The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Objective:To explore the independent risk factors for uremic encephalopathy(UE)in maintenance hemodialysis(MHD)patients and provide evidence for early clinical warning and intervention.Methods:A case-control study was conducted,enrolling 67 MHD patients diagnosed with UE(UE group)at Laibin People's Hospital from January 2010 to December 2024,and 67 non-UE patients during the same period(control group).Demographic characteristics,dialysis parameters,laboratory indicators,and infection events were collected.Univariate and multivariate logistic regression analyses were used to identify independent risk factors for UE.Results:The UE group had significantly higher rates of infection(58.2％vs.29.9％),serum creatinine(789 vs.702 μmol/L),and iPTH levels(568 vs.385 pg/mL)compared to the control group(P＜0.05).Multivariate analysis revealed that concurrent infection(OR=3.022,95％CI:1.312-6.958),elevated serum creatinine(OR=1.004,95％CI:1.000-1.008),and elevated iPTH(OR=1.002,95％CI:1.001-1.003)were independent risk factors for UE(P＜0.05).The combined prediction model achieved an AUC of 0.878(95％CI:0.822-0.934),with 82.1％sensitivity and 80.6％specificity.Conclusion:Infection,elevated serum creatinine,and elevated iPTH significantly increase the risk of UE in MHD patients.Clinical management should emphasize infection prevention,toxin clearance optimization,and parathyroid function regulation to reduce UE incidence.

Objective:To explore the incidence status,influencing factors and short-term prognosis characteristics of early onset coronary heart disease in women in Wansheng District of Chongqing,and to provide scientific basis for formulating regional prevention and treatment strategies.Methods:This study was a single-center retrospective study,100 coronary heart disease in women from January 2022 to December 2023 at Chongqing Wansheng Economic and Technological Development Zone People's Hospital were prospective selected,and they were divided into early onset group of 40 cases(≤ 65 years old)and late onset group of 60 cases(＞65 years old)based on their age of onset.Another 60 healthy women who underwent physical examinations during the same period to exclude coronary heart disease were selected as the control group.Univariate factor and multiple factor logistic regression analysis were used to identify independent risk factors for early onset coronary heart disease in women.Draw receiver operating characteristic(ROC)curve for the subjects,the efficacy of risk factors in predicting early onset coronary heart disease based on the area under the curve(AUC)of ROC curve were evaluated.Patients were followed up for 1 year to observe the occurrence of major adverse cardiovascular events(MACE).Result:Among 100 fcoronary heart disease in women,the early onset group accounted for 40.00％(40/100).Univariate analysis showed that age,hyperlipidemia history,smoking history,hypertension history,family history,diabetes history,total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C)were related to the early onset coronary heart disease.Multivariate analysis showed that,hyperlipidemia history(OR=4.124,95％CI:2.343-7.217),smoking history(OR=3.564),hypertension(OR=3.253),family history(OR=2.981),diabetes history(OR=2.873)were independent risk factors.ROC curve analysis results showed that joint evaluation had the best predictive value,with AUC of 0.829,which was higher than the AUC of individual evaluation for each factor.The incidence of MACE in the early onset group(45.00％)was significantly higher than that in the late onset group(P＜0.05).Conclusion:Early onset coronary heart disease in women in Wansheng District of Chongqing is related to the hyperlipidemia history,smoking,hypertension history,family history and diabetes history.The incidence of MACE in early-onset patients followed up for 1 year is higher than that in late-onset patients.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

Neuroinflammatory responses play an important role in the pathogenesis of various diseases, particularly those affecting the central nervous system. Inhibition of neuroinflammation is a crucial therapeutic strategy for the management of central nervous system disorders. The intestinal microbial-gut-brain axis serves as a key regulatory pathway that modulates neuroinflammatory processes. Intestinal flora metabolites such as short-chain fatty acids, indoles and their derivatives, lipopolysaccharides, trimethylamine oxide, and secondary bile acids exert direct or indirect effects on neuroinflammation. Studies have shown that electroacupuncture (EA) modulates the composition of the intestinal microbiota and its metabolites, while also suppressing neuroinflammation by targeting the TLR4/NF- κ B, NLRP3/caspase-1, and microglial cell M2-type transformation pathways. This review discusses the mechanisms by which EA regulates neuroinflammation via intestinal microbiota and its metabolites, providing information and a foundation for further investigation of the precise therapeutic mechanisms of EA in neurological disorders.
Humans ; Gastrointestinal Microbiome ; Electroacupuncture ; Neuroinflammatory Diseases/metabolism* ; Animals

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.