\\n\\n
IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\\n\\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/132"}},components:[{type:"htmlEditorComponent",content:'With the desire to make book publishing more relevant for the digital age and offer innovative Open Access publishing options, we are thrilled to announce the launch of our new publishing format: IntechOpen Book Series.
\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"10549",leadTitle:null,fullTitle:"Preclinical Animal Modeling in Medicine",title:"Preclinical Animal Modeling in Medicine",subtitle:null,reviewType:"peer-reviewed",abstract:"The results of preclinical animal research have been successfully implemented in various medical and biological practices. The use of animals in medicine is based on significant anatomical, physiological, and molecular similarities between humans and animals. Particularly, mammals that have vast biological commonalities with humans represent not only a valuable model to explore the mechanisms of varied human diseases, but also to define new diagnostic and treatment strategies. This book covers broad but important aspects of animal modeling for scientific medicine as well as for translational systems and biological sciences. Alternative methods such as cell culture and in vitro experiments that do not require the sacrifice of an animal are encouraged for scientific and medical studies.",isbn:"978-1-83968-805-8",printIsbn:"978-1-83968-804-1",pdfIsbn:"978-1-83968-806-5",doi:"10.5772/intechopen.92923",price:139,priceEur:155,priceUsd:179,slug:"preclinical-animal-modeling-in-medicine",numberOfPages:304,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"9604117cecaa0ae107ab2d03a4463148",bookSignature:"Enkhsaikhan Purevjav, Joseph F. Pierre and Lu Lu",publishedDate:"March 9th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/10549.jpg",numberOfDownloads:2493,numberOfWosCitations:0,numberOfCrossrefCitations:3,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:7,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:10,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 15th 2020",dateEndSecondStepPublish:"December 2nd 2020",dateEndThirdStepPublish:"January 31st 2021",dateEndFourthStepPublish:"April 21st 2021",dateEndFifthStepPublish:"June 20th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"231585",title:"Prof.",name:"Enkhsaikhan",middleName:null,surname:"Purevjav",slug:"enkhsaikhan-purevjav",fullName:"Enkhsaikhan Purevjav",profilePictureURL:"https://mts.intechopen.com/storage/users/231585/images/system/231585.jpg",biography:"Dr. Enkhsaikhan Purevjav earned her MD from the Leningrad Pediatric Medical Institute (LMPI), Russia in 1989, followed by an internship and residency in pediatrics at the Mongolian National Medical University, a fellowship in pediatric cardiology at LPMI, and a Ph.D. in Medical Genetics and Molecular Biology from Shimane Medical University, Japan. Dr. Purevjav joined Baylor College of Medicine and Texas Children’s Hospital as a postdoctoral trainee and instructor and then Cincinnati Children’s Hospital Medical Center as an assistant professor. She currently works as an associate professor at the University of Tennessee Health Science Center where she continues to study the genetics of heart diseases, specifically focusing on pediatric cardiomyopathies and arrhythmias.",institutionString:"University of Tennessee Health Science Center",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Tennessee Health Science Center",institutionURL:null,country:{name:"United States of America"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"337466",title:"Assistant Prof.",name:"Joseph F.",middleName:null,surname:"Pierre",slug:"joseph-f.-pierre",fullName:"Joseph F. Pierre",profilePictureURL:"https://mts.intechopen.com/storage/users/337466/images/system/337466.jpg",biography:"Dr. Joseph F. Pierre is currently an Assistant Professor of Nutritional Sciences and Surgery, University of Wisconsin-Madison. The Pierre lab addresses a range of basic, translational, and clinical research questions focused on the gastrointestinal microbiome, nutrition, and gut physiology and disease. Dr. Pierre utilizes experimental models that include bariatric surgery, parenteral and enteral nutrition, gnotobiotics, and organoid approaches. Where relevant, his research examines microbiome community composition and function to investigate host-microbial interactions. Dr. Pierre received his BS in Natural Science and Ph.D. in Nutritional Sciences from the University of Wisconsin-Madison before completing a postdoc fellowship in Gastroenterology, Hepatology, and Nutrition at the University of Chicago. He holds an adjunct faculty position at the University of Tennessee Health Science Center within the College of Medicine.",institutionString:"University of Tennessee Health Science Center",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Tennessee Health Science Center",institutionURL:null,country:{name:"United States of America"}}},coeditorTwo:{id:"346043",title:"Prof.",name:"Lu",middleName:null,surname:"Lu",slug:"lu-lu",fullName:"Lu Lu",profilePictureURL:"https://mts.intechopen.com/storage/users/346043/images/system/346043.png",biography:"Dr. Lu Lu is a professor in the Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center (UTHSC). His research focuses on the examination of genetic effects on complex traits. He and his colleagues have developed large resources for the study of systems genetics that include the largest mouse genetic reference population, which includes BXD recombinant inbred lines, high-density genotypes, thousands of phenotypes, hundreds of transcriptomic data sets, and whole-genome sequence for all 152 inbred BXD strains. All these resources provide great power for genetic analysis of complex traits and are being used by many researchers for their studies of polygenetic diseases. As Principal Investigator, he has been funded by seven NIH R01 grants and has published ~200 science papers within the last seventeen years.",institutionString:"University of Tennessee Health Science Center",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"University of Tennessee Medical Center",institutionURL:null,country:{name:"United States of America"}}},coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"694",title:"Genetic Engineering",slug:"engineering-biomedical-engineering-genetic-engineering"}],chapters:[{id:"76560",title:"Recombinant Inbred Mice as Models for Experimental Precision Medicine and Biology",doi:"10.5772/intechopen.96173",slug:"recombinant-inbred-mice-as-models-for-experimental-precision-medicine-and-biology",totalDownloads:176,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Recombinant inbred rodents form immortal genome-types that can be resampled deeply at many stages, in both sexes, and under multiple experimental conditions to model genome-environment interactions and to test genome-phenome predictions. This allows for experimental precision medicine, for which sophisticated causal models of complex interactions among DNA variants, phenotype variants at many levels, and innumerable environmental factors are required. Large families and populations of isogenic lines of mice and rats are now available and have been used across fields of biology. We will use the BXD recombinant inbred family and their derived diallel cross population as an example for predictive, experimental precision medicine and biology.",signatures:"David G. Ashbrook and Lu Lu",downloadPdfUrl:"/chapter/pdf-download/76560",previewPdfUrl:"/chapter/pdf-preview/76560",authors:[{id:"337602",title:"Assistant Prof.",name:"David G.",surname:"Ashbrook",slug:"david-g.-ashbrook",fullName:"David G. Ashbrook"},{id:"337603",title:"Prof.",name:"Lu",surname:"Lu",slug:"lu-lu",fullName:"Lu Lu"}],corrections:null},{id:"80284",title:"Parenteral Nutrition Modeling and Research Advances",doi:"10.5772/intechopen.101692",slug:"parenteral-nutrition-modeling-and-research-advances",totalDownloads:84,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Parenteral nutrition (PN) provides nutritional support intravenously to individuals who have gastrointestinal (GI) failure or contraindication to enteral feeding. Since the initial development of PN, researchers have developed specialized formulas with complete macronutrients, micronutrients, vitamins, minerals, and electrolytes to support patients’ metabolic needs. These formulas prevent malnutrition and optimize patient health, especially under long-term feeding circumstances. Although PN is commonly used and essential in preterm and malnourished patients, complications associated with PN feeding include gastrointestinal defects, infection, and other metabolic abnormalities such as liver injury and brain related disorders. In this chapter, we highlight an overview of PN and its association with abnormalities of microbiome composition as well as with gastrointestinal (GI), immune, hepatic, and neuronal disfunction. Within the gut, PN influences the number and composition of gut-associated lymphoid tissue (GALT) cells, altering adaptive immune responses. PN also modulates intestinal epithelium cell turnover, secretions, and gut barrier function, as well as the composition of the intestinal microbiome leading to changes in gut permeability. Collectively, these changes result in increased susceptibility to infection and injury. Here, we highlight animal models used to examine parenteral nutrition, changes that occur to the major organ systems, and recent advancement in using enteric nervous system (ENS) neuropeptides or microbially derived products during PN, which may improve GI, immune cell, hepatic, and neuronal function.",signatures:"Roshan Kumari, Lydia M. Henry and Joseph F. Pierre",downloadPdfUrl:"/chapter/pdf-download/80284",previewPdfUrl:"/chapter/pdf-preview/80284",authors:[{id:"337466",title:"Assistant Prof.",name:"Joseph F.",surname:"Pierre",slug:"joseph-f.-pierre",fullName:"Joseph F. Pierre"},{id:"427563",title:"Ms.",name:"Lydia M.",surname:"Henry",slug:"lydia-m.-henry",fullName:"Lydia M. Henry"},{id:"427564",title:"Mrs.",name:"Roshan",surname:"Kumari",slug:"roshan-kumari",fullName:"Roshan Kumari"}],corrections:null},{id:"75629",title:"Gut Feeding the Brain: Drosophila Gut an Animal Model for Medicine to Understand Mechanisms Mediating Food Preferences",doi:"10.5772/intechopen.96503",slug:"gut-feeding-the-brain-em-drosophila-em-gut-an-animal-model-for-medicine-to-understand-mechanisms-med",totalDownloads:359,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Fruit fly, Drosophila melanogaster is a most powerful animal model for exploring fundamental biological processes and modeling molecular and cellular aspects of human diseases. It provides the flexibility and tool box with which scientists can experimentally manipulate and study behavior as well as gene expression in specific, defined population of cells in their normal tissue contexts. The utility and increasing value of a sophisticated genetic system of flies, the tool box available for studying physiological function, functional imaging, neural circuitry from gut to brain, taste receptors expression and controlling gene expression by determining the specific cells in the intestine, makes fly gut the most useful tissue for studying the regulation of feeding behavior under changing internal state. To understand the intestine and its connectivity with the brain, Drosophila has proved an ideal model organism for studying gut brain axis aspects of human metabolic diseases. Various markers and fly lines are available to characterize the expression of transgenes in the intestine. The newly generated genetic tools aim to streamline the design of experiments to target specific cells in intestine for genetic manipulations based on their type and location within physiologically specialized intestinal regions. This chapter will be useful for understanding post-ingestive sensing system that mediate food preferences and to investigate fundamental biological processes and model human diseases at the level of single cells in the fly gut. Furthermore, the utility of adult fly gut can be extended to the study of dietary and environmental factors relevant to health and disease by screening for cells and micro circuits stimulated by internal state or the consumption of various nutrients.",signatures:"Zoha Sadaqat, Shivam Kaushik and Pinky Kain",downloadPdfUrl:"/chapter/pdf-download/75629",previewPdfUrl:"/chapter/pdf-preview/75629",authors:[{id:"306728",title:"Dr.",name:"Pinky",surname:"Kain",slug:"pinky-kain",fullName:"Pinky Kain"},{id:"335402",title:"Dr.",name:"Zoha",surname:"Sadaqat",slug:"zoha-sadaqat",fullName:"Zoha Sadaqat"},{id:"345539",title:"Mr.",name:"Shivam",surname:"Kaushik",slug:"shivam-kaushik",fullName:"Shivam Kaushik"}],corrections:null},{id:"75702",title:"Duchenne Muscular Dystrophy Animal Models",doi:"10.5772/intechopen.96738",slug:"duchenne-muscular-dystrophy-animal-models",totalDownloads:257,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Duchenne muscular dystrophy is a complex and severe orphan disease. It develops when the organism lacks the expression of dystrophin - a large structural protein. Dystrophin is transcribed from the largest gene in the human genome. At the moment, there is no cure available. Dozens of groups all over the world search for cure. Animal models are an important component of both the fundamental research and therapy development. Many animal models reproducing the features of disease were created and actively used since the late 80’s until present. The species diversity spans from invertebrates to primates and the genetic diversity of these models spans from single mutations to full gene deletions. The models are often non-interchangeable; while one model may be used for particular drug design it may be useless for another. Here we describe existing models, discuss their advantages and disadvantages and potential applications for research and therapy development.",signatures:"Tatiana V. Egorova, Ivan I. Galkin, Yulia V. Ivanova and Anna V. Polikarpova",downloadPdfUrl:"/chapter/pdf-download/75702",previewPdfUrl:"/chapter/pdf-preview/75702",authors:[{id:"340316",title:"M.Sc.",name:"Tatiana V.",surname:"Egorova",slug:"tatiana-v.