Biology subjects

Lin, M.

Publications and source records attributed to Lin, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

A Fourfold Male-Specific Lifespan Extension via Canonical Insulin/IGF-1 Signaling

Aging is a universal biological process driven by conserved genetic networks that balance somatic maintenance with growth and reproduction. The insulin/insulin-like growth factor I signaling pathway is a central architect of this balance, and inhibiting its activity has long been established as a primary mechanism to extend lifespan across diverse species. However, our understanding of this pathways limits has been constrained by a historical focus on hermaphroditic models, which inherently link longevity extensions to a rigid trade-off involving immense reproductive costs and restricted somatic growth. Here we show that the latent potential of this canonical aging pathway is profoundly amplified by male-specific biology. We demonstrate that a classic insulin receptor mutation extends male survival to an unprecedented extreme, vastly surpassing the established benchmarks of the field. We reveal that this extraordinary lifespan expansion remains strictly dependent on the canonical FOXO transcription factor, yet it fuels a male-specific metabolic reprogramming that uncouples aging from stunted growth--massively accumulating neutral lipids to support sustained somatic preservation. These findings establish biological sex as a primary determinant of longevity potential and provide a new framework for identifying hidden, sex-specific mechanisms capable of promoting extreme healthy longevity.

physiology↗

bioRxiv2025

High-resolution MRI Guided Whole Mouse Brain Cell Type Atlas using Deep Learning

Cell types represent groupings of cells defined by shared anatomical and functional properties. Traditional mouse brain cell atlases rely heavily on single-cell sequencing, which provides valuable molecular detail but lacks whole-brain, isotropic resolution. Diffusion MRI (dMRI) offers a complementary approach for probing cytoarchitecture and myeloarchitecture, with quantitative metrics increasingly used as biomarkers of brain development and neurodegenerative disorders. Although prior work has linked dMRI metrics with gene expression, the capacity of dMRI to directly predict cell types remains unclear. Here, we present a deep learning framework that integrates high-resolution dMRI with three-dimensional light-sheet microscopy (LSM) registered to the Allen Mouse Brain Common Coordinate Framework (CCFv3). We investigated correlations between dMRI and spatial transcriptomics-derived cell types and generated a whole-brain cell type atlas at 10 {micro}m isotropic resolution. Together, these results establish an efficient, high-resolution strategy for brain cell atlas generation and underscore the potential of advanced imaging to illuminate cellular mechanisms of the brain.

neuroscience↗

bioRxiv2025

Spatial Conformation of Pancreatic Cancer Is Associated with Disease Recurrence after Curative-Intent Total Neoadjuvant Therapy

Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after total neoadjuvant therapy (TNT) and curative-intent resection. Traditional histopathologic response assessments demonstrate that major pathologic response (<5-10% viable residual cancer) is associated with favorable outcomes. However, most TNT cases achieve only a minor response. We investigated whether the spatial organization of residual PDAC encodes clinically meaningful biology beyond residual tumor burden. In a retrospective cohort of 203 resected PDAC patients, all with minor pathologic response, H&E whole-slide images were segmented into cancer and stroma to subsequently quantify spatial composition (e.g., patch size/density, edge density) and configuration (e.g., patch complexity/compactness, spatial intermixing) to model treatment-resistant tumor architecture. Non-response was associated with a more fragmented interface-rich ecology, higher edge density and diversity, and reduced homotypic aggregation, independent of conventional clinicopathologic features. This demonstrates a link between emergent tissue architecture of treated PDAC and therapeutic resistance. Further, two multivariable, spatial risk models were independently associated with disease-free survival (DFS): (1) cancer mean shape index and stromal shape-index variability (high-risk median DFS 7.23 vs 11.57 months; adjusted HR 1.75, p=0.007) and (2) mean stromal area with edge density (high- vs low-risk adjusted HR 1.94, p=0.006), outperforming traditional treatment response assessments. Quantifying residual cancer-stroma topology thus yields independent, prognostic signals in post-TNT PDAC and motivates prospective, spatially informed adjuvant strategies and mechanistic studies of edge habitats and mixing as therapeutic vulnerabilities.

