Thermoplasmonic‐Triggered Release of Loads from DNA‐Modified Hydrogel Microcapsules Functionalized with Au Nanoparticles or Au Nanorods

Small ◽  
2020 ◽  
Vol 16 (22) ◽  
pp. 2000880 ◽  
Author(s):  
Chen Wang ◽  
Margarita Vázquez‐González ◽  
Michael Fadeev ◽  
Yang Sung Sohn ◽  
Rachel Nechushtai ◽  
...  
Keyword(s):  
Au Nanoparticles ◽  
Triggered Release ◽  
Au Nanorods

Rapid Epitaxial Growth of Ag on Au Nanoparticles: From Au Nanorods to Core-Shell Au@Ag Octahedrons

2010 ◽  
Vol 16 (19) ◽  
pp. 5558-5563 ◽  
Author(s):  
Ana Sánchez-Iglesias ◽  
Enrique Carbó-Argibay ◽  
Arnaud Glaria ◽  
Benito Rodríguez-González ◽  
Jorge Pérez-Juste ◽  
...  
Keyword(s):  
Epitaxial Growth ◽  
Au Nanoparticles ◽  
Core Shell ◽  
Au Nanorods

Photochemically Controlled Synthesis of Anisotropic Au Nanostructures: Platelet-like Au Nanorods and Six-Star Au Nanoparticles

ACS Nano ◽  
2010 ◽  
Vol 4 (10) ◽  
pp. 6196-6202 ◽  
Author(s):  
Xiao Huang ◽  
Xiaoying Qi ◽  
Yizhong Huang ◽  
Shaozhou Li ◽  
Can Xue ◽  
...  
Keyword(s):  
Au Nanoparticles ◽  
Controlled Synthesis ◽  
Au Nanorods

DNA-Based Hydrogels Loaded with Au Nanoparticles or Au Nanorods: Thermoresponsive Plasmonic Matrices for Shape-Memory, Self-Healing, Controlled Release, and Mechanical Applications

ACS Nano ◽  
2019 ◽  
Vol 13 (3) ◽  
pp. 3424-3433 ◽  
Author(s):  
Chen Wang ◽  
Xia Liu ◽  
Verena Wulf ◽  
Margarita Vázquez-González ◽  
Michael Fadeev ◽  
...  
Keyword(s):  
Controlled Release ◽  
Shape Memory ◽  
Au Nanoparticles ◽  
Self Healing ◽  
Au Nanorods

147% improved efficiency of dye synthesized solar cells by using CdS QDs, Au nanorods and Au nanoparticles

RSC Advances ◽  
2014 ◽  
Vol 4 (107) ◽  
pp. 62356-62361 ◽  
Author(s):  
Omid Amiri ◽  
Masoud Salavati-Niasari ◽  
Ali Rafiei ◽  
Mostafa Farangi
Keyword(s):  
Solar Cells ◽  
Au Nanoparticles ◽  
Au Nanorods ◽  
Cds Qds

Machine Learning Accelerated Genetic Algorithms for Computational Materials Search

2018 ◽  
Author(s):  
Steen Lysgaard ◽  
Paul C. Jennings ◽  
Jens Strabo Hummelshøj ◽  
Thomas Bligaard ◽  
Tejs Vegge
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Au Nanoparticles ◽  
Learning Model ◽  
Energy Calculations ◽  
Atomic Distribution ◽  
Machine Learning Model ◽  
Fold Reduction ◽  
Computational Materials

A machine learning model is used as a surrogate fitness evaluator in a genetic algorithm (GA) optimization of the atomic distribution of Pt-Au nanoparticles. The machine learning accelerated genetic algorithm (MLaGA) yields a 50-fold reduction of required energy calculations compared to a traditional GA.

Oncolytic Coxsackievirus and the Mechanisms of its Effects on Cancer: A Narrative Review

2020 ◽  
Vol 16 ◽  
Author(s):  
Ali Ahmadi ◽  
Hadi Esmaeili Gouvarchin Ghaleh ◽  
Ruhollah Dorostkar ◽  
Mahdieh Farzanehpour ◽  
Masoumeh Bolandian
Keyword(s):  
Genetic Disease ◽  
Control Cell ◽  
Gene Mutations ◽  
Therapeutic Agents ◽  
Cell Penetrating Peptides ◽  
Triggered Release ◽  
New Techniques ◽  
Viral Therapy ◽  
Cell Penetrating ◽  
Cancer Cell Targeting

Abstract:: Cancer is a genetic disease triggered by gene mutations, which control cell growth and their functionality inherited from previous generations. The targeted therapy of some tumors was not especially successful. A host of new techniques can be used to treat aptamer-mediated targeting, cancer immunotherapy, cancer stem cell (CSC) therapy, cell-penetrating peptides (CPPs), hormone therapy, intracellular cancer cell targeting, nanoparticles, and viral therapy. These include chemical-analog conjugation, gene delivery, ligand-receptor-based targeting, prodrug therapies, and triggered release strategies. Virotherapy is a biotechnological technique for turning viruses into therapeutic agents by the reprogramming of viruses to cure diseases. In several tumors, including melanoma, multiple myeloma, bladder cancer, and breast cancer, the oncolytic capacity of oncolytic Coxsackievirus has been studied. The present study aims to assess oncolytic Coxsackievirus and its mechanisms of effect on cancer cells.

scholarly journals Multi-Walled Carbon Nanotubes Decorated with Guanidinylated Dendritic Molecular Transporters: An Efficient Platform for the Selective Anticancer Activity of Doxorubicin

Pharmaceutics ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 858
Author(s):  
Kyriaki-Marina Lyra ◽  
Archontia Kaminari ◽  
Katerina N. Panagiotaki ◽  
Konstantinos Spyrou ◽  
Sergios Papageorgiou ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Anticancer Activity ◽  
Cancer Cells ◽  
Delivery System ◽  
Colloidal Stability ◽  
Triggered Release ◽  
Selective Toxicity ◽  
Molecular Transporters ◽  
Multi Walled Carbon Nanotubes ◽  
Walled Carbon Nanotubes

An efficient doxorubicin (DOX) drug delivery system with specificity against tumor cells was developed, based on multi-walled carbon nanotubes (MWCNTs) functionalized with guanidinylated dendritic molecular transporters. Acid-treated MWCNTs (oxCNTs) interacted both electrostatically and through hydrogen bonding and van der Waals attraction forces with guanidinylated derivatives of 5000 and 25,000 Da molecular weight hyperbranched polyethyleneimine (GPEI5K and GPEI25K). Chemical characterization of these GPEI-functionalized oxCNTs revealed successful decoration with GPEIs all over the oxCNTs sidewalls, which, due to the presence of guanidinium groups, gave them aqueous compatibility and, thus, exceptional colloidal stability. These GPEI-functionalized CNTs were subsequently loaded with DOX for selective anticancer activity, yielding systems of high DOX loading, up to 99.5% encapsulation efficiency, while the DOX-loaded systems exhibited pH-triggered release and higher therapeutic efficacy compared to that of free DOX. Most importantly, the oxCNTs@GPEI5K-DOX system caused high and selective toxicity against cancer cells in a non-apoptotic, fast and catastrophic manner that cancer cells cannot recover from. Therefore, the oxCNTs@GPEI5K nanocarrier was found to be a potent and efficient nanoscale DOX delivery system, exhibiting high selectivity against cancerous cells, thus constituting a promising candidate for cancer therapy.

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