Planet Neuroscience

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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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MLE-Toolbox: An Open-Source Toolbox for Comprehensive EEG and MEG Data Analysis
arXiv:2604.16463v1 Announce Type: new Abstract: MLE-Toolbox is a comprehensive open-source MATLAB toolbox for end-to-end analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data. Inspired by widely used neuroimaging platforms such as Brainstorm and FieldTrip, it integrates the full analysis pipeline within a unified and user-friendly graphical interface (GUI), covering raw data import, preprocessing, source localization, functional connectivity, oscillatory analysis, and machine learning-based classification. The toolbox includes automated artifact rejection methods, including independent component analysis (ICA), signal-space projection (SSP), and signal-space separation (SSS); multiple source localization approaches, including minimum norm estimation (MNE), dynamic statistical parametric mapping (dSPM), standardized low-resolution brain electromagnetic tomography (sLORETA), and beamforming; multi-atlas parcellation with anatomical visualization; spectral power analysis with frequency-band brain mapping; phase-amplitude coupling (PAC); graph-theoretic brain network analysis; and integrated machine learning and deep learning classifiers. MLE-Toolbox also provides native interoperability with Brainstorm, FieldTrip, EEGLAB, and FreeSurfer, allowing researchers to build on established workflows while benefiting from additional automation, interactive visualization, and one-click academic report generation. Freely available for non-commercial use, MLE-Toolbox is designed to lower the barrier to rigorous, reproducible MEG/EEG research.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Causality as a Minimum Energy Principle
arXiv:2604.17151v1 Announce Type: new Abstract: Classical causal models, such as Granger causality and structural equation modeling, are largely restricted to acyclic interactions and struggle to represent cyclic and higher-order dynamics in complex networks. We introduce a causal framework grounded in a variational principle, interpreting causality as directional energy flow from high- to low-energy states along network connections. Using Hodge theory, network flows are decomposed into dissipative components and a persistent harmonic component that captures stable cyclic interactions. Applied to resting-state fMRI connectivity, our variational framework reveals robust cyclic causal patterns that are not detected by conventional causal models, highlighting the value of variational principles for causality.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Poisson Flow Model of Cortical Folding Pattern
arXiv:2604.17291v1 Announce Type: new Abstract: Cortical folding reflects coordinated neurodevelopmental processes and provides a sensitive marker of neurological disease. In juvenile myoclonic epilepsy (JME), structural abnormalities are subtle and spatially distributed, limiting the sensitivity of conventional morphometric measures such as cortical thickness. We introduce a Poisson flow model derived from gradients of the mean curvature field on the cortical surface. The method yields a smooth scalar field obtained from a Poisson equation, whose surface gradient defines a flow representation of folding organization. This representation enables spatially coherent characterization of sulcal--gyral patterns and provides a principled geometric framework for studying distributed cortical alterations in JME.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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The Umwelt Representation Hypothesis: Rethinking Universality
arXiv:2604.17960v1 Announce Type: new Abstract: Recent studies reveal striking representational alignment between artificial neural networks (ANNs) and biological brains, leading to proposals that all sufficiently capable systems converge on universal representations of reality. Here, we argue that this claim of Universality is premature. We introduce the Umwelt Representation Hypothesis (URH), proposing that alignment arises not from convergence toward a single global optimum, but from overlap in ecological constraints under which systems develop. We review empirical evidence showing that representational differences between species, individuals, and ANNs are systematic and adaptive, which is difficult to reconcile with Universality. Finally, we reframe ANN model comparison as a method for mapping clusters of alignment in ecological constraint space rather than searching for a single optimal world model.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Support Sufficiency as Consequence-Sensitive Compression in Belief Arbitration
arXiv:2604.16434v1 Announce Type: cross Abstract: When a system commits to a hypothesis, much of the evidential structure behind that commitment is lost to compression. Standard accounts assume that selected content and scalar confidence suffice for downstream control. This paper argues that they do not, and that determining what must survive compression is itself a consequence-sensitive problem. We develop a recurrent arbitration architecture in which active constraint fields jointly determine a hypothesis geometry over candidates. Rather than carrying that geometry forward in full, the system compresses it into a support-aware control state whose resolution is regulated by current consequence geometry, arbitration memory, and resource constraints. A bounded objective formalizes the tradeoff. Too little retained support collapses policy-relevant distinctions, producing controllers that select content adequately while misrouting verification, abstention, and recovery. Too much retained support fragments learning across overly fine contexts, degrading adaptation even as discrimination improves. These failure modes yield ordered controller predictions confirmed by a minimal repeated-interaction simulation. Adaptive controllers that regulate support resolution outperform all fixed-resolution controllers in cumulative utility. Agile adaptive control outperforms sluggish adaptive control. Fixed high-resolution control achieves the best commitment accuracy but still trails adaptive controllers because resource cost and learning fragmentation offset the gains from richer retention. Support sufficiency should be understood not as a static representational threshold, but as a dynamic compression criterion. Robust arbitration depends on preserving the smallest support structure adequate for policy under the current consequence landscape, and on regulating that structure as conditions change across repeated cycles of inference and action.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Timescale Limits of Linear-Threshold Networks
arXiv:2604.16710v1 Announce Type: cross Abstract: Linear-threshold networks (LTNs) capture the mesoscale behavior of interacting populations of neurons and are of particular interest to control theorists due to their dynamical richness and relative ease of analysis. The aim of this paper is to advance the study of global asymptotic stability in LTNs with asymmetric neural interactions and heterogeneous dissipation under the structural Lyapunov diagonal stability (LDS) condition. To this end, we introduce a one-parameter family of LTNs that preserves the LDS condition and has a parameter-independent equilibrium set. In the fast limit, this family converges to a projected dynamical system (PDS), while in the slow limit, it converges to a discontinuous hard-selector system (HSS). Under LDS, we prove that the fast PDS limit is globally exponentially stable and that the HSS limit is globally asymptotically stable. This alignment suggests that the limiting systems capture essential mechanisms governing stability across the entire LTN family. Together with numerical evidence, these findings indicate that resolving stability at the fast and slow endpoints provides a promising and structurally grounded path toward establishing global stability for LTNs with biologically plausible recurrence and diagonal dissipation.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Untrained CNNs Match Backpropagation at V1: A Systematic RSA Comparison of Four Learning Rules Against Human fMRI
arXiv:2604.16875v1 Announce Type: cross Abstract: A central question in computational neuroscience is whether the learning rule used to train a neural network determines how well its internal representations align with those of the human visual cortex. We present a systematic comparison of four learning rules -- backpropagation (BP), feedback alignment (FA), predictive coding (PC), and spike-timing-dependent plasticity (STDP) -- applied to identical convolutional architectures and evaluated against human fMRI data from the THINGS-fMRI dataset (720 stimuli, 3 subjects) using Representational Similarity Analysis (RSA). Crucially, we include an untrained random-weights baseline that reveals the dominant role of architecture. We find that early visual alignment (V1/V2) is primarily architecture-driven: an untrained CNN achieves rho = 0.071, statistically indistinguishable from BP (rho = 0.072, p = 0.43). Learning rules only differentiate at higher visual areas: BP dominates at LOC/IT, and PC with local Hebbian updates achieves IT alignment statistically indistinguishable from BP (p = 0.18). FA consistently impairs representations below the random baseline at V1. Partial RSA confirms all effects survive pixel-similarity control. These results demonstrate that the relationship between learning rules and cortical alignment is region-specific: architecture determines early alignment, while supervised objectives drive late alignment.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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How Much Data is Enough? The Zeta Law of Discoverability in Biomedical Data, featuring the enigmatic Riemann zeta function
arXiv:2604.17581v1 Announce Type: cross Abstract: How much data is enough to make a scientific discovery? As biomedical datasets scale to millions of samples and AI models grow in capacity, progress increasingly depends on predicting when additional data will substantially improve performance. In practice, model development often relies on empirical scaling curves measured across architectures, modalities, and dataset sizes, with limited theoretical guidance on when performance should improve, saturate, or exhibit cross-over behavior. We propose a scaling-law framework for cross-modal discoverability based on spectral structure of data covariance operators, task-aligned signal projections, and learned representations. Many performance metrics, including AUC, can be expressed in terms of cumulative signal-to-noise energy accumulated across identifiable spectral modes of an encoder and cross-modal operator. Under mild assumptions, this accumulation follows a zeta-like scaling law governed by power-law decay of covariance spectra and aligned signal energy, leading naturally to the appearance of the Riemann zeta function. Representation learning methods such as sparse models, low-rank embeddings, and multimodal contrastive objectives improve sample efficiency by concentrating useful signal into earlier stable modes, effectively steepening spectral decay and shifting scaling curves. The framework predicts cross-over regimes in which simpler models perform best at small sample sizes, while higher-capacity or multimodal encoders outperform them once sufficient data stabilizes additional degrees of freedom. Applications include multimodal disease classification, imaging genetics, functional MRI, and topological data analysis. The resulting zeta law provides a principled way to anticipate when scaling data, improving representations, or adding modalities is most likely to accelerate discovery.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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High-fidelity and Network-based Spatio-temporal Mathematical Models of Alzheimer's Disease Progression and their Validation Against PET-SUVR Imaging Data
arXiv:2604.18470v1 Announce Type: cross Abstract: Alzheimer's disease is the most common neurodegenerative disorder. Its pathological development is connected with the misfolding and accumulation of two toxic proteins: amyloid-beta and tau proteins. Mathematical models provide a valuable quantitative tool for monitoring disease progression. In this work, we proposed and compare a novel framework where the spatio-temporal dynamics of amyloid-beta and tau proteins is modeled based on employing either three-dimensional patient-specific geometries or through reduced network-based models defined on the brain connectome. More specifically, a high-fidelity biophysical model is proposed on three-dimensional brain geometries reconstructed from magnetic resonance imaging, whereas a network-based reduced formulation is defined on the brain connectome. For both approaches, a suitable numerical discretisation is proposed. A sensitivity analysis is presented to quantify the influence of model parameters on protein concentration patterns as well as compare the quality of the predictions. For both approaches, the results are validated against PET-SUVR clinical data using 18FAZD4694 for amyloid-beta and 18FMK6240 for tau protein. The results indicate that the three-dimensional model provides the most accurate and biologically consistent description of the disease progression, but remains computationally demanding. On the other hand, the reduced graph-based model is cheaper, but it is not always able to achieve reliable results.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Subjective functions
arXiv:2512.15948v2 Announce Type: replace-cross Abstract: Where do objective functions come from? How do we select what goals to pursue? Human intelligence is adept at synthesizing new objective functions on the fly. How does this work, and can we endow artificial systems with the same ability? This paper proposes an approach to answering these questions, starting with the concept of a subjective function, a higher-order objective function that is endogenous to the agent (i.e., defined with respect to the agent's features, rather than an external task). Expected prediction error is studied as a concrete example of a subjective function. This proposal has many connections to ideas in psychology, neuroscience, and machine learning.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Multimodal branched transport infers anatomically aligned brain reaction maps
arXiv:2603.19761v2 Announce Type: replace-cross Abstract: How external stimulation is transformed into distributed reaction patterns remains unresolved at the level of propagation architecture. Existing large-scale control models quantify transition costs on prescribed networks but do not infer the routing map itself from source and target activity. Here we combine task-related blood-oxygen-level-dependent responses, source-reconstructed electrophysiology and tractography-derived anisotropy to estimate stimulation and reaction measures, define an anatomical transport cost, and infer a branched propagation architecture by variational optimisation. Unlike standard transport formulations, branched transport favours aggregation of signal into shared neural highways before redistribution. We further attach a stochastic graph-induced dynamics to the inferred map and quantify the trade-off between geometric efficiency and dynamical controllability. We show that multimodal data generate anatomically aligned brain reaction maps, that anisotropic costs qualitatively reshape routing backbones relative to isotropic baselines, and that hybrid geometric--dynamical optimisation reveals non-trivial rank reversals across branching regimes.
in arXiv: Quantitative Biology: Neurons and Cognition on 2026-04-21 04:00:00 UTC.
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Considering a generative mechanism of consciousness from the perspective of inter-level causation
arXiv:2511.04047v5 Announce Type: replace-cross Abstract: Why do some physical systems possess consciousness, while others do not? Is this a question of physics? Or is it a question of the theory of causation? Physics and the theory of causation serve different descriptive purposes, and in this study we refer to them respectively as the Physical Stance and the Causal Stance. We propose that the generation of consciousness is determined by its internal causal mechanisms in the Causal Stance. To describe a causal model, we will introduce an asymmetric relation between cause and effect into the formulation that is necessary for describing causality, though not physical laws. We argue that the causal conditions for the generation of consciousness are constituted by internal causal mechanisms of the system, rather than by external interventions. To explain such intrinsic causes, this study focuses on inter-level causality. Traditionally, inter-level causality has been considered an emergent phenomenon rather than a mechanism. We devise a method to implement these mechanisms explicitly in a causal model by examining how causes originating at higher levels are transmitted to lower levels within the system. We then propose a Dual-Laws Model (DLM), which features distinct dynamical laws at higher and lower levels. Finally, we discuss the generation of functional consciousness and its causality based on the DLM. Note that this study does not address the causal efficacy of the phenomenological aspect.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Cooperative Coevolution versus Monolithic Evolutionary Search for Semi-Supervised Tabular Classification
arXiv:2604.16412v1 Announce Type: new Abstract: This paper studies semi-supervised tabular classification in the extreme low-label regime using lightweight base learners. The paper proposes a cooperative coevolutionary method (CC-SSL) that evolves (i) two feature-subset views and (ii) a pseudo-labeling policy, and compares it to a matched monolithic evolutionary baseline (EA-SSL) and three lightweight SSL baselines. Experiments on 25 OpenML datasets with labeled fractions {1%,5%,10%} evaluate test MacroF1 and accuracy, together with evolutionary and pseudo-label diagnostics. CC-SSL and EA-SSL achieve higher median test MacroF1 than the lightweight baselines, with the largest separations at 1% labeled data. Most CC-SSL vs. EA-SSL comparisons are statistical draws on final test performance. EA-SSL shows higher best-so-far fitness and higher diversity during search, while time-to-target is comparable and generations-to-target favors EA-SSL in several multiclass settings. Pseudo-label volume, ProbeDrop, and validation optimism show no significant differences between CC-SSL and EA-SSL under the shared protocol.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Breaking Validity-Induced Boundaries to Expand Algorithm Search Space: A Two-Stage AST-Based Operator for LLM-Driven Automated Heuristic Evolution
arXiv:2604.16420v1 Announce Type: new Abstract: Large Language Model (LLM) based automated heuristic design (AHD) has shown great potential in discovering efficient heuristics. Most existing LLM-AHD frameworks use semantic evolutionary operators that rely entirely on the LLM's pre-trained knowledge. These one-stage methods strictly require the generated code to be valid during the operation and often rely on a ``thought-code'' representation. We argue that this end-to-end generation fundamentally limits the exploration ability within the algorithm search space. In this paper, we propose a two-stage, structure-based evolutionary operator for LLM-AHD. In the first stage, our approach directly performs crossover and mutation on the Abstract Syntax Trees (ASTs) of the heuristic code, intentionally generating diverse but often invalid structural variants. In the second stage, the LLM is employed to repair these invalid heuristics into executable, high-quality code. Depending on the underlying framework, either the raw invalid variants or the repaired heuristics are integrated into the population to preserve potential structural patterns. We demonstrate that the proposed operator can significantly enhance the search ability of state-of-the-art LLM-AHD algorithms, such as EoH-S. Experimental results on the Traveling Salesman Problem (TSP) and the Online Bin Packing Problem (OBP) show that our method effectively improves both optimization performance and convergence speed.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Fuzzy Encoding-Decoding to Improve Spiking Q-Learning Performance in Autonomous Driving
arXiv:2604.16436v1 Announce Type: new Abstract: This paper develops an end-to-end fuzzy encoder-decoder architecture for enhancing vision-based multi-modal deep spiking Q-networks in autonomous driving. The method addresses two core limitations of spiking reinforcement learning: information loss stemming from the conversion of dense visual inputs into sparse spike trains, and the limited representational capacity of spike-based value functions, which often yields weakly discriminative Q-value estimates. The encoder introduces trainable fuzzy membership functions to generate expressive, population-based spike representations, and the decoder uses a lightweight neural decoder to reconstruct continuous Q-values from spiking outputs. Experiments on the HighwayEnv benchmark show that the proposed architecture substantially improves decision-making accuracy and closes the performance gap between spiking and non-spiking multi-modal Q-networks. The results highlight the potential of this framework for efficient and real-time autonomous driving with spiking neural networks.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Spike-driven Large Language Model
arXiv:2604.16475v1 Announce Type: new Abstract: Current Large Language Models (LLMs) are primarily based on large-scale dense matrix multiplications. Inspired by the brain's information processing mechanism, we explore the fundamental question: how to effectively integrate the brain's spiking-driven characteristics into LLM inference. Spiking Neural Networks (SNNs) possess spike-driven characteristics, and some works have attempted to combine SNNs with Transformers. However, achieving spike-driven LLMs with billions of parameters, relying solely on sparse additions, remains a challenge in the SNN field. To address the issues of limited representational capacity and sparsity in existing spike encoding schemes at the LLM level, we propose SDLLM, a spike-driven large language model that eliminates dense matrix multiplications through sparse addition operations. Specifically, we use the plug-and-play gamma-SQP two-step spike encoding method to ensure that the quantization process aligns with the model's semantic space, mitigating representation degradation caused by binary spikes. Furthermore, we introduce bidirectional encoding under symmetric quantization and membrane potential clipping mechanisms, leading to spike trains with no or low firing counts dominating, significantly reducing the model's spike firing rate, while halving the number of time steps. Experimental results show that SDLLM not only significantly reduces inference costs but also achieves state-of-the-art task performance under the spike-based paradigm. For example, compared to previous spike-based LLMs, SDLLM reduces energy consumption by 7x and improves accuracy by 4.2%. Our model provides inspiration for the architecture design of the next generation of event-driven neuromorphic chips.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization
arXiv:2604.16496v1 Announce Type: new Abstract: Continual learning, the ability to acquire new tasks sequentially without forgetting prior knowledge, is essential for deploying neural networks in dynamic real-world environments, from nuclear digital twin monitoring to grid-edge fault detection. Existing synaptic importance methods, such as Elastic Weight Consolidation (EWC) and Synaptic Intelligence (SI), rely on gradient computation, making them incompatible with neuromorphic hardware that lacks backpropagation support. We propose ISI-CV, the first gradient-free synaptic importance metric for SNN continual learning, derived from the Coefficient of Variation (CV) of Inter-Spike Intervals (ISIs). Neurons that fire regularly (low CV) encode stable, task-relevant features and are protected from overwriting; neurons with irregular firing are permitted to adapt freely. ISI-CV requires only spike time counters and integer arithmetic, all of which are native to every neuromorphic chip. We evaluate on four benchmarks of increasing difficulty: Split-MNIST, Permuted-MNIST, Split-FashionMNIST, and Split-N-MNIST using real Dynamic Vision Sensor (DVS) event data. Across three seeds, ISI-CV achieves zero forgetting (AF = 0.000 +/- 0.000) on Split-MNIST and Split-FashionMNIST, near-zero forgetting on Permuted-MNIST (AF = 0.001 +/- 0.000), and the highest accuracy with the lowest forgetting on real neuromorphic DVS data (AA = 0.820 +/- 0.012, AF = 0.221 +/- 0.014). On N-MNIST, gradient-based methods produce unreliable importance estimates and perform worse than no regularization; ISI-CV avoids this failure by design.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Impact of leaky dynamics on predictive path integration accuracy in recurrent neural networks
