\r\n\tThis book chapter’s main theme will be focused on transmission dynamics, pathogenesis, mechanisms of host interaction and response, epigenetics and markers, molecular diagnosis, RNA interacting proteins, RNA binding proteins, advanced development of tools for diagnosis, possible development of concepts for vaccines and anti drugs for RNA viruses, immunological mechanisms, treatment, prevention and control. \r\n\t
",isbn:"978-1-80355-667-3",printIsbn:"978-1-80355-666-6",pdfIsbn:"978-1-80355-668-0",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"52f8a3a1486912beae40b34ac557fed3",bookSignature:"Ph.D. Yogendra Shah",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11369.jpg",keywords:"HIV, Dengue, Zika, West Nile Virus, Chikungunya, Rabies, SARS-CoV2, MERS-CoV, Hanta Virus, Influenza, Whole Genome Sequencing, DNA Sequencing",numberOfDownloads:217,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 4th 2021",dateEndSecondStepPublish:"November 1st 2021",dateEndThirdStepPublish:"December 31st 2021",dateEndFourthStepPublish:"March 21st 2022",dateEndFifthStepPublish:"May 20th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"10 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"Dr. Shah obtained his Ph.D. degree in Veterinary Medicine from Hokkaido University, Japan. He was awarded the Young Science and Technology Award from the Nepal Academy of Science and Technology (NAST) in 2019. His research interests include infectious diseases, zoonotic infectious diseases, and vector-borne diseases.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"278914",title:"Ph.D.",name:"Yogendra",middleName:null,surname:"Shah",slug:"yogendra-shah",fullName:"Yogendra Shah",profilePictureURL:"https://mts.intechopen.com/storage/users/278914/images/system/278914.jpg",biography:"Dr. Yogendra Shah is a consultant microbiologist/virologist, senior research microbiologist, and lecturer at Seti Provincial Hospital, COVID-19 PCR laboratory, National Zoonoses and Food Hygiene Research Center, and Kathmandu College of Science and Technology, Nepal. He obtained a Ph.D. in Veterinary Medicine (Bacteriology) from the Graduate School of Veterinary Medicine, Hokkaido University, Japan, in 2017. His research focuses on better understanding the molecular epidemiological features/transmission dynamics of infectious diseases and zoonotic infectious diseases in Nepal by employing molecular techniques like ELISA, polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), and DNA sequencing. He was awarded the Young Science and Technology Award from the Nepal Academy of Science and Technology (NAST) in 2019. His research interests include infectious diseases, zoonotic infectious diseases, and vector-borne diseases. 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1. Introduction
Plants are essential natural resource for the survival and welfare of human being. The many uses of plants can be summarized in “TREES” word, an abbreviation for timber, restoration, ecological, educational and recreation, and source of sustenance [1]. Given the importance of plants, people have been upgrading both productivity and quality of cultivated plants. Plant breeding technique comes as an art, science, and business of manipulating the genetic pattern of plants by humans to develop superior cultivars, related to improving humankind, ranging from unintentional changes that are resulted by conventional selection to precision breeding by molecular tools [2, 3].
Plant breeding activities are considered to have been going on for at least 10,000 years, as long as the age of human civilization from nomadic hunter-gatherer to sedentary lifestyle [2]. The earlier farmers collected their best seeds to be replanted. This conscious human selection activity to get the best performing plant, although relatively simple, is the fundamental principle of phenotype-selection based. Later people incorporated some superior properties of different closely related parents through artificial mating or sexual hybridization, generating new genetic recombination which dramatically led to increased crop yields, easy cultivation, tolerant to environmental stresses, and resistant against pest [2, 3, 4].
The advance of molecular biology and genetic engineering provides new opportunities in plant breeding technology. Moreover, the application of molecular markers developed from QTL analysis enhances breeding efficiency by enabling marker-assisted selection for particular agronomic traits [5]. On the other hand, next generation sequencing (NGS) has revolutionized genomic and transcriptomic approaches to biology. These new sequencing tools are also valuable for discovery, validation, and assessment of genetic marker in populations. NGS technologies have conferred new opportunities for high-throughput genotyping in various plant species. Recent improvements in high-throughput sequencing have enable sequences to be used to detect and score single nucleotide polymorphisms (SNPs) by bypassing time-consuming process of marker development. However, genotype-by-sequencing (GBS), a series of genetic analyses that includes molecular marker discovery and genotyping using NGS technologies, has opened new possibilities in plant breeding and plant genetics studies, including linkage maps, genome-wide association studies, genomic selection, and genomic diversity studies [6]. Furthermore, horizontal gene transfer (HGT), also known as lateral gene transfer, refers to the movement of genetic information across normal mating barriers, between more or less distantly related organisms, and thus stands in distinction to the standard vertical transmission of genes from parent to offspring [7]. HGT from bacteria to plants has been restricted to Agrobacterium rhizogenes, and the related bacterium A. tumefaciens transforms a wide variety of host plants by transferring a segment of the large tumor-inducing plasmid, called T-DNA into host cells [8]. Most genetic engineering of plants uses AMT to introduce novel gene content.
