Muscle Atrophy and Hypertrophy Signaling in Patients with Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: The molecular mechanisms of muscle atrophy in chronic obstructive pulmonary disease (COPD) are poorly understood. In wasted animals, muscle mass is regulated by several AKT-related signaling pathways. OBJECTIVES: To measure the protein expression of AKT, forkhead box class O (FoxO)-1 and -3, atrogin-1, the phosphophrylated form of AKT, p70(S6K) glycogen synthase kinase-3beta (GSK-3beta), eukaryotic translation initiation factor 4E binding protein-1 (4E-BP1), and the mRNA expression of atrogin-1, muscle ring finger (MuRF) protein 1, and FoxO-1 and -3 in the quadriceps of 12 patients with COPD with muscle atrophy and 10 healthy control subjects. Five patients with COPD with preserved muscle mass were subsequently recruited and were compared with six patients with low muscle mass. METHODS: Protein contents and mRNA expression were measured by Western blot and quantitative polymerase chain reaction, respectively. MEASUREMENTS AND MAIN RESULTS: The levels of atrogin-1 and MuRF1 mRNA, and of phosphorylated AKT and 4E-BP1 and FoxO-1 proteins, were increased in patients with COPD with muscle atrophy compared with healthy control subjects, whereas atrogin-1, p70(S6K), GSK-3beta, and FoxO-3 protein levels were similar. Patients with COPD with muscle atrophy showed an increased expression of p70(S6K), GSK-3beta, and 4E-BP1 compared with patients with COPD with preserved muscle mass. CONCLUSIONS: An increase in atrogin-1 and MuRF1 mRNA and FoxO-1 protein content was observed in the quadriceps of patients with COPD. The transcriptional regulation of atrogin-1 and MuRF1 may occur via FoxO-1, but independently of AKT. The overexpression of the muscle hypertrophic signaling pathways found in patients with COPD with muscle atrophy could represent an attempt to restore muscle mass.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".