Carrie Ferguson

Effects of single bout of very high-intensity exercise on metabolic health biomarkers in overweight/obese sedentary men

PURPOSE This study aimed to investigate the effects of a single session of sprint interval training (SIT) and a single extended sprint (ES), matched for total work, on metabolic health biomarkers. METHODS Ten overweight/obese men aged 26.9±6.2years participated. Following a pre-trial incremental exercise test and SIT familiarization, each participant undertook three 2-day trials in randomized order. On Day 1 participants either undertook no exercise (CON), four maximal 30-s sprints, with 4.5min recovery between each (SIT), or a single maximal extended sprint (ES) matched with SIT for work done. On Day 2, participants had a fasting blood sample taken, undertook an oral glucose tolerance test to determine insulin sensitivity index (ISI), and had blood pressure measured. RESULTS Total work done during exercise did not differ between SIT and ES (61.7±2.9 vs. 61.3±2.8kJ; p=0.741). Mean power was higher in SIT than ES (518±21 vs. 306±16W, p<0.0005), resulting in a shorter high-intensity exercise duration in SIT (120±0 vs. 198±10s, p<0.0005). ISI was 44.6% higher following ES than CON (9.4±2.1 vs. 6.5±1.3; p=0.022), but did not differ significantly between SIT and CON (6.6±0.9 vs. 6.5±1.3; p=0.208). However, on the day following exercise fat oxidation in the fasted state was increased by 63% and 38%, compared to CON, in SIT and ES, respectively (p<0.05 for both), with a concomitant reduction in carbohydrate oxidation (p<0.05). CONCLUSION A single ES, which may represent a more time-efficient alternative to SIT, can increase insulin sensitivity and increase fat oxidation in overweight overweight/obese sedentary men.

Human Exercise-Induced Circulating Progenitor Cell Mobilization Is Nitric Oxide-Dependent and Is Blunted in South Asian Men

Objective—Circulating progenitor cells (CPC) have emerged as potential mediators of vascular repair. In experimental models, CPC mobilization is critically dependent on nitric oxide (NO). South Asian ethnicity is associated with reduced CPC. We assessed CPC mobilization in response to exercise in Asian men and examined the role of NO in CPC mobilization per se. Methods and Results—In 15 healthy, white European men and 15 matched South Asian men, CPC mobilization was assessed during moderate-intensity exercise. Brachial artery flow-mediated vasodilatation was used to assess NO bioavailability. To determine the role of NO in CPC mobilization, identical exercise studies were performed during intravenous separate infusions of saline, the NO synthase inhibitor l-NMMA, and norepinephrine. Flow-mediated vasodilatation (5.8%±0.4% vs 7.9%±0.5%; P=0.002) and CPC mobilization (CD34+/KDR+ 53.2% vs 85.4%; P=0.001; CD133+/CD34+/KDR+ 48.4% vs 73.9%; P=0.05; and CD34+/CD45− 49.3% vs 78.4; P=0.006) was blunted in the South Asian group. CPC mobilization correlated with flow-mediated vasodilatation and l-NMMA significantly reduced exercise-induced CPC mobilization (CD34+/KDR+ −3.3% vs 68.4%; CD133+/CD34+/KDR+ 0.7% vs 71.4%; and CD34+/CD45− −30.5% vs 77.8%; all P<0.001). Conclusion—In humans, NO is critical for CPC mobilization in response to exercise. Reduced NO bioavailability may contribute to imbalance between vascular damage and repair mechanisms in South Asian men.

Hypocapnia increases the prevalence of hypoxia-induced augmented breaths

Augmented breaths promote respiratory instability and have been implicated in triggering periods of sleep-disordered breathing. Since respiratory instability is well known to be exacerbated by hypocapnia, we asked whether one of the destabilizing effects of hypocapnia might be related to an increased prevalence of augmented breaths. With this question in mind, we first sought to determine whether hypoxia-induced augmented breaths are more prevalent when hypocapnia is also present. To do this, we studied the breath-by-breath ventilatory responses of a group of freely behaving adult rats in a variety of different respiratory background conditions. We found that the prevalence of augmented breaths was dramatically increased during hypocapnic-hypoxia compared with room air conditions. When hypocapnia was prevented during exposure to hypoxia by adding 5% CO2 to the inspired air, the rate of occurrence of augmented breaths was no greater than that observed in room air. The addition of CO2 alone to room air had no effect on the prevalence of augmented breaths. We conclude that in spontaneously breathing rats, hypoxia promotes the generation of augmented breaths, but only in poikilocapnic conditions, where hypocapnia develops. Our results, therefore, reveal a means by which CO2 exerts a stabilizing influence on breathing, which may be of particular relevance during sleep in conditions commonly associated with respiratory instability.

