The involvement of CD62L in the effect of IVIg on the cytotoxic activity of CD8 T cells. (P5031)
Bibliographic record
Abstract
Abstract Intravenous immunoglobulin (IVIg) is used for the treatment of an increasing number of autoimmune disorders. In the past decades, its uses increased constantly, creating a potential risk of shortage. In order to further understand the mechanisms by which IVIg exerts immunomodulatory effects, our group previously demonstrated that IVIg inhibits the in vitro CD8 T cell activation. The CD8 T cell response is known to contribute to the progression of several autoimmune diseases. Our results showed that antigen-mediated CD8 T cells activation was reduced by more than 50% (proliferation, CD69 expression) in the presence of IVIg (Trépanier et al., Blood 2012). In addition, recent results showed a decreased lytic activity of CD8 T cells in the presence of IVIg. In this work, we used an in vitro cross-presentation assay with bone marrow-derived dendritic cells (DC) from C57BL/6 mice and ovalbumin-specific CD8 T cells (OT-I) to study the mechanism by which IVIg affects cytotoxicity. Preliminary results suggest that IVIg prevents the shedding of CD62L/L-selectin from the surface of T cells. Shedding of CD62-L from the surface of cytotoxic T cells was recently shown to be linked to the acquisition of lytic activity. Therefore, the effect of IVIg observed on the expression of CD62L on the CD8 T cell surface may contribute to the decreased cytotoxicity of these cells. The elucidation of the mechanisms of immunomodulatory effects of IVIg could help to design a potent substitute.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".