Biology subjects

Ren, F.

Publications and source records attributed to Ren, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Human brain white matter charts in international populations

Brain charts provide normative references for identifying neurodevelopmental milestones and clinically meaningful deviations. Existing white matter (WM) charts are derived predominantly from European and North American populations, limiting generalizability. Here, we established the first set of population-specific WM charts of 198 morphological and microstructural phenotypes for both Chinese (N=19,215) and Western (N=15,584) populations across the human lifespan. Developmental trajectories and spatial organization of WM maturation and degeneration were broadly conserved across the populations, whereas maturational timing varied across pathways and metrics. The Chinese population showed earlier maturation in several projection and sensorimotor pathways, but more protracted maturation in higher-order association and limbic pathways. Chinese population-matched charts more accurately predicted WM phenotypes and detected more extreme disease-related deviations in brain health in the Chinese population than Western-derived models. Individual deviation patterns further discriminated patients from healthy controls and predicted cognitive performance and plasma biomarkers. Our findings reveal population-specific WM maturation and show that reference-population mismatch can reduce the accuracy and clinical sensitivity of normative brain charts.

neuroscience↗

bioRxiv2026

From Hodgkin-Huxley to Pretrained Neural Inference AI

High-density probes record from thousands of neurons simultaneously, yet resolving single-neuron identity remains an illposed inverse problem. While detailed simulations precisely characterize the biophysical forward process, their utility for interpreting brain signal remains unclear. Here we show that biophysical simulations of population neuronal electrical signals serve as an effective bridge between theory and experiment. By pre-training artificial neural networks exclusively on large-scale synthetic data, we demonstrate robust zero-shot generalization across diverse brain regions, experimental paradigms and species, enabling the accurate inference of single-unit activities and cell-type properties without exposure to real data. Further-more, uncovering a substantial population of functionally competent but weakly active neurons systematically obscured by conventional heuristics, our framework resolves a long-standing discrepancy regarding ocular dominance in mouse primary visual cortex. These findings establish biophysical simulations as a reference standard, bridging the gap between theoretical understanding and experimental observation through data-driven inference.

neuroscience↗

bioRxiv2026

Integrating AI and causal genetics to prioritize therapeutic targets for aging and age-related diseases

Aging is increasingly viewed as a pathologic process and a principal driver of diverse age-related diseases (ARDs). Framing aging as a disease offers an opportunity to identify therapeutic targets capable of modifying multiple chronic disorders simultaneously. Here, we developed an AI-driven target discovery framework that integrates large-scale multi-omic datasets to prioritise therapeutic targets shared between aging and 12 ARDs across four major disease areas: neurological, inflammatory, metabolic, and fibrotic disorders. We identified 29 high-confidence and 16 previously unrecognized aging-associated targets implicated across selected disease areas, together with convergent pathway perturbations characterized by robust upregulation of interferon and inflammatory signaling, alongside coordinated downregulation of MYC-driven proliferative programs, consistent with heightened inflammatory activation and reduced anabolic activity during aging. Hallmarks of aging assessment revealed chronic inflammation as the most enriched hallmark across aging and ARDs. Mendelian randomization provided genetic causal support for IL6, IL6R, NLRP3, NOS2, TLR4, and GLP1R in aging-related traits and multiple ARDs, highlighting potential opportunities for drug repurposing. Co-localization analysis further demonstrated a shared genetic signal at the IL6R locus between gene expression levels and parental survival. Together, our findings outline a scalable AI-guided multi-omic framework for identifying causal and repurposable therapeutic targets for aging and ARDs. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/705676v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@b94af7org.highwire.dtl.DTLVardef@e89e80org.highwire.dtl.DTLVardef@1fde804org.highwire.dtl.DTLVardef@8b817b_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2026

Polyploid cardiomyocytes define disease-specific transcriptional states in the mammalian heart

