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James Cameron Morehen, Warren Jeremy Bradley, Jon Clarke, Craig Twist, Catherine Hambly, John Roger Speakman, James Peter Morton and Graeme Leonard Close

Rugby League is a high-intensity collision sport competed over 80 min. Training loads are monitored to maximize recovery and assist in the design of nutritional strategies although no data are available on the total energy expenditure (TEE) of players. We therefore assessed resting metabolic rate (RMR) and TEE in six Super League players over 2 consecutive weeks in-season including one game per week. Fasted RMR was assessed followed by a baseline urine sample before oral administration of a bolus dose of hydrogen (deuterium 2H) and oxygen (18O) stable isotopes in the form of water (2H2 18O). Every 24 hr thereafter, players provided urine for analysis of TEE via DLW method. Individual training load was quantified using session rating of perceived exertion (sRPE) and data were analyzed using magnitude-based inferences. There were unclear differences in RMR between forwards and backs (7.7 ± 0.5 cf. 8.0 ± 0.3 MJ, respectively). Indirect calorimetry produced RMR values most likely lower than predictive equations (7.9 ± 0.4 cf. 9.2 ± 0.4 MJ, respectively). A most likely increase in TEE from Week 1 to 2 was observed (17.9 ± 2.1 cf. 24.2 ± 3.4 MJ) explained by a most likelyincrease in weekly sRPE (432 ± 19 cf. 555 ± 22 AU), respectively. The difference in TEE between forward and backs was unclear (21.6 ± 4.2 cf. 20.5 ± 4.9 MJ, respectively). We report greater TEE than previously reported in rugby that could be explained by the ability of DLW to account for all match and training-related activities that contributes to TEE.

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Kian Peng Goh, Hwei Yee Lee, Dawn Pingxi Lau, Wilma Supaat, Yiong Huak Chan and Angela Fang Yung Koh

Objectives:

The primary aims of the study were to examine the effect of resveratrol on skeletal muscle SIRT1 expression and energy expenditure in subjects with Type 2 diabetes mellitus (T2DM).

Background:

Animal and in vivo studies indicate that resveratrol increases SIRT1 expression that stimulates PGC1α activity. Subsequent upregulation of AMPK and GLUT4 expression are associated with improved insulin sensitivity in peripheral tissues.

Methods:

Ten subjects with T2DM were randomized in a double-blind fashion to receive 3g resveratrol or placebo daily for 12 weeks. Secondary outcomes include measures of AMPK, p-AMPK and GLUT4 expression levels, energy expenditure, physical activity levels, distribution of abdominal adipose tissue and skeletal muscle fiber type composition, body weight, HbA1c, plasma lipid subfraction, adiponectin levels, and insulin sensitivity.

Results:

There was a significant increase in both SIRT1 expression (2.01 vs. 0.86 arbitrary units [AU], p = .016) and p-AMPK to AMPK expression ratio (2.04 vs. 0.79 AU, p = .032) in the resveratrol group compared with the placebo group. Although the percentage of absolute change (8.6 vs. –13.9%, p = .033) and percentage of predicted resting metabolic rate (RMR; 7.8 vs. –13.9%, p = .013) were increased following resveratrol, there was a significant reduction in average daily activity (–38 vs. 43.2%, p = .028) and step counts (–39.5 vs. 11.8%, p = .047) when compared with placebo.

Conclusions:

In patients with T2DM, treatment with resveratrol regulates energy expenditure through increased skeletal muscle SIRT1 and AMPK expression. These findings indicate that resveratrol may have beneficial exercise-mimetic effects in patients with T2DM.

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Andrew Pardue, Eric T. Trexler and Lisa K. Sprod

Extreme body composition demands of competitive bodybuilding have been associated with unfavorable physiological changes, including alterations in metabolic rate and endocrine profile. The current case study evaluated the effects of contest preparation (8 months), followed by recovery (5 months), on a competitive drug-free male bodybuilder over 13 months (M1-M13). Serum testosterone, triiodothyronine (T3), thyroxine (T4), cortisol, leptin, and ghrelin were measured throughout the study. Body composition (BodPod, dualenergy x-ray absorptiometry [DXA]), anaerobic power (Wingate test), and resting metabolic rate (RMR) were assessed monthly. Sleep was assessed monthly via the Pittsburgh Sleep Quality Index (PSQI) and actigraphy. From M1 to M8, testosterone (623–173 ng∙dL-1), T3 (123–40 ng∙dL-1), and T4 (5.8–4.1 mg∙dL-1) decreased, while cortisol (25.2–26.5 mg∙dL-1) and ghrelin (383–822 pg∙mL-1) increased. The participant lost 9.1 kg before competition as typical energy intake dropped from 3,860 to 1,724 kcal∙day-1; BodPod estimates of body fat percentage were 13.4% at M1, 9.6% at M8, and 14.9% at M13; DXA estimates were 13.8%, 5.1%, and 13.8%, respectively. Peak anaerobic power (753.0 to 536.5 Watts) and RMR (107.2% of predicted to 81.2% of predicted) also decreased throughout preparation. Subjective sleep quality decreased from M1 to M8, but objective measures indicated minimal change. By M13, physiological changes were largely, but not entirely, reversed. Contest preparation may yield transient, unfavorable changes in endocrine profile, power output, RMR, and subjective sleep outcomes. Research with larger samples must identify strategies that minimize unfavorable adaptations and facilitate recovery following competition.

