Cross-reactivity of monoclonal antibodies (anti-mycotoxins & microcystins) applied in a monitoring study in Brazil.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"3627",leadTitle:null,fullTitle:"Mechatronic Systems Applications",title:"Mechatronic Systems",subtitle:"Applications",reviewType:"peer-reviewed",abstract:"Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing.\r\n\r\nMechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers.\r\n\r\nChapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools.",isbn:null,printIsbn:"978-953-307-040-7",pdfIsbn:"978-953-51-5892-9",doi:"10.5772/206",price:139,priceEur:155,priceUsd:179,slug:"mechatronic-systems-applications",numberOfPages:364,isOpenForSubmission:!1,isInWos:1,hash:null,bookSignature:"Annalisa Milella Donato Di Paola and Grazia Cicirelli",publishedDate:"March 1st 2010",coverURL:"https://cdn.intechopen.com/books/images_new/3627.jpg",numberOfDownloads:67937,numberOfWosCitations:18,numberOfCrossrefCitations:25,numberOfDimensionsCitations:39,hasAltmetrics:0,numberOfTotalCitations:82,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:null,dateEndSecondStepPublish:null,dateEndThirdStepPublish:null,dateEndFourthStepPublish:null,dateEndFifthStepPublish:null,currentStepOfPublishingProcess:1,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,editors:[{id:"1065",title:"Dr.",name:"Annalisa",middleName:null,surname:"Milella",slug:"annalisa-milella",fullName:"Annalisa Milella",profilePictureURL:"https://mts.intechopen.com/storage/users/1065/images/system/1065.jpg",biography:"I received the Laurea (summa cum laude) and Research Doctorate degrees from the Politecnico of Bari, Italy, in 2002 and 2006, respectively, both in Mechanical Engineering. In 2005, I was a visiting PhD student at the EPFL Autonomous Systems Laboratory. Currently, I am a researcher at the Institute of Intelligent Systems for Automation (ISSIA), National Research Council (CNR) of Bari, Italy.\nMy main research interests include:\n- computer vision applied to robotics and intelligent systems\n- self-localization methods for mobile robots\n- robotic non-destructive inspection\n- robotic surveillance systems",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Institute of Intelligent Systems for Automation",institutionURL:null,country:{name:"Italy"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"17156",title:"Dr.",name:"Grazia",middleName:null,surname:"Cicirelli",slug:"grazia-cicirelli",fullName:"Grazia Cicirelli",profilePictureURL:"https://mts.intechopen.com/storage/users/17156/images/system/17156.jpg",biography:"Grazia Cicirelli received the Laurea degree (summa cum laude) in Computer Science from the University of Bari (Italy) in 1994. Until 2001 she held grants from the Italian National Research Council (CNR) for research activities in Robotics and Image Processing. From 2001 she is a Technologist Researcher at the Institute of Intelligent Systems for Automation (ISSIA) of CNR in Bari. Her principal interests include pattern recognition, artificial intelligence, image processing for robotic applications and intelligent systems for video-surveillance. She has worked on and directed numerous research projects in different research areas such as Quality Control, Intelligent Transportation Systems, Autonomous Mobile Robotics. She is author of numerous research papers published in International Conference Proceedings, National and International Journals. She is a co-inventor of 1 international patent on the development of a visual system for event detection in a sport context.\n\nDr. Cicirelli regularly serves as reviewer on various Conferences and International Journals including:\n\nIndustrial Robot: An International Journal\nInternational Journal of Advanced Robotics Systems\nIEEE Transactions on Intelligent Transportation Systems.\nShe received the 2013 Award for Excellence as Outstanding Reviewer to “Industrial Robot: An International Journal” (Emerald) for the significant contribution made throughout 2012. She is a member of the Editorial Board at the International Journal of Advanced Robotic Systems (IJARS). 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Agricultural products, such as vegetables and fruits, are the basis of the food chain. Additional mechanical injuries during postharvest processing, storage and transportation may cause further points of contamination, leading to reduced quality, and compromising safety.
Preserving food products involves controlling external and internal conditions to avoid undesirable microbial growth and/or degradation processes, as well as the biosynthesis of unavoidable secondary metabolites, namely mycotoxins and phycotoxins.
Globalization demands high quality and competitiveness throughout the food chain. Quality and safety are typically achieved through a Hazard Analysis and Critical Control Points (HACCP) Risk Assessment. Providing raw materials of high quality and safe ingredients also includes the quality of water employed in food processes, which should be free of contaminants. Such strategies involve the detection of toxic secondary metabolites through continuous monitoring with reliable analytical methods, which should not only be restricted at the qualitative occurrence level but also the exact quantitative level compared with the maximal contamination limit proposed by guidelines.
The recommended techniques to detect ng and µg levels of toxic metabolites, and waste contaminants are based on High Performance Liquid Chromatography (HPLC) coupled with high sensitivity mass spectrometry (MS), which analyses residual contamination in a wide variety of products and materials.
These improvements are in contrast with the reality in raw material producing countries, highlighting the need for the innovative implementation of rapid methods combining simplicity, sensitivity and accuracy. Additionally, sequential processing and material resources in the food industry should be continuously monitored for safety and quality, which requires rapid monitoring in loco.
The rapid detection of natural toxins, such as mycotoxins and cyanotoxins, has been focused on immunochemical methods developed with highly specific monoclonal antibodies (mAb) matched with chromatographic methods. Such techniques arose based on antibodies, highlighting the immunoaffinity column (IAC) for the clean-up step, and enzyme linked immunosorbent assay (ELISA) with the advantage of eliminating toxic solvents (using buffer). The current commercial kits have been the practical tool of choice and have an important role in avoiding hazards for animals and humans. Immunoassays are advancing with developments in nano-engineering, resulting in compact, miniaturized electronic devices, such as biosensors, which combine high specificity and biological diversity with automation of diagnostics. The advantages of these developments are their specificity, speed and simplicity for the detection of dangerous levels of natural toxins.
Nevertheless, both chemical and biological analytical methods are destructive, i.e., the decision concerning the total batch is extrapolated based on data obtained with samples that were already destroyed for analysis. Non-invasive and non-destructive chemical-free techniques came as a welcome option in the industrial process, including optical methods (Fourier Transform coupled to Infrared Spectroscopy, FT-IR spectroscopy and transmittance in the near infrared, near-IR), as well as an "electronic nose" for volatile compounds. These technologies are able to integrate with online quality control monitoring systems in the food chain in real time and are able to detect imbalances caused by deteriorated quality, which can also indicate undesirable toxic metabolites.
Continuous tracking in the food chain should focus on safety and quality using practical and reliable analytical techniques. The combination of rapid biological assays, non-destructive physical technologies and primary chemical analysis are desirable procedures for extending the shelf life of a product.
We begin by presenting data on corn, a topic of concern in the food chain, as it is a universal ingredient with unavoidable mycotoxin hazards – even with extensive monitoring in the agro-industrial region of Southern Brazil. An ic-ELISA-based immunoassay was developed, established and optimized to analyse different food groups, using specific MAb produced by hybridomas (especially against non-immunogenic low molecular mass ochratoxin (OTA), aflatoxin (AF), deoxynivalenol (DON), zearalenone (ZEA), fumonisin B1(FB1), OTA and microcystin-LR (MCLR)). This has become important for rapid tracking, monitoring safety and quality, and providing guidance for the best conduct to establish a long-lasting trend focusing on harmless/sustainable management in uninterrupted tropical-subtropical farming, and in replacing chemical agrotoxicants. The control of natural toxins should begin at the field level through sustainable management, adequate water quality, predictive modelling, as well as in the food processing systems in agroindustry. Such an overall approach, could result in the production of healthy foods in potential food producing regions in Brazil.
Brazil has a vast cultivated area of 53.20 million ha and continues to expand production, with 10.9 % in grain volume corresponding to 184.30 million from the 2012/2013 crop harvest, compared with 166.17 million ton in 2011/2012 [1]. Estimates indicate that grain production will be approximately 200.08 million ton in 2014/2015, 3.4 % higher than the 2013/2014 production [2]. The total cultivated area of grain also showed growth (57.03 million to 57.39 million hectares), with the promising increase of second crops allowed by tropical climates.
Corn (Zea mays L.) is one of the major cereal crops in Brazil, with an annual production of 78.689 million (metric) ton, ranking the country as the third largest corn producer in the world. Paraná State was the second largest producer with 14.504 million ton in 2014 [3]. An abrupt increase in trading has occurred due to the large territorial extension associated with climatic diversity; i.e., the tropical climate in midwestern and northern regions, and subtropical-temperate climates in southern and southeastern Brazil, which enables production throughout the year. Therefore, the exportation of 3.37 million ton in February 2013 was 297 % higher than in January 2012. Corn is the second most produced crop (39.29 %), preceded only by soybean (47.19 %). From February 2014 to January 2015 – with 20.9 million ton, Brazilian exports were 400,000 ton higher than the projected capacity. The main corn importers were Iran, Vietnam, South Korea, Taiwan, Egypt, Indonesia, Malaysia, Japan, Saudi Arabia and Morocco [2].
Figure 1 shows the production of corn immediately following the soybean harvest, which allows up to three crop cycles per year in producing regions.
Harvesting of precocious soybean followed by simultaneous planting of corn as the second crop.
Approximately 70 % of Brazilian corn is intended for swine and broiler feeds, whereas processing for human consumption corresponds to 15 % [4]. Nevertheless, its high nutritional quality introduces risk for the growth of toxigenic fungi favoured by tropical and subtropical climates. Mycotoxins are natural thermostable metabolites responsible for substantial economic losses and their persistent residual levels can be detected even in post-processed meat, eggs, milk and dairy products. The Food and Agricultural Organization (FAO) estimated the worldwide mycotoxin contamination in crops at 25 %.
The most important mycotoxins in tropical developing countries, such as Brazil, have been fumonisins produced mainly by Fusarium verticillioides and F. proliferatum [5], and aflatoxins produced by Aspergillus flavus and A. parasiticus [6].
Corn quality associated with fungal and mycotoxin contamination in Paraná State, southern Brazil, has been studied since the 1980s, when fumonisin caused animal poisonings. The first report involving an animal outbreak detected fumonisin B1 (FB1) and B2 (FB2) in feed samples and determined that F. verticillioides isolates were acutely toxic to ducklings [7]. A survey of fumonisin in corn kernels also reported its occurrence in the states of Mato Grosso do Sul and Goiás [8], the most progressive region of grain production, where FB1 and FB2 were detected in 97.4 % and 94.8 % samples, respectively [2]. All corn from Northern Paraná (n = 39) was fumonisin positive (mean level of FB1 = 4.79 μg g-1 and FB2 = 3.95 μg g-1). The samples from Mato Grosso and Goiás States (n = 9) showed mean FB1 levels of 10.59 and 5.83 μg g-1 and FB2 levels of 10.31 and 3.62 μg g-1, respectively.
The co-occurrence of fumonisins and aflatoxins was investigated in 150 freshly harvested corn samples (1994/1995 crop) from the central-southern (n = 27 samples), central-western (n = 86) and northern (n = 37) regions of Parana State. Fumonisins and aflatoxins were detected in 98 % and 11.3 % samples, respectively. All the aflatoxin positive samples (mean, 191 ng g-1) were from the central-western region and were co-contaminated with fumonisins. Higher fumonisin levels were detected in corn from the northern (9.85 µg g-1) and central-western regions (5.08 µg g-1) relative to the central-southern region (1.14 µg g-1), suggesting an effect of climatic conditions in addition to the local predominance of toxigenic Fusarium biotypes [9].
