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Record W2083591609 · doi:10.1074/jbc.m310091200

Link Protein Has Greater Affinity for Versican than Aggrecan

2004· article· en· W2083591609 on OpenAlexaffabout
Shuiliang Shi, Suzanne Grothé, Yiping Zhang, Maureen D. O'Connor‐McCourt, A. Robin Poole, Peter J. Roughley, John S. Mort

Bibliographic record

VenueJournal of Biological Chemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsMcGill UniversityNational Research Council CanadaBiotechnology Research InstituteShriners Hospitals for Children - Canada
Fundersnot available
KeywordsVersicanAggrecanProteoglycanChemistryRecombinant DNACell biologyBiochemistryExtracellular matrixBiologyGeneArticular cartilage

Abstract

fetched live from OpenAlex

The function of link protein in stabilizing the interaction between aggrecan and hyaluronan to form aggrecan aggregates, via the binding of link protein to the aggrecan G1 domain and hyaluronan, is well established. However, it is not known whether link protein can function with similar avidity with versican, another member of the large hyaluronan-binding proteoglycan family that also binds to hyaluronan via its G1 domain. To address this issue, we have compared the interaction of the versican and aggrecan G1 domains with link protein and hyaluronan using recombinant proteins expressed in insect cells and BIAcore analysis. The results showed that link protein could significantly improve the binding of both G1 domains to hyaluronan and that its interaction with VG1 is of a higher affinity than that with AG1. These observations suggest that link protein may function as a stabilizer of the interaction, not only between aggrecan and hyaluronan in cartilage, but also between versican and hyaluronan in many tissues.

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 score0.005
Threshold uncertainty score0.017

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)0.0050.001

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 head0.048
GPT teacher head0.283
Teacher spread0.235 · 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

Citations46
Published2004
Admission routes2
Has abstractyes

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