-egorova",fullName:"Tatiana V. Egorova"},{id:"340335",title:"Dr.",name:"Anna V.",surname:"Polikarpova",slug:"anna-v.-polikarpova",fullName:"Anna V. Polikarpova"},{id:"340337",title:"Dr.",name:"Ivan I.",surname:"Galkin",slug:"ivan-i.-galkin",fullName:"Ivan I. Galkin"},{id:"346667",title:"MSc.",name:"Yulia V.",surname:"Ivanova",slug:"yulia-v.-ivanova",fullName:"Yulia V. Ivanova"}],corrections:null},{id:"79211",title:"Left Ventricular Noncompaction Cardiomyopathy: From Clinical Features to Animal Modeling",doi:"10.5772/intechopen.101085",slug:"left-ventricular-noncompaction-cardiomyopathy-from-clinical-features-to-animal-modeling",totalDownloads:143,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Cardiomyopathy or disease of the heart muscle involves abnormal enlargement and a thickened, stiff, or spongy-like appearance of the myocardium. As a result, the function of the myocardium is weakened and does not sufficiently pump blood throughout the body nor maintain a normal pumping rhythm, leading to heart failure. The main types of cardiomyopathies include dilated hypertrophic, restrictive, arrhythmogenic, and noncompaction cardiomyopathy. Abnormal trabeculations of the myocardium in the left ventricle are classified as left ventricular noncompaction cardiomyopathy (LVNC). Myocardial noncompaction most frequently is observed at the apex of the left ventricle and can be associated with chamber dilation or muscle hypertrophy, systolic or diastolic dysfunction, or both, or various forms of congenital heart disease. Animal models are incredibly important for uncovering the etiology and pathogenesis involved in this disease. This chapter will describe the clinical and pathological features of LVNC in humans and present the animal models that have been used for the study of the genetic basis and pathogenesis of this disease.",signatures:"Enkhsaikhan Purevjav, Michelle Chintanaphol, Buyan-Ochir Orgil, Nelly R. Alberson and Jeffrey A. Towbin",downloadPdfUrl:"/chapter/pdf-download/79211",previewPdfUrl:"/chapter/pdf-preview/79211",authors:[{id:"231585",title:"Prof.",name:"Enkhsaikhan",surname:"Purevjav",slug:"enkhsaikhan-purevjav",fullName:"Enkhsaikhan Purevjav"},{id:"345566",title:"Prof.",name:"Jeffrey A.",surname:"Towbin",slug:"jeffrey-a.-towbin",fullName:"Jeffrey A. Towbin"},{id:"425381",title:"B.Sc.",name:"Michelle",surname:"Chintanaphol",slug:"michelle-chintanaphol",fullName:"Michelle Chintanaphol"},{id:"425382",title:"Dr.",name:"Buyan-Ochir",surname:"Orgil",slug:"buyan-ochir-orgil",fullName:"Buyan-Ochir Orgil"},{id:"425383",title:"MSc.",name:"Nelly R.",surname:"Alberson",slug:"nelly-r.-alberson",fullName:"Nelly R. Alberson"}],corrections:null},{id:"76811",title:"Experimental Animal Models of Cerebral Ischemic Reperfusion Injury",doi:"10.5772/intechopen.97592",slug:"experimental-animal-models-of-cerebral-ischemic-reperfusion-injury",totalDownloads:50,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Restitution of blood flow in the ischemic region helps liberate cells from mortification in any tissue or organ. Reperfusion post cerebral ischemia worsen the condition and lead to “cerebral reperfusion injury”. In cerebral reperfusion injury, significant changes observed are infarct size, behavioural deficits, hematoma formation, inflammatory mediators, and oxidative stress markers representing the extent of brain injury. Experimental In vivo models mimicking pathological and neurological processes are key tools in researching cerebral reperfusion injury and potential therapeutic agents’ development. This review explains currently used In vivo models like middle cerebral artery occlusion model, emboli stroke model, two-vessel occlusion model of forebrain ischemia, four-vessel occlusion model of forebrain ischemia, photochemical stroke model, collagenase induced brain haemorrhage model, autologous whole blood induced haemorrhage model. This review provides contemplative facts to setup authentic and relevant animal models to study cerebral reperfusion injury.",signatures:"Prabhakar Orsu and Y. Srihari",downloadPdfUrl:"/chapter/pdf-download/76811",previewPdfUrl:"/chapter/pdf-preview/76811",authors:[{id:"341478",title:"Assistant Prof.",name:"Prabhakar",surname:"Orsu",slug:"prabhakar-orsu",fullName:"Prabhakar Orsu"},{id:"414970",title:"Dr.",name:"Y.",surname:"Srihari",slug:"y.-srihari",fullName:"Y. Srihari"}],corrections:null},{id:"76410",title:"Mouse Models of Acute Kidney Injury",doi:"10.5772/intechopen.97523",slug:"mouse-models-of-acute-kidney-injury",totalDownloads:428,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Acute Kidney Injury (AKI) is a poor prognosis in hospitalized patients that is associated with high degree of mortality. AKI is also a major risk factor for development of chronic kidney disease. Despite these serious complications associated with AKI there has not been a great amount of progress made over the last half-century. Here we have outlined and provided details on variety of mouse models of AKI. Some of the mouse models of AKI are renal pedicle clamping (ischemia reperfusion injury), Cisplatin induced nephrotoxicity, sepsis (LPS, cecal slurry, and cecal ligation and puncture), folic acid, and rhabdomyolysis. In this chapter we describe in detail the protocols that are used in our laboratories.",signatures:"Navjot Pabla, Yogesh Scindia, Joseph Gigliotti and Amandeep Bajwa",downloadPdfUrl:"/chapter/pdf-download/76410",previewPdfUrl:"/chapter/pdf-preview/76410",authors:[{id:"345349",title:"Associate Prof.",name:"Aman",surname:"Bajwa",slug:"aman-bajwa",fullName:"Aman Bajwa"},{id:"345350",title:"Dr.",name:"Navjot",surname:"Pabla",slug:"navjot-pabla",fullName:"Navjot Pabla"},{id:"345351",title:"Dr.",name:"Yogesh",surname:"Scindia",slug:"yogesh-scindia",fullName:"Yogesh Scindia"},{id:"351420",title:"Dr.",name:"Joseph",surname:"Gigliotti",slug:"joseph-gigliotti",fullName:"Joseph Gigliotti"}],corrections:null},{id:"75497",title:"Animal Pain Models for Spinal Cord Stimulation",doi:"10.5772/intechopen.96403",slug:"animal-pain-models-for-spinal-cord-stimulation",totalDownloads:242,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Spinal cord stimulation (SCS) is an electrical neuromodulation technique with proven effectiveness and safety for the treatment of intractable chronic pain in humans. Despite its widespread use, the mechanism of action is not fully understood. Animal models of chronic pain, particularly rodent-based, have been adapted to study the effect of SCS on pain-like behavior, as well as on the electrophysiology and molecular biology of neural tissues. This chapter reviews animal pain models for SCS, emphasizing on findings relevant to advancing our understanding of the mechanism of action of SCS, and highlighting the contribution of the animal model to advance clinical outcomes. The models described include those in which SCS has been coupled to neuropathic pain models in rats and sheep based on peripheral nerve injuries, including the chronic constriction injury (CCI) model and the spared nerve injury model (SNI). Other neuropathic pain models described are the spinal nerve ligation (SNL) for neuropathic pain of segmental origin, as well as the chemotherapy-induced and diabetes-induced peripheral neuropathy models. We also describe the use of SCS with inflammatory pain and ischemic pain models.",signatures:"Joseph M. Williams, Courtney A. Kelley, Ricardo Vallejo, David C. Platt and David L. Cedeño",downloadPdfUrl:"/chapter/pdf-download/75497",previewPdfUrl:"/chapter/pdf-preview/75497",authors:[{id:"337591",title:"Ph.D.",name:"David L.",surname:"Cedeño",slug:"david-l.-cedeno",fullName:"David L. Cedeño"},{id:"337596",title:"Dr.",name:"Ricardo",surname:"Vallejo",slug:"ricardo-vallejo",fullName:"Ricardo Vallejo"},{id:"346305",title:"Dr.",name:"Joseph M.",surname:"Williams",slug:"joseph-m.-williams",fullName:"Joseph M. Williams"},{id:"346306",title:"Ms.",name:"Courtney A.",surname:"Kelley",slug:"courtney-a.-kelley",fullName:"Courtney A. Kelley"},{id:"346307",title:"Mr.",name:"David C.",surname:"Platt",slug:"david-c.-platt",fullName:"David C. Platt"}],corrections:null},{id:"76040",title:"An Overview of Glaucoma: Bidirectional Translation between Humans and Pre-Clinical Animal Models",doi:"10.5772/intechopen.97145",slug:"an-overview-of-glaucoma-bidirectional-translation-between-humans-and-pre-clinical-animal-models",totalDownloads:256,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Glaucoma is a multifactorial, polygenetic disease with a shared outcome of loss of retinal ganglion cells and their axons, which ultimately results in blindness. The most common risk factor of this disease is elevated intraocular pressure (IOP), although many glaucoma patients have IOPs within the normal physiological range. Throughout disease progression, glial cells in the optic nerve head respond to glaucomatous changes, resulting in glial scar formation as a reaction to injury. This chapter overviews glaucoma as it affects humans and the quest to generate animal models of glaucoma so that we can better understand the pathophysiology of this disease and develop targeted therapies to slow or reverse glaucomatous damage. This chapter then reviews treatment modalities of glaucoma. Revealed herein is the lack of non-IOP-related modalities in the treatment of glaucoma. This finding supports the use of animal models in understanding the development of glaucoma pathophysiology and treatments.",signatures:"Sophie Pilkinton, T.J. Hollingsworth, Brian Jerkins and Monica M. Jablonski",downloadPdfUrl:"/chapter/pdf-download/76040",previewPdfUrl:"/chapter/pdf-preview/76040",authors:[{id:"342969",title:"Prof.",name:"Monica M.",surname:"Jablonski",slug:"monica-m.-jablonski",fullName:"Monica M. Jablonski"},{id:"342970",title:"Ms.",name:"Sophie",surname:"Pilkinton",slug:"sophie-pilkinton",fullName:"Sophie Pilkinton"},{id:"346686",title:"Dr.",name:"T.J.",surname:"Hollingsworth",slug:"t.j.-hollingsworth",fullName:"T.J. Hollingsworth"},{id:"349145",title:"Dr.",name:"Brian",surname:"Jerkins",slug:"brian-jerkins",fullName:"Brian Jerkins"}],corrections:null},{id:"75476",title:"An Overview of Age-Related Macular Degeneration: Clinical, Pre-Clinical Animal Models and Bidirectional Translation",doi:"10.5772/intechopen.96601",slug:"an-overview-of-age-related-macular-degeneration-clinical-pre-clinical-animal-models-and-bidirectiona",totalDownloads:357,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Age-related macular degeneration (AMD) is a multifactorial disease that results from a complex and unknown interplay among environmental, genetic, and epidemiologic factors. Risk factors include aging, family history, obesity, hypercholesterolemia, and hypertension, along with cigarette smoking, which is the most influential modifiable risk factor. Single nucleotide polymorphisms (SNPs) in numerous genes such as complement factor H (CFH) pose some of the known genetic risks. The pathophysiology in AMD is incompletely understood, but is known to involve oxidative stress, inflammation, dysregulated antioxidants, lipid metabolism, and angiogenesis. Animal models have been integral in expanding our knowledge of AMD pathology. AMD is classified as non-exudative or exudative. Because there is no perfect animal model that recapitulates all aspects of the human disease, rodents, rabbits, and non-human primates offer different advantages and disadvantages to serve as models for various aspects of the disease. Scientific advances have also allowed for the creation of polygenic pre-clinical models that may better represent the complexity of AMD, which will likely expand our knowledge of disease mechanisms and serve as platforms for testing new therapeutics. There have been, and there continues to be, many drugs in the pipeline to treat both exudative and non-exudative AMD. However, Food and Drug Administration (FDA)-approved therapies for exudative AMD that mainly target angiogenic growth factors are the only therapeutics currently being used in the clinics. There remains no FDA-approved therapy for the non-exudative form of this disease. This chapter contains a basic overview and classification of AMD and multiple animal models of AMD are highlighted. We include an overview of both current FDA-approved treatments and those in development. 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Systems",doi:"10.5772/intechopen.79742",slug:"intelligent-robotic-perception-systems",body:'In robotics, perception is understood as a system that endows the robot with the ability to perceive, comprehend, and reason about the surrounding environment. The key components of a perception system are essentially sensory data processing, data representation (environment modeling), and ML-based algorithms, as illustrated in Figure 1. Since
Key modules of a typical robotic perception system: sensory data processing (focusing here on visual and range perception); data representations specific for the tasks at hand; algorithms for data analysis and interpretation (using AI/ML methods); and planning and execution of actions for robot-environment interaction.
