Biology subjects

Cai, S.

Publications and source records attributed to Cai, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Cellular context shapes the transcriptomic impact of somatic variants

Somatic SNVs are commonly prioritized by recurrence or sequence annotation, leaving the molecular consequences of private variants unresolved. We developed PrismSNV and Ligo-Seq, a single-cell full-length transcriptome sequencing platform, to quantify transcriptomic displacement associated with within-cell SNV-state toggling. Across 26 samples from three cancer types, more than 60% of candidate SNVs showed significant cell-type-specific displacement with over 30% variation in magnitude. Sequence-based deleteriousness was poorly aligned with cellular displacement, and fewer than 3% of top-displacement SNVs across six tumor types were catalogued in ClinVar. Displacement was strongest in transcriptionally plastic, less differentiated states. Analysis of 655,349 CD4+ T-cell transcriptomes further showed that SNV-gene associations changed in magnitude and sometimes direction during activation. Lack of recurrence or clinical annotation does not imply transcriptomic inertness; variant impact is shaped by cellular context rather than sequence alone, establishing the variant-cell pair as a critical unit for interpreting somatic variation.

genetics↗

bioRxiv2026

Dissociable changes in temporal precision and causal expectations following perceptual training

A common behavioral gain does not necessarily reflect a common learning mechanism. Perceptual learning may sharpen sensory evidence without updating higher-level expectations about its causes. Across three experiments, we examined audiovisual binding and its plasticity in children with ADHD and typically developing children. Children with ADHD were more susceptible to the sound-induced flash illusion (Experiment 1) and showed markedly flatter temporal tuning of it (Experiment 2), yet conventional temporal binding window (TBW) estimates did not distinguish the groups, behavior alone could not localize the difference. Following six days of simultaneity-judgment training, both groups became comparably less susceptible to the illusion. A temporally explicit two-dimensional Bayesian causal inference model, however, revealed sharply different latent changes. Typically developing children reduced their causal prior expectation that auditory and visual signals shared a common cause. Children with ADHD showed no corresponding prior recalibration but instead exhibited a marked reduction in temporal uncertainty, indicating more precise perceptual evidence that did not propagate to the slower, more abstract estimate of environmental causal structure. Thus, perceptual learning converged at the behavioral level while diverging computationally. These findings argue against unitary accounts of multisensory plasticity and show how the same perceptual endpoint can conceal adaptation at different levels of the inferential hierarchy.

neuroscience↗

bioRxiv2026

Dietary sugar type determines the response to protein restriction in females, but not males

Low protein (LP) diets improve metabolic health in rodents and humans. In rodents, LP diets are typically implemented by replacing protein with carbohydrates like sucrose or cornstarch, keeping diets isocaloric. However, humans can choose from many different types of carbohydrate, and how dietary carbohydrate quality - the precise composition of the dietary sugars - impacts the response to dietary protein remains largely unexplored. Here, mice were fed control (21% protein) or LP (7% protein) diets with four different carbohydrate sources: sucrose, a 1:1 glucose/fructose mixture, glucose, or fructose. While LP diets improved metabolic health across all groups in male mice, carbohydrate quality also significantly altered specific health outcomes, with fructose-fed mice having the lowest body weight and adiposity of all control diets. In female mice, responses to LP diets were influenced by carbohydrate quality, with certain sugars inducing a stronger metabolic response to LP diets than previously seen. Finally, in female APP/PS1 mice, a model of Alzheimer's disease, we find that although LP diets reduce A-beta; plaque burden irrespective of carbohydrate type, dietary sugar type does influence spatial memory. Together, these results demonstrate that while dietary protein is a critical determinant of metabolic and neurological health, carbohydrate quality influences these outcomes in a sex-specific manner.

