Indirect inhibition of in vivo and in vitro T-cell responses by intravenous immunoglobulins due to impaired antigen presentation
Bibliographic record
Abstract
Several clinical studies done with intravenous immunoglobulin (IVIg)-treated autoimmune patients as well as several in vitro studies have revealed that IVIg can reduce polyclonal T-cell activation and modify their cytokine secretion pattern. However, their effect on (auto)antigen-specific T-cell responses has never been addressed directly. In the present work, we used an in vivo model of induction of antigen-specific T-cell responses and an in vitro antigen presentation system to study the effects of IVIg on T-cell responses. The results obtained showed that IVIg inhibited both the in vivo and in vitro antigen-specific T-cell responses but that this effect was the indirect consequence of a reduction in the antigen presentation ability of antigen-presenting cells. The inhibitory effect of IVIg was FcgammaRIIb-independent, suggesting that IVIg must interfere with activating FcgammaRs expressed on antigen-presenting cells to reduce their ability to present antigens. Such inhibition of T-cell responses by reducing antigen presentation may therefore contribute to the well-known anti-inflammatory effects of IVIg in autoimmune diseases.
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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) | 0.001 | 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) | 0.002 | 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".