Robotic perception is crucial for a robot to make decisions, plan, and operate in real-world environments, by means of numerous functionalities and operations from occupancy grid mapping to object detection. Some examples of robotic perception subareas, including autonomous robot-vehicles, are obstacle detection [2, 3], object recognition [4, 5], semantic place classification [6, 7], 3D environment representation [8], gesture and voice recognition [9], activity classification [10], terrain classification [11], road detection [12], vehicle detection [13], pedestrian detection [14], object tracking [3], human detection [15], and environment change detection [16].
Nowadays, most of robotic perception systems use machine learning (ML) techniques, ranging from classical to deep-learning approaches [17]. Machine learning for robotic perception can be in the form of unsupervised learning, or supervised classifiers using handcrafted features, or deep-learning neural networks (e.g., convolutional neural network (CNN)), or even a combination of multiple methods.
Regardless of the ML approach considered, data from sensor(s) are the key ingredient in robotic perception. Data can come from a single or multiple sensors, usually mounted onboard the robot, but can also come from the infrastructure or from another robot (e.g., cameras mounted on UAVs flying nearby). In multiple-sensors perception, either the same modality or multimodal, an efficient approach is usually necessary to combine and process data from the sensors before an ML method can be employed. Data alignment and calibration steps are necessary depending on the nature of the problem and the type of sensors used.
Sensor-based environment representation/mapping is a very important part of a robotic perception system. Mapping here encompasses both the acquisition of a metric model and its semantic interpretation, and is therefore a synonym of environment/scene representation. This semantic mapping process uses ML at various levels, e.g., reasoning on volumetric occupancy and occlusions, or identifying, describing, and matching optimally the local regions from different time-stamps/models, i.e., not only higher level interpretations. However, in the majority of applications, the primary role of environment mapping is to model data from exteroceptive sensors, mounted onboard the robot, in order to enable reasoning and inference regarding the real-world environment where the robot operates.
Robot perception functions, like localization and navigation, are dependent on the environment where the robot operates. Essentially, a robot is designed to operate in two categories of environments: indoors or outdoors. Therefore, different assumptions can be incorporated in the mapping (representation) and perception systems considering indoor or outdoor environments. Moreover, the sensors used are different depending on the environment, and therefore, the sensory data to be processed by a perception system will not be the same for indoors and outdoors scenarios. An example to clarify the differences and challenges between a mobile robot navigating in an indoor versus outdoor environment is the ground, or terrain, where the robot operates. Most of indoor robots assume that the ground is regular and flat which, in some manner, facilitates the environment representation models; on the other hand, for field (outdoors) robots, the terrain is quite often far from being regular and, as consequence, the environment modeling is itself a challenge and, without a proper representation, the subsequent perception tasks are negatively affected. Moreover, in outdoors, robotic perception has to deal with weather conditions and variations in light intensities and spectra.
Similar scenario-specific differences exist in virtually all use-cases of robotic vision, as exemplified by the 2016 Amazon Picking Challenge participants’ survey [18], requiring complex yet robust solutions, and therefore considered one of the most difficult tasks in the pick-and-place application domain. Moreover, one of the participating teams from 2016 benchmarked a pose estimation method on a warehouse logistics dataset, and found large variations in performance depending on clutter level and object type [2]. Thus, perception systems currently require expert knowledge in order to select, adapt, extend, and fine-tune the various employed components.
Apart from the increased training data sizes and robustness, the end-to-end training aspect of deep-learning (DL) approaches made the development of perception systems easier and more accessible for newcomers, as one can obtain the desired results directly from raw data in many cases, by providing a large number of training examples. The method selection often boils down to obtaining the latest pretrained network from an online repository and fine-tuning it to the problem at hand, hiding all the traditional feature detection, description, filtering, matching, optimization steps behind a relatively unified framework. Unfortunately, at the moment an off-the-shelf DL solution for every problem does not exist, or at least no usable pretrained network, making the need for huge amounts of training data apparent. Therefore, large datasets are a valuable asset for modern AI/ML. A large number of datasets exist for perception tasks as well, with a survey of RGB-D datasets presented by Firman [5] (up-to-date list available online: http://www.michaelfirman.co.uk/RGBDdatasets/), and even tools for synthetically generating sensor-based datasets, e.g., the work presented by Handa et al. [4] which is available online: http://robotvault.bitbucket.org/. However, the danger is to overfit to such benchmarks, as the deployment environment of mobile robots is almost sure to differ from the one used in teaching the robot to perceive and understand the surrounding environment. Thus, the suggestions formulated by Wagstaff [19] still hold true today and should be taken to heart by researchers and practitioners.
As pointed out recently by Sünderhauf et al. [17], robotic perception (also designated robotic vision in [17]) differs from traditional computer vision perception in the sense that, in robotics, the outputs of a perception system will result in decisions and actions in the real world. Therefore, perception is a very important part of a complex, embodied, active, and goal-driven robotic system. As exemplified by Sünderhauf et al. [17], robotic perception has to translate images (or scans, or point-clouds) into actions, whereas most computer vision applications take images and translate the outputs into information.
Among the numerous approaches used in environment representation for mobile robotics, and for autonomous robotic-vehicles, the most influential approach is the occupancy grid mapping [20]. This 2D mapping is still used in many mobile platforms due to its efficiency, probabilistic framework, and fast implementation. Although many approaches use 2D-based representations to model the real world, presently 2.5D and 3D representation models are becoming more common. The main reasons for using higher dimensional representations are essentially twofold: (1) robots are demanded to navigate and make decisions in higher complex environments where 2D representations are insufficient; (2) current 3D sensor technologies are affordable and reliable, and therefore 3D environment representations became attainable. Moreover, the recent advances in software tools, like ROS and PCL, and also the advent of methods like Octomaps, developed by Hornung et al. [21], have been contributing to the increase in 3D-like environment representations.
The advent and proliferation of RGBD sensors has enabled the construction of larger and ever-more detailed 3D maps. In addition, considerable effort has been made in the semantic labeling of these maps, at pixel and voxels levels. Most of the relevant approaches can be split into two main trends: methods designed for online and those designed for offline use. Online methods process data as it is being acquired by the mobile robot, and generate a semantic map incrementally. These methods are usually coupled with a SLAM framework, which ensures the geometric consistency of the map. Building maps of the environment is a crucial part of any robotic system and arguably one of the most researched areas in robotics. Early work coupled mapping with localization as part of the simultaneous localization and mapping (SLAM) problem [22, 23]. More recent work has focused on dealing with or incorporating time-dependencies (short or long term) into the underlying structure, using either grid maps as described in [8, 24], pose-graph representations in [25], and normal distribution transform (NDT) [16, 26].
As presented by Hermans et al. [27], RGBD data are processed by a random forest-based classifier and predict semantic labels; these labels are further regularized through the conditional random field (CRF) method proposed by Krahenbuhl and Koltun [28]. Similarly, McCormac et al. [29] use the elastic fusion SLAM algorithm proposed by Whelan et al. [30] to fuse CNN predictions about the scene in a geometrically consistent map. In the work of Sünderhauf et al. [6], a CNN is used to incrementally build a semantic map, with the aim of extending the number of classes supported by the CNN by complementing it with a series of one-vs-all classifiers which can be trained online. A number of semantic mapping approaches are designed to operate offline, taking as input a complete map of the environment. In the methods described by Ambrus et al. [31, 32] and Armeni et al. [33], large-scale point clouds of indoor buildings are processed, and then, after segmenting the input data, the method’s outputs are in the form of a set of “rooms.” Ambrus et al. [31, 32] use a 2D cell-complex graph-cut approach to compute the segmentation with the main limitation that only single floor buildings can be processed, while Armeni et al. [33] process multifloor structures by detecting the spaces between the walls, ceilings, etc., with the limitation that the building walls have to be axis-aligned (i.e., the Manhattan world assumption). Similarly, in the work proposed by Mura et al. [34], a large point cloud of an indoor structure is processed by making use of a 3D cell-complex structure and outputting a mesh containing the semantic segmentation of the input data. However, the main limitation in [34] is that the approach requires knowledge of the positions from which the environment was scanned when the input data were collected.
