Abnormal angiogenesis in blood outgrowth endothelial cells derived from von Willebrand disease patients
Bibliographic record
Abstract
: Bleeding associated with angiodysplasia is a common, often intractable complication in patients with von Willebrand disease (VWD). von Willebrand factor (VWF), the protein deficient or defective in VWD, is a negative regulator of angiogenesis, which may explain the pathologic blood vessel growth in VWD. This study explores the normal range of angiogenesis in blood outgrowth endothelial cells (BOECs) derived from healthy donors and compares this to angiogenesis in BOECs from VWD patients of all types and subtypes. BOECs were assessed for VWF and angiopoietin-2 (Ang-2) gene expression, secretion, and storage. To explore angiogenic potential, we characterized cellular proliferation, matrix protein adhesion, migration, and tubule formation. We found great angiogenic variability in VWD BOECs with respect to each of the angiogenesis parameters. However, type 1 and 3 VWD BOECs had higher Ang-2 secretion associated with impaired endothelial cell migration velocity and enhanced directionality. Type 2A and 2B BOECs were the most proliferative and multiple VWD BOECs had impaired tubule formation in Matrigel. This study highlights the angiogenic variability in BOECs derived from VWD patients. Abnormal cell proliferation, migration, and increased Ang-2 secretion are common features of VWD BOECs. Despite the many abnormalities of VWD BOECs, significant heterogeneity among individual VWD phenotypes precludes a simple description of relationship between VWD type and in vitro surrogates for angiodysplasia.
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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".