The regulation of placental pericyte function through transforming growth factor β-1 signalling
Bibliographic record
Abstract
In the placenta, fetal-derived pericytes wrap the villous capillaries, directly interacting with endothelial cells to orchestrate the branching angiogenesis required to meet the demands of the growing fetus. In animal models of preeclampsia (PE), there is a positive correlation between reduced αSMA-expressing pericyte coverage and reduced vascular branching. Transforming Growth Factor β-1 (TGFβ-1) signalling is critical to placental development, is altered in placental pathology and alters pericyte function in other organs. However, the factors that influence placental pericyte function are under-investigated. In the present study, we investigated the in vitro effects of TGFβ-1 signalling on the population dynamics and functional measures of isolated term human placental pericytes, including angiogenic and inflammatory secretions, extracellular matrix (ECM) production, and phagocytic capacity. TGFβ-1 treatment promoted a proangiogenic phenotype with increased pro-angiogenic secretion of VEGFA and MMP-2 and reduced vessel stabilizing secretion of (ANG-1), without affecting the production of ECM components. Pericyte secretion of inflammation-associated adhesion molecule sVCAM-1, cytokine IL-6, chemokine MCP-1, and their phagocytosis capacity were attenuated with TGFβ-1 treatment. While some effects were mediated via the type I receptor ALK5, others were not, suggesting that TGFβ-1 signalling in placental pericytes may additionally occur via ALK1. Thus, it is likely that locally secreted TGFβ-1, contributes to the regulation of villous pericyte properties and their barrier function, and may implicate dysregulated TGFβ-1 signalling as a mechanism for the compromised placental fetal vascular branching observed in many placental pathologies. These findings are timely with emerging evidence that TGFβ is involved in the pathogenesis of PE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".