Effects of GRF in early gestation on foetal development in Large White and Genex-Meishan gilts
Bibliographic record
Abstract
The effects of growth hormone-releasing factor (GRF), given in early gestation, on reproductive traits, foetal development and pre-weaning growth of piglets from two breeds were studied. Large White (LW, n = 26) and Genex-Meishan (GM, containing 50% Meishan genes, n = 37) pregnant gilts were divided in two groups: (1) saline injections (n = 33) and, (2) injections of 6.66 µg kg-1 of a GRF analogue (n = 30), given thrice daily from days 18 to 33 of gestation. Jugular blood samples were collected on days 17, 34 and 109 of gestation and were assayed for various hormones and metabolites. Thirty-six gilts were slaughtered on day 110 of gestation and uterine, foetal and placental measurements were obtained. The other 27 gilts farrowed. There was a day × treatment interaction (P < 0.001) for glucose, insulin, free fatty acids (FFA) and insulin-like growth factor I (IGF-I), with values being greater on day 34 in gilts receiving GRF. The increase in insulin concentration was greater in LW- than in GM-treated gilts (P = 0.02). Exogenous GRF increased foetal weight in LW litters only (1.13 ± 0.04 vs. 1.05 ± 0.03 kg; P = 0.04) whereas fat content of carcasses tended to be lower only in foetuses of treated GM gilts (5.3 ± 0.2 vs. 5.8 ± 0.2%; P = 0.1). Weight of the longissimus muscle and its fibre number were not influenced by GRF. Furthermore, growth of piglets to 28 d was not affected by GRF treatment (P > 0.1). In conclusion, GRF given in early gestation seems to have different effects in LW and GM litters, yet it does not alter pre-weaning growth rate. Key words: Molybdenum, molybdenosis, copper, mine tailings, reclamation, animal health
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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 | 0.001 |
| 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 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".