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FOXO1‐induced Atrophy Changes in Phospholipid Profiles of Skeletal Muscle

2016· article· en· W2890874222 on OpenAlexfundno aff
Nanami Senoo, Noriyuki Miyoshi, Eri Kobayashi, Akihito Morita, Yasutomi Kamei, Shinji Miura

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsnot available
FundersBio-oriented Technology Research Advancement InstitutionCouncil for Science, Technology and InnovationSwine Innovation Porc
KeywordsSkeletal musclePhospholipidEndocrinologyPhosphatidylethanolamineCoactivatorInternal medicineFOXO1ChemistryMuscle atrophyBiologyGlycolysisBiochemistryPhosphatidylcholineMetabolismTranscription factorMedicineGene

Abstract

fetched live from OpenAlex

Exercise training influences phospholipid fatty acid composition in skeletal muscle and these changes are associated with physiological phenotypes. Recently we have found that peroxisome proliferator‐activated receptor γ coactivator 1α (PGC‐1α), a nuclear receptor coactivator, affected lipid profiles in skeletal muscle and increased several phospholipid species in glycolytic muscle, namely phosphatidylcholine (PC) (18:0/22:6) and phosphatidylethanolamine (PE) (18:0/22:6). We also found that exercise training increased PC (18:0/22:6) and PE (18:0/22:6) in glycolytic muscle and that PGC‐1α was required for these alterations. On the other hand, a decrease in docosahexaenoic acid [22:6 (n‐3)] from the skeletal muscle phospholipid fraction was observed in dystrophic mdx mice, suggesting changes of phospholipid fatty acid composition related with physiological phenotypes of skeletal muscle. However, the molecular mechanism of this influence on compositional changes is poorly understood. Forkhead box protein O1 (FOXO1) is a transcriptional factor that plays an important role in regulation of skeletal muscle mass. Because we have demonstrated that muscle‐specific overexpression of FOXO1 is sufficient to cause skeletal muscle atrophy in vivo, we speculated that FOXO1 contribute to the atrophy‐mediated change in phospholipid fatty acid composition. To determine the role of FOXO1, we performed lipidomics analyses of skeletal muscle from genetically modified mice that overexpress FOXO1 in skeletal muscle. After lipid extraction from EDL or soleus by Bligh and Dyer method, the lipid samples were injected into LC‐MS and determined peaks were re‐analyzed by MS/MS for identification of lipid species. Using these data, principal component analysis was done to classified the changes of lipid species depending on muscle fiber type and FOXO1 expression. As a result, we observed that PC and PE containing specific fatty acid species changed in both of EDL and soleus derived from mice that overexpress FOXO1 in skeletal muscle. From these results, it was suggested that FOXO1 expression changed fatty acid composition of PC and PE and these changes might be involved in the physiological phenotype of muscle atrophy. Support or Funding Information This study was supported by the Council for Science, Technology and Innovation (CSTI), Cross‐ministerial Strategic Innovation Promotion Program (SIP, No.14533567), and “Technologies for creating next‐generation agriculture, forestry and fisheries” (funding agency: Bio‐oriented Technology Research Advancement Institution, NARO), The Tojuro Iijima Foundation for Food Science and Technology (Chiba, Japan), Grants‐in‐Aid for Scientific Research (KAKENHI, No. 26282184, 26560400, 21300240) from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT, Tokyo), The Uehara Memorial Foundation (Tokyo, Japan), The Kao Research Council for the Study of Healthcare Science (Tokyo, Japan, No. A‐31006), and University of Shizuoka Grant for Scientific and Educational Research.

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 score0.007

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)0.0020.000

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 head0.024
GPT teacher head0.270
Teacher spread0.245 · 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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Citations1
Published2016
Admission routes1
Has abstractyes

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