MICROENCAPSULATION OF NEONATAL PORCINE ISLETS: PROTECTION FROM HUMAN ANTIBODY/COMPLEMENT-MEDIATED CYTOLYSIS IN VITRO AND LONG-TERM REVERSAL OF DIABETES IN NUDE MICE1
Bibliographic record
Abstract
BACKGROUND: Recently, we have developed a simple and reliable method to efficiently isolate large numbers of neonatal porcine islets (NPI). We and others have shown that NPI are susceptible to cytolysis by the activation of human complement in vitro. Microencapsulation of islets may be one strategy to protect NPI from this form of rejection. We examined whether microencapsulation can prevent lysis of NPI induced by human antibody and complement in vitro and also assessed their ability to reverse hyperglycemia in diabetic nude mice. METHODS: NPI were microencapsulated with purified alginate, cultured for 2 days, then tested for sensitivity to fresh human serum using an established in vitro cytotoxicity assay or transplanted into alloxan-induced diabetic nude mice. RESULTS: Incubation of nonencapsulated NPI for 24 hr in the presence of fresh human serum resulted in a 53% loss of cellular insulin content, a 51% reduction in recoverable DNA content, and a marked reduction of insulin secretory responsiveness when compared with controls cultured in heat-inactivated human serum. In contrast, exposure of encapsulated islets to fresh human serum had no cytotoxic effect on the islets. Transplantation of 2000 encapsulated NPI i.p. into diabetic nude mice (n=16) corrected hyperglycemia in all mice within 8 weeks. Similar results were obtained when 2000 nonencapsulated NPI were implanted under the kidney capsule (n=10); however recipients of nonencapsulated NPI placed i.p. failed to obtain euglycemia and survived for only 3 weeks posttransplantation. CONCLUSION: Microencapsulation protects NPI from the cytotoxic effects of human antibody and complement and allows for long-term reversal of diabetes in nude mice.
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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) | 0.001 | 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 | 0.001 |
| 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".