Atorvastatin mediates increases in intralesional BAX and BAK expression in human end-stage abdominal aortic aneurysms
Bibliographic record
Abstract
Chronic apoptosis activation may participate in abdominal aortic aneurysm (AAA) expansion. Statin treatment slows AAA progression independent of cholesterol lowering. We hypothesized that Atorvastatin treatment alters apoptosis protein expression and activation in AAAs. Protein was isolated from the central and distal portions of end-stage human AAA tissue obtained during surgical repair from non-statin (NST) and Atorvastatin-treated (AT) patients. Expression was compared using immunoblots. Bcl-2 expression was unchanged but Bak (4-fold, p < 0.013) and Bax (3-fold, p < 0.035) expression was increased in AT (n = 12) versus NST (n = 15) patients. No cytochrome c release or caspase 3 activation was detected and Clusterin, GRP78, and BNIP1 expression was similar in NST and AT samples. Bcl-2 and Bax cDNA sequences from AAA tissue (n = 10) and the general population were identical. Thus, the increase in Bax and Bak in AT-treated AAAs did not activate the mitochondria or endoplasmic reticulum mediated apoptosis pathways. Bcl-2, Bax, and Bak have non-apoptosis related functions that include maintenance of endoplasmic reticulum (ER), homeostasis, and adaptation to stress. We speculate that Atorvastatin-mediated increases in Bax and Bak may positively affect their non-apoptosis related cell functions to account for the beneficial effect of statins to slow AAA expansion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".