ObjectiveTo analyze the prevalence and influencing factors of overweight and obesity among primary school students in a community of Fengxian District, Shanghai, and to provide references for formulating prevention and control strategies against overweight and obesity. MethodsData on height and weight of all primary school students in a community in Fengxian District, Shanghai, in 2023 were obtained by physical examination, and 1 759 primary school students were included according to the entry criteria. Overweight and obesity were determined using body mass index (BMI). Additionally, a questionnaire survey was performed to 1 045 students to collect their demographic characteristics, dietary behaviors, dietary habits, sleep and physical activity information. Chi-square test and logistic regression analysis were used to analyze the influencing factors of overweight and obesity. ResultsIn 2023, among the 1 759 primary school students in the community in Fengxian District, 923 (52.47%) were male and 836 (47.53%) were female, with an overweight/obesity detection rate of 28.08%. The detection rate of overweight and obesity was 33.37% in males and 22.25% in females, which was significantly higher in males than that in females (χ²=26.845, P<0.001). Students aged 10‒12 years had a higher overweight/obesity detection rate (32.55%) than those aged 6‒<10 years (26.53%), and the difference was statistically significant (χ²=10.925, P<0.001). Logistic regression analysis revealed that being female, with young age, parental education level of bachelor’s degree and above, a high global dietary recommendation healthy (GDR-healthy) score, preference for vegetables and sweeter home-cooked meals, and a slow eating speed were negatively correlated with overweight/obesity. Whereas, parental overweight and obesity, binge eating, and a faster eating pace than same-age, same-gender peers may be positively correlated with overweight/obesity. ConclusionThe detection rate of overweight and obesity among primary school students in the community in Fengxian District of Shanghai is higher than the national level. Gender, age, parental BMI, parental education level, dietary behaviors and habits are the main influencing factors of overweight/obesity among primary school students.

Objective To investigate the differences in radiation dose during chest CT examinations among children of different age groups and establish dose estimation regression models. Methods Chest CT data from 135 children aged 4 to 15 years were retrospectively collected from the First Affiliated Hospital of Soochow University between January 2022 and December 2023. The children were divided into three age groups: 4-5 years, 6-10 years and 11-15 years. CT scanning parameters (tube voltage, tube current, scan range) and dosimetry parameters including volume CT dose index (CTDI_vol) dose length product (DLP), and size-specific dose estimate (SSDE) were recorded. The Kruskal-Wallis test was used to compare intergroup differences. A Pearson correlation analysis was performed to assess the relationship between age and dose indicators. Both linear and nonlinear regression models were constructed. Results Age showed a weak positive correlation with CTDI_vol (r = 0.27), a moderate positive correlation with DLP (r = 0.60), and a moderate negative correlation with SSDE (r = −0.55). Linear regression analysis revealed that DLP increased with age (y = 117.85 + 9.81x, R² = 0.36), while SSDE decreased with age (y = 12.4 − 0.18x, R² = 0.32). Using orthogonal distance regression, the goodness-of-fit of the nonlinear models for DLP and SSDE significantly improved (R² = 0.99 and 0.94, respectively). Conclusion In pediatric chest CT dose assessment, CTDI_vol underestimates radiation dose compared to SSDE and fails to account for patient body size. The dose estimation models constructed with orthogonal distance regression outperform those established using the least squares method, demonstrating higher fitting accuracy, and can serve as a reference for personalized dose management in pediatric CT examinations.

As activated hepatic stellate cells (aHSCs) play a central role in fibrogenesis, they have become key target cells for anti-fibrotic treatment. Nevertheless, the therapeutic efficiency is constrained by the exosomes they secrete, which are linked to energy metabolism and continuously stimulate the activation of neighboring quiescent hepatic stellate cells (qHSCs). Herein, an intercellular communication interference strategy is designed utilizing paeoniflorin (PF) loaded and hyaluronic acid (HA) coated copper-doped ZIF-8 (PF@HA-Cu/ZIF-8, PF@HCZ) to reduce energy-related exosome secretion from aHSCs, thus preserving neighboring qHSCs in a quiescent state. Simultaneously, the released copper and zinc ions disrupt key enzymes involved in glycolysis to reduce bioenergy synthesis in aHSCs, thereby promoting the reversion of aHSCs to a quiescent state and further decreasing exosome secretion. Therefore, PF@HCZ can effectively sustain both aHSCs and qHSCs in a metabolically dormant state to ultimately alleviate liver fibrosis. The study provides an enlightening strategy for interrupting exosome-mediated intercellular communication and remodeling the energy metabolic status of HSCs with boosted antifibrogenic activity.

