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

Intervertebral disc degeneration (IDD) is largely attributed to impaired endogenous repair. Nucleus pulposus-derived stem cells (NPSCs) senescence leads to endogenous repair failure. Small extracellular vesicles/exosomes derived from mesenchymal stem cells (mExo) have shown great therapeutic potential in IDD, while whether mExo could alleviate NPSCs senescence and its mechanisms remained unknown. We established a compression-induced NPSCs senescence model and rat IDD models to evaluate the therapeutic efficiency of mExo and investigate the mechanisms. We found that mExo significantly alleviated NPSCs senescence and promoted disc regeneration while knocking down thioredoxin (TXN) impaired the protective effects of mExo. TXN was bound to various endosomal sorting complex required for transport (ESCRT) proteins. Autocrine motility factor receptor (AMFR) mediated TXN K63 ubiquitination to promote the binding of TXN on ESCRT proteins and sorting of TXN into mExo. Knocking down exosomal TXN inhibited the transcriptional activity of nuclear factor erythroid 2-related factor 2 (NRF2) and activator protein 1 (AP-1). NRF2 and AP-1 inhibition reduced endogenous TXN production that was promoted by exosomal TXN. Inhibition of NRF2 in vivo diminished the anti-senescence and regenerative effects of mExo. Conclusively, AMFR-mediated TXN ubiquitination promoted the sorting of TXN into mExo, allowing exosomal TXN to promote endogenous TXN production in NPSCs via TXN/NRF2/AP-1 feed-forward circuit to alleviate NPSCs senescence and disc degeneration.

Coptis chinensis Franch. and Panax ginseng C. A. Mey. are traditional herbal medicines with millennia of documented use and broad therapeutic applications, including anti-diabetic properties. However, the synergistic effect of total alkaloids from Coptis chinensis and total ginsenosides from Panax ginseng on type 2 diabetes mellitus (T2DM) and its underlying mechanism remain unclear. The research demonstrated that the optimal ratio of total alkaloids from Coptis chinensis and total ginsenosides from Panax ginseng was 4∶1, exhibiting maximal efficacy in improving insulin resistance and gluconeogenesis in primary mouse hepatocytes. This combination demonstrated significant synergistic effects in improving glucose tolerance, reducing fasting blood glucose (FBG), the weight ratio of epididymal white adipose tissue (eWAT), and the homeostasis model assessment of insulin resistance (HOMA-IR) in leptin receptor-deficient (db/db) mice. Subsequently, a T2DM liver-specific network was constructed based on RNA sequencing (RNA-seq) experiments and public databases by integrating transcriptional properties of disease-associated proteins and protein-protein interactions (PPIs). The network recovery index (NRI) score of the combined treatment group with a 4∶1 ratio exceeded that of groups treated with individual components. The research identified that activated adenosine 5'-monophosphate-activated protein kinase (AMPK)/acetyl-CoA carboxylase (ACC) signaling in the liver played a crucial role in the synergistic treatment of T2DM, as verified by western blot experiment in db/db mice. These findings demonstrate that the 4∶1 combination of total alkaloids from Coptis chinensis and total ginsenosides from Panax ginseng significantly improves insulin resistance and glucose and lipid metabolism disorders in db/db mice, surpassing the efficacy of individual treatments. The synergistic mechanism correlates with enhanced AMPK/ACC signaling pathway activity.
Animals ; Panax/chemistry* ; Ginsenosides/administration & dosage* ; Diabetes Mellitus, Type 2/metabolism* ; Mice ; Male ; Alkaloids/pharmacology* ; Coptis/chemistry* ; Drug Synergism ; Insulin Resistance ; Mice, Inbred C57BL ; Humans ; Transcriptome/drug effects* ; Blood Glucose/metabolism* ; Hypoglycemic Agents/administration & dosage* ; Drugs, Chinese Herbal/administration & dosage* ; Hepatocytes/metabolism*

AIM To study the chemical constituents from the buds of Aralia chinensis L.var.nuda Nakai and their in vitro anti-inflammatory activities.METHODS The 70％ethanol extract from the buds of A.chinensis var.nuda was isolated and purified by silica gel,Sephadex LH-20,ODS and semi-preparative HPLC,then the structures of compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities in vitro were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as 4-(2,2-dibutoxyethyl)phenol(1),trans-linalool-3,7-oxide-6-O-β-D-glucopyranoside(2),2'-O-(9Z,12Z,15Z-octadecatrienoyl)glyceryl β-D-galactopyranoside(3),quercetin-3-O-β-D-glucopyranoside(3'→ O-3''')quercetin-3-O-β-D-galactopyranoside(4),syringaresinol-4'-O-β-D-glucopyranoside(5),p-hydroxybenzaldehyde(6),7α-hydroxystigmasterol 3-O-β-D-glucopyranoside(7),trans-p-hydroxy cinnamic acid methyl ester(8),funingensin A(9),3,4-dihydroxy-acetophenone(10),N-acetyltyramine(11),3,4-di-O-caffeoyl quinic acid(12),chlorogenic acid(13),aralia cerebroside(14),caffeic acid methyl ester(15),tetradecanoic acid(16).The IC50values of compounds 8,10,12 and 13 were(22.19±1.59),(35.25±1.30),(13.38±0.72),(15.73±1.16)μmol/L,respectively.CONCLUSION Compound 1 is a new compound,2-13 are isolated from genus Aralia for the first time.Compounds 8,10,12,13 exhibit significant in vitro anti-inflammatory activities.

