Tyrosine nitration in human spermatozoa: a physiological function of peroxynitrite, the reaction product of nitric oxide and superoxide
Bibliographic record
Abstract
Tyrosine nitration is a widely used marker of peroxynitrite (ONOO-) produced from the reaction of nitric oxide (NO.) with superoxide (O2(.-)). Since human spermatozoa are able to produce both NO. and O2(.-) during capacitation in vitro, we investigated whether spontaneous tyrosine nitration of proteins occurs in human spermatozoa and evaluated the physiological effects of peroxynitrite on sperm function. We report here that human spermatozoa, incubated for 8 h under conditions conducive to capacitation, display a reproducible pattern of protein tyrosine nitration. Several proteins with mol. wt of 105-14 kDa become increasingly tyrosine-nitrated after 15 min incubation and then minimal changes are observed. Treatment of capacitated spermatozoa with human follicular fluid or calcium ionophore causes an increase of the nitrotyrosine content of proteins at the mol. wt of 85 kDa. Moreover, exposure of spermatozoa to ONOO- (2.5-50 micromol/l) increases motility and primes spermatozoa to respond earlier to human follicular fluid. ONOO- also increases protein tyrosine nitration and phosphorylation in a concentration-dependent manner. Taken together, these results demonstrate that tyrosine nitration of sperm proteins occurs in capacitated human spermatozoa, and that low concentrations of ONOO- modulate sperm functions, emphasizing the concept that capacitation is part of an oxidative process.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".