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Record W3144197674 · doi:10.4093/dmj.2020.0250

Hyperinsulinemia in Obesity, Inflammation, and Cancer

2021· review· en· W3144197674 on OpenAlexaff
Anni Zhang, Elizabeth A. Wellberg, Janel L. Kopp, James D. Johnson

Bibliographic record

VenueDiabetes & Metabolism Journal · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHyperinsulinemiaMedicineDiabetes mellitusInsulinObesityContext (archaeology)Type 2 diabetesCancerHyperinsulinismEndocrinologyInternal medicineInflammationType 2 Diabetes MellitusInsulin resistanceBioinformaticsBiology

Abstract

fetched live from OpenAlex

The relative insufficiency of insulin secretion and/or insulin action causes diabetes. However, obesity and type 2 diabetes mellitus can be associated with an absolute increase in circulating insulin, a state known as hyperinsulinemia. Studies are beginning to elucidate the cause-effect relationships between hyperinsulinemia and numerous consequences of metabolic dysfunctions. Here, we review recent evidence demonstrating that hyperinsulinemia may play a role in inflammation, aging and development of cancers. In this review, we will focus on the consequences and mechanisms of excess insulin production and action, placing recent findings that have challenged dogma in the context of the existing body of literature. Where relevant, we elaborate on the role of specific signal transduction components in the actions of insulin and consequences of chronic hyperinsulinemia. By discussing the involvement of hyperinsulinemia in various metabolic and other chronic diseases, we may identify more effective therapeutics or lifestyle interventions for preventing or treating obesity, diabetes and cancer. We also seek to identify pertinent questions that are ripe for future investigation.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.302
Teacher spread0.285 · 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 teacher head, not a consensus.

Study designOther design
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

Citations286
Published2021
Admission routes1
Has abstractyes

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