965 resultados para exercise tolerance


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Exercise-based cardiac rehabilitation (CR) is efficacious in reducing mortality and hospital admissions; however it remains inaccessible to large proportions of the patient population. Removal of attendance barriers for hospital or centre-based CR has seen the promotion of home-based CR. Delivery of safe and appropriately prescribed exercise in the home was first documented 25 years ago, with the utilisation of fixed land-line telecommunications to monitor ECG. The advent of miniature ECG sensors, in conjunction with smartphones, now enables CR to be delivered with greater flexibility with regard to location, time and format, while retaining the capacity for real-time patient monitoring. A range of new systems allow other signals including speed, location, pulse oximetry, and respiration to be monitored and these may have application in CR. There is compelling evidence that telemonitored-based CR is an effective alternative to traditional CR practice. The long-standing barrier of access to centre-based CR, combined with new delivery platforms, raises the question of when telemonitored-based CR could replace conventional approaches as the standard practice.

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Poor health and injury represent major obstacles to the future economic security of Australia. The national economic cost of work-related injury is estimated at $57.5 billion p/a. Since exposure to high physical demands is a major risk factor for musculoskeletal injury, monitoring and managing such physical activity levels in workers is a potentially important injury prevention strategy. Current injury monitoring practices are inadequate for the provision of clinically valuable information about the tissue specific responses to physical exertion. Injury of various soft tissue structures can manifest over time through accumulation of micro-trauma. Such micro-trauma has a propensity to increase the risk of acute injuries to soft-tissue structures such as muscle or tendon. As such, the capacity to monitor biomarkers that result from the disruption of these tissues offers a means of assisting the pre-emptive management of subclinical injury prior to acute failure or for evaluation of recovery processes. Here we have adopted an in-vivo exercise induced muscle damage model allowing the application of laboratory controlled conditions to assist in uncovering biochemical indicators associated with soft-tissue trauma and recovery. Importantly, urine was utilised as the diagnostic medium since it is non-invasive to collect, more acceptable to workers and less costly to employers. Moreover, it is our hypothesis that exercise induced tissue degradation products enter the circulation and are subsequently filtered by the kidney and pass through to the urine. To test this hypothesis a range of metabolomic and proteomic discovery-phase techniques were used, along with targeted approaches. Several small molecules relating to tissue damage were identified along with a series of skeletal muscle-specific protein fragments resulting from exercise induced soft-tissue damage. Each of the potential biomolecular markers appeared to be temporally present within urine. Moreover, the regulation of abundance seemed to be associated with functional recovery following the injury. This discovery may have important clinical applications for monitoring of a variety of inflammatory myopathies as well as novel applications in monitoring of the musculoskeletal health status of workers, professional athletes and/or military personnel to reduce the onset of potentially debilitating musculoskeletal injuries within these professions.

