2022
DOI: 10.1002/adhm.202201889
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Liquid Core Nanoparticle with High Deformability Enables Efficient Penetration across Biological Barriers

Abstract: Biological barriers significantly limit the delivery efficiency of drug delivery systems, resulting in undesired therapeutic effects. When designing a delivery system with optimized penetration behavior across the biological barriers, mechanical properties, such as deformability, are emerging as important parameters that need to be considered, although they are usually neglected in current research. Herein, a liquid core nanoparticle (LCN) composed of a polymer‐encapsulated edible oil droplet is demonstrated. … Show more

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Cited by 7 publications
(10 citation statements)
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References 31 publications
(24 reference statements)
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“…Through molecular design, self-assembly, or coassembly with other materials, we aim to finely regulate the drug release kinetics of azocalixarenes based on the individual characteristics of diseases. The application of machine learning techniques holds great potential for the field of azocalixarene research. By training models on large data sets of known azocalixarene structures and their corresponding properties like binding affinities and hypoxia responsive kinetics, machine learning can aid in discovering novel azocalixarene derivatives with desired characteristics. Azocalixarenes can cooperate with other biomaterials in a covalent or noncovalent way, for instance, polymers, peptides, and proteins. ,,, Some living biomaterials such as living cells, bacteria, and cell/bacteria-derived biofilms can also be taken into consideration, which will harness the advantages of different materials and can be better used in biomedicine. Azocalixarenes have therapeutic activities. For example, QAAC4A can induce immunogenic cell death efficiently .…”
Section: Discussionmentioning
confidence: 99%
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“…Through molecular design, self-assembly, or coassembly with other materials, we aim to finely regulate the drug release kinetics of azocalixarenes based on the individual characteristics of diseases. The application of machine learning techniques holds great potential for the field of azocalixarene research. By training models on large data sets of known azocalixarene structures and their corresponding properties like binding affinities and hypoxia responsive kinetics, machine learning can aid in discovering novel azocalixarene derivatives with desired characteristics. Azocalixarenes can cooperate with other biomaterials in a covalent or noncovalent way, for instance, polymers, peptides, and proteins. ,,, Some living biomaterials such as living cells, bacteria, and cell/bacteria-derived biofilms can also be taken into consideration, which will harness the advantages of different materials and can be better used in biomedicine. Azocalixarenes have therapeutic activities. For example, QAAC4A can induce immunogenic cell death efficiently .…”
Section: Discussionmentioning
confidence: 99%
“…Azocalixarenes can cooperate with other biomaterials in a covalent or noncovalent way, for instance, polymers, peptides, and proteins. ,,, Some living biomaterials such as living cells, bacteria, and cell/bacteria-derived biofilms can also be taken into consideration, which will harness the advantages of different materials and can be better used in biomedicine.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…and mucus layers. 41 However, only using the characteristics of nanoparticles, the passive targeting effect is not ideal, so people design nanoparticles and put forward the second generation of targeting nanoparticles.…”
Section: Passive Targetingmentioning
confidence: 99%
“…Wang et al designed a nanoparticle formed by polymer-coated edible oil droplets, which is deformable and can effectively penetrate biological barriers such as BBB, deep brain tissues and mucus layers. 41 However, only using the characteristics of nanoparticles, the passive targeting effect is not ideal, so people design nanoparticles and put forward the second generation of targeting nanoparticles.…”
Section: Nanoparticle Targeting Mechanismmentioning
confidence: 99%