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Record W2618037390

Mechanisms Linking the Metabolic Syndrome and Cardiovascular Disease: Role of Hepatic Insulin Resistance

2009· article· en· W2618037390 on OpenAlexaff
Reza Meshkani, Khosrow Adeli

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2009
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsInsulin resistanceEndocrinologyInternal medicineInsulin receptorMetabolic syndromeResistinInsulinBiologyIRS1IRS2InflammationLipogenesisMedicineAdipose tissueDiabetes mellitusAdipokine
DOInot available

Abstract

fetched live from OpenAlex

The worldwide prevalence of insulin resistant states such as the metabolic syndrome has grown rapidly over the past few decades. The metabolic syndrome is a constellation of common metabolic disorders that promote the development of atherosclerosis and cardiovascular disease. Studies in both human and animal models suggest that hepatic inflammation and insulin resistance are key initiating factors in the development of the metabolic syndrome. Chronic inflammation is known to be associated with visceral obesity and is characterized by production of abnormal adipokines and cytokines such as tumor necrosis factor a, interleukin-1 (IL-1), IL-6, leptin, and resistin. These factors inhibit insulin signaling in the liver (hepatocytes) by activating suppressors of cytokine signalling proteins; several kinases such as c-Jun N-terminal kinases, IKK-β, and Protein kinase C; and protein tyrosine phosphatase 1B, that in turn impair insulin signaling at insulin receptor and insulin receptor substrate level. Hepatic insulin resistance in turn causes impaired suppression of glucose production by insulin in hepatocytes leading to hyperglycemia, induction of very low density lipoprotein production, and de novo lipogenesis. Increased production of C-reactive protein (CRP) and plasminogen activator inhibitor-1, both markers of an inflammatory state, is also observed in insulin resistance. All of the above metabolic abnormalities can directly or indirectly promote atherosclerosis. In particular, hyperglycemia induces endothelial dysfunction, cellular proliferation, changes in extracellular matrix conformation, and impairment of low density lipoproteins (LDL)-receptor-mediated lipoprotein uptake. Small dense LDLs have higher affinity to the intimal proteoglycans, leading to the penetration of more LDL particles into the arterial wall. CRP can also accelerate atherosclerosis by increasing the expression of PAI-1 and adhesion molecules in endothelial cells, inhibition of nitric oxide formation, and increasing LDL uptake into macrophages. In summary, hepatic insulin resistance is a critical early event that underlies the development of the metabolic syndrome and progression to atherosclerosis and cardiovascular disease.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.445
Teacher spread0.355 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2009
Admission routes1
Has abstractyes

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