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The increasing prevalence of obesity in society has been associated with a number of atherogenic risk factors such as insulin resistance. Aerobic training is often recommended as a strategy to induce weight loss, with a greater impact of high-intensity levels on cardiovascular function and insulin sensitivity, and a greater impact of moderate-intensity levels on fat oxidation. Anaerobic high-intensity (supramaximal) interval training has been advocated to improve cardiovascular function, insulin sensitivity and fat oxidation. However, obese individuals tend to have a lower tolerance of high-intensity exercise due to discomfort. Furthermore, some obese individuals may compensate for the increased energy expenditure by eating more and/or becoming less active. Recently, both moderate- and high-intensity aerobic interval training have been advocated as alternative approaches. However, it is still uncertain as to which approach is more effective in terms of increasing fat oxidation given the issues with levels of fitness and motivation, and compensatory behaviours. Accordingly, the objectives of this thesis were to compare the influence of moderate- and high-intensity interval training on fat oxidation and eating behaviour in overweight/obese men. Two exercise interventions were undertaken by 10-12 overweight/obese men to compare their responses to study variables, including fat oxidation and eating behaviour during moderate- and high-intensity interval training (MIIT and HIIT). The acute training intervention was a methodological study designed to examine the validity of using exercise intensity from the graded exercise test (GXT) - which measured the intensity that elicits maximal fat oxidation (FATmax) - to prescribe interval training during 30-min MIIT. The 30-min MIIT session involved 5-min repetitions of workloads 20% below and 20% above the FATmax. The acute intervention was extended to involve HIIT in a cross-over design to compare the influence of MIIT and HIIT on eating behaviour using subjective appetite sensation and food preference through the liking and wanting test. The HIIT consisted of 15-sec interval training at 85 %VO2peak interspersed by 15-sec unloaded recovery, with a total mechanical work equal to MIIT. The medium term training intervention was a cross-over 4-week (12 sessions) MIIT and HIIT exercise training with a 6-week detraining washout period. The MIIT sessions consisted of 5-min cycling stages at ±20% of mechanical work at 45 %VO2peak, and the HIIT sessions consisted of repetitive 30-sec work at 90 %VO2peak and 30-sec interval rests, during identical exercise sessions of between 30 and 45 mins. Assessments included a constant-load test (45 %VO2peak for 45 mins) followed by 60-min recovery at baseline and the end of 4-week training, to determine fat oxidation rate. Participants’ responses to exercise were measured using blood lactate (BLa), heart rate (HR) and rating of perceived exertion (RPE) and were measured during the constant-load test and in the first intervention training session of every week during training. Eating behaviour responses were assessed by measuring subjective appetite sensations, liking and wanting and ad libitum energy intake. Results of the acute intervention showed that FATmax is a valid method to estimate VO2 and BLa, but is not valid to estimate HR and RPE in the MIIT session. While the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax (0.16 ±0.09 and 0.14 ±0.08 g/min, respectively), fat oxidation was significantly higher at minute 25 of MIIT (P≤0.01). In addition, there was no significant difference between MIIT and HIIT in the rate of appetite sensations after exercise, but there was a tendency towards a lower rate of hunger after HIIT. Different intensities of interval exercise also did not affect explicit liking or implicit wanting. Results of the medium-term intervention indicated that current interval training levels did not affect body composition, fasting insulin and fasting glucose. Maximal aerobic capacity significantly increased (P≤0.01) (2.8 and 7.0% after MIIT and HIIT respectively) during GXT, and fat oxidation significantly increased (P≤0.01) (96 and 43% after MIIT and HIIT respectively) during the acute constant-load exercise test. RPE significantly decreased after HIIT greater than MIIT (P≤0.05), and the decrease in BLa was greater during the constant-load test after HIIT than MIIT, but this difference did not reach statistical significance (P=0.09). In addition, following constant-load exercise, exercise-induced hunger and desire to eat decreased after HIIT greater than MIIT but were not significant (p value for desire to eat was 0.07). Exercise-induced liking of high-fat sweet (HFSW) and high-fat non-sweet (HFNS) foods increased after MIIT and decreased after HIIT (p value for HFNS was 0.09). The intervention explained 12.4% of the change in fat intake (p = 0.07). This research is significant in that it confirmed two points in the acute study. While the rate of fat oxidation increased during MIIT, the average rate of fat oxidation during 30-min MIIT was comparable with the rate of fat oxidation at FATmax. In addition, manipulating the intensity of acute interval exercise did not affect appetite sensations and liking and wanting. In the medium-term intervention, constant-load exercise-induced fat oxidation significantly increased after interval training, independent of exercise intensity. In addition, desire to eat, explicit liking for HFNS and fat intake collectively confirmed that MIIT is accompanied by a greater compensation of eating behaviour than HIIT. Findings from this research will assist in developing exercise strategies to provide obese men with various training options. In addition, the finding that overweight/obese men expressed a lower RPE and decreased BLa after HIIT compared with MIIT is contrary to the view that obese individuals may not tolerate high-intensity interval training. Therefore, high-intensity interval training can be advocated among the obese adult male population. Future studies may extend this work by using a longer-term intervention.

