Biology subjects

Sun, S.

Publications and source records attributed to Sun, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Smartphone Placement Recognition during Walking: Performance Determinants and Real-World Generalizability

The opportunity to collect movement data from smartphones for prolonged periods has opened new perspectives in the field of clinical movement analysis. However, when monitoring peoples mobility in free-living conditions, smartphone placement can influence the validity of the extracted digital mobility outcome. This study aimed to develop and validate an automatic smartphone placement recognition classifier and to investigate potential critical factors that can influence performance. The classifier was trained on data from 15 healthy participants using inertial signals collected from smartphones placed at six body placements during free-living walking and externally validated on over 3,000 individuals from external datasets, including blind participants and patients with cardiovascular or Parkinsons disease. A decision-tree ensemble model was developed using feature subsets of increasing dimensionality, with the optimal subset comprising 50 features. Classification accuracy increased consistently when front and back pocket placements were aggregated (81.1%) and further improved when coat pocket was also included in the pocket class (88.5%), underscoring the challenge of distinguishing between fine-grained pocket placements. The best-recognized placements across the external datasets were lower back (precision: 100%, recall: 72.5%), hand (precision: 94.2%, recall: 94.5%), and the aggregated pocket class (precision: 86.7%, recall: 90.2%). Recognition accuracy changed across cohorts (0.73 - 0.85), activities (0.63 - 0.94) and speed (0.79 - 0.87), however it stayed consistent across various technological and environmental factors. Overall, this study demonstrates the feasibility of robust placement recognition in walking and underscores the importance of accounting for key influencing factors when designing frameworks intended for deployment in heterogeneous real-world or clinical contexts. HighlightsO_LIMachine learning accurately identifies smartphone placement during real-world gait C_LIO_LISix on-body placements recognized, including pockets, hand, bag, and lower-back C_LIO_LIFree-living data used for training, ensuring robust performance across conditions C_LIO_LIFeature selection and hyperparameter tuning optimize classification accuracy C_LIO_LIExternal validation confirms generalizability across >3,000 healthy and diseased adults C_LI

bioengineering↗

bioRxiv2026

Systematic Profiling of Essential Fungal Transcription Factors Uncovers Ezt1 as a Central Pathobiological and Morphogenic Regulator in Cryptococcus neoformans

Cryptococcus neoformans is a global fungal pathogen that causes fatal cryptococcosis, and the limitations of current antifungals underscore the urgent need for new therapeutics. Here we systematically investigate essential transcriptional regulators in C. neoformans as potential antifungal targets, developing experimental pipelines that assess growth requirement, essentiality and function through conditional gene expression, constitutive overexpression, and meiotic spore analysis. We identify one quasi-essential (growth-required but non-essential) transcription factor, Fhl1, and 13 essential transcriptional regulators, three of which are transcription factors (Ezt1, Ezt2 and Cbf1) highly divergent from counterparts in other eukaryotes. Notably, Ezt1 modulates the expression of more than 1,200 genes, controlling growth, antifungal drug and stress responses, sexual development and virulence. Our findings define the essential transcriptional regulator landscape of C. neoformans and provide a framework for prioritising divergent essential regulators, particularly Ezt1, for antifungal target discovery.

