Levels of hypoglycemia proposed when reporting in clinical trials and as defined by the ADA.
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Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
\n\nThis achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
\n\nWe are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
\n\nThank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
\n\n\n\n\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:"5902",leadTitle:null,fullTitle:"Interdisciplinary Expansions in Engineering and Design With the Power of Biomimicry",title:"Interdisciplinary Expansions in Engineering and Design With the Power of Biomimicry",subtitle:null,reviewType:"peer-reviewed",abstract:'People have been finding inspiration in nature in solving their problems, from the very beginning of their existence. In the most general sense, biomimicry, defined as "inspire from the nature," has brought together the engineers and designers nowadays. This collaboration creates innovative and creative outcomes that encourage people with their interdisciplinary relationships. Accordingly, the aim of this book is to bring together different works or developments on biomimetics in interdisciplinary relationship between different areas, especially biomimicry, engineering, and design. The twenty-first century has conceived many new and amazing designs. The book in your hands will surely be an important guide to take a quick look at the future possibilities.',isbn:"978-953-51-3936-2",printIsbn:"978-953-51-3935-5",pdfIsbn:"978-953-51-3993-5",doi:"10.5772/65987",price:119,priceEur:129,priceUsd:155,slug:"interdisciplinary-expansions-in-engineering-and-design-with-the-power-of-biomimicry",numberOfPages:194,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"074a748d02254c7c5643be52cb70be68",bookSignature:"Gulden Kokturk and Tutku Didem Akyol Altun",publishedDate:"March 28th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/5902.jpg",numberOfDownloads:12579,numberOfWosCitations:3,numberOfCrossrefCitations:9,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:16,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:28,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 24th 2016",dateEndSecondStepPublish:"November 14th 2016",dateEndThirdStepPublish:"July 29th 2017",dateEndFourthStepPublish:"August 29th 2017",dateEndFifthStepPublish:"October 29th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"95921",title:"Dr.",name:"Gulden",middleName:null,surname:"Kokturk",slug:"gulden-kokturk",fullName:"Gulden Kokturk",profilePictureURL:"https://mts.intechopen.com/storage/users/95921/images/7119_n.jpg",biography:"Assist. Prof. Dr. Gülden Köktürk is an electrical and electronic engineer in Dokuz Eylül University, Department of Electrical and Electronic Engineering in Izmir (Turkey). She has been working as a lecturer in Dokuz Eylül University since finishing her PhD degree. She obtained her graduate degree and PhD degree in Electrical and Electronic Engineering in 1987 and 1999, respectively. Her research interests are signal and image processing, biomedical image processing, sustainability in energy, biodesign, and biomimicry. Dr. Köktürk has published many scientific papers, conference presentations, and exhibitions. She is one of the founding members of the Turkish Biodesign Team (TBT), which is the first biodesign team of Turkey and has an interdisciplinary structure study between biomimetic, engineering, science, and design intersection. She continues to work on biodesign in science and engineering with her teammates.\n\nOther InTech publications \nBook chapter Wavelet Based Speech Strategy in Cochlear Implant by Gulden Köktürk in the book Cochlear Implant Research Updates edited by Cila Umat and Rinze Anthony Tange, ISBN 978-953-51-0582-4, InTech, April 4, 2012.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Dokuz Eylül University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"198922",title:"Dr.",name:"Tutku Didem",middleName:"Akyol",surname:"Altun",slug:"tutku-didem-altun",fullName:"Tutku Didem Altun",profilePictureURL:"https://mts.intechopen.com/storage/users/198922/images/7120_n.jpg",biography:"Assoc. Prof. Dr. Didem Akyol Altun is an architect in Dokuz Eylül University, Department of Architecture. She lives in Izmir (Turkey), a city located in the west of the country. She has been working at the Dokuz Eylül University as an instructor for 17 years now. She obtained her graduate degree in 2000 and PhD degree in Architecture in 2010. She deals with all areas of design and continues to work in the biomimetics, nature-inspired architecture, and design-engineering interface. She has many published scientific papers, conference presentations, exhibitions, awards from architectural competitions, and one TUBITAK (Scientific and Technological Research Council of Turkey) project coordinatorship. She is one of the founding members of the Turkish Biodesign Team (TBT), which is the first biodesign team of Turkey and has an interdisciplinary structure study between biomimetic, science, and design intersection. She continues to work on biodesign with her teammates.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"690",title:"Biomimetics",slug:"biomimetics"}],chapters:[{id:"58587",title:"Towards an Agile Biodigital Architecture: Supporting a Dynamic Evolutionary and Developmental View of Architecture",doi:"10.5772/intechopen.72916",slug:"towards-an-agile-biodigital-architecture-supporting-a-dynamic-evolutionary-and-developmental-view-of",totalDownloads:1413,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"Architecture and biology are fields of high complexity. Generative design approaches provide access to continuously increasing complexity in design. Some of these methods are based on biological principles but usually do not communicate the conceptual base necessary to appropriately reflect the input from biology into architecture. To address this, we propose a model for analysis and design of architecture based on a multistaged integrated design process that extends the common morphological process in digital morphogenesis with a typology-based ontological model. Biomimetics, an emerging field to strategically search for information transfer from biology to technological application, will assist in delivering a frame of reference and methodology for establishing valid analogies between the different realms as well as integration of the biological concept into a larger framework of analogy to biological processes. As the biomimetic translation of process and systems information promises more radical innovation, this chapter focuses on the dynamic perspectives provided by biological development and evolution to model the complexity of architecture. The proposed process was used to inform five parallel workshops to explore dynamic biological concepts in design. The potential of the process to investigate biomimetic processes in architecture is then discussed, and future work is outlined.",signatures:"Petra Gruber, Tim McGinley and Manuel Muehlbauer",downloadPdfUrl:"/chapter/pdf-download/58587",previewPdfUrl:"/chapter/pdf-preview/58587",authors:[{id:"201922",title:"Dr.",name:"Petra",surname:"Gruber",slug:"petra-gruber",fullName:"Petra Gruber"},{id:"203307",title:"Dr.",name:"Tim",surname:"McGinley",slug:"tim-mcginley",fullName:"Tim McGinley"},{id:"203308",title:"Ms.",name:"Manuel",surname:"Muehlbauer",slug:"manuel-muehlbauer",fullName:"Manuel Muehlbauer"}],corrections:null},{id:"58436",title:"Human Eye Behaviors Inform Systems Design for Inter-Building Communication",doi:"10.5772/intechopen.72911",slug:"human-eye-behaviors-inform-systems-design-for-inter-building-communication",totalDownloads:1072,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Adaptive sensory environments optimize in real time to consistently improve performance. One optimization method involves communication between buildings to dramatically compound positive effects—but the way these buildings communicate, matters. To design such a communication framework, this chapter uses a biomimetic approach to derive lessons from the human eye and its focusing abilities. With each focusing action, coordination occurs as muscles move to expand and contract the eye’s lens to achieve varying focal distances. And when both eyes focus together, they are able to achieve stereopsis, a field of depth and perception not attainable with only the focus of one eye. By dissecting this collaboration between eye muscle coordination and stereopsis, this chapter uncovers how a communication framework between adaptive sensory environments can create indirect, yet powerful, collective occupant and building behaviors. For example, communicating adaptive sensory environments evoke greener occupant behaviors, which, in turn, bring added benefit to the natural environment. Communication framework aspects include gamification, social media, and augmented reality that blur the boundaries between built-environments in different ways. These “communication bridges” allow buildings to take on new symbiotic relationships with each other to harness and enhance how entire urban areas uplift quality of life.",signatures:"Maria Lorena Lehman",downloadPdfUrl:"/chapter/pdf-download/58436",previewPdfUrl:"/chapter/pdf-preview/58436",authors:[{id:"205780",title:null,name:"Maria Lorena",surname:"Lehman",slug:"maria-lorena-lehman",fullName:"Maria Lorena Lehman"}],corrections:null},{id:"58691",title:"Taking Inspiration from Flying Insects to Navigate inside Buildings",doi:"10.5772/intechopen.72918",slug:"taking-inspiration-from-flying-insects-to-navigate-inside-buildings",totalDownloads:1224,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:1,abstract:"These days, flying insects are seen as genuinely agile micro air vehicles fitted with smart sensors and also parsimonious in their use of brain resources. They are able to visually navigate in unpredictable and GPS-denied environments. Understanding how such tiny animals work would help engineers to figure out different issues relating to drone miniaturization and navigation inside buildings. To turn a drone of ~1 kg into a robot, miniaturized conventional avionics can be employed; however, this results in a loss of their flight autonomy. On the other hand, to turn a drone of a mass between ~1 g (or less) and ~500 g into a robot requires an innovative approach taking inspiration from flying insects both with regard to their flapping wing propulsion system and their sensory system based mainly on motion vision in order to avoid obstacles in three dimensions or to navigate on the basis of visual cues. This chapter will provide a snapshot of the current state of the art in the field of bioinspired optic flow sensors and optic flow-based direct feedback loops applied to micro air vehicles flying inside buildings.",signatures:"Julien R. Serres",downloadPdfUrl:"/chapter/pdf-download/58691",previewPdfUrl:"/chapter/pdf-preview/58691",authors:[{id:"201014",title:"Dr.",name:"Julien",surname:"Serres",slug:"julien-serres",fullName:"Julien Serres"}],corrections:null},{id:"58540",title:"Biomimetic Design for a Bioengineered