Initiation of Medial Calcification: Revisiting Calcium Ion Binding to Elastin
Bibliographic record
Abstract
Pathological calcification of elastin, a key connective tissue protein in the medial layers of blood vessels, starts with the binding of calcium ions. This Mini-Review focuses on understanding how calcium ions interact with elastin to initiate calcification at a molecular level, and emphasizes water's critical role in mediating this interaction. In the past decade, great strides have been made in understanding and modeling ion-specific hydration and its effects on biomolecule interactions. However, these advances have been largely absent from our understanding of elastin calcification. Historically, charge-neutral backbone carbonyls and negatively charged carboxyl groups have been proposed as elastin's calcium binding sites. Recently, tropoelastin's only four carboxyl groups have been identified as binding sites from classical molecular dynamics (MD). While carboxyl groups have a much higher affinity for binding calcium ions than backbone carbonyls, conflicting evidence persists for both functional group's importance in elastin calcification. This can be attributed to the fact that divalent ions strongly polarize water, leading to a hydration shell that shields electrostatic forces. The hydration shell surrounding both a calcium ion and either of the proposed binding sites must be displaced to enable binding. Providing our own extended X-ray absorption fine structure (EXAFS) data and complementary simulations, we discuss the potential structures of calcium binding in elastin and review prior knowledge regarding the relative importance of the two proposed binding sites.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".