Objective: To explore the association between sleep quality, sleep duration with blood pressure in primary and secondary school students with different nutritional status, so as to provide a reference for targeted intervention measures. Methods: By using stratified cluster random sampling method, a total of 10 871 students aged 7 to 18 years were selected from 36 primary and secondary schools in 6 counties of Yangzhou from October to November 2023. Physical examination and questionnaire survey were conducted respectively. Student Health Status and Influencing Factors Questionnaire was used to collected basic information. The overweight/obesity and sleep quality of primary and secondary school students were determined according to the Screening for Overweight and Obesity among School age Children and Adolescents and the Pittsburgh Sleep Quality Index scale. The χ 2 test was used to compare the prevalence of elevated blood pressure in different groups of primary and secondary school students. Multivariate Logistic regression model was used to explore the association between sleep and blood pressure in primary and secondary school students. Results: The prevalence of elevated blood pressure among primary and secondary school students in Yangzhou was 13.86 %, higher among boys (15.13%) than girls (12.62%) ( χ 2=14.30, P <0.01). The elevated blood pressure rate of obese and overweight primary and secondary school students were 26.98% and 14.90%, respectively, higher than 8.71% of non overweight and obese children ( χ 2=482.58, P <0.01). There were statistically significant differences in elevated blood pressure rate among primary and secondary school students in different sleep quality and sleep duration ( χ 2= 8.45, 71.58, P <0.05). After controlling for gender, residence, educational stage, parental education, sedentary time, the results of multiple Logistic regression analysis showed that no correlation between sleep quality and elevated blood pressure under different nutritional status was found among primary and secondary school students. In primary and secondary school students with obesity, prevalence of elevated blood pressure was higher among those with sleep duration <8 and 8 to <9 h/d ( OR=1.54, 1.72, P <0.05). However, there was no significant association found in the other groups ( OR=1.04-1.28, P >0.05). In gender stratification, sleep duration < 8, 8 to <9 and 9 to <10 h/d of obese boys were positively correlated with elevated blood pressure ( OR=1.97, 2.09, 1.86, P <0.05). Conclusion Among obese primary and secondary school students, sleep duration <9 h/d is associated with an increased risk of elevated blood pressure, especially among obese boys.

BACKGROUND: Delayed platelet engraftment is a common complication after umbilical cord blood transplantation (UCBT), and there is no standard therapy. Avatrombopag (AVA) is a second-generation thrombopoietin (TPO) receptor agonist (TPO-RA) that has shown efficacy in immune thrombocytopenia (ITP). However, few reports have focused on its efficacy in patients diagnosed with thrombocytopenia after allogeneic hematopoietic stem cell transplantation (allo-HSCT). METHODS: We conducted a retrospective study at the First Affiliated Hospital of the University of Science and Technology of China to evaluate the efficacy of AVA as a first-line TPO-RA in 65 patients after UCBT; these patients were compared with 118 historical controls. Response rates, platelet counts, megakaryocyte counts in bone marrow, bleeding events, adverse events and survival rates were evaluated in this study. Platelet reconstitution differences were compared between different medication groups. Multivariable analysis was used to explore the independent beneficial factors for platelet implantation. RESULTS: Fifty-two patients were given AVA within 30 days post-UCBT, and the treatment was continued for more than 7 days to promote platelet engraftment (AVA group); the other 13 patients were given AVA for secondary failure of platelet recovery (SFPR group). The median time to platelet engraftment was shorter in the AVA group than in the historical control group (32.5 days vs . 38.0 days, Z  = 2.095, P  = 0.036). Among the 52 patients in the AVA group, 46 achieved an overall response (OR) (88.5%), and the cumulative incidence of OR was 91.9%. Patients treated with AVA only had a greater 60-day cumulative incidence of platelet engraftment than patients treated with recombinant human thrombopoietin (rhTPO) only or rhTPO combined with AVA (95.2% vs . 84.5% vs . 80.6%, P  <0.001). Patients suffering from SFPR had a slightly better cumulative incidence of OR (100%, P  = 0.104). Patients who initiated AVA treatment within 14 days post-UCBT had a better 60-day cumulative incidence of platelet engraftment than did those who received AVA after 14 days post-UCBT (96.6% vs . 73.9%, P  = 0.003). CONCLUSION Compared with those in the historical control group, our results indicate that AVA could effectively promote platelet engraftment and recovery after UCBT, especially when used in the early period (≤14 days post-UCBT).
Humans ; Female ; Male ; Thrombocytopenia/etiology* ; Adult ; Retrospective Studies ; Cord Blood Stem Cell Transplantation/adverse effects* ; Middle Aged ; Adolescent ; Young Adult ; Thiazoles/adverse effects* ; Platelet Count ; Receptors, Thrombopoietin/agonists* ; Child ; Thiophenes

