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PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗

PubMed2025

Exploring potential targets and molecular mechanisms of traumatic brain injury exacerbated by Benzo(a)pyrene via network toxicology and molecular dynamics simulation.

Benzo(a)pyrene (BaP) is a common environmental pollutant from combustion sources that promotes oxidative stress, neuroinflammation and disruption of blood-brain barrier (BBB). However, its contribution to worsening traumatic brain injury (TBI) remains unclear. In this study, we aimed to assess the contribution of BaP to secondary injury in TBI. By integrating data from e.g., the Comparative Toxicogenomics Database, GeneCards, and Online Mendelian Inheritance in Man, 121 overlapping core targets were identified between BaP and TBI. Enrichment analyses via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, combined with protein-protein interaction networks and topological algorithms (degree, closeness centrality, betweenness centrality, average shortest path length, topological coefficient and partner of multi-edged node pairs), highlighted five hub genes (TP53, EGFR, AKT1, ACTB, and TNF) implicated in mitogen-activated protein kinase signaling, oxidative stress, and neuroinflammation. Molecular docking showed strong binding affinities of BaP to these hub proteins, with energies from -9.3 to -12.1 kcal/mol, tighter than co-crystal ligands and existing protein-binding drugs. Molecular dynamics simulations confirmed interaction stability through low root-mean-square deviation (< 0.5 nm), fluctuation, and radius of gyration values. Calculation of binding free energies using MM-PBSA validated the strong binding affinity between BaP and binding pockets of each hub genes. Toxicity prediction analysis revealed an oral LD50 of 316 mg/kg for BaP, with high probabilities for neurotoxicity, BBB permeability, carcinogenicity, and mutagenicity, associated with aryl hydrocarbon receptor activation. These findings reveal a "neurovascular homeostasis disruption" network underlying BaP-exacerbated TBI pathology and highlight potential targets to reduce pollution-related risks in TBI management.

Benzo(a)pyrene↗

PubMed2025

Balanced state of networks of winner-take-all units.

Irregularly timed action potentials, or spikes, are pervasively observed in the brain activity of awake mammals. However, the role of this temporal irregularity in neural computation is still not well understood. In canonical network models irregular spiking emerges via balanced, fluctuating input currents, leading to collective responses that track inputs linearly. How networks characterized by irregular spiking could support flexible nonlinear dynamics needed for general-purpose computation remains under ongoing debate. Here we characterize the dynamics of networks whose elementary unit is not a single neuron but a small group of neurons, with distinct tunings, that compete at each timestep via a winner-take-all (WTA) interaction. While WTA has long been proposed as an elementary functional motif in the brain and represents a powerful computational primitive, how large networks of such units behave has received less investigation. We show that these networks, like classic excitatory-inhibitory balanced networks, exhibit a chaotic fluctuation-driven regime characterized by sustained irregular activity resembling realistic cortical spiking, which we interpret as a multidimensional balance spread over several competing neural populations with different tunings. We develop a mean-field theory for the network, which shows how irregular spiking sustained by time-varying input fluctuations can support flexible nonlinear collective dynamics. Using the theory we predict and verify network regimes in which input fluctuations alone yield multistability, stable sequence generation, or complex heterogeneous firing rate dynamics-three core dynamical primitives thought to underlie memory-dependent neural computation-via consistent Poisson-like spiking produced through chaos. Thus, networks of WTA units support a chaotic fluctuation-driven regime characterized by irregular spiking that can power complex nonlinear collective dynamics. This represents a new model of brain activity capable of simultaneously reproducing realistic spike trains and diverse nonlinear firing rate patterns well posed for flexible computation, and which can be trained or fit to data.

Models, Neurological↗

PubMed2026

Investigating the mechanisms of PhIP-induced colorectal cancer through network toxicology, machine learning, and molecular dynamics simulation.

