NIH scoring criteria
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"10269",leadTitle:null,fullTitle:"Network-on-Chip - Architecture, Optimization, and Design Explorations",title:"Network-on-Chip",subtitle:"Architecture, Optimization, and Design Explorations",reviewType:"peer-reviewed",abstract:"Limitations of bus-based interconnections related to scalability, latency, bandwidth, and power consumption for supporting the related huge number of on-chip resources result in a communication bottleneck. These challenges can be efficiently addressed with the implementation of a network-on-chip (NoC) system. This book gives a detailed analysis of various on-chip communication architectures and covers different areas of NoCs such as potentials, architecture, technical challenges, optimization, design explorations, and research directions. In addition, it discusses current and future trends that could make an impactful and meaningful contribution to the research and design of on-chip communications and NoC systems.",isbn:"978-1-83968-158-5",printIsbn:"978-1-83968-148-6",pdfIsbn:"978-1-83968-159-2",doi:"10.5772/intechopen.91110",price:119,priceEur:129,priceUsd:155,slug:"network-on-chip-architecture-optimization-and-design-explorations",numberOfPages:110,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"7f244dbc91db3a8dc7b68cd5a944e6dc",bookSignature:"Isiaka A. Alimi, Oluyomi Aboderin, Nelson J. Muga and António L. Teixeira",publishedDate:"April 6th 2022",coverURL:"https://cdn.intechopen.com/books/images_new/10269.jpg",numberOfDownloads:1259,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:3,numberOfDimensionsCitationsByBook:0,hasAltmetrics:0,numberOfTotalCitations:3,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"July 2nd 2020",dateEndSecondStepPublish:"October 2nd 2020",dateEndThirdStepPublish:"December 1st 2020",dateEndFourthStepPublish:"February 19th 2021",dateEndFifthStepPublish:"April 20th 2021",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"208236",title:"Dr.",name:"Isiaka",middleName:"Ajewale",surname:"Alimi",slug:"isiaka-alimi",fullName:"Isiaka Alimi",profilePictureURL:"https://mts.intechopen.com/storage/users/208236/images/system/208236.jpg",biography:"Isiaka A. Alimi received his Ph.D. in Telecommunications Engineering from the University of Aveiro, Portugal. He was with the Federal Radio Corporation of Nigeria as a senior engineer (RF transmission and management) and the Department of Electrical and Electronics Engineering, Federal University of Technology, Akure, Nigeria, as a lecturer. He is currently a researcher at the Instituto de Telecomunicações, Aveiro, Portugal, where he has been participating in various R&D activities. He has authored/co-authored more than forty technical papers, nine book chapters, and has co-edited one book. His research interests include optical communications, microwave photonics, network security, fixed-mobile broadband (wired and wireless technologies) convergence, and their applications for effective resources management in access networks. He is a member of the Institute of Electrical and Electronics Engineers (IEEE).",institutionString:"Instituto de Telecomunicações",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Instituto de Telecomunicações",institutionURL:null,country:{name:"Portugal"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"281158",title:"Dr.",name:"Oluyomi",middleName:null,surname:"Aboderin",slug:"oluyomi-aboderin",fullName:"Oluyomi Aboderin",profilePictureURL:"https://mts.intechopen.com/storage/users/281158/images/system/281158.png",biography:"Oluyomi Aboderin obtained a Ph.D. in Telecommunications Engineering from the University of Porto, Portugal. He also obtained a master’s degree in Personal Mobile and Satellite Communications from the University of Bradford, United Kingdom, and a bachelor’s degree from the Ladoke Akintola University of Technology, Nigeria. He joined the National Space Research and Development Agency in 2005 and is currently an assistant director with the agency, in the frequency coordination and management team. He was a researcher with Instituto de Telecommunicações, Aveiro, Portugal, and has been participating in various research and development activities. He has published more than ten technical papers, including a patent. His research interests include satellite channel modeling, frequency management, antenna design, underwater communications, and microwave photonics.",institutionString:"Instituto de Telecomunicações",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Instituto de Telecomunicações",institutionURL:null,country:{name:"Portugal"}}},coeditorTwo:{id:"318930",title:"Dr.",name:"Nelson J.",middleName:null,surname:"Muga",slug:"nelson-j.-muga",fullName:"Nelson J. Muga",profilePictureURL:"https://mts.intechopen.com/storage/users/318930/images/system/318930.jpg",biography:"Nelson Muga graduated in Physics from the University of Porto, Portugal, in 2002. He received a master\\'s degree in Applied Physics in 2006, and a Ph.D. in Physical Engineering in 2011, both from the University of Aveiro, Portugal. He has been a lecturer in the Physics Department, the University of Aveiro since 2016, where he teaches courses related to optics, optoelectronics, and photonics. Currently, he is an auxiliary researcher at the Instituto de Telecomunicações, Aveiro, where, over the years, he has participated as a researcher in more than twenty-five R&D projects, developing expertise in the field of high-speed optical communications and quantum-secure optical communication systems and technologies. He has published more than forty papers in international journals and more than sixty international conference proceedings. 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He joined the University of Aveiro in 1999 and is presently a full professor and a senior researcher in the Instituto de Telecomunicações. Since 2014, he has been the dean of the Doctoral School, University of Aveiro. Dr. Teixeira has worked at several industrial organizations, including Nokia Siemens Networks, Coriant, and PICadvanced, a startup in photonics that he cofounded that employs more than forty highly skilled persons. He holds eleven patents and has published more than 400 papers. He has supervised more than seventy MSc and fifteen Ph.D. students and has participated in more than thirty-five national and international projects.",institutionString:"Universidade de Aveiro",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorFour:null,coeditorFive:null,topics:[{id:"735",title:"Circuit Design",slug:"circuit-design"}],chapters:[{id:"76322",title:"Retracted: Design and Optimization of Networks-on-Chip",doi:"10.5772/intechopen.97341",slug:"retracted-design-and-optimization-of-networks-on-chip",totalDownloads:129,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"The modules on the IC unit now and then semiconductor science centers schematizing fluctuated elements of the PC framework and unit intended to be ordinary among the feeling of organization science. Another issue in NoC environmental factors is that the directing recipe. Regarding conveying system, for example alteration strategy, their unit contrasting sorts of adjustment strategies like circuit change, bundle alteration, and empty adjustment. The configurable interconnection parts give a data profitable, significantly progressed association from the processor and information perilous in place based knowledge official structures. What’s extra, the configurable Interconnect supports a multi-layer topography that guarantees the fundamental plan of assessment and low torpidity for each related Ip and it gives related advancements, as for voltage and repeat scaling. The Open Core Protocol can be a fitting and play interface for a middle having every master and slave interfaces. Organization interfacing: The achievement of the NoC style worldview relies significantly upon the normalization of the interfaces between science centers and furthermore the interconnection material. As demonstrated inside the figure beneath, for a center having each expert and slave interfaces, the OCP agreeable signs of the deliberate science block square measure packetized by a subsequent interface.",signatures:"Riko Herwanto and Nurfiana",downloadPdfUrl:"/chapter/pdf-download/76322",previewPdfUrl:"/chapter/pdf-preview/76322",authors:[null],corrections:null},{id:"75261",title:"Direct and External Hybrid Modulation Approaches for Access Networks",doi:"10.5772/intechopen.96085",slug:"direct-and-external-hybrid-modulation-approaches-for-access-networks",totalDownloads:173,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:"The demand for low-cost high-speed transmission is a major challenge for 5G future networks. To meet this optical communication demand, holistic and painstaking approaches are required in designing a simplified system model. Since the demands for high bandwidth are growing at unprecedented speed as we approach the Zettabyte era, it is crucial to minimize chromatic dispersion (CD) associated to high bit-rate signals. Mitigating CD electronically comes at high cost which may not be compatible with 5G. Photonic Integrated Circuit (PIC) as an enabler for fast speed optical transmission is still undergoing its growth stage and its major speed and efficiency have not yet been attained. However, proper and right combination of components and approaches can potentiate this technology in a more cost-efficient way. Hybrid modulation (HM)-PIC presents a simplified approach in terms of cost and efficiency for 5G networks. Hybridization of existing modulation components and approaches in PIC can enhance the generation of high bit-rate signals without the need for electrical CD compensation. A detailed study of hybrid multilevel signal modulation concept as a valuable solution for Data Centers (DC) high data-rate signals and next-generation Passive Optical Networks (PONs) is proposed.",signatures:"Adebayo E. Abejide, Madhava R. Kota, Sushma Pandey, Oluyomi Aboderin, Cátia Pinho, Mário Lima and António Teixeira",downloadPdfUrl:"/chapter/pdf-download/75261",previewPdfUrl:"/chapter/pdf-preview/75261",authors:[{id:"208242",title:"Dr.",name:"António L.",surname:"Teixeira",slug:"antonio-l.-teixeira",fullName:"António L. Teixeira"},{id:"282599",title:"Ph.D.",name:"Cátia",surname:"Pinho",slug:"catia-pinho",fullName:"Cátia Pinho"},{id:"295785",title:"Prof.",name:"Mário",surname:"Lima",slug:"mario-lima",fullName:"Mário Lima"},{id:"330084",title:"Mr.",name:"Adebayo E.",surname:"Abejide",slug:"adebayo-e.