The application of immunosuppressants has significantly reduced the incidence rate of rejection reaction after liver transplantation， but the clinical efficacy of immunosuppressants is greatly affected by individual differences between patients. This article systematically reviews the recent research advances in the interaction between immunosuppressants and gut microbiota， with a focus on the regulatory role and mechanism of intestinal microflora communities on the efficacy of immunosuppressants. Studies have shown that intestinal microbiome is one of the key factors influencing the efficacy of immunosuppressive therapy after liver transplantation. This review aims to provide a theoretical basis for in-depth research in this field and provide new insights for developing individualized immunosuppressive treatment regimens based on the regulation of intestinal microflora.

BACKGROUND:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

BACKGROUND:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

Objective To construct a prediction model for the population with hypertension and diabetes to assess the risk of chronic kidney disease (CKD), and to provide a scientific basis for formulating targeted CKD prevention and control measures. Methods Based on physical examination data from community residents aged 60 years and above in Nanjing in 2022, 10 221 patients with hypertension and diabetes were selected as the study subjects. Variables associated with CKD prevalence were screened using univariate analysis, and further variable selection was performed using LASSO regression. Finally, a CKD risk prediction model was constructed based on logistic regression. The model's performance was evaluated using the ROC curve and calibration curve. Results The prevalence rate of CKD in the study population was 22.71%, with a mean age of 71.66 years. LASSO regression identified seven variables associated with CKD: age, blood urea nitrogen (BUN), hemoglobin, uric acid, triglyceride-glucose (TyG) index, urine protein-to-creatinine ratio (UPCR), and medical insurance type. The final logistic regression model incorporated six variables: age [OR=1.067 (95% CI: 1.058-1.076)], BUN [OR=1.377 (95% CI: 1.338-1.418)], hemoglobin [OR=0.992 (95% CI: 0.989-0.995)], uric acid [OR=1.004 (95% CI: 1.003-1.004)], TyG index [OR=1.445 (95% CI: 1.324-1.577)], and self-payment medical insurance [OR=1.732 (95% CI: 1.542-1.945)]. The model had an AUC of 0.759 (95% CI: 0.747-0.770) and a Brier score of 0.140 (95% CI: 0.136-0.145), indicating good predictive performance. The calibration curve showed good agreement between the predicted risk and the observed value. Conclusion The constructed LASSO-logistic regression risk prediction model in this study can effectively assess the risk of CKD in elderly individuals aged 60 years and above with hypertension and diabetes, providing a basis for early identification of high-risk individuals and the formulation of targeted CKD prevention and control measures.

ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus （PTDM） using multiple machine learning algorithms， and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1， 2020 to December 31， 2024， and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set， i.e.， logistic regression （LR）， decision tree （DT）， Naive Bayes （NB）， random forest （RF）， K-nearest neighbor （KNN）， extreme gradient boosting （XGBoost）， and adaptive boosting （AdaBoost）. In the validation set， various methods were used to assess the predictive performance of each model， such as accuracy， precision， recall rate， specificity， F1 score， area under the receiver operating characteristic curve （AUROC）， and area under the precision-recall curve （AUPRC）. The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models， and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled， among whom 26 developed PTDM， and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex， overweight or obesity， anhepatic phase， time of operation， length of hospital stay， early postoperative hypomagnesemia， and impaired fasting glucose （IFG）. In the validation set， the XGBoost model showed the best predictive performance， with an AUROC of 0.907 （95% confidence interval ［CI］： 0.807 — 0.989）， an AUPRC of 0.649 （95%CI： 0.339 — 0.955）， an accuracy of 0.878， a precision of 0.667， a recall rate of 0.750， an F1-score of 0.706， a specificity of 0.909， and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667， application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance， followed by time of operation， overweight or obesity， sex， IFG， anhepatic phase， and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals； however， multicenter large-sample data are needed for further validation.

