Antisense DNA and RNA: Potential Therapeutics for Viral Infection
Bibliographic record
Abstract
Antisense DNA and RNA are valuable tools to inhibit expression of a target gene in a sequence-specific manner. These molecules are not only widely used for gene functional study but also for therapeutic purpose. The strategy for therapeutics is attributed to its specific inhibition of gene expression of pathogens or disease-causing genes. Three types of anti-mRNA strategies can be distinguished, including antisense oligodeoxynucleotide (AODN), nucleic acid enzymes, and double-stranded small interfering RNA (siRNA). In this article we overview the basic principles of AODN and siRNA and then focus on their potential applications in antiviral therapy including our own data on coxsackieviral infection, a common pathogen of human myocarditis. In addition, we also briefly discuss the problems and difficulties in these drug developments, which need to be overcome to achieve the final goal in clinical application. Keywords: Antisense oligodeoxynucleotide, small interfering RNA, antiviral agents, coxsackievirus B3
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".