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Rainfall evolution and diurnal variation are important components in the North American monsoon system (NAMS). In this study these components are numerically studied using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) with high resolution (12-km grids) in contrast to most previous model studies that used relatively coarse spatial resolutions (>25 km grids). The model was initialized at the start of each month and allowed to run for 31 days. The study shows that, in general, the model results broadly matched the patterns of satellite-retrieved rainfall data for monthly rainfall accumulation. The rainfall timing evolution in the monsoon core region predicted by the model generally matched the gauge observations. However, the differences among the three precipitation estimates (model, satellite, and gauge) are obvious, especially in July. The rainfall diurnal cycle pattern was reproduced in the monsoon core region of western Mexico, but there were differences in the diurnal intensity and timing between modeled and observed results. Furthermore, the model cannot capture the diurnal variation over Arizona. Modeling results showed heavy monsoon rains shift northward along the western Mexico coast in association with the northward evolution of the subtropical highs. This is consistent with previous data analyses. The rainfall diurnal cycle was associated mainly with sea–land/mountain–valley circulations over western Mexico and adjacent oceans. The simulations show that the model has deficiencies in predicting precipitation over the Gulf of Mexico. The model cannot reproduce the low-level inversion above the marine boundary layers and thus does not generate enough convective inhibition (CIN) to suppress the convection. The model also cannot produce realistic variations of day-to-day atmospheric conditions with only a single initialization at the start of the month. [ABSTRACT FROM AUTHOR]

Background: Children in foster care are classified as a highly vulnerable population and struggle with both physical and mental health problems. Medical conditions, like poor nutritional status, remain understudied in children in foster care. To our knowledge, few studies in children in U.S. foster care have quantified the prevalence of anemia, and no studies have examined the association between anemia status and relevant developmental and behavioral outcomes., Objective/aims: (1) To determine the prevalence of anemia among children in or adopted from Pennsylvania foster care, between the ages of six months to ten years and (2) To examine if a child's anemia status is associated with greater odds of relevant developmental and behavioral diagnoses., Methods: We conducted a secondary data analysis utilizing the Medicaid Analytic eXtract database between 2010-2015. Children six months-ten years were included in the analysis if they were in or had been adopted from Pennsylvania foster care. Logistic regression was used to calculate adjusted odds ratios (AOR) with 95% confidence intervals for the association between iron status and health outcomes., Results: A total of 50,311 children were included in our sample, of which 1,365 children (2.7%) were diagnosed with anemia. Children diagnosed with anemia had greater odds of delayed milestones (AOR: 2.38 [1.64-3.45]), specific delays in development (AOR: 1.59 [1.23-2.07]), adjustment disorder (AOR: 1.59 [1.06-2.39]), and irritability (AOR: 10.57 [3.36-33.25]), than children not diagnosed with anemia., Conclusion: The prevalence of anemia among children between six months-ten years in or adopted from the Pennsylvania foster care system is within the national rate of U.S. childhood anemia. Odds of several relevant developmental and behavioral diagnoses were greater among children diagnosed with anemia than children who were not., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Arcot et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Several dietary components have been shown to be neuroprotective against risk of neurodegeneration. However, limited observational studies have examined the role of overall diet quality on risk of Parkinson's disease., Objectives: We examined the associations between diet quality and risk of Parkinson's disease in a prospective cohort study and meta-analysis., Methods: Included in the cohort study were 3,653 participants (1,519 men and 2,134 women; mean age: 81.5 years) in the Geisinger Rural Aging Study longitudinal cohort in Pennsylvania. Diet quality was assessed using a validated dietary screening tool containing 25 food- and behavior-specific questions in 2009. Potential Parkinson's cases were identified using electronic health records based on ICD9 (332.*), ICD10 (G20), and Parkinson-related treatments. Hazard ratios (HRs) and 95% confidence intervals (CIs) across diet quality tertiles were calculated using Cox proportional hazards models after adjusting for potential confounders. We further performed a meta-analysis by pooling our study with four published papers on this topic. Random-effects model was utilized to calculate the pooled risk ratios and 95% CIs., Results: During a mean of 6.94 years of follow-up, 47 incident Parkinson's cases were documented. Having high diet quality at baseline was associated with lower Parkinson's disease risk (adjusted HR for the highest vs the lowest diet quality tertile = 0.39; 95% CI: 0.17, 0.89; p-trend = 0.02). The meta-analysis including 140,617 individuals also showed that adherence to high diet quality or a healthy dietary pattern was associated with lower risk of Parkinson's disease (pooled risk ratio = 0.64; 95% CI: 0.49, 0.83)., Conclusion: Having high diet quality or a healthy dietary pattern was associated with lower future risk of Parkinson's disease.

