Rosiglitazone-Mediated Activation of PPARγ Induces PlGF Expression in Trophoblast Cells
Bibliographic record
Abstract
Preeclampsia (PE) is a hypertensive pregnancy disorder marked by impaired trophoblast invasion and placental vascular dysfunction, resulting in severe maternal and fetal complications. Placental growth factor (PlGF) is critical for proper placental angiogenesis and is transcriptionally regulated by glial cell missing-1 (GCM1), a downstream effector of peroxisome proliferator-activated receptor-gamma (PPARγ). Decreased PPARγ activity in PE may therefore contribute to diminished PlGF levels, worsening placental pathology. In this study, we investigated the mechanistic role of rosiglitazone, a PPARγ agonist, in rescuing PlGF expression under 1.5% oxygen/reoxygenation stress mimicking PE. Using JEG-3 trophoblast cells, we show that rosiglitazone enhances PPARγ nuclear translocation, leading to increased GCM1 and cyto-protective heme oxygenase-1 (HO-1) expression, and subsequent upregulation of PlGF production under both 21% oxygen and 1.5% oxygen/reoxygenation conditions. Pharmacologic inhibition of PPARγ with T0070907 or siRNA-mediated knockdown abrogated these effects, underscoring PPARγ's essential role in maintaining GCM1-driven PlGF expression. Notably, rosiglitazone treatment rescued PlGF production in 1.5% oxygen/reoxygenation-stressed cells, highlighting a potential therapeutic strategy to mitigate placental dysfunction. These findings define the PPARγ-GCM1-PlGF axis as a mechanistic cornerstone of placental health and suggest that pharmacological activation of PPARγ may offer clinical benefit in improving pregnancy outcomes in PE.
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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 | 0.001 |
| 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".