Literature DB >> 23037364

Comparison of principal component analysis and biochemical component analysis in Raman spectroscopy for the discrimination of apoptosis and necrosis in K562 leukemia cells.

Yi Hong Ong1, Mayasari Lim, Quan Liu.   

Abstract

Raman spectroscopy has been explored as a promising label-free technique in discriminating apoptosis and necrosis induced cell death in leukemia cells. In addition to Principal component analysis (PCA) as commonly employed in Raman data analysis, another less commonly used but powerful method is Biochemical Component Analysis (BCA). In BCA, a Raman spectrum is decomposed into the contributions from several known basic biochemical components, such as proteins, lipid, nucleic acids and glycogen groups etc. The differences in terms of classification accuracy and interpretability of resulting data between these two methods in Raman spectroscopy have not been systematically investigated to our knowledge. In this study, we utilized both methods to analyze the Raman spectra measured from live cells, apoptotic and necrotic leukemia cells. The comparison indicates that two methods yield comparable accuracy in sample classification when the numbers of basic components are equal. The changes in the contributions of biochemical components in BCA can be interpreted by cell biology principles in apoptosis and necrosis. In contrast, the contributions of most principle components in PCA are difficult to interpret except the first one. The capability of BCA to unveil fine biochemical changes in cell spectra and excellent accuracy in classification can impel the broad application of Raman spectroscopy in biological research.

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Year:  2012        PMID: 23037364     DOI: 10.1364/OE.20.022158

Source DB:  PubMed          Journal:  Opt Express        ISSN: 1094-4087            Impact factor:   3.894


  34 in total

1.  Quantitative Raman spectral changes of the differentiation of mesenchymal stem cells into islet-like cells by biochemical component analysis and multiple peak fitting.

Authors:  Xin Su; Shaoyin Fang; Daosen Zhang; Qinnan Zhang; Yingtian He; Xiaoxu Lu; Shengde Liu; Liyun Zhong
Journal:  J Biomed Opt       Date:  2015       Impact factor: 3.170

2.  Development of a classification model for non-alcoholic steatohepatitis (NASH) using confocal Raman micro-spectroscopy.

Authors:  Jie Yan; Yang Yu; Jeon Woong Kang; Zhi Yang Tam; Shuoyu Xu; Eliza Li Shan Fong; Surya Pratap Singh; Ziwei Song; Lisa Tucker-Kellogg; Peter T C So; Hanry Yu
Journal:  J Biophotonics       Date:  2017-06-21       Impact factor: 3.207

3.  An Expandable Mechanopharmaceutical Device (3): a Versatile Raman Spectral Cytometry Approach to Study the Drug Cargo Capacity of Individual Macrophages.

Authors:  Vernon LaLone; Márcio A Mourão; Theodore J Standiford; Krishnan Raghavendran; Kerby Shedden; Kathleen A Stringer; Gus R Rosania
Journal:  Pharm Res       Date:  2018-11-06       Impact factor: 4.200

4.  Beneficial effects of cerium oxide nanoparticles in development of chondrocyte-seeded hydrogel constructs and cellular response to interleukin insults.

Authors:  Sathish Ponnurangam; Grace D O'Connell; Irina V Chernyshova; Katherine Wood; Clark Tung-Hui Hung; Ponisseril Somasundaran
Journal:  Tissue Eng Part A       Date:  2014-06-25       Impact factor: 3.845

5.  Optimization of advanced Wiener estimation methods for Raman reconstruction from narrow-band measurements in the presence of fluorescence background.

Authors:  Shuo Chen; Yi Hong Ong; Xiaoqian Lin; Quan Liu
Journal:  Biomed Opt Express       Date:  2015-06-19       Impact factor: 3.732

6.  Macromolecular Profiling of Organelles in Normal Diploid and Cancer Cells.

Authors:  Svitlana M Levchenko; Andrey N Kuzmin; Artem Pliss; Junle Qu; Paras N Prasad
Journal:  Anal Chem       Date:  2017-09-26       Impact factor: 6.986

7.  Surface-enhanced Raman scattering analysis of urine from deceased donors as a prognostic tool for kidney transplant outcome.

Authors:  Jingmao Chi; Yiwei Ma; Francis L Weng; Heather Thiessen-Philbrook; Chirag R Parikh; Henry Du
Journal:  J Biophotonics       Date:  2017-05-09       Impact factor: 3.207

8.  Denoising Raman spectra by Wiener estimation with a numerical calibration dataset.

Authors:  Yanru Bai; Quan Liu
Journal:  Biomed Opt Express       Date:  2019-12-10       Impact factor: 3.732

9.  Depth-sensitive Raman spectroscopy for skin wound evaluation in rodents.

Authors:  Joshua Weiming Su; Qiang Wang; Yao Tian; Leigh Madden; Erica Mei Ling Teo; David Laurence Becker; Quan Liu
Journal:  Biomed Opt Express       Date:  2019-11-06       Impact factor: 3.732

10.  Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

Authors:  Petru Manescu; Young Jong Lee; Charles Camp; Marcus Cicerone; Mary Brady; Peter Bajcsy
Journal:  Med Image Anal       Date:  2017-01-06       Impact factor: 8.545

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