Objective:To analyze the implementation and effectiveness of standardized training for medical aesthetic practitioners in Guangdong province from 2015 to 2023.Methods:Training data from 2015 to 2023 were retrospectively collected from programs organized by the Guangdong Medical Association, including sessions in aesthetic surgery, dermatology, dentistry, traditional Chinese medicine, laser aesthetics, and injectable aesthetics. The training implementation was summarized. A random sample of 120 trainees was selected to complete a questionnaire to assess training outcomes.Results:A total of 45 offline standardized training sessions were held, covering both theoretical and practical instruction. The total training duration reached 180 days, involving 6 776 participant attendances. Aesthetic surgery accounted for the highest number (1 701 attendances), followed by aesthetic dermatology (1 197 attendances). Among specialized technical programs, laser aesthetics (1 708 attendances) and injectable aesthetics (1 578 attendances) had the most participants. Most trainees (5 705 attendances) were physicians from tertiary public general hospitals. A total of 116 questionnaires were collected, with 115 participants expressing satisfaction with the course content, teaching arrangement, and training materials. All trainees passed the skills assessment and received training certificates.Conclusions:The standardized training for medical aesthetic practitioners in Guangdong province from 2015 to 2023 has been well implemented and shows favorable outcomes. It contributes to improving the technical competence of professionals in the medical aesthetics field.

Objective:To systematically analyze the registration status of clinical trials related to inflammatory bowel disease (IBD) in China Clinical Trial Registry (ChiCTR); To focus on the characteristics and shortcomings of TCM research; To provide data support and theoretical basis for optimizing clinical trial design and improving the quality of TCM research.Methods:The IBD-related clinical trials registered by ChiCTR from the establishment of the database to September 18, 2024 were retrieved. SPSS 26.0 software was used to analyze the frequency of research objects, registration time, registration area and institution, source of funds, research type and design scheme, random method and blind method, trial staging and research center, sample size, intervention measures and outcome indicators.Results:There were 317 clinical trials of IBD. Shanghai, Jiangsu, Beijing, Guangdong and Zhejiang accounted for 72.87% of the total number of registrations. Most of the registered projects were intervention studies (51.42%), 48 studies used blind method, and randomized controlled study was the main research design type. In the 68 clinical trials related to TCM, the intervention measures were divided into 4 categories, of which Chinese materia medica was the most (42 items); the sample size was the most in the intervention study, with a total of 6 787 cases; the total frequency of outcome indicators was 1 866 times, and the quality of life and mental health were the most (147 items).Conclusions:The number of registered IBD clinical trials is generally increasing, but there may be problems such as uneven distribution of regions and institutions, poor design of sample size, blind method and other research, and non-standard filling of registration information. In the research of TCM treatment of IBD, it is suggested to further strengthen the depth and breadth, especially the characteristic therapy of TCM.

Objective To explore the mechanism of Lacticaseibacillus paracasei E6 for improving vinorelbine-induced immunosuppression in zebrafish.Methods The intestinal colonization of L.paracasei E6 labeled by fluorescein isothiocyanate(FITC)in zebrafish was observed under fluorescence microscope.In a zebrafish model of vinorelbine-induced immunosuppression,the immunomodulatory activity of L.paracasei E6 was assessed by analyzing macrophage and neutrophil counts in the caudal hematopoietic tissue(CHT),the number of T-lymphocyte,and the expressions of interleukin-12(IL-12)and interferon-γ(IFN-γ).The contents of short-chain fatty acids(SCFAs)in L.paracasei E6 fermentation supernatant and the metabolites of L.paracasei E6 in zebrafish were detected by LC-MS/MS-based targeted metabolomics.The immunomodulatory effects of the SCFAs including sodium acetate,sodium propionate and sodium butyrate were evaluated in the zebrafish model of immunosuppression.Results After inoculation,green fluorescence of FITC-labeled L.paracasei E6 was clearly observed in the intestinal ball,midgut and posterior gut regions of zebrafish.In the immunocompromised zebrafish model,L.paracasei E6 significantly alleviated the reduction of macrophage and neutrophil counts in the CHT,increased the fluorescence intensity of T-lymphocytes,and promoted the expressions of IL-12 and IFN-γ.Compared with MRS medium,L.paracasei E6 fermentation supernatant showed significantly higher levels of acetic acid,propionic acid and butyric acid,which were also detected in immunocompromised zebrafish following treatment with L.paracasei E6.Treatment of the zebrafish model with sodium acetate and sodium propionate significantly increased macrophage and neutrophil counts in the CHT and effectively inhibited vinorelbine-induced reduction of thymus T cells.Conclusion L.paracasei E6 can improve vinorelbine-induced immunosuppression in zebrafish through its SCFA metabolites acetic acid and propionic acid.

