Biology subjects

Yao, H.

Publications and source records attributed to Yao, H..

At least 19 recordsLinked to original sources

bioRxiv2026

Salt Stress Shifts Isatis indigotica to Prioritize Defense over Goitrin Biosynthesis

Soil salinization threatens the cultivation quality of Isatis indigotica, a medicinal plant whose root bioactivity depends on the glucosinolate-derived compound (R,S)-goitrin. Although moderate abiotic stress is widely assumed to stimulate secondary metabolite accumulation, the temporal dynamics of goitrin biosynthesis under salt stress remain poorly understood. This study quantified goitrin content across four NaCl concentrations (100 - 400 mmol/L) and four time points (2, 6, 12, and 24 h). Time-series transcriptome sequencing was performed under 100 mmol/L NaCl. Contrary to prevailing assumptions, goitrin content declined progressively from 2 to 12 h before partially recovering at 24 h, indicating that salt stress transiently suppresses goitrin accumulation rather than promoting it. Transcriptomic analysis identified 7 glucosinolate biosynthesis genes whose expression positively correlated with goitrin content (p < 0.05), and 6 salt stress-responsive genes negatively correlated with goitrin content (p < 0.05). These opposing patterns suggest that stress defense is transiently prioritized over biosynthesis, with partial metabolic recovery as plants adapt. These findings reveal a defense-biosynthesis trade-off mechanism in I. indigotica roots and provide a transcriptomic framework for understanding how abiotic stress reshapes secondary metabolism in medicinal plants.

plant biology↗

bioRxiv2026

Archetype analysis of multiplexed antibody imaging reveals interpretable morphological programs in optical pooled screens

High-content imaging-based screens with small molecule or genetic perturbations rely on rich optical phenotypes, yet how distinct subcellular markers contribute complementary biological information remains unclear. Here, we introduce CellMAPP, a multiplexed organelle imaging platform that uses optical pooled screens with iterative antibody staining to map cellular architecture under perturbation. Using 17 markers across 524 genetic perturbations in MCF-7 cells, we systematically examined how individual, and combinations of, markers capture diverse morphological responses. We find that markers provide complementary views of perturbation effects, with increased multiplexing improving signal and the breadth of hit recovery, although some phenotypes are better recovered from a subset of features rather than a full profile. Because non-molecular image-based profiles can be challenging to link with interpretable biology, we developed CHART (available at https://github.com/Genentech/CHART), an archetype analysis framework that identifies distinct reference morphological states for each marker and uses multimodal large language models (MLLMs) to automatically annotate them, connecting cellular images to recognizable organelle phenotypes. Integrating archetypes across multiple markers revealed modular morphological programs that describe coordinated organelle reorganization in response to perturbation. This framework identified regulators of defined organelle states such as micronuclei, nominated novel gene functions and revealed complex patterns of multi-organelle reposition. Together, optical profiling with MAPP and CHART provides an interpretable, scalable framework for image-based screens that sheds light on rules governing cellular structural reprogramming.

systems biology↗

bioRxiv2026

Inferring cascade drivers of VEXAS syndrome by a causal machine learning tool CauNagi

VEXAS syndrome is an adult-onset severe autoinflammatory disease caused by somatic mutations in UBA1, yet the cascade mechanisms linking primitive hematopoietic abnormalities to mature myeloid dysfunctions remain largely unknown. Identifying master regulators of a progressive disease, a black-box process, from complex transcriptomic data also remains challenging. To address this challenge, we developed CauNagi, a computational framework for prioritizing cascade candidate regulators (CCRs). CauNagi integrates a causal representation learning module derived from CausCell with an iterative deep learning backbone adapted from UNAGI; in addition, CauNagi extends these two components with a unique downstream module for CCRs analysis designed to characterize regulatory propagation across hierarchical cellular states. Mechanistically, CauNagi iteratively integrates causal disentangled representation learning with (1) disease-stage cell-state trajectory reconstruction and (2) dynamic regulatory analysis. Benchmarking on single-cell transcriptomic datasets showed that CauNagi preserved cell-type structure in idiopathic pulmonary fibrosis (IPF) and enriched known acute myeloid leukemia(AML)-associated genes among its top-ranked global regulators. When applied to VEXAS syndrome, CauNagi readily revealed inflammatory responses, endoplasmic reticulum stress, and myeloid bias, consistent with the disease features. Furthermore, the CCRs analysis module of CauNagi assisted us in identifying 36 causal drivers, with SPI1, NFKB1, STAT3, and FOS prioritized as high-confidence regulatory hubs linking aberrant myeloid differentiation and inflammatory programs. These findings were further supported by an independent single-cell transcriptomic dataset from a murine VEXAS model. Overall, CauNagi provides a computationally efficient and systematic framework for identifying candidate causal regulators. Beyond hematopoietic diseases, CauNagi may also be applicable to other progressive disorders for which multistage single-cell transcriptomic datasets are available. CauNagi is available at https://github.com/steamed-stuffed-bun/CauNagi.

