<i>In Vivo</i> Phenotypic Vascular Dysfunction Extends Beyond the Aorta in a Mouse Model for Fibrillin-1 ( <i>FBN1</i> ) Mutation
Bibliographic record
Abstract
Abstract In individuals with Marfan Syndrome (MFS), fibrillin-1 gene ( FBN1 ) mutations can lead to vascular wall weakening and dysfunction. The experimental mouse model of MFS ( FBN1 C1041G/+ ) has been advantageous in investigating MFS-associated life-threatening aortic aneurysms. Although the MFS mouse model presents an accelerated-aging phenotype in elastic organs (e.g., lung, skin), the impact of FBN1 mutations on other central and peripheral arteries function and structure with the consideration of the impact of sex remains underexplored. In this study, we investigate if FBN1 mutation contributes to sex-dependent alterations in central and cerebral vascular function similar to phenotypic changes associated with normal aging in healthy control mice. In vivo ultrasound imaging of central and cerebral vasculature was performed in 6-month-old male and female MFS and C57BL/6 mice and sex-matched 12-month-old (middle-aged) healthy control mice. Our findings confirm aortic enlargement (aneurysm) and wall stiffness in MFS mice, but with exacerbation in male diameters. Coronary artery blood flow velocity (BFV) in diastole was not different but left pulmonary artery BFV was decreased in MFS and 12-month-old control mice regardless of sex. At 6 months of age, MFS male mice show decreased posterior cerebral artery BFV as compared to age-matched control males, with no difference observed between female cohorts. Reduced mitral valve early-filling velocities were indicated in MFS mice regardless of sex. Male MFS mice also demonstrated left ventricular hypertrophy. Overall, these results underscore the significance of biological sex in vascular function and structure in MFS mice, while highlighting a trend of pre-mature vascular aging phenotype in MFS mice that is comparable to phenotypes observed in older healthy controls.
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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 | 0.000 |
| 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 | 0.001 |
| 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".