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Record W2147140873 · doi:10.4172/2155-6156.1000127

Mechanisms of Fatty Acid-Induced Insulin Resistance in Muscle and Liver

2011· article· en· W2147140873 on OpenAlexaff
Rafik Ragheb, Amina M. Medhat

Bibliographic record

VenueJournal of Diabetes & Metabolism · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoUniversity Health NetworkMount Sinai Hospital
FundersAin Shams University
KeywordsInsulin resistanceMedicineDiabetes mellitusFatty liverInsulinInternal medicineEndocrinologyBioinformaticsBiologyDisease

Abstract

fetched live from OpenAlex

Insulin Resistance occurs as a result of disturbances in lipid metabolism and increased levels of circulating fatty acids that accumulate within the insulin sensitive tissues such as muscle, liver and adipose tissues.Increased fatty acid flux has been suggested to be strongly associated with insulin resistant states such as obesity and type 2-diabetes.Fatty acids appear to cause this defect in glucose transport by inhibiting insulin -stimulated tyrosine phosphorylation of insulin receptor substrate-1 (IRS-1) and reducing IRS-1 associated phosphatidyl-inositol 3-kinase activity that implicate other insulin signaling components downstream of the insulin signaling cascade.A number of different metabolic abnormalities may increase intramyocellular or intrahepatic fatty acid metabolites that induce the disease state of insulin resistance through a number of different cellular mechanisms.The current review point out the link between enhanced FFA flux and activation of PKC and how it impacts on both the insulin signaling in muscle and liver.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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 designObservational
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

Citations43
Published2011
Admission routes1
Has abstractyes

Explore more

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