JMJD6 Dysfunction Due to Iron Deficiency in Preeclampsia Disrupts Fibronectin Homeostasis Resulting in Diminished Trophoblast Migration
Bibliographic record
Abstract
The mechanisms contributing to excessive fibronectin in preeclampsia, a pregnancy-related disorder, remain unknown. Herein, we investigated the role of JMJD6, an O2- and Fe2+-dependent enzyme, in mediating placental fibronectin processing and function. MALDI-TOF identified fibronectin as a novel target of JMJD6-mediated lysyl hydroxylation, preceding fibronectin glycosylation, deposition, and degradation. In preeclamptic placentae, fibronectin accumulated primarily in lysosomes of the mesenchyme. Using primary placental mesenchymal cells (pMSCs), we found that fibronectin fibril formation and turnover were markedly impeded in preeclamptic pMSCs, partly due to impaired lysosomal degradation. JMJD6 knockdown in control pMSCs recapitulated the preeclamptic FN phenotype. Importantly, preeclamptic pMSCs had less total and labile Fe2+ and Hinokitiol treatment rescued fibronectin assembly and promoted lysosomal degradation. Time-lapse imaging demonstrated that defective ECM deposition by preeclamptic pMSCs impeded HTR-8/SVneo cell migration, which was rescued upon Hinokitiol exposure. Our findings reveal new Fe2+-dependent mechanisms controlling fibronectin homeostasis/function in the placenta that go awry in preeclampsia.
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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".