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Nazeer SS, Venkataraman RK, Jayasree RS, Bayry J. Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check. Anal Chem 2024; 96:957-965. [PMID: 38164878 DOI: 10.1021/acs.analchem.3c02590] [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: 01/03/2024]
Abstract
Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.
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Affiliation(s)
- Shaiju S Nazeer
- Department of Chemistry, Indian Institute of Space Sciences and Technology, Thiruvananthapuram, Kerala 695547, India
| | - Ravi Kumar Venkataraman
- Ultrafast Laser Spectroscopy Lab, Center for Integrative Petroleum Research, King Fahd University of Petroleum and Minerals, Dhahran 31261, Kingdom of Saudi Arabia
| | - Ramapurath S Jayasree
- Division of Biophotonics and Imaging, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala 695012, India
| | - Jagadeesh Bayry
- Department of Biological Sciences and Engineering, Indian Institute of Technology Palakkad, Palakkad 678623, India
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Liang Y, Zhao L, Guo J, Wang H, Liu S, Wang L, Chen L, Chen M, Zhang N, Liu H, Nie C. Just-in-Time Learning-Integrated Partial Least-Squares Strategy for Accurately Predicting 71 Chemical Constituents in Chinese Tobacco by Near-Infrared Spectroscopy. ACS OMEGA 2022; 7:38650-38659. [PMID: 36340111 PMCID: PMC9631892 DOI: 10.1021/acsomega.2c04139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
Near-infrared spectroscopy has been widely used to characterize the chemical composition of tobacco because it is fast, economical, and nondestructive. However, few predictive models perform ideally when applied to large spectral libraries of tobacco and its various chemical indicators. In this study, the just-in-time learning-integrated partial least-squares (JIT-PLS) modeling strategy was applied for the first time to quantitatively analyze 71 chemical components in Chinese tobacco. Approximately 18000 tobacco samples from China were analyzed to find appropriately similar measurements and propose suitable and flexible similar subsets from the calibration for each test sample. In total, 879 representative aged tobacco leaf samples and 816 cigarette samples were used as external instances to evaluate the practical predicting ability of the proposed method. The most suitable similar subsets for each test sample could be selected by limiting the Euclidean distance and number of similar subsets to 0-3.0 × 10-9 and 10-300, respectively. The majority of the JIT-PLS models performed significantly better than traditional PLS models. Specifically, using JIT-PLS instead of traditional PLS models increased the R 2 values from 0.347-0.984 to 0.763-0.996, and from 0.179-0.981 to 0.506-0.989 for the prediction of 67 and 71 components in aged tobacco leaf and cigarette samples, respectively. Good prediction ability was demonstrated for routine chemical components, polyphenolic compounds, organic acids, and other compounds, with the mean ratios of prediction to deviation (RPDmean) being 7.74, 4.39, 4.05, and 5.48, respectively). The proposed methodology could simultaneously determine 67 major components in large and complicated tobacco spectral libraries with high precision and accuracy, which will assist tobacco and cigarette quality control in collecting as well as processing stages.
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Affiliation(s)
- Youyan Liang
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Le Zhao
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Junwei Guo
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Hongbo Wang
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Shaofeng Liu
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Luoping Wang
- Technology
Center of China Tobacco Yunnan Industrial Co. Ltd., Kunming650231, China
| | - Li Chen
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Mantang Chen
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Nuohan Zhang
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Huimin Liu
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
| | - Cong Nie
- Zhengzhou
Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China
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ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:4777434. [PMID: 35707272 PMCID: PMC9192200 DOI: 10.1155/2022/4777434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 05/13/2022] [Accepted: 05/19/2022] [Indexed: 11/18/2022]
Abstract
Endometriosis is one of the most common gynecological diseases among young women of reproductive age. Thus far, it has not been possible to define a parameter that is sensitive and specific enough to be a recognized biomarker for diagnosing this disease. Nonspecific symptoms of endometriosis and delayed diagnosis are impulses for researching noninvasive methods of differentiating endometriosis from other gynecological disorders. We compared three groups of individuals in our research: women with endometriosis (E), patients suffering from other gynecological disorders (nonendometriosis, NE), and healthy women from the control group (C). Partial least squares discriminant analysis (PLS-DA) models were developed based on selected serum biochemical parameters, specific regions of the serum’s infrared attenuated total reflectance (FTIR ATR) spectra, and combined data. Incorporating the spectral data into the models significantly improved differentiation among the three groups, with an overall accuracy of 87.5%, 97.3%, and 98.5%, respectively. This study shows that infrared spectroscopy and discriminant analysis can be used to differentiate serum samples among women with advanced endometriosis, women without this disease, i.e., healthy women, and, most importantly, also women with other benign gynecological disorders.
