References studying the engineering properties of several seeds
\\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!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 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 261 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!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"7000",leadTitle:null,fullTitle:"Legume Crops - Characterization and Breeding for Improved Food Security",title:"Legume Crops",subtitle:"Characterization and Breeding for Improved Food Security",reviewType:"peer-reviewed",abstract:"Legumes are flowering plants found in most of the archeological records of plants. Legumes are efficiently used as food crops for humans and animals, pulps for paper and timber manufacturing, sources for fuel and oil production, ornamental plants, and cover crops such as cereals and other staple foods. Additionally, they can be utilized for other purposes, including the production of massive amounts of organic nitrogen. This book reviews the fundamental advances related to the characterization and breeding of legume crops for improved food security. Moreover, it sheds new light on the current research trends and future research directions related to legume crop studies. This book will provoke interest for various readers, researchers, and scientists, who may find this information useful for the advancement of legume productivity.",isbn:"978-1-83968-087-8",printIsbn:"978-1-83968-086-1",pdfIsbn:"978-1-83968-088-5",doi:"10.5772/intechopen.73753",price:119,priceEur:129,priceUsd:155,slug:"legume-crops-characterization-and-breeding-for-improved-food-security",numberOfPages:122,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"4d0f73bf883bbb984cc2feef1259a9a7",bookSignature:"Mohamed Ahmed El-Esawi",publishedDate:"December 11th 2019",coverURL:"https://cdn.intechopen.com/books/images_new/7000.jpg",numberOfDownloads:7422,numberOfWosCitations:5,numberOfCrossrefCitations:6,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:15,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:26,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"August 30th 2018",dateEndSecondStepPublish:"September 20th 2018",dateEndThirdStepPublish:"November 19th 2018",dateEndFourthStepPublish:"February 7th 2019",dateEndFifthStepPublish:"April 8th 2019",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"191770",title:"Dr.",name:"Mohamed A.",middleName:null,surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. El-Esawi",profilePictureURL:"https://mts.intechopen.com/storage/users/191770/images/system/191770.jpeg",biography:"Dr. Mohamed A. El-Esawi is a visiting research fellow at the University of Cambridge, United Kingdom, and Associate Professor of Molecular Genetics, Botany Department, Faculty of Science, Tanta University, Egypt. Dr. El-Esawi received his BSc and MSc from Tanta University, and his Ph.D. degree in Plant Genetics and Molecular Biology from Dublin Institute of Technology, Technological University Dublin, Ireland. After obtaining his Ph.D., Dr. El-Esawi joined the University of Warwick, United Kingdom; University of Sorbonne, France; and University of Leuven (KU Leuven), Belgium as a visiting research fellow. His research focuses on plant genetics, genomics, molecular biology, molecular physiology, developmental biology, plant-microbe interaction, and bioinformatics. He has authored several international peer-reviewed articles, book chapters, and books, and has participated in more than sixty conferences and workshops worldwide. Dr. El-Esawi is currently involved in several biological science research projects.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"8",totalChapterViews:"0",totalEditedBooks:"9",institution:{name:"Tanta University",institutionURL:null,country:{name:"Egypt"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"350",title:"Agrology",slug:"agrology"}],chapters:[{id:"69148",title:"Introductory Chapter: Characterization and Improvement of Legume Crops",doi:"10.5772/intechopen.89369",slug:"introductory-chapter-characterization-and-improvement-of-legume-crops",totalDownloads:590,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Mohamed A. El-Esawi",downloadPdfUrl:"/chapter/pdf-download/69148",previewPdfUrl:"/chapter/pdf-preview/69148",authors:[{id:"191770",title:"Dr.",name:"Mohamed A.",surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. El-Esawi"}],corrections:null},{id:"68094",title:"Novel Therapeutic Uses of Legume Crops in Southern South America",doi:"10.5772/intechopen.85659",slug:"novel-therapeutic-uses-of-legume-crops-in-southern-south-america",totalDownloads:1122,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The Argentine flora comprises more than 10,000 species, and many of them have been recorded as having medicinal, antimicrobial, and nutraceutical uses in humans as well as veterinary uses. In this chapter, native species/populations from the north of Argentina have been identified, selected, and characterized using morphological, chemical, and molecular techniques. Bauhinia forficata subsp. pruinosa was found to have anti-inflammatory, antidiabetic, diuretic, and analgesic activity and Senna spectabilis var. spectabilis has been found to have antibacterial, antibiofilm, antifungal, and antioxidant properties. The characterization and conservation of the native germplasm will allow us to propose future protocols of adaptation and technological processes to improve the quality of life in the rural areas and sustainable growth. This process will be achieved through a future integral and rational use that contemplates the conservation of the wild populations and their habitat. Thus, new resources will be generated, and the native flora of the country will gain value, strengthening the regional and territorial development of the agricultural and agroindustrial system. In addition, the domestication practices oriented to an integral management of the crop without extraction of the biological resource from the natural habitat minimize the impact of ecosystem degradation by overexploitation associated with landscape fragmentation.",signatures:"Renée Hersilia Fortunato, Virginia Fuentes Baluzzi, Fernando De Diego, Rodrigo T. Biagioni and Alejandro Daniel Esquivel",downloadPdfUrl:"/chapter/pdf-download/68094",previewPdfUrl:"/chapter/pdf-preview/68094",authors:[{id:"272187",title:"Dr.",name:"Renée",surname:"Fortunato",slug:"renee-fortunato",fullName:"Renée Fortunato"},{id:"288386",title:"BSc.",name:"Virginia",surname:"Fuentes Baluzzi",slug:"virginia-fuentes-baluzzi",fullName:"Virginia Fuentes Baluzzi"},{id:"288387",title:"MSc.",name:"Fernando",surname:"De Diego",slug:"fernando-de-diego",fullName:"Fernando De Diego"},{id:"288388",title:"Mr.",name:"Rodrigo",surname:"Biagioni",slug:"rodrigo-biagioni",fullName:"Rodrigo Biagioni"},{id:"288390",title:"Mr.",name:"Alejandro",surname:"Esquivel",slug:"alejandro-esquivel",fullName:"Alejandro Esquivel"}],corrections:null},{id:"64900",title:"Ethnomedicinal Values of Legume Plants in Pakistan",doi:"10.5772/intechopen.82762",slug:"ethnomedicinal-values-of-legume-plants-in-pakistan",totalDownloads:673,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The data on medicinal plants in the vegetation of Pakistan was studied and surveyed from September to November, 2018. Different ethnomedicinal species were recorded which are used by local inhabitants as a medicine, fodder, fuel, and for agricultural purpose. Many of the medicinal plants recorded are used for the treatment of two or more diseases by the local people. The family Fabaceae was dominant with respect to medicinal plants. The precious knowledge of medicinal flora is rapidly vanishing due to the illiteracy among the local people and also due to destruction of the medicinal plants. The present study was designed to convey the knowledge and importance of medicinal flora as well as traditional uses of such plants in daily life.",signatures:"Faisal Hussain and Farzana Usman",downloadPdfUrl:"/chapter/pdf-download/64900",previewPdfUrl:"/chapter/pdf-preview/64900",authors:[{id:"199137",title:"Dr.",name:"Faisal",surname:"Hussain",slug:"faisal-hussain",fullName:"Faisal Hussain"},{id:"272448",title:"Dr.",name:"Farzana",surname:"Usman",slug:"farzana-usman",fullName:"Farzana Usman"}],corrections:null},{id:"66497",title:"Starch Granules from Cowpea, Black, and Carioca Beans in Raw and Cooked Forms",doi:"10.5772/intechopen.85656",slug:"starch-granules-from-cowpea-black-and-carioca-beans-in-raw-and-cooked-forms",totalDownloads:1093,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Starch applications in food systems are mainly influenced by solubility, gelatinization, paste viscosity, digestibility, and retrogradation. These characteristics result from properties such as the size and shape of granules, amylose and amylopectin contents, distribution of polymer chains, degree of crystallinity, and extraction of waste. In beans, the percentage of starch contents on dry basis is between 45 and 60%, being 24–65% amylose. This chapter evaluated the structure of common beans starch granules (Phaseolus vulgaris) and cowpea (Vigna unguiculata) in raw and cooked forms, by optical microscopy (OM) and scanning electron microscopy (SEM). Thus it was possible to observe the gelatinization of the starch granules especially in cowpea and carioca beans, as well as the “hard-to-cook” phenomenon in the black beans.",signatures:"Joyce Aparecida Tavares de Miranda, Lucia Maria Jaeger de Carvalho, Izabela Miranda de Castro, José Luiz Viana de Carvalho, André Luiz de Alcântara Guimarães and Ana Cláudia de Macêdo Vieira",downloadPdfUrl:"/chapter/pdf-download/66497",previewPdfUrl:"/chapter/pdf-preview/66497",authors:[{id:"97047",title:"Prof.",name:"Lucia Maria Jaeger",surname:"De Carvalho",slug:"lucia-maria-jaeger-de-carvalho",fullName:"Lucia Maria Jaeger De Carvalho"},{id:"200652",title:"Dr.",name:"André",surname:"Guimarães",slug:"andre-guimaraes",fullName:"André Guimarães"},{id:"209351",title:"Dr.",name:"Joyce",surname:"Miranda",slug:"joyce-miranda",fullName:"Joyce Miranda"},{id:"209473",title:"Dr.",name:"Izabela Miranda De",surname:"Castro",slug:"izabela-miranda-de-castro",fullName:"Izabela Miranda De Castro"},{id:"276507",title:"Dr.",name:"Ana",surname:"Vieira",slug:"ana-vieira",fullName:"Ana Vieira"},{id:"295486",title:"MSc.",name:"Jose",surname:"Carvalho",slug:"jose-carvalho",fullName:"Jose Carvalho"}],corrections:null},{id:"66478",title:"Mungbean (Vigna radiata L. Wilczek): Retrospect and Prospects",doi:"10.5772/intechopen.85657",slug:"mungbean-em-vigna-radiata-em-l-wilczek-retrospect-and-prospects",totalDownloads:1244,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Mungbean (Vigna radiata L. Wilczek) is economically most important crop of Vigna group. It is also known as green gram, golden gram, moong, Chickasaw, Oregon pea, and chop suey bean and this legumes have a strategic position in Southeast Asian countries for nutritional security and sustainable crop production. Being rich in quality protein, minerals and vitamins, they are inseparable ingredients in the diets of a vast majority of Indian population. When supplemented with cereals, they provide a perfect mix of essential amino acids with high biological value. These crops have the ability to fix atmospheric nitrogen (58–109 kg per ha in kg per ha mungbean) in symbiotic association with Rhizobium bacteria, which enables them to meet their own nitrogen requirement and also benefit the succeeding crops. This crop has also been reported to smother weed flora appreciably (20–45%) when intercropped with tall cereals or pigeonpea and consequently, minimize the cost incurred on weed control. On account of short duration and photo-thermo insensitivity, they are considered excellent crops for crop intensification and diversification. A seed of mungbean is highly nutritious containing 24–28% protein, 1.0–1.5% fat, 3.5–4.5% fibre, 4.5–5.5% ash and 59–65% carbohydrates on dry weight basis and provide 334–344 kcal energy. Mungbean protein is considered to be easily digestible. Mungbean are tropical grain legumes widely grown in the sub-tropical countries of South and Southeast Asia. Nevertheless, these crops are cultivated over a wide range of latitudes in the regions where average diurnal temperatures during the growing season are warmer than about 20°C.",signatures:"Suhel Mehandi, Syed Mohd. Quatadah, Sudhakar Prasad Mishra, Indra Prakash Singh, Nagmi Praveen and Namrata Dwivedi",downloadPdfUrl:"/chapter/pdf-download/66478",previewPdfUrl:"/chapter/pdf-preview/66478",authors:[{id:"275243",title:"Dr.",name:"Suhel",surname:"Mehandi",slug:"suhel-mehandi",fullName:"Suhel Mehandi"},{id:"275245",title:"Dr.",name:"Indra Prakash",surname:"Singh",slug:"indra-prakash-singh",fullName:"Indra Prakash Singh"},{id:"275246",title:"Prof.",name:"Sudhakar",surname:"Prasad Mishra",slug:"sudhakar-prasad-mishra",fullName:"Sudhakar Prasad Mishra"},{id:"290295",title:"Dr.",name:"Syed",surname:"Mohd. Quatadah",slug:"syed-mohd.