Biology subjects

Wang, L.

Publications and source records attributed to Wang, L..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

Integrating spatial and single-cell multi-omics analysis of induced pluripotent stem cell-derived cervical adenocarcinoma model

Human papillomavirus 18 (HPV18) preferentially infects cervical stem cell-like cells and is strongly associated with adenocarcinoma. However, the mechanisms underlying differentiation into cervical adenocarcinoma remain unclear due to the lack of appropriate experimental models. We aimed to establish a model of HPV18-associated cervical adenocarcinoma and elucidate its molecular and cellular differentiation mechanisms. HPV18 E6/E7 were introduced into induced pluripotent stem cell-derived reserve cell-like cells (iRCs) to generate tumor models. Spatial transcriptomics and single-cell multi-omics analyses were performed to integrate histological and molecular data. A distinct component (Gland_A) exhibited morphological and immunohistochemical features of cervical adenocarcinoma and was efficiently induced in iRC-18 tumors. Gland_A showed increased chromatin accessibility and elevated expression of FOXA1, FOXA2, and ALDH1A1. Analysis of clinical samples confirmed enrichment of ALDH1A1 in HPV-associated adenocarcinomas. This model recapitulates key features of HPV18-associated cervical adenocarcinoma and provides insights into its differentiation mechanisms.

cancer biology↗

bioRxiv2026

PEPR-GNN: Perturbation-Enhancer-Promoter-RNA Graph Neural Networks for Multiome Perturb-Seq modeling of regulomes

Cellular reprogramming is a complex interplay between perturbations and regulatory elements, culminating in gene expression changes. Current computational approaches do not explicitly model these regulatory interactions. Here, we performed combinatorial reprogramming with cardiac transcription factors, followed by Multiome Perturb-Seq to measure perturbations, open chromatin, and gene expression in individual cells. We then developed PEPR-GNN (Perturbation-Enhancer-Promoter-RNA Graph Neural Network), a theoretical and computational framework to model regulome responses during complex genetic perturbations. By statistically associating gene regulatory relationships, PEPR-GNN organizes genes into regulomes with shared gene regulatory responses to reprogramming, including easy-to-reprogram cardiac genes, difficult-to-reprogram fibroblast genes, and context-specific genes where the impact of a reprogramming factor depends on the presence of others. Finally, we use PEPR-GNN for in silico modeling of how genetic modifications of enhancers can be used to tune gene responses to reprogramming. Overall, through the use of causal perturbation information and an enhancer-aware regulome model of gene regulation, PEPR-GNN can effectively model complex cellular responses to perturbation. HighlightsO_LIMultiome Perturb-Seq of GHMT reprogramming in MEFs with RNA/ATAC-Seq readout. C_LIO_LIPEPR-GNN: a computational framework to model perturbation-induced regulomes. C_LIO_LIPEPR-GNN aids the interpretation of regulomes by diverse reprogramming responses. C_LIO_LIPEPR-GNN enables in silico perturbation to tune gene responses to reprogramming. C_LI

genomics↗

bioRxiv2026

A generative reference grammar of healthy TCR repertoires reveals cancer-associated immune remodeling

T-cell receptor (TCR) repertoires record how adaptive immunity is organized and how cancer and therapy reshape it, but this signal is hard to read: treatment-associated change is entangled with the V(D)J recombination constraints that shape every repertoire. We present CRAFT (Cancer Repertoire Anomaly Finding Transformer), a conditional sequence-to-sequence transformer that learns a nucleotide-level generative grammar of productive TCR-beta CDR3 sequences from healthy donors, conditioned on germline V(D)J assignments. A dual-head decoder mirrors the independence of V-D and D-J recombination, and curriculum training produces embeddings that define a healthy-reference coordinate system in which cancer-associated change appears as structured, measurable deviation. In proof-of-concept applications to a neoadjuvant checkpoint-blockade cohort sampled longitudinally across blood, and to serial single-cell profiling of T-cell subsets during oncolytic immunotherapy, CRAFT geometric metrics capture response-associated remodeling, including shifts in repertoire organization over time. On antigen-labeled benchmarks, CRAFT organizes specificity classes coherently, recovering structure that reflects shared antigen recognition.

cancer biology↗

bioRxiv2026

Multimodal alignments of in vivo imaging and spatial biology datasets at cellular resolution

