Amino Thiols, Detoxification and Oxidative Stress in Pre-Eclampsia and Other Disorders of Pregnancy
Bibliographic record
Abstract
New knowledge of placental development and function suggests that several common complications of pregnancy could share a similar origin. It is suggested that impaired placental development in early pregnancy may lead to placental oxidative stress and subsequently to the maternal syndromes such as recurrent early pregnancy loss and pre-eclampsia. Oxidative stress has been most extensively investigated in pre-eclampsia, resulting in hundreds of publications and many reviews. In general the literature points to the presence of placental and maternal oxidative stress. However, conformity amongst the relevant data is not absolute, most probably the result of the diversity of biomarkers investigated and the methods employed to assess oxidative stress, which generally depend on the assessment of end products of oxidative stress. Recently, new techniques have been developed that use different approaches based on the "real-time" measurement of oxidative stress by the redox status of thiols or the assessment of superoxide generation, whereas the role of Phase I/Phase II biotransformation pathways in oxidative stress was recognised. This review focuses on this biotransformation system, the thiol redox status and the involvement of these systems in oxidative stress associated with reproduction and pregnancy disorders, with the emphasis being laid on the syndrome of pre-eclampsia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".