Epstein-Barr virus-induced gene 3 (EBI3) can mediate IL-6 trans-signaling
Bibliographic record
Abstract
Epstein-Barr virus-induced gene 3 (EBI3) is a subunit of the composite cytokines IL-27 and IL-35. Both have beneficial functions or effects in models of infectious and autoimmune diseases. This suggests that administration of EBI3 could be therapeutically useful by binding free p28 and p35 to generate IL-27 and IL-35. IL-27- and IL-35-independent functions of EBI3 could compromise its therapeutic uses. We therefore assessed the effects of EBI3 on cytokine receptor-expressing cells. We observed that EBI3 activates STAT3 and induces the proliferation of the IL-6-dependent B9 mouse plasmacytoma cell line. Analyses using blocking mAbs and Ba/F3 transfectants expressing gp130 indicate that EBI3 activity was linked to its capacity to mediate IL-6 trans -signaling, albeit less efficiently than soluble IL-6Rα. In line with this interpretation, co-immunoprecipitation and SPR experiments indicated that EBI3 binds IL-6. An important pro-inflammatory function of IL-6 trans -signaling is to activate blood vessel endothelial cells. We observed that EBI3 in combination with IL-6 could induce the expression of chemokines by human venal endothelial cells. Our results indicate that EBI3 can promote pro-inflammatory IL-6 functions by mediating trans -signaling. These unexpected observations suggest that use of EBI3 as a therapeutic biologic for autoimmune diseases will likely require co-administration of soluble gp130 to prevent the side effects associated with IL-6 trans -signaling. Together with previous studies that demonstrated activation of IL-6R by p28 (IL-30), new findings further suggest a complex interrelation between IL-27 and IL-6.
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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".