Development and Characterization of a Human Model of Arteriovenous Malformations (AVM)-on-a-Chip
Bibliographic record
Abstract
Arteriovenous Malformation (AVM) is a vascular disease characterized by arteriovenous shunting that results in dilated and fragile vessels. So far, there are no pharmaceutical treatments available for AVMs. To address this need, we engineered an AVM-on-a-Chip that allows for real-time assessment of barrier function and morphological characteristics. The AVM-on-a-chip is created using a heterogeneous culture of immortalized human umbilical vein endothelial cells (HUVECs) with KRAS-mutant HUVECs, a know mutations associated with AVM formation, and supporting fibroblasts. A fibrin cell suspension is seeded into the platform to naturally form tubular and perfusable vascular networks. Key hallmarks of AVM were captured through areas of vascular dysplasia from KRAS mutant HUVECs, which affected the overall vascular structure. We found a significant increase in vascular permeability due to cell-cell junction breakdown in KRAS-positive vessel segments. Additionally, KRAS positive segments led to increase in vessel width and decreased branch length. Treatment with MEK inhibitor, a previously investigated reagent in AVM therapy, only recovered barrier function but not vascular distension.
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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 | 0.001 | 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".