Expression of leptin and its long form receptor at the porcine maternal-fetal interface: contrasting healthy and arresting conceptus attachment sites during early and mid-pregnancy
Bibliographic record
Abstract
BACKGROUND: It is well established that spontaneous conceptus loss in swine is associated with an imbalance of both angiogenic and immunological factors. Leptin (LEP), a metabolic hormone, has also been implicated in the promotion of angiogenesis. In this study, LEP and its long form receptor (OB-Rb) were evaluated during porcine pregnancy to assess their basal level of expression and their potential role in conceptus development. METHODS: Expression and secretion of LEP and OB-Rb were quantified in the endometrium of non-pregnant (n = 5), and in the endometrium and chorioallantoic membrane (CAM) of pregnant sows (parity 2 to 5) at gestational days (gd) 20 (n = 8) and 50 (n = 8). Data were analyzed by a 3-way ANOVA testing the effects of conceptus health, tissue type and gestational day. RESULTS: Leptin and OB-Rb transcripts were significantly higher (P < 0.05) in pregnant than in non-pregnant sows. Significantly greater LEP (P < 0.001) was detected in the endometrial tissue at gd20 compared with gd50. At the protein level, the lowest LEP expression (P < 0.01) was detected in the CAM at gd50, while OB-Rb protein was significantly lower (P < 0.01) at gd50 in the CAM than in the endometrium collected from gd20 and gd50 conceptus attachment sites. Immunofluorescence staining confirmed the expression of these proteins at both gestational days and in both tissue types. CONCLUSIONS: Changes in the expression patterns of LEP and OB-Rb between gd20 and gd50 suggest a role for the LEP/OB-R complex at the early stages of porcine pregnancy, possibly affecting the attachment process. Further mechanistic studies are warranted to understand the specific role of leptin in porcine pregnancy.
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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".