The recent work presented by Brucker et al. [7] builds on the segmentation of Ambrus et al. [31, 32] and explores ways of fusing different types of information, such as presence of objects and cues of the types of rooms to obtain a semantic segmentation of the environment. The aim of the work presented by Brucker et al. [7] is to obtain an intuitive and human-like labeling of the environment while at the same time preserving as many of the semantic features as possible. Also, Brucker et al. [7] use a conditional random field (CRF) or the fusion of various heterogeneous data sources and inference is done using Gibbs sampling technique.
Processing sensory data and storing it in a representation of the environment (i.e., a map of the environment) has been and continues to be an active area in robotics research, including autonomous driving system (or autonomous robotic-vehicles). The approaches covered range from metric representations (2D or 3D) to higher semantic or topological maps, and all serve specific purposes key to the successful operation of a mobile robot, such as localization, navigation, object detection, manipulation, etc. Moreover, the ability to construct a geometrically accurate map further annotated with semantic information also can be used in other applications such as building management or architecture, or can be further fed back into a robotic system, increasing the awareness of its surroundings and thus improving its ability to perform certain tasks in human-populated environments (e.g., finding a cup is more likely to be successful if the robot knows a priori which room is the kitchen and how to get there).
Once a robot is (self) localized, it can proceed with the execution of its task. In the case of autonomous mobile manipulators, this involves localizing the objects of interest in the operating environment and grasping them. In a typical setup, the robot navigates to the region of interest, observes the current scene to build a 3D map for collision-free grasp planning and for localizing target objects. The target could be a table or container where something has to be put down, or an object to be picked up. Especially in the latter case, estimating all 6 degrees of freedom of an object is necessary. Subsequently, a motion and a grasp are computed and executed. There are cases where a tighter integration of perception and manipulation is required, e.g., for high-precision manipulation, where approaches like visual servoing are employed. However, in every application, there is a potential improvement for treating perception and manipulation together.
Perception and manipulation are complementary ways to understand and interact with the environment and according to the common coding theory, as developed and presented by Sperry [35], they are also inextricably linked in the brain. The importance of a tight link between perception and action for artificial agents has been recognized by Turing [36], who suggested to equip computers “with the best sense organs that money can buy” and let them learn from gathered experiences until they pass his famous test as described in [37].
The argument for embodied learning and grounding of new information evolved, considering the works of Steels and Brooks [38] and Vernon [39], and more recently in [40], robot perception involves planning and interactive segmentation. In this regard, perception and action reciprocally inform each other, in order to obtain the best results for locating objects. In this context, the localization problem involves segmenting objects, but also knowing their position and orientation relative to the robot in order to facilitate manipulation. The problem of object pose estimation, an important prerequisite for model-based robotic grasping, uses in most of the cases precomputed grasp points as described by Ferrari and Canny [41]. We can categorize this topic in either template/descriptor-based approaches or alternatively local feature/patch-based approaches. In both cases, an ever-recurring approach is that bottom-up data-driven hypothesis generation is followed and verified by top-down concept-driven models. Such mechanisms are assumed, as addressed by Frisby and Stone [42], to be like our human vision system.
The approaches presented in ([43, 44, 45] make use of color histograms, color gradients, depth or normal orientations from discrete object views, i.e., they are examples of vision-/camera-based perception for robots. Vision-based perception systems typically suffer from occlusions, aspect ratio influence, and from problems arising due to the discretization of the 3D or 6D search space. Conversely, in the works of [46, 47, 48], they predict the object pose through voting or a PnP algorithm [49]. The performance usually decreases if the considered object lacks texture and if the background is heavily cluttered. In the works listed above, learning algorithms based on classical ML methods and deep-learning (e.g., CNN) have been employed.
The importance of mobile manipulation and perception areas has been signaled by the (not only academic) interest spurred by events like the Amazon Robotics (formerly Picking) Challenge and the workshop series at the recent major computer vision conferences associated with the SIXD Challenge (http://cmp.felk.cvut.cz/sixd/workshop_2018/). However, current solutions are either heavily tailored to a specific application, requiring specific engineering during deployment, or their generality makes them too slow or imprecise to fulfill the tight time-constraints of industrial applications. While deep learning holds the potential to both improve accuracy (i.e., classification or recognition performance) and also to increase execution speed, more work on transfer learning, in the sense of generalization improvement, is required to apply models learned in real-world and also in unseen (new) environment. Domain adaptation and domain randomization (i.e., image augmentations) seem to be important directions to pursue, and should be explored not only for vision/camera cases, but also for LiDAR-based perception cases.
Usually, in traditional mobile robot manipulation use-cases, the navigation and manipulation capabilities of a robot can be exploited to let the robot gather data about objects autonomously. This can involve, for instance, observing an object of interest from multiple viewpoints in order to allow a better object model estimation, or even in-hand modeling. In the case of perception for mobile robots and autonomous (robot) vehicles, such options are not available; thus, its perception systems have to be trained offline. However, besides AI/ML-based algorithms and higher level perception, for autonomous driving applications, environment representation (including multisensor fusion) is of primary concern [50, 51].
The development of advanced perception for (full) autonomous driving has been a subject of interest since the 1980s, having a period of strong development due to the DARPA Challenges (2004, 2005, and 2007) and the European ELROB challenges (since 2006), and more recently, it has regained considerable interest from automotive and robotics industries and academia. Research in self-driving cars, also referred as autonomous robot-cars, is closely related to mobile robotics and many important works in this field have been published in well-known conferences and journals devoted to robotics. Autonomous driving systems (ADS) comprise, basically, perception (including sensor-fusion and environment modeling/representation), localization, and navigation (path planning, trajectory following, control) and, more recently, cooperation (V2X-based communication technologies). However, the cornerstone of ADS is the perception system because it is involved in most of the essential and necessary tasks for safe driving such as the “segmentation,” detection/recognition, of: road, lane-markings, pedestrians, and other vulnerable road users (e.g., cyclists), other vehicles, traffic signals, crosswalks, and the numerous other types of objects and obstacles that can be found on the roads. In addition to the sensors (e.g., cameras, LIDAR, Radar, “new” solid-state LiDAR technology) and the models used in ADS, the common denominator in a perception system consists of AI/ML algorithms, where deep learning is the leading technique for semantic segmentation and object detection [50].
One of current trends in autonomous vehicles and robotics is the promising idea of incorporating cooperative information, from connected environment/infrastructure, into the decision loop of the robotic perception system. The rationale is to improve robustness and safety by providing complementary information to the perception system, for example: the position and identification of a given object or obstacle on the road could be reported (e.g., broadcasted through a communication network) in advance to an autonomous car, moments before the object/obstacle are within the onboard sensor’s field/range of view.
The EU FP7 Strands project [52] is formed by a consortium of six universities and two industrial partners. The aim of the project is to develop the next generation of intelligent mobile robots, capable of operating alongside humans for extended periods of time. While research into mobile robotic technology has been very active over the last few decades, robotic systems that can operate robustly, for extended periods of time, in human-populated environments remain a rarity. Strands aims to fill this gap and to provide robots that are intelligent, robust, and can provide useful functions in real-world security and care scenarios. Importantly, the extended operation times imply that the robotic systems developed have to be able to cope with an ever-increasing amount of data, as well as to be able to deal with the complex and unstructured real world (Figure 2).
The Strands project (image from
Figure 3 shows a high level overview of the Strands system (with more details in [52]): the mobile robot navigates autonomously between a number of predefined waypoints. A task scheduling mechanism dictates when the robot should visit which waypoints, depending on the tasks the robot has to accomplish on any given day. The perception system consists, at the lowest level, of a module which builds local metric maps at the waypoints visited by the robot. These local maps are updated over time, as the robot revisits the same locations in the environment, and they are further used to segment out the dynamic objects from the static scene. The dynamic segmentations are used as cues for higher level behaviors, such as triggering a data acquisition and object modeling step, whereby the robot navigates around the detected object to collect additional data which are fused into a canonical model of the object [53]. The data can further be used to generate a textured mesh through which a convolutional neural network can be trained which can successfully recognize the object in future observations [31, 32]. The dynamics detected in the environment can be used to detect patterns, either through spectral analysis (i.e., by applying a Fourier transform on the raw detection data), as described in [54], or as part of a multitarget tracking system based on a Rao-Blackwellized particle filter.
The Strands system—Overview.
In addition to the detection and modeling of objects, the Strands perception system also focuses on the detection of people. Beyer et al. [55] present a method to continuously estimate the head-pose of people, while in [15] laser and RGB-D are combined to reliably detect humans and to allow human-aware navigation approaches which make the robot more socially acceptable. Beyer et al. [56] propose a CNN-based system which uses laser scanner data to detect objects; the usefulness of the approach is demonstrated in the case scenario, where it is used to detect wheelchairs and walkers.
Robust perception algorithms that can operate reliably for extended periods of time are one of the cornerstones of the Strands system. However, any algorithm deployed on the robot has to be not only robust, but also able to scale as the robot makes more observations and collects more information about the world. One of the key parts that would enable the successful operation of such a robotic system is a perception stack that is able to continuously integrate observations about the world, extract relevant parts as well as build models that understand and are able to predict what the environment will look like in the future. This spatio-temporal understanding is crucial, as it allows a mobile robot to compress the data acquired during months of autonomous operation into models that can be used to refine the robot’s operation over time. Modeling periodicities in the environment and integrating them into a planning pipeline is further investigated by Fentanes et al. [57], while Santos et al. [58] build spatio-temporal models of the environment and use them for exploration through an information-theoretic approach which predicts the potential gain of observing particular areas of the world at different points in time.
Advanced robots operating in complex and dynamic environments require intelligent perception algorithms to navigate collision-free, analyze scenes, recognize relevant objects, and manipulate them. Nowadays, the perception of mobile manipulation systems often fails if the context changes due to a variation, e.g., in the lightning conditions, the utilized objects, the manipulation area, or the environment. Then, a robotic expert is needed who needs to adjust the parameters of the perception algorithm and the utilized sensor or even select a better method or sensor. Thus, a high-level cognitive ability that is required for operating alongside humans is to continuously improve performance based on introspection. This adaptability to changing situations requires different aspects of machine learning, e.g., storing experiences for life-long learning, generating annotated datasets for supervised learning through user interaction, Bayesian optimization to avoid brute-force search in high-dimensional data, and a unified representation of data and meta-data to facilitate knowledge transfer.
The RobDREAM consortium automated and integrated different aspects of these. Specifically, in the EU’s H2020 RobDREAM project, a mobile manipulator was used to showcase the intuitive programming and simplified setup of robotic applications enabled by automatically tuning task execution pipelines according to user-defined performance criteria.
As illustrated in Figure 4, this was achieved by a semantically annotated logging of perceptual episodic memories that can be queried intuitively in order to analyze the performance of the system in different contexts. Then, a ground truth annotation tool can be used by the user to mark satisfying results, or correct unsatisfying ones, where the suggestions and interactive capabilities of the system reduced the cognitive load of this often complicated task (especially when it comes to 6 DoF pose annotations), as shown in user studies involving computer vision expert and nonexpert users alike.
