Advanced Materials · 2018 · 184 citations · 43 references
PharmacyBiomedical EngineeringPharmaceuticsDrug DeliveryNanomaterialsNanoparticle Drug DeliveryCarbon NanomaterialsDrug EncapsulationNanomedicineNanoparticle Delivery SystemsNanoparticle FormulationsPhotodynamic TherapyCancer Photodynamic TherapyCarbon-based NanocarriersGrapheneGraphene NanocompositesNanoparticle DeliveryNanoparticle Delivery VectorsNanoparticle Imaging AgentsPhotodynamic Therapy Nanomaterials
Abstract Photosensitizers (PS) are an essential component of photodynamic therapy (PDT). Conventional PSs are often porphyrin derivatives, which are associated with high hydrophobicity, low quantum yield in aqueous solutions, and suboptimal tumor‐to‐normal‐tissue (T/N) selectivity. There have been extensive efforts to load PSs into nanoparticle carriers to improve pharmacokinetics. The approach, however, is often limited by PS self‐quenching, pre‐mature release, and nanoparticle accumulation in the reticuloendothelial system organs. Herein, a novel, nanoparticle‐based PS made of gadolinium‐encapsulated graphene carbon nanoparticles (Gd@GCNs), which feature a high 1 O 2 quantum yield, is reported. Meanwhile, Gd@GCNs afford strong fluorescence and high T 1 relaxivity (16.0 × 10 −3 m −1 s −1 , 7 T), making them an intrinsically dual‐modal imaging probe. Having a size of approximately 5 nm, Gd@GCNs can accumulate in tumors through the enhanced permeability and retention effect. The unbound Gd@GCNs cause little toxicity because Gd is safely encapsulated within an inert carbon shell and because the particles are efficiently excreted from the host through renal clearance. Studies with rodent tumor models demonstrate the potential of the Gd@GCNs to mediate image‐guided PDT for cancer treatment. Overall, the present study shows that Gd@GCNs possess unique physical, pharmaceutical, and toxicological properties and are an all‐in‐one nanotheranostic tool with substantial clinical translation potential.
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Raman Spectra of Graphite Oxide and Functionalized Graphene Sheets
Konstantin N. Kudin, Bulent Ozbas, Hannes C. Schniepp et al. · Nano Letters · 2007 · 4.4K citations