Biology subjects

Hu, Z.

Publications and source records attributed to Hu, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Spatiotemporal lineage mapping of tumor immune escape with eTRACER

The plasticity-first hypothesis posits that phenotypic plasticity emerges first in novel environments, followed by (epi)genetic changes that stabilize adaptive phenotypes. Whether tumor evolution follows this model, and how non-genetic mechanisms sustain long-term therapeutic resistance, remain unclear. Here, we develop eTRACER, an endogenously targeted, high-resolution and spatially-resolved CRISPR-Cas9 lineage-tracing system, to study tumor adaptation during longitudinal CD8+ T cell-mediated immunotherapy. Integrated clonal and single-cell transcriptomic analyses show that tumor immune evasion is governed by clonal state composition rather than clonal identity, arguing against selection from pre-existing genetic heterogeneity. Spatiotemporal lineage tracing reveals highly reversible state transitions prior to therapy, followed by consolidated epithelial-mesenchymal transition (EMT) during therapy. Single-cell multiomics identifies AP-1 as a key regulator of EMT stabilization and its inhibition enhances tumor sensitivity to immune killing. Together, these findings show that tumor plasticity precedes stable immune evasion, revealing an AP-1-centered mechanism underlying plasticity-first tumor evolution.

cancer biology↗

bioRxiv2025

Visual stimulus-evoked blood velocity responses in individual human posterior cerebral arteries measured with dynamic phase-contrast functional MR angiography

Functional MRI (fMRI) tracks brain activity through the associated hemodynamic changes via neurovascular coupling. Neurons communicate with the microvessels of the parenchyma to initiate a hemodynamic response, and these microvessels then communicate with upstream arterioles and arteries. The role of the larger feeding arteries--far upstream from the site of neuronal activity--in coordinating this response is incompletely understood, yet is important for the interpretation of fMRI. Functional Transcranial Doppler (fTCD) can noninvasively measure blood velocity changes in a subset of the largest macrovessels, albeit with poor spatial resolution, whereas existing functional MR angiography (fMRA) methods can assess blood velocity in mid-sized macrovessels but still lack the temporal resolution required to capture dynamic responses. This study aims to propose a new, quantitative fMRA method for measuring blood velocity responses in individual vessels in humans at high spatiotemporal resolution. A dynamic functional phase-contrast MRA approach was developed to quantify responses evoked by visual stimuli in the "P2" segment of the posterior cerebral artery (PCA), located [~]6 cm away from primary visual cortex. The achieved temporal resolution is comparable to that of conventional blood-oxygenation-level-dependent (BOLD) fMRI, enabling block-design stimulation paradigms similar to those used in conventional fMRI studies. The temporal and spatial properties of the blood velocity responses were evaluated using both long- and short-duration visual stimuli presented to either the full visual field or a single hemifield. Robust responses were measured on both 3T and 7T clinical MRI scanners, and an approximately 3.3 {+/-} 1.2 cm/s increase in the blood velocity in the targeted segment was observed, which is roughly a 10% increase from baseline. Visual hemifield stimulation generated a measurable blood velocity response only in the contralateral cerebral hemisphere, indicating that systemic physiological changes occurring with stimulation cannot account for the observed response, suggesting that they instead reflect neurovascular coupling initiated in the visual cortex. The observed arterial blood velocity response is consistent with a downstream reduction in microvascular resistance and may represent a passive response rather than an active vessel dilation at the targeted arterial segment. The proposed method has the potential to extend the capability of commonly used approaches, such as fTCD, in clinical applications.

