Characterization of sirolimus metabolites in pediatric solid organ transplant recipients
Why this work is in the frame
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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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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it