Investigation of human adipose‐derived stem‐cell behavior using a cell‐instructive polydopamine‐coated gelatin–alginate hydrogel
Bibliographic record
Abstract
Hydrogels can be fabricated and designed to exert direct control over stem cells' adhesion and differentiation. In this study, we have investigated the use of polydopamine (pDA)-treatment as a binding platform for bioactive compounds to create a versatile gelatin-alginate (Gel-Alg) hydrogel for tissue engineering applications. Precisely, pDA was used to modify the surface properties of the hydrogel and better control the adhesion and osteogenic differentiation of human adipose-derived stem cells (hASCs). pDA enabled the adsorption of different types of bioactive molecules, including a model osteoinductive drug (dexamethasone) as well as a model pro-angiogenic peptide (QK). The pDA treatment efficiently retained the drug and the peptide compared to the untreated hydrogel and proved to be effective in controlling the morphology, cell area, and osteogenic differentiation of hASCs. Overall, the findings of this study confirm the efficacy of pDA treatment as a valuable strategy to modulate the biological properties of biocompatible Gel-Alg hydrogels and further extend their value in regenerative medicine.
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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 | 0.000 | 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) | 0.000 | 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".