized annotation, and accessible visualization. This paper presents a workflow for building, annotating, visualizing, and sharing kinetic metabolic models. Our method integrates community standards and open-source tools to ensure reproducibility, interoperability, and user accessibility. This procedure enables researchers to produce reusable and well-documented kinetic models, advancing their role as powerful tools in metabolic research.in PLoS Computational Biology on 2026-04-20 14:00:00 UTC.
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La benchmarking large language models for extracting biobank-derived insights into health and disease
by Manuel Corpas, Alfredo Iacoangeli
Biobank-scale datasets such as the UK Biobank have become foundational resources for advancing biomedical discovery. Yet the complexity and heterogeneity of these resources, spanning genomics, imaging, clinical records, and metadata, pose substantial barriers to access and interpretation. Large Language Models (LLMs) offer a promising avenue for making such datasets more navigable through natural language interfaces. However, the extent to which current general-purpose LLMs can retrieve and synthesize biobank-specific insights has not yet been systematically evaluated. In this study, we present a reproducible, multi-metric evaluation framework to benchmark the capabilities of leading LLMs. We evaluated six leading large language models: Gemini 3 Pro, Claude Opus 4.5, Claude Sonnet 4, GPT-5.2, Mistral Large, and DeepSeek V3, on four benchmark tasks designed to assess biobank-related knowledge retrieval. We evaluate model performance across six dimensions (coverage, semantic accuracy, factual correctness, domain knowledge, reasoning quality, and biobank specificity) and assessed output consistency using curated UK Biobank references and a robust random baseline. All models outperformed the baseline by 16× to 25 × , with strong statistical separation (p < 0.001), confirming meaningful biobank-specific knowledge retrieval. Gemini 3 Pro achieved the highest overall accuracy across tasks such as keyword synthesis, institution recognition, and topic inference, while Claude Sonnet 4 demonstrated the most uniform performance across evaluation dimensions. Our benchmark provides a rigorous framework for evaluating LLMs in biomedical settings. Using the UK Biobank as a real-world testbed, we highlight both the capabilities and limitations of current models, measuring their capacity to recall structured biomedical knowledge consistent with authoritative biobank metadata.in PLoS Computational Biology on 2026-04-20 14:00:00 UTC.
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We need to correct the wide-spread omission of equal contribution in article indexing
by Wenying Shou
As team science grows, so do ‘equal contribution’ designations, yet this information is routinely hidden or lost, creating inequity in recognition and crediting. We must fix this problem, now. Equal contribution designations (co-first and co-last authorship) is on the rise, yet this information is routinely lost, creating inequity in recognition and crediting. This Perspective calls for improvements to the system for transferring this information to indexing sites such as PubMed.in PLoS Biology on 2026-04-20 14:00:00 UTC.
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Emerging pathogens associated with acute respiratory infections in children in Hanoi, Vietnam: an analysis of microbiology assay data from 2019 to 2023 [version 3; peer review: 1 approved, 1 not approved]
Background The COVID-19 pandemic has caused changes in respiratory infectious diseases. Examining the patterns of pathogens associated with acute respiratory infection (ARI) in children before, during, and after the COVID-19 pandemic would help to understand the impact of the pandemic on pathogen emergence or re-emergence. Methods We analyzed de-identified data from microbiology assays of nasopharyngeal and blood samples of children ≤15 years old with ARI who visited Vinmec Times City International Hospital in Hanoi, Vietnam from 01/01/2019 to 31/12/2023. The data were aggregated by month, and time-series analysis and visualization were performed. Results A Bacterial Polymerase Chain Reaction (PCR) panel was performed on 4,125 samples (67% positive), Mycoplasma pneumonia (MP) IgM was performed on 5,049 samples (39% positive), bacterial culture was performed on 10,280 samples (43% positive), and viral PCR or rapid test was performed on 42,300 samples (23% positive). After the COVID-19 pandemic from mid-2022, Haemophilus influenzae (HI) and Streptococcus pneumoniae (SP) have re-emerged as epidemic pathogens associated with lower respiratory tract infection (LRI). Influenza type A and type B have re-established regular cycles of peaks in winter-spring months after an early rebound together with an unprecedented new emergence of Human Adenovirus (HAdV) soon after the relief of COVID-19 restriction in mid-2022. Late after the COVID-19 pandemic, from mid-2023, atypical pneumonia pathogen Mycoplasma pneumonia (MP) has emerged remarkably and has become epidemic; there was also a small, brief emergence of Chlamydophila pneumoniae (CP) infection. Conclusion Our data characterize the influence of the COVID-19 pandemic on the patterns of respiratory infection pathogens in children and is useful for disease surveillance and public health interventions.in F1000Research on 2026-04-20 11:04:11 UTC.
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The Effect of Corporate Governance and Transformational Leadership on Business Strategy and Business Performance Moderated by Government Policy [version 2; peer review: 1 approved, 1 approved with reservations]
Background The performance of regional-owned multi-business enterprises (BUMD Aneka Usaha) in Indonesia is crucial for regional economic development, yet many still face challenges related to weak corporate governance, leadership, and business strategy. Methods Data were collected through a questionnaire survey administered to 176 directors of regional-owned multi-business enterprises across Indonesia. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM), with higher-order constructs estimated in SmartPLS. Results The findings show that corporate governance and transformational leadership have positive and significant effects on business strategy and business performance. Business strategy also has a positive and significant effect on business performance and mediates the effects of corporate governance and transformational leadership on performance. Government policy significantly moderates the relationships between corporate governance, transformational leadership, business strategy, and business performance, strengthening their positive impact. Conclusions These results highlight the need to reinforce internal capabilities through stronger governance practices, transformational leadership, and flexible, innovation-oriented strategies, while ensuring a supportive government policy environment so that regional-owned enterprises can improve their business performance.in F1000Research on 2026-04-20 11:03:58 UTC.
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Mapping Research Trends in AI-Based Tourism and Hospitality Marketing: A Bibliometric and Thematic Review [version 2; peer review: 2 approved]
Background Artificial intelligence (AI) has fundamentally transformed tourism and hospitality marketing through enhanced data-driven decision-making, personalized customer experiences, and intelligent destination management. However, the field lacks a comprehensive synthesis of its intellectual landscape and thematic evolution, limiting understanding of research trajectories and emerging directions. Methods A systematic literature review following the SPAR-4-SLR procedure was conducted on 320 peer-reviewed papers published between 2003 and 2025, sourced from the Scopus database. Publication trends, leading journals, prolific authors, trending areas, and bibliographic coupling of documents and countries were visualized using bibliometric analysis tools (VOSviewer and Biblioshiny). Thematic analysis employed keyword co-occurrence networks to identify emerging research themes. Results Academic publications on AI in tourism and hospitality demonstrated a significant surge during 2017–2020, reflecting the industry’s growing emphasis on smart marketing applications. Thematic analysis identified four major research clusters: (i) Digital Influence and Tourist Behaviour Analytics; (ii) AI-Enabled Smart Tourism and Commerce Ecosystems; (iii) Technology-Driven Hospitality and Experience Innovation; and (iv) Data-Driven Decision Making in Predictive Tourism Modelling. Conclusions This bibliometric and thematic assessment reveals the evolving intellectual landscape of AI applications in tourism and hospitality marketing, documenting substantive research growth and the emergence of distinct thematic clusters that shape current and future research agendas in this dynamic field.in F1000Research on 2026-04-20 10:55:22 UTC.
