ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

Objective: To evaluate the efficacy of a short video based health education model in enhancing e-cigarette awareness among junior high school students, so as to provide empirical evidence for optimizing school based health education in the digital era. Methods: In December 2024, a cluster sampling method was applied to recruit 465 eighth grade students from a middle school in Kunming for a survey. The intervention was implemented through playing short videos produced by the research team in the classroom, and a self designed adolescent e-cigarette questionnaire was used to conduct assessments before and after intervention, along with qualitative interviews with 60 teachers and students by purposive sampling. Pre and post intervention outcomes were compared by using paired t-test and Chi-square test. Qualitative data underwent a three stage coding process of "open, axial, and selective coding" to construct an explanatory framework. Results: Quantitative analysis showed significant post intervention increases in both baseline awareness scores（92.1±6.6）and deep awareness scores (70.0±17.6) compared with pre intervention( 78.2± 14.0，46.1±20.5)( t =23.54，26.72，both P <0.05), both meeting the criteria for large effect sizes (Cohen s d =1.09, 1.24). The improvement in deep awareness was particularly pronounced, specifically regarding addictive ingredients, illicit additives(tiletamine,metomidate,etomidate), and misconceptions about smoking cessation efficacy ( χ 2=150.54,113.27,117.40,112.92, 69.93 , all P <0.01). Qualitative insights revealed that narrative transportation and visual enhancement were the core mechanisms of efficacy: 87.3% of students preferred contextualized narratives, 85.5% of students decoded cognitive bottlenecks more effectively because of visual enhancement, and 72.7% relied on short videos for micro learning. Conclusion Short video based health education can effectively enhance e-cigarette awareness among junior high school students, offering a pragmatically viable digital pathway for school based health education.

Objective:To construct and validate a predictive model and application program for stone recurrence after endoscopic retrograde cholangiopancreatography (ERCP) based on machine learning algorithms in patients with common bile duct stones (CBDS).Methods:A multicenter retrospective cohort study was conducted, 862 CBDS patients underwent ERCP from June 2020 to September 2023 in Changshu First People′s Hospital (data set 1, 759 cases, including a training set of 588 cases and a validation set of 171 cases) and Changshu Hospital of Traditional Chinese Medicine (data set 2, 103 cases, used as a test set). The demographics, medical history, ERCP procedural records and laboratory indices were collected. All patients were followed up for 1 year, and the stone recurrence was recorded. In training set, the feature selection was conducted by the least absolute shrinkage and selection operator (LASSO) algorithm, and a conventional Logistic regression model was constructed based on selected features. The 3 machine learning algorithms (gradient boosting machine model, extreme gradient boosting model and random forest model) and a conventional Logistic regression model (LASSO model) were trained to fit predictive models. The model performance was assessed by area under curve (AUC) of receiver operating characteristic curve. The model interpretability was analyzed by feature importance evaluation, Shapley additive explanations (SHAP) and force plots. The best-performing model was deployed as an online application by Streamlit framework (V1.36.0).Results:Among the 862 patients, 158 patients (18.33%) developed stone recurrence after ERCP. There were no statistical difference in demographics, medical history, ERCP procedural records and laboratory indices between training set and a validation set ( P>0.05). LASSO regression analysis result showed that 6 key variables (in descending order of significance: endoscopic sphincterotomy, common bile duct angulation, stone diameter, stone count, common bile duct diameter, and periampullary diverticulum) influencing stone recurrence. ROC curve analysis result showed that the random forest model exhibited the highest predictive performance (it had the largest AUC of 0.900). SHAP analysis result showed that common bile duct angulation, common bile duct diameter, stone diameter, endoscopic sphincterotomy and stone count were the top 5 contributing factors in the random forest model. Using Python, the random forest model was implemented into a Streamlit-based application with a user-friendly visual interface, providing predictive outcomes, confidence levels, SHAP force diagram and health recommendations. In the test set, the application program achieved an accuracy of 84.5% (87/103), sensitivity of 82.6% (19/23), and specificity of 85.0% (68/80). SHAP plots and force diagram intuitively illustrated the impact of key features on stone recurrence prediction, offering a clear visualization of each variable′s role within the model. Conclusions:The predictive model and application program based on the random forest machine learning algorithms demonstrate excellent predictive performance and practical usability in predicting stone recurrence after ERCP in patients with CBDS.

