Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 145 records · Page 8Linked to original sources

bioRxiv2025

Position-dependent effects of SCN2A premature stop codons on neuronal excitability and behavior

SCN2A encodes the voltage-gated sodium channel NaV1.2, a key determinant of spike initiation and propagation in glutamatergic neurons. Premature termination codons are often assumed to produce uniform haploinsufficiency via nonsense-mediated decay, yet whether distinct SCN2A premature stop codons yield equivalent molecular, cellular, and behavioral outcomes remains unknown. We generated two mouse lines carrying patient mutations--Scn2aY84X/+ (p.Tyr84UAA; early coding sequence) and Scn2aR1627X/+(p.Arg1627UGA; terminal coding exon)--on a C57BL/6J background. Allele-specific expression was quantified by targeted next-generation sequencing of whole-brain reverse transcribed cDNA. NaV1.2 protein was measured in half-brain lysates by automated western blot and ex vivo whole-cell recordings were obtained from layer 5b pyramidal-tract neurons in medial prefrontal cortex. A panel of behavioral assays assessed locomotion/exploration, motor learning, anxiety-like behavior, sociability, sensorimotor gating, and seizure susceptibility. Allele-specific RNA handling diverged by position: mRNA carrying Y84X engaged partial nonsense-mediated decay, whereas R1627X transcripts were at allelic balance. Despite this difference in RNA fate, NaV1.2 protein was comparably reduced in both lines. Electrophysiologically, both premature termination codon mutations slowed the action-potential upstroke, with a larger decrement in Scn2aY84X/+than in Scn2aR1627X/+. Spike threshold was depolarized only in Scn2aY84X/+, whereas Scn2aR1627X/+ remained similar to wild type. Frequency-current relations showed reduced firing at near-rheobase inputs in both mutants, with responses approaching wild type at stronger currents. Behaviorally, locomotion, sociability, and sensorimotor gating were preserved. Both lines exhibited increased grooming--consistent with restrictive, repetitive behavior; Scn2aY84X/+alone showed greater exploration in the elevated-risk context and a male-predominant deficit in rotarod learning. In maximal electroshock testing, mortality was lower in both lines without differences in seizure threshold or severity. Our results show that distinct SCN2A premature termination codons are not equivalent to one another, nor to a uniform haploinsufficient state. An early, nonsense-mediated decay-competent premature stop codon (Y84X) and a terminal-exon one (R1627X) produce partially overlapping yet allele-specific effects on neuronal excitability and behavior. These findings establish premature termination codon position as a determinant of phenotype, supporting allele-tailored mechanistic studies and therapeutic strategies.

neuroscience↗

bioRxiv2025

Decoding the Oral Microbiome: Metagenomic Insights into Host Metabolic Health

The oral microbiome may capture system-specific information about host metabolic health, yet large-scale, multi-system evidence remains scarce. We analyzed 9,431 participants in the Human Phenotype Project (HPP), integrating buccal-swab oral whole-metagenome profiles with 44 metabolic measures spanning liver ultrasound, continuous glucose monitoring (CGM), and dual-energy X-ray absorptiometry (DXA). Using a microbiome-wide association study (MWAS) framework, we constructed a multilayer map across strains, gene families and pathways, revealing widespread associations: 213 strains, 124,603 gene families and 299 pathways were significantly associated with metabolic measures. Prioritizing the strongest and cross-phenotype signals, we identified multiple oral features with most significant associations to metabolic health. For example, acyl carrier protein (ACP) was associated with lower liver inflammation and reduced adiposity, whereas polyamine biosynthesis and ceramide -oxidation tracked higher glucose variability and adverse liver and adiposity phenotypes. Leveraging these MWAS-derived signals, we trained disease classification models using phenotype-selected oral features, which outperformed full-feature oral models across six metabolic diseases. These association signals were also robust in oral-health sensitivity analyses in HPP, and key BMI and waist-circumference associations directionally replicated at the genus level in an independent cohort (n = 20,293). Together, these findings provide a population-scale oral-metabolic association map and highlight the potential of oral microbial markers as non-invasive tools for metabolic risk stratification.

microbiology↗

bioRxiv2025

Proinflammatory circulating extracellular vesicles from type 1 diabetes patients contribute to beta cell cytotoxicity and disease pathogenicity