World",doi:"10.5772/intechopen.72912",slug:"biomimetic-design-for-a-bioengineered-world",totalDownloads:1380,totalCrossrefCites:1,totalDimensionsCites:3,hasAltmetrics:0,abstract:"Biodesign can be explained as a method that includes various researches and applications related to taking inspiration from natural functions, systems, components, or processes in solving a problem. Accordingly, biodesign is commonly used in the design of artificial devices, structures, and buildings in the field of bioengineering. The recent developments in the field of biotechnology and bioengineering bring out various products that are designed in collaboration with different engineering disciplines. In this chapter, the possible use of bacteria, microalgae, and fungi for biomimetic design and the role of biomimicry for these designs will be briefly discussed.",signatures:"Irem Deniz and Tugba Keskin-Gundogdu",downloadPdfUrl:"/chapter/pdf-download/58540",previewPdfUrl:"/chapter/pdf-preview/58540",authors:[{id:"204855",title:"Dr.",name:"Irem",surname:"Deniz",slug:"irem-deniz",fullName:"Irem Deniz"},{id:"204856",title:"Dr.",name:"Tugba",surname:"Keskin Gundogdu",slug:"tugba-keskin-gundogdu",fullName:"Tugba Keskin Gundogdu"}],corrections:null},{id:"59632",title:"Biomimetic Facade Applications for a More Sustainable Future",doi:"10.5772/intechopen.73021",slug:"biomimetic-facade-applications-for-a-more-sustainable-future",totalDownloads:2777,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:1,abstract:"Mankind has often taken inspiration from the nature to solve problems since nature has sophisticated processes, refined for thousands of years. While manmade systems are unsustainable, natural processes embody sustainability principles; therefore, there are many things to learn from nature in order to solve design problems and create a more sustainable future. This is the promise of a biomimetic design approach. Another design approach is biodesign, and it also involves utilizing natural elements inside the design. The building façade is a problematic research area since it is at the intersection between living spaces and natural environment; thus it faces many problems especially regarding energy-air-water transition between indoors and outdoors. Application of key sustainability concepts in architecture such as energy requirements, form and structure, and sustainability considerations can be enhanced by learning from natural processes. This chapter looks at cutting-edge design principles, materials, and designs in building façades through the lens of biomimetics and biodesign. First, the design principles and then the materials and some cases are explained. The concepts of biomimicry and biodesign are in harmony with the concept of sustainability; however, to reach sustainable façade solutions, the sustainability principles should be at the core of the design problem definition.",signatures:"Ayça Tokuç, Fatma Feyzal Özkaban and Özge Andiç Çakır",downloadPdfUrl:"/chapter/pdf-download/59632",previewPdfUrl:"/chapter/pdf-preview/59632",authors:[{id:"200339",title:"Ph.D.",name:"Ayça",surname:"Tokuç",slug:"ayca-tokuc",fullName:"Ayça Tokuç"},{id:"200342",title:"Dr.",name:"Feyzal",surname:"Ozkaban",slug:"feyzal-ozkaban",fullName:"Feyzal Ozkaban"},{id:"200536",title:"Dr.",name:"Özge",surname:"Andiç Çakır",slug:"ozge-andic-cakir",fullName:"Özge Andiç Çakır"}],corrections:null},{id:"58622",title:"Bio-inspired Adaptable Facade Control Reflecting User's Behavior",doi:"10.5772/intechopen.72917",slug:"bio-inspired-adaptable-facade-control-reflecting-user-s-behavior",totalDownloads:1673,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The purpose of this research is to develop the process of methodology in designing adaptable façade. This study focuses on the processes of façade operation control for each resident’s unit according to the user’s lifestyle. This study aims to develop the design methods that are applicable to the adaptable facade, which is inspired by the design inspiration of the biomimicry. The ideal façade to increase comfort in internal space is an adaptable façade that can constantly respond to changes in the environments. This chapter attempts in active adoption of adaptable facade that makes it possible to respond to changing requirements and environments, eventually enabling the creation of customized services for users. This chapter explores the processes of designing an adaptable façade controlled by three rules inspired by the behaviors of flocks of birds. This chapter shows how adopted bird intelligence can produce various façade controls. Also, this chapter demonstrates biomimetic façade control that has been implemented by behavior-based design. Through this demonstration, this chapter identifies the potentials of biomimetic design in facade using rules of bird flocking as source of design inspiration. This study concludes that a behavior-based approach provides flexibly responding façade to environments increasing users’ quality of life.",signatures:"Hyunsoo Lee and Nayeon Kim",downloadPdfUrl:"/chapter/pdf-download/58622",previewPdfUrl:"/chapter/pdf-preview/58622",authors:[{id:"220502",title:"Prof.",name:"Hyunsoo",surname:"Lee",slug:"hyunsoo-lee",fullName:"Hyunsoo Lee"},{id:"220507",title:"Ms.",name:"Nayeon",surname:"Kim",slug:"nayeon-kim",fullName:"Nayeon Kim"}],corrections:null},{id:"58676",title:"Switchable and Reversible Superhydrophobic Surfaces: Part One",doi:"10.5772/intechopen.73022",slug:"switchable-and-reversible-superhydrophobic-surfaces-part-one",totalDownloads:1778,totalCrossrefCites:2,totalDimensionsCites:4,hasAltmetrics:0,abstract:"In this chapter, most of the methods used in the literature to prepare switchable and reversible superhydrophobic surfaces are described. Inspired by Nature, it is possible to induce the Cassie-Baxter−Wenzel transition using different external stimuli such as light, temperature, pH, ion exchange, voltage, magnetic field, mechanic stress, plasma, ultrasonication, solvent, gas or guest. Such properties are extremely important for various applications but especially for controllable oil/water separation membranes, oil-absorbing materials and water harvesting systems.",signatures:"Sabri Taleb, Thierry Darmanin and Frédéric Guittard",downloadPdfUrl:"/chapter/pdf-download/58676",previewPdfUrl:"/chapter/pdf-preview/58676",authors:[{id:"201524",title:"Dr.",name:"Thierry",surname:"Darmanin",slug:"thierry-darmanin",fullName:"Thierry Darmanin"},{id:"201530",title:"Dr.",name:"Sabri",surname:"Taleb",slug:"sabri-taleb",fullName:"Sabri Taleb"},{id:"201531",title:"Prof.",name:"Frédéric",surname:"Guittard",slug:"frederic-guittard",fullName:"Frédéric Guittard"}],corrections:null},{id:"58690",title:"Switchable and Reversible Superhydrophobic Surfaces: Part Two",doi:"10.5772/intechopen.73020",slug:"switchable-and-reversible-superhydrophobic-surfaces-part-two",totalDownloads:1266,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"In this book chapter, most of the methods used in the literature to prepare switchable and reversible superhydrophobic surfaces are described. Inspired by Nature, it is possible to induce the Cassie-Baxter-Wenzel transition using different external stimuli such as light, temperature, pH, ion exchange, voltage, magnetic field, mechanic stress, plasma, ultrasonication, solvent, gas or guest. 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The identification of DNA polymorphisms in human populations is an important step towards understanding the contribution of functional genetic variants to predisposition of diseases or clinical phenotypes. Approach to the determination of the predisposition uses polymorphisms as marker for a disease in an affected DNA population compared to a control DNA population. Subsequently, the polymorphisms statistically associated with the disease group may be directly informative or linked to the probable causative variant. There are currently over 10 million single nucleotide polymorphisms (SNPs) including insertion/deletion variants in public databases that potentially provide a marker set for disease-gene association studies. This large variant set might not represent the variants causative of disease because it was performed in genomes of only a limited number of individuals. For this reason, the discovery genetic variation in regions of functional DNA sequence in the genomes of individuals with disease is important for disease-gene association studies. However, this situation is not practicable for complex polygenic disease. Therefore, recently, genome-wide association (GWA) or candidate gene approaches are used in the understanding of the molecular genetic background of complex polygenic disease.
Insulin resistance has a complex and heterogeneous genetic background. Insulin resistance is caused by the reduced ability of peripheral target tissues to respond properly to insulin stimulation. Insulin resistance predates beta cell dysfunction and plays the crucial role in the pathogenesis of type 2 diabetes. In addition, insulin resistance is considered the core factor in the pathogenesis of atherosclerosis and the metabolic syndrome, and is often associated with obesity, hypertension and also a dyslipidemic profile characterized by high plasma triacylglycerol concentrations and low HDL-C (Reaven, 1988; Filippi et al., 2004). Until now, many hypotheses have been proposed to explain the molecular mechanisms of insulin resistance such as insulin signaling cascade, the role of free fatty acids, adipocytokines, and inflammation (Perseghin et al., 2003; Bhattacharya et al. 2007; Choi & Kim, 2010; Erion & Shulman, 2010; Muoio &, Newgard, 2008). Given the crucial roles of pathways in the pathogenesis of liver and muscle insulin resistance, understanding the molecular mechanism of insulin resistance is vital for the development of new and more effective therapies for metabolic disorders. The homeostasis model assessment (HOMA) index for insulin resistance was calculated as the product of fasting plasma insulin (in microunits per milliliter) and fasting plasma glucose (in millimoles per liter), divided by 22.5 (Matthews et al. 1985). Higher HOMA values indicate higher insulin resistance.
Genetic and epidemiological studies strongly suggest that insulin resistance is, at least in part, genetically determined. However, the involved genes and their effective variants are mostly unknown. The numerous genes have been suggested as a potential candidate gene for insulin resistance, but the findings of these studies were controversial. This chapter is to provide an overview of our recent understanding of genetic predisposition to insulin resistance. It is aimed to summarize the results of the recent studies about the genetics of insulin resistance.
Fatty acid-binding proteins (FABPs) are members of a superfamily of lipid-binding proteins. These tissue specific proteins (FABP1-4) play the physiological role in the uptake, intracellular metabolism and excretion of long-chain fatty acids (LCFA) (Zimmerman & Veerkamp, 2002). The polymorphisms of these genes have been studied in several metabolic phenotypes such as obesity, metabolic syndrome, hypertriglyceridemia and insulin sensitivity (Mansego et al. 2012).
