Chemoprotection by<scp>d</scp>-methionine against cisplatin-induced side-effects: insight from in vitro studies using human plasma
Bibliographic record
Abstract
Animal studies have shown that the nephrotoxicity and ototoxicity of the anti-cancer drug cisplatin (CP) can be ameliorated by the co-administration with D-methionine. The molecular mechanisms of this activity, however, are not well understood. Since CP is intravenously administered, the underlying chemistry may involve the interaction of CP-derived Pt-species with D-methionine in the bloodstream. Our previous studies have shown that the chemoprotective agents N-acetyl-l-cysteine and sodium thiosulfate modulate the metabolism of CP in human plasma in vitro, albeit in a different manner. Using a metallomics approach, we show that the incubation of human plasma with D-methionine and CP (molar ratio of 20 : 1) leads to the formation of a Pt-D-methionine complex independent of the order of addition. These results were corroborated by analogous experiments that were carried out using PBS-buffer instead of plasma. In addition, CP and D-methionine were added simultaneously to PBS-buffer and samples were analyzed at certain time intervals by the same metallomics method and LC-ESI-MS over a ∼21 h time period. Whereas the intermediate [Pt(NH3)Cl(D-methionine)](+) species was detected between 1-4 h, only the terminal [Pt(D-methionine)2](+) complex was present 21 h later. Combined, these studies demonstrate that in plasma and at the 20 : 1 D-methionine : CP molar ratio, an early CP hydrolysis product reacts with D-methionine to form a 1 : 1 complex that is followed by the formation of a 2 : 1 compound at a later time point. The formation of these Pt-D-methionine species may therefore play an important role in the processes by which D-methionine protects mammalian organisms against CP-induced toxicities.
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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".