T cells interact with T cells via CD40‐CD154 to promote autoimmunity in type 1 diabetes
Bibliographic record
Abstract
We have investigated the role of CD40 signaling in islet-reactive, diabetogenic CD4(+) Th1 T-cell clones. Using multispectral flow cytometry, we showed that CD40 and CD154 are co-expressed and form complexes on the surface of activated T cells. We also demonstrate that activated Tcells can transactivate CD4(+) CD40(+) T cells through the CD40-CD154 pathway. To investigate the role of CD40 signaling on Th1 cells, we used the diabetogenic clone BDC-5.2.9 retrovirally transduced with a truncated form of the CD40 molecule to produce a CD40 dominant-negative T-cell clone. Upon challenge with antigen in vitro, the production of IFN-γ by BDC-5.2.9 CD40DN was greatly reduced and, in vivo, the dominant-negative variant was unable to induce diabetes. Transduction with the CD40DN vector was also effective in preventing transfer of disease by primary NOD CD4(+) T cells. Ex vivo analysis of pancreatic infiltrates after transfer of BDC-5.2.9 CD40DN cells revealed an overall reduction of cell numbers and cytokine production by both T cells and macrophages. These data indicate that CD40 is an important signaling molecule on autoreactive CD4(+) T cells and contributes to their pathogenic effector function.
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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) | 0.000 | 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) | 0.002 | 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".