Facile PEG-based isolation and classification of cancer extracellular vesicles and particles with label-free surface-enhanced Raman scattering and pattern recognition algorithm

Yin, Pengju; Li, Guoqian; Zhang, Baoyue; Haque, Farjana; Zhao, Lei; Qin, Hongwei; Hu, Bo; Ou, Jian Zhen; Tian, Jie

doi:10.1039/d0an02257h

Cited by 15 publications

(17 citation statements)

References 34 publications

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“…Among them, the localized manipulation of d-electron states is the major factor for transition MOXs to achieve abundant high free electron concentration and mobility to generate plasmon resonances in the visible and near-infrared regions ( Alsaif et al., 2021 ). In addition, similar plasmonic properties have appeared in 2D amorphous MoO 3 quantum dots and are expected to be used for Raman spectroscopy detection ( Alsaif et al., 2016 ; Ge et al., 2021 ; Guo et al., 2019 ; Li et al., 2018 ; Liu and Xu, 2018 ; Ren et al., 2019 ; Yin et al., 2021 ; Shangguan et al., 2021 ). Further, it has been proved that 2D heterostructures, constructed from vdW stacking (2D vertical heterostructures) or edge covalent bonding (2D lateral heterostructures) of different 2D materials, can not only address the problem of insufficient performance of a single 2D material in applications such as photodetectors and gas sensing but also generate many peculiar properties through the synergistic advantages of individual 2D materials.…”

Section: Basics Of 2d Metal Oxidesmentioning

confidence: 87%

Recent advances in the fabrication of 2D metal oxides

et al. 2022

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Summary Atomically thin two-dimensional (2D) metal oxides exhibit unique optical, electrical, magnetic, and chemical properties, rendering them a bright application prospect in high-performance smart devices. Given the large variety of both layered and non-layered 2D metal oxides, the controllable synthesis is the critical prerequisite for enabling the exploration of their great potentials. In this review, recent progress in the synthesis of 2D metal oxides is summarized and categorized. Particularly, a brief overview of categories and crystal structures of 2D metal oxides is firstly introduced, followed by a critical discussion of various synthesis methods regarding the growth mechanisms, advantages, and limitations. Finally, the existing challenges are presented to provide possible future research directions regarding the synthesis of 2D metal oxides. This work can provide useful guidance on developing innovative approaches for producing both 2D layered and non-layered nanostructures and assist with the acceleration of the research of 2D metal oxides.

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Section: Basics Of 2d Metal Oxidesmentioning

confidence: 87%

Recent advances in the fabrication of 2D metal oxides

et al. 2022

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“…This is specifically useful in clinical cases, where diagnostic criteria or biomarkers are known, and the objective is to have a predictive model. Supervised ML models for EVs analysis has been used for the detection of cancers [ 176 , 204 , 255 , 259 ] and neurodegenerative diseases [ 248 ].…”

Section: Discussionmentioning

confidence: 99%

“…Unsupervised ML algorithms are not trained on prelabeled datasets and therefore must interpret data patterns on their own. Clustering and PCA are examples of unsupervised ML that are used in EVs research [ 156 , 64 , 157 , 168 , 176 , 204 ]. The interesting aspect of unsupervised learning is the potential to discover previously unknown underlying patterns within datasets that the algorithms have identified without human input.…”

Section: Discussionmentioning

confidence: 99%

“…Yin and co-authors proposed a new isolation method for cancer cell-derived EVs and a new label-free SERS substrate [ 176 ]. Specifically, they used a PEG-based method to isolate the EVs by simply incubating a PEG solution with conditioned media for 24 h at 4 °C and centrifuging the mixture for 15 min at 3000 g. Three types of male cancer cell lines COLO-205 (colorectal cancer), THP-1 (leukemia), and DU-145 (prostate cancer), and healthy male blood samples were selected for EVs isolation.…”

Section: Characterization Of Evs Molecular Contentmentioning

confidence: 99%

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Recent advances in optical label-free characterization of extracellular vesicles

et al. 2022

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Extracellular vesicles (EVs) are complex biological nanoparticles endogenously secreted by all eukaryotic cells. EVs carry a specific molecular cargo of proteins, lipids, and nucleic acids derived from cells of origin and play a significant role in the physiology and pathology of cells, organs, and organisms. Upon release, they may be found in different body fluids that can be easily accessed via noninvasive methodologies. Due to the unique information encoded in their molecular cargo, they may reflect the state of the parent cell and therefore EVs are recognized as a rich source of biomarkers for early diagnostics involving liquid biopsy. However, body fluids contain a mixture of EVs released by different types of healthy and diseased cells, making the detection of the EVs of interest very challenging. Recent research efforts have been focused on the detection and characterization of diagnostically relevant subpopulations of EVs, with emphasis on label-free methods that simplify sample preparation and are free of interfering signals. Therefore, in this paper, we review the recent progress of the label-free optical methods employed for the detection, counting, and morphological and chemical characterization of EVs. We will first briefly discuss the biology and functions of EVs, and then introduce different optical label-free techniques for rapid, precise, and nondestructive characterization of EVs such as nanoparticle tracking analysis, dynamic light scattering, atomic force microscopy, surface plasmon resonance spectroscopy, Raman spectroscopy, and SERS spectroscopy. In the end, we will discuss their applications in the detection of neurodegenerative diseases and cancer and provide an outlook on the future impact and challenges of these technologies to the field of liquid biopsy via EVs.

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“…Plasmonic materials have been employed to boost the Raman technique’s sensitivity. Pengju and colleagues utilized a calculation based on ML to classify the ordinary and extracellular cancer vesicles and parties [ 238 ].…”

Section: Nlo Processes Analyzed With MLmentioning

confidence: 99%

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

et al. 2022

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The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

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Facile PEG-based isolation and classification of cancer extracellular vesicles and particles with label-free surface-enhanced Raman scattering and pattern recognition algorithm

Abstract: Extracellular vesicles and particles (EVPs), which contain the same surface proteins as their mother cells, are promising biomarkers for cancer liquid biopsy.

Cited by 15 publications

References 34 publications

Recent advances in the fabrication of 2D metal oxides

Recent advances in the fabrication of 2D metal oxides

Recent advances in optical label-free characterization of extracellular vesicles

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

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