Athletic Cardiac Adaptation in Males Is a Consequence of Elevated Myocyte Mass

Background—Cardiac remodeling occurs in response to regular athletic training, and the degree of remodeling is associated with fitness. Understanding the myocardial structural changes in athlete’s heart is important to develop tools that differentiate athletic from cardiomyopathic change. We hypothesized that athletic left ventricular hypertrophy is a consequence of increased myocardial cellular rather than extracellular mass as measured by cardiovascular magnetic resonance. Methods and Results—Forty-five males (30 athletes and 15 sedentary age-matched healthy controls) underwent comprehensive cardiovascular magnetic resonance studies, including native and postcontrast T1 mapping for extracellular volume calculation. In addition, the 30 athletes performed a maximal exercise test to assess aerobic capacity and anaerobic threshold. Participants were grouped by athleticism: untrained, low performance, and high performance (O2max <60 or>60 mL/kg per min, respectively). In athletes, indexed cellular mass was greater in high- than low-performance athletes 60.7±7.5 versus 48.6±6.3 g/m2; P<0.001), whereas extracellular mass was constant (16.3±2.2 versus 15.3±2.2 g/m2; P=0.20). Indexed left ventricular end-diastolic volume and mass correlated with O2max (r=0.45, P=0.01; r=0.55, P=0.002) and differed significantly by group (P=0.01; P<0.001, respectively). Extracellular volume had an inverse correlation with O2max (r=−0.53, P=0.003 and left ventricular mass index (r=-0.44, P=0.02). Conclusions—Increasing left ventricular mass in athlete’s heart occurs because of an expansion of the cellular compartment while the extracellular volume becomes relatively smaller: a difference which becomes more marked as left ventricular mass increases. Athletic remodeling, both on a macroscopic and cellular level, is associated with the degree of an individual’s fitness. Cardiovascular magnetic resonance ECV quantification may have a future role in differentiating athlete’s heart from change secondary to cardiomyopathy.

High-intensity interval training: key data needed to bridge the gap from laboratory to public health policy

The World Health Organization and a number of national bodies recommend adults undertake at least 150 min/week of moderate intensity physical activity, or 75 min/week of vigorous intensity physical activity. However, a large proportion of the population do not achieve these targets. Lack of time is often cited as a primary barrier,1 and many researchers have suggested that high-intensity interval training (HIIT), with interval durations from 10 s to 4 min and intensities ranging from 85% maximal heart rate (HRmax) to ‘all out’ efforts, may provide a time-efficient solution to improve public health.2 A wealth of evidence has demonstrated that HIIT can elicit a range of health benefits such as improved cardiorespiratory fitness, insulin sensitivity and vascular function, with these benefits being of at least a similar magnitude to those seen with standard moderate intensity physical activity interventions.3 ,4 These data are clear and convincing. However, they largely emanate from …

Data collection, handling, and fitting strategies to optimize accuracy and precision of oxygen uptake kinetics estimation from breath-by-breath measurements

Phase 2 pulmonary oxygen uptake kinetics (ϕ2 τV̇o2P) reflect muscle oxygen consumption dynamics and are sensitive to changes in state of training or health. This study identified an unbiased method for data collection, handling, and fitting to optimize V̇o2P kinetics estimation. A validated computational model of V̇o2P kinetics and a Monte Carlo approach simulated 2 × 105 moderate-intensity transitions using a distribution of metabolic and circulatory parameters spanning normal health. Effects of averaging (interpolation, binning, stacking, or separate fitting of up to 10 transitions) and fitting procedures (biexponential fitting, or ϕ2 isolation by time removal, statistical, or derivative methods followed by monoexponential fitting) on accuracy and precision of V̇o2P kinetics estimation were assessed. The optimal strategy to maximize accuracy and precision of τV̇o2P estimation was 1-s interpolation of 4 bouts, ensemble averaged, with the first 20 s of exercise data removed. Contradictory to previous advice, we found optimal fitting procedures removed no more than 20 s of ϕ1 data. Averaging method was less critical: interpolation, binning, and stacking gave similar results, each with greater accuracy compared with analyzing repeated bouts separately. The optimal procedure resulted in ϕ2 τV̇o2P estimates for transitions from an unloaded or loaded baseline that averaged 1.97 ± 2.08 and 1.04 ± 2.30 s from true, but were within 2 s of true in only 47-62% of simulations. Optimized 95% confidence intervals for τV̇o2P ranged from 4.08 to 4.51 s, suggesting a minimally important difference of ~5 s to determine significant changes in τV̇o2P during interventional and comparative studies.NEW & NOTEWORTHY We identified an unbiased method to maximize accuracy and precision of oxygen uptake kinetics (τV̇o2P) estimation. The optimum number of bouts to average was four; interpolation, bin, and stacking averaging methods gave similar results. Contradictory to previous advice, we found that optimal fitting procedures removed no more than 20 s of phase 1 data. Our data suggest a minimally important difference of ~5 s to determine significant changes in τV̇o2P during interventional and comparative studies.

