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Record W2473657250 · doi:10.1002/cphg.1

Fabry Disease Biomarkers: Analysis of Urinary Lyso‐Gb<sub>3</sub> and Seven Related Analogs Using Tandem Mass Spectrometry

2016· article· en· W2473657250 on OpenAlexafffund
Paméla Lavoie, Michel Boutin, Mona Abaoui, Christiane Auray‐Blais

Bibliographic record

VenueCurrent Protocols in Human Genetics · 2016
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsUniversité de Sherbrooke
FundersFondation des EtoilesCanadian Institutes of Health ResearchStars Foundation
KeywordsGlobotriaosylceramideFabry diseaseMultiplexTandem mass spectrometryChemistryUrinary systemMass spectrometryUrineSphingolipidMetabolomicsChromatographyMedicineInternal medicineDiseaseBioinformaticsBiochemistryBiology

Abstract

fetched live from OpenAlex

Fabry disease is an X-linked lysosomal storage disorder caused by the absence or reduction of the enzyme α-galactosidase A activity. Currently, globotriaosylsphingosine (lyso-Gb3 ) and globotriaosylceramide (Gb3 ) are used as biomarkers to diagnose and monitor Fabry patients. However, recent metabolomic studies have shown that several glycosphingolipids are also elevated in biological fluids of affected patients and may be related to disease manifestations. This unit describes a multiplex methodology targeting the analysis of urinary lyso-Gb3 and seven structurally related analogs. A solid-phase extraction process is performed, then lyso-Gb3 and its analogs are analyzed simultaneously with an internal standard by ultra-performance liquid chromatography (UPLC) coupled to a tandem mass spectrometry (MS/MS) system. This methodology can be useful for the diagnosis of Fabry patients, including patients with cardiac variant mutations, but also to monitor the efficacy of therapeutic interventions, considering that lyso-Gb3 analogs are more elevated than lyso-Gb3 itself in urine. © 2016 by John Wiley & Sons, Inc.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.061
GPT teacher head0.378
Teacher spread0.317 · 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 designObservational
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

Citations12
Published2016
Admission routes2
Has abstractyes

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