Chronic cerebral hypoperfusion (CCH) plays an important role in the occurrence and development of vascular dementia (VD). Recent studies have indicated that multiple stages of immune-inflammatory response are involved in the process of cerebral ischemia, drawing increasing attention to immune therapies for cerebral ischemia. This study aims to identify potential immune therapeutic targets for CCH using bioinformatics methods from an immunological perspective. We identified a total of 823 differentially expressed genes associated with CCH, and further screened for 9 core immune-related genes, namely RASGRP1, FGF12, SEMA7A, PAK6, EDN3, BPHL, FCGRT, HSPA1B and MLNR. Gene enrichment analysis showed that core genes were mainly involved in biological functions such as cell growth, neural projection extension, and mesenchymal stem cell migration. Biological signaling pathway analysis indicated that core genes were mainly involved in the regulation of T cell receptor, Ras and MAPK signaling pathways. Through LASSO regression, we identified RASGRP1 and BPHL as key immune-related core genes. Additionally, by integrating differential miRNAs and the miRwalk database, we identified miR-216b-5p as a key immune-related miRNA that regulates RASGRP1. In summary, the predicted miR-216b-5p/ RASGRP1 signaling pathway plays a significant role in immune regulation during CCH, which may provide new targets for immune therapy in CCH.
Humans ; Computational Biology/methods* ; Brain Ischemia/therapy* ; Immunotherapy ; MicroRNAs/genetics* ; Signal Transduction ; Dementia, Vascular/genetics* ; Chronic Disease

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.
Big Data ; Humans ; Virus Diseases/virology* ; Artificial Intelligence

OBJECTIVES: The study of medicine formulas is a core component of traditional Chinese medicine (TCM), yet traditional learning methods often lack interactivity and contextual understanding, making it challenging for beginners to grasp the intricate composition rules of formulas. To address this gap, we introduce Formula-S, a situated visualization method for TCM formula learning in augmented reality (AR) and evaluate its performance. This study aims to evaluate the effectiveness of Formula-S in enhancing TCM formula learning for beginners by comparing it with traditional text-based formula learning and web-based visualization. METHODS: Formula-S is an interactive AR tool designed for TCM formula learning, featuring three modes (3D, Web, and Table). The dataset included TCM formulas and herb properties extracted from authoritative references, including textbook and the SymMap database. In Formula-S, the hierarchical visualization of the formulas as herbal medicine compositions, is linked to the multidimensional herb attribute visualization and embedded in the real world, where real herb samples are presented. To evaluate its effectiveness, a controlled study (n=30) was conducted.Participants who had no formal TCM knowledge were tasked with herbal medicine identification, formula composition, and recognition. In the study, participants interacted with the AR tool through HoloLens 2. Data were collected on both task performance (accuracy and response time) and user experience, with a focus on task efficiency, accuracy, and user preference across the different learning modes. Results The situated visualization method of Formula-S had comparable accuracy to other methods but shorter response time for herbal formula learning tasks. Regarding user experience, our new approach demonstrated the highest system usability and lowest task load, effectively reducing cognitive load and allowing users to complete tasks with greater ease and efficiency. Participants reported that Formula-S enhanced their learning experience through its intuitive interface and immersive AR environment, suggesting this approach offers usability advantages for TCM education. CONCLUSIONS The situated visualization method in Formula-S offers more efficient and accurate searching capabilities compared to traditional and web-based methods. Additionally, it provides superior contextual understanding of TCM formulas, making it a promising new solution for TCM learning.
Medicine, Chinese Traditional/methods* ; Humans ; Learning ; Drugs, Chinese Herbal

The healing of the tendon-bone interface is a complex dynamic process involving the interaction of multiple cellular and molecular signaling pathways. Bone mesenchymal stem cells (BMSCs) have the potential to differentiate into various types of cells, including osteoblasts, chondrocytes and adipocytes, etc., and have the potential to regenerate damaged tissues. They are potential seed cells for promoting tendon-bone healing. How to precisely regulate the proliferation and differentiation of BMSCs to accelerate the process of tendon-bone healing is a current research hotspot. Monomers of traditional Chinese medicine can promote tendon-bone healing by regulating signaling pathways such as Wnt/β-catenin and BMP/Smad to induce osteogenic and chondrogenic differentiation of BMSCs. This article reviews from several aspects such as the regulatory role of related signaling pathways on tendine-bone healing, traditional Chinese medicine monomers and their mechanism of regulating BMSCs to promote tendine-bone healing in order to providing new ideas for promoting tendine-bone healing.
Mesenchymal Stem Cells/cytology* ; Humans ; Animals ; Bone Marrow Cells/cytology* ; Bone and Bones/drug effects* ; Wound Healing/drug effects* ; Medicine, Chinese Traditional ; Tendons/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Signal Transduction/drug effects* ; Cell Differentiation/drug effects*

