MétaCan
Menu
Back to cohort
Record W2084439571 · doi:10.2174/1568006043481275

Insulin Resistance as a Therapeutic Target for Improved Endothelial Function:Metformin

2004· review· en· W2084439571 on OpenAlexaff
Lori A. Brame, Subodh Verma, Todd J. Anderson, Amale Lteif, Kieren J. Mather

Bibliographic record

VenueCurrent Drug Targets - Cardiovascular & Hematological Disorders · 2004
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsInsulin resistanceMetforminMedicineInsulinEndothelial dysfunctionBiguanideEndotheliumDiabetes mellitusMetabolic syndromeInternal medicineBioinformaticsEndocrinologyBiology

Abstract

fetched live from OpenAlex

Endothelial dysfunction is a feature of a variety of clinical states of insulin resistance, and increasingly it is recognized that pre-diabetic states of insulin resistance are associated not only with insulin resistance but with increased cardiovascular risk. The metabolic syndrome which typically accompanies insulin resistance brings aberrations in a number of classical cardiovascular risk factors, but it appears that insulin resistance itself represents an additional, non-classical risk factor. Therefore, the approach to treating the endothelium in patients with the metabolic syndrome might include therapies targeting insulin resistance. In this review, we provide a detailed overview of the current state of knowledge regarding the biguanide metformin and its effects on the endothelium. Its mode of action is reviewed, along with the available data from laboratory and experimental studies related to vascular function in animals and in humans. Metformin has beneficial effects on endothelial function which appear to be mediated through its effects to improve insulin resistance. Therapeutically targeting insulin resistance appears to be a viable route to improving endothelial function in clinical states of insulin resistance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.292
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueCurrent Drug Targets - Cardiovascular & Hematological DisordersSame topicMetabolism, Diabetes, and CancerFrench-language works237,207