Estimation of Heat Production Rate using Thermal Data During Exercise in Indoor Environments: A Study of Heat Storage Rate in Male Athletes.

The increasing preference for indoor exercise spaces highlights the relationship between indoor thermal environments and physiological responses, particularly concerning thermal comfort during physical activity. Determining the metabolic heat production rate during exercise is essential for optimizing the thermal comfort, well-being, and performance of individuals engaged in physical activities. This value can be determined during the activity using several methods, including direct calorimetry measurement, indirect calorimetry that uses analysis of respiratory gases, or approximations using collected data such as speed, body mass, and heart rate. The study aimed to calculate the metabolic heat production rate by infrared thermal evaluation (ITE) based on the body's thermal balance approach and compare it with the values determined by indirect calorimetry (IC). Fourteen participants volunteered for the study, using a cycling ergometer in a controlled climatic chamber. After the familiarization sessions, maximal O2 intake levels (VO2max) were determined through maximal graded exercise tests. Subsequently, constant work rate exercise tests were performed at 60% of VO2max for 20 min. The metabolic heat production rates were calculated by IC and ITE for each athlete individually. Respiratory gases were used to determine IC, while body skin and core temperatures, along with physical environmental data, were applied to calculate ITE using the human body thermal balance approximation of ASHRAE. According to the results, heat storage rates were misleading among the body's heat transfer modes, particularly during the first 8 min of the exercise. ITE showed a moderate level of correlation with IC (r: 0.03-0.86) with a higher level of dispersion relative to the mean (CV%: 12-84%). Therefore, a new equation (ITEnew) for the heat storage rates was proposed using the experimental data from this study. The results showed that ITEnew provided more precise estimations for the entire exercise period (p > 0.05). Correlations between ITEnew and IC values were consistently strong throughout the exercise period (r: 0.62-0.85). It can be suggested that ITEnew values can predict IC during the constant work rate steady-state exercise.

Do PON1-Q192R and PON1-L55M polymorphisms modify the effects of hypoxic training on paraoxonase and arylesterase activity?

BACKGROUND: Low levels of antioxidant paraoxonase 1 (PON1) enzyme activity, PON1-Q192R polymorphism (a glutamine (Q) to arginine (R) substitution at position 192), PON1-L55M polymorphism (a leucine (L) to methionine (M) substitution at position 55), and oxidized low-density lipoprotein (oxLDL) are risk factors for coronary heart disease. Aerobic exercise improves PON1 activity, but the effects of hypoxic exercise are yet unclear. The aim of this study was to determine the effects of hypoxic underwater rugby training on PON1 activity and oxLDL levels and the role of the mentioned polymorphisms. METHODS: Serum PON1 and arylesterase activities (ARE), PON1, PON3, and oxLDL protein levels (by using the enzyme-linked immunosorbent assays) were determined in an athletic group (42 trained male underwater rugby players; age = 21.7 ± 4.2 years, mean ± SD) and a control group (43 sedentary men; age = 23.9 ± 3.2 years). The polymorphisms were determined from genomic DNA samples. RESULTS: PON1 activity (25.1%, p = 0.052), PON3 (p < 0.001), and oxLDL (p < 0.001) of the athletic group, including most genotype groups, were higher than those of the control group. In comparison to the controls, PON1 activity levels (p = 0.005) of the PON1-Q192R homozygote QQ genotype group and PON1 activity levels (30%, p = 0.116) of the PON1-L55M homozygote LL genotype group were higher, whereas ARE activity values of athletic R allele carrier (Rc = QR + RR) (p = 0.005) and LL group (p = 0.002) were lower than the control genotype groups related to their polymorphisms. CONCLUSION: Hypoxic training can cause (1) significant oxidative stress, including oxLDL, and an antioxidant response (increase in PON1 activity and PON3), (2) differences in the activity of PON1 and ARE, which are modified by PON1-Q192R and PON1-L55M polymorphisms, respectively, and (3) improvements in PON1 activity of QQ and LL groups. However, hypoxic training can cause a disadvantage of LL and Rc groups for ARE.

Assessing Acute Responses to Exercises Performed Within and at the Upper Boundary of Severe Exercise Domain.