microbiology↗

bioRxiv2026

XIST Is a Key Modulator Associated with the Adhesome Network

A long non-coding RNA (lncRNA) known as the X-inactivation specific transcript (XIST) plays a central role in X chromosome inactivation - a transcriptional process that silences one of the two X chromosomes in females to ensure dosage compensation between males and females. Much research has been conducted on how XIST regulates X chromosome transcription critical to embryonic development, but recent studies suggest a non-canonical role for XIST in regulating cancer stem cells and cellular plasticity. As cell adhesion and adhesome genes are integral to the regulation of cancer stemness, we explored the previously unrecognized link between XIST and the adhesome network. By performing gene expression and gene ontology analysis on XIST-knockdown ovarian cancer cells, our study showed that XIST loss altered adhesome gene expression and downstream adhesion pathways. Using Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets, we identified distinct correlations between XIST lncRNA and adhesome genes across normal and cancer tissue samples, which are associated with cell stemness. Furthermore, network analysis suggests that XIST may interact with specific adhesome genes within the cell nucleus. This interaction may have significant functional implications, as demonstrated by the hazard ratio analysis of XIST and adhesome gene expression in relation to clinical outcomes. Overall, our results show that among well-annotated functional lncRNAs, XIST appears to be a modulator strongly associated with the adhesome network and cell stemness. Our findings thus support a novel link between lncRNA-mediated epigenetic regulation of cell adhesion genes, highlighting XIST as a key regulator contributing to the adhesome network. Significance StatementThis study identified that XIST, a long non-coding RNA essential for X-chromosome dosage compensation and embryonic development, plays a significant role in modulating the adhesome network. We found that XIST knockdown affected adhesion pathways in ovarian cancer cells, whereas XIST expression is strongly correlated with adhesome gene expression across all tissues. We observed that the interaction between XIST and adhesome genes changes significantly between tumors and normal tissues, and this altered interaction is associated with certain cancer outcomes. These findings reveal a possible link between lncRNA-mediated regulation and adhesome control that is associated with cell stemness signatures and the emergence of cancerous tissues.

cell biology↗

bioRxiv2026

Cell-nanoplastics association impacts cell proliferationand motility

Detection of micro- and nanoplastics (MNPs) in human tissues has raised growing concern about their biological effects on tissue and cell function. While previous studies have examined MNP-cell interaction, most focused on limited cell and plastic types. Here, we present a comprehensive, quantitative investigation into how different types of nanoplastics (NPs) associate with and affect diverse cell types under physiologically relevant conditions. Using microfluidic-calibrated fluorescence microscopy, we quantify NP accumulation in cells in vitro and match cellular NP concentrations to levels reported in human tissues. While cell-associated NPs could be gradually released in vitro, they persist in vivo for over one month without detectable reduction in a mouse model. We discover that NP exposure at these levels broadly impairs cell proliferation across epithelial, endothelial, fibroblast, and immune cells, with cell type-dependent sensitivity. NP exposure also reduces motility in T cells and fibroblasts, with more complex effects observed in macrophages. Mechanistically, NP-cell association and trans-epithelial transport involved not only classical endocytic regulators but also pathways related to ion and water transport. Notably, NP association and release were highly sensitive to the extracellular fluid environment within the physiological range. By testing inhibitors of these pathways, we identified molecules that reduce NP-cell association and promote release. We further compared common NPs found in human samples and widely used in research: polystyrene (PS), polyethylene (PE), and polypropylene (PP). Although these NPs similarly impaired proliferation and motility, they showed markedly different cellular association and release dynamics. These findings reveal the impact of NPs on tissue cell functions and uncover novel regulatory pathways, establishing a quantitative framework for studying NP-cell interactions in biologically relevant conditions.

cell biology↗

bioRxiv2026

Survey of Climate-structured Mycobiomes in Staple Maize: Implications for Endemic Keshan and Kashin-Beck Diseases

Keshan disease (KD) and Kashin-Beck disease (KBD) are geographically restricted disorders in rural China with overlapping environmental and dietary risk factors. Selenium deficiency alone cannot explain their regional heterogeneity. Maize, a dietary staple in endemic areas, represents a key exposure pathway for climate-sensitive foodborne fungi and their metabolites. We profiled maize-associated fungal communities from seven villages across KD-, KBD-, KD-KBD co-endemic, and non-endemic regions using ITS sequencing and integrative bioinformatics. Fungal diversity, composition, trophic structure, and predicted biosynthetic gene cluster potential differed markedly among regions. KD-endemic areas were enriched in saprotrophic taxa such as Penicillium and Aspergillus, KBD-endemic regions favored cold- and humidity-adapted fungi, and KD-KBD co-endemic areas exhibited the highest predicted mycotoxin potential. Fungal patterns were strongly associated with regional temperature and humidity. These findings support a climate-sensitive, foodborne exposome framework, suggesting that variation in maize-associated fungi may contribute to endemic disease risk and highlighting the need for fungal surveillance in public health strategies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/716289v1_ufig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@2cf23borg.highwire.dtl.DTLVardef@d31e5aorg.highwire.dtl.DTLVardef@6dbcadorg.highwire.dtl.DTLVardef@7e0734_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2026