arXiv:2604.16547v1 Announce Type: new Abstract: Experimental evidence indicates that intrinsic temporal dynamics operating across multiple time scales are closely associated with the emergence of periodic spatial activity of increasing complexity. However, how information encoded in grid-like firing patterns for path integration is processed across these intrinsic time scales remains unclear. To address this question, we introduce adaptive time scales through a leak term in recurrent neural networks (RNNs), forming leaky RNNs discretized from the continuous attractors of firing rate models. Our results demonstrate that leaky RNNs substantially enhance the emergence of well-defined and highly regular hexagonal firing patterns. Compared with vanilla RNNs lacking a leak term, the trained leaky RNNs produce more accurate position estimates while generating reliable grid-cell-like representations. Furthermore, under identical noise conditions, leaky RNNs consistently exhibit more stable dynamics and better-defined grid structures. The learned dynamics also give rise to stable torus attractors with a clear central hole, supporting robust and regular grid-like activity. Overall, the dynamic leak acts as a low-pass filtering mechanism that protects recurrent neural circuitry from noise, stabilizes network dynamics, and improves path-integration accuracy in recurrent neural networks.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Monotone but Exciting: On Evolving Monotone Boolean Functions with High Nonlinearity
arXiv:2604.17342v1 Announce Type: new Abstract: Monotone Boolean functions are a structurally important class of Boolean functions, but their restricted form imposes strong limitations on achievable nonlinearity. In this paper, we investigate whether evolutionary computation can evolve monotone Boolean functions with high nonlinearity, both in the balanced and imbalanced settings. We consider three solution encodings: the standard truth table representation, a balanced truth table encoding that preserves Hamming weight, and a symbolic tree-based genetic programming representation. To guide the search toward monotone increasing functions, we introduce a non-monotonicity penalty and combine it with fitness functions targeting balancedness and nonlinearity. Experimental results are reported for dimensions from $n=5$ to $n=14$. The results show that evolutionary search can discover monotone Boolean functions with nonlinearities clearly exceeding those of majority functions, and in several cases approaching the best currently known values for monotone functions. At the same time, the experiments reveal substantial differences between encodings: the balanced truth table encoding performs poorly for larger dimensions, while the standard truth table and genetic programming encodings remain competitive, with genetic programming becoming especially relevant in the largest tested dimensions.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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On Scalability of Multi-Objective Evolutionary Algorithms on Combinatorial Optimisation Problems
arXiv:2604.17872v1 Announce Type: new Abstract: Scalability of evolutionary algorithms refers to assessing how their performance changes as problem size increases. In the area of multi-objective optimisation, research on the scalability of multi-objective evolutionary algorithms (MOEAs) has predominantly focussed on continuous problems. However, multi-objective combinatorial optimisation problems (MOCOPs) differ from continuous ones. Their discrete and rigid structure often brings rugged landscape, numerous local optimal solutions and disjoint global optimal regions. This leads to different behaviour of MOEAs. For example, SEMO, a simple MOEA without mating selection and diversity maintenance mechanisms, has been shown to be highly competitive, and in many cases to outperform more sophisticated MOEAs on MOCOPs. Yet, it remains unclear whether such findings hold for large-scale cases. In this paper, we conduct an empirical investigation into the scalability of MOEAs on combinatorial problems, with problem size from 50 to 5,000. Our results show that SEMO experiences a decline in convergence speed as dimensionality increases, compared to other MOEAs such as NSGA-II, SMS-EMOA and MOEA/D. We further demonstrate that the absence of crossover is a major contributor to SEMO's underperformance in large-scale problems, and that incorporating crossover into SEMO can substantially accelerate convergence in general, despite being detrimental in spreading solutions over the Pareto front.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Similarity-based Portfolio Construction for Black-box Optimization
arXiv:2604.18196v1 Announce Type: new Abstract: In black-box optimization, a central question is which algorithm to use to solve a given, previously unseen, problem. Selecting a single algorithm, however, entails inherent risks: inaccuracies in the selector may lead to poor choices, and even well-performing algorithms with high variance can yield unsatisfactory results in a single run. A natural remedy is to split the evaluation budget across multiple runs of potentially different algorithms. Such sequential algorithm portfolios benefit from variance reduction and complementarities between algorithms, often outperforming approaches that allocate the entire budget to a single solver. While effective portfolios can be constructed post-hoc, transferring this idea to the algorithm selection setting is non-trivial. We show that a naive portfolio constructed over the full training set already outperforms the strongest traditional baseline, the virtual best solver. We then propose a simple yet effective k-nearest-neighbor-based finetuning approach to construct portfolios tailored to unseen instances, yielding further improvements and highlighting the effectiveness of portfolio selection in fixed-budget black-box optimization.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Neutrally Evolving Interlocking Complexity in the Quandary Den
arXiv:2604.18361v1 Announce Type: new Abstract: Molecular biology features numerous complexes of proteins that coordinate in an interlocking fashion to fulfill different functions. Adaptive evolution explains some of this complexity, but needn't be the default when neutral explanations suffice. A new artificial life model ``organism,'' the Quandary Den, is introduced to explore different neutral evolution scenarios where complexity increases in the absence of greater informational needs. Two interlocking complexity scenarios emerge. Subfunctionalization leads to functionality diffusing through the complex. Masking allows intracomplex interference to accumulate genetically, requiring that it be blocked at the level of expression.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Full Feature Spiking Neural Network Simulation on Micro-Controllers for Neuromorphic Applications at the Edge
arXiv:2604.16474v1 Announce Type: cross Abstract: Microcontroller units (MCU), which have an order of magnitude lower Size, Weight and Power (SWaP) than standard computers, makes them suitable for applications at the edge. Neuromorphic computing, which can realize low SWaP, relies on Spiking Neural Networks (SNNs). Until now, software based simulations of SNNs required GPU-based workstations, application classified core processors such as the ARM Cortex-A53, or specialized hardware like Intel's Loihi. In the present work, we demonstrate that the SNN simulator CARLsim can run its full feature set on a MCU RP2350 with 8 MB memory. We accomplished this by utilizing IEEE 16-bit float point numbers, which reduced memory requirements without loss of function. We were able to run the Synfire4 benchmark which comprises 1200 neurons. The accuracy was 97.5% compared to the standard single precision numbers. Furthermore, we show that CARLsim runs a Synfire4 benchmark scaled-down to 186 neurons on a MCU in real-time at only 20 mW. Compared to the smallest application class ARM processor used by Raspberry in their Pi Zero 2 W, our MCU implementation is five times more energy efficient for the SNN itself, and an order of magnitude better when compared to the complete SoC (MCU/CPU + Board).
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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When Spike Sparsity Does Not Translate to Deployed Cost: VS-WNO on Jetson Orin Nano
arXiv:2604.17040v1 Announce Type: cross Abstract: Spiking neural operators are appealing for neuromorphic edge computing because event-driven substrates can, in principle, translate sparse activity into lower latency and energy. Whether that advantage survives deployment on commodity edge-GPU software stacks, however, remains unclear. We study this question on a Jetson Orin Nano 8 GB using five pretrained variable-spiking wavelet neural operator (VS-WNO) checkpoints and five matched dense wavelet neural operator (WNO) checkpoints on the Darcy rectangular benchmark. On a reference-aligned path, VS-WNO exhibits substantial algorithmic sparsity, with mean spike rates decreasing from 54.26% at the first spiking layer to 18.15% at the fourth. On a deployment-style request path, however, this sparsity does not reduce deployed cost: VS-WNO reaches 59.6 ms latency and 228.0 mJ dynamic energy per inference, whereas dense WNO reaches 53.2 ms and 180.7 mJ, while also achieving slightly lower reference-path error (1.77% versus 1.81%). Nsight Systems indicates that the request path remains launch-dominated and dense rather than sparsity-aware: for VS-WNO, cudaLaunchKernel accounts for 81.6% of CUDA API time within the latency window, and dense convolution kernels account for 53.8% of GPU kernel time; dense WNO shows the same pattern. On this Jetson-class GPU stack, spike sparsity is measurable but does not reduce deployed cost because the runtime does not suppress dense work as spike activity decreases.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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A fully parallel densely connected probabilistic Ising machine with inertia for real-time applications
arXiv:2604.17109v1 Announce Type: cross Abstract: Ising machines -- special-purpose hardware for heuristically solving Ising optimization problems -- based on probabilistic bits (p-bits) have been established as a promising alternative to heuristic optimization algorithms run on conventional computers. However, it has -- until now -- been thought that Ising spins that are connected in probabilistic Ising machines cannot be updated in parallel without ruining the machine's solving ability. This has been a major challenge for using probabilistic Ising machines as fast solvers for densely connected problems. Here, we circumvent this by introducing a modified Ising spin dynamics with an added inertia term, and verify in algorithm simulations, FPGA hardware emulation, and FPGA experiments that it enables fully parallel, synchronous updates while improving rather than degrading success probability. We evaluated on various types of abstract (Max-Cut and Sherrington-Kirkpatrick-model) and application-derived (MIMO, wireless detection) dense Ising benchmark instances. Performing fully parallel updates results in a speed advantage that grows faster than linearly with the number of spins, giving rise to large time-to-solution increases for practical problem sizes. For both Max-Cut and the SK-1 model at a problem size of 200, our approach achieved an average speedup of $\approx 35\times$, with the best single-instance speedup reaching $150\times$. As an example of the practical utility of our approach in an application where speed is critical, we further show by co-designing the algorithm dynamics with the hardware implementation -- co-optimizing for solver ability and silicon resource usage -- that probabilistic Ising machines based on our approach satisfy the stringent solution quality and latency/throughput requirements for real-time MIMO detection in modern 5G cellular wireless networks while using a practically reasonable silicon area.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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On the Generalization Bounds of Symbolic Regression with Genetic Programming
arXiv:2604.17402v1 Announce Type: cross Abstract: Symbolic regression (SR) with genetic programming (GP) aims to discover interpretable mathematical expressions directly from data. Despite its strong empirical success, the theoretical understanding of why GP-based SR generalizes beyond the training data remains limited. In this work, we provide a learning-theoretic analysis of SR models represented as expression trees. We derive a generalization bound for GP-style SR under constraints on tree size, depth, and learnable constants. Our result decomposes the generalization gap into two interpretable components: a structure-selection term, reflecting the combinatorial complexity of choosing an expression-tree structure, and a constant-fitting term, capturing the complexity of optimizing numerical constants within a fixed structure. This decomposition provides a theoretical perspective on several widely used practices in GP, including parsimony pressure, depth limits, numerically stable operators, and interval arithmetic. In particular, our analysis shows how structural restrictions reduce hypothesis-class growth while stability mechanisms control the sensitivity of predictions to parameter perturbations. By linking these practical design choices to explicit complexity terms in the generalization bound, our work offers a principled explanation for commonly observed empirical behaviors in GP-based SR and contributes towards a more rigorous understanding of its generalization properties.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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The Magnitude of Dominated Sets: A Pareto Compliant Indicator Grounded in Metric Geometry
arXiv:2604.18147v1 Announce Type: cross Abstract: We investigate \emph{magnitude} as a new unary and strictly Pareto-compliant quality indicator for finite approximation sets to the Pareto front in multiobjective optimization. Magnitude originates in enriched category theory and metric geometry, where it is a notion of size or point content for compact metric spaces and a generalization of cardinality. For dominated regions in the $\ell_1$ box setting, magnitude is close to hypervolume but not identical: it contains the top-dimensional hypervolume term together with positive lower-dimensional projection and boundary contributions. This paper gives a first theoretical study of magnitude as an indicator. We consider multiobjective maximization with a common anchor point. For dominated sets generated by finite approximation sets, we derive an all-dimensional projection formula, prove weak and strict set monotonicity on finite unions of anchored boxes, and thereby obtain weak and strict Pareto compliance. Unlike hypervolume, magnitude assigns positive value to boundary points sharing one or more coordinates with the anchor point, even when their top-dimensional hypervolume contribution vanishes. We then formulate projected set-gradient methods and compare hypervolume and magnitude on biobjective and three-dimensional simplex examples. Numerically, magnitude favors boundary-including populations and, for suitable cardinalities, complete Das--Dennis grids, whereas hypervolume prefers more interior-filling configurations. Computationally, magnitude reduces to hypervolume on coordinate projections; for fixed dimension this yields the same asymptotic complexity up to a factor $2^d-1$, and in dimensions two and three $\Theta(n\log n)$ time. These results identify magnitude as a mathematically natural and computationally viable alternative to hypervolume for finite Pareto front approximations.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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The hop-like problem nature -- unveiling and modelling new features of real-world problems
arXiv:2406.01215v2 Announce Type: replace Abstract: Benchmarks are essential tools for the optimizer's development. Using them, we can check for what kind of problems a given optimizer is effective or not. Since the objective of the Evolutionary Computation field is to support the tools to solve hard, real-world problems, the benchmarks that resemble their features seem particularly valuable. Therefore, we propose a hop-based analysis of the optimization process. We apply this analysis to the NP-hard, large-scale real-world problem. Its results indicate the existence of some of the features of the well-known Leading Ones problem. To model these features well, we propose the Leading Blocks Problem (LBP), which is more general than Leading Ones and some of the benchmarks inspired by this problem. LBP allows for the assembly of new types of hard optimization problems that are not handled well by the considered state-of-the-art genetic algorithm (GA). Finally, the experiments reveal what kind of mechanisms must be proposed to improve GAs' effectiveness while solving LBP and the considered real-world problem.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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SiLIF: Structured State Space Model Dynamics and Parametrization for Spiking Neural Networks
arXiv:2506.06374v4 Announce Type: replace Abstract: Multi-state spiking neurons combine sparse binary activations with rich second-order nonlinear recurrent dynamics, making them a promising alternative to standard deep learning models. However, gradient propagation through these dynamics often leads to instabilities that hinder scalability and performance. Inspired by the stable training and strong performance of state space models (SSMs) on long sequences, we introduce two SSM-inspired Leaky Integrate-and-Fire (SiLIF) neuron models. The first extends a two-state neuron with a learnable discretization timestep and logarithmic reparametrization, while the second additionally incorporates the initialization scheme and structure of complex-state SSMs, enabling oscillatory regimes. Our two SiLIF models achieve new state-of-the-art performance among spiking neuron models on both event-based and raw-audio speech recognition datasets. We further demonstrate a favorable performance-efficiency trade-off compared to SSMs, even surpassing them while using half the computational cost through the use of synaptic delays. Our code is available at https://github.com/Maxtimer97/SSM-inspired-LIF.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Benchmarking ERP Analysis: Manual Features, Deep Learning, and Foundation Models
arXiv:2601.00573v2 Announce Type: replace Abstract: Event-related potential (ERP), a specialized paradigm of electroencephalographic (EEG), reflects neurological responses to external stimuli or events, generally associated with the brain's processing of specific cognitive tasks. ERP plays a critical role in cognitive analysis, the detection of neurological diseases, and the assessment of psychological states. Recent years have seen substantial advances in deep learning-based methods for spontaneous EEG and other non-time-locked task-related EEG signals. However, their effectiveness on ERP data remains underexplored, and many existing ERP studies still rely heavily on manually extracted features. In this paper, we conduct a comprehensive benchmark study that systematically compares traditional manual features (followed by a linear classifier), deep learning models, and pre-trained EEG foundation models for ERP analysis. We establish a unified data preprocessing and training pipeline and evaluate these approaches on two representative tasks, ERP stimulus classification and ERP-based brain disease detection, across 12 publicly available datasets. Furthermore, we investigate various token-embedding strategies within advanced Transformer architectures to identify embedding designs that better suit ERP data. Our study provides a landmark framework to guide method selection and tailored model design for future ERP analysis. The code is available at https://github.com/DL4mHealth/ERP-Benchmark
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Motif Diversity in Human Liver ChIP-seq Data Using MAP-Elites
arXiv:2601.17808v2 Announce Type: replace Abstract: Motif discovery is a core problem in computational biology, traditionally formulated as a likelihood optimization task that returns a single dominant motif from a DNA sequence dataset. However, regulatory sequence data admit multiple plausible motif explanations, reflecting underlying biological heterogeneity. In this work, we frame motif discovery as a quality-diversity problem and apply the MAP-Elites algorithm to evolve position weight matrix motifs under a likelihood-based fitness objective while explicitly preserving diversity across biologically meaningful dimensions. We evaluate MAP-Elites using three complementary behavioral characterizations that capture trade-offs between motif specificity, compositional structure, coverage, and robustness. Experiments on human CTCF liver ChIP-seq data aligned to the human reference genome compare MAP-Elites against a standard motif discovery tool, MEME, under matched evaluation criteria across stratified dataset subsets. Results show that MAP-Elites recovers multiple high-quality motif variants with fitness comparable to MEME's strongest solutions while revealing structured diversity obscured by single-solution approaches.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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SparrowSNN: A Hardware/software Co-design for Energy Efficient ECG Classification
arXiv:2406.06543v2 Announce Type: replace-cross Abstract: Deep learning has driven significant technological advancements, but its high energy consumption limits its use on battery-operated edge devices. Spiking Neural Networks (SNNs) offer promising reductions in inference-time energy consumption. However, existing neuromorphic architectures optimize scalable, many-core NoC execution, suited to large models but mismatched to edge devices, and their prevalent integrate-and-fire neurons re-read weights across $T$ timesteps, inflating data-movement and dynamic-control energy. To address this challenge, we propose SparrowSNN, an optimized end-to-end design tailored for edge applications. SparrowSNN proposes: (1) a hardware-friendly spike activation function SSF (Sum-Spike-and-Fire); (2) a customizable $\mu$W-level-power quantized hybrid ANN-SNN model that can be designed per application; (3) a compact and low-power reconfigurable ASIC architecture, supporting the aforementioned designs. Evaluated on biomedical MIT-BIH ECG and DEAP EEG datasets, SparrowSNN achieves state-of-the-art accuracy with $20\times$ to $100\times$ lower energy consumption, significantly outperforming existing ultra-low power solutions.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Adaptive Domain Models: Bayesian Evolution, Warm Rotation, and Principled Training for Geometric and Neuromorphic AI
arXiv:2603.18104v4 Announce Type: replace-cross Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relative to inference, optimizer complexity, and structural degradation of geometric properties through training are consequences of this arithmetic substrate. This paper develops an alternative training architecture grounded in three prior results: the Dimensional Type System and Deterministic Memory Management framework [6], which establishes stack-eligible gradient allocation and exact quire accumulation as design-time verifiable properties; the Program Hypergraph [8], which establishes grade preservation through geometric algebra computations as a type-level invariant; and the b-posit 2026 standard [10], which makes posit arithmetic tractable across hardware targets conventionally considered inference-only. Their composition enables depth-independent training memory bounded to approximately twice the inference footprint, grade-preserving weight updates, and exact gradient accumulation, applicable uniformly to loss-function-optimized and spike-timing-dependent neuromorphic models. We introduce Bayesian distillation, a mechanism by which the latent prior structure of a general-purpose model is extracted through the ADM training regime, resolving the data-scarcity bootstrapping problem for domain-specific training. For deployment, we introduce warm rotation, an operational pattern in which an updated model transitions into an active inference pathway without service interruption, with structural correctness formalized through PHG certificates and signed version records. The result is a class of domain-specific AI systems that are smaller and more precise than general-purpose models, continuously adaptive, verifiably correct with respect to the physical structure of their domains, and initializable from existing models.
in arXiv: Computer Science: Neural and Evolutionary Computing on 2026-04-21 04:00:00 UTC.
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Acinetobacter baumannii’s ecology– more than meets the eye

