Biology subjects

Zhang, L.

Publications and source records attributed to Zhang, L..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

Continental-scale multi-omics reveals a distinct microbial-viral biome in sandy beach ecosystems structured by tidal zonation

Sandy beaches are dynamic coastal interfaces shaped by strong physical forcing and intense exchange between marine and terrestrial environments, yet their microbiomes remain poorly resolved at the genomic scale. Here we present a genome-resolved survey of microbial and viral communities across sandy beaches spanning a continental-scale latitudinal gradient along the Chinese coastline. By integrating cross-shore sampling, coastal geochemistry and large-scale multi-omics, we generated 978 metagenomes, 63 viromes and 72 metatranscriptomes, reconstructing 13,337 metagenome-assembled genomes and 38,255 viral populations. Sandy beach microbiomes exhibit exceptionally high genomic novelty, with more than 90% of species-level genomes representing previously undescribed taxa, suggesting that permeable coastal sediments constitute a distinct microbial and viral reservoir. Tidal zonation emerged as a dominant ecological driver structuring microbial diversity, metabolic strategies and virus-host interactions across cross-shore gradients. Genome-resolved analyses revealed systematic metabolic shifts from oxic heterotrophy in supratidal sediments toward increasingly chemolithotrophic and autotrophic pathways toward the low-intertidal and subtidal zone. Sandy beach microbiomes further encode broad potential for hydrocarbon and plastic transformation, together with diverse biosynthetic and antibiotic resistance repertoires that may mediate microbial chemical interactions. Together, these findings identify sandy beaches as a previously under-recognized microbial-viral biome shaped by tidal forcing, providing insight into microbiome evolution and coastal ecosystem resilience under increasing anthropogenic pressure.

microbiology↗

bioRxiv2026

Photo-downregulation of SIRT4 mitigates aging in mice by enhancing H3K9ac via fatty acid metabolism

As organisms age, mitochondrial metabolic activity declines, and disrupted gene expression regulation mediated by histone acetylation induces the emergence of senescent physiological phenotypes in tissues. In this study, we found that periodic exposure to red light significantly increased histone H3 Lys9 acetylation (H3K9ac) levels in the tissues and organs of aged mice. Following red light exposure, silent information regulation factor 4 (SIRT4) protein levels in keratinocytes were notably reduced, whereas glycolysis, fatty acid metabolism, and the tricarboxylic acid (TCA) cycle were significantly activated in keratinocytes. The reduction in mitochondrial SIRT4 levels enhances the acetylation of mitochondrial metabolic proteins, particularly malonyl-CoA decarboxylase (MCD), a potent inhibitor of the key rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A) in fatty acid oxidation. This process promotes mitochondrial fatty acid oxidation and TCA cycle. Additionally, the decrease in SIRT4 activates SIRT1 through feedback mechanisms, thereby alleviating its inhibition on PPAR- in senescent keratinocytes and comprehensively activating the expression of genes related to lipid metabolism. This lipid metabolism activation ultimately facilitates the accumulation of acetyl-CoA within keratinocytes, increases H3K9ac levels, and reshapes the expression patterns of senescence-related genes. Eventually, cellular aging is effectively mitigated by the synergistic regulation of metabolism, inflammation, and gene expression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/717004v2_ufig1.gif" ALT="Figure 1"> View larger version (82K): org.highwire.dtl.DTLVardef@ba3865org.highwire.dtl.DTLVardef@1cc9a58org.highwire.dtl.DTLVardef@1a90e7borg.highwire.dtl.DTLVardef@1f5e88f_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractMechanism of anti-aging action of red light: Red light can reduce SIRT4 signalling in keratinocytes, thereby reactivating lipid metabolism and increasing levels of acetyl-CoA. This promotes histone acetylation, which in turn remodels the expression of age-related inflammatory factors and genes.

