Bioaerosol concentrations in poultry houses.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\n'}],latestNews:[{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"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"6178",leadTitle:null,fullTitle:"Hansen's Disease - The Forgotten and Neglected Disease",title:"Hansen's Disease",subtitle:"The Forgotten and Neglected Disease",reviewType:"peer-reviewed",abstract:"Hansen's Disease - The Forgotten and Neglected Disease provides concise information on the relevant aspects of the disease of leprosy, including immunological, epidemiological, clinical and molecular studies that are of great importance in the study of an often-ignored disease, which remains a great challenge to humanity. It collects contributions made by professional experts in the study of Mycobacterium leprae, providing perspectives with knowledge, experience and research, highlighting that the disease continues to be of interest to public health. It is expected that this book will be useful and contribute to the expansion of information and interest about the disease commonly known as leprosy.",isbn:"978-1-78984-987-5",printIsbn:"978-1-78984-986-8",pdfIsbn:"978-1-83881-998-9",doi:"10.5772/intechopen.68432",price:119,priceEur:129,priceUsd:155,slug:"hansen-s-disease-the-forgotten-and-neglected-disease",numberOfPages:170,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"c68f443f518dcee16e6083e7295a2532",bookSignature:"Wellman Ribòn",publishedDate:"February 6th 2019",coverURL:"https://cdn.intechopen.com/books/images_new/6178.jpg",numberOfDownloads:9098,numberOfWosCitations:2,numberOfCrossrefCitations:2,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:4,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:8,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 21st 2017",dateEndSecondStepPublish:"April 11th 2017",dateEndThirdStepPublish:"September 23rd 2017",dateEndFourthStepPublish:"October 23rd 2017",dateEndFifthStepPublish:"December 23rd 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"88491",title:"Dr.",name:"Wellman",middleName:null,surname:"Ribón",slug:"wellman-ribon",fullName:"Wellman Ribón",profilePictureURL:"https://mts.intechopen.com/storage/users/88491/images/system/88491.jpeg",biography:"Wellman Ribón, bacteriologist and clinical laboratory professional of the Industrial University of Santander, Master\\'s degree in Biochemistry from Universidad Javeriana; with more than fifteen years of experience as public health adviser, Colciencias (Departamento Administrativo de Ciencia y Tecnología de Colombia) senior researcher in scientific and technological development. He has worked at the National Health Institute of Colombia as coordinator of the mycobacteria group, manager of research projects and member of Centro Colombiano de Excelencia de Investigación en Tuberculosis (CCITB), EurolabTB Consortium and the SLAMTB. Ribón was the Microbiology School director and is currently a professor in Medicine School and works as professor and researcher at the Industrial University of Santander,.He is also the director of the Mycobacterium Research laboratory. Mr. Ribón has published articles about tuberculosis, leprosy and mycobacteriosis diseases, and has written four book chapters. His major area of interest and research is Mycobacterium tuberculosis complex.",institutionString:"Industrial University of Santander",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"6",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Industrial University of Santander",institutionURL:null,country:{name:"Colombia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1046",title:"Infectious Diseases",slug:"infectious-diseases"}],chapters:[{id:"64773",title:"Introductory Chapter: Hansen ́s Disease – The Forgotten and Neglected Disease",doi:"10.5772/intechopen.82427",slug:"introductory-chapter-hansen-s-disease-the-forgotten-and-neglected-disease",totalDownloads:810,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Lina Fernández and Wellman Ribón",downloadPdfUrl:"/chapter/pdf-download/64773",previewPdfUrl:"/chapter/pdf-preview/64773",authors:[{id:"88491",title:"Dr.",name:"Wellman",surname:"Ribón",slug:"wellman-ribon",fullName:"Wellman Ribón"}],corrections:null},{id:"60017",title:"The Distribution and Origins of Ancient Leprosy",doi:"10.5772/intechopen.75260",slug:"the-distribution-and-origins-of-ancient-leprosy",totalDownloads:1370,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:1,abstract:"Human leprosy is primarily caused by Mycobacterium leprae, but also by the related ‘M. lepromatosis’. Ancient leprosy can be recognised in archaeological materials by the paleopathology associated with multi-bacillary or lepromatous forms of the disease. Whole M. leprae genomes have been obtained from human skeletons, and diagnostic aDNA fragments have been recovered. The derived M. leprae phylogenies, based on single nucleotide polymorphisms, mirror past human migrations, as M. leprae is usually an obligate pathogen. The detection of M. leprae in historical leprosy cases is assisted by the hydrophobic M. leprae cell envelope, which is composed of unusual lipids that can be used as specific biomarkers. Lipid biomarkers are more stable than aDNA and can be detected directly without amplification. Indigenous human leprosy is extinct in Western Europe, but recently, both M. leprae and ‘M. lepromatosis’ were found in British red squirrels. Leprosy may also be found in nine-banded armadillos (Dasypus novemcinctus) where it can cause a zoonotic human infection. Certain leprosy-like diseases, caused by uncultivable species in cats, for example, may be related to M. leprae. The closest extant relatives of leprosy bacilli are probably members of the M. haemophilum taxon, emerging pathogens with genomic and lipid biomarker similarities.",signatures:"Helen D. Donoghue, G. Michael Taylor, Tom A. Mendum, Graham R.\nStewart, Leen Rigouts, Oona Y-C. Lee, Houdini H.T. Wu, Gurdyal S.\nBesra and David E. Minnikin",downloadPdfUrl:"/chapter/pdf-download/60017",previewPdfUrl:"/chapter/pdf-preview/60017",authors:[{id:"81479",title:"Prof.",name:"David",surname:"Minnikin",slug:"david-minnikin",fullName:"David Minnikin"},{id:"88527",title:"Prof.",name:"Gurdyal",surname:"Besra",slug:"gurdyal-besra",fullName:"Gurdyal Besra"},{id:"88528",title:"Dr.",name:"Oona",surname:"Lee",slug:"oona-lee",fullName:"Oona Lee"},{id:"88529",title:"Dr.",name:"Helen",surname:"Donoghue",slug:"helen-donoghue",fullName:"Helen Donoghue"},{id:"173387",title:"Dr.",name:"Houdini",surname:"Wu",slug:"houdini-wu",fullName:"Houdini Wu"},{id:"226778",title:"Prof.",name:"G. Michael",surname:"Taylor",slug:"g.-michael-taylor",fullName:"G. Michael Taylor"},{id:"226779",title:"Dr.",name:"Tom A.",surname:"Mendum",slug:"tom-a.-mendum",fullName:"Tom A. Mendum"},{id:"226780",title:"Prof.",name:"Graham R.",surname:"Stewart",slug:"graham-r.-stewart",fullName:"Graham R. Stewart"},{id:"226781",title:"Dr.",name:"Leen",surname:"Rigouts",slug:"leen-rigouts",fullName:"Leen Rigouts"}],corrections:null},{id:"64425",title:"An Update on the Epidemiology, Diagnosis and Treatment of Leprosy",doi:"10.5772/intechopen.80557",slug:"an-update-on-the-epidemiology-diagnosis-and-treatment-of-leprosy",totalDownloads:1431,totalCrossrefCites:2,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Leprosy is a granulomatous, chronic infection caused by Mycobacterium leprae that has been reported for than 2000 years. The infection primarily affects the skin and peripheral nerves. M. leprae is bacterium that cannot be cultured in vitro and transmission and pathophysiological data is still uncertain and limited. Today the prevalence of this ancient disease is declining in most around the world. This decline is a direct effect of widespread administration by public health workers of multidrug therapy. However, emerging despite the use of multidrug therapy, identifying and monitoring resistance are still necessary.",signatures:"Nebahat Demet Akpolat, Ayse Akkus and Emre Kaynak",downloadPdfUrl:"/chapter/pdf-download/64425",previewPdfUrl:"/chapter/pdf-preview/64425",authors:[{id:"208481",title:"M.D.",name:"Demet",surname:"Akpolat",slug:"demet-akpolat",fullName:"Demet Akpolat"},{id:"209524",title:"Dr.",name:"Emre",surname:"Kaynak",slug:"emre-kaynak",fullName:"Emre Kaynak"},{id:"212484",title:"Ms.",name:"Ayse",surname:"Akkus",slug:"ayse-akkus",fullName:"Ayse Akkus"}],corrections:null},{id:"60910",title:"Molecular and Biotechnological Approaches in the Diagnosis of Leprosy",doi:"10.5772/intechopen.75506",slug:"molecular-and-biotechnological-approaches-in-the-diagnosis-of-leprosy",totalDownloads:1077,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Leprosy is a worldwide health problem, which needs the development of new and innovative strategies to be controlled. Early diagnosis of leprosy is an important contribution to reducing the incidence of the disease; thus, the development of biotechnology platforms, which include the mapping of antigens with potential to be used in immunodiagnostic and molecular methods for the detection of Mycobacterium leprae, is an important tool to confirm the clinical diagnostic. Molecular biology and biotechnological methods have been used to assist in the diagnosis of this disease, each one with its advantages and drawbacks. Enzyme-linked immunosorbent assay (ELISA) is the used method for leprosy diagnosis, and it allows the detection of infection-related antigens. Alternatively, due to their versatility to perform the same functions as the protein and non-protein natural antigens, mimetic peptides are considered an important tool. On the other hand, lateral flow assay (LFA) and optical and electrochemical biosensors are rapid and portable methods, capable of performing diagnosis in the field without sample preparation. This chapter presents such techniques, their uses in the diagnosis and detection of M. leprae, as well as the potential for the development of new techniques and strategies that can help to control and understand mycobacteriosis.",signatures:"Mayara Ingrid Sousa Lima, Emilly Caroline dos Santos Moraes,\nJaqueline Diniz Pinho, Gustavo Henrique Corrêa Soares and Ítalo\nVinícius Cantanhêde Santos",downloadPdfUrl:"/chapter/pdf-download/60910",previewPdfUrl:"/chapter/pdf-preview/60910",authors:[{id:"207924",title:"Dr.",name:"Mayara",surname:"Lima",slug:"mayara-lima",fullName:"Mayara Lima"},{id:"218997",title:"BSc.",name:"Emilly",surname:"Moraes",slug:"emilly-moraes",fullName:"Emilly Moraes"},{id:"218998",title:"MSc.",name:"Jaqueline",surname:"Diniz",slug:"jaqueline-diniz",fullName:"Jaqueline Diniz"},{id:"242501",title:"BSc.",name:"Italo",surname:"Santos",slug:"italo-santos",fullName:"Italo Santos"},{id:"242502",title:"BSc.",name:"Gustavo",surname:"Soares",slug:"gustavo-soares",fullName:"Gustavo Soares"}],corrections:null},{id:"58135",title:"Leprosy Reactions",doi:"10.5772/intechopen.72481",slug:"leprosy-reactions",totalDownloads:1294,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Sudden changes in immune-mediated response to Mycobacterium leprae antigen are referred to as leprosy reactions. The reactions manifest as acute inflammatory episodes rather than chronic infectious course. There are mainly two types of leprosy reactions. Type 1 reaction is associated with cellular immunity and particularly with the reaction of T helper 1 (Th1) cells to mycobacterial antigens. This reaction involves exacerbation of old lesions leading to the erythematous appearance. Type 2 reaction or erythema nodosum leprosum (ENL) is associated with humoral immunity. It is characterized by systemic symptoms along with new erythematous subcutaneous nodules.",signatures:"Leyla Bilik, Betul Demir and Demet Cicek",downloadPdfUrl:"/chapter/pdf-download/58135",previewPdfUrl:"/chapter/pdf-preview/58135",authors:[{id:"188909",title:"Dr.",name:"Betul",surname:"Demir",slug:"betul-demir",fullName:"Betul Demir"},{id:"194149",title:"Prof.",name:"Demet",surname:"Cicek",slug:"demet-cicek",fullName:"Demet Cicek"},{id:"208651",title:"Dr.",name:"Leyla",surname:"Bilik",slug:"leyla-bilik",fullName:"Leyla Bilik"}],corrections:null},{id:"64038",title:"Demyelination in Leprosy",doi:"10.5772/intechopen.76892",slug:"demyelination-in-leprosy",totalDownloads:976,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Leprosy is a chronic infectious disease caused by Mycobacterium leprae that has a predilection for peripheral nerves, especially Schwann cells (SCs). Leprosy medications may only eradicate the bacteria without preventing or recovering peripheral nerve damage. Early nerve damage detection is necessary. The expression of Krox-20 in Schwann cells will be examined immunohistochemically, and the level of neuron growth factor (NGF), neuregulin 1 (NRG1), protein 0 (P0), and peripheral myelin protein 22 (PMP22) will be examined in the blood plasmas. A significant decrease was noticed in Krox-20 and NGF, NRG1, P0, and PMP22 level (p < 0.05) in disability degree 1 compared to degree 0. Studies proved that markers have shown promising results; Krox-20, NGF, NRG1, P0, and PMP22 could be useful diagnostic tools for early peripheral nerve damage detection in leprosy.",signatures:"Dhelya Widasmara and Sri Linuwih Menaldi",downloadPdfUrl:"/chapter/pdf-download/64038",previewPdfUrl:"/chapter/pdf-preview/64038",authors:[{id:"217208",title:"Dr.",name:"Dhelya",surname:"Widasmara",slug:"dhelya-widasmara",fullName:"Dhelya Widasmara"},{id:"220477",title:"Dr.",name:"Sri Linuwih",surname:"Menaldi",slug:"sri-linuwih-menaldi",fullName:"Sri Linuwih Menaldi"}],corrections:null},{id:"60014",title:"Immunogenetics of MHC and KIR in the Leprosy",doi:"10.5772/intechopen.75253",slug:"immunogenetics-of-mhc-and-kir-in-the-leprosy",totalDownloads:1196,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"Several genetic polymorphisms in immune response genes have been associated to leprosy. This fact converges on the main hypothesis that genetic factors are involved in the disease susceptibility in two distinct steps: leprosy per se and their clinical forms. These genes play an important role in the recognition process, in the activation of the main metabolic pathway of the immune response and in the evolution of the disease. The scope of this project was to highlight the role of the immune response genes in the context of leprosy, emphasizing the participation of some of them in the signaling and targeting processes in response to bacillus infection and on disease evolution, such as HLA, KIR and MIC genes. Some environmental and genetic factors are important when the exposure to the bacillus occurs, leading to cure or not. Factors that favor a cellular or humoral immune response may influence the clinical manifestations after the infection inducting to one of extreme poles. Furthermore, some genetic factors were associated to the type of reaction that some individuals present during the disease development. Thus, it is very important to highlight the participation of some genetic factors in the immunopathogenesis of leprosy.",signatures:"Hugo Vicentin Alves, Bruna Tiaki Tiyo, Ana Maria Sell and Jeane\nEliete Laguila Visentainer",downloadPdfUrl:"/chapter/pdf-download/60014",previewPdfUrl:"/chapter/pdf-preview/60014",authors:[{id:"170124",title:"Dr.",name:"Ana Maria",surname:"Sell",slug:"ana-maria-sell",fullName:"Ana Maria Sell"},{id:"170125",title:"Dr.",name:"Jeane",surname:"Visentainer",slug:"jeane-visentainer",fullName:"Jeane Visentainer"},{id:"208936",title:"MSc.",name:"Hugo Vicentin",surname:"Alves",slug:"hugo-vicentin-alves",fullName:"Hugo Vicentin Alves"},{id:"208937",title:"Ms.",name:"Bruna Tiaki",surname:"Tiyo",slug:"bruna-tiaki-tiyo",fullName:"Bruna Tiaki Tiyo"}],corrections:null},{id:"59506",title:"Genetic Variation in Pattern-Recognition Receptors and Association with Leprosy",doi:"10.5772/intechopen.73871",slug:"genetic-variation-in-pattern-recognition-receptors-and-association-with-leprosy",totalDownloads:945,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Mycobacterium leprae is a highly infectious and low pathogenic microorganism that is the causal agent of leprosy. The differences in vulnerability to leprosy, the spectral immune response, and the clinical manifestations of this disease are related to different genetic backgrounds among individuals. In this sense, genetic variants, especially in genes related to mycobacteria recognition and host immune response, may be key factors to explain individual susceptibility and resistance to leprosy and their conditions. In this chapter, studies regarding association of genetic variants in pattern-recognition receptors (PRRs) and leprosy will be reviewed revealing the importance of molecules such as Toll-like receptors (TLRs) and nucleotide-binding oligomerization domain-containing protein 2 (NOD2) in leprosy initiation and maintenance.",signatures:"Karina Talita de Oliveira Santana Jorge and Frederico Marianetti\nSoriani",downloadPdfUrl:"/chapter/pdf-download/59506",previewPdfUrl:"/chapter/pdf-preview/59506",authors:[{id:"219482",title:"Ph.D.",name:"Frederico",surname:"Soriani",slug:"frederico-soriani",fullName:"Frederico Soriani"},{id:"229557",title:"MSc.",name:"Karina",surname:"Talita De Oliveira Santana Jorge",slug:"karina-talita-de-oliveira-santana-jorge",fullName:"Karina Talita De Oliveira Santana Jorge"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"4567",title:"Tuberculosis",subtitle:"Expanding Knowledge",isOpenForSubmission:!1,hash:"6620343e9ad62f2984bc393701cee6ff",slug:"tuberculosis-expanding-knowledge",bookSignature:"Wellman Ribon",coverURL:"https://cdn.intechopen.com/books/images_new/4567.jpg",editedByType:"Edited by",editors:[{id:"88491",title:"Dr.",name:"Wellman",surname:"Ribón",slug:"wellman-ribon",fullName:"Wellman Ribón"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"5853",title:"Mycobacterium",subtitle:"Research and Development",isOpenForSubmission:!1,hash:"073e7ca9fbfdd31da5499271f17ecdf2",slug:"mycobacterium-research-and-development",bookSignature:"Wellman Ribón",coverURL:"https://cdn.intechopen.com/books/images_new/5853.jpg",editedByType:"Edited by",editors:[{id:"88491",title:"Dr.",name:"Wellman",surname:"Ribón",slug:"wellman-ribon",fullName:"Wellman Ribón"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,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"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"825",title:"Current Topics in Tropical Medicine",subtitle:null,isOpenForSubmission:!1,hash:"ef65e8eb7a2ada65f2bc939aa73009e3",slug:"current-topics-in-tropical-medicine",bookSignature:"Alfonso J. 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The specific microclimate of farm buildings promotes the accumulation of bioaerosols containing harmful biological substances. Microbial concentrations in poultry houses increase over time and contribute to the sick building syndrome. Very high and often logarithmic growth rates are reported for aerobic mesophilic bacteria, which account for the majority of known pathogenic bacteria. In addition to Gram-positive cocci (
The combined effect of airborne pollutants is one of the key stressors in poultry farms. High concentrations of microorganisms, endotoxins, mycotoxins, gas, and dust exert adverse effects on the structure and protective functions of mucous membranes, in particular in the respiratory system and the conjunctiva, leading to allergic reactions, inflammations, and increasing susceptibility to infectious diseases. Numerous studies have demonstrated that excessive ammonia concentrations in hen house lower productivity [2, 9–11]. Airborne pollutants also have an adverse influence on farm employees [2]. The pollutants emitted by poultry farms have negative environmental consequences. Nitrogen compounds contaminate soil and ground waters [12], whereas gases such as CO2, CH4, and N2O contribute to the greenhouse effect [13, 14]. Recent years have witnessed an increasing interest in volatile organic compounds (VOCs), which are odor-producing compounds [15, 16].