Parallel revolutions in intravital microscopy and spatial biology techniques have respectively enabled large-scale recordings of cellular dynamics in live animals and multi-dimensional molecular profiling at single-cell resolution. However, due to the challenges of aligning data from different modalities at cellular resolution, these two transformational approaches have generally been applied on separate biological samples, stymying the ability to link activity patterns and molecular attributes in the same exact cells. To enable routine, multimodal investigations of cells in vivo dynamics and molecular content, we created TRU-FACT (Total Registration Under Functional Activity, Connectivity, and Transcriptomics), a broadly applicable experimental and computational pipeline for registering large populations of individual cells across intravital imaging and spatial biology datasets. The pipeline combines three key innovations: an optomechanical tissue handling and alignment method to parallelize specimen planes, a graph-theoretic method to register individual cells based on their geometric relationships to neighboring cells, and a statistical framework that provides for each cell an a posteriori probability of correct registration. We validated TRU-FACT with several preparations for imaging neural Ca2+ activity in cortical and deep brain areas in head-fixed and freely behaving mice, RNA-barcode-expressing viruses for labeling neural projections, and low- and high-plex spatial transcriptomic methods. In mice performing a skilled reaching task, TRU-FACT alignments revealed the movement-related signaling patterns of intratelencephalic, extratelencephalic, and striatum-, superior colliculus-, and thalamus-projecting motor cortical neurons. Overall, TRU-FACT constitutes a scalable, multimodal discovery platform that is applicable to diverse tissue-types and spatial biology techniques, thereby enabling multiscale analyses of many complex biological systems.

neuroscience↗

bioRxiv2026

Olfactomedin 4 marks luminal progenitor cells that give rise to a secretory cell lineage in the mouse cervix

Development of the female reproductive tract in mice occurs in early postnatal life. The current model identifies Trp63 as the master regulator that initiates differentiation of simple columnar Keratin 8+ epithelium in the cervix and vagina into a stratified squamous epithelium. Thereafter Trp63+ basal progenitors maintain cervicovaginal epithelial cell homeostasis and in the adult serve as the progenitor for hormone-regulated shifts in stratified squamous and secretory luminal cells. This model differs from the human in which two progenitors, one columnar and the other basal gives rise to secretory cells in the endocervix and stratified squamous epithelia in the ectocervix and vagina respectively. In the current study, we identify a population of Krt8+, Tp63- epithelial cells that are retained in the cervicovaginal epithelium during the postnatal developmental period and into adulthood. Single cell datasets from the cervices of adult mice, identify Olfactomedin 4 (Olfm4), as a unique marker of the Krt8+Trp63- population. Adult lineage tracing and reassessment of gene markers during postnatal development support a revised model in which two progenitors are delineated in the mouse cervix and vagina by PND15. Olfactomedin 4+ progenitors give rise to specialized secretory goblet cells, while Trp63+ basal progenitors give rise to stratified squamous luminal cells in the cervix and vagina of nonpregnant and pregnant mice. Consistent with the expansion of goblet cells in pregnancy, the Olfm4+ progenitor is highly proliferative in early pregnancy and progesterone regulates increased goblet cell differentiation. These findings reveal a previously unrecognized species similarity between mice and humans in which goblet cell and squamous keratinized cell subtypes are derived from two progenitor populations respectively. HIGHLIGHTSO_LITwo epithelial progenitors (Trp63 and Olfm4) populations are delineated in the cervix and vagina within the first two weeks of postnatal life. C_LIO_LIThe Trp63+ progenitor gives rise to keratinized epithelial cells, whereas the Olfm4+ progenitor cells give rise to secretory goblet cells. C_LIO_LIlfm4 is not required for maintenance of the luminal progenitor or differentiation of goblet cells in the cervix and vagina during adulthood and pregnancy. C_LIO_LIIn adults, progesterone promotes differentiation of Olfm4+ progenitors into goblet cells. C_LI

developmental biology↗

bioRxiv2026

SpatialBench: Comparative cross-platform benchmarking of high-resolution spatial transcriptomics using matched mouse lymphoid tissue

Spatial transcriptomics (ST) has rapidly expanded with the introduction of multiple high-resolution platforms, yet cross-platform benchmarking remains limited and largely focused on technical performance. Here we present SpatialBench, a matched multi-platform resource comprising Visium HD, Xenium and MERSCOPE data together with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 knockout mouse spleen model. In this system, loss of T-bet in B cells disrupts germinal center (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. We leveraged this system to systematically evaluate ST platform performance using technical and biological readouts. Across platforms, immune organization and Tbx21-associated programs were consistently recovered, indicating robustness of major biological signals. Platforms instead differed in the level of biological resolution accessible. Visium HD enabled transcriptome-scale GC characterization and, together with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity. SpatialBench provides a biologically defined reference dataset for evaluation of ST technologies, method development, computational benchmarking, and studies of GC spatial organization in lymphoid tissue.

