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Xu, X.

Publications and source records attributed to Xu, X..

At least 19 recordsLinked to original sources
bioRxiv2026

Live Spatial Transcriptomics Enables Longitudinal Tissue Mapping

Spatial transcriptomics has become an important technology in biomedical research by preserving the spatial context of gene expression in tissues and enabling the study of cellular states and interactions in situ. However, most existing methods provide only static snapshots of individual tissue specimens, requiring inference of the molecular dynamics underlying development, disease progression, and therapeutic response from different specimens rather than direct tracking in the same living tissue. Here, we introduce Live Spatial Transcriptomics (Live-ST), a technology that enables longitudinal, transcriptome-wide profiling of living tissue. Live-ST combines electroporation-based intracellular sampling and spatial barcoding to enable repeated, spatially resolved mRNA measurements in intact living tissue through next-generation sequencing. We demonstrate its capabilities by (i) benchmarking spatial mRNA capture in patterned two-dimensional cell systems, (ii) spatially profiling transcriptomes in intact, patient-derived living melanoma tissues while preserving tissue viability, and (iii) longitudinally tracking drug-response dynamics within the tumor microenvironment. Together, Live-ST enables repeated, non-destructive measurements of spatial gene expression, providing a new framework for studying dynamic tissue biology in native physiological and pathological contexts.

bioengineering↗
bioRxiv2026

In Utero MRI of Radial Glial Fibers Highlights Their Role in Modulating Fetal Cortical Folding

The process of cortical folding is fundamental to early human brain development. While the differential growth of the cortical layers is a known driver, the biomechanical contribution of key cellular microstructures remains unclear, and there is a lack of direct in vivo markers of cortical microstructures for time-resolved observations. Using a multimodal approach combining in utero and ex vivo fetal brain MRI, histology, and computational mechanical simulation, we investigated whether developmental reorganization of cortical radial microstructures, particularly the radial glial cell (RGC)-associated scaffold, is linked to cortical folding and may modulate its mechanical progression. We characterized this radial organization noninvasively using diffusion MRI-based radial fiber density (FDrad). ex vivo fetal brain MRI and histology supported that regional variations in FDrad were strongly associated with vimentin-labelled radial architecture. Our in utero MRI data revealed closely coordinated developmental changes in cortical FDrad and curvature, with their regional timings and spatial patterns significantly coupled across the cortex. Longitudinal in utero MRI data further supported the synchronized within-individual co-development of FDrad and curvature. Furthermore, biomechanical simulations showed that reducing radial reinforcement modulated differential-growth-driven buckling, producing earlier folding and a greater cortical curvature under otherwise matched model conditions. Collectively, this study introduces FDrad as a noninvasive in utero MRI measure sensitive to radial glial fibers. By integrating spatial, temporal, histological, and computational evidence, our findings suggested a model in which developmental disassembly of the radial scaffold may modulate the mechanical response of the fetal cortex to differential growth, thereby contributing to cortical folding.

neuroscience↗
bioRxiv2026

Pre-saccadic suppression and compensatory cortical distortions support predictive visual remapping

Perceptual continuity across saccades relies on the predictive remapping of receptive fields (RFs) of visual neurons, driven by corollary discharge (CD). However, how the brain achieves accurate and coherent remapping within its non-uniform visual representation remains unclear. Here, we present a generalized framework of recurrent 2D network in which neurons conjunctively tuned to retinotopic location and planned saccade direction integrate CD signals to predictively remap. We show that pre-saccadic suppression (PS) stabilizes this process by counteracting direction selectivity distortions, while recurrent connectivity preserves cell-cell RF relationship against input noise by constraining the cortical map to a low-dimensional manifold. Analyzing macaque V2 recordings, we validate saccade direction selectivity, the role of PS, and conserved RF relationships. Lastly, we show that while non-uniform representation introduces eccentricity-dependent remapping errors in the model, countervailing distortions systematically reduce them. Our study reveals how network architecture can reconcile the demands of visual acuity and perceptual continuity.

