| 光谱学与光谱分析 |
|
|
|
|
|
| Fourier Transform Infrared Spectroscopy Combined with Attenuated Total Reflection Applied to Reagent-Free Quantitative Analysis of Thalassemia Screening Indicators |
| LONG Xiao-li1, LIU Gui-song2, XIAO Qing-qing3, CHEN Jie-mei3* |
1. Department of Optoelectronic Engineering, Jinan University, Guangzhou 510632, China
2. Department of Mathematics, Jinan University, Guangzhou 510632, China
3. Department of Biological Engineering, Jinan University, Guangzhou 510632, China |
|
|
|
|
Abstract A simultaneous quantitative analysis method for the thalassemia screening indicators mean corpuscular hemoglobin (MCH), mean corpuscular volume (MCV), and hemoglobin (Hb) was developed with Fourier transform infrared (FTIR) spectrometers and attenuated total reflection (ATR) combined with partial least squares (PLS). A total of 380 human peripheral blood samples were collected, which were composed of 180 positive samples and 200 negative samples according to the criteria of hematological indicator screening for thalassemia. One hundred fifty samples (64 negative, 86 positive) were randomly selected from all samples as the validation set, the remaining 230 samples (136 negative, 94 positive) were used as modeling samples; and then the modeling set was further subdivided into calibration set (68 negative, 47 positive, and 115 in total) and prediction set (68 negative, 47 positive, and 115 in total) for 200 times. Comparison of experimental results show that the prediction effect of PLS models in mid-infrared (MIR) fingerprint region (1 600～900 cm-1) was significantly better those of PLS models in the full scanning region (4 000～600 cm-1), and model complexity is significantly reduced. Based on PLS model in MIR fingerprint region, the optimal numbers of PLS factors for MCH, MCV and Hb were 10, 10 and 6, respectively, and the root mean square error (M_SEPAve) and the correlation coefficient (M_RP, Ave) of prediction in the modeling set were 2.19 pg, 0.902 for MCH, 5.13 fL, 0.898 for MCV and 8.0 g·L-1, 0.922 for Hb, respectively. The root mean square error (V_SEP) and the correlation coefficient (V_RP) of prediction in the validation set were 2.22 pg, 0.900 for MCH, 5.38 fL, 0.895 for MCV and 7.7 g·L-1, 0.929 for Hb, respectively. The sensitivity and specificity for thalassemia screening achieved 100.0% and 95.3%, respectively. Conclusion: FTIR/ATR spectroscopy combined with PLS method could provide a new reagent-free and rapid technique for thalassemia screening for large populations.
|
|
Received: 2014-05-20
Accepted: 2014-07-22
|
|
|
|
Corresponding Authors:
CHEN Jie-mei
E-mail: tchjm@jnu.edu.cn
|
|
[1] Galanello R, Eleftheriou A, Traeger-Synodinos J, et al. Prevention of Thalassaemias and other Haemoglobin Disorders, Vol. 1, Nicosia Cyprus: Team up Creations Ltd, 2003.
[2] Xu X M, Zhou Y Q, Luo G X, et al. Clin. Pathol., 2004, 57(5): 517.
[3] Xiong F, Sun M, Zhang X, et al. Clin. Gene., 2010, 78(2): 139.
[4] Cao A, Rosatelli M C, Monni G, et al. Clin. North. Am., 2002, 29(2): 305.
[5] Langlois S, Ford J C, Chitayat D. J. Obstet. Gynaecol. Can., 2008, 30(10): 950.
[6] Liu K Z, Tsang K S, Li C K. Clin. Chem., 2003, 49(7), 1125.
[7] PENG Li-xin, WANG Gui-wen, YAO Hui-lu(彭立新，王桂文，姚辉璐). Chinese J. Anal. Chem.(分析化学), 2008, 36(10), 1369.
[8] Mirabella F M, Harrick N J. Internal Reflection Spectroscopy: Review and Supplement. New York: Harrick Scientific Corporation, 1985.
