Reactive Oxygen Species and Protein Kinases Modulate the Level of Phospho-MEK-Like Proteins During Human Sperm Capacitation1
Bibliographic record
Abstract
Capacitation is an essential process by which spermatozoa acquire fertilizing ability. Reactive oxygen species (ROS), protein kinase A (PKA), protein kinase C (PKC), protein tyrosine kinases (PTKs), and the extracellular signal-regulated protein kinase (ERK or mitogen-activated protein kinase [MAPK]) pathway regulate sperm capacitation. Our aim was to evaluate the phosphorylation of MEK (MAPK kinase or MAP2K) or MEK-like proteins in human sperm capacitation and its modulation by ROS and kinases. Immunoblotting using an anti-phospho-MEK antibody indicated that the phosphorylation of three protein bands (55, 94, and 115 kDa) increased in spermatozoa treated with fetal cord serum ultrafiltrate (FCSu), BSA, or isobutylmethylxanthine plus dibutyryl cAMP as capacitating agents. These phospho-MEK-like proteins are localized along the sperm flagellum. The MEK-inhibitors PD98059 and U126 prevented this phosphorylation, suggesting that these proteins are MEK-like proteins. The ROS scavengers prevented, and the addition of H(2)O(2) or spermine-NONOate (nitric oxide donor) triggered, the increase of phospho-MEK-like proteins. The capacitation-related increases in phospho-MEK-like proteins induced by FCSu, H(2)O(2), and spermine-NONOate were similarly modulated by PKA, PKC, and PTK, suggesting ROS as mediators in this phenomenon. These results indicate that phospho-MEK-like proteins are modulated by ROS and kinases and probably represent an intermediary step between the early events and the late tyrosine phosphorylation associated with capacitation.
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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) | 0.002 | 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".