Alterations in Skeletal Muscle Cell Homeostasis in a Mouse Model of Cigarette Smoke Exposure
Bibliographic record
Abstract
BACKGROUND: Skeletal muscle dysfunction is common in chronic obstructive pulmonary disease (COPD), a disease mainly caused by chronic cigarette use. An important proportion of patients with COPD have decreased muscle mass, suggesting that chronic cigarette smoke exposure may interfere with skeletal muscle cellular equilibrium. Therefore, the main objective of this study was to investigate the kinetic of the effects that cigarette smoke exposure has on skeletal muscle cell signaling involved in protein homeostasis and to assess the reversibility of these effects. METHODS: A mouse model of cigarette smoke exposure was used to assess skeletal muscle changes. BALB/c mice were exposed to cigarette smoke or room air for 8 weeks, 24 weeks or 24 weeks followed by 60 days of cessation. The gastrocnemius and soleus muscles were collected and the activation state of key mediators involved in protein synthesis and degradation was assessed. RESULTS: Gastrocnemius and soleus were smaller in mice exposed to cigarette smoke for 8 and 24 weeks compared to room air exposed animals. Pro-degradation proteins were induced at the mRNA level after 8 and 24 weeks. Twenty-four weeks of cigarette smoke exposure induced pro-degradation proteins and reduced Akt phosphorylation and glycogen synthase kinase-3β quantity. A 60-day smoking cessation period reversed the cell signaling alterations induced by cigarette smoke exposure. CONCLUSIONS: Repeated cigarette smoke exposure induces reversible muscle signaling alterations that are dependent on the duration of the cigarette smoke exposure. These results highlights a beneficial aspect associated with smoking cessation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".