Cell Seeding on UV‐C‐Treated 3D Polymeric Templates Allows for Cost‐Effective Production of Small‐Caliber Tissue‐Engineered Blood Vessels
Bibliographic record
Abstract
There is a strong clinical need to develop small-caliber tissue-engineered blood vessels for arterial bypass surgeries. Such substitutes can be engineered using the self-assembly approach in which cells produce their own extracellular matrix (ECM), creating a robust vessel without exogenous material. However, this approach is currently limited to the production of flat sheets that need to be further rolled into the final desired tubular shape. In this study, human fibroblasts and smooth muscle cells were seeded directly on UV-C-treated cylindrical polyethylene terephthalate glycol-modified (PETG) mandrels of 4.8 mm diameter. UV-C treatment induced surface modification, confirmed by Fourier-transform infrared spectroscopy (FTIR) analysis, was necessary to ensure proper cellular attachment and optimized ECM secretion/assembly. This novel approach generated solid tubular conduits with high level of cohesion between concentric cellular layers and enhanced cell-driven circumferential alignment that can be manipulated after 21 days of culture. This simple and cost-effective mandrel-seeded approach also allowed for endothelialization of the construct and the production of perfusable trilayered tissue-engineered blood vessels with a closed lumen. This study lays the foundation for a broad field of possible applications enabling custom-made reconstructed tissues of specialized shapes using a surface treated 3D structure as a template for tissue engineering.
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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".