The adult mammalian heart has a limited regenerative capacity. Following injury, cardiomyocytes undergo a hypertrophic response accompanied by polyploidization, which has been described as a barrier to proliferation and regeneration of the heart1,2. However, the unique molecular programs of polyploidy, or genome multiplied cardiomyocytes, and their influence on the disease-related myocardial remodelling process remains unclear. Here, we integrate single-nuclei and high-resolution spatial multi-omics across human, rat, and mouse hearts to define novel cardiac cell states and their tissue niches in ischemic and non-ischemic heart disease. Computational analysis across scales allowed us to generate detailed networks of the cardiac tissue remodelling process as well as tissue and sub-cellular environments uniquely enriched in polyploid cardiomyocytes or their diploid origins. We identify a conserved, dichotomous transcriptional program distinguishing diploid from polyploid cardiomyocytes. Polyploid cardiomyocytes demonstrated rewired metabolic and chromatin-remodeling transcriptional programs and recapitulate the gene signature of immature human fetal cardiomyocytes. Notably, we observe that polyploid cardiomyocytes--rather than the general myocyte population--are the primary sites of enrichment for major heart-failure drug targets, including the mineralocorticoid, {beta}1-adrenergic, and glucagon-like peptide-1 receptors. Based on our cross-species dataset we further identified TNIK, a Wnt-pathway regulator expressed in polyploid cardiomyocytes across species, as a potential therapeutic target and demonstrate that pharmacological TNIK inhibition improves cardiac function after myocardial infarction in rats. Together, this species-spanning, disease-resolved study redefines cardiomyocyte heterogeneity in heart disease and suggests a therapeutic path to heart failure treatment by targeting polyploid cardiomyocytes.

genomics↗

bioRxiv2025

Advancing Target Discovery Through Disease-Specific Integration of Multi-Modal Target Identification Models and Comprehensive Target Benchmarking System

Target identification is crucial for drug development. AI-driven approaches leveraging multi-omics and computational modeling can accelerate this process. However, integrating multi-modal data for disease-specific target identification and predicting translational potential remains challenging. Moreover, the absence of a systematic evaluation framework for model performance limits confidence in target reliability. We present a unified platform combining machine learning-based target identification with comprehensive benchmarking. As a testbed, we developed Target Identification Pro (TargetPro), a disease-specific model spanning 38 diseases across oncology, metabolic, immune, fibrotic, and neurological categories. TargetPro shows strong predictive performance for clinical-stage targets and reveals disease-specific patterns, underscoring the need for tailored target detection models. We next created Target Identification Benchmark (TargetBench 1.0) to rigorously assess target identification systems, including large language models, based on their ability to recover established targets and find high-quality novel candidates. This integrated approach offers a streamlined strategy to evaluate target discovery models, ultimately improving drug development efficiency.

bioinformatics↗

bioRxiv2025

DORA AI Scientist: Multi-agent Virtual Research Team for Scientific Exploration Discovery and Automated Report Generation

Modern goal-oriented scientific research process involves hierarchical teams of researchers of diverse backgrounds performing generalist and domain-specific tasks. Many of these tasks include hypothesis generation, literature review, data collection, cleanup, processing and analysis, experimental design, virtual and physical experiments, research report and academic paper writing, reference management, bibliography and quality control. Most of these tasks can be performed automatically or in a co-pilot mode by the generative reinforcement learning systems. In this paper, we introduce a versatile multi-agent scientific exploration and draft outline research assistant (DORA), which provides multiple templates and workflows for automated or semi-automated research studies and report generation. Under user guidance, it employs hierarchical teams of AI agents based on the plug-and-play generalist and domain-specific large language models (LLMs) exploiting a variety of specialized research tools and open data repositories and generates high-quality research outputs publication drafts with maximally-accurate references. DORA is designed to minimize the time and effort required for manuscript preparation, thereby enabling researchers to devote more attention to high-value discovery tasks. The system is constantly evolving with user feedback with regular feature and resource updates. The platform is available at https://dora.insilico.com.

bioinformatics↗

bioRxiv2025

AI-Driven Toolset for IPF and Aging Research Associates Lung Fibrosis with Accelerated Aging