\nThe above threats have led to the initiation of various measures to limit pollution at the source, including legal regulations (international conventions and the resulting legal acts that are binding for the signatory countries) and methods aiming to neutralize the adverse effects of pollution (dietary, production, and hygiene standards). The concentrations of biological and chemical air pollutants vary significantly between farms and livestock facilities, and they are determined not only by the animal species, but also by the housing and management system. For this reason, safe pollution thresholds are very difficult to define. Guidelines for limiting the exposure to selected chemical and physical factors have been developed in occupational medicine, but general threshold limit values (TLV) for biological compounds are very difficult to establish due to an absence of epidemiological data describing the correlations between exposure and health consequences [17]. Different organisms have varied susceptibility to toxic substances; there is a general absence of standardized measurement methods and a scarcity of source data relating to the most widespread bioaerosols, which further exacerbates the problem. Threshold values for farm buildings are even more difficult to determine due to a higher number of limiting factors. Air pollution poses a serious health threat for animals and farm employees; therefore, new research into the type and concentrations of airborne pollutants in various housing systems is needed to effectively mitigate the problem.
\nThis manuscript reviews the results of our previous work and other studies into quantitative and qualitative identification of microbial and gaseous contaminants in poultry houses and methods for the prevention of contamination at the source.
\nThe level of microbial contamination in poultry houses is one of the most important sanitary and hygienic indicators. The main sources of microorganisms in poultry houses are birds, their excrements, feed, litter, ventilation air, and even employees. Microbes carried by dust, water vapor, and secretions from the respiratory tract form bioaerosol. Birds breathe air which acts as a major vector for microorganisms. Most microbes are saprophytes, but some airborne microorganisms may be pathogenic. Pathogens that enter the respiratory system with liquid droplets and dust may cause infections. The smallest particles measuring <50 nm pose the greatest epizootic risk because they are slowly deposited and spread even at low air flow rates. The flock is constantly exposed to pathogenic bioaerosols when sick or infected birds are present in the poultry house [18].
\nFlock (no. of birds, rearing period) | \nHousing type (no. of buildings, ventilation system, type of bedding, season) | \nTotal microorganisms level (log10 cfu/m3) mean range (min- max) | \nReferences | \n|
---|---|---|---|---|
Broilers (230 400 birds, 8 weeks) | \n12 buildings, mechanical ventilation, sawdust or straw litter | \n4.8 (3.1–5.2) | \nBaykov and Stoyanov [20] | \n|
Broilers (5300 birds, six weeks) | \nOne building, mechanical ventilation, sawdust or wood shaving litter, spring | \n5.1 (4.2–5.3) | \nVučemilo et al. [4] | \n|
Broilers (350 birds, five weeks) | \nOne building, mechanical ventilation, straw litter, winter | \n5.1 (5.1–5.3) | \nWitkowska et al. [19] | \n|
Broilers (360 birds, six weeks) | \nOne building, mechanical ventilation, straw litter, summer and winter | \nSummer 5.9 (5.0–6.2) | \nWinter 6.0 (4.9–6.4) | \nWójcik et al. [21] | \n
Broilers (41 000 birds, six weeks) | \nTwo buildings, mechanical ventilation, straw litter, spring/summer | \n– (5.1–5.7) | \nLonc and Plewa [22] | \n|
Lying hens (19 500 birds) | \nThree buildings mechanical ventilation, straw litter, spring–autumn | \n7.8 (4.7–8.3) | \nBródka et al. [23] | \n|
Turkeys (2000 birds) | \nOne building, Louisiana-type, wood chips or straw litter | \n6.9 (4.5–7.6) | \nSaleh et al. [26] | \n|
Broilers (5300 birds, 6 weeks) | \nOne building, mechanical ventilation, sawdust or wood shaving litter, spring | \n4.5 (4.0–4.9) | \nVučemilo et al. [4] | \n|
Broilers (350 birds, 5 weeks) | \nOne building, mechanical ventilation, straw litter, winter | \n4.5 (4.2–4.7) | \nWitkowska et al. [19] | \n|
Broilers (360 birds, 6 weeks) | \nOne building, mechanical ventilation, straw litter, summer and winter | \nSummer 5.3 (4.6–5.8) | \nWinter 5.5 (4.7–5.9) | \nWójcik et al. [21] | \n
Broilers (41 000 birds, 6 weeks) | \nTwo buildings, mechanical ventilation, straw litter, spring/summer | \n– (4.6–5.0) | \nLonc and Plewa [22] | \n|
Lying hens (19 500 birds, 1 year) | \nThree buildings, mechanical ventilation, straw litter, spring–autumn | \n5.3 (3.8 Spr–5.8 Aut) | \nSowiak et al. [24] | \n|
Turkeys (2000 birds) | \nOne building, Louisiana-type, wood chips or straw litter | \n5.0 (2.7–5.5) | \nSaleh et al. [26] | \n
Bioaerosol concentrations in poultry houses.
Microbial survival is determined by temperature, humidity, and other environmental parameters. Relative humidity in poultry houses generally does not support bacterial proliferation (the 50–80% range is lethal for bacteria), and microbial contamination of air, litter, and surfaces in poultry farm buildings can be attributed mainly to high flock density and the continued presence of microbial sources. Poultry farms are significant pollutants of the external environment, and they could pose an epidemiological risk if biosecurity principles are not observed.
\nThe microbial concentrations reported inside and outside poultry farms (Tables 1 and 2) differ considerably in the literature [4, 19, 20–26]. Our previous work and other studies revealed aerial contamination in the range of 3.1–6.4 log10 cfu/m3 in broiler houses, 4.5–7.6 log10 cfu/m3 in turkey houses, and 4.7–8.3 log10 cfu/m3 in laying hen houses. Fungal concentrations in broiler, hen, and turkey houses were determined at 4.0–5.9, 3.8–5.8, and 2.7–5.5 log10 cfu/m3, respectively. Outdoor concentrations were reported at 0–5.6 log10 cfu/m3 for bacteria and 0–4.8 log10 cfu/m3 for fungi, depending on the distance. Microbial contamination levels are influenced by various factors, including bird species, stocking density, season, ventilation system, microclimate, and litter quality.
\n\n\nType of farm (no. of birds) | \nTotal microorganisms level (log10 cfu/m3) mean range (min–max) | \nDistance | \nReferences | \n
---|---|---|---|
Broilers (19 200) | \n– (2.3–5.6) | \n3 km–10 m | \nBaykov and Stoyanov [20] | \n
Broilers (350) | \n2.6 (0–2.9) | \n3 m | \nWitkowska et al. [19] | \n
Broilers (360) | \n3.9 (0–4.4) | \n3 m | \nWójcik et al. [21] | \n
Broilers (41 000) | \n– (1.6–3.9) | \n– | \nLonc and Plewa [22] | \n
Broilers (23 000) | \n– (3.7–4.1) | \n125–10 m | \nPlewa-Tutaj et al. [25] | \n
Broilers (350) | \n3.0 (0–3.2) | \n3 m | \nWitkowska et al. [19] | \n
Broilers (360) | \n3.8 (0–4.3) | \n3 m | \nWójcik et al. [21] | \n
Broilers (41 000) | \n– (1.3–4.1) | \n– | \nLonc and Plewa [22] | \n
Lying hens (19 500) | \n4.6 (4.2–4.8) | \n– | \nSowiak et al. [24] | \n
Bioaerosol concentrations around poultry houses.
Witkowska et al. [19] studied the total counts of aerobic mesophilic bacteria and fungi in fresh litter and in the air in a broiler house under changing temperature and humidity conditions, and changing physicochemical properties of litter throughout the rearing period. The total counts of aerobic mesophilic bacteria and fungi in fresh litter tended to increase during the rearing period, to reach 9 and 8 log10 cfu/g, respectively, in the last week. An insignificant increase in litter pH was also noted throughout the experiment, which—combined with increasing excreta amounts and fermentation processes in fresh litter—could promote microbial growth. The above factors enhanced ammonia production in litter (6 mg/kg at the beginning of the experiment vs. 12 mg/kg in the last week). Despite a gradual decrease in indoor temperature accompanied by an increase in humidity, microbial air contamination did not follow the same pattern as litter contamination. Bacterial and fungal counts varied between weeks of the rearing period, most likely due to changes in dust levels and ventilation efficiency. Bacterial counts were lowest in week 3 (4.6 log10 cfu/m3) and highest at the end of rearing (5.3 log10 cfu/m3). Fungal counts were lowest at the beginning of the experiment (4.2 log10 cfu/m3) and highest in weeks 2 and 5 (4.7 log10 cfu/m3). Lawniczek-Walczyk et al. [27] observed a significant increase in the concentrations of bacterial and fungal aerosols and endotoxins in chicken houses in successive stages of production. They also reported seasonal correlations in the size of bacterial populations. The concentrations of airborne bacteria were significantly higher in summer than in winter.
\nBacterial and fungal species and serotypes isolated from poultry farms are presented in Table 3. Numerous studies [4, 19–25] revealed that bioaerosols from poultry houses contain Gram-positive bacteria, including
Species | \nSerotypes | \nInside houses | \nOutside houses | \nReferences | \n
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+ | \n− | \nBaykov and Stoyanov 1999 [20]; Vučemilo et al. [4]; Lonc and Plewa 2011 [22]; Bródka et al. 2012 [23]; Lawniczek-Walczyk et al. 2013 [27]; Plewa-Tutaj et al. 2014 [25] | \n||
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+ | \n− | \nVučemilo et al. 2007 [4]; Witkowska et. al. 2010 [19]; Wójcik et al. 2010 [21]; Lonc, Plewa 2011 [22]; Sowiak et al. 2012 [24]; Lawniczek−Walczyk et al. 2013 [27] | \n||
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The most common microorganisms isolated from poultry farms.
*Microorganisms classified into group 2 according to level of risk of infection [27].
Some microbial species and serotypes, such as
Broiler houses are particularly infested by fungi of the genera
Bioaerosols also contain suspended endotoxins. These lipopolysaccharide complexes are associated with the cell membrane of Gram-negative bacteria which are released after the death of bacterial cells. High endoxin concentrations are also observed in poultry houses. Inhaled bioaerosol particles carrying endotoxins have pro-inflammatory and allergenic properties and may lead to chronic respiratory diseases in poultry [5]. The mean concentrations of endotoxins in aerosol fractions from poultry houses were determined in the range of 11.2–3406 ng/m3 and were significantly higher than in other livestock buildings [3, 5, 27]. Seedorf et al. [31] observed the highest endotoxin concentrations in laying hen houses. Lawniczek-Walczyk et al. [27] observed that endotoxin concentrations in poultry houses increased significantly in successive stages of production. The above authors concluded that high levels of airborne microorganisms and their bioproducts could pose a serious risk of respiratory diseases. For this reason, widely accepted guidelines for hygiene evaluation need to be established in poultry farms.
\nIn Poland, the proposed threshold limit values (TLV) are 5.0 log10 cfu/m3 for bacteria and 4.7 log10 cfu/m3 for fungi [27], but those limits apply to bioaerosol concentrations in employee facilities. Krzysztofik [32] recommended a limit of 5.0 log10 cfu/m3 for bacteria and a more restrictive threshold value for fungi at 3.3 log10 cfu/m3. The TLV for endotoxins recommended by the Polish Expert Committee for Biohazards in Indoor Environments is 200 ng/m3 [18, 27]. There are no guidelines for poultry houses.
\nThe composition of air in poultry houses significantly differs from atmospheric air. In addition to basic gaseous components (N2—nitrogen, O2—oxygen, Ar—argon, and CO2—carbon dioxide), the air inside poultry houses also contains compounds that are not normally found in atmospheric air. Birds, their excrements, feed, and process equipment are the main sources of volatile chemical compounds in poultry houses. Ammonia and carbon dioxide are most frequently encountered in farm buildings, and they contribute to the risk of disease if present in excessive concentrations. For this reason, ammonia and carbon dioxide are regarded as the most toxic gases in poultry houses.
\nCarbon dioxide (CO2) is a natural component of air, and its concentrations generally do not exceed 300 ppm (0.03%). Carbon dioxide is responsible for breathing control in the respiratory system. In densely stocked poultry houses, carbon dioxide concentrations are significantly higher than in atmospheric air, but they should not exceed 2000 ppm. At higher concentrations in poultry houses, CO2 weakens respiratory defense mechanisms and increases susceptibility to respiratory diseases. Carbon dioxide poses a serious hazard to health and life at concentrations higher than 10 000 ppm. Carbon dioxide levels in poultry houses are a robust indicator of ventilation efficiency. Its concentrations increase rapidly in poorly ventilated buildings.
\nIn poultry houses, ammonia (NH3) is released from excreta which contain nitrogen in the form of uric acid. Ammonia is produced in the process of microbial fermentation. Ammonia production increases in conditions that support microbial proliferation, including high temperature, high humidity, high pH, and presence of organic matter. In poultry houses, ammonia concentrations should not exceed 13 ppm for adult birds and 10 ppm for chicks. At higher concentrations, NH3 can compromise growth, whereas exposure to more than 30 ppm of ammonia can lead to respiratory dysfunctions such as intensified mucus secretion, shallow breathing, and bronchoconstriction. High levels of ammonia can impair immunity and increase susceptibility to respiratory infections and ocular abnormalities in poultry.