cell biology↗

bioRxiv2026

CPS: Mapping Physical Coordinates to High-Fidelity Spatial Transcriptomics via Privileged Multi-Scale Context Distillation

MotivationSpatial transcriptomics enables the dissection of tissue heterogeneity within native contexts, yet current platforms are inherently constrained by high sparsity and low signal-to-noise ratios that obscure fine-grained biological signals. Current efforts to recover these signals are limited by image registration dependencies or the inherent context-blindness of implicit neural representations. ResultsWe introduce the Cell Positioning System (CPS), a context-aware implicit neural representation framework designed to map physical coordinates to high-fidelity spatial transcriptomics via a privileged multi-scale context distillation strategy. CPS treats multi-scale tissue niches as privileged information, employing a teacher network equipped with a multi-scale niche attention mechanism to capture adaptive biological interactions during training. This structural knowledge is explicitly distilled into a student coordinate network, enabling the generation of context-aware expression landscapes solely from spatial coordinates during inference. Benchmarking on the DLPFC dataset demonstrates that CPS achieves state-of-the-art performance in spatial and gene expression imputation and denoising. Furthermore, CPS enables super-resolution to recover high-resolution mouse brain anatomical details and offers interpretability by identifying the scale effective size of biological interactions within human breast cancer tissues. Finally, the framework exhibits superior scalability for large-scale datasets with linear computational complexity. AvailabilitySoftware is available online at https://github.com/tju-zl/CPS.

bioinformatics↗

bioRxiv2026

Multimodal imaging reveals no evidence for magnetite-based magnetoreceptors in the mole-rat eye

Magnetoreception, the ability to perceive the geomagnetic field, is widespread across animals. The underlying sensory mechanism remains elusive, but a long-standing hypothesis proposes single-domain magnetite linked to mechanosensitive ion channels. The Ansells mole-rat (Fukomys anselli) is a subterranean rodent with a magnetic sense, and published behavioral and histological data are consistent with magnetite-based magnetoreceptors in the cornea or retina. Here, we systematically screened for magnetite in the mole-rat eye, combining iron detection via enhanced Prussian blue staining and synchrotron X-ray fluorescence microscopy (XFM) with magnetic detection via MRI quantitative susceptibility mapping (MRI-QSM) and quantum-diamond microscopy (QDM). This revealed only a few iron particles in the retina and cornea, which predominantly overlapped with titanium or chromium, indicating a non-biogenic origin. XFM showed iron-enriched lines in the cornea, but these did not show ferrimagnetic signals. Focusing on other ocular tissues, MRI-QSM revealed the highest susceptibility in the ciliary body, where iron-rich pigmented cells were identified. A TEM-screen, however, failed to detect single-domain magnetite particles in these cells. We conclude that our high-sensitivity multimodal screen provides no evidence for magnetite-based magnetoreceptors in the mole-rat eye, suggesting that mole-rat magnetoreceptors either do not reside in the eye or are based on different physical principles.

neuroscience↗

bioRxiv2026

MolClaw: An Autonomous Agent with Hierarchical Skills for Drug Molecule Evaluation, Screening, and Optimization

Computational drug discovery, particularly the complex workflows of drug molecule screening and optimization, requires orchestrating dozens of specialized tools in multi-step workflows, yet current AI agents struggle to maintain robust performance and consistently underperform in these high-complexity scenarios. Here we present MolClaw, an autonomous agent that leads drug molecule evaluation, screening, and optimization. It unifies over 30 specialized domain resources through a three-tier hierarchical skill architecture (70 skills in total) that facilitates agent long-term interaction at runtime: tool-level skills standardize atomic operations, workflow-level skills compose them into validated pipelines with quality check and reflection, and a discipline-level skill supplies scientific principles governing planning and verification across all scenarios in the field. Additionally, we introduce MolBench, a benchmark comprising molecular screening, optimization, and end-to-end discovery challenges spanning 8 to 50+ sequential tool calls. MolClaw achieves state-of-the-art performance across all metrics, and ablation studies confirm that gains concentrate on tasks that demand structured workflows while vanishing on those solvable with ad hoc scripting, establishing workflow orchestration competence as the primary capability bottleneck for AI-driven drug discovery.

