Author: Ghorbanizamani, Faezeh; Moulahoum, Hichem; Zihnioglu, Figen; Evran, Serap; Cicek, Candan; Sertoz, Ruchan; Arda, Bilgin; Goksel, Tuncay; Turhan, Kutsal; Timur, Suna
                    Title: Quantitative paper-based dot blot assay for spike protein detection using fuchsine dye-loaded polymersomes  Cord-id: 7tf5lfkj  Document date: 2021_1_1
                    ID: 7tf5lfkj
                    
                    Snippet: Real-time reverse transcriptase-polymerase chain reaction (RT-PCR)-based assays are the gold standard for virus diagnosis. Point-of-care (POC) technologies have shown great progress during this period. Herein, we propose a novel fuchsine dye-loaded polymersome for a colorimetric paper-based dot blot spike protein diagnostic assay for COVID-19 via smartphone-assisted sensing. The prepared platform aimed to create an adaptable tool that competes with traditional nanoparticle-based assays employing
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: Real-time reverse transcriptase-polymerase chain reaction (RT-PCR)-based assays are the gold standard for virus diagnosis. Point-of-care (POC) technologies have shown great progress during this period. Herein, we propose a novel fuchsine dye-loaded polymersome for a colorimetric paper-based dot blot spike protein diagnostic assay for COVID-19 via smartphone-assisted sensing. The prepared platform aimed to create an adaptable tool that competes with traditional nanoparticle-based assays employing gold and silver. Analytical characterization and application of the testing platform showed high sensitivity (10 times better than gold nanoparticles), stability, fast turnaround, and reproducibility. The potential and possibilities demonstrated by the current platform could be observed in its adaptability for different markers and pathologies. In addition, smartphone-assisted sensing emphasizes the ability to use the tool at home by common peoples which can lower the burden on the healthcare facilities and reach more underdeveloped regions.
 
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