Dipeptide Boronic Acid, a Novel Proteasome Inhibitor, Prevents Islet-Allograft Rejection
Bibliographic record
Abstract
BACKGROUND: We have demonstrated previously in vitro that proteasome inhibitors suppress the proliferation, and induce the apoptosis, of activated T cells. This implies that they could be used as a novel category of immunosuppressants to block allograft rejection. Therefore, in this study, dipeptide boronic acid (DPBA) was tested for its effect on mouse islet transplantation. METHODS: First, DPBA was investigated in vitro for its effect on mouse mixed lymphocyte reaction (MLR) and cytotoxic T-lymphocyte (CTL) activity. DPBA was then used in vivo to treat mouse islet-allograft rejection. RESULTS: Both MLR and CTL were dose dependently suppressed by the proteasome inhibitor. A 17-day DPBA regimen resulted in islet-allograft survival in 50% of the recipients for a duration of up to 60 days, whereas the control group without immunosuppressants rejected the islet graft in 7 days. DPBA showed moderate side effects according to blood biochemistry; the function of endogenous islets after treatment appeared normal on glucose challenge. CONCLUSIONS: The proteasome inhibitor could inhibit islet-allograft rejection in mice without serious side effects at therapeutic dose levels. This has opened a new dimension in the development of better immunosuppression regimens for islet transplantation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".