Biology subjects

Li, D.

Publications and source records attributed to Li, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Conserved Genic Composition Unravels Rapid Karyotype Evolution and Polyploidization across Plants

Chromosomal variation underlies species evolution, but reconstructing its large-scale dynamics remains challenging, obscuring its adaptive significance. Here, we introduce GouMang, a framework that mines conserved genic section compositions across diverse species to trace karyotype evolution. In grasses, applied to 818 highly varied chromosomes spanning eight subfamilies, GouMang resolved a shared karyotype evolution path of 9 [->] 18 ({rho} whole-genome duplication, {rho}WGD) [->] 12 chromosomes, followed by lineage-specific rearrangements or WGDs. Genes retained from the early {rho}WGD are linked to cold/light adaptation, supporting a key biomass-expansion event that impacted subsequent global ecological pattern and human agricultural civilization, in which K-Pg global cooling and subsequent forest degradation drove early understory grasses to sun plants. Parallel analysis in Brassicaceae reconstructed karyotype evolution as well as {beta}WGD which unlinked to cold/light adaptation, reflecting a divergent biogeographic history compared to grasses. Together, GouMang depicts a widespread plant evolutionary pattern where karyotype constantly diversified with WGDs recurrently fueling adaptation.

evolutionary biology↗

bioRxiv2026

3D Passive Cavitation Mapping (3D-PCM) with a Large-aperture Planar Array

Urinary stone disease is a common urological condition with increasing incidence, particularly in developed countries. Laser lithotripsy (LL) has become a preferred minimally invasive treatment due to its high precision and low tissue damage. Recent studies suggest that cavitation plays a critical role in stone damage during LL, and three-dimensional passive cavitation mapping (3D-PCM) has emerged as a promising tool for detecting these events. However, clinical translation of 3D-PCM remains challenging due to limitations in imaging depth, field of view (FOV), and procedural compatibility. Here, we present a large-FOV dual-modality imaging system (3D-PCM and B-mode ultrasound) based on a large-aperture planar ultrasound array. Through array optimization and model-based reconstruction, our system achieves an expanded FOV of [~]40 x 40 mm2 at a clinically relevant imaging depth of [~]110 mm, while maintaining high spatial resolution of [~]0.6 mm laterally and [~]0.4 mm axially. In vivo experiments in a porcine model demonstrate that the reconstructed cavitation distribution correlates well with stone damage. Our technology has the potential to provide real-time treatment feedback during LL without disrupting the standard workflow.

bioengineering↗

bioRxiv2026

Symptomatic human norovirus infection in zebrafish embryos uncovers neural infection and extracellular vesicle-mediated transmission dynamics

