DcR3 Protects Islet β Cells from Apoptosis through Modulating <i>Adcyap1</i> and <i>Bank1</i> Expression
Bibliographic record
Abstract
The islet primary nonfunction (PNF) is a serious problem in islet transplantation. In this study, we investigated whether DcR3-secreting transgenic (Tg) islets could reduce PNF. We generated Tg mice expressing human DcR3. The transgenically expressed DcR3 protected islets from IFN-gamma plus IL-1beta- or TNF-alpha plus IL-1beta-induced dysfunction and apoptosis in vitro. The Tg islets presented significantly reduced PNF after transplantation. Mechanistically, in addition to the known FasL apoptotic pathway, components of two other apoptosis pathways, that is, HVEM/LTbetaR for the LIGHT pathway and DR3 for the TL1A pathway, were found to be expressed in islets. Recombinant LIGHT- and TL1A-induced islet apoptosis in the absence of the FasL/Fas pathway, as well as DcR3, could block such induction. These results for the first time demonstrated that LIGHT and TL1A were capable of inducing islet apoptosis in addition to FasL, while DcR3 protected the islets by blocking all three apoptosis pathways. By DNA microarray analysis, we discovered that Adcyap was up-regulated >700-fold and Bank1 was down-regulated 50-fold in the cytokine-assaulted Tg islets, compared with WT islets. Forced overexpression of Adcyap1 by plasmid transfection or knockdown of Bank1 expression by small interfering RNA in insulinoma NIT-1 cells protected them from cytokine-triggered apoptosis, indicating that indeed DcR3 protects beta cells via the action of these two downstream molecules. This study has revealed novel mechanisms by which DcR3 protects islet survival, and it has identified new therapeutic targets of diabetes.
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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) | 0.000 | 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 | 0.001 |
| 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".