Mutant p53 Directs PARP to Regulate Replication Stress and Drive Breast Cancer Metastasis

TP53 mutations occur in 80-90% of triple-negative breast cancers (TNBCs) and drive genomic instability and metastatic progression. Poly (ADP-ribose) polymerase (PARP) is critical for DNA repair and replication fork stability. How oncogenic signaling influences PARP function to sustain proliferation during replication stress remains unclear. Mutant p53 (mtp53) R273H associates tightly with chromatin, forms complexes with PARP, and enhances PARP recruitment to replication forks [1-3]. The C-terminal region of mtp53 mediates mtp53-PARP and mtp53-Poly (ADP-ribose) (PAR) interactions that facilitate S phase progression [4, 5]. The PARP inhibitor talazoparib (TAL) combined with the alkylating agent temozolomide (TMZ) produces synergistic cytotoxicity selectively in mtp53, but not wild-type p53 (wtp53), breast cancer cells and organoids. Herein we evaluated the mechanism of mtp53-associated cell death and tested if this could translate to a preclinical xenograft model. We found that TMZ+TAL treatment induced elevated cleaved PARP and {gamma}H2AX and reduced the metastasis-promoting oncoprotein MDMX. In orthotopic xenografts expressing mtp53 R273H, but not wtp53, combination therapy significantly decreased circulating tumor cells (CTCs) and lung metastases. Transcriptomic profiling of tumors from combination treated animals demonstrated downregulation of MDMX, VEGF, and NF-{kappa}B, consistent with the observed suppression of CTCs and lung metastasis, and increased {gamma}H2AX, indicative of replication stress in mtp53 xenografts. Inhibition of metastasis was also observed in mtp53 R273H WHIM25 and p53-undetectable WHIM6 TNBC patient-derived xenografts (PDX). The mtp53 C-terminal domain (347-393) demonstrated a critical tumor promoting function, as CRISPR-mediated deletion impaired replication fork progression, tumor growth, and metastatic dissemination. DNA fiber combing showed that expression of full-length mtp53 R273H, but not C-terminal deleted {Delta}347-393, supported sustained single-stranded DNA gaps (ssGAPs) following Poly (ADP-ribose) glycohydrolase (PARG) inhibition. These findings support that mtp53 uses C-terminal amino acids to exploit PARP to enable replication stress adaptation and that mtp53 is a predictive biomarker for combined PARP inhibitor and DNA damaging therapies targeting TNBC. Significance statementTP53 mutations are the most common genetic alterations in TNBC and a major driver of replication stress and metastasis. This study shows that missense mutant p53 uses C-terminal amino acids to reprogram PARP activity to maintain tumor cell survival under replication stress. We demonstrate that p53 status governs the response to combined PARP inhibitor (PARPi) and DNA-damaging chemotherapy, establishing an additional molecular basis beyond BRCA1 mutations for treating TNBC with PARPi therapy. These findings reveal a previously unrecognized mechanism by which the mutant p53-PARP axis enables replication stress tolerance and drives cancer metastasis. We show mutation of p53 in TNBC provides an additional biomarker-guided framework to improve PARPi therapeutic outcomes.

cancer biology↗

bioRxiv2026

A fungal effector targets the chloroplast to support biotrophy by balancing disease and plant health

