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Record W3080980264 · doi:10.1042/bsr20200026

Diabetic atherosclerosis: is there a role for the hypoxia-inducible factors?

2020· review· en· W3080980264 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBioscience Reports · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsDiabetes mellitusMetabolic syndromeInsulin resistanceEndothelial dysfunctionMedicineDiseaseHypoxia (environmental)Transcription factorInflammationObesityBioinformaticsRegulatorInternal medicineRisk factorEndocrinologyBiologyChemistryGeneticsGene

Abstract

fetched live from OpenAlex

Atherosclerosis is a major cause of mortality worldwide and is driven by multiple risk factors, including diabetes. Diabetes is associated with either an insulin deficiency in its juvenile form or with insulin resistance and obesity in Type 2 diabetes mellitus, and the latter is clustered with other comorbidities to define the metabolic syndrome. Diabetes and metabolic syndrome are complex pathologies and are associated with cardiovascular risk via vascular inflammation and other mechanisms. Several transcription factors are activated upon diabetes-driven endothelial dysfunction and drive the progression of atherosclerosis. In particular, the hypoxia-inducible factor (HIF) transcription factor family is a master regulator of endothelial biology and is raising interest in the field of atherosclerosis. In this review, we will present an overview of studies contributing to the understanding of diabetes-driven atherosclerosis, integrating the role of HIF in this disease with the knowledge of its functions in metabolic syndrome and diabetic scenario.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.047
GPT teacher head0.303
Teacher spread0.256 · 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