-quatadah",fullName:"Syed Mohd. Quatadah"},{id:"290728",title:"MSc.",name:"Nagmi",surname:"Praveen",slug:"nagmi-praveen",fullName:"Nagmi Praveen"},{id:"290731",title:"Dr.",name:"Namrata",surname:"Dwivedi",slug:"namrata-dwivedi",fullName:"Namrata Dwivedi"}],corrections:null},{id:"64941",title:"The Productivity of Selected Species and Cultivars of Legumes Grown for Seeds in Organic Production System",doi:"10.5772/intechopen.82686",slug:"the-productivity-of-selected-species-and-cultivars-of-legumes-grown-for-seeds-in-organic-production-",totalDownloads:540,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The aim of the study was to assess the yielding of selected legume species with diversified morphological structure cultivated for seeds in ecological system. The field experiment was carried out in 2016–2018. The first factor was legume species: faba bean, field pea, yellow lupine, and blue lupine, and the second factor was varieties of legumes: faba bean (Granit and Amulet), field pea (Hubal and Batuta), blue lupine (Kurant and Regent), and yellow lupine (Bursztyn and Perkoz). After the harvest, the grain yield of legume plants and the weight of a thousand seeds were determined. The plant structure was determined (length of the part of fruiting stem, number of pods and seeds per plant, number of seeds in the pod, number of fruiting nodes, number of pods and seeds from the node). In addition, the content of selected nutrients (protein, fiber, fat, macroelements) was determined in seeds. Studies showed that in ecological conditions, the pea cultivation, especially Hubal variety (with bipinnate leaves), enabled obtaining the largest seed yield, while the smallest seed yields yellow lupine independent of the morphological type. The self-completing varieties of faba bean, yellow lupine, and blue lupines were yielded at a higher level than varieties with a traditional growth type. Among the pea varieties assessed, the variety Hubal yielded better (with bipinnate leaves). Significantly, higher yield of protein is provided by faba bean cultivation, while the smaller level of pea and yellow lupine.",signatures:"Księżak Jerzy and Bojarszczuk Jolanta",downloadPdfUrl:"/chapter/pdf-download/64941",previewPdfUrl:"/chapter/pdf-preview/64941",authors:[{id:"170281",title:"Prof.",name:"Jerzy",surname:"Księżak",slug:"jerzy-ksiezak",fullName:"Jerzy Księżak"},{id:"170282",title:"Dr.",name:"Jolanta",surname:"Bojarszczuk",slug:"jolanta-bojarszczuk",fullName:"Jolanta Bojarszczuk"}],corrections:null},{id:"64927",title:"Influence of Adjuvants on Efficacy of Postemergence Herbicides Commonly Used in Peanut (Arachis hypogaea L.)",doi:"10.5772/intechopen.82708",slug:"influence-of-adjuvants-on-efficacy-of-postemergence-herbicides-commonly-used-in-peanut-em-arachis-hy",totalDownloads:904,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Field studies were conducted for 2 years in the High Plains of Texas (34.1826o N, 101.9505o W) and in South Texas (29.1634o N, 97.0725o W) to evaluate weed control when using different adjuvants with commonly used peanut herbicides. In the High Plains, Amaranthus palmeri L. control with acifluorfen, imazapic, lactofen, and 2,4-DB at the 1X dose improved with the use of an adjuvant over no adjuvant. A. palmeri control with imazethapyr was similar to that seen with imazapic and lactofen with the exception of the 1/2X rate of imazethapyr, which showed improved control with Agridex over the use of no adjuvant or Induce in 1 year, while Induce was better than no adjuvant or Agridex in the other year. In 1 year in South Texas, A. palmeri control with imazapic at the 1X dose was ≥73% with/without an adjuvant. In another year, the 1X dose of imazapic controlled A. palmeri 64% without an adjuvant, while the addition of Cide Kick II resulted in 83% control. An adjuvant did not improve A. palmeri control with lactofen or Cucumis melo L. control with either imazapic or lactofen. Urochloa texana (Buckl.) control with clethodim at the 1X dose was not improved by the addition of an adjuvant in either year. U. texana control was not improved when using the 1X dose of fluazifop-P with any adjuvant.",signatures:"William James Grichar, Peter A. Dotray and Mark A. Matocha",downloadPdfUrl:"/chapter/pdf-download/64927",previewPdfUrl:"/chapter/pdf-preview/64927",authors:[{id:"13502",title:"Prof.",name:"W. James",surname:"Grichar",slug:"w.-james-grichar",fullName:"W. James Grichar"},{id:"14656",title:"Dr.",name:"Peter A.",surname:"Dotray",slug:"peter-a.-dotray",fullName:"Peter A. Dotray"},{id:"283163",title:"Prof.",name:"Mark",surname:"Matocha",slug:"mark-matocha",fullName:"Mark Matocha"}],corrections:null},{id:"65957",title:"Breeding Elite Cowpea [Vigna unguiculata (L.) Walp] Varieties for Improved Food Security and Income in Africa: Opportunities and Challenges",doi:"10.5772/intechopen.84985",slug:"breeding-elite-cowpea-em-vigna-unguiculata-em-l-walp-varieties-for-improved-food-security-and-income",totalDownloads:1256,totalCrossrefCites:3,totalDimensionsCites:10,hasAltmetrics:0,abstract:"Cowpea, Vigna unguiculata (L.) Walp, is among the most important grain legumes in Africa. Its nutritional value and biological nitrogen fixation (BNF) potential coupled with a high plasticity to environmental conditions places this legume in a unique position in Sub-Saharan Africa (SSA) in the context of food and nutritional security. However, cowpea yield and BNF contribution to agricultural systems in this sub-continent is far behind the average global values. The inability to run effective breeding programs to timely generate and deliver high yielding, nutritious and climate smart cowpea varieties, coupled with poor crop husbandry practices has been in the forefront of the current situation. In this chapter, the main constrains and opportunities to establish and run successful and effective cowpea production and breading programs in SSA are discussed. The discussion is built around the argument that SSA can benefit from its rich collection of landraces, as well as from high-throughput methodologies to assist the screening and the development of adapted, high yielding and nutritious varieties.",signatures:"Ana Maria Figueira Gomes, Nascimento Nhantumbo, Manuela Ferreira-Pinto, Rafael Massinga, José C. Ramalho and Ana Ribeiro-Barros",downloadPdfUrl:"/chapter/pdf-download/65957",previewPdfUrl:"/chapter/pdf-preview/65957",authors:[{id:"171036",title:"Dr.",name:"Ana I.",surname:"Ribeiro-Barros",slug:"ana-i.-ribeiro-barros",fullName:"Ana I. Ribeiro-Barros"},{id:"275914",title:"MSc.",name:"Ana",surname:"Gomes",slug:"ana-gomes",fullName:"Ana Gomes"},{id:"275915",title:"Prof.",name:"Nascimento",surname:"Nhantumbo",slug:"nascimento-nhantumbo",fullName:"Nascimento Nhantumbo"},{id:"275916",title:"Prof.",name:"Rafael",surname:"Massinga",slug:"rafael-massinga",fullName:"Rafael Massinga"},{id:"275917",title:"Dr.",name:"José",surname:"Ramalho",slug:"jose-ramalho",fullName:"José Ramalho"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"5781",title:"Phytohormones",subtitle:"Signaling Mechanisms and Crosstalk in Plant Development and Stress Responses",isOpenForSubmission:!1,hash:"054eaa85c13ebe3d04fb8852005d2bad",slug:"phytohormones-signaling-mechanisms-and-crosstalk-in-plant-development-and-stress-responses",bookSignature:"Mohamed El-Esawi",coverURL:"https://cdn.intechopen.com/books/images_new/5781.jpg",editedByType:"Edited by",editors:[{id:"191770",title:"Dr.",name:"Mohamed A.",surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. 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Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"41671",title:"Moisture-Dependent Engineering Properties of Chia (Salvia hispanica L.) Seeds",doi:"10.5772/53173",slug:"moisture-dependent-engineering-properties-of-chia-salvia-hispanica-l-seeds",body:'These seeds have been investigated and recommended due to their oil content with the highest proportion of α-linolenic acid (omega-3) compared to other natural source known to date [3, 4], and also because of their high levels of protein, antioxidant, dietary fiber, vitamins and minerals [5, 6]. Chia seeds from Argentina exhibited 30.0 - 38.6 g oil/100 g, with 60.7 - 67.8 g/100 g of α-linolenic acid [7, 8]. Figure 1 shows the chemical composition of chia seed [9].
Chia seed is traditionally consumed in Mexico, the southwestern U.S., and South America, but it is not widely known in Europe. However, in 2009, the European Union approved chia seeds as a novel food, allowing them to comprise up to 5% of a bread product\'s total matter [10]. Today, chia is mostly grown in Mexico, Bolivia, Argentina, Ecuador, Australia, and Guatemala, and it has been demonstrated that the species has great potential as a future crop plant [7, 11].
Chemical composition of chia seed (% d.b.)
Photographs of dark and white chia seeds (13x)
The knowledge of engineering properties constitutes important and essential data for the design of machines, storage structures, and processes. The value of this basic information is not only important to engineers but also to food scientists, processors, and other scientists who may exploit these properties and find new uses.
Engineering seed properties and their dependence on moisture content are necessary in the design of equipment for transporting, storage and/or processing. The knowledge of the morphology and size distribution of chia seeds is essential for the adequate design of the equipment for cleaning, grading and separation. Gravimetric properties are useful for the design of equipment related to aeration, drying, storage and transport. Bulk density determines the capacity of storage and transport systems while true density is useful for separation equipment; porosity of the mass of seeds determines the resistance to airflow during the aeration and drying of seeds. The frictional properties, such as the angle of repose and the static coefficient of friction, are important for the design of grain bins and other storage structures whose operation is influenced by the compressibility and flow behaviour of materials. Several researchers investigated the moisture dependence of engineering properties of seed or grain and reported different behaviour of these properties as a function moisture content.
The aim of this work was to evaluate the engineering properties of dark chia seed as a function of the moisture content and to compare their behavior with that of other grains.
Chia seeds (20 kg) were obtained from commercial sources in Salta, Argentina (25° S, 65.5° W). Seeds were packed in hermetic plastic vessels and stored at 5 ± 1°C until use. The seeds were manually cleaned to remove all foreign matter, such as stones, dirt, and broken seeds. In this way, a randomized sample of chia seeds (about 2 kg) was picked by a sample splitter (CPASA, Centro Proveedor Agropecuario, Buenos Aires, Argentina). The seeds were manually separated according to their white or dark pericarp surface.