neuroscience↗
bioRxiv2026

ScienceRSI: Recursive Scientific Self-Improvement

Scientific AI can improve cumulatively when capabilities developed in one model become useful learning signals for the next. We introduce ScienceRSI, a framework for recursive scientific self-improvement organized around specialize, verify, transfer, and reuse. Compact experts develop complementary scientific capabilities; shared evaluation identifies their useful contributions; a target model integrates those contributions and can serve as the starting point for further specialization. This organization connects reasoning, model scaling, and iteration through reusable scientific capabilities. We evaluate its transfer step in 4B[->]4B, 4B[->]8B, and 8B[->]27B configurations. ScienceRSI ranks first among the compared methods on all five science benchmarks for the 4B and 8B students. Relative to rubric-based reinforcement learning, scientific-reasoning averages improve by 2.0 and 1.9 percentage points, and domain-science averages by 3.3 and 2.1 points, respectively. In a separate cross-generation 27B extension, reported scores improve over Vanilla on all seven benchmarks, with the unweighted mean rising from 87.3% to 94.0%. These results support verified capability transfer across model scales as a practical foundation for ScienceRSI. Accumulating these gains over repeated rounds is the next step toward sustained recursive scientific improvement.

bioinformatics↗
bioRxiv2026

The effects of DNA repair factor-Cas9 fusions on homing drive performance

CRISPR-based homing gene drives achieve super-Mendelian inheritance by converting wild-type alleles into drive alleles through homology-directed repair (HDR). However, competing end-joining repair can generate resistance alleles that limit drive spread. Although fusing Cas9 to DNA repair-associated proteins has improved HDR in conventional genome editing systems, its effectiveness in gene drives remains unclear. Here, we systematically evaluated in Drosophila melanogaster eight Cas9 fusion constructs previously reported to improve HDR in other systems. Although none of the fusion constructs significantly increased HDR-associated signals in S2 cells, several candidates retained relatively high activity comparable to standard Cas9. These candidates were then tested in vivo across multiple split drive systems, regulatory elements, target loci, and parental sexes. Cas9-POLD3 significantly increased female drive inheritance in contexts with low baseline efficiency or substantial nonfunctional resistance formation, likely by increasing effective cutting rate and potentially also by biasing repair outcomes toward drive conversion. Cas9-Geminin degron generally maintained germline drive performance while reducing embryo resistance. Together, these findings identify Cas9-POLD3 and Cas9-Geminin degron as complementary, context-specific tools for enhancing drive conversion and limiting embryo resistance, respectively. These results highlight the importance of matching fusion modules to the regulatory and genetic context of individual drive systems.

genetics↗
bioRxiv2026

Reinforcement learning with evolutionary priors unlocks multi-site enzyme optimization from sparse experimental feedback

Industrial enzymes underpin sustainable manufacturing, yet natural proteins rarely combine the activity, robustness and application compatibility required for practical use. Engineering such properties requires identifying beneficial combinations of interacting mutations within vast sequence spaces that are too large to search exhaustively and too sparsely sampled to model reliably. Here we introduce AlphaVariant, a reinforcement-learning (RL) framework that couples a generative evolutionary prior with iteratively updated low-N fitness models to enable feedback-driven search of large combinatorial protein sequence spaces. Across six experimentally measured protein fitness landscapes, AlphaVariant ranked first on the three large, non-enumerable multi-site landscapes. In two successive rounds of savinase activity optimization, AlphaVariant-designed libraries yielded 75.4% and 83.8% activity-improved variants among experimentally characterized candidates even as the accessible mutation space expanded from 25 to 67 positions. The search identified beneficial mutation combinations involving up to 17 structurally dispersed sites and produced a variant with 7.1-fold higher activity than wild type after only two design-test cycles. We then extended AlphaVariant to jointly optimize activity, thermostability and a patent-informed constraint for intellectual-property freedom. This multi-objective search yielded variants that outperformed the commercial protease Uno 100 L in both biochemical assays and application-relevant detergent washing tests. These results demonstrate that generative RL can efficiently navigate vast protein fitness landscapes, progressively incorporate multiple engineering objectives and convert sparse experimental feedback into enzyme variants with industrially relevant performance, effectively resolving the limits of biocatalyst engineering.

