Effects of Long-Term Supplementation of Bovine Colostrum on Iron Homeostasis, Oxidative Stress, and Inflammation in Female Athletes: A Placebo-Controlled Clinical Trial
Bibliographic record
Abstract
Bovine colostrum supplementation has been suggested as a potential factor in reducing oxidative stress and inflammation. The primary objective of this study was to evaluate the effects of six months of bovine colostrum supplement intake (3.2 g; four capsules/day) in highly trained female athletes on changes in oxidative stress level, inflammation, and iron metabolism biomarkers after intense exercise. In this study, 20 trained female athletes were recruited. Participants were divided into two groups: 11 in the bovine colostrum (6-month supplementation) and 9 in the placebo group (6-month placebo supplementation). All participants completed an intense exercise test at the beginning of the experiment and after six months post-treatment. Blood samples were taken before, following exercise, and after 3 h recovery. Compared to the placebo group, the colostrum group showed a significant decrease in TBARS level (p< 0.01) at all time points, whereas a marked increase was observed in IL-6 (p < 0.01; pre-exercise) and SOD activity (p < 0.01), and transferrin (p < 0.01; rest period) and lactoferrin (p < 0.05; post-exercise) levels. The results suggested that 6-months of bovine colostrum supplementation is beneficial in the reduction of the harmful effects produced by free radicals (ROS), oxidative stress, and inflammation. In consequence, alleviation of the inflammatory response by bovine colostrum supplementation may also cause positive action on iron homeostasis in female athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".