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Record W1989099710 · doi:10.1002/rcm.1844

Global and site‐specific detection of human integrin <i>α</i> 5 <i>β</i> 1 glycosylation using tandem mass spectrometry and the StrOligo algorithm

2005· article· en· W1989099710 on OpenAlexafffund
Martin Ethier, Oleg V. Krokhin, Werner Ens, Kenneth G. Standing, John A. Wilkins, Hélène Perreault

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsUniversity of Manitoba
FundersNational Institutes of HealthNatural Sciences and Engineering Research Council of CanadaU.S. Public Health ServiceCanada Research Chairs
KeywordsChemistryGlycanGlycosylationGlycomicsMass spectrometryTandem mass spectrometryGlycoproteomicsChromatographyGlycoproteinMatrix-assisted laser desorption/ionizationN-linked glycosylationTrypsinProteomicsBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Glycans are oligosaccharides associated with proteins, and are known to confer specific functions and conformations on glycoproteins. As protein tridimensional structures are related to function, the study of glycans and their impact on protein folding can provide important information to the field of proteomics. The subdiscipline of glycomics (or glycoproteomics) is rapidly growing in importance as glycans in proteins have shown to be involved in protein-protein or protein-(drug, virus, antibody) interactions. Glycomics studies most often aim at identifying glycosylation sites, and thus are performed on deglycosylated proteins resulting in loss of site-specific details concerning the glycosylation. In order to obtain such details by mass spectrometry (MS), either whole glycoproteins must be digested and analyzed as mixtures of peptides and glycopeptides, or glycans must be isolated from glycopeptide fractions and analyzed as pools. This article describes parallel experiments involving both approaches, designed to take advantage of the StrOligo algorithm functionalities with the aim of characterizing glycosylation microheterogeneity on a specific site. A hybrid quadrupole-quadrupole-time-of-flight (QqTOF) instrument equipped with a matrix-assisted laser desorption/ionization (MALDI) source was used. Glycosylation of alpha 5 beta 1 subunits of human integrin was studied to test the methodology. The sample was divided in two aliquots, and glycans from the first aliquot were released enzymatically, labelled with 2-aminobenzamide, and identified using tandem mass spectrometry (MS/MS) and the StrOligo program. The other aliquot was digested with trypsin and the resulting peptides separated by reversed-phase high-performance liquid chromatography (HPLC). A specific collected fraction was then analyzed by MS before and after glycan release. These spectra allowed, by comparison, detection of a glycopeptide (several glycoforms) and elucidation of peptide sequence. Compositions of glycans present were proposed, and identification of possible glycan structures was conducted using MS/MS and StrOligo.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.020
GPT teacher head0.300
Teacher spread0.281 · 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

Citations20
Published2005
Admission routes2
Has abstractyes

Explore more

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