Time Limit at vV02max and V02max Slow Component in Swimming: a pilot study of University Students

The aim oftms study was to measure in swimming-pool conditions, the time to exhaustion at the minimum velocity that elicits maximal oxygen consumption (TLim-vV02max) and to verify the existence of an oxygen uptake slow component (02SC) in freestyle swimming. Ten university students performed a continuous incremental protocol for vV02max assessment. Forty-eight hours later, they swam to exhaustion at vV02max to assess TLim-vV02max and 02SC. V02 was directly measured and swimming velocity was controlled by a visual pacer. Blood lactate concentrations ([La-]) and heart rate (HR) values were also measured. Mean V02max for the incremental test was 54.2±8.2 m1.kg'l.min'l, and the correspondent vV02max was 1.19±O.08 m.S,l The mean duration ofthe TLim-vV02max test was 325±76.5 s. 02SC appeared in the allout swim at VV02max (279.0±195.2 ml.min'l) and it was found to significant1y correlate with the TLim-vV02max (r = .74, p< .05). These results demonstrated that 02SC is observed also in swimming-pool conditions and that TLim-vV02max values are in accordance with typical formulations of aerobic power training sets for swimmers.We wish to thank Prof Dr. José Soares, from the Laboratory of Exercise Physiology of our faculty, for his significant contribution.info:eu-repo/semantics/publishedVersio

Improvement of adiponectin in relation to physical performance and body composition in young obese males subjected to twenty-four weeks of training programs

Obesity and related metabolic diseases represent a worldwide health problem. The main factor predisposing to obesity is an unhealthy lifestyle including the lack of physical activity. A pivotal role in the etio-pathogenesis of obesity is carried out by adipose tissue, an endocrine organ secreting several adipokines involved in numerous metabolic and inflammatory processes. Among these, of particular importance is adiponectin, an adipokine involved in the regulation of insulin sensibility and in anti-inflammatory processes. The aim of the study was to determine the effects of 24 weeks of two different training programs polarized (POL) and threshold training (THR) on body composition, physical capacities and adiponectin expression. Thirteen male obese subjects (BMI: 32.0 ± 3.0 kg m-2) followed 24 weeks of two different training programs, POL and THR, consisting of walking or running (or a combination of the two methods) in their normal living conditions. Before (T0) and after the end of the program (T1), the assessment of body composition was assessed by bioelectrical impedance and the concentration of salivary and serum adiponectin was analyzed by enzyme-linked immunosorbent assay and western blotting. Although the results obtained did not show significant differences between the two training programs, body mass and body mass index decreased by a mean of −4.46 ± 2.90 kg and 1.43 ± 0.92 kg m−2 (P < 0.05). Fat mass decreased by −4.47 ± 2.78 kg (P < 0.05). V′O2max increased by a mean of 0.20 ± 0.26 L min−1 (P < 0.05) Also, we observed an increase in saliva and in serum of adiponectin concentrations at T1 compared to T0 by 4.72 ± 3.52 μg mL−1 and 5.22 ± 4.74 ng mL−1 (P < 0.05) respectively. Finally, we found significant correlations between Δ serum adiponectin and Δ Hip (R = −0.686, P = 0.001) and between Δ salivary adiponectin and ΔWaist (R = −0.678, P = 0.011). Our results suggest that a 24 weeks training program, independently from intensity and volume, induces an amelioration of body composition and fitness performance. These improvements are associated with an increase in total and HMW adiponectin expression in both saliva and in serum

The point of maximum curvature as a marker for physiological time series

We present a geometric analysis of the model of Stirling. In particular we analyze the curvature of a heart rate time series in response to a step like increment in the exercise intensity. We present solutions for the point of maximum curvature which can be used as a marker of physiological interest. This marker defines the point after which the heart rate no longer continues to rapidly rise and instead follows either a steady state or slow rise. These methods are then applied to find analytic solutions for a mono exponential model which is commonly used in the literature to model the response to a moderate exercise intensity. Numerical solutions are then found for the full model and parameter values presented in Stirling

Metabolic Factors Limiting Performance in Marathon Runners

Each year in the past three decades has seen hundreds of thousands of runners register to run a major marathon. Of those who attempt to race over the marathon distance of 26 miles and 385 yards (42.195 kilometers), more than two-fifths experience severe and performance-limiting depletion of physiologic carbohydrate reserves (a phenomenon known as ‘hitting the wall’), and thousands drop out before reaching the finish lines (approximately 1–2% of those who start). Analyses of endurance physiology have often either used coarse approximations to suggest that human glycogen reserves are insufficient to fuel a marathon (making ‘hitting the wall’ seem inevitable), or implied that maximal glycogen loading is required in order to complete a marathon without ‘hitting the wall.’ The present computational study demonstrates that the energetic constraints on endurance runners are more subtle, and depend on several physiologic variables including the muscle mass distribution, liver and muscle glycogen densities, and running speed (exercise intensity as a fraction of aerobic capacity) of individual runners, in personalized but nevertheless quantifiable and predictable ways. The analytic approach presented here is used to estimate the distance at which runners will exhaust their glycogen stores as a function of running intensity. In so doing it also provides a basis for guidelines ensuring the safety and optimizing the performance of endurance runners, both by setting personally appropriate paces and by prescribing midrace fueling requirements for avoiding ‘the wall.’ The present analysis also sheds physiologically principled light on important standards in marathon running that until now have remained empirically defined: The qualifying times for the Boston Marathon

How Do Humans Control Physiological Strain during Strenuous Endurance Exercise?

