Polymorphisms in the Human Tropoelastin Gene Modify In Vitro Self-Assembly and Mechanical Properties of Elastin-Like Polypeptides
Bibliographic record
Abstract
Elastin is a major structural component of elastic fibres that provide properties of stretch and recoil to tissues such as arteries, lung and skin. Remarkably, after initial deposition of elastin there is normally no subsequent turnover of this protein over the course of a lifetime. Consequently, elastic fibres must be extremely durable, able to withstand, for example in the human thoracic aorta, billions of cycles of stretch and recoil without mechanical failure. Major defects in the elastin gene (ELN) are associated with a number of disorders including Supravalvular aortic stenosis (SVAS), Williams-Beuren syndrome (WBS) and autosomal dominant cutis laxa (ADCL). Given the low turnover of elastin and the requirement for the long term durability of elastic fibres, we examined the possibility for more subtle polymorphisms in the human elastin gene to impact the assembly and long-term durability of the elastic matrix. Surveys of genetic variation resources identified 118 mutations in human ELN, 17 being non-synonymous. Introduction of two of these variants, G422S and K463R, in elastin-like polypeptides as well as full-length tropoelastin, resulted in changes in both their assembly and mechanical properties. Most notably G422S, which occurs in up to 40% of European populations, was found to enhance some elastomeric properties. These studies reveal that even apparently minor polymorphisms in human ELN can impact the assembly and mechanical properties of the elastic matrix, effects that over the course of a lifetime could result in altered susceptibility to cardiovascular disease.
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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 | 0.000 | 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".