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Record W2734792313 · doi:10.1021/acs.analchem.7b01877

High-Throughput Screening and Quantitation of Target Compounds in Biofluids by Coated Blade Spray-Mass Spectrometry

2017· article· en· W2734792313 on OpenAlex
Marcos Tascón, Germán Augusto Gómez‐Ríos, Nathaly Reyes‐Garcés, Justen Poole, Ezel Boyacı, Janusz Pawliszyn

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnalytical Chemistry · 2017
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryChromatographyMass spectrometryAnalyteReproducibilitySample preparationThroughputProcess engineeringComputer science

Abstract

fetched live from OpenAlex

Most contemporary methods of screening and quantitating controlled substances and therapeutic drugs in biofluids typically require laborious, time-consuming, and expensive analytical workflows. In recent years, our group has worked toward developing microextraction (μe)-mass spectrometry (MS) technologies that merge all of the tedious steps of the classical methods into a simple, efficient, and low-cost methodology. Unquestionably, the automation of these technologies allows for faster sample throughput, greater reproducibility, and radically reduced analysis times. Coated blade spray (CBS) is a μe technology engineered for extracting/enriching analytes of interest in complex matrices, and it can be directly coupled with MS instruments to achieve efficient screening and quantitative analysis. In this study, we introduced CBS as a technology that can be arranged to perform either rapid diagnostics (single vial) or the high-throughput (96-well plate) analysis of biofluids. Furthermore, we demonstrate that performing 96-CBS extractions at the same time allows the total analysis time to be reduced to less than 55 s per sample. Aiming to validate the versatility of CBS, substances comprising a broad range of molecular weights, moieties, protein binding, and polarities were selected. Thus, the high-throughput (HT)-CBS technology was used for the concomitant quantitation of 18 compounds (mixture of anabolics, β-2 agonists, diuretics, stimulants, narcotics, and β-blockers) spiked in human urine and plasma samples. Excellent precision (∼2.5%), accuracy (≥90%), and linearity ( R 2 ≥ 0.99) were attained for all the studied compounds, and the limits of quantitation (LOQs) were within the range of 0.1 to 10 ng·mL –1 for plasma and 0.25 to 10 ng·mL –1 for urine. The results reported in this paper confirm CBS’s great potential for achieving subsixty-second analyses of target compounds in a broad range of fields such as those related to clinical diagnosis, food, the environment, and forensics.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.017
GPT teacher head0.289
Teacher spread0.272 · 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