Background: Methodology/principal Findings: Conclusions/significance: Distance running performance is a viable model of human locomotion.To evaluate the physiologic strain during competitions ranging from 5-100 km, we evaluated heart rate (HR) records of competitive runners (n = 211). We found evidence that: 1) physiologic strain (% of maximum HR (%HRmax)) increased in proportional manner relative to distance completed, and was regulated by variations in running pace; 2) the %HRmax achieved decreased with relative distance; 3) slower runners had similar %HRmax response within a racing distance compared to faster runners, and despite differences in pace, the profile of %HRmax during a race was very similar in runners of differing ability; and 4) in cases where there was a discontinuity in the running performance, there was evidence that physiologic effort was maintained for some time even after the pace had decreased.The overall results suggest that athletes are actively regulating their relative physiologic strain during competition, although there is evidence of poor regulation in the case of competitive failures.2.308 SJR (2008) Q1, 60/1774 Medicine (miscellaneous), 19/144 Biochemistry, genetics and molecular biology (miscellaneous), 15/175 Agricultural and biological sciences (miscellaneous)UE

A 1-Year Study of Endurance Runners: Training, Laboratory Tests, and Field Tests

Purpose: To compare critical speed (CS) measured from a single-visit field test of the distance–time relationship with the “traditional” treadmill time-to-exhaustion multivisit protocol. Methods: Ten male distance runners completed treadmill and field tests to calculate CS and the maximum distance performed above CS (D′). The field test involved 3 runs on a single visit to an outdoor athletics track over 3600, 2400, and 1200 m. Two field-test protocols were evaluated using either a 30-min recovery or a 60-min recovery between runs. The treadmill test involved runs to exhaustion at 100%, 105%, and 110% of velocity at VO2max, with 24 h recovery between runs. Results: There was no difference in CS measured with the treadmill and 30-min- and 60-minrecovery field tests (P .05). A typical error of the estimate of 0.14 m/s (95% confidence limits 0.09–0.26 m/s) was seen for CS and 88 m (95% confidence limits 60–169 m) for D′. A coefficient of variation of 0.4% (95% confidence limits: 0.3–0.8%) was found for repeat tests of CS and 13% (95% confidence limits 10–27%) for D′. Conclusion: The single-visit method provides a useful alternative for assessing CS in the field

Differences in forearm strength, endurance, and hemodynamic kinetics between male boulderers and lead rock climbers

This study examined differences in the oxygenation kinetics and strength and endurance characteristics of boulderers and lead sport climbers. Using near infrared spectroscopy, 13-boulderers, 10-lead climbers, and 10-controls completed assessments of oxidative capacity index and muscle oxygen consumption (mV̇O2) in the flexor digitorum profundus (FDP), and extensor digitorum communis (EDC). Additionally, forearm strength (maximal volitional contraction MVC), endurance (force–time integral FTI at 40% MVC), and forearm volume (FAV and ΔFAV) was assessed. MVC was significantly greater in boulderers compared to lead climbers (mean difference = 9.6, 95% CI 5.2–14 kg). FDP and EDC oxidative capacity indexes were significantly greater (p = .041 and .013, respectively) in lead climbers and boulderers compared to controls (mean difference = −1.166, 95% CI (−3.264 to 0.931 s) and mean difference = −1.120, 95% CI (−3.316 to 1.075 s), respectively) with no differences between climbing disciplines. Climbers had a significantly greater FTI compared to controls (mean difference = 2205, 95% CI= 1114–3296 and mean difference = 1716, 95% CI = 553–2880, respectively) but not between disciplines. There were no significant group differences in ΔFAV or mV̇O2. The greater MVC in boulderers may be due to neural adaptation and not hypertrophy. A greater oxidative capacity index in both climbing groups suggests that irrespective of climbing discipline, trainers, coaches, and practitioners should consider forearm specific aerobic training to aid performance.N/

Age differences in physiological responses to self-paced and incremental V˙O2max\dot V O_{2max} testing

Purpose: A self-paced maximal exercise protocol has demonstrated higher $\dot V O_{2max}$ values when compared against traditional tests. The aim was to compare physiological responses to this self-paced $\dot V O_{2max}$ protocol (SPV) in comparison to a traditional ramp $\dot V O_{2max}$ (RAMP) protocol in young (18–30 years) and old (50–75 years) participants. Methods: Forty-four participants (22 young; 22 old) completed both protocols in a randomised, counter-balanced, crossover design. The SPV included 5 × 2 min stages, participants were able to self-regulate their power output (PO) by using incremental ‘clamps’ in ratings of perceived exertion. The RAMP consisted of either 15 or 20 W min$^{−1}$. Results: Expired gases, cardiac output (Q), stroke volume (SV), muscular deoxyhaemoglobin (deoxyHb) and electromyography (EMG) at the vastus lateralis were recorded throughout. Results demonstrated significantly higher $\dot V O_{2max}$ in the SPV (49.68 ± 10.26 ml kg$^{−1}$ min$^{−1}$) vs. the RAMP (47.70 ± 9.98 ml kg$^{−1}$ min$^{−1}$) in the young, but not in the old group (>0.05). Q and SV were significantly higher in the SPV vs. the RAMP in the young (0.05). No differences seen in deoxyHb and EMG for either age groups (>0.05). Peak PO was significantly higher in the SPV vs. the RAMP in both age groups (<0.05). Conclusion: Findings demonstrate that the SPV produces higher $\dot V O_{2max}$, peak Q and SV values in the young group. However, older participants achieved similar $\dot V O_{2max}$ values in both protocols, mostly likely due to age-related differences in cardiovascular responses to incremental exercise, despite them achieving a higher physiological workload in the SPV