Porous hollow membrane sheet for tissue engineering applications
Bibliographic record
Abstract
In spite of the present advances in the scaffolds fabrication and bioreactor systems, the ability to create functional thick tissue masses in vitro is still a great tissue engineering challenge. To overcome this problem, the fabrication of a capillary bed, for nutrient supply to and waste product removal from the tissue engineering construct as it grows, is essential. However, the technical construction of a capillary-like architecture is complex and challenging. This study reports, for the very first time, a simple method to design and fabricate a porous hollow membrane sheet (PHMsh) to provide both a capillary bed and a scaffold to support tissue growth. The PHMsh composed of a flexible porous sheet involving parallel porous channels and can be used as flat-, rolled-, or sandwiched-shape scaffold. The PHMsh was fabricated from poly(epsilon-caprolactone) polymer solution using solvent casting methods (i.e., immersion precipitation and air casting). Optical microscopy and scanning electron microscopy were used for the morphological analyses. The PHMsh was surface treated using n-hepthylamine plasma polymer (HApp) and X-ray photoelectron spectroscopy confirmed successful surface coating. Human umbilical vein endothelial cells (HUVECs) and fibroblast cells were used to evaluate the capability of PHMsh toward cell adhesion. The HApp coating enhanced both HUVEC and fibroblast cells adhesion. The obtained preliminary results demonstrated the successful fabrication of the PHMsh, with potential application for tissue engineering scaffolds, particularly in large tissue mass generation under perfusion systems in vitro, which is our future research direction.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".