In Type 1 diabetes (T1D), {beta}-cell loss and autoimmunity initiate years before disease diagnosis. However, the mechanisms remain unknown. Here, we investigated the role and mechanisms of circulating extracellular vesicles (cEVs) on T1D pathogenesis and {beta}-cell cytotoxicity. We used cEVs isolated from healthy donors (HD), T1D, multiple autoantibody-positive (AAb+), pre- and post-islet transplantation T1D subjects, NOD-T1D mice, and T1D PBMCs. Patient T1D-cEVs significantly induced apoptosis in vitro in human {beta}-cells but not -cells compared to HD-cEVs. cEVs from AAb+ subjects and pre-diabetic mice were cytotoxic, demonstrating that cEV-induced {beta}-cell cytotoxicity precedes T1D onset and diagnosis. cEV reduction in prediabetic NOD-T1D mice improved {beta}-cell health implying cEV contribution to T1D development. Proteomic analysis of patient T1D-cEVs found several proinflammatory proteins, including interferon gamma, which induced {beta}-cell cytotoxicity. Our data using cEVs from pre- and post-islet transplant and PBMC-EVs from T1D patients implicated immune cells as a potential cellular source of cytotoxic cEVs in T1D. Collectively, our data using T1D patient samples coupled with studies in mice demonstrate that cEVs contribute to {beta}-cell cytotoxicity and to the progression of T1D pathogenicity. Our study is one of the first to demonstrate a functional role of the proinflammatory cEV protein cargo on glucose homeostasis, {beta}-cell health, and insulitis. Our studies on T1D-cEVs may lead to discovery of novel biomarkers and therapeutic targets for T1D.

cell biology↗

bioRxiv2025

A Nanoscale Jitterbug Transformer from DNA

Many viruses have intricate polyhedral shells capable of symmetric transformations in response to external stimuli to initiate payload release. Such deployable auxetic nanostructures are not available in the synthetic realm. Here we present a nanoscale Jitterbug transformer using DNA origami that can reconfigure its structure upon chemical and optical signals while maintaining a Poissons ratio of -1. By leveraging molecular dynamics simulations, we design the Jitterbug DNA to form a compact octahedron by storing elastic energy and spontaneously transition into an expanded cuboctahedron by releasing it. DNA transformers are explored like viruses that can create nanopores on lipid membranes and regulate payload release into vesicles. This work integrates programmable DNA self-assembly with free-energy-guided mechanical design, providing a pathway toward adaptive nanomaterials with potential in synthetic organelles and stimuli-responsive nanodevices.

biophysics↗

bioRxiv2025

FlashRNA: An Efficient Model for Regulatory Genomics

Transformer-based genomic sequence-to-function models effectively capture long-range genomic interactions but incur high computational costs due to the quadratic complexity of their self-attention layers. In this work, we introduce FlashRNA, which significantly improves computational and memory efficiency through FlashAttention, advancements in model architecture, and optimized training setup. FlashRNA achieves comparable or slightly improved predictive performance compared to similar sized Borzoi or Flashzoi models, notably without depending on pre-trained weights - a major limitation of Flashzoi. Remarkably, we trained FlashRNA from scratch in one day on a single GPU, significantly accelerating training and inference speed. These improvements can facilitate further developments in models for regulatory genomics by reducing computational cost. We demonstrate this in two downstream applications: 1) we train a large ensemble of 16 FlashRNA models and distill them into a single model to improve performance while maintaining efficiency, and 2) we fine-tune FlashRNA on three prediction tasks - ChIP-seq, RNA half-life, and translation efficiency - achieving performance matching or exceeding state-of-the-art task-specific models. Code: https://github.com/deepgenomics/flashrna

genomics↗

bioRxiv2025

Machine learning-based definition of cellular senescence reveals pro-senescence potential implication in lung adenocarcinoma

Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell burden across cancer types continue to limit mechanistic studies and clinical translation. To address this, we developed the Predictive Cellular Senescence Model (PreCSenM), a machine learning-based tool that assigns a CS score by integrating senescence-associated features across 888 samples. Benchmarking analyses confirmed that PreCSenM markedly outperforms existing methodologies in reliably predicting senescent states within both normal and cancerous transcriptomic datasets. In lung adenocarcinoma (LUAD), PreCSenM identified the CS score as a robust predictor of clinical outcomes. Multi-omics analyses further revealed that lower CS levels correlate with decreased genomic stability and enhanced immune responses, aligning with clinical observations. Notably, drug discovery using PreCSenM identified histone deacetylase inhibitors (HDACis) as potent inducers of CS in LUAD. Transcriptional and epigenetic profiling of HDACi-treated cells pinpointed FOSB as a core transcription factor driving CS, and FOSB knockdown blocked HDACi-induced senescence. Overall, our study establishes PreCSenM as a multidimensional senescence quantification tool, bridging computational prediction with clinical relevance and mechanistic validation to enable senescence-directed therapies in precision oncology.

bioinformatics↗

bioRxiv2025

Beyond P-values: A Multi-Metric Framework for Robust Feature Selection and Predictive Modeling

High-dimensional biomedical datasets routinely contain sparse signals embedded among vast, correlated features, making variable selection central to building models that generalize. Although significance-based selection is widely used across modalities (e.g., imaging, EHR, multi-omics), statistical significance does not guarantee predictive utility, and vice versa. Yet few methods unify inferential and predictive evidence within a single selection framework. We introduce MIXER (Multi-metric Integration for eXplanatory and prEdictive Ranking), a domain-agnostic approach that integrates multiple selection metrics into one consensus model via adaptive weighting that quantifies each criterions contribution. Through simulation studies, we demonstrate that different selection metrics identified markedly different feature sets whose over-laps depended on the underlying feature distributions and signal strength. Applied to Alzhemiers disease in UK Biobank, MIXER outperformed every individual criterion, including statistical significance, and generalized to an external disease-specific cohort, Alzheimers Disease Sequencing Project, yielding higher discrimination and stronger risk stratification. The MIXER framwork is also modular and readily extends to other selection criteria and data modalities, providing a practical route to more accurate, interpretable, and transportable predictive models.

bioinformatics↗

bioRxiv2025

Cold sensing by a glutamate receptor drives avoidance behavior in Drosophila larvae

The ability to sense and avoid noxious environments is essential for animal survival; yet, how this is achieved at the behavioral, neuronal, and molecular levels is not well understood. Here, we use Drosophila larvae as a model to investigate how animals sense and avoid cold temperatures. By implementing custom-built thermoelectric devices capable of delivering rapid and precise thermal stimuli, we find that cold delivered to the larval head evokes robust escape behavioral responses. We identify a group of head-located cold-sensitive neurons as necessary and sufficient for such avoidance responses. We further demonstrate that the kainate-type glutamate receptor Clumsy acts as a novel cold sensor required for head cold sensitivity. Knockdown of Clumsy in head cold-sensing neurons suppresses their cold sensitivity. Heterologous expression of Clumsy confers cold sensitivity. Our results show that Drosophila larvae have evolved the capacity to detect and avoid cold temperatures through a previously uncharacterized cold-sensing mechanism.

neuroscience↗

bioRxiv2025

De Novo Design of Anti-Aging Peptides

Aging, a universal biological process in complex organisms, is increasingly recognized to be driven by progressive loss of epigenetic information, as proposed in the Information Theory of Aging (ITOA). However, research on anti-aging peptides remains scarce, with most existing efforts confined to derivatives of natural proteins, while systematic design attempts are virtually absent. This limitation not only restricts discovery within the evolutionary sequence space but also hampers the identification of candidates with novel mechanisms and improved efficacy. Here, we present ElixirSeeker2, the first computational framework for de novo design of anti-aging peptides. By integrating modeling of known anti-aging peptides, activity scoring from the IC50 database, and penalty constraints from toxic peptides, ElixirSeeker2 enables large-scale virtual screening and identification of novel peptide candidates. Several lead peptides demonstrated significant effects in delaying cellular senescence, restoring cellular functions in vitro and in enhancing locomotor activity of aged Caenorhabditis elegans. This study not only validates the feasibility of de novo design in anti-aging interventions but also establishes a strategy for the development of next-generation biologics.

bioinformatics↗

bioRxiv2025

Prolonged Starvation Drives Epigenetic Remodeling: Insights from DNA Methylation Profiling in the Aquatic Pathogen Flavobacterium columnare