It has been popular and challenging to undertake researches on the delay of acquired resistance of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI). As key cells for tumor initiation, cancer stem cells (CSC) play an important role in the process of resistance to EGFR-TKI. Although preliminary studies found that traditional Chinese medicine (TCM) could inhibit CSC properties and delay EGFR-TKI resistance, the specific molecular mechanism remains unclear. By summarizing the empirical syndrome treatment of EGFR-TKI resistance via TCM and combining recent researches on TCM intervention in CSC to delay EGFR-TKI resistance, this review discussed the potential molecular pathways and mechanisms of deceleration in resistance to EGFR-TKI by TCM via inhibiting CSC characteristics, in order to expand the research ideas of TCM in combination with targeted therapy.
Humans ; Neoplastic Stem Cells/metabolism* ; Drug Resistance, Neoplasm/drug effects* ; ErbB Receptors/genetics* ; Protein Kinase Inhibitors/therapeutic use* ; Medicine, Chinese Traditional ; Neoplasms/drug therapy* ; Animals ; Drugs, Chinese Herbal/therapeutic use*

The innate immune response is the first line of defense for the host against viral infections. Targeted degradation of pathogenic microorganisms through autophagy, in conjunction with pattern recognition receptors synergistically inducing the production of interferon (IFN), constitutes an important pathway for the body to resist viral infections. Rubicon, a Run domain Beclin 1-interacting and cysteine-rich domain protein, has an inhibitory effect on autophagy and IFN production. On the one hand, Rubicon, as a component of the phosphoinositide 3-kinase (PI3K) complex, interacts with different domains of vacuolar protein sorting 34 (Vps34), ultraviolet radiation resistance associated gene (UVRAG), guanosine triphosphate (GTP) kinase, and RAS oncogene family member 7 (Rab7) to mediate the inhibition of autophagy maturation; on the other hand, Rubicon inhibits the ubiquitination of nuclear factor κB essential modulator (NEMO) and the dimerization of interferon regulatory factor 3 (IRF3), thereby blocking the signal transduction related to IFN production. Research has revealed that various viruses, such as Kaposi's sarcoma-associated herpesvirus (KSHV), hepatitis B virus (HBV), Sendai virus (SeV), and hepatitis C virus (HCV), achieve innate immune evasion by regulating the expression or function of Rubicon. Rubicon is expected to be a new target for antiviral therapy.
Humans ; Autophagy/immunology* ; Immunity, Innate ; Interferons/immunology* ; Immune Evasion ; Animals ; Virus Diseases/virology* ; Signal Transduction ; Viruses/immunology* ; Intracellular Signaling Peptides and Proteins/immunology* ; Autophagy-Related Proteins

Objective To investigate the common molecular features of immunothrombosis, thus enhancing the comprehension of thrombosis triggered by immune and inflammatory responses and offering crucial insights for identifying potential diagnostic and therapeutic targets. Methods Differential gene expression analysis and functional enrichment analysis were conducted on datasets of systemic lupus erythematosus (SLE) and venous thromboembolism (VTE). The intersection of differentially expressed genes in SLE and VTE with those of neutrophil extracellular traps (NET) yielded cross-talk genes (CG) for SLE-NET and VTE-NET interaction. Further analysis included functional enrichment and protein-protein interaction (PPI) network assessments of these CG to identify hub genes. Venn diagrams and receiver operating characteristic (ROC) curve analysis were employed to pinpoint the most effective shared diagnostic CG, which were validated using a graft-versus-host disease (GVHD) dataset. Results Differential expression genes in SLE and VTE were associated with distinct biological processes, whereas SLE-NET-CG and VTE-NET-CG were implicated in pathways related to leukocyte migration, inflammatory response, and immune response. Through PPI network analysis, several hub genes were identified, with matrix metalloproteinase 9 (MMP9) and S100 calcium-binding protein A12 (S100A12) emerging as the best shared diagnostic CG for SLE (AUC: 0.936 and 0.832) and VTE (AUC: 0.719 and 0.759). Notably, MMP9 exhibited good diagnostic performance in the GVHD dataset (AUC: 0.696). Conclusion This study unveils the common molecular features of SLE, VTE, and NET, emphasizing MMP9 and S100A12 as the optimal shared diagnostic CG, thus providing valuable evidence for the diagnosis and therapeutic strategies related to immunothrombosis. Additionally, the expression of MMP9 in GVHD highlights its critical role in the risk of VTE associated with immune system disorders.
Humans ; Computational Biology/methods* ; Lupus Erythematosus, Systemic/immunology* ; Protein Interaction Maps/genetics* ; Venous Thromboembolism/therapy* ; Matrix Metalloproteinase 9/genetics* ; Extracellular Traps/metabolism* ; Gene Regulatory Networks ; Thrombosis/immunology* ; Graft vs Host Disease/genetics* ; Gene Expression Profiling

