Examining the Interaction between Exercise, Gut Microbiota, and Neurodegeneration: Future Research Directions.

Physical activity has been demonstrated to have a significant impact on gut microbial diversity and function. Emerging research has revealed certain aspects of the complex interactions between the gut, exercise, microbiota, and neurodegenerative diseases, suggesting that changes in gut microbial diversity and metabolic function may have an impact on the onset and progression of neurological conditions. This study aimed to review the current literature from several databases until 1 June 2023 (PubMed/MEDLINE, Web of Science, and Google Scholar) on the interplay between the gut, physical exercise, microbiota, and neurodegeneration. We summarized the roles of exercise and gut microbiota on neurodegeneration and identified the ways in which these are all connected. The gut-brain axis is a complex and multifaceted network that has gained considerable attention in recent years. Research indicates that gut microbiota plays vital roles in metabolic shifts during physiological or pathophysiological conditions in neurodegenerative diseases; therefore, they are closely related to maintaining overall health and well-being. Similarly, exercise has shown positive effects on brain health and cognitive function, which may reduce/delay the onset of severe neurological disorders. Exercise has been associated with various neurochemical changes, including alterations in cortisol levels, increased production of endorphins, endocannabinoids like anandamide, as well as higher levels of serotonin and dopamine. These changes have been linked to mood improvements, enhanced sleep quality, better motor control, and cognitive enhancements resulting from exercise-induced effects. However, further clinical research is necessary to evaluate changes in bacteria taxa along with age- and sex-based differences.

Body Composition Profiles of Applicants to a Physical Education and Sports Major in Southeastern Mexico.

This study aimed to determine the body composition profile of candidates applying for a Physical Education and Sports major. 327 young adults (F: 87, M: 240) participated in this cross-sectional study. Nutritional status and body composition analysis were performed, and the profiles were generated using an unsupervised machine learning algorithm. Body mass index (BMI), percentage of fat mass (%FM), percentage of muscle mass (%MM), metabolic age (MA), basal metabolic rate (BMR), and visceral fat level (VFL) were used as input variables. BMI values were normal-weight although VFL was significantly higher in men (<0.001; η2 = 0.104). MA was positively correlated with BMR (0.81 [0.77, 0.85]; p < 0.01), BMI (0.87 [0.84, 0.90]; p < 0.01), and VFL (0.77 [0.72, 0.81]; p < 0.01). The hierarchical clustering analysis revealed two significantly different age-independent profiles: Cluster 1 (n = 265), applicants of both sexes that were shorter, lighter, with lower adiposity and higher lean mass; and, Cluster 2 (n = 62), a group of overweight male applicants with higher VFL, taller, with lower %MM and estimated energy expended at rest. We identified two profiles that might help universities, counselors and teachers/lecturers to identify applicants in which is necessary to increase physical activity levels and improve dietary habits.

Short-Term High-Intensity Circuit Training Does Not Modify Resting Heart Rate Variability in Adults during the COVID-19 Confinement.

BACKGROUND/OBJECTIVE: The quarantine caused by the COVID-19 pandemic increased sedentary behavior, psychological stress, and sleep disturbances in the population favoring the installation of alterations in the cardiovascular system. In this sense, physical exercise has widely been suggested as an efficient treatment to improve health. The current study determined the impact of short-term high-intensity circuit training (HICT) on resting heart rate variability (HRV) in adults. METHODS: Nine healthy participants (age: 31.9 ± 4.4 yr.) performed 36 HICT sessions (3 times per day; 3 days per week) and four participants (age: 29.5 ± 1.7 yr.) were assigned to a control group. The HICT consisted of 12 min of whole-body exercises performed during a workout. Twenty-four hours before and after the exercise program, HRV parameters were recorded. RESULTS: The heart rate exercise during the last session trended to be lower when compared with the first HICT session (p = 0.07, d = 0.39, 95% CI = -13.50, 0.72). The interval training did not modify the HRV time (Mean NN, SDNN, RMSSD, NN50, pNN50) and frequency (LF, HF, LF/HF ratio, total power) domain parameters. CONCLUSION: Thirty-six HICT sessions did not provide enough stimuli to modify the resting HRV in adults during social isolation elicited by the COVID-19 pandemic. However, the data suggested that exercise protocol did not induce cardio-vagal adaptations.

Profiling Physical Fitness of Physical Education Majors Using Unsupervised Machine Learning.

The academic curriculum has shown to promote sedentary behavior in college students. This study aimed to profile the physical fitness of physical education majors using unsupervised machine learning and to identify the differences between sexes, academic years, socioeconomic strata, and the generated profiles. A total of 542 healthy and physically active students (445 males, 97 females; 19.8 [2.2] years; 66.0 [10.3] kg; 169.5 [7.8] cm) participated in this cross-sectional study. Their indirect VO2max (Cooper and Shuttle-Run 20 m tests), lower-limb power (horizontal jump), sprint (30 m), agility (shuttle run), and flexibility (sit-and-reach) were assessed. The participants were profiled using clustering algorithms after setting the optimal number of clusters through an internal validation using R packages. Non-parametric tests were used to identify the differences (p < 0.05). The higher percentage of the population were freshmen (51.4%) and middle-income (64.0%) students. Seniors and juniors showed a better physical fitness than first-year students. No significant differences were found between their socioeconomic strata (p > 0.05). Two profiles were identified using hierarchical clustering (Cluster 1 = 318 vs. Cluster 2 = 224). The matching analysis revealed that physical fitness explained the variation in the data, with Cluster 2 as a sex-independent and more physically fit group. All variables differed significantly between the sexes (except the body mass index [p = 0.218]) and the generated profiles (except stature [p = 0.559] and flexibility [p = 0.115]). A multidimensional analysis showed that the body mass, cardiorespiratory fitness, and agility contributed the most to the data variation so that they can be used as profiling variables. This profiling method accurately identified the relevant variables to reinforce exercise recommendations in a low physical performance and overweight majors.

Hemodynamic Adaptations Induced by Short-Term Run Interval Training in College Students.

Perceived lack of time is one of the most often cited barriers to exercise participation. High intensity interval training has become a popular training modality that incorporates intervals of maximal and low-intensity exercise with a time commitment usually shorter than 30 min. The purpose of this study was to examine the effects of short-term run interval training (RIT) on body composition (BC) and cardiorespiratory responses in undergraduate college students. Nineteen males (21.5 ± 1.6 years) were randomly assigned to a non-exercise control (CON, n = 10) or RIT (n = 9). Baseline measurements of systolic and diastolic blood pressure, resting heart rate (HRrest), double product (DP) and BC were obtained from both groups. VO2max and running speed associated with VO2peak (sVO2peak) were then measured. RIT consisted of three running treadmill sessions per week over 4 weeks (intervals at 100% sVO2peak, recovery periods at 40% sVO2peak). There were no differences in post-training BC or VO2max between groups (p > 0.05). HRrest (p = 0.006) and DP (p ≤ 0.001) were lower in the RIT group compared to CON at completion of the study. RIT lowered HRrest and DP in the absence of appreciable BC and VO2max changes. Thereby, RIT could be an alternative model of training to diminish health-related risk factors in undergraduate college students.