Raman Spectral Characterization of Urine for Rapid Diagnosis of Acute Kidney Injury

被引:8
作者
Jeng, Ming-Jer [1 ,2 ,3 ]
Sharma, Mukta [1 ]
Lee, Cheng-Chia [2 ]
Lu, Yu-Sheng [1 ]
Tsai, Chia-Lung [1 ,2 ,3 ]
Chang, Chih-Hsiang [2 ]
Chen, Shao-Wei [4 ]
Lin, Ray-Ming [1 ]
Chang, Liann-Be [1 ,3 ]
机构
[1] Chang Gung Univ, Dept Elect Engn, Taoyuan 333, Taiwan
[2] Change Gung Mem Hosp, Kidney Res Ctr, Dept Nephrol, Linkou Branch, Taoyuan 244, Taiwan
[3] Chang Gung Univ, Green Technol Res Ctr, Taoyuan 333, Taiwan
[4] Chang Gung Mem Hosp, Dept Cardiothorac & Vasc Surg, Linkou Branch, Taoyuan 244, Taiwan
关键词
acute kidney injury; Raman spectroscopy; partial least squares; linear discriminant analysis; urine; SPECTROSCOPY;
D O I
10.3390/jcm11164829
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Acute kidney injury (AKI) is a common syndrome characterized by various etiologies and pathophysiologic processes that deteriorate kidney function. The aim of this study is to identify potential biomarkers in the urine of non-acute kidney injury (non-AKI) and AKI patients through Raman spectroscopy (RS) to predict the advancement in complications and kidney failure. Selected spectral regions containing prominent peaks of renal biomarkers were subjected to partial least squares linear discriminant analysis (PLS-LDA). This discriminant analysis classified the AKI patients from non-AKI subjects with a sensitivity and specificity of 97% and 100%, respectively. In this study, the RS measurements of urine specimens demonstrated that AKI had significantly higher nitrogenous compounds, porphyrin, tryptophan and neopterin when compared with non-AKI. This study's specific spectral information can be used to design an in vivo RS approach for the detection of AKI diseases.
引用
收藏
页数:9
相关论文
共 29 条
[11]   Multiclass classification of autofluorescence images of oral cavity lesions based on quantitative analysis [J].
Jeng, Ming-Jer ;
Sharma, Mukta ;
Chao, Ting-Yu ;
Li, Ying-Chang ;
Huang, Shiang-Fu ;
Chang, Liann-Be ;
Chow, Lee .
PLOS ONE, 2020, 15 (02)
[12]   Raman Spectroscopy Analysis for Optical Diagnosis of Oral Cancer Detection [J].
Jeng, Ming-Jer ;
Sharma, Mukta ;
Sharma, Lokesh ;
Chao, Ting-Yu ;
Huang, Shiang-Fu ;
Chang, Liann-Be ;
Wu, Shih-Lin ;
Chow, Lee .
JOURNAL OF CLINICAL MEDICINE, 2019, 8 (09)
[13]  
Laposata M., 2014, CLIN LAB REFERENCE V
[14]   Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps [J].
Lee, Loong Chuen ;
Liong, Choong-Yeun ;
Jemain, Abdul Aziz .
ANALYST, 2018, 143 (15) :3526-3539
[15]   Dual-Modality Detection of Early-Stage Drug-Induced Acute Kidney Injury by an Activatable Probe [J].
Liu, Lingyan ;
Jiang, Liping ;
Yuan, Wei ;
Liu, Zhongkuan ;
Liu, Dongya ;
Wei, Peng ;
Zhang, Xinyu ;
Yi, Tao .
ACS SENSORS, 2020, 5 (08) :2457-2466
[16]   Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models [J].
Liu, Wenjing ;
Sun, Zhaotian ;
Chen, Jinyu ;
Jing, Chuanbo .
JOURNAL OF SPECTROSCOPY, 2016, 2016
[17]   Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis [J].
Martins Bispo, Jeyse Aliana ;
de Sousa Vieira, Elzo Everton ;
Silveira, Landulfo, Jr. ;
Fernandes, Adriana Barrinha .
JOURNAL OF BIOMEDICAL OPTICS, 2013, 18 (08)
[18]   Use of ATR-FTIR for detection of Salmonella typhi infection in human blood sera [J].
Naseer, Khulla ;
Ali, Salmann ;
Mubarik, Sumaira ;
Hussain, Syed Zajif ;
Qazi, Javaria .
INFRARED PHYSICS & TECHNOLOGY, 2020, 110
[19]   Urine analysis by laser Raman spectroscopy [J].
Premasiri, WR ;
Clarke, RH ;
Womble, ME .
LASERS IN SURGERY AND MEDICINE, 2001, 28 (04) :330-334
[20]   Biofluid analysis and classification using IR and 2D-IR spectroscopy [J].
Rutherford, Samantha H. ;
Nordon, Alison ;
Hunt, Neil T. ;
Baker, Matthew J. .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2021, 217