-abejide",fullName:"Adebayo E. Abejide"},{id:"337970",title:"Mr.",name:"Madhava",surname:"R. Kota",slug:"madhava-r.-kota",fullName:"Madhava R. Kota"},{id:"337971",title:"Ms.",name:"Sushma",surname:"Pandey",slug:"sushma-pandey",fullName:"Sushma Pandey"},{id:"337972",title:"Dr.",name:"Oluyomi",surname:"Aboderin",slug:"oluyomi-aboderin",fullName:"Oluyomi Aboderin"}],corrections:null},{id:"75882",title:"MAS: Maximum Energy-Aware Sense Amplifier Link for Asynchronous Network on Chip",doi:"10.5772/intechopen.95075",slug:"mas-maximum-energy-aware-sense-amplifier-link-for-asynchronous-network-on-chip",totalDownloads:158,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"A real-time multiprocessor chip model is also called a Network-on-Chip (NoC), and deals a promising architecture for future systems-on-chips. Even though a lot of Double Tail Sense Amplifiers are used in architectural approach, the existing DTSA with transceiver exhibits a difficulty of consuming more energy than its gouged design during various traffic condition. Novel Low Power pulse Triggered Flip Flop with DTSA is designed in this research to eliminate the difficulty. The Traffic Aware Sense amplifier MAS consists of Sense amplifiers (SA’s), Traffic Generator, and Estimator. Among various SA’S suitable (DTSA and NLPTF -DTSA) SA are selected and information transferred to the receiver. The performance of both DTSA with Transceiver and NLPTF-DTSA with transceiver compared under various traffic conditions. The proposed design (NLPTF-DTSA) is observed on TSMC 90 nm technology, showing 5.92 Gb/s data rate and 0.51 W total link power.",signatures:"Erulappan Sakthivel and Rengaraj Madavan",downloadPdfUrl:"/chapter/pdf-download/75882",previewPdfUrl:"/chapter/pdf-preview/75882",authors:[{id:"328158",title:"Associate Prof.",name:"Erulappan",surname:"Sakthivel",slug:"erulappan-sakthivel",fullName:"Erulappan Sakthivel"},{id:"347254",title:"Dr.",name:"Rengaraj",surname:"Madavan",slug:"rengaraj-madavan",fullName:"Rengaraj Madavan"}],corrections:null},{id:"76266",title:"Network-on-Chip Topologies: Potentials, Technical Challenges, Recent Advances and Research Direction",doi:"10.5772/intechopen.97262",slug:"network-on-chip-topologies-potentials-technical-challenges-recent-advances-and-research-direction",totalDownloads:487,totalCrossrefCites:0,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Integration technology advancement has impacted the System-on-Chip (SoC) in which heterogeneous cores are supported on a single chip. Based on the huge amount of supported heterogeneous cores, efficient communication between the associated processors has to be considered at all levels of the system design to ensure global interconnection. This can be achieved through a design-friendly, flexible, scalable, and high-performance interconnection architecture. It is noteworthy that the interconnections between multiple cores on a chip present a considerable influence on the performance and communication of the chip design regarding the throughput, end-to-end delay, and packets loss ratio. Although hierarchical architectures have addressed the majority of the associated challenges of the traditional interconnection techniques, the main limiting factor is scalability. Network-on-Chip (NoC) has been presented as a scalable and well-structured alternative solution that is capable of addressing communication issues in the on-chip systems. In this context, several NoC topologies have been presented to support various routing techniques and attend to different chip architectural requirements. This book chapter reviews some of the existing NoC topologies and their associated characteristics. Also, application mapping algorithms and some key challenges of NoC are considered.",signatures:"Isiaka A. Alimi, Romil K. Patel, Oluyomi Aboderin, Abdelgader M. Abdalla, Ramoni A. Gbadamosi, Nelson J. Muga, Armando N. Pinto and António L. Teixeira",downloadPdfUrl:"/chapter/pdf-download/76266",previewPdfUrl:"/chapter/pdf-preview/76266",authors:[{id:"208236",title:"Dr.",name:"Isiaka",surname:"Alimi",slug:"isiaka-alimi",fullName:"Isiaka Alimi"},{id:"281158",title:"Dr.",name:"Oluyomi",surname:"Aboderin",slug:"oluyomi-aboderin",fullName:"Oluyomi Aboderin"},{id:"318930",title:"Dr.",name:"Nelson J.",surname:"Muga",slug:"nelson-j.-muga",fullName:"Nelson J. Muga"},{id:"208242",title:"Dr.",name:"António L.",surname:"Teixeira",slug:"antonio-l.-teixeira",fullName:"António L. Teixeira"},{id:"294778",title:"Dr.",name:"Abdelgader M.",surname:"Abdalla",slug:"abdelgader-m.-abdalla",fullName:"Abdelgader M. Abdalla"},{id:"346367",title:"Dr.",name:"Romil K.",surname:"Patel",slug:"romil-k.-patel",fullName:"Romil K. Patel"},{id:"346368",title:"Dr.",name:"Armando N.",surname:"Pinto",slug:"armando-n.-pinto",fullName:"Armando N. Pinto"},{id:"463476",title:"Dr.",name:"Ramoni A.",surname:"Gbadamosi",slug:"ramoni-a.-gbadamosi",fullName:"Ramoni A. Gbadamosi"}],corrections:null},{id:"74294",title:"A Novel Approach for the Design of Fault-Tolerant Routing Algorithms in NoCs: Passage of Faulty Nodes, Not Always Detour",doi:"10.5772/intechopen.94773",slug:"a-novel-approach-for-the-design-of-fault-tolerant-routing-algorithms-in-nocs-passage-of-faulty-nodes",totalDownloads:197,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Due to the faults in system fabrication and run time, designing an efficient fault-tolerant routing algorithm with the property of deadlock-freeness is crucial for realizing dependable Network-on-Chip (NoC) systems with high communication performance. In this chapter, we introduce a novel approach for the design of fault-tolerant routing algorithms in NoCs. The common idea of the fault-tolerant routing has been undoubtedly to detour faulty nodes, while our approach allows passing through faulty nodes with the slight modification of NoC architecture. As a design example, we present an XY-based routing algorithm with the passage function. To investigate the effect of the approach, we compare the communication performance (i.e. average latency) of the XY-based algorithm with well-known region-based algorithms under the condition of with and without virtual channels. Finally, we provide possible directions of future research on the fault-tolerant routing with the passage function.",signatures:"Masaru Fukushi and Yota Kurokawa",downloadPdfUrl:"/chapter/pdf-download/74294",previewPdfUrl:"/chapter/pdf-preview/74294",authors:[{id:"327906",title:"Dr.",name:"Masaru",surname:"Fukushi",slug:"masaru-fukushi",fullName:"Masaru Fukushi"},{id:"327907",title:"Mr.",name:"Yota",surname:"Kurokawa",slug:"yota-kurokawa",fullName:"Yota Kurokawa"}],corrections:null},{id:"79521",title:"Digital Control of Active Network Microstructures on Silicon Wafers",doi:"10.5772/intechopen.101486",slug:"digital-control-of-active-network-microstructures-on-silicon-wafers",totalDownloads:115,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter presents a promising digital control of active microstructures developed and tested on silicon chips by current division and thus independent Joule heating powers, especially for planar submillimeter two-dimensional (2-D) grid microstructures built on silicon wafers by surface microfabrication. Current division on such 2-D grid networks with 2 × 2, 3 × 3, and n × n loops was modeled and analyzed theoretically by employing Kirchhoff’s voltage law (KVL) and Kirchhoff’s current law (KCL), which demonstrated the feasibility of active control of the networks by Joule heating effect. Furthermore, in situ testing of a typical 2-D microstructure with 2 × 2 loops by different DC sources was carried out, and the thermomechanical deformation due to Joule heating was recorded. As a result, active control of the current division has been proven to be a reliable and efficient approach to achieving the digital actuation of 2-D microstructures on silicon chips. Digital control of such microstructural networks on silicon chips envisions great potential applications in active reconfigurable buses for microrobots and flexible electronics.",signatures:"Zhongjing Ren, Jianping Yuan and Peng Yan",downloadPdfUrl:"/chapter/pdf-download/79521",previewPdfUrl:"/chapter/pdf-preview/79521",authors:[{id:"15527",title:"Prof.",name:"Jianping",surname:"Yuan",slug:"jianping-yuan",fullName:"Jianping Yuan"},{id:"423215",title:"Dr.",name:"Zhongjing",surname:"Ren",slug:"zhongjing-ren",fullName:"Zhongjing Ren"},{id:"441608",title:"Prof.",name:"Peng",surname:"Yan",slug:"peng-yan",fullName:"Peng Yan"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"8723",title:"Telecommunication Systems",subtitle:"Principles and Applications of Wireless-Optical Technologies",isOpenForSubmission:!1,hash:"8bf1ec49936ab44fcdfc9fea042e73d7",slug:"telecommunication-systems-principles-and-applications-of-wireless-optical-technologies",bookSignature:"Isiaka A. 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Human leukocyte antigen (HLA) molecules are expressed on almost all nucleated cells, and they are the major molecules that initiate graft rejection. There are three classical loci at HLA class I: HLA-A, -B, and -Cw, and five loci at class II: HLA-DR, -DQ, -DP, -DM, and -DO. HLA loci are the most genetically variable gene loci in human. Two hundred and twenty four loci of HLA complex have been identified so far. Among these, 128 are functional loci that encode proteins, and 39.8% of HLA genes are related to the immune system, particularly those belong to class II loci. Almost all these genes display immune-related functions. Approximately 100 HLA genes loci have been cloned and named and at least 18 of them have alleles. Since these loci have various amounts of alleles and each allele encodes a corresponding HLA antigen, the HLA complex has the most abundant genetic polymorphism in the human immune system.
Systemic investigations of the alleles in HLA loci began in 1987. There were just over 10 identified alleles at that time. The allele numbers in HLA-I and HLA-II loci were increased to 100 and 50 respectively in 1989. The allele number of HLA-I and HLA-II reached 1028 in 2000. As of July 2013, the total allele number of HLA loci has reached 9719. HLA-A, HLA-B and HLA-C loci have 2365, 3015 and 1848 alleles respectively. DRA site has 7 and DRB site has 1456 alleles. DQA1 and DQB1 sites have 51 and 416 alleles respectively; DPB1 sites have 37 and 190 alleles, respectively (Fig 1). Theoretically, it is very difficult to find an unrelated donor with a perfectly matched HLA genotype (at the allele level) in the general population.
