OBJECTIVES: Injury to human cardiac microvascular endothelial cells (HCMECs) compromises myocardial microcirculation and may contribute to major cardiovascular events such as coronary heart disease, posing a serious health threat. Understanding the mechanisms of hypoxia-induced HCMEC damage is thus of great clinical relevance. This study aims to investigate the protective effects and underlying mechanisms of Li Qi Huo Xue Di Wan against hypoxia-induced HCMEC injury. METHODS: HCMECs were cultured under hypoxic conditions for 24 hours to establish a cellular model of hypoxic injury. Cells were divided into six groups: normal control, hypoxia, hypoxia + low-dose Li Qi Huo Xue Di Wan, hypoxia + medium-dose, hypoxia + high-dose, and hypoxia + salvianolic acid B (positive control). Cell viability was assessed using the MTS assay. Lactate dehydrogenase (LDH) release and malondialdehyde (MDA) content were measured to evaluate cytotoxicity and oxidative stress. Activities of superoxide dismutase (SOD), catalase (CAT), caspase-3, and caspase-8 were determined with corresponding assay kits. Apoptosis was analyzed by flow cytometry, and expression of necroptosis-related proteins, receptor-interacting protein kinase 1 (RIPK1) and its phosphorylated form (p-RIPK1), receptor-interacting protein kinase 3 (RIPK3) and its phosphorylated form (p-RIPK3), mixed lineage kinase domain-like protein (MLKL) and its phosphorylated form (p-MLKL), was examined via Western blotting. RESULTS: Compared with the control group, hypoxia significantly decreased cell viability (P<0.01), increased MDA levels (P<0.05), and reduced CAT and SOD activity (P<0.05), accompanied by elevated apoptosis (P<0.01) and increased levels of p-RIPK1, p-RIPK3, and p-MLKL (P<0.05). High-dose Li Qi Huo Xue Di Wan significantly improved cell viability (P<0.01), reduced MDA content (P<0.05), increased CAT activity (P<0.05), and suppressed necroptosis-related protein expression (P<0.05) compared with the hypoxia group. CONCLUSIONS Li Qi Huo Xue Di Wan exerts a protective effect against hypoxia-induced injury in HCMECs. This effect is mediated by attenuation of oxidative stress, thereby reducing both apoptosis and necroptosis.
Humans ; Apoptosis/drug effects* ; Necroptosis/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Cell Hypoxia/drug effects* ; Endothelial Cells/pathology* ; Oxidative Stress/drug effects* ; Cells, Cultured ; Cell Survival/drug effects* ; Receptor-Interacting Protein Serine-Threonine Kinases/metabolism*

