Powering up the molecular therapy of RNA interference by novel nanoparticles
Bibliographic record
Abstract
RNA interference technology has been widely applied in biomedical therapy in recent years. A type of small RNA molecule - siRNA could regulate the expression of disease related genes by breaking down the integrity of mRNA with high specificity. However, the low efficiency of siRNA delivery to its target seriously hampered the RNAi therapy. Compared with viral-based delivery systems, non-viral-based nanoparticles are more suitable for disease treatment due to reduced cellular toxicity, higher loading capacity, and better biocompatibility. This review article highlights several nanoparticle-based siRNA delivery systems, including liposomes, cationic solid lipid nanoparticles, reconstituted high density lipoprotein, polymeric nanoparticles, cationic cell penetrating peptides, and inorganic nanoparticles. The molecular mechanism of gene silencing, clinical examples, and the limitations of current technology related to nanomaterial sciences, are also discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".