Advances, Nuances, and Potential Pitfalls When Exploiting the Therapeutic Potential of RNA Interference
Bibliographic record
Abstract
The discovery of RNA interference (RNAi) holds the potential to alter the paradigm of medical therapeutics. With the ability to selectively silence the function of a gene, RNAi not only provides an indispensable research tool for determining the function of a gene, but also offers potential for the development of novel therapeutics that will inhibit specific genes involved in disease. New concepts in therapeutics have been uncovered through the study of RNAi. Nuances have emerged. For instance, global RNAi pathways can be affected by somatic mutations in cancer and cellular stress, such as hypoxia. Also, viral gene therapy can have unexpected effects on endogenous short noncoding RNA pathways. Therefore, it is important to understand where RNAi therapeutics enter the processing pathways. We highlight the evolving use of RNAi as a new class of therapeutics, such as for amyloidosis, and address some of the anticipated challenges associated with its clinical application.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".