bioinformatics↗

bioRxiv2026

Conformational Preference Classification of Integrin-Binding Ligands Using Free Energy Perturbation

Integrins are crucial cell adhesion receptors and attractive therapeutic targets, but developing safe small-molecule inhibitors has been challenging, at least in part due to inadvertent partial agonism caused by stabilization of the integrins open, high-affinity state. To address this challenge, we present a computational approach using Absolute Binding Free Energy Perturbation (AB-FEP) calculations to predict whether a ligand will stabilize the open or closed integrin states, leveraging the difference between the ligands binding free energy to the respective end states. Despite challenges posed by Ca and Mg ions, metal-coordinating residues in the binding pocket, and the subtlety of structural differences between states, AB-FEP achieved excellent classification performance on a set of known opening and closing ligands, significantly outperforming docking scores and MM-GBSA results. We also showed a good correlation between AB-FEP binding free energy differences and experimental values. Furthermore, AB-FEP provided insights into intermediate integrin states and analysis of simulation trajectories confirmed the formation of a water-mediated hydrogen bond network with an ion in the binding pocket to be characteristic for closing ligands. This work demonstrates AB-FEP as a robust method for classifying integrin ligands by the conformation they stabilize and for understanding their functional mechanisms, offering valuable guidance for designing safe and conformationally selective integrin therapeutics. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/721214v2_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1a0b8eforg.highwire.dtl.DTLVardef@cd6b56org.highwire.dtl.DTLVardef@420cc0org.highwire.dtl.DTLVardef@533963_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Integration of spatial single-cell proteomics and spatial metabolomics reveals tumor microenvironment predictive of immunotherapy response in mucosal melanoma

Mucosal melanoma (MuM) is a rare but aggressive malignancy with limited benefit from immune checkpoint inhibition and few predictive biomarkers. We integrated single-cell spatial proteomics (COMET) and spatial metabolomics (MALDI-IMS) to profile 97 tissue cores from 26 patients treated with PD-1/PD-L1 and/or CTLA-4 inhibitors. We profiled 695,444 cells and resolved 25 cell states across eight major cell types. Cellular neighborhood (CN) analysis revealed distinct tumor- and stromal-associated spatial architectures. Responders were enriched for tumor-associated CNs (invasive tumor and tumor boundary) with close spatial proximity among Ki67 tumor cells, CD163 macrophages, and CD11c dendritic cells (DCs), and increased proliferating/cytotoxic CD8+ T-cell subsets. Non-responders showed stromal CN dominance with reduced immune infiltration. Spatial metabolomics identified lower abundance of indole-derived metabolites and reduced indole/tryptophan pathway activity in responders within tumor and TME regions that tracked with DC/macrophage-enriched spatial contexts. This study advances MuM spatial biology and provides a framework for biomarker-driven immunotherapy strategies. Statement of significanceMucosal melanoma (MuM) responds poorly to immune checkpoint blockade, and predictive biomarkers are limited. Integrated spatial proteomics and metabolomics reveal response-associated tumor-immune neighborhood architecture, stromal contexts linked to immune exclusion, and altered indole/tryptophan metabolism in the microenvironment. These spatial features nominate biomarkers and therapeutic hypotheses to improve immunotherapy for MuM.

cancer biology↗

bioRxiv2026

Endocytic accessory proteins assemble clathrin while simultaneously destabilizing protein condensates