BACKGROUND: Over the past few years, 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP)- a compound from grilled or processed meats-has emerged as a major player in cancer development, especially colorectal cancer (CRC). This work dives into its potential links to CRC and uncovers the key genes that bridge this connection. METHODS: We tapped into various databases to pinpoint target genes tied to PhIP and CRC, then ran protein-protein interaction (PPI) analyses for visualization. Next, we explored underlying mechanisms through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. To nail down predictions, we tested 107 machine learning pipelines and picked the best one, validating its accuracy and the core genes' prognostic value across datasets. Next, molecular docking and dynamics simulations probed the interactions between these genes and PhIP. Finally, cell proliferation was assessed using Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2'-deoxyuridine (EdU) assays, and polymerase chain reaction (PCR) was performed to validate the expression levels of the hub genes. RESULTS: Our analysis identified 39 overlapping genes, from which a machine learning model (glmBoost + Enet) identified six candidate targets: CDK4, CEBPB, COMT, SOX9, TIMP1, and TOP2A. To prioritize these, a hierarchical screening framework was applied. Molecular docking and dynamics simulations identified CDK4, COMT, and TIMP1 as the most stable interactors with PhIP. Functional assays confirmed that PhIP treatment significantly enhanced the proliferation of CRC cells. Crucially, quantitative PCR (qPCR) validation in multiple CRC cell lines identified TIMP1 as the primary target, showing the most consistent and significant upregulation upon PhIP exposure. CONCLUSIONS: In essence, these genes drive PhIP is role in CRC, offering novel insights into its molecular pathways. This could reshape how we tackle food-related pollutants, paving the way for better prevention and targeted therapies.

Colorectal cancer (CRC)↗

PubMed2026

Validating the potential mechanism and therapeutic effect of Qinlian Jiangxia decoction in the treatment of type 2 diabetes mellitus complicated with hyperlipidemia through network pharmacology, molecular docking, molecular dynamics simulation, andexperiments.

OBJECTIVE: To investigate the mechanism of action of Qinlian Jiangxia decoction (, QLJXD) in the treatment of type 2 diabetes mellitus (T2DM) complicated by hyperlipidemia using network pharmacology, molecular docking, molecular dynamics simulation and in vivo experiments. METHODS: Drug components, targets and disease targets were identified using databases such as TCM systems pharmacology database and analysis platform and GeneCards. The intersecting targets were subjected to protein-protein interaction analysis using the search tool for the retrieval of interacting genes/proteins database. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersecting targets were conducted using the Metascape platform to identify core components and targets. The results were validated using molecular docking, molecular dynamics simulations and in vivo experiments. RESULTS: QLJXD contains 76 active ingredients and 136 disease targets. The core ingredients are quercetin, β-sitosterol, wogonin and baicalein, while the core targets are fatty acid binding protein 4 (FABP4) and peroxisome proliferative activated receptor gamma (PPARG). Molecular docking and molecular dynamics simulations revealed that the core ingredients bound well to the core targets. Animal experiments demonstrated that QLJXD effectively inhibited the expression of FABP4 and increased the expression of PPARG, thereby enhancing disorders of glycolipid metabolism. CONCLUSION: The putative therapeutic efficacy of QLJXD in the management of T2DM complicated with hyperlipidemia may be ascribed to the synergistic actions of multiple components, such as quercetin, β-sitosterol, wogonin, and baicalein, which collectively modulate FABP4 and PPARG molecular targets.

Molecular Docking Simulation↗

PubMed2026

Dynamic Fusion of Genomics and Functional Network Connectivity in UK Biobank Reveals Schizophrenia-Related SNP Manifolds.

Many mental disorders show strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) has shown high sensitivity to brain changes related to mental disorders. However, previous studies linking dFNC to genetics largely follow a paradigm to identify associations between one set of genetic factors and multiple sets of connectivity features from different dFNC states, ignoring the potential variability in genetic correlates across states. We propose a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned genetic manifolds. A sliding window approach was utilized to estimate four dFNC states and compute subject-level state-average dFNC (sa-dFNC) features. The sa-dFNC features of each state were combined with schizophrenia risk single nucleotide polymorphisms (SNPs) within a jICA fusion framework, resulting in four parallel fusions in 32,861 individuals of the UK Biobank cohort. The extracted four sets of joint SNP-dFNC components were further validated for clinical relevance in a combined schizophrenia cohort of 820 individuals (348 patients). The similarity of SNP-dFNC components across four parallel fusions was evaluated as a measure of state variability. We observed a mixture of "state-invariant" and "state-variant" components for SNP and dFNC modalities. Particularly, the schizophrenia-related state-variant SNP components, or manifolds, complemented each other by capturing different SNPs involved in the same biological functions, revealing a partition of genomic risk particularly elicited by the dynamics of brain function. By augmenting the SNP factors to state-variant manifolds, this dynamic fusion framework promises additional insights into the underlying genetic risk of disease-related alterations in dynamic brain function.

