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Record W2220428076 · doi:10.1186/s12915-015-0221-6

Nitrate enhances skeletal muscle fatty acid oxidation via a nitric oxide-cGMP-PPAR-mediated mechanism

2015· article· en· W2220428076 on OpenAlexfundno aff
Tom Ashmore, Lee D. Roberts, Andrea J. Morash, Aleksandra Kotwica, John R. Finnerty, James A. West, Steven A. Murfitt, Bernadette Fernandez, Cristina Branco, Andrew S. Cowburn, Kieran Clarke, Randall S. Johnson, Martin Feelisch, Julian L. Griffin, Andrew J. Murray

Bibliographic record

VenueBMC Biology · 2015
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaWYNG FoundationResearch Councils UKBritish Heart FoundationWellcome TrustMedical Research CouncilDirectorate for Biological SciencesWellcome
KeywordsBiologyBeta oxidationMitochondrial biogenesisCarnitinePeroxisomeBiochemistryPeroxisome proliferator-activated receptorSkeletal muscleAMP-activated protein kinaseMitochondrionUCP3Nitric oxideOxidative phosphorylationInternal medicineEndocrinologyProtein kinase AAMPKFatty acidAdipose tissuePhosphorylationUncoupling proteinReceptorBrown adipose tissue

Abstract

fetched live from OpenAlex

BACKGROUND: Insulin sensitivity in skeletal muscle is associated with metabolic flexibility, including a high capacity to increase fatty acid (FA) oxidation in response to increased lipid supply. Lipid overload, however, can result in incomplete FA oxidation and accumulation of potentially harmful intermediates where mitochondrial tricarboxylic acid cycle capacity cannot keep pace with rates of β-oxidation. Enhancement of muscle FA oxidation in combination with mitochondrial biogenesis is therefore emerging as a strategy to treat metabolic disease. Dietary inorganic nitrate was recently shown to reverse aspects of the metabolic syndrome in rodents by as yet incompletely defined mechanisms. RESULTS: Herein, we report that nitrate enhances skeletal muscle FA oxidation in rodents in a dose-dependent manner. We show that nitrate induces FA oxidation through a soluble guanylate cyclase (sGC)/cGMP-mediated PPARβ/δ- and PPARα-dependent mechanism. Enhanced PPARβ/δ and PPARα expression and DNA binding induces expression of FA oxidation enzymes, increasing muscle carnitine and lowering tissue malonyl-CoA concentrations, thereby supporting intra-mitochondrial pathways of FA oxidation and enhancing mitochondrial respiration. At higher doses, nitrate induces mitochondrial biogenesis, further increasing FA oxidation and lowering long-chain FA concentrations. Meanwhile, nitrate did not affect mitochondrial FA oxidation in PPARα(-/-) mice. In C2C12 myotubes, nitrate increased expression of the PPARα targets Cpt1b, Acadl, Hadh and Ucp3, and enhanced oxidative phosphorylation rates with palmitoyl-carnitine; however, these changes in gene expression and respiration were prevented by inhibition of either sGC or protein kinase G. Elevation of cGMP, via the inhibition of phosphodiesterase 5 by sildenafil, also increased expression of Cpt1b, Acadl and Ucp3, as well as CPT1B protein levels, and further enhanced the effect of nitrate supplementation. CONCLUSIONS: Nitrate may therefore be effective in the treatment of metabolic disease by inducing FA oxidation in muscle.

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 score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.293
Teacher spread0.255 · 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

Citations53
Published2015
Admission routes1
Has abstractyes

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