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Record W2129699253 · doi:10.1002/jms.1218

Quantitation of phenylalanine and its <i>trans</i>‐cinnamic, benzoic and hippuric acid metabolites in biological fluids in a single GC‐MS analysis

2007· article· en· W2129699253 on OpenAlexafffund
Christineh N. Sarkissian, Charles R. Scriver, Orval Mamer

Bibliographic record

VenueJournal of Mass Spectrometry · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsMcGill UniversityMontreal Children's Hospital
FundersCanadian Institutes of Health ResearchBioMarin Pharmaceutical
KeywordsChemistryHippuric acidPhenylalanineChromatographyBenzoic acidCinnamic acidIsotopomersDetection limitIsotope dilutionPhenylalanine ammonia-lyaseUrineMass spectrometryOrganic chemistryBiochemistryAmino acid

Abstract

fetched live from OpenAlex

We describe a sensitive, simple and convenient stable isotope dilution assay developed to study endogenous metabolism of administered stable isotope-labeled phenylalanine (Phe) in phenylketonuric (PKU) mice treated experimentally with phenylalanine ammonia lyase (PAL). Mouse urine and plasma containing endogenous and administered labeled Phe together with internal standard Phe bearing a different pattern of labeling are converted by in situ diazotization to 2-chloro-3-phenylpropionic acid (CPP). A single solvent extraction is then used to isolate the isotopomers of CPP along with the trans-cinnamic acid (TCA) produced from Phe by PAL, as well as the TCA metabolites benzoic and hippuric acids. This procedure eliminates the need for a separate ion-exchange isolation step for Phe on a second sample aliquot and separate GC-MS analysis. Extracted CPP and the Phe metabolites are then measured by conversion to the pentafluorobenzyl esters and a single analysis by electron capture negative ion GC-MS. The estimated lower limit of quantitation is 0.1 microM.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.252
Teacher spread0.241 · 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 designBench or experimental
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

Citations9
Published2007
Admission routes2
Has abstractyes

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