bioinformatics↗

bioRxiv2026

Agentic transcranial functional ultrasound imaging: @fUS

Functional ultrasound (fUS) imaging provides deep, wide-field access to brain function, but instrument cost and complex acquisition and analysis workflows restrict its wider adoption. Here we introduce @fUS, an agentic transcranial imaging platform with an open architecture that integrates purpose-built hardware with executable experimental skills and persistent structured memory. The system combines 128-channel, 16-bit acquisition at 125 MHz with GPU-based processing and enables functional imaging through the intact scalp and skull of mice, with approximately 100-m spatial resolution and 10-Hz temporal sampling, providing a basis for longitudinal studies without cranial-window surgery. Its agent connects scientific objectives to experimental design, direct instrument control and data analysis, retaining context across interactions and supporting inspectable workflows through text and hands-free voice control. Neuroscience trainees with limited engineering experience independently configured the system within 30 min. Agent-assisted exploration of whisker-stimulation datasets revealed low-frequency vascular changes beyond conventional response mapping, supported by complementary two-photon measurements of single-vessel diameter. By combining transcranial imaging with accessible instrument control and analysis, @fUS provides a foundation for wider adoption and larger, more diverse neuroscience datasets. More broadly, it offers a framework for scientific instruments in which measurement, computation and experimental reasoning are developed as parts of the same system.

bioengineering↗

bioRxiv2026

Plant-adapted OTO staining improves ultrastructural imaging by transmission electron microscopy

Transmission electron microscopy (TEM) is widely used to examine plant cellular ultrastructure, but sample preparation remains challenging because polysaccharide-rich cell walls, large vacuoles and complex membrane systems compromise staining and structural preservation. Here, we developed a plant-adapted TEM preparation method based on a modified osmium-thiocarbohydrazide-osmium (OTO) staining workflow combined with optimized washing, dehydration and resin infiltration. Using tomato roots and leaves, we show that the optimized method produces cleaner backgrounds, better-defined cellular boundaries and improved preservation of cellular morphology compared with conventional preparation. Fine membrane-associated structures, including mitochondrial cristae, chloroplast grana and stroma lamellae, nuclear membranes and other endomembrane structures, were more clearly resolved, while staining-related precipitates and diffuse background artifacts were reduced. This method provides a practical approach for high-contrast TEM imaging of plant tissues and ultrastructural analysis of plant cells and organelles.

plant biology↗

bioRxiv2026

Global tree encoding of atlas-scale single-cell genomics

The rapid expansion of single-cell genomic datasets has led to the compilation of biological resources comprising hundreds of millions of cells across tissues, developmental stages, and disease states. This has underscored the need for scalable and interpretable data representations that preserve the complex relationships and multi-scale organization of cellular states, while remaining computationally tractable at atlas scale. Existing approaches based on discrete abstractions have enabled cell annotation, clustering, and trajectory inference, but are often optimized for local inference tasks and may obscure continuous cellular relationships and multi-resolution structure within complex transcriptional and other genomic landscapes. Moreover, increasing dataset sizes often require information-reduction strategies such as random downsampling, limiting the resolution of rare cell populations and heterogeneous cellular states. Here, we present MILK, a scalable computational framework that organizes high-dimensional single-cell populations into unified tree representations. Across large-scale transcriptomic atlases, MILK enables representative subsampling with preserved information, supporting the tractable application of existing algorithms for tasks including deep generative model training and foundation model benchmarking. Additionally, MILK enables holistic, multi-resolution analyses that capture global developmental trajectories, characterize disease-associated cellular perturbations across tissues, and facilitate comparison of transcriptional programs across species within a coherent hierarchical framework. Together, these results establish the hierarchical organization of biological data as a scalable and unifying representation of cellular identity, enabling integrative analysis of single-cell genomic data across diverse contexts.