Schematics of the RobDREAM approach (image based on deliverables of
These annotations are then used by a Bayesian optimization framework to tune the off-the-shelf pipeline to the specific scenarios the robot encounters, thereby incrementally improving the performance of the system. The project did not focus only on perception, but on other key technologies for mobile manipulation as well. Bayesian optimization and other techniques were used to adapt the navigation, manipulation, and grasping capabilities independently of each other and the perception ones. However, the combinatorial complexity of the joint parameter space of all the involved steps was too much even for such intelligent meta-learners. The final industrially relevant use-case demo featured the kitting and mounting of electric cabinet board elements, for which a pose-annotated database was built using two RBD-D cameras and released to the public (http://www.dlr.de/rm/thr-dataset).
When deploying robots in scenarios where they need to share the environment and interact with a large number of people, it is increasingly important that their functionalities are “socially aware.” This means that they respect the personal space (and also privacy) of encountered persons, does not navigate s.t. to cut up cues or groups, etc. Such functionalities go beyond the usual focus of robotics research groups, while academics focusing on user experience typically do not have the means to develop radically new robots. However, the EU’s FP7 program funded such an interdisciplinary project, called SPENCER, driven by an end-user in the aviation industry.
Since around 80% of passenger traffic at different hubs, including Schiphol in Amsterdam, is comprised of passengers who are transferring from one flight to the other, KLM is interested in an efficient management of their movements. For example, when transfer times are short, and finding one’s way in a big airport is difficult due to language and alphabet barriers, people are at risk to losing their connection. In such, and similar cases, robotic assistants that can be deployed and booked flexibly can possibly help alleviate some of the problem. This use-case was explored by the SPENCER demonstrator for smart passengers’ flow management and mobile information provider, but similar solutions are required in other domains as well (Figure 5).
Concept and results of the SPENCER project (images from
The SPENCER consortium integrated the developed technologies onto a robot platform whose task consists in picking up short-transfer time passenger groups at their gate of arrival, identifying them with an onboard boarding pass reader, guiding them to the Schengen barrier and instructing them to use the priority track [59]. Additionally, the platform was equipped with a KLM information kiosk and provides services to passengers in need of help.
In crowded environments such as airports, generating short and safe paths for mobile robots is still difficult. Thus, social scene understanding and long-term prediction of human motion in crowds is not sufficiently solved but highly relevant for all robots that need to quickly navigate in human environments, possibly under temporal constraints. Social scene understanding means, in part, that a reliable tracking and prediction of people’s motion with low uncertainty is available, and that is particularly hard if there are too many occlusions and too many fast changes of motion direction. Classical path planning approaches often result in an overconstrained or overly cautious robot that either fails to produce a feasible and safe path in the crowd, or plans a large and suboptimal detour to avoid people in the scene.
The AUTOCITS (https://www.autocits.eu/) project will carry out a comprehensive assessment of cooperative systems and autonomous driving by deploying real-world Pilots, and will study and review regulations related to automated and autonomous driving. AUTOCITS, cofinanced by the European Union through the Connecting Europe Facility (CEF) Program, aims to facilitate the deployment of autonomous vehicles in European roads, and to use connected/cooperative intelligent transport systems (C-ITS) services to share information between autonomous vehicles and infrastructure, by means of V2V and V2I communication technology, to improve safety and to facilitate the coexistence of autonomous cars in real-world traffic conditions. The AUTOCITS Pilots, involving connected and autonomous vehicles (including autonomous shuttles, i.e., low-speed robot-vehicles), will be deployed in three major European cities in “the Atlantic Corridor of the European Network”: Lisbon (Portugal), Madrid (Spain), and Paris (France).
A number of technologies are involved in AUTOCITS, ranging from the onboard and road-side units (OBU, RSU) to the autonomous driving systems that equip the cars. Today, the autonomous and/or automated driving technology we see on the roads belongs to the levels 3 or 4 (with respect to the SAE’s levels of automation in vehicles). In AUTOCITS, the Pilot’s deployment will be of level 3 to 4. In this context, it is important to say that level 5 cars (i.e., 100% self-driving or full-automated cars: the driving wheels would be unnecessary) operating in real-world roads and streets are still far from reality.
We can say that the perception system is in charge of all tasks related to object and event detection and response (OEDR). Therefore, a perception system—including of course its software modules—is responsible for sensing, understanding, and reasoning about the autonomous car’s surroundings. Within a connected and cooperative environment, connected cars would leverage and complement onboard sensor data by using information from vehicular communication systems (i.e., V2X technology): information from other connected vehicles, from infrastructure, and road users (and vice-versa).
So just how capable is current perception and AI, and how close did/can it get to human-level performance? Szeliski [60] in his introductory book to computer vision argued that traditional vision struggled to reach the performance of a 2-year old child, but today’s CNNs reach super-human classification performance on restricted domains (e.g., in the ImageNet Large Scale Visual Recognition Challenge: http://www.image-net.org/challenges/LSVRC/).
The recent surge and interest in deep-learning methods for perception has greatly improved performance in a variety of tasks such as object detection, recognition, semantic segmentation, etc. One of the main reasons for these advancements is that working on perception systems lends itself easily to offline experimentation on publicly available datasets, and comparison to other methods via standard benchmarks and competitions.
Machine learning (ML) and deep learning (DL), the latter has been one of the most used keywords in some conferences in robotics recently, are consolidated topics embraced by the robotics community nowadays. While one can interpret the filters of CNNs as Gabor filters and assume to be analogous to functions of the visual cortex, currently, deep learning is a purely nonsymbolic approach to AI/ML, and thus not expected to produce “strong” AI/ML. However, even at the current level, its usefulness is undeniable, and perhaps, the most eloquent example comes from the world of autonomous driving which brings together the robotics and the computer vision community. A number of other robotics-related products are starting to be commercially available for increasingly complex tasks such as visual question and answering systems, video captioning and activity recognition, large-scale human detection and tracking in videos, or anomaly detection in images for factory automation.
Diabetes mellitus (DM) is a growing metabolic health problem, and around 346 million people are currently affected by diabetes worldwide, and it is anticipated to double by 2030 [http://www.who.int/mediacentre/factsheets/fs312/en/index.html]. Macro and microvascular complications are the major cause of morbidity and mortality in patients with type 2 diabetes [1]. The important pathology associated with vascular diseases is the formation and accumulation of atherosclerotic plaques leading to the process of atherosclerosis, which ultimately results in the narrowing of the blood vessels [2].
Vascular endothelial cells (ECs) are monolayers of cells that line the inner surface of the luminal vessel wall. It acts as a physical barrier between the bloodstream and the luminal wall [3, 4]. The term endothelial cell dysfunction (ECD) is referred to as loss/dysregulation of EC cells function: such as impairment of the barrier function, reduction of the anti-coagulants, disturbance in the balance between the vasodilation and vasoconstrictions, increased pro-inflammatory response, attachment, and adhesion of leukocytes to the endothelial cell surface, increase the production of pro-oxidant molecules [5, 6]. These points highlight the importance of ECs in maintaining normal vascular homeostasis.
During endothelial injury, oxidized lipids and protein adducts (advanced glycation end products) accumulate in the arterial walls. Then the circulating monocytes adhere to the endothelial cells that express adhesion molecules, such as vascular adhesion molecule-1 (VCAM-1) and selectins, and then migrate into the sub-endothelial space. These monocytes that infiltrate the arterial wall get differentiated into macrophages, and this macrophage also accumulates oxidized lipids to form foam cells. Then the foam cells attract the T-lymphocytes, which in turn induce the proliferation of smooth muscle cells in arterial walls. The entire process leads to the formation of a lipid-rich atherosclerotic lesion and rupture of this lesion leads to vascular infarction. Additionally, increased platelet aggregation and coagulation are also observed due to impaired nitric oxide generation, free-radical generation from the platelet, and elevated levels of plasminogen activator inhibitor. All these factors contribute to the vascular wall occlusion and further increase the risk of cardiovascular events as shown in Figure 1 [2, 7].
Mechanism of AGEs-induced oxidative stress in the formation of atherosclerotic plaque.
Numerous studies have demonstrated the existence of an association between elevated AGE levels and cardiovascular disease in DM patients. In line with this, clinical studies reported that CML and pentosidine levels are increased in the progression of the disease and act as a predictor of cardiovascular events [8, 9, 10, 11, 12, 13, 14]. A fourfold increase in the incidence of coronary artery disease, a 10-fold increase in peripheral vascular disease and a 3–4-fold higher mortality rate with as much as 75% of diabetics ultimately dying from vascular disease have been reported [15].
Vascular complications are classified into two types, namely macrovascular and microvascular. Wherein the large vessels such as arteries and veins get affected in macrovascular disease and microvascular involves small vessels such as capillaries. Chronic hyperglycemia initiates the production of AGE and turns on diabetic vascular complications through elevated production of reactive oxygen species, which instigates various signaling cascades such as Receptor for advanced glycation end product receptor (RAGE) activation, protein kinase C (PKC) and Mitogen activated protein kinases (MAPK) pathways. Macrovascular complications associated with diabetes are arteriosclerotic cardiovascular diseases (ASCVDs) such as coronary heart disease (CHD), peripheral artery disease (PAD), and stroke [2]. Microvascular complications associated with diabetes are diabetic retinopathy (DR), neuropathy, and nephropathy [16, 17] as shown in Figure 2.
AGEs-induced macrovascular and microvascular complications.
The pathogenic mechanisms underlying diabetic nephropathy involve the generation of reactive oxygen species (ROS), accumulation of AGEs, and activation of intracellular signaling molecules such as PKC [18, 19]. Studies suggest that increased formation of AGEs in the vitreous may be involved in the development of diabetic retinopathy by inducing the production of interleukins −6 (IL-6) from retinal Müller cells [20]. AGEs interaction RAGE plays an important role in the pathogenesis of DR [21]. In DR, AGEs (both early and late Amadori products) have been localized to vascular cells (endothelial and pericytes), neurons, glia, and also in the vitreous [22, 23]. Pentosidine and Nε-(carboxymethyl)lysine (CML) levels are increased in aqueous, vitreous, and serum of DR patients when compared with non-diabetic controls especially increased in proliferative DR (PDR) patients than non-proliferative DR (NPDR) and referred to as biomarker for microvascular complications [24, 25] with the progression of DR with decreased visual acuity, emphasizing that AGEs are novel biomarkers/risk markers for type 2 DR [26, 27]. In addition to the above AGEs, methylglyoxal derivative hydroimidazolone was also increased in DR patients [28, 29].
AGEs are a heterogeneous group of compounds generated by non-enzymatic glycation of proteins or lipids with glucose through Amadori rearrangement and its accumulation increases with aging and in diabetes [30]. The term AGEs has been applied to a broad range of advanced glycation end products such as CML, Nε-(carboxymethyl)hydroxylysine, pyrraline, and pentosidine [31]. Among these, CML is the predominant epitope in the AGE adducts detected in tissue proteins of diabetic patients [32, 33, 34]. Its level is found to be increased in serum and aqueous humor of type 2 diabetic patients with retinopathy (DR) [2]. It is also used as a biomarker to predict the progression of different stages of DR. AGEs-stimulated cell response is initiated by its engagement with the receptors present on the cell surface [35]. The most studied AGE receptor is RAGE. Several other AGE receptors identified so far consist of AGE-receptor complex (AGER1/OST-48, AGER2/80 K-H, AGER3/Gal-3), some members of the Toll-like Receptor (TLRs) family (TLR4, TLR2), and scavenging receptors (SRs) family (SR-AI, SR-AII, CD36, LOX-1, FEEL-1, and FEEL-2). The expression of these AGE-activated receptors depends on the cell/tissue type [36].
