Objective: To analyze the association and dose response relationship between physical activity and inflammatory markers in college students, so as to provide a reference for promoting cardiometabolic health in college students. Methods: A cluster random sampling method was used to select 747 college students from two universities in Hefei, Anhui Province and Shangrao, Jiangxi Province from April to May 2019. Physical activity was assessed by using the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and peripheral blood was collected to detect plasma inflammatory factor levels [including hypersensitive C reactive protein (hsCRP), interleukin-10 (IL-10), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α)]. The differences between the groups were compared by using the χ 2 test and the Kruskal-Wallis rank sum test, and the association between physical activity and inflammatory markers was analyzed by using the Generalized Linear Model. The dose response relationship between physical activity and inflammatory markers was analyzed using the Restricted Cubic Spline Model. Results: The proportions of low physical activity, moderate physical activity, and high physical activity groups of college students were 15.9%, 53.7% and 30.4%, respectively. The levels of hsCRP, IL-10, IL-1β, IL-6 and TNF-α in the high physical activity group were 0.38(0.21, 1.10)mg/L, 70.74(47.90, 116.43)pg/mL, 1.75(1.21, 2.64)pg/mL, 4.33(2.93, 6.82) pg/mL , 5.27(3.89, 7.30)pg/mL,the levels in the low physical activity group were 0.80(0.31, 1.30)mg/L, 73.88 (47.90, 124.24)pg/mL, 1.88(1.42, 2.81) pg/mL, 4.82 (3.64, 6.67) pg/mL, 5.63 (4.34, 7.62)pg/mL, the levels in the moderate physical activity group were 0.63(0.25, 1.30)mg/L, 89.78(58.21, 127.65)pg/mL, 2.21(1.59, 3.27)pg/mL, 5.15( 3.72 , 7.72)pg/mL, 5.87( 4.63 , 8.00)g/mL, and the differences were statistically significant ( H=10.66, 11.38, 27.79, 14.13, 9.44, P <0.05). After adjusting for variables such as gender, body mass index, smoking, alcohol consumption and health status, the results of Generalized Linear Model showed that compared with the high physical activity group, the low physical activity group ( OR=2.20, 95%CI = 1.46- 3.31) and the moderate physical activity group ( OR=1.65, 95%CI =1.22-2.25) were more likely to have high levels of hsCRP, and the moderate physical activity group was more likely to have high levels of IL-1β ( OR=1.85, 95%CI =1.36-2.51), IL-6 ( OR=1.44, 95%CI =1.06-1.96), and TNF-α ( OR=1.43, 95%CI =1.05-1.94) ( P <0.05). The Restricted Cubic Spline Model showed that there was no linear dose response relationship between the time of moderate to vigorous physical activity weekly and IL-10, IL-6, II-1β, and TNF-α ( P <0.05). Conclusion There is an association between physical activity and inflammation in college students, and moderate to high intensity per week could reduce inflammation levels to promote cardiometabolic health in college students.

ObjectiveThis study aims to identify cuproptosis-related gene biomarkers in Alzheimer's disease（AD） using bioinformatics and machine learning methods， validate them at the clinical specimen level， and predict potential traditional Chinese medicine（TCM）. MethodsDifferentially expressed genes in the AD group and normal group were obtained using the Gene Expression Omnibus （GEO） database， and intersections were taken with reported cuproptosis-related genes to obtain differentially expressed cuproptosis-related genes. Machine learning methods were applied to identify core differential genes of cuproptosis in AD. Peripheral blood's single nucleated cells from clinical AD patients were collected， and the relative gene expression was clinically verified by real-time polymerase chain reaction（Real-time PCR）. Potential TCM regulating cuproptosis for AD were predicted by COREMINE database. ResultsA total of 12 cuproptosis-related genes were obtained， mainly involved in pathways of tricarboxylic acid cycle， 2-oxocarboxylic acid metabolism， and carbon metabolism. Five core cuproptosis-related genes， dihydrolipoamide dehydrogenase （DLD）， glutaminase （GLS）， pyruvate dehydrogenase E1 subunit beta （PDHB）， full name nuclear factor （erythroid-derived 2）-related factor 2 （NFE2L2）， and dihydrolipoamide branched-chain transacylase E2 （DBT） were finally screened using four machine methods. Thirty cases each of normal and AD patients were collected clinically. Compared with those in the normal group， minimum mental state examination （MMSE） and Montreal cognitive assessment （MoCA） were significantly decreased in the AD group （P<0.01）， Homocysteine（Hcy）， interleukin（IL）-6， C-reactive protein（CRP） ， and β amyloid protein（Aβ） indexes were significantly increased （P<0.01）， and malondialdehyde（MDA） indexes were decreased （P<0.05）. Superoxide dismutase（SOD） levels were significantly decreased （P<0.01）. The mRNA relative expressions of NFE2L2 and DBT were up-regulated （P<0.05）， and those of DLD， GLS， and PDHB were significantly down-regulated （P<0.01）. The TCM regulating cuproptosis-related genes for the treatment of AD were mainly based on the four Qi such as warmth， calmness， and cold， and the five flavors including bitterness， sweetness， and pungency， and it was attributed to the meridians of the liver， spleen， stomach， and kidney， with the efficacy of tonifying Qi， activating blood， eliminating phlegm， and resoling dampness. ConclusionDLD， GLS， NFE2L2， PDHB， and DBT can be used as novel diagnostic molecular markers for AD cuproptosis-related genes， and the corresponding potential therapeutic TCM can provide new ideas for the treatment of AD by TCM.

