Can the supplementation of vitamin D, sun exposure, and isolation during the COVID-19 pandemic affect the seasonal concentration of 25(OH)D and selected blood parameters among young soccer players in a one-year training season?
Bibliographic record
Abstract
Objective This study examined the effect of vitamin D supplementation, sunlight radiationradiation, and home isolation during the COVID-19 pandemic on the seasonal changes in 25(OH)D concentration and selected biomarkers in young soccer players along a one-year training cycle.Method Forty elite young soccer players (age: 17.2 ± 1.16 years, body mass: 70.2 ± 5.84, and body height: 179.1 ± 4.26 cm) participated in the research. Only 24 players completed the measurements during all four time- points (T1-: September 2019, T2-: December 2019, T3-: May 2020, and T4-: August 2020) and were divided into two subgroups: supplemented group (GS) and placebo group (GP). Players from GS received 5,000 IU of vitamin D for 8 weeks (January-MarchJanuary–March 2020). Several biomarkers such as 25(OH)D, white blood cells (WBC), red blood cells (RBC), hemoglobin (HGB), muscle damage markersmarkers, and lipid profile were measured.Results AnalysisThe analysis of the total group demonstrated significant seasonal changes in 25(OH)D, HGB, asparagine aminotransferaseaminotransferase, and creatine kinase along the one1-year training cycle. The level of 25(OH)D concentrationinconcentration in T4 was significantly (p < 0.001, pη [ = 0.82) higher in both subgroups in comparison to T2 and T3. Moreover, the significant (p = 0.023) but poor (r = −0.23) correlation between 25(OH)D and WBC was calculated.Conclusion Current research confirmed the significant seasonal changes in 25(OH)D concentration during four seasons. 8-weekEight-week vitamin D supplementation had no extended effect on the level of 25(OH)D concentration.
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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 | 0.001 |
| 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".