A 89Zr-labeled lipoplex nanosystem for image-guided gene delivery: design, evaluation of stability and in vivo behavior
Bibliographic record
Abstract
Istvan Hajdu,1 Amal Makhlouf,1,2 Viswas Raja Solomon,3 Deborah Michel,1 Mays Al-Dulaymi,1 Kishor M Wasan,1 Humphrey Fonge,3,4 Ildiko Badea1 1Drug Discovery and Development Research Group, College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada; 2Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Cairo University, 12411 Cairo, Egypt; 3Department of Medical Imaging, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N 0W8, Canada; 4Department of Medical Imaging, Royal University Hospital Saskatoon, SK S7N 0W8, Canada Background: With the advances in radiopharmaceutical research, the development of image-guided therapy has become a major interest. While the development of theranostic nanotherapeutics is frequently associated with cancer chemotherapy, phototherapy and radiotherapy, there is little information available on the in vivo monitoring of gene delivery systems and the application of image-guided approach in gene therapy. The goal of this work was to determine the in vivo behavior of DNA delivery nanosystems - based on cationic gemini surfactants – designed for image-guided gene therapy. We tested the feasibility of monitoring tumor accumulation of gene delivery nanoparticles by positron emission tomography.Methods: To be able to conjugate radiotracers to the nanoparticles, a deferoxamine-modified gemini surfactant was synthesized, DNA-containing lipoplex nanoparticles were formulated, and radiolabeled with Zirconium-89 (89Zr). The pharmacokinetics and biodistribution of 89Zr labeled surfactant and 89Zr labeled nanoparticles were monitored in mice by microPET/CT imaging and ex vivo gamma counting. Results: Modification of the nanoparticles with deferoxamine did not alter their physicochemical properties. The radiolabeled nanoparticles (labeling efficiency of 95±3%) were stable in PBS and serum. The biological half-life of the 89Zr labeled nanoparticles was significantly higher compared to 89Zr labeled surfactant. As expected, the nanoparticles had significantly higher liver accumulation than the radiolabeled surfactant alone and lower kidney accumulation. Tumor uptake was detected at 2 hours post injection and decreased throughout the 3-day monitoring. Conclusion: We propose that radiolabeling DNA delivery lipoplex nanosystems is a promising approach for the design and optimization of image-guided nanomedicines, especially in the context of cancer gene therapy.Keywords: gemini surfactant, pharmacokinetic, biodistribution, melanoma, microPET imaging
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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".