期刊
BIOSENSORS-BASEL
卷 12, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/bios12100875
关键词
Ag nanowire; cell culture model; SERS; machine learning; spatial resolution
资金
- National Key R&D Program of China [2017YFA0700500]
- National Natural Science Foundation of China [21874068, 22174060]
In this study, we used silver nanowires to extract SERS spectra in situ from cell culture models and applied machine learning algorithm for analysis. The results showed significant differences in protein abundance between 2D and 3D models, and nucleic acid-rich and protein-rich regions can be accurately distinguished.
Establishing a systematic molecular information analysis strategy for cell culture models is of great significance for drug development and tissue engineering technologies. Here, we fabricated single silver nanowires with high surface-enhanced Raman scattering activity to extract SERS spectra in situ from two-dimensional (2D) and three-dimensional (3D) cell culture models. The silver nanowires were super long, flexible and thin enough to penetrate through multiple cells. A single silver nanowire was used in combination with a four-dimensional microcontroller as a cell endoscope for spectrally analyzing the components in cell culture models. Then, we adopted a machine learning algorithm to analyze the obtained spectra. Our results show that the abundance of proteins differs significantly between the 2D and 3D models, and that nucleic acid-rich and protein-rich regions can be distinguished with satisfactory accuracy.
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