Combined Coinhibitory and Costimulatory Modulation with Anti-BTLA and CTLA4Ig Facilitates Tolerance in Murine Islet Allografts
Bibliographic record
Abstract
Complex interactions between positive and negative cosignaling receptors ultimately determine the fate of the immune response. The recently identified coinhibitory receptor, B and T lymphocyte attenuator (BTLA), contributes to regulation of autoimmune and potentially alloimmune responses. We investigated the role of BTLA in a fully major histocompatibility complex-mismatched mouse islet transplant model. We report that anti-BTLA mAb (6F7) alone does not accelerate graft rejection. Rather, while CTLA4Ig alone improved allograft survival, the addition of anti-BTLA mAb to CTLA4Ig led to indefinite (>100 days) allograft survival. Immediately after treatment with anti-BTLA mAb and CTLA4Ig, islet allografts showed intact islets and insulin production despite a host cellular response, with local accumulation of Foxp3+ cells. We clearly demonstrate that combined therapy with anti-BTLA mAb and CTLA4Ig mice induced donor-specific tolerance, since mice accepted a second donor-specific islet graft without further treatment and rejected third party grafts. CTLA4Ig and anti-BTLA mAb limited the initial in vivo proliferation of CFSE-labeled allogeneic lymphocytes, and anti-BTLA mAb enhanced the proportion of PD-1 expressing T cells while depleting pathogenic BTLA+ lymphocytes. We conclude that targeting the BTLA pathway in conjunction with CTLA4Ig costimulatory blockade may be a useful strategy for promoting immunological tolerance in murine islet allografts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".