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Record W2883498253 · doi:10.1113/jp275558

Smoke‐induced neuromuscular junction degeneration precedes the fibre type shift and atrophy in chronic obstructive pulmonary disease

2018· article· en· W2883498253 on OpenAlexafffund
Sophia Kapchinsky, Madhusudanarao Vuda, Kayla Míguez, Daren Elkrief, Angela Rico de Souza, Carolyn J. Baglole, Sudhakar Aare, Norah J. MacMillan, Jacinthe Baril, Paul Rozakis, Vita Sonjak, Charlotte H. Pion, Mylène Aubertin‐Leheudre, José A. Morais, R. Thomas Jagoe, Jean Bourbeau, Tanja Taivassalo, Russell T. Hepple

Bibliographic record

VenueThe Journal of Physiology · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsJewish General HospitalUniversité de MontréalInstitut Universitaire de Gériatrie de MontréalUniversité du Québec à MontréalRoctest (Canada)McGill University Health CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsPulmonary diseaseDegeneration (medical)AtrophyMedicineNeuromuscular junctionCigarette smokeNeuromuscular diseasePathologyDiseaseInternal medicineNeuroscienceBiology

Abstract

fetched live from OpenAlex

KEY POINTS: Chronic obstructive pulmonary disease (COPD) is largely caused by smoking, and patient limb muscle exhibits a fast fibre shift and atrophy. We show that this fast fibre shift is associated with type grouping, suggesting recurring cycles of denervation-reinnervation underlie the type shift. Compared to patients with normal fat-free mass index (FFMI), patients with low FFMI exhibited an exacerbated fibre type shift, marked accumulation of very small persistently denervated muscle fibres, and a blunted denervation-responsive transcript profile, suggesting failed denervation precipitates muscle atrophy in patients with low FFMI. Sixteen weeks of passive tobacco smoke exposure in mice caused neuromuscular junction degeneration, consistent with a key role for smoke exposure in initiating denervation in COPD. ABSTRACT: A neurological basis for the fast fibre shift and atrophy seen in limb muscle of patients with chronic obstructive pulmonary disease (COPD) has not been considered previously. The objective of our study was: (1) to determine if denervation contributes to fast fibre shift and muscle atrophy in COPD; and (2) to assess using a preclinical smoking mouse model whether chronic tobacco smoke (TS) exposure could initiate denervation by causing neuromuscular junction (NMJ) degeneration. Vastus lateralis muscle biopsies were obtained from severe COPD patients [n = 10 with low fat-free mass index (FFMI), 65 years; n = 15 normal FFMI, 65 years) and healthy age- and activity-matched non-smoker control subjects (CON; n = 11, 67 years), to evaluate morphological and transcriptional markers of denervation. To evaluate the potential for chronic TS exposure to initiate these changes, we examined NMJ morphology in male adult mice following 16 weeks of passive TS exposure. We observed a high proportion of grouped fast fibres and a denervation transcript profile in COPD patients, suggesting that motor unit remodelling drives the fast fibre type shift in COPD patient limb muscle. A further exacerbation of fast fibre grouping in patients with low FFMI, coupled with blunted reinnervation signals, accumulation of very small non-specific esterase hyperactive fibres and neural cell adhesion molecule-positive type I and type II fibres, suggests denervation-induced exhaustion of reinnervation contributes to muscle atrophy in COPD. Evidence from a smoking mouse model showed significant NMJ degeneration, suggesting that recurring denervation in COPD is probably caused by decades of chronic TS exposure.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.000

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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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

Citations47
Published2018
Admission routes2
Has abstractyes

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