The dark chia seeds were further divided into seven lots and they were conditioned to obtain a moisture content range of 4.6 - 17.7% (d.b.).To obtained a less moisture content, a predetermined quantity of seeds was dried down to the desired moisture content (convection air oven, 40 - 45°C). Higher moisture contents were reached indirectly through the saturation of the atmosphere in contact with the seeds. For this purpose, small, clean and dry vessels containing the seeds were placed into a container with 100 cm3 of water, which was then hermetically sealed for 36 - 240 h. These moisture levels were selected according to the conditions usually applied in harvesting and most processing operations of grains [13].
The moisture content of the samples was determined by the ASAE standard method used for rapeseed [14], using a convection air oven at 130 ±1°C for 4 h.
The engineering properties of seeds were assessed at all moisture levels, as described below.
In order to determine the average size of the seeds, a sample of 100 seeds was randomly selected. For each individual seed, the three principal dimensions, namely length (
The geometric mean diameter (
The specific surface area (
To determine the mass of a thousand seeds (
The bulk density (
The porosity value (ε) defined as the fraction of space in the bulk seed which is not occupied by the seed [18], was determined from bulk and true densities using the relationship given by [19] and [20] as follows:
The seed volume (
where
The equivalent diameter (
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Cumin | \n\t\t\t7.0 - 22.0 | \n\t\t\tSingh and Goswami, 1996. [13] | \n\t\t
Sunflower | \n\t\t\t4.0 - 20.0 | \n\t\t\tGupta and Das, 1997. [15] | \n\t\t
Fenugreek | \n\t\t\t8.9 - 20.1 | \n\t\t\tAltuntaş et | \n\t\t
Safflower | \n\t\t\t3.7 - 15.6 | \n\t\t\tBaümler et | \n\t\t
Sunflower | \n\t\t\t2.0 – 18.8 | \n\t\t\tde Figueiredo et al., 2006 [18] | \n\t\t
Sunflower | \n\t\t\t2.9 – 20.1 | \n\t\t\tde Figueiredo et al., 2006 [18] | \n\t\t
Quinoa | \n\t\t\t4.6 - 25.8 | \n\t\t\tVilche et | \n\t\t
Soybean | \n\t\t\t8.7 - 25.0 | \n\t\t\tDeshpande et | \n\t\t
Amaranth | \n\t\t\t7.7 - 43.9 | \n\t\t\tAbalone et | \n\t\t
Chia | \n\t\t\t4.6 - 17.7 | \n\t\t\tGuiotto et | \n\t\t
Cotton | \n\t\t\t8.3 - 13.8 | \n\t\t\tÖzarslan, 2002. [26] | \n\t\t
Flaxseed | \n\t\t\t6.1 - 16.2 | \n\t\t\tCoşkuner and Karababa, 2007 [27] | \n\t\t
Rapeseed | \n\t\t\t4.7 - 24.0 | \n\t\t\tÇalişir et | \n\t\t
References studying the engineering properties of several seeds
* Moisture content range considered in each study
The static coefficient of friction was measured using two structural materials, namely galvanized iron and aluminum. These materials are commonly used for transport, storage, and handling operations of grains, pulses, and seed and for building storage and drying bins. A PVC cylinder (50 mm diameter, 50 mm high, open at both ends) was placed on an adjustable tilting table, faced with the test surface, and filled with the sample. The structural surface with the cylinder resting on it was tilted gradually with a screw device until the cylinder just started to slide down [22]. The angle (α) was read on a graduated scale and the friction coefficient was calculated using the following relationship:
where μ is the static coefficient of friction, and α is the angle of tilt (degrees). The static coefficient of friction was replicated reading ten times for each moisture content.
Different authors evaluated the engineering properties of several seeds as a function of seed moisture content (Table 1). These data were considered to compare the behavior of different grain properties with regard to moisture content.
Dark seeds represented 89% by mass of the samples studied. The initial moisture content was 10.0% and 10.9% d.b., for dark and white seeds, respectively. Averages of the three principal dimensions were
Principal dimensions (a) length (
The geometric mean of the axial dimensions is useful in estimating the projected area of a particle moving in the turbulent or near-turbulent region of an air stream. It is therefore generally indicative of its pattern of behavior in air streams, especially with respect to the ease of separating extraneous materials from the particle during cleaning by pneumatic means [26]. Significant differences (
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Amaranth [24] | \n\t\t\t1.071 + 0.00385 x | \n\t\t\t0.99 | \n\t\t
Chia [25] | \n\t\t\t1.2075 + 0.0057 | \n\t\t\t0.97 | \n\t\t
Flaxseed [27] | \n\t\t\t1.941 + 0.011 x | \n\t\t\t0.97 | \n\t\t
Quinoa [22] | \n\t\t\t1.359 + 0.009819 x | \n\t\t\t0.99 | \n\t\t
Soybean [23] | \n\t\t\t4.882 + 0.0253 x | \n\t\t\t0.99 | \n\t\t
Regression equation as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for geometric diameter (
Effect of moisture content (x, % d.b.) on specific area (
Bulk density, true density, and porosity (the ratio of inter granular space to the total space occupied by the grain) can be useful in sizing grain hoppers and storage facilities; they can affect the rate of heat and mass transfer of moisture during aeration and drying processes. The theories used to predict the structural loads for storage structures have bulk density as basic parameter. Bulk density and porosity are major considerations in designing near-ambient drying and aeration systems, as these properties affect the resistance to airflow of the stored mass. Grain bed with low porosity will have greater resistance to water vapor scape during the drying process, which may lead to higher power to drive the aeration fans.
True density average of dark chia seeds with different moisture content was 1.069 g cm-3. Statistical analysis showed significant differences (
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Cumin [13] | \n\t\t\t1010 + 6.05 x | \n\t\t\t0.98 | \n\t\t
Flaxseed [27] | \n\t\t\t826.92 + 28.91 x | \n\t\t\t0.99 | \n\t\t
Fenugreek [16] | \n\t\t\t1275.8 – 37.555 x | \n\t\t\t0.99 | \n\t\t
Quinoa [22] | \n\t\t\t853.19 + 13.16 x | \n\t\t\t0.98 | \n\t\t
Sunflower [15] | \n\t\t\t694.6 + 3.72 x | \n\t\t\t0.92 | \n\t\t
Sunflower* [18] | \n\t\t\t706.12 + 4.06 x | \n\t\t\t0.94 | \n\t\t
Soybean [23] | \n\t\t\t1254.8 – 5.258 x | \n\t\t\t0.99 | \n\t\t
Amaranth [24] | \n\t\t\t(1411(100 + x))/ (100 + 1,25 x) | \n\t\t\t0.99 | \n\t\t
Safflower [17] | \n\t\t\t0,7887+(0,000298 x)-(0,0004551 x2) | \n\t\t\t0.99 | \n\t\t
Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for true density (ρ
* black-hull oilseed
Chia seed bulk density decreased from 0.713 to 0.644 g cm-3 as a function of the increase of moisture content. Table 4 shows the relationship of bulk density with moisture content reported by different authors for several seeds. Regarding bulk density, chia seeds presented a behavior similar (non-linear) to those of cumin and safflower seeds. The negative linear relationship of bulk density with moisture content was observed by other authors for amaranth, flaxseed, fenugreek, quinoa, rapeseed, sunflower and soybean (Table 4). The decrease in bulk density of seed with increase in moisture content indicates that the increase in volumetric expansion is greater than weight.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Amaranth [24] | \n\t\t\t869 – 3.50 x | \n\t\t\t0.87 | \n\t\t
Chia [25] | \n\t\t\t697.7+ 5.0 x – 0.4 x2\n\t\t\t | \n\t\t\t0.99 | \n\t\t
Cumin [13] | \n\t\t\t407 + 15.67 x – 0.70 x2\n\t\t\t | \n\t\t\t0.97 | \n\t\t
Flaxseed [27] | \n\t\t\t822.43 – 15.308 x | \n\t\t\t0.99 | \n\t\t
Fenugreek [16] | \n\t\t\t726.76 – 27.675 x | \n\t\t\t0.98 | \n\t\t
Quinoa [22] | \n\t\t\t771.5 – 3.94 x | \n\t\t\t0.98 | \n\t\t
Rapeseed [28] | \n\t\t\t616.74 – 1.4518 x | \n\t\t\t0.93 | \n\t\t
Safflower [17] | \n\t\t\t452.2 – 0.12 x2\n\t\t\t | \n\t\t\t0.96 | \n\t\t
Sunflower [15] | \n\t\t\t472.4 – 1.69 x | \n\t\t\t0.88 | \n\t\t
Sunflower* [18] | \n\t\t\t446.35 – 201 x | \n\t\t\t0.87 | \n\t\t
Sunflower** [18] | \n\t\t\t528,75 – 2.24 x | \n\t\t\t0.80 | \n\t\t
Soybean [23] | \n\t\t\t748.9 – 1.6626 x | \n\t\t\t0.99 | \n\t\t
Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for bulk density (ρ
* black-hull oilseed, **striped-hull oilseed
These discrepancies observed for as much true density as for bulk density could be due to cell structure and the volume and mass increase characteristics of the seeds as moisture content increases [29].
The average porosity observed for all dark samples was 35.3%, with significant differences
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Amaranth [24] | \n\t\t\t28 + 0.16 x | \n\t\t\t0.75 | \n\t\t
Cumin [13] | \n\t\t\t48 + 0.643 x | \n\t\t\t0.93 | \n\t\t
Flaxseed [27] | \n\t\t\t11.453 + 2.7621 x | \n\t\t\t0.99 | \n\t\t
Fenugreek [16] | \n\t\t\t42.987 + 0.555 x | \n\t\t\t0.95 | \n\t\t
Quinoa [22] | \n\t\t\t13.1 + 1.22 x | \n\t\t\t0.98 | \n\t\t
Rapeseed [28] | \n\t\t\t44.659 + 0.6656 x | \n\t\t\t0.99 | \n\t\t
Safflower [17] | \n\t\t\t39.53 + 0.342 x | \n\t\t\t0.93 | \n\t\t
Sunflower [15] | \n\t\t\t32.27 + 0.54 | \n\t\t\t0.95 | \n\t\t
Sunflower* [18] | \n\t\t\t36.99 + 0.58 x | \n\t\t\t0.92 | \n\t\t
Sunflower** [18] | \n\t\t\t30.10 + 0.37 x | \n\t\t\t0.91 | \n\t\t
Soybean [23] | \n\t\t\t40.5 – 0.1365 x | \n\t\t\t0.98 | \n\t\t
Regression equations as a function of moisture content (x, %d.b.) with their respective coefficient of determination (R2) for porosity (ε, %).
* black-hull oilseed, **striped-hull oilseed
(a) volume (
Since porosity depends on bulk and true densities, the magnitude of its variation depends mainly on these properties. Therefore, the porosity of each type of seed or grain could respond differently with increasing moisture content. This fact could be attributed to the seeds\' morphological characteristics; the relative changes in their length, width, and thickness; and the associated bulk and true densities. Taking into account the high level of polyunsaturated fatty acids, chia seeds can be easily affected by temperature. For this reason, aeration is an important process to maintain a low uniform temperature and prevent the moisture migration. The resistance to airflow or pressure drop is affected by different factors, such as the bulk density, porosity, and moisture content. Due to the low bulk density and size of chia seeds, the grain bed will have an important pressure drop, requiring a high level of power for driving the aeration fans [25].