Nutrient scarcity is a common environmental stressor encountered by bacteria. Despite its significance in bacterial virulence and physiology, the underlying epigenetic mechanisms of bacterial adaptation to prolonged starvation remain poorly understood. In this study, we utilized the latest Nanopore R10.4.1 sequencing technology to comprehensively characterize the genome-wide methylation landscape of the freshwater fish pathogen Flavobacterium columnare following long-term starvation at different temperatures. Our results revealed significant methylation plasticity under starvation conditions, characterized by distinct motif-dependent patterns. Notably, demethylation of the 6mA-modified CAYNNNNNRTG motif emerged as a robust epigenetic signature of starvation adaptation, with functional enrichment of genes involved in pathways for translation and metabolism, suggesting the role of this methylase in regulating essential cellular functions under starvation stress. Additionally, another 6mA-modified GCAGA motif exhibited temperature-dependent variation, indicating its potential role in temperature-specific response. Together, this study provides novel insights into the epigenetic mechanisms underlying the bacterial adaptation to nutrient deprivation and establishes a valuable methodological reference for bacterial epigenetics analysis utilizing advanced Nanopore sequencing technologies.

microbiology↗

bioRxiv2025

Hyperactivated Glycolysis Drives Spatially-Patterned Kupffer Cell Depletion in MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) progression is characterized by hepatic inflammation and cell death, yet the mechanisms underlying Kupffer cells (KCs) loss remain poorly understood. Here, we sought to elucidate the metabolic basis of KCs death during MASLD. Using metabolomics, immunostaining, and flow cytometry, we evaluated metabolic alterations and KCs death throughout early MASLD progression. We found that KCs death is an early hallmark of MASLD, exhibiting greater susceptibility and displaying a spatial distribution consistent with KCs zonation. Moreoever, KCs undergo progressive metabolic reprogramming toward enhanced glucose utilization during MASLD development, which is correlated with KCs death. In combination of biochemical agonist, isotope tracing and primary KCs culture, we further demonstrated that augmented glycolytic metabolism directly drives KCs death in vitro. Consistently, using Chil1-deficient mice, we further demonstrated that increased glucose utilization accelerates KCs death in vivo. Together, these findings establish a causal link between glycolytic activation and KCs loss during MASLD progression, highlighting glucose metabolic pathways as potential therapeutic targets to preserve KCs homeostasis and mitigate MASLD.

pathology↗

bioRxiv2025

Hypercholesterolaemia promotes epigenetic memory in hematopoietic stem cells that persists after lipid lowering and causes systemic immunometabolic dysfunction mediated by macrophage metabolic reprogramming

In patients with atherosclerotic cardiovascular disease (ASCVD) lowering LDL cholesterol (LDL-C) reduces the risk of adverse cardiovascular events. However, these patients remain at continued risk of adverse cardiovascular events despite achieving optimal LDL-C lowering. We hypothesised that this residual risk is mediated by epigenetic programming of haematopoietic stem cells (HSC) which persists after cholesterol levels are lowered and results in sustained effects on innate immune cell metabolism, that is not resolved by cholesterol lowering. We found that exposure to high cholesterol (HC) in vivo induced long-term metabolic changes in macrophages differentiated ex vivo from bone marrow, leading to a pro-inflammatory profile; these changes persisted in vivo despite cholesterol lowering. HSC from HC mice had altered chromatin accessibility that persisted after cholesterol lowering and was also present in bone marrow monocytes and tissue resident macrophages. HC provoked RUNX1-dependent downregulation of stearoyl-CoA desaturase (SCD) which reduced mono-unsaturated fatty acid (MUFA) availability for OxPhos in murine and human monocytes and macrophages. Supplementation with MUFA restored OxPhos capacity and promoted a shift towards a less pro-inflammatory macrophage phenotype in HC-trained BMDM. Bone marrow chimera and lineage tracking studies revealed that prior exposure of HSC to HC conferred adverse systemic metabolic effects on normocholesterolemic mice, with increased adipose tissue mass and increased migration of macrophages derived from HC-exposed HSC into adipose tissue, resulting in increased adipose tissue inflammation and systemic glucose intolerance. These findings indicate that HC results in long-lasting immuno-epigenetic memory in HSC which is refractory to lipid lowering, and provide strong evidence that exposure to HC can have prolonged consequences that require new therapeutic approaches, beyond cholesterol lowering.

immunology↗

bioRxiv2025

Therapeutic Salmonella induces long-term protective trained immunity in NK cells against cancer metastasis

