Objective To understand the present status and explore the influencing factors of quality of life(QOL)among medical students,so as to provide a reference for the improvement of the QOL. Methods A total of 1 898 medical students sampled by stratified cluster sampling method were recruited and investigated by wHO-BREF scale. The influencing factors were assessed by t-test and one-way ANOVA. The data were analyzed by SPSS 19.0. Results Scores of the physical,psychological,social relationship,environmental domain of quality of life were 64.99±13.28,61.85± 13.79,61.58±14.53,and 54.91±13.91,respectively. The results indicated grade,monthly income of family,physical training,quality of sleep and history of trauma were the influencing factors of QOL among medical students,and the differences were all statistically significant(P<0.05). Con?clusion The score of environmental domain of QOL among medical students was the lowest. In order to improve the QOL of medical students, schools should take different measures to them according to different grades or monthly income.

Since the examination of doctor's qualifications came into effect, methods that are set by standard to judge whether one passes the examination or not were in dispute all the while. This article is going to introduce four kinds of methods (Angoff method、Modified Angoff method、Nedelsky method、Borderline group method) which are commonly used at home and abroad. Summarizing their advantages, disadvantages and the usage in the process of standards setting in various countries, we aim to provide reference for setting cutoff score of the examination of doctor's qualifications in China.

Purpose/Significance User portraits of doctors offering free medical advice in online live streaming are constructed and further used to analyze the behavioral characteristics of various types of doctors,so as to provide references for improving the effect of live streaming and their influence.Method/Process A sample of 1 816 doctors who offer free medical advice on the Haodf.com platform is used for clustering analysis to generate different doctor group portraits by using the two-step clustering algorithm.Then an evaluation system for live streaming influence is constructed to explore the differences in online influence among doctors with different styles of live streaming.Result/Conclusion Three types of doctor group portraits are identified,including knowledge-sharing,self-promotional and sociable.There are significant differences in their online influence and three dimensions of live streaming effects including activeness,reputation,and hotness among different doctor groups.Comparative analysis is further performed to find potential solutions for enhancing their live streaming influence.

Aim To study the effect of liraglutide on myocardial metabolites and related metabolic pathways in diabetic cardiomyopathy(DCM)rats.Methods Among 60 SPF male SD rats aged 3 weeks,10 rats were randomly selected as normal control group(n=10),and the remaining 50 rats were established by peritoneal injection of streptozoto-cin combined with high-sugar and high-fat diet for DCM rat model.A total of 36 rats were successfully modeled for DCM and randomly divided into DCM model group(DCM group,n=12),low-dose liraglutide treatment group(LL group,n=12)and high-dose liraglutide treatment group(HL group,n=12).Rats in LL group(100 μg/kg)and HL group(200μg/kg)were given intraperitoneal injection of liraglutide once a day.And after 12 weeks of intervention,the rats were killed under anesthesia after echocardiography to detect cardiac function,and the heart tissues were taken for metabolomics detection.The differential metabolites and related pathways that may be related to liraglutide improving myocardial metab-olism in DCM rats were screened and enriched.Results Compared with normal control group,left ventricular ejection fraction(LVEF)and left ventricular fractional shortening(LVFS)in DCM group were significantly decreased,and the ra-tio of early to late diastolic mitralflow velocities(E/A)was significantly increased(P＜0.05).Compared with DCM group,LVEF and LVFS in LL group and HL group were significantly increased,and E/A ratio was significantly decreased(P＜0.05),suggesting that the impairment of left ventricular systolic and diastolic function in LL group and HL group was significantly alleviated.395 metabolites were detected by metabolomics,among which 239,116 and 187 different metab-olites and 13,6 and 20 metabolic pathways were enriched in DCM group and normal control group,LL group and DCM group,HL group and DCM group.In the above three groups,29 key differential metabolites were identified related to 3 metabolic pathways including choline metabolic pathway,caffeine metabolic pathway and valine,leucine and isoleucine bi-osynthesis pathway,among which choline metabolic pathway had the most significant differences.Conclusion These results indicated that liraglutide can ameliorate cardiac dysfunction in DCM rats through improving myocardial metabolism in which choline metabolism pathway may play a key role.

BACKGROUNDSome research groups have hypothesized that human rhinoviruses (HRVs) delayed the circulation of the 2009 pandemic influenza A(H1N1) virus (A(H1N1)pdm09) at the beginning of Autumn 2009 in France. This study aimed to evaluate the relationship between HRV and A(H1N1)pdm09 in pediatric patients with influenza-like illness in Beijing, China.

