rna Interference and micro-rna–Oriented Therapy in Cancer: Rationales, Promises, and Challenges
Bibliographic record
Abstract
The discovery that RNA interference (RNAi) and its functional derivatives, small interfering RNAs (SiRNAs) and micro-RNAs (MiRNAs) could mediate potent and specific gene silencing has raised high hopes for cancer therapeutics. The prevalence of these small (18-25 nucleotide) non-coding rnas in human gene networks, coupled with their unique specificity, has paved the way for the development of new and promising therapeutic strategies in re-directing or inhibiting small rna phenomena.Three strategies are currently being developed: De novo RNAi programming using synthetic SiRNAS to target the expression of genes. Strengthening or recapitulation of the physiologic targeting of messenger RNAs by specific MiRNAs. Sequence-specific inhibition of Mi RNA functions by nucleic acid analogs. Each strategy, currently being developed both in academia and in industry, holds promise in cancer therapeutics.
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 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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".