Biology subjects

Han, S.

Publications and source records attributed to Han, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Pore-Resolved High-Throughput Quantification of Amyloid Aggregation and Amplification

Amyloid fibrils are implicated in a wide spectrum of neurodegenerative and systemic disorders, yet their biological consequences are governed not only by total fibril content but also by how fibrillar species are organized, clustered, and amplified within heterogeneous populations. Conventional thioflavin T (ThT)-based assays provide sensitive sample-level readouts of {beta}-sheet-rich material but offer limited access to the local population structure underlying amyloid aggregation and amplification. Here, we introduce the Amyloid Pore Quantification (APQ) chip, a pore-resolved geometric partitioning platform that converts heterogeneous amyloid assembly states into fluorescence intensity distributions across thousands of defined pore-level units. Using hen egg-white lysozyme as a model amyloid-forming protein, we combine length-controlled truncated amyloid nanofibrils with vacuum-assisted ThT infiltration to establish a reproducible pore fluorescence intensity reference. APQ provided quantitative concentration-dependent calibration across a 50-fold concentration range, enabling bulk-comparable quantification while preserving pore-level distribution information. Deviations from this reference resolved pH-dependent fibril clustering near the isoelectric point as pore-signal suppression and accessibility loss, captured pepsin-associated fibrillar amplification as a population-wide increase in pore intensity, and distinguished monomer- and oligomer-driven fibril processing through coupled amplification-aggregation fingerprints. When benchmarked against ensemble fluorescence measurements and AFM morphological analysis, APQ revealed assembly-state changes that were not fully represented by sample-level ThT intensity alone. These results establish APQ as a high-throughput, distribution-aware analytical framework for translating amyloid aggregation and amplification into quantitative pore-resolved fingerprints.

bioengineering↗

bioRxiv2026

Mechanochemically Programmed, Oligomer-Selective Amyloid Assembly via Axial Rotation

Amyloid oligomers have been widely implicated as primary cytotoxic intermediates; however, their selective and scalable production remains challenging due to rapid fibril amplification. Here, we demonstrated that sustained axial rotation enables programmable mechanochemical control over amyloid pathway selection without the use of chemical additives. Using a thermal axial rotator, native monomeric hen egg-white lysozyme was incubated at 60 {degrees}C under quantitatively tunable rotational speeds, imposing defined centrifugal forces and wall-associated shear that restructured the hydrodynamic boundary conditions. A discrete transition emerged near 600 RPM, separating the two distinct assembly regimes. Below this threshold, aggregation followed a fibril-amplifying pathway characterized by elevated {beta}-sheet content and elongated fibrillar morphologies. Above this threshold, fibrillar growth was strongly attenuated and oligomer-dominant assemblies predominated. Spectroscopic analyses and atomic force microscopy revealed that axial rotation redistributes the amyloid assembly states rather than simply suppressing aggregation. Functionally, the RPM-defined assemblies exhibited kinetically distinct seeding behaviors and induced divergent cytotoxic phenotypes in SH-SY5Y neuroblastoma cells. These findings establish axial rotation-mediated hydrodynamic boundary control as a scalable, chemical-free strategy for reprogramming amyloid assembly pathways and producing oligomer-rich assemblies with well-defined structural and functional properties.

bioengineering↗

bioRxiv2026

Sex Differences in Bed Nucleus of the Stria Terminalis Response to Calcitonin Gene-Related Peptide