OBJECTIVES: To explore the mechanism of Lacticaseibacillus paracasei E6 for improving vinorelbine-induced immunosuppression in zebrafish. METHODS: The intestinal colonization of L. paracasei E6 labeled by fluorescein isothiocyanate (FITC) in zebrafish was observed under fluorescence microscope. In a zebrafish model of vinorelbine-induced immunosuppression, the immunomodulatory activity of L. paracasei E6 was assessed by analyzing macrophage and neutrophil counts in the caudal hematopoietic tissue (CHT), the number of T-lymphocyte, and the expressions of interleukin-12 (IL-12) and interferon-γ (IFN-γ). The contents of short-chain fatty acids (SCFAs) in L. paracasei E6 fermentation supernatant and the metabolites of L. paracasei E6 in zebrafish were detected by LC-MS/MS-based targeted metabolomics. The immunomodulatory effects of the SCFAs including sodium acetate, sodium propionate and sodium butyrate were evaluated in the zebrafish model of immunosuppression. RESULTS: After inoculation, green fluorescence of FITC-labeled L. paracasei E6 was clearly observed in the intestinal ball, midgut and posterior gut regions of zebrafish. In the immunocompromised zebrafish model, L. paracasei E6 significantly alleviated the reduction of macrophage and neutrophil counts in the CHT, increased the fluorescence intensity of T-lymphocytes, and promoted the expressions of IL-12 and IFN-γ. Compared with MRS medium, L. paracasei E6 fermentation supernatant showed significantly higher levels of acetic acid, propionic acid and butyric acid, which were also detected in immunocompromised zebrafish following treatment with L. paracasei E6. Treatment of the zebrafish model with sodium acetate and sodium propionate significantly increased macrophage and neutrophil counts in the CHT and effectively inhibited vinorelbine-induced reduction of thymus T cells. CONCLUSIONS L. paracasei E6 can improve vinorelbine-induced immunosuppression in zebrafish through its SCFA metabolites acetic acid and propionic acid.
Animals ; Zebrafish/immunology* ; Acetic Acid/metabolism* ; Propionates/metabolism* ; Fatty Acids, Volatile/metabolism*