\nAmmonia and other nitrogen compounds (NOx) originating from poultry production contaminate soil and groundwater. Some gaseous compounds emitted by poultry farms, in particular CO2 and NOx, are greenhouse gases which contribute to global warming. Many volatile compounds are classified as odors, and hundreds of volatile organic compounds (VOCs) are identified in poultry houses. There are no guidelines concerning the odor detection threshold or VOCs’ impact on odor formation in poultry farms due to the scarcity of simple instruments for measuring air contamination in the production process. Research studies revealed the presence of aromatic and aliphatic hydrocarbons, aldehydes, ketones, alcohols, free fatty acids, mercaptans, esters, phenols, cyclic amines, nitriles, and sulfur compounds in bird farms [7–8, 13, 15, 18, 33].
\nWitkowska [33] conducted qualitative and quantitative identification of gaseous contaminants on a commercial turkey farm by Fourier transform infrared spectroscopy (FTIR). It was found that ammonia and carbon dioxide were the predominant gases in turkey houses, and both were present throughout the entire growth cycle, which is consistent with the findings of other authors. The mean concentrations of carbon dioxide and ammonia were 220–2058 ppm (min = 176 ppm, max = 2460 ppm) and 4–31 ppm (min = 4 ppm, max = 58 ppm), respectively. The highest carbon dioxide concentrations (approx. 2000 ppm) were reported in farm buildings in weeks 4 and 7, and a significant decrease in 600 ppm was observed in week 10. A lessening tendency was noted until the end of the production cycle; in week 19, mean carbon dioxide concentrations in turkey houses were approximately 90% lower than at the beginning of the experiment. Average ammonia concentrations increased from 7 ppm at the beginning of the study to over 30 ppm in week 7. A significant decrease in ammonia levels was observed in subsequent weeks. The decreasing trend was sustained until the end of the rearing period, and the mean concentrations of NH3 were 90% lower in the second half of the cycle. The decrease resulted from higher ventilation and air exchange rates in turkey houses (at the last stage of the study, and the rate of ventilation was 10-fold higher than at the initial stage). The increase in CO2 and NH3 levels in week 7 was related to diet modification and increased excreta moisture. Thiols, nitriles, amines, aldehydes, hydrocarbons, and other volatile organic and inorganic compounds were also identified in the air inside the buildings, but they were emitted periodically and their mean concentrations were significantly lower in comparison with CO2 and NH3. In contrast to the majority of other contaminants, nitrogen compounds (nitriles, amines, aldehydes) and some hydrocarbons (chloroethane, 1.3-butadiene) were present at higher concentrations in the second half of the production cycle. During the experiment, trace amounts of alcohols, organic acids, ketones, phenols, nitrogen oxides, and sulfur oxides were also detected in the air inside farm buildings. Mixtures of those compounds act as odorants even at low concentrations.
\nAccording to EU directives and Polish regulations, ammonia concentrations in broiler and laying hen houses should not exceed 20 ppm, and carbon dioxide concentrations should be limited to 3000 ppm. Gas concentrations have to be kept within safe limits in turkey, duck, and geese houses [33]. More restrictive limits have been recommended by some authors [18], and further research is needed to determine tolerable limits for different poultry species and rearing systems.
\nThe search for effective, inexpensive, and environmentally friendly methods of lowering contamination levels in poultry production has continued for many years. Ventilation systems play a key role in maintaining the optimal microclimate in poultry houses, and devices that generate negative ions remove dust and moisturize air can also be installed in farms to limit air pollution. Unfortunately, such solutions are relatively expensive, and they are not widely used in poultry production.
\nWitkowska and Sowińska [34] study aimed to assess the antibacterial effects of natural essential oils (peppermint oil—PO and thyme oil—TO) in broiler houses. The results of the study demonstrated that essential oil mist may improve hygiene standards in broiler farms. The mean total counts of aerobic mesophilic bacteria in the control room were significantly higher than in rooms treated with essential oils—5.8 log10 cfu/m3 vs. 5.6 log10 cfu/m3 (PO) and 5.5 log10 cfu/m3 (TO). A similar trend was observed with regard to wall contamination—total mesophilic counts ranged from around 2.4 log10/100 cm3 in rooms fogged with essential oils to 3.3 log10/100 cm3 in the control room, and the statistic differences between control and experimental groups were determined. Total bacterial counts on drinker surfaces in rooms fogged with essential oils were lower than in the control room (PO–4.6 log10, TO–4.3 log10). Average drinker contamination was significantly (by 0.5 log10) higher in the control room than in the room fogged with thyme oil. The average total count of litter bacteria ranged from 8.9 log10 cfu/g in the control group to 8.2 log10 cfu/g in the thyme oil group, and the noted difference was statistically significant. Litter contamination was also lower in the room fogged with peppermint oil (8.5 log10 cfu/g), compared with the control room, but the difference was not significant. An analysis of extreme values of bacterial counts in the air on the walls and drinkers and in litter revealed that bacterial contamination levels were effectively reduced by essential oils. The average counts of bacteria of the family
According to Tymczyna et al. [3, 7, 35, 36], biofilters offer a relatively cheap and effective solution for poultry farms. Biofilters are containers with many partitions that house a high-pressure fan, an air moisturizing chamber and a biofiltration chamber. The biofiltration chamber is a bed of various media, such as peat, compost, horse manure, and wheat straw. Toxic gases are partially or completely biodegraded by bacteria that occur naturally in bed media or are artificially introduced to substrates. Bacterial proliferation is influenced by the parameters of bed media, including fertility, moisture content, temperature, and pH. The cited authors demonstrated that ammonia and other toxic compounds (nitrates, nitrites, sulfates, chlorides, phosphates) present in ventilation systems can be effectively eliminated with the use of open biofilters in laying hen farms. Biological beds composed of peat, treated compost, horse manure, and wheat straw reduced ammonia concentrations by 36–89% (68.6% on average) and eliminated other harmful compounds in 66–100%.
\nChmielowiec-Korzeniowska et al. [37] evaluated the effectiveness of a prototype container biofilter in eliminating organic air pollutants in a chick hatchery. The biofilter bed was composed of sallow peat (30%), fibrous peat (30%), treated compost (10%), fermented horse manure (10%), and wheat straw (20%). The tested device decreased the levels of all pollutants by 66% on average, and it was most effective in removing hexanal (95%) and toluene (76%).
\nThe same team of researchers [3] evaluated the effectiveness of organic and organic-mineral biofilters in eliminating Gram-negative bacteria, dust, and bacterial endotoxins from exhaust air leaving a chick hatchery. All evaluated filters were effective in removing bacterial aerosols and somewhat less effective in reducing dust pollution. Endotoxins were not effectively eliminated. A biofilter with an organic-mineral bed containing 20% halloysite, 40% compost, and 40% peat was most effective in lowering contamination levels.
\nNumerous research studies demonstrated that aluminum silicates can be effectively used as bed media in air filtering devices. An important advantage of aluminum silicates is that they are relatively cheaper and less toxic for animals and the environment than commercially available chemical sorbents.
\nOpaliński et al. [38] evaluated the ability of selected aluminum silicates to absorb ammonia. The tested substrates were raw halloysite, roasted halloysite, activated halloysite, raw bentonite clay, and expanded vermiculite (EV). The experiment was conducted under strictly controlled laboratory conditions. The analyzed substrates’ sorptive capacity was determined based on differences in ammonia concentrations in a stream of air before and after it passed a sorptive bed with a known volume. All evaluated sorbents lowered ammonia concentrations in air. The most effective sorbent was activated halloysite, followed by raw halloysite, roasted halloysite, and raw bentonite, whereas vermiculite was least effective in capturing ammonia.
\nOpaliński et al. [39] also analyzed the ability of selected aluminum silicates to eliminate noxious odors in conditions similar to those found in animal facilities. Chicken droppings were placed in fertilizer chambers, and the odor capturing abilities of raw halloysite, roasted halloysite activated halloysite, raw bentonite, roasted bentonite, and expanded vermiculite were evaluated after 24 h. Ammonia was most effectively removed (81%) by activated halloysite, whereas roasted halloysite was the least effective sorbent. In addition to ammonia, the analyzed air samples also contained 24 odorous volatile compounds, including five toxic substances. All of the tested aluminum silicates effectively decreased the concentrations of the identified compounds, and their average sorptive capacity ranged from 56% for raw halloysite to 84% for roasted bentonite. Roasted bentonite reduced the levels of seven odorous compounds by more than 90% and eliminated IH-indole, dimethyl trisulfide, and pyridine in even 100%.
\nOrganic and mineral compounds are added to litter to improve its quality [40, 41]. The objective of Korczyński et al. [42] study was to determine the effectiveness of expanded vermiculite (EV) and raw halloysite (HS) in reducing the emissions of ammonia and volatile organic compounds (VOCs) from litter in turkey houses. Mean ammonia concentrations were lower in the sectors where the analyzed sorbents were used. The average differences in NH3 levels between the control sector and the sectors where vermiculite and halloysite were added to litter reached 15.1 and 14.6%, respectively. The highest efficacy of both sorbents was noted in the first week of the study (statistically significant differences). The application of halloysite and vermiculite decreased ammonia concentrations by 38 and 25%, respectively, compared with the control sector. Similar trends were observed in the subsequent 2 weeks, but differences in ammonia concentrations between the control sector and experimental sectors were much lower (3.4–11.4%) and statistically non-significant. A total of 15, 14, and 11 volatile organic compounds were identified in the air in the control, HS and EV sectors, respectively. Pentadecane, 1-phenylethanone, dimethyl tetrasulfide, and 4-hydroxytoluene were detected in the control sector, but they were not found in experimental sectors. Methylbenzene and 4-methyl-2-heptanone were identified in the air in the sectors where the sorbents were used, and 2-undecanone was detected in the HS sector—those compounds were not found in the control sector. Chlorobenzene was the predominant VOC in the air in all sectors. Sorbents added to litter were most effective in reducing the emissions of compounds with more complex molecular structure. VOC levels decreased by 73.4 and 83.1% following the use of halloysite and vermiculite, respectively.
\nManafi et al. [43, 44] observed that high grade sodium bentonite in diet reduced the toxicity of aflatoxin and marginally ameliorated the effect of ochratoxin A and aflatoxin B1 in broilers.
\nIn a search for effective methods to reduce contamination levels in poultry production, various litter additives were analyzed [28, 45–47], including a microbiological preparation (Biosan-GS®) and disinfecting preparations (Lubisan®, Stalosan F®, Profistreu®). All additives contributed to a decrease in litter pH and moisture content [28, 46] thus reducing ammonia concentrations in the air and litter [45, 46], and microbial air contamination levels in poultry houses [28]. Birds kept on “optimized” litter were characterized by higher body weight gains [46] and lower culling and mortality rates, at similar feed intake levels. An analysis of internal organs (liver, spleen, kidneys, lungs, cornea) and selected blood parameters showed that the above litter additives were safe and posed no threat to bird health [45, 47].
\nSaponin extracts from the South American plants of Mojave yucca (
Litter can also be disinfected with calcium compounds before animals are introduced to a farm building [50]. Many authors demonstrated that the addition of calcium oxide to poultry litter significantly decreases bacterial counts, in particular
In the literature, there are no recommendations regarding the optimal doses of calcium additives in litter, but calcium compounds are popularly used in poultry farms on account of their low cost. Despite the above, calcium additives should be applied with caution because exposure to excessive calcium concentrations can irritate or burn mucosal membranes and the skin. Calcium oxide reacts with water to increase temperature, which can harm birds reared on litter. Mituniewicz [53] attempted to determine the optimal doses of calcium compounds (CaO and CaOMgO) which can be safely added to litter before birds are introduced to poultry houses. The cited author analyzed the physicochemical and microbiological parameters of litter, microclimate conditions, selected blood biochemical parameters and bird performance to conclude that a single application of 250 g CaO or CaOMgO per square meter of litter delivered the best results. Calcium compounds had a positive effect on the physicochemical parameters of litter and microbial counts. The tested additives, in particular calcium oxide, led to a significant increase in litter temperature within the safe limits. Calcium oxide also lowered the relative moisture content of litter, in particular in the last weeks of the rearing period. The combination of calcium oxide and magnesium oxide induced a greater improvement in the analyzed parameters. Calcium compounds were effective disinfectants which reduced the counts of incubated yeasts already in the third week of the experiment. Ammonia concentrations were significantly lowered in a poultry house where calcium compounds were added to litter. The results of blood serum biochemistry analyses revealed that calcium compounds did not exert a negative effect on the birds’ health. Chickens reared on litter with calcium additives were characterized by higher weight gains and improved performance.
\nCalcium peroxide (CaO2) is an inorganic compound and a source of oxygen. This compound is sparingly soluble in water, and hydrogen peroxide, a source of free radicals (chemical oxidation) and oxygen, is gradually released during the slow decomposition of CaO2. The above creates a supportive environment for aerobic microorganisms [54]. Piotrowska [55] attempted to determine the optimal dose at which calcium oxide should be combined with litter to improve hygiene conditions in broiler houses and broiler performance. During a four-week laboratory experiment (without birds) involving analyses of the qualitative parameters of chicken litter and microclimate conditions in broiler houses, the cited author determined the optimal dose of CaO2 at 2 g m−2 litter. The above dose was then tested under production conditions in a poultry farm. The surface temperature of the experimental litter was reduced by 1°C, and its moisture content decreased in comparison with the control litter (57.11% vs. 70.33%), which lowered the counts of aerobic mesophilic bacteria. Ammonia concentrations in the experimental poultry house did not exceed 10 ppm throughout the experiment and were lower than in the control poultry house. Aerobic mesophilic counts in air increased in both poultry houses in successive stages of production, but were lower in the house containing CaO2 than in the control facility in weeks 3, 4, and 6. Calcium peroxide also reduced average yeast and mold counts in the experimental poultry house relative to control. The addition of CaO2 at 2 g/m2 litter did not compromise the birds’ health and had a positive impact on performance.
\nIn addition to technical devices and sanitary solutions, other measures are also introduced to minimize pollutant emissions from chicken houses. One of such measures relies on phytoremediation, namely the use of selected plants to accumulate and degrade polluting substances.
\nSobczak et al. [56] and Domagalski et al. [57] analyzed the ability of selected greenhouse plants to reduce pollution levels in exhaust air from poultry houses. Sobczak et al. [56] demonstrated a decrease in the concentrations of carbon dioxide, ammonia, and dust when exhaust air was passed through an experimental greenhouse containing Indian shot (
Domagalski et al. [57] investigated the deodorizing properties of Indian shot (
The results of the above studies demonstrate that poultry farms are significant reservoirs and emitters of microbiological and gaseous contaminants into the environment and that the type and concentrations of bioaerosols and gases produced in poultry farms are determined by various factors, including bird species, stocking density, season, time of day, stage of the production cycle, temperature, moisture content and the physicochemical parameters of litter, sampling site, ventilation efficiency, technical and process solutions, and farm management methods.
\nA microbiological analysis of bird facilities revealed that threshold concentrations of airborne bacteria and fungi recommended in the literature [27, 32] are often exceeded in practice. In cited studies, the lowest bacterial concentrations in a broiler house were determined at 3.1 log10 cfu/m3; however, in the most cases, minimum value approximated the safe threshold for poultry houses (5.0 log10 cfu/m3) already at the beginning of the production cycle. The highest concentrations of airborne bacteria were determined in hen houses at 8.3 log10 cfu/m3. The proposed safe threshold for fungal concentrations of 3.3 log10 cfu/m3 for poultry was also most often exceeded at the beginning of the production cycle, and fungal concentrations ranged from 2.7 (turkeys) to 5.9 log10 cfu/m3 (broilers).
\nPoultry litter was an even more abundant source of microorganisms. In our study, the highest bacterial concentrations in hen house litter reached 9–10 log10 cfu/g, and the highest fungal concentrations reached 8 log10 cfu/g, but the above results cannot be compared with reference values due to an absence of normative threshold levels in the literature.