cancer biology↗

bioRxiv2025

Odyssey: reconstructing evolution through emergent consensus in the global proteome

We present Odyssey, a family of multimodal protein language models for sequence and structure generation, protein editing and design. We scale Odyssey to more than 102 billion parameters, trained over 1.1 x 1023 FLOPs. The Odyssey architecture uses context modalities, categorized as structural cues, semantic descriptions, and orthologous group metadata, and comprises two main components: a finite scalar quantizer for tokenizing continuous atomic coordinates, and a transformer stack for multimodal representation learning. Odyssey is trained via discrete diffusion, and characterizes the generative process as a time-dependent unmasking procedure. The finite scalar quantizer and transformer stack leverage the consensus mechanism, a replacement for attention that uses an iterative propagation scheme informed by local agreements between residues. Across various benchmarks, Odyssey achieves landmark performance for protein generation and protein structure discretization. Our empirical findings are supported by theoretical analysis.

synthetic biology↗

bioRxiv2025

Adipose Tissue Overexpression of Nicotinamide Phosphoribosyltransferase Prevents Metabolic Dysfunction in Obese Mice

Nicotinamide adenine dinucleotide (NAD+) is a vital coenzyme and a central factor in energy metabolism. Nicotinamide phosphoribosyltransferase (NAMPT) maintains the cellular NAD+ pool by synthesizing the NAD+ precursor, nicotinamide mononucleotide (NMN), and diminished adipocyte NAMPT activity has been implicated in aging- and obesity-related metabolic dysfunction. Herein, we examined the effects of overexpressing or knocking out NAMPT in adipocytes on metabolic dysfunction and interorgan communication in mice. We generated new adipocyte-specific NAMPT overexpressing(ANOV) mice model. Male ANOV mice are protected from diet-induced metabolic dysfunction including adipose tissue inflammation, glucose intolerance, and insulin resistance. In contrast female ANOV mice were less protected from metabolic dysfunction, possibly due to higher endogenous expression of NAMPT in WT female mice. Livers of ANOV mice showed improved insulin signaling, increased NAD content, and reduced steatosis, suggesting that NAMPT regulates interorgan communication between adipocytes and hepatocytes. Extracellular vesicles (EV) isolated from ANOV mice enhanced insulin signaling in HepG2 cells and improved glucose tolerance in WT obese mice. In contrast, EV from ANKO mice suppressed HepG2 insulin signaling and inhibition of EV release improved glucose tolerance in ANKO female mice. Collectively, these data highlight a novel mechanism by which adipocyte NAD+ metabolism regulates systemic metabolic dysfunction via EVs.

physiology↗

bioRxiv2025

VesiclePy: A Machine Learning Vesicle Analysis Toolbox for Volume Electron Microscopy

Vesicles are critical components of neurons that package neurotransmitters and neuropeptides for their release, in order to communicate with other neurons and cells. However, due to their small size, the reconstruction of the full vesicle endowment across an entire neuronal morphology remains challenging. To achieve this, we have used, as a tool to identify and visualize vesicles, Volume Electron Microscopy (vEM), a method that has the nanoscale resolution to detect individual vesicle boundaries, content, and 3D locations. However, the large volume of vEM datasets poses a challenge in the segmentation, classification, and spatial analysis of tens of thousands of vesicles and their target cell in 3D. Here we report the development of VesiclePy, an integrated pipeline for automated segmentation, classification, proofreading, and spatial analysis of vesicles, relative to neuron masks in large-volume electron microscopy data. Our package integrates the efficiency of deep learning and the accuracy of human proofreading and provides a streamlined package in chunked processing and accurate indexing, localization, and visualization of single vesicle resolution in large vEM data. We demonstrate the viability of VesiclePy using high-pressure frozen serial EM data of Hydra vulgaris and quantify the performance of the package using ground truth manual annotations. We show that VesiclePy can process a multiterabyte serial EM dataset, efficiently annotate 53,851 vesicles from 20 complete neurons, and classify vesicles into 5 types. Each vesicle has a unique ID and 3D location for further spatial analysis in relation to neuron or non-neuronal targets nearby. Finally, by combining vesicle data and morphological information of each neuron, we can quantitatively cluster neurons into subtypes. VesiclePy is available at https://github.com/PytorchConnectomics/VesiclePy under an MIT license.

