Methotrexate Promotes Platelet Apoptosis via JNK-Mediated Mitochondrial Damage: Alleviation by N-Acetylcysteine and N-Acetylcysteine Amide
Bibliographic record
Abstract
Thrombocytopenia in methotrexate (MTX)-treated cancer and rheumatoid arthritis (RA) patients connotes the interference of MTX with platelets. Hence, it seemed appealing to appraise the effect of MTX on platelets. Thereby, the mechanism of action of MTX on platelets was dissected. MTX (10 μM) induced activation of pro-apoptotic proteins Bid, Bax and Bad through JNK phosphorylation leading to ΔΨm dissipation, cytochrome c release and caspase activation, culminating in apoptosis. The use of specific inhibitor for JNK abrogates the MTX-induced activation of pro-apoptotic proteins and downstream events confirming JNK phosphorylation by MTX as a key event. We also demonstrate that platelet mitochondria as prime sources of ROS which plays a central role in MTX-induced apoptosis. Further, MTX induces oxidative stress by altering the levels of ROS and glutathione cycle. In parallel, the clinically approved thiol antioxidant N-acetylcysteine (NAC) and its derivative N-acetylcysteine amide (NACA) proficiently alleviate MTX-induced platelet apoptosis and oxidative damage. These findings underpin the dearth of research on interference of therapeutic drugs with platelets, despite their importance in human health and disease. Therefore, the use of antioxidants as supplementary therapy seems to be a safe bet in pathologies associated with altered platelet functions.
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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".