Biology subjects

Huang, Q.

Publications and source records attributed to Huang, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

Matched Plasma and Tissue Proteomics Reveal the Selective Nature of Circulating Biomarkers of Human Aging

Aging is systemic, yet how circulating proteins reflect molecular aging within solid tissues remains unclear. We profiled 5,415 proteins using Olink Explore HT in 178 adults aged 20-87 years, including matched plasma-muscle (n = 56) and plasma-ovary (n = 24) pairs. Plasma-tissue concordance was limited, with 50 muscle and 17 ovarian proteins significantly correlated, indicating that plasma selectively reflects tissue protein abundance. Age-correlated proteins and pathways differed markedly across sex and tissue strata, Including immune/inflammatory signatures in female plasma, vascular and extracellular-matrix pathways in male plasma, and collagen remodeling in the ovary. Expression Variation Analysis further revealed predominantly context-specific age-related changes in protein coordination, including FAS/FADD/TRAIL death-receptor networks in plasma and a TP53-CDKN1A senescence-associated axis in muscle. Exploratory multivariate models identified additional plasma associations with subsets of tissue proteins, including tissue-restricted muscle proteins. Together, these findings define plasma as a selective, context-dependent window into human tissue aging.

systems biology↗

bioRxiv2026

Motor learning refines premotor cortical constraint during skilled forelimb behavior

Motor learning transforms variable actions into reliable skilled behavior, but how premotor cortex supports this transformation remains unclear. We longitudinally recorded bilateral local field potentials and single-unit activity from the rat rostral forelimb area while animals acquired a single-pellet retrieval task. Here, we show that improved skill was accompanied by reduced, rather than increased, task-related premotor recruitment. Despite this attenuation, firing remained dominated by suppression around pellet retrieval, and stronger pre-retrieval suppression was associated with greater odds of successful performance. Population neural state analysis further showed that successful actions were most strongly coupled to sustained pre-retrieval engagement early in learning, whereas later success occurred with less population-level engagement. These findings reveal premotor cortical constraint as a population-level process that is progressively refined as motor learning transforms variable actions into reliable skilled behavior.

neuroscience↗

bioRxiv2026

BI-TfR1 CapX rapidly transits the blood-brain barrier for efficient, low-dose gene delivery throughout the CNS

Safe, efficient gene delivery throughout the CNS remains a central obstacle to treating genetic diseases of the brain and spinal cord. We describe BI-TfR1 CapX, a human transferrin receptor (TfR1)-binding AAV capsid that, after a low intravenous dose in adult humanized TFRC mice, transduced more than 80% of cortical and spinal neurons and ~60% of cortical astrocytes, with reduced distribution and expression in several peripheral tissues relative to AAV9. Unlike other engineered BBB-crossing capsids, CapX bound the CNS vasculature within minutes and a large fraction of its genomes reached parenchymal nuclei within 24 hours. Delivering a Prnp-targeted epigenetic silencer (Prnp-CHARM), CapX reduced brain Prnp mRNA by over 95% requiring 18-fold fewer vector genomes per brain cell than AAV-PHP.eB for 50% lowering. A CapX delivered dual-vector cytosine base editor installed a protein-truncating PRNP stop codon lowering brain prion protein by 80%. These properties make CapX an attractive vehicle for human CNS gene therapy.

neuroscience↗

bioRxiv2026

Functional reorganization of large-scale brain systems underlies emotion regulation maturation