bioinformatics↗
bioRxiv2026

BioMINTREL expands biological problem solving through cross-disciplinary representations

Biological research agents often rely on familiar analytical methods, limiting the questions explored in existing data. We introduce BioMINTREL, an AI agent that finds methods from other disciplines and connects them to biological measurements. It can draw on relationships among datasets and complementary ideas from several methods to develop new questions and analyses. We evaluate it on BioMDC-Bench, which assesses 228 possible applications of computational methods to biological tasks. Compared with GPT-5.4 mini and Qwen3.6-35B, BioMINTREL improves F1 agreement with human experts by up to 45.3 percentage points and increases coverage of applications supported by studies published in subsequent years by up to 58.8 percentage points. Four case studies on real data go beyond previous analyses to reveal dose-specific variant effects, constraints on spatial cell communication and routes through perturbation-response states, and identify the sampling needed to test whether rare high-state cells predict later lineage size. These results highlight BioMINTREL's potential to expand questions in existing data and suggest directions for subsequent research.

bioinformatics↗
bioRxiv2026

Decoding super-enhancer regulatory grammar and pathogenic gain-of-function variants directly from DNA sequence

Super-enhancers (SEs) drive cell-identity gene expression, yet their identification relies on epigenomic profiling (e.g., H3K27ac ChIP-seq), precluding discovery in unprofiled cellular states and leaving their underlying sequence grammar unknown. Here, we present Borzoi-SE, a deep learning framework built upon the genomic transformer Borzoi that formulates SE discovery as hierarchical, cell-type-resolved genomic object detection directly from long-range sequence across 90 human lineages. Base-resolution attribution recovers lineage-defining master transcription factors across cell types. Within SEs shared across lineages, it reveals lineage-dependent motif usage, suggesting that the same regulatory regions can support distinct cell-type-specific programs. Using in silico ablation, Borzoi-SE decoded the functional hierarchy of the {beta}-globin super-enhancer, prioritizing hypersensitive site 2 (HS2) as the dominant constituent, which we experimentally verified via CRISPR interference. Trained without variant-effect labels, Borzoi-SE identified gain-of-super-enhancer variants in different tissues. At the CHRM2 locus, a single-nucleotide variant created a de novo glucocorticoid receptor (GR) motif that recruited activated GR and potentiated adjacent MEF2 regulatory syntax, nucleating a cardiac super-enhancer. Orthogonal multi-omics and population-genetic evidence linked this variant to increased CHRM2 expression and variation in resting heart rate and PR-interval duration. Borzoi-SE establishes a general framework for decoding SE regulatory grammar and prioritizing causal non-coding variants directly from sequence.

genomics↗
bioRxiv2026

Charting sex divergence in the human brain across the lifespan

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

neuroscience↗
bioRxiv2026

Antiviral Sulfonated Polymersomes Inhibit Corona-, Influenza-, and Alphavirus

A broad-spectrum antiviral is required to enable rapid intervention against current, newly emerging and mutating viruses. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), Sindbis virus (SINV) and chikungunya virus (CHIKV) all engage negatively charged moieties on host cells, such as heparan sulfate (HS) and sialic acid, to facilitate attachment for entry and infection. We designed HS-mimetic nanoparticles in the form of polymer vesicles (polymersomes) by blending membrane-forming and sulfonated copolymers. These biocompatible polymersomes successfully inhibited host cell infection of HS-dependent SARS-CoV-2 and HS-independent IAV in vitro with sub-nanomolar potency. Multivalent interaction of several virus ligands with a single polymersome as quantified by fluorescence correlation spectroscopy likely contributes to their potency. The sulfonated polymersomes also functioned in vivo as demonstrated by a reduction in the spread of SINV, an alphavirus model for CHIKV, in zebrafish embryos, which led to a significantly increased survival. Hence, our polymersomes could form the basis for an urgently required multifunctional broad-spectrum antiviral nanomedicine.