The polymorphism of HLA makes it difficult to find a match between unrelated donor and recipient in the allo-transplantation. Currently, the most commonly used HLA typing in organ transplantations around the world is based on HLA-A, B, C and DR genes. There are up to 8600 alleles in these genes corresponding to more than 100 specific antigens. With the increasing number of patients who need hematopoietic stem cell transplantation, the lack of appropriate donors has become a significant challenge. Therefore, there is an urgent need to develop novel scientific, practical, and feasible HLA typing methods in the field of organ and hematopoietic stem cell transplantation.
Increasing number of HLA alleles from 1987 to July 2013
The influence of HLA compatibility on organ transplant survival was analyzed in more than 150,000 recipients transplanted from 1987 to 1997 at transplant centers participating in the Collaborative Transplant Study. A statistically highly significant effect of HLA matching on graft and patient survival rates was found in the analysis of kidney transplants (P < 0.0001). Ten years after transplantation, the graft survival rate of first cadaver kidney transplants with a complete mismatch (6 HLA-A+B+DR mismatches) was 17% lower than that of grafts with no mismatch. During the first post-transplant year, the class II HLA-DR locus had a stronger impact than the class I HLA-A and HLA-B loci. During subsequent years, however, the influence on graft survival of the three loci was found to be equivalent and additive. For optimal graft outcome, compatibility at all three HLA loci is, therefore, desirable. The excellent correlation of HLA matching observed in recipients of cadaver kidneys with very short ischemic preservation (0-6 hours) or recipients of kidneys from living unrelated donors contradicts reports that short ischemia can eliminate the influence of matching.
Although HLA has a significant effect on graft outcome regardless of the state of presensitization, the matching effect is potentiated in patients with highly reactive preformed lymphocytotoxic antibodies. Among first cadaver transplant recipients with an antibody reactivity against > 50% of the test panel, the difference in graft survival at 5 years between patients with 0 or 6 mismatches reached 30%. A collaborative project, in which molecular DNA typing methods were employed, showed that the correction of serological HLA typing errors by more accurate DNA typing results in a significantly improved HLA matching effect. Moreover, matching for the class II locus HLA-DP, a locus that can be typed reliably only by DNA methods, showed a significant effect in cadaver kidney retransplants, especially in the presence of preformed lymphocytotoxic antibodies. The analysis of heart transplants showed a highly significant impact of HLA compatibility on graft outcome (P < 0.0001). This result is of particular interest because donor hearts are not allocated according to the HLA match. A biasing influence of donor organ allocation (i.e. a preferential allocation of good matches to good risk recipients) can, therefore, be excluded. In liver transplantation, neither matching for HLA class I nor HLA class II could be shown to influence transplant outcome.
The first successful human bone marrow transplantation between identical twins in 1957 has provided a new approach for the treatment of leukemia and other hematologic malignancies. After the successful hematopoietic stem cell transplantation between unrelated donor and recipient with matched HLA, a bone marrow donor registry was established in 1988 (National Marrow Donor Program, NMDP) in the USA. Later on, a public cord blood bank was established. According to the World Marrow Donor Association (WMDA), as of July 2012, the association has 68 bone marrow banks in 49 countries and regions. It also has 46 cord blood banks in 30 countries and regions. The registered bone marrow and umbilical cord blood donors have exceeded 20 million. Meanwhile, the technology of HLA typing has been transformed from simple serotyping to more accurate genotyping. Although there are hundreds of reports regarding the effect of HLA matching degree on the efficacy of hematopoietic stem cell transplantation, these results are not consistent due to the differences in sample size, disease type and stage, and HLA typing. In addition, the interpretation of HLA genotyping results and their biological significance is becoming increasingly complicated. It is challenging for the clinicians outside of the HLA field to select an unrelated donor with the best-matched HLA. To meet this challenge, WMDA, NMDP of the USA and European Federation of Immunogenetics (EFI) have provided guidelines for HLA typing.
The technology for HLA typing has evolved from the serological level to the cellular level, to the molecular level. Serotyping was the mainstream method for HLA type and has played a critical role in organ transplantations before 1990s. However, most HLA antisera are polyclonal and often have cross-reactions, making it difficult to distinguish antigens with subtle structural differences, and leading to misidentifications. Furthermore, many factors, such as a prolonged transportation time of the blood sample and excessive amount of immature cells, may affect the result of serotyping and cellular typing.
The development of polymerase chain reaction (PCR) and its application in biomedical sciences has made the HLA typing at the DNA level possible. Therefore, using molecular methods to type HLA at the DNA level has gradually replaced serotyping and cellular typing. Commonly used DNA based HLA typing methods include PCR based sequence specific primers (PCR-SSP), and PCR based restriction fragment length polymorphism (PCR-RFLP), single-strand conformation polymorphism (PCR-SSCP), sequence-specific oligonucleotide (PCR-SSO) and single nucleotide polymorphism (PCR-SNP).
In recent years, there have been emerged many advanced techniques applied into HLA typing, such as microarray, reference strand mediated conformation (RSCA), PyrosequencingTM, flow cytometry and DNA sequencing. In the early 1990s, new permissible mismatching strategies based on HLA epitope and/or similarity between donor-recipient pairs were also established and employed in clinical application.
As early as 1956, Gorer et al. created a complement-dependent cytotoxicity assay for detecting alloantibodies in mice. In 1964, at the University of California, Los Angeles (UCLA), the Terasaki group introduced the microlymphocytotoxicity testing technique (microcytotoxicity assay) to human leukocyte antigen (HLA) typing studies after making several improvements and scaling down the procedures of HLA serological testing. Because the method was simple, reliable, and precise, yielding reproducible results, it was widely adopted for serological study of HLA and became an international standard technology recognized by the United States National Institute of Health (NIH). HLA cytotoxic antibodies are IgG and IgM isotypes. In the presence of complements, these antibodies are capable of binding with their corresponding antigens on the surface of lymphocytes and inducing holes on the membrane. There is no such effect if the lymphocytes do not carry the corresponding antigens. The principle for this reaction is shown in Figure 2. Dead lymphocytes with damaged membrane can be observed in a number of ways, the simplest of which staining with eosin or trypan blue. Dead cells are stained and appear expanded due to incorporation of the dye; live cells are not stained. Generally, the extent of the antigen-antibody reaction is determined on the basis of the percentage of dead cells. NIH criteria are shown in Table 1.
Subsequently, an improved one-step method was developed in which antibodies, lymphocytes, and complement are successively added and then stained and fixed. Results were observed under a microscope. An operational diagram is shown in Figure 3.
Microlymphocytotoxicity test principle diagram
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\t0-10 | \n\t\t\tNegative | \n\t\t
\n\t\t\t\t | \n\t\t\t11-20 | \n\t\t\tNegative | \n\t\t
\n\t\t\t\t | \n\t\t\t21-50 | \n\t\t\tWeak positive | \n\t\t
\n\t\t\t\t | \n\t\t\t51-80 | \n\t\t\tpositive | \n\t\t
\n\t\t\t\t | \n\t\t\t81-100 | \n\t\t\tStrong positive | \n\t\t
\n\t\t\t\t | \n\t\t\t\n\t\t\t | Not determinable | \n\t\t
NIH scoring criteria
Schematic diagram of the one-step microlymphocytotoxicity test
Microlymphocytotoxicity tests have significantly promoted HLA research in basic and clinical applications since their introduction into serotyping. Some claim that serological typing techniques are the basis of HLA research because they are such important tools. In modern research, serological typing methods are still the main methods in HLA-I antigen typing. However, as advancing HLA research has placed increasing demands on typing techniques, shortcomings of serotyping methods have been identified, and these have been difficult to overcome. (1) The standard antiserum in serological methods is mainly from human serum or placenta. Because the rate of positive HLA antibody in sera is generally low, in particular, for some rare antibodies, it can only be obtained through collection and screening of a large number of serum samples. The technology for screening antisera is complex, difficult, and resource and labor intensive. (2) There are significant numbers of strong cross-reactions that can occur between serological tests; it is difficult to distinguish the sample antigen from the subtype antigen. (3) A high variability between serum batches significantly affects the quality of HLA typing reagents. (4) Serological match plates must be transported and preserved at low temperatures (−80°C), constraints that are inconvenient for clinical applications.
In order to solve such problems in serological typing, Terasaki et al. in the late 1980s began to develop HLA monoclonal antibodies to replace the standard antiserum. Formal production of HLA monoclonal antibody matching reagents plates began in 1992, and its availability has significantly improved the quality of HLA matching reagents. A comparison of the main technical indicators of monoclonal antibody match plates with serological match plate is shown in Table 2.
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
\n\t\t\t\t | \n\t\t\tspecific and non-specific | \n\t\t\tspecific | \n\t\t
\n\t\t\t\t | \n\t\t\tunivalent and polyvalent | \n\t\t\tunivalent | \n\t\t
\n\t\t\t\t | \n\t\t\tlow (<1:8) | \n\t\t\thigh (>20000) | \n
\n\t\t | \n\tlimited | \n\talmost unlimited | \n
\n\t\t | \n\tmay exist | \n\tnon | \n
\n\t\t | \n\tstable | \n\tun-stable | \n
\n\t\t | \n\tDry ice low temperature | \n\troom temperature | \n
\n\t\t | \n\t-80°C | \n\t-20°C | \n
Comparison of key indicators of HLA monoclonal antibody typing plates with serological typing plates
A homozygous typing cell (HTC) is homozygous for the A antigen, A/A. In the assay, HTCs are used as stimulator cells. Cells to be examined contain an unknown antigen, X/X, and are responding cells. In the reaction, a one way mixture lymphocyte culture (MLC) consists of HTC (A/A) stimulator cells and the responder cells (X/X) being examined. An MLC reaction indicates that the responder cells could recognize the stimulator cells’s A antigens, and that the responder cells being examined do not have A antigens. Absence of the MLC reaction indicates that the cells being examined have A antigens. The examined cells could be either A heterozygous (A/X) or A homozygous (A/A). In a repeated test, cells can be determined to have the same antigen only when the cells are examined with a negative HTC cell reaction. This procedure is also known as negative typing. This technique is rarely used because of the difficulty in identifying HTC individuals by this method.