Background and Purpose: Perioperative stroke remains a devastating complication after cardiac surgery and is associated with significant morbidity and mortality. Despite the significant contribution of stroke to perioperative mortality, risk factors for perioperative stroke-related mortality have not been well characterized. Our aim was to identify independent predictors of perioperative stroke-related mortality after cardiac surgery, using the Pennsylvania Health Care Cost Containment Council (PHC4) database which provides information on cause of death., Methods: We retrospectively examined patient medical records from 2012 to 2014 of 3345 patients (ages 18-99) who underwent a cardiac surgical procedure and suffered perioperative (30-day) mortality. Perioperative stroke-related mortality was identified by International Classification of Diseases, Tenth Revision, Clinical Modification cause of death codes. We performed Fisher's exact test and multivariate analysis to identify comorbidities that independently predict perioperative stroke-related mortality., Results: After controlling for all variables with multivariate analysis, we found that patients with carotid stenosis were 4.9 (adjusted odds ratio [aOR], 95% confidence interval [CI] 1.8-12.8) times more likely to die from a stroke than from other causes, when compared to patients without carotid stenosis. Other independent predictors of perioperative stroke-related mortality included in-hospital stroke (aOR 108.8, 95%CI 48.2-245.9), history of stroke (aOR 17.1, 95%CI 3.3-88.4), and age ≥ 80 (aOR 4.9, 95%CI 2.1-11.2)., Conclusions: This is the first study to establish carotid stenosis, among other comorbidities, as an independent predictor of perioperative stroke-related mortality after cardiac surgery. Understanding risk factors for mortality from stroke will help enhance the efficacy of preoperative screening, intraoperative neurophysiological monitoring, and potential treatments for stroke. Interventions to manage carotid stenosis and other identified risk factors prior to, during, or immediately after surgery may have the potential to reduce perioperative stroke-related mortality after cardiac surgery., Competing Interests: Conflict of Interest None., (Copyright © 2020. Published by Elsevier Inc.)

The oldest old (aged ≥80 years) are often the population subgroup at high nutritional risk due to age-related metabolic changes. We performed a validation analysis of a dietary screening tool (DST) which was developed for older adults among the oldest old. We examined dietary intakes using three 24-hour dietary recalls and the DST among 122 participants (aged 82-97) of the Geisinger Rural Aging Study. DST scores were compared with the Health Eating Index (HEI)-2015 scores, which were calculated based on three-day dietary recalls. Pearson correlations were used to characterize concurrent validity and Bland-Altman plots were used to identify potential bias. DST scores were significantly correlated with HEI scores (adjusted r = 0.68; p < 0.001) in an age- and sex-adjusted model. Those within the not-at-risk DST group had significantly higher HEI scores (adjusted means = 79.6 ± 3.68) compared with those who were in the at-risk (adjusted means = 51.2 ± 1.56) and the possibly-at-risk (adjusted means = 66.3 ± 1.79) groups (p-trend < 0.001). The DST appears to be a valid measure of diet quality in the oldest old when compared with the HEI and may be a potential tool to assess overall diet quality in this population.