Inhibition of antigen cross-presentation by intravenous immunoglobulins (100.41)
Bibliographic record
Abstract
Abstract Intravenous immunoglobulins (IVIg) are therapeutic preparations of human IgG used to treat primary and secondary immunodeficiencies. In addition, IVIg exert anti-inflammatory effects in several autoimmune disorders, and the constant increase in their use exposes providers and patients to considerable risks of shortage. Understanding their numerous and complex mechanisms of action is required to develop appropriate substitutes. Our research group recently demonstrated that IVIg inhibited the in vitro and in vivo activation of CD4 T cells following interaction with dendritic cells (DC) (Aubin et al, Blood 2010). In the present work, we investigated whether IVIg could also interfere with the activation of CD8 T cells, which contribute to the persistence and severity of certain autoimmune conditions. C57BL/6 bone marrow-derived DC were treated with IVIg and used to cross-present ovalbumin to fluorescently labelled ova-specific OT-I CD8 T cells. Cell activation was assessed by measuring T cell fluorescence distribution by flow cytometry. Results showed that IVIg-treated DC were significantly less efficient in activating CD8 T cells. The inhibition correlated with a decrease in IL-2 and IFN-y pro-inflammatory cytokine secretion. These results support a novel immunomodulatory mechanism by which IVIg decrease DC capacity to cross-present antigens to CD8 T cells. The molecular mechanisms of this inhibition and its importance in vivo are currently being investigated.
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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) | 0.001 | 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".