Potential role of matrix metalloproteinase-2,-9 and tissue inhibitors of metalloproteinase-1,-2 in exudative pleural effusions
Bibliographic record
Abstract
PURPOSE: To investigate diagnostic values of pleural fluid matrix metalloproteinase-2 (MMP-2), MMP-9, tissue inhibitors of metalloproteinase-1 (TIMP-1) and TIMP-2 measurements in tuberculous pleurisy(TP) and malignat pleurisy (MP). METHODS: The study included 24 patients with TP, 22 patients with MP and 15 patients with pleural effusion of non-tuberculous and non-malignant origin as controls. MMP-2,-9 and TIMP-1,-2 levels in pleural fluid were measured by ELISA method. RESULTS: Pleural fluid MMP-2 and MMP-9 levels were higher (P < 0.001, P < 0.001, respectively) in TP than in MP and controls. MP patients have higher pleural fluid MMP-2 and MMP-9 levels (P < 0.01, P < 0.05, respectively) than controls. Pleural fluid TIMP-2 levels were higher (P < 0.01 and P < 0.001, respectively) in MP than in TP and controls. Pleural fluid MMP-9 levels were negatively correlated with pleural fluid TIMP-2 levels (r: 0.464, P=0.029) in patients with MP. CONCLUSIONS: Determination of TIMP-2 in pleural fluid may contribute to differentiate TP from MP. These results suggest that overproduction of MMP-9 and TIMP-2 is associated with accumulation of the pleural effusion in malignancy. Further studies with a greater number of patients are needed to confirm this hypothesis.
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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 | 0.002 |
| 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 | 0.000 |
| 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".