OBJECTIVE:Elevated blood pressure increases the risk of cardiovascular diseases.Isometric exercise training has been shown to significantly reduce resting blood pressure,but the factors influencing its effectiveness remain unclear,and specific application guidelines are yet to be established.This study aims to evaluate the impact of isometric exercise training on resting blood pressure through meta-analysis,explore its moderating factors,and provide evidence-based recommendations based on its dose-response relationship.METHODS:Following the PRISMA guidelines,a systematic search was conducted in PubMed,Embase,Cochrane Library,Scopus,and Web of Science databases using keywords"Isometric exercise training,""Systolic blood pressure,"and"Diastolic blood pressure,"covering literature up to September 2024.Randomized controlled trials involving isometric exercise training and resting blood pressure were included.Three independent researchers performed literature screening and data extraction,assessing bias risk and quality grades using the Risk of Bias 2.0 tool and GRADE framework.Main effect pooling,publication bias assessment,subgroup,and regression analysis were conducted using R software(version 4.3.4).RESULTS:A total of 28 articles(comprising 32 randomized controlled trials)involving 977 participants were included.(1)Meta-analysis results indicated that isometric exercise training significantly reduced resting systolic blood pressure(MD=-8.01,95％CI=-9.22 to-6.80,P＜0.01,I2=18.20％,low evidence grade)and diastolic blood pressure(MD=-3.46,95％CI=-4.64 to-2.28,P＜0.01,I2=0％,moderate evidence grade)compared to no exercise.(2)Subgroup analysis results revealed significant influences of gender,health status,exercise modality,frequency,intensity,duration,sets per session,rest duration,and baseline blood pressure on the main effects for both systolic(P＜0.01)and diastolic blood pressure(P＜0.05).(3)Regression analysis results did not show any significant influencing factors,but body mass index(β=-4.11,P=0.091)showed a significant negative trend on the main effect for systolic blood pressure.(4)No significant publication bias was observed in the meta-analysis results(P＞0.05).CONCLUSION:(1)Isometric exercise training significantly lowers systolic(low evidence grade)and diastolic(moderate evidence grade)blood pressure with clinically meaningful thresholds.(2)Participant characteristics(gender,health status,baseline blood pressure,and body mass index)and isometric exercise training protocols(modality,frequency,intensity,duration,cycle,sets per session,and rest duration)influence its antihypertensive effects.(3)The article recommends the optimal blood pressure management prescription:three sessions per week,with four sets per session,each set lasting 2 minutes with a 2-minute rest,at an intensity of 95％HRpeak using isometric wall squat exercises;the intervention period can be adjusted around a 6-week node.Future high-quality research is urgently needed to further validate and support these conclusions.

OBJECTIVE:Elevated blood pressure increases the risk of cardiovascular diseases.Isometric exercise training has been shown to significantly reduce resting blood pressure,but the factors influencing its effectiveness remain unclear,and specific application guidelines are yet to be established.This study aims to evaluate the impact of isometric exercise training on resting blood pressure through meta-analysis,explore its moderating factors,and provide evidence-based recommendations based on its dose-response relationship.METHODS:Following the PRISMA guidelines,a systematic search was conducted in PubMed,Embase,Cochrane Library,Scopus,and Web of Science databases using keywords"Isometric exercise training,""Systolic blood pressure,"and"Diastolic blood pressure,"covering literature up to September 2024.Randomized controlled trials involving isometric exercise training and resting blood pressure were included.Three independent researchers performed literature screening and data extraction,assessing bias risk and quality grades using the Risk of Bias 2.0 tool and GRADE framework.Main effect pooling,publication bias assessment,subgroup,and regression analysis were conducted using R software(version 4.3.4).RESULTS:A total of 28 articles(comprising 32 randomized controlled trials)involving 977 participants were included.(1)Meta-analysis results indicated that isometric exercise training significantly reduced resting systolic blood pressure(MD=-8.01,95％CI=-9.22 to-6.80,P＜0.01,I2=18.20％,low evidence grade)and diastolic blood pressure(MD=-3.46,95％CI=-4.64 to-2.28,P＜0.01,I2=0％,moderate evidence grade)compared to no exercise.(2)Subgroup analysis results revealed significant influences of gender,health status,exercise modality,frequency,intensity,duration,sets per session,rest duration,and baseline blood pressure on the main effects for both systolic(P＜0.01)and diastolic blood pressure(P＜0.05).(3)Regression analysis results did not show any significant influencing factors,but body mass index(β=-4.11,P=0.091)showed a significant negative trend on the main effect for systolic blood pressure.(4)No significant publication bias was observed in the meta-analysis results(P＞0.05).CONCLUSION:(1)Isometric exercise training significantly lowers systolic(low evidence grade)and diastolic(moderate evidence grade)blood pressure with clinically meaningful thresholds.(2)Participant characteristics(gender,health status,baseline blood pressure,and body mass index)and isometric exercise training protocols(modality,frequency,intensity,duration,cycle,sets per session,and rest duration)influence its antihypertensive effects.(3)The article recommends the optimal blood pressure management prescription:three sessions per week,with four sets per session,each set lasting 2 minutes with a 2-minute rest,at an intensity of 95％HRpeak using isometric wall squat exercises;the intervention period can be adjusted around a 6-week node.Future high-quality research is urgently needed to further validate and support these conclusions.

