4.7 Article

RGD Peptide Modified Erythrocyte Membrane/Porous Nanoparticles Loading Mir-137 for NIR-Stimulated Theranostics of Glioblastomas

期刊

NANOMATERIALS
卷 12, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/nano12091464

关键词

mesoporous silica; indocyanine green; microRNAs-137; red blood cell membranes; glioblastomas; synergistic treatment

资金

  1. National Natural Science Foundation of China [22174031]
  2. Fundamental Research Funds for the Central Universities [HIT.OCEF.2021026]
  3. Yu Wei Han Academician Outstanding Youth Development Fund [DQYWH201603]
  4. National Natural Science Foundation of Heilongjiang Province [LH2021H114]

向作者/读者索取更多资源

Cell-derived drug carriers have the ability to imitate natural properties of source cells, making them a promising option for theranostics. In this study, a nanoplatform was developed using mesoporous silica nanoparticles, indocyanine green, microRNAs-137, red-blood-cell membranes, and tumor-targeting peptides. The nanoplatform showed photothermal and gene therapy properties and had unique features such as biocompatibility and tumor recognition.
Cell-derived drug carriers have increasingly gained the interest of the scientific community due to their ability to imitate various natural properties of their source cells. We developed theranostics nanoplatforms composed of mesoporous silica nanoparticles (MSNs), indocyanine green (ICG) molecules, microRNAs-137 (miR-137), red-blood-cell membranes (RM), and tumor-targeting cyclo Arg-Gly-Asp-d-Phe-Cys peptides (cRGD(fC)), which were abbreviated as MSNs/ICG/miR/RM/RGD particles. These particles possessed photothermal and gene therapy properties due to ICG and miR-137, respectively. The photothermal conversion efficiency was similar to 18.7%. Upon 808 nm light irradiation, the tumor inhibition rate reached 94.9% with dosage of 10 mg/kg. The developed nanoplatform possessed unique properties, such as exceptional biocompatibility, immune escaping, and specific recognition, which was also used for near-infrared fluorescence, photoacoustic (PA) bimodal imaging-guided tumor recognition.

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