Biology subjects

Lu, H.

Publications and source records attributed to Lu, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Are Synaptic Clefts Directionally Oriented?

Synapses are fundamental building blocks of cortical circuits, yet their geometry is typically regarded as a local property, independent of mesoscale architecture. The prevailing assumption is that synaptic clefts are isotropically oriented in space. Here, we test this assumption by analyzing approximately 117 million synaptic clefts from two independent 1 mm3 electron microscopy datasets: the human H01 middle temporal gyrus and the mouse MICrONS primary visual cortex, using three independent cleft-extraction methods. Across both volumes, we observe that synaptic cleft orientations are not randomly distributed, but instead show statistically significant and spatially coherent directional biases across cortical layers. This mesoscale anisotropy is conserved across species, yet is stronger and more consistent in human association cortex than in mouse sensory cortex, a difference that may reflect the expanded dendritic arbors and greater integrative demands of human pyramidal neurons. We propose that cleft orientation bias is a geometric consequence of the axonal and dendritic architecture that shapes synapse formation, representing a new candidate organizational feature of cortical microarchitecture with potential implications for circuit computation and neuromodulation. These findings motivate targeted physiological studies to determine whether synaptic orientation contributes causally to cortical function.

neuroscience↗

bioRxiv2025

Nuclear N-Glycosylation Redefines the Glycoscape and Directs Cell Identity

Glycans modify nucleic acids, proteins and lipids in fundamental biological processes, but have long been considered confined to the secretory pathway and cell surface. Here, we challenge this view with evidence that N-glycosylation, a ubiquitous glycan modification, occurs within cell nuclei across tissues and species, exhibiting cell type-dependent abundance and localization patterns. Using a multi-faceted approach, we show that numerous classical membrane and secreted glycoproteins localize to the nucleus with N-glycan modifications, exemplified by the cell adhesion molecule L1CAM. Mechanistically, we show that the N-glycosylated L1CAM is transported to the nucleus by KPNB1, where it transcriptionally modulates neuronal differentiation. Moreover, this nuclear N-glycosylation event contributes to neurodevelopmental disorders and is pharmacologically reversible. These findings revise the cellular geography of N-glycosylation and expand the known routes of protein trafficking, and highlight nuclear N-glycosylation pathways as potential therapeutic entry points for developmental disorders.

cell biology↗

bioRxiv2025

Vascular Microbleeds Without Brain Atrophy: A Microvascular Signature of Mid-Stage 5xFAD Pathology

Cerebral microbleeds are increasingly recognized as a downstream manifestation of vascular injury in Alzheimers disease (AD), arising secondary to cerebral amyloid angiopathy (CAA). Here, we examined the pathological specificity of microbleeds by comparing an amyloidosis mouse model (5xFAD) with a small-vessel disease (SVD) model characterized by vascular smooth-muscle cell loss. In vivo multimodal MRI, including gradient-echo, spin-echo, and diffusion-weighted imaging, was complemented by ex vivo high-resolution anatomical scans for validation. Both in vivo and ex vivo gradient-echo MRI consistently revealed hippocampal microbleeds in the 5xFAD model without macroscopic atrophy or ventricular enlargement, whereas no microbleeds or blood-brain barrier disruption were detected in the SVD model. Diffusion-weighted MRI further showed region-specific alterations in apparent diffusion coefficient within the midbrain of 5xFAD mice, but not in other regions or in the SVD cohort. These findings indicate that microbleeds are a pathology-specific marker of amyloid-related vascular injury. The imaging evidence underscores the potential of microbleeds as a disease-specific biomarker for detecting amyloid-driven vascular fragility and refining diagnostic and therapeutic strategies for AD.

neuroscience↗

bioRxiv2025

Vascular smooth muscle cell loss, but not neuroinflammation, drives cerebrovascular reactivity impairment in Alzheimer disease