Human norovirus (hNoV) is the leading global cause of acute gastroenteritis, imposing a substantial health and economic burden worldwide. Progress in understanding hNoV pathogenesis has been hindered by the lack of tractable small-animal models that recapitulate symptomatic infection. Although zebrafish larvae support hNoV replication, infection remains asymptomatic, limiting their utility for studying disease mechanisms and host-pathogen interactions. In this study, we report that the zebrafish embryo infection model, in which microinjection of hNoV at the early cell stage, resulted in robust systemic viral replication accompanied by overt pathological manifestations, including pericardial and renal edema, yolk and cranial opacity, and mortality by 3 days post-infection. Disease severity displayed marked individual variability and correlated closely with viral burden. Integrated multi-omics analyses, including bulk transcriptomics, untargeted metabolomics, and single-cell RNA sequencing, demonstrated that embryonic infection elicits a stronger and more coordinated antiviral response than larval-stage infection, while enabling widespread viral dissemination across diverse cell lineages. Approximately two-thirds of infected cells were derived from the nervous system or neural crest lineages, providing a potential mechanistic basis for the neurological complications occasionally reported in hNoV-infected patients. Furthermore, we identified a developmental stage-dependent role for extracellular vesicle (EV)-associated hNoV transmission: free virions mediated more efficient infection and higher symptomatic incidence in immunologically immature embryos, whereas EV-associated virions exhibited enhanced infectivity in more immunocompetent larvae. Together, these findings establish the zebrafish embryo as a versatile and accessible in vivo platform for studying symptomatic hNoV infection, reveal host maturity-dependent viral transmission strategies, and provide new opportunities for mechanistic studies and high-throughput evaluation of antiviral and vaccine candidates. Author summaryHuman norovirus is the leading cause of stomach flu worldwide but studying it has been difficult because the lack of a simple, small-animal model that actually gets sick from the virus. While older zebrafish larvae can harbor the virus, they do not show symptoms. In this study, we successfully created a new model by injecting human norovirus into zebrafish embryos at their early cell stage. Unlike the older larvae, these embryos developed clear symptoms, including fluid buildup around the heart and kidneys, tissue cloudiness, and death within three days. Using advanced genetic and metabolic tracking, we discovered that the virus spreads widely throughout the embryos body, particularly targeting cells in the nervous system. This link might explain why human patients occasionally suffer from neurological symptoms. Additionally, our study revealed that the virus changes its transmission strategy based on the animals age: it travels freely to infect vulnerable embryos but hides inside lipid vesicles to infect older, more immune-developed larvae. Ultimately, these findings provide a practical, efficient animal model to better understand norovirus sickness and rapidly test new vaccines and treatments.

microbiology↗

bioRxiv2026

scIsoAgent enables autonomous isoform-resolved characterization and sequence-informed interpretation of long-read single-cell transcriptomes

Alternative isoform usage can alter gene function independently of total gene expression, creating a need to resolve transcript isoforms at single-cell resolution. Long-read single-cell RNA sequencing meets this need by linking cellular identity to transcript isoforms and sequence-level features. Realizing its full biological value requires reproducible workflows that connect specialized long-read analysis with biological interpretation. Existing large language model (LLM)-based biomedical agents support general omics analysis, but are not designed for isoform-resolved long-read single-cell workflows. Here, we present scIsoAgent, an autonomous LLM-powered scientific agent for long-read single-cell RNA-seq analysis. scIsoAgent turns heterogeneous long-read single-cell inputs into traceable isoform-resolved workflows, using stage-aware planning and persistent computational context to support both execution and interpretation. Across complementary evaluations, this design improved the continuity from analysis planning to executable, interactive workflows compared with general-purpose LLM baselines. In real-data reanalysis, scIsoAgent recovered major findings from published long-read single-cell resources and extended a representative differential transcript usage event into a sequence-informed functional hypothesis. By linking full-length isoform sequences with model-inferred transcript properties, scIsoAgent connects observed isoform usage with potential sequence-level functional consequences. These results demonstrate that autonomous scientific agents can transform fragmented long-read single-cell analysis into coherent, reproducible workflows for isoform-resolved discovery and biological interpretation.

bioinformatics↗

bioRxiv2026

Targeting Lysosomal MCOLN1/TRPML1 Ion Channels to Finely Alleviate Diabetes Mellitus via a Ca 2+ - CaMKKβ-AMPK pathway

Type 2 Diabetes mellitus (T2DM) is a metabolic syndrome characterized by hyperglycemia and various complications. Current drugs are limited by side effects and resistance, necessitating novel targets and therapies. Previous studies have shown that MK-83, a synthetic agonist of transient receptor potential mucolipin 1 (TRPML1/ MCOLN1), a lysosomal Ca2+ channel, activates adenosine 5'-monophosphate-activated protein kinase (AMPK), a key therapeutic target in diabetes. However, whether targeting TRPML1 can treat T2DM remains unclear. In this study, we found that transgenic overexpression or pharmacological activation of TRPML1 finely controls AMPK phosphorylation via a Ca2+-CaMKK{beta}-dependent mechanism. This activation promotes glucose transporter 4 (GLUT4) translocation and dramatically increases intracellular glucose uptake. Conversely, genetic inactivation or pharmacologically inhibition of TRPML1 blocks both AMPK activation and glucose uptake. More importantly, pharmacological activation of TRPML1 in vivo dramatically alleviates hyperglycemia in db/db mice (a T2DM model), as evidenced by random blood glucose levels, fasting blood glucose levels and HbA1c levels. Furthermore, other hallmark features of db/db mice-including impaired oral glucose tolerance, reduced insulin tolerance, and elevated ALT and AST levels- were all ameliorated upon TRPML1 activation. Hence, targeting lysosomal TRPML1 channel represents a promising therapeutic strategy for T2DM, with highly specific TRPML1 agonists as potential anti-diabetic agents.

