Comparative hydrolysis and plasma protein binding of cis-platin and carboplatin in human plasma in vitro
Why this work is in the frame
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Bibliographic record
Abstract
Platinum-based anti-cancer drugs are widely used to treat cancer in patients, but they also exhibit severe toxic side-effects. Considering that cis-platin and carboplatin are intravenously administered, their biotransformations in the bloodstream are likely to be directly involved in determining their toxic side-effects, but they are poorly understood. We added pharmacologically relevant doses of cis-platin or carboplatin to human plasma from healthy male or female volunteers in vitro at 37 °C and determined the platinum-distribution in plasma after 5 min, 3 h and 24 h using size exclusion chromatography-inductively coupled plasma atomic emission spectrometry (SEC-ICP-AES). The results revealed a negligible inter-individual variation of the platinum-distribution between males and females and faster hydrolysis of cis-platin than carboplatin. Related to this, 95% of platinum was protein-bound 24 h after the addition of cis-platin to plasma, whereas 40% of platinum was protein-bound in the case of carboplatin. Interestingly, cis-platin and carboplatin-derived platinum species appeared to bind to the same 3 plasma proteins at the 3 h time point and thereafter. The analysis of cis-platin and carboplatin-spiked phosphate buffered saline (PBS) revealed a common platinum-containing hydrolysis product that was also detected in plasma. Since cis-platin is associated with more toxic side-effects in patients than carboplatin (even though it is administered at lower doses), our in vitro data suggest that the toxic side-effects of the investigated platinum-drugs may be predominantly determined by the indiscriminate translocation of the parent drugs to malignant and healthy cells. This information may help to mitigate the toxic side-effects of platinum-containing drugs by devising strategies to delay the influx of the parent drugs into non-target tissues.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it