Characterization of the Role of Major Histocompatibility Complex in Type 1 Diabetes Recurrence after Islet Transplantation
Bibliographic record
Abstract
BACKGROUND: Major histocompatibility complex (MHC) molecules are essential determinants of beta-cell destruction in type 1 diabetes (T1D). MHC class I- or class II-null nonobese diabetic (NOD) mice do not spontaneously develop autoimmune diabetes and are resistant to adoptive transfer of disease. Both CD4+ and CD8+ T cells are associated with graft destruction after syngeneic islet transplantation. MHC molecules within the graft (i.e., on beta-cells or donor lymphocytes) may influence the interactions between antigen presenting cells and effector T cells and, therefore, the survival outcome of the graft. METHODS: Donor islets from NOD mice deficient in one or both of beta2-microglobulin and class II transactivator genes were transplanted into diabetic NOD mice. Immunohistochemistry was performed to identify the phenotype of infiltrating cells and to assess graft insulin production. The presence of cytokines in the grafts was assayed by reverse transcription polymerase chain reaction. RESULTS: MHC class II-null islets demonstrated rates of rejection comparable with control wild-type (wt) islets. In contrast, MHC class I- and II-null islets demonstrated indefinite survival (over 100 days). Infiltrates of both failed and surviving grafts were comprised of cytotoxic lymphocytes (CTL), helper T cells, and macrophages. Grafts also showed the presence of both Th1- and Th2-type cytokines (interleukin [IL]-2, IL-4, IL-10, and interferon-gamma), independent of graft status. CONCLUSIONS: These results demonstrate the primary importance of MHC class I molecules in the pathogenesis of diabetes recurrence postislet transplantation. Conversely, MHC class II expression is not a necessary mechanistic component of transplant destruction. In addition, these results implicate MHC class I-restricted CTLs but not MHC class II-restricted T cells in disease recurrence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".