Oxidative versus reductive stress: a delicate balance for sperm integrity
Bibliographic record
Abstract
Despite the long-standing notion of “oxidative stress,” as the main mediator of many diseases including male infertility induced by increased reactive oxygen species (ROS), recent evidence suggests that ROS levels are also increased by “reductive stress,” due to over-accumulation of reductants. Damaging mechanisms, like guanidine oxidation followed by DNA fragmentation, could be observed following reductive stress. Excessive accumulation of the reductants may arise from excess dietary supplementation over driving the one-carbon cycle and transsulfuration pathway, overproduction of NADPH through the pentose phosphate pathway (PPP), elevated levels of GSH leading to impaired mitochondrial oxidation, or as a result NADH accumulation. In addition, lower availability of oxidized reductants like NAD+, oxidized glutathione (GSSG), and oxidized thioredoxins (Trx-S2) induce electron leakage leading to the formation of hydrogen peroxide (H2O2). In addition, a lower level of NAD+ impairs poly (ADP-ribose) polymerase (PARP)-regulated DNA repair essential for proper chromatin integrity of sperm. Because of the limited studies regarding the possible involvement of reductive stress, antioxidant therapy remains a central approach in the treatment of male infertility. This review put forward the concept of reductive stress and highlights the potential role played by reductive vs oxidative stress at pre-and post-testicular levels and considering dietary supplementation.
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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) | 0.000 | 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 | 0.001 |
| 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".