neuroscience↗

bioRxiv2025

Learning the bistable cortical dynamics of the sleep-onset period

Humans just dont fall asleep like a log - or step-function. Rather, the sleep-onset period (SOP) exhibits dynamic and non-monotonous changes of electroencephalogram (EEG) with high, and so far poorly understood, intra- and inter-individual variability. Computational models of the sleep regulation network have suggested that the transition to sleep can be viewed as a noisy bifurcation at a saddle point which is determined by an underlying control signal or "sleep drive". However, such models do not describe how internal control signals in the SOP can produce rapid switches between stable wake and sleep states, nor how these state-space changes are translated in the macroscopic EEG. Here, we propose a minimally-parameterized stochastic dynamical model, in which one slowly-varying control parameter drives the wake-to-sleep transition while exhibiting noise-driven bistability. We provide a procedure for estimating the parameters of the model given single observations of experimental sleep EEG data, and show that it can reproduce a wide variety of SOP phenomenology. Using the model to analyze a pre-existing sleep EEG dataset, we find that the estimated model parameters correlate with subjective sleepiness reports. These results suggest that the bistable characteristics of the SOP can serve as biomarkers for tracking intra- and inter-individual variability of sleep-onset disorders. Author summaryRecent neuroscience research has showed a growing interest in understanding the complexity of how we fall asleep. Electroencephalographic (EEG) recordings of the sleep onset period show all the hallmarks of a noise-driven bistable system, but there currently exists no computational model that can be fitted on experimental data to understand this behavior. In this paper, we propose a minimally-parameterized model, which dynamics corresponds to the motion of an noisy overdamped particle in a slowly tilting bistable landscape, as well as a way to fit it to an individuals sleep-onset EEG. We show that the fitted parameters of individual participants correlate with their subjective reports of sleepiness, suggesting that the model can capture important aspects of inter-individual variability, as well as provide potential biomarkers for sleep-onset disorders.

neuroscience↗

bioRxiv2025

The Fengshu Large Model for Wugu Fengdeng: An Innovation Engine for Knowledge Integration in the Soybean Field

Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emerged as the core pathway to safeguard food security. As the worlds fourth-largest food crop, soybean (Glycine max) possesses multiple strategic values for food security, livestock feed, and industrial raw materials, thanks to its high protein content (accounting for over 40% of the dry weight of seeds) and oil resource attributes. However, the soybean industry is confronted with multiple challenges: the long cycle of genetic breeding (8-10 years required by traditional methods), annual losses from diseases and pests reaching 40% (data from FAO 2023), and the reliance on empirical decision-making in field management, all of which urgently call for intelligent solutions.At present, agricultural knowledge is experiencing explosive growth - more than 4,000 new soybean-related literatures are added annually in PubMed, and agricultural technology Q&A platforms (Zhihu, Baidu Tieba, etc.) generate over 3,000 daily questions. However, this multi-source heterogeneous knowledge is scattered in books, literatures, Q&A communities, and gene databases, lacking systematic integration, resulting in a knowledge utilization rate of less than 30%. In response to this, this paper proposes the "Fengshu-Agri" large model, an agricultural knowledge integration and innovation engine based on the collaboration of Retrieval-Augmented Generation (RAG) and Knowledge Graph (KG). The model achieves breakthroughs through the following core technological innovations: O_LIDeep integration of multi-source heterogeneous data: For the first time, a systematic integration of 256 agricultural monographs (covering standardized knowledge such as planting techniques and pest control), 66,772 cutting-edge research literatures (genomics, agronomic trait analysis, etc.), 880,000 production practice Q&A (covering scenarios such as pest diagnosis and environmental stress response), and 120,000 gene annotation data (functional genes, expression regulation mechanisms) has been carried out to construct the largest knowledge graph in the agricultural field - containing 2 million entity nodes, realizing full-chain knowledge modeling from molecular-level gene regulation to field management. C_LIO_LIDouble-layer collaborative retrieval mechanism: Innovatively integrating RAG semantic vector retrieval with KG structured reasoning to solve problems such as low recall rate (<65%) and semantic ambiguity in traditional systems. Specifically, it achieves dual matching through local keywords (entity-level) and global keywords (relationship-level); C_LIO_LIOptimization of domain-specific generation engine: Based on the QWEN-QWQ32B large language model, a three-stage fine-tuning is carried out (pre-training, agricultural instruction fine-tuning, and reinforcement learning from human feedback) [15], which improves the professionalism of generated texts by 35% (manual evaluation index) and significantly reduces the LLM hallucination problem [12]. Experimental results show that Fengshu-Agri achieves an accuracy rate of 89.6% in soybean knowledge retrieval tasks (a 25.4% improvement over traditional RAG models), a recall rate of 87.3% (20.5% higher than pure KG reasoning models), and an F1 score of 88.4%. It can efficiently answer complex questions involving multi-entity associations (such as "the impact mechanism of CRISPR-editing the GmSWEET gene on lepidopteran pest resistance"). Analysis of typical cases indicates that the models responses not only cover technical principles (sgRNA design, Agrobacterium transformation procedures) but also integrate metabolomics data (70% improvement in insect resistance with no significant yield reduction), demonstrating cross-modal knowledge fusion capabilities. In the future, this model will be expanded to crops such as maize and potato to construct an agricultural intelligent ecosystem covering the entire process of cultivation management and breeding improvement, promoting the upgrading of precision agriculture toward a data-driven model. C_LI