In 1975 SheChy and others established a primed lymphocyte typing method (PLT) based on characteristics of a secondary response. It can specifically identify primed cells and it is also known as positive typing. In the initial MLC of responding cells A and stimulation cells B, after 9–12 days of culture, responding cells A proliferated into lymphoblastoid cells, after which they reverted to small lymphocytes. These inactive small lymphocytes were actually sensitized memory cells, also known as primed lymphocytes (PLs). When PLs and former stimulator cells were tested in a second MLC, there were very high responses within 20–24 hours. The stimulator cells are called primed cells (priming) in this process. According to this principle, experimental results of PLT depend on both priming and responding cells. Therefore, when conducting PLT, PL grouped cells must be carefully selected. More than one type of PL should be used in the identification of a PLT antigen. Preparation and sources of pretreatment cells are complex and difficult, so this method is rarely used.
In 1964, Bain and Bach et al. found that lymphocytes from two unrelated individuals could stimulate each other in a mixed culture in a suitable in vitro environment. A lymphocyte could be activated and converted into a mother cell, resulting in the proliferation. After further research, other groups confirmed that mixed lymphocyte culture (MLC) is a good in vitro model for studying the cellular immune response, especially transplantation immunity. MLC technology was once widely used in organ transplantation and hematopoietic stem cell transplant matching. Because the technology is complex, has long testing cycles, involves radioactive elements, and has other drawbacks, it is gradually being replaced by the more convenient and higher-resolution genotyping methods. I will not go into the details of that method.
The technology for HLA typing has evolved from the serological level to the cellular level, to the molecular level. Serotyping was the mainstream method for HLA type and has played a critical role in organ transplantations before 1990s. However, most HLA antisera are polyclonal and often have cross-reactions, making it difficult to distinguish antigens with subtle structural differences, and leading to misidentifications. Furthermore, many factors, such as a prolonged transportation time of the blood sample and excessive amount of immature cells, may affect the result of serotyping and cellular typing. These are the limitations of traditional HLA typing methods. The development of polymerase chain reaction (PCR) and its application in biomedical sciences have made the HLA typing the DNA level possible. Therefore, using molecular methods to type HLA at the DNA level has been gradually replacing serotyping and cellular typing. Commonly used DNA based HLA typing methods include PCR with sequence specific primers (PCR-SSP), and PCR detection of restriction fragment length polymorphism (PCR-RFLP), single-strand conformation polymorphism (PCR-SSCP), sequence-specific oligonucleotide (PCR-SSO) and single nucleotide polymorphism (PCR-SNP).
To identify point mutations in a DNA molecule, Newton invented the amplification refractory mutation system (ARMS) for in vitro DNA amplification. The technique requires an allele sequence specific 3’ primer for the PCR amplification. Otherwise the PCR reaction will not be effective. This is because the Taq DNA polymerase used in the PCR reaction has 5’ to 3’ polymerase activity and 5’ to 3’ exonuclease activity but 3’ to 5’ exonuclease activity. Therefore, the enzyme cannot repair the single mismatched nucleotide in the 3’ primer. In order to amplify the allele with a specific sequence, the primer with the corresponding sequence is designed. The conditions for PCR reaction are strictly controlled so that the amplification of the fragment with its sequence perfectly matching to the primer is much more effective than the sequence with one or more mismatched nucleotide. One mismatched nucleotide between the 3’ primer and the template is sufficient to prevent the amplification. The PCR product is further analyzed by electrophoresis to determine whether the amplicon corresponds to the anticipated primer-specific product. Since the DNA sequence of HLA class I and class II genes are known, PCR primers can be designed based on the specific sequence of each allele for PCR-SSP genotyping.
The encoding allele sequences of various HLA antigens can be amplified with sequence specific primers. By controlling the conditions of PCR reaction, a specific primer can only amplify its corresponding allele, not other alleles. Therefore, whether there is a PCR product can be used to determine the presence or absence of a specific allele. The specificity of PCR product can be further determined by agarose gel electrophoresis. Fig 4 shows the principle of PCR-SSP.
The diagram of PCR reaction
In the first step of PCR reaction, double-stranded DNA is denatured into single-stranded DNA. In the second step, specific primers anneal to the template DNA. In the third step, double stranded DNA is generated by TaqDNA polymerase by incorporating 4 types of dNTP into the newly synthesized DNA strand. After 30 cycles of amplification, the target gene is increased to 108 fold.
The main advantage of this method is that it is simple and fast, and the result is easy to interpret. The heterozygosity can be easily detected as well. Therefore, PCR-SSP is the currently most used method for HLA typing. There are several FDA approved high-resolution and low-resolution detection kits available for HLA class I and class II typing. Many clinical laboratories in China have been using this method for accurate pre-transplantation HLA typing. The procedure of PCR-SSP is shown in Fig 5. One disadvantage of this method is that it requires multiple primers in order to amply all relevant alleles.
The process of PCR-SSP
Restriction endonucleases have unique recognition sites. Using computer software, restriction endonucleases that can recognize HLA sequence polymorphism are chosen to digest the PCR product. Because of sequence difference among the alleles, enzyme digestion will yield DNA fragments with unique patterns of length, which can be distinguished by electrophoresis.
Compared to serotyping, PCR-RFLP method is specific, simple and rapid and does not require probes. It can accurately detect single nucleotide difference and two linked polymorphic sites. The disadvantage of this method is that if the enzyme cannot completely digest the PCR product, the DNA fragments with similar lengths may be difficult to distinguish after electrophoresis. In addition, alleles need to have endonuclease recognition sites. Furthermore, PCR-RFLP cannot distinguish certain HLA heterozygosities. It requires multiple endonucleases for those alleles with high polymorphism such as HLA-DRB1, and may produce complicated restriction maps. For these reasons, this method is rarely used for HLA typing nowadays.
Orita
This method is simple, rapid, sensitive, requiring no special equipment and suitable for clinical applications. However, this method can only detect mutations. The location and the type of the mutation need to be determined by sequencing. In addition, the conditions of electrophoresis need to be tightly controlled. Furthermore, point mutations in certain locations may have no effect or little effect on the DNA conformation. Therefore, different DNA molecules may not be able to separate by PAGE due to these reasons and other factors. Nevertheless, this method has a relatively high detection sensitivity compared with other methods. It can detect mutations in unknown locations in the DNA molecule. Takao has demonstrated that SSCP can detect 90% single nucleotide mutations in a DNA fragment smaller than 300bp. He believes that most of known single nucleotide mutations can be detected by this method. Mutant DNA molecules can be separated and purified by PAGE due to the different migration rates, and the mutation can be eventually identified by DNA sequencing.
In SSCP analysis, the separation of single stranded DNA by non-denaturing PAGE is not just based on their molecular weights and electric charges, but also on the retention force caused by their spatial conformations. Therefore, the migration rate of a DNA fragment does not reflect its molecular size. Since the wild type and mutant DNA molecules may migrate very closely and be difficult to be distinguished, it is generally required for DNA molecules to migrate for more than 16-18 cm in the gel. Mobility is calibrated using reference DNA as an internal control. Because of these reasons, this method cannot clearly determine the HLA genotype.
In PCR-SSO, specific probes are synthesized according to the sequence in the HLA polymorphic region. The target DNA fragment is amplified
The diagram of PCR-SSO process
In 1986, Saiki
Overall, PCR-SSO is an accurate HLA genotyping method, and can identify all known HLA alleles for accurate analysis of HLA polymorphism. HLA is a super gene family and new alleles are continuously been identified. SSO probes can only be designed based on the sequences of known alleles. Although PCR-SSO may discover new HLA polymorphism through its hybridization pattern, dot-hybridization often leads to false positives. In addition, when an allele is identified in the sample, it is difficult to determine whether the allele is homozygous or heterozygous. Therefore, the HLA allele frequency and haplotype frequency cannot be precisely determined by this method.
Single nucleotide polymorphism (SNP) is the inheritable and stable biallelic single nucleotide difference. In the human genome, every 1000 base pairs have one to 10 SNPs. SNP may have some regulatory functions in gene expression and protein activity. High SNP density has been found in HLA class I genes with one SNP in every 400bp, setting the basis for high-throughput MHC-SNP analysis. Compared with other methods, SNP is less time consuming and with a low cost. Gou
In this method, 4 primers are used for the PCR amplification. Two primers are used to amplify the DNA fragment containing the SNP region, and the other two primers are SNP specific. The primer extension error is significantly reduced when 4 primers simultaneously carry out the PCR reaction, thereby the accuracy of SNP analysis is greatly improved. With the development of third-generation genetic markers, it is expected to find a series of single nucleotide polymorphisms in the HLA complex, and generate high-density SNP maps. In order to develop SNP technology into a simple and effective HLA typing method, production of high-density SNP maps in the HLA regions and development of HLA-SNP genotyping kits have been proposed in the 13th IHWC conference.
Arguello
The diagram of RSCA
Compared with PCR-SSP, the most commonly used method of HLA genotyping, RSCA has the following advantages: (1) high resolution and sensitivity. RSCA is based on the differential migration rate of fluorescent-labeled double stranded DNA during the electrophoresis. Alleles with different sequences will produce DNA duplexes with different spatial structures after hybridization with their fluorescent labeled probes. Two alleles with one nucleotide difference will cause a change in the spatial structure of hybridized duplex, resulting in an altered migration rate in electrophoresis. Therefore, RSCA can distinguish the alleles with a single nucleotide difference. For example, HLA*0207 and A*0209 alleles only differ one nucleotide at the site 268 of exon 2 and 3. In this site, A*0207 has a G while A*0207 has an A. Likewise, HLA-A*0224 and A*0226 only differ one nucleotide. These alleles all can be distinguished by RSCA. (2) high reproducibility. In RSCA, each lane in the non-denature polyacrylamide gel has markers and each gel has a DNA ladder. Therefore, the alteration caused by different gels or lanes can be eliminated. (3) new allele or mutation identification. RSCA is based on the electrophoretic mobility difference caused by different spatial structure of the duplexes after allele-FLR hybridization. New alleles or mutations will have electrophoretic mobility different from that of known alleles. (4) RSCA can be applied at a large scale with a low cost.
