Altered plasma and erythrocyte phospholipid fatty acid profile in elite female water polo and football players
Bibliographic record
Abstract
The impact of chronic, intense exercise, such as in elite athletes, on phospholipids fatty acids (FA) composition has not been studied in women so far. This study aimed to investigate FA profiles in plasma and erythrocytes phospholipids in elite female water polo (N = 15) and football (N = 19) players in comparison with sedentary women. In spite of similar dietary patterns, as assessed by a food frequency questionnaire, plasma FA profile in the football players showed significantly higher proportions of stearic acid, oleic acid, and monounsaturated FA (MUFA), and significantly lower proportions of total and n-6 polyunsaturated FA (PUFA) than in the water polo and control group. The water polo players had higher percentages of palmitoleic acid and arachidonic acid than the control subjects. Erythrocyte FA profile differed among groups. We found significantly higher proportion of oleic acid and MUFA in the football group than in the controls, and decreased stearic acid and elevated palmitic and palmitoleic acid in the water polo players than in the other 2 groups. Both groups of athletes had significantly lower percentages of n-6 dihomo-γ-linolenic acid, n-6 PUFA, and total PUFA compared with the controls. The estimated activities of elongase and desaturases in erythrocytes were also altered in the athletes. Our results indicate that long-term, intense physical training significantly affects FA status of plasma and erythrocyte phospholipids in women. The observed differences between the water polo and the football players suggest that the type of regular training may contribute to the altered metabolism of FA, although possible genetic differences among the 3 study groups cannot be ruled out.
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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 | 0.001 | 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".