Encapsulation of Human Islets Using a Biomimetic Self-Assembled Nanomatrix Gel for Protection against Cellular Inflammatory Responses
Bibliographic record
Abstract
The major concern of pancreatic islet transplantation is that the implanted islets are exposed to the immune system of the recipient. To overcome this challenge, the peptide amphiphile (PA) nanomatrix gel was used for immunoisolation of islets through microencapsulation. The PA can self-assemble to form a nanomatrix gel with an extracellular matrix-mimicking, islet nurturing microenvironment and a semipermeable immune barrier. In this study, the islet protective effect of the PA nanomatrix gel was evaluated by coculture of PA-encapsulated human islets with differentiated U937 cells (human monocyte cell-line) for 3 and 7 days. The coculture of the bare islets with the differentiated U937 cells stimulated proinflammatory cytokine (IL-1β and TNF-α) secretion and caused islet death after 7 days, which simulated an early inflammatory response environment after islet transplantation. The PA-encapsulated islets, however, did not stimulate proinflammatory cytokine secretion and maintained islet viability up to 7 days. More insulin-producing β cells were observed in PA-encapsulated islets compared to bare islet controls after exposure to differentiated U937 cells for 7 days compared to the bare islets. This result was confirmed by dithizone staining analysis. Further evaluation of islet functionality was assessed by a glucose-stimulated insulin secretion test. The PA-encapsulated islets showed greater insulin secretion response to glucose stimulation than the bare islets with the differentiated U937 cells after 3 and 7 days. These results demonstrated that islet encapsulation with the PA nanomatrix gel was able to improve islet survival and function in the presence of inflammatory responses, which will increase the success rate of islet engraftment and the efficacy of islet transplantation.
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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) | 0.000 | 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".