The disadvantages of RSCA are (1) time-consuming for a single sample; (2) requiring high quality samples; PCR-SSP requires 10-100ng/ml of DNA, which can be obtained with a regular DNA purification kit from patients even with a low amount of white blood cells. However, RSCA requires 50-100ng/ml of DNA. It may require an increased amount of blood sample for patients with low levels of white blood cell in order to obtain sufficient DNA; and (3) insufficient database.
Pyrosequencing is a new HLA genotyping technology based on real time sequencing during DNA amplification. The reaction system contains 4 enzymes (DNA polymerase, ATP sulfurylase, luciferase and apyrase), substrate (APS: adenosine 5’ phosphosulfate), fluorescein (luciferin), primers and the single stranded DNA template. After one type of dNTP (dATP, dTTP, dCTP and dGTP) is added to the reaction system, it will be incorporated into the newly synthesized chain if it is complementary to the nucleotide on the template. Incorporation of dNTP will generate the same molar amount of pyrophosphate (PPi). ATP sulfurylase converts APS and PPi into ATP, which provides energy for luciferase to oxidate luciferin and emit light. The amount of light signal is proportional to the amount of ATP. The optical signal is detected by a CCD (charge couple device) camera and generates a peak in the pyrogram. The principle of Pyrosequencing is shown in Fig 8.
The height of each signal’s peak is proportional to the number of incorporated nucleotide. Unincorporated dNTPs and excessive ATP are converted to dNDPs, which are further converted to dNMPs by apyrase. The optical signal is quenched and the system is regenerated for the next reaction. The next dNTP can be added to the system to start the next reaction after the unincorporated dNTPs and excessive ATP are removed. The reaction cycle continues until the complementary DNA strand is synthesized. Under the room temperature, it takes 3-4 seconds from polymerization to light detection. In this system, 1 pmol of DNA will generate 6x1011 pmol of ATP, which in turn yields 6x109 pmol of photon with a wavelength of 560nm. The signal can be easily detected by a CCD camera. For the analysis of DNA with unknown sequence by Pyrosequencing, a cyclic nucleotide dispensation order (NDO) is used. dATP, dGTP, dTTP and dCTP are sequentially added to the reaction. After one nucleotide is incorporated, the other three will be degraded by the apyrase. For the DNA with known sequence, non-cyclic NDO can be used and will yield a predicted pyrogram. The sequence of the complementary DNA strand can be determined based on the NDO and peak value in the pyrogram.
The principle of Pyrosequencing
Since nucleotides are differentially incorporated, Pyrosequencing can produce high-resolution results. Typing HLA-DRB1*04, 07 and DRB4* in the donor’s DRB genes by Pyrosequencing not only yields the same result as using the SSOP typing kit, but also produces the result with a higher resolution. Compared with SSP, SSOP, direct or reverse hybridization, Pyrosequencing can be used to solve ambiguous allele combinations of HLA-DQ and HLA-A/B in a short time. The types of HLA-DQB1 and HLA-DRB alleles have been accurately determined by Pyrosequencing.
An inherent problem with this technology is the de novo sequencing of polymorphic region in heterozygous DNA, although polymorphism can be detected in most cases. When the nucleotide in the polymorphic region is altered, synchronized extension can be achieved by the addition of the substituted nucleotides. If there is a deletion or insertion in the polymorphic region, and the deleted or inserted nucleotide is the same as the adjacent nucleotide on the template, the sequence after the polymorphic region will be synchronized. However, if the deleted or inserted nucleotide is different from the adjacent nucleotide on the template, the sequence reaction can be out of phase, making the subsequent sequence analysis difficult. Another issue with this technology is the difficulty in determining the number of incorporated nucleotides at the homopolymeric region. The light signal will become nonlinear after the incorporation of more than 5-6 identical nucleotides. Studies on the polymerization efficiency of the homopolymeric region have shown that it is possible to incorporate less than 10 identical nucleotides in the presence of apyrase. However, it needs specific software algorithm of signal integration to determine the precise number of incorporated nucleotides. For re-sequencing, the nucleotide is added twice to ensure complete polymerization in the homopolymeric region. Another limitation of this technology is the length of the sequencing.
Flow cytometry has failed to become a main method for HLA typing since it was applied to the field of immunology for the first time in 1977. This is mainly due to the large number of specific probes required for HLA typing. The flow analyzer LABScan100 that combines the flow cytometry and reverse SSO technology has a trend to replace three conventional methods, SSO, SSP and SBT (sequence-based typing, direct sequencing), in HLA typing.
On a suspension platform, multiple types of color-coded beads conjugated with SSO probes specifically bind to the single stranded DNA. Each type of bead has its unique spectral characteristics due to the different amount of fluorescent dye conjugated to the beads. When beads pass through a flow cytometer, the difference in the light scattering pattern from various angles can distinguish HLA genotypes.
Currently, LabType TM SSO is a relatively more mature technique compared with others in HLA typing. Its unique advantage is that thousands of molecules can be simultaneously analyzed in a matter of seconds. Therefore, this technique can be used for a large-scale analysis. Overall, this technique has following main advantages. (1) It has increased accuracy due to the automated detection system. (2) The workload and reagent consumption are reduced. One reaction tube can have 100 different SSO probes, thus greatly reducing the workload and reagent consumption. (3) It produces rapid and objective results. The ambiguous results can be avoided with Specialty Probe Technology TM (SP Technology). (4) Unlike regular flow cytometry that requires fresh samples, this technique can examine the sample at any time upon request or retrospectively. DNA samples can be analyzed right after extraction or stored at –20oC for more than 1 year without affecting the results. (5) The technique can analyze multiple HLA loci with low, medium and high resolutions. (6) It can be used in laboratories with large or small sample size. More than 100 probes can be put in one test tube for one sample or in a 96-well plate for 96 samples. The analysis of 96 samples takes less than 90 min after amplification. (7) The pollution to the environment and potential harm to the staff are reduced because electrophoresis is not required in this method.
In gene chip or DNA microarray, large amount of probe molecules (usually 6x104 molecules/cm2) are attached to a solid surface. Labeled DNA samples are hybridized to the probes. The amount and sequence information of the target can be determined by the intensity of the hybridization signal. Gene chip or DNA microarray technology was first developed by Affymetrix in the USA, and has been improved significantly within a few years. The technology is based on the principle of reverse dot hybridization. Thousands of oligonucleotide probes representing different genes are spotted on a solid surface by a robot. These probes will bind to radioactive isotope or fluorescent dye labeled DNA or cDNA through complementary sequences. After autoradiography or fluorescence detection, signals are processed and analyzed by computer software. The intensity and distribution of hybridization signal reflect the expression level of the gene in the sample. The operation process of microarray is shown in Fig 9. Balazs
The procedure of gene chip/microarray analysis
Compared with existing genotyping methods, gene chip or microarray has the following advantages. (1) high intensity; The dot intensity on a chip can be higher than 6x104/cm2. Therefore, probes to thousands of HLA-A, B, C, DR, DQ and DP sequences can be spotted on a tiny chip of several square centimeters to obtain the information of individual HLA genes simultaneously. (2) high resolution; It can obtain information at the allele level. (3) simple operation; The results are generated by fluorescence scanning instead of gel electrophoresis, which greatly simplifies the procedure and shortens operation time. (4) high sensitivity; Signals are amplified twice with first PCR amplification of the template DNA and second amplification of fluorescence signal. Therefore, the sensitivity is greatly improved. (5) high accuracy; The intensity of the fluorescent signal generated by the perfect pairing of the probe and the sample is 5 to 35 times higher than the signal generated by the probe and the sample with one or two mismatched nucleotide. Accurate detection of fluorescent signal intensity is the basis of the detection specificity. Studies have shown that the consistency between microarray and Sanger sequencing in the detection of mutations and polymorphism is 99.9%. (6) high efficiency; The whole process is highly automatic, which saves manpower and time for data analysis. Genotyping of genes such as HLA-A, B, DR and DQ in multiple samples can be done with one PCR reaction and hybridization on one chip. (7) high level of standardization; Using a variety of multi-point synchronized hybridization and automated analysis, the human error is minimized to ensure the specificity and objectivity. (8) low cost. Since the chip fabrication and signal detection are all automatic, only small amount of probes and samples are required. One chip can be used for the analysis of samples from multiple individuals, which further reduces the cost. The biggest drawback of microarray analysis is its expensive equipment, which prevents it from becoming widely used. Only institutions with a large program can afford the equipment.
For the analysis of gene structure, sequencing is the most direct and accurate method. In this case, the DNA fragment is amplified by PCR and followed by sequencing. The basic process of this method is shown in Figure 10. Since the entire nucleotide sequence of the amplified fragment is obtained, this is the most reliable and through genotyping method. It can not only identify the sequence and genotype, but also lead to the discovery of new genotypes. Currently, the newly identified HLA alleles can only be verified by sequencing. It has been reported that if the HLA type cannot be determined by serotyping or the results from PCR-SSP and PCR-SSOP are inconsistent, sequence-based typing (SBT) often can yield accurate and reliable results with a high resolution. Hurley
The advantage of SBT over PCR-SSP and PCR-SSOP is its ability to analyze the entire gene sequence including the non-polymorphic region. SBT can be used not only for DNA sequencing but also for cDNA sequencing to determine gene expression. With increasing popularity of DNA sequencing technology, the PCR-SBT method has gained much attention for genotyping. PCR-SBT has advantages over other typing methods in terms of accuracy, efficiency and the degree of automation. Specialized software and solid phase sequencing kits with automatic loading are available for HLA typing. In addition, the cost of DNA sequencing has been greatly reduced. Therefore, PCR-SBT is an ideal method for HLA typing in researches. With the further decrease in the cost of automatic sequencing, this genotyping method will be widely used.
