Biology subjects

Lyu, W.

Publications and source records attributed to Lyu, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Brain Mechanisms of Lexicality in Bilingual Emotion Processing

Understanding how native speakers and second language (L2) learners process language differently is fundamental to theories of language acquisition, comprehension, and use. A central debate in this literature concerns the inconsistent findings in emotional prosody processing between native speakers and L2 learners, partly attributable to stimulus lexicality: some studies use real words, whereas others use pseudowords. To resolve this discrepancy, we measured fMRI responses in 15 native speakers and 15 L2 learners while they listened to Mandarin real-word and pseudoword stimuli. Both groups engaged in overlapping auditory, cognitive, and affective regions, including the auditory cortex, inferior frontal cortex, superior temporal cortex, and the temporoparietal junction. However, the two groups showed distinct responses depending on lexicality: native speakers showed stronger recruitment of temporal regions for pseudowords, whereas L2 learners showed greater frontoparietal activation for real words. These patterns were consistent across positive and negative prosody conditions. Furthermore, among L2 learners, higher proficiency was associated with greater frontal activation for real words, but not pseudowords. Together, these findings demonstrate that the differences between native speakers and L2 learners depend critically on stimulus lexicality, highlighting the role of lexicality in bilingual emotion processing.

neuroscience↗

bioRxiv2026

A closed-loop reinforcement learning framework for rapid compound directed optimization

Generative artificial intelligence (AI) holds transformative potential for drug discovery, yet existing architectures typically operate in open loops without experimental feedback. Here we introduce rapid compound directed optimization (RCDO), a closed-loop reinforcement learning framework that accelerates the optimization process by bridging dry-lab computation with wet-lab feedback. RCDO couples a three-dimensional structure-guided generative model with a multi-level reward system updated after each design cycle using experimental measurements from all synthesized compounds, including inactive or developability-failed compounds. By continuously aligning the generative model with accumulated wet-lab measurements, RCDO substantially compresses optimization timelines. We evaluated RCDO through retrospective benchmarking against historical optimization trajectories and prospective wet-lab campaigns targeting ROR1, NLRP3, and NSD3. Across prospective evaluations, RCDO rapidly resolved key optimization bottlenecks within two to three design cycles: improving the oral exposure of an ROR1 inhibitor by 40-fold while maintaining antitumor efficacy, reducing CYP2C19 inhibition of an NLRP3 antagonist by 20-fold while preserving inflammasome activity, and boosting the binding affinity of an NSD3 hit by 18-fold. By directly coupling wet-lab feedback to generative learning, RCDO establishes an efficient platform for compound directed optimization, transforming AI-driven drug discovery from static generation into continuous experimental adaptation.

bioinformatics↗

bioRxiv2026

Decoding Immune Reconstitution Failure in People Living with HIV through Single-cell Genomics

Immune non-responders (INRs), a subset of people living with HIV (PLWH), fail to achieve full immune reconstitution and remain at increased risk of morbidity, mortality, and non-AIDS-related illnesses. As the mechanisms underlying this impaired immune recovery remain poorly understood, we performed single-cell multi-omics profiling on peripheral blood mononuclear cells from 43 INRs, 47 immune responders and 53 healthy donors. Our dataset comprises 2,744,009 transcriptomes and 1,226,658 chromatin-accessibility profiles across 58 identified immune cell types. INRs exhibited markedly elevated inflammatory signaling, increased apoptotic activity, and dysregulation of immune-activating ligand-receptor interactions. Additionally, we identified 2,996 interaction cis-eGenes and 5,938 cis-caPeaks, and validated key cell type-specific cis-xQTL effects associated with immune reconstitution failure. Furthermore, we identified 3,551 sc-eQTLs and 872 cell-state interaction eQTLs (ieQTLs) in CD4+ T cells. A genotype-specific upregulation of OAS3 in INRs, likely regulated by STAT1, was identified based on these results. We developed scPRISM (single cell Predictive Reconstitution Immune Status Model), a multi-modal framework that integrates scRNA-seq and scATAC-seq data to perform the dual tasks of differentiating disease states and predicting gene expression from chromatin accessibility, thereby deciphering the cell type-specific cis-regulatory basis of the disease. Our study delineates the transcriptional and epigenomic landscape of immune dysregulation in INRs and provides new genetic insights into HIV-associated immune reconstitution failure. These findings offer a foundation for developing biomarkers and precision therapies to restore immune function in PLWH.