Fumonisin monitoring in real time was established (2003-2004 crop) on critical steps (field, reception and pre-drying) of the corn chain [10]. Fumonisins were analysed in 490 samples of freshly harvested corn (2003-2004 crop) collected at three points of the production chain in Northern Paraná State, and correlated with the time interval between harvesting and the pre-drying step. The mean fumonisin level increased gradually from ≤ 5.0 µg g-1 to 19.0 µg g-1 when the time interval between harvesting and the pre-drying step increased from 3.22 to 8.89 hours. Fumonisin levels were correlated positively (p ≤ 0.05) with time interval (ρ=0.96), indicating that a delay in the drying process could increase the levels of contamination.
A study [11] evaluated fumonisin in 870 freshly harvested corn samples (2003 and 2004 crops) used by processing industries in Northern Paraná State. Sampling was performed at two points of the corn chain, i.e., at reception and the pre-drying step in the processing industry. Fumonisins (FB1 + FB2) were detected in all samples from the two points in both crops. Fumonisin levels in reception (2.24 μg g-1) and pre-drying samples (2.87 µg g-1) of the 2003 and 2004 crops (1.46 and 1.52 µg g-1, respectively) showed similar profiles, indicating that corn used by processing industries in this region showed lower fumonisin levels than in previous studies [8, 9, 12]. Years of monitoring have shown a decreasing trend of fumonisin contamination, which may be due to changing procedures at food and feed processing facilities.
Because determination of the degree of exposure is one of the most important parameters concerning the risk assessment of chemical compounds, a study [13] estimated the maximum probable daily intake (PDIM) of fumonisins in a local population. This study was based on fumonisin monitoring in 300 freshly harvested corn (2003 and 2004 crops) samples collected at two points of the production chain (reception and pre-drying) in Northern Paraná State. Based on the highest mean fumonisin levels being detected in the pre-drying samples (3.12 µg g-1) and the average consumption of corn-based products, the maximum probable daily intake (PDIM) of FB1 estimated in the Brazilian population (0.95 µg kg-1 body weight day-1) was below the tolerable daily intake (2.0 µg kg-1 body weight day-1).
Such monitoring allowed the identification of fumonisin levels in different regions of the state, enabling it to gain a prominent position in corn exportation. Currently, the State of Paraná is responsible for 14.3 million tons/year, corresponding to 17.9 % of the national corn production [3].
Advanced techniques in liquid chromatography using different detectors (UV-Vis-PDA, FLD, MS and LC-MS/MS) have been introduced for the analysis of chemicals in different matrices (food, microbial/plant metabolites, and water). Chromatographic techniques provide the most reliable data due to their precision and accuracy of analysis; therefore, they have also been recommended for use in evaluating alternative rapid techniques. Analytical methods should be appropriate and efficient for each matrix array, i.e., each modification introduced must be in accordance with validation criteria and the specific requests of regulatory organization.
Incomplete extraction and matrix effects of crude extract in the cleaning step can lead to a sub-estimation of real concentrations in analysis; thus, a minimum preparation is advantageous. The multi-toxin methods for HPLC and sequential mass spectrometry (LC-MS/MS) provides a high selectivity, lower limits of quantification and detection, the possibility of generating structural information of the analyte with minimal sample treatment, and the reduction of errors associated with pre-and post-column derivatization. Analyses by LC-MS/MS has gained much interest in analytics [14, 15].
Although there have been other advances in analytics, HPLC coupled with fluorescence and ultraviolet detectors remain the main detection method in Brazil [16, 17, 18]. In addition, the unavoidable occurrence of mycotoxins has obliged several countries to adopt regulatory guidelines, and maximum tolerated levels vary widely among countries [19].
Current regulations are increasingly based on international organizations, such as the FAO/WHO Joint Expert Committee on Food Additives of the United Nations (JECFA), and the European Commission. Strict guidelines on mycotoxins have been imposed by importing countries, demanding a rigorous and continuous monitoring of the food chain. The prevailing guidelines for mycotoxins require different protocols of extraction and analysis, and foods for infants and young children with more restrictive limits increases the number of analyses [20]. Such diversity in extraction procedures results in costly work.
Safe raw materials should be tracked by reliable analytical methods, and rapid methods are useful tools, especially in food-producing countries. Immunoassays based on ic-ELISA with highly specific monoclonal antibodies (MAb) against ochratoxin (OTA), fumonisin (FB), aflatoxin (AF), deoxynivalenol (DON), zearalenone (ZEA) and microcystin (MC) have been developed, previously tested for cross-reactivity with each analogue group, and correlated with HPLC as the primary method (Table 1, 2 and 3). A careful evaluation of ic-ELISA was conducted in the analysis of natural toxins in the food chain targeted to field/storage stage, beginning with the monitoring of fumonisins in corn [21]. The successful rapid technique motivated to use of this analysis for OTA in coffee and wine [22, 23], aflatoxin [24, 25], DON [26, 27, 28] and ZEA [29].
\n\t\t\t\tHybridoma\n\t\t\t | \n\t\t\t\n\t\t\t\tToxin\n\t\t\t | \n\t\t\t\n\t\t\t\tCross reactivity (%)*\n\t\t\t | \n\t\t\t\n\t\t\t\tHybridoma\n\t\t\t | \n\t\t\t\n\t\t\t\tToxin\n\t\t\t | \n\t\t\t\n\t\t\t\tCross reactivity (%)*\n\t\t\t | \n\t\t
\n\t\t\t\tCell line\n\t\t\t | \n\t\t\t\n\t\t\t\tCell line\n\t\t\t | \n\t\t||||
AF.2[30]\n\t\t\t | \n\t\t\tAFB1\n\t\t\t | \n\t\t\t100 | \n\t\t\tZEN.2[34]\n\t\t\t | \n\t\t\tZEA | \n\t\t\t100 | \n\t\t
\n\t\t\t | AFB2\n\t\t\t | \n\t\t\t133 | \n\t\t\t\n\t\t\t | α-Zearalenol | \n\t\t\t60 | \n\t\t
\n\t\t\t | AFG1\n\t\t\t | \n\t\t\t13.4 | \n\t\t\t\n\t\t\t | β-Zearalenol | \n\t\t\t5.7 | \n\t\t
\n\t\t\t | AFG2\n\t\t\t | \n\t\t\t14.7 | \n\t\t\t\n\t\t\t | α-Zearalanol | \n\t\t\t7.1 | \n\t\t
\n\t\t\t | AFM1\n\t\t\t | \n\t\t\t0.9 | \n\t\t\t\n\t\t\t | β-Zearalanol | \n\t\t\t0.9 | \n\t\t
DON.3[31]\n\t\t\t | \n\t\t\tDON | \n\t\t\t100 | \n\t\t\tM8H5[35]\n\t\t\t | \n\t\t\tMCLR | \n\t\t\t100 | \n\t\t
\n\t\t\t | 15-acetil DON | \n\t\t\t333 | \n\t\t\t\n\t\t\t | MCRR | \n\t\t\t106 | \n\t\t
\n\t\t\t | NIV | \n\t\t\t5 | \n\t\t\t\n\t\t\t | MCYR | \n\t\t\t44 | \n\t\t
\n\t\t\t | 4-acetil NIV; Toxin T-2 tetraol | \n\t\t\t1.2 | \n\t\t\t\n\t\t\t | MCLA | \n\t\t\t26 | \n\t\t
\n\t\t\t | Others * | \n\t\t\t<0.5 | \n\t\t\t\n\t\t\t | 3-desmethyl MCLR | \n\t\t\t51 | \n\t\t
\n\t\t\t | \n\t\t\t | \n\t\t\t | \n\t\t\t | 7-desmethyl MCLR | \n\t\t\t48 | \n\t\t
OTA.1 / OTA.7[32]\n\t\t\t | \n\t\t\tOTA | \n\t\t\t100 / 100 | \n\t\t\t\n\t\t\t | MCLR GSH conjugate | \n\t\t\t47 | \n\t\t
\n\t\t\t | OTC | \n\t\t\t63.1 / 79.4 | \n\t\t\t\n\t\t\t | MCLR methyl ester | \n\t\t\t30 | \n\t\t
\n\t\t\t | (4R)-4-HydroxyOTA | \n\t\t\t1.19 / 1.24 | \n\t\t\t\n\t\t\t | Nodularin | \n\t\t\t20 | \n\t\t
\n\t\t\t | OTB | \n\t\t\t0.63 / 1.07 | \n\t\t\t\n\t\t\t | 6 (Z)-Adda -MCLR and - MCRR | \n\t\t\t<7 | \n\t\t
FB 1-2[33]\n\t\t\t | \n\t\t\tFB1\n\t\t\t | \n\t\t\t100 | \n\t\t\tMC. 5-3/ 8-3 / 2[36]\n\t\t\t | \n\t\t\tMCLR | \n\t\t\t100 | \n\t\t
\n\t\t\t | FB2\n\t\t\t | \n\t\t\t224 | \n\t\t\t\n\t\t\t | MCRR | \n\t\t\t146 / 113 / 60 | \n\t\t
\n\t\t\t | FB3\n\t\t\t | \n\t\t\t72 | \n\t\t\t\n\t\t\t | MCYR | \n\t\t\t88 / 65 / 113 | \n\t\t
Cross-reactivity of monoclonal antibodies (anti-mycotoxins & microcystins) applied in a monitoring study in Brazil.
AFB1: Aflatoxin B1; AFB2: Aflatoxin B2; AFG1: Aflatoxin G1; AFG2: Aflatoxin G2; AFM1: Aflatoxin M1; DON: Deoxynivalenol; NIV: Nivalenol; ZEA: Zearalenone; OTA: Ochratoxin A; OTC: Ochratoxin C; OTB: Ochratoxin B; FB1: Fumonisin B1; FB2: Fumonisin B2; FB3: Fumonisin B3; MCLR: Microcystin-LR; MCRR: Microcystin-RR; MCYR: Microcystin-YR; and MCLA: Microcystin-LA.
* Percentage of relative cross-reactivity was calculated as the amount of toxin required for 50 % binding inhibition/amount of other toxins requiring 50 % binding inhibition × 100.
** Others: 3-acetyl DON, 3,4-diacetyl NIV, tetraacetyl NIV, Toxin T-2, Toxin T-2 acetyl, and diacetoxyscirpenol.
[30] Kawamura et al., 1988; [31] Kawamura, 2005; [32] Kawamura et al., 1989; [33] Iijima et al., 1996; [34] Kawamura e Emoto, 2006; [35] Nagata et al., 1995; [36] Tabuchi et al., 2015.
Table 1 shows the cross-reactivity of MAb (anti-mycotoxins & microcystins). It confirmed the high specificity of selected hybridomas, which were adequate for application in rapid surveys. Cross-reaction in immunoassays would be expected due to the biosynthesis of natural toxins in a sequential cluster of closely related structural substances. Nevertheless, the cross-reactivity within analogues can be advantageous in screening surveys of natural toxins compared with strongly specific individual analogue detection by HPLC.