Cell Biology↗

bioRxiv2026

Goal-dependent resource-rational compression of attribute differences explains nonlinearities in multi-attribute decision making

Why do multi-attribute choices so often depart from classical weighted-additive decision rules? Rather than attributing such deviations solely to biases or heuristics, we propose a resource-rational account in which value differences are encoded via capacity-limited information channels. Under resource-rational compression, these difference representations are systematically distorted, such that behavior deviates from weighted-additive predictions because value differences are not represented veridically. This theoretical account makes testable predictions about power-law relationships between true and internally represented differences. The amount of power-law-like compression is determined by information-processing capacity, emergent long-tailed prior distributions over attribute differences, and, in choice contexts, goal-dependent subjective weights that govern the allocation of limited capacity across attribute channels. We test and find support for these predictions in an attribute difference-estimation task and by reanalyzing existing food- and social-choice datasets. These results provide converging evidence for a normative, information-theoretic account of systematic nonlinearities in multi-attribute decision making. Together they show how goals can interact with cognitive capacity and priors to shape representational precision in ways that may facilitate or impair decision making.

neuroscience↗

bioRxiv2026

Controlling metal-carbonate phase, form, and function through de novo protein design

Biomineralization enables living systems to construct hybrid materials by controlling the location, orientation, and polymorph of inorganic crystals with proteins and other biomolecules. Despite decades of study, the molecular principles underlying these processes remain difficult to harness in engineered materials, in part because native biomineralization proteins are often intrinsically disordered, heterogeneous, or insoluble. Here we show that de novo designed protein interfaces can be assembled into reconfigurable two-dimensional arrays which template calcite nanocrystals. By fine-tuning RFdiffusion2 on repeat protein scaffolds, we further enable the design of protein architectures which selectively form aragonite, a metastable polymorph of calcium carbonate, in nucleation conditions that otherwise result in a mixture of phases. Extending beyond inorganics found in biological systems, we show that lattice-matched protein designs template cobalt carbonate formation: a flat helical repeat protein interface promotes unconfined growth, whereas soluble D3 cage assemblies yield more homogenous cobalt carbonate nanocrystals confined to the interior of the cage. These protein-cage cobalt carbonate hybrid materials function as electrocatalysts for alkaline water splitting. Our results demonstrate the potential of deep learning-based methods to unlock the structural and functional activity of protein-mineral composites.

biochemistry↗

bioRxiv2026

Distinguishing Photoacoustic and Photothermal Neuron Stimulation Through Quantitative Mapping Spatiotemporal Field Evolution

Neuromodulation is a rapidly advancing strategy for modulating brain function and treating neurological disorders, yet the mechanisms of optical neural stimulation remain incompletely understood. A central challenge is that photoacoustic (PA) and photothermal (PT) effects are typically generated simultaneously and evolve on overlapping spatial and temporal scales, making their contributions to neuronal activation difficult to distinguish. Here, we overcome this limitation by integrating two carbon-based emitters with a spatial-offset pump-probe imaging platform to distinguish PA and PT neuromodulation through direct mapping of spatiotemporal field evolution. The two emitters produce nearly identical thermal fields while exhibiting a 26-fold difference in acoustic output, enabling decoupled comparison of thermal and acoustic contributions. To directly characterize the physical fields, we establish a spatial-offset pump-probe imaging system capable of visualizing both temperature and pressure evolution, confirming matched thermal profiles between the two emitters. Neuronal stimulation experiments further show that neurons are markedly more responsive to PA stimulation than to PT stimulation. Beyond resolving a longstanding mechanistic question, this work demonstrates the enhanced efficiency of PA stimulation and provides general guidance for designing high-performance optical neural interfaces.

