Migration- and exercise-induced changes to flight muscle size in migratory birds and association with<i>IGF1</i>and<i>myostatin</i>mRNA expression
Bibliographic record
Abstract
Seasonal adjustments to muscle size in migratory birds may result from preparatory physiological changes or responses to changed workloads. The mechanisms controlling these changes in size are poorly understood. We investigated some potential mediators of flight muscle size (myostatin and insulin-like growth factor, IGF1) in pectoralis muscles of wild wintering or migrating white-throated sparrows (Zonotrichia albicollis), captive white-throated sparrows that were photoperiod manipulated to be in a `wintering' or `migratory' (Zugunruhe) state, and captive European starlings (Sturnus vulgaris) that were either exercised for 2 weeks in a wind tunnel or untrained. Flight muscle size increased in photo-stimulated `migrants' and in exercised starlings. Acute exercise but not long-term training caused increased expression of IGF1, but neither caused a change in expression of myostatin or its metalloprotease activator TLL1. Photo-stimulated `migrant' sparrows demonstrated increased expression of both myostatin and IGF1, but wild sparrows exhibited no significant seasonal changes in expression of either myostatin or IGF1. Additionally, in both study species we describe several splice variants of myostatin that are shared with distantly related bird species. We demonstrate that their expression patterns are not different from those of the typical myostatin, suggesting that they have no functional importance and may be mistakes of the splicing machinery. We conclude that IGF1 is likely to be an important mediator of muscle phenotypic flexibility during acute exercise and during endogenous, seasonal preparation for migration. The role of myostatin is less clear, but its paradoxical increase in photo-stimulated `migrants' may indicate a role in seasonal adjustments of protein turnover.
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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".