Women are disproportionately affected by chronic pain, yet the neural mechanisms underlying sex differences in affective pain processing remain incompletely understood. The bed nucleus of the stria terminalis (BNST), a sexually dimorphic structure implicated in aversion and chronic pain, receives dense input from aversive calcitonin gene-related peptide (CGRP)-expressing neurons arising from the parabrachial nucleus (PBN). Although CGRP signaling has been implicated in sex differences in clinical pain conditions, whether CGRP transmission within the PBN[->]BNST pathway is sexually dimorphic has not been determined. Here, we tested the hypothesis that CGRP signaling in the BNST differs between sexes. Contrary to our prediction, PBN CGRP neurotransmitter release in the BNST was sex-independent. However, CGRP neuromodulation of BNST excitability exhibited sex-dependent features. While CGRP potentiated PBN[->]BNST glutamatergic signaling in both sexes, spontaneous inhibitory signaling was selectively increased in males. Together, these findings indicate that sex differences in this circuit arise not from differential peptide release, but from downstream modulation of inhibitory tone, biasing female BNST neurons toward greater excitation. Such circuit-specific sex differences may contribute to the enhanced susceptibility of females to affective components of chronic pain and highlight targets for sex-informed therapeutic interventions.

neuroscience↗

bioRxiv2026

Basal gland localization and focal distribution of OLFM4-expressing cells in increasing severity of gastric intestinal metaplasia

Patients with gastric intestinal metaplasia (GIM), a precancerous lesion, are at high risk for progressing to gastric cancer. Identifying these patients is critical to enable gastric cancer interception. Current approaches rely primarily on histologic evaluation of GIM severity and extent, which may be improved by incorporating molecular features that distinguish high-risk lesions. Our prior single-cell and spatial transcriptomics study identified differentially expressed genes associated with the highest-risk category of GIM. They included ANPEP expressed in enterocytes and CPS1 and OLFM4 expressed in intestinal stem-like or progenitor cells. We evaluated the protein expression and localization of these three markers to understand the cellular features associated with GIM risk and their spatial distribution within metaplastic tissues. Using multiplex immunofluorescence, whole slide image analysis and confocal microscopy, we examined protein expression from 100 tissue biopsies annotated for metaplasia severity using the Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) system. Tissue samples included control gastric tissue, GIM, dysplasia and adenocarcinoma. Quantitative whole slide image analysis demonstrated that CPS1 expression had a modest association with disease severity. Although ANPEP was strongly associated with GIM severity, it was also frequently expressed in stromal regions outside epithelial glands. In contrast, OLFM4 expression was largely restricted to epithelial glands and showed a strong association with increased OLGIM severity. These OLFM4-positive epithelial cells were present in discrete glandular foci that expanded with increasing severity of metaplasia. Within individual metaplastic glands, OLFM4 expression was highest at the gland base with decreased expression toward the gland surface. Overall, these findings identified OLFM4 as a protein marker associated with high-risk GIM. The spatial organization of OLFM4-expressing cells at the base of metaplastic glands and their focal expansion within tissues suggest the presence of a stem cell-like epithelial compartment that may contribute to the progression of GIM towards gastric cancer.

cancer biology↗

bioRxiv2026

TransXplorer: An automated translational discovery platform for RNA-seq data

RNA-seq experiments routinely identify thousands of differentially expressed genes, but translating these into biological insights and therapeutic hypotheses often requires integrating multiple tools. Existing web platforms such as iDEP, NetworkAnalyst, and GEPIA2 address individual steps, differential expression, network visualization, or TCGA queries, but lack a unified environment spanning raw data processing to clinical and pharmacological interpretation. TransXplorer (https://transxplorer.org) is a freely available web platform that addresses this limitation by integrating the complete RNA-seq analytical workflow. It supports processing from raw FASTQ files using HISAT2 or Salmon, as well as direct GEO dataset import with automated metadata handling. Differential expression analysis is implemented via DESeq2, edgeR, and limma-voom, followed by functional enrichment across more than 1,800 species using Bioconductor resources. Batch effects are automatically detected and corrected using a composite of PVCA, kBET, and Silhouette metrics without requiring predefined batch annotations. Downstream analyses include co-expression network construction (WGCNA), protein-protein interaction mapping (STRING), cell-type deconvolution, and transcription factor inference using integrated DoRothEA and TFLink resources. The platform further links gene signatures to drug candidates through DGIdb and OpenTargets and enables survival and tumour-normal comparisons across TCGA cohorts. Application to cardiac endothelial differentiation (GSE151427) and kidney renal papillary cell carcinoma (TCGA-KIRP) datasets demonstrates accurate batch correction, biologically consistent pathway enrichment, recovery of expected cell-type proportions, and identification of clinically relevant genes and drug candidates. TransXplorer is freely available without a login.