neuroscience↗

bioRxiv2026

Selective inhibition of respiratory complex I reveals a bioenergetic vulnerability in Francisella

F. tularensis is a highly infectious Gram-negative bacterial pathogen that causes tularemia, a re-emerging zoonosis of public health concern. Here we identify respiratory complex I as a selective vulnerability in Francisella and define the mechanism of action of a pyrazole compound, tolfenpyrad, with species-specific antibacterial activity. Using F. novicida as a surrogate model, we demonstrated that tolfenpyrad selectively inhibits growth with no measurable effect on E. coli or P. aeruginosa. Tolfenpyrad rapidly suppressed oxygen consumption, depleted ATP, collapsed proton motive force, and induced reactive oxygen species, indicating disruption of bacterial metabolism. Biochemical assays demonstrated selective inhibition of NADH-dependent respiration and membrane-associated NADH oxidation, whereas succinate-driven respiration was unaffected. Moreover, the alternative NADH dehydrogenase (ndh) was not required for tolfenpyrad activity. Structural docking identified a potential tolfenpyrad-binding pocket within the membrane subunit NuoM. These findings reveal species-specific inhibition of Francisella complex I and establish respiratory metabolism as a promising antimicrobial target in these bacteria.

microbiology↗

bioRxiv2026

Reorganization of Human Brain Waves Across Diverse States of Consciousness

Brain waves are ubiquitous phenomena of human brain activity. As they propagate, they coordinate neural communication, shaping conscious perception. Understanding how brain waves unfold across space and time is thus critical for uncovering the neural mechanisms that support and suppress consciousness. Here, we analyzed data from the Human Connectome Project alongside multiple independent human datasets of various states of consciousness collected during non-rapid eye movement sleep, propofol anesthesia, and psychedelic states produced by lysergic acid diethylamide, N,N-dimethyltryptamine, psilocybin, nitrous oxide, and ketamine. We then applied complex principal component analysis to map spatiotemporal propagation patterns of blood oxygen level-dependent activity across the human brain, under these diverse states of consciousness. We identified four dominant motifs of wave propagation: a global synchronized wave supporting unimodal-transmodal propagation, an anti-correlated unimodal-transmodal wave, an anti-correlated task-positive/task-negative wave, and an anti-correlated visual-somatomotor wave. Among them, the global wave exhibited the most pronounced state-dependent reconfiguration: in diminished states (sleep and anesthesia), the time needed for the wave to propagate across brain regions consistently increased and the distribution of regional contributions to the waves power became more spatially concentrated and heterogeneous across individuals, indicating slower, more fragmented, and less stereotyped dynamics. In contrast, propagation duration decreased under psychedelic states, reflecting accelerated global wave dynamics alongside a trend towards more spatially distributed and uniform regional contributions, consistent with a more integrated global wave propagation pattern. Beyond this global mode, diminished states slowed propagation primarily along the unimodal-transmodal axis, whereas psychedelic states selectively accelerated propagation along the task-positive/task-negative axis. Together, our findings reveal that diminished (sleep and anesthesia) and psychedelic states alter the spatiotemporal structure of wave propagation across the brain in opposite and distinct ways, providing a unifying account of how macroscale brain dynamics are dynamically reshaped under pharmacological and endogenous perturbations of consciousness.

neuroscience↗

bioRxiv2026

Distinct defense strategies against interbacterial antagonism underpin Acinetobacter persistence in polymicrobial environments