genomics↗

bioRxiv2026

Proteome Profiling of Human Tear Fluid Following Acute Exercise

Acute exercise induces systemic molecular perturbations that are not fully reflected by individual biomarkers. Tear fluid is amenable to non-invasive and repeated collection and contains a diverse array of bioactive molecules, thereby constituting a practical biological specimen for evaluating exercise-related physiological responses. However, the immediate proteome-wide alterations in tear fluid following acute exercise have not been characterized. In this study, we performed quantitative proteomic profiling of paired tear samples obtained from healthy female participants before and immediately after a single exercise session, using data-independent acquisition liquid chromatography-tandem mass spectrometry (DIA-LC- MS/MS). Among the 3,173 identified proteins, 744were significantly altered post-exercise, of which 484 exhibited up-regulation and 260 exhibited down-regulation. Functional enrichment analysis demonstrated that the up-regulated proteins were predominantly associated with translation and ribosome biogenesis, whereas down-regulated proteins were primarily involved in glycan metabolism, lysosomal processing, and extracellular matrix organization. Collectively, these observations indicate that acute exercise elicits a rapid and coordinated reconfiguration of the tear proteome. To our knowledge, this investigation provides the first proteomic evidence of the immediate tear response to physical activity, offering a molecular basis for understanding exercise-mediated modulation of tear composition and ocular surface homeostasis.

physiology↗

bioRxiv2026

Discovery of an NRAS isoform and activation-state selective macrocyclic peptide

Macrocyclic peptides have gained increased attention amid claims they are a "Goldilocks" therapeutic modality that can encode the selectivity of a biologic in a footprint close to that of a small molecule. Here we attempt to find a peptide that binds selectively to NRAS, sparing HRAS and KRAS, while accessing the cytosol via passive cell permeability. To do so, we combine subtractive affinity selection with mRNA display to identify Compound 1, an 11mer macrocyclic peptide which binds NRAS at a novel allosteric site between Helix 3 and Helix 4 of the GTPase domain. Compound 1 has total isoform selectivity and can be tuned to achieve activation-state selectivity with a single amino acid change. While it has preferential affinity for oncogenic NRAS-specific mutations, it does not inhibit NRAS function or achieve passive membrane permeability.

cancer biology↗

bioRxiv2026

A Chairside Multimodal Platform for Temporomandibular Joint Biomechanical Assessment: Technical Evaluation and Illustrative Application

BackgroundTemporomandibular joint (TMJ) biomechanics can be characterized by mandibular motion, masticatory muscle activity, and bite force generation. When acquired synchronously, these functional variables can serve as model-ready inputs for subject-specific computational analyses of internal joint mechanics. However, existing tools typically measure these signals using separate hardware and software platforms, limiting synchronized acquisition within a clinically practical chairside workflow. MethodsWe developed and technically evaluated a compact multimodal platform for chairside acquisition of TMJ functional data and demonstrated its analytical utility in an illustrative orthognathic surgery application. The platform integrates motion, bite force, muscle activity, acoustic, and event-timing measurements with software for real-time preview, protocol guidance, and synchronized export. We assessed technical performance and chairside feasibility and analyzed representative pre- and postoperative data from an orthognathic surgery patient using kinematic, force-control, and computational modeling workflows. FindingsMotion capture demonstrated submillimeter accuracy, with static and dynamic errors of approximately 0.04 mm and 0.12 mm. Bite force sensors showed excellent linearity (R{superscript 2} = 0.998). Chairside deployment required approximately 15 minutes each for setup and data collection. The illustrative case demonstrated that synchronized chairside data can support preoperative and postoperative kinematic analysis, bite force control capacity assessment, and estimation of TMJ disc stress. InterpretationThe proposed platform enables time-efficient chairside acquisition of synchronized, model-ready multimodal datasets for quantitative TMJ biomechanical assessment. This platform and workflow could support subject-specific biomechanical analysis and future clinical studies of temporomandibular joint function.

bioengineering↗

bioRxiv2026

Multiscale Biomechanical and Electrophysiological Modeling of Nociceptive Activation in Musculoskeletal Joint Disorders: Insights from the Temporomandibular Joint