Objective Performing physical tasks in the low-pressure environment of space poses a significant physiological challenge for astronauts.This study investigates the localized thermophysiological effects of typical physical tasks on different body segments and analyzes the mechanisms by which low-pressure environments influence human task performance.The findings aim to provide a theoretical basis for the thermal control design of spacesuits,focusing on both localized thermoregulation and overall task performance.Methods Two typical physical tasks—15 kg weighted walking and 25 kg load-carrying—were conducted in a simulated low-pressure composite environment chamber.The chamber was set to an altitude-equivalent pressure of 57 kPa(4500 m),with a temperature of 26℃and humidity of 40％.Six non-acclimatized adult male participants were recruited.After environmental stabilization,12-point skin temperatures were recorded throughout the tasks,and localized temperature data were statistically analyzed.Results Under low-pressure conditions,different body regions exhibited distinct thermal responses over time depending on the task type,while the same body region showed varied responses under different task conditions.During walking,temperatures in the primary active regions(thighs and calves)decreased,with most other body regions(except the pelvis and feet)gradually cooling as the task progressed.In contrast,during load-carrying,temperatures in the primary active regions(back and upper arm muscles)increased significantly.Conclusion Astronauts performing different tasks in low-pressure environments experience distinct localized thermophysiological effects.Therefore,spacesuit thermal control systems should not only account for task intensity and metabolic differences but also adapt localized heating/cooling based on task-specific thermal profiles.This approach enables targeted intelligent thermal regulation,enhancing operational support in specific mission scenarios.

Objective To develop and validate risk prediction models utilizing five machine learning algorithms for assessing postoperative pulmonary infection(PPI)risk in lung cancer patients undergoing grade Ⅳ thoracoscopic surgery.Methods A retrospective cohort study included 2,380 lung cancer patients who underwent grade Ⅳ thoracoscopic surgery at a tertiary hospital in Shanghai(January 2022 to June 2024).Patients were stratified into training(n=1,665)and validation(n=715)cohorts.Five machine learning algorithms—Logistic regression(LR),artificial neural network(ANN),support vector machine(S VM),random forest(RF),and extreme gradient boosting(XGB)—were employed to construct predictive models.A nomogram was developed for clinical utility.Results Among 2,380 patients,226(9.5％)developed PPI.The Least Absolute Shrinkage and Se-lection Operator(LASSO)regression identified eight predictive variables:daily cigarette consumption,diabetes history,preoperative diffusing capacity,maximal tumor diameter,24-hour postoperative chest drainage volume,perioperative oral nutritional supplementation(ONS),postoperative urinary cathe-terization,and intraoperative pleural adhesion severity.All models demonstrated robust discrimina-tion,with area under the curve(AUC)values ranging from 0.862 to 0.947.The XGB model a-chieved superior performance(AUC=0.947,95％CI,0.937 to 0.962),followed closely by the LR model(AUC=0.926,95％CI,0.918 to 0.933).Conclusion Machine learning-based algo-rithms models effectively stratify PPI risk in lung cancer patients following grade Ⅳ thoracoscopic surgery.The derived nomogram provides a practical tool for perioperative risk management by healthcare providers.

Background::Risk assessment and treatment stratification for three-vessel coronary disease (TVD) remain challenging. This study aimed to investigate the prognostic value of left atrial volume index (LAVI) with the Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) score II, and its association with the long-term prognosis after three strategies (percutaneous coronary intervention [PCI], coronary artery bypass grafting [CABG], and medical therapy [MT]) in patients with TVD.Methods::This study was a post hoc analysis of a large, prospective cohort of patients with TVD in China, that aimed to determine the long-term outcomes after PCI, CABG, or optimal MT alone. A total of 8943 patients with TVD were consecutively enrolled between 2004 and 2011 at Fuwai Hospital. A total of 7818 patients with available baseline LAVI data were included in the study. Baseline, procedural, and follow-up data were collected. The primary endpoint was major adverse cardiac and cerebrovascular events (MACCE), which was a composite of all-cause death, myocardial infarction (MI), and stroke. Secondary endpoints included all-cause death, cardiac death, MI, revascularization, and stroke. Long-term outcomes were evaluated among LAVI quartile groups. Results::During a median follow-up of 6.6 years, a higher LAVI was strongly associated with increased risk of MACCE (Q3: hazard ratio [HR] 1.20, 95% confidence interval [CI] 1.06-1.37, P = 0.005; Q4: HR 1.85, 95%CI 1.64-2.09, P <0.001), all-cause death (Q3: HR 1.41, 95% CI 1.17-1.69, P <0.001; Q4: HR 2.54, 95%CI 2.16-3.00, P <0.001), and cardiac death (Q3: HR 1.81, 95% CI 1.39-2.37, P <0.001; Q4: HR 3.47, 95%CI 2.71-4.43, P <0.001). Moreover, LAVI significantly improved discrimination and reclassification of the SYNTAX score II. Notably, there was a significant interaction between LAVI quartiles and treatment strategies for MACCE. CABG was associated with lower risk of MACCE than MT alone, regardless of LAVI quartiles. Among patients in the fourth quartile, PCI was associated with significantly increased risk of cardiac death compared with CABG (HR: 5.25, 95% CI: 1.97-14.03, P = 0.001). Conclusions::LAVI is a potential index for risk stratification and therapeutic decision-making in patients with three-vessel coronary disease. CABG is associated with improved long-term outcomes compared with MT alone, regardless of LAVI quartiles. When LAVI is severely elevated, PCI is associated with higher risk of cardiac death than CABG.

