Immunoprotection and Functional Improvement of Allogeneic Islets in Diabetic Mice, Using a Stable Indoleamine 2,3-Dioxygenase Producing Scaffold
Bibliographic record
Abstract
BACKGROUND: We have previously shown that an immunomodulatory enzyme, indoleamine 2,3-dioxygenase (IDO) in dermal fibroblasts generates a tryptophan-deficient environment that selectively inhibits proliferation and induces apoptosis of bystander CD4+ and CD8+ T cells, but not pancreatic islets. Because these immune cells are involved in islet allograft rejection, we hypothesized that transplantation of islets embedded in a novel 3-dimensional composite scaffold within which stable IDO-expressing fibroblasts serve as source of local immunosuppression would lead to normoglycemia in a streptozotocin-induced diabetic mouse model. METHODS: Islet grafts were prepared by embedding stable IDO-expressing fibroblasts and allogeneic islets into a protease-resistant composite scaffold. Islets function and survival were evaluated in vitro using immunohistochemistry. Allografts were transplanted under the kidney capsule of streptozotocin-induced diabetic mice; viability, function, and criteria for graft take were evaluated. Flow cytometry was performed to determine specific intragraft, draining lymph nodes and spleen T-cell population, and splenocytes alloantigen responsiveness of graft recipients. RESULTS: The results of a series of in vitro experiments revealed that IDO-expressing fibroblasts do not compromise islet function or survival. The expression of IDO suppressed the proliferation of alloantigen-stimulated splenocytes. The in vivo experiments revealed that local IDO expression delivered by lentiviral vector prolonged islet allograft survival (51.0 ± 2.9 days) by increasing the population of FOXP3+ regulatory T cells at the graft site and graft-draining lymph nodes and preventing T-cell infiltration. CONCLUSIONS: This study shows that incorporation of islets within our novel matrix that is equipped with stable IDO-expressing fibroblasts prolongs allograft survival.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".