Purpose: The highest work-rate that provides maximal oxygen uptake (V˙O2max) may be one of the best exercise stimuli to yield both V˙O2max and lactate accumulation. The aim of this study was to analyze physiological and metabolic acute responses of an exercise modality performed at the upper boundary of the severe exercise domain, and compare those responses with exercise modalities applied within the severe exercise domain. Method: Ten trained male cyclists participated in this study. The V˙O2max, corresponding power output (POVO2max), and the highest work-rate that provides the V˙O2max (IHIGH) were determined by constant work-rate exercises. Cyclists performed three high-intensity interval training (HIIT) strategies as follows; HIIT-1: 4-6 × 3-min at 95% of POVO2max with 1:1 (workout/rest ratio); HIIT-2: 16-18 × 1-min at 105% of POVO2max with 1:1; HIIT-3: 4-7 × 1-2-min at the IHIGH with 1:2. Capillary blood samples were analyzed before, immediately after HIIT sessions, and at the first, third, and fifth minutes of recovery periods. Lactate difference between the highest lactate response and resting status was considered as the peak lactate response for each HIIT modality. Results: Time spent at V˙O2max was greater at HIIT-1 and HIIT-3 (272 ± 127 and 208 ± 111 seconds, respectively; p = 0.155; effect size = 0.43) when compared to the HIIT-2 (~26 seconds; p < 0.001), while there was a greater lactate accumulation at HIIT-3 (~16 mmol·L-1) when compared to HIIT-1 and HIIT-2 (12 and 14 mmol·L-1, respectively; p < 0.001). Conclusions: In conclusion, HIIT-3 performed at IHIGH was successful to provide time spent at V˙O2max with a greater lactate accumulation in a single session.

Development potentials of commonly used high-intensity training strategies on central and peripheral components of maximal oxygen consumption.

The aim of this study was to reveal the development potentials of five high-intensity training models on central and peripheral components of maximal oxygen consumption (VO2max). Following VO2max determination, maximal cardiac output (Qmax), maximal stroke volume (SVmax), and maximal arteriovenous O2 difference (a-vO2diff_max) were analysed. Short-interval- (short-HIIT), long-interval (long-HIIT), alternating work-rate continuous (alter-HIT), constant work-rate continuous (const-HIT), and sprint interval (SIT) sessions were performed on separate days with iso-effort and iso-time methods. Time spent (tspent) at > 95% of VO2max was the highest in long-HIIT (p < 0.05). The tspent at > 90% of Qmax was higher in alter-HIT than long-HIIT and SIT (p < 0.05), while there was no significant difference for tspent at > 90% of SVmax amongst high-intensity trainings. The tspent at > 90% of a-vO2diff_max was higher in short-HIIT and long-HIIT than other modalities (p < 0.05). It can be said that continuous modalities seem to have a higher potential to improve central part of VO2max, while interval modalities may be better to develop peripheral component.

Grey Zone: A Gap Between Heavy and Severe Exercise Domain.

ABSTRACT: Ozkaya, O, Balci, GA, As, H, Cabuk, R, and Norouzi, M. Grey zone: A gap between heavy and severe exercise domain. J Strength Cond Res 36(1): 113-120, 2022-The aim of this study was to determine a critical threshold (CT) interpreted as "the highest exercise intensity where V̇o2 can be stabilized before reaching 95% of V̇o2max (V̇o2peak)" and compare it with commonly used anaerobic threshold indices. Ten well-trained male cyclists volunteered for this study. Ventilatory threshold (VT) was determined from incremental tests. Multisession constant-load trials were performed to reveal V̇o2max. Mathematically modeled critical power (CP) was estimated through the best individual fit parameter method. Maximal lactate steady state (MLSS) was detected by 30-minute constant-load exercises. The individual CT load of each cyclist was tested by constant-load exercises to exhaustion with +15 W intervals until minimal power output to elicit V̇o2peak. The results showed that work rate corresponding to CT (329.5 ± 41.5 W) was significantly greater than that of the MLSS (269.5 ± 38.5 W; p = 0.000), VT (279.6 ± 33 W; p = 0.000), and CP (306.3 ± 39.4 W; p = 0.000), and CP overestimated both VT and MLSS (p = 0.000). There was no significant V̇o2 difference between the 10th and 30th minute of MLSS and MLSS + 15 W exercise (0.36-0.13 ml·min-1·kg-1; p = 0.621). Exercising V̇o2 response of MLSS + 15 W could not exceed the level of 95% V̇o2max (57.02 ± 3.87 ml·min-1·kg-1 and 87.2 ± 3.1% of V̇o2max; p = 0.000), whereas V̇o2 responses greater than 95% of V̇o2max were always attained during exercises performed at CT + 15 W (64.52 ± 4.37 ml·min-1·kg-1 and 98.6 ± 1% of V̇o2max; p > 0.05). In conclusion, this study indicates that there is a "grey zone" between heavy and severe exercise domain. This information may play a key role in enhancing athletic performance by improving the quality of training programs.

