Role of oxidative stress in the dysfunction of the placental endothelial nitric oxide synthase in preeclampsia
Bibliographic record
Abstract
Preeclampsia (PE) is a multifactorial pregnancy disease, characterized by new-onset gestational hypertension with (or without) proteinuria or end-organ failure, exclusively observed in humans. It is a leading cause of maternal morbidity affecting 3–7% of pregnant women worldwide. PE pathophysiology could result from abnormal placentation due to a defective trophoblastic invasion and an impaired remodeling of uterine spiral arteries, leading to a poor adaptation of utero-placental circulation. This would be associated with hypoxia/reoxygenation phenomena, oxygen gradient fluctuations, altered antioxidant capacity, oxidative stress, and reduced nitric oxide (NO) bioavailability. This results in part from the reaction of NO with the radical anion superoxide (O2•−), which produces peroxynitrite ONOO-, a powerful pro-oxidant and inflammatory agent. Another mechanism is the progressive inhibition of the placental endothelial nitric oxide synthase (eNOS) by oxidative stress, which results in eNOS uncoupling via several events such as a depletion of the eNOS substrate L-arginine due to increased arginase activity, an oxidation of the eNOS cofactor tetrahydrobiopterin (BH4), or eNOS post-translational modifications (for instance by S-glutathionylation). The uncoupling of eNOS triggers a switch of its activity from a NO-producing enzyme to a NADPH oxidase-like system generating O2•−, thereby potentiating ROS production and oxidative stress. Moreover, in PE placentas, eNOS could be post-translationally modified by lipid peroxidation-derived aldehydes such as 4-oxononenal (ONE) a highly bioreactive agent, able to inhibit eNOS activity and NO production. This review summarizes the dysfunction of placental eNOS evoked by oxidative stress and lipid peroxidation products, and the potential consequences on PE pathogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".