The Influence of Arginine Methylation in Immunity and Inflammation
Bibliographic record
Abstract
Exploration in the field of epigenetics has revealed that protein arginine methyltransferases (PRMTs) contribute to disease, and this has given way to the development of specific small molecule compounds that inhibit arginine methylation. Protein arginine methylation is known to regulate fundamental cellular processes, such as transcription; pre-mRNA splicing and other RNA processing mechanisms; signal transduction, including the anti-viral response; and cellular metabolism. PRMTs are also implicated in the regulation of physiological processes, including embryonic development, myogenesis, and the immune system. Finally, the dysregulation of PRMTs is apparent in cancer, neurodegeneration, muscular disorders, and during inflammation. Herein, we review the functions of PRMTs in immunity and inflammation. We also discuss recent progress with PRMTs regarding the modulation of gene expression related to T and B lymphocyte differentiation, germinal center dynamics, and anti-viral signaling responses, as well as the clinical relevance of using PRMT inhibitors alone or in combination with other drugs to treat cancer, immune, and inflammatory-related diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".