89-OR: Immunoprivileged Hydrogels Extend Functionality of Islets in Immunocompetent Animals
Bibliographic record
Abstract
Background: Despite the promise of current islet cell transplantation, the need for systemic immune suppression significantly limits its utility for patients with diabetes. Until safe and immune-evasive cells are realized, physical immuno-protection offers an alternate route to allogeneic islet implants. Our proprietary synthetic hydrogels provide shape-agnostic, robust and retrievable Islet environments with anti-fouling and non-fibrotic properties. Methods: Rat and human donor islets were encapsulated and implanted in the peritoneal space of streptozotocin (STZ)-induced diabetic immunocompetent mice and pigs to assess islet functionality over time through measurement of blood glucose, C-peptide, and HbA1c. Next generation shape-agnostic hydrogels were also tested for in-vitro and in-vivo function. Results: Our hydrogels enabled rapid and persistent blood glucose control for 140+ days in immunocompetent mice with marginal loads of 1000 rat IEQ/mouse. Human donor islet function in mice was extended to day 45 (~8x longer than free human islets), with C-peptide detected at day 50, and corresponding HbA1c decreases. Our hydrogels showed minimal fibrosis when explanted after 45 days and showed robustness and integrity at day 340 post-implant in immunocompetent mice. Next-gen shape-agnostic hydrogels successfully excluded immune components including IgG and maintained good islet function in vitro. Our data also demonstrate function of human donor islets in immunocompetent pigs, based on C-peptide and cell viability data. Conclusion: Our proprietary synthetic and retrievable hydrogels show strong immune protection in xenogenic transplants of donor islets into immune-competent animals. We are currently scaling to therapeutic doses in large animals, in pursuit of a curative therapy based on an optimal balance of Islet protection and functionality, without immunosuppression. Disclosure H.Stover: Employee; Allarta Life Science Inc.
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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) | 0.002 | 0.001 |
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".