Currently, PCR-SBT is the gold standard of HLA typing. This method has several advantages. (1) It can accurately determine gene type in the exon 8 by a high-resolution sequencing, sufficient to meet the need in researches and clinics. (2) It can analyze more than 15,000 samples every month with high throughput detection. (3) Automated SOP and advanced data management system can reduce human error. (4) It has high quality assurance. Ten percent blind samples are used repeatedly as internal quality control and 100% accuracy is achieved for 10 consecutive times using UCLA external quality assurance samples. The results are confirmed by SSP. (5). It may lead to the discovery of new alleles. (6) HLA genotype can be updated by re-analyzing the sequence after the HLA database is updated.
The diagram of DNA sequencing
In organ transplantation, the degree of matching is generally determined by counting the number of mismatched HLA-A, B, DR antigens of the donor. It is well known that the zero-antigen mismatches have the highest success rates but why do so many mismatched transplants do so well? The answer to this question may be related to the fact that antibodies produced against HLA mismatches are significant risk factors for transplant failure. An important consideration is that HLA antigens have multiple epitopes that can be recognized by specific antibodies. The original description of the epitope repertoire was based on serological cross-reactivity between HLA antigens and antibody specificities against so-called private and public determinants. Elucidation of three-dimensional molecular structures and amino acid sequence differences between HLA antigens has made it possible to define the structural basis of HLA epitopes. The general concept is that HLA epitopes are determined by polymorphic amino acid residues on the molecular surface. Three-dimensional modeling of HLA antigens has revealed many clusters of polymorphic residues. In spite of this highly complex polymorphism it has become possible to determine HLA compatibility at the structural level.
HLA MATCHMAKER is a computer algorithm that assesses human leukocyte antigen (HLA) compatibility at a structural level by intralocus and interlocus comparisons of polymorphic amino acid sequences of HLA molecules. In its first version, each HLA antigen was seen as a chain of short, lineal sequences of polymorphic amino acids in an antibody-binding position (triplets); these triplets are considered the key elements of epitopes able to induce specific antibody production. The most recent version—Eplets HLA Matchmaker—introduces the concept of sequences of polymorphic amino acids in discontinuous positions that create on the surface of the HLA molecule conformational epitopes. The eplet version provides a broader repertoire of structural defined HLA epitopes and may provide a more accurate evaluation of the HLA compatibility.
HLA Matchmaker is based on the following principles. First, each HLA antigen is represented by different chains of epitopes structurally defined as potential immunogenic particles capable of inducing specific antibody production. Second, patients cannot produce antibodies against epitopes present on their own HLA molecules. Initially, the program was developed to increase the chances of finding acceptable donors for hypersensitized patients. Subsequently, Duquesnoy et al demonstrated that it might also be useful in predicting the risk of graft loss according to the number of HLA-I mismatch triplets. This was proved in sensitized and nonsensitized patients. Haririan et al also showed that this triplet compatibility could give information about renal graft outcome in African-American patients. Nevertheless, Laux et al based on their own studies questioned the predictive role of triplet compatibility in graft survival. Other authors have also questioned the consistency of the epitopes in which this algorithm is based, pointing out that they might not be the unique epitopes inducing antibody formation. HLA Matchmaker has also been evaluated for clinical use in the selection of donors in pediatric renal desensitized receptors and HLA allosensitized thrombocytopenic patients. It has also been applied in unrelated bone marrow transplantation, lacking definitive proof of its benefit in patient survival.
When there is no genotypically identical sibling and there are several alternative potential donors that all have a mismatch at an HLA class I or II locus, the allogenicity of mismatches may be estimated using the Sequence Similarity Matching concept described by our working group. In this concept the amino acid differences between HLA alleles are evaluated and rated with regard to position within the molecule (peptide binding, contact with the T-cell receptor) and with regard to functional similarity of amino acids within proteins. This procedure led to a dissimilarity score (allogenicity index) whereby high values represent high dissimilarity. When there are several mismatched donors, dissimilarity scores may be calculated for any of them, and the donor with the least may be preferred.
The importance of HLA-DPB1 matching for the outcome of allogeneic hematologic stem cell (HSC) transplantation is controversial. Previous findings identified HLA-DPB1 alleles as targets of cytoxic T cells mediating in vivo rejection of an HSC allograft. These HLA-DPB1 alleles encode T-Cell epitopes shared by a subset of HLA-DPB1 alleles that determine non-permissive mismatches for HSC transplantation. Retrospective evaluation of transplantations showed that the presence of non-permissive HLA-DPB1 mismatches was correlated with significantly increased hazards of acute grade II to IV graft-versus-host disease and transplantation-related mortality but not relapse as compared with the permissive group. Based on these findings, an algorithm for prediction of non-permissive HLA-DPB1 mismatches was developed (details in http://www.mh-hannover.de/institute/transfusion/histocheck/).
Currently, PCR-SSP genotyping is a commonly used method for HLA typing in clinical laboratories worldwide. Like SSP method, PCR-SSP method depends on specific primers for genotyping. Although the process is simple and rapid, high-resolution genotyping requires a large number of sequence specific primers, which leads to a high cost and prolonged operation time. Similarly, SSO technique is based on the sequence-specific oligonucleotide probes. High-resolution genotyping by SSO significantly increases the cost and complexity. Therefore, it is rarely used for HLA typing today. PCR-SNP is a simple and fast method with a high resolution. PCR-SNP is expected to become more popular in HLA typing as the technology continues to improve. Although RSCA and Pyrosequencing can achieve high-resolution results, their applications in HLA typing will be gradually eliminated as the technology of gene chip and sequencing continues to improve and the cost continues to decrease. HLA-chip genotyping is still largely dependent on the known sequence. It cannot identify new alleles with unknown sequence. At this moment, PCR-SBT technology has significant advantages over other HLA typing methods in terms of accuracy, efficiency and automation. There are specialized software and automatically loaded sequencing reagents for HLA typing by PCR-SBT. In addition, the operation cost has been greatly reduced. In conclusion, PCR-SBT technology with HLA-chip is the best method for HLA typing in research. With the reduction in the cost of automated nucleic acid sequencing, this genotyping method will be widely used in the field of basic research as well as in clinical transplantation.
Supported by grants from the State Key Development Program for Basic Research of China (No.2003CB515509 and 2009CB522401) and from National Natural Scientific Foundation of China(No.81070450 and 30470751) to Dr. X.-Y.Z.
This chapter stands as an introduction to the field of biometrics which is rising as an advanced layer to many user- and enterprise-centric security systems. In fact, conventional authentication methods, such as traditional passwords, have long been a weak point for security systems. Biometrics aims to answer this issue by linking proof-of-identity to our physiological traits and behavioral patterns. It is therefore important to present the concepts and primitives of performance metrics due to their impact on secure biometric systems. Thus, a brief overview is given to describe the main biometric traits along with their properties as well as the various biometric system operating modalities and the relatively known vulnerabilities. Finally, the criteria for performance evaluation have been defined to determine the system accuracy and security which are related to the applicability in real-world deployments.
Various biometric modalities have been developed over the years making the biometric technology landscape very vibrant. Prominent examples of physiological/biological and behavioral biometric characteristics, which have been the purpose of major real-world applications, are illustrated in Figure 1.
Examples of physiological/biological and behavioral traits applied in biometric recognition applications.
Biological biometrics make use of traits at a genetic and molecular level which may include features like DNA or blood, whilst physiological biometrics involve the individual physical traits like a fingerprint, iris, or the shape of the face. On the other hand, behavioral biometrics are based on patterns unique to each person, for example, how an individual walks, speaks, or even types on a keyboard. Some examples of biometric traits are briefly described below.
Fingerprint: Fingerprint recognition, which measures a finger’s unique pattern, is one of the oldest forms of biometric identification. This trait appears as a series of dark lines and white spaces when captured from the device and it consists of a set of ridges and valleys located on the surface tips of a human finger to uniquely distinguish individuals from each other. The fingerprint features are generally categorized into— (i) macroscopic ridge flow patterns (core and delta points), (ii) minutia features (which consists of the ridge bifurcations/trifurcation and the ridge endings), and (iii) pores and ridge contour attributes (incipient ridges, pore, shape, and width). Fingerprints of identical twins are different and so are the prints on each finger of the same person [1].
Face: Facial features use the location and shape (geometry) of the face, including the distance between the eyes, the distance from the chin to the forehead, or other measures that involve eyebrows, nose, lips, and jawline [2]. This kind of recognition is a nonintrusive method with reasonable authentication performance in commercially available systems. However, several constraints may be imposed by the systems on how the facial images are obtained to work properly, for example, controlled illumination and background. Moreover, its susceptibility to change due to factors such as aging or expression may present a challenge [3].
Hand geometry: This trait is based on the geometric characteristics of the hand such as the length and width of fingers, their curvature, and their relative position to other features of the hand. Though once a dominant method of biometric measurement due to the requirement of the low complexity in feature extraction and low-cost imaging, modern advances in biometrics have replaced its relevance in most applications [4]. Furthermore, such a biometric trait is not known to be very distinctive and hand geometry-based recognition systems cannot be scaled up for systems requiring the identification of an individual from a large population. In addition, hand-geometry features from both hands are expected to be similar, as their anatomy is quite similar [5].
Iris: Systems based on this trait are among the most accurate biometric systems available. This human characteristic refers to the colored part in the eye that consists of thick, thread-like muscles characterized by unique folds and patterns that can be used to identify and verify the identity of humans. Furthermore, this biometric trait is stable because iris patterns do not vary during the course of a person’s life and are not susceptible to loss, manipulation, or theft, making an iris recognition system robust to spoofing attacks. One interesting point worth noting is that even the two eyes in the same person have different patterns [6].
Ear acoustic: The main purpose of this kind of recognition system is to map one aspect within acoustic ear recognition, namely the performance of the ear characteristics bands and peaks. An ear signature is generated by probing the ear with inaudible sound waves which are reflected bouncing in different directions and picked up by a small microphone. The shape of the ear canal determines the acoustic transfer function which forms the basis of the signature. The recognition process is also possible, whilst the subject is on the move and caters to the protection of secrecy, which expands the applicability of this technology [7].