INTRODUCTIONCerebrovascular reactivity (CVR) impairment is a key feature of Alzheimers disease (AD), but its mechanistic basis remains unclear. This study examined whether vascular smooth muscle cell (VSMC) loss, rather than amyloidosis or neuroinflammation, underlies CVR deficits. METHODSNon-contrast MRI, including phase-contrast and pseudo-continuous arterial spin labeling, was performed in mouse models of amyloidosis (5xFAD), VSMC degeneration (CADASIL), and lipopolysaccharide-induced neuroinflammation. Characterization of vascular, amyloid-{beta}, and inflammatory markers were performed for pathological assessment. RESULTSCVR impairment emerged only when VSMC loss was present in CADASIL mice and at older ages in 5xFAD mice (9-12 months). Amyloid-{beta} deposition occurred earlier than VSMC loss or CVR decline. Neuroinflammation primarily altered baseline cerebral blood flow without affecting CVR or VSMC integrity. DISCUSSIONThese findings identify VSMC degeneration as an important driver of CVR impairment independent of cerebral amyloid angiopathy or inflammation, highlighting vascular integrity as a potential therapeutic target in AD. HighlightsO_LICerebrovascular reactivity (CVR) impairment occurred in 5xFAD mice only when vascular smooth muscle cell (VSMC) loss was present C_LIO_LI5xFAD mice exhibited prominent parenchymal but minimal vascular amyloid-{beta} deposition C_LIO_LIVSMC developmental deficiency resulted in CVR impairment in a small-vessel disease (SVD) model C_LIO_LINeuroinflammation primarily altered baseline cerebral blood flow (CBF) without affecting CVR C_LI

bioengineering↗

bioRxiv2025

Predicting individual incubation of opioid craving by whole-brain functional connectivity

A high risk of relapse triggered by craving during abstinence remains a main challenge in opioid addiction treatment. Multiple brain regions have been implicated in opioid craving, but the brain-wide neural mechanisms underlying this process remain poorly understood. Using resting-state fMRI and connectome-based predictive modeling, we identified a whole-brain connectome that predicted the time-dependent increases (incubation) in oxycodone craving in individual rats after voluntary abstinence induced by exposure to an electric barrier. Incubation of oxycodone craving was operationally defined as the increase in non-reinforced lever pressing during relapse tests from early (day 1) to late (day 15) abstinence (incubation score). We found that changes in whole-brain functional connectivity during abstinence, but not during oxycodone self-administration, predicted the incubation score. Greater decreases in functional connectivity were associated with higher incubation scores. The predictive connectome involved complex interactions across multiple brain systems, including frontal-striatal, frontal-insula, insula-striatal, and hippocampal and sensorimotor circuits. To test causality of the predictive connectome, we examined the effect of pharmacological inactivation of dorsomedial striatum (DMS), which significantly decreased oxycodone seeking after electric barrier-induced abstinence. DMS inactivation increased connectivity strength within the predictive connectome, supporting a causal role of this connectome in incubation of oxycodone craving. The predictive connectome did not predict food-reward seeking after electric barrier-induced abstinence, indicating specificity to oxycodone craving. Our findings identify a brain-wide connectome marker that predicts individual differences in the incubation of opioid craving and provide potential targets for developing personalized interventions and monitoring therapeutic outcomes in opioid addiction treatment. Significance statementRelapse driven by craving remains a central challenge in treating opioid addiction. Using resting-state fMRI and connectome-based predictive modeling, we identified a whole-brain connectivity pattern that predicted incubation of oxycodone craving after voluntary abstinence in rats. Connectivity changes during abstinence predicted the magnitude of incubation, measured by increased oxycodone seeking from early to late abstinence. The predictive connectome involved interactions among cortical, basal ganglia, insular, hippocampal and sensorimotor systems. Pharmacological inactivation of the dorsomedial striatum modulated connectivity strength within this network, demonstrating a causal role of the connectome in incubation of craving. These findings identify a brain-wide marker of incubation of opioid craving and provide a translational framework for developing targeted interventions and monitoring therapeutic outcomes in opioid addiction treatment.

neuroscience↗

bioRxiv2025

Network modularity reveals context and state-dependent reorganization of time-varying functional connectivity in single-cell resolved neural activity recordings

An important goal of neuroscience is to understand how biological neural networks organize activity at multiple scales to enable complex information processing and behavioral output. To address this challenge, large-scale neural activity datasets with increased resolution and wider coverage have become more prevalent across many model systems. However, bridging the gap in scale between changes in pairwise functional connectivity between neurons and changes in brain-wide organization of activity remains a key challenge. In this work, we demonstrate application of modularity-based community detection and network modularity to single-cell resolved recordings, for the first time, as a method to summarize complex changes in time-varying functional connectivity, facilitating comparisons across multiple time windows, recordings, and conditions. We apply these methods to both single-cell resolved multi-cell and whole-brain activity recordings. In the multi-cell recordings, we find that food odor changes functional connectivity between existing network modules in a C. elegans locomotory interneuron network, rather than reorganizing them. In spontaneous whole-brain activity, we identify several key hub neurons and combinations that significantly destabilize module assignments when silenced. Together, these results demonstrate community detection and modularity as a method for detecting context and network state-dependent changes in functional connectivity at the intermediate scale of network modules in single-cell resolved neural activity. Results from these analyses facilitate future investigation of mechanisms that mediate organization of neural activity at intermediate scales.

