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Nunes PP, Almeida MR, Pacheco FG, Fantini C, Furtado CA, Ladeira LO, Jorio A, Júnior APM, Santos RL, Borges ÁM. Detection of carbon nanotubes in bovine raw milk through Fourier transform Raman spectroscopy. J Dairy Sci 2024; 107:2681-2689. [PMID: 37923204 DOI: 10.3168/jds.2023-23481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 10/11/2023] [Indexed: 11/07/2023]
Abstract
The potential use of carbon-based methodologies for drug delivery and reproductive biology in cows raises concerns about residues in milk and food safety. This study aimed to assess the potential of Fourier transform Raman spectroscopy and discriminant analysis using partial least squares (PLS-DA) to detect functionalized multiwalled carbon nanotubes (MWCNT) in bovine raw milk. Oxidized MWCNT were diluted in milk at different concentrations from 25.00 to 0.01 µg/mL. Raman spectroscopy measurements and PLS-DA were performed to identify low concentrations of MWCNT in milk samples. The PLS-DA model was characterized by the analysis of the variable importance in projection (VIP) scores. All the training samples were correctly classified by the model, resulting in no false-positive or false-negative classifications. For test samples, only one false-negative result was observed, for 0.01 µg/mL MWCNT dilution. The association between Raman spectroscopy and PLS-DA was able to identify MWCNT diluted in milk samples up to 0.1 µg/mL. The PLS-DA model was built and validated using a set of test samples and spectrally interpreted based on the highest VIP scores. This allowed the identification of the vibrational modes associated with the D and G bands of MWCNT, as well as the milk bands, which were the most important variables in this analysis.
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Affiliation(s)
- Philipe P Nunes
- Department of Veterinary Clinic and Surgery, Veterinary School, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Mariana R Almeida
- Department of Chemistry, Institute of Exact Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Flávia G Pacheco
- Laboratory of Carbon Nanostructure Chemistry, Nuclear Technology Development Center, Belo Horizonte, MG 31270-901, Brazil
| | - Cristiano Fantini
- Department of Physics, Institute of Exact Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Clascídia A Furtado
- Laboratory of Carbon Nanostructure Chemistry, Nuclear Technology Development Center, Belo Horizonte, MG 31270-901, Brazil
| | - Luiz O Ladeira
- Department of Physics, Institute of Exact Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Ado Jorio
- Department of Physics, Institute of Exact Science, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Antônio P M Júnior
- Department of Veterinary Clinic and Surgery, Veterinary School, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Renato L Santos
- Department of Veterinary Clinic and Surgery, Veterinary School, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil
| | - Álan M Borges
- Department of Veterinary Clinic and Surgery, Veterinary School, Federal University of Minas Gerais, Belo Horizonte, MG 31270-901, Brazil.
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2
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Ma H, Guo J, Liu G, Xie D, Zhang B, Li X, Zhang Q, Cao Q, Li X, Ma F, Li Y, Wan G, Li Y, Wu D, Ma P, Guo M, Yin J. Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review. Crit Rev Food Sci Nutr 2024:1-23. [PMID: 38523442 DOI: 10.1080/10408398.2024.2329956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.
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Affiliation(s)
- Haiyang Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Jiajun Guo
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Guishan Liu
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Delang Xie
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Bingbing Zhang
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Xiaojun Li
- School of Electronic and Electrical Engineering, Ningxia University, Yinchuan, China
| | - Qian Zhang
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Qingqing Cao
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Xiaoxue Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Fang Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Yang Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Guoling Wan
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Yan Li
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Di Wu
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Ping Ma
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Mei Guo
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
| | - Junjie Yin
- School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China
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3
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Yao S, Miyagusuku-Cruzado G, West M, Nwosu V, Dowd E, Fountain J, Giusti MM, Rodriguez-Saona LE. Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman). Foods 2024; 13:157. [PMID: 38201185 PMCID: PMC10779085 DOI: 10.3390/foods13010157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 12/20/2023] [Accepted: 12/23/2023] [Indexed: 01/12/2024] Open
Abstract
A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.