Emotion regulation via cognitive reappraisal is essential for socioemotional development and mental health, yet the organizational logic of its supporting brain systems across youth remains unclear. Using a large multisite cohort, we demonstrate that maturation of reappraisal capacity reflects reorganization of a distributed architecture rather than progressive strengthening of prefrontal control. Reappraisal robustly reduced negative affect, with non-linear gains concentrated between 6 and 10.5 years. Bayesian systems identification resolved this architecture into four functionally distinct systems-reappraisal-specific, common-appraisal, modifiable-emotion, and non-modifiable-emotion components-spanning prefrontal-control, salience, default-mode and dorsal-attention networks. Age-related variation in anterior temporal cortex, emerged as essential hub, statistically accounted for developmental gains in reappraisal success. Multivariate modelling together with intersubject analyses further identified a cross-site-generalizable whole-brain reappraisal signature and revealed an age-dependent shift in brain-behaviour coupling, with neurobehavioural convergence increasing with age. These findings establish distributed network reorganization as a core mechanism of emotion regulation development and provide mechanistic targets for stage-matched interventions.

neuroscience↗

bioRxiv2026

Pichinde virus models intrauterine infection by hemorrhagic fever-causing arenaviruses

Arenavirus infection during pregnancy can cause severe maternal disease, congenital infection, and fetal demise. Many arenaviruses are endemic in economically disadvantaged areas and must be studied in high containment laboratories, which has limited our understanding of arenavirus pathogenesis in the placenta. Pichinde virus (PICV) is a nonpathogenic arenavirus that recapitulates many aspects of viral hemorrhagic fever in guinea pigs. Using a combination of experiments in human placental cells and guinea pigs, we characterized the tropism and impact of PICV infection during pregnancy. PICV replicated in human trophoblast stem cells (TSCs), TSC-derived trophoblasts, and explanted term placenta. When guinea pigs were infected at mid-gestation, PICV caused fetal demise. High infectious titers were recovered from placenta and decidua, but PICV was infrequently detected in fetal tissues or amniotic fluid. In situ hybridization confirmed that the placenta, decidua, and fetal membranes were all infected by the virus. Transcriptional profiling of PICV-infected human trophoblasts and guinea pig tissues revealed that infection upregulated canonical antiviral responses, which could contribute to placental dysfunction and pregnancy loss. Thus, PICV is safe and tractable model of zoonotic arenavirus infection during pregnancy with utility for preclinical therapeutic and vaccine development.

microbiology↗

bioRxiv2026

Aging and reorganization of the neural hierarchy underlying action perception: older adults prioritize affective-communicative information

Everyday action perception unfolds in complex contexts, requiring coordinated processing from low-level visual information to higher-level inferences about action types and social interactions. Aging is accompanied by sensory and cognitive changes, raising the question of how these processes may be altered. Here, we combined action similarity judgments with analyses of time-resolved and source-localized brain activity measured with magnetoencephalography (MEG) to investigate age differences in action perception when younger and older adults viewed naturalistic actions. Using cross-validated variance partitioning within a multivariate representational framework, three key findings were uncovered. First, affective-communicative features predicted similarity judgments better than, and independent of, visual and action-related features in both age groups. Second, neural processes in both groups followed a hierarchy from visual to action-related and affective-communicative features and recruited similar functional regions. However, older adults showed delayed visual processing but earlier affective-communicative processing, indicating selective prioritization rather than uniform slowing of subprocesses. Third, when sensory uncertainty was increased through visual blurring, older adults showed hierarchical reorganization, with affective-communicative features emerging earlier than action-related features, whereas younger adults preserved the original hierarchy. Together, these findings unveil adapted information prioritization in healthy aging, whereby socially meaningful information increasingly guides action perception when sensory input becomes unreliable.