genetics↗

bioRxiv2026

The binding of OTULIN restrains LUBAC activity to prevent TNF-driven immunopathology

Met1-linked ubiquitin chains (Met1-Ub), synthesised by the linear ubiquitin chain assembly complex (LUBAC) and disassembled by the deubiquitinase OTULIN, critically regulate inflammatory signalling. Although OTULINs activity is essential to prevent TNF-driven autoinflammatory pathology and embryonic lethality, the regulatory significance of its direct interaction with LUBAC remains unclear. Here, we reveal that mice harbouring a point mutation (OTULINY56A) in the OTULIN PUB-interacting motif, which disrupts OTULIN-LUBAC interaction, are viable without spontaneous immunopathology. However, OtulinY56A/Y56A mice exhibited hypersensitivity to TNF-induced toxicity, which was not prevented by inhibiting RIPK1 kinase-mediated cell death. Mechanistically, disruption of the OTULIN-LUBAC interaction led to Met1-linked autoubiquitination, which enhanced LUBACs activity and increased Met1-Ub accumulation at the TNF receptor signalling complex. This stabilised the signalling complex even after dissociation from TNF, increased NF-{kappa}B signalling and, contrary to loss of OTULIN or its activity, protected cells from TNF-induced apoptosis. During systemic Listeria monocytogenes infection, the increased response to TNF in OtulinY56A/Y56A mice exaggerated pathology without affecting bacterial burden. Collectively, we identify the physical association of OTULIN to LUBAC as a critical brake that restricts LUBACs function and Met1-Ub-dependent inflammatory signalling, thereby preserving tissue integrity and promoting disease tolerance during acute immune activation.

molecular biology↗

bioRxiv2025

Single-Molecule Imaging Reveals Transcription-Driven Supercoiling in Unconstrained DNA

In vitro studies of supercoiling dynamics have relied on externally applied force to twist constrained DNA. It is thus unknown whether transcription alone can generate supercoiling in topologically unconstrained DNA, and whether RNAP complexes could act as the topological barriers required to confine this stress. Here, using single-molecule imaging of 20k base pair long double strand DNA, we reveal that RNAP dynamically generates and confines supercoiling in unconstrained DNA. We demonstrate that multiple transcription events create transient topological domains, which allow plectonemes to stabilize between them; in contrast, a single transcription event does not lead to plectoneme formation. Furthermore, we show that this transcription-induced supercoiling is modulated by topoisomerase activity. Crucially, by observing that RNAP itself provides sufficient topological barriers, we establish that transcription-induced supercoiling is an inherently localized phenomenon. These findings redefine the physical basis of transcription-coupled supercoiling, providing a new mechanistic framework for modeling gene regulation based on local topology, with broader implications for genome editing and genome evolution.

molecular biology↗

bioRxiv2025

Factorial variation of saccade vigor with dual decision processes

Canonical stochastic models of decision-making treats decision and action as independent and sequential processes. However, studies involving limb movements consistently show that movement duration and kinematics are influenced by the quality of evidence. We tested whether saccade velocity varies with the quality of evidence in monkeys performing a visual search GO/NOGO task in which singleton elongation cued the GO/NOGO stimulus-response rule and the location of a color singleton specified saccade endpoint. We factorially manipulated the efficiency of stimulus-response cue discrimination by varying the elongation of the singleton and the efficiency of singleton localization by varying the color similarity between the singleton and distractors. The effectiveness of the manipulations was revealed by the response times on correct trials that were separately modified by the singleton localizability and stimulus-response cue discriminability, by the incidence of localization and response selection errors with separately modified error response times. Saccade velocity was higher on correct relative to error trials and was inversely proportional to response time. Saccade velocity was separately modified by singleton localizability and stimulus-response cue discriminability. Distinct patterns of error rates and saccade velocity across monkeys indicated individual differences in decision-making strategies. These findings demonstrate that the process selecting endpoints can influence both the timing and dynamics of saccadic eye movements. Incorporating saccade vigor can provide valuable constraints on biologically plausible decision models and help address the persistent challenge of model mimicry.