[9] Nakanishi K, Hashimoto A, Pan T, et al. Appl. Spectrosc., 2003, 57(12): 1510.
[10] Pan T, Hashimoto A, Kanou M, et al. Bioproc. Biosyst. Eng., 2003, 26(2): 33.
[11] Pan T, Hashimoto A, Kanou M, et al. Jpn. J. Food Eng., 2004, 5(1): 22.
[12] CHEN Jie-mei, PAN Tao, CHEN Xing-dan(陈洁梅, 潘 涛, 陈星旦). Optics and Precision Engineering(光学精密工程), 2006, 14(1): 1.
[13] YIN Hao, PAN Tao, TIAN Pei-ling(尹 浩, 潘 涛, 田佩玲). Chinese Journal of Spectroscopy Laboratory(光谱实验室), 2009, 26(2): 431.
[14] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立, 袁洪福, 陆婉珍). Prog. Chem.(化学进展), 2004, 16(4): 528.
[15] CHU Xiao-li, XU Yu-peng, LU Wan-zhen(褚小立, 许育鹏, 陆婉珍). Chinese J. Anal. Chem.(分析化学), 2008, 36(5): 702.
[16] Chen H Z, Pan T, Chen J M, et al. Chemometr. Intell. Lab., 2011, 107(1): 139.
[17] Pan T, Li M M, Chen J M, et al. Appl. Spectrosc., 2014, 68(3): 263.
[18] Pan T, Chen Z H, Chen J M, et al. Anal. Methods, 2012, 4(4): 1046.
[19] Pan T, Liu J M, Chen J M, et al. Anal. Methods, 2013, 5(4): 4355.
[20] Liu Z Y, Liu B, Pan T, Spectrochim. Acta A, 2013, 102: 269.
[21] XIE Jun, PAN Tao, CHEN Jie-mei(谢 军, 潘 涛, 陈洁梅). Chinese J. Anal. Chem.(分析化学), 2010, 38(3): 342.
[22] PAN Tao, WU Zhen-tao, CHEN Hua-zhou(潘 涛, 吴振涛, 陈华舟). Chinese J. Anal. Chem.(分析化学), 2012, 40(6): 920.
[23] LIU Zhen-yao, PAN Tao(刘振尧, 潘 涛). Optics and Precision Engineering(光学精密工程), 2012, 20(10): 2171. |
| [1] |
GUO Ya-fei1, CAO Qiang1, YE Lei-lei1, ZHANG Cheng-yuan1, KOU Ren-bo1, WANG Jun-mei1, GUO Mei1, 2*. Double Index Sequence Analysis of FTIR and Anti-Inflammatory Spectrum Effect Relationship of Rheum Tanguticum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 188-196. |
| [2] |
LIU Hao-dong1, 2, JIANG Xi-quan1, 2, NIU Hao1, 2, LIU Yu-bo1, LI Hui2, LIU Yuan2, Wei Zhang2, LI Lu-yan1, CHEN Ting1，ZHAO Yan-jie1*，NI Jia-sheng2*. Quantitative Analysis of Ethanol Based on Laser Raman Spectroscopy Normalization Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3820-3825. |
| [3] |
LIN Hong-jian1, ZHAI Juan1*, LAI Wan-chang1, ZENG Chen-hao1, 2, ZHAO Zi-qi1, SHI Jie1, ZHOU Jin-ge1. Determination of Mn, Co, Ni in Ternary Cathode Materials With
Homologous Correction EDXRF Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3436-3444. |
| [4] |
HUANG Li, MA Rui-jun*, CHEN Yu*, CAI Xiang, YAN Zhen-feng, TANG Hao, LI Yan-fen. Experimental Study on Rapid Detection of Various Organophosphorus Pesticides in Water by UV-Vis Spectroscopy and Parallel Factor Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3452-3460. |
| [5] |
LI Zhong-bing1, 2, JIANG Chuan-dong2, LIANG Hai-bo3, DUAN Hong-ming2, PANG Wei2. Rough and Fine Selection Strategy Binary Gray Wolf Optimization
Algorithm for Infrared Spectral Feature Selection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3067-3074. |
| [6] |