The liver FABP (FABP1) is an abundant cytosolic lipid-binding protein that regulates lipid transport and metabolism. The c.334-135G>A polymorphism (rs2197076) located in the 3 prime untranslated region (UTR) of the FABP1 gene was associated with the risk of type 2 diabetes and HOMA index in the Spanish population. In this study, it has been shown that carriers of the allele A of this polymophism had HOMA index values higher than homozygotes GG. However, none of the other analyzed variants in FABP2, FABP3 and FABP4 genes were associated with type 2 diabetes and insulin resistance in this study (Mansego et al. 2012).
The intestinal FABP (FABP2) plays a key role in the absorption and intracellular transport of dietary LCFA (Weiss, 2002). Therefore, the FABP2 gene has been suggested as a possible candidate gene for type 2 diabetes and insulin resistance. In vitro experiments have shown that Ala54Thr polymorphism increases the affinity of FABP2 for LCFA and is associated with increased triglyceride transport in human intestinal cells (Baier et al., 1996; Prochazka et al., 1993). Previous studies have reported significant associations between the FABP2 gene and increased prevalence of insulin resistance (Baier et al., 1995; Mitchell et al., 1995; Yamada et al. 1997; Chiu et al., 2001; Kim et al., 2001) as well as no association was found in Finnish individuals (Sipiläinen et al., 1997) and Spanish population (Mansego et al. 2012). Baier et al. reported the significant associations between the common FABP2 Ala54Thr polymorphism (rs1799883) and increased fasting insulin concentration, fasting fatty acid oxidation, and decreased insulin sensitivity in Pima Indians, a population with a high prevalence of obesity and type 2 diabetes (Baier et al., 1995). Furthermore, the linkage analysis of the FABP2 locus with insulin resistance was also found in a study in Mexican Americans who were of a mixed American-Indian and -European ancestry (Mitchell et al., 1995). However, sib-pair analysis failed to detect any linkage of the FABP2 locus or the Ala54Thr polymorphism with diabetes-related phenotypes in other ethnic groups. The homozygous Thr54/Thr54 genotype has found the associations with higher fasting insulin levels and also TNF-α levels in 33 adult obese women (Albala et al., 2004). However, the findings of this study would need to be confirmed in studies involving a larger number of subjects. A number of conflicting and inconclusive studies have investigated the possible association of the FABP2 Ala54Thr polymorphism with insulin resistance. A meta-analysis of these published studies has suggested that the Thr54 allele of the FABP2 Ala54Thr is weakly associated with a higher degree of insulin resistance, higher fasting insulin and blood glucose level. As gender and ethnicity probably were important variables in determining associative risk with insulin resistance and type 2 diabetes, Zhao et al. have performed subgroup analyses of gender and ethnicity. These weak effects of Ala54Thr polymorphism on insulin resistance and fasting insulin have been particularly established in East Asians (Zhao et al., 2010).
Elongase of long chain fatty acids family 6 (ELOVL6) is expressed in lipogenic tissues. This enzyme specifically catalyze the elongation of saturated and monounsaturated fatty acids with 12, 14 and 16 carbons. A population-based study has suggested that the genetic variations in the ELOVL6 gene are related with insulin resistance. In this study, five SNPs of the ELOVL6 gene and their haplotypes were analyzed. In this population from southern Spain, carriers of the minor alleles of the rs9997926 and rs6824447 polymorphisms had a lower risk of having high HOMA index, whereas carriers of the minor allele rs17041272 had a higher risk of being insulin resistant. Finally, Morcillo et al. has suggested that the ELOVL6 gene could be a future therapeutic target in the treatment of diabetes and related disorders (Morcillo et al., 2011). However, the validation of associations between this novel candidate gene and insulin resistance should be performed in different and large populations.
Apolipoprotein E (ApoE) is primarily involved in plasma lipid homeostasis. However, a number of studies with experimental mouse models have shown that apoE also has an important role in the development of obesity and insulin resistance (Kypreos et al., 2009; Gao et al., 2007). ApoE is involved in excess fat accumulation and energy metabolism, including the regulation of food intake and energy expenditure. Therefore, excess fat accumulation via an apoE-dependent pathway might play a role in the development of insulin resistance (Kypreos et al., 2006). Some studies have suggested that the APOE ε2/ε3/ε4 polymorphism may modify the effect of insulin on CHD or some CHD risk factors, including obesity and lipid profile levels (Després et al., 1993; Valdez et al., 1995; Elosua et al., 2003), whereas the Framingham Offspring Study and Turkish Adult Risk Factor (TARF) Study found that this polymorphism was not associated with insulin resistance (Meigs et al., 2000; Komurcu-Bayrak et al., 2011). Two other of the functional SNPs, i.e., -219G>T (rs405509) and +113G>C (rs440446) in APOE gene had shown association with plasma apoE concentrations (Lambert et al., 2000; Moreno et al., 2003), insulin resistance (Viitanen et al., 2001), insulin sensitivity in response to a diet rich in satured fats (Moreno et al., 2005). In a cross-sectional study, the impacts of these polymorphisms have been analyzed on lipid, apolipoprotein, glucose, and serum insulin concentrations in the TARF cohort, a representative of Turkish adults. In this study, the -219G>T and +113G>C genotypes and diplotypes of haplotype 2 (TCε3) showed negative correlation to serum fasting insulin and the HOMA index, but not to serum lipids. The significant associations between these functional polymorphisms and fasting insulin levels and the HOMA index were found only in the apoE3 group (ε3ε3 genotypes of the APOE ε2/ε3/ε4 polymorphism) without type 2 diabetes (Komurcu-Bayrak et al., 2011). On the other hand, a large population-based family study related with type 2 diabetes found a relationship for the polymorphisms of the APOE gene and the nearby muscle glycogen synthase (GYS1) gene on chromosome 19 with cardiovascular mortality, independently of each other (Fredriksson et al., 2007). Other functional polymorphisms in the GYS1 gene may relate to developing insulin resistance.
Uncoupling protein 2 and 3 (UCP2 and UCP3) play an important role in human energy homeostasis (Brand et al., 200 4) and have been considered candidate genes for obesity, type 2 diabetes and insulin resistance. Thus, UCP2 and UCP3 are involved in regulating ATP synthesis, generation of reactive oxygen species and glucose-stimulated insulin secretion by pancreatic β cells. The -866G>A (rs659366) polymorphism of UCP2 gene was located in a region with putative binding sites for two β-cell transcription factors (Dalgaard et al., 2003). A number of studies have been performed seeking for an association between genetic variants in this gene cluster with type 2 diabetes and/or insulin resistance. These studies have demonstrated association of the -866A-allele with increased (D’Adamo et al., 2004; Krempler et al., 2002; Gable et al., 2006) and decreased (Wang et al., 2004; Bulotta et al., 2005; Lyssenko et al., 2005; Rai et al., 2007) risk of type 2 diabetes as well as no association at all (Kovacs et al., 2005; Reis et al., 2004; Zee et al., 2011). Finally, the two recent meta-analysis on the association of type 2 diabetes with -866G>A polymorphism concluded that this variant does not confer increased risk of type 2 diabetes (Xu et al., 2011; 40, Andersen et al., 2012). However, Andersen et al has found an association between this variant and obesity in Danish individuals and established case-control studies. This study has shown that the -866G-allele was associated with elevated fasting serum insulin levels and insulin resistance (HOMA index) and decreased insulin sensitivity in Danish subjects (Andersen et al., 2012). Furthermore, in a study performed with a Spanish group of 193 obese children and adolescents and 170 controls, Ochoa et al. reported that the -55C>T (rs1800849) polymorphism of the UCP3 gene directly associated with higher fasting insulin levels and insulin resistance in heterozygous subjects from the control group. In addition, they found that the individual polymorphisms were not associated with obesity, but the (-866G) - (Del; 45 bp) - (-55T) haplotype was significantly associated with obesity and its presence in the control group increased about nine times the insulin resistance risk (Ochoa et al., 2007). Recently, a study has demonstrated that morbidly obese patients with –55CT genotype (n=15) had higher weight, fat mass, and insulin resistance (HOMA index) than the individuals with −55CC genotype (n=32) (de Luis Roman et al., 2010).
β-adrenoceptors (ADRB1, ADRB2, ADRB3) in the sympathetic nervous system play a role in regulating energy expenditure and lipolysis. ADRBs gene variation is an intense area of investigation because β-adrenoceptors are well described in organ system distribution, catecholamine-mediated physiological processes, disease states and treatment targets (Eisenach & Wittwer, 2010). One of the most studied polymorphism (rs1801253) in the ADRB1 gene encode for arginine or glycine in amino acid 389 (Arg389Gly). In 238 healthy young Caucasians and African-Americans, Gly389 carriers had a higher level of insulin and insulin resistance than non-carriers, and this allele was more prevalent in the subjects with higher body mass index (BMI; Lima et al. 2007). In previous studies, it has been found that this polymorphism was associated with serum insulin levels and insulin resistance (HOMA index) but, no association with obesity among Swedish women (Mottagui-Tabar et al., 2008). However, there are limited number of studies evaluating the association between these genes and insulin resistance. In larger scale studies with different populations should be performed for these genes to support the association between genotype and phenotype.