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Eric T. Trexler, Katie R. Hirsch, Bill I. Campbell and Abbie E. Smith-Ryan

The purpose of the current study was to evaluate changes in body composition, metabolic rate, and hormones during postcompetition recovery. Data were collected from natural physique athletes (7 male/8 female) within one week before (T1) competition, within one week after (T2), and 4–6 weeks after (T3) competition. Measures included body composition (fat mass [FM] and lean mass [LM] from ultrasongraphy), resting metabolic rate (RMR; indirect calorimetry), and salivary leptin, testosterone, cortisol, ghrelin, and insulin. Total body water (TBW; bioelectrical impedance spectroscopy) was measured at T1 and T2 in a subsample (n = 8) of athletes. Significant (p < .05) changes were observed for weight (T1 = 65.4 ± 12.2 kg, T2 = 67.4 ± 12.6, T3 = 69.3 ± 13.4; T3 > T2 > T1), LM (T1 = 57.6 ± 13.9 kg, T2 = 59.4 ± 14.2, T3 = 59.3 ± 14.2; T2 and T3 > T1), and FM (T1 = 7.7 ± 4.4 kg, T2 = 8.0 ± 4.4, T3 = 10.0 ± 6.2; T3 > T1 and T2). TBW increased from T1 to T2 (Δ=1.9 ± 1.3 L, p < .01). RMR increased from baseline (1612 ± 266 kcal/day; 92.0% of predicted) to T2 (1881 ± 329, 105.3%; p < .01) and T3 (1778 ± 257, 99.6%; p < .001). Cortisol was higher (p < .05) at T2 (0.41 ± 0.31 μg/dL) than T1 (0.34 ± 0.31) and T3 (0.35 ± 0.27). Male testosterone at T3 (186.6 ± 41.3 pg/mL) was greater than T2 (148.0 ± 44.6, p = .04). RMR changes were associated (p ≤ .05) with change in body fat percent (ΔBF%; r = .59) and T3 protein intake (r= .60); male testosterone changes were inversely associated (p≤ .05) with ΔBF%, ΔFM, and Δweight (r=-0.81–-0.88). TBW increased within days of competition. Precompetition RMR suppression appeared to be variable and markedly reversed by overfeeding, and reverted toward normal levels following competition. RMR and male testosterone increased while FM was preferentially gained 4–6 weeks postcompetition.

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Margo L. Mountjoy, Louise M. Burke, Trent Stellingwerff and Jorunn Sundgot-Borgen

this edition outlining the pitfalls of measuring LEA, showing that a multifactorial and multimarker approach is currently required. Could it be that a depressed measured resting metabolic rate compared with predicted will be a practical surrogate for energy deficiency? Staal et al. ( 2018 ) explore

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Bill I. Campbell, Danielle Aguilar, Laurin Conlin, Andres Vargas, Brad Jon Schoenfeld, Amey Corson, Chris Gai, Shiva Best, Elfego Galvan and Kaylee Couvillion

, and body fat percentage). Secondary DVs included maximal strength (back squat and deadlift) and resting metabolic rate (RMR). Participants Healthy, young, aspiring female physique athletes volunteered to participate in the study. To qualify, all participants were required to have resistance trained

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Raffy Dotan

different individuals. Resting Metabolic Rate Versus VO 2 max The noted relationship between body’s surface area and metabolic rate and its ~0.67 associated mass exponent, found quite valid in many warm-blooded vertebrates, has been based on basal or resting metabolic rate (RMR). The relationship between

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Francisco J. Amaro-Gahete, Lucas Jurado-Fasoli, Alejandro R. Triviño, Guillermo Sanchez-Delgado, Alejandro De-la-O, Jørn W. Helge and Jonatan R. Ruiz

morning type). The resting metabolic rate was measured by indirect calorimetry during 15 minutes in peaceful and relaxing room (temperature: 22.6 [0.7]°C; humidity: 44.5% [6.1%]). After that, a maximal walking speed protocol on a treadmill (H/P/cosmos pulsar; H/P/Cosmos Sports & Medical GmbH, Nußdorf

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Nessan Costello, Jim McKenna, Louise Sutton, Kevin Deighton and Ben Jones

(g) 42 84 100.0 Protein (g) 142 331 133.1 Alcohol (g) 18 0 −100 Total energy intake (MJ) 16.7 24.5 46.7 Total Energy Expenditure Assessment Resting metabolic rate was assessed using an online gas analyzer (Metalyzer 3BR3; Cortex, Leipzig, Germany) 1 day prior to the start of the total energy

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Nicolas Aguilar-Farias, Wendy J. Brown, Tina L. Skinner and G.M.E.E. (Geeske) Peeters

each activity for at least 5 minutes and remain silent during the recording period. EE was used as a proxy for resting metabolic rate (RMR) while lying down and remaining silent in a quiet environment without disturbance. During the walking activity, participants were asked to walk at their usual