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OpenMBD: An Open-Source Multibody Dynamics Simulator for Biomechanics Research and Education [version 1; peer review: awaiting peer review]
Background Multibody dynamics simulation is a core technique in computational biomechanics and mechanical systems research. Existing open-source platforms are either poorly suited to biomechanics researchers or lack contact mechanics and graphical user interfaces. No single lightweight Python-native package provides forward dynamics, penalty contact, physiological joint constraints, and a graphical interface in combination. Methods OpenMBD is implemented in Python 3 with three external dependencies (NumPy, Matplotlib, Pillow). The dynamics engine applies the Principle of Virtual Power with analytic ZYX-Euler Jacobians and a Recursive Newton-Euler algorithm to assemble and solve the equations of motion with minimal coordinates. Contact mechanics use a penalty-based nonlinear viscoelastic model with hysteresis, applied to ellipsoid body geometry. Physiological joint range-of-motion limits for all major joints of the human body are enforced by continuous penalty spring-dampers parameterised from normative data. Numerical integration uses the Symplectic Euler scheme at a set time step. A Tkinter graphical user interface and a standalone browser-based JSON model editor are provided. Results OpenMBD is distributed with model files: an adult male, an adult female, a car and a bicycle, defined in an open JSON format. Use cases are presented covering fall, sport collisions and custom model definition using the JSON format and browser-based editor. Three output files are automatically generated per simulation run: an output CSV, a summary text file, and a GIF animation. Conclusions OpenMBD addresses a genuine gap in the open-source biomechanics software landscape by providing a Python-native forward dynamics simulator that is installation-trivial, GUI-accessible, and biomechanically parameterised. The software is released under the MIT licence and is available at https://gtbiomech.github.io/OpenMBD/.in F1000Research on 2026-04-20 09:15:54 UTC.
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A discrete serotonergic circuit involved in the generation of tinnitus behavior
Proceedings of the National Academy of Sciences, Volume 123, Issue 17, April 2026.
SignificanceTinnitus, a prevalent hearing disorder linked to dysregulated serotonergic system, has poorly understood neural circuits. Using cutting-edge neuroscience tools, our study reveals a discrete 5-HTDRN→DCNcircuit driving tinnitus in ...in PNAS on 2026-04-20 07:00:00 UTC.
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Micro‐Stimulation Timing Framed Around an Averaged Theta Period of Stimulation Determines Hippocampal Recruitment in Cued Fear Conditioning
ABSTRACT
The importance of precise timing of neuronal activity, relative to ongoing slower oscillations, is reshaping the engram theory and our understanding of how memories are encoded and stored. The hippocampal theta-wave phase-encoding of neuronal firing predicts behavioral outcomes and cognitive performance in memory tasks. A single external stimulus or a sensory/cognitive cue may induce Phase-Resetting shift of theta waves, without changing their frequency or power. This phenomenon seems to be a core mechanism for temporal coordination, information encoding, and memory formation. We hypothesize that not only Phase-Resetting, but temporally coded neuromodulation packaged around an averaged theta cycle of 140 ms, plays a role in engram formation. Inter-pulse microstimulation patterns (MS) consisting of six stimuli within a 140 ms period were applied to the intermedial CA3 hippocampal area of C57/BL6 mice. Each MS-pattern consisted of a 10-bit word (each bit representing a 14-ms bin), indicating the phase at which MS was applied. The randomized (MSr) or fixed pattern (MSf) stimulus was applied during a 30 s presentation of a pure tone (CS) that terminated with a 2 s/0.4 mA footshock (US). Sham animals underwent surgery and cued fear conditioning, but no MS. Cued fear memory was tested by presenting the CS (without MS) in a different context. The group of mice that received the MSf during conditioning showed higher levels of freezing compared to the Sham group; the MSr group did not. We measured c-Fos/NeuN labeling as a proxy for neuronal activity 90 min after memory retrieval. As expected, since cued-fear memory is predominantly amygdala-dependent, all groups showed an increase in c-Fos expression in the amygdala. However, only the MSf group had higher hippocampal activation after retrieval, suggesting that fixed pattern stimulation framed around an averaged theta cycle led to neuronal integration into the memory trace. Our findings indicate that temporal organization plays a crucial role in how memories are stored and accessed.
in Hippocampus on 2026-04-20 06:36:57 UTC.
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Motoneuron Excitability in Parkinson’s Disease: Effects of Dopaminergic Medication
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-20 06:21:22 UTC.
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Intermittent phrenic afferent activation induces phrenic motor plasticity
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-20 06:12:25 UTC.
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A motor thalamic site in humans that suppresses involuntary breathing without awareness
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-20 06:11:25 UTC.
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A Primary Central Source Determines Perturbation-Evoked N1 Amplitudes in Younger Adults
Journal of Neurophysiology, Ahead of Print.
in Journal of Neurophysiology on 2026-04-20 06:01:22 UTC.
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Functional changes in spinal circuitry in essential tremor revealed with analysis of intramuscle synergies
Journal of Neurophysiology, Volume 135, Issue 5, Page 1145-1158, May 2026.
in Journal of Neurophysiology on 2026-04-20 05:03:47 UTC.
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Effect sizes and test power to evaluate spike sorting
Journal of Neurophysiology, Volume 135, Issue 5, Page 1134-1144, May 2026.
in Journal of Neurophysiology on 2026-04-20 05:03:46 UTC.
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Positive association between local brain hypercorrelations and posttraumatic stress disorder symptom severity
Journal of Neurophysiology, Volume 135, Issue 5, Page 1126-1133, May 2026.
in Journal of Neurophysiology on 2026-04-20 05:03:45 UTC.
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Feedback-driven adaptation of gravity-related sensorimotor control to an upside-down posture
Journal of Neurophysiology, Volume 135, Issue 5, Page 1099-1108, May 2026.
in Journal of Neurophysiology on 2026-04-20 05:03:43 UTC.
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Ectopic action potentials in regular spiking neurons in the anesthetized mouse
Journal of Neurophysiology, Volume 135, Issue 5, Page 1109-1125, May 2026.
in Journal of Neurophysiology on 2026-04-20 05:03:41 UTC.
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Pharmacological Profile of Early Sharp Waves in the Neonatal Rat Hippocampus
ABSTRACT
Early activity patterns support the development of neuronal networks by promoting synaptic plasticity. In the hippocampus of neonatal rats and mice in vivo, early sharp waves (eSPWs) are the first pattern of synchronized network activity. The activation of glutamate- and GABA(A)-mediated synaptic currents was described during eSPWs. However, the contribution of different receptor subtypes to eSPW generation is still obscure. To explore the receptor mechanisms of eSPW generation we used a «superfused hippocampus» preparation, which allows a drug application directly to the large area of the hippocampal surface in vivo. Using silicon probe recordings from the superfused hippocampus of neonatal Wistar rats, we assessed electrophysiological properties of eSPWs in control conditions and during the superfusion with glutamate and GABA receptor antagonists. We showed that blocking the AMPA/kainate and NMDA glutamate receptors reduced to a different degree the eSPW frequency and neuronal firing associated with eSPWs. Only when applied simultaneously did the AMPA/kainate and NMDA receptor antagonists completely suppress eSPWs. At the same time, GABA(A) receptors appeared to have a limited role in eSPW generation as eSPWs persisted after GABA(A) receptor blockade alternating with recurrent epileptiform discharges; yet, eSPW amplitude was reduced after epileptiform activity onset. We also observed no changes in eSPW properties produced by blocking the GABA(B) receptors. Taken together, our findings reveal a predominant involvement of AMPA/kainate and NMDA glutamate receptors in eSPW generation and emphasize the role of eSPWs in providing conditions for NMDA receptor-mediated plasticity in the developing hippocampus.
in Hippocampus on 2026-04-20 04:45:43 UTC.
