Effects of fumarates on inflammatory human astrocyte responses and oligodendrocyte differentiation
Bibliographic record
Abstract
Abstract Objective Dimethyl fumarate ( DMF ) is a fumaric acid ester approved for the treatment of relapsing‐remitting multiple sclerosis ( RRMS ). In both the brain and periphery, DMF and its metabolite monomethyl fumarate ( MMF ) exert anti‐inflammatory and antioxidant effects. Our aim was to compare the effects of DMF and MMF on inflammatory and antioxidant pathways within astrocytes, a critical supporting glial cell in the central nervous system ( CNS ). Direct effects of fumarates on neural progenitor cell ( NPC ) differentiation toward the oligodendrocyte lineage were also assessed. Methods Primary astrocyte cultures were derived from both murine and human brains. Following pretreatment with MMF , DMF , or vehicle, astrocytes were stimulated with IL ‐1 β for 24 h; gene and micro RNA expression were measured by qPCR . Cytokine production and reactive oxygen species ( ROS ) generation were also measured. NPC s were differentiated into the oligodendrocyte lineage in the presence of fumarates and immunostained using early oligodendrocyte markers. Results In both murine and human astrocytes, DMF , but not MMF , significantly reduced secretion of IL ‐6, CXCL 10, and CCL 2; neither fumarate promoted a robust increase in antioxidant gene expression, although both MMF and DMF prevented intracellular ROS production. Pretreatment with fumarates reduced micro RNA s ‐146a and ‐155 upon stimulation. In NPC cultures, DMF increased the number of O4 + and NG 2 + cells. Interpretation These results suggest that DMF , and to a lesser extent MMF , mediates the anti‐inflammatory effects within astrocytes. This is supported by recent observations that in the inflamed CNS , DMF may be the active compound mediating the anti‐inflammatory effects independent from altered antioxidant gene expression.
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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 | 0.000 |
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".