RAGE and TLRs are well-known Pattern Recognition Receptors (PRRs), which recognize molecules found in pathogens (Pathogen-Associated Molecular Patterns–PAMPs, ex-LPS) or molecules released from damaged or stressed cells such as high mobility group B (HMGB1) and serum amyloid proteins referred as Damage-Associated Molecular patterns (DAMPs) [37]. It is expressed on the surface of various cells, including endothelial, epithelial, and fibroblast mediates multiple signaling pathways such as MAPK kinase and Nuclear factor kappa B (NFĸB), which activate a pro-inflammatory response [38, 39]. Among various TLRs, TLR-2 and 4 are reported to be increased in monocytes of type 1 and type 2 diabetic patients [40, 41] associated with microvascular complications such as retinopathy, nephropathy, and neuropathy [42].
Although various pathways are involved in the pathogenesis of endothelial dysfunction such as activation of the polyol pathway, auto-oxidation of glucose, PKC pathway activation, and formation of AGEs, all these pathways may intersect at several points to increase the complexity of the disease [43]. Among these, increased formations of AGEs (advanced glycation end product) is one of the causes of ECs dysfunction, which has been implicated in the pathogenesis of diabetes-induced vascular complications, as evident by their
The high glucose-induced “oxidative stress” and “endoplasmic reticulum (ER) stress” of the endothelium may play major roles in the initiation and progression of cardiovascular clinical manifestations in diabetes [45]. While diabetes management has largely focused on the control of hyperglycemia, the rising burden of this disease is mainly correlated to its vascular complications [46]. This is reflected by a type II diabetes differs principally from type I diabetes in that it is accompanied by a period of hyperinsulinemia and is characterized by late as opposed to early onset of hyperglycemia. In type I DM, vascular involvement (through endothelial dysfunction) occurs as a result of metabolic insult/hyperglycemia, while in type II DM, endothelial dysfunction plays a more direct role and is aggravated by, rather than caused by, hyperglycemia [6].
One of the best-characterized actions of AGEs on ECs is the induction of ROS [47, 48]. There is considerable evidence to show that AGE induces ROS generation and diminishes the antioxidant defense of the cells [49, 50, 51].
Oxidative stress is induced either by the abundant production of ROS or the failure of the antioxidative machinery mechanism. The main source of ROS is the electrons present in the mitochondrial respiratory chain, which results in the formation of superoxide anion (O2-), hydroxyl radical (OH.) hydrogen peroxide (H2O2). AGEs induce mitochondrial dysfunction through the generation of ROS production.
Mitochondria are complex organelle that undergoes complete fusion and division under physiological or pathological conditions. Mitochondrial fission is defined as the division of a mitochondrion from two or more separate mitochondrial compartments, and this process is essential in the distribution of mtDNA during cell division and helps in the removal of damaged mitochondria through mitophagy. Mitochondrial fusion is merging two or more mitochondria. It is regulated by at least three proteins: optic atrophy 1 (OPA1), mitofusin 1 (MFN1), and mitofusin 2 (MFN2), and mitochondrial fission are controlled by dynamin-related protein 1 (DRP1/DLP1/DNM1), fission 1 (FIS1), and mitochondrial fission factor (MFF) [52, 53]. Studies show that in diabetes, mitochondrial fission is increased [54, 55, 56]. Diabetic animal model (diabetic-STZ model) study demonstrated that HG alters the mitochondrial respiration and alters glomerular bioenergetics, whereas podocytes isolated from those mice showed fragmented mitochondria [57]. Another study in Sprague-Dawley rats (STZ induced) reported an increase in neuronal pyknosis with increased DRP1 expression in neurons when compared with Normal control (NC) group associating that High glucose (HG) aggravated ischemic brain damage and alteration in mitochondrial dynamics [58]. Very importantly, AGEs such as AGE-BSA promoted mitochondrial fission, loss of membrane potential, and apoptosis through the RAGE pathway, whereas blocking the RAGE signaling reduces the events of mitochondrial abnormalities in endothelial and osteoblastic cells [59, 60]. In a rodent model, AGE-BSA disturbs the mitochondrial respiratory chain and induces mitochondrial pore formation with an increase in RAGE expression suggesting the fact that AGE-induced mitochondrial dysfunction plays a major role in diabetic neuropathy [61]. Proteomics study by tandem mass spectrometry (nanoLC-ESI-ETD MS/MS) revealed that renal tubular cells exposed to HG increased phosphorylation and oxidation of mitochondrial proteins when compared with the NG [62]. CML-BSA, another AGE, produces detrimental effects in diabetic db/db mice inducing mitophagy. In this study, CML-BSA treatment in pancreatic β-cells increased RAGE and ROS with a decrease in membrane potential and ATP production with elevated levels of mitochondrial fission (Drp1) and mitophagic proteins (Parkin and PTEN) supporting the factor that increases the concentration of AGEs damage the β-cells and reduces the insulin cells function by making vulnerable to AGEs-induced damages [63].
Under physiological conditions, low concentrations of ROS are needed to maintain cellular proliferation, migration, and survival [64]. However, during the pathological condition, overproduction of ROS induces deleterious effects on the cells and tissues, and to overcome this, the cellular environment has an antioxidative defense system that is capable of scavenging the ROS. The antioxidant defense system includes low-molecular ROS scavengers, antioxidative enzymes, and degrading or repairing proteins [50]. The low-molecular ROS scavengers include glutathione (GSH), vitamin C, and D. Secondly, the antioxidative enzymes superoxide dismutases (SOD) and catalase, which can convert ROS into less reactive ions. The last part of the defense system includes the proteasome and protease system, which will degrade the damaged proteins. The impairments in the antioxidant defense system lead to oxidative stress, which eventually activates various cellular signaling pathways.
Further, AGEs also increase pro-inflammatory response, by augmenting endoplasmic reticulum (ER) stress and amplifying the angiogenic potential of ECs, which has been observed in a myriad of human diseases such as atherosclerosis, acute/chronic inflammatory diseases, vascular complication, and aging [65, 66, 67, 68].
Numerous AGEs-induced vascular diseases display elevated levels of pro-inflammatory cytokine either by directly activating ROS or through engaging with RAGE receptor. AGE-RAGE is a prominent axis that facilitates the activation of NFĸB and MAPK signaling pathways, which subsequently induces the expression of cytokines, chemokines, and adhesion molecules [38, 69]. Elevated levels of AGEs enhanced the release of pro-inflammatory cytokines such as interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor (TNF-α), and interferon-beta (IL-1β). RAGE also binds HMGB1, commonly referred to as damage-associated molecules (DAMPs), and acts as an inflammatory mediator and is released into circulation when there is an injury [70]. Recognition of HMGB1 by RAGE induces the NFĸB activation and its downstream cytokines IL-6, IL-8, and TNF-α. [70, 71] Accumulating evidence shows that DAMPs are reported to mediate the pathogenesis of atherosclerosis and diabetic vascular complications.
Another important feature of inflammatory response is the recruitment and attachment of circulating leukocytes to the endothelium, which is the initial stage in the development of atherosclerosis. Increased adhesion of leukocytes to ECs is facilitated by enhanced expression of chemokines such as monocyte chemoattractant protein (MCP-1) and adhesion molecules such as intercellular adhesion molecules (ICAM), vascular cell adhesion molecules (VCAM), and E-selectins. Studies also demonstrate that direct interaction exists between the ECs adhesion molecules and lymphocyte-function-associated antigen 1 (LFA-1), macrophage-1 antigen (Mac-1), and very late antigen-1 (VLA-1), which are the major counter receptors present on the surface of the leukocytes [39, 72]. Abundant studies show that AGEs elevate the expression of adhesion molecules on the surface of the endothelial cells [73, 74].
Numerous studies provided molecular insights, highlighting the functional link existing between endothelial dysfunction and endoplasmic reticulum (ER) stress [75]. ER is the vital organelle that plays important role in protein folding, lipid biosynthesis, and calcium (Ca2+) regulation. When the ER homeostasis is disturbed either due to increased synthesis of protein, accumulation of misfolded proteins, increased oxidative stress, or alteration in calcium load leads to a condition termed as ER stress. It is closely monitored by the evolutionarily conserved quality control system called unfolded protein response (UPR) [75, 76].
The UPR system is activated by three transmembrane proteins: 1) RNA-dependent protein kinase-like ER eukaryotic initiation factor-2α kinase (PERK), 2) inositol-requiring ER-to-nucleus signaling protein 1 (IRE1), and 3) activating transcription factor 6 (ATF6). These three sensors are inactive form when they are bound with glucose-regulated protein kinase-78 (GRP78) and released upon induction of ER stress. These sensors resolve the ER stress by 1) activating the induction of UPR genes, which enhances the protein folding; 2) attenuation of protein translation, therefore, it reduces the workload of ER; and 3) activating ER-associated degradation (ERAD) pathway activation, which eliminates the unfolded protein through proteasome degradation pathway [75, 77].
During ER stress, activation of the PERK pathway leads to phosphorylation of the eukaryotic translation initiation factor 2 alpha (eIF2α), resulting in the attenuation of protein translation and activating the ATF4 (activating transcription factor-4). ATF4 subsequently induces the activation of pro-apoptotic mediator CHOP (C/EBPα-homologous protein, also known as GADD153) and its downstream target gene, DNA-damage-inducible protein-34 (GADD34). Activation of IRE1 promotes splicing of the endoribonuclease unconventional splicing of an mRNA encoding the transcription factor X-box-binding protein 1 (XBP1s). XBP1s activation further induces the activation of UPR genes, which either increases the ER folding capacity or intersects with AFT4-CHOP to activate the apoptosis. Another UPR pathway is the activation of AFT6, which translocates to the Golgi apparatus. It alleviates misfolded proteins through activation of the ERAD pathway mediated by ATF6-XBP1as shown in Figure 3 [75, 76].
AGEs-induced ER stress in endothelial cells.
Studies reported that under stress conditions, ER show an unusual morphological pattern called ER whorls, which can be used as a biomarker for ER stress [78]. Further compared with the normal cells, DTT treatment (inducer of ER stress) activated the formation of ER whorls, which are seen beneath the plasma membrane, which is in turn imported into the vacuole and proceeds for autophagy [79]. Earlier a study has shown the presence of whorl-like sER in the Leydig cells of STZ-induced mouse model indicating that diabetes can induce morphological changes in ER. Till now there are no studies that have described the effect of AGE on ER morphology. Whereas there are studies that have highlighted the distorted mitochondrial morphology (mitochondrial fission) seen during mitochondrial fission in diabetic animal models [80, 81].
