Lipocalin-2 deficiency or blockade protects against aortic abdominal aneurysm development in mice
Bibliographic record
Abstract
AIMS: To study the role of lipocalin-2 (Lcn2) and the effect of Lcn2 blockade via anti-Lcn2 antibody in the development of abdominal aortic aneurysm (AAA). METHODS AND RESULTS: Expression mRNA and protein levels of Lcn2 and its human orthologue neutrophil gelatinase-associated lipocalin (NGAL) in aortic wall samples from experimental mouse and human AAA samples, respectively, were analysed by real-time PCR and immunohistochemistry. Experimental AAA was induced by aortic elastase perfusion in wild-type mice (WT) and Lcn2-deficient mice (Lcn2-/-). NGAL/Lcn2 mRNA and protein levels in human and murine AAA samples were increased compared with healthy aortas. Decreased AAA incidence and reduced aortic expansion were observed in Lcn2-/- mice or mice preoperative treated with a polyclonal anti-Lcn2 antibody compared with WT mice or mice treated with control IgG, respectively, at Day 14 after elastase perfusion. Moreover, immunohistochemical analysis of AAA tissues from Lcn2-/- or anti-Lcn2-treated mice showed diminished elastin damage, reduced microvessels and polymorphonuclear neutrophil (PMN) infiltration, and enhanced preservation of vascular smooth muscle cells compared with WT aortas. Fluorescent molecular tomography revealed decreased MMP activity in AAA of Lcn2-/- mice compared with WT controls. Therapeutic administration of anti-Lcn2 antibody to WT mice 3 days after elastase perfusion decreased aortic dilatation and PMN infiltration compared with WT mice treated with control IgG. CONCLUSION: Either Lcn2 deficiency or anti-Lcn2 antibody blockade limits AAA expansion in mice by decreasing PMN infiltration in the aorta. Lcn2 modulation may therefore be a viable new therapeutic option for the treatment of AAA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".