Adiponection is an adipokine secreted by adipocytes. The polymorphisms in adiponectin (APM1,ADIPOQ, ACRP30) gene, and its receptors (ADIPOR1 and ADIPOR2) are strongly associated with metabolic syndrome, obesity, type 2 diabetes and, insulin resistance. High adiponectin predicts increased insulin sensitivity (Tschritter et al. 2003). There is evidence indicating that insulin directly affects plasma adiponectin (Möhlig et al., 2002; Hung et al., 2008; Brame et al., 2005). In recent studies, plasma adiponectin concentrations were reduced in type 2 diabetes and obesity (Arita et al., 1999; Lindsay et al. 2002; Spranger et al., 2003). Furthermore, administration of thiazolidinediones (TZD), an insulin-sensitising class of drugs, to insulin-resistant subjects significantly increased the plasma adiponectin levels, and this effect was correlated with the amelioration of insulin resistance in these subjects (Maeda et al., 2001). Many studies have, in fact, reported the association between polymorphisms of the APM1, ADIPOR1, and ADIPOR2 and adiponectin concentrations, insulin resistance, type 2 diabetes and metabolic syndrome phenotypes (Kondo et al., 2002; Hara et al., 2002; Menzaghi et al., 2002; Stumvoll et al., 2002; Hivert et al., 2008; Menzaghi et al.,2007; Sheng et al., 2008; Ferguson et al., 2010). While, in the study from Stumvoll et al, the +45T>G (rs2241766) polymorphism was associated with obesity and derangement of insulin sensitivity (Stumvoll et al., 2002), in the study from Melistas et al, this polymorphism was associated with lower insulin levels in Greek women without diabetes (Melistas et al., 2009). In a study from Menzaghi et al, a haplotype of the adiponectin gene was associated with several features of insulin resistance in nondiabetic individuals, including low serum adiponectin levels (Menzaghi et al., 2002). In addition, the +276G>T (rs1501299) polymorphism in the adiponectin gene was associated with higher insulin levels and insulin resistance (HOMA index) in Italian population from the Lazio region (diabetes and/or the metabolic syndrome was excluded) (Filippi et al., 2004) and in Greek female population without diabetes (Melistas et al., 2009). The association of the -11391G>A (rs17300539) polymorphism with plasma insulin and HOMA index was independent of plasma adiponectin in another study, which implies a direct effect of this polymorphism on plasma insulin and insulin sensitivity (Henneman et al., 2010). Recently, Vasseur et al have reported on the association of a haplotype G-G (including -11391G>A and -11377C>G polymorphisms located in the APM1 proximal promoter) with plasma adiponectin levels and type 2 diabetes, although no association with HOMA index was observed (Vasseur et al., 2002). The reasons for partially discrepant results between polymorphisms in these genes and metabolic measures could be due to the different genetic background of the studied populations or environmental interactions, particularly dietary factors. Gene-nutrient interactions can modulate in the development of metabolic phenotypes. Although, so far, there has been little focus on gene-nutrient interactions with adiponectin and its receptors, two studies found that there was an interaction between the rs266729 polymorphism of APM1 and the percentage of dietary-derived energy from fat with the development of obesity in women (Santos et al., 2006) and an association between this polymorphism and also the rs10920533 polymorphism of ADIPOR1 and plasma saturated fatty acids with the insulin resistance (Ferguson et al., 2010).
Thyroid hormones are known to upregulate the expression of glucose transporter type 4 (GLUT4) in skeletal muscle, and consequently increase glucose uptake (Weinstein et al., 1994). Thyroxine (T4), a major secretory product of the thyroid gland, needs to be converted to triiodothyronine (T3) to exert its biological activity. Type 2 deiodinase (D2) catalyzes T4 to T3 conversion, and plays a critical role in maintaining intracellular T3 levels in specialized tissues, such as the anterior pituitary and brown adipose tissue (Bianco et al., 2005). Thr92Ala polymorphism of D2 gene showed an association with lower glucose disposal rate in nondiabetic subjects and also a higher prevalence of insulin resistance in Pima Indians and Mexican–Americans (Mentuccia et al., 2002). Furthermore, D2 Ala/Ala genotype was also associated in previous studies with increased insulin levels and increased insulin resistance (increased HOMA index) and also worse glycemic control (increased HbA1c levels) in a cohort of patients with type 2 diabetes (Grozovsky et al., 2009; Dora et al., 2010). In addition, this polymorphism was associated with greater insulin resistance in type 2 diabetes patients and with lower enzyme activity in thyroid tissue samples (Canani et al., 2005). However, some population-based studies failed to demonstrate an association between the D2 Thr92Ala polymorphism and increased risk for type 2 diabetes (Mentuccia et al., 2005; Maia et al., 2007; Grarup et al. 2007). Thyroid hormone interacts with the TSH receptor (TSHR) in the thyroid gland. A previous study has investigated the association between serum thyroid parameters and the TSHR Asp727Glu polymorphism in nondiabetic elderly men. Peeters et al. reported that this polymorphism was associated with relative insulin resistance. Carriers of the Glu727 allele had also a significantly higher glucose, insulin, HOMA index and leptin levels, but no association with serum TSH levels (Peeters et al., 2007). Peeters et al. have suggested that this association was studied in one cohort only, and as the mechanism remains to be elucidated, replication of results in an independent cohort (of healthy elderly subjects) was essential.
Some studies have suggested that the polymorphisms in genes encoding sex hormones may be effective on the development of insulin resistance. Previous studies have shown that androgen supplementation in the presence of central obesity and low testosterone levels increases insulin sensitivity in men (Mårin et al., 1992; Simon et al., 2001; Boyanov et al., 2003). Moreover, polycystic ovarian syndrome was associated with higher risk of type 2 diabetes and insulin resistance in women (Dunaif, 1995). Recent studies have demonstrated that higher levels of circulating sex hormone binding protein (SHBG) were associated with reduce risk of type 2 diabetes (Ding et al., 2009; Perry et al., 2010). In addition, rs6259, rs6257 and rs1799941 polymorphisms in the SHBG gene were strongly associated with SHBG levels and type 2 diabetes (Zeggini et al., 2008; Perry et al., 2010). However, there was no evidence that this variant is associated with diabetes-related intermediate traits, including several measures of insulin secretion and resistance (Perry et al., 2010).
Leptin (LEP), a hormone secreted by adipocytes, and its receptor (LEPR) are other candidate genes for insulin resistance. Common variants in the LEPR gene have been associated with hyperinsulinemia (Lakka et al., 2000; Wauters et al., 2002), type 2 diabetes (Lakka et al., 2000), obesity, and leptin levels (Chagnon et al., 1999; Chagnon et al., 2000; Chagnon et al., 2001; de Luis Roman et al., 2006). However, the roles of leptin and its receptor in the development of metabolic traits in the general population are less clear. A few studies have, in fact, reported the association between polymorphisms of the LEP and LEPR genes and insulin resistance (Wauters et al., 2001; de Luis et al., 2008; Gu et al., 2012; Takahashi-Yasuno et al., 2004; Ren et al., 2004). While, in the study from Wauters et al, Lys109Arg, Gln223Arg, and Lys656Asn polymorphisms in LEPR gene were associated with insulin and glucose metabolism in postmenopausal obese women with impaired glucose homeostasis (Wauters et al., 2001), in the study from de Luis et al, Lys656Asn polymorphism was associated with higher levels of insulin, HOMA, and leptin in men without diabetes (de Luis et al., 2008), in the study from Gu et al, Lys109Arg was associated with waist-to-hip ratio, oral glucose tolerance test (OGTT)-2h glucose, and HOMA index in Chinese subjects with essential hypertension, but no correlation between Lys109Arg polymorphism and hypertension were found (Gu et al., 2012). Also’ -2549C>A polymorphism in the promoter region of the LEP gene is related to fasting plasma leptin level (Mammès et al., 1998; Le Stunff et al., 2000; Gu et al., 2012), obesity phenotypes (Mammès et al., 1998; Mammès et al., 2000; Le Stunff et al., 2000), and also fasting serum insulin level and HOMA index in Chinese patient with type 2 diabetes (Ren et al., 2004). However, the findings of the study from Ren et al. should be confirmed with studies involving larger number of subjects and different populations.
Retinol-binding protein 4 (RBP4) is an adipokine with potential contribution to systemic insulin resistance (Yang et al., 2005). The -803G>A promoter polymorphism (rs3758539) of RBP4 gene is associated with increased risk for obesity and type 2 diabetes in adults (Munkhtulga et al., 2010 ; Munkhtulga et al., 2007; van Hoek et al., 2008). Munkhtulga et al. have reported in 2010 that the -803A allele of this polymorphism was associated with higher BMI in Japanese men and women and in Mongolian women (Munkhtulga et al., 2010) and also in 2007 they found that the rare alleles of four SNPs (-803G>A, +5169C>T, +6969G>C, +7542T>del) were associated with increased risk of diabetes in Mongolian case-control study (Munkhtulga et al., 2007). van Hoek et al. have shown that homozygosity for the −803A allele was associated with increased risk of type 2 diabetes in the Rotterdam population (van Hoek et al., 2008). More recent studies failed to confirm an association of this variant with circulating RBP4 levels, type 2 diabetes susceptibility, adiposity or metabolic parameters (Friebe et al., 2011; Kovacs et al., 2007; Shea et al., 2010; Wu et al., 2009; Craig et al., 2007). Shea et al. have analyzed five SNPs including -803G>A polymorphism within RBP4 gene and they have found a significant association between the minor allele of rs10882280 (C>A intron) and rs11187545 (A>G intron) polymorphisms and higher serum HDL-C levels in Newfoundland population, but not between insulin resistance and any polymorphism (Shea et al., 2010). Craig et al. have found that only a haplotype (-804G, 390G, 406T, 759G, 6969G, 9476T, 10670G, and 11881C) in RBP4 gene showed an association with type 2 diabetes in African Americans and Caucasians. Furthermore, -803G>A and +9476T>G (rs34571439) polymorphisms were associated with reduced insulin secretion, and +390C>G (novel) with reduced insulin sensitivity in Caucasians (Craig et al., 2007). The discrepancy among previous publications about insulin resistance may be resolved by analyzing a larger number of samples.