\nAn IR spectroscopy analysis of chemical air pollution in a commercial turkey farm supported the determination of the type and concentrations of inorganic compounds (ammonia, carbon dioxide, nitric oxide, and phosphine) and VOC (sulfur and nitrogen compounds: nitriles, amines, and aldehydes; hydrocarbons: methane, dichloromethane, chloromethane, bromomethane, 1,3-butadiene). In most studies, volatile compounds in farm buildings are identified by gas chromatography. This method is characterized by high precision, but it is rarely used in practice because analyses have to be performed under laboratory conditions. A comparison of our findings with the results of chromatographic analyses indicates that FTIR is a practical method for evaluating gas contamination in field conditions because analyses can be conducted
Selected volatile compounds, which were also determined in our study of hen houses (e.g., ethanethiol, methanethiol, acrylonitrile), can be harmful at very low concentrations at the limit of detection of measuring devices equipped with electrochemical sensors for selective detection [58]. Due to analytical constraints, only general threshold limit values (TLV) have been determined for carbon dioxide, ammonia, and hydrogen sulfide at 1800–3000, 10–30, and 5–10 ppm, respectively, in housing facilities for juvenile and adult animals [18]. The relevant legal regulations set TLVs for NH3, CO2 and H2S for calves and pigs, and NH3 and CO2 for chickens at 3000, 20, and 5 ppm, respectively. The regulations addressing other animal species, including turkeys, merely state that VOC concentrations should be kept at a safe level [59].
\nThe growing number of protests staged by local communities against odor-producing animal farms, in particular animal production facilities situated inside the protective zone surrounding residential districts, has attracted researchers’ attention to the odor-producing qualities of approximately 300 identified volatile compounds. The detection limit of many gases, including mercaptans, amines, sulfur compounds, and phenol derivatives, can be very low. Measures that effectively limit the production of odorous gas mixtures at the source require the identification of the highest number of components, even at very low concentrations. Analyses of trace amounts of toxic compounds are often burdened with error; therefore, the higher the number of replications and standardized measuring techniques, the greater the effectiveness of the proposed protective measures.
\nThe EU climate and energy package places the Member States under the obligation to reduce their greenhouse gas emissions. Animal farms contribute to an increase in atmospheric concentrations of CO2, CH4, and NOx. Farm emissions are determined based on standard formulas and computer simulations that do not account for hygiene standards. This approach could lead to unjust prosecution of farmers who take active steps to reduce pollution at the source. For this reason, gas concentrations and actual emissions from farm buildings characterized by different hygiene levels should be determined to effectively reduce atmospheric concentrations of pollutants.
\nIn our study, the attempts to limit the concentrations of harmful gases and microbiological pollutants in farm buildings generated positive results. Total bacterial counts, including
Reliable criteria for evaluating poultry exposure to biological and chemical pollutants and the relevant reference values should be developed to maintain high poultry welfare standards in farms. For such criteria to be acceptable, they have to be carefully balanced to ensure that they deliver the highest level of poultry welfare and are achievable in practice with the involvement of the available methods.
\nInflammation is the response of an organism’s immune system to damage caused to its cells and vascularized tissues by bacterial pathogens and by any other biological, chemical, physical, or mechanical aggressor. Such an inflammatory response must be self-limiting in time and intensity since, if this is not the case and if there is no perfect coordination between the innate and adaptive immune systems, a severe systemic inflammatory syndrome with positive feedback systems will occur, eventually causing a cytokine storm that can lead to multi-organ failure [1, 2]. In the establishment, maintenance and termination of this cytokine storm, at the molecular level, in cases of sepsis and severe viral infections such as that associated with COVID-19, the toll-like receptors (TLRs), NOD-like receptors (NLRs), and RIG-like helicase receptors (RLRs), cytokines, chemokines and growth factors, and the purinergic system will be fundamental in the establishment, maintenance, and termination of this cytokine storm.
In the late 1990s, the ability of infectious agents (bacteria, viruses, zoonoses, or parasitic and/or fungal infections) to trigger cytokine storm syndrome (CSS) was first described with the recognition of a case series of hemophagocytic lymphohistiocytosis (HLH) of viral origin [3]. Such a cytokine storm is basically characterized by an exaggerated production of proinflammatory and profibrotic soluble mediators (especially IL-1β, IL-6, and TNF-α), together with an aberrant immunopathological reaction, involving an uncoordination between the innate and adaptive immunity system, there being generally an overactivation of the innate immune system, the main cellular actors being macrophages, dendritic cells, monocytes, neutrophils, and T lymphocytes [4, 5, 6, 7]. As a consequence of this cytokine storm, a situation of multi-organ hyperinflammation will be provoked, which usually affects mainly the lung and pancreas, among other organs, and which usually results in acute respiratory distress syndrome (ARDS) and/or acute lung injury (ALI), which can lead to multi-organ failure.
Although the association of increased levels of proinflammatory and profibrotic cytokines and chemokines with increased levels of morbidity and mortality following an infectious process is well known, we still lack a suitable drug to treat the cytokine storm [8].
The innate immune system is able to recognize molecular structures specific to viruses, bacteria, fungi, and other pathogens; these structures are known as pathogen-associated molecular patterns (PAMPSs) [9, 10, 11]. PAMPSs are small-molecule sequences that are repeated in groups of pathogens recognized by the so-called pattern recognition receptors (PRRs). These include the toll-like receptors (TLRs) family of membrane receptors, NOD-like receptors (NLRs) and RIG-like helicase receptors (RLRs), among which the NLRP receptors stand out, oligomeric structures called inflammasomes, responsible for generating the mechanism of pyropoptosis by hyperproduction of hyperinflammatory cytokines, used as a trigger for the hyperproduction of IL-1β and IL-18 [12]. These molecular patterns are essential for the recognition of microorganisms by innate immunity cells, which respond differently depending on the microorganism identified [9, 10, 11].
Analyzing the detection capabilities of all these receptors, both DAMPS and PAMPS, we conclude that the main receptors involved in innate immunity against infections are TLR2, TLR3, TLR4, TLR7, TLR9, NOD1, NOD2, RIGI, and NLRP3. In Table 1, we summarize the PAMPS and DAMPS that are able to activate them [13, 14, 15, 16, 17].
TLR 2 receptors are activated mainly by bacteria and fungi, and although their activation has been described in SARS COV-2 infection, it is possible that this is due not directly to the SARS COV-2 virus but to the existence of a concomitant bacterial infection.
TLR 3 receptors are activated mainly by viruses, although SARS COV-2 is not activated to the same extent as other viruses, such as influenza virus, respiratory syncytial virus (RSV), or herpes virus. TLR 4 receptors are activated mainly by bacteria, but activation is also seen in viruses, although it is unclear whether this is due to a posteriori DAMPS. TLR 7 receptors are mainly activated by viruses. TLR 9 receptors are activated by both RNA and DNA so that viruses, bacteria, fungi, or any pathogen can activate them. Cytoplasmic receptors, since they detect most pathogen fragments, including DNA and RNA, can be activated by both viruses and bacteria, although NOD1 is activated more strongly by bacteria. It appears that RIG I is only activated by viral and not bacterial RNA [13, 14, 15, 16, 17]. (++ maximal activation, + intermediate or mild activation, no activation).
Considering the different receptors involved in cytokine storms associated with infectious processes, we can deduce that the activation of the transcription factors AP-1 (activator protein 1) and NF-kβ (nuclear factor kappa light chain enhancer of activated B cells), both common denominators in almost all pattern recognition pathways, will provoke the dreaded cytokine storm, resulting in a state of generalized hyperinflammation. The most affected organs are lung or pancreas, with the consequent associated fibrotic reaction, producing irreparable anatomopathological damage with loss of function in the most affected organs.
A fact especially associated with the cytokine storm associated with SARS COV-2 is that a decrease in the production of type I interferons is observed, which causes dysregulation in the coordination of the innate and adaptive immunity systems, facilitating the appearance of the dreaded severe pneumonia that on many occasions determines the patient’s admission to the ICU [18].
It is very difficult to explain the existence of a cytokine storm by the activation of a single receptor. If this were so, treatment of the cytokine storm by a single monoclonal antibody, for example, a monoclonal antibody against IL-1β or against IL-6, would always be effective, and this we know almost never occurs. Moreover, even if in the first instance only one of the receptors is activated, the simple initiation of its metabolic cascade will provoke the appearance of DAMPS that will stimulate other receptors. If we add to this the fact that in the majority of cytokine storms associated with infections we do not see a single causative pathogen, but rather a group of them, we will understand that there is almost always a joint activation of several of these receptors, producing between them phenomena of agonism and synergy, as well as antagonism [19]. Any of them can have agonistic relationships with others, if they are stimulated at the same time. However, if these same receptors are activated with a significant time lag between them of hours or even days, the most likely mutual relationship they will establish will be one of antagonism [19]. Thus, the types of cytokines and chemokines that will be released as a result of the activation of the different receptors will depend on the sets of receptors that are primarily activated by PAMPS and, once initiated, such release of pro-inflammatory and profibrotic mediators will be prolonged and augmented over time by positive feedback from the same receptors or even the addition of others, by the stimuli elicited by DAMPS, which could lead to reactive phenomena even autoimmunity.
In the cytokine storm, we must also consider the intervention of the purinergic system [20, 21, 22]. Extracellular adenosine triphosphate (eATP) or its enzymatic degradation products, such as ADP, AMP, and adenosine, can stimulate a number of membrane receptors [23]. More specifically, the P2X7 receptor is widely distributed on innate cells of the adaptive immune system, a system that constitutes the first line of defense against invading pathogens. These cells are lymphocytes, granulocytes, macrophages (including microglia), and dendritic cells in peripheral tissues [24, 25, 26]. Activation of the P2X7 receptor has been associated with the establishment and prolongation of inflammation and cytokine storm in septic infections, including SARS-COV-2 infection [27, 28, 29]. The stimulation of the P2X7 receptor by adenosine triphosphate (ATP) causes the activation of the NLRP3 inflammasome, and consequently of caspase 1, stimulating this the exaggerated secretion of IL-1β and IL-18 [30]. For all these reasons, the ideal immunomodulatory treatment of the cytokine storm associated with moderate and severe infections should include the P2X7 receptor (generating antagonism) or P1-like receptors (generating agonism) as a therapeutic target [29].
The treatments tested to date to control cytokine storms associated with infectious processes have been based on the use of monoclonal antibodies used alone or in combination. The hypothesis put forward by our group proposes as a treatment a biological therapy based on the use of allogeneic-conditioned medium derived from M2-type macrophages and enriched with mesenchymal stem cells (MSCs). Mesenchymal stem cells, placed in co-culture with macrophages, not only respond to macrophages and adjust their secretome accordingly but also induce macrophages to respond to them, creating a feedback loop that contributes to immune regulation [31]. In the complex composition of this conditioned medium are present all growth factors, cytokines, and chemokines that are naturally produced by M2-type macrophages and MSCs, associated with innate immunity respecting natural pleiotropic relationships. The immunomodulatory cytokine profile of this medium confers a potent anti-inflammatory and anti-fibrotic action, and even, thanks to the results obtained with the secretome of MSCs on macrophages stimulated with TLR7/8 ligand, possibly antiviral [32]. Different studies have shown that the secretome of these two cell types is modified and modulated when co-cultures of these cells are performed [33]. The immunomodulation mechanisms mediated by MSCs are due, among other factors, to the release of PGE-2 (prostaglandin E-2) and TSG-6 (TNF-stimulated gene 6 protein) [34]. M2 (anti-inflammatory) macrophages secrete high levels of IL-10 and low levels of IL-12p70 and IL-17, in a process that is directly mediated by other factors produced by MSCs (such as IL-6 and HGF) [35, 36]. It has been experimentally demonstrated that factors secreted by pro- or anti-inflammatory macrophages activate the immunomodulatory potential of MSCs. In this regard, IL-10 release by anti-inflammatory macrophages activates MSCs to release PGE-2 [37], which in turn modulates macrophages producing a cascade of additive molecular interactions in favor of immunotolerant and anti-inflammatory mechanisms. Basically, the polarization of macrophages to M2 type with immunoregulatory phenotype will be maintained [38], which, in turn, will express more IL-6, IL-10, and IGF-1 and inhibit their production of IL-12 and TNF-α. MSCs are also capable, through secretion of these same factors, of inhibiting the migration, maturation, and differentiation of dendritic cells [39, 40, 41]. Similarly, monocyte-derived M2 macrophages co-cultured with MSCs have been shown to increase mitochondrial function and ATP turnover, both in vitro and in vivo, resulting in an increase in the ADP/ATP ratio [42]. In addition, MSCs maintain ATPase and CD73 enzymatic activities on their surface, converting ATP to ADP and AMP to adenosine, respectively [43]. Adenosine, the last molecule in these reactions, has immunoregulatory functions through the activation of the P1 receptor [44]. Importantly, activation of monocyte P1 receptors, such as A2A and A2B, inhibits TNF-α production [44].
Several previous experiences demonstrate how secretomes from both cell types possess immunomodulatory properties. For example, direct injection of the supernatant of cultured mesenchymal stem cells (MSCs) containing a variety of growth factors, prostaglandins, and cytokines can be applied to the treatment of kidney injury [45]. Both co-culture with M2 macrophages and treatment with M2 macrophage supernatant have also been shown to increase endothelial cell viability in a bacterial lipopolysaccharide-generated lung sepsis model [46]. In addition, the efficacy and safety of multiple sclerosis treatment by intravenous infusion of conditioned medium from mesenchymal stem cell culture have also been demonstrated [47].
The advantage of using the complete conditioned medium versus one of its purified components lies in the synergistic mechanism between its different components [48], the result of subjecting the cell populations to a culture that, in vitro, attempts to emulate the anti-inflammatory, anti-fibrotic, and regenerative immunomodulatory microenvironment that occurs in vivo in diseased tissue.
Production and characterization of allogeneic-conditioned medium derived from M2-type macrophages and enriched with MSCs.
First, to obtain MSCs, a lipoaspirate sample was obtained from which the stromal vascular fraction (SVF) was extracted, following the protocol described by Lapuente et al. [49]. SVF was harvested by centrifugation under the same conditions as earlier-mentioned, seeded at a density of approximately 30,000 cells per cm2 in 100-mm diameter culture plates (this and all culture plastic used was from Corning, Corning, NY, USA) and cultured at 37°C and 5% CO2 in culture medium (DMEM + 10% fetal bovine serum (FBS) + 1% P/S). At 24 h, the culture was washed with phosphate-buffered saline (PBS) to remove nonadherent cells and the adherent cell population, called processed lipoaspirate (PLA), was cultured to subconfluence under the same conditions as earlier-mentioned, changing the culture medium three times a week and performing the necessary passages with trypsin 0.05% (Gibco), until a homogeneous population of mesenchymal-type stromal cells, also called mesenchymal stem cells (MSCs), was obtained. After culture, the cells were frozen at a freezing ramp of −0.5°C/min to −80°C in freezing medium composed of 10% dimethyl sulfoxide (DMSO, Sigma) in FBS or culture medium, then immersed in liquid N2 and maintained until use.
Secondly, monocytes were isolated from one altruistic blood donation bag of 450 ml with 12% citrate–phosphate-dextrose (Grifols, Barcelona, Spain) from the blood bank of the Fuenlabrada Universitary Hospital. To isolate the leukocytes, each bag was divided into 50-ml tubes (Corning) and centrifuged at 1500 x g for 10 min at room temperature (RT). The intermediate band, leukocyte buffy coat, was collected and deposited on a clean tube. Immediately, 24 ml of this concentrate was carefully placed on 18 ml of Ficoll Histopaque 1077 (Sigma) and centrifuged at 400 × g for 30 min at room temperature (RT) and without brake. The mononuclear cell band was collected, and after adding PBS in a 1:1 ratio, centrifuged at 300 x g for 5 min at RT. The supernatant was discarded and the resulting pellet was resuspended in a fivefold volume of erythrocyte lysis buffer and incubated at RT for 10 min. Subsequently, a 10-fold volume of PBS was added and centrifuged under the same conditions as earlier-mentioned to obtain the cell pellet after discarding the supernatant. This last wash was repeated once more and, after this, the resulting peripheral blood mononuclear cell pellet (PBMC) was resuspended in CTS-AIM-V medium (Gibco) supplemented with 0.1% Dipeptiven 200 mg/ml (Frenesius Kabi Austria GmbH, Graz, Austria) and cultured in T-175 culture flasks (Corning, approximately 200 million PBMCs per flask) at 37°C and 5% CO2 atmosphere for 90 min. The next step was to wash the flasks twice with plenty of PBS to remove unattached cells. The cells were immediately lifted with a cell scraper (Corning) to obtain a cell suspension in PBS, which was centrifuged for 5 min at 300 × g at room temperature. The resulting pellet was resuspended in AIMV + Dipeptiven + 10 ng/ml M-CSF (R&D Systems, McKinley, Minneapolis, USA) for co-culture. All cell counts and viabilities (trypan blue exclusion method) were performed with an automatic counter TC20 (BioRad, Hercules, CA, USA), strictly following the manufacturer’s instructions, marking a lower threshold of 8 μm to disregard possible erythrocytes, platelets, and other contaminating cellular debris.
