Low Serum Magnesium Level Is Associated with Microalbuminuria in Chinese Diabetic Patients

Whether serum magnesium deficiency is independently associated with the prevalence of microalbuminuria is still unclear. The objective of the present study was to elucidate the association between serum magnesium and microalbuminuria in diabetic patients. A cross-sectional study was conducted in 1829 diabetic subjects (aged ≥ 40 years) from Shanghai, China. Subjects were divided into three groups according to serum magnesium tertiles. A first-voided early-morning spot urine sample was obtained for urinary albumin-creatinine ratio (UACR) measurement. Microalbuminuria was defined as 30 mg/g ≤ UACR < 300 mg/g. Overall, 208 (11.37%) of the study population had microalbuminuria, with similar proportions in both genders (). The prevalence of microalbuminuria in tertile 1 of serum magnesium was higher than the prevalence in tertile 2 and tertile 3 (15.98%, 9.72%, and 8.46%, resp.; for trend <0.0001). After adjustment for age, sex, BMI, blood pressure, lipidaemic profile, HbA1c, eGFR, history of cardiovascular disease, HOMA-IR, antihypertensive and antidiabetic medication, and diabetes duration, we found that, compared with the subjects in tertile 3 of serum magnesium, those in tertile 1 had 1.85 times more likeliness to have microalbuminuria. We concluded that low serum magnesium level was significantly associated with the prevalence of microalbuminuria in middle-aged and elderly Chinese

Human respiratory syncytial virus subgroups A and B outbreak in a kindergarten in Zhejiang Province, China, 2023

BackgroundIn May–June 2023, an unprecedented outbreak of human respiratory syncytial virus (HRSV) infections occurred in a kindergarten, Zhejiang Province, China. National, provincial, and local public health officials investigated the cause of the outbreak and instituted actions to control its spread.MethodsWe interviewed patients with the respiratory symptoms by questionnaire. Respiratory samples were screened for six respiratory pathogens by real-time quantitative polymerase chain reaction (RT-PCR). The confirmed cases were further sequenced of G gene to confirm the HRSV genotype. A phylogenetic tree was reconstructed by maximum likelihood method.ResultsOf the 103 children in the kindergarten, 45 were classified as suspected cases, and 25 cases were confirmed by RT-PCR. All confirmed cases were identified from half of classes. 36% (9/25) were admitted to hospital, none died. The attack rate was 53.19%. The median ages of suspected and confirmed cases were 32.7 months and 35.8 months, respectively. Nine of 27 confirmed cases lived in one community. Only two-family clusters among 88 household contacts were HRSV positive. A total of 18 of the G gene were obtained from the confirmed cases. Phylogenetic analyses revealed that 16 of the sequences belonged to the HRSV B/BA9 genotype, and the other 2 sequences belonged to the HRSV A/ON1 genotype. The school were closed on June 9 and the outbreak ended on June 15.ConclusionThese findings suggest the need for an increased awareness of HRSV coinfections outbreak in the kindergarten, when HRSV resurges in the community after COVID-19 pandemic

The Image of China in a BBC Documentary and Chinese Audiences\u27 Reception of it: The Case of The Chinese Are Coming

China’s economic rise has led to competing images of the nation-state in the world’s media. Chinese audiences, for their part, are increasingly concerned with how the foreign media represent China. Against this background and taking into consideration the well-known reputation of BBC documentary film as one of the most authoritative Western media genres, this paper examines the 2011 BBC documentary film The Chinese Are Coming’s portrayal of China and its reception by selected graduate students at the Communication University of China and commentators at three online Chinese forums. The first part uses content analysis to break down the film into segments and examines its content in terms of seven subject areas and a series of key events, with a particular focus on the different tones of their treatment. It discovers that while a majority of the content is presented in a neutral tone, the film does contain one-sided representations of China’s global economic activities and thus contributes to the construction of a negative image of China. The reception analysis is equally mixed. Some audience members believe that The Chinese Are Coming is a media product that stigmatizes China on purpose. However, along with a minority of student interviewees and online commentators, I argue that the Chinese audience should take this film as an opportunity to reflect upon their government’s global strategies and foreign policies

