Extracellular matrix, regional heterogeneity of the aorta, and aortic aneurysm
Bibliographic record
Abstract
Aortic aneurysm is an asymptomatic disease with dire outcomes if undiagnosed. Aortic aneurysm rupture is a significant cause of death worldwide. To date, surgical repair or endovascular repair (EVAR) is the only effective treatment for aortic aneurysm, as no pharmacological treatment has been found effective. Aortic aneurysm, a focal dilation of the aorta, can be formed in the thoracic (TAA) or the abdominal (AAA) region; however, our understanding as to what determines the site of aneurysm formation remains quite limited. The extracellular matrix (ECM) is the noncellular component of the aortic wall, that in addition to providing structural support, regulates bioavailability of an array of growth factors and cytokines, thereby influencing cell function and behavior that ultimately determine physiological or pathological remodeling of the aortic wall. Here, we provide an overview of the ECM proteins that have been reported to be involved in aortic aneurysm formation in humans or animal models, and the experimental models for TAA and AAA and the link to ECM manipulations. We also provide a comparative analysis, where data available, between TAA and AAA, and how aberrant ECM proteolysis versus disrupted synthesis may determine the site of aneurysm formation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".