Mucus production, lung inflammation and functional decay in IPF
Bibliographic record
Abstract
Background. In idiopatic pulmonary fibrosis (IPF) the progression of the disease can be slow or rapid and the rate of progression strongly influences prognosis. Variations in MUC5B promoter, resulting in a variable increase in mucin expression, have been associated with IPF. It is not known if mucus production could be related to the rate of FVC decay. Aims: 1)To quantify mucus content in severe IPF lungs and to investigate its relation to rate of FVC decline (rapid or slow) and lung inflammation; 2)To compare mucus content in IPF with severe COPD. Methods. Explanted lungs of 14 IPF patients (age:55±10) classified as slow or rapid progressors based on yearly FVC decline ( 10%predicted) were studied. 7 severe COPD explanted lungs and 7 healthy donors lungs were included for comparison. Mucus content was quantified by point counting in Periodic Schiff stained sections. Inflammation was quantified by immunohistochemistry. Results. The volume fraction of mucus in IPF (median;range 2.1;0.4-10.6%) was increased compared to donors (0;0-0.2%;p<0005) and COPD subjects (0.4;0.2-1.1%;p<0.005). Mucus content in COPD subjects was increased compared to donors (p=0.001). When IPF patients were stratified by FVC decline, the mucus content of rapid progressors was twice that present in slow progressors (3.5;1-10.6vs1.4;0.4-10%), but did not reach statistical significance. In IPF lungs mucus content correlated positively with the number of lymphocytes, particularly B (p<0.05,r=0.61) and C8 + (p<0.05,r=0.64). Conclusions. A prominent mucus production is a distinct finding in the lungs of patients with severe IPF, even surpassing the amount in lungs with COPD. The mucus content paralleled the degree of lung inflammation and FVC decline.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".