Characterization and discrimination of human colorectal cancer cells using terahertz spectroscopy

Cao, Yuqi; Chen, Jiani; Zhang, Guangxin; Fan, Shuyu; Ge, Weiting; Hu, Wangxiong; Huang, Pingjie; Hou, Dibo; Zheng, Shu Li

doi:10.1016/j.saa.2021.119713

Cited by 25 publications

(14 citation statements)

References 28 publications

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“…The category classes were: Gram-positive bacteria (including S. epidermidis , E. faecalis , S. aureus , S. pneumoniae , B. cereus , B. thuringiensis , and B. subtilis ), Gram-negative bacteria (including E. coli and P. aeruginosa ), and fungi (including C. albicans , C. tropicalis , and C. glabrata ). As expected, although a few bacterial species can be identified by the variation in hydration state that was associated with the THz absorption coefficients, it is difficult to accurately identify microorganisms solely by their THz absorption due to the possibility of potentially similar hydration states as the number of sampled species increases [ 23 ].…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…A previous study demonstrated that the use of principal component analysis (PCA) and random forest (RF) classifiers was helpful in the analysis of THz-ATR spectra for extracting features of human colorectal cancer cell lines [ 23 ]. The results indicate that the absorption coefficient is the most sensitive parameter for cancer cell discrimination [ 23 ]. In addition, the literature reveals that THz-ATR spectroscopy, integrated with PCA and quadratic discriminant analysis (QDA), can be used to identify DNA oligonucleotides with single-base mutations [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

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THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

Shi

Huang

et al. 2022

Biosensors

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The demand for rapid and accurate identification of microorganisms is growing due to considerable importance in all areas related to public health and safety. Here, we demonstrate a rapid and label-free strategy for the identification of microorganisms by integrating terahertz-attenuated total reflection (THz-ATR) spectroscopy with an automated recognition method based on multi-classifier voting. Our results show that 13 standard microbial strains can be classified into three different groups of microorganisms (Gram-positive bacteria, Gram-negative bacteria, and fungi) by THz-ATR spectroscopy. To detect clinical microbial strains with better differentiation that accounts for their greater sample heterogeneity, an automated recognition algorithm is proposed based on multi-classifier voting. It uses three types of machine learning classifiers to identify five different groups of clinical microbial strains. The results demonstrate that common microorganisms, once time-consuming to distinguish by traditional microbial identification methods, can be rapidly and accurately recognized using THz-ATR spectra in minutes. The proposed automatic recognition method is optimized by a spectroscopic feature selection algorithm designed to identify the optimal diagnostic indicator, and the combination of different machine learning classifiers with a voting scheme. The total diagnostic accuracy reaches 80.77% (as high as 99.6% for Enterococcus faecalis) for 1123 isolates from clinical samples of sputum, blood, urine, and feces. This strategy demonstrates that THz spectroscopy integrated with an automatic recognition method based on multi-classifier voting significantly improves the accuracy of spectral analysis, thereby presenting a new method for true label-free identification of clinical microorganisms with high efficiency.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

Shi

Huang

et al. 2022

Biosensors

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“…Recently, we described a plasmonic system based on a nanohole array biosensor to discriminate live single cancer cells from normal cells [ 23 ]. Other techniques, including confocal refractive index microscopy, terahertz spectroscopy and quantitative phase imaging [ 24 , 25 , 26 ], have been used for label-free imaging of living cells or cell-derived structures. The confocal imaging techniques have an advantage in investigating whole cells, which is due to their larger propagation depth, when there are no specific subcellular structures to target.…”

Section: Introductionmentioning

confidence: 99%

Plasmonic Biosensing for Label-Free Detection of Two Hallmarks of Cancer Cells: Cell-Matrix Interaction and Cell Division

et al. 2022

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Two key features of cancer cells are sustained proliferation and invasion, which is preceded by a modification of the adhesion properties to the extracellular matrix. Currently, fluorescence-based techniques are mainly used to detect these processes, including flow cytometry and fluorescence resonance energy transfer (FRET) microscopy. We have previously described a simple, fast and label-free method based on a gold nanohole array biosensor to detect the spectral response of single cells, which is highly dependent on the actin cortex. Here we used this biosensor to study two cellular processes where configuration of the actin cortex plays an essential role: cell cycle and cell–matrix adhesion. Colorectal cancer cells were maintained in culture under different conditions to obtain cells stopped either in G0/G1 (resting cells/cells at the initial steps of cell growth) or G2 (cells undergoing division) phases of the cell cycle. Data from the nanohole array biosensor showed an ability to discriminate between both cell populations. Additionally, cancer cells were monitored with the biosensor during the first 60 min after cells were deposited onto a biosensor coated with fibronectin, an extracellular matrix protein. Spectral changes were detected in the first 20 min and increased over time as the cell–biosensor contact surface increased. Our data show that the nanohole array biosensor provides a label-free and real-time procedure to detect cells undergoing division or changes in cell–matrix interaction in both clinical and research settings.

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“…What's more, many molecules have strong rotational and vibrational absorption features at THz frequencies, leading to spectroscopic fingerprinting in the THz range [3]. Rapid developments in terahertz technologies, such as sources and detectors, have promoted various applications in sensing [4,5], non-destructive imaging [6] and spectroscopy [7]. However, water vapor and other gas molecules during transmission process could lead to severe absorptions, which limit the applications of terahertz technology.…”

Section: Introductionmentioning

confidence: 99%

Spatially, Spectrally Single-Mode and Mechanically Flexible 3D-Printed Terahertz Transmission Waveguides

Chen

Wei

et al. 2022

IEEE Photonics J.

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Emerged terahertz transmission waveguides or fibers will enable novel terahertz systems and applications. Highquality output beam profiles, mechanical flexibility and reliability are among the most crucial and challenging characteristics of terahertz transmission waveguides. Here, we design and fabricate the flexible and stretchable transmission waveguides by 3D printing to guide radiation from terahertz (THz) quantum cascade lasers (QCLs) lasing at the frequency of 2.58 THz. Composite silver nanoparticles and polydimethylsiloxane are coated on the inner surface of the 3D-printed polycarbonate/rubber substrate tube. Output beam profiles from the transmission waveguides, which are captured by a room-temperature terahertz camera, demonstrate single-mode spatial intensity distribution. Transmission spectra are measured out from the waveguides and single-mode characteristics of THz QCLs are preserved from threshold to peak bias. More than 300 times of bending and forcestrain curves are tested for the 3D-printed flexible terahertz transmission waveguides, the propagation losses exhibit no obvious change, demonstrating a superior mechanical endurance.

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Characterization and discrimination of human colorectal cancer cells using terahertz spectroscopy

Cited by 25 publications

References 28 publications

THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

THz-ATR Spectroscopy Integrated with Species Recognition Based on Multi-Classifier Voting for Automated Clinical Microbial Identification

Plasmonic Biosensing for Label-Free Detection of Two Hallmarks of Cancer Cells: Cell-Matrix Interaction and Cell Division

Spatially, Spectrally Single-Mode and Mechanically Flexible 3D-Printed Terahertz Transmission Waveguides

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