physiology↗

bioRxiv2026

Selective GRAB sensors reveal distinct endocannabinoid dynamics in vivo

The endocannabinoid system modulates diverse physiological processes via two endogenous lipid ligands, 2-arachidonoylglycerol (2-AG) and anandamide (AEA); however, their specific spatiotemporal dynamics remain poorly understood owing to the lack of selective probes. Here, we developed GRAB2-AG2.0 and GRABAEA2.0, two genetically encoded fluorescent sensors that selectively detect 2-AG and AEA, respectively. Both sensors exhibited high apparent affinity and molecular specificity for their respective ligands, enabling the real-time detection of 2-AG and AEA release evoked by electrical stimulation in cultured neurons and acute brain slices. In freely behaving mice, these sensors revealed ligand- and context-specific eCB dynamics: aversive stimulation preferentially evoked 2-AG, whereas psychoactive drugs produced distinct 2-AG and AEA responses. Notably, {Delta}9-THC elicited a sustained 2-AG signal in the nucleus accumbens shell, and local deletion of Dagla markedly attenuated both this signal and {Delta}9-THC-induced hypolocomotion. These sensors therefore enable detecting 2-AG and AEA signaling seperately and reveal an endogenous 2-AG component of the behavioral response to {Delta}9-THC.

neuroscience↗

bioRxiv2026

Morphomechanically-Informed Spatial Curvature Sequencing in Prostate Cancer

Morphological changes in prostate glands, assessed by Gleason grading, remain the gold standard for diagnosing prostate cancer, yet molecular biomarkers associated with gland shape are not well understood. Here, we introduce CurvSeq, a mechanomorphology-informed framework for spatial sequencing data, and CurvSee, its complementary version for proteomic and imaging datasets. These methods integrate gland boundary curvature, pocket architecture, microenvironmental composition, and molecular profiles to study morphomechanical relationships in prostate adenocarcinoma. Using five independent spatial transcriptomic and multiplexed imaging datasets, we segmented individual prostate glands, extracted gland contours, quantified local curvature and pocket-like concavities, and projected these features onto spatially resolved gene and protein measurements. In Xenium data, CurvSeq distinguished benign and GG1 glands, identifying cancer-associated genes such as PCA3 and AMACR in GG1 glands and basal, basement membrane, and mechanotransduction-associated programs in benign glands. In Visium data, a diffusion-based morphomechanical score ordered benign glands by area, circularity, pocket number, smooth muscle abundance, immune-cell proximity, and remodeling-associated genes including MMP7. In GG4 glands, CurvSeq identified neuroendocrine-like boundary regions associated with MMP7 expression, COL1A1-rich adjacent stroma, and immune-cell accumulation. Finally, CurvSee extended this framework to multiplexed protein imaging, where combined morphology and protein-expression features distinguished Gleason-associated gland states. Together, CurvSeq and CurvSee provide a quantitative framework for linking gland architecture, local microenvironment, and molecular state, showing that prostate gland morphology can be integrated with spatial omics to identify morphomechanical niches associated with cancer progression.

systems biology↗

bioRxiv2026

Age-Related Increases in 40Hz Neural Synchrony Are Specific to Typical Development: A Cross-Sectional Study of Autism Spectrum Disorder

Background: The 40Hz auditory steady-state response (ASSR) is a measure of gamma-band neural synchrony sensitive to excitation-inhibition (E/I) balance. Disruptions to E/I balance have been implicated in autism spectrum disorder (ASD), making ASSR an efficient tool for investigating neural synchrony development in this population. Whether age-related differences in 40Hz ASSR are detectable across development in ASD remains understudied. Phelan-McDermid syndrome (PMS), a rare genetic disorder with a phenotype overlapping with autism, caused by SHANK3 disruption, provides a genetically defined model for further investigating E/I-related neural synchrony disruptions. Methods: We examined 40Hz inter-trial phase coherence (ITPC) as an index of neural synchrony across a wide age range (2-37 years) in 127 participants from four groups: TD (n=43), ASD without intellectual disability (w/o ID; n=37), ASD with intellectual disability (w/ID; n=24), and PMS (n=23). Given the distinct age and cognitive profiles of ASD subgroups in this sample, analyses were conducted in separate models: TD vs. ASD w/o ID across all ages, and TD vs. ASD w/ID vs. PMS restricted to participants under 18. Results: For the first time in a cross-sectional sample spanning a large age range, we show that 40Hz ITPC increases significantly with age in TD individuals, while this developmental trajectory is absent in ASD without intellectual disability. Among children and adolescents under 18, 40Hz ITPC did not differ across TD, ASD w/ID, and PMS, and IQ did not predict ITPC in clinical groups. A post-hoc analysis revealed higher ITPC in TD males than females, with no sex differences in ASD or PMS. Conclusions: We demonstrate that gamma-band ITPC trajectories diverge between TD and ASD, specifically in adulthood, with no such difference detectable in childhood. No significant group differences were found among TD, ASD w/ID, and PMS individuals under 18. These findings highlight the importance of age as a critical variable when measuring ASSR, and underscore the need for lifespan studies, particularly in genetically defined conditions such as PMS, to determine whether similar divergence emerges in adulthood.

