Identification of MMP-9 as a biomarker for detecting progression of chronic obstructive pulmonary disease
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is a complex immunological disease with multiple pathological features that is primarily induced by smoking together with additional genetic risk factors. COPD is frequently underdiagnosed; forced expiratory volume in the first second (FEV1) is considered to be the main diagnostic measure for COPD, yet it is insufficiently sensitive to monitor disease progression. Biomarkers capable of monitoring COPD progression and severity are needed. In this report, we evaluated matrix metalloproteinase-9 (MMP-9) as an early marker for the detection and staging of COPD, by assessing the mRNA levels of MMP-9 in peripheral blood samples collected from 22 COPD patients, 6 asymptomatic smokers, and 5 healthy controls. Our results demonstrate that the mRNA levels of MMP-9 increased more than two-fold in severe COPD relative to non-COPD smokers or moderate COPD groups. Moreover, in the very severe COPD group, MMP-9 mRNA levels showed a 4-fold increase relative to the non-COPD smokers or the moderate COPD groups, while there was a mild increase (∼40%) when compared to the severe COPD group. Taken together, our results suggest that MMP-9 serves as a biomarker for the grade and severity of COPD.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".