Objective To compare the postoperative enhanced recovery outcomes of lobectomy performed under non-intubated video-assisted thoracic surgery (NIVATS) versus intubated video-assisted thoracic surgery (IVATS). Methods Computerized searches were performed in the following databases: China National Knowledge Infrastructure (CNKI), Wanfang Data, VIP Information, China Biomedical Literature Database (CBMdisc), Web of Science, Clinicaltrials.gov, The Cochrane Library, EMbase, and PubMed. We collected randomized controlled trials (RCTs) and observational studies comparing NIVATS and IVATS. The search period extended from the inception of each database to April 1, 2023. Two independent researchers screened the literature and assessed study quality. Results A total of 14 studies were included, comprising 4 RCTs, 7 retrospective cohort studies, and 3 propensity score matching studies, involving 1 840 patients. Meta-analysis results indicated that, compared to IVATS, NIVATS was associated with significantly shorter operative time [MD=–13.39, 95%CI (–20.16, –6.62), P<0.001], shorter length of hospital stay [MD=–0.81, 95%CI (–1.39, –0.22), P=0.005], shorter chest tube duration [MD=–0.73, 95%CI (–1.36, –0.10), P=0.02], shorter postoperative anesthesia recovery time [MD=–20.34, 95%CI (–26.83, –13.84), P<0.001], and shorter time to oral intake after surgery [MD=–5.68, 95%CI (–7.63, –3.73), P<0.001]. Furthermore, NIVATS showed a lower incidence of postoperative airway complications [OR=0.49, 95%CI (0.34, 0.71), P<0.001] and less total chest tube drainage volume [MD=–251.11, 95%CI (–398.25, –103.98), P<0.001], all contributing to significantly accelerated postoperative enhanced recovery for patients. Conclusion NIVATS is a safe and technically feasible anesthesia method in thoracoscopic lobectomy, which can to some extent replace IVATS.

Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

Objective: To explore the longitudinal correlation between smartphone multitasking and depressive symptoms, so as to provide an evidence based basis for promoting the mental health of college students. Methods: A total of 967 college students were recruited from one university in Taiyuan, Chongqing, and Shenzhen cities, China, by using multi stage randomized cluster sampling from October to December 2021 at baseline, and a follow up survey was conducted in May 2022. Smartphone multitasking behaviors were assessed by means of the Assessment of Smartphone Multitasking for Adolescents (ASMA), and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9) among college students. Chi square tests were performed to compare the differences in depressive symptoms between different groups of demographic characteristics, and binary Logistic regression models were employed to analyze the associations between smartphone multitasking and depressive symptoms among college students. Results: The rates of depressive symptoms among college students at baseline and follow up were 35.2% and 42.3%, respectively. Compared to the low level smartphone multitasking index group at baseline, the moderate and high level groups were more likely to experience depressive symptoms at baseline (moderate level group: OR=1.74, 95%CI =1.22-2.50, high level group: OR=2.77, 95%CI =1.94-3.95) and followup (moderate level group: OR=1.41, 95%CI =1.01-1.95, high level group: OR=1.64, 95%CI =1.17-2.29) ( P <0.05). In addition, compared to the persistently low smartphone multitasking index, increased risk of depressive symptoms was associated with maintaining a moderate to high ( OR=2.94, 95%CI =1.83-4.71), and a higher ( OR=2.07, 95%CI =1.31-3.27) or lower smartphone multitasking index ( OR=2.02, 95%CI =1.27-3.19) ( P <0.05). Moreover, higher smartphone multitasking index scores were positively associated with the risk of new-onset depressive symptoms at follow up ( OR=1.87, 95%CI=1.07-3.27, P <0.05). Conclusions Smartphone multitasking behaviors are find to be associated with an increased risk of depressive symptoms in college students. There is a need to reduce smartphone multitasking in order to decrease depressive symptoms and promote students mental health.

