Why Mechanical Properties of Collagen Scaffolds Should Be Tested in a Pseudo-Physiological Environment?
Bibliographic record
Abstract
Collagen gels constitute an adequate scaffold for supporting the adhesion, proliferation and tissue regeneration of vascular cells inside a bioreactor. However, their mechanical properties should be enhanced not only for their manipulation but also to resist the mechanical constraints applied in the bioreactor. Actually, assessing the mechanical properties of a hydrogel requires many precautions since they are very sensitive to the environmental conditions (temperature, ionic strength, aqueous environment, etc). Whereas mechanical properties are usually measured directly in the air, the aim of this work was to evaluate the effects of a pseudo-physiological environment (PPE) on the mechanical properties of collagen gels. Furthermore, reinforcement was also tested using UV treatments (λ = 254 nm, 20 J/cm 2 ), known to induce crosslinking. Irradiated samples were more resistant to enzymatic degradation and swelling tests showed that the crosslink density was increased by a factor of 30. This increase was thereafter correlated to the mechanical properties. Results showed that the UV-treated samples were stiffer and more brittle than the non-treated ones when tested in air. However, a 20% decrease and 40% increase were respectively measured on the linear modulus and strain at rupture when the gels were tested in the PPE. In the perspective of vascular tissue regeneration, these results show that the mechanical properties of a hydrogel should be performed in PPE in order to take into account the plasticization phenomenon that will occur in a bioreactor.
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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 | 0.001 | 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) | 0.006 | 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".