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Background While compensatory eating following acute aerobic exercise is highly variable, little is known about the underling mechanisms that contribute to alterations in exercise-induced eating behaviour. Methods Overweight and obese women (BMI = 29.6 ± 4.0kg.m2) performed a bout of cycling individually tailored to expend 400kcal (EX), or a time-matched no exercise control condition in a randomised, counter-balanced order. Sixty minutes after the cessation of exercise, an ad libitum test meal was provided. Substrate oxidation and subjective appetite ratings were measured during exercise/time-matched rest, and during the period between the cessation of exercise and food consumption. Results While ad libitum EI did not differ between EX and the control condition (666.0 ± 203.9kcal vs. 664.6 ± 174.4kcal, respectively; ns), there was marked individual variability in compensatory energy intake (EI). The difference in EI between EX and the control condition ranged from -234.3 to +278.5kcal. Carbohydrate oxidation during exercise was positively associated with post-exercise EI, accounting for 37% of the variance in EI (r = 0.57; p = 0.02). Conclusions These data indicate that capacity of acute exercise to create a short-term energy deficit in overweight and obese women is highly variable. Furthermore, exercise-induced CHO oxidation can explain part of the variability in acute exercise-induced compensatory eating. Post-exercise compensatory eating could serve as an adaptive response to facilitate the restoration of carbohydrate balance.

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The objective of exercise training is to initiate desirable physiological adaptations that ultimately enhance physical work capacity. Optimal training prescription requires an individualized approach, with an appropriate balance of training stimulus and recovery and optimal periodization. Recovery from exercise involves integrated physiological responses. The cardiovascular system plays a fundamental role in facilitating many of these responses, including thermoregulation and delivery/removal of nutrients and waste products. As a marker of cardiovascular recovery, cardiac parasympathetic reactivation following a training session is highly individualized. It appears to parallel the acute/intermediate recovery of the thermoregulatory and vascular systems, as described by the supercompensation theory. The physiological mechanisms underlying cardiac parasympathetic reactivation are not completely understood. However, changes in cardiac autonomic activity may provide a proxy measure of the changes in autonomic input into organs and (by default) the blood flow requirements to restore homeostasis. Metaboreflex stimulation (e.g. muscle and blood acidosis) is likely a key determinant of parasympathetic reactivation in the short term (0–90 min post-exercise), whereas baroreflex stimulation (e.g. exercise-induced changes in plasma volume) probably mediates parasympathetic reactivation in the intermediate term (1–48 h post-exercise). Cardiac parasympathetic reactivation does not appear to coincide with the recovery of all physiological systems (e.g. energy stores or the neuromuscular system). However, this may reflect the limited data currently available on parasympathetic reactivation following strength/resistance-based exercise of variable intensity. In this review, we quantitatively analyse post-exercise cardiac parasympathetic reactivation in athletes and healthy individuals following aerobic exercise, with respect to exercise intensity and duration, and fitness/training status. Our results demonstrate that the time required for complete cardiac autonomic recovery after a single aerobic-based training session is up to 24 h following low-intensity exercise, 24–48 h following threshold-intensity exercise and at least 48 h following high-intensity exercise. Based on limited data, exercise duration is unlikely to be the greatest determinant of cardiac parasympathetic reactivation. Cardiac autonomic recovery occurs more rapidly in individuals with greater aerobic fitness. Our data lend support to the concept that in conjunction with daily training logs, data on cardiac parasympathetic activity are useful for individualizing training programmes. In the final sections of this review, we provide recommendations for structuring training microcycles with reference to cardiac parasympathetic recovery kinetics. Ultimately, coaches should structure training programmes tailored to the unique recovery kinetics of each individual.

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This study seeks to bring the discipline of exercise science into the discussion of Quantitative Skills (QS) in Science. The author’s experiences of providing learning support to students and working with educators in the field are described, demonstrating the difficulty of encouraging students to address their skills deficit. A survey of students’ perceptions of their own QS and of that required for their course, demonstrates the difficulties faced by students who do not have the prescribed assumed knowledge for the course. Limited results from academics suggest that their perceptions of students’ QS deficits are even more dire than those of the under-prepared students.

