Peroxisome Proliferator-Activated Receptor-γ as a Potential Therapeutic Target in the Treatment of Preeclampsia
Bibliographic record
Abstract
Preeclampsia is a multisystemic disorder of pregnancy characterized by hypertension, proteinuria, and maternal endothelial dysfunction. It is a major cause of maternal and perinatal morbidity and mortality and is thought to be attributable, in part, to inadequate trophoblast invasion. Peroxisome proliferator-activated receptor-γ (PPAR-γ) is a ligand-activated transcription factor expressed in trophoblasts, and the vasculature of which activation has been shown to improve endothelium-dependent vasodilatation in hypertensive conditions. We investigated the effects of the administration of a PPAR-γ agonist using the reduced uterine perfusion pressure (RUPP) rat model of preeclampsia. The selective PPAR-γ agonist, rosiglitazone, was administered to pregnant rats that had undergone RUPP surgery. To investigate whether any observed beneficial effects of PPAR-γ activation were mediated by the antioxidant enzyme, heme oxygenase 1, rosiglitazone was administered in combination with the heme oxygenase 1 inhibitor tin-protoporphyrin IX. RUPP rats were characterized by hypertension, endothelial dysfunction, and elevated microalbumin:creatinine ratios. Rosiglitazone administration ameliorated hypertension, improved vascular function, and reduced the elevated microalbumin:creatinine ratio in RUPP rats. With the exception of microalbumin:creatinine ratio, these beneficial effects were abrogated in the presence of the heme oxygenase 1 inhibitor. Administration of a PPAR-γ agonist prevented the development of several of the pathophysiological characteristics associated with the RUPP model of preeclampsia, via a heme oxygenase 1-dependent pathway. The findings from this study provide further insight into the underlying etiology of preeclampsia and a potential therapeutic target for the treatment of preeclampsia.
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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 | 0.000 | 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) | 0.000 | 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".