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Record W2163802391 · doi:10.1109/tnsre.2003.817674

Prevention of muscle disuse atrophy by low-frequency electrical stimulation in rats

2003· article· en· W2163802391 on OpenAlexaff
A.C. Dupont Salter, F.J.R. Richmond, Gerald E. Loeb

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2003
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsAtrophyStimulationMuscle atrophyInternal medicineMedicineEndocrinology

Abstract

fetched live from OpenAlex

When muscles lose neural drive, they atrophy rapidly. Neuromuscular electrical stimulation (NMS) has been used in attempts to prevent or reverse the atrophy, but optimal stimulation programs and parameters are not well defined. In this study, we investigated the effects of four different stimulation patterns on disuse atrophy produced in the tibialis anterior, lateral gastrocnemius, and soleus muscles of rats paralyzed with tetrodotoxin for seven days. Stimulation paradigms differed from one another by their stimulation frequency (2 or 10 pulses/s) and by their stimulation period (2 or 10 h a day). Results showed that stimulation with 2 pulses/s, paradigms were more effective at preventing disuse muscle atrophy than higher-frequency stimulation. The most marked difference was in the slow soleus muscle, which had only 10% mean atrophy when stimulated at 2 pulses/s for 10 h, compared to 26% atrophy when stimulated at 10 pulses/s for either 2 or 10 h and 32% atrophy in unstimulated, paralyzed controls. The level of atrophic change was not correlated with the levels of serum creatine kinase, used as an index of muscle damage. Results suggest that remediation of disuse atrophy may be accomplished using unphysiologically low rates of motor-unit activation despite the relatively low force produced by such unfused contractions. This may have significant implications for the design of therapies for muscle paralysis consequent to upper-motoneuron lesions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.204
Teacher spread0.199 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations54
Published2003
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Neural Systems and Rehabilitation EngineeringSame topicMuscle activation and electromyography studiesFrench-language works237,207