Hepatitis B virus (HBV)-specific CD8⁺ T cells play a central role in controlling HBV infection; however, their function is impaired during chronic HBV infection, manifesting as a state of dysfunction. Recent studies have revealed that CD8⁺ T cell dysfunction in chronic HBV infection differs from the classical exhaustion observed in other viral infections or tumors. In 2024, several pivotal studies further elucidated novel mechanisms underlying CD8⁺ T cell dysfunction in chronic HBV infection and identified new therapeutic targets, including 4-1BB and transforming growth factor-beta (TGF-β). This review, while elucidating the dysfunction of CD8⁺ T cells in chronic HBV infection and its underlying mechanisms, focuses on summarizing the key findings from these latest studies and explores their translational value and clinical significance.
Humans ; Hepatitis B, Chronic/virology* ; CD8-Positive T-Lymphocytes/immunology* ; Hepatitis B virus/physiology* ; Animals ; Transforming Growth Factor beta/immunology*

Objective To explore macrophage subpopulations in ischemic stroke (IS) by using single-cell RNA sequencing (scRNA-seq) data analysis and High-Dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Methods Based on single-cell sequencing data, transcriptomic information for different cell types was obtained, and macrophages were selected for subpopulation identification. hdWGCNA, cell-cell communication, and pseudotime trajectory analysis were used to explore the characteristics of macrophage subpopulations following IS. Key genes related to IS were identified using microarray data and validated for diagnostic potential through Receiver Operating Characteristic (ROC) analysis. Gene Set Enrichment Analysis (GSEA) was conducted to investigate the potential functions of these genes. Results The scRNA-seq data analysis revealed significant changes in macrophage subpopulation composition after IS. A specific macrophage subpopulation enriched in the stroke group was identified and designated as MCAO-specific macrophages (MSM). Pseudotime trajectory analysis indicated that MSM cells were in an intermediate stage of macrophage differentiation. Cell-cell communication analysis uncovered complex interactions between MSM cells and other cells, with the CCL6-CCR1 signaling axis potentially playing a crucial role in neuroinflammation. Two gene modules associated with MSM were identified via hdWGCNA, significantly enriched in pathways related to NOD-like receptors and antigen processing. By integrating differentially expressed MSM genes with conventional transcriptomic data, three IS-related hub genes were identified: Arg1, CLEC4D, and CLEC4E. Conclusion This study reveals the characteristics and functions of macrophage subpopulations following IS and identifies three hub genes with potential diagnostic value, providing novel insights into the pathological mechanisms of IS.
Macrophages/metabolism* ; Computational Biology/methods* ; Single-Cell Analysis/methods* ; Transcriptome ; Ischemic Stroke/metabolism* ; Animals ; Gene Regulatory Networks ; Gene Expression Profiling ; Humans ; Male

Objective Through integrative bioinformatics analysis of multi-source transcriptomic data, potential biomarkers to asthma epithelial cells were identified. The expression of these candidate target was subsequently validated in lung tissues and epithelial cells from asthma models. Methods The gene expression profile data of epithelial cells from three asthma patient cohorts and corresponding healthy controls were integrated from the Gene Expression Omnibus (GEO) database. Differential expression analysis and gene co-expression network analysis were performed to identify key genes and biological pathways associated with asthma. The key genes were validated in lung tissues and epithelial cells in asthma animal models. Results Differential gene expression analysis revealed 1121 upregulated and 1484 downregulated genes in epithelial cells from asthma patients compared with healthy controls. The biological pathway enrichment analysis revealed that the upregulated genes were mainly involved in glycosylation processes, whereas the downregulated genes were mainly associated with immune cell differentiation process. The gene co-expression network analysis revealed that module 9, enriched in glycosylation-related pathways, was significantly positively correlated with asthma, whereas module 17, associated with insulin and other signaling pathways, showed a significant negative correlation with asthma. We identified the genes of polypeptide N-acetylgalactosaminyltransferase 5 (GALNT5), pyrroline-5-carboxylate reductase 1 (PYCR1), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) as key genes within module 9, all of which were significantly upregulated in asthma. Finally, we validated that the expression levels of GALNT5, PYCR1, and CEACAM5 were significantly upregulated in epithelial cells from asthmatic lung tissue. Additionally, using a rat asthma model, we further confirmed that the protein levels of these three genes were significantly upregulated in lung tissues of the model group. Conclusion Through data integration and experimental validation, this study identified key genes and biological pathways closely associated with asthma pathogenesis. These findings provide a novel theoretical basis and potential targets for the diagnosis and treatment of asthma.
Asthma/metabolism* ; Humans ; Epithelial Cells/metabolism* ; Animals ; Biomarkers/metabolism* ; Gene Expression Profiling ; Transcriptome ; Gene Regulatory Networks ; Rats ; Computational Biology