neuroscience↗

bioRxiv2025

High-throughput Single Cell Motility Analysis using Nanowell-in-Microwells

Cell motility is important to many biological processes including cancer, immune response, and tissue repair. Conventional assays measure bulk cell motility, potentially overlooking important heterogeneity and missing important high motility subpopulations. Here, we introduce a high-throughput single-cell motility assay using nanowell-in-microwell plates to precisely track single cell position and analyze their migratory trajectories. By physically confining individual cells in nanowells, we eliminate cell-cell interactions and simplify cell segmentation and tracking. Using this platform, we characterized the motility of single cells across different culture conditions to identify distinct motility phenotypes. Single-cell trajectory analysis revealed pronounced directional persistence, with cells predominantly maintaining their direction of travel and trajectory along nanowell boundaries. Additionally, our approach facilitates the generation of labeled image datasets suitable for AI models to rapidly identify cell motility phenotypes from single-cell images. Together, our platform provides a robust, scalable method to analyze cell motility phenotypes and migration behavior at single-cell resolution. Significance StatementA novel single-cell motility assay that uses confinement in nanowell-in-microwell to enable high-throughput profiling of single cell motility phenotypes.

bioengineering↗

bioRxiv2025

A global P-Process map to avoid P-value abuse

P-abuse is serious in difference identification analysis of data. How to avoid P-abuse is a huge challenge. Here, we evolve P-value (a single value) to P-Process (a global landscape of P-values under different sample size) to help researchers correctly recognize and use p-value. We observed -ln(P-Process) after rotation has very similar morphology with Wiener Process (or Brownian motion). Based on this property, for any sample size, we estimated the 95% fluctuation range of P-value and further estimated how many samples (N95()) could make sure 95% of P-values less than the given significant level . Tests proved that the estimation obtains a good performance with only a small number of samples in each group. For broader accessibility, a free web-service, P-Process Map, is available online to show the whole landscape of P-Process. At the end of the article, we explained 10 of the most typical P-abuse problems which can be easily voided by using P-Process. This "rethinking" of P-value from a higher position, which is profoundly different from the way we have seen this for the past century, would yield a new era - 2P era in which hypothesis testing is strongly required to evolve from P-value to P-Process.

bioinformatics↗

bioRxiv2025

IQI: Individualized Quantitative trait loci (QTL) Index

There is currently no standard efficient method to precisely detecting and characterizing the difference of quantitative trait loci (QTL) effect among groups and/or populations at individual level. The main reason is that the traditional global regression based QTL analyses can only derive an overall effect of genetic variants on the quantitative trait in a specific group. It is a big challenge to obtain the individual-level QTL effect, which is necessary for accurate testing and precise characterization. Here, we first proposed an individualized QTL index (IQI) that represents the degree of regulation between genetic variants and the trait for each individual. Based on IQI, Differential QTL (DQ) analysis framework was presented to accurately detect the case-control differences in more detail. In addition, IQI can be a new feature/biomarker applied to various accurate bioinformatics analysis, such as differential analysis, disease prediction, and survival analysis. Overall, IQI affords a new perspective on pathogenic mechanisms and will facilitate the study of genetic regulation more detailedly and precisely.

bioinformatics↗

bioRxiv2024

UltimateSynth: MRI Physics for Pan-Contrast AI

Magnetic resonance imaging (MRI) is commonly used in healthcare for its ability to generate diverse tissue contrasts without ionizing radiation. However, this flexibility complicates downstream analysis, as computational tools are often tailored to specific types of MRI and lack generalizability across the full spectrum of scans used in healthcare. Here, we introduce a versatile framework for the development and validation of AI models that can robustly process and analyze the full spectrum of scans achievable with MRI, enabling model deployment across scanner models, scan sequences, and age groups. Core to our framework is UltimateSynth, a technology that combines tissue physiology and MR physics in synthesizing realistic images across a comprehensive range of meaningful contrasts. This pan-contrast capability bolsters the AI development life cycle through efficient data labeling, generalizable model training, and thorough performance benchmarking. We showcase the effectiveness of UltimateSynth by training an off-the-shelf U-Net to generalize anatomical segmentation across any MR contrast. The U-Net yields highly robust tissue volume estimates, with variability under 4% across 150,000 unique-contrast images, 3.8% across 2,000+ low-field 0.3T scans, and 3.5% across 8,000+ images spanning the human lifespan from ages 0 to 100.

bioinformatics↗

bioRxiv2024

Enalapril mitigates aging by targeting antioxidative genes via phosphorylated Smad1/5/9