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72338-3
Acinetobacter baumannii is mainly considered a human pathogen. Yet, its habitat range is uncertain. In a recent article, Wilharm et al. use a large multisource data set to show that decomposing plants and soil are natural habitats for this bacterium, thus advancing our understanding of A. baumannii’s ecology.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Kinetics-controlled radical coupling on dual redox-active sites for selective formamide production

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72215-z
Researchers developed a dual-active-site photocatalyst that stabilizes ●NO radicals on Ni2+ sites while coupling them with transient CH3●O radicals, achieving 99.5% selectivity and g-scale formamide production by kinetics-controlled radical coupling.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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SMG7 and eIF4A constitute a homeostatic module controlling P-body condensation and function of meiotic bodies

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72218-w
eIF4A is actively recruited to P-bodies through the action of SMG7 where it restricts their growth under both normal and stress conditions, thereby ensuring proper cellular function and successful reproduction.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Prolonged β2-agonist treatment enhances muscle-specific glucose uptake in individuals with overweight and obesity: a randomized placebo-controlled trial

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-71897-9
The study showed in a placebo-controlled crossover design that 4-week treatment with β2-adrenergic agonist clenbuterol enhances insulin-stimulated glucose uptake in skeletal muscle but not brown adipose tissue in individuals with obesity.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Dual-path suppression of thermal and wetting-driven steel corrosion for marine structure

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-71930-x
Dual-functional coating with radiative cooling and superhydrophobicity protects marine structures by cooling below ambient temperature and repelling seawater. Cooling slows corrosion, while hydrophobicity prevents wetting.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Auricular vagus nerve stimulation drives analgesia via an auricle–brain axis in a mouse model of neuropathic pain

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72214-0
The neuroanatomical basis of auricular vagus nerve stimulation-induced analgesia remains unclear. Here, the authors identify an auricle-to-brain axis from the auricular concha to the ventrolateral periaqueductal gray, which engages the descending antinociceptive pathway.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Mitochondrial respirasome-like supercomplexes support metabolic flexibility in yeast

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72228-8
Mitochondrial respiratory enzymes are organized in supercomplexes. Here, the authors show that specific interactions between yeast supercomplexes and NADH dehydrogenases facilitate coenzyme Q-dependent electron transfer and metabolic flexibility.
in Nature Communications on 2026-04-21 00:00:00 UTC.
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Overcoming redox barriers in black phosphorus negative electrodes through lattice P–N engineering for fast-charging Li-ion batteries

Nature Communications, Published online: 21 April 2026; doi:10.1038/s41467-026-72193-2
Fast-charging black phosphorus electrodes are limited by slow multiphase redox reactions. Here, authors engineer P–N bonds in the phosphorus bulk to accelerate lithium insertion and boost performance. Pouch cells can hit 80% charge in 10 min, delivering 282 Wh/kg and lasting over 3,400 cycles.
in Nature Communications 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 Europe
in 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 China
in 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 Videos
in 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 Region
in 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 dujardinii
in Nature scientific data on 2026-04-21 00:00:00 UTC.
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A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level

Scientific Data, Published online: 21 April 2026; doi:10.1038/s41597-026-07251-x
A multi-modal dataset for insect biodiversity with imagery and DNA at the trap and individual level
in 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 signalling
in 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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Maternal-infant immune signatures in infants at risk for SARS-CoV-2-associated neurodevelopmental disorders

Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10019-z
Serum proteomics revealed dysregulated biomarkers associated with neuronal inflammatory pathways in children with antenatal maternal SARS-CoV-2 exposure, providing potential mechanistic insight into the higher frequency of neurodevelopmental disorders.
in Nature communications biology on 2026-04-21 00:00:00 UTC.
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Morphological and anatomical variations in subcortical anatomy between humans and chimpanzees associated with heritability patterns related to human behavioral traits

Communications Biology, Published online: 21 April 2026; doi:10.1038/s42003-026-10066-6
Using surface-based MRI comparisons between humans and chimpanzees combined with heritability analyses from Human Connectome Project data, Blostein et al. show that evolutionarily expanded regions of the striatum are highly heritable and associated with cognitive behavioral measures. In contrast, more evolutionarily conserved regions of the thalamus and globus pallidus are linked to affective behaviors, suggesting a functional gradient between cognitive and emotional specialization in subcortical evolution.
in Nature communications biology 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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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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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 Vsx1CreER^T2 line; type 1b, 2, and 6 bipolar cells in the Lhx3CreER^T2 line; and type 2, 3, 4, and 5 bipolar cells in the Lhx4CreER^T2 line. In addition, Lhx4CreER^T2 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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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 mission
in 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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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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A daily three-dimensional dataset of the Kuroshio axis and boundaries in the East China Sea and Luzon Strait

Scientific Data, Published online: 20 April 2026; doi:10.1038/s41597-026-07275-3
A daily three-dimensional dataset of the Kuroshio axis and boundaries in the East China Sea and Luzon Strait
in Nature scientific data on 2026-04-20 00:00:00 UTC.
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Zinc-dependent Zip7-MAZ-MYBL2 axis promotes prostate cancer metastasis

Communications Biology, Published online: 20 April 2026; doi:10.1038/s42003-026-10074-6
Zip7 regulates PCa metastasis by facilitating MAZ nuclear import to promote MYBL2 transcription. Targeting Zinc-dependent Zip7- MAZ-MYBL2 could be a valuable strategy to ameliorate advanced prostate cancer metastasis.
in Nature communications biology on 2026-04-20 00:00:00 UTC.
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Vegetation type conversion in Northeast China under permafrost change

Communications Biology, Published online: 20 April 2026; doi:10.1038/s42003-026-10046-w
Higher frequency of permafrost type change is shown to exhibit higher vegetation conversion rates, with these areas characterized by grassland decline and expansion of broad-leaved forest and shrubland.
in Nature communications biology on 2026-04-20 00:00:00 UTC.
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Hypoxia-induced Schwann cells-derived extracellular vesicles carrying LncRNA TNXA-PS1 promote recovery post sciatic nerve injury