bioengineering↗
bioRxiv2026

AbRefine: Framework-Conditioned Refinement for Structure-Guided Antibody CDR Design

Structure-guided antibody CDR design constrains residue selection using backbone geometry, but structural evidence alone may leave multiple amino acids plausible. We investigate whether the fixed antibody framework provides complementary sequence information for resolving this ambiguity. We introduce AbRefine, an information-aware fusion framework that combines backbone-conditioned structural predictions with framework-conditioned sequence distributions derived from a pretrained antibody language model with all designed CDRs masked. Its Information-Aware Fusion (IAF) module learns residue-specific fusion weights from the uncertainty, disagreement, and information content of the two predictive distributions, while keeping both pretrained experts frozen. Controlled interventions show that the signal is target specific: matched frameworks outperform shuffled frameworks by 7.37 percentage points, and the largest gain occurs at positions with high structural uncertainty and informative framework evidence (+5.77$ points). Compared with static fusion, IAF further improves AbMPNN recovery by +1.53 points (95\% CI +0.93$ to +2.14$) and significantly reduces native negative log-likelihood for both AbMPNN and AntiFold, without detectable degradation in fold-back structural compatibility. These results show that framework context provides information beyond backbone geometry and that learning its residue-specific utility enables effective adaptive fusion for antibody CDR design.

bioinformatics↗
bioRxiv2026

Validation of behavioural tests for personality assessment in tie-stall dairy cows

The study of animal personality has gained increasing attention in recent years, as researchers recognize that non-human animals exhibit stable individual differences in behaviour. In dairy cattle, understanding personality traits holds potential for improving animal welfare, enhancing management practices, and supporting productivity outcomes. However, validating the behavioural tests used to assess these traits remains a significant challenge. The present study aimed to evaluate the consistency and validity of five commonly used behavioural tests in dairy cows: the Human Approach Test (HAT), Sudden Test (SUD), Novel Object Test (NOT), Open Field Test (OFT), and Novel Surface Test (NST). These tests were chosen for their potential to assess personality dimensions that parallel components of human personality, particularly Openness, Neuroticism, Extraversion, and Agreeableness. Repeated assessments were conducted across three time periods to evaluate both intra-test (temporal) and inter-test (contextual) consistency. Results revealed that only the SUD exhibited significant behavioural consistency across all periods, suggesting its potential as a reliable tool for personality assessment. Additionally, a moderate correlation between the HAT and SUD was observed, indicating that these tests may capture overlapping personality traits. In contrast, the remaining tests (NOT, OFT, NST) lacked consistent behavioural patterns over time and across contexts, raising questions about their reliability and the complexity of trait expression. These findings highlight the challenges of identifying stable personality traits in cattle and emphasize the need for more rigorous validation of behavioural tests. This research contributes to the growing field of animal personality by providing insights into trait stability, the limitations of current testing methods, and the potential application of personality assessment in future livestock management practices.

animal behavior and cognition↗
bioRxiv2026

Hypomagnetic field inhibits seed germination via ROS signaling and reprogramming transcriptome in Arabidopsis thaliana

