Mechanical Properties of Tissue-Engineered Vascular Constructs Produced Arterial or Venous Cells
Bibliographic record
Abstract
There is a clinical need for better blood vessel substitutes, as current surgical procedures are limited by the availability of suitable autologous vessels and suboptimal behavior of synthetic grafts in small caliber arterial graft (<5 mm) applications. The aim of the present study was to compare the mechanical properties of arterial and venous tissue-engineered vascular constructs produced by the self-assembly approach using cells extracted from either the artery or vein harvested from the same human umbilical cord. The production of a vascular construct comprised of a media and an adventitia (TEVMA) was achieved by rolling a continuous tissue sheet containing both smooth muscle cells and adventitial fibroblasts grown contiguously in the same tissue culture plate. Histology and immunofluorescence staining were used to evaluate the structure and composition of the extracellular matrix of the vascular constructs. The mechanical strength was assessed by uniaxial tensile testing, whereas viscoelastic behavior was evaluated by stepwise stress-relaxation and by cyclic loading hysteresis analysis. Tensile testing showed that the use of arterial cells resulted in stronger and stiffer constructs when compared with those produced using venous cells. Moreover, cyclic loading demonstrated that constructs produced using arterial cells were able to bear higher loads for the same amount of strain when compared with venous constructs. These results indicate that cells isolated from umbilical cord can be used to produce vascular constructs. Arterial constructs possessed superior mechanical properties when compared with venous constructs produced using cells isolated from the same human donor. This study highlights the fact that smooth muscle cells and fibroblasts originating from different cell sources can potentially lead to distinct tissue properties when used in tissue engineering applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 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".