The variation of volume (
The sphericity varied between 65.8% and 67.6%, values higher than the data reported for sunflower and safflower seed, but lower than those of amaranth, quinoa, rapeseed and soybean seed (Table 6).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Amaranth [24] | \n\t\t\t82 # | \n\t\t
Fenugreek[16] | \n\t\t\t60.79 – 64.06 | \n\t\t
Quinoa [22] | \n\t\t\t77 – 80 | \n\t\t
Rapeseed [28] | \n\t\t\t93 – 92 | \n\t\t
Safflower [17] | \n\t\t\t58 – 62 | \n\t\t
Sunflower* [18] | \n\t\t\t49 – 52 | \n\t\t
Sunflower** [18] | \n\t\t\t47 – 50 | \n\t\t
Soybean [23] | \n\t\t\t80.6 – 81.6 | \n\t\t
Sphericity (
# mean value, * black-hull oilseed, **striped-hull oilseed
The high
As can be seen in Figure 6, the equivalent diameter (
Effect of moisture content (x, % d.b.) on volume seed (
The
The frictional characteristics are important for the proper design of agricultural product handling equipment. Friction between a seed and a surface has an influence on the movement of particles on oscillating conveyors, separation on oscillating sieves and unloading and loading operations. The static coefficient of friction of dark chia seeds was determined on two structural surfaces: galvanized iron and aluminum. The values obtained were higher for aluminum (mean: 0.30, minimum: 0.26, maximum: 0.37) than for galvanized iron (mean: 0.28, minimum: 0.25, maximum: 0.34). Increments of 28.4% and 29.5% were recorded for the galvanized iron and aluminum surfaces, respectively, as the moisture content increased from 4.6% to 17.7% d.b. The reason for the increased friction coefficient at higher moisture content may be that the water present in the seed offered a cohesive force on the contact surface and the seed became rougher and sliding characteristics are diminished [22, 26]. For both structural surfaces, the coefficient of static friction increased linearly with an increase in moisture content. Similar trends were reported for cumin, flaxseed, quinoa and sunflower (Figure 7).
Effect of moisture content (x, % d.b.) on coefficient of static friction. Dates correspond to the adjusted function reported by () [
The engineering properties of dark chia seeds were evaluated as a function of the moisture content, in the range of 4.6% to 17.7% d.b. and their behavior was compared with amaranth, cumin, flaxseed, fenugreek, quinoa, rapeseed, safflower, soybean and sunflower. The principal dimensions of dark chia seed (length, width and thickness), geometric diameter, specific surface area, volume, equivalent diameter, and thousand seeds mass and static coefficient of friction on galvanized sheet and aluminium increased linearly as increasing the seed moisture content. Chia seed is one of the smallest (similar to amaranth and quinoa), and very light.
The sphericity did not present significant differences in the range of moisture content studied for dark chia seed. The most spherical seeds which were compared with chia seed ones were rapeseed, amaranth, soybean and quinoa. An increase in moisture content yields a decrease in bulk and true density. The bulk density and porosity varied nonlinearly for chia seeds, showing a quadratic concave behavior as a function of moisture content.
The friction caused by the aluminum surface was slightly higher than that presented by the galvanized iron surface.
In general, the variation of the engineering properties of chia seed with the moisture content showed a similar trend to that reported for other seeds, with some exceptions. Nevertheless, they presented different variation ranges. It could be attributed to the seeds morphological and physiological characteristics.
The comparison of the data of the different seeds can be important for the design and adaptation of equipment for transporting, storage and processing.
This work was supported by a grant from Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT); Argentina (PICT 2007-1085), Universidad Nacional de La Plata (UNLP) (11/X502), and Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA). E.N. Guiotto is recipient of a doctoral fellowship from the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) and Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT); V.Y. Ixtaina and M.C. Tomás are members of the career of Scientific and Technological Researcher of Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina; and S.M. Nolasco is a research scientist of Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA), Argentina.
d.b. dry basis
x Moisture content (% d.b.)
α Angle of tilt, degree
Cancer is a major public health problem worldwide. It ranks as a leading cause of death along with cardiovascular disease (CVD). Cancer is the leading cause of death in 57 countries (including China), while CVD is the leading cause in 70 countries (including Brazil and India) [1]. In 23 other countries, it ranks either third or fourth. The GLOBOCAN 2020 report showed that there was approximately 19.3 million new cases and 10 million cancer deaths in 2020, thus making cancer the new challenge of the 21st century [2]. This increase in the number of cancer cases implies an increase in cancer-associated complications and morbidities. One such complication is malnutrition.
Cancer-related malnutrition is a broad term that encompasses complex poorly understood processes that are associated with specific types of cancers and their treatment protocols. Specific cancers such as oesophageal and pancreatic cancer are a high risk for malnutrition. Factors such as cancer-related symptoms (e.g. anorexia, early satiety, fatigue), treatment complications (eg, mucositis, nausea, taste changes), and psychologic distress all play a role and/or are risk factors in the development of malnutrition. Malnutrition is a common problem among cancer patients with high negative consequences. In cancer, it is associated with poor prognosis, reduced survival, increased therapy toxicity, reduced tolerance and compliance to treatments, and diminished response to antineoplastic drugs. Surveys done in the past showed a prevalence rate of between 25 and 70% with about 10–20% linked to malnutrition and not the malignancy itself. Malnutrition in cancer patients is distinctly different from malnutrition as a result of starvation, as the former arises from a combination of anorexia and metabolic dysregulation, caused by the tumour itself or by its treatment. Malnutrition when left untreated can progress to cachexia. Cachexia is defined as “a multifactorial syndrome characterized by an ongoing loss of skeletal muscle mass (with or without loss of fat mass) that cannot be fully reversed by conventional nutritional support and leads to progressive functional impairment” [3]. The pathophysiology of cachexia has an underlying variable combination of reduced food intake and abnormal metabolism leading to a negative protein and energy balance. Cachexia is frequent in chronic diseases, and in cancer, it may account for about 20% of cancer deaths [4]. A diagnosis of cachexia is made in patients when the total body weight loss is >5% in the past six months (in the absence of starvation) or weight loss >2% in patients with body mass index (BMI) of <20 kg/m2 [5]. Currently, cachexia is classified into three stages of clinical relevance, namely pre-cachexia, cachexia, and refractory cachexia [3]. Blum et al. defined pre-cachexia as weight loss >1 kg but <5% of usual body weight/6 months, but with an increased C- reactive protein (CRP) level and appetite loss, while refractory cachexia was weight loss >15% in the last 6 months + BMI < 23 kg/m2 or weight loss >20% in the last 6 months + BMI <27 kg/m2 [6]. If untreated, cancer cachexia would lead to a progressive functional loss, poor quality of life, chemotherapy-related toxicity, diminished response to antineoplastic treatments, and poor survival. At the refractory cachexia stage, the cancer is usually refractory to chemotherapy.
The relationship between malnutrition and the systemic inflammatory process is not a new one. Systemic inflammation is closely associated with weight loss and malnutrition in cancer [7, 8, 9]. Systemic inflammation has been fingered in the genesis and progression of malnutrition. It is known to affect important metabolic and neuroendocrine pathways as well as cause elevated energy expenditure at rest, decreased lean mass and reduced physical performance [10, 11]. Furthermore, cytokines especially tumour necrosis factor (TNF) alpha, interleukin (IL) 1 and IL-6 have been fingered in the induction of muscle wasting providing evidence for a link between malnutrition and inflammation. As aforementioned, systemic inflammation is thus a harbinger not only for malnutrition but for various comorbidities in cancer patients. Identification of cancer patients at risk of malnutrition is highly recommended. The PreMiO study highlighted the prevalence of malnutrition at the first visit by cancer patients [12]. The European Society for Clinical Nutrition and Metabolism (ESPEN) in its latest pre-operative nutritional care assessment highlighted the degree of systemic inflammation among other things for individuals at nutritional risk [13]. Soeters et al. reinforced the urgency of including an assessment of inflammatory activity in the diagnosis of malnutrition [14]. Recent studies have shown that inflammatory models can be used to predict prognosis, as well as cancer-related malnutrition [15]. High level of systemic inflammatory factors which can facilitate tumour cell proliferation and metastasis are also known to be induced by malnutrition [16]. Thus, malnutrition can enhance a systemic inflammatory response. Control of inflammation in cancer can help modify poor nutritional status resulting in better response to therapy and improved survival. The early recognition of systemic inflammatory response should therefore be an integral part of nutritional management in cancer patients to improve short and long term outcomes.
Malnutrition is a universal condition in cancer patients with grave clinical implications such as impaired quality of life, poor performance status, weight loss and cachexia. Studies from different countries across Europe shows a high prevalence of cancer-related malnutrition ranging from 25 to 70% based on nutritional assessments [17, 18, 19]. However, this differs across cancer types and stages of the disease [12, 20]. In the often-cited landmark study by Dewys et al., cancer type and treatment play a role in cancer-related malnutrition [21]. Tumour stage and age have also been noted as risk factors in malnutrition [22, 23]. In an epidemiological observation study, Pressoir et al. observed that pre-existing obesity (BMI⩾30), and Performance status ⩾2 were associated with increased risk of malnutrition among cancer patients in 17 French Comprehensive Cancer Centres [19]. The Prevalence of Malnutrition in Oncology (PreMiO), a cross-sectional, observational study involving almost 2000 patients in 22 sites in Italy, revealed that 51.1% of treatment-naïve patients at their first visit to a medical oncology centre were already affected by a nutritional impairment, including risk for malnutrition (43%) and overt malnutrition (9%). Poor appetite was present in over 40% of cancer patients, with variable severity scores depending on the tumour type and stage of the disease, and ascribed mainly to early satiety, taste changes, and nausea [24].
The picture is not very different in developing countries. Pastore et al. in Brazil reported only 13.7% of lung and gastrointestinal cancer patients in a study were well-nourished [8]. Opanga et al. in Kenya reported that 33.8% of participants required critical nutrition care, 34. 8% symptoms management, 14.2% constant nutrition education and pharmacological intervention [25]. Ntekim et al. at Ibadan, Nigeria used nutritional screening assessment tools and reported a prevalence of 60% [26]. Children with cancer are also known to develop some form of malnutrition [27], however, the frequency may vary according to the type of cancer [28], and region [29, 30]. Brinksma, et al. reported the prevalence of malnutrition at diagnosis for developed countries, through a systematic review which included patients with different types of childhood cancer, aged from 0 to 18 years of age for acute leukaemias, the prevalence was 10%, 20–50% for neuroblastoma, and those classified as “other malignancies” was 0–30% [31]. This prevalence is lower than what is obtained in developing countries [28, 29, 30]. Villanueva et al. reported a prevalence of almost 50% [32]. Lemos et al. in Brazil reported that the prevalence of malnutrition is higher among paediatric patients with malignancies than in the general population though the difference was not significant [33]. These facts high- light the need for nutritional assessment in cancer patients regardless of age or region. Cancer patients should be assessed at several points during their management to identify aetiology and candidates that require nutritional support.
Cancer-related malnutrition can have profound negative effects on cancer patients’ wellbeing and therapeutic outcomes. It usually results from local effects of a tumour, the host response to the tumour and anticancer therapies. Cancer cachexia which is a severe form of malnutrition is characterised by progressive weight loss, anorexia, asthenia, and anaemia. Cachexia is a poor prognostic sign, and is associated with reduced food intake and increased energy expenditure [34]. Cachexia also expresses itself as nutritional imbalances in a number of ways in cancer patients which include glucose intolerance and insulin resistance, loss of adipose tissue and lipolysis with increased fat oxidation rates [35], decreased lipogenesis, impaired lipid deposition and adipogenesis [36]. A decrease in protein synthesis and increase in protein degradation does occur in cancer cachexia [37] which is a key feature of skeletal muscle atrophy. Other features such as altered hormone levels [38], elevated cytokines [39, 40], increased insulin resistance [38], elevated synthesis of acute-phase proteins [34] and altered nutrient utilisation can be attributed to inflammatory mediators as well a host of other factors. Inflammatory markers have been implicated in all metabolic derangements in cancer-related malnutrition, and a better understanding of these markers with either the host or the tumour is necessary for better management of malnutrition and its complications.