Background and objectiveMusculoskeletal joint disorders often show inconsistent relationships between structural degeneration and nociceptive pain. Temporomandibular joint (TMJ) disc displacement represents a clinically relevant model for investigating the structure-function-pain relationship. This study aimed to develop a multiscale computational framework integrating biomechanics, three-dimensional (3D) neural morphology, and electrophysiology to quantitatively link TMJ structural alterations, biomechanical loading, and peripheral nociceptive activation. MethodsStrain distributions in the TMJ disc and retrodiscal tissue during mouth opening and clenching were computed in ArtiSynth under varying degrees of displacement. Human TMJ 3D nerve architecture was reconstructed using porcine TMJ nerve mapping data as an anatomical reference, and ion channel dynamics were implemented in NEURON. Model coupling was achieved by mapping biomechanical strain fields onto nociceptor membranes to simulate mechanosensitive currents and action potential propagation to the trigeminal ganglion. ResultsAnterior DDwoR induced a severity dependent strain pattern in the TMJ disc and retrodiscal tissue, including posterior redistribution, increased strain magnitude, prolonged activation, and broader retrodiscal tissue involvement. Displacements of 4, 6, and 8 mm produced larger mechanosensitive currents, broader terminal depolarization, and higher trigeminal firing rates during mouth opening (6, 18, and 28 Hz) and clenching (8, 20, and 28 Hz), whereas 0- and 2-mm displacements produced negligible neural activation. ConclusionsThis study establishes a multiscale biomechanical-electrophysiological framework linking TMJ structural alterations to peripheral nociceptive activation. The framework quantitatively connects macroscale strain patterns with microscale neural activation, suggesting that anterior disc displacement may amplify peripheral nociceptive signaling by increasing the overlap between elevated strain and densely innervated retrodiscal tissue.

bioengineering↗

bioRxiv2026

A Glutamine antagonist-modulated tumor microenvironment unleashes enzalutamides immunotherapeutic effects

Androgen receptor (AR) antagonists, such as enzalutamide, suppress prostate cancer (PCa) cells to achieve temporary therapeutic effects. In addition to tumor cell-autonomous suppressive function, AR antagonists can also potentially exert anti-tumor effects via mitigating cytotoxic T cells exhaustion. However, strategies for effectively harnessing enzalutamides immunotherapeutic effects remain elusive. In studying a recently described glutamine antagonist prodrug (DRP-104) in PCa models, we found that despite the initial response, tumors ultimately became resistant. Intriguingly, compared to the untreated (DRP-104 treatment-naive) tumors, the resistant tumors became highly susceptible to enzalutamide in vivo. Additionally, treating tumors with DRP-104 and enzalutamide simultaneously also yielded superior therapeutic efficacy. We demonstrated that DRP-104 therapy promoted the infiltration of CD8+ T cells as well as regulatory T cells (Treg) in responsive tumors, and the tumor-infiltrating Treg were mostly depleted upon enzalutamide treatments. Mechanistically, we showed that Treg differentiation from mouse CD4+ T cells was attenuated by enzalutamide. We further demonstrated that Treg induction was accompanied by the interaction between AR and aryl hydrocarbon receptor (AhR), the nuclear receptor indispensable for Treg differentiation, in the nuclei of CD4+ T cells, and this interaction was diminished by enzalutamide. In further support of AR signaling in Treg biogenesis, analysis of available gene expression datasets found that AR expression was elevated in Treg when compared to CD4+ T cells in human peripheral blood mononuclear cells (PBMCs). In addition, it was positively correlated with Treg module scores in several human cancer types. Finally, using an anti-GPC3 (Glypican 3) vaccination model, we demonstrated that CD4+ T cells subjected to Treg induction in the presence of enzalutamide were less effective in protecting GPC3-expressing tumor cells from CD8+ T cells cytotoxic killing. Collectively, these results suggest that AR promotes Treg s differentiation and/or immunosuppressive functions, and nominate enzalutamide as a Treg-mitigating agent for potentiating immunotherapies. Our results also demonstrate that an otherwise unintended, Treg-promoting property of DRP-104 can be leveraged to unleash the immune-regulatory function of enzalutamide for the treatment of PCa.

cancer biology↗

bioRxiv2026

Virtual phenotypic screening discovers novel scaffolds inhibiting the PI3K/mTOR pathway

