Identification of von Willebrand factor D4 domain mutations in patients of Afro‐Caribbean descent: In vitro characterization
Bibliographic record
Abstract
Background: ) revealed the presence of multiple variants located throughout the gene, including variants located in the D4 domain of VWF: p.(Pro2145Thrfs*5) in one patient and p.(Cys2216Phefs*9) in the other patient. Interestingly, D4 variants have not been studied often. Objectives: Our goal was to characterize how the D4 variants p.(Pro2145Thrfs*5) and p.(Cys2216Phefs*9) influenced VWF biosynthesis/secretion and functions using in vitro assays. Methods: Recombinant VWF (rVWF), mutant or wild-type, was produced via transient transfection of the human embryonic kidney cell line 293T. The use of different tags for the wild-type and the mutant allele allowed us to distinguish between the two forms when measuring VWF antigen in medium and cell lysates. Binding of rVWF to its ligands, collagen, factor VIII, ADAMTS13, and platelet receptors was also investigated. Results: Homozygous expression of the p.(Cys2216Phefs*9)-rVWF mutation resulted in an almost complete intracellular retention of the protein. Heterozygous expression led to secretion of almost exclusively wild-type-rVWF, logically capable of normal interaction with the different ligands. In contrast, the p.(Pro2145Thrfs*5)-rVWF exhibited reduced binding to type III collagen and αIIbβ3 integrin compared to wild-type-rVWF. Conclusions: We report two mutations of the D4 domains that induced combined qualitative and quantitative defects.
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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".