Inflammation has been shown to play a major role in cancer development, progression and outcome and has been termed the seventh hallmark of cancer [41]. The observation of leukocytes within tumours by Rudolf Virchow in the 19th century gave a clue of a possible link between inflammation and cancer. This link is due to chronic inflammation which is mediated by pro-inflammatory cytokines, chemokines, adhesion molecules, and inflammatory enzymes with the promotion of all stages of tumorigenesis. Inflammation is the body’s physiological response to tissue damage as a result of any pathological insult to the body’s homeostasis. The body’s inflammatory response can either be a resolution to the insult, or persistence of the insult in the form of chronic inflammation. Chronic inflammation can cause cellular changes and influence innate and adaptive immunity towards tumour growth. When this happens, an imbalance of pro-inflammatory and anti-inflammatory mediators can lead to cell mutation and injury creating an environment that is conducive to the development of cancer. This scenario holds for the onset of cancer but is important for the progression of the disease. Such progression is characterised by clinical signs and symptoms including nutritional impact symptoms and co-morbid metabolic abnormalities. This invariably leads to weight loss, chronic anaemia, wasting syndrome, fatigue with loss of quality of life. These symptoms are very prominent in cancer-related malnutrition. While multiple mechanisms can be associated with these symptoms, however, they are interrelated and the unifying factor is inflammation.
Inflammation is associated with tumorigenesis at every stage of its development including survival and metastasis [42]. On the other hand chronic inflammation is known to facilitate treatment resistance and this form of acquired resistance is a result of the production of cytokines, chemokines and growth factors by the tumour micro-environment rendering chemotherapy ineffective [43]. Besides, inflammatory responses can be induced by anti-cancer therapies [44, 45]. chronic inflammation is also known to worsen chemotoxicity [46]. A better understanding of the relationship between chronic inflammation and cancer can lead to the development of new strategies in the management of cancers as well as some of the complications such as malnutrition and chemotoxicity that arise during treatments.
A large number of cancer patients are known to show a form of cachexia syndrome which is characterised by anorexia, loss of adipose tissue and skeletal muscle mass. Most of these symptoms have been linked to inflammation. The Global Leadership Initiative on Malnutrition (GLIM) requires the combination of at least one phenotypic and one etiologic criterion is to establish the diagnosis of malnutrition. The phenotypic criteria include non-volitional weight loss, low body mass index, reduced muscle mass. In addition to this, etiologic criteria include reduced food intake or assimilation and disease burden/inflammatory condition [47].
Inflammation is so intertwined with the pathogenesis of malnutrition that the ESPEN recommended dividing malnutrition into disease-related malnutrition with and without inflammation [48]. For Disease-related malnutrition with inflammation, it is defined as underlying diseases causing inflammation with a consecutive lack of food intake or as uptake with a negative nutrient balance [49]. Inflammation is reported to have several metabolic effects. Cytokines such as IL-6, and TNF-
Anaemia is a common problem in cancer patients. Anaemia prevalence is remarkably high and varies widely among cancer patients. It is estimated from various studies that between 30–90% of cancer patients had anaemia [54]. Anaemia is considered an indicator of poor nutrition and poor health especially through the malabsorption or non-utilisation of iron, folate, cobalamin and other micronutrients needed for the production of red blood cells. The prevalence is determined by the definition of anaemia. According to the World Health Organisation (WHO), normal Hb values are 12 g/dL in women, and 13 g/dL in men [55]. Maccio et al. reported a prevalence of 78.8% of anaemia in lung cancer patients [56]; Akinbami et al. reported a prevalence of 58% among breast cancer patients [57]. Anaemia is known to be associated with several co-morbidities including a decline in patients’ performance status (PS), cognitive function, and decreased survival [56, 58]. While anaemia in cancer generally is known to have various aetiopathology, cancer-related anaemia (CRA) is believed to arise as a consequence of chronic inflammation.
Cancer-related anaemia (CRA) refers to a condition occurring without bleeding, haemolysis, neoplastic bone marrow infiltration, kidney and/or hepatic failure [59], and principally results from the chronic inflammation associated with advanced-stage cancer and the synthesis of pro-inflammatory cytokines by both immune and cancer cells. Unlike iron deficiency anaemia, CRA is typically normochromic (MCH >27 pg), normocytic (MCV between 80 and 100 fl), with a low reticulocyte count (<25,000/mL) and a low value of reticulocyte index (normal range between 1 and 2 which is a more accurate measure of the reticulocyte count corrected against the severity of anaemia based on haematocrit). In addition, it has normal/low serum iron concentrations (normal range 55–160 mg/dl for men and 40–155 mg/dl for women) and reduced total iron-binding capacity (transferrin saturation < 50%); ferritin values may be normal (30–500 ng/ml) or more often increased (>500 ng/mL), with increased iron storage [59]. The normal level of iron within the bone marrow reflects the body tacit handling of iron metabolism which is termed as “functional iron deficiency” which is also present in other types of anaemia associated with chronic inflammation. In addition, circulating levels of erythropoietin (EPO) is often not optimal for the level of anaemia thus presenting with also bone marrow hypoplasia. Adamson highlighted some of the pathogenetic mechanism of inflammation of chronic anaemia which includes: shortened erythrocyte survival in conjunction with increased erythrocyte destruction, suppressed erythropoiesis in bone marrow, effects of inflammation on erythropoietin production and alterations in iron metabolism that result in iron-restricted erythropoiesis induced by hepcidin increase [60]. According to Jain et al., the soluble transferrin receptor/log ferritin index can differentiate pure cases of anaemia of chronic disease from iron deficiency anaemia [61].
Like other types of anaemia in cancer, CRA has multifactorial pathophysiology with immune, nutritional and metabolic components affecting its severity. Many studies have demonstrated that inflammatory cytokines are a major contributor to the aetiopathogenesis of CRA. They achieve this through the derangement of various metabolic pathways including glucose metabolism, impairment of lipoprotein lipase, which controls the uptake of circulating triglycerides into adipocytes, and changing protein synthesis and degradation, with subsequent depletion in lean body mass [62]. In particular, proinflammatory cytokines like interleukin 1 and 6 released by cancer and activated immune cells in response to malignancy, may result in anaemia by inducing changes to iron balance, inhibition of erythropoiesis, impairment of EPO synthesis and activity, reduction of erythrocytes lifespan and changes of energy metabolism. IL-1 and TNF also induce the transcription factors GATA2 and nuclear factor-kB, both of which are negative regulators of the hypoxia-inducible factor 1 (HIF1) expression [63]. Reactive oxygen species (ROS) which are a major player in chronic inflammation are known to inhibit EPO synthesis by mimicking a false O2 signal in the renal peritubular interstitial cells. They equally inhibit erythroid precursor proliferation [64]. IL-6 regulates the synthesis of hepcidin, a 25 amino acid peptide made by the hepatocytes and involved in iron homeostasis by mediating the degradation of the iron export protein ferroportin 1, thereby inhibiting iron absorption from the small intestine and release of iron from macrophages.
The process of CRA is not an isolated one. It has been shown that malnutrition along with weight loss and reduced food intake is correlated with anaemia in patients with the chronic inflammatory disease [65]. CRA is therefore not a single condition, but associated with weight loss and remodelling of energy metabolism; thus CRA is a crossroad for both inflammation and nutritional status. Therefore management of CRA would involve not only anaemia but malnutrition as a whole.
Anorexia can be defined as a loss of appetite associated with chronic illness in cancer patients and is associated with weight loss [66]. It is common in cancer patients and frequently associated with early satiety and taste changes. It occurs in half of the newly diagnosed cancer patients and up to 70% of patients with advanced disease. Cancer-related anorexia is an important clinical co-morbidity in cancer patients, and it harms nutritional status in advanced cancer. There are many causes of anorexia. They are classified as either being due to central or peripheral mechanisms. Peripheral causes include (i) tumours causing dysphagia or directly impinging on gastrointestinal function; (ii) tumours producing substances that alter food intake, e.g. lactate, tryptophan, or parathormone-related peptide; (iii) tumours leading to alterations in nutrients resulting in anorexia, e.g. zinc; or (iv) tumours producing inflammation leading to cytokine release. Alterations in gastrointestinal function can alter visceral receptor function, leading to altered secretion of gastrointestinal peptides, e.g. peptide tyrosine (PYY), and alterations in stomach emptying can alter feedback of satiating hormones. Peripherally, chemotherapy can alter taste perception and cause nausea, vomiting, mucositis, abdominal cramping, bleeding, and ileus [67]. Depression, pain, or a variety of alterations in central neurotransmitters are some of the central causes. Some centrally acting chemotherapy can also induce anorexia. For example, tamoxifen used in breast cancer treatment can inhibit fatty acid synthase in the hypothalamus, leading to an accumulation of malonyl coenzyme A (CoA). Increased malonyl CoA is associated with anorexia in cancer [68, 69]. The resultant effect of cancer-related anorexia is reduced caloric intake and alteration in nutrient metabolism with consequent loss of fat and lean mass.
Several studies have focused on the mechanisms underlying the metabolic changes observed in cancer-related anorexia and weight loss and some cytokines have been implicated including TNFα, IL-1, and IL-6 [70]. These cytokines are known to mimic leptin signalling and suppress orexigenic ghrelin and neuropeptide Y (NPY) signalling inducing sustained anorexia and weight loss. These cytokines are elevated in many cancers [71] and their chronic administration can induce anorexia and wasting [72, 73]. Interleukin 1 is produced by lymphocytes and macrophages and is a potent anorexigenic cytokine that is at least 1000-fold more effective than leptin [74]. IL-1 is reported to reduce the size, duration, and frequency of meals but does not reduce the desire for food [75]. It achieves this by the stimulation of corticotrophin-releasing factor (CRF) production by the hypothalamus [76]. TNFα is produced by monocytes, tissue macrophages and some tumours, and directly on the CNS to produce its anorectic effects by crossing the blood-brain barrier. An inhibitor of TNFα increased food intake in anorectic tumour-bearing rats [77].
Interferon-γ when administered centrally is known to reduce food intake and duration. Administration of TNF-α to laboratory animals induces a state of cachexia, with anorexia and depletion of adipose tissue and lean body mass [78]. Interleukin-6 is secreted by T-cells and macrophages as well as microglia, astrocytes, and neurons and has a well-established association with the onset of cachexia in both rodent and human wasting conditions [79]. While there are many mediators of anorexia in different disease states, IL-6 has been shown to regulate food intake and metabolism [80], signalling through neural gp130 receptors and even in non-cancer-related cachexia, plasma IL-6 is associated with the incidence of anorexia [81, 82].
Decreased caloric intake alone does not account for the profound weight loss observed in cancer patients. Metabolic abnormalities with subsequent elevation in basal energy expenditure are also contributing factors. Weight loss in cancer though affects both fat and lean mass, the latter seems more affected. In a study of 50 cancer patients by Cohn et al., Weight-losing cancer patients appeared to have lost both fat and lean tissue, but the loss of lean body tissue, particularly skeletal muscle, was the more striking feature [83]. This pattern is in contrast to starvation, in which fat is lost and lean tissue is better preserved. TNF-α, IL-1 and IL-6 have been shown to increase basal energy expenditure causing weight loss [84]. The muscle wasting that occurs in cancer is a result of a decrease in protein synthesis, an increase in protein degradation or a combination of both. These changes are attributed to the upregulation of inflammatory mediators, the activation of related transcription factors and signalling pathways, abnormalities in the expression of angiotensin II (Ang II), insulin-like growth factor-1 (IGF-1) and various receptors, proteins and kinases, and organelle dysfunction [85]. Muscle wasting thus occurs as a result of these processes.
