Self/Co-Assembling Peptide, EAR8-II, as a Potential Carrier for a Hydrophobic Anticancer Drug Pirarubicin (THP)—Characterization and in-Vitro Delivery
Bibliographic record
Abstract
A short ionic-complementary peptide, EAR8-II, was employed to encapsulate the hydrophobic anticancer drug pirarubicin (THP). EAR8-II was designed to inherit advantages from two previously introduced peptides, AAP8 and EAK16-II, in their self/co-assembly. This peptide is short, simple, and inexpensive to synthesize, while possessing a low critical assembly concentration (CAC). The choice of alanine (A) residues in the peptide sequence provides moderate hydrophobic interactions, causing a minimal degree of aggregation, compared with other more hydrophobic residues. EAR8-II is an ionic-complementary peptide, similar to EAK16-II, can self/co-assemble with hydrophobic compounds such as THP, and forms a stable fibular nanostructure in aqueous solution. Physiochemical properties and cellular activities of the EAR8-II and THP complexes were evaluated and show dependency on the peptide-to-drug ratio. The complex at the peptide-to-drug mass ratio of 5:1 provides a stable solution, uniform nanostructure, and highly effective anticancer activity against various cancer cell lines. This work forms the basis for detailed studies on EAR8-II and THP formulations in vitro and in vivo, for future development of peptide-based delivery systems for hydrophobic anticancer drugs.
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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".