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Background: Diabetic kidney disease (DKD) is a prevalent complication of diabetes and the leading cause of end-stage renal disease. Recent evidence suggests that total flavonoids of Astragalus (TFA) has promising effects on diabetes; however, its influence on DKD and the underlying mechanism remains unclear. Methods: In this study, we induced the DKD model using streptozotocin (STZ) in male C57BL/6J mice and utilized glomerular endothelial cell (GEC) lines for in vitro investigations. We constructed a network pharmacology analysis to understand the mechanism of TFA in DKD. The mechanism of TFA action on DKD was investigated through Western blot analysis and multi-immunological methods. Results: Our findings revealed that TFA significantly reduced levels of urinary albumin (ALB). Network pharmacology and intracellular pathway experiments indicated the crucial involvement of the PI3K/AKT signaling pathway in mediating these effects. In vitro experiments showed that TFA can preserve the integrity of the glomerular filtration barrier by inhibiting the expression of inflammatory factors TNF-alpha and IL-8, reducing oxidative stress. Conclusion: Our findings demonstrated that TFA can ameliorates the progression of DKD by ameliorating renal fibrosis and preserving the integrity of the kidney filtration barrier. These results provide pharmacological evidence supporting the use of TFA in the treatment of kidney diseases. [ABSTRACT FROM AUTHOR]

This article reports a mixed-methods study about using virtual reality (VR) tools (Google Cardboard and Expeditions) for developing students' oral proficiency in learning Chinese as a second language. Twelve students role-played as tour guides for six locations throughout a semester: four of them with VR tools and two without. Data collection included oral presentations recorded at four different times of the semester (for Presentations 1, 3, 4, and 6), class observations, participants' reflection papers, and individual interviews at the end of the semester. Results revealed that the content and vocabulary of participants' oral presentations when using VR tools scored statistically significantly higher than when not using VR tools. Qualitative data showed that participants felt that VR tools facilitated preparation and encouraged active learning. [ABSTRACT FROM AUTHOR]

The practice of dispensing free samples has been widely adopted by US pharmaceutical companies. Despite physicians' significant gatekeeper-and decision-maker role in dispensing samples, very few studies in the pharmaceutical marketing literature have empirically examined physicians' free-sample dispensing decisions or their influence on future prescription decisions. The primary objective of this article is to fill the gap in the literature by examining the key determinants in physician sample-dispensing and quantity decisions at the individual-physician level while controlling for targeted marketing activities and unobserved physician heterogeneity. We conceptualize the dual roles of drug samples, experimentation and subsidy, in physicians' prescription decision making, empirically test for the existence of these dual roles, and quantify their long-run sales impact using physician panel data from two therapeutic categories. Our analysis yields strong empirical support for the existence of the dual roles in physician sample-dispensing behavior. Finally, we discuss implications of our findings for pharmaceutical managers and policymakers. [ABSTRACT FROM AUTHOR]

We model the length of time that it takes for a patent application to be granted by the US Patent and Trademark Office (USPTO), conditional on the patent actually being awarded eventually. Survival analysis is applied and both the nonparametric Kaplan-Meier and parametric accelerated failure time models are used to analyse the data. We find that the number of claims a patent makes, the number of citations a patent makes, the patent's technological category, and the type of applicant all have significant effects on the duration that a patent is under consideration. A log-normal survival model is the preferred parametric specification, and the results suggest that the hazard function is nonmonotonic over time. [ABSTRACT FROM AUTHOR]

Analyzes individual airborne particles using a computer-controlled scanning electron microscope (CCSEM). Particle class balance (PCB) model; Data description; Application of an adaptive resonance theory (ART) neural network; Significance of the study.

Background: The triglyceride-glucose (TyG) index and estimated glucose disposal rate (eGDR), which are calculated using different parameters, are widely used as markers of insulin resistance and are associated with cardiovascular diseases and prognosis. However, whether they have an additive effect on the risk of mortality remains unclear. This study aimed to explore whether the combined assessment of the TyG index and eGDR improved the prediction of long-term mortality in individuals with and without diabetes., Methods: In this cross-sectional and cohort study, data were derived from the National Health and Nutrition Examination Survey (NHANES) 2001-2018, and death record information was obtained from the National Death Index. The associations of the TyG index and eGDR with all-cause and cardiovascular mortality were determined by multivariate Cox regression analysis and restricted cubic splines., Results: Among the 17,787 individuals included in the analysis, there were 1946 (10.9%) all-cause deaths and 649 (3.6%) cardiovascular deaths during a median follow-up of 8.92 years. In individuals with diabetes, the restricted cubic spline curves for the associations of the TyG index and eGDR with mortality followed a J-shape and an L-shape, respectively. The risk of mortality significantly increased after the TyG index was > 9.04 (all-cause mortality) or > 9.30 (cardiovascular mortality), and after eGDR was < 4 mg/kg/min (both all-cause and cardiovascular mortality). In individuals without diabetes, the association between eGDR and mortality followed a negative linear relationship. However, there was no association between the TyG index and mortality. Compared with individuals in the low TyG and high eGDR group, those in the high TyG and low eGDR group (TyG > 9.04 and eGDR < 4) showed the highest risk for all-cause mortality (hazard ratio [HR] = 1.592, 95% confidence interval [CI] 1.284-1.975) and cardiovascular mortality (HR = 1.683, 95% CI 1.179-2.400) in the overall population. Similar results were observed in individuals with and without diabetes., Conclusions: There was a potential additive effect of the TyG index and eGDR on the risk of long-term mortality in individuals with and without diabetes, which provided additional information for prognostic prediction and contributed to improving risk stratification., (© 2024. The Author(s).)