A precise theoretical method for high- throughput screening of novel organic electrode materials for Li-ion batteries

Organic electrode materials have gained significant attention due to their flexibility, lightweight characteristics, abundant resources in nature, and low CO2 emission. It's urgently needed for setting up an accurate high-throughput screening theoretical scheme that could find out possible candidates of electrode materials. Currently, the error between the theoretical potentials calculated by the PBE-D2 (DFT-D2, dispersion-corrected density functional theory) method and the experimental values is larger than 12%. Thus, it's essential to finding a more accurate method. In the present work, hybrid functionals and vdW correction methods are applied to investigate six reported organic electrode materials for Li-ion batteries. The results show that the hybrid functional combined with the D2 dispersion corrected method, i.e., HSE06-D2 (Heyd, Scuseria, and Ernzerhof, dispersion-corrected), is able to predict the potential of the organic material precisely with an average error of approximately 5%. This method occupies much hardware resources and being very time consuming, but it could be applied as the final ultrafine step in the high-throughput screening program

Explainable Machine-Learning Predictions for Peak Ground Acceleration

Peak ground acceleration (PGA) prediction is of great significance in the seismic design of engineering structures. Machine learning is a new method to predict PGA and does have some advantages. To establish explainable prediction models of PGA, 3104 sets of uphole and downhole seismic records collected by the KiK-net in Japan were used. The feature combinations that make the models perform best were selected through feature selection. The peak bedrock acceleration (PBA), the predominant frequency (FP), the depth of the soil when the shear wave velocity reaches 800 m/s (D800), and the bedrock shear wave velocity (Bedrock Vs) were used as inputs to predict the PGA. The XGBoost (eXtreme Gradient Boosting), random forest, and decision tree models were established, and the prediction results were compared with the numerical simulation results The influence between the input features and the model prediction results were analyzed with the SHAP (SHapley Additive exPlanations) value. The results show that the R2 of the training dataset and testing dataset reach up to 0.945 and 0.915, respectively. On different site classifications and different PGA intervals, the prediction results of the XGBoost model are better than the random forest model and the decision tree model. Even if a non-integrated algorithm (decision tree model) is used, its prediction effect is better than the numerical simulation methods. The SHAP values of the three machine learning models have the same distribution and densities, and the influence of each feature on the prediction results is consistent with the existing empirical data, which shows the rationality of the machine learning models and provides reliable support for the prediction results

Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007-2018.

BackgroundHemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS.ObjectiveHuludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City.MethodsOur researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007-2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors.ResultsDuring the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04-2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31-5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01-1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01-1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00-1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02-1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02-1.76), -9 degrees Celsius (1.37, 95% CI: 1.04-1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03-1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level.ConclusionsOur study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius

Estimation of Layered Ground Thermal Properties for Deep Coaxial Ground Heat Exchanger

A ground heat exchanger (GHE) can efficiently exploit geothermal energy, and a ground source heat pump (GSHP) is an important type of geothermal application. The distributed thermal response test (DTRT) is widely used to measure layered ground thermal properties for shallow GHEs, but nowadays, there is a lack of studies applying the DTRT to deep coaxial GHEs (DCGHEs). This study proposes a new parameter estimation method (PEM) by adopting the DTRT data of a DCGHE to estimate layered ground thermal properties and applies the proposed PEM to simulated DTRTs under different boundary conditions, and the estimated values of the layered ground thermal properties are compared with the true values. Under heat output rate or inlet temperature boundary conditions, the relative errors of the thermal conductivities and heat capacities of ground estimated using the proposed PEM are basically within 2% and 4%, respectively, except for shallower layers with a depth range of 0–800 m. The larger errors for shallower layers may be caused by weaker heat transfer between the fluid and ground, and the errors are basically lower for higher heat output rates. The predicted fluid temperature distributions during 120 d using the estimated values of the layered ground thermal properties match well with those using the true values. The results show that the proposed PEM is viable for DCGHE DTRT interpretation under heat output rate and inlet temperature boundary conditions, is a cost-effective way to establish key parameters for GSHP design, and would promote geothermal development