neuroscience↗

bioRxiv2026

BCL11B predetermines a persister state in breast cancer that is reversed by TNFα

The frequent development of chemoresistance in cancer presents a significant clinical challenge, yet the underlying causes for heterogeneous drug responses remain largely elusive. Here, we systematically assessed the cellular differentiation status of human breast cancer cells utilizing single-cell atlases and identified a distinct population of immature basal-like cancer cells marked by BCL11B. Notably, higher levels of BCL11B+ cancer cells are significantly associated with early relapse in breast cancer patients who received chemotherapy. Functioning as a central regulator, BCL11B delineates an immature cell state that preferentially transitions to a drug-resistant persister state during treatment through multiple pre-existing and adaptive drug-resistance programs. Importantly, the cytokine tumor necrosis factor alpha (TNF) is revealed as a natural inhibitor of BCL11B and can directly reverse the emergence of chemoresistant persister cells. Therefore, we identify BCL11B as an unappreciated pre-determinant of drug response and a therapeutic target for a subset of breast cancer patients at high risk of developing chemoresistance.

Cancer Biology↗

bioRxiv2026

Magnetically guided macrophage immunobots coordinate iron-metabolic cascades and immunogenic ferroptosis for tumor immunotherapy

Adoptive cell therapy (ACT) remains challenging in solid tumors, where poor tumor infiltration, metabolic heterogeneity, and an immunosuppressive tumor microenvironment (TME) constrain therapeutic efficacy. Here, we developed a magnetically actuated macrophage-based immune microrobot (immunobot) for active solid tumor immunotherapy. Immunobots were constructed by loading bone marrow-derived macrophages (BMDMs) with lipopolysaccharide-modified Janus L1-FePt magnetic microrollers (LMRs), enabling hard-magnetic actuation. Optimized LMR loading supported robust propulsion, retention under flow, and enhanced barrier penetration. LMRs further promoted M1-like polarization through LPS-driven inflammatory activation and FePt-derived labile iron-amplified oxidative stress, with altered iron homeostasis, increased reactive oxygen species (ROS), and enhanced NF-{kappa}B signaling. Immunobots also induced ferroptosis-associated immunogenic cell death in tumor cells. In vivo, magnetically guided immunobots suppressed tumor growth, reprogrammed tumor-associated macrophages (TAMs), promoted dendritic cell maturation, and enhanced CD8 T cell activation. This work establishes a microrobotic immunotherapy platform for active magnetic transport, iron-metabolic regulation, and immune remodeling in solid tumors.

bioengineering↗

bioRxiv2026

Comprehensive Complete-Genome Analysis of Lactobacillaceae and Bifidobacteriaceae Reveals Strain-Specific Metabolic Interactions in Chinese Gut Microbiota

Bifidobacteriaceae and Lactobacillaceae are key probiotic families and widely used in food production, yet a comprehensive understanding of strain functions and their gut microbial interactions based on complete genomes remain understudied. Here we constructed a complete-genome dataset of 3,300 strains from these two families, including 1,151 newly isolated from China. Compared with draft assemblies, complete genomes substantially recovered a gene functional landscape encompassing stress tolerance, surface exopolysaccharide synthesis, nutrient utilization, and mobile genetic elements. Major species from both families exhibited a prevalence >60% in the Chinese population, far higher than that in US/Dutch cohorts. Notably, as a core probiotic species with remarkable genomic plasticity and gut-adaptive potential, Lactiplantibacillus plantarum stood out in our dataset for its enriched functional profile and was particularly abundant in the Chinese population. Moreover, compared with non-Chinese genomes, our isolates of key species displayed less metabolic complementarity and stronger competition with potentially pathogenic keystone species in the gut, thereby linking strain origin to enhanced probiotic potential and ecological fitness to benefit human gut health.

microbiology↗

bioRxiv2026

Coordinated phase separation and phase transition underlie synaptic ribbon condensate formation and plasticity

