Polydopamine-coated paper-stack nanofibrous membranes enhancing adipose stem cells' adhesion and osteogenic differentiation
Bibliographic record
Abstract
In the fabrication of 3-D complex tissues for implantation, layer-by-layer (LBL) electrospun nanofibrous scaffolds have recently received intensive interest. However, poor cell adhesion and cell expansion between the layers in an LBL stack remain important issues. In this study, we report a mussel-inspired, biomimetic approach to functionalize the surface of PCL/gelatin nanofibrous membranes coated with poly (dopamine) (PDA). Our study demonstrates that a PDA coating on electrospun PCL/gelatin nanofibers leads to a significant change in their surface properties and a higher adhesion force. Furthermore, we found that PDA coating promotes the adhesion and growth of adipose stem cells (ADSCs). In 3-D LBL stacked scaffolds, more cells survived in a PAD-coated scaffold than in a non-coated one. The PDA coating was further demonstrated to promote the osteogenic differentiation of ADSCs in LBL paper-stacking membranes. Our study suggests that PDA-coated paper-stacking nanofiber membranes present a facile and economic method for the development of 3D tissue engineering.
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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) | 0.001 | 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".