Sex-Specificity of Oxidative Stress in Newborns Leading to a Personalized Antioxidant Nutritive Strategy
Bibliographic record
Abstract
Oxidative stress is a critical process that triggers several diseases observed in premature infants. Growing recognition of the detriment of oxidative stress in newborns warrants the use of an antioxidant strategy that is likely to be nutritional in order to restore redox homeostasis. It appears essential to have a personalized approach that will take into account the age of gestation at birth and the sex of the infant. However, the link between sex and oxidative stress remains unclear. The aim of this study was to find a common denominator explaining the discrepancy between studies related to sex-specific effects of oxidative stress. Results highlight a specificity of sex in the levels of oxidative stress markers linked to the metabolism of glutathione, as measured in the intracellular compartments. Levels of all sex-dependent oxidative stress markers are greater and markers associated to a better antioxidant defense are lower in boys compared to girls during the neonatal period. This sex-specific discrepancy is likely to be related to estrogen metabolism, which is more active in baby-girls and promotes the activation of glutathione metabolism. CONCLUSION: our observations suggest that nutritive antioxidant strategies need to target glutathione metabolism and, therefore, should be personalized considering, among others, the sex specificity.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".