neuroscience↗

bioRxiv2026

Algebraic Morphogenesis Through Cochain Operators

AO_SCPLOWBSTRACTC_SCPLOWCellular automata and graph reaction-diffusion systems encode local spatial interactions in different mathematical forms. We develop a cochain-operator calculus for these two settings. Over a finite field Fq, every local rule on a finite neighborhood has a unique reduced polynomial representative. On an oriented line, the coboundary and endpoint maps recover the left and right shifts. Our main theorem shows that these operators, together with linear operations, constant cochains, and the degree-zero cup product, generate every finite-radius polynomial cellular automaton. Explicit formulas for Rules 30, 110, and 22 show how reflection-invariant linear coupling, directed transport, and nonlinear neighbor interactions enter the calculus. On a general graph, d*d is the unweighted combinatorial Laplacian and enters a graph reaction- diffusion recurrence. Over [R], the term - Dd*d with D [≥] 0 admits the usual diffusion interpretation; over Fq, the corresponding expression defines modular coupling without an intrinsic order. In the morphogenetic examples, we therefore distinguish pattern-generating dynamics from finite-state observation and use the Betti numbers of active induced subcomplexes to summarize observed patterns. This yields a common algebraic representation without identifying real-valued diffusion with finite-field dynamics.

biophysics↗

bioRxiv2026

Extracellular vesicle associated nucleic acids and proteins as a complementary fraction for fish biodiversity monitoring and physiological signal recovery

Monitoring the biodiversity and physiological condition of aquatic organisms under environmental stress is central to aquatic ecosystem management. Environmental nucleic acid methods (eDNA and eRNA) have transformed biomonitoring but face well-documented limitations, including susceptibility to degradation, difficulty distinguishing living from legacy or transported signals, and limited capacity to report organism condition. Extracellular vesicles (EVs) released from all kinds of species, are stable and widespread vesicles in environment, showing biomarker potential. Here we evaluate whether nucleic acids and proteins recovered from EVs provide a complementary capture fraction that helps address these limitations. All four targets (eDNA, eRNA, EV-DNA, EV-RNA) shared an identical 12S rRNA metabarcoding workflow and differed only in the pre-analytical capture step, filtration for bulk environmental nucleic acids versus sequential 0.22 {micro}m filtration, tangential flow filtration, and ultracentrifugation for the EV-encapsulated fraction. In a controlled aquarium, EV-DNA recovered all seven reference species (100% sensitivity) versus 85.7% for bulk methods, including a low-abundance detection of Anguilla japonica that warrants independent confirmation. In field sampling at Xinglinwan Reservoir, EV-RNA recovered 11 of 12 expected species (91.7% sensitivity) compared with 50-58% for bulk methods, including four reference taxa detected only by the EV fraction. EV-based methods also captured more even community representation, and EV-RNA showed lower human-read contamination than eDNA. Metaproteomic analysis of reservoir EVs recovered fish-derived proteins, dominated by Cyprinus carpio, including candidate stress-associated functions (chaperones, metallothioneins, oxidoreductases), independently corroborating the EV-based detection of C. carpio. Their abundance varied with seasons, suggesting their ability to respond to environmental changes. Together, these results indicate that EV-associated nucleic acids and proteins constitute an informative complementary fraction for integrated biodiversity and physiological-signal monitoring in impacted aquatic environments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/735187v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@ee0e6borg.highwire.dtl.DTLVardef@f4d1daorg.highwire.dtl.DTLVardef@fd5123org.highwire.dtl.DTLVardef@da0ddc_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Most inhibitors with defined yeast targets have limited activity against the microsporidian Nematocida parisii

Microsporidia are obligate intracellular parasites that infect diverse animals. Budding yeast has long been used to define core molecular pathways and inhibitors that target them. To test whether these compounds can target conserved pathways in the microsporidian Nematocida parisii, we assessed 15 inhibitors with defined yeast targets that had not previously been tested for effects on infection of Caenorhabditis elegans. Most showed little activity against N. parisii, except tunicamycin. These results identify tunicamycin as a potential tool for studying endoplasmic reticulum stress in microsporidia, while indicating that most yeast-targeted inhibitors are largely ineffective in this system.

microbiology↗

bioRxiv2026

A Neuroimmune Feedforward Circuit Linking REM Sleep with Stress-Related Behavioral Susceptibility

