Evaluation of β-cyclodextrin-modified gemini surfactant-based delivery systems in melanoma models
Bibliographic record
Abstract
Deborah Michel,1 Waleed Mohammed-Saeid,1 Heather Getson,1 Caitlin Roy,1 Masoomeh Poorghorban,1 Jackson M Chitanda,2 Ronald Verrall,2 Ildiko Badea1 1Drug Design and Discovery Research Group, College of Pharmacy and Nutrition, 2Department of Chemistry, University of Saskatchewan, Saskatoon, SK, Canada Abstract: Novel drug delivery systems are developed to improve the biological behavior of poorly soluble drugs and to improve therapeutic outcomes. In melanoma therapy, the goal is efficient drug delivery and mitigation of drug resistance. Melphalan (Mel), a currently used therapeutic agent for melanoma, requires solvent system for solubilization, leading to poor chemical stability. Moreover, drug resistance often renders the drug inefficient in clinical setting. A novel β-cyclodextrin-modified gemini surfactant (CDgemini) delivery system was developed to incorporate Mel in order to improve its physicochemical and biological behavior. Melphalan nanoparticles (Mel-NP) showed optimal particle size in the 200–250 nm range for endocytosis and induced significantly higher cell death compared with Mel (50% of inhibitory concentration [IC50] of 36 µM for the complexes vs 82 µM for Mel). The CDgemini delivery system did not alter the pathway of the cellular death triggered by Mel and caused no intrinsic toxicity to the cells. The Mel-NP complexes induced significant cell death in melanoma cells that were rendered resistant to Mel. These findings demonstrate in principle the applicability of the CDgemini delivery system as safe and efficient alternative to the current melanoma therapy, especially in chemoresistant cases. Keywords: lipid nanoparticles, anticancer agent, drug resistance, apoptosis, spheroid, zeta potential, flow cytometry
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".