Characterization of sirolimus metabolites in pediatric solid organ transplant recipients
Bibliographic record
Abstract
Potential age-dependent changes of sirolimus metabolite patterns in pediatric renal transplant recipients remain elusive. Thirteen pediatric solid organ transplant recipients (10 kidney, one combined liver-kidney, two liver, mean age 8.0 +/- 5.0 yr) underwent a sirolimus pharmacokinetic profile in steady-state with 10 samples drawn over 12 h post-intake to calculate the AUC(0-12 h). Concentrations of sirolimus and metabolite were quantified using a validated LC-MS/MS assay and metabolite structures were identified directly in blood extracts using LC-MS/iontrap. Average sirolimus AUC(0-12 h) was 64.9 +/- 29.7 ng h/mL. Median (range) AUC(0-12 h) for each metabolite (ng h/mL) was: 12-hydroxy-sirolimus 7.6 (0.2-18.8), 46-hydroxy sirolimus 3.1 (0.0-12.4), 24-hydroxy sirolimus 4.3 (0.0-12.6), piperidine-hydroxy sirolimus 3.5 (0.0-8.3), 39-O-desmethyl sirolimus 3.6 (0.0-11.3), 16-O-desmethyl sirolimus 5.0 (0.1-9.9), and di-hydroxy sirolimus 4.3 (0.0-32.5). The metabolites reached a median total AUC(0-12 h) of 60% of that of sirolimus. The range was 2.6-136%, indicating significant variability. In all, 77.5% of the metabolites were hydroxylated, while 39-O-desmethyl sirolimus accounted for only 8.4% of the AUC(0-12 h). This is clinically relevant as 39-O-desmethyl sirolimus shows 86-127% cross-reactivity with the antibody of the widely used Abbott sirolimus immunoassay. The metabolism of sirolimus in the children included in our study differed from that reported in adults, which should be considered when monitoring sirolimus exposure immunologically.
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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) | 0.000 | 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) | 0.000 | 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 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".