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Record W2988977772 · doi:10.1186/s13395-019-0214-1

LIM and cysteine-rich domains 1 (LMCD1) regulates skeletal muscle hypertrophy, calcium handling, and force

2019· article· en· W2988977772 on OpenAlexaff
Duarte M. S. Ferreira, Arthur J. Cheng, Leandro Z. Agudelo, Igor Červenka, Thomas Chaillou, Jorge C. Correia, Margareta Porsmyr‐Palmertz, Manizheh Izadi, Alicia Hansson, Vicente Martínez-Redondo, Paula Valente‐Silva, Amanda T. Pettersson-Klein, Jennifer L. Estall, Matthew M. Robinson, K. Sreekumaran Nair, Johanna T. Lanner, Jorge L. Ruas

Bibliographic record

VenueSkeletal Muscle · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsMontreal Clinical Research InstituteYork University
FundersNational Center for Advancing Translational SciencesNational Institute of Diabetes and Digestive and Kidney DiseasesSvenska Sällskapet för Medicinsk ForskningNovo Nordisk FondenCentrum för idrottsforskningStiftelsen Lars Hiertas MinneNational Institutes of HealthVetenskapsrådetNovo NordiskMayo ClinicKarolinska InstitutetGeorgia Clinical and Translational Science AllianceWenner-Gren Stiftelserna
KeywordsSkeletal muscleSarcopeniaCalcineurinMuscle atrophyMuscle hypertrophyMyocyteDysferlinBiologyITGA7Muscle contractionGene expressionEndocrinologyInternal medicineCell biologyMedicineBiochemistryGeneTransplantation

Abstract

fetched live from OpenAlex

Abstract Background Skeletal muscle mass and strength are crucial determinants of health. Muscle mass loss is associated with weakness, fatigue, and insulin resistance. In fact, it is predicted that controlling muscle atrophy can reduce morbidity and mortality associated with diseases such as cancer cachexia and sarcopenia. Methods We analyzed gene expression data from muscle of mice or human patients with diverse muscle pathologies and identified LMCD1 as a gene strongly associated with skeletal muscle function. We transiently expressed or silenced LMCD1 in mouse gastrocnemius muscle or in mouse primary muscle cells and determined muscle/cell size, targeted gene expression, kinase activity with kinase arrays, protein immunoblotting, and protein synthesis levels. To evaluate force, calcium handling, and fatigue, we transduced the flexor digitorum brevis muscle with a LMCD1-expressing adenovirus and measured specific force and sarcoplasmic reticulum Ca2+ release in individual fibers. Finally, to explore the relationship between LMCD1 and calcineurin, we ectopically expressed Lmcd1 in the gastrocnemius muscle and treated those mice with cyclosporine A (calcineurin inhibitor). In addition, we used a luciferase reporter construct containing the myoregulin gene promoter to confirm the role of a LMCD1-calcineurin-myoregulin axis in skeletal muscle mass control and calcium handling. Results Here, we identify LIM and cysteine-rich domains 1 (LMCD1) as a positive regulator of muscle mass, that increases muscle protein synthesis and fiber size. LMCD1 expression in vivo was sufficient to increase specific force with lower requirement for calcium handling and to reduce muscle fatigue. Conversely, silencing LMCD1 expression impairs calcium handling and force, and induces muscle fatigue without overt atrophy. The actions of LMCD1 were dependent on calcineurin, as its inhibition using cyclosporine A reverted the observed hypertrophic phenotype. Finally, we determined that LMCD1 represses the expression of myoregulin, a known negative regulator of muscle performance. Interestingly, we observed that skeletal muscle LMCD1 expression is reduced in patients with skeletal muscle disease. Conclusions Our gain- and loss-of-function studies show that LMCD1 controls protein synthesis, muscle fiber size, specific force, Ca2+ handling, and fatigue resistance. This work uncovers a novel role for LMCD1 in the regulation of skeletal muscle mass and function with potential therapeutic implications.

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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

Citations41
Published2019
Admission routes1
Has abstractyes

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