Effective small interfering RNA delivery in vitro via a new stearylated cationic peptide
Bibliographic record
Abstract
A crucial bottleneck in RNA interference-based gene therapy is the lack of safe and efficient delivery systems. Here, a novel small interfering RNA (siRNA) delivery peptide, STR-HK, was constructed by conjugating a stearyl end to the N-terminus of the peptide sequence HHHPKPKRKV, where PKPKRKV is an altered sequence of the nucleus localization signal (PKKKRKV) and contributes to the cytosol localization of STR-HK-siRNA complexes. Histidine is a linker and plays an important role in disrupting the endosomal membrane via the proton sponge effect. As expected, STR-HK formed complexes with siRNA with a particle size of 80-160 nm in diameter and efficiently delivered Cy3-labeled glyceraldehyde 3-phosphate dehydrogenase siRNA into PC-3 human prostate cancer cells. The transfection efficiency of STR-HK at molar ratio of 60/1 was comparable to that of Lipofectamine 2000, one of the most efficient commercially available transfection reagents. Furthermore, the STR-HK-siRNA complexes exhibited minimal cytotoxicity, which was significantly lower than that of Lipofectamine. Taken together, the strategy of conjugating the stearyl moiety with HHHPKPKRKV as a non-viral siRNA delivery system is advantageous.
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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) | 0.000 | 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 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".