Aging increases the risk of a myriad of chronic diseases, which are expensive and difficult to treat owing to their various risk factors. Repurposing existing medications has accelerated the development of therapies aimed at slowing aging. In this study, we revealed that enalapril, a drug widely prescribed for hypertension, can improve both cellular senescence and individual health. Mechanistically, phosphorylated Smad1/5/9 act as pivotal mediators of the anti-senescence properties of enalapril. It stimulates downstream genes involved in cell cycle regulation and antioxidative defense, facilitating cell proliferation and diminishing the production of reactive oxygen species (ROS), thus increasing the antioxidative ability of enalapril. At the organismal level, enalapril has been shown to bolster the physiological performance of various organs; it notably enhances memory capacity and renal function and relieves lipid accumulation. Our work highlights the potential of enalapril to augment antioxidant defenses and combat the effects of aging, thereby indicating its promise as a treatment strategy for aging-associated diseases and its use for healthy aging.

cell biology↗

bioRxiv2024

A new synonym for Viburnum erosum (Viburnaceae) in East China, based on morphological and molecular evidence

The critical observations of living plants in the field, along with the examination of type specimens and protologues, led us to conclude that the key characteristics, including the length of the petiole, stipules and peduncles, as well as the shape of leaves of Viburnum fengyangshanense, all fall within the variation range of V. erosum. Additionally, molecular analysis of nuclear ribosomal internal transcribed spacer (nrITS) and three plastid DNA markers (rbcL, matK and ndhF) indicates that V. fengyangshanense and V. erosum are deeply nested within a clade. Therefore, based on morphological and molecular evidence, it is demonstrated that V. fengyangshanense should be regarded as a new synonym of V. erosum.

plant biology↗

bioRxiv2024

The Growing Little Brain: Cerebellar Functional Development from Cradle to School

Despite the cerebellums crucial role in brain functions, its early development, particularly in relation to the cerebrum, remains poorly understood. Here, we examine cerebellocortical connectivity using over 1,000 high-quality resting-state functional MRI scans of children from birth to 60 months. By mapping cerebellar topography with fine temporal detail for the first time, we show the hierarchical organization of cerebellocortical functional connectivity from infancy. We observe dynamic shifts in cerebellar network gradients, which become more focal with age while generally maintaining stable anchor points similar to adults, highlighting the cerebellums evolving yet stable role in functional integration during early development. Our findings provide the first evidence of cerebellar connections to higher-order networks at birth, which generally strengthen with age, emphasizing the cerebellums early role in cognitive processing beyond sensory and motor functions. Our study provides insights into early cerebellocortical interactions, reveals functional asymmetry and sex-specific patterns in cerebellar development, and lays the groundwork for future research on cerebellum-related disorders in children.

neuroscience↗

bioRxiv2023

Estimating temporally variable selection intensity from ancient DNA data II

Recent technological innovations, such as next generation sequencing and DNA hybridisation enrichment, have made it possible to recover DNA information from historical and archaeological biological materials, which has motivated the development of various statistical approaches for inferring selection from allele frequency time series data. Recently, He et al. (2023a,b) introduced methods that can utilise ancient DNA (aDNA) data in the form of genotype likelihoods, therefore enabling the modelling of sample uncertainty arising from DNA molecule damage and fragmentation. However, their performance suffers from the underlying dependency on the allele age. Here we introduce a novel particle marginal Metropolis-Hastings within Gibbs framework for Bayesian inference of time-varying selection from aDNA data in the form of genotype like-lihoods. To circumvent the performance issue encountered in He et al. (2023a,b), we devise a novel numerical scheme for backward-in-time simulation of the Wright-Fisher diffusion and mix forward- and backward-in-time simulations in the particle filter for likelihood computation. Our framework also enables us to reconstruct the underlying population allele frequency trajectories, integrate temporal information in genotype likelihood calculations and test hypotheses on the drivers of past selection events. We conduct extensive evaluations through simulations and show its utility with an application to aDNA data from pigmentation loci in ancient horses.

genetics↗

bioRxiv2023

Cryo-EM structure of the human G-protein coupled receptor 1 (GPR1) - Gi protein complex bound to the chemerin C-terminal nonapeptide

Chemerin is an adipokine with chemotactic activity to a subset of leukocytes. Chemerin mainly acts through its C-terminal nonapeptide (YFPGQFAFS, C9) that bind to three G protein-coupled receptors including chemokine-like receptor 1 (CMKLR1), G-protein coupled receptor 1 (GPR1) and C-C chemokine receptor-like 2 (CCRL2). We examined C9 signaling through GPR1 and found this receptor capable of Gi signaling but very weak {beta}-arrestin signaling. Here we report high-resolution cryo-EM structures of GPR1-Gi complexes bound to full-length chemerin and to C9, respectively. Unlike C9 that inserts directly into a transmembrane binding pocket, full-length chemerin uses its N-terminal globular core for extensive interaction with the N terminus of GPR1. Within the binding pocket, the C terminal loop containing the nonapeptide takes the same "S-shape" pose as synthetic C9 nonapeptide. These findings explain why the nonapeptide is a full agonist of GPR1, and demonstrate that chemerin uses a "two-site" model for interaction with GPR1. An analysis of the GPR1-Gi protein interface found high similarities to the CMKLR1-Gi complex, as confirmed by site-directed mutagenesis with functional verifications. Our structural analysis demonstrates shared features with chemokines in that chemerin acts as a "reverse chemokine" with switched functions of its N and C termini in the interaction with GPR1.