Idiopathic pulmonary fibrosis (IPF) is a condition predominantly affecting the elderly and leading to a decline in lung function. Our study investigates the aging-related mechanisms in IPF using artificial intelligence (AI) approaches. We developed a pathway-aware proteomic aging clock using UK Biobank data and applied it alongside a specialized version of Precious3GPT (ipf-P3GPT) to demonstrate an AI-driven mode of IPF research. The aging clock shows great performance in cross-validation (R2=0.84) and its utility is validated in an independent dataset to show that severe cases of COVID-19 are associated with an increased aging rate. Computational analysis using ipf-P3GPT revealed distinct but overlapping molecular signatures between aging and IPF, suggesting that IPF represents a dysregulation rather than mere acceleration of normal aging processes. Our findings establish novel connections between aging biology and IPF pathogenesis while demonstrating the potential of AI-guided approaches in therapeutic development for age-related diseases.

bioinformatics↗

bioRxiv2024

Precious3GPT: Multimodal Multi-Species Multi-Omics Multi-Tissue Transformer for Aging Research and Drug Discovery

We present a multimodal multi-species multi-omics multi-tissue transformer for aging research and drug discovery capable of performing multiple tasks such as age prediction across species, target discovery, tissue, sex, and disease sample classification, drug sensitivity prediction, replication of omics response and prediction of biological and phenotypic response to compound treatment. This model combines textual, tabular, and knowledge graph-derived representations of biological experiments to provide insights into molecular-level biological processes. We demonstrate that P3GPT has developed an intuition for the interactions between compounds, pathologies, and gene regulation in the context of multiple species and tissues. In these areas, it outperforms existing LLMs and we highlight its utility in diverse case studies. P3GPT is a general model that may be used as a target identification tool, aging clock, digital laboratory, and scientific assistant. The model is intended as a community resource available open source as well as via a Discord server.

bioinformatics↗

bioRxiv2024

Structures of PSI-FCPI from Thalassiosira pseudonana in high light provide convergent evolution and light-adaptive strategies in diatom FCPIs

Diatoms achieve great survival success in the fluctuating oceanic environment, rely on fucoxanthin chlorophyll a/c-binding proteins (FCPs) to complete light harvesting and quenching, which provide about 20% primary productivity on earth. We report two cryo-electron microscopic structures of photosystem I (PSI) with 13 or 5 FCPIs respectively at 2.78 [A] and 3.20 [A] resolution from Thalassiosira pseudonana under high light conditions. 8 Lhcr FCPIs are found detached from the PSI-13FCPI supercomplex under high light conditions, remaining 5 FCPIs are stably combined with the PSI core including Lhcr3, RedCAP, Lhcq8, Lhcf10, and FCP3 subunits. The specific pigment network in this centric diatom T. pseudonana demonstrates a higher proportion of Chlorophylls a, diadinoxanthins, and diatoxanthins but fewer fucoxanthins compared with the huge PSI-FCPI from another centric diatom Chaetoceros gracilis, thus exhibiting more efficiency in energy transfer and dissipation among FCPI antennas. These results reveal the assembly mechanism of several types of peripheral FCPIs and corresponding light-adaptive strategies in T. pseudonana, as well as the convergent evolution of the diatoms PSI-FCPI structures.

plant biology↗

bioRxiv2024

Antibiotics affect the pharmacokinetics of n-butylphthalide in vivo by altering the intestinal microbiota

ObjectiveN-butylphthalide (NBP) is a monomeric compound extracted from natural plant celery seeds, whether intestinal microbiota alteration can modify its pharmacokinetics is still unclear. The purpose of this study is to investigate the effect of intestinal microbiota alteration on the pharmacokinetics of NBP and its related mechanisms. MethodsAfter treatment with antibiotics and probiotics, plasma NBP concentrations in SD rats were determined by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The effect of intestinal microbiota changes on NBP pharmacokinetics was compared. Intestinal microbiota changes after NBP treatment were analyzed by 16S rRNA sequencing. Expressions of CYP3A1 mRNA and protein in the liver and small intestine tissues under different intestinal flora conditions were determined by qRT-PCR and Western Blot. KEGG analysis was used to analyze the effect of intestinal microbiota changes on metabolic pathways. ResultsCompared to the control group, the values of Cmax, AUC0-8, AUC0-{infty}, t1/2 in the antibiotic group increased by 56.1% (P<0.001), 56.4% (P<0.001), 53.2% (P<0.001), and 24.4% (P<0.05), respectively. In contrast, the CL and Tmax values decreased by 57.1% (P<0.001) and 28.6% (P<0.05), respectively. Treatment with antibiotics could reduce the richness and diversity of the intestinal microbiota. CYP3A1 mRNA and protein expressions in the small intestine of the antibiotic group were 61.2% and 66.1% of those of the control group, respectively. CYP3A1 mRNA and protein expressions in the liver were 44.6% and 63.9% of those in the control group, respectively. There was no significant change in the probiotic group. KEGG analysis showed that multiple metabolic pathways were significantly down-regulated in the antibiotic group. Among them, the pathways of drug metabolism, bile acid biosynthesis and decomposition, and fatty acid synthesis and decomposition were related to NBP biological metabolism. ConclusionAntibiotic treatment could affect the intestinal microbiota, decrease CYP3A1 mRNA and protein expressions and increase NBP exposure in vivo by inhibiting pathways related to NBP metabolism.

