Haematological changes in elite kayakers during a training season

Lymphocyte and dendritic cell response to a period of intensified training in young healthy humans and rodents: A systematic review and meta-analysis

Background: Intensified training coupled with sufficient recovery is required to improve athletic performance. A stress-recovery imbalance can lead to negative states of overtraining. Hormonal alterations associated with intensified training, such as blunted cortisol, may impair the immune response. Cortisol promotes the maturation and migration of dendritic cells which subsequently stimulate the T cell response. However, there are currently no clear reliable biomarkers to highlight the overtraining syndrome. This systematic review and meta-analysis examined the effect of intensified training on immune cells. Outcomes from this could provide insight into whether these markers may be used as an indicator of negative states of overtraining. Methods: SPORTDiscus, PUBMED, Academic Search Complete, Scopus and Web of Science were searched until June 2022. Included articles reported on immune biomarkers relating to lymphocytes, dendritic cells, and cytokines before and after a period of intensified training, in humans and rodents, at rest and in response to exercise. Results: 164 full texts were screened for eligibility. Across 57 eligible studies, 16 immune biomarkers were assessed. 7 were assessed at rest and in response to a bout of exercise, and 9 assessed at rest only. Included lymphocyte markers were CD3⁺, CD4⁺ and CD8⁺ T cell count, NK cell count, NK Cytolytic activity, lymphocyte proliferation and CD4/CD8 ratio. Dendritic cell markers examined were CD80, CD86, and MHC II expression. Cytokines included IL-1β, IL-2, IL-10, TNF-α and IFN-γ. A period of intensified training significantly decreased resting total lymphocyte (d= -0.57, 95% CI -0.30) and CD8⁺ T cell counts (d= -0.37, 95% CI -0.04), and unstimulated plasma IL-1β levels (d= -0.63, 95% CI -0.17). Resting dendritic cell CD86 expression significantly increased (d = 2.18, 95% CI 4.07). All other biomarkers remained unchanged. Conclusion: Although some biomarkers alter after a period of intensified training, definitive immune biomarkers are limited. Specifically, due to low study numbers, further investigation into the dendritic cell response in human models is required.

Effects of Ashwagandha (Withania somnifera) on Physical Performance: Systematic Review and Bayesian Meta-Analysis

Ashwagandha (Withania somnifera) is considered a potent adaptogen and anti-stress agent that could have some potential to improve physical performance. This preferred reporting items for systematic reviews and meta-analyses (PRISMA)-based comprehensive systematic review and Bayesian meta-analysis aimed to evaluate clinical trials up to 2020 from PubMed, ScienceDirect, and Google Scholar databases regarding the effect of Ashwagandha supplementation on physical performance in healthy individuals. Besides implementing estimation statistics analysis, we developed Bayesian hierarchical models for a pre-specified subgroup meta-analysis on strength/power, cardiorespiratory fitness and fatigue/recovery variables. A total of 13 studies met the requirements of this systematic review, although only 12 were included in the quantitative analysis. A low-to-moderate overall risk of bias of the trials included in this study was detected. All Bayesian hierarchical models converged to a target distribution (Ȓ = 1) for both meta-analytic effect size (μ) and between-study standard deviation (τ). The meta-analytic approaches of the included studies revealed that Ashwagandha supplementation was more efficacious than placebo for improving variables related to physical performance in healthy men and female. In fact, the Bayesian models showed that future interventions might be at least in some way beneficial on the analyzed outcomes considering the 95% credible intervals for the meta-analytic effect size. Several practical applications and future directions are discussed, although more comparable studies are needed in exercise training, and athletic populations are needed to derive a more stable estimate of the true underlying effect.

