The maximal capacity to utilise fat (peak fat oxidation, PFO) may have implications for health and ultra-endurance performance and is commonly determined by incremental exercise tests employing 3-min stages. However, 3-min stages may be insufficient to attain steady-state gas kinetics, compromising test validity. We assessed whether 4-min stages produce steady-state gas exchange and reliable PFO estimates in adults with peak oxygen consumption < 40 mL·kg-1·min-1. Fifteen participants (9 females) completed a graded test to determine PFO and the intensity at which this occurred (FATMAX). Three short continuous exercise sessions (SCE) were then completed in a randomised order, involving completion of the graded test to the stage (i) preceding, (ii) equal to (SCEequal), or (iii) after the stage at which PFO was previously attained, whereupon participants then continued to cycle for 10 min at that respective intensity. Expired gases were sampled at minutes 3-4, 5-6, 7-8, and 9-10. Individual data showed steady-state gas exchange was achieved within 4 min during SCEequal. Mean fat oxidation rates were not different across time within SCEequal nor compared with the graded test at FATMAX (both p > 0.05). However, the graded test displayed poor surrogate validity (SCEequal, minutes 3-4 vs. 5-6, 7-8, and 9-10) and day-to-day reliability (minutes 3-4, SCEequal vs. graded test) to determine PFO, as evident by correlations (range: 0.47-0.83) and typical errors and 95% limits of agreement (ranges: 0.03-0.05 and ±0.09-0.15 g·min-1, respectively). In conclusion, intraindividual variation in PFO is substantial despite 4-min stages establishing steady-state gas exchange in individuals with low fitness. Individual assessment of PFO may require multiple assessments.
This study assessed the effects of glucose-fructose co-ingestion during recovery from high-intensity rugby training on subsequent performance. Nine professional, senior academy Rugby Union players performed two trials in a double-blind, randomized, crossover design. Identical rugby training sessions were separated by a 3-hour recovery period, during which participants ingested protein (0.3 g×kg BM×h-1) and carbohydrate-containing (0.8 g×kg BM×h-1) recovery drinks, comprised of glucose polymers (GLUCOSE ONLY) or a glucose-fructose mixture (GLUCOSE+FRUCTOSE). Performance outcomes were determined from global positioning systems combined with accelerometry and heart rate monitoring. Mean speed during sessions 1 (am) and 2 (pm) of GLUCOSE ONLY was (mean±SD) 118±6 and 117±4 m×min-1, respectively. During GLUCOSE+FRUCTOSE, mean speed during session 1 and 2 was 117±4 and 116±5 m×min-1, respectively (time x trial interaction, p = 0.61). Blood lactate concentrations were higher throughout recovery in GLUCOSE+FRUCTOSE (mean ±SD: 1-h 3.2 ±2.0 mmol×L-1; 3-h 2.1 ±1.2 mmol×L-1) compared to GLUCOSE ONLY (1-h 2.0 ±1.0 mmol×L-1; 3-h 1.4 ±1.0 mmol×L-1; trial effect p = 0.05). Gastrointestinal discomfort low in both conditions. These data suggest glucose-fructose mixtures consumed as protein-carbohydrate recovery drinks following rugby training do not enhance subsequent performance compared to glucose-based recovery drinks.
When sedentary, breakfast omission often results in reduced overall energy intake due to inadequate compensation at lunch. The effect on energy balance however, particularly in the context of exercise, is less clear. PURPOSE: To define the effect of breakfast prior to exercise on energy balance following subsequent ad libitum intake. METHODS: Nine physically active men completed three 5-h trials in a randomized, crossover design: 1) breakfast consumption (451 kcal) followed by rest (control); 2) breakfast followed 2 hours later by 60 min of cycling at 50% Wmax (fed); and 3) extended overnight fasting followed by cycling (fasted). At the end of each trial, energy intake was determined by an ad libitum lunch. Expired breath was sampled hourly at rest, and every 15 min during exercise, to estimate substrate oxidation and energy expenditure. Substrate oxidation and nutrient intake were used to determine energy and substrate balance. RESULTS: During control, energy expenditure and energy intake (including breakfast) were 457±59 and 1642±361 kcal, respectively, leading to an energy balance of 1185±404 kcal. Exercise increased energy expenditure to 1075±116 and 1096±122 kcal (both p<0.05 vs control), when performed fasted and fed, respectively. Energy intake was lower when exercise was performed in the fasted (1300±264 kcal) vs fed state (1558±222 kcal, p<0.01), which led to an energy balance which was less positive with exercise in the fasted (226±324 kcal) vs fed state (462±290 kcal, p<0.05), but both exercise trials produced a less positive energy balance than control (p<0.05). Carbohydrate balance did not differ when exercise was performed in the fasted (-364±132 g) vs fed state (-381±116 g, p>0.05), but was higher with control (162±63 g, p<0.001). In contrast, fat balance was lower with exercise in the fed state (-46±45 g) vs control (3±26 g, p<0.05), but more negative when exercise was performed in the fasted state (-72±30 g, p<0.05) vs both other trials. CONCLUSION: Neither energy expended with exercise, nor energy consumed at breakfast was fully compensated for at lunch. This led to a reduction in energy balance with exercise, lowered further by breakfast omission. The lower energy balance with breakfast omission is mainly accounted for by lower fat, but not carbohydrate balance. Supported by ESPEN and Rank Prize Funds.