The geomagnetic field (GMF) is a ubiquitous yet poorly understood environmental factor that affects plant growth and development. It has been suggested that the blue-light photoreceptor cryptochrome (CRY) functions as a critical magnetic-field sensor in birds and insects through the radical-pair mechanism (RPM). However, whether CRY acts as a bona fide transducer of GMF signals and what are the downstream cascades remain largely elusive in plants. To address these key issues, we generated hypomagnetic field (HMF) via Helmholtz coils and passive magnetic shielding to investigate the GMF deprivation effects in Arabidopsis thaliana. HMF significantly delays the germination speed without altering the final germination rate, suggesting that HMF specifically modulates germination kinetics rather than seed viability. Time-resolved transcriptomic profiling revealed a coordinated transcriptional shift characterized by downregulation of growth-promoting genes and concurrent upregulation of defense-related genes under HMF. This biphasic transcriptional reprogramming coincides with a significant increase of reactive oxygen species (ROS), linking redox perturbation to the germination delay. Consistently, supplementation with ROS-scavenging antioxidants (e.g., reduced glutathione and ascorbic acid) rescues both germination speed and the misregulated expression of a subset of HMF-responsive genes, suggesting the central role of ROS in mediating HMF bioeffects. Genetic analysis using cry1 cry2 double mutants further indicated that HMF-induced germination delay operates through both CRY-dependent and -independent signaling pathways, suggesting the involvement of additional magnetosensitive modules beyond the canonical CRY-based RPM. These findings suggest that the GMF acts as a positive environmental cue that fine tunes the growth-defense trade-off through a redox-dependent signaling.

plant biology↗
bioRxiv2026

Xenon improves autism-like behaviors in mice through potentiation of PVT-CeA glutamatergic neurotransmission

Autism spectrum disorder (ASD) is a common neurodevelopmental disease with no currently effective treatments. In this study, Xenon (Xe), a noble gas used clinically as an anesthetic and a neuroprotectant, has been investigated for its potential therapeutic effects in ASD. Two genetic ASD mouse models (Mef2c mutant and Shank3-/- mice) were exposed to a low concentration of xenon (25%) mixed with oxygen (30%) and balanced with nitrogen for a single exposure of 30 min or for 10 min per day for 10 days. These Xe exposure paradigms rescued ASD-like behaviors in both male and female mice. The behavioral improvements persisted for up to 10 days following termination of the 10-day exposure paradigm. Mechanistically, Xe reduced glutamic acid decarboxylase expression in the inhibitory neurons (verified with RNAseq) of the paraventricular thalamic nucleus (PVT) and decreased GABA release during social interaction. Targeted infusion of the GABAA receptor agonist muscimol into the PVT abolished the Xe-mediated behavioral improvements. Reduced GABAergic transmission following Xe exposure increased PVT glutamatergic neuronal activity. Chemogenetic inhibition of these neurons eliminated the therapeutic effects of Xe, whereas chemogenetic activation mimicked the Xe-induced behavioral improvements. Furthermore, opto-inhibition of PVT glutamatergic projections to the central amygdala (CeA) blocked Xe-mediated behavioral improvement. Opto-activation of the PVT-CeA glutamatergic circuit reversed ASD-like behaviors. These findings demonstrate that Xe ameliorates ASD-like phenotypes in mouse models by modulating the PVT Glu-CeA circuit, supporting Xe as a novel potential therapy for ASD.

animal behavior and cognition↗
bioRxiv2026

Temporal TOC1-CLV3-WUS cascade controls organogenesis and rhythmic stem development

Coordinated organogenesis and rhythmic stem development determine shoot morphogenesis, which governs distinct plant architecture and crop yield. The shoot apical meristem (SAM) drives organ initiation and stem growth, with its activity sustained by the spatially defined CLAVATA3 (CLV3)-WUSCHEL (WUS) feedback loop. However, how the temporal CLV3-WUS module modulates SAM activity remains elusive. Here, we demonstrate that both CLV3 and WUS are required for circadian stem elongation. The clock component TIMING OF CAB EXPRESSION1 (TOC1) directly activates and sustains the circadian expression of CLV3, and this regulatory process is controlled by the APETALA1-CIRCADIAN CLOCK-ASSOCIATED1 module. Notably, the rhythmic expression pattern of CLV3, rather than its transcript abundance, plays a more important role in regulating WUS expression and sustaining SAM activity, and CLV3 confers circadian rhythmicity to WUS protein accumulation. Transcriptome and ChIP seq analyses reveal that WUS modulates multiple developmental programs, including meristem homeostasis, phytohormone responses, and cell wall remodeling. Mechanistically, WUS directly activates PECTIN METHYLESTERASE5 expression to promote stem elongation. Collectively, our findings uncover a spatiotemporal regulatory cascade that fine-tunes SAM activity to coordinate rhythmic organogenesis and stem development, thereby establishing optimal phyllotactic patterning in plants.