OBJECTIVES: Chronic obstructive pulmonary disease (COPD) is a major chronic respiratory condition with high morbidity and mortality, imposing a serious economic and public health burden. The World Health Organization ranks COPD among the top 4 chronic diseases worldwide. Zangsiwei Qingfei Mixture (ZSWQF), a novel Tibetan herbal formulation independently developed by our research team, has shown therapeutic potential for chronic respiratory diseases. This study aims to evaluate the effects of aerosolized ZSWQF on cigarette smoke-induced COPD in mice and explore its underlying mechanisms. METHODS: Thirty C57 mice were randomly divided into a Control group, a COPD group, and a ZSWQF group. The Control group received saline aerosol inhalation without cigarette smoke exposure; both the COPD group and the ZSWQF group were exposed to cigarette smoke, with the former receiving saline inhalation and the latter treated with ZSWQF aerosol. White blood cell (WBC) count was performed using a fully automatic blood cell analyzer. Serum, alanine transaminase (ALT), and serum creatinine (SCr), as well as interleukin (IL)-6, IL-8, and tumor necrosis factor (TNF)-α levels in serum and bronchoalveolar lavage fluid (BALF) were measured by enzyme-linked immunosorbent assay (ELISA). BALF cell classification was determined using a hematology analyzer. Lung function was assessed with a small animal pulmonary function system, including airway resistance (RI) and cyclic dynamic compliance (CyDN). Lung tissues were stained with hematoxylin and eosin (HE), and mean linear intercept (MLI) and destruction index (DI) were calculated to evaluate morphological changes. Network pharmacology was applied to identify disease-related and ZSWQF-related targets, followed by intersection and protein-protein interaction (PPI) network analysis, and enrichment analysis of biological functions and pathways. Primary type II alveolar epithelial cell (AEC II) from SD rats were isolated and divided into a Control group, a lipopolysaccharide (LPS) group, a normal serum group, a water extract of ZSWQF (W-ZSWQF) group, a ZSWQF containing serum group, and a MLN-4760 [angiotensin-converting enzyme (ACE) 2 inhibitor]. Western blotting was performed to assess protein expression of ACE, p38 [a mitogen-activated protein kinase (MAPK)], phospho (p)-p38, extracellular signal-regulated kinases 1 and 2 (ERK1/2), p-ERK1/2, c-Jun N-terminal kinase (JNK), p-JNK, inhibitor of nuclear factor-kappa B alpha (IκBα), p-IκBα, and p-p65 subunit of nuclear factor-kappa B (NF-κBp65). RESULTS: WBC counts were significantly higher in the COPD group than in controls (P<0.01) and decreased following ZSWQF treatment (P<0.05). No significant intergroup differences were found in organ weights, ALT, or SCr (all P>0.05). Serum and BALF levels of IL-6, IL-8, and TNF-α, as well as total BALF cells, neutrophils, and macrophages, were elevated in the COPD group compared with controls and reduced by ZSWQF treatment (P<0.05). COPD mice exhibited increased RI, decreased CyDN, marked alveolar congestion, inflammatory infiltration, thickened septa, and higher MLI and DI values versus controls (P<0.05); ZSWQF treatment significantly reduced MLI and DI (P<0.05). Network pharmacology identified 151 potential therapeutic targets for ZSWQF against COPD, with key nodes including TNF, IL-6, protein kinase B (Akt) 1, albumin (ALB), tumor protein p53 (TP53), non-receptor tyrosine kinase (SRC), epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT) 3, matrix metalloproteinase (MMP)-9, and beta-catenin (CTNNB1). Enrichment analysis indicates involvement of cancer-related, phosphatidylinositol 3-kinase (PI3K)/Akt, hypoxia-inducible factor (HIF)-1, calcium, and MAPK signaling pathways. Western blotting results showed that compared with the LPS group, AEC II treated with ZSWQF-containing serum exhibited decreased expression of ACE, p-p38/p38, p-ERK1/2/ERK1/2, p-JNK/JNK, p-IκBα/IκBα, and p-NF-κBp65, while ACE2 expression was upregulated, consistent with the MAPK/nuclear factor-kappa B (NF-κB) pathway regulation predicted by network pharmacology. CONCLUSIONS Aerosolized ZSWQF provides protective effects in COPD mice by reducing airway inflammation and remodeling.
Animals ; Pulmonary Disease, Chronic Obstructive/etiology* ; Drugs, Chinese Herbal/therapeutic use* ; Mice ; Mice, Inbred C57BL ; Male ; Network Pharmacology ; Smoke/adverse effects* ; Bronchoalveolar Lavage Fluid ; Administration, Inhalation ; Inflammation/drug therapy* ; Tumor Necrosis Factor-alpha ; Lung/drug effects* ; Interleukin-6/blood*