plant biology↗

bioRxiv2025

Plasmin-Mediated Processing of Clumping Factor A Impacts Bacterial Aggregation and Abscess Formation during Staphylococcus aureus Infection

The interface between pathogenic bacteria and the host plays a critical role during the progression of infection. Bacterial surface components, such as the Staphylococcus aureus cell wall-anchored protein clumping factor A (ClfA), interact with host factors. ClfA promotes bacterial aggregation in plasma by binding to fibrinogen. Here, we show that the host serine endopeptidase plasmin cleaves ClfA, disrupting its interaction with fibrinogen and promoting bloodstream survival and virulence in S. aureus. We found that plasmin cleaves ClfA between residues Arg214 and Ala215. Cleavage occurs in human serum regardless of whether plasmin becomes activated by host tissue-plasminogen activator or by the activity of the S. aureus enzyme staphylokinase. Expressing a plasmin-resistant form of ClfA, and a truncated form that mimics the plasmin-cleaved product on the bacterial cell surface, revealed that following cleavage, ClfA cannot mediate aggregation of S. aureus in fibrinogen. Truncated ClfA on the cell surface cannot bind to fibrinogen and promotes the establishment of renal abscesses in vivo. Collectively, our findings suggest that activation of plasmin during infection leads to site-specific processing of ClfA, and this not only abrogates fibrinogen binding but also facilitates enhanced S. aureus persistence in the host. Thus, we demonstrate that proteolytic processing by plasmin is a mechanism for modulating the host-pathogen interaction during infection. Author SummaryStaphylococcus aureus is a major human bacterial pathogen that binds to host factors during infection using its surface adhesins. Here we describe a novel mechanism by which host proteolytic activity modulates bacterial interaction with the plasma protein fibrinogen to influence the course of infection. The surface adhesin clumping factor A (ClfA), binds to fibrinogen, causing bacterial aggregation in the bloodstream. In this study, we show that the host enzyme plasmin cleaves ClfA at a specific site, disrupting its ability to bind fibrinogen. Cleavage eliminates ClfA-mediated aggregation in plasma fibrinogen and enhances S. aureus virulence in vivo, increasing the formation of kidney abscesses. Our work therefore demonstrates that specific protease-mediated processing of bacterial adhesins by host factors can influence the progression of infection.

microbiology↗

bioRxiv2025

Tracing colorectal malignancy transformation from cell to tissue scale

The transformation of normal intestinal epithelium into colorectal cancer (CRC) involves coordinated changes across molecular, cellular, and architectural scales; yet, how these layers integrate remains poorly resolved. Here, we survey colorectal tumorigenesis by combining whole-transcriptome spatial molecular imaging (WTx CosMx SMI) with single-nucleus RNA-sequencing (snPATHO-seq) and digital histopathology on colon samples containing reference mucosa, adenomas and carcinomas, as well as a metastatic lymph node. Leveraging (discrete) histological annotations and (continuous) data-driven trajectories, we quantify the dynamics of cellular density, heterogeneity, function and signaling along the reference-adenoma-carcinoma axis, which is concordant in its spatial and molecular definition. This combination of analytical approaches across different data views let us chart tissue transformation across dimensions (physical/transcriptional) and scales (cell/tissue). We resolve [~]3.5 million cells into 43 epithelial, immune, and stromal subpopulations that exhibit a bi-furcating tumor evolution: On the one hand, LGR5+ stem-like epithelial cells are enriched in highly homogeneous proliferative tumor cores. On the other hand, MMP7+ fetal-like states are restricted to immunosuppressive invasive fronts, rich in cancer-associated fibroblasts (CAFs) and tumor-associated macrophages. These subpopulations form concentric spatial layers that organize transformed regions, and their compound aligns with histological malignancy. We further define transition crypts - single colonic crypts with divided histological and transcriptional makeup - that arise from rare crypt fusion or abrupt transformation events. Finally, we trace MMP7+ fetal-like tumor cell states and concomitant myofibroblast-like FAP+ CAFs to lymphovascular invasion sites and matched lymph node metastases, thereby recapitulating invasive programs at single-cell resolution and across sites. In all, we present single cell- and WTx-resolved spatial data that are among the first of their kind. These open up spatial-centric, out-of-the-box analytical avenues to resolve the molecular, cellular and architectural dynamics that attend tissue transformation during CRC onset, progression and dissemination.

