Exogenous genistein in late gestation: effects on fetal development and sow and piglet performance
Bibliographic record
Abstract
Due to their functional similarity to estradiol, phytoestrogens could prove to be beneficial in late gestating sows. The goal of this study was to determine the impact of providing the phytoestrogen genistein during late pregnancy on the performance of sows and their litters. In total, 56 gilts were equally divided into the two following groups on day 90 of gestation: (1) controls (CTL); and (2) two daily i.m. injections of 220 mg of genistein (GEN). Treatments were carried out until farrowing. Jugular blood samples were collected from 16 gilts/treatment on days 89 and 110 of gestation, and on days 3 and 21 of lactation. Milk samples were also obtained from those sows on day 3 of lactation. A male piglet from 16 CTL and 15 GEN litters was slaughtered at 24 h postpartum and a blood sample was obtained. The liver, heart and visceral organs were weighed and the semitendinosus (ST) muscle was collected and carcass composition was determined. The treatment increased (P0.1) on weight or backfat loss of sows during lactation, milk composition or weights of piglets. The pre-weaning mortality rate of piglets was very low (0.1). However, carcasses from GEN litters contained more fat than those from CTL litters (9.63% v. 8.34%, P0.1). In conclusion, injecting gilts with 440 mg/day of genistein in late gestation increased IGF1 concentrations in gilts and carcass fat in neonatal piglets, but had minimal effect on muscle development of piglets at birth and on the performance of lactating sows and their litters.
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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".