Objective: To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students. Methods: A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression. Results: The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05). Conclusions Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.

AIM:The paper is to explore a rapid and simple method for the culture of mouse primary thyroid cells.METHODS:Mouse thyroid cells were isolated by enzyme digestion and cultured with improved medium,and their morphology,characteristics and secretory function were observed within 14 d.RESULTS:In the cultures,the active pri-mary cells were obtained from the thyroid tissue after digestion for 25 min;adherent growth was observed on the 2nd day.And secondary follicles appeared from the 5th to 7th day.Over 95%cells were detected with thyroglobulin.The secretion of total triiodothyronine and total thyroxine maintains over 60%in 7 d.The expression levels of specific genes can still maintain more than 50%in 10 d.CONCLUSION:Mouse thyroid primary cells can be rapidly cultured by this method,and the cells can be used for studying thyroid endocrine secretion within 7 d and studying thyroid genes within 10 d.

Objective To observe the effects of Daizong Prescription on glycogen metabolism in adipose tissue of obese mice;To explore its regulatory mechanism in activating browning in the white adipose tissue.Methods A obesity model was established by feeding high-fat diet to C57BL/6J mice.The obese mice were divided into model group,metformin group(0.15 g/kg),and Daizong Prescription low-(0.20 g/kg)and high-dosage(0.40 g/kg)groups.Mice fed a standard diet were set as the normal group,with 12 mice in each group.Each medication group was given corresponding drugs by gavage for 6 consecutive weeks.Body mass and fasting blood glucose were monitored,serum triglycerides(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),and low-density lipoprotein cholesterol(LDL-C)contents were measured.Brown adipose tissue from the interscapular region and white adipose tissue from the inguinal,perirenal and epididymal region were collected,the adipose tissue mass was measured,and the body fat coefficient was calculated.HE staining was performed to observe morphological changes in adipose tissue,PAS staining was used to observe glycogen distribution in adipose tissue,immunohistochemistry staining was performed to detect the expressions of Gys2,Ppp1r3c,and GSK-3β in inguinal white adipose tissue.Results Compared with the normal group,the body mass and fasting blood glucose in different time points of the model group significant increase(P<0.05,P<0.01),and serum TC and HDL-C contents significantly increased(P<0.01);the mass and body fat coefficient of white adipose tissue in inguinal,perirenal,and epididymis significantly increased(P<0.01),the cells in white adipose tissue in inguinal were hypertrophic and appeared as large vacuoles,with less glycogen accumulation,the expressions of Gys2 and Ppp1r3c significantly decreased(P<0.01).Compared with the model group,the mice in Daizong Prescription high-dosage group showed a significant decrease in body mass and fasting blood glucose at 4 and 6 weeks of administration(P<0.05,P<0.01),and the contents of serum TG,TC,HDL-C,and LDL-C were significantly decreased(P<0.01);the mass and body fat coefficient in white adipose tissue of perirenal and epididymal significantly decreased(P<0.05,P<0.01),and the mass of inguinal white adipose tissue significantly decreased(P<0.05),multiple irregularly shaped small vacuoles could be seen in inguinal white adipose tissue,accompanied by nuclear aggregation and increased glycogen accumulation,the expressions of Gys2 and Ppp1r3c significantly increased(P<0.01).There was no significant difference in the expression of GSK-3β inguinal white adipose tissue of mice among the groups.Conclusion Daizong Prescription can increase the activity of Gys2 by upregulating the expression of Ppp1r3c,promote glycogen synthesis,induce browning of adipose tissue,increase fat heat production,and improve obesity and related disorders of glycolipid metabolism.

Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.

Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.