neuroscience↗

bioRxiv2025

marApp: An R package and web portal to calculate mutations- and genetic diversity-area relationship for conservation

International conservation policies including the Kunming-Montreal Global Biodiversity Framework now consider genetic diversity of wild species in their targets. However, scalable, theory-driven tools to assess and predict genetic diversity loss are still emerging, limiting their use in conservation planning. Analogous to the species-area relationship, recent work has shown that genetic diversity scales with area, described by the mutations-area relationship (MAR) or genetic-diversity-area relationship (GDAR), can approximate the genetic diversity loss in a species from habitat reduction. To enable application of these insights for conservation practitioners and policy makers, we present the mar R package and marApp web portal, a fast and user-friendly tool for MAR/GDAR analysis. The mar package connects genetic diversity patterns in space to ecological theory, and automates steps from reading genetic and geographic data to simulating various habitat extinction scenarios using MAR/GDAR. The mar package estimates only short-term genetic diversity, providing a lower-limit for the far greater long-term genetic losses, underscoring the need to maximize present-day habitat conservation before it becomes irreversible. As a case example, we showcase predictions of coral (Acropora sp.) genetic diversity loss from reef coverage impacts. We demonstrate the usage of marApp without requirements for prior genetics or coding experiences, and provide downloadable reports for conservation.

ecology↗

bioRxiv2025

Emergence of Genetic Sex Determination in an Environmentally Sex-Determined Animal

The evolution of genetic sex determination (GSD) from environmental sex determination (ESD) remains a fundamental issue in evolutionary biology. However, the mechanisms driving such a transition, particularly in its earliest stages, are largely unknown. Here, we report on a genetic variant in the ESD species, Daphnia pulex, in which structural variations and selection on chromosome have suppressed recombination. This suppression has facilitated the accumulation of antagonistic features of the two chromosome- haplotypes, resulting in heterozygosity and differentiation of the sex-determining gene Dfh on two haplotypes. Consequently, this process has driven the emergence of a mixed-mating system, in which sex determination is jointly regulated by genetic and environmental factors. Additionally, we detected ongoing divergence in chromosomal structure between the two haplotypes at the population level. These findings suggest that processes analogous to early sex-chromosome evolution are occurring in this ESD species, offering novel insights into the molecular mechanisms underlying the emergence of GSD.

evolutionary biology↗

bioRxiv2025

The Brain/MINDS 3D Digital Marmoset Brain Atlas Version 2.0: Population-based Cortical Region Parcellations with Multi-Modal Standard Templates

We present our new Brain/MINDS 3D digital marmoset brain atlas version 2.0 (BMA2.0), a population-based 3D digital brain atlas of the common marmoset (Callithrix jacchus), designed to overcome the limitations of previous single subject atlases that are prone to structural biases arising from individual variation. Here, manually delineated cortical regions from 10 myelin-stained brains were used to create a generalized cortical parcellation. Newly refined subcortical regions from a previous atlas and a completely new cerebellum parcellation were also incorporated, resulting in a comprehensive whole brain parcellation for both hemispheres. To facilitate multimodal data analysis, the atlas package includes co-registered average templates for myelin and Nissl staining from the same individuals, ex vivo MRI T2 (91 individuals), and in vivo MRI T2 (446 individuals). Cortical flat maps and pial, cortical mid-thickness, and white matter surfaces are also provided. BMA2.0 provides a central brain space for multimodal data integration, spatial analysis, and comparative neuroscience. Standard formats and transformations are provided for easy integration into existing workflows and interoperability with existing atlases.

neuroscience↗

bioRxiv2025

Endothelial LRRC8C associates with LRRC8A and LRRC8B to regulate vascular reactivity and blood pressure

