To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

AIM: To evaluate the efficacy and safety of 3% diquafosol sodium eye drops in children wearing orthokeratology lenses and with dry eye disease(DED)or at risk of DED.METHODS: Randomized controlled trials. Children with DED or at risk of DED were randomly assigned in a 1:1 ratio to receive either 3% diquafosol sodium eye drops 6 times daily or a blank control at Chongqing Aier Children's Eye Hospital from November 2023 to November 2024. The primary endpoint was the change in the Dry Eye Questionnaire-5(DEQ-5)score from baseline at 12 wk. Secondary assessments included non-invasive breakup time(NIBUT), tear meniscus height, Schirmer's test, corneal fluorescein staining score, and axial length.RESULTS: A total of 80 participants(80 eyes)were enrolled(40 in each group), the average age of the participants was 11.11±1.88 years, with 43 females(54%)and 37 males(46%), and all completed the trial. After 12 wk, the DEQ-5 scores for the diquafosol sodium group and the blank control group were 1.88±2.02 and 2.88±2.79, respectively(P=0.079). The diquafosol sodium group demonstrated a significant improvement in DEQ-5 dryness symptom scores(-0.33±0.66 vs. 0.05±0.81, P=0.023)and NIBUT(6.18±3.73 vs. -1.09±4.40 s, P<0.001)at 12 wk. Additionally, the diquafosol sodium group showed no axial length elongation, in contrast to the blank control group, which exhibited elongation(0.00±0.08 vs. 0.05±0.10 mm, P=0.013). No other significant differences were found in the secondary endpoints. No adverse events occurred during the trial.CONCLUSION: Although no statistically significant improvements were noted in the overall DEQ-5 scores, the 3% diquafosol sodium eye drops significantly improved dryness symptoms and NIBUT when compared to the blank control group.

BackgroundIndividuals with schizophrenia are prone to higher rates of hospital readmission， presenting significant clinical challenges and imposing considerable social burdens within the mental health domain. In recent years， various risk prediction models have been developed to forecast readmission in patients with schizophrenia and support clinical decision-making， but their predictive performance and clinical applicability require comprehensive evaluation. ObjectiveTo systematically evaluate the risk prediction models for readmission in patients with schizophrenia， so as to provide insights for the development of high-performance and highly applicable readmission risk prediction models for patients with schizophrenia. MethodsOn July 5， 2025， a systematic literature search was conducted across multiple electronic databases， including PubMed， Embase， Cochrane Library， Web of Science， CINAHL， CNKI， China Biomedical Literature Database， Wanfang Database， and VIP Database， to identify risk prediction models for readmission in patients with schizophrenia. The search period was from the establishment of the databases to July 1， 2025. Two researchers independently performed literature screening， data extraction， risk of bias assessment， and applicability assessment. ResultsA total of 9 studies were included in this review， encompassing 18 risk prediction models for readmission in patients with schizophrenia. Among them， 4 models reported the area under the receiver operating characteristic （ROC） curve （AUC）， ranging from 0.734 to 0.820， 16 models provided AUC values of 0.642–0.879 for internal validation， and 1 model demonstrated an AUC of 0.841 for external validation. Key predictors included disease duration and the concomitant therapy of antipsychotic medications. The risk of bias was assessed as "high" in all included studies. ConclusionThe development of risk prediction models for readmission in patients with schizophrenia remains in an exploratory stage. Although the model exhibits favorable predictive performance， it is associated with a high risk of bias and insufficient performance evaluation.

