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Record W2000919336 · doi:10.1074/mcp.m100020-mcp200

A Proteomic Approach for the Identification of Cell-surface Proteins Shed by Metalloproteases

2002· article· en· W2000919336 on OpenAlexaff
Lin Guo, June Eisenman, Rajeev Mahimkar, Jacques J. Peschon, Raymond J. Paxton, Roy A. Black, Richard S. Johnson

Bibliographic record

VenueMolecular & Cellular Proteomics · 2002
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsResearch & Development Corporation
Fundersnot available
KeywordsIdentification (biology)Computational biologyMetalloproteinaseProteomicsCell biologyChemistryBiologyBiochemistryGeneEnzymeBotany

Abstract

fetched live from OpenAlex

Proteolytic cleavage (shedding) of extracellular domains of many membrane proteins by metalloproteases is an important regulatory mechanism used by mammalian cells in response to environmental and physiological changes. Here we describe a proteomic system for analyzing cell surface shedding. The method utilized short-term culture supernatants from induced cells as starting material, followed by lectin-affinity purification, deglycosylation, and polyacrylamide gel electrophoresis separation. Relative quantitation of proteins was achieved via isotope dilution. In this study, a number of proteins already known to be shed were identified from activated monocytes and endothelial cells, thereby validating the method. In addition, a group of proteins were newly identified as being shed. The method provides an unbiased means to screen for shed proteins.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.020
GPT teacher head0.250
Teacher spread0.230 · 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

Citations94
Published2002
Admission routes1
Has abstractyes

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