Objective:To determine the levels of interleukin-2 (IL-22) and interleukin-26 (IL-26) in pleural effusion and serum in patients with tuberculous pleurisy, and analyze the diagnostic value of their combination for tuberculous pleurisy.Methods:From January 2016 to December 2023, 310 patients with tuberculous pleurisy admitted to Xi′an Hi-tech Hospital were included as the study group, and another 310 patients with non tuberculous pleurisy were regarded as the control group. The pleural effusion and serum samples of hospitalized patients were collected. Serum samples were collected from patients at 2 months after treatment for testing of IL-22 and IL-26 levels. The diagnostic value and correlation of IL-22 and IL-26 levels in pleural effusion and serum were analyzed.Results:Compared with the control group, the levels of pleural effusion and serum IL-26 and IL-22 in the study group were increased: (84.68 ± 12.17) ng/L vs. (69.33 ± 9.82) ng/L, (82.45 ± 11.75) ng/L vs. (39.53 ± 5.66) ng/L and (74.38 ± 10.57) ng/L vs. (53.32 ± 7.54) ng/L, (21.45 ± 3.14) ng/L vs. (14.45 ± 2.05) ng/L, and the differences were statistically significant ( P<0.01). Compared with before treatment, serum IL-26 and IL-22 levels decreased after treatment: (61.66 ± 8.72) ng/L vs. (74.38 ± 10.57) ng/L, (17.38 ± 2.59) ng/L vs. (21.45 ± 3.14) ng/L, and the difference was statistically significant ( P<0.01). The AUC of IL-26 and IL-22 in pleural effusion and serum samples in the diagnosis of tuberculous pleurisy was 0.895, 0.820, 0.929 and 0.893, respectively. The AUC of IL-26 and IL-22 combined detection in pleural effusion and serum samples in the diagnosis of tuberculous pleurisy was 0.964 and 0.970, respectively. Pleural effusion IL-26 was positively correlated with serum IL-26 ( r = 0.733, P<0.01) and positively correlated with pleural effusion IL-22 ( r = 0.544, P<0.01); pleural effusion IL-22 was positively correlated with serum IL-22 ( r = 0.532, P<0.01); serum IL-22 was positively correlated with serum IL-26 ( r = 0.619, P<0.01). Conclusions:The levels of IL-22 and IL-26 in pleural effusion and serum of patients with tuberculous pleurisy are elevated, and the two may jointly participate in the immune regulation of tuberculous pleurisy. It can be used as one of the biochemical diagnostic methods for patients with tuberculous pleurisy.