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Reasons for performing the study As growth hormone increases lean body mass, it could be a therapy for obese horses. However, growth hormone use induces hyperinsulinaemia in some species, so further investigation is warranted. Objectives To investigate the effects of feeding, exercise and growth hormone therapy on basal insulin concentrations in healthy horses. Study design In vivo experimental study. Methods Blood samples were obtained every 30 min from 12 geldings over 24 h, to establish basal serum insulin concentrations, before they underwent a 3-week exercise programme. Horses were allocated into 2 groups and exercised for another 4 weeks. Group A received daily i.m. injections of recombinant equine growth hormone; 5 mg/day for 5 days, then 12.5 mg/day for 16 days. Blood samples were taken daily before feeding. Insulin vs. time area under curve of Groups A and B were compared using a Student's unpaired t test. Results Horses demonstrated insulin peaks within 2 h of feeding of 577 ± 108.3 pmol/l at 09.30 h and 342.4 ± 75.7 pmol/l at 17.30 h, despite receiving the same meal. The nadir was between midnight and 07.30 h. Exercise had no effect on basal insulin concentrations prior to equine growth hormone administrations. The equine growth hormone injections increased serum insulin concentrations (P = 0.01) within Group A, from 44.4 ± 15.3 pmol/l initially to 320.9 ± 238.2 pmol/l by Day 12. Exogenous growth hormone caused variable hyperinsulinaemia, which was alleviated once equine growth hormone administration ceased. Conclusions Single serum samples taken prior to the morning meal provide basal insulin concentrations. Exercise did not change basal insulin concentrations. However, equine growth hormone injections increased basal insulin concentrations, which were not ameliorated by exercise. Potential relevance This therapy is not recommended to address obesity in insulin-resistant equids.

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"This is the protocol for a review and there is no abstract. The objectives are as follows: To assess the effects (benefits and harms) of whole-body cryotherapy (cold air exposure) for preventing and treating muscle soreness after exercise in adults." -- publisher website

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Quantity and timing of protein ingestion are major factors regulating myofibrillar protein synthesis (MPS). However, the effect of specific ingestion patterns on MPS throughout a 12 h period is unknown. We determined how different distributions of protein feeding during 12 h recovery after resistance exercise affects anabolic responses in skeletal muscle. Twenty-four healthy trained males were assigned to three groups (n = 8/group) and undertook a bout of resistance exercise followed by ingestion of 80 g of whey protein throughout 12 h recovery in one of the following protocols: 8 × 10 g every 1.5 h (PULSE); 4 × 20 g every 3 h (intermediate: INT); or 2 × 40 g every 6 h (BOLUS). Muscle biopsies were obtained at rest and after 1, 4, 6, 7 and 12 h post exercise. Resting and post-exercise MPS (l-[ring-(13)C6] phenylalanine), and muscle mRNA abundance and cell signalling were assessed. All ingestion protocols increased MPS above rest throughout 1-12 h recovery (88-148%, P < 0.02), but INT elicited greater MPS than PULSE and BOLUS (31-48%, P < 0.02). In general signalling showed a BOLUS>INT>PULSE hierarchy in magnitude of phosphorylation. MuRF-1 and SLC38A2 mRNA were differentially expressed with BOLUS. In conclusion, 20 g of whey protein consumed every 3 h was superior to either PULSE or BOLUS feeding patterns for stimulating MPS throughout the day. This study provides novel information on the effect of modulating the distribution of protein intake on anabolic responses in skeletal muscle and has the potential to maximize outcomes of resistance training for attaining peak muscle mass.

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Background The pattern of protein intake following exercise may impact whole-body protein turnover and net protein retention. We determined the effects of different protein feeding strategies on protein metabolism in resistance-trained young men. Methods: Participants were randomly assigned to ingest either 80g of whey protein as 8x10g every 1.5h (PULSE; n=8), 4x20g every 3h (intermediate, INT; n=7), or 2x40g every 6h (BOLUS; n=8) after an acute bout of bilateral knee extension exercise (4x10 repetitions at 80% maximal strength). Whole-body protein turnover (Q), synthesis (S), breakdown (B), and net balance (NB) were measured throughout 12h of recovery by a bolus ingestion of [ 15N]glycine with urinary [15N]ammonia enrichment as the collected end-product. Results PULSE Q rates were greater than BOLUS (?19%, P<0.05) with a trend towards being greater than INT (?9%, P=0.08). Rates of S were 32% and 19% greater and rates of B were 51% and 57% greater for PULSE as compared to INT and BOLUS, respectively (P<0.05), with no difference between INT and BOLUS. There were no statistical differences in NB between groups (P=0.23); however, magnitude-based inferential statistics revealed likely small (mean effect90%CI; 0.590.87) and moderate (0.800.91) increases in NB for PULSE and INT compared to BOLUS and possible small increase (0.421.00) for INT vs. PULSE. Conclusion We conclude that the pattern of ingested protein, and not only the total daily amount, can impact whole-body protein metabolism. Individuals aiming to maximize NB would likely benefit from repeated ingestion of moderate amounts of protein (?20g) at regular intervals (?3h) throughout the day.