plant biology↗
bioRxiv2026

Spatiotemporal atlas resolves the mesenchymal-epithelial stem cell axis governing human hair follicle aging and pathology

How adult stem cell populations coordinate tissue regeneration across physiological and pathological states remains unclear. Hair follicles contain epithelial and mesenchymal stem cells that codetermine hair regeneration. Here, we integrate a multimodal spatiotemporal atlas with functional validation to define the mesenchymal-epithelial stem cell dynamics governing human hair follicle homeostasis, aging, and androgenetic alopecia. Aging is characterized by passive depletion of hDSC-derived regenerative cues, whereas AGA involves a shift of hDSC toward an inhibitory signaling hub that promotes HFSC dysfunction. We further pinpoint hDSC-secreted PTN as a key regenerative factor that promotes hair growth and counteracts androgen-induced growth suppression. This study provides a holistic framework of adult stem cell crosstalk across physiological and pathological states, offering a mechanistic roadmap to reinstate tissue regeneration.

cell biology↗
bioRxiv2026

Conserved microglial programmes, non-transferable classifiers: boundaries of the single-cell TBI molecular clock

Background: Traumatic brain injury (TBI) pathology evolves over hours to months, and molecular staging could complement clinical and imaging-based assessment. Single-cell transcriptomics captures cell-type-resolved temporal programs, but whether a transcriptional "molecular clock" trained on one injury model can be transferred to others remains unknown. Methods: We compiled four public mouse TBI single-cell/single-nucleus datasets spanning two injury models - controlled cortical impact (GSE277487; CEREBRI) and fluid percussion injury (GSE160763) - plus an independent mild-FPI cohort reserved for validation (GSE247339), totalling 307,991 cells across four pathological stages (control, acute, subacute, chronic). Classifiers were evaluated at cell and sample levels (held-out libraries) against a permutation null, with per-cell-type, strict leave-one-dataset-out (LODO) generalization, glial-only transfer and gene-level SHAP analyses. Results: Within GSE277487, sample-level balanced accuracy reached 0.67 (permutation null 0.32 +/- 0.09; p = 0.001), and the signal was reproduced in the independent mild-FPI cohort (0.40 vs null 0.19 +/- 0.05; p = 0.0010). Cell-level cross-validation overestimated performance by ~0.16, quantifying within-sample leakage. Cross-dataset generalization was poor (strict LODO balanced accuracy 0.20-0.31); the acute immediate-early response was untransferable (recall 0.002) and 80% of chronic (6-month) cells were assigned to the subacute class. Glial-only models raised subacute recall across models (0.91 and 0.75), but precision was indistinguishable from a subacute-only classifier (0.51 vs 0.50; 0.58 vs 0.58) and one-vs-rest AUROC was at or below chance (0.38-0.54) across four classifier families - classifier collapse, not transferable discrimination. The reproducible cross-model component was instead a gene-expression programme: a microglial complement/lysosomal damage programme (Trem2-Apoe axis) was up-regulated across the severe CCI and FPI models (13/13 concordant genes), whereas the immediate-early module was model-specific. Conclusions: A single-cell molecular clock for TBI staging is feasible within datasets once within-sample leakage is controlled, but it does not transfer across datasets as a classifier: apparent cross-model transfer reflected classifier collapse onto the majority class, and the reproducible cross-model component was a microglial complement/lysosomal gene-expression programme. These findings define the boundaries of cross-dataset time inference in TBI and provide evaluation criteria for claims of transferable single-cell classifiers.

neuroscience↗