VEGF‐A regulated by progesterone governs uterine angiogenesis and vascular remodelling during pregnancy
Bibliographic record
Abstract
The features and regulation of uterine angiogenesis and vascular remodelling during pregnancy are poorly defined. Here we show that dynamic and variable decidual angiogenesis (sprouting, intussusception and networking), and active vigorous vascular remodelling such as enlargement and elongation of 'vascular sinus folding' (VSF) and mural cell drop-out occur distinctly in a spatiotemporal manner in the rapidly growing mouse uterus during early pregnancy - just after implantation but before placentation. Decidual angiogenesis is mainly regulated through VEGF-A secreted from the progesterone receptor (PR)-expressing decidual stromal cells which are largely distributed in the anti-mesometrial region (AMR). In comparison, P4 -PR-regulated VEGF-A-VEGFR2 signalling, ligand-independent VEGFR3 signalling and uterine natural killer (uNK) cells positively and coordinately regulate enlargement and elongation of VSF. During the postpartum period, Tie2 signalling could be involved in vascular maturation at the endometrium in a ligand-independent manner, with marked reduction of VEGF-A, VEGFR2 and PR expressions. Overall, we show that two key vascular growth factor receptors - VEGFR2 and Tie2 - strikingly but differentially regulate decidual angiogenesis and vascular remodelling in rapidly growing and regressing uteri in an organotypic manner.
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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".