In vivo characterization of doxycycline-mediated protection of aortic function and structure in a mouse model of Marfan syndrome-associated aortic aneurysm
Bibliographic record
Abstract
Aortic aneurysm is the most life-threatening complication in Marfan syndrome (MFS) patients. Doxycycline, a nonselective matrix metalloproteinases inhibitor, was reported to improve the contractile function and elastic fiber structure and organization in a Marfan mouse aorta using ex vivo small chamber myography. In this study, we assessed the hypothesis that a long-term treatment with doxycycline would reduce aortic root growth, improve aortic wall elasticity as measured by pulse wave velocity, and improve the ultrastructure of elastic fiber in the mouse model of MFS. In our study, longitudinal measurements of aortic root diameters using high-resolution ultrasound imaging display significantly decreased aortic root diameters and lower pulse wave velocity in doxycycline-treated Marfan mice starting at 6 months as compared to their non-treated MFS counterparts. In addition, at the ultrastructural level, our data show that long-term doxycycline treatment corrects the irregularities of elastic fibers within the aortic wall of Marfan mice to the levels similar to those observed in control subjects. Our findings underscore the key role of matrix metalloproteinases during the progression of aortic aneurysm, and provide new insights into the potential therapeutic value of doxycycline in blocking MFS-associated aortic aneurysm.
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 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 | 0.000 | 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) | 0.000 | 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 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".