EMMPRIN confers metabolic advantage for monocytes and macrophages to promote disease in a model of multiple sclerosis
Bibliographic record
Abstract
Abstract Monocytes and monocyte-derived macrophages have important roles in the initiation and progression of multiple sclerosis (MS). These cells undergo metabolic reprogramming to generate immunophenotypes that promote leukocyte infiltration, axonal degeneration and demyelination, worsening MS pathology. The mechanisms that dictate metabolic programs in monocytes and macrophages in MS remain unclear. We previously reported that extracellular matrix metalloproteinase inducer (EMMPRIN, CD147), a glycoprotein that acts as a chaperone of monocarboxylate transporter 4 (MCT4), assisted with glycolysis-driven pro-inflammatory phenotype in macrophages in experimental autoimmune encephalomyelitis (EAE), an animal model of MS. Using newly-generated CCR2Cre ERT2 :EMMPRIN fl/fl (CCR2:EMMP) mice, we report that presymptomatic deletion of EMMPRIN in CCR2+ monocytes prevented or reduced clinical disability of EAE. This was correspondent with decreased infiltration of leukocytes into the CNS. Single cell RNA-seq of blood monocytes from EAE and proteomics analysis of macrophages from CCR2:EMMP −/− mice revealed significant alterations in metabolic programs, particularly reduced glycolysis and elevated mitochondrial electron transport and fatty acid oxidation, which were linked to their reduced pro-inflammatory traits. Our findings implicate EMMPRIN as a key regulator of metabolic pathways that exacerbate pro-inflammatory functions of monocytes in MS.
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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) | 0.002 | 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".