The glucagon receptor (GCGR) is a critical target for the treatment of metabolic disorders such as Type 2 Diabetes Mellitus (T2DM) and obesity. Activation of GCGR enhances systemic insulin sensitivity through paracrine stimulation of insulin secretion, presenting a promising avenue for treatment. However, the discovery of effective GCGR agonists remains a challenging and resource-intensive process, often requiring time-consuming wet-lab experiments to synthesize and screen potential compounds. Recent advances in artificial intelligence technologies have demonstrated great potential in accelerating drug discovery by streamlining screening and efficiently predicting bioactivity. In the present work, we propose DeepGCGR, a two-layer deep learning model that leverages graph convolutional networks (GCN) integrated with a multiple attention mechanism to expedite the identification of GCGR agonists. In the first layer, the model predicts the bioactivity of various compounds against GCGR, efficiently filtering large chemical libraries to identify promising candidates. In the second layer, DeepGCGR classifies high bioactive compounds based on their functional effects on GCGR signaling, identifying those with potential agonistic or antagonistic effects. Moreover, DeepGCGR was specifically applied to identify novel GCGR-regulating compounds for the treatment of T2DM from natural products derived from traditional Chinese medicine (TCM). The proposed method will not only offer an effective strategy for discovering GCGR-targeting compounds with functional activation properties but also provide new insights into the development of T2DM therapeutics.
Deep Learning ; Drug Discovery/methods* ; Humans ; Diabetes Mellitus, Type 2/metabolism* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/pharmacology*

Traditional Chinese medicine formula (TCMF) represents a fundamental component of Chinese medical practice, incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities, while providing comprehensive insights into health and disease. The foundation of TCMF lies in its holistic approach, manifested through herbal compatibility theory, which has emerged from extensive clinical experience and evolved into a highly refined knowledge system. Within this framework, Chinese herbal medicines exhibit intricated characteristics, including multi-component interactions, diverse target sites, and varied biological pathways. These complexities pose significant challenges for understanding their molecular mechanisms. Contemporary advances in artificial intelligence (AI) are reshaping research in traditional Chinese medicine (TCM), offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs. This review explores the application of AI in uncovering these mechanisms, highlighting its role in compound absorption, distribution, metabolism, and excretion (ADME) prediction, molecular target identification, compound and target synergy recognition, pharmacological mechanisms exploration, and herbal formula optimization. Furthermore, the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms, promoting the modernization and globalization of TCM.
Artificial Intelligence ; Drugs, Chinese Herbal/pharmacokinetics* ; Humans ; Medicine, Chinese Traditional ; Animals

Network pharmacology has gained widespread application in drug discovery, particularly in traditional Chinese medicine (TCM) research, which is characterized by its "multi-component, multi-target, and multi-pathway" nature. Through the integration of network biology, TCM network pharmacology enables systematic evaluation of therapeutic efficacy and detailed elucidation of action mechanisms, establishing a novel research paradigm for TCM modernization. The rapid advancement of machine learning, particularly revolutionary deep learning methods, has substantially enhanced artificial intelligence (AI) technology, offering significant potential to advance TCM network pharmacology research. This paper describes the methodology of TCM network pharmacology, encompassing ingredient identification, network construction, network analysis, and experimental validation. Furthermore, it summarizes key strategies for constructing various networks and analyzing constructed networks using AI methods. Finally, it addresses challenges and future directions regarding cell-cell communication (CCC)-based network construction, analysis, and validation, providing valuable insights for TCM network pharmacology.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Network Pharmacology/methods* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Drug Discovery

Due to its synergistic effects and reduced side effects, combination therapy has become an important strategy for treating complex diseases. In traditional Chinese medicine (TCM), the "monarch, minister, assistant, envoy" compatibilities theory provides a systematic framework for drug compatibility and has guided the formation of a large number of classic formulas. However, due to the complex compositions and diverse mechanisms of action of TCM, it is difficult to comprehensively reveal its potential synergistic patterns using traditional methods. Synergistic prediction based on molecular compatibility theory provides new ideas for identifying combinations of active compounds in TCM. Compared to resource-intensive traditional experimental methods, artificial intelligence possesses the ability to mine synergistic patterns from multi-omics and structural data, providing an efficient means for modeling and optimizing TCM combinations. This paper systematically reviews the application progress of AI in the synergistic prediction of TCM active compounds and explores the challenges and prospects of its application in modeling combination relationships, thereby contributing to the modernization of TCM theory and methodological innovation.
Artificial Intelligence ; Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal/pharmacology* ; Humans ; Drug Synergism

