Physiological determinants of VO2max and the methods to evaluate it: A critical review

Validity and reliability of the step test to estimate maximal oxygen consumption in pediatric population

Cardiorespiratory fitness is the most important variable related to health and a strong predictor of mortality. However, it is rarely used in clinics due to costs, specialized equipment, space needs, and the requirements of expert staff such as an exercise physiologist, physician, or other health professional. This work aims to validate and test the reliability of a submaximal step test to estimate VO2max of 8-to 16-year-old pediatric populations as a simple and low-cost tool for clinical practice. A cross-sectional study included 242 children and adolescents (42.1% girls) aged 8-16. Cardiorespiratory fitness was determined by a maximal incremental test on a treadmill until exhaustion. The step test entailed maintaining a steady pace of 22 steps per minute for 3 min (60 bpm), with the heart rate being recorded at the end of the test. Nutritional status was computed through BMI z-score. A multiple linear regression model validated the step test and developed a new equation to predict VO2max, including the third-minute heart rate, weight, and height. The reliability among predicted and measured VO2max was assessed by Bland-Altman analysis. The mean age was 12.5 ± 2.6; 51.6% were overweight or obese. The cardiorespiratory fitness measured as VO2max was 35.01 ± 0.58 ml·min-1·kg-1. A robust correlation was observed between the predicted VO2max from the step test and the measured VO2max (r = 0.86, p < 0.001). Bland-Altman analysis indicated statistical concordance between predicted and measured VO2max. Our findings indicate that the step test protocol is valid and reliable for estimating VO2max in children and adolescents. Furthermore, the predictive equation is suitable for application among children aged 8-16.

Peripheral chemoreceptor, a new player in metabolic sensing during physical exertion: a hypothetical scenario

The cardiorespiratory and metabolic response to exercise has been associated with meeting the organism's metabolic demands during physical exertion. Of note, an incremental exercise is characterized by 1) cardiodynamic phase related to cardiac output enhancement mainly determined by a positive chronotropic response, 2) ventilatory threshold one, associated with a significant contribution of cardiovascular and pulmonary ventilation, and 3) ventilatory threshold two, correlated with a tremendous increase in breathing and metabolic responses to exercise. Notably, it has been shown that the ventilatory response to exercise increases concomitantly with the release and accumulation of metabolites (i.e., lactate released from skeletal muscle). The principal peripheral chemoreceptors are the carotid bodies (CBs), allocated into the carotid bifurcation and demonstrated to respond to several stimuli, triggering autonomic and ventilatory responses. Indeed, in past and recent years, it has been shown that CB could respond to lactate in in vitro and in vivo preparations, eliciting an increase in CB activity and ventilation. However, not all evidence indicates that peripheral chemoreceptors respond to lactate. Thus, considering that CB chemoreceptors' role in lactate-dependent breathing response is not completely clear and their potential preponderance as metabolic sensors during exercise has not been thoroughly explored, the present review was focused on the possible role of CB chemoreceptors as metabolic sensors during physical exertion in a physiological context, proposing it as a new actor in exercise physiology.

Genetic Determinants of Endurance: A Narrative Review on Elite Athlete Status and Performance

This narrative review explores the relationship between genetics and elite endurance athletes, summarizes the current literature, highlights some novel findings, and provides a physiological basis for understanding the mechanistic effects of genetics in sport. Key genetic markers include ACTN3 R577X (muscle fiber composition), ACE I/D (cardiovascular efficiency), and polymorphisms in PPARA, VEGFA, and ADRB2, influencing energy metabolism, angiogenesis, and cardiovascular function. This review underscores the benefits of a multi-omics approach to better understand the complex interactions between genetic polymorphisms and physiological traits. It also addresses long-standing issues such as small sample sizes in studies and the heterogeneity in heritability estimates influenced by factors like sex. Understanding the mechanistic relationship between genetics and endurance performance can lead to personalized training strategies, injury prevention, and improved health outcomes. Future studies should focus on standardized classification of sports, replication studies involving diverse populations, and establishing solid physiological associations between polymorphisms and endurance traits to advance the field of sports genetics.