Vascular patterns: This biometric trait has been largely investigated for its advantages over other features. In fact, the vascular pattern of the human body is unique to every individual, even between identical twins [8], remains steady during the course of a person’s life, and lies underneath the human skin ensuring confidentiality and robustness to counterfeiting, as opposed to other intrinsic and extrinsic biometric traits that are more vulnerable to spoofing, thus leading to important security and privacy concerns [9]. To acquire the network structure of blood vessels underneath the human skin, a vascular-based recognition system uses near-infrared light to reflect or transmit images of blood vessels, since they are almost invisible in normal lighting conditions [10]. The most commonly used vascular biometric solutions use hand-oriented modalities, such as finger vein, palm vein, hand dorsal vein, and wrist vein recognition, as well as eye-oriented modalities, such as retina and sclera recognition [11].
Electrocardiogram (ECG): This trait considers the human heart and body anatomic features form the shape of the ECG signal typically acquired using a few electrodes, amplifiers, filters, and a data acquisition module, and which reports the strength and timing of the electrical activity of the heart [12]. However, scientific findings to date throw doubt on the specificities of real-world application scenarios and acceptability by the potential end users, which pose several constraints and questions.
Deoxyribonucleic acid (DNA): DNA matching is based on a common molecular biology method named short tandem repeat (STR)2 analysis, which is used to compare allele repeats at specific locations on a chromosome in DNA between two or more samples [14, 15]. DNA-based biometric recognition has been widely used in forensic science and scientific investigation due to its very high accuracy, despite the fact that identifications require tangible physical samples and cannot be done in real time.
Keystrokes, handwriting, gait, how a person uses a mouse, and other movements are some of the behavioral traits that a biometric system may analyze to assess the individual’s identity.
Gait: This characteristic may be changeable over a large time span due to various reasons, such as weight gain [16]. Thus, it can be used in low-security applications for massive crowd surveillance as it can quickly identify people from afar based on their walking style, even harnessing the potential of a large number of surveillance cameras installed in public locations into a biometric system. In fact, such a system does not require the individuals to be cooperative, nor that they wear any special device or equipment to be recognized [17].
Mobile interactions: It is based on the unique ways in which users swipe, tap, pinch-zoom, type, or apply pressure on the touchscreen of mobile devices like tablets and phones, thus providing characteristic patterns that may be used to identify people, even considering further features deriving from on-board sensors such as GPS, gyroscope, and accelerometers [18], which can also be configured to collect data in passive mode. Therefore, mobile interactions-based biometrics focuses not so much on the outcome of the user’s actions but rather on the way a user performs those actions.
Signature: Signature recognition is the most widely accepted method for documents authentication and it makes use of shorter handwriting probes compared to text-independent writer recognition methods, but it requires to write the same sign every time. A signature authentication scheme can be categorized into two methods—(i) off-line or static (the signature is digitized after the writing process) and (ii) online or dynamic (the signature is digitized during the writing process). Signature biometric features are extracted by analyzing curves, edges, spatial coordinates, inclination, the center of gravity, pen pressure, and pen stroke of the signature samples in both off-line and online applications. However, dynamic information like writing speed and stroke order is available only in online signatures [19].
Mouse dynamics: It makes use of patterns in mouse or trackpad cursor movement including clicks, trajectories, direction changes, tracking speed, and the relationships between them. Mouse-generated movement features are relatively stable for the same individual and different compared to other users, as such can be used to authenticate individuals [20]. These methods are most often used to continuously verify the user’s identity.
Keystrokes: Keystroke dynamics (also known as typing biometrics) include the tracking of the rhythm used to type on a keyboard. Two events constitute a keystroke event—key down and key up. The first one occurs when an individual presses a key, whilst the second one is associated with the event that occurs when the pressed key is released. Making use of these events, a set of inter-key and intra-key features known as delay times, hold times, and key down-key downtimes can be extracted. In general, keystroke recognition will work on the computer or virtual keyboards, mobile phones, smartwatches, and touchscreen panels, providing a low-cost authentication method that can be easily deployed in a variety of scenarios [21].
Voice: Voice recognition technology falls under both the physiological and behavioral biometric categories. Voice biometric recognition allows to distinguish among humans’ voice for personal authentication as voice features include physical characteristics such as vocal tracts, nasal cavities, mouth, and larynx [22]. Behaviorally, the way a person speaks or says something, for example, tone, movement variations, accent, pace, and so on, is also considered unique to each individual. Using data from both physiological and behavioral biometrics creates, therefore, a precise vocal signature, though mismatches may occur due to illness or other factors.
The main requirements that should be satisfied before a trait can be characterized as suitable for its applicability in a biometric recognition system, are briefly discussed as follows [23].
Universality: Every individual or at least most of them, accessing the biometric application should possess the characteristic.
Distinctiveness (or uniqueness): The given trait should be sufficiently different across individuals comprising the user population. Otherwise, the proportion of times the biometric system grants access to unauthorized individuals would be unacceptably high.
Permanence: The biometric trait of an individual should be sufficiently invariant (with respect to the matching criterion) over a period of time. This implies that the given trait should not change significantly over time otherwise the proportion of times the biometric system denies access to authorized individuals would be unacceptably high.
Collectability: The biometric trait can be measured quantitatively with particular regard to the easiness of obtaining the biometric data using suitable devices that do not cause undue inconvenience to the user.
Even though any human characteristic can be used as a biometric trait as long as the previous requirements are satisfied, in real-world biometric recognition applications there are a number of other issues that should be considered, such as:
Performance: This is a property aimed at assessing the verification or identification accuracy, the computational time required for a single recognition, as well as the operational and environmental factors that may affect or not the recognition accuracy and speed.
Acceptability: It indicates the extent to which people are willing to accept the use of a specific biometric application as well as their willingness to provide their biometric data. Nowadays, this is a crucial aspect to be considered due to the current pandemic situation caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [24], raising questions about how safe using touch-based biometric systems really is as touching the sensors can potentially spread viruses. As a consequence, less-constrained biometrics will likely be the preferred modality, whilst there may be less demand for other solutions that rely on physical contact with a reader.
Circumvention: This property reflects how easily the system can be deceived through potential spoofing attacks. It refers to the ways in which an attacker can endeavor to bypass a biometric system and finally attack the weak spot of such a system in order to gain unauthorized access.
Real-life biometric recognition systems ought to meet the requirements of accuracy, speed, and resource constraints, be harmless to the users, be accepted by the intended population as well as sufficiently robust to various fraudulent methods and attacks to the system [25].
Table 1 is reported a comparison study of the most popular traits based on the characteristics of biometric entities [26].
Biometric trait | Universality | Uniqueness | Permanence | Collectability | Performance | Acceptability | Circumvention |
---|---|---|---|---|---|---|---|
Fingerprint | M | H | H | M | H | M | H |
Face | H | L | M | H | L | H | H |
Hand geometry | M | M | M | H | M | M | M |
Iris | H | H | H | M | H | L | L |
Ear | M | M | H | M | M | H | M |
Vascular patterns | H | H | M | M | H | M | L |
DNA | H | H | H | L | H | L | L |
Gait | M | L | L | H | L | H | M |
Signature | L | L | L | H | L | H | H |
Keystroke dynamics | L | L | L | M | L | M | M |
Voice | M | L | L | M | L | H | H |
Comparison study of the most common traits based on the characteristics of biometric entities.
H = High; M = Medium; L = Low.
A biometric system can provide two kinds of operating modes (identity management functionalities), namely,
Basic building blocks of a generic biometric recognition system.
Different operating modes of a biometric system—(a) enrollment mode, (b) authentication mode (the dashed line is an optional operation aimed at updating a specific user’s template), and (c) identification mode.
In the authentication mode, the purpose of the biometric system is to verify whether an individual’s claimed identity is genuine or not (binary classification). Thus, the captured biometric data (query) is compared only with the biometric template(s) stored in the system database and corresponding to the claimed identity (one-to-one or one-to-few comparison). Given a claimed identity
where
In the identification mode, the purpose of the biometric system is to recognize an individual’s identity by searching the templates of all the enrolled individuals in the system database for a match (one-to-many comparison) without the subject having to claim an identity.
This operating mode can be further split into negative and positive identification—in the negative identification (also known as
where
The identification mode is typically employed for screening4, where the aim is to prevent a single person from using multiple identities [28].
Biometric-based cybersecurity solutions ensuring tight access control are essential in preventing intrusions and unauthorized accesses. However, even though a biometric system enhances user convenience and security, does not necessarily mean that it is also exempt from security and privacy issues. Many security measures in biometric systems are designed to protect one or more facets of the CIA triad, which is a common framework that refers to confidentiality, integrity, and availability [31].
Confidentiality is roughly equivalent to privacy. Measures undertaken to ensure confidentiality are designed to prevent sensitive information from reaching unauthorized people. It is perhaps the most obvious aspect of the CIA triad when it comes to security; but correspondingly, it is also the one which is attacked most often. Confidentiality covers a wide spectrum of access controls and measures that protect data from getting misused by any unauthorized access. Cryptography and encryption methods are an example of an attempt to prevent illegitimate access ensuring the confidentiality of (sensitive) data.
Integrity of information refers to the ability to protect information from being modified or destroyed by unauthorized parties, thus ensuring nonrepudiation and authenticity of the information. Thus, integrity involves maintaining the consistency and trustworthiness of data. One type of security attack is to intercept some important data and make changes to it before sending it on to the intended receiver.
Availability of information refers to ensuring that only legitimate and authorized parties are able to access the information when needed. Problems affecting the information system could make it impossible to access information, thereby making the information unavailable. Some types of security attacks attempt to deny access to the appropriate user, either for the sake of inconveniencing them, or because there is some secondary effect.