The development of AMT technology is supported by research on RNA interference technology for functional analyses of genes involved in transformation mechanism or gene(s) of interest and gene editing technology that allows precise manipulation of targeted genome sequences [9]. Although there are several species of Agrobacterium that have the capability to cause tumors—such as A. rhizogenes that cause hairy roots disease, the discussion of Agrobacterium-mediated transformation in this chapter specifically refers to A. tumefaciens. The Agrobacterium-plant interaction is a complex process that its effectiveness and efficiency are affected by many factors. This review focuses on the mechanism of AMT and updates technology to increase the successfulness of plant-gene transformation mediated by A. tumefaciens.
The generation of transgenic plant mediated by A. tumefaciens basically mimics the event of naturally plant transformation. The dawn of natural plant transformation study began when fleshy rough roundish surface morphology on the roots’ crown (region joining root and shoot) of over 20 different fruit trees was observed [10]. To investigate the causative agent of these tumor-like outgrowths later named “crown gall disease,” infected root crown tissues were isolated. The bacteria described as Agrobacterium tumefaciens then were presented [11]. While these Gram-negative soil bacteria were inoculated to wounded young tissues of healthy plants, secondary tumors that cannot be distinguished from the crown gall were produced. On the other hand, the old tissues were not very susceptible [10].
The development of in vitro cultivation technique supports the study of secondary tumor. Explant derived from the interior of secondary tumor continued to unlimited proliferation in auxin in auxin and cytokinin lacking medium and synthesized unusual amino acid derivative; guanido amino acids octopine N2-(D-1-carboxyethyl)-L-arginine and nopaline N2-(1,3-dicarboxypropyl)-L-arginine [9, 12]. Both properties distinguished tumor cells than normal cells.
Bacterial isolation from secondary tumor cultures revealed that no one of these cultures has yielded any growth of A. tumefaciens. Injection of paste from these bacteria-free cultures to healthy plants exhibited no evidence of tumor initiation as it is observed due to paste injection from young primary tumors. The fact that volume of secondary tumor still increased—although bacteria were absent, indicated that bacteria only trigger tumorigenesis, not involved in the whole process. Somehow, the host cells were permanently transformed so that they were able to convert normal cells into neoplastic cells [13].
Further investigation to confirm the involvement of A. tumefaciens in early step of tumorigenesis was conducted through temperature challenge. Bacterial inoculation on periwinkle plant (Vinca rosea L.) at temperature of 32°C did not inducted swelling growth, even bacterial and plant cells grew well at that temperature. The bacterial inability to forming tumorous property was not influenced by host plant physiological disturbances as a whole but was solely dependent upon environmental change of bacterial inoculation site, in this case an elevated temperature.
Plants inoculated with bacteria at a temperature of 26°C for 5 days, before being held at 32°C, retained tumorigenic state. These periods provided sufficient opportunity for bacteria to interact with host plants, and then they drove the cellular alteration of the plants. Once the cellular alteration was fully complete, temperature at 32°C would not matter; plants were entirely independent in converting normal cells into neoplastic cell. The nature of plant oncogenic transformation as bacterial influence was known as “tumor-inducing principle” [13, 14].
The development of molecular technique made a breakthrough in the investigation of the origin of tumor-inducing principle. On the examination of the pathogenic strains of A. tumefaciens, one or several homolog large (±140–235 kbp in size) supercoiled circular plasmids were isolated [15]. None of the avirulent Agrobacterium strains tested belonged to such a plasmid. Based on its association in inducing tumors, the plasmid was called “tumor-inducing(Ti)-plasmid” [15, 16].
