Autoantibodies purified from therapeutic preparations of intravenous immunoglobulins (IVIg) induce the formation of autoimmune complexes in normal human serum: a role in the in vivo mechanisms of action of IVIg?
Bibliographic record
Abstract
Although intravenous immunoglobulins (IVIg) are widely used in the treatment of many autoimmune and inflammatory diseases, the mechanisms of action are still unclear in most cases. We have recently reported the presence of soluble autoimmune complexes (auto-IC) in human serum after the addition of a dose of IVIg similar to the one used in therapy. Here, we report the isolation and characterization of the responsible auto-IgG present in IVIg. The auto-IgG were purified by affinity chromatography on serum proteins immobilized on Sepharose. The purified auto-IgG constituted approximately 3% of the IgG present in IVIg and recognized a wide variety of structures in ELISA as well as many serum proteins on western blots. Auto-IC were formed in human serum following the addition of an amount of purified auto-IgG sufficient to over-saturate the auto-IgG inhibitory mechanisms known to be present in normal serum. These results indicate that most of the IgG present in IVIg are not involved in the formation of the soluble auto-IC, raising the possibility of preparing from IVIg a novel product which could be used for the treatment of the autoimmune diseases in which IC are thought to play an important role.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".