METHODSA systematic analysis to detect A(H1N1)pdm09 and seasonal influenza A virus (FLU A) was performed on 4 349 clinical samples from pediatric patients with influenza-like illness during the period June 1, 2009 to February 28, 2010, while a one-step real-time RT-PCR (rRT-PCR) assay was used to detect HRV in 1 146 clinical specimens selected from those 4 349 specimens.

RESULTSDuring the survey period, only one wave of A(H1N1)pdm09 was observed. The percentage of positive cases for A(H1N1)pdm09 increased sharply in September with a peak in November 2009 and then declined in February 2010. Data on the monthly distribution of HRVs indicated that more HRV-positive samples were detected in September (2.2%) and October (3.3%), revealing that the peak of HRV infection in 2009 was similar to that of other years. Among the 1 146 specimens examined for HRVs, 21 (1.8%) were HRV-positive, which was significantly lower than that reported previously in Beijing (15.4% to 19.2%) (P < 0.01). Overall, 6 samples were positive for both A(H1N1)pdm09 and HRV, which represented a positive relative frequency of 1.60% and 2.08% HRV, considering the A(H1N1)pdm09-positive and -negative specimens, respectively. The odds ratio was 0.87 (95% CI 0.32; 2.44, P = 0.80).

CONCLUSIONSHRVs and A (H1N1)pdm09 co-circulated in this Chinese population during September and October 2009, and the HRV epidemic in 2009 did not affect A(H1N1)pdm09 infection rates in Beijing, China as suggested by other studies. However, the presence of A(H1N1)pdm09 might explain the unexpected reduction in the percentage of HRV positive cases during the period studied.

Child ; Child, Preschool ; China ; epidemiology ; Female ; Humans ; Influenza A Virus, H1N1 Subtype ; pathogenicity ; Influenza, Human ; epidemiology ; Male ; Picornaviridae Infections ; epidemiology ; Rhinovirus ; pathogenicity

Background Metals and metalloids in fine particulate matter (PM_2.5) may cause damage to the respiratory and circulatory systems of the human body, and long-term exposure is prone to causing chronic poisoning, cancer, and other adverse effects. Objective To assess the distribution characteristics of metals and metalloids in outdoor PM_2.5 in a southern city of China, conduct source apportionment, and evaluate the associated health risks, thereby providing theoretical support for further pollution control measures. Methods PM_2.5 samples were collected in districts A, B, and C of a southern China city, and the concentrations of 17 metals and metalloids were detected by inductively coupled plasma-mass spectrometry (ICP-MS). Pollution sources were assessed through enrichment factor and principal components analysis, and the main pollution sources were quantified using absolute principal component scores-multivariate linear regression (APCS-MLR). Health risks were evaluated based on the Technical guide for environmental health risk assessment of chemical exposure (WS/T777—2021). Results The ambient air PM_2.5 concentrations in the city were higher in winter and spring, and lower in summer and autumn. The annual average concentrations of ambient PM_2.5 in districts A, B, and C were 36.7, 31.9, and 24.4 μg·m⁻³, respectively. The ambient PM_2.5 levels in districts B and C were below the second-grade limit set by the Ambient air quality standards (GB 3095—2012). The enrichment factors of cadmium (Cd), aluminum (Al), and antimony (Sb) were greater than 10, those of copper (Cu), lead (Pb), arsenic (As), nickel (Ni), mercury (Hg), and molybdenum (Mo) fell between 1 and 10, and those of manganese (Mn), vanadium (V), chromium (Cr), cobalt (Co), barium (Ba), beryllium (Be), and uranium (U) were below or equal to 1. The comprehensive evaluation of source analysis showed that the main pollution sources in districts A and C and the whole city were coal-burning. In district B, the main pollution source was also coal combustion, followed by industrial process sources and dust sources. The carcinogenic risks of As and Cr were between 1×10⁻⁶ and 1×10⁻⁴. However, the hazard quotients for 15 metals and metalloids in terms of non-carcinogenic risk were below 1. Conclusion Cr and As in the atmospheric PM_2.5 of the city present a certain risk of cancer and should be paid attention to. In addition, preventive control measures should be taken against relevant pollution sources such as industrial emission, dust, and coal burning.