Traditional Chinese medicine (TCM) demonstrates distinctive advantages in disease prevention and treatment. However, analyzing its biological mechanisms through the modern medical research paradigm of "single drug, single target" presents significant challenges due to its holistic approach. Network pharmacology and its core theory of network targets connect drugs and diseases from a holistic and systematic perspective based on biological networks, overcoming the limitations of reductionist research models and showing considerable value in TCM research. Recent integration of network target computational and experimental methods with artificial intelligence (AI) and multi-modal multi-omics technologies has substantially enhanced network pharmacology methodology. The advancement in computational and experimental techniques provides complementary support for network target theory in decoding TCM principles. This review, centered on network targets, examines the progress of network target methods combined with AI in predicting disease molecular mechanisms and drug-target relationships, alongside the application of multi-modal multi-omics technologies in analyzing TCM formulae, syndromes, and toxicity. Looking forward, network target theory is expected to incorporate emerging technologies while developing novel approaches aligned with its unique characteristics, potentially leading to significant breakthroughs in TCM research and advancing scientific understanding and innovation in TCM.
Artificial Intelligence ; Medicine, Chinese Traditional ; Humans ; Network Pharmacology/methods* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Multiomics

Objective:To analyze the clinical characteristics and prognostic factors of patients with acute low-frequency hearing loss（ALHL） and explore the potential role of migraine in its pathogenesis. Methods:A total of 56 ALHL patients treated at our outpatient clinic from June 2024 to January 2025 were randomly divided into two groups: a standardized treatment group and an anti-migraine treatment group. The standardized group received oral/intravenous steroids + oral/intravenous Ginkgo biloba extract, while the anti-migraine group received postauricular steroid injection/oral steroids + oral flunarizine for 2 weeks. Audiological, clinical, and psychological characteristics were collected, and statistical analysis was performed to assess clinical features and treatment outcomes, exploring the potential mechanism of migraine in ALHL. Results:The anti-migraine treatment group showed a significantly higher recovery rate than the standardized treatment group（92.86% vs 71.43%, P=0.036）. Among the anti-migraine group, 6 patients（21.43%） had a history of ALHL, 13（46.43%） had a confirmed migraine history, 26（92.86%） had anxiety, 26（92.86%） had depression, 5（17.86%） had irritable bowel syndrome, 21（75.00%） had sleep disorders, and 1（3.57%） experienced recurrence within 6 months. Conclusion:Anti-migraine therapy significantly improves the recovery rate in ALHL patients, suggesting that migraine may have a certain correlation with the pathogenesis of acute low-frequency hearing loss.
Humans ; Migraine Disorders/complications* ; Ginkgo biloba ; Male ; Female ; Flunarizine/therapeutic use* ; Plant Extracts/therapeutic use* ; Adult ; Treatment Outcome ; Middle Aged ; Ginkgo Extract

