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1  Test Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia.
Academic Editor: Humbert G. Díaz

Abstract:

*Note: Mol2Net conference is associated to different MDPI journals special issues guest edited by Mol2Net Conference Committee members. This is an strategy to increase the online post-publication visibility of papers and conference, promote post-publication brainstorming discussion, and increase authors feedback. This association implies that our conference perform post-publication indexing of selected papers already published in MDPI journals with the consent of the issue editors. We publish free-of-cost these post-publication summaries. They include a shortened title, corresponding author info, and paper cover pdf file. The cover pdf file contains paper first page with all authors, abstract, full reference , and link to original papers.

Reference: This is a post-publication summary note for the paper published in the special issue Sustainable Materials and Technologies for Drug Delivery and Tissue Engineering, Edited by: Dr. I.A. Neacsu and Dr. B.S. Vasile, Managing Editor: C. Zha, Visit the link to see original paper. Reference: Pharmaceutics 2022, 14(11),
2403; https://doi.org/10.3390/pharmaceutics14112403

Summary. Many natural products with greater therapeutic efficacy are limited to target several chronic diseases such as cancer, diabetes, and neurodegenerative diseases. Among the natural products from hops, i.e., Xanthohumol (XH), is a prenylated chalcone. The present research work focuses on the enhancement of the poor oral bioavailability and weak pharmacokinetic profile of XH. We exemplified the development of a Xanthohumol-loaded solid lipid nanoparticles (XH-SLNs) cargo system to overcome the limitations associated with its bioavailability. The XH-SLNs were prepared by a high-shear homogenization/ultrasonication method and graphical, numerical optimization was performed by using Box–Behnken Design. Optimized XH-SLNs showed PS (108.60 nm), PDI (0.22), ZP (−12.70 mV), %EE (80.20%) and an amorphous nature that was confirmed by DSC and PXRD. FE-SEM and HRTEM revealed the spherical morphology of XH-SLNs. The results of release studies were found to be 9.40% in 12 h for naive XH, whereas only 28.42% of XH was released from XH-SLNs. The slow release of drugs may be due to immobilization of XH in the lipid matrix. In vivo pharmacokinetic study was performed for the developed XH-SLNs to verify the enhancement in the bioavailability of XH than naive XH. The enhancement in the bioavailability of the XH was confirmed from an increase in Cmax (1.07-folds), AUC0-t (4.70-folds), t1/2 (6.47-folds) and MRT (6.13-folds) after loading into SLNs. The relative bioavailability of XH loaded in SLNs and naive XH was found to be 4791% and 20.80%, respectively. The cytotoxicity study of naive XH, XH-SLNs were performed using PC-3 cell lines by taking camptothecin as positive control. The results of cytotoxicity study revealed that XH-SLNs showed good cell inhibition in a sustained pattern. This work successfully demonstrated formulation of XH-SLNs with sustained release profile and improved oral bioavailability of XH with good anticancer properties against PC-3 cells.

Pharmaceutics 2022, 14(11), 2403; https://doi.org/10.3390/pharmaceutics14112403

Keywords: Box–Behnken Design; oral bioavailability; drug release; solid lipid nanoparticles; Xanthohumol
Comments on this paper
Shan He
Dear authors thank you for your support to the conference.
Now we closed the publication phase and launched the post-publication phase of the conference. REVIEWWWERS'08 Brainstorming Workshop is Now Open from 2023-Jan-01 to 2023-Jan-31. MOL2NET Committee, Authors, and Validated Social Media Followers Worldwide are ... Invited to Post Moderated Questions/Answers, Comments, about papers. Please kindly post your public Answers (A) to the following questions in order to promote interchange of scientific ideas. These are my Questions (Q) to you:

Q. Have you considered to using AI/ML techniques to optimize the XH-SLNs synthesizing?

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