Table 2 shows how ic-ELISA became established as reliable rapid technique to analyse mycotoxins and microcystins. Such local set-ups can allow safe supervision in one of the major food producing regions in Brazil, which was made possible due to joint research involving cell culture technologies, adaptation and proliferation of MAb producing hybridomas, and the development of immunoassays in loco. The standardized immunoassay was obtained through enhancing its sensitivity and adjusting to local conditions for the reagents, dilutions in ic-ELISA steps (upgrading crude extract preparation, antigen-protein conjugates for microplate coating, and dilutions of both the first and second antibody), and the analogue group for detection. The safety of the food, derived products, and water for analysis were amplified by awareness. These assays should be conducted for local consumption safety, the balance of agribusiness and exportation demand and importation independence.
\n\t\t\t\tItem\n\t\t\t | \n\t\t\t\n\t\t\t\tHybridoma\n\t\t\t | \n\t\t\t\n\t\t\t\tToxins\n\t\t\t | \n\t\t\t\n\t\t\t\tReagents: ic-ELISA steps\n\t\t\t | \n\t\t\t\n\t\t\t\tLOD / LOQ\n\t\t\t\t \n\t\t\t\t(µg kg-1)\n\t\t\t | \n\t\t\t\n\t\t\t\tELISA/\n\t\t\t\t \n\t\t\t\tHPLC\n\t\t\t\t \n\t\t\t\t(r)\n\t\t\t | \n\t\t\t\n\t\t\t\tCereal & products\n\t\t\t | \n\t\t||
\n\t\t\t\tCell line\n\t\t\t | \n\t\t\t\n\t\t\t\tMycotoxin/ Cyanotoxin\n\t\t\t | \n\t\t\t\n\t\t\t\tCoating\n\t\t\t | \n\t\t\t\n\t\t\t\tFirst MAb\n\t\t\t | \n\t\t\t\n\t\t\t\tSecond Ab: IgG-enzyme\n\t\t\t | \n\t\t||||
1 | \n\t\t\tDON.3 | \n\t\t\tDON | \n\t\t\tDON-HG-OVA 2 µg mL-1\n\t\t\t | \n\t\t\t1200 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t177.1 / - | \n\t\t\t0.93 | \n\t\t\tWheat grain[26]; wheat flour[27]\n\t\t\t | \n\t\t
2 | \n\t\t\tDON-HS-OVA 2 µg mL-1\n\t\t\t | \n\t\t\t19.2 µg mL-1\n\t\t\t | \n\t\t\t1:1000 | \n\t\t\t113.5 / 445.3 | \n\t\t\t\n\t\t\t | Wheat grain[28]\n\t\t\t | \n\t\t||
3 | \n\t\t\tDON-HS-OVA 2 µg mL-1\n\t\t\t | \n\t\t\t10.9 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t159.3 / 370 | \n\t\t\t- | \n\t\t\tBiscuita\n\t\t\t | \n\t\t||
4 | \n\t\t\tZEN.2 | \n\t\t\tZEA | \n\t\t\tZEN-OVA 2.5 µg mL-1\n\t\t\t | \n\t\t\t10.3 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t33.7 / 87 | \n\t\t\t- | \n\t\t\tWheat graina\n\t\t\t | \n\t\t
5 | \n\t\t\tZEN-OVA 2.5 µg mL-1\n\t\t\t | \n\t\t\t10.3 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t9.7 / 23.7 | \n\t\t\t- | \n\t\t\tBiscuita\n\t\t\t | \n\t\t||
6 | \n\t\t\tFB 1-2 | \n\t\t\tFB1\n\t\t\t | \n\t\t\tFB1- OVA 0.77 µg mL-1\n\t\t\t | \n\t\t\t1:50 | \n\t\t\t1:5000 | \n\t\t\t93 / - | \n\t\t\t0.94 | \n\t\t\tCorn graina,[21]\n\t\t\t | \n\t\t
7 | \n\t\t\tAF.2 | \n\t\t\tAF | \n\t\t\tAFB1-BSA 0.25 µg mL-1\n\t\t\t | \n\t\t\t0.094 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t2.0 / 4.6 | \n\t\t\t- | \n\t\t|
8 | \n\t\t\tDON.3 | \n\t\t\tDON | \n\t\t\tDON-HS-OVA 2 µg mL-1\n\t\t\t | \n\t\t\t10.9 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t302.8 / 589.3 | \n\t\t\t- | \n\t\t|
9 | \n\t\t\tZEN.2 | \n\t\t\tZEA | \n\t\t\tZEN-OVA 2.5µg mL-1\n\t\t\t | \n\t\t\t10.3 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t51.7 / 93.2 | \n\t\t\t0.91 | \n\t\t|
10 | \n\t\t\tAF.2 | \n\t\t\tAF | \n\t\t\tAFB1-BSA 0.25 µg mL-1\n\t\t\t | \n\t\t\t0.094 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t1.25 / 1.43 | \n\t\t\t0.97 | \n\t\t\tBroiler feed[24]\n\t\t\t | \n\t\t
11 | \n\t\t\tAFB1-BSA 0.25 µg mL-1\n\t\t\t | \n\t\t\t0.094 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t1.41 / 1.75 | \n\t\t\t0.98 | \n\t\t\tLaying hen feed[25]\n\t\t\t | \n\t\t||
12 | \n\t\t\tOTA.1 | \n\t\t\tOTA | \n\t\t\tOTA-BSA 0.077 µg mL-1\n\t\t\t | \n\t\t\t0.043 µg mL-1\n\t\t\t | \n\t\t\t1:1000 | \n\t\t\t0.17 / 0.32 | \n\t\t\t0.97 | \n\t\t\tRed winea\n\t\t\t | \n\t\t
13 | \n\t\t\t0.14 / 0.23 | \n\t\t\tWhite winea\n\t\t\t | \n\t\t||||||
14 | \n\t\t\t0.17 / 0.32 | \n\t\t\tTable winea\n\t\t\t | \n\t\t||||||
15 | \n\t\t\tOTA.7 | \n\t\t\tOTA | \n\t\t\tOTA-BSA 4.76 µg mL-1\n\t\t\t | \n\t\t\t1:2000 | \n\t\t\t1:1000 | \n\t\t\t3.75/ - | \n\t\t\t0.98 | \n\t\t\tGreen cofee[22]\n\t\t\t | \n\t\t
16 | \n\t\t\tM8H5 | \n\t\t\tMCLR | \n\t\t\tMCLR-BSA 1:20000 | \n\t\t\t1:20000 | \n\t\t\t1:5000 | \n\t\t\t- / 0.05 | \n\t\t\t- | \n\t\t\tFresh Water[37]\n\t\t\t | \n\t\t
Development of ic-ELISA: standardized immunoassay for mycotoxins and microcystins analysis.
ic-ELISA: Indirect competitive enzyme linked immunosorbent assay.
DON: Deoxynivalenol; ZEA: Zearalenone; FB1: Fumonisin B1; AF: Aflatoxin; OTA: Ochratoxin A; MCLR: Microcystin-LR; DON-HG-OVA: Deoxynivalenol-hemiglutarate-ovalbumin; DON-HS-OVA: Deoxynivalenol-hemisuccinate-ovalbumin; ZEN-OVA: Zearalenone-ovalbumin; AFB1-BSA: Aflatoxin B1- Bovine Serum Albumin; OTA-BSA: ochratoxin A- Bovine Serum Albumin; and MCLR-BSA: Microcystin-LR - Bovine Serum Albumin.
[26]Santos et al. 2011; [27] Santos et al. 2013; [28] Souza et al. 2014; [21] Ono et al. 2001; [24] Rossi et al. 2013a; [25] Rossi et al. 2013b; [22] Fujii et al, 2006; [37] Kamogae et al. 2006; aData not published.
The optimized ic-ELISA showed a correlation coefficient of >0.9 with HPLC (Table 2). The result obtained with anti-OTA MAb produced by hybridoma OTA.1 was adequate to analyse wine using 1:10,000 anti-OTA MAb and 1:30,000 OTA-BSA. However, the matrix interference in the OTA analysis in wine by ic-ELISA should be considered. In analysing 60 wine samples, only one was OTA positive by HPLC (0.12 ± 0.01 ng mL-1), whereas 11 false-positives were observed by ic-ELISA (range from 0.32 ± 0.02 to 0.47 ± 0.14 ng mL-1). False-positive data in red wine may be attributed to the interference of anthocyanins and other pigments on OTA-binding to the antibody [38, 39]. The influence of matrix interference in OTA detection by ic-ELISA could be explained using a principal component analysis through the relationship of higher trans-resveratrol and OTA levels in the positive samples (Figure 2). In contrast, the addition of condensed tannins can inhibit the binding activity of antibodies in ELISA [40].
Principal Component Analysis in the evaluation of wine samples, Paraná State: OTA (ochratoxin A), CAO (antioxidant capacity), trans-resveratrol and chromatic (hgraus, L*, C*). a) graphical representation in two dimensions (Principal Component 1- CP1 and Principal Component 2- CP2) and b) cluster analysis of parameters.
The undesired matrix effect and be minimized by diluting the crude extract prior to ic-ELISA; a 1:100 dilution of coffee extract minimized the matrix effect on OTA detection, regardless of the maturity stage [22]. Additionally, a dilution factor of 1:80 minimized the matrix effect when anti-DON MAb produced by Hybridoma DON.3 was used in ic-ELISA for wheat grain.
Table 3 shows the monitoring of natural toxins (mycotoxins & microcystins) by ic-ELISA developed for different food specimens, as well as in the freshwater since the 1990s. Corn, coffee, wheat, grain-derived products, wine, broiler and laying hen feeds, and fresh water in agricultural regions were analysed (Table 3). The table also shows some maximum limits established by Brazilian guidelines, the European Commission, and the World Health Organization.