cancer biology↗

bioRxiv2025

Mechanism of PMC (2,2,5,7,8-pentamethyl-6-chromanol), a sterically hindered phenol antioxidant, in rescuing oxidized low-density lipoprotein-induced cytotoxicity in human retinal pigment epithelial cells

Geographic atrophy or late stage dry age-related macular degeneration (AMD) is characterized by drusen deposition and progressive retinal pigment epithelium (RPE) degeneration, leading to irreversible vision loss. The formation of drusen leads to dyshomeostasis, oxidative stress and irreversible damage to RPE. In this study, we used an in vitro model of oxidized-low density lipoproteins (ox-LDL) induced human RPE damage/death model to investigate the mechanism whereby a sterically hindered phenol antioxidant compound, PMC (2,2,5,7,8-pentamethyl-6-chromanol) protects RPE against ox-LDL-induced damage. We show that PMC exerts its protective effect by preventing the upregulation of stress-responsive heme oxygenase-1 (HMOX1/HO-1) and NAD(P)H:quinone oxidoreductase (NQO1) at mRNA and protein levels. This effect was due to PMCs blockade of ROS generation, which in turn blocked nuclear translocation of the Nuclear factor erythroid 2-related factor 2 (Nrf2) transcription factor, ultimately preventing the upregulation of antioxidant response elements (ARE), including HMOX1 and NQO1. A key role for HO-1 was demonstrated when the protective effect of PMC was inhibited by the knockdown of HMOX1. Additionally, treatment of PMC under different experimental conditions and time points revealed that the continuous presence of PMC is required for optimal protection against ox-LDL-induced cytotoxicity, defining the cellular pharmacokinetics of the molecule. Our data demonstrate the involvement of a key antioxidant pathway through which PMC mitigates oxidative stress induced by ox-LDL and provides a potential therapeutic strategy to suppress RPE degeneration/damage during AMD progression.

molecular biology↗

bioRxiv2025

Transient binding facilitates super-resolution imaging of functional amyloid fibrils on living bacteria

Curli, which are the major proteinaceous component of the Escherichia coli biofilm extracellular matrix, help protect cells against environmental stressors including dehydration and antibiotics. Composed of the amyloid proteins CsgA and CsgB, curli self-assemble as these protomers are secreted into the extracellular space. The mechanisms of curli assembly and their functional roles within the extracellular matrix are incompletely understood. High-resolution imaging tools compatible with live-cell conditions provide a critical means to investigate the assembly and function of curli in their native context. In this study, we use super-resolution imaging to visualize curli fibrils on living bacterial cells. Transient amyloid binding of the fluorogenic dye Nile blue facilitates two complementary super-resolution fluorescence microscopy approaches: single-molecule localization microscopy and super-resolution optical fluctuation imaging. Additionally, imaging fluorescence correlation spectroscopy was used to measure the characteristic relaxation times associated with Nile blue binding to CsgA fibrils. Together, these approaches offer a framework for imaging-based biophysical characterization of curli structures on living cells. Importance/impact statementEscherichia coli and other enteric bacteria secrete amyloid proteins that self-assemble into fibrillar structures called curli, forming a key component of biofilm extracellular matrices. Bacterial biofilms confer resilience to harsh environments with broad implications for human health. In this study, we extend transient amyloid binding to the novel application of super-resolution fluorescence microscopy of curli on living cells, offering promising approaches to gain structural and mechanistic insights.