Exercise intensity measurement using fractal analysis of heart rate variability: Reliability, agreement and influence of sex and cardiorespiratory fitness

The study aimed to establish the test-retest reliability of detrended fluctuation analysis of heart rate variability (DFA-α1) based exercise intensity thresholds, assess its agreement with ventilatory- and lactate-derived thresholds and the moderating effect of sex and cardiorespiratory fitness (CRF) on the agreement. Intensity thresholds for thirty-seven participants (17 females) based on blood lactate (LT1/LT2), gas-exchange (VT1/VT2) and DFA-α1 (αTh1/αTh2) were assessed. Heart rate (HR) at αTh1 and αTh2 showed good test-retest reliability (coefficient of variation [CV] < 6%), and moderate to high agreement with LTs (r = 0.40 - 0.57) and VTs (r = 0.61 - 0.66) respectively. Mixed effects models indicated bias magnitude depended on CRF, with DFA-α1 overestimating thresholds versus VTs for lower fitness levels (speed at VT1 <8.5 km⋅hr-1), while underestimating for higher fitness levels (speed at VT2 >15 km⋅hr-1; VO2max >55 mL·kg-1·min-1). Controlling for CRF, sex significantly affected bias magnitude only at first threshold, with males having higher mean bias (+2.41 bpm) than females (-1.26 bpm). DFA-α1 thresholds are practical and reliable intensity measures, however it is unclear if they accurately represent LTs/VTs from the observed limits of agreement and unexplained variance. To optimise DFA-α1 threshold estimation across different populations, bias should be corrected based on sex and CRF.

Prediction of white blood cell count during exercise: a comparison between standalone and hybrid intelligent algorithms

Decades of research in exercise immunology have demonstrated the profound impact of exercise on the immune response, influencing an individual's disease susceptibility. Accurate prediction of white blood cells (WBCs) count during exercise can help to design effective training programs to maintain optimal the immune system function and prevent its suppression. In this regard, this study aimed to develop an easy-to-use and efficient modelling tool for predicting WBCs count during exercise. To achieve this goal, the predictive power of a range of machine-learning algorithms, including six standalone models (M5 prime (M5P), random forest (RF), alternating model trees (AMT), reduced error pruning tree (REPT), locally weighted learning (LWL), and support vector regression (SVR)) were assessed along with six types of hybrid models trained with a bagging (BA) algorithm (BA-M5P, BA-RF, BA-AMT, BA-REPT, BA-LWL, and BA- SVR). A comprehensive database was constructed from 200 eligible people. The models employed post-exercise training WBCs counts as the output parameter and seven WBCs-influencing factors, including intensity and duration of exercise, pre-exercise training WBCs counts, age, body fat percentage, maximal aerobic capacity, and muscle mass as input parameters. Comparing the prediction results of the models to the observed WBCs using standard statistics indicated that the BA-M5P model had the greatest potential to produce a robust prediction of the number of lymphocytes, neutrophils, monocytes, and WBC compared to other models. Moreover, pre-exercise training WBCs counts, intensity and duration of exercise and body fat percentage were the most important features in predicting WBCs counts. These findings hold significant implications for the advancement of exercise immunology and the promotion of public health.

Allometric exponents for scaling running economy in human samples: A systematic review and meta-analysis

Ratio-scaled VO2 is the widely used method for quantifying running economy (RE). However, this method should be criticized due to its theoretical defect and curvilinear relationship indicated by the allometric scaling, although no consensus has been achieved on the generally accepted exponent b value of body weight. Therefore, this study aimed to provide a quantitative synthesis of the reported exponents used to scale VO2 to body weight. Six electronic databases were searched based on related terms. Inclusion criteria involved human cardiopulmonary testing data, derived exponents, and reported precision statistics. The random-effects model was applied to statistically analyze exponent b. Subgroup and meta-regression analyses were conducted to explore the potential factors contributing to variation in b values. The probability of the true exponent being below 1 in future studies was calculated. The estimated b values were all below 1 and aligned with the 3/4 power law, except for the 95 % prediction interval of the estimated fat-free body weight exponent b. A publication bias and a slightly greater I2 and τ statistic were also observed in the fat-free body weight study cohort. The estimated probabilities of the true body weight exponent, full body weight exponent, and fat-free body weight exponent being lower than 1 were 93.8 % (likely), 95.1 % (very likely), and 94.5 % (likely) respectively. 'Sex difference', 'age category', 'sporting background', and 'testing modality' were four potential but critical variables that impacted exponent b. Overall, allometric-scaled RE should be measured by full body weight with exponent b raised to 3/4.