ObjectiveThis paper aims to conduct the feature analysis and correlation analysis on the ocular collateral features and differential metabolites in patients with chronic hepatitis B （CHB） complicated by glucose metabolism disorder （GMD），particularly those with the damp-heat syndrome type，by integrating shadowless scleral imaging and metabolomics technologies. MethodsA total of 313 patients were recruited from the Hepatology and Endocrinology Outpatient Departments of Public Health Clinical Center of Chengdu according to the inclusion/exclusion criteria，and they were divided into a CHB group and a CHB complicated by GMD groups （damp-heat syndrome group and non-damp-heat syndrome group）. All patients underwent high-definition ocular image acquisition and feature extraction using an intelligent analysis system for shadowless scleral imaging to analyze the differences in the counting of morphological feature scores of ocular collaterals among groups. By using a digital sampling method，24 patients from each group were randomly selected，along with 20 healthy volunteers，for untargeted metabolomic analysis of peripheral serum. Differential metabolites were identified，statistically analyzed，and subjected to potential biomarker analysis and pathway enrichment. Spearman method was performed to conduct the correlation analysis on the differential ocular collateral features and differential metabolites，followed by correlation network construction. ResultsCompared with those in the CHB group，patients with CHB complicated by GMD showed significant changes in ocular collateral feature scores such as "hillock"，"blood vessels"，and "pale dusky coloration" （P<0.05）. In comparison with those in the healthy group，metabolites including N-acetylglucosamine，acetylhomoserine，and myo-inositol （AUC>0.7） were identified as potential biomarkers for the disease. Compared with those in the CHB complicated by GMD group with non-damp-heat syndrome，patients with damp-heat syndrome exhibited significant changes in feature scores of "plaques"，"yellow coloration"，"spleen"，and "gallbladder" （P<0.05）. In comparison with those in the healthy group，metabolites such as O²′-4a-cyclic tetrahydrobiopterin，theobromine，xanthurenic acid，and L-glutamic acid 5-phosphate （AUC>0.7） were identified as potential biomarkers for the damp-heat syndrome type. The Spearman correlation analysis reveals weak to moderate linear correlations between the differential scleral collateral features and metabolites. By constructing a "disease-syndrome" network of ocular diagnosis and metabolites，"xanthurenic acid-gallbladder" and "theobromine-plaque/yellow coloration" were identified as specific molecular-phenotypic correlated biomarker clusters for CHB complicated by GMD with dampness-heat syndrome. ConclusionPatients with CHB complicated by GMD demonstrate differential ocular diagnostic features and serum metabolites corresponding to disease states and dampness-heat syndrome. These objective biomarkers can guide both clinical syndrome differentiation and medication. The macro-micro integration based on ocular feature clusters and potential metabolic biomarkers offers an innovative approach to a combined traditional Chinese and Western medicine diagnosis and treatment model for this disease.

