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A Simple High-Performance Liquid Chromatography Assay for Simultaneous Measurement of Adenosine, Guanosine, and the Oxypurine Metabolites in Plasma

2000· article· en· W2040788830 on OpenAlexaff
J. D. Z. Feng, Pollen Yeung

Bibliographic record

VenueTherapeutic Drug Monitoring · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and Molecular Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChromatographyChemistryHigh-performance liquid chromatographyHypoxanthineInosineDetection limitXanthineAdenosineUric acidAnalyteGuanosineBiochemistryEnzyme

Abstract

fetched live from OpenAlex

To study the effect of pharmacologic agents on the biologic fate of adenosine, a reversed-phase high-performance liquid chromatography (HPLC) assay coupled with a solid-phase extraction (SPE) method was developed for simultaneous determination of plasma adenosine, hypoxanthine, xanthine, inosine, guanosine, and uric acid. The HPLC system consisted of a reversed phase C18 column, UV detector set at 254 nm, and a mobile phase composed of 0.01 M ammonium phosphate: methanol (9.5 : 0.5) vol/vol with the final pH adjusted to 3.9. The standard curves were linear between 0.1-2 microg/mL for all the analytes (except uric acid 50-400 microg/mL), with r2 > 0.99. The absolute recoveries were >60% and accuracy >85% in almost all cases. The limit of detection was <1 ng based on absolute injection of the analytes. The intraassay variations were <10% and interassay variations <15%. The presence of a wide range of medications in plasma samples did not interfere with the assay. The assay was applied successfully to measure plasma adenosine and the oxypurine metabolites in humans and rats. It was noted that plasma concentrations of adenosine and the oxypurine metabolites can vary considerably depending on the method of blood sample collection, and that species differences are apparent.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.013
GPT teacher head0.254
Teacher spread0.242 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

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