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Record W2594017190 · doi:10.3389/fphys.2017.00114

Eccentric Ergometer Training Promotes Locomotor Muscle Strength but Not Mitochondrial Adaptation in Patients with Severe Chronic Obstructive Pulmonary Disease

2017· article· en· W2594017190 on OpenAlexafffund
Norah J. MacMillan, Sophia Kapchinsky, Yana Konokhova, Gilles Gouspillou, Riany de Sousa Sena, R. Thomas Jagoe, Jacinthe Baril, Tamara E. Carver, Ross E. Andersen, Ruddy Richard, Hélène Perrault, Jean Bourbeau, Russell T. Hepple, Tanja Taivassalo

Bibliographic record

VenueFrontiers in Physiology · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsJewish General HospitalUniversité du Québec à MontréalMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health ResearchMcGill University Health CentreNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMedicinePulmonary diseaseEccentricAdaptation (eye)Eccentric exercisePhysical therapyBicycle ergometerCardiologyInternal medicineCardiorespiratory fitnessPhysical medicine and rehabilitationDiseaseStrength trainingBiologyMuscle damageHeart rateNeuroscience

Abstract

fetched live from OpenAlex

Eccentric ergometer training (EET) is increasingly being proposed as a therapeutic strategy to improve skeletal muscle strength in various cardiorespiratory diseases, due to the principle that lengthening muscle actions lead to high force-generating capacity at low cardiopulmonary load. One clinical population that may particularly benefit from this strategy is chronic obstructive pulmonary disease (COPD), as ventilatory constraints and locomotor muscle dysfunction often limit efficacy of conventional exercise rehabilitation in patients with severe disease. While the feasibility of EET for COPD has been established, the nature and extent of adaptation within COPD muscle is unknown. The aim of this study was therefore to characterize the locomotor muscle adaptations to EET in patients with severe COPD, and compare them with adaptations gained through conventional concentric ergometer training (CET). Male patients were randomized to either EET (n=8) or CET (n=7) for 10 weeks and matched for heart rate intensity. EET patients trained on average at a workload that was three times that of CET, at a lower perception of leg fatigue and dyspnea. EET led to increases in isometric peak strength and relative thigh mass (p<0.01) whereas CET had no such effect. However EET did not result in fiber hypertrophy, as morphometric analysis of muscle biopsies showed no increase in mean fiber cross-sectional area (p=0.82), with variability in the direction and magnitude of fiber-type responses (20% increase in Type 1, p=0.18; 4% decrease in Type 2a, p=0.37) compared to CET (26% increase in Type 1, p=0.04; 15% increase in Type 2a, p=0.09). EET had no impact on mitochondrial adaptation, as revealed by lack of change in markers of mitochondrial biogenesis, content and respiration, which contrasted to improvements (p<0.05) within CET muscle. While future study is needed to more definitively determine the effects of EET on fiber hypertrophy and associated underlying molecular signaling pathways in COPD locomotor muscle, our findings promote the implementation of this strategy to improve muscle strength. Furthermore, contrasting mitochondrial adaptations suggest evaluation of a sequential paradigm of eccentric followed by concentric cycling as a means of augmenting the training response and attenuating skeletal muscle dysfunction in patients with advanced COPD.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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.

Study designObservational
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

Citations63
Published2017
Admission routes2
Has abstractyes

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