OBJECTIVE: Paridis Rhizoma (Chonglou in Chinese), a traditional Chinese herbal medicine, has been shown have strong anti-tumor effects. Paris saponin VII (PSVII), an active constituent isolated from Paridis Rhizoma, was demonstrated to significantly suppress the proliferation of BxPC-3 cells in our previous study. Here, we aimed to elucidate the anti-pancreatic ductal adenocarcinoma (PDAC) effect of PSVII and the underlying mechanism. METHODS: Cell viability was determined by CCK-8, colony formation, and cell migration assays. Cell apoptosis and reactive oxygen species (ROS) production were measured by flow cytometry with annexin V/propidine iodide (Annexin V/PI) and 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA), respectively. Pyroptosis was evaluated by morphological features, Hoechst 33342/PI staining assay, and release of lactate dehydrogenase (LDH). JC-1 fluorescent dye was employed to measure mitochondrial membrane potential. Western blotting and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) were used to determine the levels of proteins or mRNAs. The effect in vivo was assessed by a xenograft tumor model. RESULTS: PSVII inhibited the viability of PDAC cells (BxPC-3, PANC-1, and Capan-2 cells) and induced gasdermin E (GSDME) cleavage, as well as the simultaneous cleavage of Caspase-3 and poly (ADP-ribose) polymerase 1 (PARP). Knockdown of GSDME shifted PSVII-induced pyroptosis to apoptosis. Additionally, the effect of PSVII was significantly attenuated by Z-Asp(OMe)-Glu(OMe)-Val-Asp(OMe)-fluoromethylketone (Z-DEVD-FMK), on the induction of GSDME-dependent pyroptosis. PSVII also elevated intracellular ROS accumulation and stimulated Bax and Caspase-3/GSDME to conduct pyroptosis in PDAC cells. The ROS scavenger N-acetyl cysteine (NAC) suppressed the release of LDH and inhibited Caspase-9, Caspase-3, and GSDME cleavage in PDAC cells, ultimately reversing PSVII-induced pyroptosis. Furthermore, in a xenograft tumor model, PSVII markedly suppressed the growth of PDAC tumors and induced pyroptosis. CONCLUSION These results demonstrated that PSVII exerts therapeutic effects through Caspase-3/GSDME-dependent pyroptosis and may constitute a novel strategy for preventing chemotherapeutic resistance in patients with PDAC in the future.

Objective To develop an endothelialized microfluidic chip model that simulates the spatial architecture and bioactivity of retinal vasculature,enabling thrombosis modeling and thrombolytic efficacy validation.Methods A tri-level microvascular network chip(300/200/100 μm diameters)with bifurcated architecture was fabricated using soft lithography.Human retinal microvascular endothelial cells(HRMECs)were perfused into channels,with endothelial coverage monitored via phase-contrast microscopy and F-actin staining.Cellular bioactivity was assessed using mitochondrial membrane potential probes(5,5,6,6-Tetrachloro-1,1,3,3-tetraethylbenzimidazolylcarbocyanine iodide,JC-1)and nitric oxide(NO)quantification.Fresh blood samples from 10 healthy donors(Yongchuan Hospital Affiliated to Chongqing Medical University,March to June 2024)were perfused with digital injection pump to mimic blood flow in human body into 3 experimental groups:normal whole blood,and TNF-α-activated endothelium+normal blood,TNF-α-activated endothelium+TNF-α-treated blood.Three inlet blood flow rates of 37.8、11.1 and 3.5 μL/min were set in each group.Two experimental groups,normal saline and recombinant human tissue-type plasminogen activator(rtPA),were established using the endothelialized microfluidic thrombosis model to validate thrombolytic efficacy.Endothelial functional impacts were assessed through integrated DAPI/NO staining and thrombosis model analysis across 3 intervention phases:pre-thrombosis,post-thrombosis,and post-thrombolysis.Results A tri-level microfluidic vascular model(300/200/100 μm diameters)was successfully constructed.In 72 h after endothelial cell perfusion,complete channel coverage was achieved,with phase-contrast microscopy and F-actin staining confirming confluent cellular alignment.JC-1/NO assays validated preserved endothelial bioactivity.Compared with the whole blood group,both TNF-α-activated endothelium+normal blood and TNF-α-activated endothelium+TNF-α-treated blood groups exhibited significantly increased thrombus occupancy rates at identical flow rates(all P<0.001).Notably,TNF-α-activated endothelium+TNF-α-treated blood group demonstrated the highest thrombus ratio at 3.5 μL/min(P<0.001).The rtPA group showed superior thrombolytic efficacy versus saline(P<0.001).Endothelial monolayer integrity was maintained across intervention phases,with thrombosis triggering significant NO elevation(P<0.001).Conclusion Our retinal vasculature-mimetic microfluidic model enables precise thrombosis modeling and drug evaluation,providing new methodology for studying retinal vascular occlusive diseases.