Objective: To analyze the prevalence and determinants of comorbid overweight/obesity and elevated blood pressure among primary and secondary school students in Yangzhou City, and to explore the association between sleep patterns, eating behavior and the comorbidity of overweight/obesity and elevated blood pressure, so as to provide reference for developing prevention strategies targeting common comorbidities in students. Methods: By using stratified cluster random sampling, a total of 8 735 primary and secondary school students were selected from 36 schools in six counties of Yangzhou from October to November 2023. Students underwent physical examinations and a questionnaire survey was conducted using the questionnaire on students health status and influencing factors. The Chi square test was used to compare the detection rate of comorbid overweight/obesity and elevated blood pressure in different groups of primary and secondary school students. The Logistic regression model was used to explore the association between sleep and dietary behaviors and their combined effects and coexistence. Results: The detection rate of comorbid overweight/obesity and elevated blood pressure among primary and secondary school students in Yangzhou was 9.85%, which was higher among boys (12.14%) than girls (7.59%)( χ 2=50.86, P <0.01). After controlling for gender, residence, educational stage, parental education, smoking, drinking, and moderate to vigorous exercise, multivariate Logistic regression analysis showed that irregular breakfast consumption and inadequate daily sleep were associated with a higher risk of comorbidities compared with regular breakfast consumption and adequate daily sleep among overall and primary school students (overall: OR =1.52, 95% CI =1.18- 1.96 , primary school students: OR =2.79, 95% CI =1.61-4.82)(both P <0.05). From the perspective of primary school students of different genders, the risk of comorbidities in girls who consumed breakfast irregularly and had inadequate daily sleep was 3.59 times higher than that in girls who consumed breakfast irregularly and had inadequate daily sleep (95% CI =1.65-7.82, P <0.01). Conclusion The sleep patterns and breakfast behaviors of primary and secondary school students are found to be associated with comorbid overweight/obesity and elevated blood pressure, especially in primary school girls.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

OBJECTIVES: The Charlson comorbidity index reflects overall comorbidity burden and has been applied in cardiovascular medicine. However, its role in predicting in-hospital mortality in patients with acute myocardial infarction (AMI) complicated by ventricular arrhythmias (VA) remains unclear. This study aims to evaluate the predictive value of the Charlson comorbidity index in this setting and to construct a nomogram model for early risk identification and individualized management to improve outcomes. METHODS: Using the open-access critical care database MIMIC-IV (Medical Information Mart for Intensive Care IV), we identified intensive care unit (ICU) patients diagnosed with AMI complicated by VA. Patients were grouped according to in-hospital survival. The predictive performance of the Charlson comorbidity index and other clinical variables for in-hospital mortality was analyzed. Key predictors were selected using the least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable Logistic regression. A nomogram model was constructed based on the regression results. Model performance was assessed using receiver operating characteristic (ROC) curves and calibration plots. RESULTS: A total of 1 492 patients with AMI and VA were included, of whom 340 died and 1 152 survived during hospitalization. Significant differences were observed between survivors and non-survivors in sex distribution, vital signs, comorbidity burden, organ function, and laboratory parameters (all P<0.05). The area under the curve (AUC) of the Charlson comorbidity index for predicting in-hospital mortality was 0.712 (95% CI 0.681 to 0.742), significantly higher than albumin, international normalized ratio (INR), hemoglobin, body temperature, and platelet count (all P<0.001), but comparable to Sequential Organ Failure Assessment (SOFA) score (P>0.05). LASSO regression identified seven key predictors: the Charlson comorbidity index (quartile groups: T1, <6; T2, ≥6-<7; T3, ≥7-<9; T4, ≥9), ventricular fibrillation, age, systolic blood pressure, respiratory rate, body temperature, and SOFA score. Multivariate Logistic regression showed that compared with T1, mortality risk increased significantly in T2 (OR=1.996, 95% CI 1.135 to 3.486, P=0.016), T3 (OR=3.386, 95% CI 2.192 to 5.302, P<0.001), and T4 (OR=5.679, 95% CI 3.711 to 8.842, P<0.001). Age (OR=1.056, P<0.001), respiratory rate (OR=1.069, P<0.001), SOFA score (OR=1.223, P<0.001), and ventricular fibrillation (OR=2.174, P<0.001) were independent risk factors, while systolic blood pressure (OR=0.984, P<0.001) and body temperature (OR=0.648, P<0.001) were protective factors. The nomogram incorporating these predictors achieved an AUC of 0.849 (95% CI 0.826 to 0.871) with high discrimination and good calibration (mean absolute error=0.014). CONCLUSIONS The Charlson comorbidity index is an independent predictor of in-hospital mortality in AMI patients complicated by VA, with performance comparable to the SOFA score. The nomogram model based on the Charlson comorbidity index and additional clinical variables effectively estimates mortality risk and provides a valuable reference for clinical decision-making.
Humans ; Nomograms ; Hospital Mortality ; Myocardial Infarction/complications* ; Male ; Female ; Comorbidity ; Middle Aged ; Aged ; Arrhythmias, Cardiac/complications* ; ROC Curve ; Intensive Care Units

