The influences of chokeberry extract supplementation on redox status and body composition in handball players during competition phase
Bibliographic record
Abstract
The aim of our study was to investigate the influence of 12 weeks of consumption of chokeberry extract on redox status, body composition, lipid profile, and biochemical parameters in active handball players. The study included 16 handball players aged 16–24 years (20.26 ± 2.86 years). Every morning before training, players received 30 mL of liquid chokeberry extract for 12 weeks during the regular competition season. The research consisted of morphofunctional and biochemical testing, which was performed at three points (at the beginning of the study and at 6 and 12 weeks after extract consumption). After the chokeberry extract treatment, we observed significant changes in three main aspects. The 12 week supplementation with chokeberry extract decreased the levels of prooxidants (TBARS and nitrites) and increased catalase activity. Analyzing the dynamic of body composition showed a decrease in body fat (9.4 ± 0.5 vs. 7.3 ± 0.6 kg) as well as its percent in a body (11.4 ± 0.4% vs. 8.8 ± 0.4%). On the other hand, the analysis showed an increase of high-density lipoprotein (1.3 ± 0.3 vs. 1.6 ± 0.2 mmol/L) and hemoglobin (144.4 ± 11.7 vs. 151.7 ± 9.9 g/L) after 6 weeks of treatment. At the same time, a decrease in leukocytes (7.2 × 109 ± 2.8 vs. 6.5 ± 1.2 × 109/L) and an increase in red blood cells count (4.9 ± 0.4 × 109 vs. 5.5 ± 0.5 × 109/L) were observed. Overall, these results emphatically show that the use of chokeberry extract dietary supplement induced a wide range of beneficial effects in the examined group of athletes.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".