Despite intense interbacterial antagonism mediated by mechanisms such as the type VI secretion system (T6SS), pathogenic Acinetobacter frequently persist within highly competitive polymicrobial infections. How these pathogens navigate such hostile environments to achieve co-existence remains poorly understood. Here, we show that pathogenic Acinetobacter employ distinct, multifaceted strategies to resist elimination by both distantly related competitors and closely related kin. T6SS-active strains outcompete heterologous bacteria by deploying a large and diverse repertoire of antibacterial effectors. In contrast, some naturally T6SS-deficient strains resist exogenous T6SS attacks by elaborating a unique, high-density polysaccharide capsule (KL34) that functions as an effective physical shield. Most intriguingly, we uncover a mechanism that prevents lethal competition among kins. A conjugative multidrug-resistant plasmid encoding T6SS repressors is transferred into aggressive strains upon T6SS-mediated attack, leading to suppression of their antibacterial activity. We also found that conjugation is induced by T6SS attack, which effectively suppresses attacking kin and promotes co-infection in vivo. Together, these findings reveal a dynamic and multilayer defense program that enables Acinetobacter to withstand interbacterial warfare while facilitating co-existence. Our study establishes a paradigm in which damage-triggered plasmid transfer enforces targeted suppression, reshaping microbial interactions in polymicrobial communities.

microbiology↗

bioRxiv2026

Pansoma, a machine learning tool for identifying somatic variants using pangenome graphs

Somatic variant calling, the identification of mutations in non-germline cells acquired over an individuals lifetime, is critical for studying diseases, including cancer, and for developing precision oncology strategies. Traditional somatic variant calling methods rely on linear reference genomes, which do not adequately capture human genetic diversity and result in reference bias, compromising the accuracy of somatic variant detection. Recently developed graph-based human pangenome reference represents diverse genetic variants across human populations and has promised to drive advances in many genetics and genomics studies. In this study, we introduced Pansoma, a novel pangenome-native and machine learning-based tool specifically designed for somatic variant calling using a pangenome graph reference. Pansoma performs somatic variant detection from both short- and long-read sequencing data by learning tensor representations of alignment on graph nodes rather than on a linear reference. Pansoma outputs variant representations anchored to the pangenome graph paths and conventional somatic variant calls remapped to the linear reference. Additionally, we provide accompanying bioinformatics tools tailored for graph-based genomic data management and variant calling results analysis. Benchmarking shows that Pansoma not only improves tumor-only somatic variant detection but also preserves graph-specific variant representations that are not directly recoverable from linear- reference outputs.

genomics↗

bioRxiv2026

M1 macrophage-mediated lymphangiogenesis aggravates liver fibrosis via MDK/YAP signaling pathway

BackgroundLymphangiogenesis plays a critical role in various liver diseases, yet its function in liver fibrosis remains controversial. This study aimed to explore the role of lymphangiogenesis in liver fibrogenesis and its underlying regulatory mechanisms. MethodsLiver fibrotic mice were established by carbon tetrachloride (CCl4) or Thioacetamide (TAA)-induced injection or bile duct ligation. Lymphatic vessels were marked by podoplain (Pdpn) staining in mice and D2-40 staining in clinical samples. Lymphatic vessels area and density were measured to indicate lymphangiogenesis. Multiplexing immunohistochemistry was used to detect co-localization of proteins. ResultsIn the present study, we first verified increased lymphangiogenesis in human and murine fibrotic livers. Afterwards, we identified VEGFC rather than VEGFD as the primary driver of lymphangiogenesis in liver fibrosis. Furthermore, we demonstrated that M1 macrophages serve as the major source of VEGFC. Founctional studies revealed that VEGFC-mediated lymphangiogenesis exacerbates hepatic fibrosis, while its inhibition alleviated fibrosis. Bioinformatic analysis uncovered Midkine (MDK) as a key downstream of lymphangiogenesis. Both in vivo and in vitro studies confirmed that exogenous MDK promotes liver fibrosis via activating hepatic stellate cells (HSCs), whereas MDK inhibition counteracts the profibrotic effects of VEGFC-induced lymphangiogenesis. Importantly, we discovered that MDK activates HSCs through the Hippo/YAP signaling pathway. ConclusionsM1 macrophage-mediated lymphangiogenesis aggravates liver fibrosis via MDK secretion, which activates HSCs. These findings provide novel insights into coordinated crosstalk between macrophages, lymphatic endothelial cells and HSCs in liver fibrosis and suggest lymphangiogenesis and MDK as potential therapeutic targets for fibrotic liver diseases.