Third, co-culture was established to produce the conditioned medium. For this purpose, the obtained monocytes were seeded at a density of 500,000 cells/cm2 in inserts (Transwels, with a polyethersulfone membrane of 1 μm pore size, from Corning) of 6-well plates and cultured under standard conditions for 4 days with the described medium. When the culture medium was removed, the inserts were washed twice with PBS and added to the plates on which the MSCs had been seeded and cultured in pass 4 (24 h earlier, in Corning 6-well plates at a density of 10,000 cells/cm2 under standard conditions), previously washed twice with copious PBS and using CTS-AIMV-V medium supplemented with 0.1% Dipeptiven to maintain the co-culture under standard conditions of temperature and CO2 concentration. The co-culture was maintained for 4 weeks by collecting the conditioned medium and adding fresh medium twice a week. To preserve the different collections, they were immediately frozen by immersion in carbonic snow and kept at −80°C until analysis. To perform the analysis, the cultures were thawed at 4°C and analyzed immediately after filtering through a 0.45-μm pore nitrocellulose filter (Merck KGaA, Darmstadt, Germany). To obtain secretome controls for MSCs and different monocytes, the different cell populations were cultured separately under the conditions described for co-culture.
Subsequently, phenotypic characterization of MSCs and monocytes was performed and samples were taken from both populations at time 0, 7 days, 14 days, and 28 days. MSCs were lifted with trypsin and monocytes with scraper as described earlier and, after centrifugation at 300 × g 5 min at 4°C, resuspended each cell type in PBS, permeabilized the monocytes with Perm/Wash buffer (BD Biosciences, Franklin Lakes, NJ, USA), and incubated the cells for 15 min at RT and in the dark with the following fluorochrome-conjugated antibodies (and their related isotypes as negative controls) at 1:50 concentration: CD73-APC, CD90-APC, CD45-FITC, HLA-DR-FITC, CD31-PE, CD68-FITC, and CD163-PE (all from BD Biosciences). The fluorescence minus one technique was used to adjust the voltages and compensate for fluorescence, and propidium iodide (Sigma) was used to determine dead cells according to the manufacturer’s instructions. A Guava EasyCyte flow cytometer (Merck) was used to acquire the samples and InCyte software (Merck) was used to analyze the results.
To quantify the secretome of both cell types and the co-culture, 30 growth factors, cytokines, and chemokines were quantified using either ELISA or Multiplex assay (ProcartaPlex 23 PLEX, Invitrogen, Grand Island, NY, USA), strictly following the manufacturer’s instructions. A Luminex Labscan 100 plate reader (Luminex Corporation, Austin, TX, USA) was used for the determinations. The molecules quantified by Multiplex were the following: MIP1-α, IL-2, IL-6, TIMP-1, IL-8, IL-10, IL-12 P70, IL-1 RA, RANTES, GM-CSF, leptin, HGF, MMP-3, MCP1, BNGF, EGF, adiponectin, TNF-α, MMP-1, TRAIL, FGF-2, PDGF-BB, and VEGF-A. For quantification of IGF-1, BMP-6, IL-1β, IL-4, TGF-β1, TGF-β3, and VEGF-C, a double sandwich ELISA technique was used following the manufacturer’s instructions (DuoSet ELISA kit, R&D) and quantification was determined using an iMark plate reader (BioRad).
THP-1 cell line culture and subsequent differentiation to macrophages were performed to generate in vitro models of biosafety and efficacy. THP-1 monocytic cells (CellLineService, cat. No.: 300356) were cultured and expanded using RPMI 1640 (Lonza, Basile, Switzerland) supplemented with 10% fetal bovine serum (FBS) (Corning, NY, USA), 1% penicillin/streptomycin (P/S) (Lonza), 1 mM sodium pyruvate (Lonza), and 1% MEM nonessential amino acids (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) starting now THP-1 medium. Cells were maintained at a density ranging from 2.5 × 105 to 106 cells/ml to ensure adequate growth and a stable phenotype. Forty-eight hours prior to lipopolysaccharide (LPS) stimuli, cells were differentiated into resting macrophages using phorbol 12-myristate 13-acetate (PMA) (Sigma–Aldrich, Saint Louis, MO, USA) at 5 ng/ml in THP-1 medium as described in the protocol used by Park et al. [50]. After this differentiation process, the cells were used for our experiments. All cell cultures were maintained at 37°C in an atmosphere of 5% CO2 and 98% relative humidity. The in vitro inflammation model was generated by differentiating 400,000 THP-1/ml cells in exponential growth phase into resting macrophages in 12-well plates (Nunc, ThermoFisher) (final volume 1 ml) and after 48-h pretreatment with PMA, the cells were washed three times with 0.5 ml of tempered THP-1 medium without PMA and allowed to incubate for 30 min before LPS stimuli. Once at rest, rest, the cells were treated with 10 ng/ml LPS (Sigma–Aldrich) in RPMI 1640 medium and the investigational product, which had been previously quenched at room temperature or quenched THP-1 medium, using as control the same THP-1 culture treated with the same amount of LPS, but adding in this case 10 μg/ml hydrocortisone. The final volume of each well was 1 ml with 400,000 cells each. Stimulation was carried out for 5 h.
After 5 h of stimulation, supernatants were removed from each well, divided into aliquots, and flash-frozen by immersion in dry ice for further analysis. Total RNA was extracted from the cells using an RNeasy Plus Mini kit (Qiagen, Hilden, Germany), and extraction was carried out strictly according to the manufacturer’s instructions. This kit included a genomic DNA removal step. The resulting RNA was eluted from the columns using nuclease-free water, divided into aliquots, and stored at −80°C to avoid degradation by environmental RNAases. From the 40 μl of RNA solution from each sample, an aliquot was extracted to assess RNA integrity and concentration. Total RNA integrity was assessed by agarose gel electrophoretic run of total RNA on a 2% agarose-TBE gel for 30 min at 120 V and 400 mAh. Quantification of total RNA was performed by a fluorimetric method using a highly sensitive fluorimetric kit (Qubit HS RNA quantification kit, Applied Biosystems, ThermoFisher). The cDNA was synthesized from total RNA for quantitative PCR of our genes of interest. A high-capacity cDNA reverse transcription kit (Applied Biosystems) was used for synthesis, and a total of 150-ng total RNA was used, for each synthesis reaction. Each sample had 5 cDNA synthesis reactions to achieve sufficient volume for downstream applications. The synthesis protocol was performed using an RNAase inhibitor following the manufacturers’ recommendations, and their protocol was strictly followed. Random hexamers were used to perform reverse transcription of all mRNAs into double-stranded cDNA. After synthesis, the cDNAs were divided into aliquots and stored at −20°C, for later use. An aliquot of these cDNAs was extracted for quantification using a Qubit dsDNA HS Assay kit (Applied Biosystems). Primer concentrations were optimized using a cDNA pool to determine the most appropriate concentrations of the primers in the qPCR protocol. For such determination, a standard PCR was performed using a 2× PCR MasterMix (DreamTaq HotStart PCR MasterMix) (Applied Biosystems). Cycling conditions were 98°C for 3 min, then 35 cycles at 95°C for 45 s, 60°C for 30 s, and 72°C for 30 s. After these 35 cycles, the temperature was set at 72°C for 5 min and then held at 4°C indefinitely. The optimal primer concentration was determined by selecting the sharpest specific bands on agarose electrophoresis, uncontaminated by the presence of primer dimers at the front of the gel or nonspecific products. Ideal primer concentrations were 250 nM for forward and reverse primers. Primer sequences and amplicon sizes are attached in Table 2.
Gene name | Forward 5′→3′ | Reverse 3′→5′ | Gene ID | Amplicon size (bp) |
---|---|---|---|---|
TLR-2 | CCACCTGCCTGGAACTCAG | CAGTCACCTGAGAGAACGCC | 7097 | 216 |
TLR-3 | AACGACTGATGCTCCGAAGG | CAGGGTTTGCGTGTTTCCAG | 7098 | 207 |
TLR-4 | TAGCGAGCCACGCATTCACA | TTAGGACCACCTCCACGCAG | 7099 | 165 |
TLR-7 | CCCTGGCCACAGACAATCAT | TCCTGTGACAGACGTTGGTG | 51,284 | 210 |
TRAF6 | CCGCGCACTAGAACGAGCAA | GGCAGTTCCACCCACACTATC | 7189 | 157 |
MyD88 | ATGCCTTCATCTGCTATTGCCC | GGCCTTCTAGCCAACCTCTTT | 4615 | 175 |
RIPK1 | ACTAGGTGGCAGGGTACAG | TGATCATGAGTCCCTGGGTT | 8737 | 202 |
IKKβ | TGGACGTGGTCACAGACGGA | CGAGGAACCACCATGTGAGA | 3551 | 203 |
NF-kβ | TTAGGAGGGAGAGCCCAC | AGTCGGATCTGTGGTTGAAA | 4790 | 241 |
CASP1 | CAGTCACACAAGAAGGGAGG | CCCCTTTCGGAATAACGGAC | 834 | 227 |
NLRP3 | GCTGGCATCTGGATGAGGAA | AAAGTTCTCCTGTTGGCTCG | 114,548 | 247 |
GAPDH | GCACCACCAACTGCTTAGC | GCATGGACCGTGGTCATGAG | 2597 | 131 |
Primer sequences and amplicon sizes.
The following Thermo Fisher primers (coupled to FAM) were also used for A2a (Hs00169123_m1), A3 (Hs04194761_s1), and P2X7 (Hs00175721_m1) receptors.
Subsequently to perform qPCR, total RNA was extracted from 400,000 THP-1 cells using a Qiagen RNeasy plus mini kit (Qiagen, Hilden, Germany). THP-1 cells had been previously differentiated to resting macrophages using 5 ng/ml phorbol 12-mystirate 13-acetate (PMA) (Sigma–Aldrich, Saint Louis, MA, USA) in cell culture medium 48 h prior to the experimental model. A total of 0.75 μg of RNA was retrotranscribed to cDNA using a high-capacity cDNA synthesis kit (ThermoFisherScientific, Waltham, USA) employing random hexamers. For qPCR, 10 ng of cDNA per reaction was amplified using a Power SYBR-Green PCR master mix (Applied Biosystems, Thermo Fisher) on a StepOnePlus real-time PCR machine (Perkin Elmer, Waltham, MA, USA) and using the primers listed in Table 1 (primer table). Thermal cycling conditions included an initial denaturation step at 95°C for 5 min, followed by 40 cycles at 95°C for 30 s, 60°C for 30s, and 72°C for 30s. Melting curve analysis of each qPCR was performed on the final products. Messenger RNA fold changes were calculated using the ΔΔΔCt method with GAPDH as a calibrator gene.
Finally, in order to have an approximation of the mechanism of action of our PRS® CK STORM conditioned medium, two studies were performed. Firstly, a quantification of the ATP/ADP ratio contained in the drug. The Sigma–Aldrich colorimetric ADP/ATP ratio assay kit (Ref: MAK135) was used for this purpose, and the Biorad iMark plate reader was used for its reading. Secondly, a quantification of extracellular ATP in THP-1 cells placed in culture, comparing the results when stimulated by LPS and/or treated with PRS® CK STORM conditioned medium. For this purpose, the ELISA ATP Assay Kit Colorimetric (Ref: ab83355) from Abcam was used, and the Biorad iMark plate reader was used for reading.
To perform the experimental model of acute lung injury, the experimental model described by Stephens et al. [51] was used. For this model, 8–10 weeks old male C57BL/6 mice were used and administered 5 mg/kg of bacterial lipopolysaccharide (LPS) in 50 μl of physiological solution retro-orbital under anesthesia. To decrease the possible suffering of the mice due to LPS, they were administered buprenorphine hydrochloride in water at the established dose of 0.056 mg/ml. A total of 25 animals were used, with a number of animals per group of 5. The mice were conditioned 1 week prior to the procedure and were housed in standard conditions with access to food and water ad libitum with 12-h light/dark cycles at a temperature of 25°C and humidity greater than 40% over the course of the project.
Basal group – animals given no LPS or treatment/basal data (n = 5; mice number 1–5).
Vehicle control – animals administered 50 μl of vehicle (n = 5; mice number 6–10).
Positive control group – animals given LPS but no treatment, vehicle only (n = 5; mice number 11–15).
Gold standard-treated animals – LPS-treated animals given gold standard – Anakinra treatment at a dose of 200 mg/kg/day orally (defined in Stephens et al. [51]). (n=5; mice number 16–20).
PRS® CK STORM-treated animals – LPS-treated animals given the drug intravenously (n = 5; mice number 21–25).
The vehicle used in the vehicle control group is PBS (phosphate-buffered saline). The gold standard treatment consists of the administration of Anakinra (IL-1Ra) before and after inoculation with LPS. The test group received the established dose of imatinib 24 h prior to LPS administration. The animals were administered the drug every 24 h starting from the retro-orbital administration of LPS. Treatment was administered intravenously (40 μl), upon generation of the model and then every 24 h thereafter. Blood samples were taken 24, 48, and 72 h after generation of the model from the submaxillary sinus from which 120 μl were collected for hemodynamic and general biochemical study, which was performed with the Comprehensive Diagnostic Profile protocol (#500–0038), of the VetScan V2 device (Abaxis). After 72 h from the generation of the model, the animals were sacrificed and exsanguinated and plasma samples were collected for final biochemical and cytokine analysis. Specifically, TNF-α, IL-1β, and IL-6 as proinflammatory cytokines and IL-10 as anti-inflammatory cytokine were quantified. They were analyzed by Luminex: MILLIPLEX MAP Mouse Cytokine/Chemokine Magnetic Bead Panel – Immunology Multiplex Assay (Cat: MCYTOMAG-70 K) (Merck). During the study, hyperthermia/hypothermia, respiratory distress, weight loss, food and water consumption, as well as the existence of other behavioral disorders were monitored. After euthanasia and subsequent necropsy, the major organs (heart, lung, liver, kidney, and spleen) were removed and fixed and preserved in 4% formalin for histological study. A small portion of each organ, prior to fixation, was preserved directly by immersion in dry ice to study inflammatory cytokine content in future assays. All animals underwent Irwin’s test every 24 h to obtain neuropharmacology data following the protocol of Mathiasen et al. [52].
The MTT and cytokine release assays, as well as the cytokine analysis of the culture supernatants, the biochemical values of the blood of the different groups of treated mice, and the values obtained in the qPCRs, were subjected to statistical analysis. For these, a two-tailed Student’s t-test was performed to obtain the p-value between the different experimental groups and to analyze the existence of significant differences (p < 0.05). Statistical analysis was performed with Excel (Microsoft, Albuquerque, NM, USA).
The yield achieved in the isolation of MSCs was approximately 1 × 105 cells per ml of lipoaspirate, and it was necessary to incubate for 16 days under the conditions described in the previous section to bring the culture to pass 4 (Figure 1a). The yield provided by the monocyte donor can be seen in Table 3.
Age | Sex | Complete blood (millions/μl) | Buffy volumen (ml) | PBMCs (millions) | Monocytes (millions) | ||
---|---|---|---|---|---|---|---|
Luekocytes | Red blood cells | Platelets | |||||
45 | M | 54.3 | 2.4 | 69 | 145 | 668.8 | 65.65 |
Data and yields obtained from monocyte donors.
