Yanlei Zhan, Zhichao Chang, Chang Liu, Ziyu Zhang, Runtong Zhang, Yi Lu, Jianping Qi, Wei Wu, Haisheng He
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引用次数: 0
Abstract
Elucidating in vivo lipolysis is crucial for clarifying the underlying mechanisms and in vivo fates of lipid-based nanocarriers, which are essential oral drug delivery carriers. Current mainstream methodologies use various in vitro digestion models to predict the in vivo performance of lipid formulations; however, their accuracy is often impeded by the complicated environment of the gastrointestinal tract. Although fluorescence labeling with conventional probes partly reveals the in vivo translocation of lipid nanocarriers, it fails to elucidate the lipolysis process because of poor signal discrimination among nanocarriers, free probes, and mixed micelles (lipolysis end-products). Here, a polarity-sensitive probe (PN-C18) with aggregation-caused quenching properties for labeling lipid nanocarriers is developed and optimized. PN-C18 successfully eliminates interference from both free probes and mixed micelles during lipolysis. In a representative in vitro lipolysis model, PN-C18 labeling shows stronger correlation between fluorescence intensity and lipolysis progression than those of previous methods. In vivo, the translocation and lipolysis of lipid nanoparticles are clearly visualized and effectively monitored, owing to the high tissue-penetrating capability of PN-C18 NIR-II photons. This study provides practical means for elucidating the in vivo fate of lipid-based drug delivery systems and offers valuable insights and reference for further studies in this domain.
Small MethodsMaterials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍:
Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques.
With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community.
The online ISSN for Small Methods is 2366-9608.