biophysics↗

bioRxiv2025

Mechanistic dissection of Candidatus Liberibacter Triggered Chronic Immune Disease

Immunity is generally considered critical for plant health against pathogen infection. Citrus Huanglongbing (HLB) caused by the phloem colonizing bacterial pathogen Candidatus Liberibacter asiaticus (CLas) was suggested to be a pathogen triggered chronic immune disease. However, the genetic evidence and mechanistic understanding for such a disease model is lacking. Here, we show CLas triggers phloem cell death, reactive oxygen species (ROS) production and callose deposition in photosynthesis tissues, but little or none in non-photosynthesis tissues of citrus. We further demonstrate that CLas triggers ROS production in chloroplasts. Overexpression of flavodoxin (Fld), an electron shuttle, in chloroplasts reduced ROS production, cell death and HLB symptoms, but not phloem callose deposition induced by CLas. Knockout, silencing, and overexpression of phloem callose synthase genes CsCalS7a, CsCalS7b, or CsCalS7c demonstrated that phloem callose deposition also caused phloem cell death. Trunk injection with 2-deoxy-d-glucose, a callose deposition inhibitor, reduced fruit drop and increased fruit yield of HLB symptomatic trees in field trials. Using tomato-Ca. L. psyllaurous (Lpsy) as a model, knockout of Eds1 and Pad4 but not RbohB, Bik1 and Sobir1 abolished ROS production, phloem callose deposition, cell death and disease damages caused by Lpsy. This study provides genetic evidence for Ca. Liberibacter-triggered immune disease and reveals that tuning plant immune responses converts Ca. Liberibacter into a benign endophyte, providing a promising strategy for precision breeding to enhance resistance/tolerance against HLB.

plant biology↗

bioRxiv2025

A Reductive Uric Acid Degradation Pathway in Anaerobic Bacteria

Uric acid is a key intermediate in purine degradation across diverse organisms, while its accumulation in humans leads to inflammation and gout disease. Aerobic organisms degrade uric acid via a well-known "oxidative pathway" involving dearomatization of the purine core catalyzed by uric acid oxidases or dehydrogenases. The ability to degrade uric acid is also widespread in anaerobic bacteria, including gut bacteria, although the mechanisms are incompletely understood. Here, we report the biochemical characterization of a recently identified uric acid degradation gene cluster from Escherichia coli, and show that it encodes a "reductive pathway" for uric acid degradation. In this pathway, uric acid is first reduced to isoxanthine (2,8-dioxopurine) by a xanthine dehydrogenase homolog (XdhD), followed by dearomatization of the purine core catalyzed by a flavin-dependent reductase (YgfK). Stepwise cleavage of the pyrimidine and imidazole rings forms 2,3-diureidopropionate, and stepwise cleavage of the 2- and 3-ureido groups then forms 2,3-diaminopropionate, which is cleaved by a pyridoxal 5-phosphate-dependent lyase (YgeX) to pyruvate and ammonia. Detection of isoxanthine in clinical serum samples suggests it is a physiologically relevant circulating metabolite. A probiotic E coli Nissle strain was engineered for constitutive overexpression of the gene cluster, and oral administration in a uricase-knockout hyperuricemic mouse model significantly reduced the serum uric acid level and alleviated associated kidney injury, suggesting a potential route towards uricolytic probiotics.

biochemistry↗

bioRxiv2025

APPLE-MS: A affinity purification-mass spectrometry method assisted by PafA-mediated proximity labeling