Phenotypic drug discovery has yielded many first-in-class small-molecule drugs by discovering modulators of disease phenotypes in physiologically relevant cellular systems. However, high-content phenotypic assays lack the ultra-high-throughput scalability of target-based screens. Recent advances in virtual screening present an opportunity to address this bottleneck, but have been limited to simple phenotypes like viability, restricted to small repurposing libraries, or lack in-depth biological validation. Here, we present PhenoCompass, a multimodal co-embedding model that aligns compound structures and high-content phenotypic imaging to enable virtual phenotypic screening over billion-compound libraries. Following training on the Joint Undertaking in Morphology dataset with more than 100,000 Cell Painting compound profiles, retrospective validation with historical biochemical high-throughput screening data demonstrates that PhenoCompass ranks compounds according to their biochemical target engagement. Leveraging PhenoCompass, we performed a prospective screen of 3.8 billion Enamine REAL compounds for inhibitors of PI3K/mTOR pathway, a critical signaling cascade whose aberrant activation is a common tumor driver. This search identified 11 novel compounds with pathway-consistent Cell Painting readout and diverse scaffolds, a 54-fold enrichment over the training set. Orthogonal validation experiments using a FOXO3A reporter assay and direct kinase inhibition confirmed seven structurally novel inhibitors with distinct mechanisms of action. These results highlight the convergence of diverse molecular target profiles onto a shared morphological pathway signature and establish PhenoCompass as a robust framework for high-content phenotypic virtual screening.

bioinformatics↗

bioRxiv2026

Gonadal PIP-seq reveals genes involved in germ cell development and sexual differentiation in sea lamprey ( Petromyzon marinus )

Vertebrate sex determination is highly diverse, with distinct mechanisms that have evolved repeatedly and independently across phylogeny. The sea lamprey (Petromyzon marinus) is an extant jawless vertebrate that remains sexually labile during its larval stage that lasts around 3-20 years. Their gonad contains bipotential, female, and male germ cells before metamorphosis. To examine the genetic programs in germ cells at different developmental stages, we profiled transcriptomes of dissociated gonadal cells from larvae and recently metamorphosed juvenile (transformers, sex-determined) using fluorescence-activated cell sorting (BD FACS Aria IIu) and PIPseqTM (Fluent BioSciences/Illumina). 66,676 cells were sequenced and classified into 19 cell clusters according to their gene expression profiles. Primordial germ cells differentially expressed genes encoding various heat-shock proteins, hormones, growth factors, and their receptors, and proteins sensitive to iron, nitrogen starvation, sugar and lipid metabolisms, and oxidative stress, providing possible links between environmental factors, cellular functions, and cell fate determinants. Germ cells in larvae had enriched expression of genes involved in DNA replication, transcription, translation, apoptosis, autophagy, cell cycle, cell differentiation, cell adhesion and migration, cell survival, chromatin remodeling, and proliferation. Specifically, female germ cells differentially expressed various transcript isoforms of AEP1, CUZD1, S100A1, and ZP genes, whereas male germ cells differentially expressed BOLL and PIWIL1. Pseudotime trajectory and Gene Ontology (GO) analysis revealed that genes with changing expressions along the female differentiation pathway were involved in binding of sperm to zona pellucida, egg coat formation, prevention of polyspermy and positive regulation of acrosome reaction. On the other hand, genes with changing expressions along the male differentiation pathway were involved in ribosome assembly and translation. Several WNT5 transcripts were differentially expressed in germ cells or somatic cells. Our results suggest that sea lamprey sex determination and sexual differentiation likely involve the coordinated action of numerous genes that interact with various environmental factors and regulate germ cell specification and development.

Developmental Biology↗

bioRxiv2026

Exercise-induced sweat suppresses depression-like behaviors in mice

Depression represents a major global public health challenge. Current antidepressant therapies are often limited by significant side effects, delayed onset of action, and suboptimal efficacy, creating an urgent need for the development of novel interventions. In this study, using a transcriptome-based bioinformatics pipeline, we found that the gene signature of depression is significantly anti-correlated with that of exercise-induced sweat (EIS), suggesting that EIS may have the potential to treat depression. To validate this prediction, we first established a lipopolysaccharide-induced mouse model of depression and then evaluated the therapeutic effects of EIS in comparison with the positive control fluoxetine. Our results show that EIS treatment significantly suppresses depressive and anxiety-like behaviors, as evidenced by increased sucrose preference in the sucrose preference test, reduced immobility in the tail suspension test, and enhanced exploratory activity in the elevated plus maze. Notably, high-dose EIS intervention achieved therapeutic efficacy comparable to, or even better than, that of fluoxetine. This study identifies EIS as a novel bioactive intervention and an innovative strategy for treating depression, and opens a new avenue in sports medicine by investigating the potential beneficial effects of EIS.

neuroscience↗

bioRxiv2026

The Structural Code of Breast Cancer Proteoform: Alternative Splicing-driven Protein Isoform Variation and Functional Diversification

