Complex Networks Models and Spectral Decomposition in the Analysis of Swimming Athletes' Performance at Olympic Games

Intra- and Inter-Seasonal Fitness and Training Load Variations of Elite U20 Soccer Players

Inherent physical and anthropometric traits of elite soccer players, influenced by nature and nurture, account for the emergence of performances across time. Purpose: The present study aimed to evaluate inter- and intraseasonal differences and the influence of playing position on training and fitness metrics in talented young soccer players. Methods: A total of 74 male players from U20 teams of a single elite club were tested both at beginning, during, and at the end of three consecutive competitive seasons. Players under went anthropometric measurement and were tested for aerobic, jumping, and sprinting performances; the GPS-derived measures of metabolic power (MP) and equivalent distance index (ED) of every athlete were analyzed. Results: Difference between teams emerged in Mognoni's test, while it did not in countermovement jump and anthropometrics. ED was different across seasons. The model selection criteria revealed that the Bosco-Vittori test achieved the best fit. BMI and countermovement jump (CMJ) increased, and fat mass decreased, during season; different intraseasonal trends for CMJ. MP was slightly greater in midfielder. Conclusion: Network approaches in modeling performance metrics in sports team could unveil original interconnections between performance factors. In addition, the authors support multiparametric longitudinal assessments and a huge database of sports data for facilitating talent identification.

Development of a Dynamic Network Model to Identify Temporal Patterns of Structural Malformations in Zebrafish Embryos Exposed to a Model Toxicant, Tris(4-chlorophenyl)methanol

Embryogenesis is a well-coordinated process relying on precise cues and environmental signals that direct spatiotemporal embryonic patterning. Quite often, when one error in this process occurs, others tend to co-occur. We posit that investigating the co-occurrence of these abnormalities over time would yield additional information about the mode of toxicity for chemicals. Here, we use the environmental contaminant tris(4-chlorophenyl)methanol (TCPMOH) as a model toxicant to assess the relationship between exposures and co-occurrence of developmental abnormalities in zebrafish embryos. We propose a dynamic network modeling approach to study the co-occurrence of abnormalities, including pericardial edema, yolk sac edema, cranial malformation, spinal deformity, delayed/failed swim bladder inflation, and mortality induced by TCPMOH exposure. TCPMOH-exposed samples revealed increased abnormality co-occurrence when compared to controls. The abnormalities were represented as nodes in the dynamic network model. Abnormalities with high co-occurrence over time were identified using network centrality scores. We found that the temporal patterns of abnormality co-occurrence varied between exposure groups. In particular, the high TCPMOH exposure group experienced abnormality co-occurrence earlier than the low exposure group. The network model also revealed that pericardial and yolk sac edema are the most common critical nodes among all TCPMOH exposure levels, preceding further abnormalities. Overall, this study introduces a dynamic network model as a tool for assessing developmental toxicology, integrating structural and temporal features with a concentration response.

Associations among sleep, hematologic profile, and aerobic and anerobic capacity of young swimmers: A complex network approach

Although the link between sleep and hematological parameters is well-described, it is unclear how this integration affects the swimmer’s performance. The parameters derived from the non-invasive critical velocity protocol have been extensively used to evaluate these athletes, especially the aerobic capacity (critical velocity—CV) and the anaerobic work capacity (AWC). Thus, this study applied the complex network model to verify the influence of sleep and hematological variables on the CV and AWC of young swimmers. Thirty-eight swimmers (male, n = 20; female, n = 18) completed five experimental evaluations. Initially, the athletes attended the laboratory facilities for venous blood collection, anthropometric measurements, and application of sleep questionnaires. Over the 4 subsequent days, athletes performed randomized maximal efforts on distances of 100, 200, 400, and 800-m. The aerobic and anerobic parameters were determined by linear function between distance vs. time, where CV relates to the slope of regression and AWC to y-intercept. Weighted but untargeted networks were generated based on significant (p < 0.05) correlations among variables regardless of the correlation coefficient. Betweenness and eigenvector metrics were used to highlight the more important nodes inside the complex network. Regardless of the centrality metric, basophils and red blood cells appeared as influential nodes in the networks with AWC or CV as targets. The role of other hematologic components was also revealed in these metrics, along with sleep total time. Overall, these results trigger new discussion on the influence of sleep and hematologic profile on the swimmer’s performance, and the relationships presented by this targeted complex network can be an important tool throughout the athlete’s development.

Network Physiology of Exercise: Vision and Perspectives

The basic theoretical assumptions of Exercise Physiology and its research directions, strongly influenced by reductionism, may hamper the full potential of basic science investigations, and various practical applications to sports performance and exercise as medicine. The aim of this perspective and programmatic article is to: (i) revise the current paradigm of Exercise Physiology and related research on the basis of principles and empirical findings in the new emerging field of Network Physiology and Complex Systems Science; (ii) initiate a new area in Exercise and Sport Science, Network Physiology of Exercise (NPE), with focus on basic laws of interactions and principles of coordination and integration among diverse physiological systems across spatio-temporal scales (from the sub-cellular level to the entire organism), to understand how physiological states and functions emerge, and to improve the efficacy of exercise in health and sport performance; and (iii) to create a forum for developing new research methodologies applicable to the new NPE field, to infer and quantify nonlinear dynamic forms of coupling among diverse systems and establish basic principles of coordination and network organization of physiological systems. Here, we present a programmatic approach for future research directions and potential practical applications. By focusing on research efforts to improve the knowledge about nested dynamics of vertical network interactions, and particularly, the horizontal integration of key organ systems during exercise, NPE may enrich Basic Physiology and diverse fields like Exercise and Sports Physiology, Sports Medicine, Sports Rehabilitation, Sport Science or Training Science and improve the understanding of diverse exercise-related phenomena such as sports performance, fatigue, overtraining, or sport injuries.