Reversal of diabetes by βTC3 cells encapsulated in alginate beads generated by emulsion and internal gelation
Bibliographic record
Abstract
Encapsulation of insulin-producing cells in alginate beads could improve the treatment of type 1 diabetes by reducing or eliminating the need for immunosuppression. We have recently adapted an emulsion and internal gelation process to β-cell encapsulation. This process has the advantages of being well suited for m(3)/h production rates and allowing the use of increased alginate concentrations. Compared with 1.5% alginate beads generated by a standard extrusion process, 5% alginate emulsion-generated beads demonstrated greater in vitro stability and greater volumetric exclusion of antibody-sized pullulan. When βTC3 cells were transplanted into streptozotocin-induced allogeneic diabetic mice, a significant decrease in the blood glucose levels was seen within 2 days with the 5% emulsion-generated beads but not until >16 days with the 1.5% extrusion-generated beads. This was correlated with higher cell survival and lower graft-specific plasma immunoglobulin levels. These results suggest that higher-concentration alginate beads generated by emulsion and internal gelation have improved graft immunoprotection. The emulsion process is a promising and scalable technology for cellular therapies requiring immune isolation.
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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 | 0.001 |
| 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 | 0.001 |
| 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".