Resistin (RETN), a hormone secreted by adipocytes, has been examined as candidate gene for obesity and type 2 diabetes and insulin resistance. However, there are many conflicting findings about these metabolic phenotypes. Osawa et al. have reported that the GG genotype of RETN -420C>G promoter polymorphism (rs1862513), increased type 2 diabetes susceptibility (Osawa et al., 2004) and fasting plasma resistin (Osawa et al., 2007; Azuma et al., 2004) in the Japanese population. Silha et al. and Osawa et al. have found correlation between resistin levels and insulin resistance (Silha et al.,2003; Osawa et al., 2007), but not Lee et al. (Lee et al., 2003). Some genetic association studies have found an association between certain resistin gene variants and insulin resistance in Finnish nondiabetic individuals (Conneely et al., 2004), in nondiabetic Caucasians from Sicily and Gargano areas of Italy (Pizzuti et al., 2002), and in 20 nondiabetic Caucasians (Wang et al., 2002), while others report no such association in 60 Japanese obese nondiabetic individuals (Azuma et al., 2004) and in 258 families with 323 affected with polycystic ovary syndrome offspring (Urbanek et al., 2003). These conflicting findings have made it difficult to determine a role for resistin in insulin resistance. The reasons for discrepant results are not known, and may reside in the different genetic background of the studied populations or the different-designed studies.
The renin-angiotensin system (RAS) plays a central role in the regulation of insulin sensitivity (Reaven, 1995; Higashiura et al., 2000; Ura et al., 1999). Many studies have examined the genetic effect of homozygous deletion polymorphism (DD) in exon 16 of the angiotensin-converting enzyme gene (ACE) in insulin resistance, but their results have been controversial (Katsuya et al., 1995; Perticone et al., 2001; Yamamoto et al., 1999). Hypertension is related to insulin resistance and a number of studies have reported an association between RAS gene polymorphisms and hypertension (Sugimoto et al. 2004; Jin et al., 2003; Kikuya et al., 2003; Ono et al., 2003). Akasaka et al., 2006; The insertion/deletion (I/D) polymorphism of the angiotensin-converting enzyme gene (ACE), the Met235Thr polymorphism of the angiotensinogen gene (AGT), and the 1166A>C polymorphism of the angiotensin II type 1 receptor gene (AGTR1) were not associated with HOMA index, whereas borderline association was found between the 1166A>C polymorphism and dichotomous categorization of insulin resistance (defined as HOMA index ≥1.73). However, further studies are required to confirm the impact of these candidate gene polymorphisms in the larger and different populations.
Tumor necrosis factor alpha (TNF-α) is a multifunctional proinflammatory cytokine and also an adipokine produced in adipocytes. Increased levels of the TNF-α have been shown to elevate the risk of insulin resistance by impairing β cell function and glucose homeostasis (Hotamisligil et al., 1993; Hotamisligil et al., 1994; Katsuki et al., 1998). In addition, the TNF-α affects lipid metabolism and may lead to hypertriglyceridemia by decreasing hepatic lipoprotein lipase activity and by increasing hepatic de novo fatty acid synthesis (Zinman et al., 1999). Circulating levels of TNF-α have also been reported to correlate with insulin resistance and type 2 diabetes (Hotamisligil & Spiegelman, 1994; Hu et al., 2004). Previous studies have shown that TNF-α -308G>A polymorphism is associated with insulin resistance (Fernandez-Real et al., 1997), obesity (Hoffstedt et al., 2000), type 2 diabetes (Vendrell et al., 2003; Kubaszek et al., 2003) and metabolic syndrome (Gupta et al., 2012). However, many other studies have reported conflicting results, with no association between this variant and insulin resistance (Gupta et al., 2012; Ranjith et al., 2008). A meta-analysis of many published studies including different populations has suggested that -308A TNF-α gene variant is associated with increased risk of developing obesity compared with controls and significantly higher systolic arterial blood pressure and plasma insulin levels (Sookoian et al., 2005). On the other hand, another recent meta-analyses has reported that TNF-α -238G>A and -308G>A polymorphisms were not associated with type 2 diabetes mellitus; however, -308G>A polymorphism was positively associated with type 1 diabetes (Feng et al., 2009a; Feng et al., 2009b; Feng et al., 2011). TNF-α -857C>T polymorphism is also associated with obese type 2 diabetes (Kamizono et al. 2000) and insulin resistance in Japanese diabetic subjects with adiponectin +276GG genotype (Ohara et al., 2012). The study of Ohara et al has shown interaction of TNF-α and adiponectin genes with insulin resistance and fatty liver (Ohara et al., 2012).
Interleukin-6 (IL-6) is a proinflammatory cytokine that is associated with type 2 diabetes and insulin resistance (Di Renzo et al., 2008; Wannamethee et al., 2007; Hu et al., 2004). Recent studies has demonstrated that the association between -174G>C polymorphism (rs1800795) in the promoter region of the IL-6 gene and insulin resistance is modified by body mass index (BMI), with the -174C allele associated with higher insulin resistance and type 2 diabetes in individuals with obesity (Herbert et al., 2006; Mohlig et al., 2004; Goyenechea et al., 2007; Di Renzo et al., 2008; Underwood et al., 2012). However, in meta-analysis including 5383 diabetes cases and 12 069 controls, it has been found that -174G>C polymorphism was not associated with the risk of type 2 diabetes (Qi et al., 2006). The reasons underlying the discrepancy among studies are unclear. Other genetic or environmental factors may play important roles in modulating the relationships.
The insulin resistance is highly heritable and originates from the interactions of multiple genes and environmental factors. Figure 1 shows the main factors contributing to the development of insulin resistance and type 2 diabetes. However, the molecular mechanism of insulin resistance is not clear yet. Until now, goal of many studies was to use a candidate gene approach to identify genes associated with insulin resistance and several genes have been investigated in many association-based studies. However, most of the time, results of these studies reveal conflicting findings. These discrepant results might be due to differences in the study populations and design of these studies. In addition, the candidate gene polymorphisms have been searched in a number of small-scale studies with variable results. Limited number meta-analyses have been done to demonstrate the effect of several candidate gene polymorphisms on insulin resistance. But, the larger, well-characterized and independent association studies will be needed. On the other hand, the use of genome-wide association (GWA) studies will identify novel polymorphisms related to insulin resistance. This knowledge will allow the determination of the genetic predisposition to the insulin resistance and new approaches to treatment and prevention of the clinical phenotypes such as type 2 diabetes, obesity, hypertension and metabolic syndrome.
General overview of genetic and environmental factors contributing to the development of insulin resistance and type 2 diabetes. The combination of genetic predisposition (genetic polymorphisms effecting free fatty acid metabolism, insulin signalling, adipokines and cytokines) and some environmental factors such as excessive dietary intake and physical inactivity results with the occurrence of adipocytogenesis, lipodystrophy and obesity which increase the development risk of insulin resistance. Insulin resistance predates pancreatic beta cell dysfunction and plays the crucial role in the pathogenesis of type 2 diabetes.
Diabetes is a lifelong, chronic disease characterized by episodes of hyperglycemia [1, 2]. Treatment of diabetes, in order to be effective, must lower glucose concentration to a euglycemic level, however, the key barrier to optimal glycemic control is hypoglycemia (low blood glucose levels) despite ongoing improvements in therapies and technology [3].
Hypoglycemia is one of the most impactful adverse events in diabetes and is a common problem for people with both type one (T1D) and type two (T2D) diabetes [4]. Too much insulin or, insulin-producing medications are commonly related to a hypoglycemic event, however other factors such as delayed, missed, or reduced meals other than what was planned, unanticipated strenuous exercise, alcohol consumption or interactions with other drugs are also known contributors. Additionally, individual patient factors such as older age, nutritional status, duration of diabetes, renal or hepatic disease, history of hypoglycemic episodes [5], and hypoglycemic unawareness may increase the risk of events [6].
Despite recent advances in diabetes technology, hypoglycemia remains a key obstacle to achieving adequate glycemic control [3, 7, 8]. Even though the issue is well accepted, the size of the issue varies depending on how hypoglycemia is defined, measured, and reported. The incidence of hypoglycemia reported between randomized controlled trials vs. observational studies vs. patient-reported outcomes was found to differ by a factor of over 100 in one review [9].
The frequency of hypoglycemia varies from 42 to 91 events per patient year for adults with Type 1 diabetes (T1D) and from 20.3–44.4 events per patient year for adults with Type 2 diabetes (T2D) [10]. Severe hypoglycemia is not only a problem for insulin-treated patients but is also common among older adults with T2D across all levels of glycemic control. The risk tends to be higher in patients with either near-normal glycemia or very poor glycemic control [4]. Additionally, frequent episodes of mild hypoglycemia may compromise the hormonal counterregulatory response to produce adrenaline and subsequent autonomic warning symptoms such as trembling and sweating leading to hypo-unawareness increasing the risk of severe hypoglycemia further [6].
With the general exception of diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic syndrome (HHS), the clinical consequences of prolonged hyperglycemia are long-term. These long-term risks were demonstrated in the Diabetes Control and Complications Trial (DCCT) [11] and the United Kingdom Prospective Diabetes Study (UKPDS) [12] for T1 and T2 diabetes respectively and are the result of neuropathy, retinopathy, and/or nephropathic complications.
The clinical consequences of severe hypoglycemia on the other hand can be immediately associated with the event and include acute cerebrovascular disease, myocardial infarction, neurocognitive dysfunction, and loss of vision [13]. If left untreated, severe hypoglycemia can result in significant morbidity and mortality [14, 15].
