Fetal Endothelial Colony Forming Cells Assist Vasculogenesis in the Pregnant Uterus
Bibliographic record
Abstract
Endothelial Colony Forming Cells (ECFCs) are more robust in the fetus than adult. Uterine blood flow increases in pregnancy, triggering expansion of the uterine vasculature. Fetal ECFCs may contribute to these adaptive requirements. (i) Fluorescent fetal‐derived cells were tracked in uteri in native female mice mated with eGFP‐expressing males. (ii) Human fetal eGFP‐expressing ECFCs were tracked in uteri of pregnant NOD/SCID mice, whose fetuses had been transplanted with these cells by in vivo intracardiac injection. (iii) In human uterine microvessels of mothers with male offspring, SRY gene was quantified by RT‐QPCR and (iv) Y‐chromosome hybridised in‐situ to localise fetal cells. (i) Fetal endothelial‐like cells were identified in murine uterine vessels (n=7). (ii) Transplanted human ECFCs (n=8) integrated into the uterine endothelium. (iii) RT‐QPCR detected SRY in 50% of human uterine vessels (n=12). The number of copies corresponded to 246±45 fetal cells/mm2 maternal endothelium (≈10% vessel wall). (iv) Fetal cells were observed in the human uterine endothelium (n=4). These data suggest that fetal ECFCs assist the vasculogenesis of the pregnant uterus and potentially vascular repair in the mother.
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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) | 0.002 | 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".