Fungal pathogens are responsible for substantial crop losses worldwide. There is a pressing need to develop crops with improved disease resistance, especially given that climate change and human activities are exacerbating crop diseases. Our understanding of the molecular mechanisms by which fungi cause disease is incomplete. To address this limitation, we employed proteomics to identify candidate effector proteins from the pathogenic fungus Ustilago maydis that co-purified with the chloroplasts of maize host plants during infection. We specifically characterized the role of one putative chloroplast-associated effector, UmPce3, using heterologous expression in the non-host plant Arabidopsis thaliana. We discovered that UmPce3 interacts with the chloroplast DEAD-box RNA helicase, AtRH3. Phenotypes associated with the expression of UmPce3 in Arabidopsis mirrored those of plants with impaired AtRH3 function and included interference with chloroplast assembly, an impact on photosynthesis, and altered resistance to biotic and abiotic stresses. Support for RH3 as a bona fide effector target was obtained by identifying parallel phenotypic influences of UmPce3 in maize and by demonstrating an interaction between UmPce3 and maize ZmRH3b, an ortholog of AtRh3. Notably, UmPce3 contributes to biotrophy by promoting the virulence of U. maydis on maize seedlings and dampening virulence in plants challenged with salinity as an abiotic stress. Overall, this work highlights the chloroplast as a target of fungal pathogenesis and identifies RH3 as a potential hub for pathogen manipulation of organelle function to balance fungal proliferation and host health in support of biotrophy. Short summaryThe chloroplast plays a key role in plant immunity, in addition to its central contributions to photosynthesis, metabolism, and tolerance of abiotic stresses. The effector UmPce3 of the maize pathogen Ustilago maydis targets the DEAD-box RNA helicase RH3 in host plants to manipulate chloroplast function and enhance fungal pathogenesis. Unexpectedly, UmPce3 also influences host tolerance to salt stress thereby balancing the plant response to biotic and abiotic stressors in support of biotrophic development.

plant biology↗

bioRxiv2026

The Risk of Gulf Birds Functional Diversity Loss with Climate Change Uncovered Using Deep Learning Population Models

Climate change and sea-level rise (SLR) pose increasing threats to coastal ecosystems and biodiversity in the Gulf of America. Most efforts to anticipate these threats focus on species counts or range shifts, while changes in species functional diversity remain uncovered. We estimated the impacts of climate change and sea-level rise on hundreds of bird species populations and corresponding shifts in functional diversity. We used the generative deep learning method, Variational Gaussian Mixture Autoencoder (GMVAE), and Trait Probability Density analysis to study such impacts. We found that a generative GMVAE model uncovered species unobserved ranges, and that climate change reduced coastal ecosystem resilience and caused biodiversity loss across multiple dimensions, including functional richness, redundancy, evenness, and divergence. Surprisingly, the most impacted areas are not the exposed shoreline but the landward coastal transition zones. Specifically, shoreline functional diversity turned out to increase with climate change and sea level rise, whereas uplands showed declining functional diversity and increasing redundancy, indicating contraction of functional trait space. Furthermore, avian biodiversity expanded in coastal protected areas, serving as refugia embedded in a surrounding landscape where unique combinations of species traits are lost.

bioinformatics↗

bioRxiv2026

SCALE: Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

Virtual cell models aim to enable in silico experimentation by predicting how cells respond to genetic, chemical, or cytokine perturbations from single-cell measurements. In practice, however, large-scale perturbation prediction remains constrained by three coupled bottlenecks: inefficient training and inference pipelines, unstable modeling in high-dimensional sparse expression space, and evaluation protocols that overemphasize reconstruction-like accuracy while underestimating biological fidelity. In this work we present a specialized large-scale foundation model SCALE for virtual cell perturbation prediction that addresses the above limitations jointly. First, we build a BioNeMo-based training and inference framework that substantially improves data throughput, distributed scalability, and deployment efficiency, yielding 12.51* speedup on pretrain and 1.29* on inference over the prior SOTA pipeline under matched system settings. Second, we formulate perturbation prediction as conditional transport and implement it with a set-aware flow architecture that couples LLaMA-based cellular encoding with endpoint-oriented supervision. This design yields more stable training and stronger recovery of perturbation effects. Third, we evaluate the model on Tahoe-100M using a rigorous cell-level protocol centered on biologically meaningful metrics rather than reconstruction alone. On this benchmark, our model improves PDCorr by 12.02% and DE Overlap by 10.66% over STATE. Together, these results suggest that advancing virtual cells requires not only better generative objectives, but also the co-design of scalable infrastructure, stable transport modeling, and biologically faithful evaluation.

