A feature optimization study based on a diabetes risk questionnaire

IntroductionThe prevalence of diabetes, a common chronic disease, has shown a gradual increase, posing substantial burdens on both society and individuals. In order to enhance the effectiveness of diabetes risk prediction questionnaires, optimize the selection of characteristic variables, and raise awareness of diabetes risk among residents, this study utilizes survey data obtained from the risk factor monitoring system of the Centers for Disease Control and Prevention in the United States.MethodsFollowing univariate analysis and meticulous screening, a more refined dataset was constructed. This dataset underwent preprocessing steps, including data distribution standardization, the application of the Synthetic Minority Oversampling Technique (SMOTE) in combination with the Round function for equilibration, and data standardization. Subsequently, machine learning (ML) techniques were employed, utilizing enumerated feature variables to evaluate the strength of the correlation among diabetes risk factors.ResultsThe research findings effectively delineated the ranking of characteristic variables that significantly influence the risk of diabetes. Obesity emerges as the most impactful factor, overshadowing other risk factors. Additionally, psychological factors, advanced age, high cholesterol, high blood pressure, alcohol abuse, coronary heart disease or myocardial infarction, mobility difficulties, and low family income exhibit correlations with diabetes risk to varying degrees.DiscussionThe experimental data in this study illustrate that, while maintaining comparable accuracy, optimization of questionnaire variables and the number of questions can significantly enhance efficiency for subsequent follow-up and precise diabetes prevention. Moreover, the research methods employed in this study offer valuable insights into studying the risk correlation of other diseases, while the research results contribute to heightened societal awareness of populations at elevated risk of diabetes

The Impact of Sediment–Water Ratio and Hydraulic Residence Time on the Release of Inorganic Nitrogen from Sediments in the Pearl River Delta

Black-odorous water bodies in the Pearl River Delta have been treated. However, the re-release of nitrogen (N)-containing compounds in sediment can cause a relapse of black-odorous water bodies. Sediment–water ratio (SWR) and hydraulic residence time (HRT) influence pollutant release. Therefore, how to control SWR and HRT during the treatment process has become an urgent problem. This study focuses on the dynamic release of endogenous inorganic N from sediments into overlying water in a river channel of Dongguan City, Guangdong Province. Physicochemical parameters (dissolved inorganic nitrogen (DIN), NH4+-N, NO3−-N, NO2−-N, dissolved oxygen (DO), pH, oxidation-reduction potential (ORP), chemical oxygen demand (COD), Fe and total phosphorus (TP)) of overlying water were monitored under different SWRs (0.71, 0.38, and 0.16) and HRTs (13 days and 6.5 days), and the nitrogen release flux under different conditions was compared. Finally, the correlation and influence pathways among environmental factors were analyzed. The results showed that SWR significantly affected DO, pH, ORP, and sediment N release fluxes while prolonging HRT-promoted denitrification. DIN → NO2−-N → DO pathway had a total effect of 19.6%, and DIN may promote low DO concentration via NO2− oxidation. Maintaining reasonable SWR and HRT can reduce the release of inorganic N from sediment into the overlying water. This study provides a theoretical basis for controlling black-odorous water bodies

Effects of Air Pollution Exposure during Preconception and Pregnancy on Gestational Diabetes Mellitus

This study aimed to investigate the association between air pollution and gestational diabetes mellitus (GDM) in small- and medium-sized cities, identify sensitive periods and major pollutants, and explore the effects of air pollution on different populations. A total of 9820 women who delivered in Handan Maternal and Child Health Hospital in the Hebei Province from February 2018 to July 2020 were included in the study. Logistic regression and principal component logistic regression models were used to assess the effects of air pollution exposure during preconception and pregnancy on GDM risk and the differences in the effects across populations. The results suggested that each 20 μg/m3 increase in PM2.5 and PM10 exposure during preconception and pregnancy significantly increased the risk of GDM, and a 10 μg/m3 increase in NO2 exposure during pregnancy was also associated with the risk of GDM. In a subgroup analysis, pregnant women aged 30–35 years, nulliparous women, and those with less than a bachelor’s education were the most sensitive groups. This study provides evidence for an association between air pollution and the prevalence of GDM, with PM2.5, PM10, and NO2 as risk factors for GDM

Quiescin-sulfhydryl oxidase inhibits prion formation <i>in vitro</i>

International audiencePrions are infectious proteins that cause a group of fatal transmissible diseases in animals and humans. The scrapie isoform (PrPSc) of the cellular prion protein (PrPC) is the only known component of the prion. Several lines of evidence have suggested that the formation and molecular features of PrPSc are associated with an abnormal unfolding/refolding process. Quiescin-sulfhydryl oxidase (QSOX) plays a role in protein folding by introducing disulfides into unfolded reduced proteins. Here we report that QSOX inhibits human prion propagation in protein misfolding cyclic amplification reactions and murine prion propagation in scrapie-infected neuroblastoma cells. Moreover, QSOX preferentially binds PrPSc from prion-infected human or animal brains, but not PrPC from uninfected brains. Surface plasmon resonance of the recombinant mouse PrP (moPrP) demonstrates that the affinity of QSOX for monomer is significantly lower than that for octamer (312 nM vs 1.7 nM). QSOX exhibits much lower affinity for N-terminally truncated moPrP (PrP89-230) than for the full-length moPrP (PrP23-231) (312 nM vs 2 nM), suggesting that the N-terminal region of PrP is critical for the interaction of PrP with QSOX. Our study indicates that QSOX may play a role in prion formation, which may open new therapeutic avenues for treating prion diseases