Intracellular ribozyme applications
Bibliographic record
Abstract
The exquisite target selectivity of trans -acting ribozymes has fostered their use as potential therapeutic agents and tools for down-regulating cellular transcripts. In living cells, free diffusion of RNAs is extremely limited, if it exists at all. Thus, getting ribozymes to base-pair with their cognate targets requires co-localizing the ribozyme transcript with the target RNA. In addition, not all sites along a given target RNA are equally accessible to ribozyme base pairing. Cellular proteins greatly influence the trafficking and structure of RNA, and therefore making ribozymes work effectively in cells a significant challenge. This article addresses the problems of getting engineered ribozymes to effectively pair with and cleave targets in cells. The work described here illuminates methods for target-site selection on native mRNAs, methods for ribozyme expression, and strategies for obtaining a discrete intracellular localization of ribozymes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".