Detection and quantification of (<i>R</i>) and (<i>S</i>)‐dechloroethylifosfamide metabolites in plasma from children by enantioselective LC/MS/MS
Bibliographic record
Abstract
Ifosfamide (IF), a potent chemotherapeutic agent for solid tumors, is known to cause high rates of nephrotoxicity in children with cancer, which is most likely due to the renal production of the metabolite chloroacetaldehyde. Using plasma samples obtained from pediatric oncology patients, we developed a simple nonderivatizing enantioselective liquid chromatography mass spectrometry method to detect the (R) and (S)-2- and 3-dechloroethylifosfamide metabolites. The (R) and (S)-enantiomers of the 2- and 3-DCEIF (N-3-dechlroethylifosfamide) were detectable in all 22 patients' samples with levels ranging from 9.9 to 238.7 ng/ml for (R)-2-DCEIF, 15.8 to 663.0 ng/ml for (S)-2-DCEIF, 20.8 to 852.8 ng/l for (R)-3-DCEIF and 28.0 to 862.0 ng/ml for (S)-3-DCEIF. In addition, the lower limit of quantification for this method is 1 ng/ml. Future studies should concentrate on (R) or (S) production of the 2-DCEIF and 3-DCEIF and subsequently chloroacetaldehyde formation with the aim of considering the administration of only the (R)-IF as its metabolism results in a lower production of chloroacetaldehyde.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".