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Record W4400930415 · doi:10.3389/jpps.2024.13080

The role of acetylation in obesity-induced cardiac metabolic alterations

2024· review· en· W4400930415 on OpenAlexafffundvenue
Ezra B. Ketema, Gary D. Lopaschuk

Bibliographic record

VenueJournal of Pharmacy & Pharmaceutical Sciences · 2024
Typereview
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsObesityHeart failureInternal medicineEndocrinologyMedicineBeta oxidationEnergy metabolismMetabolismBioinformaticsBiology

Abstract

fetched live from OpenAlex

Obesity is a growing public health problem, with its prevalence rate having tripled in the last five decades. It has been shown that obesity is associated with alterations in cardiac energy metabolism, which in turn plays a significant role in heart failure development. During obesity, the heart becomes highly dependent on fatty acid oxidation as its primary source of energy (ATP), while the contribution from glucose oxidation significantly decreases. This metabolic inflexibility is associated with reduced cardiac efficiency and contractile dysfunction. Although it is well recognized that alterations in cardiac energy metabolism during obesity are associated with the risk of heart failure development, the molecular mechanisms controlling these metabolic changes are not fully understood. Recently, posttranslational protein modifications of metabolic enzymes have been shown to play a crucial role in cardiac energy metabolic changes seen in obesity. Understanding these novel mechanisms is important in developing new therapeutic options to treat or prevent cardiac metabolic alteration and dysfunction in obese individuals. This review discusses posttranslational acetylation changes during obesity and their roles in mediating cardiac energy metabolic perturbations during obesity as well as its therapeutic potentials.

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.121
GPT teacher head0.489
Teacher spread0.368 · 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

Citations5
Published2024
Admission routes3
Has abstractyes

Explore more

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