Trained immunity, a form of innate immune memory initially recognized in pathogen defense, has recently been reported to aid in combating cancer. Although trained immunity has been well-characterized in myeloid lineage cells, its presence in innate lymphoid cells, particularly natural killer (NK) cells, remains largely unexplored. Here, we report that a single dose of Salmonella YB1, an attenuated candidate anticancer vaccine strain, provides long-lasting protection against cancer metastasis in mice by inducing trained natural killer (NK) cells. Functional assays coupled with multiomics analysis revealed that Salmonella-trained NK (stNK) cells establish an enduring reprogrammed epigenome characterized by enhanced pro-survival signaling and immune effector functions, resulting in more potent IFN-{gamma} release and cytotoxicity upon secondary stimulation. We further revealed that IL-12 and IL-18 are essential but insufficient for this NK cell training effect. Crucially, stNK cells far outperform the common immune checkpoint therapies, including PD-1 and TIGIT blockade, in suppressing metastasis, underscoring the unique immunological mechanisms in combating metastasis. These findings uncover a novel long-term anti-metastatic function of trained immunity in NK cells, highlighting its potential as an effective antitumor strategy.

immunology↗

bioRxiv2025

EBNA1 SUMOylation by PIAS1 Suppresses EBV Lytic Replication and Enhances Episome Maintenance

Epstein-Barr virus nuclear antigen 1 (EBNA1) is essential for the replication and stable maintenance of the viral episome in infected cells. Here, we identify the SUMO E3 ligase PIAS1 as a key regulator of EBNA1 through site-specific SUMOylation. Our Chromatin-Immunoprecipitation Sequencing (ChIP-seq) analysis revealed that PIAS1 is enriched at the viral origin of plasmid replication (oriP), where it physically associates with EBNA1 and catalyzes its SUMOylation. Using mutational analysis, we identified three lysine residues on EBNA1 (K17, K75, and K241) as major SUMOylation sites. Disruption of these sites compromises EBNA1s ability to restrict EBV lytic replication. In addition, both PIAS1 depletion and the disruption of EBNA1 SUMOylation lead to reduced retention of EBNA1-OriP-based EBV mini-replicon, indicating the importance of EBNA1 SUMOylation in viral episome maintenance. Together, these results uncover a conserved post-translational mechanism by which PIAS1-mediated SUMOylation modulates EBNA1 function and EBV episome maintenance and suggests a broader role for SUMOylation in viral latency, lytic replication and persistence. IMPORTANCEEpstein-Barr virus (EBV) persists in infected cells by maintaining its episome through the viral protein EBNA1. We discovered that PIAS1 SUMOylates EBNA1 at specific sites, a process essential for EBNA1 to retain viral episome and suppress reactivation. When SUMOylation is disrupted, EBV-based replicon becomes less stable and EBV is more likely to reactivate. These findings reveal a new layer of host control of EBV latency and reactivation, and highlight PIAS1-mediated EBNA1 SUMOylation as a key mechanism regulating viral persistence.

microbiology↗

bioRxiv2025

Preserving Integrity: Innovative In Vitro Methods for Extracellular Matrix Decellularization and Collagen Purification

BackgroundIn tissue engineering and cell therapy development, synthetic biomaterials are frequently supplemented with collagen or other extracellular matrix (ECM) components to enhance biocompatibility. To support these applications, novel methods for collagen purification and ECM decellularization were developed, with a focus on preserving the structural and biochemical integrity of the final products. ResultsThe effectiveness of these methods was validated using solid-state NMR and fluorescence spectroscopy, bright-field and confocal microscopy, amino acid analysis, and transmission electron microscopy. Intact cells were dislodged from ECM-producing cultures through the application of cytoskeleton-targeting drugs, while the native protein composition of the ECM was maintained. In parallel, collagen purified using chymotrypsin was shown to retain its native triple-helical structure and post-translational modifications. ConclusionsBoth techniques are broadly applicable to various cell types capable of producing collagen and/or ECM in vitro, thereby expanding the availability of species- and tissue-specific sources. These advances hold particular promise for human-relevant tissue engineering and drug discovery applications.

bioengineering↗

bioRxiv2025

pH-driven evolutionary divergence and ongoing speciation in the cosmopolitan cyanobacterium Microcoleus vaginatus

