Endogenous Antiviral Mechanisms of RNA Interference: A Comparative Biology Perspective
Bibliographic record
Abstract
RNA interference (RNAi) is a natural process that occurs in many organisms ranging from plants to mammals. In this process, double-stranded RNA or hairpin RNA is cleaved by a RNaseIII-type enzyme called Dicer into small interfering RNA duplex. This then directs sequence-specific, homology-dependent, posttranscriptional gene silencing by binding to its complementary RNA and triggering its elimination through degradation or by inducing translational inhibition. In plants, worms, and insects, RNAi is a strong antiviral defense mechanism. Although, at present, it is unclear whether RNA silencing naturally restricts viral infection in vertebrates, there are signs that this is certainly the case. In a relatively short period, RNAi has progressed to become an important experimental tool both in vitro and in vivo for the analysis of gene function and target validation in mammalian systems. In addition, RNA silencing has subsequently been found to be involved in translational repression, transcriptional inhibition, and DNA degradation. In this article we review the literature in this field, which may open doors to the many uses to which this important technology is being put, including the potential of RNAi as a therapeutic strategy for gene regulation to modulate host-pathogen interactions.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".