Combination of multi-focus Raman spectroscopy and compressive sensing for parallel monitoring of single-cell dynamics

To overcome the low efficiency of conventional confocal Raman spectroscopy, many efforts have been devoted to parallelizing the Raman excitation and acquisition, in which the scattering from multiple foci is projected onto different locations on a spectrometer’s CCD, along either its vertical, horiz...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Zhenzhen Li, Xiujuan Zhang, Chengui Xiao, Da Chen, Shushi Huang, Pengfei Zhang, Guiwen Wang
Formato: article
Lenguaje:EN
Publicado: World Scientific Publishing 2021
Materias:
T
Acceso en línea:https://doaj.org/article/3c50efb3c1fd4e2f80d729f0f21e98be
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:To overcome the low efficiency of conventional confocal Raman spectroscopy, many efforts have been devoted to parallelizing the Raman excitation and acquisition, in which the scattering from multiple foci is projected onto different locations on a spectrometer’s CCD, along either its vertical, horizontal dimension, or even both. While the latter projection scheme relieves the limitation on the row numbers of the CCD, the spectra of multiple foci are recorded in one spectral channel, resulting in spectral overlapping. Here, we developed a method under a compressive sensing framework to demultiplex the superimposed spectra of multiple cells during their dynamic processes. Unlike the previous methods which ignore the information connection between the spectra of the cells recorded at different time, the proposed method utilizes a prior that a cell’s spectra acquired at different time have the same sparsity structure in their principal components. Rather than independently demultiplexing the mixed spectra at the individual time intervals, the method demultiplexes the whole spectral sequence acquired continuously during the dynamic process. By penalizing the sparsity combined from all time intervals, the collaborative optimization of the inversion problem gave more accurate recovery results. The performances of the method were substantiated by a 1D Raman tweezers array, which monitored the germination of multiple bacterial spores. The method can be extended to the monitoring of many living cells randomly scattering on a coverslip, and has a potential to improve the throughput by a few orders.