The emerging role and significance of circular RNAs in viral infections and antiviral immune responses: possible implication as theranostic agents
Bibliographic record
Abstract
Circular RNAs (circRNAs) are ubiquitously expressed, covalently closed rings, produced by pre-mRNA splicing in a reversed order during post-transcriptional processing. Circularity endows 3'-5'-linked circRNAs with stability and resistance to exonucleolytic degradation which raises the question whether circRNAs may be relevant as potential therapeutic targets or agents. High stability in biological systems is the most remarkable property and a major criterion for why circRNAs could be exploited for a range of RNA-centred medical applications. Even though various biological roles and regulatory functions of circRNAs have been reported, their in-depth study is challenging because of their circular structure and sequence-overlap with linear mRNA counterparts. Moreover, little is known about their role in viral infections and in antiviral immune responses. We believe that an in-depth and detailed understanding of circRNA mediated viral protein regulations will increase our knowledge of the biology of these novel molecules. In this review, we aimed to provide a comprehensive basis and overview on the biogenesis, significance and regulatory roles of circRNAs in the context of antiviral immune responses and viral infections including hepatitis C virus infection, hepatitis B virus infection, hepatitis delta virus infection, influenza A virus infection, Epstein-Barr virus infection, kaposi's sarcoma herpesvirus infection, human cytomegalovirus infection, herpes simplex virus infection, human immunodeficiency virus infection, porcine epidemic diarrhoea virus infection, ORF virus infection, avian leukosis virus infection, simian vacuolating virus 40 infection, transmissible gastroenteritis coronavirus infection, and bovine viral diarrhoea virus infection. We have also discussed the critical regulatory role of circRNAs in provoking antiviral immunity, providing evidence for implications as therapeutic agents and as diagnostic markers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".