LIU Shu1, JIN Yue1, 2, SU Piao1, 2, MIN Hong1, AN Ya-rui2, WU Xiao-hong1*. Determination of Calcium, Magnesium, Aluminium and Silicon Content in Iron Ore Using Laser-Induced Breakdown Spectroscopy Assisted by Variable Importance-Back Propagation Artificial Neural Networks[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3132-3142. |
| [7] |
TIAN Ze-qi1, WANG Zhi-yong1, YAO Jian-guo1, GUO Xu1, LI Hong-dou1, GUO Wen-mu1, SHI Zhi-xiang2, ZHAO Cun-liang1, LIU Bang-jun1*. Quantitative FTIR Characterization of Chemical Structures of Highly Metamorphic Coals in a Magma Contact Zone[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2747-2754. |
| [8] |
KONG De-ming1, LIU Ya-ru1, DU Ya-xin2, CUI Yao-yao2. Oil Film Thickness Detection Based on IRF-IVSO Wavelength Optimization Combined With LIF Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2811-2817. |
| [9] |
ZHANG Xiao-xu1, LIN Xiao-xian3, ZHANG Dan2, ZHANG Qi1, YIN Xue-feng2, YIN Jia-lu3, 4, ZHANG Wei-yue4, LI Yi-xuan1, WANG Dong-liang3, 4*, SUN Ya-nan1*. Study on the Analysis of the Relationship Between Functional Factors and Intestinal Flora in Freshly Stewed Bird's Nest Based on Fourier Transform Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2452-2457. |
| [10] |
CHENG Xiao-xiang1, WU Na2, LIU Wei2*, WANG Ke-qing2, LI Chen-yuan1, CHEN Kun-long1, LI Yan-xiang1*. Research on Quantitative Model of Corrosion Products of Iron Artefacts Based on Raman Spectroscopic Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2166-2173. |
| [11] |
WANG Yu-hao1, 2, LIU Jian-guo1, 2, XU Liang2*, DENG Ya-song2, SHEN Xian-chun2, SUN Yong-feng2, XU Han-yang2. Application of Principal Component Analysis in Processing of Time-Resolved Infrared Spectra of Greenhouse Gases[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2313-2318. |
| [12] |
ZHAO Yu-wen1, ZHANG Ze-shuai1, ZHU Xiao-ying1, WANG Hai-xia1, 2*, LI Zheng1, 2, LU Hong-wei3, XI Meng3. Application Strategies of Surface-Enhanced Raman Spectroscopy in Simultaneous Detection of Multiple Pathogens[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2012-2018. |
| [13] |
CHEN Rui1, WANG Xue1, 2*, WANG Zi-wen1, QU Hao1, MA Tie-min1, CHEN Zheng-guang1, GAO Rui3. Wavelength Selection Method of Near-Infrared Spectrum Based on
Random Forest Feature Importance and Interval Partial
Least Square Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1043-1050. |
| [14] |
DENG Xiao-jun1, 2, MA Jin-ge1, YANG Qiao-ling3, SHI Yi-yin1, HUO Yi-hui1, GU Shu-qing1, GUO De-hua1, DING Tao4, YU Yong-ai5, ZHANG Feng6. Visualized Fast Identification Method of Imported Olive Oil Quality Grade Based on Raman-UV-Visible Fusion Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1117-1125. |
| [15] |
SU Ling1, 2, BU Ya-ping1, 2, LI Yuan-yuan2, WANG Qi1, 2*. Study on the Prediction Method of Pleurotus Ostreatus Protein and
Polysaccharide Content Based on Fourier Transform Infrared
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1262-1267. |
|
|
|
|
