Mechanical and Pharmacological Approaches to Investigate the Pathogenesis of Marfan Syndrome in the Abdominal Aorta
Bibliographic record
Abstract
BACKGROUND: Occurrence of disease complications in the abdominal aorta in Marfan syndrome, a connective tissue disorder caused by mutations in the gene encoding fibrillin-1, is relatively rare. We hypothesized that Marfan syndrome could affect the structure, vasomotor function and mechanical property of the abdominal aorta. METHODS AND RESULTS: Abdominal aorta from mice at 3, 6, 9 and 12 months of age, heterozygous for the Fbn1 allele encoding a cysteine substitution (Fbn1(C1039G/+), Marfan mice, n = 50), were compared with those from age-matched control littermates (n = 50). Marfan abdominal aorta demonstrated pronounced elastic fiber degradation and disorganization, concomitant with an increased aortic stiffness during aging. In the isometric force measurement, vasoconstriction in response to membrane depolarization or phenylephrine stimulation was similar in both Marfan and control abdominal aorta. However, Marfan abdominal aorta was less sensitive to the inhibition of the phenylephrine-induced contraction by indomethacin and SQ-29548, during which the release of thromboxane A(2) was one half of that of the controls. Nevertheless, the protein expression of cyclooxygenase-1 and cyclooxygenase-2 detected by Western immunoblotting was not different between the 2 strains. CONCLUSIONS: We demonstrated that Marfan syndrome affected abdominal aorta with respect to matrix elastic fiber organization, aortic stiffness and release of thromboxane A(2).
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".