An Engineered GM-CSF-CCL2 Fusokine Is a Potent Inhibitor of CCR2-Driven Inflammation As Demonstrated in a Murine Model of Inflammatory Arthritis
Bibliographic record
Abstract
CCR2 is a chemokine receptor widely expressed by lymphomyeloid cells involved in maladaptive autoimmune ailments. Therefore CCR2 is of great interest as a biological target for immune suppression due to its direct implication in autoimmune diseases such as rheumatoid arthritis. We have generated a novel fusion protein using GM-CSF and an N-terminal truncated version of MCP-1/CCL2 (6-76, GMME1) and investigated its utility as a CCR2-specific immune suppressor. Using BRET studies, we found that distinct to CCL2, GMME1 binding to CCR2 led to altered conformational changes in the CCR2 homodimer and did not induce the recruitment of beta-arrestin 2 to the receptor. However, CCR2-dependent calcium mobilization, BAX induction and caspase-3 activation followed by cell death was observed. Using Th17 cells harvested from DBA/1 mice ill with bovine collagen-induced arthritis, we demonstrate that GMME1 is capable of blocking their production of IL-17 in vitro. Upon its delivery to mice symptomatic with inflammatory arthritis, a robust clinical recovery occurred with decreased paw thickness to normal levels and a significant reduction in anti-collagen Ab titer and rheumatoid factor titer, as well as reduction of proinflammatory cytokines levels both intraarticular and systemic. Our data demonstrate that GMME1 is a powerful synthetic suppressor cytokine that coopts CCR2-dependent cellular signaling and blunts the effects of CCR2-expressing lymphomyeloid cells causative of autoimmune arthritis.
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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 | 0.001 |
| 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".