Responses of Trace Elements to Aerobic Maximal Exercise in Elite Sportsmen
Bibliographic record
Abstract
Trace elements are chemical elements needed in minute quantities for the proper growth, development, and physiology of the organism. In biochemistry, a trace element is also referred to as a micronutrient. Trace elements, such as nickel, cadmium, aluminum, silver, chromium, molybdenum, germanium, tin, titanium, tungsten, scandium, are found naturally in the environment and human exposure derives from a variety of sources, including air, drinking water and food. The Purpose of this study was investigated the effect of aerobic maximal intensity endurance exercise on serum trace elements as well-trained individuals of 28 wrestlers (age (year) 19.64±1.13, weight (Kg) 70.07 ± 15.69, height (cm) 176.97 ± 6.69) during and after a 2000 meter Ergometer test protocol was used to perform aerobic (75 %) maximal endurance exercise. Trace element serum levels were analyzed from blood samples taken before, immediately after and one hour after the exercise. While an increase was detected in Chromium (Cr), Nickel (Ni), Molybdenum (Mo) and Titanium (Ti) serum levels immediately after the exercise, a decrease was detected in Aluminum (Al), Scandium (Sc) and Tungsten (W) serum levels. Except for aluminum, the trace elements we worked on showed statistically meaningful responses (P < 0.05 and P < 0.001). According to the responses of trace elements to the exercise showed us the selection and application of the convenient sport is important not only in terms of sportsman performance but also in terms of future healthy life plans and clinically.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".