Percentage of positive cells for each antibody tested.
Optical microscopy showed that the cell morphology of the adherent cells in the cultures corresponded to that of monocytes/macrophages.
The results of flow cytometric characterization of MSCs and monocytes from three co-cultures at the times studied are shown in Figure 1. Phenotypic characterization of MSCs shows the classic phenotype of CD90 > 90%, CD73 > 90%, CD31 < 2%, CD45 < 2%, and HLA-DR < 2%. The marker CD68 is used as macrophage identifier, CD163 is mostly present on M2 type macrophages, and CD39 is expressed on macrophages/monocytes in co-culture with MSC.
The results of quantification by both ELISA and Multiplex are detailed in Table 4.
CK | MIP1-α | IL-2 | IL-6 | TIMP-1 | IL-8 | IL-10 | |
---|---|---|---|---|---|---|---|
Monocytes | AVG | 9.5643367 | <8.2 | <10.5 | 35777,0862 | 235.261369 | 3.06669833 |
SD | 3.57120227 | NP | NP | 48725,6036 | 106.055289 | 1.34471437 | |
Control MSC | AVG | <2.3 | <8.2 | 542.274142 | >167500 | 9.30152294 | 0.7036029 |
Co-culture MSC/monocytes | AVG | 6.91058459 | <8.2 | 1153.79376 | >167500 | 330.463609 | 2.58248776 |
SD | 4.45252385 | NP | 309.210936 | NP | 175.835377 | 0.53200545 | |
CK | IL-12 P70 | IL-1 RA | RANTES | GMCSF | Leptina | HGF | |
Monocytes | AVG | 2.08256741 | 476452.06 | 1.23761123 | <17.3 | 49.1307951 | 1748.29405 |
SD | 0.04597914 | 826813.74 | 0.27823114 | NP | 1.9033707 | 412.510477 | |
Control MSC | AVG | 0.70858087 | <41.4 | 4.7416231 | <17.3 | <16.3 | 145.833433 |
Co-culture MSC/monocytes | AVG | 1.68319311 | 223795.156 | 5.39009081 | <17.3 | 64.0308586 | 1630.39368 |
SD | 0.30017417 | 208257.922 | 2.88381852 | NP | 49.0665959 | 456.036333 | |
CK | MMP-3 | MCP1 | BNGF | EGF | Adiponectin | TNF-α | |
Monocytes | AVG | <16.5 | 2658.5485 | <7.4 | 1.93098264 | 189.27 | <5.9 |
SD | NP | 1672.2932 | NP | NP | 111.942 | NP | |
Control MSC | AVG | 137.490877 | 573.667894 | <7.4 | <1.2 | <89.3 | <5.9 |
Co-culture MSC/monocytes | AVG | 450.455082 | 3275.6692 | 0.48007142 | <2.2 | 173.5 | <5.9 |
SD | 322.742794 | 1773.64942 | 0.19422895 | NP | 23.5476 | NP | |
CK | MMP-1 | TRAIL | FGF-2 | PDGF-BB | VEGF-A | IGF-1 | |
Monocytes | AVG | 32.0031459 | 1.63442629 | <3 | 71.944999 | 15.6273891 | 760.452793 |
SD | 41.5287708 | 1.1152979 | NP | 37.2898086 | 26.2176915 | 1099.67079 | |
Control MSC | AVG | 560.670891 | <1.2 | <3 | 83.1238663 | 1838.37263 | 717.691553 |
Co-culture MSC/monocytes | AVG | 1364.87744 | 3.18084865 | <3 | 127.82401 | 239.64569 | 1903.91696 |
SD | 335.663559 | 2.00494659 | NP | 80.6592455 | 399,735639 | 881.409224 | |
CK | BMP-6 | IL-1β | IL-4 | TGF-β1 | TGF-β3 | VEGF-C | |
Monocytes | AVG | <156 | <1 | <10 | <31.2 | <31.2 | <62.5 |
SD | NP | NP | NP | NP | NP | NP | |
Control MSC | AVG | <156 | <1 | <10 | <31.2 | <31.2 | <62.5 |
Co-culture MSC/monocytes | AVG | <156 | <1 | <10 | <31.2 | <31.2 | <62.5 |
SD | NP | NP | NP | NP | NP | NP |
Mean values of the molecules studied.
Values are shown in picograms per milliliter. > and < indicate that the value is above or below the detection limits (respectively). SD: standard deviation; NP: not applicable.
To obtain the pattern (Figure 2), those molecules that could be quantified because they were within the detection limits of the method used in each case were studied, and statistically significant differences were sought with respect to the values taken as control (conditioned medium of M2-like monocytes/macrophages). Those values that were significantly different in all the samples studied (five samples in triplicate) were considered to form a specific and reproducible pattern of monocyte secretome modification by co-culture with MSCs. To test whether the pattern obtained was specific to the cell type co-cultured with monocytes, the expression of the same secretome molecules was obtained under the same conditions, but co-culturing monocytes with the following cell types: osteocytes, chondrocytes, tenocytes, synoviocytes, myocytes, lymphatic vascular cells, and Schwann cells, was compared. From this comparison, eight different and characteristic secretomes could be specifically differentiated, quantifying a minimum of seven molecules: IL-6, leptin, HGF, MMP-1, MMP-3, adiponectin, and VEGF-A (data not shown).
Cytokine expression patterns. Shown are 16 mean values ± standard deviation of molecular characterization (MIP-1α, IL-6, IL-8, IL-10, IL-1Ra, RANTES, Leptine, HGF, MMP-3, MCP-1, Adiponectine, MMP-1, TRAIL, PDGF-BB, VEGF-A, IGF-1). (A) Secretome of monocytes; (B) secretome of co-culture. Stars mark values where there is a statistically significant difference (p < 0.05).
THP-1 cells after 48 h of stimulation with PMA gain adherence to the culture plastic and take on a macrophage-like morphology. After 24 h of culture, the number of cells in suspension decreases and the number of cells adherent to the plastic increases, a symptom of correct differentiation. After 48 h, about 90% of the cells are adherent to the plastic and are used in the experimental model.
The in vitro inflammation model used in this research is based on stimulating the proinflammatory action of macrophages when exposed to LPS. Figure 3 shows that the addition of our conditioned medium to the culture of THP-1 cells transformed into macrophages can reverse the effect of LPS on these macrophages, and a statistically significant difference can be observed, in addition to the difference observed with the use of soluble hydrocortisone. It can also be observed that the cells are sensitive to LPS stimuli at the concentration used.
Graph a shows the results in terms of IL-1β release in the in vitro model of inflammation. Graph b shows the results in terms of TNF-α release in the in vitro model of inflammation. For these four studies, the results were analyzed in three independent experiments with two replicates of the analytical technique, for each type of experiment. Error bars indicate the standard deviation between samples. Asterisks (*) mark values where there is a statistically significant difference (p < 0.05).
The results of the Irwin test are analyzed to evaluate at a general level the effect produced by the conditioned medium administered intravenously to mice, in which the cytokine storm model had been previously induced, by retrorbital injection of LPS. A slight decrease in temperature was observed in all LPS-injected groups. LPS administration was observed to induce changes in reflexes and behavior, such as hunching, piloerection, and tremors, which were increased throughout the 3-day trial. In contrast, exploratory activity, reaction to contact, and aggressiveness were slightly decreased. In all LPS-treated mice (with or without drug administration), mild diarrhea occurred, which in untreated or gold standard-treated mice resulted in more severe dehydration than in mice treated with the conditioned medium. In general, there is a trend that the symptoms caused by LPS administration are dissipated by treatment with our conditioned medium (PRS® CK STORM), demonstrating a beneficial effect on the mice without counterproductive effects (Table 5).
Results of the Irwin test; it includes the parameters studied on the third day after generating the model. Mice 11, 18 and 22 died before completing the 3 days of the experiment [52].
The variations observed have as reference value the parameters 1 day before generating the model. Mice 11, 18, and 22 died before completing the 3 days of the experiment.
From the blood obtained after euthanasia and exsanguination of the animals, biochemical tests were performed to determine the biochemical profiles, which are shown in Table 6. The Mann–Whitney test was used for statistical analysis, considering statistical significance as*p < 0.05 in the case of statistically significant minor differences with respect to the baseline value and **p < 0.05 in the case of statistically significant major differences with respect to the baseline value.
Albumin | Alanineaminotranferase | Amylase | Totalbilirrubin | Creatinine | Glucose | Total protein | Globulin | |||
---|---|---|---|---|---|---|---|---|---|---|
Control | 0 h | Average | 41 | 23 | 945 | 4 | 34 | 20.3 | 52 | 12 |
SD | 3.5 | 3.1 | 20.1 | 24 | 9.3 | 2.2 | 2.5 | 4.2 | ||
24 h | Average | 40 | 25.8** | 946 | 7.0** | 21.0* | 22 | 55 | 15.0** | |
SD | 4.1 | 3.7 | 23.7 | 2.8 | 10.9 | 2.6 | 2.9 | 5 | ||
48 h | Average | 48.0** | 30.0** | 912 | 10.0** | 22.0* | 21.4 | 58.0** | 10.0* | |
SD | 3 | 2.7 | 17.3 | 2.1 | 8 | 1.9 | 2.1 | 3.6 | ||
72 h | Average | 40 | 25 | 960 | 5.0** | 27.0* | 23.7** | 52 | 13 | |
SD | 3.1 | 2.8 | 17.8 | 2.1 | 8.2 | 1.9 | 2.2 | 3.7 | ||
PBS | 0 h | Average | 43 | 30 | 869 | 5 | 18 | 20.9 | 54 | 11 |
SD | 2.2 | 3.4 | 29.5 | 2.4 | 3.4 | 2.5 | 1.5 | 1.5 | ||
24 h | Average | 40 | 28 | 866 | 6.0** | 24.0** | 22.8 | 54 | 14.0** | |
SD | 2.5 | 4.3 | 34.9 | 2.8 | 4 | 3 | 1.8 | 1.8 | ||
48 h | Average | 38.0* | 28 | 910 | 6.0** | 25.0** | 19.9 | 52 | 14.0** | |
SD | 1.9 | 2.9 | 25.5 | 2.1 | 2.9 | 2.2 | 1.3 | 1.3 | ||
72 h | Average | 39 | 29 | 924.5 | 5 | 25.0* | 25.6** | 51 | 12 | |
SD | 1.9 | 3 | 162.3 | 2.1 | 3 | 2.2 | 1.3 | 1.3 | ||
LPS | 0 h | Average | 33 | 33 | 758 | 5 | 20 | 13.1 | 50 | 17 |
SD | 1.6 | 3 | 71.1 | 3 | 1.4 | 2 | 1.3 | 2.4 | ||
24 h | Average | 29.0* | 26.0* | 615.0* | 5 | 15.9 | 10.5* | 51 | 22.0** | |
SD | 1.9 | 3.5 | 83.9 | 3.6 | 1.7 | 2.3 | 1.5 | 2.8 | ||
48 h | Average | 31 | 18.0* | 768 | 6.0** | 14.5 | 9.0* | 49 | 17 | |
SD | 1.4 | 2.6 | 61.3 | 2.6 | 1.2 | 1.7 | 1.1 | 2.1 | ||
72 h | Average | 31 | 84.0** | 740 | 7.0** | 16 | 8.8* | 48 | 18 | |
SD | 1.4 | 2.6 | 63 | 2.7 | 1.3 | 1.8 | 1.1 | 2.1 | ||
LPS + gold standard | 0 h | Average | 32 | 21 | 727 | 5 | 16.1 | 11 | 50 | 18 |
SD | 1.8 | 8.9 | 199.5 | 2.2 | 3.1 | 1.1 | 1.5 | 0.5 | ||
24 h | Average | 30 | 26.4** | 854.0** | 4.0* | 15.4 | 9.5* | 48 | 18 | |
SD | 2.2 | 10.5 | 135.6 | 2.6 | 3.7 | 1.2 | 1.8 | 0.6 | ||
48 h | Average | 33 | 15.0* | 1118.0** | 5 | 14.6 | 9.0* | 51 | 18 | |
SD | 1.6 | 7.7 | 171.8 | 1.9 | 2.7 | 0.9 | 1.3 | 0.4 | ||
72 h | Average | 29 | 36.0** | 1278.0** | 9.0** | 16 | 8.6* | 48 | 19 | |
SD | 1.6 | 7.9 | 176.6 | 2 | 2.8 | 0.9 | 1.3 | 0.4 | ||
PRS® CK STORM | 0 h | Average | 29.5 | 48.5 | 787.5 | 8 | 23.5 | 15 | 49 | 19 |
SD | 1 | 17.8 | 118 | 2.6 | 7.1 | 3.3 | 2 | 3.1 | ||
24 h | Average | 31.5 | 32.5* | 681.5* | 5.0* | 29.0** | 12.9* | 49 | 17.0 * | |
SD | 1.2 | 2.1 | 139.2 | 3.1 | 8.3 | 3.9 | 2.4 | 3.6 | ||
48 h | Average | 30 | 36.0* | 823 | 9.0** | 21.5 | 15.3 | 50.5 | 19 | |
SD | 0.9 | 1.5 | 101.6 | 2.3 | 6.1 | 2.8 | 1.7 | 2.6 | ||
72 h | Average | 38.5** | 48 | 783.5 | 6.5* | 21.5 | 14.5 | 52.5 | 18 | |
SD | 0.9 | 1.6 | 104.5 | 2.3 | 6.3 | 2.9 | 1.8 | 2.7 |
Results of the biochemical analysis of the mice, including the parameters studied pretreatment and posttreatment at 24, 48, and 72 h.
The Mann–Whitney test was used for the statistics, considering the statistical significance as *p < 0.05 in the case of minor statistically significant differences with respect to the basal value and **p < 0.05 in the case of major statistically significant differences with respect to the basal value.
Figure 4 shows in percentage the relative variations observed at the posttreatment times (24, 48, and 72 h), with respect to the baseline values observed in each group.
Concentration values of the different metabolites that make up the biochemical profile of the mice, expressed as a percentage with respect to the baseline value observed in each group.
The experimental model employed uses LPS as a causative agent of acute lung damage, causing a cytokine storm in the organism of mice like that produced by COVID-19 disease. We focused on the quantification of a small amount of these cytokines (TNF-α, IL-1β, IL-6, and IL-10) to evaluate the effect of the PRS® CK STORM. Figure 5 shows the evolution of these cytokines detected in the sera of the mice on each of the days that the treatment lasted.
Serum values of the different cytokines after 24, 48, and 72 h from the administration of the first treatment expressed in pg/ml as the mean of the values of the mice in each of the experimental groups. a: TNF-α. b: IL-1β. c: IL-6. d: IL-10. Values not shown are lower than the detection limit of the assay (2.8 pg/ml).
Histopathological analysis of the samples obtained from various organs of the mice obtained after the corresponding necropsies showed patchy lung thickening of the interstitium in a large part of the sample in the LPS treatment, while in the group treated with PRS® CK STORM it was observed that there was no lung damage, as in the control groups. Slight affectations were observed in liver and spleen, which the drug was also able to reverse. As for the heart and kidney, no pathological findings were detected. Figure 6 shows examples of the lung sections studied in the different groups of the experiment.
Pulmonary anatomopathological study in the different groups of mice in the experiment. It can be seen that the group treated with PRS® CK STORM (our conditioned medium), the appearance of the lung is very similar to that shown by the untreated control group. All sections have been stained with hematoxylin eosin. ×1 images are taken in MO at 4× magnification and ×2 images are taken in MO at 40× magnification.
In order to approach the mechanism of action of our conditioned medium PRS® CK STORM, qPCR study is performed in order to analyze the effects of our complex biological drug under investigation on all common molecules involved in TLR2, TLR3, TLR4, TLR7, TLR8, TLR9, NOD1, NOD2, and NLRP3 pathways, TLR9, NOD1, NOD2, and NLRP3, and it is found that the conditioned medium downregulates the hyperactivity of these pathways, immunoregulating the key proteins involved in these pathways, being very remarkable the decrease of expression observed in TRAF6, caspase-1, RIPK1, IKKB, NF-kβ, MyD88, and NLRP3 proteins.
