PSI-7 Effects of sustained hyperprolactinemia in late gestation on mammary development of gilts
Bibliographic record
Abstract
Abstract This project sought to determine the effects of sustained hyperprolactinemia on mammary development in late-pregnant gilts. Gilts were divided into 3 groups on day 90 of gestation to receive i.m. injections of: 1) canola oil (CTL, n = 18) until day 109 of gestation, 2) domperidone (dopamine receptor antagonist) until day 96 (T7, n = 17) or, 3) domperidone until day 109 (T20, n = 17). Treated gilts also received domperidone orally from days 90 to 93. Blood was sampled on days 97 and 110 for prolactin and IGF-1 assays. Mammary glands were collected at necropsy on day 110 for compositional and cell proliferation analyses. The MIXED procedure of SAS was used for statistical analyses. On day 97 of gestation, prolactin concentrations were greater for T20 and T7 than CTL gilts (19.0, 18.9 and 6.0 ± 1.6 ng/mL, respectively, P < 0.001), and were also greater for T20 than T7 and CTL gilts on day 110 (21.7, 8.9 and 10.0 ± 1.5 ng/mL, respectively, P < 0.001). Concentrations of IGF-1 were greater for T7 and T20 than CTL gilts on day 97, and were greater for T20 vs T7 and CTL gilts on day 110 (P < 0.05). There were no effects of treatment (P > 0.1) on parenchymal or extraparenchymal tissue weights, or on cellular proliferation by immunohistochemistry for Ki67. Treatments did not alter concentrations of DM, fat or DNA (P > 0.1) in parenchyma, while concentrations of protein (P < 0.01) and RNA (P < 0.05) as well as total protein, RNA and DNA in parenchyma (P < 0.05) were lower in T20 than T7 or CTL gilts. Increasing prolactin concentrations for 7 or 20 d in late gestation had no beneficial effects on mammary composition, where sustained exposure for 20 d reduced metabolic activity.
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 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) | 0.002 | 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".