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Record W2062206391 · doi:10.1039/b701423f

Evaluation of bio-compatible poly(ethylene glycol)-based solid-phase microextraction fiber for in vivo pharmacokinetic studies of diazepam in dogs

2007· article· en· W2062206391 on OpenAlexafffund
Ali Es‐haghi, Xu Zhang, Florin Marcel Musteata, Habib Bagheri, Janusz Pawliszyn

Bibliographic record

VenueThe Analyst · 2007
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Waterloo
FundersUniversity of Guelph
KeywordsChromatographyOxazepamDetection limitChemistryPharmacokineticsSolid-phase microextractionIn vivoAnalyteEthylene glycolExtraction (chemistry)Solid phase extractionDiazepamBlood samplingWhole bloodMatrix (chemical analysis)PharmacologyMass spectrometryGas chromatography–mass spectrometryMedicineSurgery

Abstract

fetched live from OpenAlex

Solid-phase microextraction probes based on poly(ethylene glycol)/C18-bonded silica were used for in vivo monitoring of drugs from circulating blood of beagles, over a period of 8 h. After sampling, the extracted drugs were subsequently quantified by liquid chromatography coupled with tandem mass spectrometry. External calibrations in whole blood and phosphate-buffered saline were used to correlate the amount of analytes extracted in regard to the total and free concentrations in blood respectively. The probe provided sufficient sensitivity for the drugs in the blood matrix, while the need for drawing blood was eliminated. The limit of detections of the method from whole blood were 1.7, 1.4 and 2.8 ng mL−1 for the analysis of diazepam, nordiazepam and oxazepam respectively, and the linear range was from 4 ng mL−1 to 2 μg mL−1. The method was applied for the monitoring of pharmacokinetic profiles of intravenous administration of diazepam and its two main metabolites in dogs, and the results were compared with profiles determined by conventional methods. This approach offered increased sensitivity and accuracy, short extraction time, and convenient calibration for in vivo sampling for dynamic monitoring.

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)0.002
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 score0.033
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.037
GPT teacher head0.373
Teacher spread0.336 · 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

Citations57
Published2007
Admission routes2
Has abstractyes

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