Evaluation of the Topographical Influence on the Cellular Behavior of Human Umbilical Vein Endothelial Cells
Bibliographic record
Abstract
Adhesion and proliferation of vascular endothelial cells are important parameters in the endothelialization of biomedical devices for vascular applications. Endothelialization is a complex process affected by endothelial cells and their interaction with the extracellular microenvironment. Although numerous approaches are taken to study the influence of the external environment, a systematic investigation of the impact of an engineered microenvironment on endothelial cell processes is needed. This study aims to investigate the influence of topography, initial cell seeding density, and collagen coating on human umbilical vein endothelial cells (HUVECs). Utilizing the MultiARChitecture (MARC) chamber, the effects of various topographies on HUVECs are identified, and those with more prominent effects were further evaluated individually using the MARC plate. Endothelial cell marker expression and monocyte adhesion assay are examined on the HUVEC monolayer. HUVECs on 1.8 μm convex and concave microlens topographies demonstrate the lowest cell adhesion and proliferation, regardless of initial cell seeding density and collagen I coating, and the HUVEC monolayer on the microlens shows the lowest monocyte adhesion. This property of lens topographies would potentially be a useful parameter in designing vascular biomedical devices. The MARC chamber and MARC plate show a great potential for faster and easy pattern identification for various cellular processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".