ArticleJournal of the American Society for Mass Spectrometry2015
Metabolomic Analysis of Oxidative and Glycolytic Skeletal Muscles by Matrix-Assisted Laser Desorption/IonizationMass Spectrometric Imaging (MALDI MSI).
Article in Journal of the American Society for Mass Spectrometry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Ceramide metabolism in oxidative and glycolytic muscle: Significance for lipid-induced insulin resistance.Molecular metabolism · 2026Article
- Aging induces sarcopenia by disrupting the crosstalk between the skeletal muscle microenvironment and myofibers.Journal of advanced research · 2026Review
- Spatially resolved metabolomics and isotope tracing reveal dynamic metabolic responses of dentate granule neurons with acute stimulation.Nature metabolism · 2023Article
- Spatially resolved metabolomics and isotope tracing reveal dynamic metabolic responses of dentate granule neurons with acute stimulation.Research square · 2023Article
- Multimodal high-resolution nano-DESI MSI and immunofluorescence imaging reveal molecular signatures of skeletal muscle fiber types.Chemical science · 2023Article
- Spatial metabolomics reveals skeletal myofiber subtypes.Science advances · 2023Article
- Redox status biomarkers in the fast-twitch extensor digitorum longus resulting from the hypoxic exercise.Nagoya journal of medical science · 2022Article
- The metabolic landscape in chronic rotator cuff tear reveals tissue-region-specific signatures.Journal of cachexia, sarcopenia and muscle · 2022Article
- Mass spectrometry imaging of mice brain lipid profile changes over time under high fat diet.Scientific reports · 2021Article
- Imaging of Triglycerides in Tissues Using Nanospray Desorption Electrospray Ionization (Nano-DESI) Mass Spectrometry.International journal of mass spectrometry · 2020Article
- Article
- Two elephants in the room: new hybrid nuclear magnetic resonance and mass spectrometry approaches for metabolomics.Current opinion in clinical nutrition and metabolic care · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Skeletal muscles are composed of heterogeneous muscle fibers that have different physiological, morphological, biochemical, and histological characteristics. In this work, skeletal muscles extensor digitorum longus, soleus, and whole gastrocnemius were analyzed by matrix-assisted laser desorption/ionization mass spectrometry to characterize small molecule metabolites of oxidative and glycolytic muscle fiber types as well as to visualize biomarker localization. Multivariate data analysis such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed to extract significant features. Different metabolic fingerprints were observed from oxidative and glycolytic fibers. Higher abundances of biomolecules such as antioxidant anserine as well as acylcarnitines were observed in the glycolytic fibers, whereas taurine and some nucleotides were found to be localized in the oxidative fibers.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.