Increased injury and intramuscular collagen of the diaphragm in COPD: autopsy observations
Bibliographic record
Abstract
Evidence for diaphragm injury in people with chronic obstructive pulmonary disease (COPD) has been reported, although the extent of injury and collagen accumulation post mortem have not previously been examined. In addition, it is not known whether the amount of injury and collagen are different in key regions of the diaphragm. The cross-sectional area of collagen and the percentage of abnormal myofibres in the post mortem diaphragm and psoas major were determined by computer-assisted image analysis of stained cross-sections of the diaphragm for collagen with picrosirius red and with haematoxylin and eosin for morphology. In the midcostal diaphragm of six subjects with COPD and six subjects with no significant respiratory disease, the COPD diaphragm displayed a greater cross-sectional area of collagen and percentage of abnormal myofibres (collagen: 24.2+/-1.0 versus 18.6+/-1.1%; injury: 28.4+/-7.2 versus 12.0+/-1.3%). In 18 patients with various respiratory conditions, the midcostal diaphragm displayed more collagen and abnormal myofibres than the crural diaphragm, while both costal and crural diaphragms displaying more collagen and abnormal myofibres than psoas major. This study reveals extensive injury and collagen accumulation in the chronic obstructive pulmonary diseased diaphragm, and reveals a regional pattern of injury and intramuscular collagen which may correspond to variations in diaphragm loading.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".