This approach provides signals for both the morphology, related to the phenotype, and the intracellular molecular content at single-cell level, that we employed to study cell populations under different stimuli. In particular, we studied macrophage cells and their response to a simulated bacterial infection upon exposure to lipopolysaccharide, and show how this approach is able to noninvasively detect the activation state at single-cell level by coupling it with multivariate analysis and machine learning algorithms. |
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Raman spectroscopy
Microscopy
Spectroscopy
Digital holography
Imaging systems
Microscopes
Cell biology