Oxidative status and telomere length are related to somatic and physiological maturation in chicks of European starlings (<i>Sturnus vulgaris</i>)
Bibliographic record
Abstract
Telomere length can be considered as an indicator of an organism's somatic state, long telomeres reflecting higher energy investment in self-maintenance. Early-life is a period of intense investment in somatic growth and in physiological maturation but how this is reflected in telomere length remains unclear. Using European starling chicks we tested: (i) how telomere length measured at asymptotic mass is related to proxies of somatic growth and physiological maturity in 17-day-old nestlings; (ii) how telomere length measured at 17 days then predicts the changes in somatic and physiological maturity occurring in fledglings (between 17 and 21 days); (iii) how growth and telomere length co-vary when chicks are under experimentally good (fed) growth conditions. Depending on environmental conditions, our data suggest links between somatic growth, physiological maturation and body maintenance parameters (positive with oxidative stress and negative with telomere length) in nestlings. Telomere length measured at day 17 predicted a subsequent change in physiological maturation variables observed in fledglings, but only in second-brood chicks: chicks with shorter telomeres had a higher pre-fledging rate of increase in haematocrit and haemoglobin content and a greater decrease in reticulocyte count. Finally, food supplementation of chicks did not change telomere length compared with that in control siblings. Our results suggest that physiological maturation prior to fledging may occur at the expense of telomere length but only when environmental conditions are sub-optimal.
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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".