\n\t\t\t\tItem\n\t\t\t | \n\t\t\t\n\t\t\t\tSAMPLING / MONITORING\n\t\t\t | \n\t\t\t\n\t\t\t\tIc-ELISA\n\t\t\t | \n\t\t|||||
\n\t\t\t\tCereal & products,\n\t\t\t | \n\t\t\t\n\t\t\t\tLocality\n\t\t\t | \n\t\t\t\n\t\t\t\tCrop Year\n\t\t\t | \n\t\t\t\n\t\t\t\tToxins\n\t\t\t | \n\t\t\t\n\t\t\t\t+/total\n\t\t\t | \n\t\t\t\n\t\t\t\tMean\n\t\t\t | \n\t\t||
\n\t\t\t\tFeed, Wine[41, 42]\n\t\t\t\t\n\t\t\t | \n\t\t\t\n\t\t\t\tMycotoxina\n\t\t\t\t\n\t\t\t | \n\t\t\t\n\t\t\t\t(n)\n\t\t\t | \n\t\t\t\n\t\t\t\t(µg kg-1)\n\t\t\t | \n\t\t||||
1 | \n\t\t\tWheat | \n\t\t\tGrain | \n\t\t\tNorth-West, North-East, South-West /RS | \n\t\t\t2006 – 2008 | \n\t\t\tDON | \n\t\t\t15 / 15 | \n\t\t\t2918.1 | \n\t\t
\n\t\t\t | \n\t\t\t | \n\t\t\t | North, Central, South-West /PR | \n\t\t\t2006 - 2008 | \n\t\t\t7 / 23 | \n\t\t\t1578.6 | \n\t\t|
\n\t\t\t | \n\t\t\t | \n\t\t\t | North/PR | \n\t\t\t2009 | \n\t\t\t36 / 50 | \n\t\t\t2379.4 | \n\t\t|
\n\t\t\t | \n\t\t\t | Flour | \n\t\t\tNorth/ PR | \n\t\t\t2009 | \n\t\t\t21 / 23 | \n\t\t\t2455.9 | \n\t\t|
2 | \n\t\t\t\n\t\t\t | Grain | \n\t\t\tCentral-South /PR | \n\t\t\t2010 - 2011 | \n\t\t\t84 / 84 | \n\t\t\t1879.3 | \n\t\t|
\n\t\t\t | \n\t\t\t | \n\t\t\t | North /PR | \n\t\t\t159 / 160 | \n\t\t\t848.9 | \n\t\t||
3 | \n\t\t\t\n\t\t\t | Biscuits | \n\t\t\tNorth /PR (Retail Market) | \n\t\t\t2013 | \n\t\t\t29 / 56 | \n\t\t\t742.4 | \n\t\t|
4 | \n\t\t\t\n\t\t\t | Grain | \n\t\t\tNorth, Central-South | \n\t\t\t2010 - 2011 | \n\t\t\tZEA | \n\t\t\t11 / 125 | \n\t\t\t161.4 | \n\t\t
5 | \n\t\t\t\n\t\t\t | Biscuits | \n\t\t\tNorth (Retail Market) | \n\t\t\t2013 | \n\t\t\t17 / 56 | \n\t\t\t56.1 | \n\t\t|
6 | \n\t\t\tCorn | \n\t\t\tGrain | \n\t\t\tCentral-South, Central-West, North / PR | \n\t\t\t1995 - 1996 | \n\t\t\tFB1\n\t\t\t | \n\t\t\t147 / 150 | \n\t\t\t5610.0 | \n\t\t
7 | \n\t\t\t\n\t\t\t | \n\t\t\t | Central-South / PR | \n\t\t\t2010 - 2012 | \n\t\t\tAF | \n\t\t\t12 / 75 | \n\t\t\t8.1 | \n\t\t
8 | \n\t\t\t\n\t\t\t | \n\t\t\t | DON | \n\t\t\t6 / 75 | \n\t\t\t2142.3 | \n\t\t||
9 | \n\t\t\t\n\t\t\t | \n\t\t\t | ZEA | \n\t\t\t36 / 75 | \n\t\t\t522.3 | \n\t\t||
10 | \n\t\t\tFeed[44]\n\t\t\t | \n\t\t\tBroiler | \n\t\t\tNorth / PR | \n\t\t\t2010 | \n\t\t\tAF | \n\t\t\t114 / 158 | \n\t\t\t2.2 -6.4 | \n\t\t
11 | \n\t\t\t\n\t\t\t | Laying hen | \n\t\t\tNorth / PR | \n\t\t\t2010 | \n\t\t\tAF | \n\t\t\t66 / 95 | \n\t\t\t9.61 | \n\t\t
12 | \n\t\t\tWine | \n\t\t\tRed | \n\t\t\tNorth / PR (Retail Market) | \n\t\t\t2006 - 2011 | \n\t\t\tOTA | \n\t\t\t8 / 47 | \n\t\t\t0.42 | \n\t\t
13 | \n\t\t\t\n\t\t\t | White | \n\t\t\t2006 - 2009 | \n\t\t\t4 / 23 | \n\t\t\t0.68 | \n\t\t||
14 | \n\t\t\t\n\t\t\t | Table wine | \n\t\t\tSouth-West, West | \n\t\t\t2010 - 2011 | \n\t\t\t10 / 34 | \n\t\t\t0.37 | \n\t\t|
15 | \n\t\t\tCoffee | \n\t\t\tGreen coffee | \n\t\t\tNorth / PR | \n\t\t\t2003 | \n\t\t\tOTA | \n\t\t\t15/68 | \n\t\t\t5.28 | \n\t\t
\n\t\t\t | \n\t\t\t | \n\t\t\t | \n\t\t\t | \n\t\t\t | Cyanotoxin | \n\t\t\t+/total | \n\t\t\tMean | \n\t\t
\n\t\t\t | \n\t\t\t | \n\t\t\t | \n\t\t\t | \n\t\t\t | (n) | \n\t\t\t(µg L-1) | \n\t\t|
16 | \n\t\t\tFresh Water[43]\n\t\t\t | \n\t\t\tTibagi River | \n\t\t\tNorth / PR | \n\t\t\t1999 - 2000 | \n\t\t\tMCLR | \n\t\t\t13 / 24 | \n\t\t\t0.28 | \n\t\t
\n\t\t\t | \n\t\t\t | Itaipu Lake | \n\t\t\tWest /PR | \n\t\t\t22 / 24 | \n\t\t\t18.35 | \n\t\t||
* | \n\t\t\t\n\t\t\t | Tibagi River | \n\t\t\tNorth /PR | \n\t\t\t2014 | \n\t\t\t1 / 6 | \n\t\t\t0.67 | \n\t\t|
\n\t\t\t | \n\t\t\t | Itaipu Lake | \n\t\t\tWest / PR | \n\t\t\t3 / 6 | \n\t\t\t0.65 | \n\t\t
Monitoring of natural toxins (mycotoxins & microcystins) by the rapid ic-ELISA method.
ic-ELISA: Indirect competitive enzyme linked immunosorbent assay.
* These analysis were carried out using a commercial Kit (Beacon Microcystin Plate Kit, USA).
PR: Paraná State; RS: Rio Grande do Sul State.
[41] The Brazilian Health Surveillance Agency (ANVISA, 2011) established the maximum levels of DON in flour and biscuits (1,750.0 µg kg-1), ZEA for biscuits (200.0 µg kg-1), AF for corn (20.0 µg kg-1), and OTA for wine (2.0 µg kg-1). The deadlines were established in RDC 07/2011 and will be extended to January 1, 2017 for DON in wheat and corn (3,000.0 µg kg-1), ZEA in wheat and corn (400.0 µg kg-1), and FB1 + FB2 in corn (5,000.0 µg kg-1) [42].
[43] The World Health Organization (WHO, 1998) established maximum levels of 1 µg of MCLR L-1 for drinking water and a Tolerable Daily Intake of 0.04 µg of MCLR kg-1 body weight.
c Mycotoxin / Cyanotoxin: DON, Deoxynivalenol; ZEA, Zearalenone; FB1, Fumonisin B1; AF, Aflatoxin; OTA, Ochratoxin A; and MCLR, Microcystin-LR.
[44] European Commission (2003). The maximum limit allowed by the European Commission is 0.02 mg aflatoxin B1 kg-1.
The application of ic-ELISA to monitoring freshly harvested corn from Paraná State (1991 to 2004 crops) indicated the widespread occurrence of fumonisins but a low occurrence of aflatoxins. In a recent study conducted in Paraná State, 74 corn samples were contaminated with an average of 1,840 µg of fumonisin kg-1, 36 of poultry feeds with 239 µg of fumonisin kg-1, and 9 corn factory residues with 23,676 µg of fumonisin kg-1, whereas the aflatoxin and trichothecene levels were approximately at the LOD values [45]. Ic-ELISAs, using monoclonal mAb produced by hybridoma cells (AF.2, ZEN.2 and DON.3), were developed and optimized for AFs, ZEA and DON detection (Table 2). In corn samples from an experimental farm in central-southern Paraná State, 12 samples were found to be positive for AF (mean of 8.1 µg kg-1), 36 samples for ZEA (mean of 522.3 µg kg-1) and 6 samples for DON (mean of 2142.3 µg kg-1) (Table 3).
An emphasis was placed on DON evaluations by ic-ELISA in wheat from 2006 to 2011 (Table 3). Paraná and Rio Grande do Sul States in southern Brazil produce 90 % of the national wheat [1]. This country depends on the importation of 5 to 6 million ton per year to provide for an annual domestic consumption of approx. 11 million ton, mainly used in bakery (55 %), pasta (17 %) and biscuit (13 %) processing [2, 46, 47]. Brazil is the world\'s second-largest biscuit producer, but the current low exportation (54,083 tons) results in nearly all production earmarked for domestic consumption, despite its ranking [48, 49]. In the wheat samples from experimental farms of north and central-southern of Parana State analysed by ic-ELISA, DON was detected in almost all of samples (243 positive samples of 244) and ZEA was detected in 10 of 125 samples (Table 3). In, wheat-based biscuits acquired from a local retail market in Londrina, Paraná State (56 samples) DON was detected in 29 samples (mean of 742.4 µg kg-1) and ZEA in 17 samples (mean of 56.1 µg kg-1) (Table 3). A study [50] analysed 23 cracker biscuit samples produced in Southern Brazil and group A trichothecene was non-detectable, but 18 samples were contaminated with DON (378 – 5295 µg kg-1), with 22 % of the samples at level over the Brazilian guideline limit (1,750 µg kg-1). When zearalenone was analysed in corn-based products (51 samples of popcorn and 50 corn grits) and cracked wheat (n = 109) commercialized in 18 counties of the Paraná state, ZEA was non-detected in cracked wheat samples, but one cracked corn sample contaminated 64 µg of ZEA kg-1 [50]. Fusariotoxin monitoring in wheat should be conducted in both domestic production and in imported wheat, which represents 50 % of the category.
Due to the possible carry-over of mycotoxins to tissues, the degree of exposure of broiler chicken and laying hens to fumonisins and aflatoxins through naturally contaminated feeds has been assessed (Table 3). Occurrence of fumonisins and aflatoxins were evaluated in four feed types intended for broilers (n=158), collected from a poultry breeding farm in Northern Paraná State [24]. Fumonisins were detected in 94.9 % of the feed samples at mean levels ranging from 0.52 µg g-1 (finisher) to 0.68 µg g-1 (pre-starter and grower), and aflatoxins were detected in 72.1 % of the feed samples at mean levels ranging from 2.22 ng g-1 (pre-starter) to 6.41 ng g-1(grower). The maximum estimated daily intake of FB1 for broilers (0.057 mg/kg body weight/day) was below the Lowest Observed Adverse Effect Level (2 mg kg-1 body weight day-1). Most of the aflatoxin positive samples (97 %) showed levels below the maximum limit allowed by the European Commission (0.02 mg aflatoxin B1 kg-1). To estimate the degree of exposure of laying hens to mycotoxins, a total of 95 mash feed samples were collected from January to December 2010 from the Experimental Farm at the University, Northern Paraná State, Brazil. Aflatoxins and fumonisins were detected in 69.7 % and 89.5 % of the feed (n=95) intended for laying hens at mean levels of 9.61 ng g-1 and 1.28 µg g-1, respectively. The estimated daily intake of FB1 for laying hens (0.038 mg kg-1 body weight day-1) was below the Lowest Observed Adverse Effect Level (2 mg kg-1 body weight day-1). Aflatoxin levels were below the maximum allowed limit by the European Commission in the majority of the positive samples (85.1 %), which indicated that some of the feed samples could have a negative effect on animal health and performance, but the risk would be very low.
Intensive agricultural activity has become an increasing concern due to the eutrophication of aquatic environments. Microcystins (MCs) were monitored in Itaipu Lake and Tibagi River in the north and west of Paraná State, respectively (1999 to 2000 and 2014). The reduction of microcystin levels in Itaipu Lake was likely a consequence of ecological programs encouraging the recovery of riparian forests, in addition to a change in planting management (Table 3). Such a reliable MAb-based rapid immunoassay has been a good choice for tracking mycotoxins and cyanotoxins and determining actions to be performed in a control strategy.