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Affiliation(s)
- Siyu Yao
- Department of Nutrition and Food Hygiene, School of Public Health, Southeast University, Nanjing 210009, China
| | - Gonzalo Miyagusuku-Cruzado
- Department of Food Science and Technology, The Ohio State University, Parker Food Science and Technology Building, 2015 Fyffe Road, Columbus, OH 43210, USA (M.M.G.); (L.E.R.-S.)
| | - Megan West
- Mars Wrigley, Inc., 1132 W. Blackhawk Street, Chicago, IL 60642, USA (E.D.)
| | - Victor Nwosu
- Mars Wrigley, Inc., 1132 W. Blackhawk Street, Chicago, IL 60642, USA (E.D.)
| | - Eric Dowd
- Mars Wrigley, Inc., 1132 W. Blackhawk Street, Chicago, IL 60642, USA (E.D.)
| | - Jake Fountain
- Department of Plant Pathology, University of Georgia, 216 Redding Building, 1109 Experiment St., Griffin, GA 30223, USA
| | - M. Monica Giusti
- Department of Food Science and Technology, The Ohio State University, Parker Food Science and Technology Building, 2015 Fyffe Road, Columbus, OH 43210, USA (M.M.G.); (L.E.R.-S.)
| | - Luis E. Rodriguez-Saona
- Department of Food Science and Technology, The Ohio State University, Parker Food Science and Technology Building, 2015 Fyffe Road, Columbus, OH 43210, USA (M.M.G.); (L.E.R.-S.)
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Smaoui S, Tarapoulouzi M, Agriopoulou S, D'Amore T, Varzakas T. Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics. Foods 2023; 12:4254. [PMID: 38231684 DOI: 10.3390/foods12234254] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 11/21/2023] [Accepted: 11/22/2023] [Indexed: 01/19/2024] Open
Abstract
Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.
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Affiliation(s)
- Slim Smaoui
- Laboratory of Microbial, Enzymatic Biotechnology, and Biomolecules (LBMEB), Center of Biotechnology of Sfax, University of Sfax-Tunisia, Sfax 3029, Tunisia
| | - Maria Tarapoulouzi
- Department of Chemistry, Faculty of Pure and Applied Science, University of Cyprus, P.O. Box 20537, Nicosia CY-1678, Cyprus
| | - Sofia Agriopoulou
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
| | - Teresa D'Amore
- IRCCS CROB, Centro di Riferimento Oncologico della Basilicata, 85028 Rionero in Vulture, Italy
| | - Theodoros Varzakas
- Department of Food Science and Technology, University of the Peloponnese, Antikalamos, 24100 Kalamata, Greece
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Kaur G, Sidhu GK, Kaur P, Kaur A. Influence of ozonation and roasting on functional, microstructural, textural characteristics, and aflatoxin content of groundnut kernels. J Texture Stud 2022; 53:908-922. [PMID: 36053754 DOI: 10.1111/jtxs.12713] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 06/28/2022] [Accepted: 08/11/2022] [Indexed: 12/30/2022]
Abstract
The present study was conducted to evaluate the influence of ozonation, roasting and their combination on the moisture content, color, functional, structural, textural components, and aflatoxins in groundnut kernels. Samples were subjected to three treatments namely, dry roasting (R): 166°C for 7 min; gaseous ozone treatment (O): 6 mg/L for 30 min; combined ozonation-roasting (OR): gaseous ozonation at 6 mg/L for 30 min followed by dry roasting at 166°C for 7 min. The ozonated-roasted samples had the lowest moisture content (3.45%), the highest total phenolic content (4.18 mg gallic acid equivalents/100 g), and antioxidants capacity (69.59%). The treatments did not induce significant changes in color of kernels (p < .05). Scanning electron microscopy indicated cracking of granules in roasted and swelling in ozonated kernels whereas more uniform orientation of granules was observed in ozonated-roasted kernels. Roasted and ozonated kernels indicated a significant reduction of fracturability force to 54.60 and 14.11%, respectively, whereas ozonated-roasted samples demonstrated a nonsignificant increase (4.37%). An increase in wave number of ozonated samples to 3,289.37 cm-1 in Fourier transform infrared (FTIR) spectrum (FTIR) indicated stretching in OH groups. FTIR spectrum of ozonated-roasted kernels suggested the formation of a new compound with CC and CC groups. The major aflatoxin B1 was reduced to maximum, that is, 100% in ozonated-roasted kernels followed by ozonated (80.95%) and roasted (57.14%) samples. The findings indicate that the ozonation-roasting treatment had a prominent role in the enhancement of functional compounds, structural and textural attributes along with the considerable reduction in aflatoxin content.
