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Record W4405577943 · doi:10.1096/fj.202401747r

Transcriptomic and lipidomic profiling reveals distinct bioactive lipid signatures in slow and fast muscles and highlights the role of resolvin‐ <scp>D2</scp> in fiber type determination during myogenesis

2024· article· en· W4405577943 on OpenAlexafffund
Lupann Rieger, Thomas Molina, Paul Fabre, Karine Greffard, Ornella Pellerito, Junio Dort, Jean‐François Bilodeau, Nicolas A. Dumont

Bibliographic record

VenueThe FASEB Journal · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of OttawaUniversité LavalUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada
KeywordsMyogenesisMyosinSkeletal muscleSoleus muscleDocosahexaenoic acidMyocyteBiochemistryLipidomicsChemistryEicosapentaenoic acidBiologyArachidonic acidLipid signalingInternal medicineCell biologyEndocrinologyFatty acidPolyunsaturated fatty acidEnzymeMedicine

Abstract

fetched live from OpenAlex

Skeletal muscles are predominantly composed of long, multinucleated muscle fibers, classified according to their metabolic and contractile phenotype. The determination of fiber types is influenced by various factors (e.g., innervation, hormones, physical demand). Our laboratory and others showed that resolvins, lipid mediators derived from omega-3 fatty acids, promote muscle regeneration and function after an injury or in models of muscular dystrophies; however, the effect of resolvins on the determination of muscle phenotype remains unknown. Here, we investigated the impact of lipid mediators on muscle phenotype during myogenesis. Transcriptomics analysis of single-nuclei RNAseq data sets revealed that the enzymes responsible for bioactive lipids biosynthesis are differentially expressed in slow fibers versus fast fibers. Lipidomics analysis of slow-twitch muscle (soleus) versus fast-twitch muscle (tibialis anterior) showed that the levels of lipids derived from arachidonic acid are similar between muscle groups, but lipids derived from alpha-linolenic acid, linoleic acid, eicosapentaenoic acid, and docosahexaenoic acid are enriched in slow-twitch muscle. Screening for different lipids in vitro showed that resolvin-D2 enhances the formation of myotubes expressing the slow myosin heavy chain isoform. In vivo, the administration of resolvin-D2 enhances muscle strength, increases myofiber size, and affects fiber typing in injured muscles but not in uninjured muscles. Resolvin-D2 promoted the transition toward the dominant fiber types in regenerating muscle (i.e., type I in the slow-twitch soleus and type IIB in the fast-twitch tibialis anterior muscle), suggesting its participation in fiber typing in conjunction with other factors. Overall, these findings identified new roles of bioactive lipids in the regulation of fiber typing, which could have therapeutic applicability in muscle injuries or dystrophies.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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