The double life of MULE in preeclamptic and IUGR placentae
Bibliographic record
Abstract
The E3 ubiquitin ligase MULE (Mcl-1 Ubiquitin Ligases E3) targets myeloid cell leukemia factor 1 (Mcl-1) and tumor suppressor p53 for proteasomal degradation. Although Mcl-1 and p53 have been implicated in trophoblast cell death in preeclampsia (PE) and intrauterine growth restriction (IUGR), the mechanisms regulating their expression in the human placenta remains elusive. Herein, we investigated MULE's involvement in regulating Mcl-1 and p53 degradation during normal and abnormal (PE, IUGR) placental development. MULE expression peaked at 5-7 weeks of gestation, when oxygen tension is low and inversely correlated with that of Mcl-1 and p53. MULE efficiently bound to Mcl-1 and p53 and regulated their ubiquitination during placental development. Exposure of first trimester villous explants to 3% O(2) resulted in elevated MULE expression compared with 20% O(2). Low-oxygen-induced MULE expression in JEG3 choriocarcinoma cells was abolished by hypoxia-inducible factor (HIF)-1α siRNA. MULE was overexpressed in both PE and IUGR placentae. In PE, MULE preferentially targeted p53 for degradation, allowing accumulation of pro-apoptotic Mcl-1 isoforms. In IUGR, however, MULE targeted pro-survival Mcl-1, allowing p53 to accumulate and exert its apoptotic function. These data demonstrate that oxygen regulates Mcl-1 and p53 stability during placentation via HIF-1-controlled MULE expression. The different preferential targets of MULE in PE and IUGR placentae classify early-onset PE and IUGR as distinct molecular pathologies.
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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) | 0.001 | 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".