IVIg therapy in brain inflammation: etiology-dependent differential effects on leucocyte recruitment
Bibliographic record
Abstract
Several studies have reported beneficial effects of intravenous immunoglobulin (IVIg) in diseases of the neuroaxis. However, IVIg effects on leucocyte recruitment, a hallmark feature of autoimmunity and acute inflammation, remain largely unexplored. Using intravital microscopy, we studied the effects of IVIg on leucocyte recruitment in experimental autoimmune encephalomyelitis, a model of multiple sclerosis. In IVIg-treated mice, a significant decrease in recruitment (rolling and adhesion) was observed prior to and following disease onset, and this was concomitant with improved clinical score. Since much of the recruitment is dependent upon alpha4-integrin (ligand for VCAM-1) we used an in vitro flow chamber system and demonstrated a 60% decrease in alpha4-integrin-dependent leucocyte adhesion to immobilized VCAM-1. Finally, we used leucocytes from multiple sclerosis patients and demonstrated that IVIg treatment decreased recruitment by 60% on human endothelium. However, when we visualized the role of IVIg in a second model of brain inflammation, cerebral ischaemia-reperfusion, IVIg actually promoted the formation of platelet-leucocyte aggregates in post-ischaemic cerebral vessels. In conclusion, we report a new mechanism of action of IVIg through interference of alpha4-integrin-dependent leucocyte recruitment in both an animal model and human multiple sclerosis. We also report that IVIg will not be beneficial in all types of pro-adhesive states and may in fact be detrimental in a situation such as stroke.
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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 | 0.000 | 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) | 0.000 | 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".