There are several clinical, biochemical and physiological indicators to diagnose malnutrition in cancer patients. One commonly used clinical indicator of malnutrition is the percentage of weight loss in a certain period. Α weight loss of more than 5% in the previous month or more than 10% in the last 3–6 months is considered significant malnutrition. Other anthropometric measurements, such as body mass index (BMI), mid-arm circumference and mid-upper-arm muscle area can give information about the nutritional status and body composition of these patients. The ASPEN guidelines for diagnosing malnutrition, which looked at six characteristics that incorporate some of these clinical indices [86].
Biochemical markers which are sometimes indicative of inflammation are often used as markers of malnutrition. They include albumin, prealbumin, C-reactive protein, transferrin, total lymphocyte count etc. However, more recently, inflammation-based scores and ratios are being seen as more sensitive markers than the traditional ones [87, 88]. Other nutritional assessment tools use questionnaires incorporated with factors such as estimation of nutritional intake, laboratory parameters and calculation of unintentional weight loss. Such tools that have been used in cancer patients include the Prognostic Nutritional Index (PNI), the Nutritional Risk Screening 2002 (NRS 2002), the Controlling Nutritional Status (CONUT), Mini Nutrition Assessment (MNA), Malnutrition Screening Tool (MST), the Nutritional Risk Index (NRI) etc. [89]. In children with cancer, the Frisancho table is used to assess their nutritional status [29].
Albumin is a serum hepatic protein with a half-life of 14–20 days. Albumin is the major carrier for many substances in the body, and also help maintain the body oncotic pressure. It enhances immunity, aids DNA synthesis as well as acts as an antioxidant [90, 91]. Due to its relatively long half-life and hepatic synthesis, it is seen as a good marker of malnutrition. However, albumin is a negative acute-phase protein, and its serum levels are down-regulated in response to inflammatory conditions and drugs especially those that affect the liver. Albumin is widely used as a marker of nutrition as well as a prognostic indicator of survival in cancer patients (though it is more of a marker for inflammatory response). Frutenicht et al. reported that albumin was a predictor of mortality in gastrointestinal tumour patients [92]. Das et al. reported that albumin was significantly correlated with Patient-Generated Subjective Global Assessment (PG-SGA) [93], thus hypoalbuminaemia is a marker of malnutrition. This was further affirmed by a study done on colorectal cancer patients where albumin was positively correlated with the MNA [94]. However, In a study of 74 cancer patients, Pastore et al. did not find significant variation between albumin and SGA [8]. In a recent study on 128 colorectal patients, at least two circulating cytokines (TNF-α and IL-10) affected the expression of serum albumin [95]. Albumin correlates with weight loss in cancer patients as well as with BMI. Albumin is equally incorporated into various indices such as the Glasgow prognostic score (GPS) and PNI. Albumin may not be the ideal marker for assessing malnutrition, but its incorporation into nutrition screening tools gives it a sense of validity.
CRP is the most common method used to assess the magnitude of systemic inflammatory response. Unlike albumin, it is a positive acute-phase protein. CRP is a prototype of short pentraxin present only in the pentameric form in plasma. It is synthesised by hepatocytes in response to trauma, inflammation and tissue damage. The synthesis of CRP is under the transcriptional control of cytokines and transcription factors. Interleukin-6 (IL-6) is the main inducer of CRP gene. CRP is associated with the development, progression and outcome of cancer [96]. In addition, some studies have found a positive association between altered CRP levels and weight loss in patients with cancer [97]. In a large international cohort of advanced cancer patients, Laird et al. reported that C-reactive protein was significantly associated with cognitive, physical, emotional and social functions as well as anorexia, pain and fatigue [98]. Yu et al. also observed a significant association between CRP and PG-SGA among patients with malignant tumours [99]. However, some other studies did not see any association between CRP and nutritional status [88, 92]. In a study done by Read et al., patients with advanced colorectal cancer were initially found to have a positive correlation between SGA and CRP. However, when two outliers were excluded, the association did not remain significant [100]. This observation may be a result of the effect of non-nutritional factors like cardiovascular disease and infections. CRP is positively correlated with weight loss, and negatively correlated with PNI. Like albumin, CRP is incorporated into some nutritional screening tools which give it some validity.
Traditional inflammatory markers like CRP and albumin have been shown to have some limitations in malnutrition diagnosis based on their low specificity. It has been muted that inflammation-based scores that combine CRP and albumin, such as the CRP/Albumin ratio (CAR), may have more significant prognostic value than each of these markers singly in malnutrition. These inflammation-based scores which include inflammatory ratios and indices, and haematological ratios have been reported to be associated with cancer progression and outcomes [101, 102].
The Glasgow prognostic score or modified Glasgow prognostic score indices which combine serum CRP and albumin levels have also been viewed as a prognostic indicator in many cancers. There have been more than 60 studies (>30,000 patients) that have examined and validated the use of the GPS or the modified GPS (mGPS) in a variety of cancer scenarios [103]. Silva et al. demonstrated the clinical utility of modified GPS in a palliative care setting and its association with SGA [104]. SGA was also strongly correlated with the Glasgow prognostic score in oesophageal cancer patients [105]. GPS currently serves an important significance as a nutritional marker in cancer.
The concept of the CRP/albumin ratio (CAR) was first proposed by Ranzani and demonstrated its value for the mortality of septic patients [106]. CAR unlike GPS is a continuous variable and is believed to have a wider clinical application than GPS. A high level of CAR is linked to survival in cancer patients [102, 107]. De Lima reported that CAR was significantly associated with weight loss and SGA in patients with gastrointestinal tumours [108]. A high preoperative CAR and low PNI strongly correlated with poor survival in pancreatic cancer [109]. In oral cancer patients, Park et al. showed that CAR was significantly associated with both PNI and mGPS, and was also a better marker for survival than the other markers [110]. Another related novel marker, CRP/Prealbumin ratio is seen as a prospective inflammatory nutritional prognostic tool in cancer [111], likewise the albumin/CRP ratio [8, 88].
Haematological test i.e. complete blood count is one of the most common, simple and accessible tests in cancer evaluation. As cellular markers of inflammation, they provide prognostic and treatment information about the cancer patient. It is now established that the presence of a pre-operative systemic inflammatory response is predictive of disease progression and poorer outcome, regardless of tumour stage, in patients with various cancers [112, 113]. Inflammation based scoring systems such as the modified Glasgow Prognostic Score (mGPS) and the Neutrophil-Lymphocyte ratio (NLR) have prognostic value in different solid tumours [112]. However, concerning the NLR, multiple thresholds have been used to define high and low NLR values and some have suggested that its prognostic value is mainly derived from the neutrophil count and that the lymphocyte count makes little contribution [114]. Platelets are known to shield tumour cells from shear forces and assault of NK cells, recruit myeloid cells by secretion of chemokines and mediate an arrest of the tumour cell platelet embolus at the vascular wall [115, 116], which indirectly makes the Platelet- lymphocyte ratio (PLR) a prognostic marker in cancer. Studies have revealed that combinations of these parameters could accurately predict the prognosis of a patient than a single index. Like with other inflammatory markers, haematological ratios are associated with malnutrition. Many studies have reported the relationship between NLR and nutritional status. In a recently published work, Siqueira et al. demonstrated the relationship between NLR and nutritional risk in some cancer patients [117]. Sato et al. equally reported a significant inverse relationship of prealbumin with NLR [118]. NLR was associated with SGA especially in severely malnourished cancer patients [119] as well as with percentage weight loss [92].
PLR is another haematological ratio and inflammation marker that has been reported to be associated with many conditions including cancers. Elevated PLR is associated with increased all-cause mortality in different conditions [120], is a prognostic marker in many cancers [121] and is also associated with nutritional status [122]. As a marker of nutrition, PLR was significantly correlated with PNI and BMI in pancreatic cancer patients [87]; along with NLR was significantly associated with PNI in hepatocellular carcinoma [123]. PLR is also associated with haemoglobin and post-op complications in colorectal cancer patients affecting morbidity rates [124]. Sarcopenia, characterised by a decline of skeletal muscle plus low muscle strength and/or physical performance was reported to be associated with NLR and PLR in both renal cell carcinoma and gastric cancer patients [125, 126]. In addition PLR significantly correlated with both BMI and haemoglobin [125]; while in the gastric cancer patients, both PLR and NLR were significantly associated with NRS, albumin, haemoglobin, and cancer stage [126]. NLR and PLR are also reported to be significantly associated with performance status in cancer [115]. The main shortcomings of the haematological ratios are the different cut off levels in various studies.
Some other haematological ratios and scores such as lymphocyte monocyte ratio (LMR), neutrophil platelet score (NPS) etc. have been reported to have some prognostic value in cancer [101]. The monocyte lymphocyte ratio (MLR) was reported to be significantly correlated to PNI and albumin [87] in pancreatic cancer making it a potential nutritional marker like NLR. Combination haematological indices such as the Combination of Platelet count and Neutrophil to Lymphocyte Ratio (COP-NLR), combination of neutrophil-lymphocyte ratio (NLR) and platelet lymphocyte ratio (PLR) (CNP), fibrinogen and NLR (F-NLR) etc. have been shown to have good prognostic value, and their association with nutritional indices should broaden the nutrition/inflammation arena further.
Cytokines are protein molecules released by lymphocytes, monocytes/macrophages and mediate as well as regulate immunity, inflammation and haematopoiesis. Cytokines are the major players in cancer-associated malnutrition, being involved in every aspect of the pathophysiology as earlier explained. They hold great promise as inflammatory markers in nutrition, however, they pose some challenges, particularly their short half-lives [127, 128]. They can be measured in serum or plasma samples; however, measurements from the different sample types cannot be used interchangeably [129].tissues or supernatant from cultured peripheral blood mononuclear cell (PBMC) preparations can also be employed in their measurement. The effect of freezing and thawing can lead to its degradation affecting the measurement. There is an equal lack of standardisation of assays, and because cytokines affect multiple pathways, there is also a lack of specificity [130].
Despite its shortcomings, cytokines are still studied in nutrition research. IL-6 is incorporated into the newly validated CAchexia SCOre (CASCO) for staging cachexic cancer patients [131], although it is not included in the simplified MiniCASCO (MCASCO) [132]. IL-6 is also associated with weight loss, and also correlates with high Prognostic Inflammatory Nutritional Index [133, 134].
Other inflammatory markers for measuring malnutrition include prealbumin, haemoglobin, transferrin, and absolute lymphocyte count (ALC). Many of them are incorporated into nutritional indices either as ratios or as scores. Prealbumin, haemoglobin and ALC are incorporated into the CASCO score [133]. For ALC, levels are associated with various degrees of malnutrition. Levels >2000 cells/m3 (normal), 1200 to 2000 cells/m3 (mild depletion), 800 to 1199 cells/m3 (moderate depletion), and < 800 cells/m3 (severe depletion) [135]. Haemoglobin is part of the haemoglobin platelet ratio (HPR) which has been shown to have diagnostic value in colon cancer [136].