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PURPOSE We have previously shown that the aminoacidemia caused by the consumption of a rapidly digested protein after resistance exercise enhances muscle protein synthesis (MPS) more than the amino acid (AA) profile associated with a slowly digested protein. Here, we investigated whether differential feeding patterns of a whey protein mixture commencing before exercise affect postexercise intracellular signaling and MPS. METHODS Twelve resistance-trained males performed leg resistance exercise 45 min after commencing each of three volume-matched nutrition protocols: placebo (PLAC, artificially sweetened water), BOLUS (25 g of whey protein + 5 g of leucine dissolved in artificially sweetened water; 1× 500 mL), or PULSE (15× 33-mL aliquots of BOLUS drink every 15 min). RESULTS The preexercise rise in plasma AA concentration with PULSE was attenuated compared with BOLUS (P < 0.05); this effect was reversed after exercise, with two-fold greater leucine concentrations in PULSE compared with BOLUS (P < 0.05). One-hour postexercise, phosphorylation of p70 S6K and rpS6 was increased above baseline with BOLUS and PULSE, but not PLAC (P < 0.05); furthermore, PULSE > BOLUS (P < 0.05). MPS throughout 5 h of recovery was higher with protein ingestion compared with PLAC (0.037 ± 0.007), with no differences between BOLUS or PULSE (0.085 ± 0.013 vs. 0.095 ± 0.010%•h, respectively, P = 0.56). CONCLUSIONS Manipulation of aminoacidemia before resistance exercise via different patterns of intake of protein altered plasma AA profiles and postexercise intracellular signaling. However, there was no difference in the enhancement of the muscle protein synthetic response after exercise. Protein sources producing a slow AA release, when consumed before resistance exercise in sufficient amounts, are as effective as rapidly digested proteins in promoting postexercise MPS.

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We determined the effect of muscle glycogen concentration and postexercise nutrition on anabolic signaling and rates of myofibrillar protein synthesis after resistance exercise (REX). Sixteen young, healthy men matched for age, body mass, peak oxygen uptake (VO2peak) and strength (one repetition maximum; 1RM) were randomly assigned to either a nutrient or placebo group. After 48 h diet and exercise control, subjects undertook a glycogen-depletion protocol consisting of one-leg cycling to fatigue (LOW), whereas the other leg rested (NORM). The next morning following an overnight fast, a primed, constant infusion of L-[ring-13C6] phenylalanine was commenced and subjects completed 8 sets of 5 unilateral leg press repetitions at 80% 1RM. Immediately after REX and 2 h later, subjects consumed a 500 ml bolus of a protein/CHO (20 g whey + 40 g maltodextrin) or placebo beverage. Muscle biopsies from the vastus lateralis of both legs were taken at rest and 1 and 4 h after REX. Muscle glycogen concentration was higher in the NORM than LOW at all time points in both nutrient and placebo groups (P < 0.05). Postexercise Akt-p70S6K-rpS6 phosphorylation increased in both groups with no differences between legs (P < 0.05). mTORSer2448 phosphorylation in placebo increased 1 h after exercise in NORM (P < 0.05), whereas mTOR increased ?4-fold in LOW (P < 0.01) and ?11 fold in NORM with nutrient (P < 0.01; different between legs P < 0.05). Post-exercise rates of MPS were not different between NORM and LOW in nutrient (0.070 ± 0.022 vs. 0.068 ± 0.018 %/h) or placebo (0.045 ± 0.021 vs. 0.049 ± 0.017 %/h). We conclude that commencing high-intensity REX with low muscle glycogen availability does not compromise the anabolic signal and subsequent rates of MPS, at least during the early (4 h) postexercise recovery period.