Communications Biology, Published online: 20 April 2026; doi:10.1038/s42003-026-10020-6
ceRNA mechanism of hypoxia-induced Schwann cells-derived extracellular vesicles reveals their protective effect in peripheral nerve injury.
in Nature communications biology 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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Structural mechanisms of pump assembly and drug transport in the AcrAB–TolC efflux system
Tripartite multidrug efflux pumps that span the cell envelope are essential for antibiotic resistance in Gram-negative bacteria. Here, we report cryo-EM structures of two endogenous efflux complexes from Escherichia coli: a TolC–YbjP subcomplex at 3.56 Å resolution and the complete TolC–YbjP–AcrABZ pump at 3.39 Å. Structural analysis reveals that YbjP, a previously uncharacterized lipoprotein, binds TolC in a 3:3 stoichiometry, bridging the TolC protomers at their equatorial domain. Clear density of the mature YbjP’s N-terminal Cys19 indicates that YbjP is anchored to the outer membrane by an N-terminal lipid moiety. Notably, YbjP remains bound as TolC undergoes AcrA-induced opening, suggesting that this accessory protein accommodates the conformational change. The AcrB trimer simultaneously presents three distinct conformational states (L, T, and O), capturing a complete transport cycle. These high-resolution structures provide insights into the architecture and mechanism of clinically relevant efflux machinery, identifying YbjP as a previously unrecognized structural component that contributes to TolC positioning, and may assist in its membrane localization.
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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The robust, high-throughput, and temporally regulated roxCre and loxCre reporting systems for genetic modifications in vivo
Cre-loxP technology, a cornerstone in fate mapping and in vivo gene function studies, faces challenges in achieving precise and efficient conditional mutagenesis through inducible systems. This study introduces two innovative genetic tools designed to overcome these limitations. The first, roxCre, enables DreER-mediated Cre release, paving the way for intersectional genetic manipulation that permits increased precision and efficiency. The second, loxCre, facilitates conditional gene targeting by allowing CreER lines to induce Cre expression with significantly enhanced efficiency. These tools incorporate a fluorescent reporter for genetic lineage tracing, simultaneously revealing efficient gene knockout in cells marked by the reporter. These strategies hold great potential for precise and efficient exploration of lineage-specific gene functions, marking a significant advancement in genetic research methodologies.
in eLife 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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Taking the biology seriously makes models better
A new biologically-informed training paradigm enables protein language models to predict affinity maturation trajectories for antibodies.
in eLife on 2026-04-20 00:00:00 UTC.
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Local gated-Hebbian learning of deep cerebellar networks with quadratic classification capacity
A central goal of neuroscience is to understand how neural circuit architecture supports learning. While recent work has clarified the computational role of depth in sensory cortical hierarchies, it remains unclear why predominantly feedforward, non-convolutional circuits such as the cerebellum and olfactory system also contain multiple processing layers. Theoretical work in deep learning has shown that two-hidden-layer networks can achieve classification capacity that scales quadratically with the number of intermediate neurons, but these results rely on nonlocal synaptic optimization and are therefore difficult to reconcile with biological learning rules. Here, we show analytically and numerically that a two-hidden-layer network with feedforward gating can achieve quadratic capacity using local three-factor Hebbian learning when intermediate activity is sparse. This architecture supports efficient one-shot learning and, in settings where backpropagation requires many repeated weight updates, offers an advantage in learning speed. Beyond random perceptron tasks, the model also performs well on structured cerebellum-related tasks, including reinforcement-learning-based motor control. Mapping the model onto cerebellar microcircuitry further suggests functional roles for dendritic compartmentalization, branch-specific inhibition, and disinhibitory interneuron pathways. Together, these results extend the Marr-Albus-Ito framework by showing how the presence of multiple intermediate layers in cerebellum-like circuits can support fast, local, and high-capacity learning.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Reproducibility and model-selection stability in connectome-constrained circuit modeling
Connectome-constrained neural network models aim to link anatomical connectivity with functional computation by training networks whose architectures reflect biological circuits. Because such models are increasingly used to infer neural mechanisms, it is important to assess their robustness to variations in training conditions and model selection criteria. Here we retrain ensembles of connectome-constrained models under nominally identical conditions and compare their correspondence to experimentally measured response properties in the Drosophila motion pathway. While task performance remains similar across models, the identification of biologically plausible circuit solutions is unstable across retraining runs. In particular, model clusters selected by lowest validation task error do not reliably correspond to experimentally observed neural tuning, and small variations in performance metrics can reorder cluster rankings. These results indicate that, in this framework, similar task performance does not reliably identify biologically plausible circuit solutions. Task error alone is therefore insufficient for mechanistic identification, and additional model-selection criteria are needed.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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P2X7 receptor-mediated astrocytic atrophy in the hippocampus of mice after status epilepticus
Genetic deletion or pharmacological blockade of P2X7 receptors (Rs) counteract status epilepticus (SE) in animal models of epilepsy. It is, however, unclear whether P2X7Rs are localized at astrocytes or neurons, and the reason for astrocytic atrophy arising in consequence of SE is also ambiguous. We conducted a combined morphological/electrophysiological study in order to investigate these issues. It has been shown that kainic acid (KA)-induced SE in mice led to the atrophy of hippocampal astrocytes and at the same time to the decrease of ezrin immunoreactivity and its co-expression with mCherry, whose synthesis has been initiated by the injection of a virus complex. mCherry expression in astrocytes enabled us to study changes in cell somata and processes brought about by KA-injection. Ezrin is a plasmalemmal-cytoskeleton linker; its grade of expression indicates changes in the existence/function of small peripheral astrocytic processes. Pretreatment of mice with the blood-brain barrier-permeable P2X7R antagonist JNJ-47965567 prevented the SE-induced damage of astrocytes. KA caused a potentiation of dibenzoyl-ATP (Bz-ATP) currents in astrocytes but not neurons of the hippocampus. This effect was also abolished by pre-treatment of mice with JNJ-47965567 before applying KA, although no similar changes occurred in hippocampal CA1 neurons. The measurement of spontaneous postsynaptic currents (sPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) indicated a presynaptic facilitation of neurotransmitter release by Bz-ATP. In conclusion, we suggest that astrocytic P2X7Rs are the primary target of ATP release from damaged CNS cells in the hippocampus which simultaneously causes damage to astrocytic somata and processes.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Sharp and Fast Dynamic Extraction and Tracking of Emitted Cellular Transients
Understanding neural correlates of brain function in neuroscience now largely involves detecting and analyzing transient signals from fluorescent sensors. Imaging technologies such as confocal and two-photon microscopy, along with onboard miniscopes, enable the visualization of neural activities and capture dynamic signals both ex vivo and in vivo. This includes monitoring Ca2+ transients via the expression of genetically encoded sensors such as GCaMP in specific brain cells. Additionally, the advent of GPCR-based neurotransmitter sensors allows for imaging the release of neurotransmitters including glutamate and GABA, as well as neuromodulators such as dopamine or noradrenaline. These approaches however generate large, high-dimensional, spatiotemporally complex datasets, presenting significant challenges for signal detection and analysis. To overcome these challenges, we developed a versatile pipeline of Dynamic Extraction and Tracking of Emitted Cellular Transients (DETECT), which combines background denoising, object segmentation, and multi-object tracking. Our user-friendly, Python-based GUI offers a low-resource platform for efficient data analysis. Validated across various imaging modalities and biological models, DETECT provides a robust and comprehensive solution for analyzing complex imaging datasets in neuroscience research.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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The functional organization of retinal input to the mouse superior colliculus
The superior colliculus integrates retinal input to drive rapid, adaptive visual behavior, yet how the functional diversity of retinal ganglion cell types is represented in superior colliculus remains poorly understood. Using chronic two-photon calcium imaging of retinal ganglion cell axonal boutons in awake mice, we recorded over 200,000 boutons across superficial superior colliculus layers --- a scale that enabled systematic comparison with large-scale ex vivo retinal datasets. This revealed that the superior colliculus receives a near-complete sampling of retinal ganglion cell functional diversity. Functionally distinct response types were organized in systematic laminar gradients: not only response properties such as direction selectivity and contrast suppression, but retinal response types themselves varied systematically with depth. To probe how this organized input encodes natural scenes, we trained a ''digital twin'' deep network model on natural movie responses and validated its generalization to parametric stimuli, including cell type identification. Leveraging this model to generate predicted responses to looming stimuli, we identify a discrete subset of retinal response types tuned for collision detection at low angular thresholds --- a specialization embedded within a broader, non-specialized retinal population. The digital twin is made publicly available as a community resource. Together, these findings provide a comprehensive functional map of retinal drive to the superior colliculus and an in silico platform for linking retinal cell types to behaviorally relevant superior colliculus computations.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Temporal Dynamics of BOLD fMRI Predict Intracranially-Confirmed Seizure Onset Zones in Drug-Resistant Epilepsy
Objective: In individuals with drug-resistant epilepsy, accurately identifying the brain regions where seizures originate is a critical prerequisite to guide surgical treatment and achieve seizure freedom. To accomplish this, intracranial EEG is considered the gold standard, providing the spatio-temporal high-resolution data necessary to pinpoint epileptogenic activity. However, this precision is achieved through an invasive procedure with significant patient burden, which is fundamentally limited by the electrode placement and spatial coverage. Methods: In this study, we investigated the potential utility of preoperative resting-state fMRI to non-invasively map alterations in brain dynamics at the whole brain level. Region-wise brain dynamics were quantified with complementary measures of local autocorrelation decay rates. We assessed the capacity of these derived features to effectively identify intracranial EEG confirmed seizure onset zones in 18 individuals with drug-resistant medial temporal lobe epilepsy. Overall, the study cohort contained 3867 implanted electrodes of which 159 classified as seizure onset zones by two independent board certified epileptologists. Results: Overall, our findings reveal more constrained temporal dynamics for brain regions associated with seizure onsets compared to non-seizure onset zones. Individual-level prediction showed a performance better than chance in 15 of the 18 patients. The overall predictive performance across all patients yielded a median AUC of 0.81, a median true positive rate of 0.75, and a median true negative rate of 0.83. Furthermore, in a subset of 13 patients, those with negative seizure outcomes showed higher probabilities of seizure onset zone predictions outside the resection area compared to those with good outcomes. Significance: Overall, our findings suggest that altered temporal dynamics derived from preoperative resting-state fMRI represent a promising non-invasive approach for delineating epileptogenic tissue, potentially informing intervention strategies and guiding electrode placement.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Temporal Interference Stimulation of the Motor Cortex Produces Frequency-Dependent Analgesia
Background: Transcranial temporal interference stimulation (tTIS) is an emerging noninvasive neuromodulation approach that enables focal, frequency-specific modulation of deep brain regions, offering a novel method for investigating therapeutic mechanisms underlying brain and mental health disorders. Pain is a key target because it is a feature of multiple disorders and is increasingly understood to depend on brain circuits. Here, we tested the effects of tTIS on bilateral evoked pain, capitalizing on converging evidence from human and animal studies indicating that the primary motor cortex (M1) contains body-wide inter-effector regions and has descending projections to regions implicated in nociceptive, motivational, and autonomic processing, making it a key cortical target for pain modulation. Methods: We conducted a pre-registered, triple-blind, randomized crossover study (N = 32, 160 study sessions), investigating frequency-dependent effects of tTIS applied to the left M1 on experimentally evoked thermal pain in healthy adults. We tested four stimulation frequencies (10 Hz, 20 Hz, 70 Hz, and sham) on separate days (>10,000 pain trials total). Noxious heat was applied to both the right and left forearms using individually calibrated temperatures both pre- and post-stimulation. Results: Active tTIS produced significant analgesia at all stimulation frequencies (10 Hz, 20 Hz, and 70 Hz) relative to sham (Cohens d = 0.46-0.82, all p < 0.05). 10 Hz produced the greatest reduction (d = 0.82), and both 10 Hz and 20 Hz produced more analgesia than 70 Hz (d = 0.44 and 0.38, respectively; p < 0.05). Stimulation-related sensations were equivalent across frequencies, and participants were blind to condition. Pain reductions remained stable over a ~40-min post-stimulation period and were bilateral, consistent with stimulation of body-wide inter-effector regions. Conclusions: These results provide the first evidence that tTIS can reliably reduce experimental pain perception in humans in a frequency-dependent manner, providing a foundation for noninvasive pain modulation with tTIS.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Reproducibility of Diffusion, Shape, and Connectivity Metrics Across Scanners: Implications for Multi-Site Tractography
Multi-site diffusion MRI studies face scanner-induced variability that can obscure biological signal. Harmonization methods such as ComBat have been developed to address this, but have been evaluated primarily on diffusion scalar metrics. Whether scanner reproducibility differs across fundamentally distinct tract-derived representations has not been systematically compared. Here, we compared the reproducibility of three metric families (diffusion, shape, and connectivity) across 36 association tracts using the MASiVar dataset (5 subjects, 4 scanners, 27 sessions). We assessed intraclass correlation coefficients (ICC) and multivariate subject discrimination at baseline, under dimensionality reduction, and after ComBat harmonization. At baseline, shape metrics showed the highest reproducibility (median ICC 0.69), followed by connectivity (0.49) and diffusion (0.34). Shape and connectivity achieved comparable subject discrimination (both 1.75), significantly exceeding diffusion (1.23). ComBat harmonization improved all families but harmonized diffusion (0.58) remained below unharmonized shape (0.69), indicating that metric family selection remains consequential even after harmonization. Under low-dimensional representation, connectivity showed the largest gains (ICC 0.86, subject discrimination 3.0), exceeding other families at any dimensionality. Analysis of principal component loadings identified a small number of cortical regions per tract (median 6) that capture 95% of the reproducible connectivity signal, providing a per-tract reference for selecting the most informative regions in future multi-site studies. These findings indicate that the choice of which tract-derived metrics to analyze in multi-site studies deserves at least as much consideration as how to harmonize them.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Analyzing multisensory integration: dos and donts
Multisensory perception is a cornerstone paradigm for understanding how the brain constructs coherent representations of the world from noisy, fragmented sensory inputs. For decades, researchers have used the magnitude of crossmodal illusions, the width of the temporal binding window, and related behavioral indices as direct proxies for 'integration strength,' and have leveraged these measures to compare multisensory function across developmental, clinical, and aging populations. Here we argue that this descriptive practice is fundamentally compromised: behavioral readouts of multisensory integration are composite measures jointly shaped by unisensory precision, amodal priors, and the binding process itself, and cannot be interpreted in isolation. Drawing on simulations within a Bayesian Causal Inference framework, we show how identical behavioral patterns can arise from very different underlying causes, leading to systematic misattribution of group differences to 'deficits' or 'enhancements' in integration. We review complementary computational frameworks, including drift diffusion, multisensory correlation detection, and statistical facilitation models, and outline their respective explanatory limits. Finally, we provide a model-based inference pipeline, from experimental design and unisensory baselines to parameter estimation and interpretation, that disentangles sensory fidelity, prior expectations, and integrative tendency. Adopting this normative approach is essential for cumulative progress in basic multisensory research and for its translation to neuropsychiatric assessment, lifespan research, and artificial perceptual systems.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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SingleBehavior Lab: behavioral sequencing and phenotyping with lightweight task specific adaptation
Understanding behavioral differences between experimental groups and quantifying action structure in behavioral experiments remains challenging. Currently, most approaches rely on pose estimation followed by downstream classification, resulting in assay specific pipelines with substantial annotation requirements. Here we present SingleBehavior Lab (SBL), a framework for modeling behavior across experimental contexts using a standardized graphical interface. SBL leverages spatiotemporal embeddings from large video foundation models and combines them with lightweight contrastive adapters, a multi-head attention pooling (MAP) module and a temporal decoder to enable behavior sequencing and task-specific refinement. The framework supports few-shot learning, allowing small models trained on pretrained embeddings to improve action segmentation and classification with limited labeled data, without fine-tuning the underlying video model. In parallel, a large segmentation model with motion-aware memory is used to extract object-centered representations that, together with shared spatiotemporal embeddings, enable unsupervised clustering of behavioral states and analysis of their structure, including cluster prioritization, transition dynamics and attention-based interpretability. Across multiple assays and species, SBL supports identification of group-level differences and rare behaviors, and provides a basis for integrating behavioral representations across experimental contexts.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Direct Assessment of Short-Latency Intracortical Inhibition via Immediate TMS-Evoked Potentials
Short interval intracortical inhibition (SICI) is the most widely used neurophysiological index of GABAergic inhibition in the human cortex. However, it is an indirect measure, inferring synaptic inhibition from suppression of peripherally recorded motor evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS). In the standard protocol, a subthreshold conditioning pulse suppresses the MEP evoked by a suprathreshold test pulse delivered 1 to 5 ms later. Interpretation is further complicated by temporal overlap with short-interval intracortical facilitation (SICF), reflecting excitatory interactions at interstimulus intervals of ~1.5 and 2.7 ms. To overcome these limitations, we recorded immediate TMS-evoked EEG potentials (iTEPs; 1 to 10 ms post-stimulus) as a more direct measure of motor cortical activity in 16 healthy volunteers (20 to 35 years; 7 male). The conventional SICI protocol suppressed only later components of the iTEP, likely corresponding to late corticospinal volleys previously identified in epidural spinal recordings after suprathreshold TMS, while the earliest iTEP component was unaffected. Importantly, later iTEPs were suppressed to a similar extent whether conditioning to test intervals coincided with SICF peaks or troughs, and the magnitude of iTEP suppression correlated with concurrently recorded paired-pulse MEP suppression. SICI also reduced an early TEP component (N15; 10 to 20 ms), but paired-pulse N15 suppression showed a different dependence on stimulus intensity and did not correlate with MEP suppression. These findings demonstrate that SICI measured via MEPs does not reflect a global index of cortical GABAergic motor cortical inhibition but instead reflects inhibition within specific cortical circuits that can be investigated directly with iTEPs.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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A standardized framework resolves ambiguity in motor neuron loss across neurodegenerative diseases
Motor neuron (MN) loss is a hallmark of neurodegenerative disorders, yet its assessment remains variable, confounding mechanistic and therapeutic interpretation. To address this, we conducted a systematic review and meta-analysis of spinal muscular atrophy (SMA) mouse studies, revealing 60% variability in reported MN loss, largely attributable to nonspecific spinal cord sampling. Using a whole-segment approach with tissue clearing, MN tracing, and multimodal imaging, we confirmed segment-dependent differences in MN counts. Common MN markers (SMI-32, Nissl) lacked specificity, whereas choline acetyltransferase (ChAT) provided robust labeling in murine and human spinal cords. Deep learning-based whole-mount segmentation enabled unbiased MN quantification and validated manual counts. Integrating analysis with computational modeling established segment sampling as a key driver of variability and revealed degeneration patterns: widespread MN loss in amyotrophic lateral sclerosis (ALS), selective MN loss in severe SMA, and preservation in mild SMA models. These findings establish a framework for reproducible MN quantification.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Mistake gating leads to energy and memory efficient continual learning
Synaptic plasticity is metabolically expensive, yet animals continuously update their internal models without exhausting energy reserves. However, when artificial neural networks are trained, the network parameters are typically updated on every sample that is presented, even if the sample was classified correctly. Inspired by the human negativity bias and error-related negativity, we propose "memorized mistake-gated learning"--a biologically plausible plasticity rule where synaptic updates are strictly gated by current and past classification errors. This reduces the number of updates the network needs to make by 50% {approx} 80%. Mistake gating is particularly well suited in two cases: 1) For incremental learning where new knowledge is acquired on a background of preexisting knowledge, 2) For online learning scenarios when data needs to be stored for later replay, as mistake-gating reduces storage buffer requirements. The algorithm can be implemented in a few lines of code, adds no hyper-parameters, and comes at negligible computational overhead. Learning on mistakes is an energy efficient and biologically relevant modification to commonly used learning rules that is well suited for continual learning.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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History of Traumatic Brain Injury with Loss of Consciousness and APOE ϵ4 Carriers Synergistically Increase Late-Life Amyloid PET Burden