Mitochondrial DNA (mtDNA) acts as a damage-associated molecular pattern to activate the stimulator of interferon genes (STING) signaling in macrophages, promoting tissue inflammation. However, its role in acute myocardial infarction (AMI) remains unclear. Macrophage-specific Sting1 knockout mice were used to validate STING's pathological role in AMI. Cardiac and liver mtDNA were used to activate macrophages in co-culture systems with cardiomyocytes to assess fibrosis and hypertrophy. Panaxatriol saponin (PTS) was tested for its ability to block mtDNA-driven macrophage activation and subsequent cardiomyocyte damage. STING-PTS binding ability was analyzed. AMI rats received PTS to evaluate its effects on myocardial inflammation and ventricular remodeling. In vivo, macrophage-specific Sting1 knockout reduced myocardial inflammation and injury after AMI. In vitro, mtDNA-activated macrophages induced cardiomyocyte fibrosis and hypertrophy through STING signaling. PTS suppressed mtDNA-driven macrophage activation by directly binding STING, thereby blocking inflammatory cascades. In AMI rats, PTS treatment attenuated acute inflammation and reversed ventricular remodeling. These findings establish the mtDNA-STING axis in macrophages as a critical driver of post-AMI inflammation and identify pharmacological STING inhibition with PTS as a promising therapeutic strategy. The study bridges genetic validation with translational applications, highlighting macrophage STING as a novel target for ischemic heart disease management.

OBJECTIVE To evaluate the innovation and sustainable development ability of traditional Chinese medicine(TCM) preparation in medical institutions, and to provide reference for the decision-making of administrative departments and the sustainable development of TCM preparation in hospitals. METHODS Based on the information data of 133 medical institutions in Zhejiang Province, analytic hierarchy process was used to construct the evaluation system of innovation and sustainable development ability of TCM preparation of medical institutions, and the prediction model of evaluation system of TCM preparation room/center was built by back propagation neural network. RESULTS The evaluation index system for innovation and sustainable development of TCM preparations in medical institutions included 4 second-level indexes and 19 third-level indexes. Among them, the number of varieties developed, the number of over one million varieties, the number of registered varieties, the way of research and development, and the area of preparation room had higher weight values, which were 0.15758, 0.12928,0.09343, 0.07879 and 0.07458, respectively. The entropy weight method and analytic hierarchy process index weights were used to construct the back propagation neural network. The overall correlation coefficients of the training models of the Levenberg-Marquardt algorithm and the Scaled Conjugate Gradient algorithm were 0.98983 and 0.93480, respectively. CONCLUSION This study establishes a scientific and effective comprehensive evaluation system for the innovation and sustainable development ability of TCM preparations in medical institutions, which can realize the prediction and evaluation of the comprehensive ability of TCM preparations in medical institutions.

ObjectiveTo assess the quality of randomized controlled trials （RCTs） of compound traditional Chinese medicine （TCM） prescriptions in the treatment of nonalcoholic steatohepatitis （NASH）， and to provide recommendations for standardizing the design and reporting of RCTs in this field. MethodsDatabases such as PubMed， Web of Science， Embase， the Cochrane Library， CNKI， VIP， and Wanfang Data were searched for RCTs of compound TCM prescriptions in the treatment of NASH published from January 1， 2018 to December 31， 2023， and the articles were screened and assessed based on the Cochrane risk-of-bias assessment tool （RoB 2）， the unified standard for clinical trial reporting （CONSORT 2010）， and CONSORT-CHM Formulas 2017 for compound TCM prescriptions. ResultsA total of 45 articles were finally included， and most of these studies were rated as high-risk bias by RoB 2.0. The analysis based on the CONSORT control checklist showed a relatively low reporting rate for most of the key items regarding the quality of RCT studies. ConclusionA relatively large risk of bias is observed in the clinical studies on compound TCM prescriptions in the treatment of NASH published in the past six years， which may lead to the poor quality of reporting and evidence. It is suggested that the top-level design of clinical studies should be taken seriously in addition to investigating the advantages of TCM， so as to improve the quality of clinical studies.