Objective:This study aims to develop a laboratory-based predictive model for early neurological deterioration (END) in patients with acute cerebral infarction (ACI) using baseline data collected at hospital admission.Methods:This study was a retrospective cohort study. Clinical and baseline laboratory test data from 502 patients with ACI admitted to the Department of Neurology at our hospital between January 1, 2022 and May 31, 2025. Of these patients, 313 were male and 189 were female, with a median age of 67 years (interquartile range: 58-73). Patients were classified into an END group and a non-END group according to the occurrence of END within 7 days of admission. Subsequently, using the caret package in R (version 4.4.2), the dataset was randomly divided into a training set ( n=351) and a validation set ( n=151) at a 7∶3 ratio, with END status as the stratification variable and a fixed random seed to ensure reproducibility. Following baseline characteristic comparisons between groups, these datasets were used for model development and validation, respectively. The differences in clinical indicators between the two patients groups were assessed using the chi-square test and the Wilcoxon rank sum test. In the training group, Lasso regression was utilized to identify variables significantly associated with END. Seven machine learning algorithms-decision tree (DT), random forest (RF), light gradient boosting machine (LGBM), extreme gradient boosting (XGB), K-nearest neighbors (KNN), support vector machine (SVM), and logistic regression (LR)-were employed to develop predictive models. The optimal hyperparameters were determined via grid search integrated with 5-fold cross-validation. The final algorithm was selected based on comprehensive model performance evaluation. Additionally, clinical data of 79 patients with ACI, collected between June 1 to August 31, 2025, were compiled as an independent test set for external validation. The cohort comprised 49 males and 30 females, with a median age of 68 years (interquartile range: 57-72). The SHapley Additive exPlanations (SHAP) method was employed to access feature importance and model interpretability. SHAP dependence plots and interaction plots were utilized to emplore the nonlinear relationships and interaction effects among the featurevariables. Results:Among the 502 patients, 166 experienced END during 7 days of hospitalization. Lasso regression identified nine significant predictors: history of hyperlipidemia, admission NIHSS score, lymphocyte-to-monocyte ratio (LMR), hemoglobin, D-dimer, albumin, neuron-specific enolase (NSE), homocysteine (HCY), and vitamin B12. The area under the receiver operating characteristic curve (AUC) for the seven machine learning models ranged from 0.709 to 0.946. The XGB model achieved the highest predictive performance, with an AUC of 0.946 (95% CI 0.924-0.960) in the training cohort and 0.867 (95% CI 0.902-0.933) in the validation cohort. SHAP analysis revealed that the top five variables contributing to END prediction were admission NIHSS score, HCY, D-dimer, history of hyperlipidemia, and vitamin B12. Conclusion:This study successfully developed a laboratory-based prediction model for END using the XGB machine learning algorithm, which demonstrated strong predictive performance.

Objective:To explore the implementation and effectiveness evaluation of an online-offline blended teaching method based on Outcome-Based Education(OBE)concept in integrated curriculum.Methods:A total of 28 students from Class 1 of the grade 2017 Information Management program,who underwent the traditional classroom teaching method before the reform of the Basic Medical Concepts course,were selected as the control group.Their evaluation was based on final exam scores(70%)and experimental scores(30%).In contrast,29 students from Class 1 of the grade 2019 Information Management program,who experienced the OBE teaching concept combined with online-offline blended teaching after the reform,were selected as the experimental group.Their evaluation included final exam scores(60%),experimental scores(20%),regular performance(10%),and online course performance(10%).The total scores,excellence rates,and course satisfaction were compared between the two groups.Result:The experimental group showed higher total scores,excellence rates,and course satisfaction compared to the control group(P＜0.01).Conclusion:In the teaching of integrated curriculum,optimizing and integrating online resources and offline classroom teaching based on the OBE concept,reforming the teaching evaluation method,and forming a scientific and reasonable comprehensive evaluation system are important ways and measures to achieve better teaching results in blended teaching.