Monitoring of the corn chain in northern Paraná showed that 81 % (n = 435, crop 2003) and 98.8 % (n = 435, crop 2004) of corn was safe for human consumption, in regard to fumonisin. The decreasing trend in fumonisin contamination, when compared to previous studies [8, 9, 12], could suggest a conscious monitoring procedure at the quality control level, in accordance with the strict guidelines imposed by importing countries.
The main approaches in corn phytosanitary control involve pesticides and agricultural practices with an emphasis on tillage and crop rotation. Efforts have been focused on novel fungicides for Fusarium sp. control to maximize grain yield [51, 52]; however, several studies have shown that fungicide application can increase mycotoxin levels [53, 54]. The recommended dose of fludioxonil + metalaxyl-M (2.5 + 1.0 %) was insufficient to inhibit F. verticillioides growth in vitro, but it increased FB1 production from 3.5-fold to 12.5-fold (2.58 µg mL-1 when compared with 0.72 µg mL-1 in control), with an alteration in mycelial morphology [55, 56]. A scanning electron microscopy analysis showed that the fungicide caused the inhibition of hyphal growth and defects of hyphae, such as excessive septation, cell wall disruption, and withered hyphae, and extracellular material around the hyphae was rarely observed (Figure 3) [57].
Therefore, efforts to reduce mycotoxin levels should be focused on sustainable production. In uninterrupted planting in tropical regions, non-drastic management of cropping systems using culture rotation in no-tillage areas under different fertilizations emphasizing nitrogen rate, and low cost organic waste remain concerns in the protection of grain and soil conservation [58, 59, 60, 28].
Electron micrographs of F. verticillioides 103 F mycelia cultured in defined liquid media in the absence (control) and presence (treatment) of fludioxonil + metalaxyl - M at the dose recommended by the manufacturer (1.5 µL mL-1) showing the fibrillar extracellular material present in the control cultures (A and C) and withered hyphae and disruption of cell walls in the treatments (B and D).
The effect of conventional and no-tillage cropping systems in corn cultivated in summer following either oats or fallow in winter on natural fumonisin levels (2006 and 2007 growing seasons) has been assessed [60]. No-till corn following oats showed stronger fumonisin contamination patterns than the other treatments (2006 season, P < 0.05). Although no-till could be advantageous from a soil conservation standpoint, it may enhance fumonisin contamination in the tropics, contrasting another report [61] that there was no significant difference between conventional and no-till in fumonisin in monoculture corn in Northern Italy. When the nitrogen fertilizer rates (0 to 90.0 kg ha-1 N) on fumonisin contamination was evaluated, higher fumonisin levels were detected in plots with lower N (≤ 22.5 kg ha-1) than ≥ 45.0 kg ha-1 N, indicating a negative correlation between fumonisin and N rates [60]. Both N stress due to deficiency and excessive rates can increase the FB1 level in corn [62].
The nitrogen-fixing potential of Azospirillum sp. in the rhizosphere can increase yields, reduce costs and improve the nutritional quality of corn kernels. An experiment was conducted matching the inoculums of the Azospirillum brasilense Ab-V5 and Ab-V6 strains in corn seeds with N doses in Northern and Central-Southern Paraná in the 2010/2011 and 2011/2012 seasons [63]. Although the seed inoculation associated with N doses showed non-significant effects on fungal count, the inoculum treated plots showed lower fumonisin levels (p < 0.05) than the non-treated plots, indicating favourable trend towards agricultural practices with inoculants. Fumonisins were detected in 90 % of samples in 2010/2011 (mean, 0.62 µg g-1) and 97.5 % in 2011/2012 (mean, 4.34 µg g-1) in the northern region, whereas its occurrence was 45 % in 2010/2011 (mean, 0.14 µg g-1) and 100 % in 2011/2012 (mean, 2.67 µg g-1) in central-southern Paraná.
The use of landfill leachate in agricultural soils as fertilizers has been suggested as an alternative for the disposal of this effluent; however, heavy metals may be a limiting factor [63]. The application of increasing doses of leachate (0 to 130.8 m3 ha-1) increased the yield, protein content, lipid and ash in corn grain, but no effect was observed on fumonisin reduction, which occurred in all samples, with 31.2 of samples with levels over the maximum tolerable limit in Brazilian guidelines (5.0 μg g-1). An increasing trend in lead content was also observed in the 2009/2010 seasons, and in sodium (2011/2012 seasons) when the leachate rate was increased [63].
The management of plant density (60 to 105 thousand plants/ha) with N doses (0 to 240 kg ha-1) showed no effect on corn fungal count, but there was an increasing trend in fumonisin levels when plant density was increased. Total fumonisins (FB1 + FB2) were detected in corn grain at levels ranging from non-detectable to 7.80 μg g-1 (mean, 1.50 μg g-1) in the 2009/2010 season, while it was non-detectable to 23.36 μg g-1 (mean, 1.72 μg g-1) in the 2010/2011 season [63].
Efforts also should be focused on the safety and quality of the wheat chain, one of major universal components in food. Although 90 % of the national crop is centred in southern Brazil, domestic consumption still depends on importation [1, 2]. Table 3 shows that natural contamination of DON in wheat was non-equally distributed among different crops and was dependent on local and climatic conditions (the impact of agricultural management practices was evaluated in 2010 and 2011 seasons). Environmental conditions can shift the metabolic route of Fusarium graminearum, changing the fusariotoxin profile in grains, ex., leading to an increase of acetylated analogues of DON [64, 65]. Although such acetylated trichothecenes are considered less toxic than DON, a rapid deacetylation can take place in the digestive tract of mammals, turning into it to DON [66]. DON of the group B has been regarded as a unique trichothecene in wheat products under current Brazilian guidelines [41], although studies have indicated that group B trichothecenes, such as nivalenol (NIV) and acetylated analogues (3-acetyl-DON and 15-acetyl-DON), should be included [17].
In addition, lactic bacteria of the Lactobacillus plantarum group have shown versatile profiles concerning genes that can code for special functions such as biodegradation, absorption, and adherence to different surfaces in the vast natural microbiota in food niches [69, 68]. Lactic acid bacteria strains can be isolated from multiple wheat sources (grains, germ, bran, and flour) and have been tested against F. graminearum strain IAPAR 2218 (Figure 4). All tested strains demonstrated some DON-reducing potential, and the non-viable autoclaved L. plantarum cells (71.19 %) showed a higher effectiveness in DON reduction than viable cells (16.41 %). The probable mechanism of reduction would be the adsorption by cell walls [69, 70]. Lactic acid bacteria can also degrade a range of low molecular weight compounds, carrier compound families, and influx and efflux facilitators and mycotoxin degrading enzymes have been detected [71].
Effect of lactic acid bacteria isolated from different wheat sources (grains, germ, bran, flour) against F. graminearum strain IAPAR 2218. Inhibition Halo scale: (-): no inhibition; (+):1 to 5 mm; (++): 6 to 10 mm; (+++): 11 to 15 mm; and (++++): >15 mm.
Another use of naturally occurring microorganisms in the biocontrol/biodegradation of undesired natural toxins has been assessed for the reduction of cyanobacteria in drinking water. The potential of microcystin (MC) biodegradation has been tested in the following microorganisms: Sphingosinicella microcystinivorans (B9) isolated of the Lago Tsukui, Kanagawa-Japan; water kefir (mixture of lactic and acetic bacteria and yeast) (P4); L. acidophilus La-5 (P5); and yeast isolated of sugarcane (L5). The strain B9 degraded 99 % of MCs, while the strains P4, P5 and L5 degraded 44, 43 and 54 % of total MCs, respectively, after 96 h (Figure 5).
Biodegradation of microcystin by Sphingosinicella microcystinivorans (strain B9), water kefir (P4), Lactobacillus acidophilus La-5 (P5) and yeast (L5).
Strain B9 (S. microcystinivorans) showed the highest MCs degradation capacity and has been evaluated for its anti-cyanobacterial activity against 5 cyanobacteria strains, Microcystis sp. (C1), Microcystis sp. (C2), Anabaena ucrainica (C3), Phormidium tenue (C4), and Synechocystis (C5). After 96 h, the inhibition percentages (cellular counts) against cyanobacteria strains ranged from 41.4 to 79.3 %, while the inhibition percentages (concerning chlorophyll-a) ranged from 34.4 to 68.9 %.
In summary, adequate agricultural practices based on crop rotation, fertilization, soil biodiversity, resistant crops, and post-harvest management could reduce mycotoxin contamination in field. Further long-term strategies encouraging no-tillage cultivation, and the maintenance of riparian forests in extensive agricultural land would be goals to maintain water quality; and the sustainable production of nutrient-rich high-quality products would still be possible.
Traditional analytical techniques for food and feed quality inspection and compositional assessment are typically invasive and time-consuming, requiring extensive sample preparation, thus being unsuitable for applications in the highly demanding, fast-paced food processing segment. Recently, novel techniques have been investigated for fast, reliable and chemical-free food quality assessments. Near-infrared (NIR) hyperspectral imaging has emerged as an efficient and advanced tool, combining both computer vision techniques and NIR spectroscopy, which can be used for continuous monitoring, process control and quality assessments of agricultural products, food and feed materials. Because most food quality features are related either to the external appearance of the product or its chemical composition, either computer vision or NIR spectroscopy alone is adequate for monitoring organic samples in a fast, reliable manner. However, such techniques are still strongly dependent on other reference methods. Prediction of physical characteristics and chemical composition using NIR spectroscopy and/or computer vision methods has been reported on meat (chicken, pork, beef, lamb), cereals and grains (corn, wheat, soy, rye, coffee, cocoa), and fruits and vegetables (apple, citrus, berries). More specifically, there has been major interest in this technique in quality control, food safety and security, i.e., detection and prediction of contamination in agricultural products.
A study [72] compared NIR calibration methods for predicting protein, oil and starch contents in both whole and ground maize samples in the spectral range of 1100–2500 nm for reflectance and 680–1235 nm in transmittance modes. While the best models were obtained for the reflectance spectra of the ground samples, it was suggested that the transmittance mode for whole grains might be more useful due to its greater speed of analysis. Another study [73] developed a rapid single kernel NIR sorting instrument for maize and soybean. Prediction models for moisture of both seed types, and protein contents for soybeans were developed utilizing a spectrometric range from 906 to 1683 nm.
NIR reflectance and transmittance technologies have been investigated for contamination assessments of a range of cereal grain physical quality and chemical traits, and detecting and predicting levels of mycotoxins. Numerous applications have been developed, and cover almost all cereals in the globally important food grains, i.e., corn, wheat, rice and barley. An additional application has been to demonstrate the value in sorting grains infected with fungus or mycotoxins, such as deoxynivalenol, fumonisins and aflatoxins [74].
A shortwave infrared (SWIR) hyperspectral imaging system in the wavelength range between 1000 and 2500 nm was used to assess the potential AFB1 contaminants on the surfaces of healthy corn kernels. Key wavelengths that can indicate AFB1 and are used to differentiate levels of AFB1 were identified. A minimum classification accuracy of 88 % was achieved for the validation set and verification set, indicating that hyperspectral imaging technology could be used to detect AFB1 at levels as low as 10 ng/g, when applied directly on the corn surface [75]. Another study assessed the applicability of NIR for the rapid identification of mycotoxigenic fungi and their toxic metabolites produced in naturally and artificially contaminated products. Two hundred and eighty corn samples were collected in north-central Italy and analysed for fungal infection, ergosterol, and FB1 content. The results indicated that NIR could predict the incidence of kernels infected by F. verticillioides and also the quantity of ergosterol and fumonisin B1 in the meal. The best predictive ability for the percentage of global fungal infection and F. verticillioides was obtained using a calibration model utilizing corn kernels (r 2 0.75 and SECV 7.43) and maize meals (r 2 0.79 and SECV) 10.95), respectively [76].
