PRG2 and AQPEP are misexpressed in fetal membranes in placenta previa and percreta <b>†</b>
Bibliographic record
Abstract
The obstetrical conditions placenta accreta spectrum (PAS) and placenta previa are a significant source of pregnancy-associated morbidity and mortality, yet the specific molecular and cellular underpinnings of these conditions are not known. In this study, we identified misregulated gene expression patterns in tissues from placenta previa and percreta (the most extreme form of PAS) compared with control cases. By comparing this gene set with existing placental single-cell and bulk RNA-Seq datasets, we show that the upregulated genes predominantly mark extravillous trophoblasts. We performed immunofluorescence on several candidate molecules and found that PRG2 and AQPEP protein levels are upregulated in both the fetal membranes and the placental disk in both conditions. While this increased AQPEP expression remains restricted to trophoblasts, PRG2 is mislocalized and is found throughout the fetal membranes. Using a larger patient cohort with a diverse set of gestationally aged-matched controls, we validated PRG2 as a marker for both previa and PAS and AQPEP as a marker for only previa in the fetal membranes. Our findings suggest that the extraembryonic tissues surrounding the conceptus, including both the fetal membranes and the placental disk, harbor a signature of previa and PAS that is characteristic of EVTs and that may reflect increased trophoblast invasiveness.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".