Can antibodies with specificity for soluble antigens mimic the therapeutic effects of intravenous IgG in the treatment of autoimmune disease?
Bibliographic record
Abstract
Intravenous Ig (IVIg) mediates protection from the effects of immune thrombocytopenic purpura (ITP) as well as numerous other autoimmune states; however, the active antibodies within IVIg are unknown. There is some evidence that antibodies specific for a cell-associated antigen on erythrocytes are responsible, at least in part, for the therapeutic effect of IVIg in ITP. Yet whether an IVIg directed to a soluble antigen can likewise be beneficial in ITP or other autoimmune diseases is also unknown. A murine model of ITP was used to determine the effectiveness of IgG specific to soluble antigens in treating immune thrombocytopenic purpura. Mice experimentally treated with soluble OVA + anti-OVA versus mice treated with OVA conjugated to rbcs (OVA-rbcs) + anti-OVA were compared. In both situations, mice were protected from ITP. Both these experimental therapeutic regimes acted in a complement-independent fashion and both also blocked reticuloendothelial function. In contrast to OVA-rbcs + anti-OVA, soluble OVA + anti-OVA (as well as IVIg) did not have any effect on thrombocytopenia in mice lacking the inhibitory receptor FcgammaRIIB (FcgammaRIIB(-/-) mice). Similarly, antibodies reactive with the endogenous soluble antigens albumin and transferrin also ameliorated ITP in an FcgammaRIIB-dependent manner. Finally, broadening the significance of these experiments was the finding that anti-albumin was protective in a K/BxN serum-induced arthritis model. We conclude that IgG antibodies directed to soluble antigens ameliorated 2 disparate IVIg-treatable autoimmune diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".