[Objective] To explore the effectiveness of applying the PDCA (Plan-Do-Check-Act) cycle to enhance the compatibility rate of five Rh blood group antigen phenotypes between donors and recipients across multiple hospital campuses. [Methods] Clinical blood transfusion data from May to July 2022 were selected. Specific improvement measures were formulated based on the survey results, and the PDCA cycle management model was implemented from August 2022. The post-intervention phase spanned from August 2022 to October 2023. The Rh phenotype compatibility rate, the detection rate of Rh system antibodies, and the proportion of Rh system antibodies among unexpected antibodies were compared between the pre-intervention phase (May to July 2022) and the post-intervention phase. [Results] After the continuous improvement with the PDCA cycle, the compatibility rate for the five Rh blood group antigen phenotypes between donors and recipients from August to October 2023 reached 81.90%, significantly higher than the 70.54% recorded during the pre-intervention phase (May to July 2022, P<0.01), and displayed a quarterly upward trend (β=0.028, P<0.05). The detection rate of Rh blood group system antibodies (β=-9.839×10^-5, P<0.05) and its proportion among all detected antibodies (β=-0.022, P<0.05) showed a quarterly decreasing trend, both demonstrating a negative correlation with the enhanced compatibility rate (r values of -0.981 and -0.911, respectively; P<0.05). [Conclusion] The implementation of targeted measures through the PDCA cycle can effectively increase the compatibility rate of five Rh blood group antigen phenotypes between donors and recipients, reduce the occurrence of unexpected Rh blood group antibodies, thereby lowering the risk of transfusion and enhancing the quality and safety of medical care.

As people’s attention to health continues to increase, the market demand for traditional Chinese medicine (TCM) is growing steadily. The quality and safety of Chinese medicinal materials have attracted unprecedented social attention. In particular, the issue of exogenous harmful residue pollution in TCM has become a hot topic of concern for both regulatory authorities and society. The Chinese Pharmacopoeia 2025 Edition further refines the detection methods and limit standards for exogenous harmful residues in TCM. This not only reflects China’s high-level emphasis on the quality and safety of TCM but also demonstrates the continuous progress made by China in the field of TCM safety supervision. Basis on this study, by systematically reviewing the development history of the detection standards for exogenous harmful residues in TCM and analyzing the revisions and updates of these detection standards in the Chinese Pharmacopoeia 2025 Edition, deeply explores the key points of the changes in the monitoring standards for exogenous harmful residues in TCM in the Chinese Pharmacopoeia 2025 Edition. Moreover, it interprets the future development directions of the detection of exogenous residues in TCM, aiming to provide a reference for the formulation of TCM safety supervision policies.

Objective To establish a model for accurate prediction of hematoma expansion（HE）following spontaneous intracerebral hemorrhage（sICH）based on CT radiomics and different machine learning algorithms. Methods A retrospective analysis was performed for the patients with sICH who were admitted to Sir Run Run Shaw Hospital and Beijing Electric Power Hospital in 2019-2022，and they were established as the training cohort and the external validation cohort，respectively. Radiomic features of hematomas were extracted from CT images and were combined with related clinical risk factors for HE to establish predictive models using four different machine learning algorithms. The receiver operating characteristic（ROC）curve was used to assess the predictive performance of each model，and the area under the ROC curve（AUC）and corresponding confusion matrix metrics were calculated. Results Compared with the other three models，the support vector machine（SVM）model showed the best predictive performance，achieving an AUC of 0.844 in the training cohort and 0.994 in the external validation cohort. In addition，the SVM model achieved the highest F1 scores（0.891 and 0.989），accuracy rates（83.8% and 98.4%），precision rates（94.5% and 99.9%），and specificities（82.4% and 99.9%）. Conclusion The radiomics model based on SVM provides a noninvasive tool for accurately predicting the risk of HE，which can help clinicians to identify high-risk sICH patients in the early stage and adjust treatment strategies in a timely manner.