All levels of hypoglycemia are associated with significant indirect costs, not only on employers but also on individuals with diabetes [16]. A recent study showed a clear link between severe hypoglycemia and the costs of lost productivity, with the highest loss in productivity attributed to non-severe nocturnal hypoglycemic events [17]. Numerous studies have shown that hypoglycemia negatively impacts patients’ ability to concentrate and participate in daily activities, thereby negatively impacting the quality of life (QoL) [17]. Even non-severe hypoglycemia, which occurs in 24–60% of patients with diabetes, can adversely affect QoL [18]. The greatest reductions in QoL are seen among those participants reporting a higher frequency of non-severe hypoglycemia [18]. As reported by Geelhoed-Duijvestijn et al., it takes an average of 50.4 min to return to normal functioning following a daytime non-severe hypoglycemic event, but negative feelings persisted for an average of 5.4 hours [19]. Following a nocturnal non-severe hypoglycemic event, functionality was diminished for an average of 80.5 min while negative feelings persisted for 12.2 hours [19].
Severe hypoglycemic episodes not only significantly affect the individual but are associated with long-term cost implications to the health system. One cohort study assessed the costs between a population requiring hospitalization due to severe hypoglycemia and a matched control. The results demonstrated that the group suffering from the severe hypoglycemic episode incurred an additional $10,873 (p < 0.001) in direct and indirect costs vs. the control for that event year [20].
Hypoglycemia detection and management remain the cornerstone of modern diabetes management and it is important that patients and their healthcare providers (HCPs) understand the strengths and limitations of various blood glucose monitoring systems (BGMS) in order to select the most appropriate system that meets their individual needs [13].
A joint position statement of the International Hypoglycemia Study Group of ADA and EASD has proposed three glucose severity levels when reporting hypoglycemia in clinical trials of glucose-lowering drugs for the treatment of diabetes (Table 1). The Group recommends that the frequency of detection of a glucose concentration < 3.0 mmol/l (<54 mg/dl), which it considers to be clinically significant biochemical hypoglycemia, should be included in clinical trial reports [21]. These levels are further aligned by the most recent version of the ADA’s Standards of Medical Care in Diabetes 2022 (Table 1).
ADA – Standards of Care 2022 | International Hypoglycaemia Study Group., 2017 | |
---|---|---|
Level 1 < 70–54 mg/dL (3.9–3.0 mmol/L) with or without symptoms | Considered clinically important (independent of the severity of acute hypoglycemic symptoms) | This need not be reported routinely in clinical studies, although this would depend on the purpose of the study |
Level 2 < 54 mg/dL (3.0 mmol/L) with or without symptoms | The threshold at which neuroglycopenic symptoms begin to occur and require immediate action to resolve the hypoglycemic event | Sufficiently low to indicate serious, clinically important hypoglycemia |
Level 3 Severe hypoglycemia not defined by a specific glucose level | Defined as a severe event characterized by altered mental and/or physical functioning that requires assistance from another person for recovery | Severe cognitive impairment requiring external assistance for recovery |
Levels of hypoglycemia proposed when reporting in clinical trials and as defined by the ADA.
According to current ISO 15197:2013 accuracy requirements, ≥95% of BG results should be demonstrated to be within ±15% of the reference method for samples with BG concentrations ≥100 mg/dL, and ± 15 mg/dL when BG concentrations are <100 mg/dL. (International Organization for Standardization.)
The FDA guidance 2020 recommends that ≥95% of all BGMS results should be within ±15%, and ≥ 99% of all BGMS results should be within ±20% of the reference laboratory method across the entire claimed to measure range of the BGMS. (US Department of Health and Human Services [22]. Food and Drug Administration.)
These more stringent guidelines recognized the limitations of evaluating BG samples at the extreme ends of the measuring range, especially in the low range where very few samples are available [23]. Recognizing the clinical importance of the accuracy of BG measurements for hypo- and hyperglycemic blood samples, both European and US authorities have requested that accuracy data be reported separately for low, normal, and high BG ranges [23]. This issue is however complicated by system accuracy requirements being applied to measurement results from the whole glycemic range. If a BGMS shows 100% accurate results at BG concentrations ≥80 mg/dL (4.44 mmol/L) (80% of results, following ISO 15197:2013) [24], this results in 25% of the samples in the low-glucose range being allowed outside the accuracy limits (5% “results outside of accuracy limits” divided by 20% “results <80 mg/dL [4.44 mmol/L]”) [23].
Despite the boundaries of ISO 2013 standards and/or FDA 2020 guidance, (International Organization for Standardization., US Department of Health and Human Services [22]. Food and Drug Administration) considerable differences exist in the performance of commercially available BGMS [25]. Such error patterns over the operating range of BGMS may lead to relevant differences in clinical and economic outcomes. These differences can potentially increase the risk of not detecting hypoglycemic events when they occur, and, therefore, inadequately identifying and treating them [25].
Thus, if a patient’s true BG concentration is 60 mg/dL (3.33 mmol/L), acceptably accurate results range from 45 to 75 mg/dL (2.50 to 4.16 mmol/L) according to the ISO limits and from 51 to 69 mg/dL (2.83 to 3.83 mmol/L) according to FDA criteria. This can make it difficult for a patient to detect and manage their hypoglycemia. If a BGMS cannot reliably differentiate between 50, 60, and 70 mg/dL (2.77, 3.33, and 3.88 mmol/L), the utility of predefined hypoglycemia thresholds comes into question [23].
Multiple post-market studies of BGMS have failed to replicate the accuracy normally required to gain market approval by the regulatory authorities [26, 27, 28, 29, 30]. Many of these products remain on the market today.
Whilst it is not difficult to obtain BG samples in the normal range it is more of a challenge to obtain and subsequently assess the accuracy of devices outside of this range. It may be unethical and potentially dangerous to purposefully cause hypoglycemia in a patient simply for the purposes of testing device accuracy. The remaining choices to assess accuracy at this level is either to accept the smaller sample size, modify the sample prior to testing, or to create a statistical model. These concepts have further been explored in the low blood glucose range and evidence shows that the accuracy of different BGMS (that were approved under ISO 2013 standards) are not the same at these critical levels and some would appear non-compliant [29, 31]. Recently a methodology was developed to demonstrate the differences in accuracy in the low blood glucose range among several BGMSs as demonstrated in Figure 1 [32, 33, 34, 35]. The differences in accuracy between devices was clinically meaningful.
Probability curves for real-world BGMSs (all meeting ISO 15197:2013 criteria) (adapted from [
Continuous glucose monitoring (CGM) devices have become more widespread over the past decade. They generally fall into two categories, real-time (rt-CGM) and intermittently scanned (is-CGM) devices. rt-CGM has shown positive improvements in improving HbA1c and reducing hypoglycemia in insulin users in RCTs [36, 37, 38] whereas is-CGM generally relies on observational data to support its use [39]. They predominantly differ from BGMS by measuring glucose concentration in the interstitial fluid, several times per hour, whereas BGMS measure blood (normally capillary) glucose once per test, up to around 10 times per day, depending on individual patient needs [1].
Unlike BGMS that have well-defined FDA and ISO accuracy criteria that must be met prior to obtaining marketing authorization, there remains no such standardized metrics for CGM accuracy requirements. In spite of this, it is commonplace for manufacturers to describe the accuracy of a CGM using Mean Absolute Relative Difference (MARD). This is calculated by averaging the absolute values of relative difference from the comparison method and does not account for positive or negative bias, i.e. all differences are made positive [40]. The MARD of some CGM systems has been reported to be in the 10–12% range whereas some BGMS has demonstrated to be below 5% [40].
One reason for the difference in MARD between some CGMs and BGMS could be attributed to measuring glucose in different compartments of the body. There is an inherent delay between glucose levels in each compartment with one study suggesting that to be between 6 and 10 minutes [41]. This makes it very difficult for a CGM to be as accurate, particularly at times of rapid glucose change. A further study demonstrated that MARD could change considerably throughout the day, approximately doubling between fasting periods and after food (8.0–16.3% and 9.1–16.3% depending on the device) [42]. This brings into question the value of such a metric if it can vary so much. Table 2 provides some examples of when BGM is needed in CGM users.
|
|
|
|
Some examples for adjunct blood glucose testing in CGM users.
ISF: interstitial fluid; CGM: continuous glucose monitoring; EU: European Union; and UK: United Kingdom.
Additionally, the detection of hypoglycemia by a CGM device is dependent on the duration of the hypoglycemic event. A recent study showed that two-thirds of all patients reported hypoglycemic events required minimum duration of 15 minutes in order to be by the CGM device [43].
A low ISF glucose reading below 3.9 mmol/L can prompt corrective actions that may be unnecessary if actual blood glucose, as measured by SMBG, is significantly higher. For instance, a user may develop hypoglycemia and take corrective action. Due to the time lag between blood glucose and ISF glucose, if the user continues to rely only on ISF glucose readings, there may be a lag in the rise of ISF over blood glucose, resulting in further and unnecessary treatment of hypoglycemia.
Similarly, experienced users may become less concerned with ISF low glucose readings than they would be with SMBG readings and take no immediate action. Each of these scenarios potentially creates unwanted risks [44].
The use of a CGM, particularly for the management of T1D, is preferred; however, all patients should learn how to use a BGMS for backup and monitoring if CGM is not available and/or desired [39]. This was further confirmed by the American Diabetes Association [1] which stated, “Every patient using a CGM must have a BGM.” The reasoning for using a BGM when using a CGM includes whenever there is suspicion that the CGM is inaccurate, while waiting for warm-up, for calibration (some sensors) or if a warning message appears, and in any clinical setting where glucose levels are changing rapidly (>2 mg/dL/min), which could cause a discrepancy between CGM and BGM readings.
The definition of hypoglycemia is based on blood glucose readings, therefore the use of BGM in CGM users remains an essential part of their diabetes management.