Following the method described in the corresponding section of this chapter, the total mRNA of the proteins named in the previous paragraph common to various pattern recognition pathways was extracted from THP-1m cells in culture used as control, from those stimulated with LPS, and from those stimulated with LPS and treated with PRS® CK STORM, obtaining by qPCR the relative expression of the genes at the mRNA level normalized against GAPDH, the results of which are shown in Figure 7.
qPCR study showing the results of relative gene expression of proteins common to various pathways related to pattern recognition in infections, at the mRNA level normalized against GAPDH, considering statistical significance as *p < 0.05.
Similarly and under the same experimental methodology, the total mRNA of the pattern recognition proteins linked to main infectious processes TLR-2, TLR-3, TLR-4, and TLR-7 was extracted from THP-1m cells in culture used as control, from those stimulated with LPS and from those stimulated with LPS and treated with PRS® CK STORM, obtaining by qPCR the relative expression of the genes at mRNA level normalized against GAPDH, whose results are shown in Figure 8.
qPCR study showing the results of relative gene expression of major pattern recognition receptor proteins in infections, at the mRNA level normalized against GAPDH, considering statistical significance as *p < 0.05.
In order to estimate the possible action of our PRS® CK STORM conditioned medium through the purinergic system (Figure 9), the results of the ATP/ADP ratio obtained were analyzed comparatively among three groups with three replicates for each group, being the first group formed by THP-1m cells placed in culture alone, THP-1m cells stimulated with LPS at the doses described in Section 2, and the same THP-1m cells stimulated with LPS but in culture in the PRS® CK STORM conditioned medium (Figure 9a). The extracellular ATP contained in the same three groups of cultures with three replicates for each group was quantified (Figure 9b). Finally, following the method described in the corresponding section of this chapter, the total mRNA of purinergic receptors A2a, A3, and P2X7 was extracted from THP-1m cells in culture used as control, from those stimulated with LPS, and from those stimulated with LPS and treated with PRS® CK STORM, obtaining by qPCR the relative expression of the genes at the mRNA level normalized against GAPDH (Figure 9c).
(a) ATP/ADP ratio analysis in three groups of cell cultures (THP-1m, THP-1m + LPS, and THP-1m + LPS + PRS® CK STORM). Asterisks (*) mark values where there is a statistically significant difference (p < 0.05). (b) Quantitative analysis of extracellular ATP in three groups of cell cultures (THP-1m, THP-1m + LPS, and THP-1m + LPS + PRS® CK STORM). Asterisks (*) mark values where there is a statistically significant difference (p < 0.05). (c) qPCR study showing the results of the relative expression of purinergic A2a, A3, and P2X7 receptor genes at the mRNA level normalized against GAPDH, considering statistical significance as *p < 0.05.
In the complex composition of this conditioned medium (PRS® CK STORM), all the growth factors, cytokines, and chemokines that are naturally produced by M2-type macrophages and MSCs, associated with innate immunity, are present, respecting the natural pleiotropic relationships, with an immunomodulatory cytokine profile from which a potent anti-inflammatory action is expected. In addition, according to the results obtained in test studies, the mechanism of action on TLR-7 receptors may possibly include some antiviral activity [32]. In fact, several experiments have shown that the secretomes of both cell types possess immunomodulatory properties. For example, direct injection of the supernatant of cultured mesenchymal stem cells (MSCs), which contains a variety of growth factors, prostaglandins and cytokines, can be applied to the treatment of kidney injury [45].
The theoretical advantage of using the complete conditioned medium versus some of its purified components lies in the synergistic mechanism between its different components [48], the result of subjecting the cell populations to a culture that, in vitro, attempts to emulate the immunomodulatory and regenerative microenvironment that occurs in vivo in diseased tissue. However, the main handicap of biological drugs with complex natural compositions will always be the variability between different batches and the practical impossibility of achieving a complete characterization, both qualitatively and quantitatively, as well as functionally [48]. Despite the earlier-mentioned, our group has been able to prove the existence of a stable cytokine pattern or fingerprint, which depends directly on the type of co-culture established and the conditions of the same and not on the donor of origin.
The anti-inflammatory capacity and potency shown by the PRS® CK STORM conditioned medium has been remarkable, showing statistically significant reductions in in vitro tests on TNF-α and IL-1β levels, these differences being very similar to those obtained with hydrocortisone. This anti-inflammatory immunomodulatory capacity, we have also been able to verify in the in vivo model, generated in mice. The mice treated with our PRS® CK STORM conditioned medium have shown normal behavior and the rest of the parameters analyzed in the Irwin test have been very similar to the control groups, where the cytokine storm had not been provoked. In fact, the comparative results in the in vivo test between the gold standard treatment used (Anakinra) and the PRS® CK STORM were clearly more favorable to the latter. It should be noted that in the group treated with PRS® CK STORM practically no pulmonary lesions were observed, while in the group treated with Anakinra inflammatory and fibrotic infiltrates were observed in a minimum of 30% of the surface of the sections. This coincides with the observation made at the time of sacrifice of the animals under study where both the control animals, in which the cytokine storm had not been provoked, and those treated with PRS® CK STORM, took more than 2 min to die in the CO2 chamber, while the animals treated with Anakinra died in 40 s and those not treated in about 30 s, and these times can be directly related to the anatomopathological state observed at the pulmonary level.
The results obtained throughout this experiment suggest that the drug PRS® CK STORM is safe for intravenous administration, since no significant adverse effects have been observed in the different parameters analyzed, those found being mild. In addition, the drug significantly attenuates the detrimental effects caused by the cytokine storm associated with LPS administration. Most of the proteins and metabolites analyzed follow the same trend, regardless of the experimental group observed. With respect to albumin, the main protein present in blood, there is a decrease in albumin in all groups to which LPS was administered, which fits with that described by Ballmer et al. [53], with hypoalbuminemia occurring when the organism undergoes sepsis due to infection. Related to this, there is a decrease in total protein: a decrease in albumin will cause a decrease in total protein since the former is at very high concentrations. A decrease in blood glucose is also observed in all mice treated with LPS and LPS + gold standard. However, those treated with PRS® CK STORM managed to normalize the levels of glycemia, albuminemia, and total proteinemia 3 days after receiving the first dose. This fact was directly related to the clinical improvement observed in these animals subjected to the experimental treatment, given that they felt better than the rest of the mice, ate better, physical activity was normalized, and diarrhea was corrected. On the other hand, a significant increase in alanine amino transferase (ALT), total bilirubin, and amylase was observed during the experiment, which could be related to reactive hepatitis [54]. This increase was observed in all groups stimulated with LPS and was maintained in those treated with gold standard. However, in those treated with PRS® CK STORM, the figures normalized 72 h after the first treatment.
In all the groups where LPS was administered, there was a rapid increase in all the cytokines analyzed. From this, we can conclude that stimulation with bacterial lipopolysaccharide (LPS) is able to induce the expected inflammatory response, being more pronounced in more acute phase, the day after treatment administration and decreasing over time. In the control group and the vehicle, the presence of proinflammatory cytokines is not observed, which confirms that LPS is the cause of this response. However, in the group treated with LPS + gold standard, a lower increase of IL-1β is observed with respect to the rest of the groups where LPS was administered. This fact can be explained by the previous administration of the gold standard, recombinant IL-1Ra. However, despite the lower increase in this proinflammatory cytokine, the decrease in IL-1β finally achieved by the gold standard is even lower than that obtained with PRS® CK STORM treatment. In general terms, our PRS® CK STORM conditioned medium achieves greater control of all the cytokines analyzed in the experiment.
The results of the mechanism of action study show that PRS® CK STORM is able to immunomodulate in an anti-inflammatory way the expression of TLR-like pattern recognition pathways especially associated with infectious processes, such as TLR-2, TLR-3, TLR-4, and TLR-7. From the same study, it can be deduced that this effect is not only localized to these receptors but also acts at the level of various proteins common to these and other pathways, such as TRAF6, RIPK1, and IKKB, with the decrease in expression observed in the proteins NF-kβ, MyD88, caspase-1, and NLRP3 being very significant.
Many published studies have demonstrated the importance of the purinergic system in the inflammation associated with the cytokine storm caused by moderate/severe infection, including COVID-19, and have shown that using various purinergic system receptors as a therapeutic target can limit the negative effects of the cytokine storm [21, 22, 55, 56, 57]. Extracellular ATP at high concentrations becomes a true alarmin [58], a potent proinflammatory signal capable of overexpressing and stimulating P2X-type purinergic receptors, especially P2X7R, located on various immune cells (neutrophils, eosinophils, monocytes, macrophages, mast cells, and lymphocytes) [59]. Extracellular adenosine triphosphate (eATP) is a well-characterized DAMP that modulates function and plasticity [60, 61]. This nucleotide can be released by stressed, injured, and dying cells or in response to TLR activation, reaching high concentrations in the extracellular medium [62].
In contrast, it has been shown that the balance between ATP and adenosine concentration is crucial in immune homeostasis. CD39 and CD73 are two ectonucleotidases that cooperate in the generation of extracellular adenosine by ATP hydrolysis, thus tipping the balance toward immunosuppressive microenvironments. Extracellular adenosine through A2A receptor stimulation has the ability to prevent activation and proliferation of both macrophages and T cells, thereby dramatically decreasing cytokine production [63].
From the results observed both in the cytometric characterization of M2 macrophages used in the co-culture to produce our conditioned medium, where a strong expression of CD39 and CD73 is observed, and from the study of the ATP/ADP ratio, where a clear increase of ADP is observed, we can deduce that one of the mechanisms of action of PRS® CK STORM is probably linked to the process of dephosphorylation of extracellular ATP, which is degraded by ectonucleotidases to adenosine, and the latter interacts with adenosine receptors, type A2A and A3, producing an immunomodulatory anti-inflammatory effect on the cytokine storm. This theory is supported by two further pieces of evidence; firstly by the statistically significant decrease observed in LPS-stimulated THP-1 cells treated with our PRS® CK STORM conditioned medium with respect to the levels observed in untreated LPS-stimulated THP-1 cells; and secondly by the combination of the observed reduction in the relative expression of P2X7 receptor mRNA with the observed increase in the relative expression of A3 and A2a receptor mRNA in LPS-stimulated THP-1 cells treated with PRS® CK STORM relative to untreated THP-1 cells.
In all assays used in the in vitro and in vivo models, both employed LPS as an inducer of inflammation. Although the immunomodulatory mechanisms induced by bacterial antigens with respect to viral antigens in immune cells are different at the mechanistic level, the inflammatory response at the level of innate immunity ends up sharing numerous points in common [64, 65]. Therefore, the effect that PRS® CK STORM has on these models of inflammation with LPS can be exportable to what can happen, at the level of immune response, during a viral infection. In fact, it has been shown that monocytes and macrophages stimulated with LPS and ATP increase the release of IL-1β [66, 67].
All these results observed in the study on the possible mechanism of action of our complete conditioned medium (PRS® CK STORM) demonstrate that the immunomodulatory anti-inflammatory effect observed is a direct consequence of the action of various molecules contained in this medium, acting in a synergistic and pleiotropic manner on various therapeutic targets associated with different proinflammatory pathways, managing to downregulate the activation of the inflammasome, the inflammatory activation of the purinergic system, the activation of various pathways of pattern recognition associated with infections, etc., thus avoiding the possible feedback effects that therapeutic approaches based on the inhibition of a single receptor or a single inflammatory pathway may have.
The co-culture of M2 macrophages with MSCs allows the simple production of a complete conditioned medium (PRS® CK STORM), which has a clear anti-inflammatory profile. In line with this characterization, it has been demonstrated that PRS® CK STORM is able to stop macrophage overactivation in an in vitro inflammation model, through several mechanisms, including the expression pattern of TLR’s and the purinergic system. Likewise, the action capacity of this drug has also been demonstrated in vivo, by improving the symptomatology and tissue damage induced in mice in another model of inflammation. Therefore, PRS® CK STORM is proposed as an effective and safe treatment to treat cytokine storms associated with moderate/severe infectious processes of any etiology, including that associated with COVID-19.
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',metaTitle:"Horizon 2020 Compliance",metaDescription:"General requirements for Open Access to Horizon 2020 research project outputs are found within Guidelines on Open Access to Scientific Publication and Research Data in Horizon 2020. The guidelines, in their simplest form, state that if you are a Horizon 2020 recipient, you must ensure open access to your scientific publications by enabling them to be downloaded, printed and read online. Additionally, said publications must be peer reviewed. ",metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"Publishing with IntechOpen means that your scientific publications already meet these basic requirements. It also means that through our utilization of open licensing, our publications are also able to be copied, shared, searched, linked, crawled, and mined for text and data, optimizing our authors' compliance as suggested by the European Commission.