Speciation models and the concept of speciation continuum have been well established in multicellular eukaryotes. However, the mechanisms underlying population differentiation and their environmental drivers in prokaryotes remain elusive. Here, we explored the population diversification of the filamentous cyanobacterium Microcoleus vaginatus, a photoautotrophic edificator with significant importance for dryland ecosystems worldwide. By constructing a 132-genome dataset spanning multiple climate zones across four continents, we integrated intraspecific genomics with environmental association analyses to elucidate the population genetic structure and molecular mechanisms underlying the divergence of the M. vaginatus continuum. Our findings reveal that adaptive differentiation is driven by the combined effects of natural selection, homologous recombination, and gene family turnover, with varying contributions across different phylogroups. The evolution of core and accessory genomes exhibits complementary patterns, with genome-wide association studies demonstrating the predominant role of the core genome in population divergence. Selection, followed by neutral evolution and recombination, mediates trade-offs in life-history strategies, while environmental factors shape these evolutionary processes. Notably, while local edaphic variables exert direct influences on Tajimas D values, they demonstrate predominantly indirect modulation through alterations in the selection-to-gene gain ratio (S/G). pH emerges as the principal abiotic driver governing population genetic signatures, operating through coordinated effects on both S/G and the proportion of selected genes undergoing recombination (SUR). This study offers novel insights into the diversification mechanisms of cosmopolitan, dominant cyanobacteria, thereby advancing our understanding of prokaryotic speciation in complex natural settings and providing a framework for predicting microbial adaptation in a changing world.

evolutionary biology↗

bioRxiv2025

Quantitative Single-Cell Imaging of Efflux Pump Heterogeneity and Antibiotic Response Dynamics

Understanding how bacterial cells survive antibiotic treatment requires tools capable of resolving dynamic physiological heterogeneity at single-cell resolution. Here, we present a high-throughput, lineage-resolved microfluidic imaging platform for quantifying the expression and spatial distribution of the AcrAB-TolC efflux pump in Escherichia coli during antibiotic exposure. The system is built around a custom-designed multilayer microfluidic device, fabricated using a direct-write photolithography protocol, which ensures uniform delivery of nutrients and antibiotics while confining thousands of individual cells in dead-end trenches. Brightfield imaging provides a label-free, high-temporal-resolution method for tracking cell growth and division, enabling accurate reconstruction of lineages over time. Efflux pump abundance is quantified using GFP-tagged AcrB, while a red fluorescent reporter driven by a constitutive promoter serves as a control to account for growth-dependent fluorescence artifacts. To analyse the sources of heterogeneity in efflux abundance and its consequences for antibiotic response dynamics, we developed a lineage-resolved analytical framework that compares cells of similar replicative age but differing spatial positions, and vice versa. This analysis was made possible by a novel machine-learning-based image processing pipeline, which enables robust cell segmentation, tracking, and lineage reconstruction across multiple fields of view. By extracting time-resolved single-cell data, this platform allows precise dissection of non-genetic variability in efflux activity and its role in determining survival outcomes, offering a powerful foundation for future quantitative studies of bacterial physiology under antibiotic stress.

systems biology↗

bioRxiv2025

UCP1 Mitigates Hepatic Steatosis and Fibrosis Independent of Cold Exposure

Non-shivering thermogenesis by brown adipose tissue (BAT) is a promising target for anti-obesity therapies, making its regulatory mechanisms of significant translational interest. While cold-induced BAT thermogenesis (CIT) is well characterized, certain high-calorie diets can also activate BAT in the absence of cold, a process known as diet-induced thermogenesis (DIT). Despite its potential relevance to modern human diets and lifestyles, the mechanisms and physiological relevance underlying DIT remain poorly understood. Here, we show that DIT reduces adiposity and protects against hepatic steatosis and fibrosis in males but not female mice. Moreover, adipose tissue-specific ablation of uncoupling protein 1 (UCP1) reveals that BAT is the primary mediator of DIT but that non-adipocyte UCP1 also contributes to body weight regulation. Transcriptome analysis suggests that DIT is triggered by intrinsic metabolic stress, distinguishing it from CIT, which is driven by sympathetic tone. Finally, BAT-specific arteriovenous metabolomics identifies glucose as the predominant circulating fuel for DIT. These findings uncover distinct molecular and metabolic features of DIT, highlighting opportunities to harness BAT activity for treating obesity and metabolic diseases without requiring cold exposure.

physiology↗