Blockade of both B7-H4 and CTLA-4 co-signaling pathways enhances mouse islet allograft survival
Bibliographic record
Abstract
Costimulation blockade is an effective way to prevent allograft rejection. In this study, we tested the efficacy of two negative co-signaling molecules in protecting islet allograft function. We used local expression of B7-H4 by adenoviral transduction of islets (Ad-B7-H4) and systemic administration of CTLA-4.Ig to investigate the outcomes of allograft survival. Five groups of streptozotocin-induced diabetic C57BL/6 mice received 400 islets each from BALB/c donors. The groups consisted of control (G1); CTLA-4.Ig (G2); Ad-LacZ (G3); Ad-B7-H4 (G4); and Ad-B7-H4 and CTLA-4.Ig combined (G5). G1 and G3 developed graft failure on average of two weeks. G2, G4 and G5 survived for 43.8 ± 34.8, 54.7 ± 31.2 and 77.8 ± 21.5 d, respectively. Activated T and B cells in the lymph nodes were significantly controlled by CTLA-4.Ig treatment. Significantly reduced infiltrates were also detected in the allografts of G2 compared with G1. By contrast, B7-H4 significantly inhibited Th1-associated IFN-gamma secretion in the early stage and increased Foxp3 (+) T cells in the long-term surviving allografts. Our study suggests that CTLA-4 and B7-H4 inhibit alloimmune responses through distinct mechanisms, and that combination therapy which activates two negative co-signaling pathways can further enhance islet allograft survival.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".