High Levels of Activin A Detected in Preeclamptic Placenta Induce Trophoblast Cell Apoptosis by Promoting Nodal Signaling
Bibliographic record
Abstract
CONTEXT: The pregnancy-specific disorder preeclampsia is a major cause of maternal mortality and morbidity. Activin A has been suggested as a potential biomarker of the disease, but whether it plays a role in the pathology of preeclampsia or is just a manifestation of the disease is not fully understood. OBJECTIVE: The objective of the study was to examine the roles of Activin A on placental trophoblast cells under pathological conditions of preeclampsia. DESIGN: Placental and plasma productions of Activin A in healthy pregnant women and preeclamptic patients were compared by using clinical samples obtained from Peking University First Hospital during November 2005 to November 2007. The role of Activin A at pathological doses was investigated in human trophoblast cells. RESULTS: Plasma and placental productions of Activin A were significantly higher in preeclamptic patients when compared with normal pregnant subjects in a Chinese Han population. Treatment of trophoblast cells with high doses of Activin A resulted in a significant increase in cell apoptosis. This effect was blocked not only by silencing Activin A's receptor activin receptor-like kinase 4 but also by knockdown of Nodal's receptor ALK7. Important to note was that Activin A could significantly increase Nodal expression in trophoblast cells, and knockdown of Nodal resulted in evident blockage on Activin A-induced trophoblast cell apoptosis. CONCLUSION: High levels of Activin A observed in preeclamptic placenta may play a role in the pathogenesis of preeclampsia by inducing excessive apoptosis in placenta indirectly through enhancing Nodal expression.
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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".