Mesoscale molecular apparatuses with diverse functions are widespread in cells. How mesoscale cellular apparatuses are formed and regulated is poorly understood. The synaptic ribbon in sensory neurons, which can dynamically adjust its size and shape in response to light or sound, is a mesoscale molecular assembly. In this study, we demonstrate that RIBEYE, the backbone protein of synaptic ribbons, via combined ordered and disordered interactions, forms micron-sized dynamic molecular assemblies. Integrated cryo-electron microscopy and tomography studies revealed that the N-terminal SAM domain and the C-terminal B domain of RIBEYE form distinct nanoscale filaments and further assemble into ribbon-like architectures via phase transition. Unexpectedly, the N-terminal intrinsically disordered region of RIBEYE softens the solid mesoscale ribbon structures via phase separation. The mesoscale size and shape of the RIBEYE condensate are bidirectionally tuned by physiological modulators such as Piccolino and CtBP1, linking synaptic ribbon structural plasticity to functional adaptability. Thus, our study demonstrates that combined phase transition and phase separation of nanoscale protein oligomers can build mesoscale functional cellular apparatuses.

biochemistry↗

bioRxiv2026

Tartrazine clears live cells while preserving viability at high refractive indices and osmolality

Tissue-clearing techniques have transformed optical imaging of fixed specimens, yet their application to living systems remains limited by toxicity and removal of key tissue components. We recently demonstrated that absorbing molecules such as tartrazine can reversibly render live mouse skin transparent. Subsequently, it was reported that isotonic protein solutions can achieve ex vivo and in vivo cellular clearing. However, discrepancies remain regarding the optimal refractive index (RI) for live-cell clearing and the impact of elevated osmolality on cell viability. Here, using cultured mammalian cells, we systematically examine the dependence of optical contrast on medium RI and the effects of hyperosmolality. We find that, contrary to the recent report of an optimal RI of 1.36[~]1.37 for suspended cells, densely-packed adherent cells exhibit a monotonic decrease in phase contrast up to an RI of 1.41 with tartrazine. Moreover, even under highly hyperosmotic conditions ([~]1200 mOsm/kg), cultured cells exhibit minimal deformation and negligible loss of viability for up to 30 min in the clearing solution. These results demonstrate that tartrazine enables effective live-cell clearing at RI up to 1.41 while preserving viability under elevated osmolality, and motivate future studies to define optimal conditions for in vivo optical clearing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=44 SRC="FIGDIR/small/717314v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@1ec9fbforg.highwire.dtl.DTLVardef@1ebe9e6org.highwire.dtl.DTLVardef@1492c3corg.highwire.dtl.DTLVardef@f75559_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

Identifying Phelan-McDermid-Like Electrophysiological Subtypes in Autism Using EEG and Machine Learning

BackgroundPhelan McDermid syndrome (PMS), caused by SHANK3 haploinsufficiency, is a genetic form of autism spectrum disorder (ASD) that provides a genetically defined model for studying ASD-related circuit dysfunction. SHANK3 mutations disrupt synaptic organization and cortical synchrony, leading to attenuated gamma-band auditory steady-state responses (ASSRs). We investigated whether PMS-related electrophysiological signatures could be identified using machine learning and whether similar patterns are present in a subset of individuals with idiopathic ASD (iASD). MethodsEEG recorded during a 40-Hz ASSR paradigm was collected from 123 participants (42 TD aged 2-30, 56 iASD aged 3-31, 25 PMS aged 2-26). We extracted time-series, ERSP, FOOOF-derived spectral, and intertrial phase coherence (ITPC) features. XGBoost models with leave-one-out cross-validation classified PMS versus TD; the best age/sex-adjusted ITPC model was then applied to iASD participants to derive a Synchrony Atypicality Index (SAI). Unsupervised clustering of high-dimensional ITPC features was also performed. ResultsITPC-based models showed the strongest discrimination between TD and PMS participants (AUROC = 0.83). When applied to iASD participants, 35.7% exhibited elevated SAI, indicating a PMS-like gamma-band phase-locking profile. Classification of iASD versus PMS performed poorly in the full sample but improved markedly after excluding high-SAI iASD individuals, consistent with substantial heterogeneity within iASD. Unsupervised clustering of ITPC features identified PMS-enriched clusters that also captured high-SAI iASD participants. Results were consistent after controlling for age in sensitivity analyses. ConclusionsReduced 40-Hz ITPC is a mechanistically interpretable electrophysiological signature of PMS and identifies a biologically meaningful PMS-like subgroup within iASD, supporting biomarker-guided stratification.