The aim of this study was to investigate the acute effect of hydration status on glycemic regulation in healthy adults and explore underlying mechanisms. In this randomized crossover trial, 16 healthy adults (8 men, 8 women) underwent an oral glucose tolerance test (OGTT) when hypohydrated and rehydrated after 4 days of pretrial standardization. One day before OGTT, participants were dehydrated for 1 h in a heat tent with subsequent fluid restriction (HYPO) or replacement (RE). The following day, an OGTT was performed with metabolic rate measurements and pre- and post-OGTT muscle biopsies. Peripheral quantitative computer tomography thigh scans were taken before and after intervention to infer changes in cell volume. HYPO (but not RE) induced 1.9% (SD 1.2) body mass loss, 2.9% (SD 2.7) cell volume reduction, and increased urinary hydration markers, serum osmolality, and plasma copeptin concentration (all P ≤ 0.007). Fasted serum glucose [HYPO 5.10 mmol/l (SD 0.42), RE 5.02 mmol/l (SD 0.40); P = 0.327] and insulin [HYPO 27.1 pmol/l (SD 9.7), RE 27.6 pmol/l (SD 9.2); P = 0.809] concentrations were similar between HYPO and RE. Hydration status did not alter the serum glucose ( P = 0.627) or insulin ( P = 0.200) responses during the OGTT. Muscle water content was lower before OGTT after HYPO compared with RE [761 g/kg wet wt (SD 13) vs. 772 g/kg wet wt (SD 18) RE] but similar after OGTT [HYPO 779 g/kg wet wt (SD 15) vs. RE 780 g/kg wet wt (SD 20); time P = 0.011; trial × time P = 0.055]. Resting energy expenditure was similar between hydration states (stable between −1.21 and 5.94 kJ·kg −1 ·day −1 ; trial P = 0.904). Overall, despite acute mild hypohydration increasing plasma copeptin concentrations and decreasing fasted cell volume and muscle water, we found no effect on glycemic regulation. NEW & NOTEWORTHY We demonstrated for the first time that an acute bout of hypohydration does not impact blood sugar control in healthy adults. Physiological responses to mild hypohydration (<2% body mass loss) caused an elevation in copeptin concentrations similar to that seen in those with diabetes as well as reducing cell volume by ~3%; both of these changes had been hypothesized to cause a higher blood sugar response.
Abstract This study investigated metabolic, endocrine, appetite and mood responses to a maximal eating occasion in fourteen men (mean: age 28 ( sd 5) years, body mass 77·2 ( sd 6·6) kg and BMI 24·2 ( sd 2·2) kg/m 2 ) who completed two trials in a randomised crossover design. On each occasion, participants ate a homogenous mixed-macronutrient meal (pizza). On one occasion, they ate until ‘comfortably full’ ( ad libitum ) and on the other, until they ‘could not eat another bite’ (maximal). Mean energy intake was double in the maximal (13 024 (95 % CI 10 964, 15 084) kJ; 3113 (95 % CI 2620, 3605) kcal) compared with the ad libitum trial (6627 (95 % CI 5708, 7547) kJ; 1584 (95 % CI 1364, 1804) kcal). Serum insulin incremental AUC (iAUC) increased approximately 1·5-fold in the maximal compared with ad libitum trial (mean: ad libitum 43·8 (95 % CI 28·3, 59·3) nmol/l × 240 min and maximal 67·7 (95 % CI 47·0, 88·5) nmol/l × 240 min, P < 0·01), but glucose iAUC did not differ between trials ( ad libitum 94·3 (95 % CI 30·3, 158·2) mmol/l × 240 min and maximal 126·5 (95 % CI 76·9, 176·0) mmol/l × 240 min, P = 0·19). TAG iAUC was approximately 1·5-fold greater in the maximal v . ad libitum trial ( ad libitum 98·6 (95 % CI 69·9, 127·2) mmol/l × 240 min and maximal 146·4 (95 % CI 88·6, 204·1) mmol/l × 240 min, P < 0·01). Total glucagon-like peptide-1, glucose-dependent insulinotropic peptide and peptide tyrosine–tyrosine iAUC were greater in the maximal compared with ad libitum trial ( P < 0·05). Total ghrelin concentrations decreased to a similar extent, but AUC was slightly lower in the maximal v . ad libitum trial ( P = 0·02). There were marked differences on appetite and mood between trials, most notably maximal eating caused a prolonged increase in lethargy. Healthy men have the capacity to eat twice the energy content required to achieve comfortable fullness at a single meal. Postprandial glycaemia is well regulated following initial overeating, with elevated postprandial insulinaemia probably contributing.
