Therapeutics
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From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis
Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics–including plasmonics, metamaterials, and metasurfaces–enhance Raman scattering…
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Label-free, real-time, whole-cell response monitoring with liquid Raman spectroscopy
Improved surface enhanced Raman spectroscopy (SERS) of biological targets in liquids is provided. Nanoparticles are treated with a surfactant to provide an electrostatic attraction between the nanoparticles and the biological targets. The resulting clustering of the nanoparticles at the biological targets improves the SERS signal. Such SERS spectroscopy enables real time monitoring of the biological…