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Annals of Neurology: Volume 99, Number 5, May 2026
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Issue Information
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Combination Disease‐Modifying Therapy for Neurodegenerative Diseases Using Repurposed Drugs
We review the positive effects of several existing drugs from different classes, such as chemical chaperones, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), iron chelators, and cluster-Abelson tyrosine kinase inhibitors (c-Abl TKIs), in preclinical disease models and in available published human data following use of these drugs in individuals with common neurodegenerative diseases (NDs), including Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD). A concept of combinatory neuroprotective therapy using a drug-repurposing approach is then discussed. Finally, we propose a strategy to design an ideal combination of drugs able to address multiple pathogenic processes involved in neurodegeneration to achieve clinically meaningful results. ANN NEUROL 2026 ANN NEUROL 2026;99:1099–1112
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Spontaneous Resolution of Dural Arteriovenous Fistula
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Confined B‐Cell Reconstruction and High T‐Cell Clonality Define Clinical Response to Cladribine Treatment
Cladribine tablets are approved for relapsing multiple sclerosis, mediating their clinical effect by moderately depleting lymphocytes. In a prospective, monocentric study including 22 patients completing 2 annual cycles of cladribine, B- and T-cell receptor repertoires and relapse activity were assessed at baseline and after 24 months. T-cell clonality increased, driven by loss of low-frequency, naive clonotypes, and re-expansion of dominant CD8 memory clonotypes, particularly in clinically stable patients. In contrast, B-cell receptor richness increased because of reconstruction by transitional and naive B cells with higher clonotype numbers observed in relapsing patients. Therefore, competing immune reconstitution following cladribine therapy could result in differential clinical responses. ANN NEUROL 2026;99:1166–1172
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Increased Numbers of CD4+ T‐Cells in the Hypocretin/Orexin Region of Narcolepsy Type 1
Narcolepsy type 1 (NT1) is presumed to be an autoimmune disorder caused by hypothalamic loss of hypocretin (Hcrt; orexin). In postmortem NT1 brains, we observed an 11-fold increase of CD4+ T-cells in the Hcrt region compared with control hypothalami, without a corresponding rise in CD8+ T-cells. CD4+ and CD8+ T-cell numbers were unchanged in other hypothalamic regions, including the paraventricular nucleus and median eminence, and in extra-hypothalamic areas such as the substantia nigra and locus coeruleus. Hcrt-region CD4+ T-cells expressed the tissue-resident memory markers CD49a and CXCR6. These findings support the autoimmune hypothesis of NT1. ANN NEUROL 2026;99:1173–1178
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Cerebral Amyloidoma: An Update Following “Fixation Duress” on PET
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Reply to “Cerebral Amyloidoma: An Update Following ‘Fixation Duress’ on PET”
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Effects of Intradural Extension of Extracranial Cervical Artery Dissection on Outcomes: A Secondary Analysis From the STOP‐CAD Study
Objective
Cervical artery dissection (CeAD) may be limited to the extracranial extradural space or extend to the intradural space. Intradural extension can potentially increase the risk of stroke and subarachnoid hemorrhage. However, the factors associated with intradural extension and its impact on clinical outcome remain unclear.
Methods
This was a secondary analysis of the STOP-CAD observational, multi-center study. Patients with CeAD and intradural extension (CeADid) were compared with those with pure CeAD extradural dissections (CeADed) using multiple regression analyses.
Results
Of 4,023 patients with CeAD, 534 (13.3%) had CeADid. In comparison to patients with CeADed, those with CeADid more often had clinical overt stroke or transient ischemic attack (TIA) at presentation, acute infarcts on imaging, a vertebral artery affected, and severe stenosis of the involved vessel (p < 0.001 for all). In contrast, carotid involvement and complete occlusions were more frequent in patients with CeADed (p < 0.001 for both). CeADid was associated with a shift in the distribution of scores on the modified Rankin Scale (mRS) toward worse functional outcome (odds ratio [OR] = 0.76, 95% confidence interval [CI] = 0.62–0.92) but the odds for favorable outcomes (mRS = 0–2) did not differ between the groups after appropriate adjustments on multivariate analysis. CeADid was independently associated with higher mortality at 180 days on multivariate analysis (adjusted OR = 2.84, 95% CI = 1.50–5.38).
Interpretation
CeADid is associated with more severe clinical presentation, a shift toward less favorable outcomes, and higher mortality rates. These findings suggest that CeADid may represent a high-risk type of CeAD. ANN NEUROL 2026;99:1189–1197
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Conditioning Electrical Stimulation for Patients with Moderate or Severe Carpal Tunnel Syndrome: Double Blinded Randomized Controlled Trial
Objective
Carpal tunnel syndrome (CTS) can drastically impair one's ability to work and interferes with activities of daily living. We recently demonstrated that, in rodents, conditioning electrical stimulation (CES) delivered to the nerve 7 days prior to surgery imparts a conditioning lesion-like effect by accelerating the rate of regeneration along the entire length of the nerve. The goal of this study is to test the hypothesis that CES could accelerate nerve regeneration and improve function in patients with moderate or severe CTS.
Methods
Using a double-blind randomized controlled study design, patients received surgery + CES or surgery + sham stimulation. They were evaluated at regular intervals for 12 months following intervention. Primary outcome was motor unit number estimation (MUNE), supplemented with secondary outcomes including motor and sensory nerve conduction studies, Semmes Weinstein Monofilaments, and Moberg Pick-Up Test.
Results
Sixty-four participants were randomized to either the treatment or control groups. There was no significant demographic or physiological difference at baseline between the groups. No major adverse event was found with treatment. Following intervention, there was significantly greater increase in MUNE of 62 ± 71 in the treatment group compared to 25 ± 66 in the controls after 12 months. In the treatment group, there was correspondingly better physiological and functional recovery and hand dexterity compared with the controls.
Interpretation
CES is a safe, feasible, and efficacious treatment to improve nerve reinnervation and functional outcomes in patients with moderate or severe CTS. This may open future possibilities for more effective treatment for other peripheral nerve injuries. ANN NEUROL 2026;99:1251–1262
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Brain‐Computer Interface‐Controlled Exoskeleton Training for Lower‐Limb Rehabilitation in Spinal Cord Injury: A Pilot Randomized Clinical Trial
Objective
This study aimed to evaluate the efficacy of brain-computer interface (BCI)-controlled exoskeleton training on lower-limb functional recovery, psychological outcomes, and neural plasticity in patients with spinal cord injury (SCI).
Methods
We conducted a single-center, prospective, randomized, single-blind pilot trial (ChiCTR2300074503) including 21 patients with SCI. Participants were randomized to a BCI-exoskeleton group (B + E, n = 10) or an exoskeleton-only group (E, n = 11) for lower-limb training. Both groups received conventional rehabilitation plus 30 minutes of training, 6 days per week, for 4 weeks. The primary outcomes were Walking Index for Spinal Cord Injury II (WISCI II) scoring. Secondary outcomes included Lower Extremity Motor Score (LEMS), Spinal Cord Independence Measure version III (SCIM III), International Association of Neurorestoratology Spinal Cord Injury Functional Rating Scale (IANR-SCIFRS), 10-Meter Walk Test (10MWT), 6-Minute Walk Test (6MWT), and Hospital Anxiety and Depression Scale (HADS). Cortical plasticity was assessed by electroencephalography (EEG) and magnetic resonance imaging (MRI).
Results
The B + E group showed a significant improvement in LEMS (p = 0.003), whereas both groups improved in IANR-SCIFRS (p < 0.05). The B + E group demonstrated significant within-group gains in walking speed (10MWT, p < 0.001) and endurance (6MWT, p = 0.031), although between-group differences were not significant. Compared with the E group, the B + E group had larger reductions in HADS scores (p = 0.003). EEG analyses revealed stronger μ/β desynchronization and increased network efficiency, whereas MRI showed no structural changes.
Interpretation
BCI-controlled exoskeleton training enhanced motor function, walking performance, and depressive symptoms more than exoskeleton training alone, likely through cortical reorganization. Extended training may further consolidate these benefits, supporting BCI-exoskeleton integration as a promising rehabilitation strategy for SCI. ANN NEUROL 2026;99:1124–1138
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Longitudinal Trajectories of Brain Health Risk Factors Measured by the Brain Care Score and Risk of Stroke, Dementia, and Depression
Objective
Evidence linking modifiable risk factors to age-related brain diseases, such as dementia, stroke, and depression (DSD), is robust, yet limited regarding long-term change in modifiable risk factors in association with these conditions, particularly in real-world settings. This study aimed to assess whether longitudinal changes in modifiable brain health risk factors were associated with reduced risk of DSD.