bioinformatics↗

bioRxiv2026

GPLD1 Regulates the Shedding of IZUMO1R to Block Polyspermy in Porcine Oocyte

Mammalian fertilization commences with the essential interaction between sperm IZUMO1 and its oocyte-surface receptor, JUNO. Following gamete fusion, JUNO is rapidly shed from the oocyte to establish a definitive membrane block to polyspermy, a pathological condition that remains a major hurdle in porcine in vitro fertilization (IVF). Despite its biological importance, the molecular networks driving JUNO cleavage has remained elusive. Here, by integrating proteomics, dual-color live-cell imaging, and functional perturbations, we identify the extended existence of JUNO and the GPI-specific phospholipase D1 (GPLD1) as the requisite enzyme mediating JUNO shedding in porcine oocytes. Targeted knockdown or pharmacological inhibition of GPLD1 stabilizes oocyte JUNO, prolongs the window of oocyte receptivity, and significantly exacerbates polyspermy, ultimately compromising embryonic developmental competence. Conversely, GPLD1 overexpression restricts redundant sperm adherence and enhances the efficiency of monospermic zygote formation and blastocyst development. Live-cell imaging reveals that fertilization triggers a transient, pulsed recruitment of GPLD1 in the oocyte, which precisely coincides with the biphasic kinetics of JUNO depletion. Our findings establish that the enzymatic cleavage of the GPI-anchor by GPLD1 is critical for JUNO release, defining a fundamental mechanism for the membrane-level block to polyspermy. This work provides a molecular framework for ensuring sperm-oocyte recognition and improving in vitro fertilization outcomes in mammals.

developmental biology↗

bioRxiv2026

Ceramide-rich extracellular vesicles as pathogenic biomarkers in traumatic brain injury

Extracellular vesicles (EVs) contribute to the damage caused by traumatic brain injury (TBI) and can cross the blood-brain barrier (BBB). We analyzed plasma-derived EVs from human TBI patients to identify factors potentially contributing to TBI pathology. EVs were isolated using membrane affinity (ExoEasy) and size exclusion chromatography (iZone), both yielding CD9(+) and CD63(+) EVs with minimal contamination by serum albumin and apolipoprotein. Immunoblotting detected GFAP in TBI but not control EVs, indicating astrocyte-derived EVs crossing the BBB. Proteomic analysis and immunoblotting of EVs from TBI samples identified C-reactive protein and 14-3-3 proteins, which were not detected in control EVs, indicating inflammation associated with TBI. Lipidomic analysis showed ceramide enrichment in TBI EVs, validated by anti-ceramide immunoprecipitation. In a mouse closed head-controlled cortical impact model, brain EVs similarly showed elevated ceramide, confirming ceramide-rich EV release after TBI. Immunocytochemistry localized acid sphingomyelinase (ASM), a ceramide-generating enzyme, to ependymal cilia, suggesting these sites as a potential source of EVs. This was further supported by the detection of ASM in both brain- and plasma-derived EVs, along with the ciliary marker Arl13b in the brain. To assess function, we treated murine neuronal (N2a) cells with TBI EVs. Transcriptomics and STRING analyses revealed enrichment of mitochondrial-associated transcripts. Immunoblotting showed increased p53 and voltage-dependent anion channel 1 (VDAC1), which mediate ceramide-induced apoptosis. Seahorse assays showed that TBI EVs suppressed glycolysis, as indicated by reduced ECAR, while mitochondrial respiration (OCR) remained unchanged. LDH assays further indicated that TBI EVs were more neurotoxic than control EVs. Together, these findings identify ceramide-rich EVs as plasma biomarkers of TBI-induced inflammation, potential mediators of neuronal mitochondrial dysfunction, and pharmacological targets to prevent TBI-induced damage.

