Oxidative Stress in Developmental Origins of Disease: Teratogenesis, Neurodevelopmental Deficits, and Cancer
Bibliographic record
Abstract
In the developing embryo and fetus, endogenous or xenobiotic-enhanced formation of reactive oxygen species (ROS) like hydroxyl radicals may adversely alter development by oxidatively damaging cellular lipids, proteins and DNA, and/or by altering signal transduction. The postnatal consequences may include an array of birth defects (teratogenesis), postnatal functional deficits, and diseases. In animal models, the adverse developmental consequences of in utero exposure to agents like thalidomide, methamphetamine, phenytoin, benzo[a]pyrene, and ionizing radiation can be modulated by altering pathways that control the embryonic ROS balance, including enzymes that bioactivate endogenous substrates and xenobiotics to free radical intermediates, antioxidative enzymes that detoxify ROS, and enzymes that repair oxidative DNA damage. ROS-mediated signaling via Ras, nuclear factor kappa B and related transducers also may contribute to altered development. Embryopathies can be reduced by free radical spin trapping agents and antioxidants, and enhanced by glutathione depletion. Further modulatory approaches to evaluate such mechanisms in vivo and/or in embryo culture have included the use of knockout mice, transgenic knock-ins and mutant deficient mice with altered enzyme activities, as well as antisense oligonucleotides, protein therapy with antioxidative enzymes, dietary depletion of essential cofactors and chemical enzyme inhibitors. In a few cases, measures anticipated to be protective have conversely enhanced the risk of adverse developmental outcomes, indicating the complexity of development and need for caution in testing therapeutic strategies in humans. A better understanding of the developmental effects of ROS may provide insights for risk assessment and the reduction of adverse postnatal consequences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".