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10.1038/srep37246 http://scihub22266oqcxt.onion/10.1038/srep37246 C5112555!5112555 !27853258     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\27853258 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Sci+Rep 2016 ; 6 (ä): 37246 Nephropedia Template TP {{tp|p=27853258 |t=2016. Digital Detection of Exosomes by Interferometric Imaging |pdf=|usr=}}{{27853258 }} gab.com Text Digital Detection of Exosomes by Interferometric Imaging JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=27853258 #FOAvip Exosomes, which are membranous nanovesicles, are actively released by cells and have been attributed to roles in cell-cell communication, cancer metastasis, and early disease diagnostics. The small size (30-100?nm) along with low refractive index contrast of exosomes makes direct characterization and phenotypical classification very difficult. In this work we present a method based on Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) that allows multiplexed phenotyping and digital counting of various populations of individual exosomes (>50?nm) captured on a microarray-based solid phase chip. We demonstrate these characterization concepts using purified exosomes from a HEK 293 cell culture. As a demonstration of clinical utility, we characterize exosomes directly from human cerebrospinal fluid (hCSF). Our interferometric imaging method could capture, from a very small hCSF volume (20?uL), nanoparticles that have a size compatible with exosomes, using antibodies directed against tetraspanins. With this unprecedented capability, we foresee revolutionary implications in the clinical field with improvements in diagnosis and stratification of patients affected by different disorders. Twit Text FOAVip Digital Detection of Exosomes by Interferometric Imaging ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=27853258 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27853258 #FOAvip English Wikipedia <ref>{{Cite pmid|27853258 }}</ref> Digital Detection of Exosomes by Interferometric Imaging #MMPMID27853258 Daaboul GG ; Gagni P ; Benussi L ; Bettotti P ; Ciani M ; Cretich M ; Freedman DS ; Ghidoni R ; Ozkumur AY ; Piotto C ; Prosperi D ; Santini B ; Ünlü MS ; Chiari M Sci Rep 2016[Nov]; 6 (ä): 37246 PMID27853258 show ga Exosomes, which are membranous nanovesicles, are actively released by cells and have been attributed to roles in cell-cell communication, cancer metastasis, and early disease diagnostics. The small size (30-100?nm) along with low refractive index contrast of exosomes makes direct characterization and phenotypical classification very difficult. In this work we present a method based on Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) that allows multiplexed phenotyping and digital counting of various populations of individual exosomes (>50?nm) captured on a microarray-based solid phase chip. We demonstrate these characterization concepts using purified exosomes from a HEK 293 cell culture. As a demonstration of clinical utility, we characterize exosomes directly from human cerebrospinal fluid (hCSF). Our interferometric imaging method could capture, from a very small hCSF volume (20?uL), nanoparticles that have a size compatible with exosomes, using antibodies directed against tetraspanins. With this unprecedented capability, we foresee revolutionary implications in the clinical field with improvements in diagnosis and stratification of patients affected by different disorders. |Cerebrospinal Fluid/*chemistry [MESH] |Exosomes/*chemistry [MESH] |HEK293 Cells [MESH] |Humans [MESH] |Interferometry/methods [MESH]Digital Detection of Exosomes by Interferometric Imaging (epmc).pdf DeepDyve Pubget Overpricing