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Metabolomics has several applications in health and disease including precision/personalized medicine, single cell, epidemiologic population studies, metabolic phenotyping, and metabolome-wide association studies (MWAS), precision metabolomics, and in combination with other omics disciplines as integrative omics, biotechnology, and bioengineering. Mass spectrometry (MS)-based metabolomics/lipidomics provides a useful approach for both identification of disease-related metabolites in biofluids or tissue and also encompasses classification and/or characterization of disease or treatment-associated molecular patterns generated from metabolites. Here, in this review, we provide a brief overview of the current status of promising MS-based metabolomics strategies and their emerging roles, as well as possible challenges.",book:{id:"8400",slug:"molecular-medicine",title:"Molecular Medicine",fullTitle:"Molecular Medicine"},signatures:"Sinem Nalbantoglu",authors:[{id:"147712",title:"Dr.",name:"Sinem",middleName:null,surname:"Nalbantoglu",slug:"sinem-nalbantoglu",fullName:"Sinem Nalbantoglu"}]},{id:"33119",doi:"10.5772/38349",title:"Additive Manufacturing Solutions for Improved Medical Implants",slug:"additive-manufacturing-solutions-for-improved-implants",totalDownloads:8038,totalCrossrefCites:7,totalDimensionsCites:21,abstract:null,book:{id:"1899",slug:"biomedicine",title:"Biomedicine",fullTitle:"Biomedicine"},signatures:"Vojislav Petrovic, Juan Vicente Haro, Jose Ramón Blasco and Luis Portolés",authors:[{id:"116774",title:"Dr.",name:"Vojislav",middleName:null,surname:"Petrovic",slug:"vojislav-petrovic",fullName:"Vojislav Petrovic"},{id:"116777",title:"MSc.",name:"Juan",middleName:"Vicente",surname:"Haro González",slug:"juan-haro-gonzalez",fullName:"Juan Haro González"},{id:"116778",title:"BSc.",name:"José Ramón",middleName:null,surname:"Blasco Puchades",slug:"jose-ramon-blasco-puchades",fullName:"José Ramón Blasco Puchades"},{id:"116779",title:"BSc.",name:"Luís",middleName:null,surname:"Portolés Griñán",slug:"luis-portoles-grinan",fullName:"Luís Portolés Griñán"}]},{id:"33113",doi:"10.5772/33951",title:"Encapsulation and Surface Engineering of Pancreatic Islets: Advances and Challenges",slug:"encapsulation-and-surface-engineering-of-pancreatic-islets-advances-and-challenges-",totalDownloads:3498,totalCrossrefCites:5,totalDimensionsCites:9,abstract:null,book:{id:"1899",slug:"biomedicine",title:"Biomedicine",fullTitle:"Biomedicine"},signatures:"Veronika Kozlovskaya, Oleksandra Zavgorodnya and Eugenia Kharlampieva",authors:[{id:"97932",title:"Prof.",name:"Eugenia",middleName:null,surname:"Kharlampieva",slug:"eugenia-kharlampieva",fullName:"Eugenia Kharlampieva"},{id:"101333",title:"Dr.",name:"Veronika",middleName:null,surname:"Kozlovskaya",slug:"veronika-kozlovskaya",fullName:"Veronika Kozlovskaya"},{id:"135852",title:"MSc.",name:"Oleksandra",middleName:null,surname:"Zavgorodnya",slug:"oleksandra-zavgorodnya",fullName:"Oleksandra Zavgorodnya"}]},{id:"33114",doi:"10.5772/38852",title:"In-Situ Forming Biomimetic Hydrogels for Tissue Regeneration",slug:"in-situ-forming-biomimetic-hydrogels-for-tissue-regeneration",totalDownloads:4053,totalCrossrefCites:2,totalDimensionsCites:9,abstract:null,book:{id:"1899",slug:"biomedicine",title:"Biomedicine",fullTitle:"Biomedicine"},signatures:"Rong Jin",authors:[{id:"120160",title:"Dr.",name:"Rong",middleName:null,surname:"Jin",slug:"rong-jin",fullName:"Rong Jin"}]},{id:"61418",doi:"10.5772/intechopen.77154",title:"Effect of Infra-Low Frequency Neurofeedback on Infra-Slow EEG Fluctuations",slug:"effect-of-infra-low-frequency-neurofeedback-on-infra-slow-eeg-fluctuations",totalDownloads:2125,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"Infra-low frequency neurofeedback (ILF NF) has been proposed as an alternative or complementary treatment method. Previous studies have reported a good effect of ILF training on the subjective perception of positive psychological changes after training. Here we study whether the objective physiological parameters reflecting the brain function also change under the influence of ILF NF. Eight participants 21–50 years of age with no history of neurological or psychiatric diseases, but reporting about some physiological or psychological complaints, performed 20 sessions of infra-low frequency neurofeedback training. EEG in visual Go/NoGo test was recorded before the course of Neurofeedback and after its completion. The spectral power of slow EEG oscillations in the post-training recording was compared with the pretraining baseline. Along with remission of the clinical complaints, significant increase of spectral power in 0–0.5 Hz frequency band was observed in all eight participants in the post-training EEG patterns compared to the pretraining EEG, which may be linked to the improvement in the metabolic balance in the brain tissue and increasing efficiency of compensatory mechanisms in the stress regulation systems.",book:{id:"6632",slug:"biofeedback",title:"Biofeedback",fullTitle:"Biofeedback"},signatures:"Vera A. Grin-Yatsenko, Valery A. Ponomarev, Olga Kara, Bernhard\nWandernoth, Mark Gregory, Valentina A. Ilyukhina and Juri D.\nKropotov",authors:[{id:"234121",title:"Ph.D.",name:"Vera",middleName:null,surname:"Grin-Yatsenko",slug:"vera-grin-yatsenko",fullName:"Vera Grin-Yatsenko"},{id:"238431",title:"Prof.",name:"Valery",middleName:null,surname:"Ponomarev",slug:"valery-ponomarev",fullName:"Valery Ponomarev"},{id:"238434",title:"Dr.",name:"Olga",middleName:null,surname:"Kara",slug:"olga-kara",fullName:"Olga Kara"},{id:"238435",title:"Dr.",name:"Bernhard",middleName:null,surname:"Wandernoth",slug:"bernhard-wandernoth",fullName:"Bernhard Wandernoth"},{id:"238437",title:"Dr.",name:"Mark",middleName:null,surname:"Gregory",slug:"mark-gregory",fullName:"Mark Gregory"},{id:"238439",title:"Prof.",name:"Valentina",middleName:null,surname:"Ilyukhina",slug:"valentina-ilyukhina",fullName:"Valentina Ilyukhina"},{id:"238441",title:"Prof.",name:"Juri",middleName:null,surname:"Kropotov",slug:"juri-kropotov",fullName:"Juri Kropotov"}]}],mostDownloadedChaptersLast30Days:[{id:"67272",title:"Introductory Chapter: Insight into the OMICS Technologies and Molecular Medicine",slug:"introductory-chapter-insight-into-the-omics-technologies-and-molecular-medicine",totalDownloads:1485,totalCrossrefCites:2,totalDimensionsCites:2,abstract:null,book:{id:"8400",slug:"molecular-medicine",title:"Molecular Medicine",fullTitle:"Molecular Medicine"},signatures:"Sinem Nalbantoglu and Abdullah Karadag",authors:[{id:"147712",title:"Dr.",name:"Sinem",middleName:null,surname:"Nalbantoglu",slug:"sinem-nalbantoglu",fullName:"Sinem Nalbantoglu"}]},{id:"68486",title:"Metabolomics: Basic Principles and Strategies",slug:"metabolomics-basic-principles-and-strategies",totalDownloads:2621,totalCrossrefCites:19,totalDimensionsCites:30,abstract:"Metabolomics is the study of metabolome within cells, biofluids, tissues, or organisms to comprehensively identify and quantify all endogenous and exogenous low-molecular-weight (<1 kDa) small molecules/metabolites in a biological system in a high-throughput manner. Metabolomics has several applications in health and disease including precision/personalized medicine, single cell, epidemiologic population studies, metabolic phenotyping, and metabolome-wide association studies (MWAS), precision metabolomics, and in combination with other omics disciplines as integrative omics, biotechnology, and bioengineering. Mass spectrometry (MS)-based metabolomics/lipidomics provides a useful approach for both identification of disease-related metabolites in biofluids or tissue and also encompasses classification and/or characterization of disease or treatment-associated molecular patterns generated from metabolites. Here, in this review, we provide a brief overview of the current status of promising MS-based metabolomics strategies and their emerging roles, as well as possible challenges.",book:{id:"8400",slug:"molecular-medicine",title:"Molecular Medicine",fullTitle:"Molecular Medicine"},signatures:"Sinem Nalbantoglu",authors:[{id:"147712",title:"Dr.",name:"Sinem",middleName:null,surname:"Nalbantoglu",slug:"sinem-nalbantoglu",fullName:"Sinem Nalbantoglu"}]},{id:"62128",title:"Body Mass Index and Colorectal Cancer",slug:"body-mass-index-and-colorectal-cancer",totalDownloads:1133,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Colorectal cancer (CRC) is one of the most common cancers in the world. Obesity is an established risk factor for colorectal carcinogenesis. Many epidemiological and experimental studies support this link and tumor-promoting effects of obesity. Body mass index (BMI) is a marker of general obesity. Obesity is also a global health problem and is defined by World Health Organization as BMI > 30 kg/m2. In this chapter, we give a general review about the mechanisms of obesity on colorectal carcinogenesis and the effects of obesity on clinical outcomes such as disease-free survival (DFS), progression-free survival (PFS) and overall survival (OS), in adjuvant setting and metastatic disease, respectively.",book:{id:"7159",slug:"body-mass-index-and-health",title:"Body-mass Index and Health",fullTitle:"Body-mass Index and Health"},signatures:"Nuri Faruk Aykan, Mehmet Artac and Tahsin Özatli",authors:[{id:"94089",title:"Prof.",name:"Nuri Faruk",middleName:null,surname:"Aykan",slug:"nuri-faruk-aykan",fullName:"Nuri Faruk Aykan"},{id:"257212",title:"Prof.",name:"Mehmet",middleName:null,surname:"Artaç",slug:"mehmet-artac",fullName:"Mehmet Artaç"},{id:"257213",title:"Dr.",name:"Tahsin",middleName:null,surname:"Özatlı",slug:"tahsin-ozatli",fullName:"Tahsin Özatlı"}]},{id:"65402",title:"Pharmacogenetics and Cancer Treatment: Progress and Prospects",slug:"pharmacogenetics-and-cancer-treatment-progress-and-prospects",totalDownloads:1587,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The response of cancer patients to chemotherapy follows a very heterogeneous pattern. Pharmacogenetics is the study of inherited differences in interindividual drug disposition and effects, with the goal of selecting the optimal drug therapy and dosage for each patient. Pharmacogenetics for cancer treatment is very significant, as cancer therapies exhibit severe systemic toxicity and unpredictable efficacy. There is presence of genetic polymorphisms in the genes which code for the metabolic enzymes and cellular targets for the majority of chemotherapy agents, but to predict the outcome of chemotherapy in patients is not currently possible for most treatments. A greater understanding of the genetic determinants of drug response can revolutionize the use of many medications. By identifying the patients at risk for severe toxicity, or those likely to benefit from a particular treatment, individualized cancer therapy can be achieved for most cancer patients. The prediction of cancer treatment outcome based on gene polymorphisms is becoming possible for many classes of chemotherapy agents, and the most clinically significant examples of chemotherapy agents are discussed in the chapter. However, further studies are needed in well characterized and larger cancer populations with proper validation of pharmacogenetic markers in experimental settings before application in clinical routine diagnostics.",book:{id:"8400",slug:"molecular-medicine",title:"Molecular Medicine",fullTitle:"Molecular Medicine"},signatures:"Munindra Ruwali",authors:[{id:"245866",title:"Dr.",name:"Munindra",middleName:null,surname:"Ruwali",slug:"munindra-ruwali",fullName:"Munindra Ruwali"}]},{id:"62138",title:"Body Mass Index (BMI) and Anthropometric Measurement of the Developing Fetus",slug:"body-mass-index-bmi-and-anthropometric-measurement-of-the-developing-fetus",totalDownloads:1040,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Medical and scientific study of the measurements and size of the human body is known as anthropometry. In anthropometry, body mass index (BMI) is one of the best indirect methods for the estimation of body fat and mass. Other methods of indirect methods include weight, stature, and abdominal circumference. Direct methods include total body water, total body counting, and criterion methods include body density. Other factors like the size and weight of the mother also influence the size and mass of the body. An earlier work was conducted by K.L. Mukherjee on the systemic anthropometric measurements of the aborted human fetus. The following chapter will deal with the importance of parental and fetal BMI and its influence on the development of the fetus at varying stages of development and their relationship with anthropometric measurements.",book:{id:"7159",slug:"body-mass-index-and-health",title:"Body-mass Index and Health",fullTitle:"Body-mass Index and Health"},signatures:"Niranjan Bhattacharya and Priyodarshi Sengupta",authors:[{id:"245970",title:"Prof.",name:"Niranjan",middleName:null,surname:"Bhattacharya",slug:"niranjan-bhattacharya",fullName:"Niranjan Bhattacharya"},{id:"252992",title:"Mr.",name:"Priyodarshi",middleName:null,surname:"Sengupta",slug:"priyodarshi-sengupta",fullName:"Priyodarshi Sengupta"}]}],onlineFirstChaptersFilter:{topicId:"169",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:8,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:286,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:9,numberOfPublishedChapters:101,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:11,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:1,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:"May 14th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:8,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:10,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",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,editorialBoard:[{id:"13633",title:"Prof.",name:"Abdelhamid",middleName:null,surname:"Mellouk",slug:"abdelhamid-mellouk",fullName:"Abdelhamid Mellouk",profilePictureURL:"https://mts.intechopen.com/storage/users/13633/images/1567_n.jpg",institutionString:null,institution:{name:"Paris 12 Val de Marne University",institutionURL:null,country:{name:"France"}}},{id:"109268",title:"Dr.",name:"Ali",middleName:null,surname:"Al-Ataby",slug:"ali-al-ataby",fullName:"Ali Al-Ataby",profilePictureURL:"https://mts.intechopen.com/storage/users/109268/images/7410_n.jpg",institutionString:null,institution:{name:"University of Liverpool",institutionURL:null,country:{name:"United Kingdom"}}},{id:"3807",title:"Dr.",name:"Carmelo",middleName:"Jose Albanez",surname:"Bastos-Filho",slug:"carmelo-bastos-filho",fullName:"Carmelo Bastos-Filho",profilePictureURL:"https://mts.intechopen.com/storage/users/3807/images/624_n.jpg",institutionString:null,institution:{name:"Universidade de Pernambuco",institutionURL:null,country:{name:"Brazil"}}},{id:"38850",title:"Dr.",name:"Efren",middleName:null,surname:"Gorrostieta Hurtado",slug:"efren-gorrostieta-hurtado",fullName:"Efren Gorrostieta Hurtado",profilePictureURL:"https://mts.intechopen.com/storage/users/38850/images/system/38850.jpg",institutionString:null,institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},{id:"239041",title:"Prof.",name:"Yang",middleName:null,surname:"Yi",slug:"yang-yi",fullName:"Yang Yi",profilePictureURL:"https://mts.intechopen.com/storage/users/239041/images/system/239041.jpeg",institutionString:"Virginia Tech",institution:{name:"Virginia Tech",institutionURL:null,country:{name:"United States of America"}}}]},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",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,editorialBoard:[{id:"13818",title:"Dr.",name:"Asim",middleName:null,surname:"Bhatti",slug:"asim-bhatti",fullName:"Asim Bhatti",profilePictureURL:"https://mts.intechopen.com/storage/users/13818/images/system/13818.jpg",institutionString:null,institution:{name:"Deakin University",institutionURL:null,country:{name:"Australia"}}},{id:"151889",title:"Dr.",name:"Joao Luis Garcia",middleName:null,surname:"Rosa",slug:"joao-luis-garcia-rosa",fullName:"Joao Luis Garcia Rosa",profilePictureURL:"https://mts.intechopen.com/storage/users/151889/images/4861_n.jpg",institutionString:null,institution:{name:"University of Sao Paulo",institutionURL:null,country:{name:"Brazil"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",institutionURL:null,country:{name:"Turkey"}}}]},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",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,editorialBoard:[{id:"1177",title:"Prof.",name:"Antonio",middleName:"J. 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He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,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",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,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},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. 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Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"351159",title:"BSc.",name:"Kalum J.",middleName:null,surname:"Ost",slug:"kalum-j.-ost",fullName:"Kalum J. Ost",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}},{id:"325029",title:"Dr.",name:"Prem Chand",middleName:null,surname:"Jain",slug:"prem-chand-jain",fullName:"Prem Chand Jain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Shiv Nadar University",country:{name:"India"}}},{id:"357275",title:"Dr.",name:"Thomas",middleName:null,surname:"Mih",slug:"thomas-mih",fullName:"Thomas Mih",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Buea",country:{name:"Cameroon"}}},{id:"305305",title:"Dr.",name:"Arturo Yosimar",middleName:null,surname:"Jaen-Cuellar",slug:"arturo-yosimar-jaen-cuellar",fullName:"Arturo Yosimar Jaen-Cuellar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"305315",title:"Dr.",name:"David Alejandro",middleName:null,surname:"Elvira-Ortiz",slug:"david-alejandro-elvira-ortiz",fullName:"David Alejandro Elvira-Ortiz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}},{id:"344374",title:"Dr.",name:"Manuel",middleName:null,surname:"Toledano-Ayala",slug:"manuel-toledano-ayala",fullName:"Manuel Toledano-Ayala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Autonomous University of Queretaro",country:{name:"Mexico"}}}]}},subseries:{item:{id:"18",type:"subseries",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11414,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,series:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983"},editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",slug:"arli-aditya-parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",slug:"cesar-lopez-camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",slug:"shymaa-enany",fullName:"Shymaa Enany",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRqB9QAK/Profile_Picture_1626163237970",institutionString:null,institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]},onlineFirstChapters:{paginationCount:9,paginationItems:[{id:"81493",title:"Rust Disease Classification Using Deep Learning Based Algorithm: The Case of Wheat",doi:"10.5772/intechopen.104426",signatures:"Shivani Sood, Harjeet Singh and Suruchi Jindal",slug:"rust-disease-classification-using-deep-learning-based-algorithm-the-case-of-wheat",totalDownloads:35,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Food Systems Resilience",coverURL:"https://cdn.intechopen.com/books/images_new/10897.jpg",subseries:{id:"91",title:"Sustainable Economy and Fair Society"}}},{id:"81428",title:"Observatory of Sustainable Development in Postgraduate Study Programs in Baja California",doi:"10.5772/intechopen.104641",signatures:"Rodolfo Martinez-Gutierrez, Maria Marcela Solis-Quinteros, Maria Esther Ibarra-Estrada and Angel Ernesto Jimenez-Bernardino",slug:"observatory-of-sustainable-development-in-postgraduate-study-programs-in-baja-california",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Globalization and Sustainability - Recent Advances, New Perspectives and Emerging Issues",coverURL:"https://cdn.intechopen.com/books/images_new/11476.jpg",subseries:{id:"91",title:"Sustainable Economy and Fair Society"}}},{id:"81235",title:"Global Food System Transformation for Resilience",doi:"10.5772/intechopen.102749",signatures:"Jasper Okoro Godwin Elechi, Ikechukwu U. 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Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment"},{id:"5",title:"Parasitic Infectious Diseases",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology"},{id:"6",title:"Viral Infectious Diseases",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 15th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:286,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRqB9QAK/Profile_Picture_1626163237970",institutionString:null,institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"onlineFirst.detail",path:"/online-first/81681",hash:"",query:{},params:{id:"81681"},fullPath:"/online-first/81681",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()