cell biology↗

bioRxiv2026

Gateway analysis reveals transient molecular programs at cell-fate transitions

Single-cell atlases have transformed our view of cell identity, but they still struggle to resolve the transient states that accompany cell-fate change. These rare interface cells are outnumbered by the stable populations on either side. As a result, the molecular programs that accompany lineage transitions are hard to detect. We developed gateway analysis, a framework that identifies cells at fate boundaries and pinpoints bell and valley genes that peak or dip there. It defines cell neighborhoods from binary mutual information (BMI) in gene on/off patterns and preserves that structure in a regularized latent model. Across four single-cell atlases spanning reprogramming, gastrulation, pancreatic endocrinogenesis, and kidney injury (3,696-126,578 cells), gateway analysis recovered rare boundary populations and the transient gene programs that distinguish them from their flanking states. These signals were missed by standard comparisons of stable endpoint states. They included epithelial remodeling at the late MET-to-iPSC interface, a gate-versus-basin partition of gastrulation regulators, a transient Cck-enriched peak at endocrine hub entry together with a candidate BH4-associated signal at a shared endocrine hilltop, and a proteostasis program at the kidney injury boundary. Orthogonal support from optimal-transport fate probabilities, known markers, and published perturbation phenotypes indicate that gateway cells mark bona fide biological transition intervals. Gateway analysis therefore provides a practical framework for detecting rare transition-state cells and the bell/valley genes that define them in single-cell atlases.

bioinformatics↗

bioRxiv2026

HMA proteins produce 2',3'-cNMP signaling molecules and activate CNL-mediated immunity in rice

Plants deploy a sensor repertoire, usually NLRs, to perceive pathogen effectors and activate executor NLR-triggered immunity. Here we reveal that rice HMA proteins function as sensors detecting the Magnaporthe oryzae MAX effector AvrPigm to trigger broad-spectrum blast resistance mediated by the CNL PigmR. AvrPigm is conserved with multiple copies in blast genomes and targets HMA proteins, facilitating HMA translocation into the cytoplasm. Cryo-EM structure of the HPP04HMA reveals a filament-like oligomer with ssDNA/RNA bound inside the filament, which display cyclic nucleotide synthase activity to generate 2',3'-cNMP in a CNL-dependent manner. We further discovered that the LRR domains of the executor CNLs perceive 2',3'-cNMP to mount immunity. Our study thus establishes an unrecognized immunity mode with a distinct repertoire of sensor receptors that produce signaling molecules that are perceived by the LRR domains of executor NLRs to mediate immunity, shedding new light on the sensor-executor conception and immune activation in plants. HighlightsO_LIHMA proteins and CNL receptors form a new sensor-executor mode in plant immunity C_LIO_LICryo-EM reveals the filament-like structure of HMA-ssRNA/ssDNA C_LIO_LIHMA proteins are cyclic nucleotide synthetases to generate 2',3'-cNMP C_LIO_LILRR domains of CNLs perceive 2',3'-cNMP to mediate immunity C_LI

plant biology↗

bioRxiv2026

In vivo-compatible spatial multi-omics via hydrogen peroxide-independent APEX2 labeling

Proximity labeling (PL) technologies like APEX2 have transformed spatial multi-omics in live cells, but their long-standing dependence on hydrogen peroxide (H2O2) disrupts redox signaling and prevents use in live animals. Here we introduce H2O2-independent APEX2 (Hi-APEX), which uses a clickable tetrazine-phenol probe, requiring no enzyme engineering. We show that APEX2 directly catalyzes TP radical formation without H2O2 via a mechanism requiring the probes tetrazine group and a key histidine residue. We benchmarked Hi-APEX-based spatial multi-omics by mapping the mitochondrial matrix and dynamic secretomes. Hi-APEX significantly outperforms traditional APEX in capturing redox-sensitive processes such as stress response and ferroptosis, enabling discovering authentic stress granule components and protein interaction networks for mitochondria-localized GPx4. One mGPx4 interactor TRMT61B--known to regulate mitochondrial m{superscript 1}A modifications--promotes ferroptosis. Crucially, Hi-APEX achieves full in vivo compatibility, enabling direct PL in tumor xenografts and hippocampal neurons, thereby expanding PL-based spatial multi-omics from cellular systems to living organisms.