The effects of vibration on efficiency in off-road cyclists.

OBJECTIVES: The aim of this study was to investigate whether vibration significantly affected the efficiency of off-road cyclists. PATIENTS AND METHODS: Eight male mountain cyclists (mean age 21.1±1 years; range, 19 to 22 years) between August 2017 and November 2017 were included. The experimental protocol included four testing sessions with a one-day interval between testing sessions: a familiarization session; performance of submaximal tests; performance of maximal graded exercise test; and a 30-min mountain bike trial performed with vibration or without vibration. Physiological measures including volume of oxygen uptake (VO2), volume of 2), VO2, VCO2, heart rate, respiratory exchange ratio, rating of perceived exertion, and gross efficiency (GE) were compared between the trials performed with vibration or without vibration. RESULTS: There was a significant increase in the GE with the addition of intermittent vibration, particularly over the last 15 min of the cycling trial (p<0.05). There were no significant effects of vibration on other parameters. CONCLUSION: This study demonstrates that addition of intermittent vibration may provide positive benefits in improving GE during a 30-min submaximal cycling trial.

Sigmoidal VO2 on-kinetics: A new pattern in VO2 responses at the lower district of extreme exercise domain.

The aim of the study was to analyse the VO2 on-kinetics belonging to the work rates within the lower district of extreme exercise domain. Maximal O2 utilisation and peak power outputs of eight well-trained cyclists were revealed by multisession trails. Critical threshold (CT) as the lower boundary of severe domain and aerobic limit power (ALP) as the upper boundary of severe domain were determined by multisession constant-load exercises. VO2 on-kinetics over time were best fitted by multicomponent exponential models described by an initial concave-up response known as cardio-dynamic phase (τ = 18.2 ± 2.88 s; a = 1.56 ± 0.39 L·min-1) before a primary concave-up phase (τ = 35.4 ± 12.4 s; a = 1.53 ± 0.36 L·min-1), and then a slow component in two of the participants (τ = 80.8 ± 37 s; a = 0.47 ± 0.05 L·min-1) or without a slow component in six of the participants during exercises performed at 50 W above the CT (R2≥0.96; SEE ≤ 0.24; p < 0.001). However, VO2 on-kinetics over time belonging to exercises performed at 50 W above the ALP were best fitted by sigmoidal model (R2≥0.98; SEE ≤ 0.14; p < 0.001) in comparison with linear (R2 = 0.37-0.66; SEE = 0.46-0.64; p < 0.01), or exponential functions (p> 0.05). Indeed, during those exercises, a short period of convex-up response (τ = 16.8 ± 3.1 s; a = 1.72 ± 0.39 L·min-1) was determined just before a concave-up primary phase in VO2 over time (τ = 24.6 ± 5.86 s; a = 1.31 ± 0.20 L·min-1). It was shown that multicomponent exponential trend in VO2 transformed into a sigmoidal shape, once the work rate exceeded the upper boundary of severe exercise domain.

Moderate Intensity Intermittent Exercise Modality May Prevent Cardiovascular Drift.