Objective: To analyze the mediating effect of self-efficacy on the relationship between social support and depression symptoms among elderly patients with type 2 diabetes mellitus (T2DM), so as to provide the evidence for improving mental health intervention strategies in this population. Methods: From June to July 2024, elderly patients aged ≥60 years with T2DM receiving basic public health management services were recruited from four community health service centers in Nanjing City using convenience sampling. Demographic and disease-related information were collected through questionnaire surveys. Depression symptoms, self-efficacy, and social support were assessed using the 9-item Patient Health Questionnaire, the Diabetes Self-Efficacy Scale, and the Social Support Rating Scale, respectively. A structural equation model was constructed using Mplus 8.3 to examine the mediating effect of self-efficacy on social support and depression symptoms. The significance of the mediating effect was tested using the Bootstrap method. Results: A total of 604 elderly patients with T2DM were surveyed. The median age was 72.00 (interquartile range, 9.00) years. There were 292 males (48.34%) and 312 females (51.66%). The median score of depression symptoms was 2.00 (interquartile range, 5.00) points. A total of 176 participants were identified as having depressive symptoms, with a detection rate of 29.10%. The median scores of self-efficacy and social support were 4.11 (interquartile range, 0.78) and 39.00 (interquartile range, 11.00) points, respectively. The mediation analysis showed that social support had a direct negative effect on depression symptoms among elderly patients with T2DM, with an effect value of -0.137 (95%CI: -0.226 to -0.043). Social support also indirectly affected depression symptoms through self-efficacy, with an effect value of -0.066 (95%CI: -0.099 to -0.037). The mediating effect accounted for 32.51% of the total effect. Conclusions Self-efficacy plays a partial mediating role between social support and depressive symptoms among elderly patients with T2DM. It is recommended to reduce the risk of depression symptoms in this population by improving social support levels and enhancing self-efficacy.

OBJECTIVE T o establish the automatic diagnosis system for varicella pneumonia based on multi-slice spiral computed tomography(MSCT)and verify its application value.METHODS The clinical data were collected from 295 patients with varicella who were treated in the hospital from Jan.2016 to Mar.2023 and assigned as the training set,the pulmonary imaging findings were acquired from the MSCT chest scanning.The automatic diagno-sis system for varicella pneumonia was established based on MSCT with the use of convolutional neural network technology.Totally 279 patients with varicella who were treated during the same period were chosen as the valida-tion set,the result of comprehensive diagnosis was set as gold standard,and the efficiency of the above system in diagnosis of varicella pneumonia was observed.RESULTS Totally 279 patients with varicella were included in the validation group,243 of whom had varicella pneumonia,and 36 had simple varicella infection.The sensitivity of the automatic diagnosis system established based on MSCT was 97.53％in diagnosis of the varicella pneumonia of the validation group,with the specificity 91.67％,the accuracy 96.77％,respectively higher than 93.83％,83.33％and 92.47％of MSCT,and it was highly consistent with the gold standard(Kappa=0.919,P＜0.001);there was consistency between MSCT and the gold standards(Kappa=0.675,P＜0.001).CONCLUSION The au-tomatic diagnosis system for varicella pneumonia established based MSCT can raise the sensitivity,specificity and accuracy in diagnosis of varicella pneumonia and have the advantages of automation and convenience,and serve as a new tool for clinical diagnosis of varicella pneumonia.