The American Association of Clinical Endocrinologists and American College of Endocrinology 2016 outpatient glucose monitoring consensus statement provided clinical situations and patients groups requiring the highest possible accuracy in glucose monitoring for detection of hypoglycemia [45]. These include those with a history of severe hypoglycemia; hypoglycemia unawareness; infants and children receiving insulin therapy; patients at risk for hypoglycemia, including patients receiving basal insulin or basal/bolus insulin therapy, patients with irregular schedules, skipped or small meals, vigorous exercise, travel between time zones, disrupted sleep schedules, shift work, and people with occupational risks that enhance possible risk from hypoglycemia (e.g., driving or operating hazardous machinery) [45].
Other patient groups include those receiving sulfonylurea or glinides [46], and people with diabetes with comorbidities such as hyperlipidemia or chronic renal disease who may also be taking multiple medications [47]. Age is also an important factor, as risk factors for hypoglycemia such as renal impairment, cardiovascular disease, and polypharmacy all increase with advancing age in adults with T2D [48, 49, 50].
The high accuracy in the low blood glucose range is also necessary for diabetes management during pregnancy, therefore CGM use in this patient population remains adjunctive use only [45, 51]. Blood glucose monitoring remains a cornerstone of glucose management during pregnancy [1].
In order to make correct therapy decisions, a correct glucose reading is essential [52]. In order to obtain a correct glucose reading, the correct device must be used. This selection spans both device types, i.e. CGM/BGM, and also specific device within the type. Accuracy variation within both system types is proven to be significant, therefore understanding the importance of education for HCP and patients to make an informed choice based on individual needs.
Medical writing was supported by Madano.
RS and JR are employees of Ascensia Diabetes Care Holdings AG.
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The literature source was Web of Science and SSCI, SCI-EXPANDED, A&HCI, CPCI-S, CPCI-SSH, and ESCI indexes. Fifty-two articles were reviewed; however, 14 of them were not been included in the study. As a result, 38 articles were examined. Level of education, field of education, and material types of AR used in education and reported educational advantages of AR have been investigated. All articles are categorized according to target groups, which are early childhood education, primary education, secondary education, high school education, graduate education, and others. AR technology has been mostly carried out in primary and graduate education. “Science education” is the most explored field of education. Mobile applications and marker-based materials on paper have been mostly preferred. The major advantages indicated in the articles are “Learning/Academic Achievement,” “Motivation,” and “Attitude”.",book:{id:"6543",slug:"state-of-the-art-virtual-reality-and-augmented-reality-knowhow",title:"State of the Art Virtual Reality and Augmented Reality Knowhow",fullTitle:"State of the Art Virtual Reality and Augmented Reality Knowhow"},signatures:"Rabia M. Yilmaz",authors:[{id:"225838",title:"Dr.",name:"Rabia",middleName:null,surname:"Yilmaz",slug:"rabia-yilmaz",fullName:"Rabia Yilmaz"}]},{id:"63639",doi:"10.5772/intechopen.81086",title:"Cooperative Learning: The Foundation for Active Learning",slug:"cooperative-learning-the-foundation-for-active-learning",totalDownloads:3491,totalCrossrefCites:18,totalDimensionsCites:25,abstract:"The role of instructors is evolving from the presenter of information to the designer of active learning processes, environments, and experiences that maximize student engagement. The more active a lesson, the more students tend to engage intellectually and emotionally in the learning activities. Cooperative learning is the foundation on which many of the active learning procedures are based. Cooperative learning is the instructional use of small groups so that students work together to maximize their own and each other’s learning. Most of the active learning procedures, such as problem-based learning, team-learning, collaborative learning, and PALS, require that students work cooperatively in small groups to achieve joint learning goals. Cooperative learning is based on two theories: Structure-Process-Outcome theory and Social Interdependence theory. Four types of cooperative learning have been derived: formal cooperative learning, informal cooperative learning, cooperative base groups, and constructive controversy. There is considerable research confirming the effectiveness of cooperative learning. To be cooperative, however, five basic elements must be structured into the situation: positive interdependence, individual accountability, promotive interaction, social skills, and group processing.",book:{id:"6929",slug:"active-learning-beyond-the-future",title:"Active Learning",fullTitle:"Active Learning - Beyond the Future"},signatures:"David W. Johnson and Roger T. Johnson",authors:[{id:"259976",title:"Dr.",name:"David",middleName:null,surname:"Johnson",slug:"david-johnson",fullName:"David Johnson"},{id:"263004",title:"Dr.",name:"Roger",middleName:null,surname:"Johnson",slug:"roger-johnson",fullName:"Roger Johnson"}]},{id:"58060",doi:"10.5772/intechopen.72341",title:"Pedagogy of the Twenty-First Century: Innovative Teaching Methods",slug:"pedagogy-of-the-twenty-first-century-innovative-teaching-methods",totalDownloads:8833,totalCrossrefCites:17,totalDimensionsCites:23,abstract:"In the twenty-first century, significant changes are occurring related to new scientific discoveries, informatization, globalization, the development of astronautics, robotics, and artificial intelligence. This century is called the age of digital technologies and knowledge. How is the school changing in the new century? How does learning theory change? Currently, you can hear a lot of criticism that the classroom has not changed significantly compared to the last century or even like two centuries ago. Do the teachers succeed in modern changes? The purpose of the chapter is to summarize the current changes in didactics for the use of innovative teaching methods and study the understanding of changes by teachers. In this chapter, we consider four areas: the expansion of the subject of pedagogy, environmental approach to teaching, the digital generation and the changes taking place, and innovation in teaching. The theory of education, figuratively speaking, has two levels. At the macro-level, in the “education-society” relationship, decentralization and diversification, internationalization of education, and the introduction of digital technologies occur. At the micro-level in the “teacher-learner” relationship, there is an active mix of traditional and innovative methods, combination of an activity approach with an energy-informational environment approach, cognition with constructivism and connectivism.",book:{id:"5980",slug:"new-pedagogical-challenges-in-the-21st-century-contributions-of-research-in-education",title:"New Pedagogical Challenges in the 21st Century",fullTitle:"New Pedagogical Challenges in the 21st Century - Contributions of Research in Education"},signatures:"Aigerim Mynbayeva, Zukhra Sadvakassova and Bakhytkul\nAkshalova",authors:[{id:"201997",title:"Dr.",name:"Aigerim",middleName:null,surname:"Mynbayeva",slug:"aigerim-mynbayeva",fullName:"Aigerim Mynbayeva"},{id:"209208",title:"Dr.",name:"Zukhra",middleName:null,surname:"Sadvakassova",slug:"zukhra-sadvakassova",fullName:"Zukhra Sadvakassova"},{id:"209210",title:"Dr.",name:"Bakhytkul",middleName:null,surname:"Akshalova",slug:"bakhytkul-akshalova",fullName:"Bakhytkul Akshalova"}]},{id:"59468",doi:"10.5772/intechopen.74344",title:"Virtual and Augmented Reality: New Frontiers for Clinical Psychology",slug:"virtual-and-augmented-reality-new-frontiers-for-clinical-psychology",totalDownloads:2364,totalCrossrefCites:13,totalDimensionsCites:21,abstract:"In the last decades, the applied approach for the use of virtual reality (VR) and augmented reality (AR) on clinical and health psychology has grown exponentially. These technologies have been used to treat several mental disorders, for example, phobias, stress-related disorders, depression, eating disorders, and chronic pain. The importance of VR/AR for the mental health field comes from three main concepts: (1) VR/AR as an imaginal technology, people can feel “as if they are” in a reality that does not exist in external world; (2) VR/AR as an embodied technology, the experience to feel user’s body inside the virtual environment; and (3) VR/AR as connectivity technology, the “end of geography’. In this chapter, we explore the opportunities provided by VR/AR as technologies to improve people’s quality of life and to discuss new frontiers for their application in mental health and psychological well-being promotion.",book:{id:"6543",slug:"state-of-the-art-virtual-reality-and-augmented-reality-knowhow",title:"State of the Art Virtual Reality and Augmented Reality Knowhow",fullTitle:"State of the Art Virtual Reality and Augmented Reality Knowhow"},signatures:"Sara Ventura, Rosa M. Baños and Cristina Botella",authors:[{id:"106036",title:"Dr.",name:"Rosa Maria",middleName:null,surname:"Baños",slug:"rosa-maria-banos",fullName:"Rosa Maria Baños"},{id:"227763",title:"Ph.D.",name:"Sara",middleName:null,surname:"Ventura",slug:"sara-ventura",fullName:"Sara Ventura"},{id:"229056",title:"Dr.",name:"Cristina",middleName:null,surname:"Botella",slug:"cristina-botella",fullName:"Cristina Botella"}]},{id:"64583",doi:"10.5772/intechopen.81714",title:"Evaluating a Course for Teaching Advanced Programming Concepts with Scratch to Preservice Kindergarten Teachers: A Case Study in Greece",slug:"evaluating-a-course-for-teaching-advanced-programming-concepts-with-scratch-to-preservice-kindergart",totalDownloads:1422,totalCrossrefCites:13,totalDimensionsCites:18,abstract:"Coding is a new literacy for the twenty-first century, and as a literacy, coding enables new ways of thinking and new ways of communicating and expressing ideas, as well as new ways of civic participation. A growing number of countries, in Europe and beyond, have established clear policies and frameworks for introducing computational thinking (CT) and computer programming to young children. In this chapter, we discuss a game-based approach to coding education for preservice kindergarten teachers using Scratch. The aim of using Scratch was to excite students’ interest and familiarize them with the basics of programming in an open-ended, project-based, and personally meaningful environment for a semester course in the Department of Preschool Education in the University of Crete. For 13 weeks, students were introduced to the main Scratch concepts and, afterward, were asked to prepare their projects. For the projects, they were required to design their own interactive stories to teach certain concepts about mathematics or physical science to preschool-age students. The results we obtained were more satisfactory than expected and, in