R1205H (Vicenza) causes conformational changes in the von Willebrand factor D′D3 domains and enhances von Willebrand factor binding to clearance receptors LRP1 and SR-AI
Bibliographic record
Abstract
BACKGROUND: von Willebrand factor (VWF)-R1205H variant (Vicenza) results in markedly enhanced VWF clearance in humans that has been shown to be largely macrophage-mediated. However, the biological mechanisms underlying this enhanced clearance remain poorly understood. OBJECTIVES: This study aimed to investigate the roles of (i) specific VWF domains and (ii) different macrophage receptors in regulating enhanced VWF-R1205H clearance. METHODS: mice. Plate-binding assays were employed to characterize VWF binding to purified scavenger receptor class A member 1 (SR-AI), low-density lipoprotein receptor-related protein-1 (LRP1) cluster II or cluster IV receptors, and macrophage galactose-type lectin. RESULTS: mice compared with WT-VWF missing the A1 domain. Importantly, R1205H in a truncated VWF-D'D3 fragment also triggered increased clearance compared with WT-VWF-D'D3. Additional in vivo studies demonstrated that VWF-R1205K (which preserves the positive charge at 1205) exhibited normal clearance, whereas VWF-R1205E (which results in loss of the positive charge) caused significantly enhanced clearance, pinpointing the importance of the positive charge at VWF-R1205. In vitro plate-binding studies confirmed increased VWF-R1205H interaction with SR-AI compared with WT-VWF. Furthermore, significantly enhanced VWF-R1205H binding to LRP1 cluster IV (P < .001) and less marked enhanced binding to LRP1 cluster II (P = .034) was observed. In contrast, VWF-R1205H and WT-VWF demonstrated no difference in binding affinity to macrophage galactose-type lectin. CONCLUSION: Disruption of the positive charge at amino acid R1205 causes conformational changes in the VWF-D'D3 domains and triggers enhanced LRP1-mediated and SR-AI-mediated clearance.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".