Modification of endothelial nitric oxide synthase by 4-oxo-2(E)-nonenal(ONE) in preeclamptic placentas
Bibliographic record
Abstract
Preeclampsia (PE) is a leading cause of pregnancy complications, affecting 3-7% of pregnant women worldwide. The pathophysiology of preeclampsia involves a redox imbalance, oxidative stress and a reduced nitric oxide (NO) bioavailability. The molecular and cellular mechanisms leading to the dysfunction of the placental endothelial NO synthase (eNOS) are not clarified. This study was designed to investigate whether aldehydes generated by lipid peroxidation products (LPP), may contribute to placental eNOS dysfunction in PE. The analysis of placentas from PE-affected patients and normal pregnancies, showed a significant increase in protein carbonyl content, indicative of oxidative stress-induced protein modification, as shown by the accumulation of acrolein, 4-hydroxynonenal (HNE), and 4-oxo-2(E)-nonenal (ONE) adducts in PE placentas. In contrast, the levels of these LPP-adducts were low in placentas from normal pregnancies. Immunofluorescence and confocal experiments pointed out a colocalization of eNOS with ONE-Lys adducts, whereas eNOS was not modified in normal placentas. LC-MS/MS analysis of recombinant eNOS preincubated with ONE, allowed to identify several ONE-modified Lys-containing peptides, confirming that eNOS may undergo post-translational modification by LPP. The preincubation of HTR-8/SVneo human trophoblasts (HTR8) with ONE, resulted in ONE-Lys modification of eNOS and a reduced generation of NO. ONE inhibited the migration of HTR8 trophoblasts in the wound closure model, and this was partly restored by the NO donor, NOC-18, which confirmed the important role of NO in the invasive potential of trophoblasts. In conclusion, placental eNOS is modified by ONE in PE placentas, which emphasizes the sensitivity of this protein to oxidative stress in the disturbed redox environment of preeclamptic pregnancies.
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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 | 0.000 | 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".