Background: Traumatic brain injury with loss of consciousness (TBI - LOC) is an established risk factor for dementia, yet the pathways linking remote TBI to Alzheimer disease (AD) biology remain incompletely defined. APOE {epsilon}4 is the strongest genetic risk factor for late - onset AD and is associated with greater amyloid accumulation; however, it remains unclear whether TBI - LOC amplifies APOE {epsilon}4 -- related vulnerability to amyloid deposition. This study assesses if a remote history of TBI - LOC synergistically interacts with APOE {epsilon}4 to increase late-life amyloid or tau burden. Methods: 429 participants completed the Ohio State University TBI screening tool and a PET amyloid scan quantified in centiloids. TBI history was classified by recency ( < 10 vs > 10 years) and severity (no TBI, dazing/confusion [TBI - DZ], TBI - LOC) with analyses stratified by degree of clinical impairment as assessed by Clinical Dementia Rating (CDR {equiv} 0 vs CDR >0 ). Logistic and linear regression models examined associations between TBI and amyloid, adjusting for age, sex, education, and APOE {epsilon} 4, including an APOE*LOC interaction term, while Fisher exact tests evaluated TBI recency and biomarker positivity. Results: In CDR{equiv}0 participants ( n {equiv} 365), 119 reported a history of TBI, comprising 56 TBI - DZ and 63 TBI - LOC. TBI - LOC but not TBI - DZ, correlated with elevated PET amyloid levels (p < 0.001; [4.6 - 17]). Furthermore, an interaction between APOE {epsilon}4 and TBI - LOC indicated that TBI - LOC augmented the amyloid - related risk associated with the APOE {epsilon} 4 allele (p {equiv} 0.003; [4.3 - 21]). The interaction persisted when stratified by TBI recency with only remote TBI - LOC (occurring more than 10 years prior) associated with increased PET amyloid (p {equiv} 0.003 [5.2 - 25]). No association between TBI and tau was identified in a subset with tau PET, and no TBI - amyloid correlations were observed among symptomatic participants (CDR > 0; n {equiv} 64) suggesting a ceiling effect of pathology once clinical dementia is present. Conclusions: History of remote TBI - LOC is linked to elevated amyloid PET levels in later life, particularly among APOE {epsilon}4 carriers with a CDR {equiv} 0. The specificity for amyloid (as opposed to tau) and its attenuation in cases with a CDR > 0 underscore the value of incorporating TBI history when screening for preclinical AD.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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GLP-1 agonism alters local field potential in the lateral septum and alters operant behavior in rats
GLP-1 agonists are an emerging treatment for disorders of consumption. They are most prominent as treatments for obesity, but recent literature suggests that they are effective at reducing the consumption of all types of hedonic substances. This clearly suggests a central, cognitive, mechanism rather than a peripheral mechanism or an interaction with a single signalling pathway, but the specific site or sites for this mechanism remain to be discovered. Candidate brain regions for this reward-modulating activity have a relative paucity of GLP-1 receptors, with the exception of lateral septum, which expresses an abundance of them. In these experiments we recorded local field potential from lateral septum while animals received either saline control or the GLP-1R agonist liraglutide. We find that liraglutide significantly reduced the power of both high-frequency oscillations and theta rhythm in the lateral septum, suggesting that GLP-1R agonism changes how lateral septum communicates with its network. In addition, we show that liraglutide causes animals to wait longer to respond for reward in a differential reinforcement of low rates paradigm. Together, these results suggest that a primary region in the control of the anticonsumptive action of GLP-1 agonists is the lateral septum, and that the coding of reward by this region is a central node in the network responsible for cognition about and behaviour with respect to reward.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Posterior parietal cortex guides sensorimotor associative learning by linking sensation to distal action
Sensorimotor associative learning enables animals to adaptively link sensory cues with motor actions, a process that is critical for survival and everyday behavior. While Hebbian mechanisms explain associations formed through temporally overlapping neural activity, a fundamental challenge arises when sensory stimuli and motor responses are separated by a delay, because sensory and motor neurons are rarely coactive. Here, we identify the rostro-lateral posterior parietal cortex (PPC-rl) as a cortical hub that bridges tactile stimuli and temporally delayed licking actions during sensorimotor associative learning. Using cortex-wide calcium imaging with single-cell resolution to track ~16,000 neurons simultaneously across sensory, motor, and association cortices, we find that PPC-rl uniquely exhibits sustained neural activity during the temporal delay early in learning, a signature that diminishes with expertise. Optogenetic silencing of this activity slows learning without impairing sensorimotor execution in expert mice. Learning strengthens the coupling of population dynamics within and between somatosensory and motor cortices. PPC-rl mediates this process by amplifying a low-dimensional communication subspace that synchronizes co-fluctuations across the somatosensory and motor cortices to facilitate linking. This PPC-rl dependent co-fluctuation dissolves post learning, underscoring the role of PPC-rl in bridging sensation to distal action. A biologically plausible network indicates that Hebbian plasticity with an eligibility trace gated by reward, PPC-rl persistent activity and PPC-rl dependent sensorimotor subspace communication synergize to support delayed association. Together, our findings uncover a PPC-rl based circuit mechanism that maintains temporal continuity to guide associative learning when sensory and motor events are separated in time.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Distinct contributions of motor imagery and execution to history-dependent biases in reaching
The recent movement history shapes motor performance, that is, previous movements can affect current movement characteristics such as trajectory shape. History effects are commonly attributed to carryover of motor-related activity. However, action execution entails sensory feedback; therefore, an alternative is that history effects stem from the sensory information produced by previous movements. To dissociate motor and sensory contributions, we assessed whether history effects emerge from imagined movements, which involve movement planning but not sensory feedback. Overt reaches around an obstacle led to systematic adjustment of the initial reach direction of following reaches - a hallmark of motor history. Imagined reaches around obstacles induced similar biases, albeit with smaller magnitude, presumably due to the need to inhibit overt execution during imagery. By contrast, execution but not imagery induced biases in late, feedback-related measures, suggesting that these history effects depended on sensory rather than motor aspects of the movement history. Thus, motor and sensory signals make distinct and complementary contributions to movement history: recent motor states shape feedforward planning, whereas recent sensory states shape feedback-related movement refinement.
in bioRxiv: Neuroscience on 2026-04-20 00:00:00 UTC.
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Correction to: Oestrogens are Not Related to Emotional Processing: a Study of Regional Brain Activity in Female-to-Male Transsexuals Under Gonadal Suppression
This is a correction to: R. S. Soleman, A. S. Staphorsius, P. T. Cohen-Kettenis, C. B. Lambalk, D. J. Veltman, M. A. A. van Trotsenburg, P. G. A. Hompes, M. L. Drent, W. P. de Ronde, B. P. C. Kreukels, Oestrogens are Not Related to Emotional Processing: a Study of Regional Brain Activity in Female-to-Male Transsexuals Under Gonadal Suppression, Cerebral Cortex, Volume 26, Issue 2, February 2016, Pages 510–516, https://doi.org/10.1093/cercor/bhu201
in Cerebral Cortex on 2026-04-20 00:00:00 UTC.
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Bringing to Light of a Nonrandom Choice of the Number of Letters, Words, and Stichs in Genesis 1–3 and Jeremiah 50–51, and Its Applications to the Approximate Reconstruction of an Hyperarchetype [version 1; peer review: awaiting peer review]
Background Certain exemplars of the Dao-De Jing are composed of exactly 4,999 characters, and an historical source affirms that there existed a version of the Dao-De Jing composed of exactly 5,000 characters. Results Here, we show with a p-value of 5 × 10−21 ⇒ Z > 9σ, that the different textual witnesses presently available attesting unto Genesis 1–3 are all descended from an hyperarchetype of exactly 4,000 letters, reconstructible from the Masoretic Text alone, and about 1/20th shorter than this one, while those attesting unto Jeremiah 50–51 are all descended from an hyperarchetype of exactly 4,000 plus 300 letters, also reconstructible from the Masoretic Text alone, but about 1/3rd shorter than this one. Discussion Our results disprove the Model b in favour of the Model a, and demonstrate that the long form of the Book of Jeremiah is not an extended edition of the short form, but that the short form is an abridged edition of the long form.
in F1000Research on 2026-04-19 06:19:12 UTC.
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Case Report: Integrative Multiomics to Establish Pathogenicity of novel GBE1 R198T Variant [version 1; peer review: awaiting peer review]
Background Glycogen Storage Disease IV (GSD IV) is a rare disease affecting 1 in every 760,000–960,000 live births. GSD IV is caused by mutations in GBE1, especially if it affects the central catalytic core domain of the glycogen branching enzyme (GBE) protein at 184th–600th residue. A novel missense mutation, GBE1 R198T, was detected in a 3-year-old boy in Indonesia. This variant has not previously been reported in allele frequency databases or classified as pathogenic. Method In this study, we used an integrative multi-omics diagnostic approach involving phenotype analysis, proband and trio genetic mutation analysis, protein molecular modeling, protein-ligand docking, and protein expression studies. We compared GBE1 R198T mutation with the wild-type and previously well-known pathogenic variants, L224P and Y329S, to analyze the clinical progression and pathogenic effects of R198T. Results Trio mutation analysis revealed that this mutation was inherited from a heterozygous parent. Functional prediction, molecular modeling, and docking analysis supported the R198T pathomechanism to cause structural changes in the GBE protein domain, which is detrimental to GBE ligand binding with maltoheptose (Glc7). An in vitro study further supported the decrease in GBE1 R198T protein expression compared to that in the WT. In addition, GBE1 R198T band intensity showed similar results to those of the GBE1 L224 variant, indicating potentially similar pathogenic characteristics exhibited by both variants. Conclusions This is the first study to establish the pathogenicity of the GBE1 R198T variant, and the first rare disease functional study reported in Indonesia.
in F1000Research on 2026-04-19 06:03:31 UTC.
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The Effect of Prehabilitation, Perioperative, and Postoperative Physiotherapy on Postoperative Outcomes in Adults Undergoing Laparoscopic Surgery: A Systematic Review [version 1; peer review: awaiting peer review]
Objective To determine the effectiveness of physiotherapy interventions for patients undergoing laparoscopic abdominal surgery on postoperative outcomes and the optimal frequency, timing, and type of intervention. Methods A literature search was performed in AMED, MEDLINE, CINAHL, Scopus, and Web of Science from 2009 to 2023. Randomised controlled trials (RCTs) that examined pre-operative and/or post-operative physiotherapy interventions on adults undergoing laparoscopic abdominal surgery were included. Intervention characteristics, outcome measures, and results were extracted. A tabulated summary and narrative discussion were generated to compare similarities and differences across each study. Results From 3811 studies identified, 9 RCTs met inclusion criteria. Preoperative incentive spirometry (IS) alone or with inspiratory muscle training (IMT) showed no postoperative pulmonary complications (PPCs) but had mixed effects on pulmonary function. Perioperative breathing interventions reduced PPCs, length of stay, and hospital costs. Trials on prehabilitation or postoperative IS found no significant PPC differences. However, prehabilitation, deep breathing exercises, IS, and mobilisation with chest physiotherapy improved pulmonary function. Mobilisation, preoperative IS, and perioperative breathing also enhanced arterial blood gas (ABG) results. Six-minute Walk test distances increased with prehabilitation, perioperative breathing, and mobilisation with chest physiotherapy. All trials had a high risk of bias, with PEDro scores of 5–8/10, indicating “fair” to “good” quality. Conclusion Perioperative breathing was the only intervention shown to reduce PPC rates. Prehabilitation, deep breathing exercises, IS, and mobilisation with chest physiotherapy improved pulmonary function. Larger, well-designed RCTs are needed to confirm the effectiveness of these interventions. PROSPERO (registration ID: 529588).
in F1000Research on 2026-04-19 06:00:13 UTC.
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Mapping Virtual Reality Research in Science Education: A Systematic and Bibliometric Review with Implications for Ethnoscience Research [version 1; peer review: awaiting peer review]
Background Virtual reality (VR) has emerged as a transformative technology in science education, offering immersive learning experiences that enhance conceptual understanding. However, its integration with ethnoscience remains underexplored. Methods This study employed a systematic literature review following PRISMA guidelines combined with bibliometric analysis. Data were collected from the Scopus and CrossRef databases (2016–2025) and analyzed using VOSviewer. Results The findings indicate a steady increase in VR-related publications, particularly in 2025. Research is predominantly conducted in higher education contexts, with chemistry and biology as the main disciplines. Research and development, as well as experimental methods, are the most commonly employed approaches, with questionnaires and tests serving as the primary data collection instruments. Bibliometric mapping identifies virtual reality as the central theme, with emerging interdisciplinary connections, including ethnoscience, although these remain limited. Conclusions VR research in science education is rapidly growing and holds strong potential to enhance learning. However, integration with ethnoscience remains limited, highlighting the need for culturally contextualized VR learning environments.
in F1000Research on 2026-04-19 05:57:43 UTC.
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Factors Influencing Customer Satisfaction and Behavioral Intention in Local Food Tourism: A Structural Equation Modeling Approach [version 1; peer review: awaiting peer review]
Local food tourism (LFT) significantly impacts destination experiences by shaping tourists’ perceptions, satisfaction, and post-visit behavior. The limited empirical understanding of how experiential attributes influence satisfaction and behavioral intention (BI). This research uses a thorough Structural Equation Modeling (SEM) framework to examine the variables affecting customer satisfaction (CS) and business intelligence (BI) in LFT. 380 valid responses were obtained from a quantitative cross-sectional survey of visitors who sampled local cuisine at particular Thai culinary sites. A structured questionnaire measured six exogenous constructs: food quality (FQ), Authenticity (AU), service quality (SQ), physical environment (PE), cultural experience (CE), and perceived value (PV) along with CS as a mediator and BI (revisit intention and Consumer referral behavior) as the endogenous outcome. Cronbach’s alpha, composite reliability (CR), average variance extracted (AVE), and discriminant validity using the Fornell-Larcker criterion were used to evaluate reliability and validity. Utilizing confirmatory factor analysis (CFA), the measurement model was validated. The findings suggest that CS is strongly and favorably influenced by FQ, AU, CE, and PV. The association between experience qualities and loyalty outcomes is partially mediated by CS, which also strongly predicts BI. A well-fitting measurement model is indicated by the model’s acceptable goodness-of-fit indices, which include a Comparative Fit Index (CFI) of 0.952, Tucker–Lewis Index (TLI) of 0.945, Root Mean Square Error of Approximation (RMSEA) of 0.056, and Standardized Root Mean Square Residual (SRMR) of 0.058. SPSS findings provide practical insights for enhancing tourist loyalty through authentic and high-quality culinary experiences.
in F1000Research on 2026-04-19 05:54:32 UTC.
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Designing a Material Requirements Planning (MRP) System Using Blockchain Technology: A Case Study in Italian Chaizlonat Furniture Exhibition / Baghdad [version 1; peer review: awaiting peer review]
Materials Requirements Planning (MRP) system focuses on planning and ensuring the availability of raw materials, parts and components, as needed during production stages, This requires highly, accurate determination of required quantities of production inputs and reliable delivery schedules. Consequently, it necessitates the development of robust and accurate databases with the organization’s suppliers. Block chain technology is one of the most important technologies of the Fourth Industrial Revolution, enabling stakeholders (organizations, partners, and individuals) to interact directly without intermediaries. This technology rely on peer-to-peer networks, and allows sharing data between the partners within a secure, encrypted platform. This research aims to design a Material Requirements Planning (MRP) system using blockchain technology in Italian Chaizlonat Furniture Exhibition/Baghdad (research site), with Corner (ES) product (research case), this by design blockchain platform that ensures Sharing the data required by the exhibition and suppliers about the corner, its components, Production and supplying timings, and tracks supply procedures without intermediaries. The research findings demonstrate the efficiency of the blockchain platform in meeting customer demand on time, eliminating the quantities and cost of stock, and increasing the profits from the corners.
in F1000Research on 2026-04-19 05:50:43 UTC.
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Dynamics of Body Mass Index and Serum Albumin Levels Before and After the Intensive Phase of Tuberculosis Treatment [version 1; peer review: awaiting peer review]
Introduction Tuberculosis remains a major global health problem and is frequently associated with malnutrition, which can negatively affect treatment outcomes. This study aimed to evaluate changes in body mass index (BMI) and serum albumin levels before and after the intensive phase of tuberculosis treatment. Methods An observational analytic study with a prospective cohort design was conducted at Dr. Wahidin Sudirohusodo Hospital, Makassar. A total of 175 newly diagnosed tuberculosis patients were enrolled. BMI and serum albumin levels were measured at baseline and after completion of the two-month intensive treatment phase. Paired sample t-tests were used to assess differences between pre- and post-treatment values. Results BMI increased significantly from 19.21 ± 3.55 kg/m2 to 19.78 ± 3.50 kg/m2 (p < 0.0001), corresponding to a 2.96% improvement. Serum albumin levels also increased significantly from 3.06 ± 0.62 g/dL to 3.25 ± 0.64 g/dL (p < 0.0001), with an average improvement of 6.17%. Additionally, the proportion of patients with normal nutritional status increased, while the proportion of underweight patients decreased significantly after treatment (p = 0.002). Conclusions Intensive-phase anti-tuberculosis therapy is associated with significant improvements in both anthropometric and biochemical nutritional parameters. Routine monitoring of BMI and serum albumin may serve as practical indicators for assessing treatment response and guiding nutritional interventions in tuberculosis patients.
in F1000Research on 2026-04-19 05:47:23 UTC.
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Bioinformatic identification of abiotic stress tolerance genes in actinomycetes isolated from Lomas Cerro Campana, Peru [version 1; peer review: awaiting peer review]
Actinomycetes from arid environments are an important source of genes associated with abiotic stress adaptation and of biotechnological interest; in this context, the study aimed to genetically characterize strains isolated from the Lomas Cerro Campana ACP (Peru) to identify factors associated with tolerance to salinity, temperature, and pH, with potential applications in bio-inputs for degraded soils. Methods Rhizosphere soil samples were collected at four locations within the ACP; Streptomyces strains were isolated and their growth was evaluated under different temperatures, pH levels, and NaCl concentrations; Additionally, the genomes were sequenced and assembled, their quality was assessed, they were functionally annotated using Prokka and eggNOG-mapper, and taxonomic identification was performed using dDDH/GBDP. Results All four strains grew within a pH range of 4–10, with optimal growth occurring between pH 6 and 8, and showed limited tolerance to high salinity, with best growth observed at low or zero NaCl concentrations; P9.2 exhibited the best overall performance under varying temperature and pH conditions, while P2.1 and Q3.3 were confirmed as known species of the genus Streptomyces, and P9.2 and Q6.2 showed dDDH values below the species threshold. The functional profile revealed genes and categories associated with thermal adaptation and proteostasis, pH homeostasis and ion flux, and osmotic tolerance and structural integrity, with P2.1 standing out for its high concentration of genes involved in replication and repair, and Q6.2 showing a strong association with energy production for the maintenance of electrochemical gradients. Conclusions The results demonstrate that the strains isolated from Lomas Cerro Campana possess a genetic and functional basis consistent with their tolerance to extreme abiotic conditions, with P9.2 standing out for its superior overall phenotypic performance and P9. 2/Q6.2 for its taxonomic uniqueness, which supports its value as a promising biotechnological resource for soil restoration and agricultural strategies in the context of climate change.
in F1000Research on 2026-04-19 05:42:58 UTC.
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Khmer–Vietnamese Bilingual Education for Ethnic Minority Primary Students in Vietnam’s Mekong Delta: Exploring Influential Factors [version 1; peer review: awaiting peer review]
Background/purpose Bilingual education plays a vital role in expanding learning opportunities, preserving indigenous languages and cultures, and supporting minority students in attaining academic success in the national language. It also fosters social equity and inclusion, thereby contributing to the sustainable development of minority communities in multicultural contexts. Against this backdrop, the present study investigates the factors influencing Khmer–Vietnamese bilingual education (KhVBE) for Khmer ethnic minority primary students in the Mekong Delta. Materials/methods Survey data were collected from 269 educational administrators and teachers who were directly responsible for program management and instructional delivery. Results The findings reveal that internal learner factors (ILF), information channels (IC), situational factors (SF), and engagement in professional development activities (EPDA) exert statistically significant positive effects on KhVBE. In contrast, contextual factors for the application of bilingual education (CABE) did not show a significant influence. Conclusion The study contributes both theoretically and practically to the field of bilingual education in Vietnam. It provides policy recommendations for administrators and stakeholders aimed at enhancing the effectiveness of Khmer–Vietnamese bilingual education programs.
in F1000Research on 2026-04-19 05:08:43 UTC.
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Contemporary global research cultures: results from a global survey about research conditions [version 1; peer review: awaiting peer review]