bioinformatics↗

bioRxiv2026

Comparative single-cell transcriptomic roadmap of mammalian fetal ovarian development

Early ovarian development establishes the cellular basis of female reproduction, yet its cellular composition and developmental dynamics remain poorly characterized across mammalian species. Here, we generated a cross-species single-cell transcriptomic atlas of early female gonadal development in cattle (E38-E112), human (PCW6-16), and mouse (E11.5-E18.5), integrating 107,930 cells across comparable developmental windows, spanning sex determination and early ovarian differentiation. We identified 11 shared gonadal cell types across three species, including germ cells and granulosa cells, and uncovered a previously undescribed bovine-specific cell population with steroidogenic features, suggesting species differences in ovarian somatic lineage development. Epigenetic regulators exhibited dynamic activation in germ cells and granulosa cells. Developmental trajectory analysis revealed shared and species-specific genes associated with germ cell and granulosa cell development, including conserved dynamically expressed genes such as TFAP2C and ZCWPW1 in germ cells and FOS and JUNB in granulosa cells. Cross-species cell type classification using a machine learning support vector machine (SVM) model revealed transcriptionally conserved cell types, such as immune cells and germ cells, while granulosa cells showed substantial cross-species divergence, associated with extracellular matrix-related gene expression. Together, our study provides a comparative framework for understanding conserved and divergent mechanisms of early ovarian development across mammals.

developmental biology↗

bioRxiv2026

STAT: A multi-agent framework for integrated and interactive spatial transcriptomics analysis

Spatial transcriptomics analysis often involves a myriad of computational methods across diverse platforms, leading analysts to spend excessive time on data assembly rather than deriving biological insights. Current AI solutions tend to either oversimplify spatial data into generic single-cell tables or operate autonomously without opportunities for intermediate review, thus hindering the visual and iterative analyses essential for spatial biology. In response to these challenges, we introduce STAT, a multi-agent framework designed to make spatial analysis more conversational and user-friendly while maintaining transparency and control. STAT integrates a persistent session, a shared interactive tissue viewer, and a staged skill-aware pipeline, enabling a more intuitive analytical experience. In a comprehensive benchmark evaluation encompassing eleven analytical task categories across three spatial platforms and both cell- and spot-resolution data, STAT demonstrates superior performance compared to a vanilla large language model and existing autonomous spatial analysis agents, excelling in task completion, analytical quality, and token efficiency. Notably, STAT enables multi-task spatial analysis of a mixed-resolution breast cancer cohort and successfully reproduces key findings from a published Visium HD colorectal cancer study using natural language prompts alone. STAT thus facilitates trustworthy and scientifically rigorous spatial transcriptomics analysis, allowing researchers to focus more on biological interpretation.

bioinformatics↗

bioRxiv2026

Healthy aging, processing speed, and mnemonic brain state engagement

Healthy older adults exhibit both selective impairments in episodic memory - memory for events situated within a specific time and place - and deficits in executive function, reflected by difficulty switching between different tasks and inhibiting task-irrelevant information. Prior work has shown that older adults show diminished mnemonic brain state engagement - recruitment of whole brain activity patterns that selectively support memory encoding and memory retrieval. Our hypothesis is that older adults are biased toward the retrieval state and, due to executive function deficits, cannot easily switch out of this state when task-irrelevant. Our goal was to determine the extent to which stimulus processing time impacts older adult mnemonic state engagement, with the expectation that longer processing times would enable older adults to switch out of a task-irrelevant retrieval state. We recorded scalp electroencephalography (EEG) while younger and older adult participants explicitly encoded and retrieved object stimuli under variable stimulus durations. Using a combination of multivariate decoding approaches, we find that under time constraints, older adults both under-recruit a young-adult like retrieval state when task-relevant, but over-recruit a participant-specific retrieval state when task-irrelevant. Older adults may thus recruit idiosyncratic activity patterns to compensate for difficulties engaging young-adult like mnemonic brain states. Taken together, these findings suggest that although older adults retain the ability to engage encoding and retrieval brain states, they require more processing time to both initiate and maintain goal-relevant mnemonic states.

