An engineered cell sheet composed of human islets and human fibroblast, bone marrow–derived mesenchymal stem cells, or adipose–derived mesenchymal stem cells: An <i>in vitro</i> comparison study
Bibliographic record
Abstract
BACKGROUND: We previously reported the utility of engineered cell sheets composed of human islets and supporting cells in vitro and in vivo. It is unclear which type of supporting cell is most suitable for constructing cell sheets with human islets. The present study aimed to compare human fibroblasts, bone marrow-derived mesenchymal stem cells (BM-MSCs), and adipose-derived mesenchymal stem cells (ADSCs) as a supporting source for cell sheets. METHODS: Engineered cell sheets were fabricated with human islets using human fibroblasts, BM-MSCs, or ADSCs as supporting cells. The islet viability, recovery rate, glucose-stimulated insulin release (determined by the stimulation index), and cytokine secretion (TGF-β1, IL-6, and VEGF) of groups-including an islet-alone group as a control-were compared. RESULTS: All three sheet groups consistently exhibited higher viability, recovery rate, and stimulation index values than the islet-alone group. The ADSC group showed the highest viability and recovery rate among the three sheet groups. There were no discernible differences in the stimulation index values of the groups. The fibroblast group exhibited significantly higher TGF-β1 values in comparison to the other groups. The IL-6 level of the ADSC group was more than five times higher than that of the other groups. The ADSC group showed the VEGF level; however, it did not differ from that of the BM-MSC group to a statistically significant extent. CONCLUSION: Engineered cell sheets composed of islets and supporting cells had a cytoprotective effect on islets. These results suggest that individual cell types could be a more attractive source for crafting engineered cell sheets in comparison to islets alone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 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".