Objective To assess the efficacy of a novel inguinal tourniquet in healthy individuals and to investigate the relationship between localized inguinal compression and femoral artery blood flow occlusion.Methods A self-controlled study was conducted.From November 9 to November 30,2024,11 volunteers were recruited at the Third Medical Center of Chinese PLA General Hospital.Three compression methods--finger pressure,a novel groin tourniquet,and a SAM junction tourniquet(SJT)—were applied bilaterally to the inguinal region until distal blood flow signals disappeared.Each compression method was tested in 22 trials with a 5-minute interval between operations.Differences in hemostatic efficacy between bilateral inguinal regions and across compression methods were compared.Subsequently,the novel tourniquet was incrementally pressurized in 120 mmHg multiples using an integrated pressure device to analyze trends in popliteal artery blood flow velocity.Observational indicators included the internal pressure of the tourniquet pressurization device,peak systolic velocity(PSV)of popliteal artery,inguinal surface pressure magnitude,inguinal surface pressure distribution,and pain scores(assessed using a single-dimensional numerical rating scale).Results No statistically significant difference was observed in the minimum pressure required to occlude femoral artery blood flow bilaterally(P>0.05).The success rates of femoral artery blood flow occlusion at the inguinal region were 100%for the novel inguinal tourniquet,SJT,and finger pressure.The novel inguinal tourniquet induced the highest pain scores,ranging from 5 to 8.A significant reduction in PSV of popliteal artery was noted when the intra-tourniquet pressure reached 360 mmHg and 480 mmHg(P<0.05),with a 95%hemostasis efficacy observed within the range of 360-600 mmHg.No significant association was observed between the recovery of popliteal artery blood flow after limb movement and inguinal pressure distribution(P>0.05).The PSV of popliteal artery exhibited the strongest negative correlation with the average pressure within the inguinal compression area(r=-0.79,P<0.001),with a linear regression fitting line of y=69.69-0.13x(P<0.001,R2=0.58).Conclusions The novel inguinal tourniquet effectively occludes femoral artery blood flow within a pressure range of 360-600 mmHg,accompanied by moderate-to-severe pain.Its hemostatic mechanism mainly relies on increasing the mean pressure within the inguinal compression area.

Objective:To investigate the prevalence of sarcopenia and potential influencing factors in middle-aged and elderly populations in Zhejiang Province.Methods:Data were obtained from Zhejiang Provincial Household Economic Status Survey, a cross-sectional survey was condcuted in middle-aged and olde adults selected through multi-stage sampling in three cities in Zhejiang (Huzhou, Jiaxing and Shaoxing) in July 2023. A total of 3 019 study participants, average age 62.3 years old, 53.5% men, were included according to the inclusion and exclusion criteria. Sarcopenia screening was conducted by using the questionnaire with five sarcopenia related-items. Univariable and multivariable logistic regression analysis was used to identify the factors associated with sarcopenia.Results:The prevalence of sarcopenia in the middle-aged and old study participants was 4.47%. Significant differences were observed between the participants with or without sarcopenia in terms of age, educational level, BMI, alcohol consumption status, diet habit, physical activity level, sleep quality, number of chronic diseases, childhood socioeconomic status, adulthood community socioeconomic status, muscle strength, walking assistance, ability to stand from seat, ability to climb stairs, and fall frequency ( P<0.05). Multivariable logistic regression analysis revealed that old age (≥75 years: OR=2.82, 95% CI: 1.60-4.97), low body weight ( OR=1.96, 95% CI: 1.06-3.62), unhealthy diet habit ( OR=1.57, 95% CI: 1.01-2.46), physical inactivity ( OR=5.80, 95% CI: 3.09-10.88), poor or very poor sleep quality ( OR=1.65, 95% CI:1.23-2.41), number of chronic diseases (1 chronic disease: OR=1.84, 95% CI: 1.08-3.14; 2 chronic diseases: OR=3.22, 95% CI: 1.81-5.71; 3 or more chronic diseases: OR=3.74, 95% CI: 2.11-6.65), poor childhood socioeconomic status ( OR=2.98, 95% CI: 1.23-7.20), and poor adulthood community socioeconomic status ( OR=3.87, 95% CI: 1.63-9.17) were significant risk factors for sarcopenia. Conclusions:The prevalence of sarcopenia was relatively low in middle-aged and old population in Zhejiang. Age, BMI, unhealthy diet, physical activity level, sleep quality, number of chronic diseases, childhood socioeconomic status, and adulthood community socioeconomic status were identified as significant influencing factors.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To analyze the research status of in situ simulation in the medical field and explore its hotspots and trends. Methods Relevant literature was searched in China National Knowledge Infrastructure and Web of Science core collection from the inception to February 2024.CiteSpace 6.3.R1 was used to analyze the authors,institutions,and keywords and draw visual knowledge maps. Results A total of 25 Chinese articles and 438 English articles were included.Only 14 English articles were from China.In Chinese articles,the authors with the largest number of articles were Dai Hengmao and Liu Shangkun,and the institution with the largest number of articles was Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology.There was little cooperation between the authors and institutions.In English articles,the author and institution with the largest number of articles was Auerbach Marc and Yale University,respectively,and the cooperation between authors and institutions was close.Emergency medicine,emergency event handling,and on-the-job training were the keywords with high frequency in Chinese articles.Patient safety,medical education,and cardiac arrest were the keywords with high frequency in English articles.A total of 4 clusters were generated for Chinese keywords and 13 clusters for English keywords. Conclusions The application of in situ simulation in the medical field is still in the initial stage,and the development is not balanced at home and abroad.The number of articles published and the cooperation between authors and institutions in China obviously lags behind those abroad.Treatment and care of emergency critical patients,emergency event handling and skill training,identification of latent safety threats,improvement of readiness,and promotion of medical quality improvement are the future research hotspots and research trends in this field.
Bibliometrics ; Humans ; China ; Simulation Training ; Education, Medical ; Emergency Medicine/education*