As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective To analyze the correlation of cholecystectomy and changes in intestinal microbiota composition and function by observing functional characteristics of differential microbial communities.Methods A cross-sectional study was conducted on the patients(PC group,n=73)undergoing cholecystectomy in our hospital from 2020 to 2021.Another 56 healthy age-and gender-matched individuals(HC group)without a history of cholecystectomy were subjected and served as the control group.Fecal specimens were collected from the 2 groups.16S rRNA sequencing analysis was performed to examine the changes in composition and function of intestinal microbiota.Results There were no statistical differences between the 2 groups in baseline indicators,such as gender,age,BMI,smoking and drinking history,blood pressure,heart rate,and comorbidities,but significant difference was observed in total bilirubin(TBIL)between them(P<0.01).Alpha diversity analysis showed no significant difference in Chao1,Shannon,and Simpson indices between the 2 groups.Beta diversity analysis using the Bray-Curtis distance algorithm revealed a significant difference between the 2 groups at the class and genus levels(P<0.05).The analysis of microbiota relative abundance using LEFSE showed that Enterobacteriaceae,Lactobacillales,Citrobacter,Megasphaera,Lactobacillus,Enterococcus,Akkermansia,Streptococcus,Klebsiella,and Ruminococcus_gnavus were up-regulated in the PC group,and Lachnospiraceae,Sutterellaceae,Lachnospirales,Lachnospira,and Sutterella were down-regulated.Kyoto Encyclopedia of Genes and Genomes(KEGG)functional prediction analysis indicated that significant differences were seen between the 2 groups in metabolic pathways,including ascorbic acid(vitamin C)metabolism and aldonic acid metabolism(P<0.05),tricarboxylic acid cycle(TCA cycle)(P<0.05),glutathione metabolism(P<0.05),glutamic acid metabolism(P<0.05),secondary bile acid metabolism(P<0.05),and pentose phosphate pathway(P<0.01).Conclusion Cholecystectomy is closely associated with the structural alterations in the composition of intestinal microbiota.Variations in microbiota composition and function may induce perturbations in TCA cycle and glutathione metabolism,glutamate metabolism,secondary bile acid metabolism,and pentose phosphate pathways.

Objective To investigate the diversity and composition of gut fungi microbiota in patients with polycystic kidney disease(PKD)and its correlation with clinical indicators.Methods A total of 44 PKD patients,44 patients with non-polycystic chronic kidney disease(NPCKD)and 22 healthy controls(HC)admitted to our hospital from February 2023 to February 2024 were recruited.ITS1 DNA sequencing was applied to analyze the gut fungal composition.Bioinformatics analysis was used to compare the diversity and structural differences of fungi among the 3 groups.Pearson correlation analysis was performed to analyze the relationship between gut fungi and clinical indicators.Results There were no significant differences in baseline characteristics(gender,age,body mass index,etc.)among the 3 groups,but statistical differences were seen in terms of serum indicators(such as serum creatinine,blood urea nitrogen,uric acid,estimated glomerular filtration rate,etc.)(P<0.01).Alpha diversity analysis showed no significant difference was seen between the PKD and HC groups,but the PKD group had significant differences to the NPCKD group(P<0.01).Beta diversity analysis revealed significant differences among the 3 groups and in pairwise comparisons(P=0.001).Fungi composition analysis found that the abundance of Candida was significantly higher in the PKD group than the other 2 groups(P<0.01),while the abundances of Aspergillus and Cladosporium were significantly lower in the PKD group than the HC group(P<0.05).Linear discriminant analysis(LEFSe)indicated that Candida was significantly enriched,while Aspergillus and Cladosporium were significantly reduced in the PKD group.Correlation analysis revealed that the abundance of Cladosporium was negatively correlated with cyst diameter and immunoglobulin light chain Kappa/Lambda ratio in the PKD group(P<0.05),while the abundance of Candida was positively correlated with liver/kidney cyst diameter(P<0.01).Conclusion PKD patients exhibit characteristic changes in gut fungi diversity and composition.The abundances of Cladosporium and Candida are closely associated with clinical indicators of PKD patients.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

To elucidate the mechanism by which steaming affects the quality of Curcuma kwangsiensis root tubers, methods such as LSCM, RVA, dual-wavelength spectrophotometry, LF-NMR, and LC-MS were employed to qualitatively and quantitatively detect changes in starch gelatinization characteristics, water distribution, and material composition of C. kwangsiensis root tubers under different steaming durations. Based on multivariate statistical analysis, the correlation between differences in gelatinization parameters, water distribution, and terpenoid material composition was investigated. The results indicate that steaming affects both starch gelatinization and water distribution in C. kwangsiensis. During the steaming process, transformations occur between amylose and amylopectin, as well as between semi-bound water and free water. After 60 min of steaming, starch gelatinization and water distribution reached an equilibrium state. The content of amylopectin, the amylose-to-amylopectin ratio, and parameters such as gelatinization temperature, viscosity, breakdown value, and setback value were significantly correlated(P≤0.05). Additionally, the amylose-to-amylopectin ratio was significantly correlated with total free water and total water content(P≤0.05). Steaming induced differences in the material composition of C. kwangsiensis root tubers. Clustering of primary metabolites in the OPLS-DA model was distinct, while secondary metabolites were classified into 9 clusters using the K-means clustering algorithm. Differential terpenoid metabolites such as(-)-α-curcumene were significantly correlated with zerumbone, retinal, and all-trans-retinoic acid(P<0.05). Curcumenol was significantly correlated with isoalantolactone and ursolic acid(P<0.05), while all-trans-retinoic acid was significantly correlated with both zerumbone and retinal(P<0.05). Alpha-tocotrienol exhibited a significant correlation with retinal and all-trans-retinoic acid(P<0.05). Amylose was extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and α-tocotrienol(P<0.05). Amylopectin was significantly correlated with zerumbone(P<0.05) and extremely significantly correlated with(-)-α-curcumene, curcumenol, zerumbone, retinal, all-trans-retinoic acid, and 9-cis-retinoic acid(P<0.01). The results provide scientific evidence for elucidating the mechanism of quality formation of steamed C. kwangsiensis root tubers as a medicinal material.
Curcuma/chemistry* ; Starch/chemistry* ; Multivariate Analysis ; Water/chemistry* ; Terpenes/analysis* ; Plant Roots/chemistry* ; Plant Tubers/chemistry* ; Drugs, Chinese Herbal/chemistry*