As it has been shown, inflammation plays a central role in cancer-related malnutrition which can lead to cachexia and eventually death. Malnutrition accounts for about 20% of all cancer deaths and is associated with reduced quality of life. Markers of inflammation play a prognostic role in cancer and are most times significantly associated with indices of malnutrition in cancer patients. Several studies have shown that inflammatory markers can be used as a screening test for malnutrition in cancer; though their specificity may be below as a result of other disease states. The inflammation-based scores are more sensitive than the single tests. These tests are cheap and easy to apply. However, their major shortcomings are different cut off levels.
The author declare no conflict of interests.
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\\n\\nFeel free to contact us at funders@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
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\n\nHowever, as Open Access becomes a more commonly used publishing option for the dissemination of scientific and scholarly content, in addition to institutions, there are a growing number of funders who allow the use of grants for covering OA publication costs, or have established separate funds for the same purpose.
\n\nPlease consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
\n\nFor Authors who are unable to obtain funding from their institution or research funding bodies and still need help in covering publication costs, IntechOpen offers the possibility of applying for a Waiver.
\n\nOur mission is to support Authors in publishing their research and making an impact within the scientific community. Currently, 14% of Authors receive full waivers and 6% receive partial waivers.
\n\nWhile providing support and advice to all our international Authors, waiver priority will be given to those Authors who reside in countries that are classified by the World Bank as low-income economies. In this way, we can help ensure that the scientific work being carried out can make an impact within the worldwide scientific community, no matter where an Author might live.
\n\nThe application process is open after your submitted manuscript has been accepted for publication. To apply, please fill out a Waiver Request Form and send it to your Author Service Manager. If you have an official letter from your university or institution showing that funds for your OA publication are unavailable, please attach that as well. The Waiver Request will normally be addressed within one week from the application date. All chapters that receive waivers or partial waivers will be designated as such online.
\n\nDownload Waiver Request Form
\n\nFeel free to contact us at funders@intechopen.com if you have any questions about Funding options or our Waiver program. If you have already begun the process and require further assistance, please contact your Author Service Manager, who is there to assist you!
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Biology",slug:"structural-biology"},numberOfBooks:9,numberOfSeries:0,numberOfAuthorsAndEditors:212,numberOfWosCitations:71,numberOfCrossrefCitations:58,numberOfDimensionsCitations:122,videoUrl:null,fallbackUrl:null,description:null},booksByTopicFilter:{topicId:"913",sort:"-publishedDate",limit:12,offset:0},booksByTopicCollection:[{type:"book",id:"10839",title:"Protein Detection",subtitle:null,isOpenForSubmission:!1,hash:"2f1c0e4e0207fc45c936e7d22a5369c4",slug:"protein-detection",bookSignature:"Yusuf Tutar and Lütfi Tutar",coverURL:"https://cdn.intechopen.com/books/images_new/10839.jpg",editedByType:"Edited by",editors:[{id:"158492",title:"Prof.",name:"Yusuf",middleName:null,surname:"Tutar",slug:"yusuf-tutar",fullName:"Yusuf Tutar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10424",title:"Homology Molecular Modeling",subtitle:"Perspectives and 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Stürzbecher",coverURL:"https://cdn.intechopen.com/books/images_new/5989.jpg",editedByType:"Edited by",editors:[{id:"58579",title:"Dr.",name:"Effrossyni",middleName:null,surname:"Boutou",slug:"effrossyni-boutou",fullName:"Effrossyni Boutou"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6649",title:"Peripheral Membrane Proteins",subtitle:null,isOpenForSubmission:!1,hash:"dd98f01959b3ba6cc9483c03e75b9e0a",slug:"peripheral-membrane-proteins",bookSignature:"Shihori Tanabe",coverURL:"https://cdn.intechopen.com/books/images_new/6649.jpg",editedByType:"Edited by",editors:[{id:"48635",title:"Dr.",name:"Shihori",middleName:null,surname:"Tanabe",slug:"shihori-tanabe",fullName:"Shihori Tanabe"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6635",title:"Protein-Protein Interaction Assays",subtitle:null,isOpenForSubmission:!1,hash:"1bed553d74f0565c89758a7159647634",slug:"protein-protein-interaction-assays",bookSignature:"Mahmood-ur-Rahman Ansari",coverURL:"https://cdn.intechopen.com/books/images_new/6635.jpg",editedByType:"Edited by",editors:[{id:"185476",title:"Dr.",name:"Mahmood-ur-Rahman",middleName:null,surname:"Ansari",slug:"mahmood-ur-rahman-ansari",fullName:"Mahmood-ur-Rahman Ansari"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"780",title:"Proteomics",subtitle:"Human Diseases and Protein Functions",isOpenForSubmission:!1,hash:"a90c4e5b369d27036134a3c66ce1cb26",slug:"proteomics-human-diseases-and-protein-functions",bookSignature:"Tsz-Kwong Man and Ricardo J. Flores",coverURL:"https://cdn.intechopen.com/books/images_new/780.jpg",editedByType:"Edited by",editors:[{id:"35047",title:"Prof.",name:"Tsz Kwong",middleName:null,surname:"Man",slug:"tsz-kwong-man",fullName:"Tsz Kwong Man"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:9,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"28196",doi:"10.5772/31776",title:"Exploring the Role of Biomarkers for the Diagnosis and Management of Traumatic Brain Injury Patients",slug:"exploring-the-role-of-biomarkers-for-the-diagnosis-and-management-of-traumatic-brain-injury-patients",totalDownloads:3015,totalCrossrefCites:9,totalDimensionsCites:22,abstract:null,book:{id:"780",slug:"proteomics-human-diseases-and-protein-functions",title:"Proteomics",fullTitle:"Proteomics - Human Diseases and Protein Functions"},signatures:"Linda Papa",authors:[{id:"88648",title:"Dr.",name:"Linda",middleName:null,surname:"Papa",slug:"linda-papa",fullName:"Linda Papa"}]},{id:"66145",doi:"10.5772/intechopen.83426",title:"New Insights into the Mechanisms Underlying NEDD8 Structural and Functional Specificities",slug:"new-insights-into-the-mechanisms-underlying-nedd8-structural-and-functional-specificities",totalDownloads:992,totalCrossrefCites:6,totalDimensionsCites:9,abstract:"Ubiquitin (Ub) and ubiquitin-like (Ubl) proteins are small polypeptides that are conjugated to substrates affecting their activity and stability. Cells encode “receptors” containing Ub-/Ubl-binding domains that interpret and translate each modification into appropriate cellular responses. Among the different Ubls, NEDD8, which is the ubiquitin’s closest relative, retains many of the structural determinants that enable ubiquitin the ability to target proteins to degradation. Nevertheless, the direct involvement of NEDD8 conjugation to proteasome recruitment has been proved only in a few cases. To date, well-defined major NEDD8 substrates are primarily members of the cullin family, and cullin neddylation does not appear to mark these proteins for degradation. Various studies have demonstrated that selectivity between ubiquitin and NEDD8 is guaranteed by small but substantial differences. Nevertheless, several issues still need to be addressed, mainly concerning which interaction surfaces mediate NEDD8 function and what domains recognize them. Recently, two novel domains identified in KHNYN and N4BP1 proteins have shed new light on this research area. Here, I discuss some recent reports that contributed to shed light on the mechanisms underlining the discrimination between ubiquitin and NEDD8. Understanding the details of these molecular mechanisms represents a prominent facet for the identification of new therapeutic targets.",book:{id:"8301",slug:"ubiquitin-proteasome-system-current-insights-into-mechanism-cellular-regulation-and-disease",title:"Ubiquitin Proteasome System",fullTitle:"Ubiquitin Proteasome System - Current Insights into Mechanism Cellular Regulation and Disease"},signatures:"Elena Santonico",authors:[{id:"271923",title:"Dr.",name:"Elena",middleName:null,surname:"Santonico",slug:"elena-santonico",fullName:"Elena Santonico"}]},{id:"28199",doi:"10.5772/31082",title:"F0F1 ATP Synthase: A Fascinating Challenge for Proteomics",slug:"f0f1-atp-synthase-a-fascinating-challenge-for-proteomics",totalDownloads:5557,totalCrossrefCites:2,totalDimensionsCites:8,abstract:null,book:{id:"780",slug:"proteomics-human-diseases-and-protein-functions",title:"Proteomics",fullTitle:"Proteomics - Human Diseases and Protein Functions"},signatures:"Federica Dabbeni-Sala, Amit Kumar Rai and Giovanna Lippe",authors:[{id:"85523",title:"Prof.",name:"Giovanna",middleName:null,surname:"Lippe",slug:"giovanna-lippe",fullName:"Giovanna Lippe"},{id:"149272",title:"Dr.",name:"Federica",middleName:null,surname:"Dabbeni-Sala",slug:"federica-dabbeni-sala",fullName:"Federica Dabbeni-Sala"},{id:"149273",title:"Dr.",name:"Amit",middleName:null,surname:"Kumar Rai",slug:"amit-kumar-rai",fullName:"Amit Kumar Rai"}]},{id:"65025",doi:"10.5772/intechopen.82883",title:"E3 Ubiquitin Ligases in Cancer and Their Pharmacological Targeting",slug:"e3-ubiquitin-ligases-in-cancer-and-their-pharmacological-targeting",totalDownloads:1681,totalCrossrefCites:2,totalDimensionsCites:8,abstract:"Ubiquitination plays many critical roles in protein function and regulation. Consequently, mutation and aberrant expression of E3 ubiquitin ligases can drive cancer progression. Identifying key ligase-substrate relationships is crucial to understanding the molecular basis and pathways behind cancer and toward identifying novel targets for cancer therapeutics. Here, we review the importance of E3 ligases in the regulating the hallmarks of cancer, discuss some of the key and novel E3 ubiquitin ligases that drive tumor formation and angiogenesis, and review the clinical development of inhibitors that antagonize their function. We conclude with perspectives on the field and future directions toward understanding ubiquitination and cancer progression.",book:{id:"8301",slug:"ubiquitin-proteasome-system-current-insights-into-mechanism-cellular-regulation-and-disease",title:"Ubiquitin Proteasome System",fullTitle:"Ubiquitin Proteasome System - Current Insights into Mechanism Cellular Regulation and Disease"},signatures:"Joseph Y. Ong and Jorge Z. Torres",authors:[{id:"186645",title:"Dr.",name:"Jorge",middleName:null,surname:"Torres",slug:"jorge-torres",fullName:"Jorge Torres"},{id:"264944",title:"Mr.",name:"Joseph",middleName:null,surname:"Ong",slug:"joseph-ong",fullName:"Joseph Ong"}]},{id:"28201",doi:"10.5772/31113",title:"Identification of the Novel Plasminogen Receptor, Plg-RKT",slug:"identification-of-the-novel-plasminogen-receptor-plg-rkt",totalDownloads:2435,totalCrossrefCites:2,totalDimensionsCites:5,abstract:null,book:{id:"780",slug:"proteomics-human-diseases-and-protein-functions",title:"Proteomics",fullTitle:"Proteomics - Human Diseases and Protein Functions"},signatures:"Lindsey A. Miles, Nicholas M. Andronicos, Emily I. Chen, Nagyung Baik, Hongdong Bai, Caitlin M. Parmer, Shahrzad Lighvani, Samir Nangia, William B. Kiosses, Mark P. Kamps, John R. Yates III and Robert J. Parmer",authors:[{id:"85634",title:"Dr.",name:"Lindsey A.",middleName:null,surname:"Miles",slug:"lindsey-a.-miles",fullName:"Lindsey A. Miles"},{id:"85772",title:"Dr.",name:"Nicholas M.",middleName:null,surname:"Andronicos",slug:"nicholas-m.