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Record W1975117643 · doi:10.1074/jbc.m108033200

GIPC Participates in G Protein Signaling Downstream of Insulin-like Growth Factor 1 Receptor

2002· article· en· W1975117643 on OpenAlexaff
Ronald A. Booth, Mario Tiberi, X. Johné Liu

Bibliographic record

VenueJournal of Biological Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of OttawaOttawa Hospital
Fundersnot available
KeywordsDownstream (manufacturing)Cell biologyInsulin-like growth factorReceptorGrowth factorInsulin receptorChemistryInsulinEndocrinologyBusinessBiologyInsulin resistanceBiochemistry

Abstract

fetched live from OpenAlex

Several recent studies have demonstrated that insulin-like growth factor (IGF)-1-induced mitogen-activated protein kinase (MAP kinase) activation is abolished by pertussis toxin, suggesting that trimeric G proteins of the G(i) class are novel cellular targets of the IGF-1 signaling pathway. We report here that the intracellular domain of the Xenopus IGF-1 receptor is capable of binding to the Xenopus homolog of mammalian GIPC, a PDZ domain-containing protein previously identified as a binding partner of G(i)-specific GAP (RGS-GAIP). Binding of xGIPC to xIGF-1 receptor is independent of the kinase activity of the receptor and appears to require the PDZ domain of xGIPC. Injection of two C-terminal truncation mutants that retained the PDZ domain blocked IGF-1-induced Xenopus MAP kinase activation and oocyte maturation. While full-length xGIPC injection did not significantly alter insulin response, it greatly enhanced human RGS-GAIP in stimulating the insulin response in frog oocytes. This represents the first demonstration that GIPC x RGS-GAIP complex acts positively in IGF-1 receptor signal transduction.

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 score0.003

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 head0.032
GPT teacher head0.247
Teacher spread0.215 · 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

Citations62
Published2002
Admission routes1
Has abstractyes

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Same venueJournal of Biological ChemistrySame topicMetabolism, Diabetes, and CancerFrench-language works237,207