Vascular tone is impacted by the endotheliums ability to detect mechanical and chemical stimulation. Leucine-Rich Repeat-Containing protein 8A, (LRRC8A), was previously identified as a required component of the mechanoresponsive endothelial LRRC8 complex regulating AKT-endothelial nitric oxide synthase (eNOS) signaling and vascular function. While LRRC8A is broadly expressed, LRRC8B, C, D and E have tissue-restricted expression. Here, we identified 2 single nucleotide polymorphisms (SNPs) in LRRC8C highly associated with elevated diastolic and systolic blood pressure in human genetic studies, implicating LRRC8C as a regulator of vascular function. While LRRC8A/B/C/D/E are expressed in endothelium, co-immunoprecipitation experiments from lung endothelium using Lrrc8a-3xFlag knock-in mice, Lrrc8c-HA knock-in mice and endothelium-specific Lrrc8a-3xFlag overexpression mice demonstrate the endothelial LRRC8 complex to be composed largely of LRRC8A/B/C heteromers. Lrrc8a/b/c knock-out studies in mice and knock-down studies in human umbilical vein endothelial cells show co-dependent expression of LRRC8A/B/C proteins, but not LRRC8D. Functionally, LRRC8A and LRRC8C depletion reduces endothelial volume regulatory anion channel (VRAC) currents, inhibits AKT-eNOS signaling, increases myogenic tone, impairs eNOS dependent vasodilation, and exacerbates angiotensin-induced hypertension. These data identify LRRC8A, LRRC8B and LRRC8C as components of the endothelial LRRC8 complex and reveal LRRC8C as having a non-redundant role in regulating endothelial AKT-eNOS, vascular relaxation and susceptibility to hypertension.

cell biology↗

bioRxiv2025

Metabolomics-Guided Machine Learning Reveals Diagnostic and Mechanistic Biomarkers in CHB with MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remains challenging, particularly in non-obese patients or those with subclinical features. This study aimed to identify metabolic signatures of CHB-related MASLD and construct a predictive model using untargeted metabolomics integrated with machine learning. MethodsSerum metabolomics was performed on 160 subjects (80 CHB + MASLD and 80 healthy controls). Differential metabolites were identified and analyzed using KEGG enrichment and 4 machine learning algorithms (Random Forest, XGBoost, SVM, and LASSO). Metabolite-clinical correlations and diagnostic model performance were evaluated. ResultsA total of 924 differential metabolites were identified, with significant enrichment in pathways related to the TCA cycle, sphingolipid metabolism, and amino acid turnover. Machine learning prioritized six robust and biologically relevant metabolites: L-aspartic acid, succinic acid, caproic acid, sebacic acid, monomenthyl succinate, and glycolaldehyde, which consistently distinguished CHB + MASLD patients from controls (AUC > 0.75). These metabolites reflect key disruptions in mitochondrial function, lipid oxidation, and redox homeostasis. Integrated models combining metabolomics with clinical indices achieved perfect classification (AUC = 1.000). ConclusionCHB-associated MASLD is driven by systemic metabolic remodeling centered on mitochondrial overload, oxidative stress, and impaired amino acid metabolism. The identified metabolites provide mechanistic insights and hold promise for non-invasive MASLD screening in CHB patients. This study underscores the potential of multi-algorithmic metabolomics in advancing early diagnosis and personalized management of complex liver comorbidities.

bioinformatics↗

bioRxiv2025

Mutant IDH silences GSX2 to reprogram neural progenitor cell fate and promote gliomagenesis

Isocitrate dehydrogenase (IDH) mutations arise early in gliomas and are associated with a defined neurodevelopmental cancer cell hierarchy. However, how mutant IDH contributes to this hierarchy and whether this interaction promotes gliomagenesis remain unclear. We captured the dynamics of IDH-mutant glioma initiation in genetically engineered mice through time-resolved, single-cell genomics. Mutant IDH activates and induces lineage switching of neural progenitor cells (NPCs). These actions expand oligodendrocyte precursor cells, the predominant cell-of-origin for these tumors, at the expense of interneurons. Lineage switching is mediated by promoter hypermethylation and silencing of Gsx2, a homeobox gene required for neurogenesis. Critically, Gsx2 ablation recapitulates NPC fate reprogramming by mutant IDH. We provide a new model of neural cell fate control by IDH oncogenes and insights into the developmental origins of glioma.

