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Record W4400948347 · doi:10.2337/db23-0802

GAS6 and AXL Promote Insulin Resistance by Rewiring Insulin Signaling and Increasing Insulin Receptor Trafficking to Endosomes

2024· article· en· W4400948347 on OpenAlexafffund
Céline Schott, Amélie Germain, Julie Lacombe, Monica Pata, Denis Faubert, Jonathan Boulais, Peter Carmeliet, Jean‐François Côté, Mathieu Ferron

Bibliographic record

VenueDiabetes · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPhagocytosis and Immune Regulation
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchCanada Research ChairsDiabetes Canada
KeywordsGAS6Insulin resistanceInsulin receptorMERTKInsulinEndocrinologyInternal medicineBiologyReceptorSignal transductionCell biologyReceptor tyrosine kinaseMedicine

Abstract

fetched live from OpenAlex

Growth arrest-specific 6 (GAS6) is a secreted protein that acts as a ligand for TAM receptors (TYRO3, AXL, and MERTK). In humans, GAS6 circulating levels and genetic variations in GAS6 are associated with hyperglycemia and increased risk of type 2 diabetes. However, the mechanisms by which GAS6 influences glucose metabolism are not understood. Here, we show that Gas6 deficiency in mice increases insulin sensitivity and protects from diet-induced insulin resistance. Conversely, increasing GAS6 circulating levels is sufficient to reduce insulin sensitivity in vivo. GAS6 inhibits the activation of the insulin receptor (IR) and reduces insulin response in muscle cells in vitro and in vivo. Mechanistically, AXL and IR form a complex, while GAS6 reprograms signaling pathways downstream of IR. This results in increased IR endocytosis following insulin treatment. This study contributes to a better understanding of the cellular and molecular mechanisms by which GAS6 and AXL influence insulin sensitivity.

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 score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

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