2020
DOI: 10.1021/acsnano.0c06104
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Prediction of Cancer Stem Cell Fate by Surface-Enhanced Raman Scattering Functionalized Nanoprobes

Abstract: Cancer stem cells (CSCs) are the fundamental building blocks of cancer dissemination, so it is desirable to develop a technique to predict the behavior of CSCs during tumor initiation and relapse. It will provide a powerful tool for pathological prognosis. Currently, there exists no method of such prediction. Here, we introduce nickel-based functionalized nanoprobe facilitated surface enhanced Raman scattering (SERS) for prediction of cancer dissemination by undertaking CSC-based surveillance. SERS profiling o… Show more

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Cited by 40 publications
(37 citation statements)
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“…Moreover, they can be functionalized for label-free SERS detection of analytes present in trace quantities. 23 3. Reproducibility of SERS Spectra Obtained Using the 3D Ni-NiO Brain Cancer Profiler.…”
Section: Synthesis and Characterization Of The 3d Ni-niomentioning
confidence: 99%
“…Moreover, they can be functionalized for label-free SERS detection of analytes present in trace quantities. 23 3. Reproducibility of SERS Spectra Obtained Using the 3D Ni-NiO Brain Cancer Profiler.…”
Section: Synthesis and Characterization Of The 3d Ni-niomentioning
confidence: 99%
“…zofingiensis-0.5Au were small and isolated, which resulted in relatively weak SERS “hot spots” among the AuNSs, while the AuNPs in C. zofingiensis-1.0Au grew into large AuHNs, leading to a coupled electromagnetic effect that is responsible for a significant SERS activity. , In terms of the SERS substrates applied in complex biological samples, the enhancement effect of AuHNs (9.7 folds) in this study is still compelling compared to other reported nanostructures (Table S3), such as the liquid-state interfacial AuNP array (16 folds) and the nickel-based functionalized nanoprobe (5–7 folds). , Coupled with the rapid sample preparation of intracellular AuHNs, this microalgae-mediated AuHN would be a powerful Raman substrate to monitor the change of microalgal biomass composition.…”
Section: Resultsmentioning
confidence: 71%
“…53,54 In terms of the SERS substrates applied in complex biological samples, the enhancement effect of AuHNs (9.7 folds) in this study is still compelling compared to other reported nanostructures (Table S3), such as the liquid-state interfacial AuNP array (16 folds) and the nickel-based functionalized nanoprobe (5−7 folds). 55,56 Coupled with the rapid sample preparation of intracellular AuHNs, this microalgae-mediated AuHN would be a powerful Raman substrate to monitor the change of microalgal biomass composition.…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…13 SERS has been widely employed to detect the biochemical composition inside the cellular environment for the aim of cell identification. 14 This strategy involves the internalization of plasmonic nanoparticles into cells, which is conventionally achieved by endocytosis. However, in this scenario, nanoparticles are generally trapped in endosomes, and functionalization of nanoparticles surfaces is required to escape the endosome pathway and promote their release into the cytoplasm of target organelles.…”
Section: ■ Introductionmentioning
confidence: 99%
“…To this end, surface-enhanced Raman scattering (SERS) appears to be a promising technique because it provides rich chemical fingerprint information with high chemical sensitivity. The fabrication of a high-quality SERS substrate is crucial for the reproducibility and reliability of SERS experiments, which remains a long-standing bottleneck since its discovery. , Silver (Ag) nanostructures exhibit a high SERS activity due to the superior plasmonic performance from the visible to near-infrared region . SERS has been widely employed to detect the biochemical composition inside the cellular environment for the aim of cell identification . This strategy involves the internalization of plasmonic nanoparticles into cells, which is conventionally achieved by endocytosis.…”
Section: Introductionmentioning
confidence: 99%