Application of the speed-duration relationship to normalize the intensity of high-intensity interval training

The tolerable duration of continuous high-intensity exercise is determined by the hyperbolic Speed-tolerable duration (S-tLIM) relationship. However, application of the S-tLIM relationship to normalize the intensity of High-Intensity Interval Training (HIIT) has yet to be considered, with this the aim of present study. Subjects completed a ramp-incremental test, and series of 4 constant-speed tests to determine the S-tLIM relationship. A sub-group of subjects (n = 8) then repeated 4 min bouts of exercise at the speeds predicted to induce intolerance at 4 min (WR4), 6 min (WR6) and 8 min (WR8), interspersed with bouts of 4 min recovery, to the point of exercise intolerance (fixed WR HIIT) on different days, with the aim of establishing the work rate that could be sustained for 960 s (i.e. 4×4 min). A sub-group of subjects (n = 6) also completed 4 bouts of exercise interspersed with 4 min recovery, with each bout continued to the point of exercise intolerance (maximal HIIT) to determine the appropriate protocol for maximizing the amount of high-intensity work that can be completed during 4×4 min HIIT. For fixed WR HIIT tLIM of HIIT sessions was 399±81 s for WR4, 892±181 s for WR6 and 1517±346 s for WR8, with total exercise durations all significantly different from each other (P<0.050). For maximal HIIT, there was no difference in tLIM of each of the 4 bouts (Bout 1: 229±27 s; Bout 2: 262±37 s; Bout 3: 235±49 s; Bout 4: 235±53 s; P>0.050). However, there was significantly less high-intensity work completed during bouts 2 (153.5±40. 9 m), 3 (136.9±38.9 m), and 4 (136.7±39.3 m), compared with bout 1 (264.9±58.7 m; P>0.050). These data establish that WR6 provides the appropriate work rate to normalize the intensity of HIIT between subjects. Maximal HIIT provides a protocol which allows the relative contribution of the work rate profile to physiological adaptations to be considered during alternative intensity-matched HIIT protocols.

Power-Velocity and Power-Efficiency Implications in the Limitation of Ramp Incremental Cycle Ergometry: Reply to Morales-Alamo et al.

to the editor: We thank Morales-Alamo et al. ([5][1]) for raising important questions worthy of further discussion. A key concern of both our studies ([3][2], [4][3]) is whether the limit of tolerance (LoT) in ramp-incremental exercise is reached with a reserve in power producing capacity. To this

Dissociating external power from intramuscular exercise intensity during intermittent bilateral knee-extension in humans.

Continuous high‐intensity constant‐power exercise is unsustainable, with maximal oxygen uptake ( V̇O2 max ) and the limit of tolerance attained after only a few minutes. Performing the same power intermittently reduces the O2 cost of exercise and increases tolerance. The extent to which this dissociation is reflected in the intramuscular bioenergetics is unknown. We used pulmonary gas exchange and 31P magnetic resonance spectroscopy to measure whole‐body V̇O2 , quadriceps phosphate metabolism and pH during continuous and intermittent exercise of different work:recovery durations. Shortening the work:recovery durations (16:32 s vs. 32:64 s vs. 64:128 s vs. continuous) at a work rate estimated to require 110% peak aerobic power reduced V̇O2 , muscle phosphocreatine breakdown and muscle acidification, eliminated the glycolytic‐associated contribution to ATP synthesis, and increased exercise tolerance. Exercise intensity (i.e. magnitude of intramuscular metabolic perturbations) can be dissociated from the external power using intermittent exercise with short work:recovery durations.

Reply to Francescato et al.: Interpreting the averaging methods to estimate oxygen uptake kinetics parameters

to the editor: We thank Dr. Francescato and colleagues for their interest in our study ([1][1]) and for their letter ([3][2]). The authors requested clarification of why we concluded that 1-s interpolation of breath-by-breath pulmonary oxygen uptake (Vo2P) data resulted in the most accurate and