neuroscience↗

bioRxiv2026

Benchmarking single-cell foundation models for real-world RNA-seq data integration

Single-cell foundation models enable reusable representations and streamlined analysis workflows, yet rigorous evaluation of their performance and robustness in real-world pharmaceutical settings remain underexplored. Here, we benchmarked leading single-cell foundation models (scGPT; scGPT_CP, a continually pretrained checkpoint of scGPT; scFoundation; scMulan; CellFM) against established baseline methods (scVI; Harmony) for data integration using over 1.5 million cells from clinical and preclinical samples. Performance was assessed using well-established and complementary metrics for technical correction and biological structure preservation. We further introduced robustness-oriented rankings to summarize metric trade-offs and quantify performance consistency across datasets and evaluation settings. Our findings show that fine-tuning improved technical correction performance; among the foundation models, fine-tuned scGPT_CP performed best. However, the baseline scVI was the top overall performer, ranking first by our multi-metric Leximax ranking and achieving the highest Pareto Front-1 hit. Collectively, our study provides practical insights for adapting foundation models to real-world drug design and development.

bioinformatics↗

bioRxiv2026

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

A major challenge in gene therapy for GJB2-related hearing loss (DFNB1)--the most common form of hereditary deafness--is achieving efficient and precise connexin 26 delivery. Herein, we engineered two cell type-specific promoters (GJB2-1 and WFS1-2274) and developed an AAV capsid, AAV-MAS012, with enhanced transduction efficiency in mature cochlear cells. Our AAV-mediated gene therapy systems restored hearing of low-to-mid-frequencies in newborn Gjb2 cKO mice to wild-type levels and maintained for 45 weeks. Additionally, our therapeutic systems restored low-to-mid-frequencies hearing function to wild-type levels in adult Gjb2 cKO mice. A humanized version of the therapy, AAV-MAS012-WFS1-2274-hGJB2, rescued hearing function in two distinct Gjb2-deficient mouse models, and demonstrated a favorable safety profile in nonhuman primates. This study represents the first successful hearing restoration in adult Gjb2-deficient mice. The significant therapeutic efficacy of the humanized gene therapy system shows great potential for clinical translation in DFNB1 patients.

genetics↗

bioRxiv2026

RUNX1-deficiency drives immune-active ER+ mammary tumorigenesis through activation of interferon signaling

AbstractRecurrent loss-of-function mutations in RUNX1 occur in estrogen receptor-positive (ER+) breast cancers, yet how RUNX1-loss contributes to breast tumorigenesis remains unclear. Here we used genetically engineered mouse models with luminal mammary epithelial cell (MEC)-restricted gene disruption to investigate its role in breast cancer initiation. Loss of RUNX1 alone, or together with RB1, was insufficient to drive tumor formation. In contrast, combined loss of RUNX1 and p53 induced mammary tumors with full penetrance. These tumors contained ER+ cancer cells and exhibited extensive T cell and macrophage infiltration, indicative of an immune hot microenvironment. Mechanistically, RUNX1-deficiency activated interferon signaling in luminal MECs, associated with derepression of RUNX1 target STAT1 and enhanced inflammatory responses. Consistent with these findings, human ER+ breast cancers with low RUNX1 expression displayed elevated immune signatures and poorer patient survival. Together, our results identify RUNX1-loss as a driver of an immune-active subtype of ER+ breast cancer.