Cardiovascular drift (CV-Drift) may occur after the ~10th min of submaximal continuous exercising. The purpose of this study was to examine whether CV-Drift is prevented by an intermittent exercise modality, instead of a continuous exercise. Seven well-trained male cyclists volunteered to take part in the study ( V ˙ O2max: 61.7 ± 6.13 mL·min-1·kg-1). Following familiarization sessions, athletes' individual maximal O2 consumption ( V ˙ O2max), maximum stroke volume responses (SVmax), and cardiac outputs (Qc) were evaluated by a nitrous-oxide re-breathing system and its gas analyzer. Then, continuous exercises were performed 30 min at cyclists' 60% V ˙ O2max, while intermittent exercises consisted of three 10 min with 1:0.5 workout/recovery ratios at the same intensity. Qc measurements were taken at the 5th, 9th, 12nd, 15th, 20th, 25th, and 30th min of continuous exercises versus 5th and 10th min of workout phases of intermittent exercise modality. Greater than a 5% SV decrement, with accompanying HR, increase, while Qc remained stable and was accepted as CV-Drift criterion. It was demonstrated that there were greater SV responses throughout intermittent exercises when compared to continuous exercises (138.9 ± 17.9 vs. 144.5 ± 14.6 mL, respectively; p ≤ 0.05) and less HR responses (140.1 ± 14.8 vs. 135.2 ± 11.6 bpm, respectively; p ≤ 0.05), while mean Qc responses were similar (19.4 ± 2.1 vs. 19.4 ± 1.5 L, respectively; p > 0.05). Moreover, the mean times spent at peak SV scores of exercise sessions were greater during intermittent exercise (1.5 vs. 10 min) (p < 0.001). In conclusion, intermittent exercises reduce CV-Drift risk and increases cardiac adaptation potentials of exercises with less physiological stress.

The Test-Retest Reliability of New Generation Power Indices of Wingate All-Out Test.

Although reliability correlations of traditional power indices of the Wingate test have been well documented, no study has analyzed new generation power indices based on milliseconds obtained from a Peak Bike. The purpose of this study was to investigate the retest reliability of new generation power indices. Thirty-two well-trained male athletes who were specialized in basketball, football, tennis, or track and field volunteered to take part in the study (age: 24.3 ± 2.2 years; body mass: 77 ± 8.3 kg; height: 180.3 ± 6.3 cm). Participants performed two Wingate all-out sessions on two separate days. Intra-class correlation coefficient (ICC), standard error measurement (SEM), smallest real differences (SRD) and coefficient of variation (CV) scores were analyzed based on the test and retest data. Reliability results of traditional power indices calculated based on 5-s means such as peak power, average power, power drop, and fatigue index ratio were similar with the previous findings in literature (ICC ≥ 0.94; CV ≤ 2.8%; SEM ≤ 12.28; SRD% ≤ 7.7%). New generation power indices such as peak power, average power, lowest power, power drop, fatigue index, power decline, maximum speed as rpm, and amount of total energy expenditure demonstrated high reliability (ICC ≥ 0.94; CV ≤ 4.3%; SEM ≤ 10.36; SRD% ≤ 8.8%). Time to peak power, time at maximum speed, and power at maximum speed showed a moderate level of reliability (ICC ≥ 0.73; CV ≤ 8.9%; SEM ≤ 63.01; SRD% ≤ 22.4%). The results of this study indicate that reliability correlations and SRD% of new generation power and fatigue-related indices are similar with traditional 5-s means. However, new time-related indices are very sensitive and moderately reliable.

Associations between Thermal and Physiological Responses of Human Body during Exercise.

