Tumor necrosis factor receptor superfamily member 25 (TNFRSF25) agonists in islet transplantation: Endogenous in vivo regulatory T cell expansion promotes prolonged allograft survival
Bibliographic record
Abstract
Regulatory T cells (Tregs) modulate alloimmune responses and may facilitate minimization or withdrawal of immunosuppression posttransplant. Current approaches, however, rely on complex ex vivo Treg expansion protocols. Herein, we explore endogenous in vivo Treg expansion through antibody-mediated agonistic stimulation of the tumor necrosis factor receptor superfamily member 25 (TNFRSF25) pathway and its potential to prolong graft survival in a mouse model of islet allotransplantation. C57BL/6 male mice were treated with a single dose of TNFRSF25 agonistic antibodies (4C12 or mPTX-35) or IgG control. Diabetes was induced using streptozotocin. Four days later, flow cytometry was completed to corroborate Treg expansion, and 500 islets (CBA/J male mice) were transplanted. Glycemia was assessed thrice weekly until rejection/endpoint. Early intra-graft Treg infiltration was assessed 36 h posttransplant. TNFRSF25 antibodies enabled pronounced Treg expansion and treated mice had significantly prolonged graft survival compared with controls (p < .001). Additionally, the degree of Treg expansion significantly correlated with graft survival (p < .001). Immunohistochemistry demonstrated marked Treg infiltration in long-term surviving grafts; intra-graft Treg infiltration occurred early posttransplant. In conclusion, a single dose of TNFRSF25 antibodies enabled in vivo Treg expansion, which promotes prolonged graft survival. TNFRSF25-mediated in vivo Treg expansion could contribute to achieving lasting immunological tolerance in organ 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".