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Record W2510884929 · doi:10.1002/dta.2020

Analysis of phenylbutazone residues in horse tissues with and without enzyme‐hydrolysis by LC‐MS/MS

2016· article· en· W2510884929 on OpenAlexaffabout
Joe O. Boison, Trisha Dowling, Ron J. Johnson, Jana Kinar

Bibliographic record

VenueDrug Testing and Analysis · 2016
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsUniversity of GuelphUniversity of SaskatchewanSaskatchewan Health Authority
Fundersnot available
KeywordsOxyphenbutazonePhenylbutazoneChemistryChromatographyEnzymatic hydrolysisMetaboliteHorseHydrolysisSolid phase extractionPharmacologyMass spectrometryMedicineBiochemistryBiology

Abstract

fetched live from OpenAlex

Phenylbutazone (PBZ) is permitted to be used for the treatment of musculoskeletal pain and inflammation in race horses but it is not approved for use in horses destined for human consumption. In a recent study initiated in our laboratory to study the disposition of PBZ and its oxyphenbutazone (OXPBZ) metabolite in equine tissues, we compared the effect of an additional enzymatic hydrolysis step with ß-glucuronidase on the results of the analysis for PBZ without enzymatic hydrolysis. Incurred tissue samples obtained from a female horse dosed with PBZ at 8.8 mg/kg for 3 days and sacrificed 6 days following the last administration were used for this study. Liver, kidney, and muscle tissues were collected, extracted, cleaned up on a silica-based solid-phase extraction (SPE) preceded by a weak-anion exchange SPE and analyzed with our in-house validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for PBZ and OXPBZ. Addition of the hydrolysis step resulted in a significant increase in recovery of both PBZ and OXPBZ residues. © 2016 Her Majesty the Queen in Right of Canada. Drug Testing and Analysis © 2016 John Wiley & Sons, Ltd.

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.248
Teacher spread0.239 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2016
Admission routes2
Has abstractyes

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