Inhibition of peptidyl-arginine deiminases reverses protein-hypercitrullination and disease in mouse models of multiple sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is the most common CNS-demyelinating disease of humans, showing clinical and pathological heterogeneity and a general resistance to therapy. We first discovered that abnormal myelin hypercitrullination, even in normal-appearing white matter, by peptidylarginine deiminases (PADs) correlates strongly with disease severity and might have an important role in MS progression. Hypercitrullination is known to promote focal demyelination through reduced myelin compaction. Here we report that 2-chloroacetamidine (2CA), a small-molecule, PAD active-site inhibitor, dramatically attenuates disease at any stage in independent neurodegenerative as well as autoimmune MS mouse models. 2CA reduced PAD activity and protein citrullination to pre-disease status. In the autoimmune models, disease induction uniformly induced spontaneous hypercitrullination with citrulline+ epitopes targeted frequently. 2CA rapidly suppressed T cell autoreactivity, clearing brain and spinal cord infiltrates, through selective removal of newly activated T cells. 2CA essentially prevented disease when administered before disease onset or before autoimmune induction, making hypercitrullination, and specifically PAD enzymes, a therapeutic target in MS models and thus possibly 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".