Neutralization of mitogenic lectins by intravenous immunoglobulin (IVIg) prevents T cell activation: does IVIg really have a direct effect on T cells?
Bibliographic record
Abstract
Intravenous immunoglobulin (IVIg) is used for the treatment of an increasing number of autoimmune diseases. Clinical observations on IVIg-treated patients have revealed a modulation of T cell populations and functions in these patients. In vitro studies aimed at understanding the mechanisms underlying the effects of IVIg on T cells led to the conclusion that IVIg directly affected lectin-activated T cell functions. However, more recent studies have suggested the absence of a direct effect of IVIg on T cells. In the present work, we revisited the effect of IVIg on T cells using lectin-stimulated human T cells and showed that IVIg inhibited T cell functions only when added simultaneously with the activating lectin. Further, we showed that IVIg depleted from lectin-reactive IgG was no longer inhibitory, suggesting that the effect of IVIg on T cells was the consequence of lectin neutralization, possibly by interaction with glycans present in F(ab')(2) portion of IgG molecules. Our results challenge the previously widely accepted notion that IVIg exerts its anti-inflammatory effects by acting directly on T cells and suggest that effects of IVIg observed in treated patients are rather a consequence of the recently reported inhibitory effect of IVIg on antigen presentation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 teacher head, 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".