In this study, thermal behaviours of the athletes were investigated with respect to thermal comfort and exercise intensity. The relationship between an index for analysing thermal comfort (Predicted Mean Vote: PMV) and Rating of Perceived Exertion (RPE) which shows exercise intensity and exhaustion level was evaluated. Eleven moderately trained male athletes ( V ˙ O2max 54 ± 9.9 mL∙min-1∙kg-1) had volunteered for the study (age: 22.2 ± 3.7 years; body mass: 73.8 ± 6.9 kg; height: 181 ± 6.3 cm; Body surface area (BSA): 1.93 ± 0.1 m²; body fat: 12.6% ± 4.2%; V ˙ O2max: 54 ± 9.9 mL∙min-1∙kg-1). Experiments were carried out by using a cycle ergometer in an air-conditioned test chamber which provided fresh air and had the ability to control the temperature and relative humidity. The study cohort was divided into two groups according to maximal oxygen consumption levels of the participants. Statistical analyses were conducted with the whole study cohort as well as the two separated groups. There was a moderate correlation between PMV and RPE for whole cohort (r: -0.51). When the whole cohort divided as low and high aerobic power groups, an average correlation coefficient at high oxygen consumption cohort decreased to r: -0.21, while the average correlation coefficient at low oxygen consumption cohort increased to r: -0.77. In conclusion, PMV and RPE have a high correlation in less trained participants, but not in the more trained ones. The case may bring to mind that thermal distribution may be better in high aerobic power group in spite of high RPE and thus the relation between PMV and RPE is affected by exercise performance status.

Re-Evaluation of Old Findings on Stroke Volume Responses to Exercise and Recovery by Nitrous-Oxide Rebreathin.

It is important to verify the old findings of Cumming (1972) and Goldberg and Shephard (1980) who showed that stroke volume (SV) may be higher during recovery rather than during exercise, in order to organize the number of intervals throughout training sessions. The purpose of this study was to re-evaluate individual SV responses to various upright cycling exercises using the nitrous-oxide rebreathing method. Nine moderate to well-trained male athletes volunteered to take part in the study (maximal O2 uptake (VO2max): 60.2 ± 7 mL⋅min-1⋅kg-1). Workloads ranging from 40-100% of VO2max were applied to determine individual peak SV (SVpeak) response. Results showed that SV responses were higher during exercise compared to recovery in all exercise loads from 40-100% of VO2max. Mean SV responses to individual SVpeak loads were also higher during exercise compared to recovery (122.9 ± 2.5 versus 105.3 ± 5.93 mL). The highest SV responses to 10 min exercises of 40-70% of VO2max were obtained in the 5th or 7.5th min of each stage (p≤0.05). Meanwhile, during 5 min exercises between 80-100% of VO2max, peak SV responses were observed in the 3rd min of loading (p≤0.05). In conclusion, individual SVpeak levels encountered over wide exercise intensity ranges showed that SVpeak development may also be correlated to exercise intensity corresponding to individual SVpeak loads.

Shorter intervals at peak SV vs.V̇O2max may yield high SV with less physiological stress.

The purpose of this study was to evaluate whether greater and sustainable stroke volume (SV) responses may be obtained by exercise intensities corresponding to peak SV (SVpeak) vs. maximal O2 consumption (VO2max), and short vs. long intervals (SI vs. LI). Nine moderate- to well-trained male athletes competing at regional level specialists of cyclist, track and field volunteered to take part in the study (VO2max: 59.7 ± 7.4 mL·min(-1)·kg(-1)). Following familiarisation sessions, VO2max was determined, and then SVpeak was evaluated using exercise intensities at 40%-100% of VO2max by nitrous-oxide rebreathing (N2ORB) method. Then each separate participant exercised wattages corresponding to individual VO2max and SVpeak during both SI (SIVO2max and SI(SVpeak)) and LI (LIVO2max and LI(SVpeak)) workouts on a cycle ergometer. Main results showed that both SIVO2max and SI(SVpeak) yielded greater SV responses than LIVO2max and LI(SVpeak) (p ≤ 0.05). Mean SV responses were greater in LI(SVpeak) than in LIVO2max (p ≤ 0.05), but there was no statistical difference between SI(SVpeak) and SIVO2max. However, there was significantly less physiological stress based on VO2, respiratory exchange ratio, heart rate and rate of perceived exhaustion in SVpeak than in [Formula: see text] intensities (p ≤ 0.05). Moreover, SV responses at exercise phases increased in the early stages and remain stable until the end of SIVO2max and SI(SVpeak) workouts (p > 0.05), while they were gradually decreasing in LIVO2max and LI(SVpeak) sessions (p ≤ 0.05). In conclusion, if the aim of a training session is to improve SVpeak with less physiological stress, SI(SVpeak) seems a better alternative than other modalities tested in the present study.