Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy
We aimed to identify the browning of white adipocytes using partial least squares regression (PLSR), infrared spectral biomarkers, and partial least squares discriminant analysis (PLS-DA) with FTIR spectroscopy instead of molecular biology. PLSR helps distinguish human beige adipocytes treated with...
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MDPI AG
2022-12-01
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| Series: | Photonics |
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| Online Access: | https://www.mdpi.com/2304-6732/10/1/2 |
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| author | Dong-Hyun Shon Se-Jun Park Suk-Jun Yoon Yang-Hwan Ryu Yong Ko |
| author_facet | Dong-Hyun Shon Se-Jun Park Suk-Jun Yoon Yang-Hwan Ryu Yong Ko |
| author_sort | Dong-Hyun Shon |
| collection | DOAJ |
| description | We aimed to identify the browning of white adipocytes using partial least squares regression (PLSR), infrared spectral biomarkers, and partial least squares discriminant analysis (PLS-DA) with FTIR spectroscopy instead of molecular biology. PLSR helps distinguish human beige adipocytes treated with norepinephrine and rosiglitazone. When PLSR was based on the selected regions of 3997–3656 and 1618–938 cm<sup>−1</sup>, PLSR achieved an R<sup>2</sup> of cross-validation of 88.95, a root mean square error of cross validation (RMSECV) of 2.13, and a ratio performance deviation (RPD) of 3.01. Infrared spectral biomarkers [1635 cm<sup>−1</sup> (β-sheet amide I), 879–882, 860–3 cm<sup>−1</sup> (A-form helix), and 629–38 cm<sup>−1</sup> (OH out-of-plane bending)] were identified in human beige adipocytes based on spectral differences between human beige adipocytes and human white adipocytes, principal component analysis-linear discriminant analysis (PCA-LDA) cluster vector, U-test, and Fisher’s score per wavenumber. PLS-DA yielded a useful classification of adipocytes and expression distribution of adipogenesis genes in adipocytes. PLSR, infrared spectral biomarkers, and PLS-DA using FTIR spectroscopy are proposed as effective tools for identifying specific biological activities in a limited environment through features that do not require labeling and are relatively inexpensive in terms of time and labor. |
| first_indexed | 2024-03-09T11:26:28Z |
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| id | doaj.art-45c7691c0f8348c28c1228288027998e |
| institution | Directory Open Access Journal |
| issn | 2304-6732 |
| language | English |
| last_indexed | 2024-03-09T11:26:28Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
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| series | Photonics |
| spelling | doaj.art-45c7691c0f8348c28c1228288027998e2023-12-01T00:00:47ZengMDPI AGPhotonics2304-67322022-12-01101210.3390/photonics10010002Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR SpectroscopyDong-Hyun Shon0Se-Jun Park1Suk-Jun Yoon2Yang-Hwan Ryu3Yong Ko4Division of Biotechnology, College of Life Sciences & Biotechnology, Korea University, Seoul 02841, Republic of KoreaDivision of Biotechnology, College of Life Sciences & Biotechnology, Korea University, Seoul 02841, Republic of KoreaR&D Department, NMS LAB, Anyang-si 14001, Republic of KoreaDivision of Biotechnology, College of Life Sciences & Biotechnology, Korea University, Seoul 02841, Republic of KoreaDivision of Biotechnology, College of Life Sciences & Biotechnology, Korea University, Seoul 02841, Republic of KoreaWe aimed to identify the browning of white adipocytes using partial least squares regression (PLSR), infrared spectral biomarkers, and partial least squares discriminant analysis (PLS-DA) with FTIR spectroscopy instead of molecular biology. PLSR helps distinguish human beige adipocytes treated with norepinephrine and rosiglitazone. When PLSR was based on the selected regions of 3997–3656 and 1618–938 cm<sup>−1</sup>, PLSR achieved an R<sup>2</sup> of cross-validation of 88.95, a root mean square error of cross validation (RMSECV) of 2.13, and a ratio performance deviation (RPD) of 3.01. Infrared spectral biomarkers [1635 cm<sup>−1</sup> (β-sheet amide I), 879–882, 860–3 cm<sup>−1</sup> (A-form helix), and 629–38 cm<sup>−1</sup> (OH out-of-plane bending)] were identified in human beige adipocytes based on spectral differences between human beige adipocytes and human white adipocytes, principal component analysis-linear discriminant analysis (PCA-LDA) cluster vector, U-test, and Fisher’s score per wavenumber. PLS-DA yielded a useful classification of adipocytes and expression distribution of adipogenesis genes in adipocytes. PLSR, infrared spectral biomarkers, and PLS-DA using FTIR spectroscopy are proposed as effective tools for identifying specific biological activities in a limited environment through features that do not require labeling and are relatively inexpensive in terms of time and labor.https://www.mdpi.com/2304-6732/10/1/2FTIRbrowningbeige adipocytesobesityPLSRinfrared spectral biomarker |
| spellingShingle | Dong-Hyun Shon Se-Jun Park Suk-Jun Yoon Yang-Hwan Ryu Yong Ko Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy Photonics FTIR browning beige adipocytes obesity PLSR infrared spectral biomarker |
| title | Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy |
| title_full | Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy |
| title_fullStr | Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy |
| title_full_unstemmed | Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy |
| title_short | Identification of Browning in Human Adipocytes by Partial Least Squares Regression (PLSR), Infrared Spectral Biomarkers, and Partial Least Squares Discriminant Analysis (PLS-DA) Using FTIR Spectroscopy |
| title_sort | identification of browning in human adipocytes by partial least squares regression plsr infrared spectral biomarkers and partial least squares discriminant analysis pls da using ftir spectroscopy |
| topic | FTIR browning beige adipocytes obesity PLSR infrared spectral biomarker |
| url | https://www.mdpi.com/2304-6732/10/1/2 |
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