Evaluation of the relationship between occupational-specific task performance and measures of physical fitness, cardiovascular and musculoskeletal health in firefighters

INTRODUCTION

Firefighters are required to perform physically strenuous tasks such as hose drags, victim rescues, forcible entries and stair climbs to complete their public safety mission. Occupational-specific tasks are often used to evaluate the ability of firefighters to adequately/safely perform their duties. Depending on the regions, occupational-specific tasks include six to eight individual tasks, which emphasize distinct aspects of their physical fitness, while also requiring different levels of cardiovascular (CVH) and musculoskeletal health (MSH). Therefore, the aim of this study was to evaluate the relationship between specific occupational task performance and measures of physical fitness, cardiovascular and musculoskeletal health.

METHODS

Using a cross-sectional design, 282 full-time male and female firefighters were recruited. A researcher-generated questionnaire and physical measures were used to collect data on sociodemographic characteristics, CVH, MSH and weekly physical activity habits. Physical measures were used to collect data on physical fitness and occupational-specific task performance.

RESULTS

Absolute cardiorespiratory fitness (abV̇O2max), grip strength, leg strength, push-ups, sit-ups and lean body mass (all p < 0.001) had an inverse association with completion times on all occupational-specific tasks. Age was positively related to the performance of all tasks (all p < 0.05). Higher heart rate variability (HRV) was associated with better performance on all tasks (all p < 0.05). Bodyfat percentage (BF%) and diastolic blood pressure were positively associated with the step-up task (p < 0.05). Lower back musculoskeletal injury (LoBMSI), musculoskeletal discomfort (MSD), and lower limb MSD were associated with a decreased odds of passing the step-up. Upper body MSIs (UBMSI), LoBMSIs and Lower back MSD were associated with decreased odds of passing the rescue drag.

CONCLUSION

Firefighters that were taller, leaner, stronger and fitter with a more favourable CVH profile, higher HRV and less musculoskeletal discomfort performed best on all occupational-specific tasks.

Brain changes: aerobic exercise for traumatic brain injury rehabilitation

Introduction

Traumatic Brain Injury (TBI) accounts for millions of hospitalizations and deaths worldwide. Aerobic exercise is an easily implementable, non-pharmacological intervention to treat TBI, however, there are no clear guidelines for how to best implement aerobic exercise treatment for TBI survivors across age and injury severity.

Methods

We conducted a PRISMA-ScR to examine research on exercise interventions following TBI in children, youth and adults, spanning mild to severe TBI. Three electronic databases (PubMed, PsycInfo, and Web of Science) were searched systematically by two authors, using keywords delineated from "Traumatic Brain Injury," "Aerobic Exercise," and "Intervention."

Results

Of the 415 papers originally identified from the search terms, 54 papers met the inclusion criteria and were included in this review. The papers were first grouped by participants' injury severity, and subdivided based on age at intervention, and time since injury where appropriate.

Discussion

Aerobic exercise is a promising intervention for adolescent and adult TBI survivors, regardless of injury severity. However, research examining the benefits of post-injury aerobic exercise for children and older adults is lacking.

Comparison of ventilatory and oxygen consumption measurements of yearling Thoroughbred colts and fillies exercising unridden on an all-weather track