While affinity purification-mass spectrometry (AP-MS) has significantly advanced protein-protein interaction (PPI) studies, its limitations in detecting weak, transient, and membrane-associated interactions remain. To address these challenges, we introduced an innovative proteomic method termed Affinity Purification coupled Proximity LabEling-Mass Spectrometry (APPLE-MS), which combines the high specificity of Twin-Strep-tag enrichment with PafA-mediated proximity labeling. This method achieves unprecedented sensitivity while maintaining high specificity (4.07-fold over AP-MS). APPLE-MS also revealed the dynamic mitochondrial interactome of SARS-CoV-2 ORF9B during antiviral responses, while endogenous PIN1 profiling uncovered novel roles in DNA replication. Notably, APPLE-MS enabled in situ mapping of GLP-1 receptor complexes, demonstrating its unique capabilities for membrane PPI studies. This versatile method advances interactome research by providing comprehensive, physiologically relevant PPI networks, opening new opportunities for mechanistic discovery and therapeutic targeting. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=184 HEIGHT=200 SRC="FIGDIR/small/652320v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@aaf55borg.highwire.dtl.DTLVardef@1d25af1org.highwire.dtl.DTLVardef@150c1acorg.highwire.dtl.DTLVardef@db0d1c_HPS_FORMAT_FIGEXP M_FIG C_FIG MOTIVATION - Cell Reports Methods onlyAffinity purification-mass spectrometry (AP-MS) has become a widely used method for capturing high-affinity protein-protein interactions (PPIs). However, it still faces several limitations, including high levels of non-specific binding, challenges in detecting weak interactions, and limited ability to identify PPIs at the cell surface in situ. To overcome these challenges, we introduce a modular AP-MS method enhanced by PafA-mediated proximity labeling, which improves both the specificity and sensitivity of PPI detection in a single, streamlined workflow. SIGNIFICANCE - Cell Chemical Biology onlyProximity labeling is a powerful tool in chemical biology, providing critical support for studying protein function, cell signaling, and disease mechanisms by chemically labeling and capturing biomolecular interactions. In this study, we introduce a modular affinity purification-mass spectrometry (AP-MS) method that integrates proximity labeling. This method leverages the proximity-dependent enzymatic activity of PafA to covalently attach PupE to nearby proteins, in combination with the high-affinity interaction between Twin-Strep-tag and streptavidin to achieve efficient binding. This innovative approach enables precise identification of protein-protein interactions (PPIs), offering a powerful tool for capturing weak and transient interactions that are often missed by traditional AP-MS techniques. By enhancing both the specificity and efficiency of protein labeling, our work provides a robust chemical biology strategy to elucidate complex protein interactions, which are essential for understanding cellular processes and developing targeted therapeutic strategies, offering new insights into protein function and interaction dynamics in both health and disease.

biochemistry↗

bioRxiv2025

Top-Down Scoring of Spectral Fitness by Image Analysis for Protein Structure Validation

Nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for protein structure determination, but traditional approaches require extensive manual assignment of hundreds to thousands of resonances. Here we present NMRFAM-BPHON, a novel "top-down" approach that treats experimental NMR spectra as continuous grayscale images and quantitatively scores the agreement with simulated spectra generated from candidate protein structures. This method does not require complete resonance assignments, though it can incorporate experimental chemical shifts when available to improve performance. The simulated spectra are generated from postulated resonance assignments, which can be derived either from empirical database predictions, direct interpretation, or a hybrid combination. BPHON employs a physics-based approximate polarization transfer model to predict cross-peak intensities from the internuclear distances in the decoy structure, and models the peak lineshapes using empirical, bulk T2 relaxation rates and literature values for scalar couplings. The resulting simulated spectra are scored relative to the experimental data by normalized cross correlation, yielding a fitness score between 0 and 1. We demonstrate BPHONs ability to discriminate structural models, particularly in the case of 13C-detected magic angle spinning solid-state NMR spectra. The software is packaged with a user-friendly graphical user interface for ChimeraX, enabling advanced NMR analysis accessible without requiring extensive manual analysis.

biophysics↗

bioRxiv2025

Mitotic phosphorylation of Lamin B1 rod domain by ULK1 and Aurora A/PLK1 promotes spindle function.