Humans↗

PubMed2026

Proteome-wide Ubiquitinome Profiling Reveals Substrate-specific Dynamics Within the USP7 Network.

USP7 is a pleiotropic deubiquitylating enzyme that is involved in tumor suppression, (neuro) development, chromatin regulation and the DNA damage response. How USP7 regulates these diverse pathways is still unclear. Here, we report data-independent acquisition and label free quantitation mass spectrometry to profile the proteome-wide impact of USP7 on substrate de-ubiquitylation and overall protein abundance. First, we identified proteins associated with endogenous USP7 by immunopurification followed by data-independent acquisition and label free quantitation mass spectrometry. Integration of our new results with earlier interactomes of epitope-tagged USP7 yielded a consensus set of high-confidence protein targets. Domain mapping analysis revealed that, in addition to the TRAF domain, the ubiquitin-like domains of USP7 play a key role in substrate selection. Using specific enrichment of tryptic K-ε-GG peptides, we mapped proteome-wide changes in ubiquitinome dynamics following inhibition of USP7. Combining unbiased proteome-wide and targeted quantitative mass spectrometry revealed that deubiquitylation by USP7 can have different effects on the stability of distinct substrates, and suggests that USP7's activity profile is substrate-dependent rather than an intrinsic enzymatic property. Thus, in addition to providing a proteome-wide map of USP7 target sites, our multi-angle proteomics approach reveals that the effects of USP7-mediated deubiquitylation on its targets are remarkably variable and substrate-specific. Finally, based on these detailed molecular insights we show how USP7 connects various neurodevelopmental syndromes and tumor suppression pathways.

Ubiquitin-Specific Peptidase 7↗

PubMed2026

dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.

SUMMARY: This study presents dAMN, a genome-scale neural-mechanistic hybrid model that combines neural networks with dynamic flux balance analysis to predict bacterial growth dynamics across diverse nutrient environments. Using a residual network architecture, dAMN predicts reaction fluxes and lag-phase parameters from initial medium composition, then integrates these predictions under stoichiometric constraints derived from genome-scale metabolic models. Trained on Escherichia coli and Pseudomonas putida growth datasets across combinatorial media, dAMN accurately forecasts temporal growth dynamics and generalizes to unseen media conditions, with mean R² ≥ 0.9. The model also reproduces biologically relevant behaviors including substrate depletion, acetate overflow, and diauxic shifts, while explicitly modeling lag phases usually absent from standard dFBA. AVAILABILITY AND IMPLEMENTATION: The dAMN software, associated models, and datasets are available at https://github.com/brsynth/dAMN-main-release and via Zenodo DOI: 10.5281/zenodo.17908125.

Escherichia coli↗

PubMed2026

Co-mutation Based Genetic Networks to Infer Temporal Mutation Dynamics in Ancient Human Mitochondrial Genomes.

The evolutionary history of Homo sapiens is marked by complex interactions between environmental, cultural, and genetic factors. To investigate the molecular signatures of these processes, we analyzed ancient mitochondrial DNA (mtDNA) across temporal and geographic contexts using principles of co-occurrence of minor alleles defined as co-mutation, through spatiotemporal co-mutation networks of variable sites. Haplogroup-based assessments of variable sites revealed a major transition from foraging to agrarian lifestyles during the Copper-Bronze Age. Genetic network analyses demonstrated that COX and CYB loci exhibited distinct temporal dynamics, with their interactions modulated by NADH dehydrogenase genes in a geological age-dependent manner. To complement the network approach, we constructed phylogeny-based gene interaction networks and assessed polymorphism-to-divergence from chimpanzee ratios. The tree-based networks displayed topologies consistent with co-mutation analyses but showed reduced gene-gene connectivity. Polymorphism/divergence analysis further indicated that the CYB gene has been under long-term purifying selection, whereas ATP6, COX, and NADH dehydrogenase genes experienced episodic purifying selection aligned with distinct historical phases. Collectively, our findings demonstrate that network-based analysis of ancient mtDNA provides insights into early human lifestyle transitions and haplogroup diversification, contributing to the evolutionary foundations of modern human populations.