cancer biology↗

bioRxiv2025

The hidden predictors of human haematopoietic clonal fate

Human haematopoietic stem and progenitor cells (HSPCs) exhibit heterogeneous lineage output, but the molecular programs underlying clonal fate remain poorly defined. To address this, we developed a human haematopoietic organoid supporting differentiation into 15 lineages and used it to track barcoded HSPC clones over time. By integrating single-cell transcriptomes, surface phenotypes, and clonal fate, we applied machine learning to identify clonal fate modules - gene and marker signatures predictive of lineage commitment. This approach uncovered hidden transcriptional and surface correlates of multipotency, including CD200, which marked a subset of HSCs with broad output capacity, which we leveraged to increase manufactured type 1 dendritic cell purity for immunotherapy applications. Our study provides a framework for decoding clonal fate decisions in human HSPCs and identifies molecular features that distinguish truly multipotent clones, advancing strategies for stem cell purification and therapeutic engineering.

cell biology↗

bioRxiv2025

A sustained Hox program delineates brainstem neurons essential for breathing

Respiratory neurons in the brainstem must diversify and acquire unique properties during development to enable breathing at birth. Dbx1-expressing progenitors give rise to functionally and molecularly distinct excitatory respiratory populations, including rhythm-generating pre-Botzinger complex (preBotC) neurons and phrenic motor neuron (MN)-projecting rostral Ventral Respiratory Group (rVRG) neurons. These neurons are organized rostrocaudally within the ventral respiratory column (VRC) but, despite their critical functions in breathing, the mechanisms that control their organization and diversification are not well understood. Here, we generate a novel genetic tool to label brainstem neurons within the VRC. We find that rVRG neurons selectively express Hox5 genes through postnatal stages. Selective deletion of all Hox5 paralogs from Dbx1-derived neurons leads to respiratory dysfunction, perinatal death, and changes in the pattern and amplitude of phrenic MN firing. We show that Hox5 inactivation leads to a caudal expansion of putative preBotC neurons, likely at the expense of the rVRG. Collectively, our findings indicate that Hox5 proteins are required for the delineation and functional specialization of excitatory brainstem neurons essential for breathing.

neuroscience↗

bioRxiv2025

B cells specific for polyomavirus-derived oncoprotein are predictive of Merkel cell carcinoma progression

Merkel cell carcinomas typically arise from clonal integration of the Merkel cell polyomavirus. Immunogenic viral oncoproteins then lead to tumorigenesis. Oncoprotein-specific T cells are essential for anti-MCC immunity, but it is unclear whether B cells promote tumor control. Here, we analyzed the frequency and phenotype of viral oncoprotein-specific and total B cells in 47 blood samples and 19 unmatched tumors from MCC patients-- of which 8 out 19 progressed. The phenotype of blood B cells did not correlate with MCC patient outcomes. In contrast, all 11 patients with robust oncoprotein-specific antibody-secreting and/or germinal center B cells in tumors experienced long-term MCC control. In vitro, B cells engineered to be specific for viral oncoproteins increased the sensitivity of oncoprotein-specific CD4+ T cells by over 50-fold. Together, our findings suggest that cancer-specific B cells promote anti-tumor immunity via increased T cell responses and that cancer-specific B cell augmentation could be therapeutically relevant. Statement of SignificanceThe link between cancer-specific B cells in anti-tumor immunity and clinical outcomes remains poorly defined. Here, we show that tumor-associated B cells specific for a viral oncoprotein expressed in MCC patient tumors predict disease control with remarkable accuracy, establishing their potential as active participants in tumor immunity.

immunology↗

bioRxiv2025

A PAM-CNN recognition approach to Muscle Fatigue of Special Operators by sEMG signals