Objective:To examine the satisfaction and teaching effectiveness of Health Statistics among students majoring in Public Utility Administration,and to provide valuable insights for optimizing current teaching practices and enhancing teaching effectiveness.Methods:A survey questionnaire,specifically designed for this study,was administered to 56 students of grade 2021 majoring in Public Utility Administration in our school.The questionnaire covered topics such as the difficulty of teaching content,learning satisfaction,and the Student Evaluation of Educational Quality(SEEQ)scale.Results:Non-parametric testing was considered the most difficult knowledge point,and male students found statistical inference of quantitative data was the most challenging,while female students found non-parametric testing was the most difficult.In terms of satisfaction,the highest score was obtained for pre-class review,while the lowest score was given to improving learning interest in Rain Classroom.The overall score for teaching effectiveness,as measured by SEEQ,was good across seven dimensions.Teaching enthusiasm received the highest score(4.40±0.43),while homework volume received the lowest score(3.23±0.37).With the exception of homework grading,satisfaction was positively correlated with most dimensions of teaching effectiveness evaluation.Conclusions:Despite perceiving the course as generally difficult,students expressed high satisfaction and overall positive evaluation of teaching effectiveness.Therefore,it is recommended to actively explore new teaching reforms to cultivate well-rounded applied talents for public utilities.

Objective:To explore influencing factors affecting the prognosis of patients with advanced non-small cell lung cancer (NSCLC) receiving immunotherapy based on hematologic indexes, thus to construct and evaluate a nomogram prediction model.Methods:The clinical data of 80 patients with advanced NSCLC treated with programmed death-1 inhibitor monotherapy or combination regimen from January 2018 to June 2020 at the Affiliated Hospital of North China University of Science and Technology and Tangshan People's Hospital were retrospectively analyzed. Hematologic indexes at the baseline, the optimal remission and the progressive disease (PD) were collected separately, and independent influencing factors for patient prognosis were analyzed using Cox proportional hazards regression model. A nomogram prediction model was constructed based on the results of the multifactorial analysis, and the predictive performance of the model was evaluated by receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curves.Results:As of the follow-up cut-off date, of the 80 patients, 63 had PD, with a median overall survival (OS) of 16.9 months. Univariate analysis showed that, age ( HR=2.09, 95% CI: 1.17-3.74, P=0.013) , number of treatment lines ( HR=2.23, 95% CI: 1.21-4.12, P=0.010) , lymphocyte to monocyte ratio (LMR) at the baseline ( HR=0.75, 95% CI: 0.57-0.97, P=0.028) , D-dimer ( HR=1.00, 95% CI: 1.00-1.00, P=0.002) and lactate dehydrogenase (LDH) ( HR=1.01, 95% CI: 1.00-1.01, P=0.006) at the optimal remission, haemoglobin ( HR=0.97, 95% CI: 0.96-0.99, P<0.001) , D-dimer ( HR=1.00, 95% CI: 1.00-1.00, P=0.002) , C-reactive protein ( HR=1.01, 95% CI: 1.00-1.01, P=0.011) , albumin (ALB) ( HR=0.91, 95% CI: 0.87-0.96, P=0.001) , neutrophil to lymphocyte ratio (NLR) ( HR=1.16, 95% CI: 1.05-1.27, P=0.002) and LMR ( HR=0.62, 95% CI: 0.42-0.90, P=0.012) at the PD were all influencing factors for the prognosis of advanced NSCLC patients receiving immunotherapy. Least absolute shrinkage and selection operator regression were used to screen the variables for P<0.10 in the univariate analysis, and nine possible influencing factors were obtained, which were age, fibrinogen and LDH at the optimal remission, haemoglobin, D-dimer, C-reactive protein, LDH, ALB and LMR at the PD. Multivariate analysis of the above variables showed that, age ( HR=0.91, 95% CI: 0.86-0.97, P=0.004) , LDH ( HR=1.01, 95% CI: 1.00-1.01, P=0.013) and ALB ( HR=0.82, 95% CI: 0.67-0.99, P=0.041) at the PD were independent influencing factors for the prognosis of patients with advanced NSCLC who received immunotherapy. The area under curve of the nomogram predicting model based on the above indexes, 1- and 2-year OS rates of patients were 0.77 (95% CI: 0.65-0.89) and 0.75 (95% CI: 0.66-0.88) , respectively, and C-index was 0.71 (95% CI: 0.64-0.78) , the calibration curves showed good consistency between predicted and actual probability of occurrence. Patients in the low-risk group ( n=40) had a median OS of 29.9 months (95% CI: 22.5 months-NA) , which was significantly better than that of the high-risk group ( n=40) [13.4 months (95% CI: 11.4-23.5 months) , χ2=11.30, P<0.001]. Conclusion:Age, LDH and ALB at the PD are independent influencing factors affecting the prognosis of patients with advanced NSCLC receiving immunotherapy, and the nomogram model constructed based on the above indexes has good differentiation and calibration for predicting 1- and 2-year OS rates in advanced NSCLC patients receiving immunotherapy.