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Record W1933183331 · doi:10.1002/rcm.6129

Using complementary mass spectrometric approaches for the determination of methylprednisolone metabolites in human urine

2012· article· en· W1933183331 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSteroid Chemistry and Biochemistry
Canadian institutionsnot available
FundersInstituto de Salud Carlos IIIDepartament d'Innovació, Universitats i Empresa, Generalitat de CatalunyaWorld Anti-Doping Agency
KeywordsChemistryChromatographyDerivatizationMass spectrometryHydroxylationElectrospray ionizationTandem mass spectrometryChemical ionizationGas chromatography–mass spectrometryLiquid chromatography–mass spectrometryOrganic chemistryIonizationEnzyme

Abstract

fetched live from OpenAlex

RATIONALE: The metabolism of methylprednisolone is revisited in order to find new metabolites that could be important for distinguishing between different routes of administration. Recently developed liquid chromatography/tandem mass spectrometry (LC/MS/MS) strategies for the detection of corticosteroid metabolites have been applied to the study of methylprednisolone metabolism. METHODS: The structures of these metabolites were studied using two complementary mass spectrometric techniques: LC/MS/MS in product ion scan mode with electrospray ionization and gas chromatography/mass spectrometry (GC/MS) in full scan mode with electron ionization. Metabolites were also isolated by semipreparative liquid chromatography fractionation. Each fraction was divided into two aliquots; one was studied by LC/MS/MS and the other by GC/MS after methoxyamine-trimethylsilyl derivatization. RESULTS: The combination of all the structural information allowed us to propose a comprehensive picture of methylprednisolone metabolism in humans. Overall, 15 metabolites including five previously unreported compounds have been detected. Specifically, 16β,17α,21-trihydroxy-6α-methylpregna-1,4-diene-3,11,20-trione, 17α,20β,21-trihydroxy-6α-methylpregna-1,4-diene-3, 11-dione, 11β,17α,21-trihydroxy-6α-hydroxymethylpregna-1,4-diene-3,20-dione, 11β,17α,20ξ,21-tetrahydroxy-6α-hydroxymethylpregna-1,4-diene-3-one, and 17α,21-dihydroxy-6α-hydroxymethylpregna-1,4-diene-3,11,20-trione are proposed as feasible structures for the novel metabolites. In addition to the expected biotransformations: reduction of the C20 carbonyl, oxidation of the C11 hydroxy group, and further 6β-hydroxylation, we propose that hydroxylation of the 6α-methyl group can also take place. CONCLUSIONS: New metabolites have been identified in urine samples collected after oral administration of 40 mg of methylprednisolone. All identified metabolites were found in all samples collected up to 36 h after oral administration. However, after topical administration of 5 g of methylprednisolone aceponate, neither the parent compound nor any of the metabolites were detected.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.097
GPT teacher head0.343
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it