OBJECTIVES: To explore the mechanism of Qingda Granules (QDG) for alleviating brain damage in spontaneously hypertensive rats (SHRs). METHODS: Twelve 5-week-old SHRs were randomized into SHR control group and SHR+QDG group treated with QDG by gavage at the daily dose of 0.9 g/kg for 12 weeks. The control rats, along with 6 age-matched WKY rats, were treated with saline only. Blood pressure changes of the rats were monitored, and pathologies and neuronal apoptosis in the cerebral cortex were examined with HE staining and TUNEL staining. Cerebral cortical expressions of miR-124 and STAT3 mRNA were detected using RT-qPCR, and the protein expressions of NeuN, STAT3, Bcl-2, Bax, and cleaved caspase-3 were detected with immunohistochemistry and Western blotting. In a HT22 cell model of oxygen and glucose deprivation/reoxygenation (OGD/R), the effects of QDG on cell viability and apoptosis, expressions of miR-124 and STAT3 mRNA, and protein expressions of STAT3, Bcl-2, Bax, and cleaved caspase-3 were evaluated using CCK8 assay, Hoechst 33342 staining, RT-qPCR, and Western blotting. RESULTS: Compared with WKY rats, SHRs had significantly elevated systolic blood pressure, diastolic blood pressure and mean arterial pressure with significantly increased neuronal apoptosis in the cerebral cortex, reduced expressions of NeuN, miR-124 and Bcl-2, and enhanced expressions of STAT3, Bax and cleaved caspase-3 (P<0.05). All these changes in the SHRs were significantly ameliorated by treatment with QDG (P<0.05). In the HT22 cell model, QDG treatment obviously reduced OGD/R-induced cell apoptosis, increased the expressions of miR-124 and Bcl-2, and suppressed the elevation of protein expressions of STAT3, Bax and cleaved caspase-3. CONCLUSIONS QDG inhibits cerebral cortical neuronal apoptosis and thereby attenuates brain damage in SHR rats by modulating the miR-124/STAT3 signaling axis.
Animals ; Rats, Inbred SHR ; MicroRNAs/metabolism* ; STAT3 Transcription Factor/metabolism* ; Signal Transduction/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Rats ; Apoptosis/drug effects* ; Rats, Inbred WKY ; Male ; Hypertension

OBJECTIVES: To investigate the protective effect of Yiqi Yangyin Huazhuo Tongluo Formula (YYHT) against high glucose-induced injury in mouse renal podocytes (MPC5 cells) and the possible mechanism. METHODS: Adult Wistar rats were treated with 19, 38, and 76 g/kg YYHT or saline via gavage for 7 days to prepare YYHT-medicated or blank sera for treatment of MPC5 cells cultured in high glucose (30 mmol/L) prior to transfection with a miR-21a-5p inhibitor or a miR-21a-5p mimic. The changes in miR-21a-5p expressions and the mRNA levels of FoxO1, PINK1, and Parkin in the treated cells were detected with qRT-PCR, and the protein levels of nephrin, podocin, FoxO1, PINK1, and Parkin were detected with Western blotting. Autophagic activity in the cells were evaluated with MDC staining. The effect of miR-21a-5p mimic on FoxO1 transcription and the binding of miR-21a-5p to FoxO1 were examined with luciferase reporter gene assay and radioimmunoprecipitation assay. RESULTS: MPC5 cells exposed to high glucose showed significantly increased miR-21a-5p expression, lowered expressions of FoxO1, PINK1, and Parkin1 mRNAs, and reduced levels of FoxO1, PINK1, parkin, nephrin, and podocin proteins and autophagic activity. Treatment of the exposed cells with YYHT-medicated sera and miR-21a-5p inhibitor both significantly enhanced the protein expressions of nephrin and podocin, inhibited the expression of miR-21a-5p, increased the mRNA and protein expressions of FoxO1, PINK1 and Parkin, and upregulated autophagic activity of the cells. Transfection with miR-21a-5p mimic effectively inhibited the transcription of FoxO1 and promoted the binding of miR-21a-5p to FoxO1 in MPC5 cells, and these effects were obviously attenuated by treatment with YYHT-medicated sera. CONCLUSIONS YYHT-medicated sera alleviate high glucose-induced injury in MPC5 cells by regulating miR-21a-5p/FoxO1/PINK1-mediated mitochondrial autophagy.
Animals ; MicroRNAs/genetics* ; Podocytes/pathology* ; Drugs, Chinese Herbal/pharmacology* ; Autophagy/drug effects* ; Rats, Wistar ; Protein Kinases/metabolism* ; Rats ; Forkhead Box Protein O1 ; Mice ; Mitochondria/drug effects* ; Ubiquitin-Protein Ligases/metabolism* ; Glucose ; Diabetic Nephropathies ; Male ; Membrane Proteins/metabolism* ; Intracellular Signaling Peptides and Proteins