Diabetes Induces Rapid Suppression of Adaptive Immunity Followed by Homeostatic T‐cell Proliferation
Bibliographic record
Abstract
Surprisingly, the effect of acute diabetes on immunity has not been examined in detail. We, herein, show for the first time that untreated acute diabetes causes rapid lymphopenia followed by homeostatic T-cell proliferation. The diabetes-induced lymphopenia was associated with an immunosuppressed state that could be sufficiently strong to allow engraftment of fully allogeneic beta-cells or block rejection of islet transplants. In contrast, homeostatic proliferation and recovery of T-cell numbers were associated with islet rejection. Thus, the timing of islet transplant challenge in relation to diabetes induction was critical in determining whether islets were accepted or rejected. In addition, we tested whether diabetes-related immunosuppression could result in an overestimation of the efficacy of a tolerance-inducing protocol. Consistent with this possibility, a protocol targeting CD40L and ICOS that we have shown induces tolerance in diabetic recipients was unable to induce tolerance in non-diabetic recipients. The data uncover a previously unrecognized suppressive effect of diabetes on adaptive immunity. Furthermore, they suggest that the standard methods of testing new tolerance-inducing protocols in islet transplantation require modification and that diabetes itself can contribute to homeostatic proliferation, a process associated with autoimmunity and a resistance to tolerance induction.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".