neuroscience↗

bioRxiv2025

StrainOptimizer empowers rational cell factory design through multi-scale metabolic models with expression and proteome constraints

The rational design of microbial cell factories for high bioproduction remains a key challenge in metabolic engineering. While advanced modelling frameworks incorporating protein resource allocation, such as enzyme-constrained models (ecGEMs) and Expression and Thermodynamic Flux (ETFL), provide superior predictive power, their application is limited by a lack of user-friendly computational tools. Here, we present strainOptimizer, a comprehensive computational platform for rational strain design that systematically evaluates key resource allocation principles: the coupling of gene expression with metabolism, subcellular compartmentalization, and enzyme capacity limitations. Our benchmark analyses demonstrate that each principle offers distinct advantages: models coupling metabolism and expression (like ETFL) enable the identification of non-metabolic targets, organelle-level proteomic constraints improve precision for high-protein-cost products, and protein-usage-based objectives consistently outperformed traditional flux-based approaches. To demonstrate its practical utility, we applied strainOptimizer to an engineered sclareol-overproducing Saccharomyces cerevisiae strain. The platform identified novel targets, and experimental validation confirmed a 67% success rate, increasing the final sclareol titer by 14-26% and productivity by up to 45%. StrainOptimizer bridges the gap between resource allocation theory and applied engineering, providing a powerful, validated tool to accelerate the development of high-performance cell factories.

bioengineering↗

bioRxiv2025

Microfluidics-Enabled Simultaneous Imaging of Neural Activity and Behavior in Chemically Stimulated, Head-Fixed C. elegans

Understanding how the brain processes sensory information and produces appropriate behavior is a fundamental question in neuroscience. In this study, we developed a novel microfluidic device that allows for simultaneous observation of neural activity and behavior in Caenorhabditis elegans (C. elegans) during chemosensory stimulation. Traditional methods often involve trade-offs between high-resolution neuronal imaging, behavioral recording, and the ability to apply chemical stimulation. Our innovative design overcomes these limitations by immobilizing the worms head, stabilizing neuronal imaging, while allowing the posterior portion of the body to move freely, enabling the study of naturalistic behaviors during chemical stimulation. We applied this device to investigate how C. elegans responds to both attractive and aversive chemical cues. By correlating neural activity with observed behavior, we identified neurons and whole-brain dynamics associated with specific movements. Our results demonstrate that providing the worm with greater freedom of movement results in more naturalistic neuronal and behavioral responses to stimuli, compared to fully immobilized setups. This new tool offers a powerful approach for studying how sensory information is processed in the C. elegans nervous system to generate behavior, with potential applications in other model organisms. Its versatility and ease of operation make this device broadly applicable for studying how neural circuits drive behavior and decision-making in complex environments.

bioengineering↗

bioRxiv2025

Aversive Learning Induces Context-Gated Global Reorganization of Neural Dynamics in Caenorhabditis elegans

Learning generates experience-dependent changes to the brain. However, how neurons of diverse functions and connectivity reorganize and modulate their activities to generate coherent changes while preserving essential functions is not well understood. Here, we address this question using an aversive olfactory learning paradigm whereby Caenorhabditis elegans learns to reduce its olfactory preference for pathogenic bacteria. Using functional imaging during olfactory stimulation in naive and trained animals, we show that, at brain-wide scale, cell type-by-cell type, learning induces context-gated reconfiguration of the organization of neural activity throughout the brain to alter neural responses only during bacteria-discrimination task, while leaving intact bacteria-sensing functions. We found that the context-gated encoding of learning is globally distributed across layers of the nervous system, composed of neurons carrying information of context or learning experience. In particular, aversive training modulates multiple functional connections within the nervous system, including those between sensory neurons and interneurons, as well as those among interneurons, in a context-gated manner. At the systems level, training modulates correlated activity of neural populations; we found that low-dimensional temporal patterns of population activity correlate well with locomotory gaits that express olfactory preferences. Upon training, the rotation and contraction of the low-dimensional neural manifolds shifts the brain into predisposed states for the context-gated display of learned behavior. Because animals encounter unpredictable environments in life, efficient learning about relevant cues while maintaining other functions is essential for survival. Our findings uncover network-level mechanisms that help explain how the brain reorganizes its activity patterns to both encode new experience and preserve essential functions.