some regards, encouraging if one considers the fact that the research participants had no prior experiences with computational thinking.",book:{id:"6936",slug:"early-childhood-education",title:"Early Childhood Education",fullTitle:"Early Childhood Education"},signatures:"Stamatios Papadakis and Michail Kalogiannakis",authors:null}],mostDownloadedChaptersLast30Days:[{id:"58060",title:"Pedagogy of the Twenty-First Century: Innovative Teaching Methods",slug:"pedagogy-of-the-twenty-first-century-innovative-teaching-methods",totalDownloads:8832,totalCrossrefCites:17,totalDimensionsCites:23,abstract:"In the twenty-first century, significant changes are occurring related to new scientific discoveries, informatization, globalization, the development of astronautics, robotics, and artificial intelligence. This century is called the age of digital technologies and knowledge. How is the school changing in the new century? How does learning theory change? Currently, you can hear a lot of criticism that the classroom has not changed significantly compared to the last century or even like two centuries ago. Do the teachers succeed in modern changes? The purpose of the chapter is to summarize the current changes in didactics for the use of innovative teaching methods and study the understanding of changes by teachers. In this chapter, we consider four areas: the expansion of the subject of pedagogy, environmental approach to teaching, the digital generation and the changes taking place, and innovation in teaching. The theory of education, figuratively speaking, has two levels. At the macro-level, in the “education-society” relationship, decentralization and diversification, internationalization of education, and the introduction of digital technologies occur. At the micro-level in the “teacher-learner” relationship, there is an active mix of traditional and innovative methods, combination of an activity approach with an energy-informational environment approach, cognition with constructivism and connectivism.",book:{id:"5980",slug:"new-pedagogical-challenges-in-the-21st-century-contributions-of-research-in-education",title:"New Pedagogical Challenges in the 21st Century",fullTitle:"New Pedagogical Challenges in the 21st Century - Contributions of Research in Education"},signatures:"Aigerim Mynbayeva, Zukhra Sadvakassova and Bakhytkul\nAkshalova",authors:[{id:"201997",title:"Dr.",name:"Aigerim",middleName:null,surname:"Mynbayeva",slug:"aigerim-mynbayeva",fullName:"Aigerim Mynbayeva"},{id:"209208",title:"Dr.",name:"Zukhra",middleName:null,surname:"Sadvakassova",slug:"zukhra-sadvakassova",fullName:"Zukhra Sadvakassova"},{id:"209210",title:"Dr.",name:"Bakhytkul",middleName:null,surname:"Akshalova",slug:"bakhytkul-akshalova",fullName:"Bakhytkul Akshalova"}]},{id:"61746",title:"Facilitation of Teachers’ Professional Development through Principals’ Instructional Supervision and Teachers’ Knowledge- Management Behaviors",slug:"facilitation-of-teachers-professional-development-through-principals-instructional-supervision-and-t",totalDownloads:3384,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"With the rise of global competition and the focus on teacher quality, teacher professional development is becoming increasingly crucial, and the stress and challenges for principals are more severe than ever. Teachers can improve their professional abilities through principals’ instructional supervision and their own knowledge-management (KM) behaviors to benefit students. Thus, this chapter analyzes the relationship among principals’ instructional supervision, teachers’ KM, and teachers’ professional development. The author believes that principals’ instructional supervision and effective KM can facilitate the professional development of teachers. The author also believes the readers can know the relationships among them, and teachers’ professional development can be improved through principal’s instructional supervision and teachers’ KM behaviors.",book:{id:"6674",slug:"contemporary-pedagogies-in-teacher-education-and-development",title:"Contemporary Pedagogies in Teacher Education and Development",fullTitle:"Contemporary Pedagogies in Teacher Education and Development"},signatures:"Chien-Chin Chen",authors:[{id:"232569",title:"Ph.D.",name:"Chien Chih",middleName:null,surname:"Chen",slug:"chien-chih-chen",fullName:"Chien Chih Chen"}]},{id:"75908",title:"From the Classroom into Virtual Learning Environments: Essential Knowledge, Competences, Skills and Pedagogical Strategies for the 21st Century Teacher Education in Kenya",slug:"from-the-classroom-into-virtual-learning-environments-essential-knowledge-competences-skills-and-ped",totalDownloads:519,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"As teachers in Kenya begin to migrate from the classroom to virtual learning spaces following COVID 19 pandemic, there is pressing need to realign Teacher Education to requisite Knowledge, competences, skills, and attitudes that will support online teaching. This chapter explores these needs using a combination of lived experiences and literature review that captured a meta-analysis of research trends on e-learning. While trends in Teacher Education indicate progression towards adoption of technology, there are disparities between the theory and practice. Evidence from recent research and reports; and the recollected experiences confirmed knowledge, competence, skills and pedagogical gaps in the implementation of online learning, that have been exacerbated by COVID-19. The researcher recommends that teacher education should sensitize and train teacher trainees on how to access, analyze and use new knowledge emerging with technology; they also should be coached on how learners learn with technology and on fundamentals of the communication process. Particularly the course on educational technology, should focus on how to create and manage online courses. The 5-stage E-Moderator Model and Universal Design for Learning (UDL) are recommended as effective pedagogical scaffold for online teaching.",book:{id:"10229",slug:"teacher-education-in-the-21st-century-emerging-skills-for-a-changing-world",title:"Teacher Education in the 21st Century",fullTitle:"Teacher Education in the 21st Century - Emerging Skills for a Changing World"},signatures:"Catherine Adhiambo Amimo",authors:[{id:"333482",title:"Dr.",name:"Catherine Adhiambo",middleName:null,surname:"Amimo",slug:"catherine-adhiambo-amimo",fullName:"Catherine Adhiambo Amimo"}]},{id:"75224",title:"Decoding the Digital Gap in Teacher Education: Three Perspectives across the Globe",slug:"decoding-the-digital-gap-in-teacher-education-three-perspectives-across-the-globe",totalDownloads:589,totalCrossrefCites:0,totalDimensionsCites:4,abstract:"Educational use of technology is regularly assessed, and results often show a gap between educational policies and what is actually practiced. This chapter will help clarify how teacher educators experience the changing educational contexts due to the digital revolution, how their meaning-making shifts, and how outside forces influence those processes. The results are based on comparative international studies. Central for this study is practitioners’ professional digital competence, their attitudes towards digital technology and the use of digital technology in education. We found that the influence and contribution of digital practice is carried out quite differently across the globe. Our research questions were: How do practitioners experience teaching in a rapidly changing context? How do attitudes change due to top-down governing of education? and What motivates teacher educators to implement digital technology?",book:{id:"10229",slug:"teacher-education-in-the-21st-century-emerging-skills-for-a-changing-world",title:"Teacher Education in the 21st Century",fullTitle:"Teacher Education in the 21st Century - Emerging Skills for a Changing World"},signatures:"Steinar Thorvaldsen and Siri Sollied Madsen",authors:[{id:"332624",title:"Associate Prof.",name:"Siri Sollied",middleName:null,surname:"Madsen",slug:"siri-sollied-madsen",fullName:"Siri Sollied Madsen"},{id:"332626",title:"Prof.",name:"Steinar",middleName:null,surname:"Thorvaldsen",slug:"steinar-thorvaldsen",fullName:"Steinar Thorvaldsen"}]},{id:"75416",title:"Self-Study Research: Challenges and Opportunities in Teacher Education",slug:"self-study-research-challenges-and-opportunities-in-teacher-education",totalDownloads:777,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This article aims to describe what self-study research is, why self-study can be a good approach to teacher educators’ professional development and improvements in practice and highlight some challenges and opportunities in this research approach. In addition, the article will shed light on some methodological aspects related to self-study. Self-study refers to teacher educators who in an intentionally and systematically way examine their practice to improve it, based on a deeper understanding of practice, as well as the context practice takes place. In the article, I argue that engaging in self-study is a learning and development process and an approach to developing personal professionalism, collective professionalism and improvements in practice.",book:{id:"10229",slug:"teacher-education-in-the-21st-century-emerging-skills-for-a-changing-world",title:"Teacher Education in the 21st Century",fullTitle:"Teacher Education in the 21st Century - Emerging Skills for a Changing World"},signatures:"Kåre Hauge",authors:[{id:"332053",title:"Associate Prof.",name:"Kåre",middleName:null,surname:"Hauge",slug:"kare-hauge",fullName:"Kåre Hauge"}]}],onlineFirstChaptersFilter:{topicId:"265",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:141,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:124,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/23.jpg",latestPublicationDate:"August 12th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"280770",title:"Dr.",name:"Katherine K.M.",middleName:null,surname:"Stavropoulos",slug:"katherine-k.m.-stavropoulos",fullName:"Katherine K.M. Stavropoulos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRdFuQAK/Profile_Picture_2022-05-24T09:03:48.jpg",biography:"Katherine Stavropoulos received her BA in Psychology from Trinity College, in Connecticut, USA and her Ph.D. in Experimental Psychology from the University of California, San Diego. She completed her postdoctoral work at the Yale Child Study Center with Dr. James McPartland. Dr. Stavropoulos’ doctoral dissertation explored neural correlates of reward anticipation to social versus nonsocial stimuli in children with and without autism spectrum disorders (ASD). She has been a faculty member at the University of California, Riverside in the School of Education since 2016. Her research focuses on translational studies to explore the reward system in ASD, as well as how anxiety contributes to social challenges in ASD. She also investigates how behavioral interventions affect neural activity, behavior, and school performance in children with ASD. She is also involved in the diagnosis of children with ASD and is a licensed clinical psychologist in California. 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