Investigation of insulin-like growth factor-1 gene with egg-laying traits in the Muscovy duck (<i>Cairina moschata</i>)
Bibliographic record
Abstract
Muscovy duck (Cairina moschata) is characterized by broodiness, and egg-laying traits in this species should be of primary concern. As a member of the IGF superfamily of proteins, insulin-like growth factor-1 (IGF-1) is an important positive regulator of growth and gonad development in vertebrates. To explore the effect of IGF-1 on the growth hormone/insulin-like growth factors (GH/IGF) axis, we cloned and characterized IGF-1 of Muscovy duck. The expression level of IGF-1 was widely expressed in all the tested tissues, and the highest level was detected in the liver. In laying ducks, IGF-1 expression levels in the hypothalamus, pituitary, and ovary were very significantly higher (P < 0.01) than that in the tissues of nesting duck, and IGF-1 expression levels in the heart and liver were significantly higher (P < 0.05) than that in nesting duck tissues. Furthermore, a single nucleotide polymorphism (SNP) (A/G) was found and significantly (P < 0.05) associated with age at first egg and egg number at 300 d. This study provides the first evidence that IGF-1 promote egg-laying traits of Muscovy duck through two axes, involving GH/IGF and hypothalamic–pituitary–gonadal axes. These findings enrich the information of IGF-1 of Muscovy duck and demonstrate for the first time the ability of IGF-1 to promote reproduction, indicating that IGF-1 could be used as an important marker gene.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".