Ancient humans↗

PubMed2026

Individual differences in brain dynamics across a social cognition network induced by cortico-cerebellar tDCS in adults with autism spectrum disorder (ASD).

Autism spectrum disorder (ASD) is a neurodevelopmental condition with core diagnostic domains of social communication impairments, restricted interests and repetitive behaviors. Idiosyncratic brain organization is a potential hallmark of ASD. Previous transcranial direct current stimulation (tDCS) studies often targeted dorsolateral prefrontal cortex, with changes oin brain dynamics averaged across the cohort. We utilized a magnetoencephalographic (MEG) array to characterize individual differences in brain dynamics induced by cortico-cerebellar tDCS across nodes of a social cognition network. A randomized, sham-controlled, double-blind, within-subject clinical trial was conducted in a cohort of 24 young adults with ASD or high autistic traits. Two separate sessions of computerized social learning activities were combined with verum/sham tDCS, with anodal electrode over right temporoparietal junction (TPJ) and cathode on right deltoid. Following stimulation, theta- and alpha-band activity were evaluated within nodes of a social cognition network: bilateral TPJ, fusiform, medial prefrontal cortex and Crus I/II of cerebellum. Idiosyncratic participant-specific up- and down-regulation of theta- and alpha-band activity occurred across the network. Activity in right Crus I/II, a region inundated by the stimulation current, strongly correlated with the change of activity summed across all cerebral cortical nodes in theta- but not alpha-band. Intrinsic theta-band activity is believed to mediate input/output relationships in cerebellar cortex and to drive synaptic plasticity. These results suggest that theta-band stimulation of cerebellar cortex might be an effective therapy for individuals on the autism spectrum who present with cerebellar hyperactivity.

Humans↗

PubMed2026

Cells and Networks in Flux: Rethinking Ontogenesis and Pathogenesis.

Organ and tissue functions emerge from the coordinated activity of cell networks. Therapeutics that act on pathogenic cell networks, modulating their cellular interplay, follow naturally. Over several decades, our laboratory has developed a series of approaches for rewiring cell networks, culminating in a class of cell surface-directed signal converter proteins (SCPs) that do so by modulating juxtacrine and autocrine signaling in and among their nodal cells. A first such SCP has now produced encouraging clinical data for cancer immunotherapy. Yet, these early network-directed fusion proteins rest on a deliberately simplified picture: discrete end-cell types plugged into graphically tractable networks. That picture is increasingly at odds with what computational cell typing and spatiotemporal analytics, along with epigenetics, now reveal-a hyperdiverse, plastic, experience-shaped cellular landscape embedded in dynamic, multiway networks. Setting the stage for a next generation of network modulators, an extended cell differentiation synthesis is proposed, which formalizes paracell ultradifferentiation and aging-associated differentiation phases. According to this model, cells are ever evolving, and no two cells are alike. A richer cellular ontology forces a more elaborate network ontology, with paralogous networks and their shifting subnetworks opening a concrete design space for next-generation network-directed SCP therapeutics. This exploration calls for a willingness to embrace complexity more fully and borrow freely from conceptual fields close and afar.

Humans↗

PubMed2026

Macrophage regulation of extracellular matrix remodeling in aging skeletal muscle.

The extracellular matrix (ECM) is a dynamic structural network that supports tissue architecture and regulates cell function. It is primarily composed of collagens, elastin, proteoglycans, and glycoproteins, which are synthesized by canonical and non-canonical ECM-producing cells. During aging, the ECM undergoes progressive changes in structure and composition, a process recently recognized as the 13th hallmark of aging. In skeletal muscle (SKM), age-associated ECM remodeling, largely regulated by immune system-ECM crosstalk, contributes to sarcopenia and impaired regeneration. Macrophages (MΦs), as key innate immune cells, regulate ECM dynamics both indirectly by activating canonical ECM-producing cells and directly by synthesizing ECM components. Notably, a distinct subset of ECM-producing MΦs that express collagen (COL+ MΦs) has been identified across multiple tissues, although their function in SKM homeostasis and aging remains poorly understood. Here, we review current knowledge of ECM production and remodeling, with special emphasis on MΦ involvement, including COL+ MΦs, as critical regulators of fibrogenesis, especially during SKM aging and regeneration.