neuroscience↗

bioRxiv2025

Epithelial-Mesenchymal Transition is Associated with Altered Immune Composition and Cytotoxic Function in Triple-Negative Breast Cancer

Epithelial-mesenchymal transition (EMT) is a dynamic process that contributes to breast cancer progression, metastasis, and therapy resistance. EMT also influences the tumor immune microenvironment, shaping immune cell infiltration and function. Although the immunological features of fully epithelial or fully mesenchymal tumor states have been characterized, the immune landscape associated with intermediate or partial EMT states remains poorly understood. To address this gap, we established five single-cell-derived clonal populations from the triple-negative 4T1 mouse mammary tumor cell line, representing a spectrum of EMT phenotypes, and analyzed tumors derived from these clones using single-cell RNA sequencing. We show that tumors derived from these clones retained their relative EMT states in vivo, and that EMT progression is associated with a graded reduction in tumor immunogenicity, accompanied by alterations in immune cell composition and function. Along the EMT spectrum, tumor cells exhibited progressive downregulation of major histocompatibility complex (MHC) class I and II gene expression, along with decreased infiltration of cytotoxic CD8+ T cells, and reduced expression of key effector and trafficking genes (Gzmb, Ccr5, Cxcr6). B cell composition also shifted, with decreased frequencies of IgG1-producing plasma cells and an enrichment of regulatory-like B cells. Natural killer (NK) cells similarly demonstrated progressive functional suppression, marked by reduced expression of cytotoxic molecules and the downregulation of key effector pathways. These findings reveal that EMT is associated with immune cell recruitment and function in a graded manner, providing a rationale for integrating EMT phenotyping into therapeutic strategies to overcome immune resistance in breast cancer.

cancer biology↗

bioRxiv2025

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling

The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5xFAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5xFAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD. HIGHLIGHTSInhibition of CGRP receptor ameliorates disease pathology in models of AD HDAC11 mediates CGRP receptor function in AD HDAC11 is a pivotal regulator in lipid metabolism by LXR{beta}/ABCA1 signaling The HDAC11/LXR{beta}/ABCA1 axis is conserved in AD humans and mice

neuroscience↗

bioRxiv2025

Fixing Hybrid Rice: >99% Efficient Apomixis with Near-Normal Seed Set

Apomixis, a form of clonal seed reproduction, offers a transformative approach to agriculture by enabling the stable fixation of hybrid vigor and elite heterozygosity across generations. However, the practical implementation of synthetic apomixis has been hindered by highly variable clonal efficiency or significant yield penalties. In this study, through integrated transcriptomic analyses, we identified a sperm-specific transcription factor in rice that likely functions as a key initiator of embryogenesis. Ectopic expression of this factor in egg cells effectively induces parthenogenesis and produces haploid progeny. When combined with clonal gametogenesis, this system achieved nearly complete synthetic apomixis, with clonal seed production rates exceeding 99% across all derived hybrid rice lines. Moreover, we generated apomictic hybrid lines that not only consistently produced over 99% clonal seeds but also exhibited seed yields comparable to conventional F1 hybrids. These findings establish a scalable and agriculturally viable platform for synthetic apomixis, achieving stable fixation of heterosis through clonal seeds and paving the way for the commercial deployment of self-perpetuating hybrid crops.

plant biology↗

bioRxiv2025

In vivo colonic epithelial cell editing attenuates intestinal inflammation in mice

Engineered epithelial cells with enhanced efferocytosis capacity promote inflammation resolution and restore tissue homeostasis. Here, we developed a therapeutic approach to generate efferocytosis boosting epithelial cells in vivo by delivering mRNA in lipid nanoparticles (LNPs). We demonstrate that LNP-mediated delivery of mRNA enables efficient in vitro and in vivo functional editing of epithelial cells. In murine models of colitis, intraperitoneal administration of mRNA-loaded nanoparticles designed to boost efferocytosis markedly attenuated intestinal inflammation and halted disease progression. This strategy provides a proof of concept that epithelial cells can be functional engineered in situ and represents a promising therapeutic avenue for mitigating inflammatory tissue damage. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/678706v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@874991org.highwire.dtl.DTLVardef@1eefbfforg.highwire.dtl.DTLVardef@e22fa6org.highwire.dtl.DTLVardef@1a6480d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments

Spatial transcriptomics analysis is a powerful approach for dissecting the structure of tissue microenvironment and uncovering the mechanism of cell-cell communications. However, existing technologies are limited by either spatial resolution or gene coverage. Most single-cell resolution technologies target only a few hundreds of pre-selected genes, whose choice plays an important role in the overall analysis. It remains a challenge to optimally design a gene panel to maximize the utility of spatial transcriptomics profiling. To fill this gap, we introduce a novel method, named ReconST, to automatically design optimal gene panels for spatial transcriptomics profiling. ReconST leverages information from existing scRNA-seq data, and identifies the optimal subset of genes by using a gated autoencoder. By using a high-coverage mouse brain MERFISH dataset as the reference benchmark, we showed that ReconST outperforms existing methods in terms of both reconstruction accuracy and spatial pattern preservation. As such, ReconST provides a useful and generally-applicable tool for optimal gene panel design, which in turn can significantly enhance the utility of spatial transcriptomics profiling in a wide range of biomedical investigations.

bioinformatics↗

bioRxiv2025

The genetic architecture of trabecular bone score and association with fracture: a genome-wide association and meta-analysis

BackgroundTrabecular bone score (TBS) is a texture-based measurement derived from DXA scans, which describes the distribution of mineral across the vertebral bodies. Identifying its genetic determinants is crucial for enhancing understanding of its biological basis and clarifying its relationship with fracture risk. MethodsWe conducted a large-scale genome-wide association study (GWAS) of TBS from 44,767 participants (95.08% European ancestry). Sex heterogeneity was assessed through sex-stratified GWAS. Post-GWAS analyses included functional annotation, gene-set enrichment analysis, and cis-expression quantitative trait locus (cis-eQTL) colocalization. Two-sample and multivariable Mendelian randomization (MR) were employed to investigate the causal effect of TBS on fractures. FindingsWe identified 33 independent variants associated with TBS, which explained 4.06% of TBS phenotypic variance. All the discovered signals map to previously identified BMD-associated loci. Additionally, we identified genetic variants in the RAB11FIP3 locus that exhibited a sex-heterogeneous effect, being associated with TBS exclusively in males. Functional annotation and colocalization identified functional genes related to TBS. The two-sample and multivariable MR analyses indicated that TBS potentially has an independent causal effect on fracture risk. InterpretationOur study unveiled 33 independent loci associated with TBS, all in BMD-associated loci. One locus was further identified as associated with TBS only in males. MR results suggested that genetically derived TBS may be causally associated with fracture risk at different sites, potentially beyond BMD. This study provides insights into the TBS genetic architecture and uncovers its potential clinical applications in fracture risk prediction. FundingAll funding information can be found in the Acknowledgements section. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSOsteoporosis is a common disease prevalent in older adults, mainly diagnosed by low bone mineral density and disruption of bone architecture. While the genetic determinants of bone mass have been well studied, the genetic architecture of bone features beyond BMD remains largely unknown. Added value of this studyThis study presents a large genome-wide association meta-analysis of the trabecular bone score (TBS), a measurement of trabecular distribution of bone mineralization across vertebral bodies. Our study identified 33 independent variants associated with TBS and one association signal only in males. Functional annotation highlighted crucial genes related to TBS. The two-sample and multivariable Mendelian randomization (MR) analyses suggested that TBS may be causally linked with fracture risk, potentially independent of BMD. Implications of all the available evidenceOur study represents an expansion of the traditional bone density phenotype used in most previous skeletal genetic studies. Based on the findings that all of the significant loci for TBS have been previously identified in GWAS of BMD, we conclude that TBS-associated variants have pleiotropic effects affecting not only mineral density but also the distribution patterns of minerals in the cancellous bone. Continuing to perform genetic studies of new skeletal phenotypes beyond BMD could ultimately impact the management and prediction of osteoporosis patients.

genomics↗

bioRxiv2025

PDE3A2 modRNA Fine-Tunes Nuclear cAMP Microdomains and Reverses Pathological Cardiac Hypertrophy