pharmacology and toxicology↗

bioRxiv2023

GABRD promotes the progression of breast cancer through CDK1-dependent cell cycle regulation

PurposeY-aminobutyric acid (GABA) is an important inhibitory amino acid neurotransmitter that exerts its biological function by binding to GABA receptors, which not only play an important role in neuromodulation, but also involved in regulating the development of tumors. Gamma-aminobutyric acid type A receptor subunit delta (GABRD) encodes the {delta} subunit of GABAA receptor, its impact on breast cancer has not been clearly studied. This study is aiming to reveal the relationship between GABRD and breast cancer development. MethodsWe performed a tissue microarray to quantify GABRD expression levels in tumor tissue and paracarcinoma tissue. The regulation of GABRD in the proliferation, migration, and apoptosis of breast cancer was examined by a loss-of-function study. A GeneChip microarray was used to probe GABRD for potential downstream molecules. The interaction between GABRD and CDK1 was verified by a set of functional tests and rescue experiments as well as coimmunoprecipitation. ResultsGABRD was expressed at significantly higher levels in tumor tissues and was associated with advanced tumor progression. Silencing GABRD resulted in a significant decrease in proliferation and migration and an increase in apoptosis of breast cancer. GABRD regulated the cell cycle by directly interacting with CDK1, which was identified as an important downstream target. ConclusionGABRD is the breast cancer-related gene and highlights the importance of the GABRD-CDK1 axis in regulating breast cancer proliferation, which provides potential for the development of novel therapeutics.

cancer biology↗

bioRxiv2023

Nifuroxazide enhances radiotherapy efficacy against hepatocellular carcinoma by upregulating PD-L1 degradation via the ubiquitin-proteasome pathway

Radiation therapy is a primary treatment for hepatocellular carcinoma (HCC), but its effectiveness can be diminished by various factors. The over-expression of PD-L1 has been identified as a critical reason for radiotherapy resistance. Previous studies have demonstrated that nifuroxazide exerts antitumor activity by damaging the Stat3 pathway, but its efficacy against PD-L1 has remained unclear. In this study, we investigated whether nifuroxazide could enhance the efficacy of radiotherapy in HCC by reducing PD-L1 expression. Our results showed that nifuroxazide significantly increased the sensitivity of tumor cells to radiation therapy by inhibiting cell proliferation and migration while increasing apoptosis in vitro. Additionally, nifuroxazide attenuated the up-regulation of PD-L1 expression induced by irradiation, which may be associated with increased degradation of PD-L1 through the ubiquitination-proteasome pathway. Furthermore, nifuroxazide greatly enhanced the efficacy of radiation therapy in H22-bearing mice by inhibiting tumor growth, improving survival, boosting the activation of T lymphocytes, and decelerating the ratios of Treg cells in spleens. Importantly, nifuroxazide limited the increased expression of PD-L1 in tumor tissues induced by radiation therapy. This study confirms, for the first time, that nifuroxazide can augment PD-L1 degradation to improve the efficacy of radiation therapy in HCC-bearing mice.

immunology↗

bioRxiv2023

Reduced brain glutathione levels during normal aging are associated with visuospatial memory

