Modulation of MHC II and costimulatory molecules expression on monocytes by intravenous immunoglobulins (147.17)
Bibliographic record
Abstract
Abstract Intravenous immunoglobulins (IVIg) are therapeutic preparations of human IgG isolated from thousands of plasma donations and are known to have anti-inflammatory effects in many autoimmune diseases. IVIg are also used as prophylactic agent to reduce episodes of allograft rejection but the mechanisms responsible for this effect remain to be determined. In the present work, we showed by using a mixed lymphocyte reaction as an in vitro model of allograft rejection and GvHD, that IVIg strongly inhibited T cell activation. To explain this inhibition, we postulated that IVIg modulated the expression of MHC II and costimulatory molecules expressed on APC and involved in antigen presentation and regulation of T cell activation. To study this hypothesis, PBMC were cultured with or without 10 mg/ml IVIg for 24 hours, followed by flow cytometry analysis of cell surface expression of 8 different molecules. Among these, the expression of 5 was significantly modulated on monocytes. IVIg decreased the expression of MHC II (50%), CD80 (80%), CD86 (52%) and L-ICOS (50%). Interestingly, preliminary results showed a 5-fold increase in the expression of PD-L1, a negative regulator of T cell activation. These results suggest that IVIg impair the presentation of allopeptides to T cells as well as induce negative signalling in these cells, leading to their reduced activation. Altogether these findings could help explain the induction of peripheral tolerance and improvement of graft survival by IVIg.
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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 | 0.000 |
| 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".