P-11: TARGETING ISLET GRAFT-REGULATED NECROSIS USING NECROSTATIN-1-ELUTING MICROPARTICLES
Bibliographic record
Abstract
Introduction: Islet transplantation (ITx) is a promising treatment for type 1 diabetes, offering the potential to restore insulin independence and hypoglycemia awareness. Barriers to the longevity and function of transplanted islets include acute cell death, multiple islet donors, and immune rejection. Herein, we examined the use of localized Necrostatin-1 (Nec-1) eluting poly(lactic-co-glycolic acid) (PLGA) microparticles (MPs) to enhance islet graft function by targeting regulated necrosis pathways. Methods: Nec-1 encapsulated PLGA microspheres were characterized in vitro using HPLC. For in vivo release kinetics, Nec-1 MPs were implanted under the kidney capsule of non-diabetic Rag mice and collected at days 1, 3, 7, 14, and 21 post-transplant (n=3-6). The protective effect of Nec-1 MPs was evaluated by co-culturing 4 mg of Nec-1 MPs with BALB/c islets for 24 hours,±Thapsigargin (Thp, 5 µM). Islet viability and function were assessed through static glucose-stimulated insulin secretion (GSIS), immunohistochemistry and pro-inflammatory cytokine release. In vivo function was evaluated using syngeneic BALB/c marginal islet mass transplants, co-transplanted with Nec-1 MP. Results: Nec-1 MP had an average diameter of 13.7±2.5 µm with an encapsulation efficiency of 35.3±2.5 %, while maintaining a constant pH of 7.45±0.03 throughout the culture. In vivo release kinetics demonstrated a rapid release of Nec-1 on day 1, followed by sustained release over 21 days. Nec-1 MP islets significantly increased GSIS compared to controls (p<0.01). Thp+islets had significantly reduced GSIS while increasing pro-inflammatory cytokine secretion compared to controls (p<0.05). However, Nec-1 MPs+Thp cultured islets exhibited superior GSIS and reduced pro-inflammatory cytokine release compared to Thp+islets (p<0.01); providing protection against induced ER stress. Interim transplant data suggests improved diabetes reversal rates in the Nec-1 treated group compared to untreated controls. Conclusions: Interim findings highlight the potential of PLGA Nec-1 MPs to enhance glucose-stimulated insulin secretion, maintain functionality under ER stress and improve islet engraftment.
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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".