Atrophy and hypertrophy signalling of the quadriceps and diaphragm in COPD
Bibliographic record
Abstract
BACKGROUND: Factors involved in the regulation of muscle mass in chronic obstructive pulmonary disease (COPD) are still poorly understood. Comparing the signalisation involved in muscle mass regulation between two muscles with different levels of activation within the same subjects is an interesting strategy to tease out the impact of local (muscle activity) versus systemic factors in the regulation of muscle mass. A study was undertaken to measure and compare the protein levels of p-AKT, AKT, Atrogin-1, p-p70S6K, p-4E-BP1, p-GSK3β as well as the mRNA expression of Atrogin-1, MuRF1 and FoxO-1 in the quadriceps and the diaphragm of 12 patients with COPD and 7 controls with normal lung function. METHODS: Diaphragm biopsies were obtained during thoracic surgery and quadriceps samples were obtained from needle biopsies. Protein content and mRNA expression were measured by western blot and quantitative PCR, respectively. RESULTS: Increased mRNA expressions of Atrogin-1, MuRF1 and FoxO-1 were found in the quadriceps compared with the diaphragm only in patients with COPD. The quadriceps/diaphragm ratio for MuRF1 was higher in COPD. The protein level of p-p70S6K was decreased in the quadriceps compared with the diaphragm in patients with COPD. The quadriceps/diaphragm ratios of p-p70S6K and p-GSK3β were lower in patients with COPD than in controls. CONCLUSIONS: These results indicate a greater susceptibility to a catabolic/anabolic imbalance favouring muscle atrophy in the quadriceps compared with the diaphragm in patients with COPD. The balance between the atrophy and hypertrophy signalling is inhomogeneous between respiratory and lower limb muscles, suggesting that local factors are likely to be involved in the regulation of muscle mass in 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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".