The effect of sodium thiosulfate on the metabolism of cis-platin in human plasma in vitro
Bibliographic record
Abstract
The anticancer drug cis-platin (CP) is widely used to treat patients, but it is also associated with significant side effects, including nephrotoxicity. Given that this metallodrug is intravenously (iv) administered, its biotransformations in the bloodstream are likely to be involved in mediating these side-effects. Previous studies have revealed that the iv administration of patients/mammalian model organisms with sodium thiosulfate (STS) can ameliorate the side effects of CP, but the underlying molecular basis remains elusive. We have studied the effect of STS on the metabolism of CP in human plasma in vitro by determining the platinum (Pt) distribution using size exclusion chromatography (SEC) coupled on-line to an inductively coupled plasma atomic emission spectrometer (ICP-AES). The addition of STS to plasma 10 min before CP was added accelerated the hydrolysis of CP and resulted in the formation of a Pt-STS complex. Conversely, when plasma was incubated with CP for up to 3 h and STS was added thereafter the analysis of the obtained mixture revealed that the formation of the same Pt-STS complex which in turn greatly diminished the plasma protein binding of CP-derived hydrolysis products. Thus, the observed amelioration of the side effects of CP by STS can be rationalized in terms of the rapid formation of a biologically inactive Pt-STS complex in the bloodstream. This is the first mechanism that can explain the amelioration of the side effects of CP by STS. Based on the fact that cis-platin remained in plasma for a considerable amount of time, the optimization of the administration sequence, the molar ratio and the time delay between the administration of both drugs emerges as a viable strategy to achieve a careful balance between ameliorating the side effects while leaving the antitumour activity intact. Our results demonstrate that in vitro studies can be useful to develop feasible strategies to mitigate the side-effects of Pt-based anticancer drugs in patients.
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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".