During endocytosis a dynamic protein network is responsible for assembly of the clathrin coat. Early in the process the Eps15 protein is thought to undergo liquid-liquid phase-separation to form biomolecular condensates. These condensates facilitate clathrin assembly, producing clathrin-coated vesicles that are ultimately excluded from the condensate as the vesicles depart from the plasma membrane. An array of distinct clathrin accessory proteins drive this process, yet their interactions with protein condensates have not been explored. Here we show that clathrin accessory proteins promote the assembly of the clathrin lattice by simultaneously destabilizing protein condensates. By adding diverse accessory proteins to Eps15 condensates, we observed that accessory proteins which cross-linked Eps15 proteins stabilized condensates, while accessory proteins that compete with Eps15-Eps15 interactions destabilized condensates. Interestingly, accessory proteins that destabilized condensates also promoted the assembly of clathrin and its exclusion from condensates. In contrast, accessory proteins that stabilized condensates opposed exclusion of clathrin. Finally, we demonstrated that decreasing condensate stability enhanced clathrin assembly and exclusion, even when no additional clathrin assembly motifs were introduced. Taken together, these results help to explain how condensates can catalyze the assembly of coated vesicles by providing both a substrate for their initiation and a driving force for their exclusion and ultimate departure. Statement of SignificanceThis work is significant because it reveals how biomolecular condensates could actively drive, rather than merely host, clathrin-mediated endocytosis. By showing that clathrin accessory proteins can tune condensate stability to simultaneously promote clathrin lattice assembly and exclusion, this study uncovers a physical mechanism that could link phase separation to membrane trafficking. The finding that condensate destabilization alone enhances clathrin exclusion reframes condensates as dynamic regulators that could provide both an initiation platform and a force for vesicle maturation and release. More broadly, this work advances our understanding of how cells coordinate assembly and disassembly of complex macromolecular structures through regulated changes in condensate material properties.

biophysics↗

bioRxiv2026

CellChem: Cellular transcriptional responses reshape molecular representation space for efficient and multi-scale drug discovery

Despite decades of progress in computational drug discovery, deep learning-based molecular representation models remain largely structure-centric, assuming that chemical similarity approximates functional similarity. However, drug effects in cells are shaped not only by chemical similarity but also by molecular interactions in the cellular context. To capture this complexity, we introduce CellChem, a cellular-chemical representation-learning framework that learns cell-guided molecular representations of small-molecule actions within cells. By incorporating large-scale cellular transcriptional profiles during pretraining, CellChem reshapes molecular representation space from structure-centric to a balanced integration of structure and function. The learned CellChem molecular representations exhibit biologically meaningful geometric organization, such that distances between molecules encode not only structural similarity but also similarity in the cellular responses they elicit, independent of downstream tasks. Using downstream derivative models such as cell-guided compound-protein interaction prediction and drug-induced transcriptional response profile generation, CellChem supports highly efficient, multi-scale drug discovery, achieving significantly better performance than traditional models.

molecular biology↗

bioRxiv2026

PanVariants: Best Practice for Pangenome-based Variant Calling Pipeline and Framework

BackgroundAlthough pangenome references offer richer population diversity compared to linear references, current mainstream pangenome-based variant callers are limited to detecting only known variants stored in the graph. To address this limitation, we developed PanVariants, a novel pipeline designed to improve the detection of both known and novel variants accurately. We systematically evaluated its performance against the traditional linear alignment solution (BWA+GATK/Manta) and the existing pangenome-aware solution (DRAGEN/PanGenie) in three contexts: small variants (SNVs/indels) and structural variants (SVs) accuracy in Genome in a Bottle samples, clinical detection on positive samples, and application in cohort-based joint calling. ResultsBy integrating k-mer-based and mapping-based methods, PanVariants significantly reduced variant errors (FPs + FNs), achieving a 73% reduction compared to BWA+GATK and a 45% reduction compared to DRAGEN for SNVs. Retraining the DeepVariant model with high-quality DNBSEQ data further decreased errors by 15%. For SVs detection, PanVariants attained an F1-score of 89.39%, markedly outperforming DRAGEN (68.18%) and BWA+Manta (58.33%), approaching long-read sequencing performance (95.22%). In validation using clinical positive samples, PanVariants successfully detected all expected pathogenic variants while PanGenie failed. In the cohort joint-calling analysis, PanVariants detected more variants, made fewer Mendelian inheritance errors, and gave better per-sample accuracy than GATK. ConclusionsPanVariants establishes a robust framework and best-practice pipeline for pangenome-based variant detection, achieving both sensitive novel variant discovery and high accuracy for SNVs, indels and SVs. Our systematic evaluation of optional processing steps and input variables offers practical guidance for users. Validated across diagnostic and population-based applications, our findings strongly support the transition from linear to pangenome references in future genomics.

bioinformatics↗

bioRxiv2026

Identification of AAV Capsids with Enhanced Intravitreal Transduction and Favorable Safety Profile in Non-Human Primates

