Bibliographic record
Abstract
Milk yield is a crucial component of a sow operation because it is a limiting factor for piglet growth rate. Stimulating mammary development is one avenue that could be used to improve sow milk production. A number of studies have shown that nutrition of gilts or sows during the periods of rapid mammary accretion occurring during prepuberty, gestation, and lactation can affect mammary development. The present review provides an overview of all the information currently published on the subject. Various nutritional treatments can bring about increases in mammary tissue weight ranging from 27% to 52%. It was clearly established that feed restriction from 90 d of age (but not before 90 d) until puberty has detrimental effects on mammary development in pigs. Ad libitum feeding during that period increased mammary parenchymal weight by 36% to 52%. Body condition is also important because gilts that were obese (36-mm backfat) or too lean (12- to 15-mm backfat) in late gestation had less developed mammary tissue. Furthermore, overfeeding energy in late gestation seems to be detrimental. On the other hand, increasing energy and protein intakes of sows during lactation was beneficial for development of mammary tissue. Feeding certain plant extracts with estrogenic or hyperprolactinemic properties may also prove beneficial in stimulating mammary development at specific physiological periods. For example, feeding genistein to prepubertal gilts increased parenchymal DNA by 44%. Even though research was carried out on the nutritional control of mammogenesis in pigs, it is evident that much remains to be learned before the best nutritional strategy to enhance mammary development can be developed.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".