ER and mitochondria are connected through mitochondrial- associated ER membranes (MAMs), which help in the transfer of Ca2+, ATP, and metabolites [82, 83]. As ER stress magnitudes, it increases the releases of Ca2+ from ER to mitochondria, which leads to the opening of mitochondrial membrane pore and releases of cytochrome C, which further intensifies the ROS production. Taken together, it creates a vicious cycle of ER stress and mitochondrial dysfunction, which progresses toward apoptotic signaling [84].
A vast number of studies link ER stress with inflammatory and oxidative signaling pathways, which play a putative role in the development and progression of endothelial dysfunction. Several lines of evidence support the fact that ER stress acts as a potent inflammatory activator because each of the UPR arms activates NFĸB pathway, which in turn releases an array of inflammatory cytokines IL-6, IL-8, and TNF-α [85, 86]. A lot of
Although several studies have identified an array of molecular entities and pathways that activate endothelial dysfunction, the cellular processes underlying endothelial dysfunction are majorly oxidative stress and inflammation. Increasing the intake of fruits and vegetables rich in polyphenols and flavonoids (anti-inflammatory and antioxidant properties) protects the endothelium and reduces the risk of cardiovascular complications [92, 93]. Increasing the endogenous antioxidant may pay way to develop a more effective and safer option. One such endogenous molecule with antioxidative, anti-apoptotic, and anti-inflammatory properties is paraoxonase [94]. Decreased serum paraoxonase (PON) activity is seen in both diabetes, and its complications have been reported, which is attributed to its glycation [95, 96]. The human PON enzyme consists of three family members, paraoxonase (PON1), paraoxonase 2 (PON2), and paraoxonase 3 (PON3). These genes are located on the long arm of chromosome no 7 (7q21-22) with nine exons. Based on the structural homology and from the evolutionary point of view, PON2 is reported to be the oldest member of the family followed by PON3 and PON1 [97]. PON1 is HDL associated and secreted in serum, whereas PON2 and PON3 are located intracellularly mainly in the endoplasmic reticulum, mitochondria, and the nuclear membrane and are ubiquitously expressed in most of the tissues including the liver, kidney, intestine, placenta, etc. [98]. Its role has been explored in many cells including epithelial, endothelial, macrophages, and smooth muscle cells.
PON2 is a ubiquitously expressed antioxidant and anti-inflammatory protein, where its expression and regulation during diabetes- induced complication have not been studied so far. In our recent study, we have established in HUVECs that AGE treatment decreases mRNA, protein, and activity of PON2, whereas overexpression of PON2 alleviates the GA and CML-induced oxidative stress, ER stress, and inflammation through NFκB and ERK1/2 phosphorylation and thereby mitigates pro-inflammatory response [99]. Further silencing of PON2 aggravates GA and CML-induced oxidative stress, ER stress, and pro-inflammatory cytokines expression in HUVEC cells. We found that in diabetic retina PON2 expression was significantly downregulated and HRECs treatment with CML increased mitochondrial fission and aggravates the mitochondrial-dependent apoptosis [100]. Conversely, overexpression of PON2 inhibits the JNK1/2-mediated signaling pathway and rescues the cells from mitochondrial fission and apoptosis as shown in Figure 4 [100].
Possible mechanistic role of PON2 in mitigating AGEs-induced ER stress, pro-inflammation, and mitochondrial dysfunction in endothelial cells.
There are a large number of studies that have established the deleterious effects of AGE on various cellular models. In this chapter, we have discussed in detail how AGEs induce mitochondrial dysfunction, inflammation and endothelial dysfunction through augmenting ER stress. We have also highlighted the association between mitochondrial stress and ER stress. The role of antioxidant PON in inhibiting these deleterious effects has also been discussed.
We thank the Council of Scientific and Industrial Research (CSIR-27 (0310)/14-EMR-11) and Indian Council of Medical Research (ICMR-ID no: 2017-0976/CMB-BMS) for providing the funding and the fellowship.
The authors declare no conflict of interest.
Ove Odredbe i uvjeti ističu pravila i regulacije u svezi korištenja IntechOpenove stranice www.intechopen.com i svih poddomena u vlasništvu IntechOpena, tvrtke sa sjedištem u 5 Princes Gate Court, London, SW7 2QJ, Ujedinjeno Kraljevstvo.
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\\n\\nSljedeća terminologija odnosi se na Odredbe i uvjete, te na sve naše ugovore:
\\n\\nKlijent, stranka, vi, vaš odnosi se na vas, osobu koja pristupa ovoj stranici i prihvaća IntechOpenove Odredbe i uvjete;
\\n\\nKompanija, tvrtka, mi, naše odnosi se na tvrtku IntechOpen;
\\n\\nStranke, strane odnosi se na klijenta i na nas, ili samo na klijenta ili nas.
\\n\\nSve odredbe koje se odnose na ponudu, prihvat ili razmatranje plaćanja, a za koja mi pružamo asistenciju klijentu, bilo na ugovoreni ili fiksni način, a s ciljem da se ostvare potrebe i želje klijenta u svezi s našim uslugama, su podložne zakonskim odredbama Ujedinjenog Kraljevstva.
\\n\\nOsim ako nije suprotno navedeno, IntechOpen i/ili svi davatelji licence vlasnici su intelektualnog vlasništva nad svim materijalima na www.intechopen.com. Sva prava intelektualnog vlasništva su pridržana. Stranice sa www.intechopen.com možete gledati, preuzimati, dijeliti, dijeliti poveznice i printati za osobnu uporabu, a temeljem pravila sadržanih u ovim Odredbama i uvjetima.
\\n\\nMi koristimo kolačiće. Korištenjem IntechOpenove stranice slažete se s korištenjem kolačića u skladu s IntechOpenovom Politikom privatnosti. Većina modernih, interaktivnih stranica koristi kolačiće kako bi omogućila ponovno pronalaženje korisničkih detalja kod svakog posjeta. Na našoj stranici kolačići se uglavnom koriste kako bi omogućili funkcionalnost i olakšali posjetiteljima korištenje stranice.
\\n\\nIntechOpen ili njegovi suradnici niti u jednom slučaju neće biti odgovorni za štete (štete uključuju gubitak podataka ili profita, druge poslovne prekide, te sve ostale štete) koje nastanu zbog korištenja materijala na IntechOpenovoj stranici ili nemogućnosti da se iste koriste, čak i ako je IntechOpen ili njegov predstavnik o takvoj šteti obaviješten pismenim ili usmenim putem. Neke jurisdikcije ne dozvoljavaju ograničenja garancija ili ograničenja obveza za posljedične ili slučajne štete pa se u tom slučaju ova ograničenja možda ne odnose na vas.
\\n\\nMaterijali koji se pojavljuju na IntechOpenovoj stranici mogu sadržavati manje greške, tipfelere ili fotografske greške. IntechOpen može napraviti promjene na bilo kojem materijalu koji se nalazi na stranici u bilo koje vrijeme.
\\n\\nIntechOpen nije formalno povezan niti s jednom vanjskom stranicom čije poveznice vode na www.intechopen.com, osim ako to nije izravno navedeno. Iz tog razloga IntechOpen nije odgovoran za sadržaj koji se pojavljuje na takvim stranicama. Poveznica na IntechOpenovu stranicu ne implicira povezanost sa IntechOpenom. Korištenje takvih poveznica isključiva je odgovornost korisnika.
\\n\\nZadržavamo pravo vlasništva nad cjelokupnom stranicom www.intechopen.com i nad svim materijalom na toj stranici. Koristeći se našim uslugama, slažete se da maknete sve poveznice na našu stranicu odmah nakon što to od vas zatražimo. Također, zadržavamo pravo da ove Odredbe i uvjete, i politiku o poveznicama izmjenimo u bilo koje vrijeme. Koristeći se poveznicama na naše stranice slažete se s ovim Odredbama i uvjetima.
\\n\\nAko smatrate da je bilo koja poveznica na našoj stranici sumnjiva iz bilo kojeg razloga, molimo vas da nas kontaktirate. U tom slučaju razmotrit ćemo micanje poveznice s naše stranice, iako nismo obvezni to napraviti.
\\n\\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\\n\\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\\n\\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
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\n\nSljedeća terminologija odnosi se na Odredbe i uvjete, te na sve naše ugovore:
\n\nKlijent, stranka, vi, vaš odnosi se na vas, osobu koja pristupa ovoj stranici i prihvaća IntechOpenove Odredbe i uvjete;
\n\nKompanija, tvrtka, mi, naše odnosi se na tvrtku IntechOpen;
\n\nStranke, strane odnosi se na klijenta i na nas, ili samo na klijenta ili nas.
\n\nSve odredbe koje se odnose na ponudu, prihvat ili razmatranje plaćanja, a za koja mi pružamo asistenciju klijentu, bilo na ugovoreni ili fiksni način, a s ciljem da se ostvare potrebe i želje klijenta u svezi s našim uslugama, su podložne zakonskim odredbama Ujedinjenog Kraljevstva.
\n\nOsim ako nije suprotno navedeno, IntechOpen i/ili svi davatelji licence vlasnici su intelektualnog vlasništva nad svim materijalima na www.intechopen.com. Sva prava intelektualnog vlasništva su pridržana. Stranice sa www.intechopen.com možete gledati, preuzimati, dijeliti, dijeliti poveznice i printati za osobnu uporabu, a temeljem pravila sadržanih u ovim Odredbama i uvjetima.
\n\nMi koristimo kolačiće. Korištenjem IntechOpenove stranice slažete se s korištenjem kolačića u skladu s IntechOpenovom Politikom privatnosti. Većina modernih, interaktivnih stranica koristi kolačiće kako bi omogućila ponovno pronalaženje korisničkih detalja kod svakog posjeta. Na našoj stranici kolačići se uglavnom koriste kako bi omogućili funkcionalnost i olakšali posjetiteljima korištenje stranice.
\n\nIntechOpen ili njegovi suradnici niti u jednom slučaju neće biti odgovorni za štete (štete uključuju gubitak podataka ili profita, druge poslovne prekide, te sve ostale štete) koje nastanu zbog korištenja materijala na IntechOpenovoj stranici ili nemogućnosti da se iste koriste, čak i ako je IntechOpen ili njegov predstavnik o takvoj šteti obaviješten pismenim ili usmenim putem. Neke jurisdikcije ne dozvoljavaju ograničenja garancija ili ograničenja obveza za posljedične ili slučajne štete pa se u tom slučaju ova ograničenja možda ne odnose na vas.
\n\nMaterijali koji se pojavljuju na IntechOpenovoj stranici mogu sadržavati manje greške, tipfelere ili fotografske greške. IntechOpen može napraviti promjene na bilo kojem materijalu koji se nalazi na stranici u bilo koje vrijeme.
\n\nIntechOpen nije formalno povezan niti s jednom vanjskom stranicom čije poveznice vode na www.intechopen.com, osim ako to nije izravno navedeno. Iz tog razloga IntechOpen nije odgovoran za sadržaj koji se pojavljuje na takvim stranicama. Poveznica na IntechOpenovu stranicu ne implicira povezanost sa IntechOpenom. Korištenje takvih poveznica isključiva je odgovornost korisnika.