Pathological cardiac hypertrophy (PCH) is a precursor to heart failure, driven in part by dysregulated nuclear-localized cAMP (NLS-cAMP) signaling. Phosphodiesterase 3A2 (PDE3A2) is a key regulator of this nuclear cAMP microdomain, yet its selective modulation remains challenging. Here, we developed PDE3A2-modified RNA (PDE3A2-modRNA) to restore nuclear PDE3A2 levels and tested its efficacy in an angiotensin II-induced PCH model. Subcellular FRET imaging revealed that PCH hearts exhibit hyperactive NLS-cAMP due to PDE3A2 depletion. PDE3A2-modRNA selectively reduced NLS-cAMP without altering cytosolic cAMP, demonstrating precise microdomain regulation. In vivo, PDE3A2-modRNA improved cardiac function, attenuated hypertrophy and fibrosis, and shifted transcriptional programs toward physiological remodeling. Single-nucleus transcriptomics and immune profiling further revealed reduced oxidative stress and an improved cardiac microenvironment. These findings highlight PDE3A2-modRNA as a novel gene therapy that selectively restores nuclear cAMP homeostasis, reversing PCH-promoting transcriptional programs while preserving physiological cAMP signaling in cytosolic microdomains.

pathology↗

bioRxiv2025

Study on Early pregnancy diagnosis in sows based on joint analysis of vaginal secretion metabolomics and machine learning

ObjectiveMetabolic transformations in female mammals throughout gestation manifest in the metabolite profiles of bodily fluids, potentially serving as biomarkers for the diagnosis of pregnancy. This investigation concentrated on sows 18 days post-mating, with the objective of identifying biomarkers pertinent to early pregnancy diagnosis through the analysis of variations in metabolic molecules within vaginal secretions. MethodsVaginal secretion samples were procured from both pregnant and non-pregnant sows 18 days post-mating, subsequently subjected to untargeted metabolomic analysis utilizing liquid chromatography-mass spectrometry (LC-MS). The samples were partitioned into training and testing datasets, and machine learning algorithms--specifically, Random Forest (RF) and support vector machine (SVM)--were integrated with metabolite weight ranking to identify key biological markers. ResultsA total of 3,249 metabolic molecules were identified, among which 534 exhibited significant differential expression in the vaginal secretions of pregnant versus non-pregnant sows. Notably, three hormones that correlate with the pregnant status of the sow were discerned: Progesterone, 3-Deoxyestradiol, and Prostaglandin E1. KEGG pathway analysis revealed that the differentially expressed metabolites were predominantly enriched in nucleotide metabolic pathways. The RF model demonstrated an impressive accuracy of 1.00 in the training dataset and 0.88 in the testing dataset, while the SVM model maintained an accuracy of 1.00 across both datasets. Utilizing model weights and differential expression data, three pivotal metabolites were identified: Indolepropionic acid, cis-Aconitate, and 4-p-Coumaroylquinic acid, which exhibited ROC curve AUC values of 0.90, 0.89, and 0.79, respectively. ConclusionThis study validates the viability of utilizing vaginal secretions for the early diagnosis of pregnancy in sows, thereby establishing a foundation for the advancement of non-invasive diagnostic methodologies.

zoology↗

bioRxiv2025

Body temperature drives azole tolerance in Candida albicans by hindering the autophagic degradation of Erg11

Human body temperature has been shown to limit the antifungal efficacy of azoles; however, the precise mechanisms underlying this limitation remain insufficiently understood. In this study, we observed that short-term exposure (24 h) to human body temperature (37{square}{degrees}C), in contrast to 30{square}{degrees}C, significantly enhances the tolerance of Candida albicans to azoles without inducing resistance. Our findings suggest that this increased tolerance is due to a reduction in the degradation of C. albicans Erg11 at 37{square}{degrees}C compared to 30{square}{degrees}C, thereby promoting azole tolerance. This phenomenon occurs because Erg11 degradation is mediated by autophagy, which is inhibited in C. albicans at 37{square}{degrees}C. The suppression of autophagy at this temperature may be associated with elevated mitochondrial production of reactive oxygen species, leading to mitochondrial dysfunction. In response to heat stress-induced mitochondrial dysfunction, autophagy-related proteins such as Atg8 accumulate around the mitochondria, while their levels in the endoplasmic reticulum decrease, consequently inhibiting autophagy in C. albicans. These findings suggest that promoting the degradation of Erg11 in C. albicans may serve as a viable strategy to augment the fungicidal efficacy of azoles in the human host.

microbiology↗