ObjectiveTo study the clinical characteristics and influencing factors of rheumatoid arthritis （RA） in the patients with cold dampness obstruction syndrome. MethodsThe RA patients treated in the Department of Traditional Chinese Medicine and Rheumatology of the China-Japan Friendship Hospital from August 2022 to June 2024 were selected. The demographic information， clinical data， laboratory test results， and traditional Chinese medicine （TCM） symptom information were collected for syndrome differentiation， on the basis of which the characteristics and influencing factors of cold dampness obstruction syndrome were analyzed. ResultsA total of 258 RA patients were selected in this study， including 88 （34.1%） patients with cold dampness obstruction syndrome， 53 （20.5%） patients with dampness and heat obstruction syndrome， 31 （12.0%） patients with wind dampness obstruction syndrome， 29 （11.2%） patients with liver-kidney deficiency syndrome， 19 （7.4%） patients with Qi-blood deficiency syndrome， 14 （5.4%） patients with phlegm-stasis obstruction syndrome， 15 （5.8%） patients with stasis obstructing collateral syndrome and 9 （3.5%） patients with Qi-Yin deficiency syndrome. The patients were assigned into two groups of cold dampness obstruction syndrome and other syndromes. The group of cold dampness obstruction syndrome had lower joint fever， 28-tender joint count （TJC28）， and 28-joint disease activity score （DAS28）-C-reactive protein （CRP） and higher central sensitization， cold feeling of joints， fear of wind and cold， cold limbs， and abdominal distention than the group of other syndromes （P<0.05）. The binary logistic regression analysis showed that central sensitization （OR 5.749， 95%CI 2.116-15.616， P<0.001） and DAS28-CRP （OR 0.600， 95% CI 0.418-0.862， P=0.006） were the independent factors influencing cold dampness obstruction syndrome in RA. ConclusionCold dampness obstruction syndrome is a common syndrome in RA patients. It is associated with central sensitization， cold feeling of joints， abdominal distension and may be a clinical syndrome associated with central sensitization.

Objective:To develop and validate machine learning-based radiomics models using preoperative CT images for individualized prediction of mitotic index (MI) in patients with gastrointestinal stromal tumors (GIST).Methods:The study was a case-control study. The data of 348 GIST patients confirmed by pathology were retrospectively collected from two independent medical centers: the Affiliated Hospital of Qingdao University (center 1) and Shandong Provincial Hospital Affiliated to Shandong First Medical University (center 2), covering the period from January 2013 to June 2018. Patients from center 1 were divided into a training cohort (176 cases) and an internal validation cohort (75 cases) at a ratio of 7∶3 using random sampling. Patients from center 2 served as an independent external validation cohort (97 cases). The primary endpoint was MI, categorized into high MI (145 cases) and low MI (203 cases) groups. Radiomic features were extracted from the portal venous phase images of preoperative contrast-enhanced CT scans. Five machine learning algorithms, including logistic regression, support vector machine, random forest, decision tree, and extreme gradient boosting (XGBoost),were employed to construct MI prediction models. The optimal model was identified using receiver operating characteristic curves. An individualized prediction model was developed by integrating the the optimal machine learning model combined with selected independent clinical factors, and the importance of features was visualized using Shapley Additive Explanation (SHAP) analysis. Patients were followed up, and Kaplan-Meier curves along with log-rank tests were used to evaluate recurrence-free survival (RFS) differences between the predicted high MI and low MI groups.Results:Among the five constructed machine learning models, the XGBoost model demonstrated the best predictive performance, with area under the curve (AUC) of 0.809 (95% CI 0.738-0.872), 0.693 (95% CI 0.571-0.809), and 0.718 (95% CI 0.605-0.822) in the training cohort, internal validation cohort, and external validation cohort, respectively. An individualized prediction model combining the XGBoost model with independent clinical factors (tumor location and tumor size) was developed. The model achieved AUC of 0.843 (95% CI 0.785-0.899), 0.791 (95% CI 0.680-0.894), and 0.777 (95% CI 0.678-0.861) in the training cohort, internal validation cohort, and external validation cohort, respectively. SHAP analysis indicated that radiomic features had the highest predictive impact. In both the training cohort and internal validation cohort, the RFS of patients predicted to be in the high MI group was lower than that of the low MI group, with statistically significant differences ( χ2=14.58, 9.52, both P<0.001). However, there was no statistically significant difference in RFS in the external validation set ( χ2=6.18, P=0.080). Conclusions:The optimal XGBoost model based on radiomic features extracted from preoperative portal venous phase CT images, when combined with clinical factors, can effectively predict the MI of GIST patients.