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Affiliation(s)
- Gurjeet Kaur
- Department of Processing and Food Engineering, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Gagandeep Kaur Sidhu
- Department of Processing and Food Engineering, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Preetinder Kaur
- Department of Processing and Food Engineering, Punjab Agricultural University, Ludhiana, Punjab, India
| | - Amarjit Kaur
- Department of Food Science and Technology, Punjab Agricultural University, Ludhiana, Punjab, India
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Evaluation of Mutton Adulteration under the Effect of Mutton Flavour Essence Using Hyperspectral Imaging Combined with Machine Learning and Sparrow Search Algorithm. Foods 2022; 11:foods11152278. [PMID: 35954045 PMCID: PMC9368686 DOI: 10.3390/foods11152278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 07/27/2022] [Accepted: 07/27/2022] [Indexed: 11/16/2022] Open
Abstract
The evaluation of mutton adulteration faces new challenges because of mutton flavour essence, which achieves a similar flavour between the adulterant and mutton. Hence, methods for classifying and quantifying the adulterated mutton under the effect of mutton flavour essence, based on near-infrared hyperspectral imaging (NIR-HSI, 1000–2500 nm) combined with machine learning (ML) and sparrow search algorithm (SSA), were proposed in this study. After spectral preprocessing via first derivative combined with multiple scattering correction (1D + MSC), classification and quantification models were established using back propagation neural network (BP), extreme learning machine (ELM) and support vector machine/regression (SVM/SVR). SSA was further used to explore the global optimal parameters of these models. Results showed that the performance of models improves after optimisation via the SSA. SSA-SVM achieved the optimal discrimination result, with an accuracy of 99.79% in the prediction set; SSA-SVR achieved the optimal prediction result, with an RP2 of 0.9304 and an RMSEP of 0.0458 g·g−1. Hence, NIR-HSI combined with ML and SSA is feasible for classification and quantification of mutton adulteration under the effect of mutton flavour essence. This study can provide a theoretical and practical reference for the evaluation and supervision of food quality under complex conditions.
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Nondorf MJ, Romanyk M, Lemenager RP, Koranne V, Malshe A, Brad Kim YH. Application of Fresh Beef Tumbling to Enhance Tenderness and Proteolysis of Cull Cow Beef Loins (
M. longissimus lumborum
). Int J Food Sci Technol 2022. [DOI: 10.1111/ijfs.16007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Mariah J. Nondorf
- Department of Animal Sciences Purdue University West Lafayette 47907 IN USA
| | - Madison Romanyk
- Department of Animal Sciences Purdue University West Lafayette 47907 IN USA
| | | | - Vishvesh Koranne
- Department of Mechanical Engineering Purdue University West Lafayette 47907 IN USA
| | - Ajay Malshe
- Department of Mechanical Engineering Purdue University West Lafayette 47907 IN USA
| | - Yuan H. Brad Kim
- Department of Animal Sciences Purdue University West Lafayette 47907 IN USA
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Correction of the moisture variation in wood NIR spectra for species identification using EPO and soft PLS2-DA. Microchem J 2021. [DOI: 10.1016/j.microc.2021.106839] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Yang H, Bao L, Liu Y, Luo S, Zhao F, Chen G, Liu F. Identification and quantitative analysis of salt-adulterated honeysuckle using infrared spectroscopy coupled with multi-chemometrics. Microchem J 2021. [DOI: 10.1016/j.microc.2021.106829] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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10
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Wang L, Yang Q, Zhao H. Sub-regional identification of peanuts from Shandong Province of China based on Fourier transform infrared (FT-IR) spectroscopy. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.107879] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Liu Z, Yang MQ, Zuo Y, Wang Y, Zhang J. Fraud Detection of Herbal Medicines Based on Modern Analytical Technologies Combine with Chemometrics Approach: A Review. Crit Rev Anal Chem 2021; 52:1606-1623. [PMID: 33840329 DOI: 10.1080/10408347.2021.1905503] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Fraud in herbal medicines (HMs), commonplace throughout human history, is significantly related to medicinal effects with sometimes lethal consequences. Major HMs fraud events seem to occur with a certain regularity, such as substitution by counterfeits, adulteration by addition of inferior production-own materials, adulteration by chemical compounds, and adulteration by addition of foreign matter. The assessment of HMs fraud is in urgent demand to guarantee consumer protection against the four fraudulent activities. In this review, three analysis platforms (targeted, non-targeted, and the combination of non-targeted and targeted analysis) were introduced and summarized. Furthermore, the integration of analysis technology and chemometrics method (e.g., class-modeling, discrimination, and regression method) have also been discussed. Each integration shows different applicability depending on their advantages, drawbacks, and some factors, such as the explicit objective analysis or the nature of four types of HMs fraud. In an attempt to better solve four typical HMs fraud, appropriate analytical strategies are advised and illustrated with several typical studies. The article provides a general workflow of analysis methods that have been used for detection of HMs fraud. All analysis technologies and chemometrics methods applied can conduce to excellent reference value for further exploration of analysis methods in HMs fraud.
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Affiliation(s)
- Zhimin Liu
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China.,School of Agriculture, Yunnan University, Kunming, China
| | - Mei Quan Yang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Yingmei Zuo
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Yuanzhong Wang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
| | - Jinyu Zhang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
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12
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Authentication and Quality Assessment of Meat Products by Fourier-Transform Infrared (FTIR) Spectroscopy. FOOD ENGINEERING REVIEWS 2020. [DOI: 10.1007/s12393-020-09251-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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