Relationship Between Long-Term Beetroot Juice Supplementation and Hematological Parameters in Elite Fencers - a Pilot Study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to analyze the long-term (4 weeks) effect of a diet and beetroot juice supplementation on hematological parameters, glutathione peroxidase activity in erythrocytes (GPx), and physical performance in elite fencers. METHODS: The study included 20 fencers and was conducted during the preparatory phase. Fencers underwent the fitness VO2max test at baseline - (B) and after two stages of implementation of the dietary recommendations – the first 4 weeks without beetroot juice (D) and the second with 26 g/d of freeze dried beetroot juice supplementation (D&J). At B and after D and D&J fasting blood samples were collected. RESULTS: After D and D&J activities of GPx were significantly higher than those in B (p < 0.000, p = 0.005 – respectively). After D&J versus D significant increased red blood cells count (p = 0.038) and hemoglobin (p = 0.029), as well as decreased platelet count (p = 0.007), were observed. Additionally, after D&J versus B a higher level of mean platelet volume (p = 0.043), energy (p = 0.001), and carbohydrate intake (p < 0.000) were observed and a lower level of red cell distribution width (p = 0.006). CONCLUSION: Our findings provide evidence that long-time consumption of beetroot juice may improve some hematological parameters (red blood cells count, hemoglobin, platelet count, mean platelet volume) - one of the key elements of physical performance. However, seems to be that this effect is largely determined by an appropriate level of energy and nutrients intake.
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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 | 0.001 | 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) | 0.003 | 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".