Objective:To investigate the feasibility of ultra-low dose (ULD) CT pulmonary angiography (CTPA) combined with deep learning reconstruction (DLR) in the diagnosis of pulmonary embolism (PE).Methods:This cross-sectional study prospectively enrolled 100 patients with suspected PE who underwent CTPA examination in Zhongshan Hospital Fudan University, and Shanghai Geriatric Medical Center from April to July 2024, and were randomly divided into the routine dose (RD) group and ULD group according to block randomization. Effective dose (ED) were calculated. The noise index of RD group and ULD group was set to 10 and 20, respectively. Other scanning parameters and contrast agent injection protocol were the same. The CT images of RD group were reconstructed using hybrid iterative reconstruction (HIR), while ULD images were reconstructed with HIR and DLR (ULD-HIR subgroup and ULD-DLR subgroup). The image quality of the three groups of images was subjectively evaluated (overall image noise, pulmonary artery display) and objectively evaluated [signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) of the images] respectively. Finally, the diagnostic results of PE by the expert committee composed of three chief physicians were taken as the gold standard, and one physician with lower qualifications independently evaluated the diagnostic rate of PE in the three groups of images. Objective image quality parameters across the three groups were compared using ANOVA, with LSD post hoc test was used for multiple comparisons. Subjective scores among the three groups were analyzed using the Kruskal-Wallis H test, with Bonferroni corrected pairwise post hoc test was applied for multiple pairwise comparisons. Results:The ED in the RD group and ULD group were (2.7±0.5) mSv and (0.7±0.2) mSv, respectively, and the differences were statistically significant ( t=26.42, P<0.001). The overall differences in CT values of pulmonary arteries at all levels in the images of the RD group, the ULD-HIR subgroup, and the ULD-DLR subgroup were not statistically significant ( P>0.05).The RD group, ULD-HIR subgroup and ULD-DLR subgroup overall differences in SNR and CNR at all levels pulmonary arteries were statistically significant ( P<0.001), in which except for the differences in CNR and SNR values of the left pulmonary arterial trunk in the RD group and the ULD-HIR subgroup, and SNR values of basal segment pulmonary artery of the lower lobe of the left lung, which were not statistically significant ( P>0.05), the differences of the rest of the indexes in the pairwise comparisons between the groups were statistically significant ( P<0.05). The overall differences in the subjective scores of image pulmonary vascular display and image noise in the RD group, ULD-HIR subgroup and ULD-DLR subgroup were statistically significant ( P<0.001), except that the differences in the subjective scores of image pulmonary vascular display in the ULD-DLR subgroup were not statistically significant when compared with that of the RD group ( P>0.05) and that of the rest of the metrics in the between-groups two-by-two comparisons were all statistically significant ( P<0.05). The difference in diagnostic rates of PE in the pulmonary artery trunk, lobe and segmental levels in the images of the RD group, ULD-HIR subgroup and ULD-DLR subgroup was not statistically significant ( P>0.05). Conclusions:DLR can significantly reduce the radiation dose of CTPA examination. Even at ultra-low radiation dose, its image quality is still better than HIR reconstruction at conventional doses and preserve diagnostic accuracy of PE at the lobe level and segment level.

Objective:To evaluate alterations in dopaminergic neurons, cortical metabolism, and functional connectivity networks in patients with early-onset Parkinson′s disease (EOPD) using multimodal neuroimaging.Methods:In this prospective cross-sectional study, 26 patients with EOPD and 16 healthy controls (HC group) were recruited from the PLA General Hospital between April and November 2023. All participants underwent integrated 11C-β-CFT PET/MR, 18F-FDG PET/CT brain imaging and resting-state functional MRI. Clinical assessments were conducted using the Unified Parkinson′s Disease Rating Scale and Hoehn-Yahr staging. Cognitive status was evaluated using the Mini-Mental State Examination and Montreal Cognitive Assessment. Standardized uptake value ratios for both 11C-β-CFT and 18F-FDG PET images were calculated using cerebellar gray matter as the reference region. Voxel-wise two-sample t-tests were performed to identify regions with significant group differences in tracer uptake. Seed regions showing altered 11C-β-CFT or 18F-FDG uptake were used to compute seed-based functional connectivity (FC) with all other brain voxels, and group differences in FC were assessed. Correlations between imaging metrics and clinical scales were evaluated using Pearson or Spearman analyses as appropriate. Results:Compared with HC group, EOPD group showed significantly reduced 11C-β-CFT uptake in the bilateral putamen, globus pallidus, and left temporal pole ( P<0.05), and decreased 18F-FDG uptake in the right superior frontal gyrus and anterior cingulate cortex ( P<0.05). Relative to HC group, EOPD group exhibited markedly lower FC between the right putamen and the left gyrus rectus as well as the right parahippocampal gyrus; the right superior frontal gyrus and the left gyrus rectus; the anterior cingulate cortex and the olfactory area of the frontal lobe, the left gyrus rectus, and the right superior parietal gyrus; the left temporal pole and the left orbitofrontal cortex as well as the left olfactory area ( P<0.05). Correlation analyses revealed no statistically significant associations between altered FC values and clinical scale scores in the EOPD group. Conclusions:Patients with EOPD demonstrate impaired nigrostriatal dopaminergic function, regional cortical hypometabolism, and aberrant functional connectivity across multiple brain networks.