Ti-plasmid borne harbored by four apparently distinct genetic loci (Figure 1). Three loci that consist of genes regulating auxin, cytokinin, and opine synthase are located on T-DNA, a highly conserved DNA fragment defined by 25 bp repeat sequence borders on each end. The genes regulating auxin and cytokinin accumulation determine the oncogenicity of the plasmid. The gene regulating opine synthesis is necessary for expression in host plants as exclusive nutrition for A. tumefaciens [17]. The fourth locus, apart from T-DNA, controls the catabolism of opine compound [9, 20]. All genes carry the signal necessary for the expression in host plant cell. During bacterial infection to host cell, only T-DNA was cleaved out of the Ti-plasmid borne, transferred, and ultimately incorporated to DNA nuclear of host plant cells [18, 19]. Therefore, the complete Ti-plasmid was not found in tumor cells, given their relatively large size could not infiltrate host nuclear ore complex passively [15]. Genes regulating auxin and cytokinin synthesis modifying the phytohormone ratio in the host cell resulting uncontrolled cell proliferation that leading to tumor growth.
Figure 1.
Schematic representation of a Ti-plasmid borne (not to scale, modified from [20, 21]).
2.2 The natural pathogenesis of A. tumefaciens
AMT is a complicated mechanism, which includes (1) signal recognition from plant host to A. tumefaciens, (2) T-DNA processing, (3) T-DNA traveling in plant host cell, (4) T-DNA integrating to plant host genome, and (5) expression of T-DNA in the plant host cell. The mechanism of T-DNA transfer is facilitated by a set of virulent genes located on Ti-plasmid borne [approximately 35 virulent genes grouped in at least 8 operons, virA, virB, virC, virD, virE, virF, virG, and virH, encoding VirA, VirB, VirC, VirD, VirE, VirF, VirG, and VirH protein, respectively (Figure 1)], apart from T-DNA, whereas others are on chromosome (chromosomal virulent genes—chv) [22, 23].
2.2.1 Signal recognition
Agrobacterium-plant interaction occurs when a large plant-derived chemicals, which include organic acid compounds (pH 5.0–5.8) as routine secreted chemical and phenolic compounds as the wound-releasing chemical, are exposed to the bacteria. Signal recognition of A. tumefaciens to plant cell involves three systems (Figure 2) [24]. First, bacterial chemotaxis attracted by phenolic compounds that are exuded from fresh wound site of plants, such as acetosyringone and α-hydroxy acetosyringone [25]. Initially, bacteria engage with plant cell surface reversibly, stimulating adhesion production that causes adhesion through unipolar polysaccharide (UPP)-dependent polar attachment and UPP-nondependent attachment. This irreversible surface attachment establishes a site for multicellular biofilms formation, matrix elaboration, cell division, biofilm maturation, and “buddy daughter” cell dispersal [26]. Secondly, host signal compounds are also recognized by transmembrane protein receptors (VirA) on periplasmic space of bacterial cell that trigger phosphorylation of positive regulatory protein VirG [25, 26, 27]. Thirdly, protein ChvG/ChvI encoded by chromosomal virulent genes perceive acidity from sugar that activate basal expression of virG too [22]. The phosphorylated VirG leads to the activation of another virulence gene [25]. Monosaccharides enhance signaling process by binding with ChvE then synergize with VirA [28].
Figure 2.
Schematic representation of A. tumefaciens signal recognition mechanism, modified from [26].
2.2.2 T-DNA processing
The process of excising T-DNA from Ti-plasmids depends on VirD1 and VirD2 as endonucleases. The 25 bp border sequences on the bottom strand of T-DNA act as nicking site for VirD1 and VirD2. VirD1, a site-specific helicase, unwinds double-stranded T-DNA. A nuclease, VirD2, cuts the bottom strand of T-DNA from the right and left border, becoming single-stranded linear DNA termed T-strand [21, 29]. VirD2 then covalently caps the 5′ end of T-strand at the right border, forming the VirD2/T-strand complex [28]. The 3′ end of the nicked right border acts as a priming site for the bottom strand of T-DNA regeneration [29]. VirC1 binding the “overdrive” sequence near the right border of T-DNA (Figure 1) through its C-terminal ribbon-helix-helix DNA binding fold enhances the number of T-strand molecules [30, 31]. The right fraction of the 25 kb terminus sequence of T-DNA determines the director of DNA transfer [32] (Figure 3).
Figure 3.
T-strand generation from T-DNA, modified from [29].