neuroscience↗

bioRxiv2026

A postnatal human lung developmental atlas reveals windows of genetic vulnerability to chronic lung disease

At birth, the lungs undergo an abrupt physiologic change, as the function of gas exchange transitions from the placenta to the lung. Subsequent postnatal development of the lungs is marked by a rapid and profound increase in the growth of the distal airways and alveolar gas exchange compartment. Insults during this period increase the risk of developing lung disease later in life, though how early-life events affect adult disease onset remains unclear. We generated a single-cell atlas of postnatal human lung development from birth through adulthood and mapped temporally regulated gene expression changes in each cell lineage. Using this atlas, we identified disease risk-associated genes with developmentally regulated expression. These analyses reveal cell type-specific and temporally restricted expression of genes associated with adult lung disease risk, including COPD. Heritability enrichment analysis demonstrated that COPD genetic risk is enriched in genes active during early postnatal endothelial development, linking early-life vascular maturation to adult disease susceptibility. These findings characterize the early window of susceptibility for adult chronic lung diseases and establish a framework to guide mechanistic studies of disease-associated genes.

developmental biology↗

bioRxiv2026

VarDCL: A Multimodal PLM-Enhanced Framework for Missense Variant Effect Prediction via Self-distilled Contrastive Learning

Missense variants are a common type of genetic mutation that can alter the structure and function of proteins, thereby affecting the normal physiological processes of organisms. Accurately distinguishing damaging missense variants from benign ones is of great significance for clinical genetic diagnosis, treatment strategy development, and protein engineering. Here, we propose the VarDCL method, which ingeniously integrates multimodal protein language model embeddings and self-distilled contrastive learning to identify subtle sequence and structural differences before and after protein mutations, thereby accurately predicting pathogenic missense variants. First, leveraging sequence and structural information before and after mutations, VarDCL generates sequence-structural multimodal features via different language models. It incorporates both global and local perspectives of feature embeddings to provide the model with dynamic, multimodal, and multi-view input data. Additionally, a Self-distilled Contrastive Learning (SDCL) module was proposed to enable more effective information integration and feature learning, enhancing the models ability to detect sequence and structural changes induced by mutations. Within this module, the multi-level contrastive learning framework excels at capturing information differences before and after mutations within the same modality; meanwhile, the feature self-distillation mechanism effectively utilizes high-level fused features to guide the learning of low-level differential features, facilitating information interaction across different modalities. The VarDCL framework not only ensures the models capacity to learn dynamic changes pre- and post-mutation but also significantly improves cross-modal information interaction between sequence and structure, thereby remarkably boosting the models performance in distinguishing pathogenic mutations from benign ones. To validate the effectiveness of VarDCL, extensive experiments were conducted. The ablation study demonstrates that all key components of VarDCL contribute significantly. On an independent test set containing 18,731 clinical variants, VarDCL achieved an AUC of 0.917, an AUPR of 0.876, an MCC of 0.690, and an F1-score of 0.789, outperforming 21 state-of-the-art existing methods. Benchmark analysis shows that VarDCL can be utilized as an accurate and potent tool for predicting missense variant effects.

bioinformatics↗

bioRxiv2026

Unravelling genome-wide mosaic microsatellite mutations at single-cell resolution

Short tandem repeats (STRs), or microsatellites, are highly mutable genomic elements that modulate gene regulations and are implicated in a range of human diseases. However, detecting mosaic STR mutations at single-cell resolution remains challenging due to both technical and biological complexities. To address this, we developed BayesMonSTR, a robust algorithm that enables accurate detection of mosaic STR mutations. Using this tool in single-cell analysis of human tissues, we reveal an accumulation of longer mosaic STR insertions and deletions (indels) in aging mitotic and post-mitotic cells. Strikingly, prefrontal cortex (PFC) neurons accumulate a higher burden of STR mutations than B cells or lung epithelium, with aged neurons exhibiting a particularly pronounced increase in longer STR deletions. These mutations are enriched at transcription start sites (TSSs) and active enhancers of highly expressed genes. Our work establishes a foundation for genome-wide, hypothesis-free discovery of disease-associated mosaic STR mutations and reveals a previously unexplored landscape of mosaic STR variation in development and aging.

bioinformatics↗

bioRxiv2026

MtDNA heteroplasmy controls tumor immune reprogramming through mitochondrial translation

