Alginate/Pluronic F127-based encapsulation supports viability and functionality of human dental pulp stem cell-derived insulin-producing cells
Bibliographic record
Abstract
Abstract Background Current approach for diabetes treatment remained several adverse events varied from gastrointestinal to life-threatening symptoms. Regenerative therapy regarding Edmonton protocol has been facing serious limitations involving protocol efficiency and safety. This led to the study for alternative insulin-producing cell (IPC) resource and transplantation platform. In this study, evaluation of encapsulated human dental pulp-derived stem cell (hDPSC)-derived IPCs by alginate (ALG) and pluronic F127-coated alginate (ALGPA) was performed. Results The results showed that ALG and ALGPA preserved hDPSC viability and allowed glucose and insulin diffusion in and out. ALG and ALGPA-encapsulated hDPSC-derived IPCs maintained viability for at least 336 h and sustained pancreatic endoderm marker (NGN3), pancreatic islet markers (NKX6.1, MAF-A, ISL-1, GLUT-2 and INSULIN), and intracellular pro-insulin and insulin expressions for at least 14 days. Functional analysis revealed a glucose-responsive C-peptide secretion of ALG- and ALGPA-encapsulated hDPSC-derived IPCs at 14 days post-encapsulation. Conclusion ALG and ALGPA encapsulations efficiently preserved the viability and functionality of hDPSC-derived IPCs in vitro and could be the potential transplantation platform for further clinical application.
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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) | 0.001 | 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 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".