Methods
We analyzed UK Biobank data (2006–2019) from 155,469 participants with general practitioner-linked data. The Brain Care Score (BCS) assesses 12 modifiable risk factors across lifestyle, physical, and social–emotional domains. Longitudinal BCS measurements were derived from repeated general practitioner (GP)-recorded measurements. Changes in the BCS were modeled using linear mixed-effects models, and associations with DSD were evaluated using multivariable Cox models, adjusting for baseline BCS and genetic risk (polygenic risk scores for stroke and depression, and APOE genotype for dementia).
Results
Among 155,469 participants (median age = 51 years, 54.3% women), the median annual BCS change was 0.14 (Q1–Q3 = 0.008–0.30) points over a median follow-up of 12.3 years (Q1–Q3 = 11.5–13.1 years). Over time, 82.1% improved their BCS, 12.9% remained stable, and 5.0% worsened over time. Each 1-point annual increase in the BCS was associated with 4% lower risk of incident age-related brain diseases (hazard ratio [HR] = 0.96, 95% confidence interval [CI] = 0.95–0.97).
Interpretation
In this large real-world cohort, improvements in modifiable risk factor profiles were associated with lower incidence of DSD, regardless of genetic risk or baseline BCS. Our results provide important information for communicating with patients about the brain health benefits of improving risk factor profiles. ANN NEUROL 2026;99:1113–1123
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Myelitis‐Predominant Aggressive Phenotype: Unveiling Unique Patterns of Late‐Onset Neuromyelitis Optica Spectrum Disorders
Objective
The objective of this study was to compare clinical features and prognosis of late-onset neuromyelitis optica spectrum disorder (LO-NMOSD, onset age ≥60 years) with adult-onset NMOSD (AO-NMOSD, onset age 18–59 years), and to provide insights for individualized management in elderly patients.
Methods
Data from 748 patients with NMOSD (diagnosed according to the 2015 International Panel for NMO Diagnosis criteria) in the China National Registry of Neuro-Inflammatory Diseases (CNRID) were analyzed. Patients were stratified into AO-NMOSD (18–59 years, n = 617) and LO-NMOSD (≥ 60 years, n = 131). Demographics, clinical manifestations, imaging, treatments, and outcomes were compared using appropriate statistical methods including Kaplan–Meier survival curves and Cox proportional hazards regression.
Results
LO-NMOSD showed distinct traits: a lower female predominance (76.34% vs 86.55%), higher transverse myelitis (TM) incidence at onset (57.36% vs 40.17%), elevated annualized relapse rate (ARR; 0.52 ± 0.03 vs 0.38 ± 0.01), and accelerated disability (median Expanded Disability Status Scale [EDSS] 4.75 vs 3.0). TM-predominant relapses (39 of 45, 86.67% in LO vs 96 of 148, 64.86% in AO) contributed significantly to disability. Kaplan–Meier analysis showed LO-NMOSD had a higher risk of relapse (hazard ratio [HR] = 1.932, 95% confidence interval [CI] = 1.427–2.615), disability (HR = 3.192, 95% CI = 1.932–5.274) and reaching visual acuity (VA) ≤20 of 30 (HR = 3.523, 95% CI = 1.585–7.828). Cox regression confirmed that onset age ≥60 years was an independent risk factor for relapse (HR = 2.05, 95% CI = 1.60–2.59), disability (HR = 3.16, 95% CI = 2.14–4.62), and reaching VA ≤20 of 30 (HR 3.26, 95% CI = 1.83–5.48).
Interpretation
LO-NMOSD is characterized by myelitis-predominance with recurrent spinal cord involvement, high risk of relapses, and severe disability. It thus underscores the need for heightened clinical attention, with rigorous monitoring that balance safety and efficacy for elderly patients with NMOSD. ANN NEUROL 2026;99:1139–1151
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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A Patient‐Derived Antibody Ameliorates Disease Severity in a Relapsing Remitting Murine Model of Multiple Sclerosis
Objective
Naturally occurring autoantibodies are commonly considered to be causative of autoimmune diseases or epiphenomena with no known biological impact. Although clinically beneficial autoantibodies have been described, there have been no naturally occurring anti-neuronal antibodies that have been found to be neuroprotective. Here, we identify a recombinant human antibody (TGM-010) derived from a patient with multiple sclerosis (MS) that binds human and mouse neurons, leading to beneficial effects.
Methods
TGM-010 was examined for its ability to be internalized by human and mouse neurons and protect neurons from death in vitro following a stress event. TGM-010 was also injected systemically into a relapsing–remitting model of experimental autoimmune encephalomyelitis (EAE) to examine its ability to impact disease score, extent of demyelination, and neuron frequency.
Results
TGM-010 demonstrates many novel characteristics including crossing the blood-brain barrier (BBB) and internalizing into neurons. TGM-010 also protects primary mouse neurons from death in vitro. In a mouse model of MS, TGM-010 ameliorates disease severity and is associated with improved neuronal survival.
Interpretation
This study identified a patient-derived neuron-binding autoantibody that crosses the BBB in mice and reduces neuron loss in a mouse model of MS. These data suggest that the human derived anti-neuronal antibody, TGM-010, may potentially be used to ameliorate neurodegeneration that underlies disability in neurodegenerative conditions. ANN NEUROL 2026;99:1152–1165
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Probabilistic Lesion Mapping to Optimize Thalamotomy Targets for Focal Hand Dystonia
Objective
Focal hand dystonia (FHD) severely impairs task-specific motor control, yet the optimal surgical target for stereotactic intervention remains uncertain. This study aimed to identify the precise thalamic lesion site associated with symptomatic improvement and to clarify its network connectivity.
Methods
We retrospectively analyzed 164 patients with FHD (mean age = 42.0 years, 26.2% women) who underwent stereotactic thalamotomy of the ventral lateral thalamus. Voxel-wise probabilistic lesion mapping was applied to relate lesion locations to clinical outcomes. Structural connectivity analyses assessed fiber tracts linked to the optimal lesion site. Model performance was evaluated by 10-fold cross-validation, validation in an out-of-sample cohort, and testing in reoperation cases.
Results
We identified that lesioning the border zone between the ventralis oralis posterior (Vop) and ventralis intermedius (Vim) nuclei was associated with improvement of FHD. The predictive model achieved high accuracy in cross-validation (area under the curve [AUC] = 0.836) and performed robustly in independent validation. Connectivity analyses showed that the Vop-Vim border zone was linked to cerebellothalamic and pallidothalamic afferents as well as thalamocortical projections to the supplementary motor area and premotor cortex. In contrast, lesions extending into the ventralis oralis anterior nucleus were associated with an increased risk of motor complications.
Interpretation
Precise targeting of the Vop-Vim border maximizes clinical benefit while minimizing adverse effects in FHD thalamotomy. These findings establish the first evidence-based thalamic target for FHD, offering practical guidance for stereotactic interventions and advancing understanding of dystonia pathophysiology. ANN NEUROL 2026;99:1227–1238
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Reframing the Risks of Deep Brain Stimulation: A Comparison of 2.8 Million Elective Surgeries From the NSQIP Database
Objective
Deep brain stimulation (DBS) is an established surgical therapy for movement disorders, epilepsy, and psychiatric conditions, yet remains underutilized due to perceived risks. We therefore endeavored to compare the safety of DBS to other common elective procedures to provide context for its relative risk.