Sex effects on ventilatory and oxygen consumption (V̇O2) measurements during exercise have been identified in humans. This study's aim was to evaluate the hypothesis that there are sex effects on ventilatory and V̇O2 measurements in exercising, untrained yearling Thoroughbreds (Tb). Forty-one Tbs (16 colts, 25 fillies; 19.8 ± 1.4 months old) were recruited. Physiological, ventilatory and exercise data were gathered from horses exercising unridden at high intensity on an all-weather track from a global positioning-heart rate unit and a portable ergospirometry system. Data were analysed with an unpaired Student's t-test and the Benjamini-Hochberg correction for multiple testing (P ≤ 0.05 significant). Mean bodyweight (BW, P = 0.002) and wither height (P = 0.04) were greater for colts than fillies. There were no differences in physiological and exercise data and absolute peak V̇O2 between groups. However, fillies had a higher mass specific peak V̇O2 (P = 0.03) than colts (121.5 ± 21.6 mL/kg.min vs. 111.9 ± 27.4 mL/kg.min). The peak breathing frequency was greater for fillies (P < 0.001) while the peak inspiratory (P < 0.001) and expiratory air flow (P < 0.001), peak expiratory tidal volume (VTE; P < 0.001) and peak minute ventilation (V̇E; P = 0.01) were greater for colts; there were no differences for peak VTE and V̇E when adjusted for BW. Differences in BW explain the differences in mass specific peak V̇O2 between groups. Given their morphological differences, it is likely that lung volumes and airway diameters are smaller for fillies, resulting in greater resistance and lower air flows and volumes. Further research is required to investigate the ventilatory differences and how they may change with maturation and impact performance.

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model

One of the important concerns in the field of exercise immunology is determining the appropriate intensity and duration of exercise to prevent suppression of the immune system. Adopting a reliable approach to predict the number of white blood cells (WBCs) during exercise can help to identify the appropriate intensity and duration. Therefore, this study was designed to predict leukocyte levels during exercise with the application of a machine-learning model. We used a random forest (RF) model to predict the number of lymphocytes (LYMPH), neutrophils (NEU), monocytes (MON), eosinophils, basophils, and WBC. Intensity and duration of exercise, WBCs values before exercise training, body mass index (BMI), and maximal aerobic capacity (VO₂ max) were used as inputs and WBCs values after exercise training were assessed as outputs of the RF model. In this study, the data was collected from 200 eligible people and K-fold cross-validation was used to train and test the model. Finally, model efficiency was assessed using standard statistics (root mean square error (RMSE), mean absolute error (MAE), relative absolute error (RAE), root relative square error (RRSE), coefficient of determination (R²), and Nash-Sutcliffe efficiency coefficient (NSE)). Our findings revealed that the RF model performed well for predicting the number of WBC with RMSE = 0.94, MAE = 0.76, RAE = 48.54, RRSE = 48.17, NSE = 0.76, and R² = 0.77. Furthermore, the results showed that intensity and duration of exercise are more effective parameters than BMI and VO₂ max to predict the number of LYMPH, NEU, MON, and WBC during exercise. Totally, this study developed a novel approach based on the RF model using the relevant and accessible variables to predict WBCs during exercise. The proposed method can be applied as a promising and cost-effective tool for determining the correct intensity and duration of exercise in healthy people according to the body's immune system response.

Influence of exercise type and duration on cardiorespiratory fitness and muscular strength in post-menopausal women: a systematic review and meta-analysis

Background and aim

Both cardiorespiratory fitness (CRF) and muscular strength are reported to decrease with age and menopause, which considered to be risk for cardiovascular diseases (CVDs). Previous relevant meta-analyses are inconclusive on the beneficial effects of exercise, particularly in post-menopausal women. In this systematic review and meta-analysis, we investigated the effects of exercise modalities on CRF and muscular strength in post-menopausal women, and identified the effective exercise type and duration.

Methods

A comprehensive search was conducted on PubMed, Web of Science, CINAHL, and Medline to identify the randomized controlled trials, which evaluated exercise effect on CRF, lower- and upper-body muscular strength, and/or handgrip strength in post-menopausal women and compared the results with control. Standardized mean differences (SMD), weighted mean differences (WMD), and 95% confidence intervals (95% CIs) were calculated using random effects models.

