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Record W4400324405 · doi:10.1080/20565623.2024.2355038

A comprehensive approach for detection of biotin deficiency from dried blood spot samples using liquid chromatography-mass spectrometry

2024· article· en· W4400324405 on OpenAlexfundno aff
Arya Raveendran, Ashutosh Gupta, Leslie Lewis, Krishnananda Prabhu, Sudheer Moorkoth

Bibliographic record

VenueFuture Science OA · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsnot available
FundersGrand Challenges Canada
KeywordsDried blood spotChromatographyMass spectrometryLiquid chromatography–mass spectrometryChemistryDried bloodHigh-performance liquid chromatographyPopulationMedicine

Abstract

fetched live from OpenAlex

Aim: The aim of the present study is to develop a liquid chromatography-mass spectrometry method to measure two important biomarkers of biotin deficiency from dried blood spot samples for effective management of the disorder. Materials & methods: The method was developed on a liquid chromatography-mass spectrometry system using pentafluorophenyl column employing a mobile phase composition of methanol and water in the isocratic mode. A full validation of the method was performed as per relevant guidelines. Results & conclusion: Correlation between the results of dried blood spot and plasma method was evaluated to determine the interconvertibility of the method. The developed method was successfully applied for establishing the reference ranges for these biomarkers in the population of Udupi, a coastal district of South India.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.255
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 source (direct Gemma or distilled Codex), 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

Citations10
Published2024
Admission routes1
Has abstractyes

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Same venueFuture Science OASame topicBiotin and Related StudiesFrench-language works237,207