neuroscience↗

bioRxiv2026

Physical continuity at biomaterial-ECM interfaces regulates fibroblast activation via NF-κB

Fibrotic responses at biomaterial-tissue interfaces limit implant integration and regenerative healing, yet how the interaction between biomaterials and the extracellular matrix (ECM) regulates fibroblast activation remains poorly understood. Granular hydrogels including microporous annealed particle scaffolds (MAP) reduce fibrosis, while chemically and mechanically matched hydrogels do not, suggesting a dominant role for scaffold architecture. In this model, MAP scaffolds allow collagen infiltration and form physically continuous composites, whereas hydrogels exclude collagen and generate interfacial slip planes. To isolate how biomaterial architecture influences extracellular matrix (ECM) integration and fibroblast activation, we developed a reductionist in vitro model that integrates collagen type I with either microporous annealed particle (MAP) scaffolds or chemically and mechanically matched bulk hydrogels. This physical integration stabilizes collagen architecture, limits fibroblast-mediated matrix compaction, suppresses contractility, and attenuates myofibroblast transition. Fibroblasts in mechanically integrated environments exhibit reduced expression and nuclear localization of NF-{kappa}B and are enriched for quiescent phenotypes. Together, these findings identify biomaterial-ECM physical continuity as a design principle for limiting fibrotic signaling.

bioengineering↗

bioRxiv2026

Novel Engineered AAV Variants Demonstrate Superior Blood-Brain Barrier Penetration and Safety in Non-Human Primates

Systemic delivery of adeno-associated virus (AAV) for gene therapy of central nervous system (CNS) disorders is limited by inefficient blood-brain barrier (BBB) penetration and dose-limiting toxicity in peripheral organs, notably the liver and dorsal root ganglia (DRG)1-5. Here, we report the development of novel AAV variants via a proprietary capsid engineering platform (REACH). In non-human primates (NHPs), intravenous administration of lead variants resulted in transgene expression levels in the brain that were 600-2000 fold higher than AAV9 at the RNA level, concomitant with a 10-50 fold reduction in liver tropism and minimal off-target exposure in the heart and DRG. These engineered capsids achieve unprecedented, pan-CNS transduction with a markedly improved safety profile, representing a transformative platform for treating a broad spectrum of neurological diseases.

neuroscience↗

bioRxiv2026

Predicting Unseen Gene Perturbation Response Using Graph Neural Networks with Biological Priors

Predicting transcriptional responses to genetic perturbations is a central challenge in functional genomics. CRISPR Perturb-seq experiments measure gene expression changes induced by targeted perturbations, yet experimentally testing all possible perturbations remains infeasible. Computational models that infer responses for unseen perturbations are therefore essential for scalable functional discovery. We introduce PerturbGraph, a biologically informed graph-learning framework for predicting transcriptional responses of unseen gene perturbations by integrating interaction networks, functional annotations, and transcriptional features. Our approach is motivated by the observation that perturbation effects propagate through molecular interaction networks and manifest as coordinated transcriptional programs. Starting from single-cell CRISPR perturbation data, we construct perturbation signatures representing expression shifts relative to control cells and project them into a compact latent program space that captures stable transcriptional variation while reducing noise. Each gene is represented using enriched biological features integrating protein-protein interaction network embeddings, network topology statistics, baseline transcriptional characteristics, and Gene Ontology annotations. A graph neural network propagates information across the interaction network to infer perturbation programs for genes whose effects are not observed during training. Across unseen-perturbation benchmarks, PerturbGraph consistently outperforms classical machine learning models, perturbation-specific deep learning approaches such as scGen and CPA, and alternative graph neural architectures. The model achieves up to 6% improvement in cosine similarity over strong tree-based baselines and more than 20% improvement over linear models while improving recovery of differentially expressed genes. These results show that integrating biological interaction networks with graph representation learning enables accurate prediction of transcriptional effects for previously unobserved genetic perturbations. Code is publicly available at https://github.com/Sajib-006/PerturbGraph.

