Combination of Anti-CD4 with Anti-LFA-1 and Anti-CD154 Monoclonal Antibodies Promotes Long-Term Survival and Function of Neonatal Porcine Islet Xenografts in Spontaneously Diabetic NOD Mice
Bibliographic record
Abstract
Type 1 diabetes mellitus (T1DM) is caused by the autoimmune destruction of pancreatic islet beta-cells, which are required for the production of insulin. Islet transplantation has been shown to be an effective treatment option for TIDM; however, the current shortage of human islet donors limits the application of this treatment to patients with brittle T1DM. Xenotransplantation of pig islets is a potential solution to the shortage of human donor islets provided xenograft rejection is prevented. We demonstrated that a short-term administration of a combination of anti-LFA-1 and anti-CD154 monoclonal antibodies (mAbs) was highly effective in preventing rejection of neonatal porcine islet (NPI) xenografts in non-autoimmune-prone B6 mice. However, the efficacy of this therapy in preventing rejection of NPI xenografts in autoimmune-prone nonobese diabetic (NOD) mice is not known. Given that the current application of islet transplantation is for the treatment of T1DM, we set out to determine whether a combination of anti-LFA-1 and anti-CD154 mAbs could promote long-term survival of NPI xenografts in NOD mice. Short-term administration of a combination of anti-LFA-1 and anti-CD154 mAbs, which we found highly effective in preventing rejection of NPI xenografts in B6 mice, failed to promote long-term survival of NPI xenografts in NOD mice. However, addition of anti-CD4 mAb to short-term treatment of a combination of anti-LFA-1 and anti-CD154 mAbs resulted in xenograft function in 9/12 animals and long-term graft (>100 days) survival in 2/12 mice. Immunohistochemical analysis of islet grafts from these mice identified numerous insulin-producing beta-cells. Moreover, the anti-porcine antibody as well as autoreactive antibody responses in these mice was reduced similar to those observed in naive nontransplanted mice. These data demonstrate that simultaneous targeting of LFA-1, CD154, and CD4 molecules can be effective in inducing long-term islet xenograft survival and function in autoimmune-prone NOD mice.
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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) | 0.001 | 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".