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Pang W, Xing Y, Morais CLM, Lao Q, Li S, Qiao Z, Li Y, Singh MN, Barauna VG, Martin FL, Zhang Z. Serum-based ATR-FTIR spectroscopy combined with multivariate analysis for the diagnosis of pre-diabetes and diabetes. Analyst 2024; 149:497-506. [PMID: 38063458 DOI: 10.1039/d3an01519j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2024]
Abstract
Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance.
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Affiliation(s)
- Weiyi Pang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
- School of Humanities and Management, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Yu Xing
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Camilo L M Morais
- Center for Education, Science and Technology of the Inhamuns Region, State University of Ceará, Tauá 63660-000, Brazil
| | - Qiufeng Lao
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Shengle Li
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Zipeng Qiao
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - You Li
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
| | - Maneesh N Singh
- Biocel UK Ltd, Hull HU10 6TS, UK.
- Chesterfield Royal Hospital, Chesterfield Road, Calow, Chesterfield S44 5BL, UK
| | - Valério G Barauna
- Department of Physiological Sciences, Federal University of Espírito Santo, Vitoria, Brazil
| | - Francis L Martin
- Biocel UK Ltd, Hull HU10 6TS, UK.
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Whinney Heys Road, Blackpool FY3 8NR, UK
| | - Zhiyong Zhang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Heath, Guilin Medical University, Guilin, 541199, Guangxi, China.
- School of Public Health, Guilin Medical University, Guilin, 541199, Guangxi, China
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Dawuti W, Dou J, Zheng X, Lü X, Zhao H, Yang L, Lin R, Lü G. Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier-transform infrared spectroscopy combined with machine learning algorithms. JOURNAL OF BIOPHOTONICS 2023; 16:e202200320. [PMID: 36707914 DOI: 10.1002/jbio.202200320] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 01/20/2023] [Accepted: 01/25/2023] [Indexed: 05/17/2023]
Abstract
Cystic echinococcosis (CE) in sheep is a serious zoonotic parasitic disease caused by Echinococcus granulosus sensu stricto (s.s.). Presently, the screening technology for CE in sheep is time-consuming and inaccurate, and novel screening technology is urgently needed. In this work, we combined machine-learning algorithms with Fourier transform infrared (FT-IR) spectroscopy of serum to establish a quick and accurate screening approach for CE in sheep. Serum samples from 77 E. granulosus s.s.-infected sheep to 121 healthy control sheep were measured by FT-IR spectrometer. To optimize the classification accuracy of the serum FI-TR method for the E. granulosus s.s.-infected sheep and healthy control sheep, principal component analysis (PCA), linear discriminant analysis, and support vector machine (SVM) algorithms were used to analyze the data. Among all the bands, 1500-1700 cm-1 band has the best classification effect; its diagnostic sensitivity, specificity, and accuracy of PCA-SVM were 100%, 95.74%, and 96.66%, respectively. The study showed that serum FT-IR spectroscopy combined with machine learning algorithms has great potential for rapid and accurate screening methods for the CE in sheep.
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Affiliation(s)
- Wubulitalifu Dawuti
- School of Public Health, Xinjiang Medical University, Urumqi, China
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Jingrui Dou
- School of Public Health, Xinjiang Medical University, Urumqi, China
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Xiangxiang Zheng
- School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China
| | - Xiaoyi Lü
- College of Software, Xinjiang University, Urumqi, China
| | - Hui Zhao
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Lingfei Yang
- Department of Abdominal Ultrasound Diagnosis, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Renyong Lin
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Guodong Lü
- School of Public Health, Xinjiang Medical University, Urumqi, China
- State Key Laboratory of Pathogenesis, Prevention, and Treatment of Central Asian High Incidence Diseases, Clinical Medical Research Institute, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
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