Molecular Evidence of Placental Hypoxia in Preeclampsia
Bibliographic record
Abstract
BACKGROUND: Oxygen plays a central role in human placental pathologies including preeclampsia, a leading cause of fetal and maternal death and morbidity. Insufficient uteroplacental oxygenation in preeclampsia is believed to be responsible for the molecular events leading to the clinical manifestations of this disease. DESIGN: Using high-throughput functional genomics, we determined the global gene expression profiles of placentae from high altitude pregnancies, a natural in vivo model of chronic hypoxia, as well as that of first-trimester explants under 3 and 20% oxygen, an in vitro organ culture model. We next compared the genomic profile from these two models with that obtained from pregnancies complicated by preeclampsia. Microarray data were analyzed using the binary tree-structured vector quantization algorithm, which generates global gene expression maps. RESULTS: Our results highlight a striking global gene expression similarity between 3% O(2)-treated explants, high-altitude placentae, and importantly placentae from preeclamptic pregnancies. We demonstrate herein the utility of explant culture and high-altitude placenta as biologically relevant and powerful models for studying the oxygen-mediated events in preeclampsia. CONCLUSION: Our results provide molecular evidence that aberrant global placental gene expression changes in preeclampsia may be due to reduced oxygenation and that these events can successfully be mimicked by in vivo and in vitro models of placental hypoxia.
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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".