Rapid eye movement (REM) sleep is strongly associated with stress susceptibility, yet the underlying neuroimmune mechanisms remain unclear, limiting therapeutic targeting. Here, we identify a pathway by which chronic stress increases splenic nerve activity, promoting recruitment of circulating monocytes to the brain through the choroid plexus. In the external globus pallidus (GPe), recruited monocytes drive regionally restricted microglial remodeling toward a pro-inflammatory state. These microglia, in turn, potentiate the sustained excitability of parvalbumin-positive (PV) neurons via IL6-gp130 signaling. Functionally, activity of GPe PV neurons during REM sleep, but not wakefulness, bidirectionally regulates anxiety-like and defensive behaviors, establishing REM sleep as a critical state through which this neuroimmune circuit governs behavioral susceptibility. Together, these findings establish a neuroimmune feedforward mechanism linking peripheral immune activation to neuronal dysregulation underlying behavioral abnormalities, and position REM sleep as a predictive and actionable physiological entry point for mitigating stress-related emotional dysregulation.

neuroscience↗

bioRxiv2026

ParSeek: Accurate cryo-EM particle picking with a deep learning model trained on synthetic data

Accurate particle picking from noisy cryo-EM micrographs is essential for high-resolution reconstruction. Current deep learning methods rely on manually annotated data, which is labor-intensive, subjective, and limits particle recall under low signal-to-noise ratio (SNR). Here we introduce ParSeek, an automated picker trained entirely on synthetic data without human annotation. Synthetic micrographs are generated by projecting known 3D structures into realistic background patches that reproduce experimental noise. On seven public cryo-EM datasets, ParSeek outperformed Topaz and CryoSegNet on four datasets, achieving the highest F1-score (up to 0.82) and reaching 0.63 on a challenging membrane protein dataset. Density maps from ParSeek-picked particles showed cross-correlation coefficients up to 0.995 with the reference and a minimal resolution difference of 0.1 [A]. ParSeek also overcame severe orientation bias on an influenza dataset, yielding a reasonable reconstruction. Applied to three experimental datasets (an antibody-antigen complex and two GPCRs), ParSeek enabled reconstructions at 5.0 [A], 4.0 [A], and 2.8 [A], respectively. The 2.8 [A] map resolved side-chain densities and ligand flexibility. This study establishes a fully synthetic-data-driven strategy that eliminates manual annotation for training cryo-EM deep-learning models, paving the way for automated, unbiased particle picking.

molecular biology↗

bioRxiv2026

Protein inverse folding through joint modeling of surface and backbone geometry

Inverse protein folding aims to generate amino acid sequences compatible with a given protein structure. While recent deep learning methods have achieved strong performance by conditioning on residue-level backbone geometry, backbone-only representations insufficiently constrain surface-exposed residues and thus incompletely capture the structural determinants of sequence identity. Here we propose Surleton, a structure-aware inverse folding framework that jointly models backbone geometry and protein surface organization. By integrating complementary surface geometric information, Surleton refines the conditional sequence distribution and improves the balance of sequence modeling across buried and exposed residues. On the CATH4.2 and SCOPe benchmarks, Surleton consistently outperforms backbone-only baselines in sequence recovery, sequence similarity, and predictive confidence, with especially strong improvements on surface-exposed residues. Together, these findings indicate that protein surface geometry serves as a complementary source of structural constraint and that surface-aware modeling may provide a promising direction for improving inverse protein folding.

