Search

Danger-associated molecular patterns (DAMPs) may be implicated in the pathophysiological pathways associated with an unfavorable outcome after acute brain injury (ABI)., SCOPUS: ar.j, info:eu-repo/semantics/published

Background: Obesity is a major public health issue in the United States (U.S.), affecting an estimated 78 million US adults. Aerobic exercise (AE) is recommended by the American College of Sports Medicine to prevent and treat obesity, yet the effects of AE on circulating hunger hormones including acylated ghrelin and its biological catalyst, ghrelin o-acyltransferase (GOAT) are less known. Objectives: We investigated the effects of AE on circulating concentrations of appetite regulating hormones and GOAT in a pilot sample of adults classified with normal weight (NW) and obese (OB) body weight status. Methods: Using a quasi-experimental design, nine adults with NW (n=4, body mass index [BMI] = 21.3±1.2 kg/m2 ) and OB (n=5, BMI = 38.9±6.2 kg/m2 ) body weight status completed a preliminary health/fitness assessment. Participants returned to the laboratory on three separate occasions, separated by ≥ 48 hours to perform cycle exercise at 30% and 60% oxygen uptake reserve (VO2 R) or a seated control session with no exercise for 40 min. Fifteen mL of blood was taken pre-and-post exercise and control and were assayed in duplicate. Nonparametric procedures determined whether mean rank differences existed between NW and OB for acylated ghrelin, leptin, insulin, and GOAT in response to exercise and control. Alpha levels were set a priori to p <0.05. Results: Significant mean rank reductions were found in GOAT after compared to before AE and control for NW and OB (p<.05). Significant mean rank differences were found in acylated ghrelin after compared to before performing AE at 60% VO2 R in NW and OB (p<.05); however, differences were not observed between NW and OB (p>.05). Conclusions: Our findings reveal the first available data regarding the effects of AE on GOAT, with NW and OB experiencing equivocal changes pre-to-post AE at 60% VO2 R, and in response to a seated control session.

Recommendations for protein intake are based on total body weight; however, these recommendations do not consider lean body mass (LBM). The purpose of the present study was to identify the average protein intake in g/kg LBM in a group of healthy Masters Athletes (>= 26 years of age, exercising >= 2 d/week). Data were obtained from a cross-sectional study. Body weight (kg), height (cm) and LBM via dual-energy X-ray absorptiometry were measured. Dietary intake was measured using a 2005 Block Food Frequency Questionnaire. The average energy intake, the percent energy from protein and the average protein intake in g/kg LBM were calculated. Differences between protein intake and the US Recommended Dietary Allowance (US RDA) (0.8 g/kg body weight) were determined. Alpha levels were set a priori to P < 0.05. A total of 176 participants (94 women, 82 men; 39 +/- 11 years of age; body mass index: 24.6 +/- 3.4 kg/m(2)) were analysed. The average energy intake, the percent protein energy and the average protein intake were 7996.9 +/- 110.9 kilojoules (kJ)/d (1,910.4 +/- 26.5 kcal), 15.5 +/- 2.6 % and 1.43 +/- 0.53 g/kg LBM, respectively. No differences existed between women and men for protein intake/kg LBM. Both sexes had significantly higher protein intakes than the US RDA (P < 0.001). We identified the average protein intake (g/kg LBM) in healthy Masters Athletes that may contribute to evolving perspectives on the determination of protein needs. The present study helps establish the relationship between protein intake and LBM so that we may further increase our accuracy when developing future protein recommendations.

Introduction/Purpose: The crossover point occurs during exercise when one transitions energy substrates from fat to carbohydrate predominance. The crossover point varies in an intensity-dependent manner; however, less is known about its specificity in sports with varying metabolic demands. The purpose of our study was to determine if various sports yield differences in the time to crossover and heart rate and percentage of maximal oxygen consumption (V O2max) at crossover during a standardized exercise protocol. Methods: A total of 77 athletes (39 women, 38 men; 39.1 + 10.4 yr of age) were measured for respiratory exchange ratio during a modified Taylor V O2max treadmill test. Sports included running (n = 20), triathlon (n = 20), rowing (n = 20), and CrossFit (n = 17). A one-way ANOVA determined differences in time to crossover. A Kruskal–Wallis test was applied to determine differences between sport types for percent V O2max and heart rate at crossover. Bonferroni correction procedures were used to control the family-wise error rate and maintain alpha levels at P < 0.05. Results: Average time to crossover for all athletes was 3:43 + 1:12 min. Times to crossover for runners, triathletes, rowers, and CrossFit athletes were 4:16 + 0:58, 3:28 + 1:08, 4:00 + 1:23, and 3:01 + 0:58 min, respectively. Significant differences were observed between groups for time to crossover (P = 0.007) and percent V O2max at crossover (P = 0.01). Pairwise analyses revealed that runners had a significantly longer time to crossover compared with CrossFit athletes (P = 0.009). Triathletes’ percent V O2max at crossover was significantly lower than rowers (P = 0.04) and runners (P = 0.04). Conclusions: We found significant differences in time to crossover between runners and CrossFit athletes, which suggests that substrate use may be dependent on sport type.

Background: Quantitative analysis of ventricular cerebrospinal fluid (vCSF) proteins following acute brain injury (ABI) may help identify pathophysiological pathways and potential biomarkers that can predict unfavorable outcome. Methods: In this prospective proteomic analysis study, consecutive patients with severe ABI expected to require intraventricular catheterization for intracranial pressure (ICP) monitoring for at least 5 days and patients without ABI admitted for elective clipping of an unruptured cerebral aneurysm were included. vCSF samples were collected within the first 24 h after ABI and ventriculostomy insertion and then every 24 h for 5 days. In patients without ABI, a single vCSF sample was collected at the time of elective clipping. Data-independent acquisition and sequential window acquisition of all theoretical spectra (SWATH) mass spectrometry were used to compare differences in protein expression in patients with ABI and patients without ABI and in patients with traumatic and nontraumatic ABI. Differences in protein expression according to different ICP values, intensive care unit outcome, subarachnoid hemorrhage (SAH) versus traumatic brain injury (TBI), and good versus poor 3-month functional status (assessed by using the Glasgow Outcome Scale) were also evaluated. vCSF proteins with significant differences between groups were compared by using linear models and selected for gene ontology analysis using R Language and the Panther database. Results: We included 50 patients with ABI (SAH n = 23, TBI n = 15, intracranial hemorrhage n = 6, ischemic stroke n = 3, others n = 3) and 12 patients without ABI. There were significant differences in the expression of 255 proteins between patients with and without ABI (p < 0.01). There were intraday and interday differences in expression of seven proteins related to increased inflammation, apoptosis, oxidative stress, and cellular response to hypoxia and injury. Among these, glial fibrillary acidic protein, SCOPUS: ar.j, info:eu-repo/semantics/published