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Start Over Author "Ren, Xiang" Publisher american chemical society
252 results on '"Ren, Xiang"'

39. Nanolaminate Plasmonic Substrates for High-Throughput Living Cell SERS Measurements and Artificial Neural Network Classification of Cellular Drug Responses.

Author

Nam, Wonil, Chen, Han, Ren, Xiang, Agah, Masoud, Kim, Inyoung, and Zhou, Wei

Abstract

Rapid in situ bio-analysis of cellular behaviors in response to external stimuli remains a formidable challenge but can open crucial opportunities in biology and medicine. The standard label-based end point assays suffer from invasiveness and complex sample handling. In this regard, label-free surface-enhanced Raman spectroscopy (SERS) has emerged as a promising non-invasive in situ bio-analysis technique for living cells. Nevertheless, achieving rapid in situ SERS bio-analysis still faces challenges in reliable high-throughput measurements and accurate multivariate analysis, which requires significant innovations in bio-interfaced SERS devices and machine learning (ML) methods. Here, we exploit cell-interfaced nanolaminate SERS substrates to demonstrate reliable high-throughput SERS measurements using well-studied living cancer cells with four drug dosages. Artificial neural network (ANN) for multiclass classification of cellular drug responses provides high accuracy (94%). Uniquely, nanolaminate SERS substrates with a high SERS enhancement factor (>107) can rapidly generate big SERS data sets with rich molecular information on living cells (10,000 spectra within 3 min) that can enable the utilization of data-hungry ML methods (e.g., ANN). By capturing additional hidden features in high-dimensional spectroscopic data, ANN is more powerful for multiclass classification than five other popular ML methods, including principal component analysis combined with linear discriminant analysis (PCA-LDA), partial least-squares discriminant analysis (PLSDA), classification tree (CT), k-nearest neighbor (KNN), and support vector machine (SVM). On the basis of the proof-of-concept demonstration using drugs on living cells, we anticipate that the nanolaminate SERS substrates can potentially monitor living cell responses to other external stimuli in a label-free and non-invasive manner. [ABSTRACT FROM AUTHOR]

Published
2022
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