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10.1016/j.bios.2021.113088 http://scihub22266oqcxt.onion/10.1016/j.bios.2021.113088 33647790!7896497!33647790     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biosens+Bioelectron 2021 ; 180 (ä): 113088 Nephropedia Template TP {{tp|p=33647790|t=2021. Machine learning-based cytokine microarray digital immunoassay analysis |pdf=|usr=}}{{33647790}} gab.com Text Machine learning-based cytokine microarray digital immunoassay analysis JO: Biosens Bioelectron http://www.kidney.de/pget.php?&tw=1&pmid=33647790 #FOAvip Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume <15 muL at concentrations < 5 pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome. Twit Text FOAVip Machine learning-based cytokine microarray digital immunoassay analysis ????Biosens Bioelectron http://www.kidney.de/pget.php?&tw=1&pmid=33647790 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33647790 #FOAvip English Wikipedia <ref>{{Cite pmid|33647790}}</ref> Machine learning-based cytokine microarray digital immunoassay analysis #MMPMID33647790 Song Y; Zhao J; Cai T; Stephens A; Su SH; Sandford E; Flora C; Singer BH; Ghosh M; Choi SW; Tewari M; Kurabayashi K Biosens Bioelectron 2021[May]; 180 (ä): 113088 PMID33647790show ga Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume <15 muL at concentrations < 5 pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome. |*Machine Learning[MESH] |*SARS-CoV-2[MESH] |COVID-19/*immunology[MESH] |Cytokine Release Syndrome[MESH] |Cytokines/*analysis[MESH] |Humans[MESH] |Image Processing, Computer-Assisted/*methods[MESH] |Immunoassay/*methods[MESH] |Immunotherapy, Adoptive[MESH] |Microarray Analysis/*methods[MESH] |Microfluidic Analytical Techniques/*methods[MESH]Machine learning-based cytokine microarray digital immunoassay analysi(epmc).pdf DeepDyve Pubget Overpricing