Nanoparticles Targeted With NGR Motif Deliver c-myc siRNA and Doxorubicin for Anticancer Therapy
Bibliographic record
Abstract
We have designed a PEGylated LPD (liposome-polycation-DNA) nanoparticle for systemic, specific, and efficient delivery of small interfering RNA (siRNA) into solid tumors in mice by modification with NGR (aspargine-glycine-arginine) peptide, targeting aminopeptidase N (CD13) expressed in the tumor cells or tumor vascular endothelium. LPD-PEG-NGR efficiently delivered siRNA to the cytoplasm and downregulated the target gene in the HT-1080 cells but not CD13(-) HT-29 cells, whereas nanoparticles containing a control peptide, LPD-PEG-ARA, showed only little siRNA uptake and gene silencing activity. LPD-PEG-NGR efficiently delivered siRNA into the cytoplasm of HT-1080 xenograft tumor 4 hours after intravenous injection. Three daily injections (1.2 mg/kg) of c-myc siRNA formulated in the LPD-PEG-NGR effectively suppressed c-myc expression and triggered cellular apoptosis in the tumor, resulting in a partial tumor growth inhibition. When doxorubicin (DOX) and siRNA were co-formulated in LPD-PEG-NGR, an enhanced therapeutic effect was observed.
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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".