molecular biology↗

bioRxiv2026

Novel Muscle-Tropic AAV Capsids with Dramatically Enhanced Transduction and Safety Profiles in Non-Human Primates

Adeno-associated virus (AAV) gene therapy holds immense promise for treating muscular dystrophies, yet its efficacy and safety are constrained by the suboptimal tissue tropism of natural serotypes. Here, we employed the REACH platform, which combines rational design and directed evolution, to engineer muscle targeting vectors. Systemic administration in non-human primates (NHPs) revealed that lead candidate M1 mediates a >10-fold increase in skeletal muscle transduction compared to the AAV9 and 2-3 fold higher than MyoAAV, while concurrently achieving a remarkable 183-fold reduction in liver distribution. Furthermore, M1 exhibited significant de-targeting from key off-target tissues, including dorsal root ganglia (11 fold), lung (27 fold), spleen (2 fold), and kidney (2 fold). These findings demonstrate that the REACH platform can generate AAV capsids with simultaneously enhanced muscle tropism and favorable safety profiles, addressing a critical bottleneck in muscle-directed gene therapy.

bioengineering↗

bioRxiv2026

Single-Cell Translation and Apoptosis Profiling to Define Human CD34⁺ Cell Response to Specific Factors

Global mRNA translation is a defining functional property of hematopoietic stem cells (HSCs) and is increasingly recognized as a critical axis of dysregulation in myelodysplastic syndromes (MDS) and other clonal hematopoietic disorders. Yet the quantitative measurement of protein synthesis at single-cell resolution across phenotypically defined HSPC subpopulations, in parallel with apoptotic state, is technically challenging. Here we describe and validate a single-tube flow cytometry protocol that simultaneously quantifies global protein synthesis by O-propargyl-puromycin (OP-Puro) incorporation and intracellular cleaved Caspase-3 with cell immunophenotyping across the canonical CD34+ HSPC hierarchy in cryopreserved human cord blood (CB) CD34+ cells. The protocol enables quantitative assessment of key dynamic cell processes in defined subsets of primary hematopoietic cells on a standard flow cytometer. We apply this assay to a four-condition factor-omission analysis of the canonical SR1 + UM729 + dmPGE2 ex vivo expansion cocktail across three independent CB donors. The analysis assigns each compound a distinct functional profile: UM729 constrains protein synthesis and supports apoptotic priming across the hierarchy; SR1 maintains a pro-survival state without modulating translation; and dmPGE2 promotes HSC cycling and progressive exit from the primitive state, with minimal direct effect on the translation or apoptotic axes measured here. This analysis resolves three mechanistically distinct small-molecule signatures using a protocol directly transferable to clinical biobank specimens. We propose it as a functional-state analytic platform that may be useful for patient-derived CD34+ cells from MDS and other myeloid neoplasms in which translational dysregulation is a recognized pathological feature.

cell biology↗

bioRxiv2026

Prediction of Transcription Factor DNA Binding Affinity with High-Throughput Kd Measurements and Deep Learning