During aging, the brain is subject to greater oxidative stress (OS), which is thought to play a critical role in cognitive impairment. Glutathione (GSH), as a major antioxidant in the brain, can be used to combatting OS. However, how brain GSH levels vary with age and their associations with cognitive function remain unclear. In this study, we combined point-resolved spectroscopy and edited spectroscopy sequences to investigate GSH levels in the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and occipital cortex (OC) of 276 healthy participants (166 females, age range 20-70 years) and examined their relationships with age and cognitive function. The results revealed decreased GSH levels with age in the PCC among all participants. Notably, the timecourse of GSH level changes in the PCC and ACC differed between males and females. Additionally, positive correlations were observed between GSH levels in the PCC and OC and visuospatial memory. Taken together, these findings enhance our understanding of the brain GSH timecourse during normal aging and associations with sex and memory, which is an essential first step for understanding the neurochemical underpinnings of OS-related diseases.

neuroscience↗

bioRxiv2022

DHHC3 mediated Cadm4 palmitoylation regulates myelination in CNS

Cell adhesion molecule 4 (Cadm4) plays important roles on plasma membrane (PM) to regulate myelin formation and the downregulation of Cadm4 is a prominent feature in many demyelination diseases. However, how Cadm4 maintains its level on PM has been elusive. Here, we identify that Cadm4 is palmitoylated at cysteine-347 (C347) and palmitoylation regulates the stable localization of Cadm4 on PM, as blocking palmitoylation by mutating C347 into alanine (C347A) results in the dissociation of Cadm4 from PM and targeting for degradation. Intriguingly, blocking Cadm4 palmitoylation by introducing C347A (Cadm4-KI) causes myelin abnormalities in CNS, characterized by loss of myelination, myelin infoldings and hypermyelination. Moreover, it is uncovered that Cadm4 palmitoylation is catalyzed by DHHC3, reducing Cadm4 palmitoylation by the deletion of DHHC3 renders the redistribution of Cadm4 for degrading. Consistently, the genetic deletion of DHHC3 leads to downregulated Cadm4 palmitoylation and defects in CNS myelination, virtually phenocopies that of the Cadm4-KI mice. Our findings suggest a mechanism that the stable localization of Cadm4 on PM regulated by protein palmitoylation is vital for myelination in CNS.

neuroscience↗

bioRxiv2022

Conserved Untranslated Regions of Multipartite Viruses: Natural Markers of Novel Viral Genomic Components and Tags of Viral Evolution

Viruses with split genomes are categorized as being either segmented or multipartite according to whether their genomic segments occur in single or different virions. Some complexity will exist, in that inherited "core" vital segments viruses may renew the others once host and environmental alterations keep driving viral evolution. Despite this uncertainty, empirical observations have been made across the split genomes in the untranslated regions (UTRs) on the short or long stretches of conserved or identical sequences. In this study, we describe a methodology that combines RNA and small RNA sequencing, conventional BLASTx, and iterative BLASTn of UTRs to detect viral genomic components even if they encode orphan genes (ORFans). Within the phylum Kitrinoviricota, novel putative multipartite viruses and viral genomic components were annotated using data obtained from our sampling or publicly available sources. The novel viruses, as extensions or intermediate nodes, enriched the information of the evolutionary networks. Furthermore, the diversity of novel genomic components emphasized the evolutionary roles of reassortment and recombination, as well as genetic deletion, strongly supporting the genomic complexity. These data also suggest insufficient knowledge of these genomic components for categorizing some extant viral taxa. The relative conservation of UTRs at the genome level may explain the relationships between monopartite and multipartite viruses and how the multipartite viruses can have a life strategy involving multiple host cells. Author summaryThe current workflows for virus identification are largely based on high-throughput sequencing and coupled protein sequence homology-dependent analysis methods and tools. However, for viruses with split genomes, the identification of genomic components whose deduced protein sequences are not homologous to known sequences is inadequate. Furthermore, many plant-infecting multipartite viruses contain conserved UTRs across their genomic components. Based on this, we propose a practical method of UTR-backed iterative BLASTn (UTR-iBLASTn) to explore the components with ORFans and study virus evolution using the UTRs as signals. These shed light on viral "dark matter"--unknown/omitted genomic components of segmented/multipartite viruses from different kingdoms and hosts, and the origins of these components.

