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A steady rise in fires in the Western United States, coincident with intensifying droughts, imparts substantial modifications to the underlying vegetation, hydrology and overall ecosystem. Drought can compound the ecosystem disturbance caused by fire, although how these compound effects on hydrologic and ecosystem recovery vary among ecosystems is poorly understood. Here we use remote sensing-derived high-resolution evapotranspiration (ET) estimates from before and after 1,514 fires to show that ecoregions dominated by grasslands and shrublands are more susceptible to drought, which amplifies fire-induced ET decline and, subsequently, shifts water flux partitioning. In contrast, severely burned forests recover from fire slowly or incompletely, but are less sensitive to dry extremes. We conclude that moisture limitation caused by droughts influences the dynamics of water balance recovery in post-fire years. This finding explains why moderate to extreme droughts aggravate impacts on the water balance in non-forested vegetation, while moisture accessed by deeper roots in forests helps meet evaporative demands unless severe burns disrupt internal tree structure and deplete fuel load availability. Our results highlight the dominant control of drought on altering the resilience of vegetation to fires, with critical implications for terrestrial ecosystem stability in the face of anthropogenic climate change in the West., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: There is limited concrete evidence connecting serum uric acid levels to female infertility. Therefore, this study aimed to find out if serum uric acid levels are independently related to female infertility., Methods: From the National Health and Nutrition Examination Survey (NHANES) 2013-2020, a total sample of 5872 chosen female participants between the ages of 18 and 49 were identified for this cross-sectional study. The serum uric acid levels (mg/dL) of each participant were tested, and the reproductive health questionnaire was used to evaluate each subject's reproductive status. Both in the analyses of the full sample and each subgroup, logistic regression models were used to evaluate the relationship between the two variables. A stratified multivariate logistic regression model was used to perform the subgroup analysis based on serum uric acid levels., Results: Infertility was found in 649 (11.1%) of the 5,872 female adults in this study, with greater mean serum uric acid levels (4.7 mg/dL vs. 4.5 mg/dL). Serum uric acid levels were associated with infertility in both the initial and adjusted models. According to multivariate logistic regression, the odds of female infertility were found to be significantly higher with rising serum uric acid levels (Q4 [≥ 5.2 mg/dL] vs. Q1 [≤ 3.6 mg/dL]), adjusted odds ratio [aOR] = 1.59, p = 0.002]. The data suggests that there is a dose-response relationship between the two., Conclusions: The results from this nationally representative sample from the United States confirmed the idea that there is a link between increased serum uric acid levels and female infertility. Future research is necessary to evaluate the relationship between serum uric acid levels and female infertility and explicate the underlying mechanisms of this relationship., (© 2023. The Author(s).)

Clinical studies are very dynamic in nature. This poses a great challenge in building an adaptable informatics platform to support evolving clinical research needs. Center for Information Technology (CIT) at the National Institutes of Health (NIH), in collaboration with the National Institute of Neurological Disorders and Stroke (NINDS), has developed a web-based Clinical Study Information System (CSIS) to support efficient management of clinical data that would improve the quality and timeliness of conducting clinical research. CSIS allows Principal Investigators(PI) to design new electronic Case Report Forms(eCRF) using a Form Designer. A patient registry module enables the study coordinators to recruit and screen new subjects. Most importantly, an ad-hoc query engine allows investigators to stratify patient groups and export data by specifying arbitrarily complex criteria without having to learn database syntax.