Carbon isotopic characterization of prednisolone and prednisone pharmaceutical formulations: Implications in antidoping analysis
Bibliographic record
Abstract
Abstract Twenty‐two pharmaceutical formulations containing prednisolone or prednisone commercially available in Italy, Belgium, Spain, Brazil, and India were analyzed through a specific gas chromatography combustion isotope ratio mass spectrometry (GC‐C‐IRMS) method. All of them showed typical non‐endogenous δ 13 C values, except for the Belgian nasal spray, Sofrasolone®, with a less depleted 13 C content (−17.84 ± 0.18‰). Observational studies were performed on two volunteers in therapy with Sofrasolone® to confirm the applicability of the method and to suggest adequate interpretation criteria also in the case of drugs with less negative δ 13 C values. Urine samples were collected before, during, and within the 36 hours after the administration of the spray. Both δ 13 C values and urinary concentrations of prednisolone and prednisone were evaluated. All samples were subjected to an adequate pre‐treatment (enzymatic hydrolysis, liquid/liquid extraction, and two sequential HPLC steps) before injection to the GC‐C‐IRMS instrument, according to the method recently developed and validated in our laboratory. Pregnanediol (PD), tetrahydro‐11‐deoxycortisol (THS), and pregnanetriol (PT) were selected as endogenous reference compounds (ERC). The excretion profile was estimated through liquid chromatography coupled to tandem mass spectrometry (LC–MS/MS) method used routinely for the quali‐quantitative detection of glucocorticoids. δ 13 C values and urinary levels of prednisolone and prednisone were also determined after the intake of one single vial of Sintredius®, a prednisolone oral formulation with a conventional more negative δ 13 C value (−29.28 ± 0.25‰). Finally, the potential masking effect that combined therapy with Sofrasolone® and Sintredius® could induce on the IRMS findings was investigated.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".