A recent study on the quality assessments of meat products [77] reported the application of NIR reflectance as a potential method to predict quality attributes of chicken breast (Pectoralis major). Spectra in the wavelengths between 400 and 2500 nm were analysed, presenting clear differences between different quality grades of chicken (Figure 6). PCA performed on the NIR dataset revealed the influence of muscle reflectance (L*) influencing the spectra. PCA was not successful to completely discriminate between pale, soft and exudative (PSE) and pale-only muscles. High-quality PLSR were obtained for L* and pH models predicted individually (R2CV of 0.91 and 0.81, and SECV of 1.99 and 0.07, respectively). Sample mincing and different spectra pre-treatments were not necessary to maximize the predictive performance of the models. The results suggest that NIR spectroscopy may represent a useful tool for the quality assessment of chicken meat.
Average spectra for dark, normal and pale chicken samples (see [76] - “Reprinted from Food Chemistry, 168, Douglas Fernandes Barbin, Cintia Midori Kaminishikawahara, Adriana Lourenco Soares, Ivone Yurika Mizubuti, Moises Grespan, Massami Shimokomaki, Elisa Yoko Hirooka, Prediction of chicken quality attributes by near infrared spectroscopy, 554-560, 2015, with permission from Elsevier”).
The contamination of meat products has also been investigated. NIR transflectance and Fourier transform-infrared (FT-IR) attenuated total reflectance spectra of intact chicken breast muscle were collected and investigated for their potential use in the rapid, non-destructive detection of spoilage. PCA and PLS2-DA regression correctly classified 8 and 14 day samples (TVC days 8 and 14= 9.61 and 10.37 log10 CFU g−1) with several correlations that highlight the effect of proteolysis influencing the spectra. These correlations indicate that an increase in free amino acids and peptides could be the main factor in the discrimination of intact chicken breast muscle.
These studies have demonstrated that NIR methodology can be applied to monitor bacterial and fungal contamination in postharvest grains and fresh meats and to distinguish contaminated from clean batches to avoid cross-contamination with other materials during storage. However, there is still a demand for the development of cost-effective technologies for high-speed sorting. In the area of food safety, it is important to create robust prediction models based on reference methods by including a wide range of samples from different regions. For instance, it is well known that a major drawback of this technology is the application of ready-to-use prediction models from one country into samples from another region of the world. Prediction models are usually built in developed countries, but they are not useful for samples originating in developing countries, mostly due to inherent differences in sample composition, cultivation methods, climate and soil characteristics, etc. Once researchers overcome these obstacles, this technology will benefit farmers, the industry and consumers if it enables contaminated grain and other food samples to be identified and removed from the food chain.
Globalization demands quality and competitiveness throughout the food chain, as well as safe raw materials without deterioration. Agribusiness exports in Brazil reached US$ 5.64 billion in January 2015, according to the foreign trade statistics system of Brazilian agribusiness [78]. The five main exporter states in Brazil were São Paulo, Paraná, Mato Grosso, Minas Gerais and Rio Grande do Sul, whose participation represented approximately 69 % of total Brazilian exports, involving soy, sugar-alcohol complex, beef, chicken meat, soybean oil, cereal sales, and coffee.
Brazil is currently the third-leading country in chicken production, behind the USA and China, and the leading exporter of chicken meat [79]. The long-term trade projection estimates a production of up to 20.576 million tons by 2023, corresponding to an increase of 46.4 % between the years 2013 and 2023. In addition, the exportation of meat has been forecasted at 4.675 million tons in 2023 [80]. Further, poultry (broilers and turkeys) trade long-term projections of the USDA (2015) indicate that exportation could reach up to 4.982 million tons in 2024.
In this scenario of globalized agribusiness, corn stands out as the major component of animal feed production [4]. Figure 7 shows a scenario concerning corn purchased as a raw material in a potential importer country. The trend for importing of Brazilian grains continues to depend on the decrease or delay of the American harvest of agriproducts due to the unmatched infrastructural facilities and the storage, transport and port system established in the United States.
Corn importation in Japan, 2008 to 2014 [81].
Even with infrastructural problems, the bar chart shows that the decision to import Brazilian raw materials could unexpectedly increase and reached nearly five times the quota between the year 2012 and 2013.
The current effort on aggregation of value in agriproducts should be combined with continuous work on safety in highly productive regions, ex. broiler chickens for export, which depends on practical and reliable analytics facilitating quality and safety. Such an overall approach could result in promising healthy foods from potential producer regions in Brazil.
The authors thank the NANOBIO/CAPES Foundation (the Co-ordination for Formation of High Level Professionals) - Ministry of Education, the CNPq (the Brazilian Government Organization for grant aid and fellowship to Brazilian researchers) - Ministry of Science & Technology, the CNPq/Ministry of Agriculture, the Araucaria Foundation, and the Parana State Fund/SETI for the financial support through projects. The authors also thank the CNPq for the productivity fellowships granted to researchers, as well as the CAPES for fellowships at the levels of Postdoctorate, Doctorate and Initiation in Science and JICA (Japan International Cooperation Agency) for distinctive training support in Japan. A special thanks to Dr Yoshio Ueno (in memoriam) for introducing us to the advanced area of Microbial Toxins.
Pain is intrinsically private, and the concept of pain is difficult to describe and assess due to its subjective nature and individuals’ unique experiences of pain [1, 2]. Up until the mid-1980s, clinicians believed that infants, toddlers and persons with disabilities, specifically those with significant communication difficulties, either do not have pain or may have very high pain thresholds [3, 4, 5]. These myths and beliefs were reinforced by McCaffery’s widely accepted definition of pain at that time that stated that “pain is what the person says it is and exists whenever he or she says it does” [6, p. 95]. By default, McCaffery’s definition therefore suggested that all persons with the inability to communicate their pain verbally (including the aforementioned) may not have pain.
\nIn addition to their limited verbal ability to express pain, communication vulnerable children’s neurology may also impact on their ability to show other tell-tale signs of pain that transform the parts of the brain responsible for the expression of pain [5]. For this reason, clinicians repeatedly overlooked other signs of pain [4], such as changes in the children’s behaviour (withdrawal, acting clownish, having mood changes, displaying aggressive behaviour or exhibiting extreme tantrums) or changes in positioning (refusing to use the body part where pain is). This is because children with communication challenges may not display pain in the typical ways such as by crying or through facial changes [7, 8, 9, 10]. Clinicians often mistakenly regard these kinds of “different reactions to pain” as challenging behaviour and not as children’s alternative attempts of trying to express their pain [11].
\nLately, clinicians have started to acknowledge that the inability to communicate pain verbally does not negate the likelihood that a person is in pain or that they require applicable pain-relieving treatment [3, 10]. The International Association for the Study of Pain (IASP) updated the definition of pain in July 2020 [2, p. 2] to: “An unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage”. According to Raja et al. [2] the IASP also added six key notes as an expansion to the definition and to provide further context to the definition and the etymology of the word “pain.” Additional notes to the latest pain definition for example highlight that a person’s report of their pain should be acknowledged and respected and that verbal expressions of pain is only one of many behaviours to express pain [2]. Nevertheless, irrespective of patients’ ability or inability to verbally self-report their pain, it remains the ethical obligation of all clinicians to acknowledge and relieve the most vulnerable patients’ pain [12].
\nChildren with severe physical, sensory and/or cognitive disabilities affecting their receptive and expressive communication may not be able to verbally communicate their pain and other pain-related experiences [10, 13]. Children with languages or cultures different to those of the treating clinicians or with limited proficiency in the latter’s language often do not have the vocabulary to express their pain [14]. Furthermore, children who are receiving treatment in intensive care units – where medical intervention such as sedation, intubation or tracheotomy can influence their ability to verbally communicate – as well as children receiving palliative end-of-life support may also not be able to communicate verbally [13]. Authors refer to these groups of children as communication vulnerable [13, 14, 15]. Communication vulnerability is defined as a reduced ability in respect of expressive and/or receptive communication and can involve permanent vulnerability (such as children with severe communication disabilities) or temporary vulnerability (such as patients in critical care units receiving medical interventions that may influence their ability to speak) [16, 17].
\nThe inability to express pain verbally may result in communication breakdowns between the child and the clinician, which could result in risks such as non-treatment, adverse medical outcomes and increased anxiety for both patients and clinicians [18]. Clinicians often find it demanding to assess pain in communication vulnerable children [7, 19], as they have to attempt to interpret the children’s bodily movements, facial expressions and physiological signs [7]. As mentioned earlier, children with communication disabilities may express their pain in atypical ways that could influence clinicians’ interpretation of the children’s pain [10, 11, 19]. In the latest recommendations for clinicians to follow during pain assessment of those unable to self-report, Herr et al. proposed that as a first step, clinicians should become aware of potential causes of pain [20]. The second step in pain assessment is to try to obtain self-report from all patients [20]. Therefore, it is vital that alternative means of communication should be investigated to enable children with severe communication difficulties to self-report their pain.
\nHay et al. [21] promoted the use of self-reporting as the primary method for measuring the intensity and other features of pain. Thus, it was recommended that parents’ proxy reports of their children’s pain should only be used once the children’s reports were in doubt [21, 22]. Research has confirmed that speaking children themselves can give a clear self-report of their pain experience by verbally expressing their pain or using various pain assessment tools such as the Coloured Analogue Scale or the Faces Pain Scale-Revised [23]. However, Schiavenato and Craig [24] are of the opinion that pain assessment tools do not do justice to a patient’s pain experience as they oversimplify the demands for rating pain intensity without taking the type of pain into consideration. For this reason, a possible solution should be found for how communication vulnerable children can self-report their pain in ways other than by verbal accounts.
\nClinicians’ expertise to support communication vulnerable children in pain depends on the availability of reliable and valid information about the existence and precise nature of the child’s distress [25]. Self-report and observational measures of pain can be reviewed from the perspective of a model of human communication [26]. Therefore, to gain a better understanding of this complex pain communication process, clinicians and researchers need to grasp the challenges that children with disabilities – and particularly those who are communication vulnerable – may encounter when trying to express their pain. The social communication model of pain [26, 27] offers an inclusive theoretical framework to be used in this chapter, because it explains the dynamic interaction between the biological, psychological and social determinants of pain [28]. An adapted social communication model of pain for communication vulnerable children based on the model proposed by Craig [27, 28] warrants further discussion in this chapter.
\nCommunication plays an important part in any action that aims to improve health [29]. Communication is a social, dynamic and interchanging reciprocal process that involves persons (acting as a sender or receiver) [30]. Communication comprises verbal (speech) as well as non-verbal modes (gestures, a shared glance, facial expression) [31]. Symbols (abstract or concrete) are used to convey information from the sender to the receiver in order to achieve a shared meaning in a specific context or environment [30]. In other words, communication involves sender(s) and receiver(s) conveying information through a communication channel. Effective communication occurs when the intent and meaning of one person (e.g. the sender) is understood by another person (e.g. the receiver) [31]. For communication vulnerable children, this communication process poses a serious challenge, due to their inability to communicate verbally (i.e. the communication intent is lost if the receiver does not understand the communication channel used by the sender). Although these children may have the desire to communicate their pain, research indicates that communication vulnerable children often opt not to communicate their pain because their previous communication attempts were ignored, or simply because it takes too much physical effort trying to communicate their pain [32].