Methods
This retrospective cohort study utilized the American College of Surgeons National Surgical Quality Improvement Program (NSQIP) database, encompassing diverse referral and community hospitals across the United States from 2015 to 2021. Patients with DBS were compared with those receiving one of the 16 most common elective procedures. The primary outcome of interest was the weighted odds of any postoperative complication at 30 days. Secondary outcomes included risk of readmission, reoperation, and discharge disposition. Logistic regression with inverse probability of treatment weighting (IPTW) based on propensity scores adjusted for baseline group heterogeneity.
Results
We identified 2,853,662 patients for analysis, including 4,749 DBS procedures. After IPTW adjustment, patients with DBS experienced lower 30-day complication rates compared with other procedures (1.3% vs 4.1%, OR = 0.32, 95% confidence interval [CI] = 0.25–0.41, p < 0.0001). Readmission rates did not differ significantly (2.2% vs 2.6%, OR = 0.84, 95% CI = 0.69–1.02, p = 0.08). DBS cases had higher odds of discharge home (98.7% vs 96.3%, OR = 2.94, 95% CI = 2.27–3.82, p < 0.0001) and lower reoperation rates (0.7% vs 1.3%, OR = 0.50, 95% CI = 0.35–0.72, p = 0.0002).
Interpretation
DBS demonstrates a favorable safety profile with substantially lower complication rates compared with the most widely performed elective surgeries. These findings support broader consideration of surgical referral for appropriate DBS candidates. ANN NEUROL 2026;99:1239–1250
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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DNase1 RS1053874 Polymorphism is Associated with Early Neurological Recovery through NET Modulation and with Long‐Term Survival in Ischemic Stroke: A Prospective Cohort Study
Objective
Immunothrombosis contributes to ischemic stroke pathophysiology through neutrophil extracellular trap (NET) formation, which promotes thrombus stabilization and microvascular dysfunction. DNase1 is the principal endonuclease responsible for NET degradation. The rs1053874 polymorphism in DNase1 gene influences enzymatic activity and protein stability in vitro, but its clinical relevance in ischemic stroke remains unexplored. We investigated whether this variant modulates systemic NET burden and impacts stroke-related outcomes.
Methods
We conducted a prospective observational cohort study including 492 patients with acute ischemic stroke. Genotyping of rs1053874 was performed via Sanger sequencing and categorized into AA versus GG + GA genotypes (dominant model). Clinical variables, NET biomarkers (elastase, myeloperoxidase [MPO], and dsDNA), DNAse1 activity, infarct volume, thrombectomy metrics, and survival were assessed. Multivariable regression and Cox proportional hazards models were used to explore associations between genotype and outcomes.
Results
AA genotype carriers (7.9%) had a significantly lower burden of prior vascular events compared to GG + GA carriers. At admission, they exhibited higher DNAse1 activity, reduced levels of circulating NET markers (elastase, MPO, and dsDNA), and lower neutrophil and monocyte counts. Despite similar initial stroke severity, AA carriers required fewer thrombectomy passes and had significantly better early neurological recovery and smaller infarcts. In adjusted models, both the AA genotype and dyslipidemia were independently associated with improved long-term survival. However, stratified analyses revealed the most robust survival benefit among AA carriers without dyslipidemia. No significant interaction was observed.
Interpretation
DNase1 rs1053874 polymorphism influences NET-related inflammation and is associated with improved vascular profile, procedural efficiency, and long-term outcomes in ischemic stroke. These findings support the potential of DNase1 as a therapeutic and prognostic target in personalized stroke care. ANN NEUROL 2026;99:1210–1223
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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The Clinical Spectrum and Neurodevelopmental Pathogenesis of KPTN‐Related Disorder in a Mouse Model
Objective
Pathogenic variants in Kaptin (KPTN) cause KPTN-related disorder (KRD). KPTN modulates mTOR signaling activation within the KICSTOR complex in response to cellular amino acid levels. We define the clinical spectrum and investigate the developmental pathogenesis of KRD.
Methods
We report the genotype and clinical phenotype of 71 KRD individuals (28 female subjects, ages 1 to 55 years) including 48 newly identified KRD individuals. The effects of Kptn knockout on brain development were assayed in vitro and in vivo.
Results
We defined 15 novel KPTN variants. Intellectual disability (ID) was identified in all KRD individuals. Macrocephaly and epilepsy were observed in 46% and 47%, respectively. Neuroimaging revealed megalencephaly but no overt structural abnormalities. Ketotic hypoglycemia and endocrinopathies were identified in KRD. Increased head size was detected in unaffected parents heterozygous for KPTN variants. Two KRD individuals with drug-resistant epilepsy were treated with the mTOR inhibitor sirolimus but did not exhibit improved seizure control. CRISPR/Cas9 Kptn knockout in vitro induced mTOR activation and an mTOR-dependent increase in cell size. Kptn−/− mice exhibited increased cortical mTOR signaling that was reduced by rapamycin. Heterotopic neurons were identified in the subcortical white matter in the Kptn −/− mouse. Focal CRISPR/Cas9 Kptn knockout in cortex via in utero electroporation resulted in white matter heterotopic neurons. Electroencephalogram (EEG) did not detect ictal or inter-ictal abnormalities.
Interpretation
KRD is a multisystem neurodevelopmental disorder associated with ID, macrocephaly, epilepsy, mTOR signaling hyperactivation, and in a mouse model, subtle structural alterations in cerebral cortical cytoarchitecture. ANN NEUROL 2026;99:1287–1302
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Clot Composition Profiling in Large Vessel Occlusion Stroke Via Radiomics
Objective
Clot composition may offer insights into the mechanism of ischemic stroke. Radiomics, a noninvasive imaging technique, enables tissue characterization through radiomic features (RFs). We aimed to evaluate clot composition using radiomics on non-contrast computed tomography (NCCT).
Methods
In the first phase, we conducted a prospective study comparing RFs with histopathology in thrombi retrieved via mechanical thrombectomy (MT). Thrombi were imaged using micro-computed tomography (micro-CT) and analyzed histologically. Matched micro-CT and histological slices identified red blood cells (RBCs) and fibrin-rich regions. RFs were extracted, and multivariate logistic regression identified features associated with each component. Spearman's correlation was used to assess associations between RFs and percentage composition. The same clots were localized on pre-MT NCCT, and RFs were extracted. Micro-CT and NCCT RFs were correlated to enable histology-informed interpretation. Receiver operating characteristic analysis evaluated the ability of NCCT RFs to discriminate clot composition. In the second phase, radiomics was applied to a retrospective NCCT dataset from patients with ischemic stroke with varying etiologies.
Results
Ten thrombi were analyzed using micro-CT. Total energy (odds ratio [OR] = 1.35, 95% confidence interval [CI] = 1.20–1.54, p < 0.001) and large dependence high gray level emphasis (OR = 1.18, 95% CI = 1.07–1.32, p = 0.01) were associated with RBCs and correlated with >70% RBCs composition on NCCT (Rho = 0.752 and Rho = 0.815). Subsequently, 150 NCCT scans were analyzed, including 50 cardioembolic, 50 large artery atherosclerosis (LAA), and 50 cryptogenic strokes. Radiomic analysis indicated RBCs-predominant composition in 72% of cardioembolic, 30% of LAA, and 50% of cryptogenic clots.
Interpretation
Radiomics is a promising, noninvasive technique for characterizing clot composition. ANN NEUROL 2026;99:1179–1188
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Enhanced Sensitivity of a Modified Quaking‐Induced Conversion Diagnostic Test for the Broad Detection of Sporadic and Inherited Prion Diseases: A Retrospective Study
Objective
Quaking-induced conversion (QuIC) tests, which detect prion-seeding activity in cerebrospinal fluid (CSF), have markedly advanced the antemortem diagnosis of prion diseases such as Creutzfeldt-Jakob disease (CJD). These tests provide high diagnostic accuracy and enable timely differentiation from other rapidly progressive neurodegenerative disorders. However, a key limitation of current QuIC tests are the reduced sensitivity in detecting inherited prion diseases and rare sporadic subtypes, including variably protease-sensitive prionopathy (VPSPr). To address this gap, we evaluated a simplified QuIC test, end-point QuIC (EP-QuIC), incorporating a novel recombinant prion protein substrate derived from the North American deer mouse (Peromyscus maniculatus).
