IVIG Down-Regulates LPS-Induced TNFα Production Via Inhibition of IκBα Activation: A Possible Mechanism of Action in the Treatment of Bacterial Infections.
Bibliographic record
Abstract
Abstract Intravenous IgG (IVIG) preparations, originally developed as a substitution therapy for patients with low plasma IgG, are used in the treatment of various immune and nonimmune disorders including hemolytic uremic syndrome, necrotizing fasciitis, and idiopathic thrombocytopenic purpura (ITP); an autoimmune pro-inflammatory condition. However, the pleotropic effects of IVIG on Fcγ receptor-bearing immune cells are not fully understood. Bacterial lipopolyssacharide (LPS) is a principal pro-inflammatory signaling molecule recognized by the innate immune system. LPS binds to monocyte/macrophage Toll-like receptor 4 (TLR4) to activate transcription factors such as NF-κB/IκBα. In turn, NF-κB activation results in cytokine secretion such as tumor necrosis factor alpha (TNFα); a key pro-inflammatory cytokine that leads to monocyte apoptosis. Since IVIG reduces pro-inflammatory responses, we hypothesized that IVIG may down-regulate the LPS-induced pro-inflammatory response in monocytes. Using the human monocyte-like cell line THP-1 that expresses FcγRs and TLR4, we examined LPS-induced intracellular signaling after in vitro treatment with IVIG. Enzyme-linked immunosorbent assay (ELISA) on culture supernatants showed that 30 minute pre-treatment of THP-1 cells with IVIG (5 mg/mL final) downregulated subsequent LPS (200 ng/mL)-induced secretion of TNFα. Western blotting showed that IVIG increased Akt phosphorylation and resulted in phosphorylation of S6 ribosomal protein and Erk1/2 signaling molecules. The activation of S6 ribosomal protein was blocked by the PI3K inhibitor LY294002. More importantly, IVIG treatment inhibited LPS-induced IκBα activation; the likely reason for the decrease in LPS-induced TNFα secretion. In conclusion, IVIG down-regulates LPS-induced signal transduction and proinflammatory cytokine secretion, an action that is likely responsible for its usefulness in the treatment of bacterial infections and in other diseases where down-regulation of NF-κB is desirable.
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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".