Alternative splicing generates extensive transcript diversity, but the extent to which this diversity contributes to the translated proteome and reshapes protein function remains unclear. Here, we develop 3DisoGalaxy, an atlas integrating transcript reconstruction, ribosome profiling, structural modelling and regulatory annotation in breast cancer. We find that 58,292 of 90,929 transcripts are linked to translation-supported ORFs, 71.9% of which arise from non-canonical transcript structures. These products are broadly accommodated within established protein fold space, indicating that alternative isoforms frequently preserve recognizable protein architectures despite substantial sequence variation. Functional divergence is instead concentrated in domains, intrinsically disordered regions, localization determinants and regulatory motifs. Motif remodelling is biased towards gains and is more extensive in cancer-driver genes than in other genes, linking isoform-associated regulatory variation to cancer-relevant proteins. As an example of domain remodelling, we identify an AKT1-{Delta}PH isoform that lacks the N-terminal PH domain while retaining the kinase core, with immunoblotting revealing a lower-molecular-weight AKT1 species consistent with this isoform. Together, our results show that alternative transcript diversity extensively enters translation-supported proteoform space and establish a systematic link between transcript variation and protein functional diversification.

cancer biology↗

bioRxiv2026

An Isoform-Centric, Structure-Aware Framework for Protein Function Prediction and Evaluation, Instantiated in 3DisoDeepPF

Understanding and accurately predicting function across protein isoforms has been a long-standing challenge with profound implications for both biological and translational research. However, most functional annotations and benchmarks remain tied to genes or reference protein sequences, leaving limited support for distinguishing protein isoforms from the same gene whose sequence, structure and domain composition may lead to different functions. To address this gap, we developed an isoform-centric framework for protein function and domain annotation that integrates a dense graph of sequence and structure similarity with protein features. We implemented this framework as 3DisoDeepPF, a graph-based multimodal model, and applied it to a breast cancer isoform atlas. Across canonical benchmarks and evaluations at isoform resolution, 3DisoDeepPF showed strong performance in predicting GO terms and Pfam domains and remained robust in tests with homology control. It further captured changes in Pfam domain composition among isoforms from the same gene, including reference-relative domain gain and loss. An evidence tracing module links predicted labels to supporting proteins in the graph, as illustrated by the calcium and integrin binding protein 1 (CIB1). Together, this study provides a framework informed by protein structure for function and domain annotation at isoform resolution, converting human protein isoform diversity into traceable functional evidence for cancer atlas interpretation.

cancer biology↗

bioRxiv2026

Aligned recordings of neural spiking activity and licking behavior in thirsty mice

Electrophysiological data, which serve as a biological signal that bridges neural activity and behavioral tasks, provide an innovative approach to neuroscience research. In this study, we constructed a dataset that contains over 2000 neurons across 117 days recorded in 20 mice containing 28,573 trials. Data for 5 mice were collected from the Secondary Motor Cortex (M2) region 8 mice was derived from the Ventrolateral Striatum (VLS) and 7 mice were from Substantia Nigra pars Reticulata (SNR). We induced licking behavior in head-fixed mice by periodically delivering water through a spout while simultaneously recording spiking activity from three brain regions and behavior related electrical signals. This dataset ensures precise temporal alignment between neural activity and behavioral events, offering a robust foundation for investigating neural encoding mechanisms and simulation of neural activities. This dataset establishes a precise spike-to-event mapping, which enables high decoding accuracy using Multilayer Perceptron (MLP) and Support Vector Machine (SVM). It can serve as a high-quality benchmark for developing encoding and decoding algorithms in neural networks, particularly Spiking Neural Networks (SNNs).

neuroscience↗

bioRxiv2026

Exercise-induced Sweat Promotes Wound Healing in Diabetic Foot Ulcers

Persistent hyperglycemia impairs wound healing in diabetic patients, and severe cases may even lead to disability or death. Glycemic control alone cannot effectively prevent the occurrence of diabetic foot ulcers, a serious complication of diabetes. However, safe, efficient, and cost-effective therapies remain unavailable and are urgently needed. Using a novel sports medicine paradigm, we predicted, based on reverse-transcriptomics, that exercise-induced sweat has the potential to promote would healing in diabetic foot ulcers. Subsequent animal experiments demonstrated that sweat can indeed promote re-epithelialization and collagen deposition, upregulate the expression of the proliferation marker Ki-67, the angiogenesis marker CD31, and -SMA, and significantly accelerate wound healing in a mouse model of diabetic foot ulcers. This study provides a new direction for sports medicine and offers a novel therapeutic strategy for patients with diabetic foot ulcers.

zoology↗