This study aims to investigate the ameliorating effect of Corni Fructus(CF) on the myocardial ischemic injury and the pharmacokinetic properties of characteristic components of CF. The mouse model of isoproterenol-induced myocardial ischemia was established and administrated with the aqueous extract of CF. The general efficacy of CF in ameliorating the myocardial ischemic injury was evaluated based on the cardiac histopathology and the levels of myocardial injury markers: creatine kinase isoenzyme(CK-MB) and cardiac troponin I(cTn-I). The metabolomics analysis was carried out for the heart and serum samples of mice to screen the biomarkers of CF in ameliorating the myocardial ischemic injury and then the predicted biomarkers were submitted to metabolic pathway enrichment. The pharmacokinetic analysis was performed for morroniside, loganin, and cornuside Ⅰ in mouse heart and serum samples to obtain the pharmacokinetic parameters of these components. The pharmacokinetic parameters were then integrated on the basis of self-defined weighting coefficients to simulate an integrated pharmacokinetic profile of CF iridoid glycosides in the heart and serum of the mouse model of myocardial ischemia. The results indicated that CF reduced the pathological damage to cardiac cells and tissue(hematoxylin-eosin staining) and lowered the levels of CK-MB and cTn-I in the serum of the mouse model of myocardial ischemia(P<0.01). Metabolomics analysis screed out 31 endogenous metabolites in the heart and 35 in the serum as biomarkers of CF in ameliorating the myocardial ischemic injury. These biomarkers were altered by modeling and restored by CF. Six metabolic pathways in the heart and 5 in the serum were enriched based on these metabolic markers. The main integrated pharmacokinetic parameters of CF iridoid glycosides were T_(max)=1 h, t_(1/2)=(1.52±0.05) h in the heart and T_(max)=1 h, t_(1/2)=(1.56±0.50) h in the serum. Both concentration-time curves showed a double-peak phenomenon. In conclusion, CF demonstrated the cardioprotective effect by regulating metabolic pathways such as taurine and hypotaurine metabolism, and pantothenic acid and coenzyme A biosynthesis. The integrated pharmacokinetics reflect the general pharmacokinetic properties of characteristic components in CF.
Animals ; Cornus/chemistry* ; Mice ; Metabolomics ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Myocardial Ischemia/metabolism* ; Humans ; Troponin I/metabolism* ; Myocardium/pathology* ; Disease Models, Animal ; Biomarkers/metabolism* ; Creatine Kinase, MB Form/metabolism*

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

In recent years, there have been frequent adverse reactions/events associated with traditional Chinese medicine(TCM), especially liver injury related to traditional non-toxic TCM, which requires adequate attention. Liver injury related to traditional non-toxic TCM is characterized by its sporadic and insidious nature and is influenced by various factors, making its detection and identification challenging. There is an urgent need to develop a strategy and method for early detection and recognition of traditional non-toxic TCM-related liver injury. This study was based on national adverse drug reaction monitoring center big data, integrating methodologies such as reporting odds ratio(ROR), network toxicology, and computational chemistry, so as to systematically research the risk signal identification and evaluation methods for TCM-related liver injury. The optimized ROR method was used to discover potential TCM with a risk of liver injury, and network toxicology and computational chemistry were used to identify potentially high-risk TCM. Additionally, typical clinical cases were analyzed for confirmation. An integrated strategy of "discovery via big data, identification via dry/wet method, confirmation via typical cases, and precise risk prevention and control" was developed to identify the risk of TCM-related liver injury. Corydalis Rhizoma was identified as a TCM with high risk, and its toxicity-related substances and potential toxicity mechanisms were analyzed. The results revealed that liver injury is associated with components such as tetrahydropalmatine and tetrahydroberberine, with potential mechanisms related to immune-inflammatory pathways such as the tumor necrosis factor signaling pathway, interleukin-17 signaling pathway, and Th17 cell differentiation. This paper innovatively integrated real-world evidence and computational toxicology methods, offering insights and technical support for establishing a risk discovery and identification strategy for TCM-related liver injury based on real-world big data, providing innovative ideas and strategies for guiding the safe and rational use of medication in clinical practices.
Corydalis/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Humans ; Chemical and Drug Induced Liver Injury/etiology* ; Medicine, Chinese Traditional/adverse effects* ; Rhizome/adverse effects* ; Male ; Female