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Record W3046572944 · doi:10.1113/jp280032

<i>In vitro</i> ketone‐supported mitochondrial respiration is minimal when other substrates are readily available in cardiac and skeletal muscle

2020· article· en· W3046572944 on OpenAlexafffund
Heather L. Petrick, Henver S. Brunetta, Chris Pignanelli, Everson Araújo Nunes, Luc J. C. van Loon, Jamie F. Burr, Graham P. Holloway

Bibliographic record

VenueThe Journal of Physiology · 2020
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsMcMaster UniversityUniversity of Guelph
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoMinistério da Ciência, Tecnologia e InovaçãoNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsKetone bodiesRespirationSkeletal muscleMitochondrionBiochemistryOxidative phosphorylationCarbohydrateCardiac muscleCarbohydrate metabolismBiologyChemistryMetabolismEndocrinologyAnatomy

Abstract

fetched live from OpenAlex

Key points Ketone bodies are proposed to represent an alternative fuel source driving energy production, particularly during exercise. Biologically, the extent to which mitochondria utilize ketone bodies compared to other substrates remains unknown. We demonstrate in vitro that maximal mitochondrial respiration supported by ketone bodies is low when compared to carbohydrate‐derived substrates in the left ventricle and red gastrocnemius muscle from rodents, and in human skeletal muscle. When considering intramuscular concentrations of ketone bodies and the presence of other carbohydrate and lipid substrates, biological rates of mitochondrial respiration supported by ketone bodies are predicted to be minimal. At the mitochondrial level, it is therefore unlikely that ketone bodies are an important source for energy production in cardiac and skeletal muscle, particularly when other substrates are readily available. Abstract Ketone bodies (KB) have recently gained popularity as an alternative fuel source to support mitochondrial oxidative phosphorylation and enhance exercise performance. However, given the low activity of ketolytic enzymes and potential inhibition from carbohydrate oxidation, it remains unknown if KBs can contribute to energy production. We therefore determined the ability of KBs (sodium dl‐β‐hydroxybutyrate, β‐HB; lithium acetoacetate, AcAc) to stimulate in vitro mitochondrial respiration in the left ventricle (LV) and red gastrocnemius (RG) of rats, and in human vastus lateralis. Compared to pyruvate, the ability of KBs to maximally drive respiration was low in isolated mitochondria and permeabilized fibres (PmFb) from the LV (∼30–35% of pyruvate), RG (∼10–30%), and human vastus lateralis (∼2–10%). In PmFb, the concentration of KBs required to half‐maximally drive respiration (LV: 889 µm β‐HB, 801 µm AcAc; RG: 782 µm β‐HB, 267 µm AcAc) were greater than KB content representative of the muscle microenvironment (∼100 µm). This would predict low rates (∼1–4% of pyruvate) of biological KB‐supported respiration in the LV (8–14 pmol s−1 mg−1) and RG (3–6 pmol s−1 mg−1) at rest and following exercise. Moreover, KBs did not increase respiration in the presence of saturating pyruvate, submaximal pyruvate (100 µm) reduced the ability of physiological β‐HB to drive respiration, and addition of other intracellular substrates (succinate + palmitoylcarnitine) decreased maximal KB‐supported respiration. As a result, product inhibition is likely to limit KB oxidation. Altogether, the ability of KBs to drive mitochondrial respiration is minimal and they are likely to be outcompeted by other substrates, compromising their use as an important energy source.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.001

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 head0.025
GPT teacher head0.259
Teacher spread0.235 · 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".

Quick stats

Citations51
Published2020
Admission routes2
Has abstractyes

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