Methods
The diagnostic performance of the modified QuIC test was evaluated using CSF samples from 61 sporadic CJD, 50 inherited prion disease, and 5 VPSPr cases.
Results
EP-QuIC with the deer mouse substrate achieved 96.6% sensitivity (111/116) and 100% specificity (35/35), outperforming both standard EP-QuIC (87.1%) and next-generation (IQ-CSF) real-time-QuIC (72.4%) across the same cohort. Notably, this enhanced assay detected inherited mutations, such as D178N, that were previously undetectable with existing diagnostic tests.
Interpretation
These findings demonstrate that adapting EP-QuIC with an optimized substrate, termed enhanced sensitivity QuIC (ES-QuIC), significantly improves diagnostic performance for inherited and atypical prion diseases. By expanding the diagnostic reach of QuIC tests, this study strengthens antemortem surveillance, reduces reliance on postmortem confirmation, and improves opportunities for early intervention and clinical trial enrollment, particularly for genetic cases most likely to benefit from emerging therapeutic strategies. ANN NEUROL 2026;99:1303–1314
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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When Does Alzheimer's Disease Start? Plasma Aβ42/40 Assays Show Steep Changes at Aβ‐PET Centiloid 15, Mean Age of 66 Years
Objective
Sporadic late-onset Alzheimer's disease (AD) is characterized by a long pre-clinical phase where amyloid-beta (Aβ) and tau begin to accumulate in the brain. The primary objective was to determine the age at which AD starts by finding the average population age when both positron emission tomography (PET) Aβ (Aβ-PET) and plasma Aβ42/40 become abnormal.
Methods
Two high performance immunoprecipitation-mass spectrometry (IP-MS) assays (WashU/C2N and Shimadzu) were tested on samples from 1,450 participants who were diagnosed as cognitively unimpaired (CU), mild cognitive impairment (MCI), or AD-dementia across 4 international cohorts. Natural history modeling and trajectory analyses of the combined Aβ-PET and plasma Aβ42/40 data were analyzed.
Results
Data from both assays demonstrated Aβ42/40 undergoes a rapid change at approximately 15 Centiloid (CL), at an average population disease age at 66 years. On average, plasma Aβ42/40 becomes abnormal approximately 2 years before Aβ-PET, whereby it falls sharply to a stable level at the onset of preclinical AD. Average disease age where Aβ42/40 becomes abnormal, and the corresponding Centiloid level are lower for APOE allele carriers compared with non-carriers.
Interpretation
Plasma Aβ42/40 ratio presents a step-like function of peripheral change shortly before the detection of plaques by Aβ-PET. Results are consistent with plasma Aβ42/40 falling to a steady-state level in participants with Aβ-PET levels greater than approximately 14CL for both assays. The age at which this occurs is dependent on APOE ε4 carriership, consistent with the approximate 7-year age difference in Centiloid abnormality between carriers and non-carriers. ANN NEUROL 2026;99:1327–1342
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Severe, Non‐apneic Respiratory Dysfunction and Hypoxia following Generalized Convulsive Seizures
Objective
Sudden unexpected death in epilepsy (SUDEP) is a devastating consequence of some generalized convulsive seizures (GCS). Recent work has focused on seizure related apnea as a biomarker of SUDEP risk, frequently without characterizing the adequacy of non-apneic ventilation or identifying other dysfunctional breathing patterns. We hypothesized that GCS frequently induce immediate, severe, non-apneic respiratory dysfunction that can induce critical hypoxia and bradycardia and sought to characterize breathing patterns after GCS.
Methods
Adult patients admitted to an epilepsy monitoring unit were studied. The effects of GCS on breathing and heart rate were analyzed using nasal pressure transducers, chest and abdominal respiratory inductance plethysmography, capillary oxygen saturation, transcutaneous CO2, electrocardiogram, electroencephalogram, and expert audiovisual analysis. Correlation analyses, the Mann–Whitney test, and an unpaired t test were used to analyze relationships between dysfunctional breathing patterns and both the severity of postictal hypoxemia and the heart rate.
Results
Thirty-two GCS from 22 patients were analyzed and 31 exhibited 1 or more of the following breathing patterns: disordered rhythmicity (n = 28/32, 87.5%), shallow breathing (n = 12/32, 37.5%), thoracoabdominal asynchrony (n = 24/30, 80.0%), and upper airway obstruction (n = 30/32, 93.8%). Oxygen desaturation was more severe when postictal breathing was shallow or irregular in amplitude. The latter was associated with absolute or relative bradycardia.
Interpretation
Nonfatal GCS frequently induce immediate, severe, non-apneic respiratory dysfunction temporally associated with severe hypoxia and bradycardia. Our study suggests that postictal respiratory and cardiac function are tightly coupled and highlights the importance of including all the relevant pathologic variables in studies of SUDEP pathogenesis. ANN NEUROL 2026;99:1263–1276
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Tau Pathology in Alzheimer's Disease Uniquely Affects Sulcal Depths
Objective
Though it is widely known that tau deposition affects brain structure, the precise localization of these effects is poorly understood, especially in relation to gyral and sulcal anatomy. We investigated whether tau pathology in Alzheimer's disease (AD) preferentially affects sulci, and particularly sulcal depths.
Methods
We analyzed 675 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with magnetic resonance imaging (MRI) and positron emission tomography (PET) data to investigate relationships between neocortical tau PET signal and cortical thickness. We then examined an advanced AD case with postmortem MRI and coregistered whole-brain phospho-tau staining for evidence of sulcal tau distribution in AD. Finally, in a sample of 187 cognitively unimpaired young and older adults with resting-state functional MRI, we examined connectivity strength between tau-vulnerable regions and the hippocampus across adulthood, prior to disease-related cognitive decline.
Results
Our findings revealed that tau-related cortical thinning predominantly occurs in sulcal regions, especially the deepest parts. Postmortem histology confirmed preferential tau accumulation in sulcal depths. Additionally, connectivity analyses revealed that, across adulthood, these primarily sulcal regions most susceptible to tau-related thinning also have stronger connectivity to the hippocampus, suggesting a role for network connectivity in the vulnerability of sulci to the effects of tau pathology later in life.
Interpretation
These findings support the hypothesis that sulci, and particularly their depths, represent structurally and functionally vulnerable regions for tau deposition in AD. Understanding the mechanisms underlying this sulcal vulnerability provides insight into general principles driving regional susceptibility to pathology, and sheds light on the detrimental functional and cognitive effects of tau pathology. ANN NEUROL 2026;99:1343–1353
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Individualized Atrophy‐Based Prediction of Dementia Progression in Familial Frontotemporal Lobar Degeneration With Bayesian Linear Mixed‐Effects Modeling
Objective
Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f-FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f-FTLD. We used a Bayesian linear mixed-effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia.
Methods
Participants included 234 asymptomatic or prodromal carriers of C9orf72, GRN, or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1-weighted scans. The BLME models established individual voxel-wise gray matter trajectories using the first 2 scans. Person-specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time-varying Cox proportional hazard models covarying for age. Receiver-operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months.
Results
The BLME cluster volume predicted conversion to dementia in f-FTLD mutation carriers overall and separately in C9orf72, GRN, and MAPT, with comparable hazard ratios observed for atrophy W-maps and regional volumes. Within a 24-month timeframe, BLME cluster volume discriminated dementia converters from non-converters with larger areas under the curve (AUCs) than other approaches.