Abstract Context Pre-exercise nutrient availability alters acute metabolic responses to exercise, which could modulate training responsiveness. We hypothesised that in men with overweight/obesity, acute exercise before versus after nutrient ingestion would increase whole-body and intramuscular lipid utilization, translating into greater increases in oral glucose insulin sensitivity over 6-weeks of training. Design and Participants We showed in men with overweight/obesity (mean±SD for BMI: 30.2±3.5 kg×m -2 for acute, crossover study, 30.9±4.5 kg×m -2 for randomized, controlled, training study) a single exercise bout before versus after nutrient provision increased lipid utilisation at the whole-body level, but also in both type I ( p< 0.01) and type II muscle fibres ( p= 0.02). We then used a 6-week training intervention to show sustained, 2-fold increases in lipid utilisation with exercise before versus after nutrient provision ( p< 0.01). Main Outcome Measures Postprandial glycemia was not differentially affected by exercise training before vs after nutrient provision ( p> 0.05), yet plasma was reduced with exercise training before, but not after nutrient provision ( p= 0.03), resulting in increased oral glucose insulin sensitivity when training was performed before versus after nutrient provision (25±38 vs −21±32 mL×min -1 ×m -2 ; p= 0.01) and this was associated with increased lipid utilisation during exercise ( r =0.50, p= 0.02). Regular exercise prior to nutrient provision augmented remodelling of skeletal muscle phospholipids and protein content of the glucose transport protein GLUT4 ( p< 0.05). Conclusions Experiments investigating exercise training and metabolic health should consider nutrient-exercise timing, and exercise performed before versus after nutrient intake (i.e., in the fasted state) may exert beneficial effects on lipid utilisation and reduce postprandial insulinemia. Précis Exercise in the fasted- versus fed-state increased intramuscular and whole-body lipid use, translating into increased muscle adaptation and insulin sensitivity when regularly performed over 6 weeks.
The aim of this study was to characterise postprandial glucose flux after exercise in the fed versus overnight fasted-state and to investigate potential underlying mechanisms. In a randomized order, twelve men underwent breakfast-rest (BR; 3 h semi-recumbent), breakfast-exercise (BE; 2 h semi-recumbent before 60-min of cycling (50% peak power output) and overnight fasted-exercise (FE; as per BE omitting breakfast) trials. An oral glucose tolerance test (OGTT) was completed post-exercise (post-rest on BR). Dual stable isotope tracers ([U-13C] glucose ingestion and [6,6-2H2] glucose infusion) and muscle biopsies were combined to assess postprandial plasma glucose kinetics and intramuscular signaling, respectively. Plasma intestinal fatty acid binding (I-FABP) concentrations were determined as a marker of intestinal damage. The results from this study showed that consuming breakfast before exercise increases post-exercise postprandial plasma glucose disposal, which is offset (primarily) by increased appearance rates of orally-ingested glucose. Therefore, metabolic responses to fed-state exercise cannot be readily inferred from studies conducted in a fasted state.
