Blockade of Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand Exacerbates Type 1 Diabetes in NOD Mice
Bibliographic record
Abstract
Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is expressed in different tissues and cells, including pancreas and lymphocytes, and can induce apoptosis in various tumor cells but not in most normal cells. The specific roles of TRAIL in health and disease remain unclear. Here we show by cDNA array analyses that TRAIL gene expression is upregulated in pancreatic islets during the development of autoimmune type 1 diabetes in nonobese diabetic (NOD) mice and in Min6 islet beta-cells activated by TNF-alpha + interferon-gamma. However, stimulation of freshly isolated pancreatic islets or Min6 cells with TRAIL did not induce their apoptosis. TRAIL blockade exacerbates the onset of type 1 diabetes in NOD.Scid recipients of transferred diabetogenic T-cells and in cyclophosphamide-treated NOD mice. TRAIL inhibits the proliferation of NOD diabetogenic T-cells by suppressing interleukin (IL)-2 production and cell cycle progression, and this inhibition can be rescued in the presence of exogenous IL-2. cDNA array and Western blot analyses indicate that TRAIL upregulates the expression of the cdk inhibitor p27(kip1). Our data suggest that TRAIL is an important immune regulator of the development of type 1 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".