bioinformatics↗

bioRxiv2026

LRP6-Guided Engineering of AAV9 Variants with Enhanced Blood-Brain Barrier Penetration and Reduced Liver Tropism in Non-Human Primates

The blood-brain barrier (BBB) severely restricts the delivery of systemically administered adeno-associated virus (AAV) vectors for central nervous system (CNS) gene therapy. To overcome this limitation, we engineered a library of AAV9 capsid variants through rational design focused on the low-density lipoprotein receptor-related protein 6 (LRP6), a conserved mediator of transcytosis. A multi-tiered screening strategy, encompassing human BBB endothelial cells followed by neuronal and glial target cells in vitro, identified three lead variants (QL9-21, QL9-22, and QL9-25) with markedly enhanced transduction potential. In mice, these variants achieved a 5-28 fold increase in brain-wide gene delivery compared to AAV9, without elevating hepatic tropism. Crucially, evaluation in non-human primates (NHPs) revealed that the lead variant, QL9-21, mediated a striking 3-40 fold enhancement in viral genome delivery across all examined brain regions versus AAV9, while concurrently reducing liver accumulation by 2.6 fold. Our study establishes an LRP6-guided engineering platform that yields novel AAV9 vectors capable of efficient, species-conserved BBB penetration coupled with a favorable safety profile, representing a significant advance toward clinically translatable CNS gene therapies.

neuroscience↗

bioRxiv2026

A FZD4/LRP5 agonist restores pericyte coverage and vascular integrity by increasing PDGFB signaling

Pericytes, specialized mural cells of capillaries, fulfill crucial physiological functions including promoting endothelial barrier function and regulating angiogenesis. Pericyte loss or dysfunction represents a central pathological feature in diabetic retinopathy (DR) and is increasingly recognized in neurodegenerative diseases as well as in poor stroke outcomes, underscoring an urgent need for therapies that restore pericyte function or promote their regeneration. Here, we utilized a Frizzled4 (FZD4) and Low-Density Lipoprotein Receptor-Related Protein 5 (LRP5) agonist antibody (F4L5.13) to investigate the functional consequences of mimicking {beta}-catenin-dependent signaling in CNS endothelial cells (ECs), which is physiologically induced by Norrin or WNT7A/B. In platelet-derived growth factor subunit B (Pdgfb) EC-specific knockout (ECKO) mice, a model of severe developmental pericyte deficiency with secondary blood-retina barrier (BRB) defects and hemorrhages, F4L5.13 significantly promoted retinal pericyte/mural cell proliferation and coverage, improved BRB function, reduced hemorrhages, and normalized vascular morphology. F4L5.13 restored Pdgfb mRNA expression levels from non-recombined cells in Pdgfb ECKO retinas. These findings highlight interactions of {beta}-catenin-dependent signaling and PDGFB production, identify a key pharmacodynamic action of F4L5.13 distinct from anti-VEGF therapies, and suggest that FZD4/LRP5 agonists may have uses as a regenerative pharmacology approach that promotes pericyte coverage in the neurovascular unit.

developmental biology↗

bioRxiv2026

Programming Biomolecular Interactions with All-Atom Generative Model

Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework trained on more than 5 million biomolecular complexes, that enables transferable molecular design across molecular scales by assembling chemically meaningful building blocks at atomic resolution. We further introduce programmable graph prompts to support user-defined chemical, topological, and geometric steering during generation, exploring hybrid and unconventional chemistries beyond canonical structures. We demonstrate that transferable learning of interaction patterns and physical constraints across molecular modalities is possible, via an atom-to-block latent space capturing both atomic details and structural priors. The framework successfully designed small molecules, peptides, and nanobodies targeting the challenging KRAS G12D switch II pocket, as well as orthosteric peptides and allosteric small-molecule inhibitors for PCSK9 in the absence of known binding site, achieving 23%-75% success with only low-throughput validation, bypassing modality-specific high-throughput screening. AnewOmni is the first to succeed in functional molecular design across all scales, from small chemical entities to large biologics, and represents a stepstone towards general molecular reasoning engines, advocating a generative foundation model for biomolecular interactions to enter regimes where data and human intuition remain limited.

