Pharmacokinetics of Peptide Mediated Delivery of Anticancer Drug Ellipticine
Bibliographic record
Abstract
The amino acid pairing peptide EAK16-II (EAK) has shown the ability to stabilize the hydrophobic anticancer agent ellipticine (EPT) in aqueous solution. In this study, we investigate pharmacokinetics of the formulation of EAK-EPT complexes in vivo. The developed formulation can achieve a sufficiently high drug concentration required in vivo animal models. The nanostructure and surface properties of EAK-EPT complexes or nanoparticle were characterized by transmission electron microscopy (TEM) and zeta potential measurements, respectively. 12 healthy male SD rats were divided into EPT group and EAK-EPT group randomly. Rats in EPT group were tail intravenously injected with the EPT (20 mg/kg); rats in EAK-EPT group were injected with EAK-EPT complexes (EPT's concentration is 20 mg/kg). EPT was extracted from rat plasma with dexamethasone sodium phosphate as internal standards (IS). The pharmacokinetic parameters were obtained using high pressure liquid chromatography (HPLC). Significant differences in main pharmacokinetic parameters between EPT and EAK-EPT complexes were observed, demonstrating that the complexation with EAK prolongs the residence time of the drug and enlarges the area under the concentration-time curve (AUC). This means that EAK can serve as a suitable carrier to increase the bioavailability of EPT.
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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) | 0.001 | 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".