Objective:To explore the implementation and effectiveness evaluation of an online-offline blended teaching method based on Outcome-Based Education(OBE)concept in integrated curriculum.Methods:A total of 28 students from Class 1 of the grade 2017 Information Management program,who underwent the traditional classroom teaching method before the reform of the Basic Medical Concepts course,were selected as the control group.Their evaluation was based on final exam scores(70%)and experimental scores(30%).In contrast,29 students from Class 1 of the grade 2019 Information Management program,who experienced the OBE teaching concept combined with online-offline blended teaching after the reform,were selected as the experimental group.Their evaluation included final exam scores(60%),experimental scores(20%),regular performance(10%),and online course performance(10%).The total scores,excellence rates,and course satisfaction were compared between the two groups.Result:The experimental group showed higher total scores,excellence rates,and course satisfaction compared to the control group(P＜0.01).Conclusion:In the teaching of integrated curriculum,optimizing and integrating online resources and offline classroom teaching based on the OBE concept,reforming the teaching evaluation method,and forming a scientific and reasonable comprehensive evaluation system are important ways and measures to achieve better teaching results in blended teaching.

Objective:This study aims to develop a laboratory-based predictive model for early neurological deterioration (END) in patients with acute cerebral infarction (ACI) using baseline data collected at hospital admission.Methods:This study was a retrospective cohort study. Clinical and baseline laboratory test data from 502 patients with ACI admitted to the Department of Neurology at our hospital between January 1, 2022 and May 31, 2025. Of these patients, 313 were male and 189 were female, with a median age of 67 years (interquartile range: 58-73). Patients were classified into an END group and a non-END group according to the occurrence of END within 7 days of admission. Subsequently, using the caret package in R (version 4.4.2), the dataset was randomly divided into a training set ( n=351) and a validation set ( n=151) at a 7∶3 ratio, with END status as the stratification variable and a fixed random seed to ensure reproducibility. Following baseline characteristic comparisons between groups, these datasets were used for model development and validation, respectively. The differences in clinical indicators between the two patients groups were assessed using the chi-square test and the Wilcoxon rank sum test. In the training group, Lasso regression was utilized to identify variables significantly associated with END. Seven machine learning algorithms-decision tree (DT), random forest (RF), light gradient boosting machine (LGBM), extreme gradient boosting (XGB), K-nearest neighbors (KNN), support vector machine (SVM), and logistic regression (LR)-were employed to develop predictive models. The optimal hyperparameters were determined via grid search integrated with 5-fold cross-validation. The final algorithm was selected based on comprehensive model performance evaluation. Additionally, clinical data of 79 patients with ACI, collected between June 1 to August 31, 2025, were compiled as an independent test set for external validation. The cohort comprised 49 males and 30 females, with a median age of 68 years (interquartile range: 57-72). The SHapley Additive exPlanations (SHAP) method was employed to access feature importance and model interpretability. SHAP dependence plots and interaction plots were utilized to emplore the nonlinear relationships and interaction effects among the featurevariables. Results:Among the 502 patients, 166 experienced END during 7 days of hospitalization. Lasso regression identified nine significant predictors: history of hyperlipidemia, admission NIHSS score, lymphocyte-to-monocyte ratio (LMR), hemoglobin, D-dimer, albumin, neuron-specific enolase (NSE), homocysteine (HCY), and vitamin B12. The area under the receiver operating characteristic curve (AUC) for the seven machine learning models ranged from 0.709 to 0.946. The XGB model achieved the highest predictive performance, with an AUC of 0.946 (95% CI 0.924-0.960) in the training cohort and 0.867 (95% CI 0.902-0.933) in the validation cohort. SHAP analysis revealed that the top five variables contributing to END prediction were admission NIHSS score, HCY, D-dimer, history of hyperlipidemia, and vitamin B12. Conclusion:This study successfully developed a laboratory-based prediction model for END using the XGB machine learning algorithm, which demonstrated strong predictive performance.