biochemistry↗

bioRxiv2026

Proteomic analysis reveals shared biological pathways linking acrolein to biomolecular changes in the acute phase of rat spinal cord injury

Spinal cord injury (SCI) pathology is highly difficult to treat due to substantial heterogeneity in injury presentation and spread, along with unclear mechanisms linking damage to pathology. Damages from injury forces (primary injury) are exacerbated by a series of biochemical events that follow the initial damage and injure additional tissue, known as secondary injury. Reactive aldehydes, such as acrolein, play a key role in propagating secondary injury cascades following SCI. Targeting acrolein after SCI has demonstrated therapeutic potential in limiting injury spread and pathology. However, injury mechanisms linking reactive aldehydes to SCI outcome have not been fully characterized. To gain a more comprehensive understanding of the cellular and molecular mechanisms underlying SCI, we generated proteomic profiles of rat spinal cords 24 h (acute phase) after subjection to SCI, sham injury, saline injection, or acrolein injection. We performed gene set enrichment analysis (GSEA) to characterize proteins and pathways significantly enriched after SCI and acrolein-injection. We then used Translatable Components Regression (TransComp-R), a framework for translating biological signatures across systems, to assess whether acrolein-associated spinal cord signatures can stratify SCI from sham outcomes. Our proteomics analysis revealed 467 differentially expressed proteins (DEPs) between the sham and SCI groups and 7 DEPs between saline and acrolein injection groups. Notably, the complement and coagulation cascades were upregulated in spinal cords subjected to SCI and acrolein injection. Our TransComp-R analysis further demonstrated that acrolein-associated signatures could distinguish SCI from sham conditions. Taken together, our findings suggest that acrolein induces proteomic alterations during the acute phase of SCI and is associated with complement and coagulation cascade activation, among other pathways. Therefore, this study reinforces the notion that understanding the role of acrolein in the acute phase of secondary SCI may be beneficial.

neuroscience↗

bioRxiv2026

PROTOTYPE-BASED CONTINUAL LEARNING FOR SINGLE-CELL ANNOTATION

Large-scale single-cell atlases provide an increasingly comprehensive view of cellular diversity, but their continued expansion across studies poses a fundamental challenge: preserving consistent cell identities while capturing biological variation in cellular states. Most existing annotation frameworks are built around static references, making it difficult to incorporate newly generated datasets into established cellular representations without retraining on historical data. When updated sequentially, these methods are further constrained by catastrophic forgetting and batch-specific biases, limiting scalability and the continuity of knowledge integration. Here we introduce scEvolver, a continual learning framework for single-cell annotation that incrementally accumulates knowledge through memory-guided refinement of cell-type prototypes without revisiting historical data. Across sequencing platforms, tissue contexts and molecular modalities, scEvolver supports robust annotation and external query mapping with substantially fewer labelled reference cells. By preserving consistent cell-type semantics across datasets while capturing biologically meaningful within-class heterogeneity, scEvolver enables the identification of epithelial cell-state transitions in inflammatory gut disease. External mapping to the healthy Human Lung Cell Atlas further reveals shared cell-state deviations across multiple diseases, including an FCGR3A+ inflammatory monocyte programme in sarcoidosis, chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis, highlighting scEvolvers potential to characterize context-specific cellular dynamics in complex disease settings.

bioinformatics↗

bioRxiv2026

Epigenetic control of microglial mitochondrial immunity by KAT7 drives Alzheimer's disease pathogenesis