The liver plays a crucial regulatory role in the storage and distribution of lipids during fed and fasted states. With obesity, non-alcoholic fatty liver disease (NAFLD) often develops, a condition characterised by hepatic steatosis. Hepatic steatosis is the result of lipid input (from lipid uptake and de novo lipogenesis) exceeding lipid export (via β-oxidation, or very-low-density lipoprotein and triglyceride secretion), resulting in net liver lipid accumulation. When present, hepatic steatosis can contribute to the development of other cardiometabolic diseases, such as type 2 diabetes and cardiovascular disease. It has been proposed that autonomic nervous system dysfunction is involved in the pathogenesis of obesity and its related co-morbidities. The liver is innervated by both afferent and efferent sympathetic and parasympathetic nerves. However, the importance of liver–brain signalling in the onset and/or the development of NAFLD has remained unclear. In a recent issue of The Journal of Physiology, Hurr et al. (2019) provided evidence to support a role for increased liver sympathetic nerve activity (SNA) in the development of hepatic steatosis in obesity. The authors used a 10 week high-fat diet (60% kcal from fat) to induce obesity and hepatic lipid accumulation in mice, which were compared to mice fed normal chow (with 5% kcal from fat). Multiunit recordings of liver SNA showed an ∼2-fold increase in the obese mice with hepatic steatosis compared to normal chow-fed mice, which was mainly attributed to increased efferent nerve activity (the removal of afferent input was achieved by measuring nerve activity after sectioning the nerve distal to the recording site). The authors then utilised both whole-body (chemical denervation via the neurotoxin 6-hydroxydopamine) and liver-specific methods (application of 10% phenol to the bundle of hepatic artery and portal vein) to inhibit liver SNA in the obese mice with hepatic steatosis. They showed that hepatic steatosis was alleviated in the treated versus the non-treated mice and this occurred despite no differential changes in body mass, energy or water intake, or energy expenditure. Interestingly, the inhibition of liver SNA in the chow-fed mice had no significant effect on liver lipid accumulation, suggesting that the increase in liver SNA following high fat diet-induced obesity is likely to be a homeostatic response to the energy and/or dietary lipid surplus. Hurr et al. (2019) also investigated potential mechanisms by which liver SNA may alter hepatic steatosis, using quantitative real time PCR to show that obese mice with hepatic steatosis exhibited an increased mRNA expression of proteins and transcription factors involved in hepatic lipid uptake and de novo lipogenesis. This upregulation of lipogenic genes was, however, mitigated by the inhibition of liver SNA. Proteins involved in lipid oxidation were also upregulated in obese mice with hepatic steatosis (versus chow-fed controls) but were not significantly altered by subsequent liver sympathetic denervation. Taken together, these findings suggest that increased liver SNA develops alongside high fat diet-induced obesity and that the inhibition of liver SNA may alleviate hepatic steatosis via lipid acquisition pathways. Consequently, interventions that alleviate the increase in liver SNA activity with obesity could help to reduce lipid accumulation in the liver and therefore offer benefits for NAFLD and associated cardiometabolic diseases. Whilst sympathetic nerve activity is important for regulating physiological processes in many tissues in healthy humans, the findings of Hurr et al. (2019) are in line with suggestions that for some tissues (e.g. skeletal muscle and the kidneys), an abnormal increase in SNA can have a role in cardiometabolic disease pathogenesis (Guarino et al. 2017). In the work of Hurr et al. (2019), the increases in efferent nerve activity suggested that obesity-associated alterations in liver SNA could be mostly attributable to central nervous system mechanisms, of which increased hypothalamic neuropeptide Y (NPY) expression is a likely candidate (Bruinstroop et al. 2014). Alterations in SNA with diet-induced obesity could also be due to factors such as hyperinsulinaemia, hyperleptinaemia, increased angiotensin II levels and/or baroreceptor dysfunction. These mechanisms could now also be explored to develop the research of Hurr et al. (2019). The authors also acknowledged that direct recordings of afferent liver SNA were needed to support their results. Indeed, greater fatty acid availability to the liver (due to the high-fat diet or heightened adipose tissue SNA and consequent increases in lipolysis) could have increased hepatic afferent signalling due to the lipid sensing role of the liver (Paolisso et al. 2000). This response is, however, likely to be achieved via the parasympathetic branch of the liver, and thus its contribution to global hepatic SNA is currently unclear (Paolisso et al. 2000). Measuring efferent and afferent liver SNA in combination with systemic lipid concentrations/hepatic lipid flux, and also investigating whether increases in SNA occur concomitantly across different tissues in obesity (or whether this response is first detected in specific tissues, e.g. in the adipose tissue before the liver) would therefore be of interest. Another logical next step for this work would be to