Background The global research and higher education landscape has expanded enormously within the last 30 years. Bibliometric data reveal the increase in knowledge production, co-authorship patterns and collaborations. There are, however, only limited data that allow for comparing the research conditions among the different regions in the world that cover different disciplines and status groups. Existing surveys on research conditions are restricted to specific groups of countries, mainly in the global north. Method Against this background, we present the results of a global survey on research conditions, conducted in partnership with the platform ResearchGate. The study draws data from more than 5,000 researchers from around the world. The study addressed key dimensions of professional environment: individual resources, perceived research conditions, work satisfaction. and network embeddedness. The survey data were enriched with other secondary data on the country level, namely, V-Dem data base as well as data on economic performance (GNI per capita). Results The results reveal significant regional disparities in funding, infrastructure, and time for research and teaching, with academics in the Global North reporting greater satisfaction and more time for research compared to their counterparts in the Global South. Academics in autocratic regimes report satisfaction with their infrastructure, although external funding remains limited. The findings demonstrate the diversity of research conditions in the organizational settings, career incentives, and institutional conditions. These findings complement bibliometric data showing rapid publication growth in autocratic countries and a tendency towards international collaboration and highlight the diversity and complexity of global research cultures, contributing to a richer understanding of epistemic diversity.
in F1000Research on 2026-04-19 05:06:02 UTC.
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How Anterior Crossbite Severity Relates to Appearance-Based Bullying in School-Age Children: Evidence from the ROMA Index [version 1; peer review: awaiting peer review]
Introduction This study examined the prevalence of anterior crossbite in school-age children, investigated the frequency of appearance- related bullying, and determined whether crossbite severity correlates with bullying exposure among children aged 8–12 years. Materials and Methods A cross-sectional study involved 2,080 children from public schools in Damascus, using random cluster sampling. Anterior crossbite and other occlusal issues were assessed using the ROMA Index. Dental appearance-related bullying was evaluated using a modified Olweus Bully/Victim Questionnaire; children reporting bullying two or more times monthly were classified as victims. Bullying types—teasing, name-calling, social exclusion, and physical aggression—were documented along with occurrence settings. Severity scores were calculated by summing numerical codes for each bullying type. Relationships between occlusal characteristics and bullying were analyzed using Chi-square tests, Cramer’s V, and logistic regression, adjusting for age and gender. Results Of 2,080 children aged 8 to 12 years, 19.6% had anterior crossbite, and 34.4%reported dental appearance-related bullying. Children with anterior crossbite were significantly more likely to experience bullying (p < 0.001), with bullying intensity increasing proportionally to crossbite severity. Teasing and mocking were the most prevalent forms, primarily occurring in playground settings. Conclusion Anterior crossbite severity functions as a meaningful risk indicator for psychosocial bullying in children, extending beyond simple dental concerns. Incorporating crossbite severity screening into school-based prevention programs offers a practical strategy to improve both oral health and psychological well-being in childhood.
in F1000Research on 2026-04-19 05:02:49 UTC.
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An Integrated Pedagogical–Technical Framework for Deep Learning in Vocational Education and Training: A Systematic Review [version 1; peer review: awaiting peer review]
Abstract* Background Vocational Education and Training (VET) institutions play a crucial role in welcoming the era of Industry and Society 5.0, where the integration of cyber-physical technology requires the mastery of employability skills that include adaptability, work readiness, and transversal competencies. Deep Learning, as an advanced data-based computational learning system, offers transformative potential for redesigning vocational learning processes. Methods This study employed a Systematic Literature Review (SLR) method following the PRISMA protocol. A total of 16 articles were identified, screened, and analyzed in depth to synthesize the pedagogical and technical parameters of Deep Learning in VET and to develop an integrated conceptual framework. Results Key findings identify that the most effective Deep Learning parameters are not only technical (learning rate, epoch), but depend on their integration with pedagogical frameworks. The key parameters that emerge are the ability of Deep Learning models to support: (1) mastery learning through adaptive learning pathways; (2) contextual learning by presenting real-world industry problems; (3) authentic learning through smart work practice simulations; and (4) immersive learning in responsive virtual environments. Conclusions The implications of this research confirm that the application of Deep Learning in VET institutions is no longer sufficient to simply adopt the technology, but must be pedagogically integrated through a model structure specifically designed to strengthen authentic and competency-based learning. This model is positioned to enable graduates to independently update their occupational skills through a Deep Learning-based adaptive system.
in F1000Research on 2026-04-19 04:58:51 UTC.
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Comparison between the protective effect of applying sodium fluoride varnish alone and applying CO2 laser with it in permanent teeth. In Vitro study [version 1; peer review: awaiting peer review]
Background Fluoride administration plays a critical role in the management and prophylaxis of dental caries. Research indicates that laser irradiation can enhance the uptake of fluoride into dental enamel, an effect that is particularly pronounced when used as an adjunct to topical fluoride treatments. The present study aimed to evaluate the impact of CO₂ laser irradiation on fluoride uptake in the enamel of permanent teeth. Methods Six human upper premolars, extracted for orthodontic reasons, were selected for this study. The roots were separated from the crowns, and each crown was then sectioned mesiodistally to create mesial and distal halves. These halves were randomly assigned to either an experimental or a control group (n = 6 per group). All specimens received an application of 5% sodium fluoride (NaF) varnish. Subsequently, the samples in the experimental group were subjected to irradiation with a 1 W CO2 laser for a duration of 15 seconds. To assess the effects of the treatments, fluoride uptake was measured and the topographic characteristics of the enamel surface were examined using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Statistical analysis of the data was performed using SPSS software version 26 (IBM, USA). Results Energy-dispersive X-ray spectrometry analysis showed a significant increase in the percentage of fluoride with the application of the laser, The results of the mean ranks showed that the fluoride and CO₂ laser group recorded significantly higher ranks in the fluoride element (8.75 vs. 4.25), reflecting a higher concentration and confirmed statistical significance. Statistically, in the Mann-Whitney U test, a significant statistical difference in fluoride ratios appeared between the two groups (P value = 0.026) smaller than (0.05), which indicates the effectiveness of using CO₂ lasers in enhancing fluoride absorption within the tooth structure. Conclusion The results showed CO₂ laser irradiation of dental enamel resulted in increased fluoride uptake.
in F1000Research on 2026-04-19 04:48:20 UTC.
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The Role of Smart Manufacturing in Supporting Production Flexibility in Light of Market and Demand Fluctuations [version 1; peer review: awaiting peer review]
Objective To study and analyze the role of smart manufacturing technologies in enhancing the production flexibility of industrial enterprises by enabling rapid responses to market and demand fluctuations, minimizing downtime and operational waste, and improving efficiency in resource utilization, thereby contributing to sustainable competitive advantage. Research Design and Methods The article is based on a survey. Data were used in a survey the many Industries Companies for Electrical and Electronic in Iraq, which is considered a significant factor in its Production Flexibility. This companies were selected because it primarily uses Smart Manufacturing Basics. Confirmatory factor analysis was used because it adopted the balanced free least squares method instead of the maximum likelihood method. Findings The research results indicate that smart manufacturing represents a strategic approach ensuring the ability of organization to respond effectively to market fluctuations and demand levels, in addition The results showed that organizations that adopt smart manufacturing have greater organizational flexibility and productivity compared to traditional organizations, which positively impacts their ability to cope with uncertainty in the business environment. Implications and Recommendations Encourage industrial organizations to invest in adopting smart manufacturing technologies (artificial intelligence, the Internet of Things, and predictive analytics) as a key tool for enhancing production flexibility, also Focus on building human capacity through continuous employee training and qualifying them to use and manage smart manufacturing technologies efficiently, enhancing organizations’ readiness to digital transformation. Contribution and Value Added While previous studies have not quantified The Role of Smart Manufacturing in Supporting Production Flexibility in Light of Market and Demand Fluctuations in industrial companies, this article makes an important contribution by providing empirical evidence on how industrial companies view their policies as a useful tool in meeting their needs when providing support and assistance for the flexibility of its production processes in industrial companies.
in F1000Research on 2026-04-19 04:37:05 UTC.
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Students’ perceptions of online learning and their impact on deep learning and proactive decision-making in higher education [version 1; peer review: awaiting peer review]
Online learning increases student flexibility and engagement, but its effectiveness depends on a design that encourages deep learning and proactive decision-making rather than just surface activities. This study aims to examine the relationships among student perceptions of online learning, deep learning tendencies, and proactive decision-making abilities in 202 students (M ± SD = 20.46 ± 1.75). Data were collected using the Distance Education Learning Environments Survey (DELES), the Revised Two Factor Study Process Questionnaire (R-SPQ-2F), and the Students’ Proactive Decision-Making Scale (SPDMS-18). Spearman’s test showed that positive perceptions of online learning were significantly related to deep learning (ρ = 0.634, p < 0.001) and proactive decision-making (ρ = 0.474, p < 0.001). Descriptive results showed a positive trend in all online learning indicators, fluctuations in motivation and deep learning strategies in the middle semester, and high stability in the proactive decision-making aspect. These findings confirm that high-quality online learning experiences encourage the adoption of deep learning approaches and proactive decision-making, including intrinsic motivation, analytical strategies, initiative, and goal-setting. Practical implications emphasize the importance of digital pedagogy training for lecturers, the development of e-learning systems that support student independence, and curricula that stimulate analysis and reflection. This research contributes to the design of digital-based higher education oriented toward 21st-century competencies.
in F1000Research on 2026-04-19 04:34:28 UTC.
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AI-Integrated Counseling Administration Quality and Organizational Support as Drivers of Early Risk Detection in Indonesian Schools [version 1; peer review: awaiting peer review]
Currently, cases of bullying and violence in secondary schools in Indonesia are showing an increasing trend. Therefore, the development of a proactive early detection system focused on the welfare and mental health of students is a primary goal. Current dynamics indicate that the use of AI in education is still dominated by technical, academic, and adaptive learning aspects, while the context of administrative counseling services and early detection of violence in schools has not been fully integrated. This study analyzes the integration of AI, administrative counseling quality, and school support in supporting the early risk detection of students in secondary schools in Indonesia. Using a quantitative approach with a survey design involving 619 students, data were collected through Google Forms and analyzed using SEM-PLS. The results of the research data analysis indicate a positive effect of AI on the quality of administrative counseling, organizational support, and early risk detection. The quality of administrative counseling also has a significant effect on school support and early risk detection, with school support having the strongest effect on early risk detection, with β = 0.497. Furthermore, administrative counseling quality and school support act as mediators of the relationship between AI variables and early risk detection. The novelty of this research lies in the development and testing of an integrative model based on socio-technical systems that places the quality of school counseling and support administration as a key factor in the effectiveness of AI utilization for the prevention of bullying and violence in secondary schools in Indonesia.
in F1000Research on 2026-04-19 04:30:51 UTC.
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Non-consensual condom removal among adults: prevalence, correlates, and outcomes in quantitative studies – A systematic review [version 1; peer review: awaiting peer review]
Background Non-consensual condom removal (NCCR), generally referred to as “stealthing,” is an increasing trend among young people yet under-recognised as a form of sexual violence and may increase risk of STI/HIV transmission, unintended pregnancy, and psychological or psychosexual harm. Despite growing attention on social media platforms over the past few years, the epidemiology of NCCR remains unclear, and legal responses are inconsistent. This review asked: What is the prevalence of NCCR among adults (≥18 years), and how does it vary across populations and settings? The objectives were to synthesise quantitative prevalence estimates, describe demographic variation where data permit, and summarise reported outcomes. Methods Following PRISMA 2020, we searched MEDLINE, CINAHL, and APA PsycINFO, supplemented by screening 200 Google Scholar records and backward/forward citation chasing. Eligible studies were English-language, peer-reviewed quantitative studies reporting NCCR prevalence (victimisation and/or perpetration) among adults. Two reviewers independently screened titles/abstracts and full texts, with disagreements resolved through discussion. EndNote was used for reference management and de-duplication. Study quality was appraised using the Joanna Briggs Institute checklist for analytical cross-sectional studies. Due to heterogeneity in populations, recall periods, and measurement approaches, findings were synthesised narratively. Results Eleven studies were included from the United States (n = 6), Australia (n = 1), Australia/New Zealand (n = 1), Canada (n = 1), Brazil (n = 1), and India (n = 1). Most were cross-sectional surveys conducted among university students (n = 5), local community (n = 4), local community and college students (n = 1), Amazon MTurk sample (n = 1) and in sexual health clinic settings (n = 1). Sample sizes varied across the included studies, ranging from 96 to 2,550 participants. Women’s victimisation prevalence ranged from 9.3% to 32%, and MSM victimisation reached 35%. Men’s perpetration prevalence ranged from 1.3% to 19.8%. However, the reasons behind it remain unclear. Common correlates included substance use, minority status (where assessed), relationship or sexual history factors, and prior victimisation. Outcomes were inconsistently measured, but studies that assessed these domains included sexual health and psychological impacts. Conclusions NCCR is reported internationally with substantial prevalence in women and MSM, although estimates vary by setting and measurement. Standardised definitions, validated measures, and consistent reporting of outcomes are needed to strengthen surveillance and inform clinical screening, prevention, and legal responses. Unlike broad scoping syntheses, this review provides an objective-led, quality-appraised synthesis of quantitative prevalence estimates and measured impacts.
in F1000Research on 2026-04-19 04:27:11 UTC.
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Dermofat Graft Implantation in Post-Axillary Dissection Defects for Lymphatic Regeneration, Lymphedema Prevention and Reconstruction in Breast Cancer: A Case Series [version 1; peer review: awaiting peer review]
Background Lymphedema remains a debilitating complication following axillary lymph node dissection (ALND) in breast cancer surgery, with limited effective preventive strategies available, particularly in low-resource settings. Dermofat graft (DFG) implantation, an autologous technique combining dermis and adipose tissue, has emerged as a potential method to restore tissue volume, and promote lymphangiogenesis. This study evaluates the feasibility, safety, and preliminary efficacy of DFG implantation in preventing lymphedema and reconstructing surgical defects following ALND in breast cancer patients. Methods A prospective case series was conducted involving seven female breast cancer patients (aged 44–66 years) undergoing modified radical mastectomy (MRM) or breast-conserving surgery (BCS) with ALND. Intraoperative DFGs harvested from the lower abdomen were implanted into axillary and/or breast defects. Outcomes included arm volume measurements (preoperatively and at 1, 3, and 6 months), incidence of lymphedema (International Society of Lymphology criteria), lymphoscintigraphy for lymphatic regeneration, and postoperative complications. Results Across all seven cases, no early-stage lymphedema (stage 0–II) was observed at six months postoperatively. Lymphoscintigraphy performed in four patients (57.1%) demonstrated new lymphatic vessel formation. Minor complications included seroma with partial fat lysis (n = 2) and transient fever (n = 1), all of which resolved without long-term sequelae. Cosmetic outcomes were favorable, with improved axillary contour and preserved breast symmetry in BCS cases. Conclusion Dermofat graft implantation is a feasible and safe technique that may simultaneously prevent lymphedema and enhance reconstructive outcomes in breast cancer surgery. DFG offers a resource-efficient alternative to microsurgical procedures, particularly valuable in low- and middle-income settings.
in F1000Research on 2026-04-19 04:21:34 UTC.
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Comparison Of Clinical Stadium Changes And Immunologic Parameter Of Adult HIV patients With Dolutegravir And Efavirenz Based Antiretroviral Therapy [version 1; peer review: awaiting peer review]
Background Human immunodeficiency virus (HIV) remains a major global health challenge. Dolutegravir-based antiretroviral therapy (ART) is recommended as the preferred first-line regimen due to its high efficacy and tolerability. However, real-world evidence comparing clinical and immunologic outcomes between dolutegravir- and efavirenz-based therapies is limited in Indonesia. This study compared changes in clinical stage and immunologic parameters among adult HIV patients receiving these regimens. Methods This observational analytic study used a retrospective cohort design. Data were collected from medical records of adult HIV patients at Dr. Wahidin Sudirohusodo Hospital (Makassar, Indonesia) from January 2020 to December 2025. Included patients were aged ≥18 years, received dolutegravir- or efavirenz-based therapy for ≥12 months, and had complete baseline, month 6, and month 12 data on WHO clinical stage and CD4 T-cell counts. Analyses used chi-square tests (p < 0.05 significance). Results Of 175 patients, most were male (76.6%) and aged <50 years (89.7%). At baseline, all had CD4 counts <200 cells/mm3; 73.1% were WHO stage III–IV. No baseline clinical stage difference existed between groups (OR 1.64; 95% CI 0.78–3.42; p = 0.12). By month 12, 77.1% achieved clinical stages I–II in both groups. Immunologic recovery occurred in 72.6% (CD4 ≥ 200 cells/mm3), with dolutegravir patients showing higher CD4 recovery (OR 2.12; 95% CI 1.06–4.25; p = 0.02). Conclusions Both regimens improved clinical and immunologic outcomes over 12 months, but dolutegravir-based ART was associated with superior CD4 recovery. Early diagnosis and timely ART initiation are essential for optimizing HIV outcomes.
in F1000Research on 2026-04-19 03:40:15 UTC.
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Knowledge of research misconduct amid North-African post-graduate dental students: A cross sectional study [version 6; peer review: 1 approved, 1 approved with reservations, 3 not approved]
Background Research misconduct (RM) in the academic community remains poorly understood among post-graduate dental students (PGDSs) in North Africa. Data on the knowledge of RM (KoRM) level in this population is lacking. This brief report assessed KoRM of Tunisian PGDSs’. Methods A cross-sectional study was conducted at the Faculty of Dental Medicine of Monastir, involving 147 PGDSs registered in 2022. Students were recruited via email invitations and convenience sampling at a medical congress. A French survey (i.e. ; Laval University quiz) with 11 questions on KoRM, offering three-choice answers (yes/no/maybe) was administered. Each correct answer received one point, and a total score below six indicated a low-level of KoRM. Results The mean±standard deviation KoRM score of the 106 students who accepted to participate in the study was 4.4±1.8, indicating a low-level of KoRM. The majority of PGDSs (85.85%) demonstrated a low-level of KoRM. A comparison between subjective and objective assessments of KoRM levels revealed that a significant percentage of PGDSs underestimated their knowledge (62.26% vs. 85.85%, respectively). Conclusion North-African PGDSs have a low-level of KoRM. This emphasizes the need for further efforts to enhance awareness and promote better KoRM in this population.
in F1000Research on 2026-04-19 03:30:14 UTC.
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Case Report: Improved Oxygenation after One Lung Ventilation in Severe Cardiomegaly due to Cor Pulmonale; analysis with Heart-Lung Interaction Approach [version 4; peer review: 2 approved with reservations]
Introduction One-lung ventilation (OLV) is used to isolate one lung during thoracic surgery, but manipulation and positioning can affect heart-lung interaction. Cardiomegaly may exacerbate these changes, especially in the left lateral decubitus (LLD) position. Objectives To investigate the effect of cardiomegaly on heart-lung interaction during OLV, particularly in the LLD position. Case presentation A 20-year-old male with recurrent spontaneous pneumothorax was scheduled for right-sided bronchopleural fistula repair via thoracotomy. The patient presented with cardiomegaly (cardiothoracic ratio 75%) and echocardiographic evidence of right ventricular and atrial dilation. In the LLD position, OLV led to desaturation when both lungs were ventilated, but oxygenation improved when only the left lung was ventilated. Results Cardiomegaly alters heart-lung interaction during OLV, particularly in the LLD position. The enlarged heart exerts pressure on the left lung, impairing ventilation. When both lungs are ventilated in this position, ventilation is directed toward the right lung, reducing oxygenation and causing desaturation. However, restricting ventilation to the left lung improved oxygenation due to better lung compliance and less interference from the enlarged heart. Conclusions Cardiomegaly affects heart-lung interaction during OLV in the LLD position. Oxygenation improves when only the left lung is ventilated, likely due to less compression of the left lung. The supine position may further enhance oxygenation even with bilateral ventilation. This case highlights the importance of considering cardiomegaly in OLV management. This section should be written as per the CARE checklist item 3.
in F1000Research on 2026-04-19 03:17:52 UTC.
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Religiosity of Indonesian Muslim as affected by Islamic religious education and other factors: A meta-analysis [version 1; peer review: awaiting peer review]
Abstract This study aimed to evaluate the effects of Islamic religious education and other factors on the religiosity of Indonesian Muslim by using a meta-analysis method. The study integrated data from 22 studies that examined various factors influencing religiosity among Muslim communities in Indonesia. Relevant literatures were sourced using the Google Scholar platform by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Articles were selected based on specific inclusion criteria, and the effect sizes (correlation values) were calculated using the Fisher Z transformation and analyzed through a random effects model. Results revealed that the meta-analysis identified several factors with significant positive correlations (P < 0.05) to Islamic religiosity, i.e., adherence to Islamic law (syariat), participation in dakwah activities, halal orientation, Islamic religious education, family education, and positive moral behavior. Negative moral behavior, such as accessing pornographic sites, exhibited a significant negative correlation (P < 0.05). Intelligence, however, was found to have no significant impact on religiosity. The findings highlight the multifaceted nature of religiosity, shaped by educational, familial, and behavioral dimensions.
