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Record W4403246569 · doi:10.1161/res.135.suppl_1.tu103

Abstract Tu103: SIRT2 Inhibition Decreases Glycolysis and Attenuates Hypertrophic Response in H9c2 Cardiomyocytes

2024· article· en· W4403246569 on OpenAlexaff
Ezra B. Ketema, Muhammad Ahsan, Kaya L. Persad, Qiuyu Sun, Liyan Zhang, Gary D. Lopaschuk

Bibliographic record

VenueCirculation Research · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSIRT2GlycolysisInternal medicineEndocrinologyCell biologyChemistryMedicinePharmacologyBiologySirtuinBiochemistryEnzymeMetabolismNAD+ kinase

Abstract

fetched live from OpenAlex

Introduction: Myocardial glycolysis increases in hypertrophic and failing hearts. Hyperacetylation also occurs in the failing heart, and many glycolytic enzymes are known to be subject to acetylation. However, it is generally considered that acetylation has inhibitory effects on glycolysis. As a result, it is not clear whether acetylation changes directly contribute to glycolysis changes in cardiac hypertrophy. We therefore determined whether changes in the acetylation of glycolytic enzymes and the activity of the cytosolic deacetylase SIRT2 regulate cardiac glycolysis. Methods: Glycolysis rates were directly measured in rat heart-derived H9c2 cardiomyocytes perfused with 5 mM [5-3H] glucose, 0.8 mM palmitate, and 4% bovine serum albumin. Before these metabolic measurements, H9c2 cells were treated with either a SIRT2 inhibitor (10 µM AGK2) or a vehicle for 24 hours. In separate experiments, SIRT2 was also knocked down in H9c2 cells using siRNA, followed by glycolysis rate determinations. The impact of SIRT2 inhibition or SIRT2 knockdown on the acetylation status of glycolytic enzyme was also assessed. Furthermore, the effects of SIRT2 inhibition on hypertrophic signalling were assessed by treating H9c2 cells with phenylephrine. Results: SIRT2 inhibition markedly decreased glycolysis rates in H9c2 cells compared to vehicle-treated cells (524±108 vs 2631±372 nmol.g dry wt-1.min-1, p<0.05). Similarly, SIRT2 knockdown resulted in a significant reduction in glycolysis rates compared to scrambled siRNA-treated H9c2 cells (745±31 vs 1659±168 nmol.g dry wt-1.min-1, p<0.05). The decrease in SIRT2 was accompanied by an increase in the acetylation status of the glycolytic enzyme glyceraldehyde phosphate dehydrogenase (GPDH). Moreover, a trend towards increased phosphofructokinase (PFK) acetylation was also observed in SIRT2 knockdown H9c2 cells compared to scrambled siRNA-treated cells. Lastly, AGK2 treatment also attenuated phenylephrine-mediated hypertrophic responses in H9c2 cells. Conclusions: Increased acetylation of glycolytic enzymes is associated with a decrease in glycolysis, and SIRT2 inhibition or deletion in H9c2 cells significantly decreases glycolysis rates and attenuates hypertrophy. SIRT2 may therefore contribute to the increased glycolysis seen in hypertrophy and heart failure.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.034
GPT teacher head0.338
Teacher spread0.304 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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