The coil-coil rod domain that mediates lateral assembly of lamin filaments has been shown by proteomic approaches to undergo phosphorylation, though the function of these modifications remains unknown. Here, we identify serine 210 (S210) within the Lamin B1 rod domain as a mitotic phospho-acceptor residue, regulated by the combined action of the autophagy-activating kinase ULK1 and the mitotic kinases Aurora A and PLK1. Using a phospho-specific antibody, we demonstrate that Lamin B1 phospho-S210 is enriched at the mitotic spindle and interacts with a network of proteins involved in spindle assembly and spindle pole focusing. Preventing S210 phosphorylation increases the number of cells with multipolar or shorter spindles and prolongs mitotic duration. Our findings indicate that mitotic phosphorylation of Lamin B1 at S210 within the rod domain is important for proper spindle organization and focusing during mitosis.

cell biology↗

bioRxiv2025

Mapping the functional differentiation and interactions among the inferior, medial frontal and posterior temporal cortex in semantic control

Semantic control refers to the ability to flexibly retrieve and manipulate stored knowledge to support context-appropriate behavior. A left-lateralized network comprising the left inferior frontal gyrus (IFG), posterior middle temporal gyrus (pMTG), and dorsal medial prefrontal cortex (dmPFC) has been consistently implicated in this process. While previous studies have established the necessity of the IFG and pMTG in semantic control, the causal role of the left dmPFC remains unclear. Additionally, it is unknown whether each of these three regions exhibits internal functional differentiation and how they interact to support semantic control. To address these questions, we combined task-based functional magnetic resonance imaging (fMRI) with fMRI-guided transcranial magnetic stimulation (TMS). We found that dmPFC, like IFG and pMTG, is causally involved in semantic control. All three regions exhibited a consistent anterior-posterior functional gradient: anterior subregions were selectively engaged during high-demand semantic processing, whereas posterior subregions responded to both easy and hard tasks. Furthermore, combined activation patterns of these regions better predicted the behavioral differences between hard and easy semantic tasks compared to the activation patterns of any single region. Semantic control modulated both the autoinhibition within individual regions and the functional connectivity among them, suggesting these regions operate in a coordinated network rather than in isolation. These findings advance our understanding of the neural architecture supporting flexible semantic behavior. Significance StatementUnderstanding how the brain supports flexible semantic behavior is critical for both cognitive neuroscience and clinical neuropsychology. While prior studies have consistently implicated the left IFG, pMTG, and dmPFC in semantic control, the causal contribution of the dmPFC and the functional dynamics among these regions have remained unclear. This study provides the first causal evidence for the dmPFCs role in semantic control, reveals functional differentiation within the IFG and pMTG, and shows that these regions interact as an integrated network. These findings challenge the notion of functionally homogeneous control nodes and highlight a topographically organized, interactive system underlying controlled semantic retrieval. This work refines our mechanistic understanding of semantic control and may inform clinical models of language and conceptual deficits.

neuroscience↗

bioRxiv2025

Absence of a prolonged macrophage and B cell response inhibits heart regeneration in the Mexican cavefish

A balanced immune response after cardiac injury is crucial to successful heart regeneration, but knowledge of what distinguishes a regenerative from a scarring response is still limited. The Mexican cavefish provides a unique comparative model to study heart regeneration and scarring within a single species. Surface-dwelling fish are capable of heart regeneration whereas their cave-dwelling Pachon counterparts lack this ability, similar to the human heart. Using single-cell transcriptomics and immune perturbations, we find significant differences in the immune response between the two populations. Unlike the transient response in the scarring Pachon, the regenerative surface fish heart generates an unexpected functionally active prolonged innate and adaptive immune response at the late stages of regeneration. Inhibiting the overall prolonged immune response impairs regeneration and cardiomyocyte proliferation. Further characterisation of specific cell types shows that late-present macrophages are phagocytic, and their depletion disrupts regeneration but not cardiomyocyte proliferation while inhibiting B cells impairs regeneration by reducing cardiomyocyte proliferation. This B cell response is conserved in zebrafish. Our findings reveal critical immune mechanisms distinguishing regenerative and non-regenerative responses, offering insights for potential therapeutic strategies to enhance heart repair.

developmental biology↗

bioRxiv2025

Single-Cell eQTL Mapping Reveals Cell Type-Specific Genetic Regulation in Lung Cancer