cancer biology↗

bioRxiv2026

Probiotic Lactiplantibacillus plantarum VB165 improves metabolic disorders in Insulin-Resistant Mice

This study investigated the effects of Lactiplantibacillus plantarum VB165, a probiotic strain with intrinsic -glucosidase inhibitor (AGI) activity, on metabolic disorders in high-fat diet (HFD)-induced insulin-resistant (IR) mice. Male C57BL/6 mice were divided into four groups: normal control diet (NCD), NCD supplemented with VB165, HFD, and HFD supplemented with VB165. After 16 weeks, VB165 supplementation significantly attenuated HFD-induced weight gain and reduced epididymal and inguinal white adipose tissue indices. VB165 also improved glucose intolerance and insulin resistance (IR), as demonstrated by oral glucose tolerance tests (OGTT) and insulin tolerance tests (ITT), and lowered fasting blood glucose, fasting insulin, and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) levels. Additionally, it ameliorated dyslipidemia by reducing serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol (LDL-C), while alleviating hepatic steatosis and adipocyte hypertrophy. Mechanistically, VB165 enhanced intestinal barrier function by upregulating tight junction proteins (ZO-1 and Occludin), reduced systemic inflammation by lowering LPS, IL-6, and IL-1{beta}. Gut microbiota analysis revealed that VB165 modulated community composition, suppressing HFD-enriched genera (e.g., Ileibacterium and Coriobacteriaceae_UCG_002) and promoting beneficial taxa (e.g., Faecalibaculum and Oscillibacter). These findings demonstrate that L. plantarum VB165 improves HFD-induced metabolic disorders via multi-target mechanisms, highlighting its potential as a probiotic intervention for IR and related metabolic diseases.

microbiology↗

bioRxiv2026

LSD1 ablation promotes mammary tumor metastasis by attenuating NK cell-mediated anti-tumor immunity

Epigenetic deregulation can alter the expression of cancer-related genes in tumor cells and may promote metastasis by influencing interactions between tumor cells and their immune microenvironment. However, the underlying immune mechanisms remain poorly understood. LSD1 (KDM1A) is a histone demethylase that has been proposed to function as a tumor and metastasis suppressor in breast cancer. Here, using the MMTV-PyMT breast cancer mouse model, we show that natural killer (NK) cells play a critical role in suppressing tumor cell metastasis to the lung, and that ablation of LSD1 leads to increased lung metastasis. This phenotype is accompanied by pronounced upregulation of immune-related genes, including major histocompatibility complex class I (MHC-I) genes, in tumor cells and by extensive remodeling of the tumor immune microenvironment, characterized by reduced abundance and maturation of NK cells. Consistent with these observations, NK cells exhibit reduced cytotoxicity toward Lsd1-null PyMT tumor cells. Notably, NK cell-mediated killing can be restored by disrupting expression of the non-classical MHC-I molecule Qa-1, a ligand for the inhibitory NK receptor CD94/NKG2A, in tumor cells. In transplantation experiments, Lsd1-null PyMT tumor cells formed significantly larger lung metastatic lesions than Lsd1-wildtype tumor cells in SCID mice, which possess functional NK cells, but not in NSG mice that lack NK cells. Collectively, these findings suggest that epigenetic deregulation in LSD1-deficient mammary tumor cells reprograms the tumor immune microenvironment, resulting in impaired NK cell-mediated tumor surveillance and enhanced metastatic progression.

cancer biology↗

bioRxiv2026

Distinct cellular DNA methylation mechanisms underlie common and rare genetic risk for brain disorders