Biometric recognition systems implicitly (and effectively) address the authentication problem included in the last issue of the CIA triad, which consists in guaranteeing access to data only to authorized users. The reason for this is because biometric traits are (generally) not susceptible to loss, manipulation, or theft, and therefore overcome the security issues affecting the conventional methods for personal authentication, such as knowledge-based and token-based systems. However, it must be kept in mind that a biometric-based security solution is composed of several different components and the recognition module, which is only capable of addressing the authentication aspect, is just one of them. Thus, a logical structure-based approach of biometric systems is used to describe the eight points of attacks illustrated in Figure 4.
An attack on the biometric sensor consists of presenting a fake biometric trait (e.g., an artificial characteristic) to perform a spoofing attack aimed to either avoid detection (false negative) or masquerade as another (false positive). Methods used to prevent spoofing attacks include layered biometrics, liveness, and combining biometrics and conventional authentication methods such as passwords, tokens, or smart cards [32].
The connection between the biometric sensor and the subsequent modules of the system may be attacked to allow input of a stored digital biometric signal. This data can be obtained, for instance, by performing an eavesdropping (disclosure) attack [31].
Attacks on the feature extractor can be used either to create impostors or to evade detection. Hence, knowledge of the algorithms involved in this module5 may be used to forge features in presented samples to cause computation of incorrect features. To achieve this, an attacker can replace the feature extractor with a Trojan horse program that produces the desired feature sets.
An attack on the output of the previous module consists of spoofing the legitimate biometric feature set to replace it with a synthetic one.
Vulnerabilities of template database concern modifying the storage (modifying, removing, or adding templates), copying stored data for future use (identity theft or directly using the acquired information to gain access), or modifying the identity to which the biometric is assigned.
The channel between the template database and the matching module is similarly vulnerable to the previous one, however, the attack against data transmission may be easier than against the template storage, especially in the case of an adversary able to intercept any information communicated by the system by observing the data (passive eavesdropping). Encryption is crucial in this case, but may still be vulnerable to key discovery [33].
The matcher module is responsible for computing a similarity score between two biometric templates in order to confer the likelihood that they are from the same subject. Even though it may not be possible to do it easily, an attack against the matcher can be possible in specific cases. For instance, it is possible to replace the matcher module with a Trojan horse program that always outputs high scores thereby defying system security [34].
An attack on the final decision module means that if the final decision can be inserted or blocked by the attacker then the authentication system function will be overridden. If it is instead reviewed by a human operator, a DoS (denial of service) attack may be performed to mislead it or to force it to mistrust the output of the system [35].
Attack points of a general biometric system.
The reliability and validity of a biometric scheme as well as the selection of a certain biometric trait for an application are determined by specific measures that are used to evaluate the recognition accuracy and effectiveness as addressed in ISO/IEC Standards [36]. Accordingly, to evaluate the accuracy of the proposed method based on a single-sample approach for unimodal biometric systems, each sample in the database should undergo a one-to-one matching test against every single stored sample. Hence, a comparison between a subject with a real identity
where
Precisely, given a threshold
false acceptance rate (FAR), that is the probability of accepting the null hypothesis
false rejection rate (FRR), that is the probability of rejecting the null hypothesis
Let
The false acceptance and false rejection rates are functions of the system threshold
The genuine acceptance rate (GAR) is instead the probability of accepting the null hypothesis
Depending on the security level required by the final application (i.e., forensics, surveillance and homeland security, civilian, or high-security applications), the same biometric system may operate at different threshold values (
Examples of biometric system error rates: (a) FAR and FRR for a given threshold
Hence, in order to evaluate the biometric system performance as a function of the threshold
The receiver operating characteristic (ROC) is a graphical plot that illustrates the trade-off between false acceptance and false rejection rates when the threshold varies, whilst the intersection point for which rejection and acceptance errors are equal is named equal error rate (EER). The curve is generated by plotting the genuine acceptance rate against the false acceptance rate at various threshold settings,
The detection error trade-off (DET) is another graphical plot that illustrates the false rejection rate against the false acceptance rate at various threshold values. The two axes are scaled nonlinearly by their standard normal deviates6 or just by logarithmic transformation.
Furthermore, the above-mentioned ROC and DET curves are threshold-independent, allowing performance comparison of different biometric systems under similar conditions [23], as illustrated in Figure 6. Given a set of thresholds
Example of vascular-based biometric systems performance comparison [
where
Since biometric systems cannot jointly provide a false acceptance rate equal to zero and a perfect verification/identification rate, the system threshold must be adjusted for the given application considering the trade-off between accuracy and false positives. Once the threshold has been set, the system can be evaluated by means of common measures that are used to assess the classification accuracy and effectiveness. In this context, we are interested in confirming or denying the identity of a subject leading thus to a dichotomous binary classification problem, where the labels are
Predicted class | ||||
---|---|---|---|---|
Example of confusion matrix for a dichotomous binary classification problem.
which completely describes the outcome of the classification task. This contingency table may be expressed using raw counts of the number of records from class times each predicted label is associated with each actual class. As illustrated in Table 2, the confusion matrix reports:
true positive (TP), the probability of correctly accepting the null hypothesis;
true negative (TN), the probability of correctly rejecting the null hypothesis;
false positive (FP), the probability of falsely rejecting the null hypothesis;
false negative (FN), the probability of falsely accepting the null hypothesis.
Based on the entries in the confusion matrix, the total number of correct predictions carried out by the model is
where obviously
it represents the worst case (perfect misclassification).
Several measures have been defined to assess the quality of a prediction [40], aimed at conveying into a single figure the structure of
where the worst case (
it is a correlation coefficient between the actual and predicted binary classifications and it returns a value between −1 (worst case) and 1 (best case).
Accuracy and F-score computed on confusion matrices have been (and still are) among the most popular adopted metrics in binary classification tasks. However, these statistical measures can dangerously show overoptimistic inflated results, especially on imbalanced datasets [40]. Hence, among all the parameters described above, the Matthews correlation coefficient (MCC) is the only one that takes into account true and false positives and negatives and is generally regarded as a balanced measure that can be used even if the classes are of very different sizes [41].
Biometric-based technologies make use of unique behavioral (extrinsic) and/or physiological/biological (intrinsic) attributes to overcome the security issues affecting the conventional methods for identity authentication. Even though biometrics has been in use for decades, the advent of technology has expanded its application from primarily criminal identification to a wide range of everyday tasks, becoming a regular security process of our nowadays life. Accurate authentication or identification is fundamental to physical security, cyber security, military applications (e.g., biometric-driven lethal autonomous weapon systems), financial transactions, contracts and employment, public services, criminal justice, national security, and more. The approaches that have been proposed in literature depend on the type and the number of the underlying biometric traits, which, in general, cannot be easily transferred between people, and thereby represents a highly secure unique identifier. As a matter of fact, various biometric modalities have been developed over the years making the biometric technology landscape very vibrant. In this book chapter, we have provided an overview of the most commonly used biometric traits along with their properties, the various biometric system operating modalities as well as various limitations and weaknesses related to these systems. Indeed, biometric technologies have a number of vulnerabilities that underscore the concerns over their employment and may result in the failure of the technology to perform as anticipated. We have also discussed how the system threshold must be adjusted for the given application considering the trade-off between accuracy and false positives since biometric systems cannot jointly provide a FAR equal to zero and a perfect recognition rate. Finally, the criteria for performance evaluation have been defined to determine the system’s accuracy and security which are related to the applicability in real-world deployments, even though the existing evaluation metrics are more related to the data quality than the security aspects of the overall system. However, despite the risks, biometrics provide very compelling security solutions remaining a growing way to verify identity offering tons of promise for the future of cybersecurity.
The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
DET | Detection error trade-off |
DNA | Deoxyribonucleic acid |
ECG | Electrocardiogram |
FAR | False acceptance related |
FN | False negative |
FRR | False rejection rate |
FP | False positive |
GAR | Genuine acceptance rate |
MCC | Matthews correlation coefficient |
NGI | Next-generation identification |
PPV | Positive predictive value |
ROC | Receiver operating characteristic |
SARS-CoV-2 | Severe acute respiratory syndrome coronavirus 2 |
STR | Short tandem repeat |
TN | True negative |
TP | True positive |
TPR | True positive rate |
Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.
",metaTitle:"IntechOpen Women in Science Program",metaDescription:"Supporting women in scientific research and encouraging more women to pursue careers in STEM fields has been an issue on the global agenda for many years. But there is still much to be done. And IntechOpen wants to help.",metaKeywords:null,canonicalURL:null,contentRaw:'[{"type":"htmlEditorComponent","content":"At IntechOpen, we’re laying the foundations for the future by publishing the best research by women in STEM – Open Access and available to all. Our Women in Science program already includes six books in progress by award-winning women scientists on topics ranging from physics to robotics, medicine to environmental science. Our editors come from all over the globe and include L’Oreal–UNESCO For Women in Science award-winners and National Science Foundation and European Commission grant recipients.
\\n\\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
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\n\nWe aim to publish 100 books in our Women in Science program over the next three years. We are looking for books written, edited, or co-edited by women. Contributing chapters by men are welcome. As always, the quality of the research we publish is paramount.
\n\nAll project proposals go through a two-stage peer review process and are selected based on the following criteria:
\n\nPlus, we want this project to have an impact beyond scientific circles. We will publicize the research in the Women in Science program for a wider general audience through:
\n\nInterested? If you have an idea for an edited volume or a monograph, we’d love to hear from you! Contact Ana Pantar at book.idea@intechopen.com.
\n\n“My scientific path has given me the opportunity to work with colleagues all over Europe, including Germany, France, and Norway. Editing the book Graph Theory: Advanced Algorithms and Applications with IntechOpen emphasized for me the importance of providing valuable, Open Access literature to our scientific colleagues around the world. So I am highly enthusiastic about the Women in Science book collection, which will highlight the outstanding accomplishments of women scientists and encourage others to walk the challenging path to becoming a recognized scientist." Beril Sirmacek, TU Delft, The Netherlands
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Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/249503",hash:"",query:{},params:{id:"249503"},fullPath:"/profiles/249503",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()