Genome-wide association studies (GWAS) have identified over 50 lung cancer risk loci; however, the precise cellular context of these genetic mechanisms remains unclear due to limitations in bulk tissue eQTL analyses. Here, we present the largest single-cell eQTL atlas of human lung tissue to date, profiling 222 donors using multiplexed scRNA-seq. We identified 16,785 eQTLs across 17 cell types, with over 90% of sc-eQTLs and 59% eGene being cell-type-specific, and fewer than 23% were detectable in paired bulk datasets. Integration with GWAS for non-small cell lung cancer highlighted epithelial and immune cells as key contributors to genetic susceptibility, identifying 28 candidate genes within known risk loci and 24 in novel regions. Notably, 47% of established NSCLC susceptibility loci exhibited cell-type-specific pleiotropic genetic regulation. This study provides a valuable resource of lung sc-eQTLs and illuminates how genetic variation modulates gene expression in a cell-type-specific fashion, contributing to lung cancer susceptibility.

genetics↗

bioRxiv2025

Multi-Omics and Machine Learning-Based Profiling of Severity Signatures in Mycoplasma Pneumoniae Infection in Children

Mycoplasma pneumoniae pneumonia (MPP) is a common respiratory infection in children, yet the mechanisms driving its progression to severe disease remain poorly understood. This study employs a comprehensive proteomic and metabolomic approach to elucidate severity-related pathways and identify potential biomarkers for improved diagnosis and targeted therapy. By analyzing blood proteomes from 57 pediatric patients with varying MPP severities alongside 10 healthy controls, and integrating multi-omics data from bronchoalveolar lavage fluid (BALF), we uncovered key severity-associated proteins and metabolites linked to inflammatory and metabolic dysregulation. Notably, alterations in L-arginine metabolism, influenced by APAF1 and SERPINB5, were found to modulate the efferocytosis pathway, while ERCC1 and MLH1, crucial components of the Fanconi anemia pathway, were associated with changes in plasmid acid metabolites affecting fatty acid elongation. Machine learning analysis further identified three critical biomarkers--TNFRSF10B, SAT1, and 4-nitrophenol-- that accurately distinguished between mild and severe MPP cases with high sensitivity (0.8) and specificity (1). These findings provide novel insights into the molecular mechanisms underlying severe MPP, highlighting efferocytosis and fatty acid metabolism as key pathways. The identification of severity-specific biomarkers offers a foundation for enhanced diagnostic precision, improved disease stratification, and the development of targeted therapeutic strategies to optimize the management of severe MPP in pediatric patients. HighlightsO_LIIdentified severity signatures in Mycoplasma pneumoniae infection in children. C_LIO_LIConducted the multi-omics analysis of bronchoalveolar lavage fluid (BALF) in children with varying severities of Mycoplasma pneumoniae infection. C_LIO_LIDiscovered biomarkers that effectively distinguish mild from severe Mycoplasma pneumoniae infection. C_LIO_LIFindings offer potential targets to improve the diagnosis and treatment of severe Mycoplasma pneumoniae C_LIO_LIinfection in children. C_LI

microbiology↗

bioRxiv2025

Multimodal general expectancy effects elicited without influencing sensory representations

Predictive coding theories posit a reduction in error-signalling neural activity when incoming sensory input matches existing expectations - a phenomenon termed expectation suppression. However, the empirical evidence for expectation suppression, as well as its underlying neural mechanism, is contentious. A further aspect of predictive coding that remains untested is how predictions are integrated across sensorimotor domains. To investigate these two questions, we employed a novel cross-domain probabilistic cueing paradigm, where participants were presented with both visual and motor cues within a single trial. These cues manipulated the orientation and temporal expectancy of target stimuli with 75% validity. Participants completed a reproduction task where they rotated a bar to match the orientation of the target stimulus while their neural and pupil responses were respectively measured via electroencephalography and eye tracking. Our results showed a consistent, feature-unspecific effect of motor expectancy across multiple measures, while evidence for visual expectancy was limited. However, neither motor nor visual expectancy modulated the fidelity of sensory representations. These results indicate that violations of temporal expectancy in the current study may reveal the brains intrinsic sensitivity to temporal regularities in the natural settings, rather than feature-specific predictions. In contrast, the absence of visual expectancy effects in both neural and pupillometry results adds to a growing body of evidence questioning the effectiveness of probabilistic cueing paradigms for establishing expectations capable of altering sensory representations. Due to null findings in the visual and sensory representation analyses, we did not further investigate cross-domain prediction integration.

neuroscience↗