The predictive value of estimated pulse wave velocity (ePWV) combined with BMI for newly diagnosed diabetes.

PURPOSE: Estimated pulse wave velocity (ePWV) and body mass index (BMI) are significant predictors of new-onset diabetes. This study aims to evaluate the impact and predictive value of combining ePWV and BMI on the incidence of new-onset diabetes. METHODS: A secondary analysis was conducted on a cohort study by Rich Healthcare (China), involving 211,833 eligible participants. Logistic regression analysis identified factors influencing diabetes occurrence, while ROC curve analysis assessed the predictive value of ePWV, BMI, and their combination for new-onset diabetes. RESULTS: Over a mean follow-up period of 3.12 years, 3,000 men (1.41%) and 1,174 women (0.55%) were diagnosed with diabetes. Logistic regression revealed that BMI, triglycerides, alanine aminotransferase, blood urea nitrogen, creatinine clearance rate, ePWV, and family history of diabetes are high-risk factors for new-onset diabetes. The combination of ePWV and BMI provided a higher area under the ROC curve (0.822) compared to ePWV or BMI alone. CONCLUSION: Elevated levels of ePWV and BMI are independent risk factors for new-onset diabetes. Combining these measures enhances predictive accuracy compared to using either indicator alone.

EVM: Incorporating Model Checking into Exploratory Visual Analysis.

Visual analytics (VA) tools support data exploration by helping analysts quickly and iteratively generate views of data which reveal interesting patterns. However, these tools seldom enable explicit checks of the resulting interpretations of data-e.g., whether patterns can be accounted for by a model that implies a particular structure in the relationships between variables. We present EVM, a data exploration tool that enables users to express and check provisional interpretations of data in the form of statistical models. EVM integrates support for visualization-based model checks by rendering distributions of model predictions alongside user-generated views of data. In a user study with data scientists practicing in the private and public sector, we evaluate how model checks influence analysts' thinking during data exploration. Our analysis characterizes how participants use model checks to scrutinize expectations about data generating process and surfaces further opportunities to scaffold model exploration in VA tools.

[Tissue distribution on methyl nonyl ketone of the volatile oil from Houttyunia cordata in mice].

OBJECTIVE: To study the tissue distribution on methyl nonyl ketone of the volatile oil from Houttuynia cordata in mice in order to provide a guidance for the clinical trial. METHODS: The concentrations of the volatile oil from Houttuynia cordata in biological samples were determined by GC method. RESULTS: After a single oral dose of 5.0 g/kg volatile oil from Houttuynia cordata in mice, parent drug was mainly distributed in windpipe, intesting, liver, kidney, heart, blood, spleen, lung, brain, muscle; after 7 hours, parent drug of every tissue decreased over 90%. CONCLUSION: Parent drug mianly distributes in windpipe, intestine, liver, kidney. The experiment provides pharmacokinetic evidence for the rational administration and the further development of Houttuynia cordata.