Objective:To establish criteria for diagnosing lymph node metastasis (LNM) in newly diagnosed papillary thyroid cancer (PTC) patients based on 18F-FDG PET/MR and evaluate its diagnostic efficiency. Methods:The data of 14 patients with PTC (all females, age (38.8±13.5) years) who underwent 18F-FDG PET/MR and ultrasound sequentially 2 weeks before surgery at the First Affiliated Hospital of the Air Force Medical University from May 2021 to August 2023 were retrospectively analyzed. Visual and semi-quantitative assessments were performed on all patients step by step (Ⅱ-Ⅵ area) and neck by neck (left, right, and central area). The dimensions of all suspected lymph nodes were measured on T 2 weighted imaging (WI)-MRI and SUV max was measured on PET. Taking postoperative pathology as the reference standard, the independent risk factors for predicting LNM were determined by multivariate logistic regression analysis, and the diagnostic efficiency of each model was evaluated by ROC curve analysis. Results:A total of 21 macroscopic regions of lymph nodes(15 were malignant, 6 were benign) and 178 lymph nodes (120 were malignant, 58 were benign) were cleared by surgery. Multivariate logistic regression analysis showed that SUV max (odds ratio ( OR)=1.865, 95% CI: 1.323-2.630, P<0.001) and short diameter on MRI (SD-MRI) ( OR=1.752, 95% CI: 1.189-2.580, P=0.005) were independent predictors of LNM. The cut-off value of SD-MRI in predicting LNM was 5.7mm (AUC=0.812, Youden index (YI)=0.463). For the SD-MRI cut-off values ≥5.7 or <5.7mm, the corresponding SUV max cut-off values were 1.6 and 1.8, respectively. When " dual threshold" quantitative criteria (SD-MRI≥5.7mm + SUV max≥1.6 or SD-MRI<5.7mm + SUV max≥1.8) was used as the diagnostic criteria of 18F-FDG PET/MR, the AUC and YI could be improved to 0.909 and 0.818. Based on the regional level analysis, sensitivity, specificity, and accuracy of LNM diagnosis by ultrasound, MRI, and 18F-FDG PET/MR " dual threshold" criteria were 11/15 vs 12/15 vs 13/15, 5/6 vs 3/6 vs 5/6, 76.2%(16/21) vs 71.4%(15/21) vs 85.7%(18/21), respectively. Conclusion:Compared with the ultrasound and MRI, the 18F-FDG PET/MR " dual threshold" criteria exhibits higher sensitivity and accuracy in determining the scope of LNM clearance for PTC patients.

This study applies a PEST-SWOT hybrid analysis framework to address key challenges in promoting the"In-ternet Plus"full-process management model for mental disorders.Key issues include the imbalance in service resource distribu-tion between urban and rural areas,insufficient effectiveness of digital technologies,and the lack of coordinated multi-stakeholder mechanisms.By analyzing macro-environmental factors,such as policy,economy,society,and technology,alongside internal strengths,weaknesses,opportunities,and threats,the study underscores the significant advantages and challenges of implemen-ting the"Internet Plus"model in mental disorder management.To achieve better promotion outcomes,it is crucial to enhance le-gal and policy frameworks,strengthen technological innovation,optimize service delivery models,and establish collaborative mechanisms among stakeholders.

Objective:To evaluate the feasibility of using the domestic ArcherQA system for fast and simplified independent verification of CyberKnife (CK) stereotactic radiotherapy (SRT) plans.Methods:SRT plans of 57 patients treated with CK at Tianjin Medical University Cancer Institute and Hospital from August 2021 to August 2022 were retrospectively analyzed, including 15 intracranial, 30 pulmonary, and 12 abdominal tumors cases. Point-dose and planar-dose verifications were performed using an ionization chamber and radiochromic films embedded in a homogeneous phantom, and the results were compared with those calculated by the treatment planning system (TPS). The localization CT images and corresponding SRT plans were imported into the ArcherQA system for independent dose verification and analysis. The correlation between ArcherQA results and phantom measurements was analyzed, with comparisons of target mean dose differences and γ pass rates.Results:Phantom measurement results showed, the measured point-dose differences for intracranial, lung, and abdominal plans were -0.94% ± 3.22%, 1.92% ± 2.05%, and 2.12% ± 0.77%, respectively. The mean dose differences in target dose calculation between ArcherQA and TPS: intracranial in the gross tumor volume (GTV) regions were 0.34% ± 2.21%, lung tumor GTV were -2.47% ± 2.46%, and abdominal tumor GTV were 0.80% ± 2.61%, respectively. Among them, the abdominal GTV region showed the highest correlation between ArcherQA and measured results ( r=0.78). The average two-dimensional γ pass rates (2 mm/2%, threshold=10%) measured using phantom films were 95.92% ± 2.35% for intracranial, 95.70% ± 2.74% for lung, and 96.74% ± 3.41% for abdominal tumors plans, respectively. The three-dimensional ArcherQA results showed comparable γ pass rates (1 mm/2%, threshold=10%) for lung and abdominal GTV and PTV regions, with similar medians and data dispersion to film measurements. Conclusions:The ArcherQA system enables rapid and efficient independent dose verification of CK SRT plans without the need for additional hardware. The verification results show good correlation with phantom measurements, supporting its potential as an auxiliary quality assurance tool in clinical CK SRT implementation.