Differential Gene Expression in Endometrium, Endometrial Lymphocytes, and Trophoblasts during Successful and Abortive Embryo Implantation
Bibliographic record
Abstract
Prenatal mortality reaching 30% occurs during the first weeks of gestation in commercial swine. Mechanisms for this are unknown although poor uterine blood supply has been postulated. In other species, vascular endothelial growth factor, hypoxia-inducible factor 1-alpha, and IFN-gamma regulate gestational endometrial angiogenesis. Vascular endothelial growth factor and hypoxia-inducible factor 1-alpha are also important for placental angiogenesis while trophoblastic expression of Fas ligand is thought to protect conceptuses against immune-mediated pregnancy loss. In this study, we document dynamic, peri-implantation differences in transcription of genes for angiogenesis, cytokine production, and apoptosis regulation in the endometrium, and laser capture microdissected endometrial lymphocytes and trophoblasts associated with healthy or viable but arresting porcine fetuses. In healthy implantation sites, endometrial gene expression levels differed between anatomic subregions and endometrial lymphocytes showed much greater transcription of angiogenic genes than trophoblasts. In arresting fetal sites, uterine lymphocytes had no angiogenic gene transcription and showed rapid elevation in transcription of proinflammatory cytokines Fas and Fas ligand while trophoblasts showed elevated transcription of IFN-gamma and Fas. This model of experimentally accessible spontaneous fetal loss, involving blocked maternal angiogenesis, should prove valuable for further investigations of peri-implantation failure of normally conceived and surgically transferred embryos in many species, including the human.
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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".