Hormones, IgG and lactose changes around parturition in plasma, and colostrum or saliva of multiparous sows
Bibliographic record
Abstract
Blood, colostrum and saliva samples were serially taken from 6 multiparous sows from day 109 of gestation until day 3 postpartum. Plasma was assayed for oestradiol-17beta (E2), progesterone (P4), prolactin (PRL), cortisol, immunoglobulin G (IgG) and lactose. Colostrum was assayed for E2, P4, IgG and lactose. Lactoserum, obtained after ultra centrifugation of colostrum, was assayed for PRL. Saliva was assayed for cortisol. Time-related variations in hormone, IgG and lactose concentrations measured in plasma were parallel to those measured in colostrum, lactoserum or saliva. However, the concentrations were higher in colostrum or lactoserum and lower in saliva than in plasma. Ratios of concentrations of cortisol in saliva and PRL in lactoserum over those in plasma did not vary with time and averaged 0.2 and 1.6, respectively. Conversely, the ratios of concentrations of E2 and P4 in colostrum over those in plasma varied with time (P < 0.05) but were quite constant before the end of parturition, averaging 2.7 and 3.6, respectively. The ratios of concentrations of IgG and lactose in colostrum over those in plasma also varied with time (P < 0.05). The concentrations of hormones in plasma on the one hand and in colostrum, lactoserum or saliva on the other hand were significantly correlated but correlations varied with time (PRL across periods: r = 0.31; cortisol across periods: r = 0.60; E2 during parturition: r = 0.83; P4 before parturition: r = 0.82; P4 during parturition: r = 0.67). The present results indicate that around parturition, assays of hormones in colostrum or saliva can be used to study the hormonal status of sows. Furthermore, variations in colostrum and plasma concentrations of IgG and lactose are good indicators of the transition from colostrum to milk synthesis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".