de-innervate the liver prior to the provision of a high-fat diet to further clarify the role of liver SNA in hepatic steatosis pathogenesis. This is important given the finding that hepatic steatosis in the obese mice was not completely reversed with either whole-body or liver-specific SNA inhibition, suggesting that hepatic steatosis may be a consequence of neural and non-neural mechanisms (although an intervention of >7 days may have resulted in a complete reversal of steatosis in the work of Hurr et al. 2019). The authors also discussed research in obese Zucker rats in which the surgical removal of liver sympathetic nerves did not alleviate hepatic steatosis. This suggests that the role of liver SNA in the development of metabolic disease may be specific to the research model employed and/or species studied. The distribution of sympathetic and parasympathetic nerves in the liver differs across species, including in mice and humans (Yi et al. 2010). Moreover, despite some genetic and physiological similarities between mice and humans, these species have evolved in different environments and differ in size, metabolic rate, sleep–wake cycles and feeding patterns. Whether the findings of Hurr et al. (2019) can be applied to humans is therefore unclear, but now warrants investigation. One potential next step would be to manipulate liver energy status in humans using diet (e.g. fructose and/or high-fat feeding) or exercise (to manipulate the liver glycogen content), which can be objectively measured using imaging techniques such as 13C nuclear magnetic resonance. When combined with measures of liver SNA, such as hepatic noradrenaline spillover rate or gall bladder contractility (Bruinstroop et al. 2014), this could provide some evidence that liver sympathetic signalling is associated with hepatic energy status in humans, at least in the short-term. Finally, although the increase in liver SNA in obesity may be locally maladaptive (i.e. manifesting as hepatic steatosis), this response may also help to protect other tissues. For example, an increased hepatic uptake of lipid could decrease systemic lipid concentrations, which may prevent ectopic storage in skeletal muscle (with benefits for insulin sensitivity) or cardiac tissue (which could help to preserve normal heart function) (Guarino et al. 2017). This would be in line with suggestions that increases in sympathetic nerve activity in some peripheral tissues (e.g. skeletal muscle) is an adaptive (albeit futile) mechanism to increase resting energy expenditure in an attempt to maintain energy balance (Guarino et al. 2017). Investigating the role of liver–brain signalling for metabolic diseases is certainly complex. Whilst autonomic nerve activity is altered in obesity, this involves tissue-specific changes in both afferent and efferent sympathetic and parasympathetic nerve activity. However, by combining different methods, the work of Hurr et al. (2019) provides novel insights into the role of liver SNA in the regulation of hepatic steatosis in mice with high fat diet-induced obesity and highlights a need to characterise liver autonomic nerve activity in the context of cardiometabolic diseases. Thus, whilst technically challenging, we should continue to pursue methods to measure and manipulate liver sympathetic signalling, as the research of Hurr et al. (2019) suggests that this may have implications for the development and/or treatment of cardiometabolic diseases. None of the authors declare any conflicts of interest in relation to this work. Both authors contributed equally to the writing of the manuscript. Both authors have read and approved the final version of this manuscript and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed. None.
This study explored lifestyle and biological determinants of peak fat oxidation (PFO) during cycle ergometry, using duplicate measures to account for day-to-day variation. Seventy-three healthy adults (age range: 19-63 years; peak oxygen consumption [V˙O2peak]: 42.4 [10.1] ml·kg BM-1·min-1; n = 32 women]) completed trials 7-28 days apart that assessed resting metabolic rate, a resting venous blood sample, and PFO by indirect calorimetry during an incremental cycling test. Habitual physical activity (combined heart rate accelerometer) and dietary intake (weighed record) were assessed before the first trial. Body composition was assessed 2-7 days after the second identical trial by dual-energy X-ray absorptiometry scan. Multiple linear regressions were performed to identify determinants of PFO (mean of two cycle tests). A total variance of 79% in absolute PFO (g·min-1) was explained with positive coefficients for V˙O2peak (strongest predictor), FATmax (i.e the % of V˙O2peak that PFO occurred at), and resting fat oxidation rate (g·min-1), and negative coefficients for body fat mass (kg) and habitual physical activity level. When expressed relative to fat-free mass, 64% of variance in PFO was explained: positive coefficients for FATmax (strongest predictor), V˙O2peak, and resting fat oxidation rate, and negative coefficients for male sex and fat mass. This duplicate design revealed that biological and lifestyle factors explain a large proportion of variance in PFO during incremental cycling. After accounting for day-to-day variation in PFO, V˙O2peak and FATmax were strong and consistent predictors of PFO.
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