In Vitro Activation of CD8 Interphotoreceptor Retinoid-Binding Protein-Specific T Cells Requires not only Antigenic Stimulation but also Exogenous Growth Factors
Bibliographic record
Abstract
In a previous study, we demonstrated that immunization with the uveitogenic peptide interphotoreceptor retinoid-binding protein (IRBP) 1-20 induces both CD4 and CD8 uveitogenic T cells in the B6 mouse. In the current study, we determined the role of the CD8 IRBP-specific T cells in the pathogenesis of experimental autoimmune uveitis. We also determined the conditions that facilitated the activation of CD8 autoreactive T cells. Our results showed that the beta2-microglobulin(-/-) mouse had a greatly decreased susceptibility to induction of experimental autoimmune uveitis by adoptive transfer of IRBP-specific T cells from B6 mice. We also showed that unlike CD4 autoreactive T cells, activated CD8 autoreactive T cells produced only a limited number and amounts of growth factors. As a result, in the absence of exogenously supplied growth factor(s), CD8 T cell activation and expansion were aborted. However, the growth and expansion of triggered CD8 autoreactive T cells could be supported by various cytokines. In addition to factors produced by activated CD4 autoreactive T cells, factors produced by nonlymphoid cells, such as IL-7 and IL-15, and unidentified factors in the culture supernatants of astrocytes and retinal pigment epithelial cells support the CD8 autoreactive T cells as well. Finally, we showed that, although several cytokines augmented the CD8 T cell response in vitro, different cytokines appeared to act on different CD8 subsets or on different activation/differentiation phases of CD8 autoreactive T cells. As a result, cytokines, such as IL-7, supported the proliferation and survival of CD8 IRBP-specific T cells, while others had only a growth-promoting effect.
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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".