Sequences derived from self-RNA containing certain natural modifications act as suppressors of RNA-mediated inflammatory immune responses
Bibliographic record
Abstract
The ability of the host to distinguish between self and foreign nucleic acids is one of the critical factors contributing to the recognition of pathogens by Toll-like receptors (TLRs). Under certain circumstances, eukaryotic self-RNA may reach TLR-containing compartments allowing for self-recognition. Specific modifications were previously demonstrated to suppress immune activation when placed at several positions in an immune stimulatory RNA or silencing RNA (siRNA). However, we show that even a simple natural modification such as a single 2'-O-methylation at different nucleotide positions throughout a sequence derived from a self-RNA strongly interferes with TLR-mediated effects. Such a single modification can even have an inhibitory effect in vitro and in vivo when placed in a different than the immune stimulatory RNA strand acting as suppressive RNA. Several safeguard mechanisms appear to have evolved to avoid cellular TLR-mediated activation by self-RNAs that may under other circumstances result in inflammatory or autoimmune responses. This knowledge can be used to include as few as a single 2'-O-methyl modification at a specific position in a siRNA sense or anti-sense strand to avoid TLR immune effects.
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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) | 0.001 | 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".