Mutation-specific hemostatic variability in mice expressing common type 2B von Willebrand disease substitutions
Bibliographic record
Abstract
Type 2B von Willebrand disease (2B VWD) results from von Willebrand factor (VWF) A1 mutations that enhance VWF-GPIbalpha binding. These "gain of function" mutations lead to an increased affinity of the mutant VWF for platelets and the binding of mutant high-molecular-weight VWF multimers to platelets in vivo, resulting in an increase in clearance of both platelets and VWF. Three common 2B VWD mutations (R1306W, V1316M, and R1341Q) were independently introduced into the mouse Vwf cDNA sequence and the expression vectors delivered to 8- to 10-week-old C57Bl6 VWF(-/-) mice, using hydrodynamic injection. The resultant phenotype was examined, and a ferric chloride-induced injury model was used to examine the thrombogenic effect of the 2B VWD variants in mice. Reconstitution of only the plasma component of VWF resulted in the generation of the 2B VWD phenotype in mice. Variable thrombocytopenia was observed in mice expressing 2B VWF, mimicking the severity seen in 2B VWD patients: mice expressing the V1316M mutation showed the most severe thrombocytopenia. Ferric chloride-induced injury to cremaster arterioles showed a marked reduction in thrombus development and platelet adhesion in the presence of circulating 2B VWF. These defects were only partially rescued by normal platelet transfusions, thus emphasizing the key role of the abnormal plasma VWF environment in 2B VWD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".