Tumor Necrosis Factor-Related Apoptosis-Inducing Ligand and CD56 Expression in Patients With Type 1 Diabetes Mellitus
Bibliographic record
Abstract
OBJECTIVES: Our previous report showed that beta-cell antigen-specific CD56+ T-cells and cytokine TRAIL mediate destruction of human pancreatic [beta] cells in vitro. To determine whether CD56 and TRAIL are present during islet cell destruction at the onset of clinical symptoms of type 1 diabetes mellitus (T1D), we studied cell marker and cytokine expression in the pancreatic islets of 2 children who died at presentation of acute-onset T1D and in T-cell lines derived from a group of children with new-onset T1D. METHODS: TRAIL, CD56, and other T-cell markers and cytokine expression were studied using immunohistochemistry on pancreatic sections from 2 children with acute-onset T1D. TRAIL and CD56 expression was analyzed by flow cytometry in the antigen-activated T-cell lines derived from 29 children with new-onset T1D. RESULTS: TRAIL+, CD56+, CD45RO+, and CD3+ cells were present in the islets of acute-onset T1D patients, while none were present in the normal islets. T-cell lines from new-onset T1D expressed TRAIL and CD56 in response to stimulation with beta-cell antigens GAD, IA-2 and insulin beta chain. CONCLUSION: The presence of TRAIL and CD56 markers is part of the T-cell response repertoire in beta-cell destruction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".