Mitochondrial DNA (mtDNA)-driven innate immune signaling sustains chronic neuroinflammation in neurological diseases such as Alzheimers disease (AD), yet how this pathway is regulated in microglia remains poorly understood. Here, we identify the histone acetyltransferase KAT7 (HBO1) as a central epigenetic regulator that links chromatin remodeling to mitochondrial immune activation. KAT7 and its histone mark H3K14ac are elevated in microglia from 5xFAD mice and human AD brains. Integrative transcriptomic and epigenomic analyses reveal that KAT7 activates transcription of Cmpk2, a mitochondrial kinase essential for mtDNA synthesis. Loss of KAT7 reduces Cmpk2 expression, impairs mtDNA replication and release, and consequently suppresses cGAS-STING and NLRP3 signaling. Importantly, both microglia-specific deletion and pharmacological inhibition of KAT7 mitigate cytosolic mtDNA-induced neuroinflammation, decrease amyloid-{beta} burden, restore synaptic plasticity, and improve cognitive function in 5xFAD mice. Together, these findings uncover an epigenetic-mitochondrial axis sustaining microglial pathogenicity and establish KAT7 as a promising therapeutic target for AD.

neuroscience↗

bioRxiv2026

Visual experience drives functional reorganization of cortical GABAergic circuits

Sensory experience shapes the development and function of neocortical circuits. Although repeated exposure to sensory stimuli can alter cortical responses, the precise relationship between sensory experience and circuit interactions remains unclear. Here, we examine how cortical circuits are shaped by repeated exposure to varied visual stimuli. We find that visually evoked beta activity, a prominent pattern of visually evoked activity that relies on somatostatin-expressing (SST) GABAergic interneurons, is robustly potentiated by visual experience. Enhanced visual experience leads to increased responses in SST interneurons and suppressed responses in vasoactive intestinal peptide-expressing (VIP) interneurons. In association with this rebalancing of cortical inhibitory activity, experience increases the recruitment and visual selectivity of excitatory neurons. This enhancement is associated with increased SST-IN influence on nearby pyramidal neurons and requires SST-IN activity during visual experience. Visual experience thus selectively reorganizes adult dendrite-targeting inhibitory circuits, promoting network synchrony and enhancing sensory encoding by excitatory neurons.

neuroscience↗

bioRxiv2026

IntelliFold-2: Surpassing AlphaFold 3 via Architectural Refinement and Structural Consistency

IntelliFold-2 is an open-source biomolecular structure prediction model that improves accuracy and robustness through architectural refinement and multiscale structural consistency. We introduce latent space scaling in Pairformer blocks, a principled atom-attention formulation with stochastic atomization, policy-guided optimization for diffusion sampling and difficulty-aware loss reweighting. On Foldbench, IntelliFold-2 improves performance in therapeutically relevant settings, with particularly strong gains for antibody-antigen interactions and protein-ligand co-folding relative to AlphaFold 3. We release three variants (Flash, v2, and Pro) to cover efficient fine-tuning through high-precision server-side inference.

bioinformatics↗

bioRxiv2026

Acute priming using elevated fluid viscosity recovers young-like single-cellsurveillance behaviors in aged human T cells

Aging is a complex biological process, often characterized by increased vulnerability to disease, infection, and death. This increased vulnerability is mechanistically linked to a progressive and functional decline of the immune system. In humans, aged lymphocytes lose their capacity to effectively surveil within diverse microenvironments, decreasing their capability for clearing infections and maintaining physiological homeostasis. However, specific mechanisms by which aged lymphocytes, specifically T cells, lose this capacity to surveil remain unclear. We profiled three core characteristics of T cell surveillance at single-cell resolution, specifically migration, deformability, and sensing. While aged T cells retained their capacity for spontaneous migration, they exhibited impaired cellular deformability and deficiencies in sensing local signaling cues. To modulate this surveillance defect, we performed mechanical reprogramming using elevated fluid viscosity. Results showed that acute priming of aged T cells with elevated fluid viscosity recovered a transient young-like surveillance phenotype, which was mechanistically linked to membrane tension, cortical F-actin, and Arp3 expression. These findings reveal a key source of surveillance defects in aged T cells and provide an effective mechanical approach to tuning their single-cell behaviors. TeaserRecovery of young-like surveillance phenotypes in aging human T cells via viscosity priming

bioengineering↗