We report the discovery of novel adeno-associated virus (AAV) capsid variants engineered for superior intravitreal (IVT) gene delivery to the primate retina. Utilizing the REACH platform, we constructed a diverse AAV variant library and employed a multi-stage screening strategy involving in vitro selection on human retinal pigment cells followed by direct in vivo screening in non-human primates (NHPs). Following IVT administration in NHPS of a barcoded variant pool, next-generation sequencing analysis of retinal tissues identified lead candidates (e.g., E52, E54, and E57) that achieved transduction levels in the neural retina and RPE 5-10 fold higher than the benchmark R100. Concurrently, these high-potency variants exhibited an exceptional ocular confinement profile, with minimal to undetectable vector genome distribution in systemic organs. This combination of markedly enhanced retinal transduction and stringent local tropism establishes these engineered capsids as promising next-generation vectors for the treatment of inherited and acquired retinal diseases via a minimally invasive IVT route.

bioengineering↗

bioRxiv2026

Inhibition of CKAMP44 attenuated seizure activity via protein phosphatase 3 regulatory subunit B-mediated GluA1 phosphorylation and synaptic transmission

Temporal lobe epilepsy (TLE) is a complex neurological disorder characterized by spontaneous recurrent seizures and its underlying mechanism remains elusive. This study aimed to investigate the role of cystine-knot AMPAR modulating protein 44 (CKAMP44) in the pathological process of TLE and its potential as a therapeutic target using kainic acid (KA)-induced epilepsy mouse model of TLE. Our results showed that CKAMP44 protein and mRNA expression was significantly increased and primarily localized to neurons during the chronic phase of TLE. Nkx2-1 regulated the transcription of CKAMP44 in the hippocampus brain tissues of KA-induced TLE mice. Inhibition of CKAMP44 suppressed seizure susceptibility and severity in the KA-induced epilepsy mice via behavioral and local field potential monitoring. Furthermore, inhibition of CKAMP44 decreased frequency and amplitudes of spontaneous excitatory postsynaptic currents indicating that the excitatory synaptic transmission was reduced in an in vitro epilepsy model. Mechanistically, inhibition of CKAMP44 specifically upregulated the membrane surface expression of GluA1 and the phosphorylation level of GluA1-ser831 by downregulating protein phosphatase 3 regulatory subunit B(PPP3r2) expression. Overexpression of PPP3r2 downregulated the phosphorylation level and surface expression of GluA1, which ultimately exacerbated the seizure activity suppressed by CKAMP44 knockdown. Collectively, our results indicate that CKAMP44 may be a potential therapeutic target for the treatment of TLE.

pathology↗

bioRxiv2026

A Rapid 10-Minute Silver Nitrate Staining Method for Visualizing the Osteocyte Lacuno-Canalicular System

AbstractsThe Ploton silver method employs a 50% silver nitrate solution (w/v; 2.943 mol/L) for staining and quantitative analysis of the osteocyte lacuno-canalicular system (LCS). We previously demonstrated that lower silver nitrate concentrations (0.5-1 mol/L) stain the LCS more effectively, revealing a greater number of LCS than the Ploton silver method. However, the staining duration of our initial modified method (60 minutes) remained comparable to that of the Ploton silver method (55 minutes), limiting its broader adoption. Here, we developed a rapid silver nitrate staining method by systematically evaluating the effects of temperature on staining efficacy. We found that incubation at 50-70{degrees}C for 10 minutes with a 1 mol/L silver nitrate solution produced optimal results. This rapid high-temperature method achieved excellent LCS visualization in bone samples from multiple animal species and in mouse pathological models. Moreover, high-temperature staining mitigated the LCS damage and insufficient staining associated with the 50% silver nitrate solution used in the Ploton silver method. This rapid 10-minute silver staining technique, designated the Wu-Wang silver method, provides a more accurate and efficient approach for LCS staining and quantitative analysis. Its adoption will facilitate systematic characterization of LCS morphological variations across vertebrate species, thereby advancing our understanding of osteocyte morphogenesis and the pathogenic mechanisms underlying bone and joint diseases. Graphical abstract (Created in BioRender, https://BioRender.com) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/719546v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@996f66org.highwire.dtl.DTLVardef@160b1a5org.highwire.dtl.DTLVardef@12eee4corg.highwire.dtl.DTLVardef@1edce8_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIElevating the staining temperature to 50-70{degrees}C enabled rapid and efficient silver nitrate staining of the osteocyte lacuna-canalicular system (LCS) within 5-10 minutes using 1 mol/L silver nitrate. C_LIO_LIThe high-temperature Wu-Wang silver method outperformed the conventional Ploton silver method, providing superior osteocyte LCS visualization while eliminating issues of osteocyte LCS damage and insufficient staining observed with the Ploton silver method. C_LI

cell biology↗

bioRxiv2026

Dietary Sodium Restriction Reprograms Gut Microbial Fermentation and Reduces Host Energy Harvest