microbiology↗

bioRxiv2021

Dysconnectivity between auditory-cognitive network associated with auditory GABA and glutamate levels in presbycusis patients

Accumulating studies suggest an interaction between presbycusis (PC) and cognitive impairment, which may be explained by the cognitive-ear link to a large extent. However, the neurophysiological mechanisms underlying this link are largely unknown. Here, 51 PC patients and 51 well-matched healthy controls were recruited. We combined resting-state functional MRI and edited magnetic resonance spectroscopy to investigate changes of intra- and inter-network functional connectivity and their relationships with auditory gamma-aminobutyric acid (GABA) and glutamate (Glu) levels and cognitive impairment in PC. Our study confirmed the plastic model of cognitive-ear link at the level of the large-scale brain network, including the dysconnectivity within high-order cognitive networks and between the auditory-cognitive network and overactivation between cognitive networks dependent on hearing loss, which was closely related to the cognitive impairment of PC patients. Moreover, GABA and Glu levels in the central auditory processing were abnormal in patients with PC. Importantly, reduction of GABA-mediated inhibition plays a crucial role in a dysconnectivity between the auditory-cognitive network, which may be neurochemical underpinnings of functional remodeling of cognitive-ear link in PC. Modulation of GABA neurotransmission may enable the development of new therapeutic strategies for the cognitive impairment of PC patients.

neuroscience↗

bioRxiv2021

SMC1A facilitates gastric cancer cells proliferation, migration and invasion via promoting SNAI2 activated EMT

Backgroundstructural maintenance of chromosomes protein 1A (SMC1A) is a crucial subunit of the cohesion protein complex and plays a vital role in cell cycle regulation, genomic stability maintenance, chromosome dynamics. Recent studies demonstrated that SMC1A participate in tumorigenesis. This reseach aims to explore the role and the underlying mechanisms of SMC1A in gastric cancer (GC). Materials and methodsRT-qPCR and western blot were used to examine the expression levels of SMC1A in GC tissues and cell lines. The role of SMC1A on GC cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT)were analyzed. Furthermore,the mechanism of SMC1A action was investigated. ResultsSMC1A was highly expressed in GC tissues and cell lines. The high expression of SMC1A indicated the poor overall survival of GC patients from Kaplan-Meier Plotter. Enhancing the expression of SMC1A in AGS remarkably promoted cell proliferation, migration and invasion. While knockdown of SMC1A in HCG27 inhibited cell proliferation, migration and invasion of HGC27 cells. Moreover, its observed that SMC1A promoted EMT and malignant cell behaviors via regulating SNAI2 Conclusionour study revealed SMC1A facilitates gastric cancer cell proliferation, migration and invasion via promoting SNAI2 activated EMT, which indicated SMC1A may be a potential target for gastric cancer therapy.

cancer biology↗

bioRxiv2021

Non-Invasive Confocal Fluorescence Imaging of Mice Beyond 1700 nm Using Superconducting Nanowire Single-Photon Detectors

Light scattering by biological tissues sets a limit to the penetration depth of high-resolution optical microscopy imaging of live mammals in vivo. An effective approach to reduce light scattering and increase imaging depth is by extending the excitation and emission wavelengths to the > 1000 nm second near-infrared (NIR-II), also called the short-wavelength infrared (SWIR) window. Here, we developed biocompatible core-shell lead sulfide/cadmium sulfide (PbS/CdS) quantum dots emitting at ~1880 nm and superconducting nanowire single photon detectors (SNSPD) for single-photon detection up to 2000 nm, enabling one-photon fluorescence imaging window in the 1700-2000 nm (NIR-IIc) range. Confocal fluorescence imaging in NIR-IIc reached an imaging depth of ~ 800 m through intact mouse head, and enabled non-invasive imaging of inguinal lymph nodes (LNs) without any surgery. In vivo molecular imaging of high endothelial venules (HEVs) with diameter down to ~ 6.6 m in the lymph nodes was achieved, opening the possibility of non-invasive imaging of immune trafficking in lymph nodes at the single-cell/vessel level longitudinally.

biochemistry↗