-andronicos",fullName:"Nicholas M. Andronicos"},{id:"85773",title:"Dr.",name:"Emily I.",middleName:null,surname:"Chen",slug:"emily-i.-chen",fullName:"Emily I. Chen"},{id:"85775",title:"MSc.",name:"Nagyung",middleName:null,surname:"Baik",slug:"nagyung-baik",fullName:"Nagyung Baik"},{id:"85776",title:"Dr.",name:"Hongdong",middleName:null,surname:"Bai",slug:"hongdong-bai",fullName:"Hongdong Bai"},{id:"85777",title:"Ms.",name:"Caitlin M.",middleName:null,surname:"Parmer",slug:"caitlin-m.-parmer",fullName:"Caitlin M. Parmer"},{id:"85778",title:"Dr.",name:"William B.",middleName:null,surname:"Kiosses",slug:"william-b.-kiosses",fullName:"William B. Kiosses"},{id:"85780",title:"Dr.",name:"John R.",middleName:null,surname:"Yates, III",slug:"john-r.-yates-iii",fullName:"John R. Yates, III"},{id:"85781",title:"Dr.",name:"Robert J.",middleName:null,surname:"Parmer",slug:"robert-j.-parmer",fullName:"Robert J. Parmer"},{id:"123594",title:"Dr.",name:"Samir",middleName:null,surname:"Nangia",slug:"samir-nangia",fullName:"Samir Nangia"},{id:"123595",title:"Dr.",name:"Shahrzad",middleName:null,surname:"Lighvani",slug:"shahrzad-lighvani",fullName:"Shahrzad Lighvani"}]}],mostDownloadedChaptersLast30Days:[{id:"70577",title:"Proteoforms: General Concepts and Methodological Process for Identification",slug:"proteoforms-general-concepts-and-methodological-process-for-identification",totalDownloads:924,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The term proteoform is used to denote all the molecular forms in which the protein product of a single gene can be found. The most frequent processes that lead to transcript modification and the biological implications of these changes observed in the final protein product will be discussed. Proteoforms arising from genetic variations, alternatively spliced RNA transcripts and post-translational modifications will be commented. This chapter will present an evolution of the techniques used to identify the proteoforms and the importance of this identification for understanding of biological processes. This chapter highlights the fundamental concepts in the field of top-down mass spectrometry (TDMS), and provides numerous examples for the use of knowledge obtained from the identification of proteoforms. The identification of mutant proteins is one of the emerging areas of proteogenomics and has the potential to recognize novel disease biomarkers and may point to useful targets for identification of therapeutic approaches.",book:{id:"9352",slug:"proteoforms-concept-and-applications-in-medical-sciences",title:"Proteoforms",fullTitle:"Proteoforms - Concept and Applications in Medical Sciences"},signatures:"Jucélia da Silva Araújo and Olga Lima Tavares Machado",authors:[{id:"30130",title:"Dr.",name:"Olga Lima Tavares",middleName:null,surname:"Machado",slug:"olga-lima-tavares-machado",fullName:"Olga Lima Tavares Machado"},{id:"310148",title:"Dr.",name:"Jucelia",middleName:null,surname:"Da Silva Araujo",slug:"jucelia-da-silva-araujo",fullName:"Jucelia Da Silva Araujo"}]},{id:"65025",title:"E3 Ubiquitin Ligases in Cancer and Their Pharmacological Targeting",slug:"e3-ubiquitin-ligases-in-cancer-and-their-pharmacological-targeting",totalDownloads:1681,totalCrossrefCites:2,totalDimensionsCites:8,abstract:"Ubiquitination plays many critical roles in protein function and regulation. Consequently, mutation and aberrant expression of E3 ubiquitin ligases can drive cancer progression. Identifying key ligase-substrate relationships is crucial to understanding the molecular basis and pathways behind cancer and toward identifying novel targets for cancer therapeutics. Here, we review the importance of E3 ligases in the regulating the hallmarks of cancer, discuss some of the key and novel E3 ubiquitin ligases that drive tumor formation and angiogenesis, and review the clinical development of inhibitors that antagonize their function. We conclude with perspectives on the field and future directions toward understanding ubiquitination and cancer progression.",book:{id:"8301",slug:"ubiquitin-proteasome-system-current-insights-into-mechanism-cellular-regulation-and-disease",title:"Ubiquitin Proteasome System",fullTitle:"Ubiquitin Proteasome System - Current Insights into Mechanism Cellular Regulation and Disease"},signatures:"Joseph Y. Ong and Jorge Z. Torres",authors:[{id:"186645",title:"Dr.",name:"Jorge",middleName:null,surname:"Torres",slug:"jorge-torres",fullName:"Jorge Torres"},{id:"264944",title:"Mr.",name:"Joseph",middleName:null,surname:"Ong",slug:"joseph-ong",fullName:"Joseph Ong"}]},{id:"65109",title:"Ubiquitin Signaling in Regulation of the Start of the Cell Cycle",slug:"ubiquitin-signaling-in-regulation-of-the-start-of-the-cell-cycle",totalDownloads:1578,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The small protein ubiquitin plays a vital role in virtually all aspects of cellular life. Among the diverse signaling outcomes associated with ubiquitination, the most well-established is the targeted degradation of substrates via the proteasome. During cell growth and proliferation, ubiquitin plays an outsized role in promoting progression through the cell cycle. In particular, ubiquitin-mediated degradation is critically important at transition points where it provides directionality and irreversibility to the cell cycle, which is essential for maintaining genome integrity. Specifically, the boundary between G1 and S-phase is tightly regulated by the ubiquitin proteasome system. Notably, the G1/S boundary represents a major barrier to cell proliferation and is universally dysfunctional in cancer cells, allowing for the unbridled proliferation observed in malignancy. Numerous E3 ubiquitin ligases, which facilitate the ubiquitination of specific substrates, have been shown to control G1/S. In this chapter, we will discuss components in the ubiquitin proteasome system that are implicated in G1/S control, how these enzymes are interconnected, gaps in our current knowledge, and the potential role of these pathways in the cancer cycle and disease proliferation.",book:{id:"8301",slug:"ubiquitin-proteasome-system-current-insights-into-mechanism-cellular-regulation-and-disease",title:"Ubiquitin Proteasome System",fullTitle:"Ubiquitin Proteasome System - Current Insights into Mechanism Cellular Regulation and Disease"},signatures:"Michael James Emanuele and Taylor Paige Enrico",authors:[{id:"264977",title:"Dr.",name:"Michael",middleName:null,surname:"Emanuele",slug:"michael-emanuele",fullName:"Michael Emanuele"},{id:"282200",title:"Ms.",name:"Taylor",middleName:null,surname:"Enrico",slug:"taylor-enrico",fullName:"Taylor Enrico"}]},{id:"60432",title:"Protein-Based Detection Methods for Genetically Modified Crops",slug:"protein-based-detection-methods-for-genetically-modified-crops",totalDownloads:1430,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"The generation of genetically modified (GM) crops is rapidly expanding each and every year around the world. The well-being and quality assessment of these harvests are vital issues with respect to buyers’ interests. This drove the administrative specialists to execute an arrangement of extremely strict strategies for the endorsement to develop and use GMOs and to produce an interest in scientific techniques equipped for identifying GM crops. The GM crops have been added to the effective fuse of various attributes by presenting transgenes, for example, Bacillus thuringiensis (Bt) insecticidal qualities, in various crop species. GM crops give critical financial, natural, well-being and social advantages to both small and large agriculturists. The detection strategies incorporate either DNA-based or protein-based measures. Different immunoassays or catalyst connected immunosorbent tests are delicate and more affordable; however, they need experienced technicians. A very simple method, that is, immunochromatographic (ICS) test, is set up in the world, which is modest, compact and simple to utilize. The ICS is a semiquantitative method for indicative screening and semi-measurement of new remote proteins presented through hereditary change of plants. The strip is the easiest method for the assessment of several Bt crop plants for insecticidal quality.",book:{id:"6635",slug:"protein-protein-interaction-assays",title:"Protein-Protein Interaction Assays",fullTitle:"Protein-Protein Interaction Assays"},signatures:"Kausar Malik, Haleema Sadia and Muhammad Hamza Basit",authors:[{id:"238750",title:"Prof.",name:"Kausar",middleName:null,surname:"Malik",slug:"kausar-malik",fullName:"Kausar Malik"},{id:"243713",title:"Dr.",name:"Haleema",middleName:null,surname:"Sadia",slug:"haleema-sadia",fullName:"Haleema Sadia"},{id:"243714",title:"Mr.",name:"Muhammad Hamza",middleName:null,surname:"Basit",slug:"muhammad-hamza-basit",fullName:"Muhammad Hamza Basit"}]},{id:"60064",title:"Rapid Endosomal Recycling",slug:"rapid-endosomal-recycling",totalDownloads:1342,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"Peripheral membrane proteins are endocytosed by constitutive processes of membrane invaginations, followed by internalization driven by diverse endocytic machinery available at the cell surface. It is believed that after endocytic uptake, cargo proteins proceed either through the endosomal recycling circuit of the cell or travel toward late endosomes for degradation. In this chapter, we analyzed trafficking of seven cargo molecules (transferrin receptor, fully conformed MHC-I, non-conformed MHC-I, cholera-toxin B subunit, CD44, ICAM1, and G-protein-coupled receptor Rae-1) known to use the distinct endocytic route. For that purpose, we developed the software for multicompartment analysis of intracellular trafficking. We demonstrate that all endocytosed molecules are rapidly recycled and propose that the rapid recycling is a constitutive process that should be considered in the analysis of intracellular trafficking of peripheral membrane proteins.",book:{id:"6649",slug:"peripheral-membrane-proteins",title:"Peripheral Membrane Proteins",fullTitle:"Peripheral Membrane Proteins"},signatures:"Hana Mahmutefendić, Gordana Blagojević Zagorac, Senka Maćešić\nand Pero Lučin",authors:[{id:"152008",title:"Prof.",name:"Pero",middleName:null,surname:"Lučin",slug:"pero-lucin",fullName:"Pero Lučin"},{id:"245873",title:"Prof.",name:"Hana",middleName:null,surname:"Mahmutefendić",slug:"hana-mahmutefendic",fullName:"Hana Mahmutefendić"},{id:"245875",title:"Prof.",name:"Gordana",middleName:null,surname:"Blagojević Zagorac",slug:"gordana-blagojevic-zagorac",fullName:"Gordana Blagojević Zagorac"},{id:"245876",title:"Prof.",name:"Senka",middleName:null,surname:"Maćešić",slug:"senka-macesic",fullName:"Senka Maćešić"}]}],onlineFirstChaptersFilter:{topicId:"913",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:28,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null}]},{type:"book",id:"7656",title:"Fuzzy Logic",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7656.jpg",slug:"fuzzy-logic",publishedDate:"February 5th 2020",editedByType:"Edited by",bookSignature:"Constantin Volosencu",hash:"54f092d4ffe0abf5e4172a80025019bc",volumeInSeries:3,fullTitle:"Fuzzy Logic",editors:[{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",institutionURL:null,country:{name:"Romania"}}}]},{type:"book",id:"9963",title:"Advances and Applications in Deep Learning",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/9963.jpg",slug:"advances-and-applications-in-deep-learning",publishedDate:"December 9th 2020",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"0d51ba46f22e55cb89140f60d86a071e",volumeInSeries:4,fullTitle:"Advances and Applications in Deep Learning",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. 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