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Kochan K, Bedolla DE, Perez-Guaita D, Adegoke JA, Chakkumpulakkal Puthan Veettil T, Martin M, Roy S, Pebotuwa S, Heraud P, Wood BR. Infrared Spectroscopy of Blood. APPLIED SPECTROSCOPY 2021; 75:611-646. [PMID: 33331179 DOI: 10.1177/0003702820985856] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.
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Affiliation(s)
- Kamila Kochan
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - Diana E Bedolla
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - David Perez-Guaita
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - John A Adegoke
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | | | - Miguela Martin
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - Supti Roy
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - Savithri Pebotuwa
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - Philip Heraud
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
| | - Bayden R Wood
- 2541Monash University - Centre for Biospectroscopy, Clayton, Victoria, Australia
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Zhang X, Wei C, Song Z. Fast Locally Weighted PLS Modeling for Large-Scale Industrial Processes. Ind Eng Chem Res 2020. [DOI: 10.1021/acs.iecr.0c03932] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Xinmin Zhang
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Chihang Wei
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Zhihuan Song
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
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Abd Rahim IM, Rahim HA, Ghazali R. Near-Infrared Data Pre-Processing for Glucose Level Prediction in Blood. 2020 IEEE 10TH INTERNATIONAL CONFERENCE ON SYSTEM ENGINEERING AND TECHNOLOGY (ICSET) 2020. [DOI: 10.1109/icset51301.2020.9265391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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Yeo WS, Saptoro A, Kumar P. Missing data treatment for locally weighted partial least square‐based modelling: A comparative study. ASIA-PAC J CHEM ENG 2020. [DOI: 10.1002/apj.2422] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Affiliation(s)
- Wan Sieng Yeo
- Department of Chemical EngineeringCurtin University Malaysia Miri Malaysia
| | - Agus Saptoro
- Department of Chemical EngineeringCurtin University Malaysia Miri Malaysia
| | - Perumal Kumar
- Department of Chemical EngineeringCurtin University Malaysia Miri Malaysia
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Kristoffersen KA, Liland KH, Böcker U, Wubshet SG, Lindberg D, Horn SJ, Afseth NK. FTIR-based hierarchical modeling for prediction of average molecular weights of protein hydrolysates. Talanta 2019; 205:120084. [DOI: 10.1016/j.talanta.2019.06.084] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Revised: 06/19/2019] [Accepted: 06/21/2019] [Indexed: 02/04/2023]
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Narayanan H, Sokolov M, Butté A, Morbidelli M. Decision Tree-PLS (DT-PLS) algorithm for the development of process: Specific local prediction models. Biotechnol Prog 2019; 35:e2818. [PMID: 30969466 DOI: 10.1002/btpr.2818] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 03/15/2019] [Accepted: 03/25/2019] [Indexed: 12/26/2022]
Abstract
This work presents a novel multivariate statistical algorithm, Decision Tree-PLS (DT-PLS), to improve the prediction and understanding of dynamic processes based on local partial least square regression (PLSR) models for characteristic process groups defined based on Decision Tree (DT) analysis. The DT-PLS algorithm is successfully applied to two different cell culture data sets, one obtained from bioreactors of 3.5 L lab scale and the other obtained from the 15 ml ambr microbioreactor system. Substantial improvement in the predictive capabilities of the model can be achieved based on the localization compared to the classical PLSR approach, which is implemented in the commercially available packages. Additionally, the differences in the model parameters of the local models suggest that the governing process variables vary for the different process regimes indicating the different states of the cell under different process conditions.
