Effectiveness of Cyclooxygenase-2 Inhibition in Limiting Abdominal Aortic Aneurysm Progression in Mice Correlates With a Differentiated Smooth Muscle Cell Phenotype
Bibliographic record
Abstract
Abdominal aortic aneurysms (AAAs) are a chronic condition that often progress over years to produce a weakened aorta with increased susceptibility for rupture, and currently, there are no pharmacological treatments available to slow disease progression. AAA development has been characterized by increased expression of cyclooxygenase-2 (COX-2), and inactivation of COX-2 before disease initiation reduces AAA incidence in a mouse model of the disease. The current study determined the effectiveness of COX-2 inhibition on AAA progression when treatment was begun after initiation of the disease. COX-2 inhibitor treatment with celecoxib was initiated after angiotensin II-induced AAA formation in a strain of nonhyperlipidemic mice that we have previously identified as highly susceptible to AAA development. When analyzed at different time points during progression of the disease, celecoxib treatment significantly reduced the incidence and severity of AAAs. The celecoxib treatment also protected the mice from aortic rupture and death. The aneurysmal lesion displayed an altered smooth muscle cell (SMC) phenotype, whereas celecoxib treatment was associated with increased expression of differentiated SMC markers and reduced dedifferentiation marker expression during AAA progression. Maintenance of a differentiated SMC phenotype is associated with the effectiveness of COX-2 inhibition for limiting AAA progression in nonhyperlipidemic mice.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".