in F1000Research on 2026-04-19 03:12:55 UTC.
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Articulator Zeroing on Condylar Guidance Values: A Comparative Study of Hanau and Artex Systems [version 1; peer review: awaiting peer review]
Purpose Accurate replication of mandibular movements is essential for successful prosthodontic rehabilitation. Semi-adjustable articulators are commonly used for this purpose, and zeroing is a preparatory step intended to standardize articulator settings. However, its influence on condylar guidance values remains unclear. Therefore the purpose of the study was to evaluate the effect of zeroing on condylar guidance values and compare measurements obtained from Hanau and Artex articulators. Methods Thirty dentate participants (20–30 years) were included. Maxillary casts were mounted using facebow transfer, and mandibular casts were mounted in maximum intercuspation. Four groups were evaluated: Hanau with zeroing (H0), Hanau without zeroing (H1), Artex with zeroing (A0), and Artex without zeroing (A1). Condylar guidance was recorded using protrusive interocclusal records. Data were analyzed using statistical tests with significance set at p < 0.05. Results Significant differences were found between Hanau and Artex articulators under both zeroing and non-zeroing conditions (p < 0.05). No statistically significant differences were observed within each articulator when comparing zeroing and non-zeroing conditions (p > 0.05). Conclusions The difference in the condylar guidance angle between zeroing and non-zeroing of the articulator is minimal and not statistically significant. However, this small variation could potentially impact the accuracy and precision of prosthesis fabrication. Additionally, there is an observable difference in the condylar guidance angle between the Hanau and Artex articulators, when comparing measurements with and without zeroing.
in F1000Research on 2026-04-19 03:00:46 UTC.
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Oral Health–Related Quality of Life and Patient-Reported Outcomes After Implant Rehabilitation Using CAS Kit–Assisted Indirect Maxillary Sinus Augmentation: A Cross-Sectional Study [version 1; peer review: awaiting peer review]
Background Partial edentulism in the posterior maxilla is frequently complicated by alveolar bone resorption and maxillary sinus pneumatization, limiting implant placement and negatively affecting oral health–related quality of life (OHRQoL). Minimally invasive sinus augmentation techniques, such as CAS KIT–assisted indirect sinus elevation, aim to reduce surgical morbidity; however, evidence regarding patient-reported outcomes and quality of life following such interventions remains limited. Objective To evaluate oral health–related quality of life and patient-reported outcomes following implant rehabilitation using CAS KIT–assisted indirect maxillary sinus augmentation. Materials and Methods This observational cross-sectional study included 34 patients who underwent CAS KIT–assisted transcrestal sinus augmentation with implant placement in the posterior maxilla. Postoperative recovery and satisfaction were assessed using the HRQOLquestionnaire over seven postoperative days. OHRQoL was evaluated using the OHIP-14 questionnaire at baseline and one month after prosthetic rehabilitation. Data were analyzed using repeated measures ANOVA with a significance level set at p < 0.05. Results HRQOLscores showed a statistically significant improvement over the seven-day postoperative period (p < 0.001), with stabilization observed from Day 5 onward. OHIP-14 scores demonstrated a highly significant reduction from baseline to post-intervention assessment (p < 0.001), indicating marked improvement in OHRQoL across all participants. Conclusion CAS KIT–assisted indirect sinus augmentation followed by implant rehabilitation results in rapid postoperative recovery and significant improvement in patient-reported outcomes, supporting its role as a predictable and patient-centered treatment modality for posterior maxillary rehabilitation.
in F1000Research on 2026-04-19 02:55:12 UTC.
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Case Report: Ovarian Dysgerminoma in a Male Patient with Ambiguous Genitalia: A Case Report [version 1; peer review: awaiting peer review]
Introduction Dysgerminoma is a malignant germ cell tumor in young women, often detected early with favorable prognosis and distinct immunological features influencing its treatment. This case highlights an unusual presentation of ovarian dysgerminoma in a phenotypic male with ambiguous genitalia. Case presentation We report a case of a phenotypically male patient in his 20s presenting with progressive abdominal distention and ambiguous genitalia. Clinical evaluation, imaging studies, and histopathological examination were performed. Physical examination revealed a mobile, non-tender mass, with ascites and ambiguous genitalia. Imaging revealed a large heterogeneous abdominal mass with para-aortic lymphadenopathy and internal female reproductive organs. Surgical resection was performed, and histopathological and immunohistochemical findings (OCT3/4 and CD117 positivity) confirmed dysgerminoma. The patient was treated with platinum-based chemotherapy and showed favorable clinical improvement. Conclusion This case highlights the importance of considering gonadal malignancies in patients with DSD and emphasizes the role of multidisciplinary and patient-centered management, particularly in resource-limited settings.
in F1000Research on 2026-04-19 02:43:22 UTC.
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“Financing the Climate Transition: Green Finance, Policy Uncertainty, and Corporate Environmental Performance in Emerging Markets” [version 1; peer review: awaiting peer review]
Background Green finance has emerged as a key mechanism for promoting corporate environmental performance and supporting sustainable development, particularly in emerging economies where environmental challenges and financing gaps remain substantial. However, the effectiveness of green finance may depend on macroeconomic conditions, especially economic policy uncertainty, which can influence firms’ willingness to undertake longterm environmental investments. Methods This study examines the relationship between green finance and corporate environmental performance using a balanced panel dataset of 1,370 listed firms across nine emerging economies from 2014 to 2024 (13,970 firm-year observations). The analysis employs two-way fixed effects panel models, interaction terms, and instrumental variable two-stage least squares (IV–2SLS) estimation to address endogeneity and examine the moderating role of economic policy uncertainty. Results The findings indicate that green finance significantly improves corporate environmental performance, suggesting that access to sustainable financial instruments enables firms to invest in environmentally friendly technologies and practices. However, the positive impact of green finance is weakened under conditions of higher economic policy uncertainty, as firms become more cautious about committing to long- term environmental investments. The results also show that strong institutional quality and higher levels of green technology adoption mitigate the negative effects of policy uncertainty, enabling firms to sustain environmental investments despite uncertain policy environments. Conclusions Overall, the study highlights the importance of stable policy environments, effective institutional governance, and technological innovation in strengthening the environmental benefits of green finance and supporting sustainable climate transitions in emerging markets.
in F1000Research on 2026-04-19 02:09:05 UTC.
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Health Literacy as A Determinant of Treatment Success in Multidrug Resistance Tuberculosis: A Systematic Review [version 1; peer review: awaiting peer review]
Background Multidrug-resistant tuberculosis (MDR-TB) remains a serious global health threat, with treatment success rates stagnating despite advances in therapy. Health literacy, defined as the ability to access, understand, evaluate, and apply health information, may play a role as a modifiable determinant of MDR-TB treatment success. Methods Two databases (PubMed and Scopus) were used following the PRISMA guidelines to find articles published between January 1st, 2015, and October 11st, 2025. A total of 231 records were identified and seven articles were included in this systematic review. Results Health literacy was operationalized via patient knowledge, counseling/education, self-care behaviors, communication, and digital adherence support, with outcomes capturing adherence, completion, attitudes, self-care, and literacy levels. Synthesis suggested a consistent directionality in which literacy-oriented strategies and communication-focused approaches aligned with improved adherence and programmatic indicators, while contextual and methodological heterogeneity limited cross-study comparability. Conclusion Available evidence supports health literacy as a promising, modifiable lever to enhance MDR-TB adherence and treatment success, particularly when addressed through multi-component, patient-centered strategies. Future work should use validated, multidomain literacy instruments and robust designs to quantify effects and guide scalable, literacy-sensitive MDR-TB programs.
in F1000Research on 2026-04-19 02:07:58 UTC.
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Prevalence and factors associated with depression and anxiety in patients with chronic kidney disease [version 1; peer review: awaiting peer review]
xx.
in F1000Research on 2026-04-19 02:01:33 UTC.
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The Relationship Between Uric Acid Level and Liver Fibrosis in Patients with Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) [version 1; peer review: awaiting peer review]
Introduction Metabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent liver condition linked to metabolic disorders. Uric acid, a pro-inflammatory mediator, has been implicated in the pathogenesis and progression of MASLD. This study aims to analyze the relationship between serum uric acid levels and the degree of liver fibrosis in patients with MASLD. Methods This cross-sectional study was conducted at Dr. Wahidin Sudirohusodo Hospital and its affiliated hospitals in Makassar form July to December 2025. A total of 128 adult patients diagnosed with MASLD were enrolled using consecutive sampling. All participants underwent serum uric acid measurement and liver fibrosis assessment using transient elastography (FibroScan). Fibrosis was categorized as non-significant (F0-F1) or significant (F2-F4). Hyperuricemia was defined as serum uric acid >7.0 mg/dL in men and >6.0 mg/dL in women. Data were analyzed using the Chi-square test to determine the association between uric acid levels and fibrosis. Results The mean age of the 128 participants was 49.8 ± 12 years, with a slight male predominance (52.3%). Significant fibrosis (F2-F4) was found in 56 patients (43.8%). Hyperuricemia was present in 65 patients (50.8%). The proportion of significant fibrosis was higher in the hyperuricemia group (52.3%) compared to the normal uric acid group (34.9%). The Chi-square analysis revealed a statistically significant association between hyperuricemia and the presence of significant liver fibrosis (χ2 = 3.93; p = 0.047). Patients with hyperuricemia had a 2.04 times higher odds of having significant fibrosis compared to those with normal uric acid levels (OR = 2.044; 95% CI: 1.004–4.161). Conclusions There is a significant relationship between elevated serum uric acid levels and the presence of significant liver fibrosis in patients with MASLD. Hyperuricemia may serve as a simple, non-invasive biomarker for stratifying the risk of fibrosis in this population.
in F1000Research on 2026-04-19 01:57:46 UTC.
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Developing and testing an optimised implementation model to improve coverage of India’s national anaemia reduction programme among pregnant women in India: A hybrid type II effectiveness-implementation study. [version 1; peer review: awaiting peer review]
Introduction Maternal anaemia is a major public health challenge globally. In India, it affects over half of all pregnant women and contributes significantly to maternal and neonatal morbidity and mortality. The Government of India launched the “Anaemia Mukt Bharat (AMB)” or “Anaemia Free India” program in 2018, focussing on iron and folic acid (IFA) supplementation and deworming. In Haryana, a northern state of India, 56.5% of pregnant women are anaemic (NFHS-5), indicating a high-burden area. This study aims to design, implement and evaluate an optimised implementation strategy for AMB in a high burden low-resource setting, setting, which will help develop a replicable model for managing this major public health issue through contextual adaptation. Methods and analysis This is a mixed-method, hybrid type II effectiveness–implementation study in Hodal block, Palwal district, of Haryana. The study will be conducted in two phases. Phase I will include formative research using the Consolidated Framework for Implementation Research (CFIR) to identify barriers and enablers, through in-depth interviews, focus groups, and facility assessments. These findings will inform the development of a co-designed implementation model using the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. Phase II will scale and evaluate the optimised strategy across four clusters, guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework. Primary outcomes are the proportion of pregnant women consuming IFA for at least 100 days and receiving a dose of albendazole. Secondary outcomes include 180-day IFA coverage, haemoglobin change, compliance with AMB treatment protocols, and acceptability and feasibility of strategies. Quantitative data will be analysed using descriptive and inferential statistics, and qualitative data thematically analysed using NVivo. This protocol is reported in accordance with SPIRIT guidelines https://doi.org/10.6084/m9.figshare.31827730. 1
in F1000Research on 2026-04-19 01:42:30 UTC.
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Medibot AI: a web-based software tool integrating Gemini API for informational over-the-counter medication guidance [version 1; peer review: awaiting peer review]
Abstract* Background Self-medication for common illnesses remains widespread and may lead to inappropriate drug selection, incorrect dosage, adverse interactions, and delayed professional care. In this context, artificial intelligence (AI) can provide informational support to promote safer therapeutic decisions. This paper presents Medibot AI, a web-based intelligent system designed to generate informational over-the-counter (OTC) medication recommendations from user-reported symptoms using Google’s Gemini API, with an emphasis on transparency, traceability, and safety warnings. Methods The system was developed iteratively using agile principles and implemented with a three-layer architecture: (i) user interface, (ii) recommendation and validation logic, and (iii) data persistence. The frontend was built using Next.js 18, React 18, and Tailwind CSS 3, while backend services were implemented with Node.js 20 and Prisma ORM 6.8 connected to PostgreSQL 17 (Neon). User inputs are transformed into a structured JSON prompt, and Gemini responses are constrained to return strict JSON outputs. A server-side validation layer verifies both JSON integrity and schema compliance before results are displayed or stored. The system also implements safety-oriented rules that suppress recommendations in high-risk scenarios and generate visible warnings. Results Medibot AI enables users to register, submit symptom descriptions with optional clinical context, obtain structured recommendations with dosage instructions and warnings, and download PDF reports. Functional integration testing confirmed stable data flow across modules and consistent schema-compliant outputs. Conclusions Medibot AI provides a reproducible and auditable approach for AI-assisted OTC medication guidance. While it does not replace clinical diagnosis or professional medical advice, it offers an educational tool that supports more informed and responsible self-medication practices.
in F1000Research on 2026-04-19 01:31:57 UTC.
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Astrocytes mediate the pro-cognitive value of α7nAChRs and of α7nAChR-targeting therapeutics
The 7nicotinic acetylcholine receptor (7nAChR) has driven extensive research over the past three decades for its pro-cognitive potential. It is the leading druggable target for the cognitive deficits associated with schizophrenia and has motivated major pharmaceutical and clinical efforts to ameliorate similar impairments in other neurological disorders, such as Alzheimer's disease (AD). Yet, a systematic evaluation of the role played by 7nAChR in cognition, and its mechanistic underpinnings, is still lacking. Here we report that 7nAChRs on principal and inhibitory forebrain neurons are largely inconsequential to mouse behavior, including in domains that are most sensitive to schizophrenia-related cognitive impairments. By contrast, loss of 7nAChR from astrocytes produces profound behavioral alterations that are cognitive domain-specific, are time-of-day dependent, coincide with reduced levels of the N-methyl D-aspartate receptor (NMDAR) co-agonist D-serine, and are fully restored by D-serine supplementation. Further, an 7nAChR partial agonist previously evaluated in Phase III trials for cognitive enhancement in schizophrenia and AD fails to augment behavior in mice lacking astrocytic 7nAChRs. Together, these findings identify astrocytes and D-serine/NMDAR signaling as a central mechanism through which 7nAChR, a major drug target, promotes cognitive behavior
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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A collicular-hypothalamic pathway for social visual awareness
Awareness of other individuals is a foundational element of social behavior. Here we examined how specific neural systems detect and signal the visual presence of conspecifics related to social arousal and motivation. We found that visual exposure to videos of other mice can activate hypothalamic oxytocin neurons and promote onset of pup retrieval behavior in naive virgin female mice. A range of social videos depicting conspecifics in diverse contexts, including but not limited to parental behavior, could accelerate onset of pup retrieval compared to non-social controls. Animals would elect to watch social videos over non-social videos. We made photo-tagged recordings from oxytocin neurons of the paraventricular nucleus (PVN), which were preferentially activated during social video viewing. Optogenetic silencing of PVN oxytocin neurons during exposure prevented this behavioral enhancement of pup retrieval onset. We also made photo-tagged recordings from a population of PVN-projecting neurons of the superficial superior colliculus (sSC[->]PVN units). Compared to other sSC neurons, the sSC[->]PVN neurons had specialized horizontal direction tuning with robust and sustained responses to social videos. sSC[->]PVN neurons differentiated visual scenes based on social content, responding most strongly to pup retrieval and less to scenes with increasing numbers of animals. Our results identify a subcortical visual pathway that signals the presence and salience of conspecifics to the oxytocin system, providing a circuit mechanism by which social visual awareness drives neuroendocrine arousal and the acquisition of parental behavior.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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TREM2 deficiency causes region-specific brain effects in a mouse model of cerebral amyloid angiopathy
Cerebral amyloid angiopathy (CAA), a major vascular contributor to cognitive decline, is present in 85-95% of Alzheimer disease (AD) patients. Despite its high prevalence, the mechanisms by which CAA contributes to neurodegeneration remain poorly understood. Triggering receptor expressed on myeloid cells 2 (TREM2), an innate immune receptor expressed exclusively by microglia, regulates activation, phagocytosis, and amyloid clearance, thereby shaping neuroinflammation. Loss-of-function mutations in TREM2 markedly increase AD risk, but its role in CAA pathology remains unknown. To investigate this, we crossed the Familial Danish Dementia (Tg-FDD) mouse model, which accumulates robust vascular amyloid, with TREM2 knockout (TREM2KO) mice to generate Tg-FDD/TREM2KO animals. Histological and transcriptomic analyses revealed region-specific effects of TREM2 deficiency. In the cortex, TREM2 loss markedly reduced vascular amyloid deposition, accompanied by decreased tau pathology. In contrast, in the cerebellum, TREM2 deletion exacerbated vascular amyloid accumulation, promoted astrogliosis, and enhanced tau pathology. Transcriptomic profiling further identified distinct neuroinflammatory signatures between cortex and cerebellum, particularly in cytokine signaling, matrix remodeling, and lipid metabolism. Together, these findings demonstrate that TREM2 deficiency leads to region-specific effects on CAA, revealing extensive regional variability in vascular amyloid pathology and underscoring the importance of considering these differences when developing TREM2-based therapies.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Frontal Brain Injury Reduces Sensitivity to Reward-Predictive Cues and Remodels the Nucleus Accumbens
Traumatic brain injuries (TBIs) are more than mere lesions and generate a persistent secondary pathology. This, combined with functional reorganization of circuits post-injury, may explain the increased risk for psychiatric disorders in patients with TBI. In the current studies, we demonstrate that frontal TBI changed the Pavlovian behavioral response to reinforcer-predicting cues and reduced the motivational value of cues. TBI also chronically impaired decision-making on a gambling-like task with reinforcer-paired cues. To investigate how these changes occur, we evaluated the nucleus accumbens (NAc) core. At a subacute time point (14 days), we confirmed reduced input to the NAc with optogenetics and evaluated electrophysiological and transcriptional changes. TBI increased neuronal excitability and the single nucleus RNA sequencing profile indicated a substantial stress and inflammatory response, but also high indicators of plasticity, particularly in D1- and D2-positive medium spiny neurons. To evaluate how these subacute changes transitioned to chronic NAc dysfunction, we measured immunohistochemical surrogates of activity post-mortem and recorded calcium activity from the NAc after TBI during Pavlovian conditioning. TBI reduced histological markers of activity and reduced cue-evoked calcium activity. Overall, these data indicate that substantial reorganization of the NAc occurs following frontal brain injury. A primary effect of this is to reduce the salience of environmental cues linked to outcomes. The inability to properly process outcomes could contribute to broader psychiatric symptoms after TBI, including impairments in decision-making, behavioral flexibility, and impulsivity but also presents a potential treatment target.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Highly replicable multisite patterns of adolescent white matter maturation
The Adolescent Brain Cognitive Development (ABCD) Study is the largest U.S.-based neuroimaging initiative of adolescent brain maturation. Diffusion MRI (dMRI) provides unique insights into white matter organization, yet applying advanced processing pipelines and managing technical variability across scanning environments remains challenging at scale. To address these issues, we present ABCD-BIDS Community Collection (ABCC) release 3.1.0, including a curated resource of more than 24,000 fully processed ABCD dMRI datasets. ABCC provides fully processed images, nuanced image quality metrics, advanced microstructural measures, and person-specific bundle tractography. Evaluating these rich data revealed that measures of diffusion restriction and non-Gaussianity--in particular the intracellular volume fraction from NODDI and return-to-origin probability from MAP-MRI--were highly sensitive to neurodevelopment and robust to variation in image quality. Additionally, harmonization of microstructural features markedly improved the cross-vendor generalizability of developmental effects. Together, ABCC accelerates reproducible, rigorous research on adolescent white matter development.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Hippocampal representations differentiate reactive and anticipatory responses during foraging under threat
