TLR9 Blockade Inhibits Activation of Diabetogenic CD8+ T Cells and Delays Autoimmune Diabetes
Bibliographic record
Abstract
Diabetogenic CD8(+) T cells are primed in the pancreatic lymph nodes (PLNs) by dendritic cells (DCs) carrying islet cell Ags. TLR signaling modifies DC function. The goal of this study was to determine the effect of TLR9 signaling on diabetogenic CD8(+) T cell activation and the course of type 1 diabetes. We explored the effects of CpG oligonucleotide, TLR9 antagonists, and genetic TLR9 deficiency on the activation of diabetogenic CD8(+) T cells. NOD bone marrow-derived DCs pulsed with freeze-thawed insulinoma cells in the presence of TLR9 agonist CpG and CD40 agonist induced diabetogenic CD8(+) T cell activation. The addition of TLR9 antagonist oligodeoxynucleotide or chloroquine inhibited bone marrow-derived DCs activation and CD8(+) T cell priming in response to CpG. CpG alone or with CD40 agonist induced CTL activity that triggered diabetes development in 8.3-TCR transgenic NOD mice. Oligodeoxynucleotide treatment of 8.3-TCR transgenic NOD mice delayed spontaneous diabetes development. Chloroquine treatment delayed the spontaneous onset of diabetes in NOD mice, coincident with the decreased activation of PLN DCs. TLR9(-/-) NOD mice had delayed onset of diabetes compared with TLR9(-/+) NOD littermates. TLR9(-/-) NOD mice had lower levels of IFN-alpha in PLNs and decreased frequencies of plasmacytoid DCs and diabetogenic CD8(+) T cells compared with NOD mice. We propose that TLR9 activation contributes to the spontaneous onset of diabetes in NOD mice by increasing IFN-alpha and promoting diabetogenic CD8 T cell activation.
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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".