bioengineering↗

bioRxiv2026

STEVE: Single-cell Transcriptomics Expression Visualization and Evaluation

Single-cell RNA sequencing (scRNA-seq) has become a key technology for characterizing cell-type heterogeneity in complex tissues. However, its utility depends on accurate and reproducible cell-type annotation, which remains a major analytical challenge. Although hundreds of computational tools have been developed for automated annotation, there is currently no systematic framework to evaluate annotation robustness in a dataset-specific manner or within the context of complete analytical pipelines. Here, we present STEVE (Single-cell Transcriptomics Expression Visualization and Evaluation), a quantitative framework designed to assess the accuracy, robustness, and reproducibility of cell-type annotation in scRNA-seq studies. STEVE implements three complementary in silico evaluation modules: (i) Subsampling Evaluation to quantify annotation stability under varying reference sizes and data partitions; (ii) Novel Cell Evaluation to assess the ability to detect previously unseen cell types; and (iii) Annotation Benchmarking to compare alternative annotation tools against ground-truth labels. In addition, STEVE includes a Reference Transfer Annotation module that enables cross-dataset cell-type mapping using external reference datasets. All modules are built upon a unified probabilistic framework that provides consistent confidence estimation across evaluation scenarios. We evaluated STEVE across four independent scRNA-seq datasets with experimentally defined or expert-curated cell-type labels. Our results show that annotation robustness is strongly influenced by the annotation method, biological separability, dataset complexity, and batch effects. STEVE provides a practical framework for quantifying annotation uncertainty and improving reproducibility in single-cell transcriptomic analyses. STEVE is freely available at GitHub (https://github.com/XiaoDongLab/STEVE).

bioinformatics↗

bioRxiv2026

A Genetic Tool for Specific Tracking of Mature Neutrophils

Tracking mature neutrophils remains challenging due to the lack of reliable cell surface markers. Although CD101 is a promising candidate for mature neutrophils, its stability under pathological conditions is unclear. Using a CD101-tdTomato reporter mouse model, we confirmed that the reporting system does not alter CD101 expression, and tdTomato fluorescence is predominantly expressed in mature neutrophils across peripheral tissues. Further analysis revealed that CD101+ and tdTomato+ neutrophils display identical characteristics of mature neutrophil, including poly-segmented nuclei, cell size, and key functions under homeostasis. By comparing tdTomato fluorescence with CD101 protein levels, we demonstrate that reduced CD101 expression under pathological states was not attributed to shedding or degradation. Our finding enhances CD101 as a robust and reliable marker of neutrophil maturity, providing a foundation for future applications in spatial transcriptomics and lineage tracing studies to dissect neutrophil heterogeneity and function. Highlights of the studyO_LIIn CD101-tdTomato homozygous mice, tdTomato is predominantly expressed in neutrophils and labels nearly 100% of mature neutrophils, aligning with the phenotype of CD101+ mature neutrophils; C_LIO_LIThe CD101-tdTomato reporting system does not interrupt CD101 expression or neutrophil functions; C_LIO_LICD101 remains a stable and reliable cell surface marker for labeling mature neutrophils, even under pathological conditions. C_LI

immunology↗

bioRxiv2026

CEACAM5/6+ Tumor Cells and IL-1β+ Macrophages Drive Resistance to Chemo-immunotherapy in Gastric Cancer