Hematological, Hormonal and Fitness Indices in Youth Swimmers: Gender-Related Comparisons

This study objective was to evaluate gender differences in hematological, hormonal and fitness variables among youth swimmers and to explore relationships between erythrocyte indices and aerobic and anaerobic capacity. 137 girls and 171 boys participated in the study and were divided into three groups based on their training experience. Blood samples were obtained to determine red blood cell counts, hemoglobin concentration, hematocrit, and plasma erythropoietin and testosterone levels. VO_2max was assessed using a submaximal cycle protocol. 76 girls and 102 boys also undertook a Wingate test to determine their peak anaerobic power. Boys had higher (p < 0.05) means than girls for all hematological variables except for erythropoietin and these variables demonstrated an increase with training in boys. The average VO_2max in l∙min^-1 and peak anaerobic power in watts were also higher in boys (2.91 ± 0.08 and 547 ± 28, respectively) than girls (2.25 ± 0.07 and 450 ± 26, respectively). Modest but significant (p < 0.05) correlations were found between VO_2max and red blood cell counts (r = 0.252), hemoglobin concentration (r = 0.345), or hematocrit (r = 0.345) and between peak anaerobic power and red blood cell counts (r = 0.304), hemoglobin concentration (r = 0.319) or hematocrit (r = 0.351). This study revealed relatively lower yet age- and gender-appropriate hematological, hormonal and fitness indices in youth swimmers. The gender-related differences in erythrocyte indices seem unrelated to erythropoietin and may be explained by the higher testosterone levels seen in boys. Given their correlation to both aerobic and anaerobic capacity, erythrocyte indices may be used as part of talent identification for sports.

Blood Biomarkers in Sports Medicine and Performance and the Future of Metabolomics

The field of sports medicine and performance has undergone an important transformation in the past years where the scientific approach is becoming increasingly more important for teams and athletes. Physical and physiological fitness, nutrition, fatigue and recovery, as well as injury prevention are key elements of the scientific monitoring of athletes nowadays. Many different methods are used nowadays as part of the scientific monitoring and testing of the competitive athlete. Among them, physiological and metabolic testing, biomechanical and movement assessments, GPS-based tracking systems, heart rate monitors, power meters, and training software are an integrative part of the scientific monitor program of many teams and athletes.Blood biomarkers through traditional blood analysis have been used for over three decades (mainly in Europe) to monitor athletic performance. In the same manner that different cells in the body respond to the stress of an infection or a disease, cells in athletes respond to the stress of competition and training. Nowadays, the area of blood biomarkers is an emerging field in the US offering important level of possibilities to monitor athletes. The field of metabolomics can offer a significantly higher level of blood biomarkers for sports medicine and performance monitoring.

Training-induced annual changes in red blood cell profile in highly-trained endurance and speed-power athletes

BACKGROUND

An extensive body of literature exists on the effects of training on hematological parameters, but the previous studies have not reported how hematological parameters respond to changes in training loads within consecutive phases of the training cycle in highly-trained athletes in extremely different sport disciplines. The aim of this study was to identify changes in red blood cell (RBC) profile in response to training loads in consecutive phases of the annual training cycle in highly-trained sprinters (8 men, aged 24±3 years) and triathletes (6 men, aged 24±4 years) who competed at the national and international level.

METHODS

Maximal oxygen uptake (VO2max), RBC, hemoglobin (Hb), hematocrit (Ht), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) and RBC distribution width (RDW) were determined in four characteristic training phases (transition, general subphase of the preparation phase, specific subphase of the preparation phase and competition phase).

RESULTS

Our main findings are that: 1) Hb, MCH and MCHC in triathletes and MCV in both triathletes and sprinters changed significantly over the annual training cycle; 2) triathletes had significantly higher values than sprinters only in case of MCH and MCHC after the transition and general preparation phases but not after the competition phase when MCH and MCHC were higher in sprinters; and 3) in triathletes, Hb, MCH and MCHC substantially decreased after the competition phase, which was not observed in sprinters. The athletes maintained normal ranges of all hematological parameters in four characteristic training phases.

CONCLUSIONS

Although highly-trained sprinters and triathletes do not significantly differ in their levels of most hematological parameters, these groups are characterized by different patterns of changes during the annual training cycle. Our results suggest that when interpreting the values of hematological parameters in speed-power and endurance athletes, a specific phase of the annual training cycle should be taken into account.