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Record W1530609286 · doi:10.1074/jbc.m103569200

Suppression of Tumor-related Glycosylation of Cell Surface Receptors by the 16-kDa Membrane Subunit of Vacuolar H+-ATPase

2001· article· en· W1530609286 on OpenAlexaff
Mhairi Skinner, Alan G. Wildeman

Bibliographic record

VenueJournal of Biological Chemistry · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCell biologyTransmembrane proteinIntegrinGlycosylationCell surface receptorCell adhesionGolgi apparatusNeural cell adhesion moleculeCell membraneTransmembrane domainReceptorCellChemistryEpidermal growth factorBiologyBiochemistryEndoplasmic reticulum

Abstract

fetched live from OpenAlex

The glycosylation of integrins and other cell surface receptors is altered in many transformed cells. Notably, an increase in the number of beta1,6-branched N-linked oligosaccharides correlates strongly with invasive growth of cells. An ectopic expression of the Golgi enzyme N-acetylglucosaminyltransferase V (GlcNAc-TV), which forms beta1,6 linkages, promotes metastasis of a number of cell types. It is shown here that the 16-kDa transmembrane subunit (16K) of vacuolar H(+)-ATPase suppresses beta1,6 branching of beta(1) integrin and the epidermal growth factor receptor. Overexpression of 16K inhibits cell adhesion and invasion. 16K contains four hydrophobic membrane-spanning alpha-helices, and its ability to influence glycosylation is localized primarily within the second and fourth membrane-spanning alpha-helices. 16K also interacts directly with the transmembrane domain of beta(1) integrin, but its effects on glycosylation were independent of its binding to beta(1) integrin. These data link cell surface tumor-related glycosylation to a component of the enzyme responsible for acidification of the exocytic pathway.

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 head0.009
GPT teacher head0.213
Teacher spread0.203 · 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

Citations14
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Biological ChemistrySame topicCellular transport and secretionFrench-language works237,207