Mitochondrial DNA (mtDNA) mutations are among the most frequent genetic alterations in human cancers, yet their molecular mechanisms in shaping tumor progression and metastasis under physiological conditions remain poorly understood. Here, we show that mtDNA heteroplasmy acts as a tumor cell-intrinsic rheostat that orchestrates fate decisions between progression and suppression. Moderate heteroplasmy induces a ribosomal storm of mitochondrial translation and ribosome biogenesis, driven by leucyl-tRNA synthetase 2 (LARS2). This response enhances metabolic fitness and licenses the secretion of S100A8/A9, enabling tumor cells to actively remodel the immune microenvironment through recruitment of myeloid-derived suppressor cells and exclusion of CD8 T cells, thereby promoting immune evasion and metastatic progression. In contrast, high heteroplasmy impairs tumorigenesis due to oxidative phosphorylation collapse. Disruption of LARS2, mitochondrial translation, or S100A9 signalling abrogates tumor progression. Our findings establish mtDNA heteroplasmy as a key regulator of cancer evolution, linking mitochondrial genetic variation to immune modulation, and reveal the LARS2-mitochondrial translation-S100A8/A9 axis as a therapeutically targetable programme within the pro-tumorigenic window of mtDNA heteroplasmy.

cancer biology↗

bioRxiv2026

Machine Learning Ensemble Reveals Distinct Molecular Pathways of Retinal Damage in Spaceflown Mice

BackgroundSpaceflight-associated neuro-ocular syndrome (SANS) poses significant risks to astronaut visual health during long-duration missions, yet its underlying molecular mechanisms remain incompletely understood. Oxidative stress and apoptosis are candidate molecular drivers, but their transcriptomic signatures in spaceflight-exposed retinal tissue have not been systematically characterized. MethodsWe applied a machine learning ensemble of linear regression models to predict two ocular phenotypes: 4-hydroxynonenal (4-HNE) immunostaining as a marker of lipid peroxidation-mediated oxidative damage; and TUNEL positivity as a marker of apoptotic cell death. In this observational study, we use bulk retinal gene expression data obtained from a controlled experiment with ground control and spaceflown mice to predict these phenotypes. Gene Ontology pathway enrichment was performed on the most predictive gene sets for each phenotype. ResultsThe 4-HNE phenotype was predicted by genes that converge on membrane-associated pathways, photoreceptor protein modification, synaptic dysfunction, and extracellular matrix dysregulation, including B2m, Tf, Cnga1, mt-Nd1, Snap25, and Efemp1. The genes predicting the TUNEL phenotype revealed a distinct signature emphasizing stress-induced apoptosis, rod photoreceptor degeneration, and endoplasmic reticulum dysfunction, with Ddit4, Nrl, Rom1, Reep6, and Gabarapl1 emerging as central regulators. ConclusionsOxidative lipid peroxidation and apoptotic cell death represent complementary and molecularly distinct pathological mechanisms in spaceflight-exposed murine retinal tissue. The gene signatures provide a putative molecular framework for developing noninvasive biomarkers and therapeutic targets to monitor and protect astronaut visual health during long-duration and deep-space missions.

bioinformatics↗

bioRxiv2026

SnapG: An Automated Tool for Myelin g-ratio Measurement with Batch Processing Capability

The g-ratio, calculated as the axon diameter divided by the total myelinated fiber diameter, is widely used to assess the degree of myelination in the central and peripheral nervous systems. Changes in g-ratios accompany demyelinating, hypomyelinating, and remyelinating conditions, and can also result from activity-dependent, adaptive myelination. Although manual tracing from electron micrographs has been the gold-standard to measure g-ratios, this process is laborious and limits throughput. To address this challenge, we developed SnapG, an automated and user-friendly software tool to streamline g-ratio analysis from electron micrographs. SnapG implements an end-to-end pipeline for axon and myelin segmentation on EM images. The tool integrates robust segmentation and post-processing steps to extract axon and fiber diameters and generates both per-image and cohort-level summary statistics. SnapG produces g-ratio distributions that agree well with expert manual annotations and established tools across imaging modalities. It reduces user intervention, supports large image and batch processing, and achieves faster processing times while delivering accurate, reproducible measurements. SnapGs automated reporting thereby facilitates high-throughput analyses and improves consistency across experiments. SnapG can accelerate studies of myelin biology and provides a practical alternative to existing tools.

neuroscience↗