Solar proton event(SPE)is the major concern for astronauts in space radiation environment.With the coming of solar activity peak of the 25th solar cycle,the frequency of occurrence of solar proton event is increasing,as well as the intense of the events.Two SPEs of the most flux in March 23rd,2024 and June 8th,2003 and one with extra-large geomagnetic storm in May 10th,2004 were used to analysis the astronaut dose both in China Space Station orbit and lunar environment.First,radiation particle spectrum outside TianHe module was used to calculate astronauts dose inside the station,which was compared with the measured dose;second,the fitting result of proton spectrum from GOES16 satellite was used to calculate astronaut dose in lunar orbit,which was compared with the dose measured by CRaTER.Besides,the change of dose with extra shield of different material was calculated.The results indicate when no extra-large geomagnetic storm occurs,middle level SPE has no influence to astronaut in station,but an obvious dose increase happens in lunar environment,approaching ten or more mGy in skin.When shielded by Al or water of 10g/cm2,the astronaut's dose could be reduced to mGy or below.Extra energetic protons would observe on station orbit when an SPE with extra-large geomagnetic storm occurs,however when the amount of energetic protons is small,the extra dose is about several 1 nGy to 1 μGy in skin,which was negligible compared with daily dose.When a middle or above level SPE occurs,the influence to astronaut in LEO needs judge immediately,which is mostly based on the geomagnetic activity,but extra shield are needed for manned lunar exploration to ensure astronaut safety.

Objective:To investigate the predictive value of thrombus enhancement (TE) and thrombus permeability in cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.Methods:The clinical and image data of 93 patients with acute middle cerebral artery occlusion who were admitted to the First Affiliated Hospital of Soochow University within 12 hours after onset from January 2020 to July 2022 were retrospectively analyzed. According to the TOAST criteria, the patients were divided into the cardioembolism (CE) group (43 cases) and the large artery atherosclerosis (LAA) group (50 cases). All patients received noncontrast CT and CT angiography, and then thrombus permeability [thrombus attenuation increase (TAI), void fraction (ε)] and TE were assessed. Independent sample t-test, Mann-Whitney U test and χ2 test were used in univariable analysis between two groups. Multivariable logistic regression analysis was used to explore the independent influencing factors for cardioembolic stroke and establish a logistic model. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive value of TAI, ε, TE and the logistic model in cardioembolic thrombus with acute middle cerebral artery occlusion. Results:There were statistically significant differences in sex, atrial fibrillation, hypertension, diabetes mellitus, smoking, baseline National Institutes of health stroke scale (NIHSS), TAI, ε and TE between the CE group and the LAA group ( P<0.05). Binary logistics regression analysis showed that TAI (OR=1.300, 95%CI 1.147-1.473, P<0.001), hypertension (OR=0.116, 95%CI 0.025-0.535, P=0.006) and baseline NIHSS (OR=1.165, 95%CI 1.040-1.304, P=0.008) were independent influencing factors for cardioembolic thrombus. The ROC curve indicated that the logistic model predicted cardioembolic thrombus with the highest AUC of 0.907 (95%CI 0.848-0.966). TE predicted cardioembolic thrombus with the highest sensitivity of 90.7%. Conclusion:TE and thrombus permeability have application value for predicting cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.

Humans ; Coronary Artery Disease/surgery* ; Percutaneous Coronary Intervention ; Heart ; Treatment Outcome ; Coronary Angiography

This paper is intended to analyze the driving force behind and main strategies for innovation and development of individual protective equipment in extreme environments by the U.S.Armed Forces,and outline the current develop-ments and representative achievements of individual protective equipment by the U.S.Armed Forces for environments of high altitude,extreme cold and extreme heat.It is recommended that the top-level design be adopted,physiological modeling and analysis technologies for big data be given more attention,key technologies be innovated,and intelligent,information-based and lightweight new individual medical protective equipment be developed with more effort.