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Overexpression of insulin‐like growth factor‐1 attenuates skeletal muscle damage and accelerates muscle regeneration and functional recovery after disuse

2013· article· en· W1532763325 on OpenAlexaff
Fan Ye, Sunita Mathur, Min Liu, Stephen E. Borst, Glenn A. Walter, H. Lee Sweeney, Krista Vandenborne

Bibliographic record

VenueExperimental Physiology · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Heart, Lung, and Blood InstituteNational Institute on AgingNational Institutes of Health
KeywordsSkeletal muscleMuscle hypertrophyMuscle atrophySoleus muscleInternal medicineEndocrinologySarcopeniaInsulin-like growth factorHindlimbRegeneration (biology)MyocyteMyostatinBiologyGrowth factorAtrophyMedicineCell biologyReceptor

Abstract

fetched live from OpenAlex

New Findings What is the central question of this study? Insulin‐like growth factor‐1 (IGF‐1) promotes muscle hypertrophy, but no studies have investigated the effect of IGF‐1 on the susceptibility of atrophied muscles to reloading‐induced muscle injury. What is the main finding and what is its importance? We employed a comprehensive set of methods, including muscle physiological measurements, molecular biology techniques and non‐invasive magnetic resonance imaging. The results concurrently demonstrate that local overexpression of IGF‐1 in a primary antigravity muscle protects the muscle from reloading‐induced muscle damage and accelerates muscle regeneration and functional recovery following cast immobilization. These findings add new physiological significance to the benefits of IGF‐1 on skeletal muscle mass and force generation during varied loading conditions. Skeletal muscle is a highly dynamic tissue that responds to endogenous and external stimuli, including alterations in mechanical loading and growth factors. In particular, the antigravity soleus muscle experiences significant muscle atrophy during disuse and extensive muscle damage upon reloading. Given that insulin‐like growth factor‐1 (IGF‐1) has been implicated as a central regulator of muscle repair and modulation of muscle size, we examined the effect of virally mediated overexpression of IGF‐1 on the soleus muscle following hindlimb cast immobilization and upon reloading. Recombinant IGF‐1 cDNA virus was injected into one of the posterior hindlimbs of the mice, while the contralateral limb was injected with saline (control). At 20 weeks of age, both hindlimbs were immobilized for 2 weeks to induce muscle atrophy in the soleus and ankle plantarflexor muscle group. Subsequently, the mice were allowed to reambulate, and muscle damage and recovery were monitored over a period of 2–21 days. The primary finding of this study was that IGF‐1 overexpression attenuated reloading‐induced muscle damage in the soleus muscle, and accelerated muscle regeneration and force recovery. Muscle T2 assessed by magnetic resonance imaging, a non‐specific marker of muscle damage, was significantly lower in IGF‐1‐injected compared with contralateral soleus muscles at 2 and 5 days reambulation (P < 0.05). The reduced prevalence of muscle damage in IGF‐1‐injected soleus muscles was confirmed on histology, with a lower fractional area of abnormal muscle tissue in IGF‐1‐injected muscles at 2 days reambulation (33.2 ± 3.3 versus 54.1 ± 3.6%, P < 0.05). Evidence of the effect of IGF‐1 on muscle regeneration included timely increases in the number of central nuclei (21% at 5 days reambulation), paired‐box transcription factor 7 (36% at 5 days), embryonic myosin (37% at 10 days) and elevated MyoD mRNA (7‐fold at 2 days) in IGF‐1‐injected limbs (P < 0.05). These findings demonstrate a potential role of IGF‐1 in protecting unloaded skeletal muscles from damage and accelerating muscle repair and regeneration.

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 score0.002

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)0.0010.000

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 head0.009
GPT teacher head0.228
Teacher spread0.220 · 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

Citations64
Published2013
Admission routes1
Has abstractyes

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