Extracellular Matrix↗

PubMed2017

Novel Influences of IL-10 on CNS Inflammation Revealed by Integrated Analyses of Cytokine Networks and Microglial Morphology.

Coordinated interactions between cytokine signaling and morphological dynamics of microglial cells regulate neuroinflammation in CNS injury and disease. We found that pro-inflammatory cytokine gene expression in vivo showed a pronounced recovery following systemic LPS. We performed a novel multivariate analysis of microglial morphology and identified changes in specific morphological properties of microglia that matched the expression dynamics of pro-inflammatory cytokine TNFα. The adaptive recovery kinetics of TNFα expression and microglial soma size showed comparable profiles and dependence on anti-inflammatory cytokine IL-10 expression. The recovery of cytokine variations and microglial morphology responses to inflammation were negatively regulated by IL-10. Our novel morphological analysis of microglia is able to detect subtle changes and can be used widely. We implemented in silico simulations of cytokine network dynamics which showed-counter-intuitively, but in line with our experimental observations-that negative feedback from IL-10 was sufficient to impede the adaptive recovery of TNFα-mediated inflammation. Our integrative approach is a powerful tool to study changes in specific components of microglial morphology for insights into their functional states, in relation to cytokine network dynamics, during CNS injury and disease.

CNS inflammation↗

PubMed2026

Mechanistic insights into Claudin-14 dysfunction implicated in veins of Galen malformation.

Claudin-14 (CLDN14) is a key component of tight junctions (TJs) critical for maintaining paracellular barrier function. Variants of CLDN14 have been linked to Vein of Galen malformations (VOGMs), a rare cerebrovascular disorder; however, the molecular mechanisms underlying their pathogenicity remain unknown. Here, we investigate the mechanistic effects of two VOGM-associated mutations, A113P and V143M, using reinforcement-learning driven enhanced sampling molecular dynamics simulations combined with DiffNets-based deep learning and independent trajectory-wide structural analyses. Our analysis reveals that A113P induces broader structural disruption of CLDN14, perturbing paracellular sealing, pore symmetry, and inter-protomer communication, whereas V143M induces structural rearrangements centred around TM3 and the TM3-ECL2 region. In both cases, mutation-specific alterations are observed in structural stability and interfacial organization across oligomeric assemblies. Notably, these effects are qualitatively consistent across different modelled architectures, despite variability in local responses. In the absence of experimentally resolved structures, the structural perturbations reported here provide a mechanistic understanding of how VOGM-associated variants may influence CLDN14 structure and dynamics.

Aneurysm↗

PubMed2026

A system-level metastable model of cancer evolution: integrating replication stress, cell cycle deregulation and chromosomal instability.

INTRODUCTION: Cancer cell proliferation occurs within the context of persistent genomic instability. In this review, we propose the RS-CCD-CIN axis as a systems-level framework in which replication stress (RS), cell cycle deregulation (CCD) and chromosomal instability (CIN) form an interdependent triad that shapes tumour evolution. This axis represents a constrained metastable state in which genomic instability is tolerated and buffered. The objective of this review is to synthesize the current understanding of how the RS-CCD-CIN axis contributes to tumour heterogeneity, adaptability and therapy response. DISCUSSION: Evidence indicates that RS, CCD and CIN operate as a dynamic, interconnected network rather than as independent processes. Replication stress induces DNA damage and mutagenesis, while partial checkpoint disruption permits cells with unresolved lesions to proliferate. Chromosomal instability generates both structural and numerical alterations, contributing to intratumoural heterogeneity. Together, these processes facilitate adaptation to environmental and therapeutic pressures. Extrachromosomal DNA, micronuclei formation and cytosolic DNA signalling, including the cGAS-STING pathway, connect genomic instability to adaptive responses and immune modulation. Single-cell and spatial profiling reveal temporal and spatial variability in RS, CCD and CIN states, highlighting the limitations of static biomarkers. Therapeutically, targeting individual components often yields limited durability, whereas approaches that simultaneously perturb multiple aspects of the RS-CCD-CIN axis may improve clinical outcomes. CONCLUSIONS: This review highlights the RS-CCD-CIN axis as a fragile and metastable architecture that supports cancer evolution, while also being susceptible to collapse. A deeper understanding of this interconnected framework may inform the development of therapeutic strategies and enhance the management of resistance.