Interpretation
Bayesian-modeled individualized atrophy scores predict dementia progression among asymptomatic f-FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Individualized Treatment in Distal and Medium Vessel Occlusion Stroke Using a Validated Explainable Counterfactual Treatment Estimation Model
Objective
The optimal treatment for distal medium vessel occlusion (DMVO) stroke remains uncertain, and evidence comparing endovascular therapy (EVT) with medical management (MM) is limited. We aimed to develop and validate a predictive modeling tool to assess individual treatment benefit in DMVO stroke using explainable counterfactual treatment estimation.
Methods
Adults with isolated DMVO stroke (M3–M4, A2–A3, or P1–P2) were retrospectively identified from 7 stroke centers. To estimate individualized probabilities of favorable outcome (modified Rankin Scale [mRS] = 0–2 at 90 days), we developed a Penalized Logistic Regression (Elastic Net) model. This framework was selected a priori over other explored machine learning algorithms (Decision Tree, Support Vector Classifier, and XGBoost) for its superior interpretability and ability to handle multicollinearity among interaction terms. Inverse Probability of Treatment Weighting (IPTW) was implemented to address confounding by indication in the observational data. Internal validation used repeated K-fold cross-validation and bootstrapping; external validation was performed on an independent cohort (n = 86).
Results
Of 321 eligible patients, 179 received EVT (55.8%) and 142 received MM (44.2%). Adjusted models showed no significant overall group differences in favorable outcome (adjusted OR [aOR] = 1.32, 95% confidence interval [CI] = 0.97–1.80), mortality (aOR = 1.20, 95% CI = 0.78–1.85), or symptomatic hemorrhage (aOR = 0.57, 95% CI = 0.21–1.58). However, the model identified significant treatment effect heterogeneity; EVT benefit was amplified in patients with higher National Institutes of Health Stroke Scale (NIHSS) and attenuated with increasing treatment delay. Internal validation demonstrated strong performance (area under the receiver operating characteristic curve [AUC] = 0.77, 95% CI = 0.71–0.82). External validation confirmed generalizability (AUC = 0.74, 95% CI = 0.63–0.84). Individualized treatment estimates showed high concordance with a benchmark causal T-Learner model (Pearson r = 0.97 internal and r = 0.98 external).
Interpretation
Although aggregate outcomes did not differ significantly, the validated Distal and Medium Vessel Occlusion Stroke (DUSK) Tool enables individualized estimation of EVT benefit in DMVO stroke. This explainable counterfactual treatment estimation framework supports precision decision making by identifying specific patient subgroups most likely to benefit from EVT over MM. ANN NEUROL 2026;99:1198–1209
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Diverse Genetic Etiologies of Unilateral Polymicrogyria
Objective
Polymicrogyria (PMG) is one of the most common human malformations of cortical development and is often classified by its radiographic pattern of distribution. Unilateral polymicrogyria (uPMG) is a subtype of PMG affecting a portion or all of one cerebral hemisphere. As most PMGs occur bilaterally, there has been no specific investigation as to whether the genetic underpinnings of uPMG comprise a subset of or a distinct entity from bilateral PMG. In this study, our goal was to assess both the genetic etiology of uPMG and the value of diagnostic genetic testing in this setting.
Methods
We conducted a retrospective analysis of clinical data from individuals with uPMG seen in the Brain Development and Genetics Clinic and/or research participants of the Walsh Laboratory at Boston Children's Hospital. The final study cohort included 35 individuals from 30 families who were diagnosed with uPMG on brain magnetic resonance imaging (MRI) and also underwent genetic testing.
Results
A likely genetic cause was identified in 26.7% (8/30) of unrelated individuals with uPMG in this cohort and segregated within one family (10/35 total subjects). Recessive genetic causes included ASPM, WDR62, and TMEM216. Dominant causes included 22q deletion syndrome, DYNC1H1, SCN3A, and hereditary hemorrhagic telangiectasia (HHT) genes, ACVRL1 and ENG. This is the first report of variants in DYNC1H1, TMEM216, and ACVRL1 in association with uPMG.
Interpretation
The genetic causes of bilateral PMG and uPMG can overlap, but some are unique to certain distributions of the malformation. Genetic explanations for uPMG are found at comparable rates to bilateral PMG, suggesting that germline testing for this unique presentation is warranted. ANN NEUROL 2026;99:1277–1286
in Annals of Neurology on 2026-04-20 04:45:35 UTC.
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Dissociable Mechanisms Underlie Differences Between Memory and Metamemory in Older Adults: The Differentiating Role of Anxiety and Depression Symptoms
ABSTRACT
The ability to remember (i.e., memory ability) and to accurately discern memory function (i.e., metamemory) are both important facets of cognition. In the present study, we examined the shared and distinct sources of variance across memory ability and metamemory using psychometrically validated measures of memory ability, metamemory, and anxiety and depression symptoms in conjunction with multimodal imaging (i.e., structural MRI, tau PET) in a sample of cognitively normal older adults (N = 72). Replicating a growing body of work, we found that metamemory was more tightly linked to anxiety and depression symptoms relative to objective measures of memory ability. Our results also revealed that the hippocampus was a critical locus of both memory ability and metamemory—hippocampal volume was positively associated with memory ability, but not metamemory, whereas increased hippocampal tau pathology exacerbated the negative effect of anxiety and depression symptoms on metamemory. Importantly, we also found that after controlling for anxiety and depression symptoms and tau burden, there was a positive association between memory ability and metamemory. Our findings also demonstrated the importance of assessing different facets of metamemory; self-reported memory contentment and ability, but not strategy use, showed the strongest relationships with both anxiety and depression symptoms and hippocampal tau burden. Together, these results suggest that both shared and distinct mechanisms underlie memory ability and metamemory processes in older adults. Chiefly, this work highlights the potential of metamemory measures as sensitive tools to understand affective processes that occur in both healthy and pathological aging, independent of memory ability.
in Hippocampus on 2026-04-20 04:11:36 UTC.
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The Dentate Gyrus Grows Throughout Life Despite Turnover of Developmentally‐Born Neurons
ABSTRACT
Adult-born hippocampal neurons are highly plastic but there remains uncertainty about the magnitude of neurogenesis and its long-term functional consequences. Theoretical predictions indicate that adult neurogenesis should lead to substantial growth of the dentate gyrus (DG) granule cell population. However, in practice, most studies find no changes in total cell number across adulthood. This discrepancy may partly be a sensitivity issue, where small sample sizes and the examination of older age windows (when neurogenesis is reduced) have prevented detection. However, neurogenic growth could also be masked by the turnover of developmentally-born DG neurons, which are known to die off in normal aging. To address the question of how neuronal birth and loss impacts DG population dynamics, here we quantified numbers of developmentally-born neurons, proliferating Ki67+ cells (as a proxy for adult-born neurons), and total DG neurons from 2–18 months of age in the rat. We estimate that over this timeframe 670,000 adult-born neurons are added (30% of the total population). Consistent with neurogenic growth, the total number of DG neurons increased across adulthood. However, net growth was only 385,000 cells, which is less than predicted by adult neurogenesis alone. Indeed, 20% of developmentally-born neurons were lost over the same interval, and so we propose that the difference is explained by neuronal turnover. Neuronal persistence and turnover may be relevant for theories of hippocampal long-term memory, as well as for understanding psychiatric conditions that are characterized by hippocampal plasticity and atrophy.
in Hippocampus on 2026-04-20 04:09:34 UTC.
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Dentate gyrus interneurons modulate winner-take-all network dynamics in freely behaving mice
Hainmueller, Heynold, et al. studied the activity and synaptic interactions of different excitatory and inhibitory neuron types in the dentate gyrus of freely behaving mice. Bidirectional optogenetic manipulations revealed roles for interneurons in selecting cell assemblies through winner-take-all dynamics that go beyond simple circuit suppression.in Neuron: In press on 2026-04-20 00:00:00 UTC.
