Effect of statins on proteolytic activity in the wall of abdominal aortic aneurysms
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to examine the effect of statin treatment on the activity of proteases in the wall of abdominal aortic aneurysms (AAAs). METHODS: The activities of matrix metalloproteinases (MMPs) 9 and 3, cathepsins B, H, K, L and S, and the cystatin C level were measured in extracts of AAA wall taken from 82 patients undergoing AAA repair; 21 patients were receiving statin treatment before surgery. All values were standardized against soluble protein (SP) concentration in the extract, and reported as median (interquartile range) or mean(s.e.m.). RESULTS: The two groups had similar demographics. Reduced activity of MMP-9 (43 (34-56) versus 80 (62-110) pg per mg SP; P < 0.001), cathepsin H (183 (117-366) versus 321 (172-644) nmol 4-methylcoumarin-7-amide released per mg SP; P = 0.016) and cathepsin L (102 (51-372) versus 287 (112-816) micromol 7-amino-4-trifluoromethylcoumarin released per mg SP; P = 0.020) was found in the statin-treated aortas compared with AAAs from patients not taking a statin. The statin-treated group had lower MMP-3 activity, but this did not reach statistical significance (P = 0.053). Cystatin C levels were higher in statin-treated aortas than in controls (41.3(3.1) versus 28.9(2.1) ng per mg SP; P = 0.003). CONCLUSION: Statins decreased the activity of proteases that have been implicated in aneurysm disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".