Potential use of <i>CRISPR/Cas13</i> system for vaccine development against various RNA-viral infections
Bibliographic record
Abstract
Emerging and re-emerging infectious diseases pose a serious threat to human health. Developing Sensitive, Rapid and simple diagnostic tools as well as antiviral therapeutics are essential for combating RNA viruses. Recently, genome and transcriptome engineering toolset based on CRISPR/Cas systems has grown rapidly. The advancement in CRISPR has made it possible to alter nucleic acids, particularly, RNA-targeting CRISPR/Cas13, to analyze and modify RNAs in endogenous microenvironments. The development of novel research tools in the disciplines of virology and biotechnology could be facilitated by the use of Cas13 effectors as a promising alternative protein machinery. Here, we present a comprehensive overview of potential application of the CRISPR/Cas13 system in vaccine development against viral RNAs. We discuss the molecular mechanism of the CRISPR/Cas13 system and its application in vaccine development for various diseases, including hepatitis C, influenza, dengue and COVID-19.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".