Mutations in fibrillin‐1 leading to classical and neonatal Marfan syndrome cause differential protease susceptibilities and protein function
Bibliographic record
Abstract
Fibrillin‐1 constitutes the backbone of extracellular matrix microfibrils, which are crucial for regulating elastic fiber biogenesis and TGF‐beta bioavailability. Mutations in fibrillin‐1 give rise to the Marfan syndrome (MFS) characterized by vascular, skeletal and ocular symptoms. To investigate molecular consequences of mutations causing severe neonatal or the milder classical form of MFS, point mutations from each group were introduced in recombinant human fibrillin‐1 fragments. Proteolytic susceptibility was probed with physiological and non‐physiological proteases. The mutant proteins harboring neonatal mutations were typically more susceptible to proteolytic cleavage than those with classic mutations. The cleavage sites were found both in close proximity and distant to the mutations, indicating structural changes and the exposure of cryptic cleavage sites. The group of neonatal mutations more severely affected the ability of fibrillin‐1 to interact with heparin/heparan sulfate, which plays a role in microfibril assembly. Fibroblasts attached less efficiently to the neonatal as compared to the classical mutant proteins. These results suggest new molecular pathogenetic concepts for MFS. In most cases the neonatal mutations resulted in more severe effects, and the biochemical variability correlates with the clinical variability observed in MFS. The work was funded by the Canadian CIHR.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".