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Astrocyte cell volume dynamics across cortical states and transitions
Deng et al. used in vivo two-photon imaging to characterize sleep-wake-dependent changes in astrocyte volume. Using chemogenetic and optogenetic activation of locus coeruleus tyrosine hydroxylase-positive neurons, they show that norepinephrine drives these volume changes, in part via α1-adrenergic receptors.in Neuron: In press on 2026-04-20 00:00:00 UTC.
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Connecting dots: Ligand-dependent allostery from protein interaction to gene regulation
Biomolecular function emerges from dynamic conformational landscapes and allosteric regulation within modular, multicomponent assemblies. Genome-wide analysis of RARα:RXR shows how ligand-dependent allostery reshapes chromatin targeting and gene networks, highlighting opportunities to tune signaling pathways and design next-generation therapeutics.in Cell Reports: Current Issue on 2026-04-20 00:00:00 UTC.
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‘Bat feast’ animal videos at African cave offer clues to how deadly viruses spread
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01259-4
Researchers filmed 10 species eating or scavenging bats at known Marburg-virus hotspot — and caught hundreds of humans visiting.in Nature on 2026-04-20 00:00:00 UTC.
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No humans allowed: scientific AI agents get their own social network
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01278-1
Autonomous agents aren’t just creating their own research — on the Reddit-style website Agent4Science, they’re chatting about it, too.in Nature on 2026-04-20 00:00:00 UTC.
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Got bugs? Here’s how to catch the errors in your scientific software
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01261-w
Computer scientists share their advice for ensuring that your scientific software does what it’s supposed to do.in Nature on 2026-04-20 00:00:00 UTC.
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A step-by-step guide to nailing your tenure promotion package
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-00990-2
It’s an important milestone in many academic careers, yet the tenure process is surprisingly nebulous. Here’s what it takes to succeed.in Nature on 2026-04-20 00:00:00 UTC.
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Thrilling, frivolous, a waste: not everyone’s happy about the Artemis II Moon mission
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01262-9
Thrilling, frivolous, a waste: not everyone’s happy about the Artemis II Moon missionin Nature on 2026-04-20 00:00:00 UTC.
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What does the future hold for the thawing Arctic?
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01258-5
Two experts unpack how trends in climate and geopolitics might unfold to shape the far north.in Nature on 2026-04-20 00:00:00 UTC.
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How hidden contributions power modern research
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01260-x
The people who work behind the scenes to keep research moving say that there should be more recognition for their roles.in Nature on 2026-04-20 00:00:00 UTC.
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Daily briefing: Immune cells have a surprising role in exercise endurance
Nature, Published online: 20 April 2026; doi:10.1038/d41586-026-01291-4
B cells seem to provide crucial support for muscles during exercise in mice. Plus, the winners of this year’s Breakthrough Prizes and the best ways to debug your scientific software.in Nature on 2026-04-20 00:00:00 UTC.
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Strong ultrafast nonlinear optical response from megaelectronvolt electrons in semiconductors
Nature Photonics, Published online: 20 April 2026; doi:10.1038/s41566-026-01894-3
Nonlinear optical responses of semiconductors induced by 150-fs and 4.2-MeV electron pulses are investigated. Sub-10-ps bandgap modulations with intensities up to 24.5% are observed near the bandgap and are explained by the band-filling effect and bandgap renormalization.in Nature Photomics on 2026-04-20 00:00:00 UTC.
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Optical excitations reshape the spin-wave spectrum in antiferromagnets
Nature Physics, Published online: 20 April 2026; doi:10.1038/s41567-026-03231-5
Charge-transfer excitations, which define the optical bandgap in many insulators, also contribute to magnetic exchange in antiferromagnets. Femtosecond optical pumping of these transitions in canted antiferromagnet DyFeO3 reshapes the spin-wave spectrum — the set of collective spin excitations that define the dynamics of the antiferromagnet — without destroying the long-range order.in Nature Physics on 2026-04-20 00:00:00 UTC.
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Average topological phase in a disordered Rydberg atom array
Nature Physics, Published online: 20 April 2026; doi:10.1038/s41567-026-03271-x
In addition to strongly protected topological phases that rely on exact symmetries, theory predicts that disorder can stabilize weakly protected phases in mixed quantum states, and an example of the latter is now observed in a Rydberg atom array.in Nature Physics on 2026-04-20 00:00:00 UTC.
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Transverse optical torque observed at the nanoscale
Nature Physics, Published online: 20 April 2026; doi:10.1038/s41567-026-03268-6
Optical forces and torques on nanoparticles are difficult to measure due to the diffraction limit of light. Now, transverse optical torque is observed through the optical trapping and spatial tracking of a designed microscale structure.in Nature Physics on 2026-04-20 00:00:00 UTC.
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How individual vigor shapes human–human physical interaction
The speed of voluntary movements varies systematically, with some individuals moving consistently faster than others across different actions. These variations, conceptualized as vigor, reflect a time–effort–accuracy tradeoff in motor planning. How do two mechanically coupled partners with different individual vigors collaborate, e.g. to move a table together? Here, we show that such dyads coordinate goal-directed movements with minimal interaction force, exhibiting a dyadic vigor with similar characteristics as individual vigor. The emerging dyadic motor plan is strongly influenced by the slower partner, whose vigor predicts dyadic vigor, with effects lasting beyond practice. Computational modeling with stochastic optimal control reveals the critical role of partners’ movement timing uncertainty and vigor in shaping coordination, allowing us to predict dyadic movements from individual behavior across diverse conditions. These findings shed light on the mechanisms underlying human collaboration and may be used in applications ranging from physical training and rehabilitation to collaborative robotics for manufacturing.in eLife on 2026-04-20 00:00:00 UTC.
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Dimorphic neural network architecture prioritizes sexual-related behaviors in male Caenorhabditis elegans
Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on the neural network architectures of male and hermaphrodite Caenorhabditis elegans and the association with sexually dimorphic behaviors. We applied graph theory and computational neuroscience methods to systematically discern the features of these two neural networks. Our findings revealed that a small percentage of sexual-specific neurons exerted dominance throughout the entire male neural network, suggesting males prioritized sexual-related behavior outputs. Based on the structural and dynamical characteristics of two complete neural networks, sub-networks containing sex-specific neurons and their immediate neighbors, or sub-networks exclusively comprising sex-shared neurons, we predicted dimorphic behavioral outcomes for males and hermaphrodites. To verify the prediction, we performed behavioral and calcium imaging experiments and dissected a circuit that is specific for the increased spontaneous local search in males for mate-searching. Our research sheds light on the neural circuits that underlie sexually dimorphic behaviors in C. elegans and provides significant insights into the interconnected relationship between network architecture and functional outcomes at the whole-brain level.in eLife on 2026-04-20 00:00:00 UTC.
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Alpha-band phase modulates perceptual sensitivity by changing internal noise and sensory tuning
Alpha-band neural oscillations (8–13 Hz) are theorized to phasically inhibit visual processing based, in part, on results showing that pre-stimulus alpha phase predicts detection (i.e., hit rates). However, recent failures to replicate and a lack of a mechanistic understanding regarding how alpha impacts detection have called this theory into question. We recorded EEG while six observers (6020 trials each) detected near-threshold Gabor targets embedded in noise. Using signal detection theory (SDT) and reverse correlation, we observed an effect of occipital and frontal pre-stimulus alpha phase on sensitivity (d'), not criterion. Hit and false alarm rates were counterphased, consistent with a reduction in internal noise during optimal alpha phases. Perceptual reports were also more consistent when two identical stimuli were presented during the optimal phase, suggesting a decrease in internal noise rather than signal amplification. Classification images revealed sharper spatial frequency and orientation tuning during the optimal alpha phase, implying that alpha phase shapes sensitivity by modulating sensory tuning towards relevant stimulus features.in eLife on 2026-04-20 00:00:00 UTC.
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