Hongsheng Dan, historically referred to as the "surgical sacred medicine", is at risk of losing its refining technology in contemporary times. This study aimed to preserve and innovate this traditional non-heritage refining technology. By utilizing the analytic hierarchy process(AHP) combined with the entropy weight method, this study established the hierarchical structure model of refining process of Hongsheng Dan and conducted a single factor experiment and an L_9(3~4) orthogonal experiment to optimize the refining method of Hongsheng Dan. Additionally, the study employed infrared thermal imaging to monitor temperature variations of Hongsheng Dan during the refining process. The optimized refining parameters for Hongsheng Dan were established as follows: a slow fire temperature of 175 ℃ with a duration of 30 minutes, a strong fire temperature of 270 ℃ with a duration of 60 minutes, and a tail fire temperature of 180 ℃ with a duration of 15 minutes. The stability and feasibility of this optimized process were confirmed through validation tests. The research focused on the material transformation of Hongsheng Dan, starting from the material changes during the refining process of Hongsheng Dan and the synthesis of mercuric oxide from nitric acid. The study investigated elemental transformations, physical phase changes, and alterations in thermal properties. 78.98% of the mercury in Hongsheng Dan and 80.21% of the mercury in mercuric oxide from nitric acid were retained. The diffraction peak intensity of the(011) crystal plane of Hongsheng Dan was highest at approximately 30.07°, indicating that the(011) crystal plane had a preferred crystalline orientation. Furthermore, the temperature range for the alteration in thermal properties during the refining process of Hongsheng Dan was found to be between 80 ℃ and 130 ℃. This research not only optimized the refining technology of Hongsheng Dan but also pioneered the application of infrared thermal imaging to study temperature changes throughout the refining process. By exploring the material transformation patterns of Hongsheng Dan and the synthesis of mercuric oxide from nitric acid, the study provided technical support for the preservation and innovation of Hongsheng Dan.
Drugs, Chinese Herbal/standards* ; Temperature

Objective Using female mice to investigate the reparative effects of human umbilical cord mesenchymal stem cells on radiation-induced ovarian injury. Methods Mice were randomly divided into three groups: a blank control group, a radiation model group, and a cell therapy group. Mice in the radiation model group and the cell therapy group received a single whole-body irradiation of 5 Gy X-rays. Within 2 hours post-irradiation, mice in the cell therapy group underwent ovarian transplantation of UC-MSCs. On days 1, 7, and 14 post-irradiation, body weight was measured, ovarian index was calculated, histopathological changes in ovarian tissue were examined, serum levels of reproductive hormones (follicle-stimulating hormone, anti-Müllerian hormone, and estradiol) were determined, and the colonization of implanted UC-MSCs in the mice was observed. Results On days 1, 7, and 14 post-irradiation, both the cell therapy group and the radiation model group showed decreased body weight compared to the blank control group (P < 0.05). On day 1 post-irradiation compared to day 1 pre-irradiation within the same group, the radiation model group exhibited a greater decrease in body weight than the cell therapy group (P < 0.05). On days 1, 7, and 14 post-irradiation, the ovarian index decreased in both the radiation model group and the cell therapy group compared to the blank control group (P < 0.05). On days 7 and 14 post-irradiation, the ovarian index in the cell therapy group was significantly higher than that in the radiation model group (P < 0.05). Ovarian tissue in the radiation model group exhibited atrophy and a reduction in the number of follicles at all stages. In contrast, follicles in the cell therapy group were large and abundant. On days 1, 7, and 14 post-irradiation, serum follicle-stimulating hormone levels in the cell therapy group were lower than those in the radiation model group, while anti-Müllerian hormone and estradiol levels were higher than those in the radiation model group (P < 0.01). In vivo fluorescence imaging demonstrated that UC-MSCs successfully colonized the ovarian tissue on days 1, 7, and 14 after transplantation. Conclusion UC-MSCs exert a repair effect on radiation-induced ovarian injury in mice.

Abstract In recent years, the prevalence of overweight and obesity among children and adolescents has risen rapidly, posing a serious threat to their physical and mental health. To provide scientific, systematic, and standardized weight management guidance for overweight and obese children and adolescents, the study focuses on the core concept of healthy lifestyle intervention, integrates multidisciplinary expert opinions and research findings,and proposes a comprehensive multidisciplinary intervention framework covering scientific exercise intervention, precise nutrition and diet, optimized sleep management, and standardized psychological support. It calls for the establishment of a multi agent collaborative management mechanism led by the government, implemented by families, fostered by schools, initiated by individuals, optimized by communities, reinforced by healthcare, and coordinated by multiple stakeholders. Emphasizing a child and adolescent centered approach, the consensus advocates for comprehensive, multi level, and personalized guidance strategies to promote the internalization and maintenance of a healthy lifestyle. It serves as a reference and provides recommendations for the effective prevention and control of overweight and obesity, and enhancing the health level of children and adolescents.