Intravenous Immunoglobulins Regulation of Human B Cells Is Mediated through Extracellular Signal-Regulated Kinase 1 and 2.
Bibliographic record
Abstract
Abstract Intravenous immunoglobulin (IVIg) has become increasingly important as therapy in autoimmune and inflammatory diseases, but its immunomodulatory action is still not fully understood. In the treatment of autoimmune diseases, the large repertoire of human immunoglobulin G (IgG), which constitutes IVIg, is assumed to modulate several immune cells including B cells. As a matter of fact, IVIg can act directly upon B cells in vitro by reducing their expansion and enhancing the differentiation of small populations of both naïve and memory B cells. In the present work, we used a panel of human cell lines representative of B cell major maturation stages and treated them with IVIg in order to identify model cell lines representative of normal B cells that could be used to further investigate IVIg effects on B cell physiology and identify the signal transduction pathways involved. Consistent with the observed effects on B cells, one of these cell lines, the DB cells, which express both FcγRIIB receptor (CD32) and surface IgG (B cell receptor [BCR]), showed reduced proliferation and upregulated secretion in presence of IVIg. As revealed by immunobloting and flow cytometry analysis, DB cells response to IVIg was paralleled by increased phosphorylation of ERK1/2, Gab1 as well as Akt, and addition of ERK1/2 activity inhibitors such as PD98059 to cultures of DB cells abolished the negative IVIg effect on proliferation of this cell line. Furthermore, in contrast to the above described IVIg consequence on ERK1/2 phosphorylation, incubation of DB cells in presence of various amounts of aggregated IgG within intramuscular immunoglobulin (IMIg) or IVIg all prevented ERK1/2 up-regulated phosphorylation. Comparable results were obtained using Pfeiffer cells, which are surface IgG+ as DB cells. Considering that CD32 can induce negative signaling when stimulated by aggregates of monomeric IgG present in IVIg, our results with the DB and Pfeiffer model cell lines thus suggest that the direct effect of IVIg on B cells could involve interaction with their BCR.
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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) | 0.002 | 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".