Adaptive behavior under threat requires balancing reward pursuit against the risk of harm. During approach-avoidance conflict, animals often pause at decision points, but whether these pauses reflect a unified process or distinct decision states remains unclear. Here, we replicate and extend findings from Calvin et al.1 by analyzing hippocampal activity in rats performing a predator-based foraging task across two cohorts. We compared three behaviors: mid-track aborts (MTAs), mid-track continues (MTCs), and attack-triggered retreats. Behaviorally, MTAs and MTCs emerged from a shared pause state but led to different outcomes, whereas retreats reflected rapid, reactive escape following attack. Despite similar behavioral endpoints (return to safety), retreats and MTAs differed markedly in movement dynamics and neural activity. During retreats, hippocampal representations remained biased toward the attack location, consistent with ongoing encoding of immediate threat. In contrast, MTAs showed a shift in representation toward safe locations following the decision to abort. During pauses, hippocampal activity differentiated future behavioral outcomes before movement diverged: pauses preceding MTAs showed stronger representation of threat-related locations, whereas pauses preceding MTCs emphasized goal-related locations. These representational biases were already present during the outbound approach, indicating that decision-related processes emerged at the beginning of the outbound journey. Across experience, representations of threat and goal locations became increasingly differentiated when encountering an attacking robot, diminished during extinction, and re-emerged when the attack was introduced again. Together, these findings extend prior work by dissociating hippocampal representations associated with reactive escape from those underlying anticipatory, anxiety-like decision-making, suggesting that the hippocampus dynamically tracks behaviorally relevant features to guide decisions under threat.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Systemic injection of metabotropic glutamate 2/3 receptor antagonist LY341495 disrupts reward-related behaviors in mice.
Metabotropic glutamate 2/3 receptors (mGluR2/3) have been implicated in depression, anxiety, learning, and memory. However, their causal role in reward-related behaviors remains unclear. Here, we examined the effects of intraperitoneal administration of LY341495, a selective mGluR2/3 antagonist, on reward-related behaviors in mice. In a head-fixed temporal conditioning task, mice received a 10% sucrose solution every 10 seconds. After training, mice exhibited anticipatory licking and pupil dilation aligned with expected reward delivery, indicating successful reward prediction. LY341495 dose-dependently reduced licking behavior without disrupting temporal prediction, as normalization analyses revealed reduced gain but preserved timing. LY341495 also induced overall pupil dilation and attenuated reward-proximity pupillary responses. To determine whether reduced licking reflected general motor impairment, we assessed spontaneous locomotion in a freely moving open-field task. LY341495 did not affect locomotor activity or excretion, suggesting intact general motor and autonomic function. To further evaluate orofacial motor function, we measured ultrasonic vocalizations (USVs) during a social interaction task. LY341495 did not significantly alter USVs, indicating preserved mouth-related motor function independent of licking. In contrast, LY341495 dose-dependently reduced food intake in a freely moving feeding task. Moreover, social preference testing revealed that LY341495 reduced social interaction, suggesting impaired processing of non-food rewards. Together, these findings demonstrate that mGluR2/3 signaling regulates reward-seeking behaviors independently of general locomotor or orofacial motor function. These results provide new insights into glutamatergic mechanisms underlying reward processing and may have clinical implications for obesity, eating disorders, and psychiatric conditions involving motivational dysfunction.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Chemical Genetic Screen Identifies PSD3 as a Direct Substrate of NUAK1 that Regulates Dendritic Spine Maturation
Novel (nua) Kinase 1 (NUAK1) encodes a serine-threonine protein kinase, mutations in which are associated with autism spectrum disorder. Direct phosphorylation targets of NUAK1 have been elusive hindering mechanistic understanding of its role in brain development. Here, we characterize autism-associated NUAK1 variants and show their differential impact on catalytic activity and subcellular distribution. We engineered ATP-analog sensitive NUAK1 and utilized its specificity towards bulky analogs to identify over 30 hitherto unknown direct phosphorylation targets of NUAK1. We demonstrate that Pleckstrin Homology and Sec7-domain containing protein 3 (PSD3) is a bona fide phosphorylation target of NUAK1. A guanine exchange factor (GEF) for ARF6 GTPase, PSD3 is phosphorylated by NUAK1 at S476. Expression of phosphodeficient PSD3 leads to aberrant activation of ARF6 and generation of PI(4,5)P2 that accumulates in intracellular vesicles. In neurons, phosphomutant PSD3 leads to enhanced spine maturation in an ARF6 dependent fashion. This study reveals direct neuronal substrates of an autism risk gene NUAK1, and delineates a mechanism by which PSD3 phosphorylation regulates ARF6 activation and spine maturation.
in bioRxiv: Neuroscience on 2026-04-19 00:00:00 UTC.
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Tailored Sports Food Exchange Lists for Lebanese Athletes: Nutrient-Based Categorization of Commercial Products sold in Lebanese Markets [version 1; peer review: awaiting peer review]
Background Food Exchange Lists are commonly used by dietitians to facilitate meal customization and help in reducing the risk of diet-related diseases. However, there are still no exchange lists for sports food products that contribute to dietary planning during training and competitions. The aim of this study is to design a sport food exchange list for dietetic practice in sport nutrition based on the sport products available in Lebanon. Methods A mapping study was conducted by trained dietitians between January 2022 and April 2022 in which the nutrition fact labels of 60 sports food products from 20 companies marketed in 50 Lebanese markets, including protein powders, protein bars, nut butters, sport chips, and sport drinks were screened. The resulting database of sports food compositions was used to define exchange lists taking into consideration the macronutrients and energy content of the sport food products in 30 grams and based on typical athlete product’s serving size. The sports food products were defined into different subgroups based on their macronutrient and energy contents. The use of this exchange system by athletes is also presented as an example. Results Results showed varying macronutrient composition which were categorized as high, moderate, and low among the sports food products with some providing greater than the recommended daily values. Conclusion This study developed a preliminary sports food exchange list based on commercial sport foods specific to the context of Lebanon. While it provides a practical tool for dietitians and sport nutritionists to complement athletes’ diets, its applicability is limited by reliance on Lebanon-specific products and the absence of validation with athletes in real-world settings. Future studies should validate and adapt this tool across different populations and sporting contexts.
in F1000Research on 2026-04-18 18:38:17 UTC.
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Relationship Between KRAS Gene Mutation Status and Clinicopathological Features of Colorectal Cancer Patients in Makassar [version 1; peer review: awaiting peer review]
Introduction Colorectal cancer (CRC) is a malignancy originating from the epithelial lining of the colon and rectal mucosa, with high morbidity and mortality rates worldwide. KRAS gene mutations play a significant role in CRC carcinogenesis and affect therapeutic responses. This study aimed to determine the relationship between KRAS gene mutation status and clinicopathological features of CRC patients in Makassar. Methods This was an observational analytic study with a retrospective cohort design using medical record data and KRAS gene mutation examination results. The study was conducted at Dr. Wahidin Sudirohusodo General Hospital and its network hospitals from May 2025 until the sample size was fulfilled. Thirty-three patients with colorectal adenocarcinoma who met the inclusion criteria were included. KRAS mutation status was assessed using PCR from paraffin-block tissue samples. Data analysis used chi-square test, Fisher exact test, independent T-test, Mann-Whitney, and logistic regression with p < 0.05 considered significant. Results Most subjects were aged ≥50 years (75.8%) and male (54.5%). KRAS mutant type was found in 42.4% of patients and wild type in 57.6%. There was no significant relationship between KRAS mutation status and histological grading (p = 0.607). However, a significant relationship was found between KRAS mutation status and tumor location (p = 0.040). KRAS mutant type was predominantly located in the right colon (64.3%), while KRAS wild type was predominantly located in the left colon (73.7%). Conclusions KRAS gene mutation status is significantly associated with tumor location but not with histological grading in colorectal cancer patients. KRAS mutant type is predominantly found in right-sided tumors, while KRAS wild type is predominantly found in left-sided tumors.
in F1000Research on 2026-04-18 18:32:56 UTC.
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Towards Protecting the Injured Party from Errors and Hallucinations of Artificial Intelligence: A Contemporary Legal Perspective [version 1; peer review: awaiting peer review]
The world has been witnessing a growing and accelerating expansion in the use of artificial intelligence (AI) systems, as leading worldwide technology businesses compete to develop systems and software that can simulate the human mind, produce technological solutions, and accomplish activities that previously needed human mental effort. This has given rise to a host of new and unfamiliar legal challenges, including those connected to errors and ‘hallucinations’ that may produce inaccurate or misleading outputs. This paper examines the technical and practical risks associated with the use of AI, with a focus on the phenomenon of hallucinations that has recently become widely discussed, and its potential effects on users and third parties. This study adopts a comparative, analytical legal approach by analyzing the current legal framework to determine the extent to which the law protects the injured party, assessing the adequacy of existing civil-liability rules, and emphasizing the difficulties associated with proving fault and causation, as well as identifying the responsible party within the complex smart-transactions ecosystems. Accordingly, the objective of this paper is to determine how civil liability arising from the use of AI systems in numerous fields may be attributed, and to identify the future legal implications of such systems in light of the general rules of the UAE Civil Transactions Law and the substance of the EU regulation. Accordingly, the study presents a contemporary legal perspective on conventional culpability to safeguard the harmed person against AI faults and hallucinations. It concludes by proposing innovative legal mechanisms, such as strict (objective) liability, transparency obligations, and compulsory insurance, to compensate the injured party for ‘digital harm’ caused by AI technologies. The research indicates that legal responsibility and technical innovation must be balanced to safeguard the damaged party.
in F1000Research on 2026-04-18 18:27:56 UTC.
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Prenatal training module (PTM) with newborn simulation model to enhance primipara mother’s knowledge and skill on newborn care in Lower-Middle-Income Setting: A quasi-experimental study [version 1; peer review: awaiting peer review]
Background Parental knowledge of newborn care is essential, as it can influence the newborn’s health, growth, and development. It is challenging due to a lack of mothers’ knowledge and skills, insufficient resources, and limited training facilities. The study evaluates the effectiveness of the prenatal training module (PTM) on maternal knowledge and skills on newborn care. Methods A quasi-experimental research design was adopted. Forty women at or beyond 36 weeks of gestation were recruited using a non-probability purposive sampling. The pre-test knowledge was assessed during the antenatal period for both the interventional and control groups. The interventional group received two sessions of prenatal training using a simulation, with a one-week interval. The post-test was conducted for both the Interventional and control groups on the third day of child birth. Results There was an evident variation between post-test knowledge score (Z = -5.345; P < 0.05) and post-test skill score (Z = -5.144; P < 0.05) among mothers on newborn care between groups. Conclusions Post-training skill demonstration and knowledge were markedly better among women in the interventional group than in the control group. The PTM with the newborn simulation model has shown success in improving knowledge and skills among mothers.
in F1000Research on 2026-04-18 16:21:10 UTC.
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A Hybrid Approach to Evaluate Business Efficiency, Profitability, and Market Valuation: An Empirical Validation [version 1; peer review: awaiting peer review]
Background Internal functional capabilities — encompassing marketing, operations, research and development, and human resources — are widely recognized as key determinants of firm competitiveness. However, most existing studies rely on linear regression models that fail to capture nonlinear interdependencies among these capabilities, and few simultaneously assess both profitability-based and market value-based performance outcomes. A methodological gap remains in combining efficiency benchmarking with predictive modeling to evaluate how capability configurations translate into financial and investor-oriented results across diverse industry contexts. Methods This study proposes a hybrid two-stage analytical framework integrating Data Envelopment Analysis and Backpropagation Neural Networks. In the first stage, Data Envelopment Analysis quantifies the relative transformation efficiency of each functional capability using objective multi-input and multi-output configurations. In the second stage, Backpropagation Neural Networks — benchmarked against Ordinary Least Squares Multiple Regression — model the nonlinear relationships between capability efficiency scores and firm performance outcomes. The empirical sample comprises 1,271 publicly listed firms in Taiwan across high-technology, manufacturing, and service industries, drawn from the Taiwan Economic Journal database covering fiscal years 2020 to 2023. Results Backpropagation Neural Networks consistently outperformed regression-based models in predictive accuracy across all three performance dimensions — market value, Tobin’s Q, and stock return. Industry-specific patterns emerged: research and development and human resource capabilities were most critical in high-technology firms, operational capability dominated in manufacturing, and marketing capability was most influential in service firms. Performance-tier segmentation further revealed that high-performing firms maintained a more balanced and strategically coherent deployment of capabilities, whereas low-performing firms exhibited excessive reliance on short-term profitability signals. Conclusions Functional capability configurations differ meaningfully across industries and performance tiers. Effective capability alignment — rather than resource possession alone — is the primary mechanism through which firms achieve superior profitability and favorable market valuation.
in F1000Research on 2026-04-18 15:20:33 UTC.
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Analyzing Students' Critical Thinking Skills in Geometry Learning through Augmented Reality: An Evaluation Using the Technology Acceptance Model. [version 1; peer review: awaiting peer review]
Background Technological innovation continues to transform mathematics education by creating new opportunities to improve students’ higher-order thinking skills and engagement. Augmented Reality (AR) has emerged as a promising learning tool in geometry education. This study examines the relationship between students’ critical thinking skills and their acceptance of AR-based learning using the Technology Acceptance Model (TAM). Methods A quantitative survey was conducted with 234 junior high school students from 13 schools in Yogyakarta, Indonesia. Data were analyzed using Structural Equation Modeling (SEM) to examine the relationships among variables in the Technology Acceptance Model framework, while Fuzzy C-Means Clustering was used to identify patterns in students’ technology adoption. Results The findings indicate that critical thinking skills significantly influence perceived usefulness and perceived ease of use of Augmented Reality-based learning applications. These perceptions subsequently affect students’ actual usage of the technology in geometry learning. Conclusions The results suggest that cognitive abilities, particularly critical thinking, play an important role in shaping students’ acceptance of educational technology. This study extends the Technology Acceptance Model by integrating critical thinking as a cognitive factor that supports the adoption of emerging technologies in mathematics learning.
in F1000Research on 2026-04-18 15:06:26 UTC.
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Psychological interventions for reducing non-cardiac Emergency Department Re-presentations – A study protocol for Randomized Controlled Trial. [version 1; peer review: awaiting peer review]
Background Psychological factors can have an impact on non-cardiac chest pain presentations to emergency departments (ED). The current study aims to investigate if providing psychological interventions for non-cardiac chest pain can reduce the number of ED re-presentations Aim The primary aim of the study is to reduce the number of ED re-presentations in the target population through provision of psychological interventions. Specifically, the aim of this study is to determine whether there are differences in outcomes for individuals who present to ED with non-cardiac chest pain and receive psychological intervention vs those who receive usual care, in relation to ED re-presentations over a 6-month period. The secondary aim is to study if the intervention will be cost effective and result in an improvement in the quality of life and reduction in psychological distress Methods This is a single-blind randomized controlled trial in which the assessor is blind to treatment vs standard care condition. All individuals between 18 and 65 who present with non-cardiac chest pain to ED will be invited to participate in the research. Consenting participants who meet the selection criteria, will be randomly allocated to either -: A) Psychological treatment group consisting of 6 sessions of psychotherapy B) Usual care/Wait list controls Outcomes will be assessed for both groups at baseline, 8 weeks, 16 weeks and 24 weeks Discussion Results are expected to inform practice guidelines for ED and referral pathways for patients with non-cardiac chest pain. Trial registration: ACTRN12619000872134 (prospectively registered on 19/06/2019) The ethics approval for the study was provided by: Human Research Ethics Committee; Townsville University Hospital Human Research Ethics Committee Reference number: HREC/2018/QTHS/47872
in F1000Research on 2026-04-18 12:59:18 UTC.
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Gene and genotype frequencies of color blindness in Basrah population [version 1; peer review: awaiting peer review]
Background The inability to differentiate between dominant hues is known as color vision deficiency. Color blindness is a hereditary condition that damages or weakens color receptors in the human eye. Race and region have an impact on color blindness. In order to determine the frequency of color blindness among primary and secondary students from different Basrah regions in Iraq, a study was conducted because there hasn’t been any prior research on the subject. Method Random samples were obtained from 2760 students (1448 males and 1312 females) from various locations of Basrah Governorate, ranging in age from 10 to 18. Color vision was evaluated using an Ishihara chart. Result Among 1448 male students, 93 (6.40%) were determined to be color blind, with 49 showing deutan and 44 showing protan. Among 1312 female students, 12 (0.91%) were found to be colorblind: 7 were deutan and 5 were protan. According to data from the X2-square test, no statistically significant difference existed between male and female students in any region. Conclusion The fact that none of the screened participants had ever taken a color vision screening test or been aware they were color blind indicates how uncommon knowledge and awareness of color blindness are in Basrah. The frequency of the colorblind allele was 0.084, while the normal allele was 0.916.
in F1000Research on 2026-04-18 12:55:43 UTC.
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Optimal Design of Ring Footing on Reinforced Sandy Soil under Eccentric-Inclined Loads [version 1; peer review: awaiting peer review]
Background This experimental study examines the performance of ring footing on geogrid-reinforced sandy soil under the combination of eccentrically inclined loading, which is a case that is commonly encountered in structures such as tower foundations, silos, tanks, and offshore supports. Methods An experimental laboratory program was conducted to evaluate three parameters: reinforcement length ratio (L/B), spacing ratio between layers (Z/B), and number of geogrid layers (N). Tests were performed under eccentricity ratios e/B = 0, 0.04, 0.08, and 0.16, and load inclination angles α = 0°, 5°, 10°, and 15°. Results The outcomes showed that the optimal values of the parameters that achieving substantial improvement in both bearing capacity and tilting resistance were identified as L/B = 5, Z/B = 0.50, and N = 4 layers, which increased the bearing capacity by approximately 200% and enhanced tilting resistance by up to 1.52 under the most critical values of (e/B = 0.16, α = 15°). On the other hand, spacing ratios of (Z/B = 0.25 and 1.25), which are too small or too large, and the addition of layers beyond N = 4 resulted in minimal benefit due to ineffective stress transfer and reduced soil-reinforcement interaction. Conclusions The study outcomes offer recommendations for the optimal values of reinforcement parameters that optimize ring footing performance while maintaining cost-effectiveness under complex loading conditions of eccentrically inclined loads.
in F1000Research on 2026-04-18 12:53:01 UTC.
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Selective Infiltration Etching as a surface modification for high-translucency zirconia: Comparative analysis of roughness, composition, and bond strength [version 1; peer review: awaiting peer review]
Background Zirconia is widely regarded as a highly promising material for dental prosthetics due to its excellent biocompatibility and mechanical strength, making it an attractive alternative to metal restorations. However, its chemical inertness and high hardness pose challenges for bonding with resin cements, potentially leading to clinical debonding. Methods Thirty-six high-translucency zirconia cubes (10 × 10 × 10 mm) were randomly assigned to three groups: Group 1 – sandblasting; Group 2 – CoJet system; Group 3 – SIE. Surface roughness, morphology, and composition were assessed using a profilometer, SEM/EDX, and AFM. Following bonding with resin cement, all specimens underwent 5,000 thermocycles. Shear bond strength was then measured. Results The SIE group demonstrated significantly greater surface roughness and bond strength compared with the other groups. SEM analysis revealed that SIE generated a well-defined nanoporous surface promoting deep resin infiltration. In contrast, sandblasting and CoJet treatments produced irregular, less retentive surface morphologies. Conclusion These findings indicate that SIE provides a superior micromechanical and chemical interface, thereby enhancing the durability of zirconia–resin bonding.
in F1000Research on 2026-04-18 12:44:46 UTC.
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Fixed-point Acceleration Algorithm of Total Asymptotically Nonexpansive Mappings [version 3; peer review: 1 not approved]
Fixed-point iterative methods play a fundamental role in nonlinear functional analysis and its applications. In this paper, we consider a real uniformly convex Banach space and introduce a modified accelerated four-step iterative scheme for approximating fixed-point of a class of total asymptotically nonexpansive TAN-mappings. The proposed approach is formulated within a general TAN framework and does not require compactness assumptions at the level of weak convergence. Weak convergence of the algorithm is established under Opial’s condition, whereas strong convergence is obtained by additionally assuming semi-compactness of the underlying mapping. Moreover, a rigorous comparative convergence analysis is provided to examine the rate of convergence of the proposed scheme relative to the HR-type iterative process. The theoretical results are supported by numerical experiments illustrating the convergence dynamics of both methods. Finally, the applicability of the framework is demonstrated by applying it to a nonlinear two-dimensional Volterra integral equation.
in F1000Research on 2026-04-18 12:38:58 UTC.

Planet Neuroscience

An aggregation of RSS feeds from various neuroscience journals.

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