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Record W2774140036 · doi:10.1002/mas.21555

Mass spectrometry for protein sialoglycosylation

2017· review· en· W2774140036 on OpenAlex

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.

Bibliographic record

VenueMass Spectrometry Reviews · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsNational Research Council CanadaQueen's University
Fundersnot available
KeywordsChemistryGlycanGlycoproteinSialic acidNeuraminic acidGlycosylationMass spectrometryBiochemistryGlycopeptideGlycolipidAmino acidElectrospray ionizationChromatography

Abstract

fetched live from OpenAlex

Sialic acids are a family of structurally unique and negatively charged nine-carbon sugars, normally found at the terminal positions of glycan chains on glycoproteins and glycolipids. The glycosylation of proteins is a universal post-translational modification in eukaryotic species and regulates essential biological functions, in which the most common sialic acid is N-acetyl-neuraminic acid (2-keto-5-acetamido-3,5-dideoxy-D-glycero-D-galactononulopyranos-1-onic acid) (Neu5NAc). Because of the properties of sialic acids under general mass spectrometry (MS) conditions, such as instability, ionization discrimination, and mixed adducts, the use of MS in the analysis of protein sialoglycosylation is still challenging. The present review is focused on the application of MS related methodologies to the study of both N- and O-linked sialoglycans. We reviewed MS-based strategies for characterizing sialylation by analyzing intact glycoproteins, proteolytic digested glycopeptides, and released glycans. The review concludes with future perspectives in the field.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.110
GPT teacher head0.399
Teacher spread0.289 · 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