\n\nZadržavamo pravo vlasništva nad cjelokupnom stranicom www.intechopen.com i nad svim materijalom na toj stranici. Koristeći se našim uslugama, slažete se da maknete sve poveznice na našu stranicu odmah nakon što to od vas zatražimo. Također, zadržavamo pravo da ove Odredbe i uvjete, i politiku o poveznicama izmjenimo u bilo koje vrijeme. Koristeći se poveznicama na naše stranice slažete se s ovim Odredbama i uvjetima.
\n\nAko smatrate da je bilo koja poveznica na našoj stranici sumnjiva iz bilo kojeg razloga, molimo vas da nas kontaktirate. U tom slučaju razmotrit ćemo micanje poveznice s naše stranice, iako nismo obvezni to napraviti.
\n\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\n\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\n\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
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His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. 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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Some specific optical nonlinear properties, such as nonlinear refraction, saturable absorption and reverse saturable absorption, two-photon absorption, and optical limiting, for femtosecond, picosecond, and nanosecond laser pulses, have been covered.",book:{id:"7349",slug:"laser-technology-and-its-applications",title:"Laser Technology and its Applications",fullTitle:"Laser Technology and its Applications"},signatures:"Yachen Gao and Deigui Kong",authors:null},{id:"61850",doi:"10.5772/intechopen.76610",title:"Fiber Lasers and Their Medical Applications",slug:"fiber-lasers-and-their-medical-applications",totalDownloads:1945,totalCrossrefCites:3,totalDimensionsCites:4,abstract:"Advancing of photonics, aided with fruitful and abundant experimental and theoretical studies, over the last four decades has brought about the invention of a large variety of lasers. Among them one of the most popular types is a fiber laser, which is a variation of the standard solid-state laser, with the medium being a clad fiber waveguide structure and different dopants inside core serve as a gain media. They were derived from erbium-doped fiber amplifiers, which are still important component for telecommunications. Since discovery, fiber laser has become a natural choice for many uses, primarily because of the physical characteristics of fiber waveguide structure. Their rapid progress may show how excellent they really are. Although fiber lasers are today widely used in various research and industrial areas, one of the most meaningful applications of fiber laser technology has been through its use in medicine. A wide variety of wavelengths generated by fiber lasers as well as the diversity of physical mechanisms employed in pulse generation also additionally underpins the flexibility of fiber laser technology. This study is devoted to background technology of fiber lasers in the light of medical applications. Basic physics and theories of optical fibers and their important properties are introduced.",book:{id:"6467",slug:"optical-amplifiers-a-few-different-dimensions",title:"Optical Amplifiers",fullTitle:"Optical Amplifiers - A Few Different Dimensions"},signatures:"Amira Tandirovic Gursel",authors:[{id:"240070",title:"Dr.",name:"Amira",middleName:null,surname:"Tandirovic Gursel",slug:"amira-tandirovic-gursel",fullName:"Amira Tandirovic Gursel"}]}],mostDownloadedChaptersLast30Days:[{id:"63129",title:"Laser Ablation Technique for Synthesis of Metal Nanoparticle in Liquid",slug:"laser-ablation-technique-for-synthesis-of-metal-nanoparticle-in-liquid",totalDownloads:2615,totalCrossrefCites:10,totalDimensionsCites:27,abstract:"Recently, the synthesis and application of metal and ceramic nanoparticle are significant subject in science and engineering. The metal nanoparticles such as silver, gold, and copper nanoparticles have more application in material science, nanomedicine, electronic, photonic, and art. One of the green methods for preparation of metal nanoparticles is laser ablation technique that offers a unique tool for nanofabrication of nanoparticles. In this technique, the high-power laser ablates the metal plate and the nanoparticles are formed in the liquid. The properties of nanoparticles using laser ablation are unique, and they are not reproducible by any other method such as chemical methods. The important parameters to produce the metal nanoparticles are energy, wavelength, repetition rate of laser, ablation time, and absorption of an aqueous solution. Laser ablation is a simple method for fabricating the metal nanoparticles without surfactant or chemical addition. In this chapter, the mechanism of formation of metal nanoparticles in liquid, significant parameters for using the laser ablation technique to prepare the metal nanoparticles, and the preparation of silver, gold and copper nanoparticles will be reviewed.",book:{id:"7349",slug:"laser-technology-and-its-applications",title:"Laser Technology and its Applications",fullTitle:"Laser Technology and its Applications"},signatures:"Amir Reza Sadrolhosseini, Mohd Adzir Mahdi, Farideh Alizadeh and\nSuraya Abdul Rashid",authors:null},{id:"73930",title:"Laser Chemical Elemental Analysis: From Total to Images",slug:"laser-chemical-elemental-analysis-from-total-to-images",totalDownloads:523,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This book chapter focuses on laser ablation employed in elemental analysis and discusses the fundamentals and instrumentation of the laser-induced breakdown spectroscopy (LIBS) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) techniques. The analytical performance of such techniques, challenges related to calibration, and strategies to improve sensitivity are discussed. In addition, the processes involved in data acquisition and imaging for acquiring the elemental spatial distribution are highlighted, and some representative examples in environmental, biological, medical, and forensic researches are presented.",book:{id:"10481",slug:"practical-applications-of-laser-ablation",title:"Practical Applications of Laser Ablation",fullTitle:"Practical Applications of Laser Ablation"},signatures:"Renata S. Amais, Danielle S. Francischini, Pedro S. Moreau and Marco A.Z. Arruda",authors:[{id:"327464",title:"Prof.",name:"Marco A.Z.",middleName:null,surname:"Arruda",slug:"marco-a.z.-arruda",fullName:"Marco A.Z. 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We describe the following applications of QD-SOA: the all-optical ultra-wideband (UWB) pulse generation based on the Mach-Zehnder interferometer (MZI) with a QD-SOA; the ultra-fast all-optical signal processor based on QD-SOA-MZI; the ultra-fast all-optical memory based on QD-SOA. The contents of the chapter are mainly based on the original results.",book:{id:"6467",slug:"optical-amplifiers-a-few-different-dimensions",title:"Optical Amplifiers",fullTitle:"Optical Amplifiers - A Few Different Dimensions"},signatures:"Yossef Ben Ezra and Boris I. Lembrikov",authors:[{id:"2302",title:"Prof.",name:"Yossef",middleName:null,surname:"Ben-Ezra",slug:"yossef-ben-ezra",fullName:"Yossef Ben-Ezra"},{id:"2359",title:"Dr.",name:"Boris I.",middleName:"I.",surname:"Lembrikov",slug:"boris-i.-lembrikov",fullName:"Boris I. Lembrikov"}]},{id:"73390",title:"Laser Machining",slug:"laser-machining",totalDownloads:571,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"The increasing demands of materials with superior properties are given priority by most of the industries in recent years due to their higher performance levels. Machining of hard materials is a challenging task since it involves higher cutting forces and rapid tool wear. This leads to complexity in shaping these difficult-to machine materials such as advanced composite and ceramics. There have been many alternative techniques developed to overcome the shortcomings of conventional machining processes. Laser beam machining (LBM) is one of the advanced noncontact machining processes that employ monochromatic light with high frequency for machining using thermal energy. The highly energized photos are focused on a material cause heating, melting and vaporizes the material which is effectively used to remove unwanted portion of a material. Due to higher coherency of laser beam, materials can be machined very precisely than conventional machining processes. Generally, the laser-based material processing is suitable for a brittle type of material with minimum conductivity. However, this laser machining can be used for all kinds of materials in most cases. 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In this chapter, recent results on the nonlinear optical properties of MNPs (including gold, silver, palladium, and platinum) have been discussed. 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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. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\r\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\r\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Orthodontist, Assoc Prof in the Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"344229",title:"Dr.",name:"Sankeshan",middleName:null,surname:"Padayachee",slug:"sankeshan-padayachee",fullName:"Sankeshan Padayachee",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"315727",title:"Ms.",name:"Kelebogile A.",middleName:null,surname:"Mothupi",slug:"kelebogile-a.-mothupi",fullName:"Kelebogile A. Mothupi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"337613",title:"Mrs.",name:"Tshakane",middleName:null,surname:"R.M.D. Ralephenya",slug:"tshakane-r.m.d.-ralephenya",fullName:"Tshakane R.M.D. Ralephenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}}]}},subseries:{item:{id:"14",type:"subseries",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.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11410,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). 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Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,series:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983"},editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",slug:"ana-isabel-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",slug:"christian-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",slug:"francisco-javier-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"}}}]},onlineFirstChapters:{paginationCount:17,paginationItems:[{id:"82751",title:"Mitochondria-Endoplasmic Reticulum Interaction in Central Neurons",doi:"10.5772/intechopen.105738",signatures:"Liliya Kushnireva and Eduard Korkotian",slug:"mitochondria-endoplasmic-reticulum-interaction-in-central-neurons",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Updates on Endoplasmic Reticulum",coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg",subseries:{id:"14",title:"Cell and Molecular Biology"}}},{id:"82716",title:"Advanced glycation end product induced endothelial dysfunction through ER stress: Unravelling the role of Paraoxonase 2",doi:"10.5772/intechopen.106018",signatures:"Ramya Ravi and Bharathidevi Subramaniam Rajesh",slug:"advanced-glycation-end-product-induced-endothelial-dysfunction-through-er-stress-unravelling-the-rol",totalDownloads:13,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Updates on Endoplasmic Reticulum",coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg",subseries:{id:"14",title:"Cell and Molecular Biology"}}},{id:"82195",title:"Endoplasmic Reticulum: A Hub in Lipid Homeostasis",doi:"10.5772/intechopen.105450",signatures:"Raúl Ventura and María Isabel Hernández-Alvarez",slug:"endoplasmic-reticulum-a-hub-in-lipid-homeostasis",totalDownloads:17,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Updates on Endoplasmic Reticulum",coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg",subseries:{id:"14",title:"Cell and Molecular Biology"}}},{id:"82103",title:"The Role of Endoplasmic Reticulum Stress and Its Regulation in the Progression of Neurological and Infectious Diseases",doi:"10.5772/intechopen.105543",signatures:"Mary Dover, Michael Kishek, Miranda Eddins, Naneeta Desar, Ketema Paul and Milan Fiala",slug:"the-role-of-endoplasmic-reticulum-stress-and-its-regulation-in-the-progression-of-neurological-and-i",totalDownloads:15,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Updates on Endoplasmic Reticulum",coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg",subseries:{id:"14",title:"Cell and Molecular Biology"}}},{id:"80954",title:"Ion Channels and Neurodegenerative Disease Aging Related",doi:"10.5772/intechopen.103074",signatures:"Marika Cordaro, Salvatore Cuzzocrea and Rosanna Di Paola",slug:"ion-channels-and-neurodegenerative-disease-aging-related",totalDownloads:12,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Ion Channels - From Basic Properties to Medical Treatment",coverURL:"https://cdn.intechopen.com/books/images_new/10838.jpg",subseries:{id:"14",title:"Cell and Molecular Biology"}}},{id:"81647",title:"Diabetes and Epigenetics",doi:"10.5772/intechopen.104653",signatures:"Rasha A. 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