\nThe social communication model of pain was developed as a framework to explain how pain is experienced and to describe the multifaceted communication process required to adequately express and interpret pain and to have pain understood by others [26, 27]. The social communication model of pain underlines both the role of the sender who is the person in pain (e.g. the communication vulnerable child) and the ability of the receiver as the observer of the pain (e.g. clinicians) in understanding the experience of pain. Biomedical models, in contrast, focus on the sensory characteristics of pain, with no emphasis on the social factors of pain [26, 27, 33]. Since this chapter will proceed to focus on pain communication of communication vulnerable children, Figure 1 depicts the suggested adaptations to the social communication model of pain (based on Craig [27, 28]) as it relates to communication vulnerable children’s expression of pain.
\nAdapted social communication model of pain for communication vulnerable children (as based on Craig [27, 28]).
A proposed three-step pain communication process altered for communication vulnerable children highlights the different factors that may intervene in the children’s pain expression, the pain assessment and the accompanying treatment [10, 27, 28]:
\nPain experience – the inward personal painful pain experience that happens over time and is stimulated by both interpersonal and intrapersonal (biological and psychological) factors involves the status of the child before the event;
\nMessage – the encoding of the pain experience (e.g. the child’s understanding or making sense of the pain) and the expression of pain through expressive behaviours such as crying, exclamations or (verbal) self-report to make the pain known to observers (e.g. clinicians or parents);
\nObserver (receiver of message) – the process whereby observers decipher or decode pain behaviours to react and respond by providing appropriate pain management or pain-relieving treatment [34].
This model also highlights the possibility that observers’ own perceptions and responses to pain as based on their own pain experiences may influence their understanding of pain as well as how they will respond to the child’s pain experience. Although researchers and clinicians should be aware of their own bias towards pain, it will not be dealt with in further detail in this chapter.
\nIn short, the adapted social communication model of pain proposes that the communication of pain begins with the communication vulnerable child who experiences pain (A); it continues to describe how this experience influences the child to make sense of the pain (B) and to express it in atypical ways or by means of augmentative and alternative communication (AAC) modes. These pain expressions are made known to the observers (C), who decode the child’s pain to take appropriate pain management actions. The adapted social communication model of pain can thus be used to help researchers and clinicians to understand the pain in communication vulnerable children. Examples are children with a variety of disabilities such as Down syndrome, intellectual disabilities, autism spectrum disorder (ASD) or cerebral palsy (CP), or children who experience temporary communication vulnerability due to medical interventions such as intubation.
\nThe model considers that there are many ways that a child can encode (B) their pain experience (A). Thus, when decoding the child’s pain, observers (C) need to be open to other modes that children may use to communicate their pain. A child’s self-report of pain is influenced by the pain context as well as their emotional, sensory, cognitive, developmental and cultural composition [2, 35, 36]. The social factors and reciprocal, repeating and dynamic effects of pain communication are acknowledged during this pain account within human beings [28]. In the social communication model of pain, a clear distinction is made between historical and current biological and social factors. For example, intrapersonal factors refer to a person’s temperament to react based on their biological, psychological and social histories. Craig [28] highlights that, during the pain event (A), the immediate social and physical environment has a powerful effect on both the person in pain (e.g. the communication vulnerable child) and on the observers (C). The internal subjective pain experiences of communication vulnerable children will now be discussed based on the adapted social communication model of pain for communication vulnerable children (Figure 1).
\nThe way persons express pain can give insight into their pain experiences. Pain expressions involve the person’s observable response (such as their pain behaviours) to a noxious stimulus, whereas a person’s pain experience is private and internal and involves severity of discomfort [27]. Based on their own experiences with pain, each individual displays different potential behavioural reactions to pain [27]. For example, children who have had negative pain experiences during needle procedures may exhibit more severe responses to pain because of their previous negative experiences. Additionally, their individual biological capabilities trigger their complicated expressions of pain [2]. Children with significant communication difficulties have different disability diagnoses with unique pain-related experiences related to these disabilities (e.g. children with CP or ASD).
\nAlong with biological capabilities, the constructs behind pain expression are the impact of language and cognitive development as well as social interaction and experiences. The expansion of pain-related vocabulary progresses along a similar sequence as does natural language development [37, 38]. The theoretical constructs that underlie pain expression within communication vulnerable children with various aetiologies will now be discussed in more detail.
\nAll children experience pain on a regular basis. Young children with typical development may respond to everyday pain such as bumps and bruises by crying, verbalisations or spoken words to express their pain experiences. They usually start to use the word “pain” by the age of 6 years [37]. On the contrary, children with disabilities might have more pain incidents more often than their peers without disabilities. For example, children with disabilities may experience more acute pain incidents due to needle procedures (such as blood drawing or receiving blood transfusions) and recurring medical procedures and treatments (such as range-of-motion manipulation during physiotherapy for children with CP) to maintain their health [3, 39, 40].
\nYoung children with CP experience high occurrences of chronic and acute pain [19, 41]. In an Australian study conducted by Ostojic and colleagues [19] to determine the prevalence of pain in children with CP, they found that two in three children with CP experienced acute pain and one in three children had chronic pain. Furthermore, the study revealed that children with CP, functioning on levels IV and V of the Gross Motor Function Scale (GMFCS), have a bigger risk of suffering from chronic pain [19]. This group also has communication challenges and may need alternative means to communicate their pain [19, 41]. Multi-factorial reasons for pain in children with CP could include spasticity, contractures and the incapacity to walk [19, 41, 42]. Spasticity and the inability to change their positioning to decrease pressure on certain body parts may also lead to contractures, musculoskeletal and gastrointestinal pain [43]. In a study among children with CP in South African schools, Adolfsson and colleagues [44] found that South African children with CP often experience hip dislocations– resulting from spasticity that caused hip displacements and ultimately lead to hip dislocations. As such, persons with CP have to undergo constant surgical procedures and medical interventions throughout their life span in an attempt to correct or rehabilitate orthopaedic problems associated with their condition [41, 43, 45]. All these procedures, including range-of-motion manipulation and assisted stretching, are painful experiences [44]. Communication through the use of AAC communication strategies is therefore crucial for children with CP to ensure that they can express their pain and receive appropriate pain treatment [41].
\nChildren with intellectual disabilities are at risk of experiencing a variety of painful somatic conditions due to comorbidities such as contractures, gastro-oesophageal refluxes, and epilepsy [11, 46]. These children with intellectual disabilities often experience socio-communicative deficits typical of children with ASD, for example they may not use facial expressions or make eye contact to display pain or other emotions [11, 46, 47]. Children with intellectual disabilities also express their pain consistent with their level of cognitive and physical development and not necessarily consistent with their chronological age [46]. Some atypical expressions, such as hand flapping or hand rubbing, smiling or freezing has been observed when children with intellectual disabilities were not able to verbalise their pain [5]. Yet, according to Doody and Bailey [9], children with intellectual disability who are unable to communicate their pain in a typical manner seem to have less opportunity to receive pain treatment.
\nChildren with Down syndrome also fall in the group of children with intellectual disability who can be expected to experience pain as a result of their disability. They are at high risk of secondary pain-related experiences such as the development of hip abnormalities and oral health issues [3, 48]. Children with Down syndrome have higher occurrences than their peers with typical development of dental problems due to frequent incidence of periodontal disease and chronic facial pain disorders [3]. They may also experience chronic pain due to congenital heart anomalies, bone fractures due to osteoporosis, or eczema – to name a few conditions [5]. Davies [48] reported that, compared to their siblings with typical development, children with Down syndrome have a decreased tendency to react to pain – but that does not mean that they are unresponsive to pain. Due to lower cognitive functioning, children with Down syndrome may not have the ability to localise the painful stimulus, because their pain-related vocabulary only tends to develop at a later stage. Their limited pain-related vocabulary may thus influence their ability to communicate pain [38].
\nAs with children with CP, children with intellectual disabilities such as Down syndrome or ASD also experience a large number of pain incidents and they are sometimes two to three times more at risk of an injury than their peers with typical development [10, 49]. Children with ASD often display challenging and self-injurious behaviour, as well as extreme tantrums that could lead to injury and pain [10]. Some children with ASD may also have trouble expressing their pain, due to their typical delay in language development and possible cognitive impairment [10, 50]. If children with ASD do use speech, they struggle to convey their emotions and the intensity of their pain experiences due to their monotone intonation. In addition, they do not usually use the same facial expressions and gestures that their peers with typical development would do to express their feelings. The pain expressions of children with ASD are distinctively individual and may differ from those of the larger population, considering the fact that children with ASD experience socio-communicative impairments and therefore may not understand social closeness as their peers with typical development would do [3].
\nBesides the communication difficulties of children with disabilities, this chapter also focuses on children who experience a temporary communication vulnerability due to medical procedures (such as intubation) or life-threatening conditions (such as cancer). For example, critically ill children who have been admitted to paediatric intensive care units suffer a temporary loss of their expressive or receptive communication [13]. These communication vulnerable children show stress, frustration and anxiety, and are at a greater risk of being treated incorrectly by clinicians who wrongly decode the children’s pain message [15, 51]. Even clinicians such as nurses often mention their feelings of frustration when they find it difficult to grasp what their paediatric patients are trying to communicate [7]. The vast significance of efficient alternative means of communication to ensure safe treatment of paediatric patients is therefore emphasised [15].
\nSpoken language is seen as the ultimate means of communicating pain [52]. Language and cognitive development influence children’s use of words to describe their pain experiences in such a way that observers (clinicians) can decode the message correctly and respond appropriately with pain-relieving treatment [53]. Language learning occurs within a physical and social context determined by actual people, objects, activities and events in the child’s environment [54]. Children learn about new concepts in the world while interacting with their physical environment, which forms the foundation for their lexical development [54]. For example, the words parents use to communicate with their children during painful experiences enable children to acquire new pain-related vocabulary [38]. Parents tend to talk to their children about pain on an age-appropriate level, thus enlarging their children’s pain-related vocabulary. For example, when a child cries when injured, the parent might respond with exclamations or words such as “Ouch! You got hurt!” thereby enabling the child to add meaning to the painful experience and to expand their repertoire of pain-related vocabulary [55].
\nHowever, since children with severe communication difficulties do not have the same contact with their social environment as their peers with typical development, they may find the language-learning process challenging [54]. Whereas children with typical development gain new knowledge about the world they live in through their encounters with their environment, children with disabilities have reduced access to their environment. This makes it more challenging for them to acquire new concepts without having the relevant previous knowledge to build on [54]. It is consequently the adults’ responsibility to guarantee that children with severe communication difficulties are exposed to a social environment that includes people, objects and possible pain experiences. This exposure to facilitate children’s language development can be achieved for instance through play activities like doctor-doctor play with peers [54].
\nLanguage development corresponds with cognitive development and as children mature cognitively, they can describe their pain more successfully [52]. Younger children tend to explain the bodily sensations they experience during pain in a more concrete manner (such as ‘my stomach hurts’) due to their limited cognitive and language skills [56]. As children’s thinking develops on a symbolic level, they start to use more graphic descriptors such as “terrible” or “beating”, while older children start to add intensifiers, such as “really bad” when describing their pain [53]. Since children with severe communication difficulties may not be able to verbally express their pain, Johnson et al. [57] proposed that clinicians such as speech-language therapists provide these children with preselected pain vocabulary that can be added to their AAC system to enable them to express their pain appropriately.