Objective:To develop and validate machine learning-based radiomics models using preoperative CT images for individualized prediction of mitotic index (MI) in patients with gastrointestinal stromal tumors (GIST).Methods:The study was a case-control study. The data of 348 GIST patients confirmed by pathology were retrospectively collected from two independent medical centers: the Affiliated Hospital of Qingdao University (center 1) and Shandong Provincial Hospital Affiliated to Shandong First Medical University (center 2), covering the period from January 2013 to June 2018. Patients from center 1 were divided into a training cohort (176 cases) and an internal validation cohort (75 cases) at a ratio of 7∶3 using random sampling. Patients from center 2 served as an independent external validation cohort (97 cases). The primary endpoint was MI, categorized into high MI (145 cases) and low MI (203 cases) groups. Radiomic features were extracted from the portal venous phase images of preoperative contrast-enhanced CT scans. Five machine learning algorithms, including logistic regression, support vector machine, random forest, decision tree, and extreme gradient boosting (XGBoost),were employed to construct MI prediction models. The optimal model was identified using receiver operating characteristic curves. An individualized prediction model was developed by integrating the the optimal machine learning model combined with selected independent clinical factors, and the importance of features was visualized using Shapley Additive Explanation (SHAP) analysis. Patients were followed up, and Kaplan-Meier curves along with log-rank tests were used to evaluate recurrence-free survival (RFS) differences between the predicted high MI and low MI groups.Results:Among the five constructed machine learning models, the XGBoost model demonstrated the best predictive performance, with area under the curve (AUC) of 0.809 (95% CI 0.738-0.872), 0.693 (95% CI 0.571-0.809), and 0.718 (95% CI 0.605-0.822) in the training cohort, internal validation cohort, and external validation cohort, respectively. An individualized prediction model combining the XGBoost model with independent clinical factors (tumor location and tumor size) was developed. The model achieved AUC of 0.843 (95% CI 0.785-0.899), 0.791 (95% CI 0.680-0.894), and 0.777 (95% CI 0.678-0.861) in the training cohort, internal validation cohort, and external validation cohort, respectively. SHAP analysis indicated that radiomic features had the highest predictive impact. In both the training cohort and internal validation cohort, the RFS of patients predicted to be in the high MI group was lower than that of the low MI group, with statistically significant differences ( χ2=14.58, 9.52, both P<0.001). However, there was no statistically significant difference in RFS in the external validation set ( χ2=6.18, P=0.080). Conclusions:The optimal XGBoost model based on radiomic features extracted from preoperative portal venous phase CT images, when combined with clinical factors, can effectively predict the MI of GIST patients.

Objective To analyze the current status of knowledge,attitude,and behavior?(KAP)of doctors and pharmacists regarding iodine contrast agent allergic reactions in medical institutions in China and the influencing factors,to provide reference for the treatment of iodine contrast agent allergic patients.Methods A questionnaire survey on iodine contrast agent allergic reactions was conducted among doctors and pharmacists in China using a self-designed questionnaire.The questionnaire was distributed online via WeChat and the participants were anonymous and voluntary.The scores of knowledge,attitude,and behavior of medical staff of different genders,departments,and titles were statistically analyzed.Wilcoxon rank sum test and multiple linear regression analysis were used to analyze the influencing factors.Results A total of 105 doctors and pharmacists from 19 provinces,autonomous regions and municipalities participated in the survey,completing 105 valid questionnaires.The knowledge score(out of 4 points),attitude score(out of 3 points),and behavior score(out of 3 points)of doctors and pharmacists regarding contrast agent allergy reactions were 2(1,2)points,1(0,2)points,and 1(1,2)points,respectively.Multivariate linear regression analysis showed that job title is a factor affecting the knowledge score.Compared to those with primary and below titles,senior title doctors and pharmacists had higher knowledge scores(P=0.007).Educational level is a influence factor affecting the attitude score.Compared to those with undergraduate and below educational levels,doctors and pharmacists with doctoral degrees had more positive attitudes(P=0.011).Attitude score is a influence factor affecting the behavior score,the more positive the attitude,the more positive the behavior(P=0.015).Conclusion The knowledge,attitude,and practice(KAP)of doctors and pharmacists regarding contrast agent allergy reactions need to be strengthened.Training should be conducted for doctors and pharmacists,taking into account the KAP differences among individuals with different job titles and educational levels,to enhance knowledge levels and actively explore safe and effective desensitization treatment methods for patients with contrast agent allergies.The use of iodinated contrast agents should be rationalized while ensuring patient safety.