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Affiliation(s)
- Harini Narayanan
- Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Switzerland
| | - Michael Sokolov
- Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Switzerland.,DataHow AG, Zurich, Switzerland
| | - Alessandro Butté
- Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Switzerland.,DataHow AG, Zurich, Switzerland
| | - Massimo Morbidelli
- Institute of Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Switzerland.,DataHow AG, Zurich, Switzerland
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Staniszewska-Slezak E, Wiercigroch E, Fedorowicz A, Buczek E, Mateuszuk L, Baranska M, Chlopicki S, Malek K. A possible Fourier transform infrared-based plasma fingerprint of angiotensin-converting enzyme inhibitor-induced reversal of endothelial dysfunction in diabetic mice. JOURNAL OF BIOPHOTONICS 2018; 11:e201700044. [PMID: 28700133 DOI: 10.1002/jbio.201700044] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Revised: 05/10/2017] [Accepted: 06/06/2017] [Indexed: 06/07/2023]
Abstract
Angiotensin-converting enzyme inhibitors (ACE-I) display vasoprotective activity and represent the cornerstone in the treatment of cardiovascular diseases. In this study, we tested whether Fourier transform infrared (FTIR)-based analysis of blood plasma is sensitive to detect vasoprotective effects of treatment with perindopril including reversal of endothelial dysfunction in diabetes. For this purpose, plasma samples were collected from untreated db/db mice, db/db mice treated with 2 or 10 mg/kg perindopril and db+ mice. The effect of perindopril on endothelial function was examined in ex vivo aortic rings; 10 mg/kg but not 2 mg/kg of perindopril reversed endothelial dysfunction. In plasma of db/db mice, the balance between conformations of plasma proteins was noted, and treatment with perindopril at a high dose but not at a low dose reversed this effect. This was revealed by amide II/amide I ratio attributed to increased β-sheet formation. Spectral markers at 3010, 1520/1238 cm-1 , representative for unsaturation degree of lipids and phosphorylation of tyrosine, respectively, were also affected by perindopril treatment. In conclusion, although metabolic abnormalities associated with type 2 diabetes mellitus such as hypertriglyceridemia and hyperglycemia strongly affected spectral FTIR profile of diabetic plasma, we identified FTIR features that seem to be associated with the vasoprotective activity of ACE-I.
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Affiliation(s)
- Emilia Staniszewska-Slezak
- Faculty of Chemistry, Jagiellonian University, Krakow, Poland
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
| | - Ewelina Wiercigroch
- Faculty of Chemistry, Jagiellonian University, Krakow, Poland
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
| | - Andrzej Fedorowicz
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
- Chair of Pharmacology, Jagiellonian University, Krakow, Poland
| | - Elżbieta Buczek
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
| | - Lukasz Mateuszuk
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
| | - Malgorzata Baranska
- Faculty of Chemistry, Jagiellonian University, Krakow, Poland
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
| | - Stefan Chlopicki
- Jagiellonian Centre for Experimental Therapeutics (JCET), Jagiellonian University, Krakow, Poland
- Chair of Pharmacology, Jagiellonian University, Krakow, Poland
| | - Kamilla Malek
- Faculty of Chemistry, Jagiellonian University, Krakow, Poland
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Bunaciu AA, Fleschin Ş, Hoang VD, Aboul-Enein HY. Vibrational Spectroscopy in Body Fluids Analysis. Crit Rev Anal Chem 2016; 47:67-75. [PMID: 27404559 DOI: 10.1080/10408347.2016.1209104] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Vibrational spectroscopy offers a unique opportunity to investigate the composition of unknown substances on a molecular basis. The spectroscopy of molecular vibrations using mid-infrared or Raman techniques has been applied to samples of body fluids. This review presents some applications related to body fluids published in the period 2005-2015.
