Raymondmaxwell5959

The findings supported a six-factor structure of the PCI-A in the current study for collegiate student-athletes compared to the seven-factor structure indicated in previous research. The findings reveal sex and concussion risk sport differences in PCI-A responses.Background Advance care planning (ACP) is recommended to align treatment with patient goals, although there has been little study of the impact of ACP on in-hospital stroke treatment. Objective To examine the association between ACP and transitions to comfort measures after stroke. Design Prospective cohort study. Setting/Subjects Hospitalized stroke patients 45 years and older and surrogate decision makers from a population-based study in Corpus Christi, TX. Measurements Surrogates were interviewed to assess presence of patient prestroke ACP, categorized as none, informal conversations only, or formal documentation. Patient records were reviewed for time from admission to transition to comfort measures only (CMO) (defined as in-hospital comfort measures or discharge with hospice services). Cox proportional-hazards models assessed the relationship between ACP and time to transition to CMO. Results Of 148 included stroke patients, 37% transitioned to CMO (median time five days). For ACP, 44% had only informal conversations, 38% had formal documentation (98% of which also reported informal conversations), and 18% had neither. After adjustment for age, severity, and baseline disability, informal conversations alone (hazard ratio [HR] 3.55; 95% confidence interval [CI] 1.35-9.33) and formal documentation (HR 2.85; 95% CI 1.05-7.72) were associated with earlier transition to comfort measures compared to no ACP. There was no difference between formal documentation and informal conversations on time to comfort measures (HR 0.80, 95% CI 0.40-1.63). Conclusions There was no additional association of formal ACP documentation over informal conversations on time to transition to comfort measures after stroke. Further study of formal ACP is warranted.The number of diabetes mellitus and borderline diabetes cases is increasing and poses a serious problem worldwide. Plants of the genus Salacia are known to have α-glucosidase inhibitory activity and to lower postprandial hyperglycemia. Two randomized, double-blind, placebo-controlled clinical trials were conducted to evaluate the efficacy of Salacia chinensis extract. Study 1 was a single-dose crossover study of 150, 300, or 600 mg of Salacia extract or placebo to determine the dose dependency of the effect on postprandial hyperglycemia. The duration of the washout period between each experimental day was a minimum of 6 days. Study 2 was a 12-week, multiple-dose, parallel-group study to evaluate the effects of 600 mg/day of Salacia extract on blood glucose parameters. In Study 1, Salacia induced significant dose-dependent suppression of postprandial blood glucose, insulin, and their incremental area under the curve values. The dose of 600 mg appeared to have the most significant effect. In Study 2, Salacia significantly improved several blood glucose-related parameters, such as hemoglobin A1c, and glucose tolerance after glucose challenge. These results suggest that S. chinensis extract may have beneficial effects in patients with diabetes.Background The purpose of this study was to evaluate the effectiveness of a 10-week blended family-based childhood obesity management program, relative to a wait-list control, in improving child body mass index (BMI) z-scores, child lifestyle behaviors, parental support for healthy eating and physical activity, and self-regulation for healthy eating and physical activity support. Methods This study was registered as a randomized wait-listed controlled trial; however, due to low recruitment and program delivery logistics, this study transitioned into a quasi-experimental design. Families with children 8-12 years of age with a BMI ≥85th percentile for age and sex were recruited (October 2018 to March 2019) in British Columbia, Canada. The intervention provided families 10 weeks of in-person and online support on improving lifestyle behaviors. Results Children's BMI z-scores were not significantly changed. Intervention group significantly improved their days of moderate-to-vigorous physical activity relative to control (0.75 ± 1.5; p  less then  0.01; ηp2 = 0.15); however, child dietary behaviors were not significantly changed. Relative to control, intervention group showed significant improvements in parental support for healthy eating (0.13 ± 0.36; p  less then  0.05; ηp2 = 0.06) and physical activity (1.0 ± 1.6; p  less then  0.05; ηp2 = 0.09) and self-regulation for healthy eating (2.0 ± 3.5; p  less then  0.01; ηp2 = 0.11) and physical activity support (2.0 ± 3.2; p  less then  0.05; ηp2 = 0.28). Conclusions Preliminary evidence showed that the intervention was not effective in improving child BMI z-scores, but it was effective in promoting children's physical activity and parents' support behaviors. A longer study period may be required to change BMI z-scores. Clinical Trial Registration number NCT03643341.Computational techniques have been successful at predicting protein function from relational data (functional or physical interactions). These techniques have been used to generate hypotheses and to direct experimental validation. With few exceptions, the task is modeled as multilabel classification problems where the labels (functions) are treated independently or semi-independently. However, databases such as the Gene Ontology provide information about the similarities between functions. learn more We explore the use of the Metric Labeling combinatorial optimization problem to make use of heuristically computed distances between functions to make more accurate predictions of protein function in networks derived from both physical interactions and a combination of other data types. To do this, we give a new technique (based on convex optimization) for converting heuristic semimetric distances into a metric with minimum least-squared distortion (LSD). The Metric Labeling approach is shown to outperform five existing techniques for inferring function from networks.