Chemo-immunotherapy is a first-line treatment for advanced gastric cancer, yet response rates remain limited and resistance mechanisms are poorly defined. Here we generate a single-cell atlas of 542,121 cells from 35 patients treated with anti-PD-1 plus chemotherapy, profiling pre- and post-treatment tumors linked to clinical response. Integrating spatial transcriptomics, immunohistochemistry, and bulk RNA sequencing, we identify two temporally distinct resistance programs. Intrinsic resistance in pre-treatment non-responders is marked by enrichment of CEACAM5/6 tumor cells that form immune-excluded spatial niches characterized by macrophage recruitment and CD8 T-cell exhaustion. Acquired resistance in post-treatment non-responders is driven by expansion of IL-1{beta} macrophages, which induces coordinated NF-{kappa}B activation across tumor and stromal compartments, promoting PD-L1 upregulation, epithelial-mesenchymal transition, and chronic inflammation. These findings delineate an evolutionary trajectory of resistance and nominate CEACAM5/6 and IL-1{beta} as predictive biomarkers and therapeutic targets to improve anti-PD-1-based combination strategies.

cancer biology↗

bioRxiv2026

Transcranial direct current stimulation combined cognitive training modulates risk-taking behavior in older adults

Risk-taking behavior is a complex cognitive function that often declines with aging, contributing to impaired decision-making and reduced quality of life. While transcranial direct current stimulation (tDCS) has shown promising effects in modulating cognitive function, its influence on ecologically valid, complex behaviors like risky decision-making in older adults remains poorly understood. We investigated whether a single-session stimulation over the medial orbitofrontal cortex (MOFC) combined with cognitive training could enhance decision-making in healthy older adults. In a randomized, sham-controlled study, bilateral MOFC stimulation (left/anode, right/cathode) was applied during a training task based on the Iowa Gambling Task. Pre- and post-intervention assessments utilized conventional behavioral measures and the Values-Plus-Perseveration computational model, alongside task-related fMRI to examine MOFC network changes. Compared to sham, tDCS significantly enhanced the ability to distinguish advantageous from disadvantageous options. Modeling analysis revealed stimulation-induced changes in multiple latent components, such as learning rate, loss aversion, and perseveration decay. Generalized Psychophysiological Interaction analysis showed that tDCS reconfigured the MOFC network by reducing fronto-frontal hyper-connectivity and enhancing fronto-striatal connectivity. These behavioral improvements were specifically associated with the left MOFC network targeted by anodal stimulation. Our results provide causal evidence that tDCS can mitigate age-related impairments in risk-taking by reconfiguring MOFC-related networks. These findings advance the mechanistic understanding of tDCS in aging and highlight its potential as an intervention to prevent age-related decline in decision making.

neuroscience↗

bioRxiv2026

Connectome lateralization in autism across the first 14 years: heterogeneity related to developmental stage, hemisphere, and pathophysiology

Hemispheric lateralization is fundamental feature to neurodevelopment, yet its dynamic evolution in autism across childhood and underlying molecular mechanisms remain unknown. Thus, using a large-scale resting-state fMRI dataset (n = 1553, ages 1-14), we investigated developmental heterogeneity in connectome lateralization. At the group level, abnormalities in dynamic connectome lateralization strength (DCLS) progressed from focal patterns in early childhood ([≤] 6 years) to widespread distributions by late childhood ([≤] 14 years), independent of symptom severity. The late-stage patterns were validated using the ABIDE dataset (n=153). Late childhood also showed marked increases in inter-individual heterogeneity. These alterations were significantly associated with clinical phenotypes, transcriptomic profiles, and multiple neurotransmitter systems, with distinct patterns across childhood groups. Our findings reveal a developmentally dynamic trajectory of connectome lateralization in autism and highlight late childhood as a critical window for stage- and individual-specific interventions tailored to substantial individual heterogeneity.

neuroscience↗