Diet is a major determinant of gut microbiome structure and function, yet the role of dietary electrolytes--particularly sodium--remains poorly defined. Here, we identify dietary sodium availability as a key regulator of gut microbial fermentation and host energy harvest. Using a controlled sodium-sufficient versus sodium-deprived dietary intervention in rats, we integrated shotgun metagenomic sequencing, functional pathway analysis, targeted short-chain fatty acid (SCFA) quantification, and host physiological phenotyping. Sodium deprivation induced a coordinated restructuring of the gut microbiome, characterized by depletion of classical saccharolytic Firmicutes, including multiple Lactobacillus species, and enrichment of stress-tolerant, metabolically flexible taxa. Functional profiling revealed a shift away from growth-associated metabolic programs toward stress-adaptive and nutrient-scavenging pathways. Consistent with these changes, fecal concentrations of key SCFAs--including acetate, butyrate, hexanoate, and valerate--were significantly reduced, indicating impaired microbial fermentative capacity. These microbiome-level alterations translated into measurable host phenotypes, including reduced cecal mass and attenuated weight gain, consistent with decreased microbial energy harvest. Together, these findings establish a functional link between luminal sodium availability, microbial metabolic efficiency, and host energy balance, extending the framework of diet-microbiome interactions beyond macronutrients to include dietary electrolytes. This work identifies sodium as a previously underappreciated ecological constraint shaping gut microbial metabolism and suggests that modulation of dietary sodium intake may influence host metabolic outcomes through microbiome-mediated mechanisms.

microbiology↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2026

TIM3+ Tumor Associated M2 Macrophages Impair Antitumor T Cell Immunity and Promote Gastric Cancer Progression and Peritoneal Metastasis

Peritoneal metastases (PM) are the leading cause of cancer-related death in gastric cancer (GC) patients with survival typically < 9 months. Here, we demonstrate that TIM3 and its ligands are increased along the GC continuum and associated with poor survival. Integrated omics analyses and functional studies revealed highly enriched TIM3 in CD163+ tumor associated M2 immunosuppressive macrophages significantly promote tumor cell invasion and tumor growth in vivo, while TIM3 depletion in macrophages reduced tumor cell malignant attributes and increased T cell immunity from PBMCs or CD45+ immune cells of malignant ascites in co-culture system. By cytokine and kinase arrays, we discovered that depletion of TIM3 in macrophages reduced the production of notable secretome of cytokines/chemokines from M2 macrophages; and the protumor function of TIM3+ macrophages rely on the p90RSK1/2/CCL20 axis. Finally, we reveal that TIM3 blockage or genetic KO had superior antitumor activity in combination with anti-PD1 immunotherapy and mitomycin C (MMC) chemotherapy. Together, this study uncovers an important role for TIM3 in tumor associated M2 macrophages and underscores the potential of TIM3 blockage in GC patients with PM. Statement of significanceIn this study, we show TIM3 increases along GC continuum, and highly enriched on tumor associated M2 macrophages that fuel tumor growth; and suppress T cell function via p90RSK1/2/CCL20 axis. TIM3 depletion restores T-cell immunity and curbs tumor growth. TIM3 blockade combined with anti-PD1 and mitomycin C provide a novel therapeutic strategy for GC patients with PM.

immunology↗

bioRxiv2026

Discovering Novel Circuit Mechanisms in Higher Cognition through Factor-Centric Recurrent Neural Network Modeling

Recurrent neural networks (RNNs) have transformed how systems neuroscientists generate hypotheses about circuit mechanisms in higher cognition. Yet their promise has been constrained by a fundamental limitation: conventional RNNs are neuron-centric and therefore often difficult to interpret mechanistically. Here we introduce Restricted-RNN, a factor-centric RNN modeling framework developed to uncover interpretable circuit mechanisms. By formalizing factor communication through subpopulations, the dual of neuron communication through subspaces, Restricted-RNN departs fundamentally from standard neuron-centric RNN models and provides a distinct framework for describing circuit mechanisms. Using this approach, we identify novel circuit mechanisms underlying sequence working memory control and the counterintuitive firing-rate reversal observed in perceptual decision-making, with key predictions supported by neurophysiological recordings from monkey frontal and parietal cortex. More importantly, factor-centric RNN modeling reveals a unified low-dimensional neural control state space that links seemingly disparate phenomena across tasks, providing a geometric framework for understanding the pervasive role of control in higher cognition.

neuroscience↗