Objectives:To investigate the effect of circular RNA (circRNA) hsa_circ_0019217 on the biological function of chorionic trophoblast cell line (HTR8/SVneo) and its mechanism in the occurrence of pre-eclampsia (PE).Methods:The circRNA expression database was used to analyze the differentially expressed circRNA in placental tissues of PE women. The expression levels of hsa_circ_0019217 and miR-526b-5p were detected by reverse transcription real-time fluorescent quantitative PCR (RT-qPCR), and the subcellular localization of hsa_circ_0019217 was detected by fluorescence in situ hybridization. The proliferation, migration and invasion of trophoblast cells were detected by cell counting kit-8 (CCK-8) assay and transwell assay. Western blot and enzyme-linked immunosorbent assay (ELISA) were used to verify the effects of hsa_circ_0019217, miR-526b-5p and decorin (DCN) on matrix metalloproteinase 2 (MMP2), tissue inhibitor of metalloproteinase 2 (TIMP2), placental growth factor (PlGF) and human chorionic gonadotropin (hCG) protein expression levels. Dual luciferase reporter gene assay and RNA immunoprecipitation (RIP) assay were used to verify the interaction between hsa_circ_0019217, miR-526-5p and DCN.Results:(1) The analysis of circRNA expression database showed that the expression level of hsa_circ_0019217 was significantly increased in the placental tissues of PE women (fold change=67, P<0.05), and it was mainly located in the cytoplasm. (2) Knockdown of hsa_circ_0019217 promoted the proliferation, migration and invasion of HTR8/SVneo cells, increased the expression levels of MMP2 and PlGF, and decreased the expression levels of TIMP2 and hCG in HTR8/SVneo cells. (3) Hsa_circ_0019217 targeted adsorption of miR-526b-5p, and inhibition of miR-526b-5p reduced the proliferation, migration and invasion of HTR8/SVneo cells. The expression levels of MMP2 and PlGF in HTR8/SVneo cells were increased, and the expression levels of TIMP2 and hCG were decreased. Hsa_circ_0019217 knockdown and inhibiting miR-526b-5p could reverse the effect of hsa_circ_0019217 knockdown on promoting the proliferation, migration and invasion of HTR8/SVneo cells, and reversed the effect of hsa_circ_0019217 knockdown on the protein expression levels of MMP2, PlGF, TIMP2 and hCG. (4) miR-526b-5p targeted DCN in HTR8/SVneo cells, hsa_circ_0019217 knockdown reduced the expression level of DCN, and inhibiting miR-526b-5p increased the expression level of DCN. When hsa_circ_0019217 and miR-526b-5p were inhibited simultaneously, there was no significant change in the protein expression level of DCN. (5) Overexpression of miR-526b-5p promoted the proliferation, migration and invasion of HTR8/SVneo cells, while overexpression of DCN inhibited the proliferation, migration and invasion of HTR8/SVneo cells. Simultaneous overexpression of miR-526b-5p and DCN reversed the effects of miR-526b-5p overexpression on cell proliferation, migration and invasion. Overexpression of miR-526b-5p increased the expression levels of MMP2 and PlGF and decreased the expression levels of TIMP2 and hCG in HTR8/SVneo cells. Overexpression of DCN reduced the expression levels of MMP2 and PlGF and increased the expression levels of TIMP2 and hCG. Overexpression of miR-526b-5p and DCN reversed the effects of miR-526b-5p on the expression of these proteins. Conclusion:Hsa_circ_0019217 regulates the expression of DCN by adsorption of miR-526b-5p, thereby affecting the proliferation, migration and invasion of trophoblast cells and regulating the protein expression levels of MMP2, TIMP2, PlGF and hCG, which might be used as a target for early prevention of PE.

Objective To analyze the influencing factors of poor incision healing in postoperative patients with breast cancer.Methods The clinical data of 150 patients with breast cancer diagnosed by the Department of Nail Milk surgery of the Fifth affiliated Hospital of Xinjiang Medical University from January 2016 to December 2023 were retrospectively analyzed.According to the postoperative wound healing,the patients were divided into two groups:good healing group(n=94)and poor healing group(n=56).The general data,operation-related data and clinicopathological characteristics of the two groups were collected for univariate analysis,and the single-factor indexes with statistical significance were analyzed by multivariate Logistic analysis to screen the risk factors of poor incision healing after operation.The statistically significant indexes of regression analysis were analyzed by receiver operating characteristic(ROC)curve to further explore its predictive value in poor incision healing after breast cancer operation.Results The data of the two groups were compared and analyzed.Multivariate Logistic regression analysis showed that BMI,diabetes,age,axillary lymph node dissection and hemoglobin were independent risk factors for poor incision healing(P＜0.05).ROC curve analysis of independent risk factors showed that when the age was more than 57.5,the area under the curve(AUC)was 0.635,the sensitivity was 55.4％,the specificity was 68.1％,and the critical value was 57.5.When BMI＞24.9 kg/m2,the area under the curve(AUC)was 0.735,the sensitivity was 87.5％,the specificity was 61.7％,and the critical value was 24.9(P＜0.001).When hemoglobin＜101.5 g/L,the area under the curve(AUC)was 0.829,the sensitivity was 57.1％,the specificity was 94.7％,and the critical value was 101.5 g/L(P＜0.001).Conclusion BMI,diabetes,hemoglobin,age and axillary lymph node dissection are independent risk factors for poor wound healing after breast cancer operation.When BMI＞24.9 kg/m2,age＞57.5 years old and hemoglobin＜101.5 g/L,it can predict the occurrence of poor incision healing in patients with breast cancer.