Flight training and dietary antioxidants have mixed effects on the oxidative status of multiple tissues in a female migratory songbird
Bibliographic record
Abstract
Birds, like other vertebrates, rely on a robust antioxidant system to protect themselves against oxidative imbalance caused by energy-intensive activities such as flying. Such oxidative challenges may be especially acute for females during spring migration, as they must pay the oxidative costs of flight while preparing for reproduction; however, little previous work has examined how the antioxidant system of female spring migrants responds to dietary antioxidants and the oxidative challenges of regular flying. We fed two diets to female European starlings, one supplemented with a dietary antioxidant and one without, and then flew them daily in a windtunnel for 2 weeks during the autumn and spring migration periods. We measured the activity of enzymatic antioxidants (glutathione peroxidase, superoxide dismutase and catalase), non-enzymatic antioxidant capacity (ORAC) and markers of oxidative damage (protein carbonyls and lipid hydroperoxides) in four tissues: pectoralis, leg muscle, liver and heart. Dietary antioxidants affected enzymatic antioxidant activity and lipid damage in the heart, non-enzymatic antioxidant capacity in the pectoralis, and protein damage in leg muscle. In general, birds not fed the antioxidant supplement appeared to incur increased oxidative damage while upregulating non-enzymatic and enzymatic antioxidant activity, though these effects were strongly tissue specific. We also found trends for diet×training interactions for enzymatic antioxidant activity in the heart and leg muscle. Flight training may condition the antioxidant system of females to dynamically respond to oxidative challenges, and females during spring migration may shift antioxidant allocation to reduce oxidative damage.
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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 | 0.000 | 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".