Loss of Timp3 Gene Leads to Abdominal Aortic Aneurysm Formation in Response to Angiotensin II
Bibliographic record
Abstract
Aortic aneurysm is dilation of the aorta primarily due to degradation of the aortic wall extracellular matrix (ECM). Tissue inhibitors of metalloproteinases (TIMPs) inhibit matrix metalloproteinases (MMPs), the proteases that degrade the ECM. Timp3 is the only ECM-bound Timp, and its levels are altered in the aorta from patients with abdominal aortic aneurysm (AAA). We investigated the causal role of Timp3 in AAA formation. Infusion of angiotensin II (Ang II) using micro-osmotic (Alzet) pumps in Timp3(-/-) male mice, but not in wild type control mice, led to adverse remodeling of the abdominal aorta, reduced collagen and elastin proteins but not mRNA, and elevated proteolytic activities, suggesting excess protein degradation within 2 weeks that led to formation of AAA by 4 weeks. Intriguingly, despite early up-regulation of MMP2 in Timp3(-/-)Ang II aortas, additional deletion of Mmp2 in these mice (Timp3(-/-)/Mmp2(-/-)) resulted in exacerbated AAA, compromised survival due to aortic rupture, and inflammation in the abdominal aorta. Reconstitution of WT bone marrow in Timp3(-/-)/Mmp2(-/-) mice reduced inflammation and prevented AAA in these animals following Ang II infusion. Treatment with a broad spectrum MMP inhibitor (PD166793) prevented the Ang II-induced AAA in Timp3(-/-) and Timp3(-/-)/Mmp2(-/-) mice. Our study demonstrates that the regulatory function of TIMP3 is critical in preventing adverse vascular remodeling and AAA. Hence, replenishing TIMP3, a physiological inhibitor of a number of metalloproteinases, could serve as a therapeutic approach in limiting AAA development or 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".