Fatigue operation was the primary accident causes of large special equipment which could lead to serious economic loss and personnel injury or death, so the establishment of early fatigue warning methods was of great significance to reduce the accident rate. In view of the working environment and biomechanics properties of operators of special equipment, theoretical and experimental method was presented to analyze the fatigue mechanism and accumulate data samples, and then a new approach was proposed to recognize muscle fatigue by classifying these datasets. Firstly, in order to deduce fatigue mechanism, hidden Markov chain was adopted to build five-element theoretical model for studying interaction between machines and operators muscles during operation process, so that influence factors and tested points of muscles were approached; Surface electromyographic (sEMG) sensors were introduced to acquire muscle signals which were taken as sample data, and wavelet packet was adopted to extract features of these data. Subsequently, a convolutional neural network (CNN) classification model based on partial attention mechanism (PAM) was proposed to execute triple fatigue classification, moreover cross entropy-Adam algorithm was applied to train and optimize this model. Finally, large crane operators were taken as case studies to verify the proposed model. By comparison results indicated when the number of extracted features was 3 and the size of patch was [5,5], PAM-CNN model could approach the optimum solution of fatigue recognition, and the average accuracy could achieve 95.6% in test datasets, which showed a good potential in practical application.

bioengineering↗

bioRxiv2025

A Universal RT-qPCR Method for DNA Aptamer Quantification

Aptamers are widely used in various applications; however, their quantification methods remain underdeveloped. In this study, we established a universal RT-qPCR-based method for DNA aptamer quantification. By incorporating reverse transcription, primers and probes could be added to aptamers, enabling their detection via qPCR (Figure 1). We developed a software tool for primer and probe design and optimized the reverse transcription process. Two aptamers, CD9-aptamer and CD63-aptamer, were selected as model systems representing two distinct aptamer types: the CD9-aptamer contains an intrinsic primer-binding site within its sequence, whereas the CD63-aptamer does not. Using this method, the limit of detection (LOD) for CD9-aptamer reached 10-14 M, while the LOD for CD63-aptamer was 10-12 M. Compared to existing quantification methods, this approach significantly improves accuracy and cost-effectiveness. Additionally, the method supports SYBR Green, TaqMan, and one-step RT-qPCR assays, broadening its applicability and enhancing precision for various aptamer-based applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/662296v1_fig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@44ec4corg.highwire.dtl.DTLVardef@f59184org.highwire.dtl.DTLVardef@2480fdorg.highwire.dtl.DTLVardef@906845_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Schematic illustration of RT-qPCR-Based Aptamer Quantification. C_FIG

molecular biology↗

bioRxiv2025

Two closed systems for long-term propagation of the marine tunicate Botryllus schlosseri isolated from natural seawater

Advanced methodologies for Botryllus schlosseri artificial seawater systems are needed to decrease dependency of large-scale culture on natural seawater and expand use of this important new model organism to more inland laboratories. We constructed two botryllid tunicate customized closed aquaculture systems, a static system consisting of lightly aerated jars fed with commercial filter feeder diet, and a recirculating aquaculture system (RAS) consisting of standard marine RAS components fed live microalgae and zooplankton diets. Initially, static tunicate culture yielded exponential growth in contrast to the RAS system, which yielded poor survival and negligible growth. Modifications were made to the RAS system to improve water treatment proficiency that greatly improved tunicate survival and growth. Experiments were performed isolating feed and water type as variables that differed between the static and RAS systems to evaluate their effects. A live feed combination achieved five-fold greater growth relative to a commercial concentrate diet. B. schlosseri maintained in optimized RAS water achieved two-fold faster growth relative to animals maintained with freshly prepared artificial seawater indicating that the RAS water was beneficial to the animals. Feeding frequency of the RAS system was increased from three times per week to daily. The RAS system and procedural modifications resulted in comparable growth rates in the static and RAS systems. Both optimized systems are suitable for long-term propagation and sustenance of botryllid tunicate populations supporting both sexual and asexual modes of reproduction with a current residence time of over 24 months.

zoology↗