Design and Evaluation of Endosomolytic Biocompatible Peptides as Carriers for siRNA Delivery
Bibliographic record
Abstract
Gene therapy using RNA interference (RNAi) technology has been explored to treat cancers, by regulating the expression of oncogene. However, even though small interfering RNA (siRNA), which triggers RNAi, may have great therapeutic potential, efforts at using them in vivo have been hampered by the difficulty of effective and safe delivery into cells of interest. In this study, to develop a safe and efficient carrier for in vitro and in vivo siRNA delivery, we designed a peptide library. These peptides are improved variants of a known peptide based siRNA carrier C6. All the modifications improved the transfection efficiency of C6 to some degree. After completing prescreening for activity, several promising candidates were used for further evaluation. Selected peptides C6M3 and C6M6 could form stable complexes with siRNA. These complexes could be greatly uptaken by cells and showed a punctate perinuclear distribution. Moreover, peptide/siRNA complexes achieved high transfection efficiency in vitro without inducing substantial cytotoxicity. We have validated the therapeutic potential of this strategy for cancer treatment by targeting Bcl-2 gene in mouse tumor models, and demonstrated that tumor growth was inhibited. In order to address possible immune side effects of these peptide carriers, biocompatibility study in terms of complement activation and cytokine activation assay were carried out, whereas none of the peptides induced such effects. In conclusion, these results support the potential of these peptides as therapeutic siRNA carrier.
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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 | 0.001 | 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".