Dual T cell receptor-expressing CD8 T cells potentiate autoreactivity
Bibliographic record
Abstract
Abstract Central tolerance serves to eliminate newly developing T cells that express strongly autoreactive T cell receptors. Although central tolerance is efficient in deleting high avidity autoreactive T cells, some lower avidity autoreactive T cells escape negative selection to cause autoimmune diseases. Although tight allelic exclusion limits thymocytes to expressing a single TCRbeta chain, rearrangement of the TCRalpha chain continues unabated until halted by positive selection, enabling thymocytes to express up to two TCRalpha chains and thus two TCRs. Moreover, it has been postulated that pathogenic low avidity autoreactive CD8 T cells may escape central tolerance through expression of a secondary benign TCR that mediates positive selection. To determine the role of dual TCR expressing CD8 T cells in autoreactivity and autoimmunity, we have compared CD8 T cell autoreactivity against the model autoantigen ovalbumin between T cells capable of expressing two TCRs (TCRalpha+/+) versus T cells capable of expressing a single TCR (TCRalpha+/−). TCRalpha+/− CD8 T cells exhibited reduced proliferative capacity upon OVA stimulation relative to TCRalpha+/+ CD8 T cells. In addition, a lower frequency of TCRalpha+/− CD8 T cell effectors produced IFN-gamma upon activation with OVA compared to TCRalpha+/+ CD8 T cell effectors. Taken together, we shown that dual TCR expression by CD8 T cells reduces the efficiency of T cell tolerance and may potentiate T cell autoreactivity. We are investigating whether dual TCR-expressing T cells are key to the pathogenesis of autoimmune diabetes in our mouse model system. Our results will provide valuable insight into the escape mechanisms exploited by pathogenic autoreactive CD8 T cells.
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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) | 0.002 | 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".