Objective To explore the mediating effect of empowerment ability between type D personality and self-management behavior of patients with diabetes mellitus(DM).Methods A total of 738 patients with type 2 diabetes mellitus(T2DM)hospitalized in the Department of Endocrinology of three tertiary hospitals in Hainan Province from December 2022 to May 2023 were selected and divided into Type D personality(Type D,n=104)group and T2DM group(n=634).The general data,biochemical indexes,scores of negative emotion(NA),social inhibition(SI),empowerment ability,and scale of DM self-management activities(SDSCA)were compared between the two groups,and the correlation between type D personality,empowerment ability and self-management ability was analyzed.The mediating effect model was used to analyze the mediating effect of empowerment ability on the four self-management behaviors of patients with type D personality,and the chain mediating effect model was used to analyze the relationship between type D personality,empowerment ability,self-management behaviors and HbA1c.Results Compared with the T2DM group,HbA1c,proportion of rural residence,proportion of complications≥3,proportion of education level of junior high school or above,proportion of monthly income<3000 yuan,and NA and SI scores were significantly higher in the Type D group(P<0.05).The empowerment ability and scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance were lower in the Type D group than in the T2DM group(P<0.05).Spearman correlation analysis showed that the empowerment ability score was positively correlated with the scores of healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).NA and SI scores were negatively correlated with empowerment ability score,healthy diet,regular exercise,blood glucose monitoring and medication compliance(P<0.05).The results of model analysis with empowerment ability as the mediating variable showed that type D personality had direct,indirect and total effects on regular exercise,blood glucose monitoring,medication compliance and SDSCA total score(P<0.05),and indirect and total effects on regular diet score(P<0.05).The mediating effect of empowerment ability was significant(Bootstrap CI did not include 0).The chain mediating effect analysis showed that type D personality could indirectly affect HbA1c through empowerment ability,healthy diet(γ=0.389,95%CI 0.206～0.591),and medication compliance(γ=0.149,95%CI 0.040～0.265),and the effect proportion was 39.4%and 14.1%,respectively.Conclusions Type D personality can indirectly influence self-management behavior through the mediating effect of empowerment,and simultaneously affecting HbA1c through the chain effect of empowerment,diet,and medication behavior.

This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

Objective To construct YOLOv10 based artificial intelligence(AI)models for the automatic detection in small bowel capsule endoscopy(SBCE)images.Methods SBCE data from two centers was collected,including 23 115 images and 35 412 annotated labels covering 11 categories of small bowel lesions.The images were annotated using the LabelMe tool and converted into the YOLO format required for deep learning model development.The pre-trained YOLOv10 and YOLOv8 models were used for transfer learning training on the constructed dataset.Model performance was comprehensively evaluated using metrics such as precision,accuracy,sensitivity,specificity,false-positive rate,and detection speed.Finally,the models were deployed on local computers for real-time detection of SBCE images and videos.Results Six different versions of YOLO object detection models were developed,namely YOLOv8n,YOLOv8s,YOLOv8m,YOLOv10n,YOLOv10s,and YOLOv10m.On the validation set,YOLOv10s model achieved the best mAP50(0.795);although its inference latency was not the fastest(4.803 ms/img),it met the requirements for clinical application.On the test set,YOLOv10s performed well,with an accuracy of 92.69%,a sensitivity of 89.23%,and a false-positive rate of 4.78%.Especially,in category-specific inference,the highest sensitivity was for"bleeding"at 96.41%,while the lowest was for"narrowing"at 82.29%.Conclusion The model constructed based on YOLOv10 neural network can rapidly and accurately detect and classify various small bowel lesions,exhibiting significant clinical application potential.