bioinformatics↗

bioRxiv2026

DNA methylation signatures of mismatch repair-deficient colorectal cancer

BackgroundColorectal cancer (CRC) is a molecularly heterogeneous disease shaped by both genetic and epigenetic alterations. Approximately 15% of CRCs display widespread CpG island hypermethylation, known as the CpG Island Methylator Phenotype (CIMP). CIMP-high (CIMP-H) tumours frequently exhibit MLH1 promoter hypermethylation, leading to mismatch repair deficiency (MMRd) and microsatellite instability (MSI). However, DNA methylation patterns associated with MSI, independent of CIMP and MLH1 silencing, and the influence of clinical variables such as anatomical location and patient age on the CRC methylome remain poorly characterised. MethodsWe performed epigenome-wide DNA methylation profiling of 259 primary CRC tissue samples using the Illumina EPICv2 array, comparing differential methylation between MSI and microsatellite stable (MSS) CRC, adjusting for tumour purity, MLH1 promoter methylation, CIMP status, and anatomical location, to account for known confounders. We further evaluated the independent effects of anatomical location and patient age on global methylation patterns. ResultsEpigenome-wide differential methylation between MSS and MSI CRC was dominated by MLH1 promoter hypermethylation. After adjusting for MLH1 hypermethylation and CIMP status, we identified a distinct set of 656 CpG sites associated with MMRd independent of MLH1 silencing. These included hypermethylation at LRP6, GSK3{beta}, and CDK12, implicating altered WNT signalling and transcriptional regulation pathways. Comparison of MSI subgroups revealed the co-occurrence of MLH1 hypermethylation with promoter hypermethylation at TXNRD1. Anatomical location showed a strong independent effect on methylation patterns, while we observed only modest effects of patient age on the CRC methylome after adjustment for confounders. ConclusionsWe identified a distinct methylation profile distinguishing MSS and MSI CRC, including MLH1-independent markers of MMRd, as well as novel differentially methylated loci within MSI subgroups. We further showed that anatomical location has a strong independent impact on the CRC methylome. Together, these findings refine the molecular characterisation of CRC and highlight potential epigenetic markers that could inform patient stratification and precision oncology.

cancer biology↗

bioRxiv2026

Sequence Design and Phylogenetic Inference with Generative Flow Networks

Phylogenetic inference remains computationally challenging due to the exponentially growing tree topology search space, and current methods rely heavily on multiple sequence alignments (MSAs) which are expensive and error-prone. We propose AncestorGFN, a proof-of-concept approach leveraging Generative Flow Networks (GFlowNets) for simultaneous sequence generation and phylogenetic exploration without requiring explicit MSAs. Our method learns to generate sequences matching a target distribution while the flow trajectories implicitly encode structural relationships among sequences. We demonstrate that greedy traceback on maximum-flow trajectories recovers shared intermediate states suggestive of common ancestry, and evaluate on the let-7 microRNA family where the learned flow structure qualitatively captures phylogenetic branching patterns. Furthermore, beam search at inference time discovers novel sequences clustering near known targets, suggesting applications in de novo sequence design. This work establishes an initial foundation for alignment-free phylogenetic exploration using generative models.

synthetic biology↗

bioRxiv2026

Nanosecond laser-driven proton FLASH spares normal tissue cells by sustaining mitochondrial homeostasis and attenuating ferroptosis

Radiotherapys clinical utility remains fundamentally constrained by the collateral damage to healthy tissues. Ultra-high-dose-rate (UHDR) irradiation, or, FLASH-radiotherapy (FLASH-RT) has emerged as a transformative paradigm to mitigate such toxicity. However, the biological effects of FLASH-RT on the high-efficiency of tumor killing and normal tissue sparing remain poorly understood. In this work, we utilized a petawatt-class laser-plasma acceleration (LPA) platform to deliver discrete 12.9-nanosecond proton pulses at an extreme instantaneous dose rate of 1.94x107 Gy/s. This temporal singularity achieved a profound sparing effect in normal bronchial epithelial cells, evidenced by a nine-fold reduction in the lethal coefficient (from 0.47 to 0.05 Gy-1), while maintaining full tumoricidal potency against lung adenocarcinoma. Mechanistically, we demonstrated that LPA-FLASH could effectively bypass the ATF3-mediated stress response and circumvent the subsequent ferroptotic cascade. This molecular evasion could preserve the mitochondrial cristae integrity and trigger an adaptive bioenergetic ATP surge--a hallmark of metabolic resilience exclusively in healthy tissue cells. Therefore, our findings identify ferroptosis-mediated mitochondrial integrity as a unifying framework for selective normal-tissue protection at the physical limits of radiation delivery, and establish LPA-FLASH-RT as a potent, compact modality for next-generation oncology.