Noncoding genetic variation contributes to brain disorder risk, but the mechanisms through which it acts in specific brain cell types remain unclear. DNA methylation (DNAm), a highly cell type-specific regulatory layer in the brain, may mediate noncoding genetic risk, yet whether methylation at CG (mCG) and neuron-enriched non-CG (mCH) dinucleotides contribute differently to that risk remains unknown. Here we develop a deep learning framework that predicts DNAm from DNA sequence and estimates variant effects across 186 brain cell subtypes in both mCG and mCH, leveraging single-nucleus DNAm profiles from 46 brain regions. The models reveal distinct transcription factor (TF) programs underlying the two methylation contexts, with mCH-associated TFs showing stronger evolutionary constraint. Predicted variant effects agree closely with cell type-matched mQTLs in both direction and magnitude. Common variants predicted to affect mCG, particularly in excitatory neurons, show substantially greater heritability enrichment for brain-related traits than variants affecting mCH. By contrast, noncoding de novo mutations in autism preferentially perturb mCH, but not mCG, at conserved neuronal regulatory regions. This pattern is replicated across two independent cohorts totaling 5,782 probands and 4,053 unaffected siblings. Together, these findings indicate that common and rare noncoding variants contribute to brain disorders through distinct DNA methylation mechanisms.

genetics↗

bioRxiv2026

Beyond the skin barrier: optical clearing enables non-invasive cortex-wide optical coherence angiography in mice in-vivo

Non-invasive, high-resolution visualization of mouse brain vasculature remains challenging due to significant light scattering and absorption by mammalian tissues, hence many optical imaging protocols require scalp and/or skull excision. Here we present a fully reversible tartrazine-based optical clearing strategy that enables cortex-wide optical coherence tomography angiography (OCTA) through intact scalp and skull. We characterized tartrazine properties in the near infrared (NIR)-II band of the 1.3 {micro}m swept-source OCTA system, confirming minimal absorption across 1.25-1.35 {micro}m wavelength range and an effectively constant refractive index, suggesting negligible OCTA distortions. Spatially selective agent application showed that intracranial vessels emerge selectively within the treated region of interest (ROI), whereas untreated regions retain strong interference by the scalp vascular features. Depth-encoded projections and cross-sectional OCTA demonstrated an increased signal recovery at depth and an extended vessel-detection range after clearing. Vessel-map changes were quantified using intersection-over-union and Dice coefficients, yielding high similarity outside the ROI and reduced similarity within the ROI, consistent with a transition from scalp to brain vasculature. Reproducibility was confirmed in three independent 11-week-old mice and validated against scalp-removed reference OCTA. Screening tartrazine in the 0.3-0.8 Molar concentration range (7-min application) identified 0.6 M as optimal for whole-cortex scanning, balancing clearing efficacy and solution handling. Finally, the protocol generalized across mice aged 5-18 weeks. This approach provides a practical route to non-invasive structural cerebrovascular mapping with OCTA.

bioengineering↗

bioRxiv2026

Heterozygote Advantage of a Single-Copy SNAP18 Truncation Allele Enables Dominant SCN Resistance and Yield Preservation in Soybean

Soybean cyst nematode (SCN, Heterodera glycines) is the most devastating pathogen threatening global soybean production. The long-term over-reliance on rhg1-a/b resistance has led to the rapid emergence of virulent SCN populations, creating an urgent demand for novel genetic resources to safeguard soybean yield. Here, we identified a rare gain-of-function allele, SNAP18lmm3, via map-based cloning of the lesion-mimic mutant (lmm3) in the SCN-susceptible Williams 82 (rhg1-c) background. This allele encodes a 24-amino-acid C-terminal truncation of SNAP18 and exhibits an unusual mixed dominance genetic profile: the autoimmune-related leaf lesion phenotype is recessive, whereas SCN resistance is dominant. Homozygous lmm3 plants suffer significant yield losses due to spontaneous cell death, but heterozygous (LMM3+/-) plants maintain normal growth, agronomic performance, and seed yield comparable to wild-type Williams 82 in SCN-free field environments. Critically, under artificial SCN inoculation in both field trials and controlled environments, LMM3+/- heterozygotes confer robust resistance, achieving a [~]4-fold yield advantage over SCN-infested Williams 82 and a [~]44% reduction in cyst formation relative to Williams 82. This resistance profile aligns with the broad-spectrum activity of the lmm3 homozygous mutant, supported by the conserved resistance mechanism of SNAP18lmm3. Transgenic expression of SNAP18lmm3 driven by the nematode-responsive HIP promoter (HIPpro) potently arrested nematode development at the J2 stage in transgenic hairy roots, as evidenced by the drastically reduced proportion of advanced-stage nematodes. Our findings establish SNAP18lmm3 as a potent, "plug-and-play" genetic resource that circumvents the limitations of traditional dosage-dependent resistance loci. This allele enables the development of high-yielding, SCN-resistant soybean cultivars through marker-assisted selection for the heterozygous state or precision genome editing, providing a practical solution for sustainable SCN management.