pharmacology and toxicology↗

bioRxiv2023

Histone lactylation antagonizes senescence and skeletal muscle aging via facilitating gene expression reprogramming

One of the prominent drivers of cellular senescence and/or aging is epigenetic alteration, through which orchestrated regulation of gene expression is achieved during the processes. Accumulating endeavors have been devoted to identifying histone modifications-related mechanisms underlying senescence and aging. Here, we show that histone lactylation, a recently identified histone modification bridging metabolism, epigenetic regulation of gene expression and cellular activities in response to internal and external cues, plays a crucial role in counteracting senescence as well as mitigating dysfunctions of skeletal muscle in aged mice. Mechanistically, the abundance of histone lactylation is markedly decreased during senescence and aging but restored following manipulation of the metabolic environment. Genome-wide distribution profiling and gene expression network analysis uncover that the maintenance of histone lactylation level is critical for suppressing senescence and aging programs via targeting of proliferation- and homeostasis-related pathways. We also confirmed that the level of histone lactylation is not only controlled by glycolysis but also regulated by NAD+ content in vivo. More intriguingly, running exercise enhances the level of histone lactylation and reconstructs the cell landscape and communications of mouse skeletal muscle, leading to rejuvenation and functional improvement. Our study highlights the role of histone lactylation in regulating senescence as well as aging-related tissue function, implying that this modification could be used as a novel marker of senescence, and provides a potential target for aging intervention via metabolic manipulation.

cell biology↗

bioRxiv2022

Estimating temporally variable selection intensity from ancient DNA data with the flexibility of modelling linkage and epistasis

Innovations in ancient DNA (aDNA) preparation and sequencing technologies have exponentially increased the quality and quantity of aDNA data extracted from ancient biological materials. The additional temporal component from the incoming aDNA data can provide improved power to address fundamental evolutionary questions like characterising selection processes that shape the phenotypes and genotypes of contemporary populations or species. However, utilising aDNA to study past selection processes still involves considerable hurdles like how to eliminate the confounding factor of genetic interactions in the inference of selection. To address this issue, we extend the approach of He et al. (2022) to infer temporally variable selection from the aDNA data in the form of genotype likelihoods with the flexibility of modelling linkage and epistasis in this work. Our posterior computation is carried out by a robust adaptive version of the particle marginal Metropolis-Hastings algorithm with a coerced acceptance rate. Our extension inherits the desirable features of He et al. (2022) such as modelling sample uncertainty resulting from the damage and fragmentation of aDNA molecules and reconstructing underlying gamete frequency trajectories of the population. We evaluate its performance through extensive simulations and show its utility with an application to the aDNA data from pigmentation loci in horses.

genetics↗

bioRxiv2022

Estimating temporally variable selection intensity from ancient DNA data

Novel technologies for recovering DNA information from archaeological and historical specimens have made available an ever-increasing amount of temporally spaced genetic samples from natural populations. These genetic time series permit the direct assessment of patterns of temporal changes in allele frequencies, and hold the promise of improving power for the inference of selection. Increased time resolution can further facilitate testing hypotheses regarding the drivers of past selection events such as the incidence of plant and animal domestication. However, studying past selection processes through ancient DNA (aDNA) still involves considerable obstacles such as postmortem damage, high fragmentation, low coverage and small samples. To circumvent these challenges, we introduce a novel Bayesian framework for the inference of temporally variable selection based on genotype likelihoods instead of allele frequencies, thereby enabling us to model sample uncertainties resulting from the damage and fragmentation of aDNA molecules. Also, our approach permits the reconstruction of the underlying allele frequency trajectories of the population through time, which allows for a better understanding of the drivers of selection. We evaluate its performance through extensive simulations and demonstrate its utility with an application to the ancient horse samples genotyped at the loci for coat colouration. Our results reveal that incorporating sample uncertainties can further improve the inference of selection.

genetics↗