Melanocortin Receptor-Mediated Anti-Inflammatory Effect of Acthar® Gel in Human Myeloid Cells
Bibliographic record
Abstract
Introduction Acthar® Gel, a complex mixture of porcine adrenocorticotropic hormone analogs that activates all 5 melanocortin receptor (MCR) subtypes, is an approved noncorticosteroid treatment for multiple sclerosis (MS) exacerbations. Methods MCR expression and anti-inflammatory effects of Acthar Gel in human monocyte-derived macrophages and human brain-derived microglia were investigated following lipopolysaccharide stimulation in vitro. Results Melanocortin receptor 1 was expressed at substantially higher levels than the other MCR subtypes in human monocyte-derived macrophages (MDMs) and was the only MCR gene detected in human adult microglia. As shown by microarray gene expression analysis, polarization of MDMs to a proinflammatory phenotype increased the expression and secretion of interleukin-6, tumor necrosis factor α, and CXC motif chemokine ligand 10, which were inhibited in a dose-dependent manner with Acthar Gel treatment. Conclusions These results are consistent with previous insights that Acthar Gel has an immunomodulatory mechanism distinct from glucocorticoids alone and suggest that Acthar Gel can improve clinical outcomes in MS and other inflammation-mediated central nervous system disorders by inhibiting multiple proinflammatory cytokine signaling pathways.
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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".