plant biology↗

bioRxiv2026

SNAP18 Truncation Triggers a Competitive Binding Switch Between NSF and ATG8f, Balancing Vesicular Trafficking and Autophagy for SCN Resistance in Soybean

Soybean cyst nematode (SCN, Heterodera glycines) poses the most devastating biotic threat to global soybean production. Traditional SCN resistance mediated by the Rhg1 locus predominantly relies on gene copy number expansion and elevated -SNAP protein dosage. Here, we report a novel resistance mechanism in a single-copy rhg1-c background, wherein a C-terminal 24-amino-acid truncation of SNAP18 (designated SNAP18lmm3) triggers a functional switch from vesicular trafficking to autophagic degradation. Biochemical assays and structural modeling demonstrate that this truncation severely impairs the canonical interaction between SNAP18 and N-ethylmaleimide-sensitive factor (NSF), disrupting SNARE complex recycling and inducing localized cytotoxicity. Concomitantly, the truncated SNAP18lmm3 exposes a binding interface for the autophagy-related protein ATG8f, routing the aberrant protein for selective autophagic clearance. This constitutively activated autophagic flux acts as a systemic detoxification system, preventing widespread cell death and ensuring normal plant growth under non-stressed conditions. Upon SCN infection, SNAP18lmm3 specifically hyper-accumulates within nematode-induced syncytia. This accumulation reaches levels fourfold higher than in adjacent cells, which overwhelms the local autophagic capacity and triggering targeted cell death that arrests nematode development. By elucidating this competitive molecular switch between NSF and ATG8f binding, our study establishes a "self-degrading toxin" model that resolves the inherent trade-off between plant growth and immunity. This work provides a new theoretical framework for engineering cellular homeostasis to enhance durable crop resistance against parasitic nematodes.

plant biology↗

bioRxiv2026

Mapping spatially organized molecular and genetic signatures of schizophrenia across multiple scales in human prefrontal cortex

The dorsolateral prefrontal cortex (dlPFC) is central to cognitive dysfunction in schizophrenia (SCZ), yet how molecular changes are organized across cortex remains unclear. Here, we applied complementary spatial transcriptomic approaches spanning laminar domains, microenvironments, and cell types in postmortem human dlPFC. At the laminar level, SCZ-associated transcriptional changes were strongest in glia-enriched domains (layer 1/meninges and white matter), including down-regulation of microglia-associated genes, whereas genetic risk localized to neuronal-rich gray matter. We next analyzed SCZ-linked microenvironments including neuropil, neuronal, perineuronal net, and vascular compartments. Within these, neuronal and synaptic transcriptional changes were most prominent in neuropil, showing down-regulation of activity-dependent synaptic genes and inhibitory neuron markers. At the cellular level, these signals reflected intrinsic alterations localized to cell types. Across analyses, patterns converged on altered BDNF-TrkB signaling and inhibitory circuit dysfunction. Together, our findings highlight spatial scale as a key determinant in resolving neuronal and non-neuronal aspects of SCZ-associated biology.

neuroscience↗