Humans↗

PubMed2024

Dynamic Pathology of Enteric Neural Network Using Curcumin-assisted Multiphoton Laser Imaging in Hirschsprung Disease.

BACKGROUND: In living tissue, it has been difficult to make microscopic-level observations without damaging the tissue. We have invented a novel intravital fluorescent observation method (IFOM) for real-time tissue observation, combining multiphoton laser scanning microscopy with curcumin vital staining (CVS-IFOM). The aim of this study was to use CVS-IFOM to analyze the enteric nervous system (ENS) in mice and human patients with hypoganglionosis and Hirschsprung disease (HSCR). METHODS: In an initial viability study, we compared live ENS images from nonfluorescent C57BL6 mice stained with curcumin (n = 5) and green fluorescent protein mice (n = 5) using multiphoton laser scanning microscopy. We then explored CVS-IFOM for the live examination of resected colon tissues from 1 patient with hypoganglionosis and 3 patients with HSCR. RESULTS: In the viability study, detailed ENS histologic features were only observed in the curcumin-stained mice. In the patient with hypoganglionosis, CVS-IFOM provided ENS details that were not visualized under hematoxylin and eosin staining or calretinin immunohistochemistry, allowing the analysis of ENS size, neural bundle number, and neural cell number per plexus. In patients with HSCR, CVS-IFOM showed a gradual hypoplastic change in the ENS from the oral edge to the anal edge, detecting disproportionate changes in the ENS within the same intestinal level, supporting a circumferentially uneven distribution of the intestinal ENS. CONCLUSIONS: CVS-IFOM may be supportive for intraoperative pathologic diagnosis during surgeries for HSCR.

Hirschsprung Disease↗

PubMed2025

Charting Postnatal Heart Development Using In Vivo Single-Cell Functional Genomics.

The transition at birth, marked by increased circulatory demands and rapid growth, necessitates extensive remodeling of the heart's structure, function, and metabolism. This transformation requires precise spatial and temporal coordination among diverse cardiac cell types; central to this process is cardiomyocyte maturation, yet the regulatory mechanisms driving these changes remain poorly understood. Here, we present a temporal and spatial atlas of postnatal hearts by integrating single-nucleus transcriptomics with image-based spatial transcriptomics, which uncovers the dynamic regulatory networks of cardiomyocyte maturation. To functionally interrogate candidate regulators in vivo , we developed Probe-based Indel-detectable Perturb-seq (PIP-seq), a high-throughput platform that uses probe-based chemistry to directly capture sgRNA expression, perturbation status, and transcriptomic profiles at single-nucleus resolution. Applying PIP-seq to postnatal cardiac development identified 21 novel regulators of cardiomyocyte maturation, highlighting critical nodal points in this process. Our study establishes a high-resolution framework for dissecting postnatal heart development, underscoring the integrative and highly ordered roles of microenvironment and intercellular communication in cardiomyocyte maturation. Importantly, PIP-seq enables systematic, high-throughput exploration of gene function and networks underlying complex biological processes in their native in vivo context.

Journal Article↗

PubMed2026

Elucidating the Mechanism of Xiaoqinglong Decoction in Chronic Urticaria Treatment: An Integrated Approach of Network Pharmacology, Bioinformatics Analysis, Molecular Docking, and Molecular Dynamics Simulations.

INTRODUCTION: Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application. METHODS: The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database. RESULTS: A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses. DISCUSSION: This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions. CONCLUSION: This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Molecular Docking Simulation↗