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Record W2159898309 · doi:10.1093/cvr/cvn115

Signalling mechanisms underlying the metabolic and other effects of adipokines on the heart

2008· review· en· W2159898309 on OpenAlexaff
Morris Karmazyn, Daniel M. Purdham, Venkatesh Rajapurohitam, Asad Zeidan

Bibliographic record

VenueCardiovascular Research · 2008
Typereview
Languageen
FieldMedicine
TopicApelin-related biomedical research
Canadian institutionsWestern University
Fundersnot available
KeywordsAdipokineLeptinAdiponectinApelinAdipose tissueInternal medicineEndocrinologyBiologyLeptin receptorMedicineReceptorObesityInsulin resistance

Abstract

fetched live from OpenAlex

Adipokines represent a family of proteins released by adipocytes that affect various biological processes including metabolism, satiety, inflammation, and cardiovascular function. The first adipokine to be identified is leptin, a product of the obesity gene whose primary function is to act as a satiety factor. However, it is now recognized that leptin and many of the newly discovered adipokines produce effects on numerous organ systems including the heart. Indeed, various adipokines including leptin, adiponectin, and apelin exert potent and diverse cardiovascular effects which are mediated by their specific receptors and involve complex and multifaceted cell-signalling pathways. Among these are effects on the heart as well as blood pressure where leptin has been proposed to potentially contribute to obesity-related hypertension. In this review, we focus primarily on the diverse effects of adipokines on the heart and discuss the potential cell-signalling mechanisms underlying their actions. The potential role of adipokines in the regulation of cardiac metabolism and function is discussed. Discussion is also presented on the emerging role, both deleterious and salutary, of various adipokines in heart disease with an examination of the possible underlying mechanisms which contribute to these effects.

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.232
GPT teacher head0.433
Teacher spread0.201 · 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

Citations117
Published2008
Admission routes1
Has abstractyes

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