Dysfunction of endothelial and smooth muscle cells in small arteries of a mouse model of Marfan syndrome
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Marfan syndrome, a connective tissue disorder caused by mutations in FBN1 encoding fibrillin-1, results in life-threatening complications in the aorta, but little is known about its effects in resistance vasculature. EXPERIMENTAL APPROACH: Second-order mesenteric arteries from mice at 3, 6 and 10 months of age (n= 30) heterozygous for the Fbn1 allele encoding a cysteine substitution (Fbn1(C1039G/+)) were compared with those from age-matched control littermates. KEY RESULTS: Stress-strain curves indicated that arterial stiffness was increased at 6 and 10 months of age in Marfan vessels. Isometric force measurement revealed that contraction in response to potassium (60 mM)-induced membrane depolarization was decreased by at least 28% in Marfan vessels at all ages, while phenylephrine (3 microM)-induced contraction was reduced by at least 40% from 6 months. Acetylcholine-induced relaxation in Marfan vessels was reduced to 70% and 45% of control values, respectively, at 6 and 10 months. Sensitivity to sodium nitroprusside was reduced at 6 months (pEC(50)= 5.64 +/- 0.11, control pEC(50)= 7.34 +/- 0.04) and 10 months (pEC(50)= 5.99 +/- 0.07, control pEC(50)= 6.99 +/- 0.14). Pretreatment with N(omega)-Nitro-L-arginine methyl ester (200 microM) had no effect on acetylcholine-induced relaxation in Marfan vessels, but reduced vasorelaxation in control vessels to 57% of control values. Addition of indomethacin (10 microM) and catalase (1000 U.mL(-1)) further inhibited vasorelaxation in Marfan vessels to a greater degree compared with control vessels. CONCLUSIONS AND IMPLICATIONS: Pathogenesis of Marfan syndrome in resistance-sized arteries increases stiffness and impairs vasomotor function.
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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 | 0.000 | 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".