Effect of manufacturing and experimental conditions on the mechanical and surface properties of silicone elastomer scaffolds used in endothelial mechanobiological studies
Bibliographic record
Abstract
BACKGROUND: Mechanobiological studies allow the characterization of cell response to mechanical stresses. Cells need to be supported by a material with properties similar to the physiological environment. Silicone elastomers have been used to produce various in vitro scaffolds of different geometries for endothelial cell studies given its relevant mechanical, optical and surface properties. However, obtaining defined and repeatable properties is a challenge as depending on the different manufacturing and processing steps, mechanical and surface properties may vary significantly between research groups. METHODS: The impact of different manufacturing and processing methods on the mechanical and surface properties was assessed by measuring the Young's modulus and the contact angle. Silicone samples were produced using different curing temperatures and processed with different sterilization techniques and hydrophilization conditions. RESULTS: . Sterilization by boiling had a tendency to stiffen samples cured at lower temperatures whereas UV and ethanol did not alter the material properties. Hydrophilization using sulphuric acid allowed to decrease surface hydrophobicity, however this effect was lost over time as hydrophobic recovery occurred. Extended contact with water maintained decreased hydrophobicity up to 7 days. Mechanobiological studies require complete cell coverage of the scaffolds used prior to mechanical stresses exposure. Different concentrations of fibronectin and collagen were used to coat the scaffolds and cell seeding density was varied to optimize cell coverage. CONCLUSION: This study highlights the potential bias introduced by manufacturing and processing conditions needed in the preparation of scaffolds used in mechanobiological studies involving endothelial cells. As manufacturing, processing and cell culture conditions are known to influence cell adhesion and function, they should be more thoroughly assessed by research groups that perform such mechanobiological studies using silicone.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".