Results

A total of 129 studies comprising 7,141 post-menopausal women with mean age and BMI ranging from ∼53 to 90 years and 22 to 35 kg/m², respectively, were included in the meta-analysis. Overall, exercise training effectively increased CRF (SMD: 1.15; 95% CI: 0.87, 1.42; p = 0.001), lower-body muscular strength (SMD: 1.06; 95% CI: 0.90, 1.22; p = 0.001), upper-body muscular strength (SMD: 1.11; 95% CI: 0.91, 1.31; p = 0.001), and handgrip strength (WMD: 1.78 kg; 95% CI: 1.24, 2.32; p = 0.001) in post-menopausal women. These increments were found to be irrespective of ages and intervention durations. Regarding exercise type, aerobic, resistance, and combined training significantly increased CRF and lower-body muscular strength, while resistance and combined training effectively increased handgrip strength. However, only resistance training increased the upper-body muscular strength in women.

Conclusion

Our findings suggest that exercise training is effective in increasing CRF and muscular strength in post-menopausal women, which might be cardioprotective. Both aerobic and resistance training alone or in combination increased CRF and lower-body muscular strength, but only resistance training increased upper-body strength in women.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=283425, identifier: CRD42021283425.

Prediction of maximal oxygen uptake based on anthropometric indices in Iranian male adults

BACKGROUND

Assessment of maximal oxygen consumption is important in both general community and occupational settings. Validity and reliability tests are needed to indicate the functionality of the cardiopulmonary system.

OBJECTIVE

This study aimed to establish a maximal oxygen consumption (VO2max) prediction model using anthropometric and demographic variables for young adults in Iran.

METHODS

This cross-sectional study was conducted on 64 healthy young men aged 19-29 years. Oxygen consumption was measured directly and the prediction models to estimate VO2max were determined by multiple linear regression. The accuracy of the prediction models was considered using regression coefficient (R), coefficient of determination (R2), and standard error of estimate (SEE).

RESULTS

The average VO2max was 44.02±4.31 ml/kg/min. Significant correlations were found between the measured VO2max and the anthropometric and demographic variables (r = 0.16-0.86, P < 0.05). Three significant regression models with acceptable accuracy were developed (R2 = 0.67-0.71, SEE = 3.19-3.21).

CONCLUSION

The predictive models consisted of 3-5 variables as significant predictors of VO2max and had acceptable accuracy for Iranian young adults. The proposed models are a simple and valid tool that can be used to estimate the VO2max in the field and in laboratory settings.

MicroRNAs as the Sentinels of Redox and Hypertrophic Signalling

Oxidative stress and inflammation are associated with skeletal muscle function decline with ageing or disease or inadequate exercise and/or poor diet. Paradoxically, reactive oxygen species and inflammatory cytokines are key for mounting the muscular and systemic adaptive responses to endurance and resistance exercise. Both ageing and lifestyle-related metabolic dysfunction are strongly linked to exercise redox and hypertrophic insensitivity. The adaptive inability and consequent exercise intolerance may discourage people from physical training resulting in a vicious cycle of under-exercising, energy surplus, chronic mitochondrial stress, accelerated functional decline and increased susceptibility to serious diseases. Skeletal muscles are malleable and dynamic organs, rewiring their metabolism depending on the metabolic or mechanical stress resulting in a specific phenotype. Endogenous RNA silencing molecules, microRNAs, are regulators of these metabolic/phenotypic shifts in skeletal muscles. Skeletal muscle microRNA profiles at baseline and in response to exercise have been observed to differ between adult and older people, as well as trained vs. sedentary individuals. Likewise, the circulating microRNA blueprint varies based on age and training status. Therefore, microRNAs emerge as key regulators of metabolic health/capacity and hormetic adaptability. In this narrative review, we summarise the literature exploring the links between microRNAs and skeletal muscle, as well as systemic adaptation to exercise. We expand a mathematical model of microRNA burst during adaptation to exercise through supporting data from the literature. We describe a potential link between the microRNA-dependent regulation of redox-signalling sensitivity and the ability to mount a hypertrophic response to exercise or nutritional cues. We propose a hypothetical model of endurance exercise-induced microRNA "memory cloud" responsible for establishing a landscape conducive to aerobic as well as anabolic adaptation. We suggest that regular aerobic exercise, complimented by a healthy diet, in addition to promoting mitochondrial health and hypertrophic/insulin sensitivity, may also suppress the glycolytic phenotype and mTOR signalling through miRNAs which in turn promote systemic metabolic health.