Lymphocyte contributions to altered endometrial angiogenesis during early and midgestation fetal loss
Bibliographic record
Abstract
Peri-implantation and midgestational fetal losses reduce potential litter sizes up to 40% in commercial swine. Peri-implantation studies [gestation days (gd)15-23] of porcine RNA from laser capture microdissected uterine lymphocytes and biopsies of mesometrial endometrium and trophoblast previously linked gd21-23 fetal arrest with transcriptional deficits in vascular endothelial growth factor (VEGF) and its regulatory factor, hypoxia inducible factor (HIF)-1alpha, and with elevations in IFN-gamma and TNF-alpha and suggested endometrial lymphocytes played a pivotal, proangiogenic role in fetal survival. Here, we address more comprehensively porcine endometrial angiogenesis by comparing transcription between endometrial endothelium and lymphocytes during early (gd20) and midgestation (gd50) losses and by incorporation of histopathology and protein immunolocalization of VEGF, placenta growth factor (PlGF), VEGF receptor I (VEGFRI), and VEGFRII. In healthy sites, endometrial lymphocytes transcribed more VEGF at gd50 than gd20, and transcripts were more abundant in lymphocytes than in endothelium or trophoblast. Arterial endothelial cells showed the most abundant transcription of PlGF. With fetal arrest, maternal transcripts for VEGF but not PlGF dropped, and fetal transcripts remained relatively stable. Maternal and fetal HIF-1alpha transcription declined. Lymphocytes preferentially transcribed VEGFRI over VEGFRII, and endometrial arterial endothelium and trophoblast preferentially transcribed VEGFRII. IFN-gamma and TNF-alpha transcripts were present in gd20 and gd50 healthy- and arresting-implantation sites. gd20 arrest was associated with greater transcription of IFN-gamma than TNF-alpha in maternal and fetal tissues. At gd50, this was reversed. Endometrial, vascular pathology was evident only at gd50. These data suggest the critical importance for lymphocyte-driven endometrial angiogenesis, which extends to midgestation.
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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".