\nApart from disability aetiology, language or cognitive development, gender is another intrapersonal factor that might have an impact on the development of children’s pain-related vocabulary [37, 38, 58, 59].
\nGender differences in pain expression and pain-related vocabulary – despite similar pain experiences – are often highlighted in literature [38, 60, 61, 62]. As girls typically develop expressive vocabulary sooner than boys, Frank et al. [38] found a slight advantage in girls’ pain-related vocabulary, which may imply that pain-related language acquisition could be related to other factors. For example, girls tend to be more emotive and more expected to complain and also report their pain experiences more frequently than boys [52]. Contrary to girls, boys tend to be more passive or have more anger-related vocabulary in response to pain due to an injury [38]. In the event of communication vulnerable children, the differences between the reactions to pain by boys and girls are not clear [8]. However, it was found in literature that adult observers’ responses to children’s pain experiences tend to be influenced by gender-stereotyped attitudes, and that girls were treated in a different way than boys [62, 63, 64]. Clinicians are often biased and expect girls to experience more pain than boys [63, 64, 65].
\nAccording to the adapted social communication model of pain, interpersonal factors such as family settings, children’s social and cultural environment, as well as previous hospitalisations may further influence children’s experience and expression of pain [27].
\nThough some characteristics of pain-related language seem to be universal, substantial influences of family and ethnic contexts are also repeated in the specificity of pain-related language due to the nature of the social setting in which children are growing up [55, 66]. The entire family is affected by children’s chronic pain experiences and these experiences are often stressful for other family members as well. The treatment prescribed to manage the child’s pain can result in interferences in planned family events, thus upsetting or disrupting the overall family system [66].
\nFrom the perspective of the family systems theory, family dynamics influence the way children understand and talk about their pain [22, 62]. Parents are the role models for their children to learn words to express pain [55]. As children’s cognitive and social skills develop, they learn to talk about pain by observing how their parents respond to and talk about their children’s pain experiences [66]. Parents’ socio-economic background, education and age may influence the way in which they respond to their children’s pain. For example, in an American study by Rowe [67] – who investigated why parents from different socio-economic statuses communicate in different ways with their children – it was found that more educated parents and parents from advantaged backgrounds tended to talk more often to their children and use a bigger variety of words and longer utterances thereby expanding their children’s language ability and pain-related vocabulary. Younger parents also tended to use different pain words in comparison with older parents [68].
\nBirth order also impacts on children’s development of pain-related vocabulary [38]. Younger children observe their older siblings’ use of pain words, which stimulates their own development of pain-related vocabulary [38]. It was reported that the presence of one or more older siblings has an impact on children’s use of pain words compared to those children without older siblings [38]. Moreover, children with siblings who had previously been hospitalised had a larger vocabulary than those with siblings who had never been hospitalised before. This suggests that experience plays a role in the learning of pain language because these children had to deal with the illness or hospitalisations of their sibling(s) [38].
\nApart from family practices, children develop an understanding of pain-related language within their sociolinguistic environment [66, 69]. Children’s language is influenced by their cultural beliefs, social groups and communities [69]. There are differences between the beliefs of diverse cultures and their views on parents’ roles in their children’s language development. In some cultures, parents may not react to their children’s utterances: they are of the opinion that adults must not teach children to talk, as they will eventually learn to talk on their own [67]. Some family and cultural beliefs can also result in disparities in the way children learn about pain and react to pain [36]. In some Nguni and Sotho cultures in South Africa, for example, boys are taught that they may not express their pain, because showing or expressing pain is a sign of weakness or lack of courage [70].
\nClinicians should therefore acknowledge cultural differences and try to understand the culture of the communication vulnerable child. They should ask detailed questions to help understand the child’s pain condition and to prevent any misunderstanding [52]. Clinicians should for instance be aware of the fact that in some cultures it is considered disgraceful to ask for pain relief, while people in other cultures believe that a godly intervention will relieve pain when necessary [62, 70].
\nChildren’s understanding (and the significance) of their first painful experience due to tissue injury will intensify with experience – either through positive or negative contextual associations [2]. Children learn the use of the word “pain” through their experiences related to injury [58]. Hospitalisations help children to develop pain vocabulary based on their personal experiences with pain. Therefore, children with previous hospitalisations who experience pain events more often and who have learnt and processed the concept of pain (and pain management) tend to have a larger pain-related vocabulary than those who have never been admitted to hospital before [38].
\nFrom the discussion above, it is clear that communication vulnerable children experience challenges to express their pain and need alternative means – such as AAC strategies and systems – to communicate their pain. AAC involves a variety of communication strategies that can be used to aid communication attempts of persons with communication challenges to either augment their speech or to be used as an alternative means to speech [31]. Regarding the adapted social communication model of pain, one can agree that when the communication vulnerable child is offered the use of AAC to express their pain (A), the form (or communication mode used) is less important than ensuring that the message (B) is understood by the observer (C). AAC systems are classified as either unaided or aided. Unaided AAC systems are defined as the use of only body parts to convey messages such as by pointing, making gestures, body language movements, facial expressions, and manual signing [31]. Aided AAC systems include low-technology aids that need no electronic programming (e.g. pen and paper, and symbol-based communication boards), as well as high-technology aids such as speech-generating devices [71]. Clinicians should be encouraged to incorporate AAC strategies and tools to enable communication vulnerable child patients to communicate their pain.
\nAAC strategies and systems have been successfully used with communication vulnerable children in various settings, including hospital settings [13, 16, 17, 18, 71, 72, 73]. Next, some potential AAC strategies are proposed to support communication vulnerable children to express their pain in order for observers (C) to understand the messages (B). The suggested AAC strategies will focus mainly on low-technology systems although all these strategies could also be incorporated in apps on digital mobile devices (smart phones or tablets) to enable communication vulnerable children as well as clinicians and researchers to gain a history of pain communication and subsequent pain treatment [74].
\nCommunication boards are low-technology AAC systems used to display pictures (photographs, line drawings or graphic symbols) to enable communication vulnerable persons to communicate [31]. When designing a communication board, aspects such as the type of symbol (photograph, type of line drawing, graphic symbols or written words), the symbol size (to best accommodate the child’s visual and motor skills), symbol colour (to ensure contrast and increase the ease of finding a word within a particular word class), board layout and display (e.g. using the left-to-right Fitzgerald-key outlay as a precursor to reading), as well as the child’s vocabulary need should be taken into consideration [71]. For example, children with physical disabilities or limited range of movement may not be able to access symbols that are too far apart.
\nJohnson et al. [53] conducted a scoping review to compile a list of children’s pain-related vocabulary in an attempt to provide clinicians and parents with possible pain words that children would typically use to express their pain. In this scoping review, 17 studies from diverse cultures in countries such as the United States of America, Canada, Finland, Kuwait, South Africa, Spain and Sweden were included. It was interesting to note that the meaning of children’s pain-related words in the native language translated to the same English word or words [53]. The study also showed that clinicians from different countries could use this list of pain-related words to compile basic pain-related communication boards that could be further individualised for their communication vulnerable paediatric clients [53].
\nIn a follow-up pilot study by Gerber [75], 6- to 9-year-old children were asked to choose which symbols from two symbol sets, namely Picture Communication Symbols [PCS™] and Bildstöd symbols (
The discussion earlier in this chapter makes it clear that children’s previous negative pain-related encounters influence how they perceive new pain experiences. Furthermore, since children with ASD and intellectual disabilities need routine to function optimally, visual schedules can be used to great benefit to prepare them for specific medical procedures. This preparation could reduce their anxiousness due to unfamiliarity with the procedure or previous negative experiences [15, 76]. A visual schedule should include a step-by-step and easily understandable format with pictures accompanied by written words (see Figure 2 for example). These will provide children with the necessary information to help them feel that they are in control of the imminent frightening procedures [77]. Visual schedules can be offered either in paper format (low-technology) or, where applicable, in a video story-based format.
\nVisual schedule of a needle procedure.
Children with severe physical disabilities and limited movements may not be able to use their fingers to point to choices on a low-technology communication board. Therefore, the use of eye gaze displays is proposed. With eye gaze, the child is instructed to use their eyes to look at a picture or word on the display and then glance at the communication partner (observer), who will then verbally confirm the child’s selection [15]. Figure 3 is an example of an eye-gaze flipchart display.
\nEye gaze flip chart.
During pain assessments of communication vulnerable children, clinicians or researchers can also ask the child pain-related questions providing them three options: “Yes”, “No”, “Not sure”. Communication vulnerable children often have clear yes/no responses (e.g. head nodding to indicate “Yes”). Should communication vulnerable children have no typical yes/no responses, the clinician can ask the child to blink their eyes (“Yes”), close their eyes (“No”), or to look away to indicate that they are not sure what to answer. In this case, the clinician should refrain from asking more than one close-ended question at a time (e.g. “Does it hurt?” and “Do you hurt in your [body part]?”). The clinician should rather ask only one question (e.g. “Does it hurt?”) to ensure that the child can give an appropriate response.
\nAppropriate pain management relies on the ability to accurately assess pain. For children, a common method to communicate pain is the use of pain scales [13]. Pain scales that are often used in clinical and research practice typically depict faces, colours or numeric grading [13]. An example of faces pain scales that are built on how children communicate their feeling(s) in a facial expression is the Faces Pain Scale-Revised (FPS-R) [78]. Colours and numeric grading are typically used in analogue scales that are based on increments to indicate pain severity, and these allow children to show that a somewhat larger or smaller pain is experienced (examples are the Colour Analogue Scale (CAS) [79]; and the Numeric Rating Scale (NRS) [80]). In a systematic review by Birnie et al. [23] on recommendations for the selection of children’s self-report rating scales for pain intensity, the FPS-R, CAS and NRS were recommended for self-report of acute pain. However, though these self-report scales are freely available, clinicians and researchers should keep in mind that they may not be effective for everyone [13]. For example, while some of these scales may not need expressive language, receptive language skills are crucial, as children are expected to comprehend and know the meaning of words such as “hurt” or “pain” when using these scales [26].
\nThis chapter aimed to address communication vulnerable children’s experiences of pain and their need for alternative ways to express their pain so as to receive appropriate pain treatment. The concept of communication vulnerability was explained framed in the context of the adapted social communication model of pain for communication vulnerable children. According to this model, there are many ways in which communication vulnerable children can encode (B) their pain experience (A). The model also emphasises the need for observers (C) to be open to other communication modes that children may use to communicate their pain. The discussion centred on the pain experiences of communication vulnerable children such as children with Down syndrome, with intellectual disabilities, autism or cerebral palsy, as well as of children in intensive care settings who experience temporary communication vulnerability. The chapter concludes with suggestions on how AAC strategies can be used to support communication vulnerable children in communicating their pain.
\nThe author would like to thank and acknowledge Prof Stefan Nilsson from Gothenburg University and Prof Juan Bornman from the Centre for AAC, University of Pretoria for their valuable comments to improve the content of this manuscript. The author would further like to thank Ms Olivia Loots for the drawings as portrayed in the three figures in this chapter.
\nThe funding from the National Research Foundation in South Africa to this project is also acknowledged.
\nThe author declares no conflict of interest.
.
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