cell biology↗

bioRxiv2026

Programming Biomolecular Interactions with All-Atom Generative Model

Biomolecular interactions lie at the core of cellular life, spanning diverse molecular modalities from small molecules to nucleic acids and proteins. Nevertheless, design strategies remain separated despite shared physicochemical principles of molecular recognition. Here we present AnewOmni, a unified generative framework trained on more than 5 million biomolecular complexes, that enables transferable molecular design across molecular scales by assembling chemically meaningful building blocks at atomic resolution. We further introduce programmable graph prompts to support user-defined chemical, topological, and geometric steering during generation, exploring hybrid and unconventional chemistries beyond canonical structures. We demonstrate that transferable learning of interaction patterns and physical constraints across molecular modalities is possible, via an atom-to-block latent space capturing both atomic details and structural priors. The framework successfully designed small molecules, peptides, and nanobodies targeting the challenging KRAS G12D switch II pocket, as well as orthosteric peptides and allosteric small-molecule inhibitors for PCSK9 in the absence of known binding site, achieving 23%-75% success with only low-throughput validation, bypassing modality-specific high-throughput screening. AnewOmni is the first to succeed in functional molecular design across all scales, from small chemical entities to large biologics, and represents a stepstone towards general molecular reasoning engines, advocating a generative foundation model for biomolecular interactions to enter regimes where data and human intuition remain limited.

bioengineering↗

bioRxiv2026

Learning the All-Atom Equilibrium Distribution of Biomolecular Interactions at Scale

Biomolecular functions are governed by dynamic conformational ensembles rather than static structures. While models like AlphaFold have revolutionized static structure prediction, accurately capturing the equilibrium distribution of all-atom biomolecular interactions remains a significant challenge due to the high computational cost of molecular dynamics (MD). We present AnewSampling, a transferable generative foundation framework designed for the high-fidelity sampling of all-atom equilibrium distributions, which is the first model to faithfully reproduce MD at the all-atom level. It uses a quotient-space generative framework to ensure mathematical consistency and leverages the largest self-curated database of protein-ligand trajectories to date, with over 15 million conformations. Statistically, AnewSampling consistently outperforms all prior generative methods on the ATLAS monomer benchmark, and the all-atom capabilities of AnewSampling enable close statistical alignment with ground-truth MD for evaluating atomic biomolecular interactions in protein-ligand dynamics. Furthermore, AnewSampling successfully recovers coupled ligand and side-chain motions in CDK2 systems, overcoming a major sampling hurdle inherent to conventional MD. AnewSampling enables rapid exploration of conformational landscapes prior to intensive simulations, elucidating fundamental biophysical mechanisms and accelerating the broader design of functional biomolecules.

bioinformatics↗

bioRxiv2026

Dual-Logistic Analysis of Time- and Concentration-Dependent Phenotypic Efficacy Evaluation Integrating Drug Targets Information

Tumor heterogeneity highlights the necessity of precision cancer medicine, making the evaluation and screening of anticancer drugs a core challenge in cancer therapy. However, current cell-based efficacy assessment methods struggle to quantify the holistic impact of drugs on cellular behavior through specific target engagement. Here, we proposed a novel approach (DL-TCP-FRET) that integrates phenotypic and target-related evaluations: the logistic fitting analysis is performed on time- and concentration-dependent cellular phenotypic characteristics to construct a phenotypic score (P), while a target score (T) is established based on the FRET efficiency between target proteins. These two scores were then further combined to generate a unified drug efficacy score (PT). Validation in A549 cells demonstrated that our method can reliably distinguish EGFR-TKIs from non-targeted drugs. DL-TCP-FRET simplifies the experimental workflow of drug efficacy evaluation and improves the accuracy of targeted drug identification, providing a novel strategy for advancing precision cancer therapy.

cell biology↗