The hypoxia-inducible factor 1 pathway plays a critical role in the development of breast muscle myopathies in broiler chickens: a comprehensive review
Bibliographic record
Abstract
In light of the increased worldwide demand for poultry meat, genetic selection efforts have intensified to produce broiler strains that grow at a higher rate, have greater breast meat yield (BMY), and convert feed to meat more efficiently. The increased selection pressure for these traits, BMY in particular, has produced multiple breast meat quality defects collectively known as breast muscle myopathies (BMM). Hypoxia has been proposed as one of the major mechanisms triggering the onset and occurrence of these myopathies. In this review, the relevant literature on the causes and consequences of hypoxia in broiler breast muscles is reviewed and discussed, with a special focus on the hypoxia-inducible factor 1 (HIF-1) pathway. Muscle fiber hypertrophy induced by selective breeding for greater BMY reduces the space available in the perimysium and endomysium for blood vessels and capillaries. The hypoxic state that results from the lack of circulation in muscle tissue activates the HIF-1 pathway. This pathway alters energy metabolism by promoting anaerobic glycolysis, suppressing the tricarboxylic acid cycle and damaging mitochondrial function. These changes lead to oxidative stress that further exacerbate the progression of BMM. In addition, activating the HIF-1 pathway promotes fatty acid synthesis, lipogenesis, and lipid accumulation in myopathic muscle tissue, and interacts with profibrotic growth factors leading to increased deposition of matrix proteins in muscle tissue. By promoting lipidosis and fibrosis, the HIF-1 pathway contributes to the development of the distinctive phenotypes of BMM, including white striations in white striping–affected muscles and the increased hardness of wooden breast–affected muscles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".