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Affiliation(s)
- Andrei A Bunaciu
- a SCIENT - Research Center for Instrumental Analysis, (CROMATEC_PLUS S.R.L.) , Tancabesti, Snagov , Romania
| | - Şerban Fleschin
- b Department of Organic Chemistry , Biochemistry and Catalysis, Faculty of Chemistry, University of Bucharest , Bucharest , Romania
| | - Vu Dang Hoang
- c Department of Analytical Chemistry and Toxicology , Hanoi University of Pharmacy , Hanoi , Vietnam
| | - Hassan Y Aboul-Enein
- d Pharmaceutical and Medicinal Chemistry Department , Pharmaceutical and Drug Industries Research Division, National Research Centre , Dokki, Giza , Egypt
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Sparse Sample Regression Based Just-In-Time Modeling (SSR-JIT): Beyond Locally Weighted Approach**This study was supported by JSPS KAKENHI 15K06554. ACTA ACUST UNITED AC 2016. [DOI: 10.1016/j.ifacol.2016.07.392] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Chen HZ, Tang GQ, Ai W, Xu LL, Cai K. Use of random forest in FTIR analysis of LDL cholesterol and tri-glycerides for hyperlipidemia. Biotechnol Prog 2015; 31:1693-702. [DOI: 10.1002/btpr.2161] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Revised: 08/21/2015] [Indexed: 11/11/2022]
Affiliation(s)
- Hua-Zhou Chen
- School of Science; Guilin University of Technology; Guilin 541004 China
| | - Guo-Qiang Tang
- School of Science; Guilin University of Technology; Guilin 541004 China
| | - Wu Ai
- School of Science; Guilin University of Technology; Guilin 541004 China
| | - Li-Li Xu
- School of Ocean; Qinzhou University; Qinzhou 535000 China
| | - Ken Cai
- School of Information Science and Technology; Zhongkai University of Agriculture and Engineering; Guangzhou 510225 China
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Pérez-Guaita D, Sánchez-Illana Á, Garrigues S, de la Guardia M. Determination of lidocaine in urine at low ppm levels using dispersive microextraction and attenuated total reflectance–Fourier transform infrared measurements of dry films. Microchem J 2015. [DOI: 10.1016/j.microc.2015.03.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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Ma M, Khatibisepehr S, Huang B. A Bayesian framework for real-time identification of locally weighted partial least squares. AIChE J 2014. [DOI: 10.1002/aic.14663] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Ming Ma
- Dept. of Chemical and Materials Engineering; University of Alberta; Edmonton Alberta Canada T6G 2G6
| | - Shima Khatibisepehr
- Dept. of Chemical and Materials Engineering; University of Alberta; Edmonton Alberta Canada T6G 2G6
| | - Biao Huang
- Dept. of Chemical and Materials Engineering; University of Alberta; Edmonton Alberta Canada T6G 2G6
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Kuligowski J, Pérez-Guaita D, Escobar J, Lliso I, de la Guardia M, Lendl B, Vento M, Quintás G. Infrared biospectroscopy for a fast qualitative evaluation of sample preparation in metabolomics. Talanta 2014; 127:181-90. [DOI: 10.1016/j.talanta.2014.04.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Revised: 04/01/2014] [Accepted: 04/04/2014] [Indexed: 10/25/2022]
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Perez-Guaita D, Sanchez-Illana A, Ventura-Gayete J, Garrigues S, de la Guardia M. Chemometric determination of lipidic parameters in serum using ATR measurements of dry films of solvent extracts. Analyst 2014; 139:170-8. [DOI: 10.1039/c3an01057k] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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