Longer Telomere Length in COPD Patients with α1-Antitrypsin Deficiency Independent of Lung Function
Bibliographic record
Abstract
Oxidative stress is involved in the pathogenesis of airway obstruction in α1-antitrypsin deficient patients. This may result in a shortening of telomere length, resulting in cellular senescence. To test whether telomere length differs in α1-antitrypsin deficient patients compared with controls, we measured telomere length in DNA from peripheral blood cells of 217 α1-antitrypsin deficient patients and 217 control COPD patients. We also tested for differences in telomere length between DNA from blood and DNA from lung tissue in a subset of 51 controls. We found that telomere length in the blood was significantly longer in α1-antitrypsin deficient COPD patients compared with control COPD patients (p = 1×10(-29)). Telomere length was not related to lung function in α1-antitrypsin deficient patients (p = 0.3122) or in COPD controls (p = 0.1430). Although mean telomere length was significantly shorter in the blood when compared with the lungs (p = 0.0078), telomere length was correlated between the two tissue types (p = 0.0122). Our results indicate that telomere length is better preserved in α1-antitrypsin deficient COPD patients than in non-deficient patients. In addition, measurement of telomere length in the blood may be a suitable surrogate for measurement in the lung.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".