Transcription factors (TFs) regulate gene expression through specific interactions with genomic DNA. While TF binding motifs from public databases describe sequence preferences, quantifying genome-wide affinity (Kd) is highly desirable for a more accurate thermodynamic description. Here, we report ivtFOODIE (in vitro FOOtprinting with DeamInasE), an assay that leverages deaminase-mediated cytosine-to-uracil conversion to measure Kd values for a given TF across accessible genomic regions from human cells. By pre-training on TF binding sites from JASPAR and fine-tuning with our ivtFOODIE data from 46 TFs representing 13 different DNA-binding domains (DBDs), we developed Seq2Kd, a deep learning model capable of predicting a TFs absolute binding affinity on DNA sequences. Seq2Kd enables de novo motif discovery of [~]500 previously uncharacterized human TFs and reveals the effects of genetic variation both in TF-coding regions and DNA-binding sites on gene expression and disease susceptibility. By correlating predicted affinity changes with the sign and magnitude of expression quantitative trait locus (eQTL) effects, we stratified TFs into activator-like and repressor-like groups. Compared to clinically benign variants, pathogenic single-nucleotide variants (SNVs) within regulatory and protein-coding regions show significantly larger predicted shifts in Kd. We provide an interactive web portal, the ENcyclopedia of Transcription-factor Interactions with Regulatory Elements (ENTIRE), which integrates the Seq2Kd model with the ivtFOODIE dataset. This resource offers thermodynamic prediction for TF-DNA interactions for functional genomics and human disease.

biophysics↗

bioRxiv2026

Chronic diazepam reveals excessive homeostatic gain in SOD1G93A mouse spinal motoneurons

Motoneurons are under strong pressure to maintain stable motor output throughout an individual life, through homeostatic regulation of their electrical properties. Dysregulated spinal motoneuron excitability has long been implicated in the pathogenesis of amyotrophic lateral sclerosis (ALS). Recent work in SOD1G93A mice suggests that the homeostatic response of motoneurons becomes dysregulated as cellular processes are disrupted by the disease, causing fluctuations in motoneuron electrical properties. Yet, few studies directly test whether ALS motoneurons respond differently than wild type motoneurons to a common chronic perturbation. Here, we used in vivo electrophysiology to test whether motoneurons from pre-symptomatic SOD1G93A mice modulate excitability differently than wild type motoneurons in response to the same homeostatic perturbation: chronic inhibition exerted by the benzodiazepine diazepam. Using linear mixed-effects statistical models, we assessed whether diazepam treatment differentially modulated passive properties, firing behavior, spike properties, and/or synaptic inputs in SOD1G93A versus wild type motoneurons. We identified a significant genotype x treatment interaction effect selectively for properties related to passive membrane integration and spike initiation, including membrane time constant, peak input resistance, and recruitment current. In contrast, firing gain, spike waveform characteristics, and synaptic inputs were largely unaffected. These findings indicate that sustained inhibitory perturbation selectively triggered overactive intrinsic compensatory mechanisms in SOD1G93A motoneurons rather than inducing widespread changes in firing or synaptic transmission. Together, our results provide direct evidence for over-active homeostatic control of motoneuron excitability and support a view of motoneuron dysfunction in ALS as a problem of altered feedback regulation rather than simply hyper- or hypo-excitability. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=52 SRC="FIGDIR/small/725609v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@25f125org.highwire.dtl.DTLVardef@faf2c9org.highwire.dtl.DTLVardef@15993a8org.highwire.dtl.DTLVardef@1ed006a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Rapid imaging of lysyl oxidase activity and fibrogenesis with a turn-on fluorophore

Fibrogenesis is essential to wound healing, but aberrant fibrogenesis is a driver of many chronic diseases and cancers. Lysyl oxidases (LOX) play a pivotal role in fibrogenesis by catalyzing the oxidation of lysine residues to reactive aldehydes (allysine) in collagens and elastin, resulting in the crosslinking and excessive deposition of these extracellular matrix components. Currently, rapid and robust histological assays to visualize the spatial distribution of LOX activity are lacking, hindering the precise validation of anti-fibrotic therapies. Here, we present a histological fluorescent staining method to visualize fibrogenesis (active fibrosis) and LOX activity in tissue sections utilizing a bioorthogonal tag and a click reaction with a turn-on fluorophore. Notably, requiring only two commercial reagents, this protocol can be completed in under two hours and is compatible with other imaging modalities, including second-harmonic generation and immunofluorescence staining. We validated this method across various healthy and fibrotic mouse and human tissue specimens.

bioengineering↗