2.2.3 T-DNA traveling
The T-DNA traveling to the host cannot separate from the role of VirD2 and VirE2. Both VirD2 and VirE2 have the C-terminal nuclear localization signal (NLS) sequence that piloted VirD2/T-strand to the host nucleus [33]. VirD2/T-strand, a rodlike structure, exits bacterial cells through Ti-pilus, type IV secretion system (T4SS), which is assembled by 11 VirB and VirD4 proteins [34]. The hydrophilic protein VirE2 is accumulated in the bacterial cytoplasm and translocated into the host cell through clathrin-mediated endocytosis. Besides helping transport the T-strand, VirE2 in the host cytoplasm coats along the T-strand noncovalently and form VirD2/T-strand/VirE2 (termed Ti-complex) to protect it from any nuclease digestive activity [35, 36, 37]. Ti-complex in the plant cytoplasm is trafficked to the plant nucleus via the endoplasmic reticulum network inside the plant cytoplasm (Figure 4) [24].
Figure 4.
T-complex traveling, modified from [38].
2.2.4 T-DNA integration
T-DNA integration followed by transgene expression is the final and crucial stage in the genetic transformation mediated by Agrobacterium. The molecular mechanism of T-DNA integration into host plant genome actually is still not fully understood. T-DNA integration occurs at random sites, not preferentially in transcriptional active or hypomethylated regions of the plant genome. Some important genes in the T-DNA integration process are limited to genes related to chromatin formation and histone modification [39].
VirE2 may play a role in T-strand targeting to chromatin by binding to the bZIP transcription factor VirE2 interacting protein 1 (VIP1). VIP1 mediates the association of VirE2/single-strand DNA with mononucleosomes, a unit of chromatin in the nucleus [39]. When T-complex arrived in the plant nucleus, its protein component should be disassembled by the ubiquitin-proteasome system so that the T-strand can be exposed. T-complex disassembling process and VirE2 degradation are assisted by VirF [40, 41].
VirD2 has no ligation activity, so T-strands are not likely to join directly with the host genome. Possibly, the host DNA polymerase copies the T-strand to form a double-stranded T-DNA, and then it joins with the site breaks of DNA host plant that it is caused by environmental stress due to Agrobacteria incubation or normal metabolic processes. Non-homologous end joining (NHEJ) as a way of repairing broken double-stranded DNA is proposed as the main pathway of bacterial plant DNA integration. NHEJ only requires little or no sequence homology on the damaged part, although in fact there are microhomology between the T-DNA and the integration points on the host chromosome [42] (Figure 5).
Figure 5.
T-DNA integration, modified from [42].
2.2.5 T-DNA expression
Bacterial T-DNA that integrates with plant genome cells faces two possible fates. First, the T-DNA is expressed, in various levels. Second, the T-DNA is only integrated but cannot be expressed. A broad range of transgene expression, from very high to totally silent, depends on species [12].
The expression on auxin and cytokinin coding genes in T-DNA causes the accumulation of both phytohormones. Phytohormone ratio abnormalities bring plant cell to uncontrolled cell proliferation, leading to tumor growth. The expression of opine synthesis coding genes produces opine—the type depends on bacterial strain, an exclusive nutrition for Agrobacterium. In young tissue, swelling is observed from the fourth or fifth day after bacterial inoculation, well-developed in a month, and growing rapidly until it reaches an inch or two in diameter for several months [10]. The overall mechanism of AMT is summarized in Figure 6.
Figure 6.
Overall mechanism schematic of AMT.
2.3 Agrobacterium-mediated transformation
2.3.1 The engineered A. tumefaciens Ti-plasmid
The wild-type Ti-plasmids are not suitable for being gene vectors because the T-DNA has oncogenes that cause tumor growth in host cells. Construction disarmed Ti-plasmid by deletion of oncogenes, and opine biosynthetic coding gene makes the plasmid non-oncogenic, the 25 bp of each repeat border sequence remaining. The promise of AMT relies on the substitution of T-DNA by any foreign DNA sequence so that A. tumefaciens can be a “vehicle” in insertion gene(s) of interest that are transmissible to the progeny [18, 43]. Selectable marker genes are inserted into the T-DNA in order to distinguish the transformed cells from normal cells, tandem with experimental transgenes. Some herbicide resistance markers that are commonly used are phosphinothricin, chlorsulfuron, sulfonamide, and glyphosate. The insertion of bacterial selectable marker, such as trimethoprim, streptomycin, spectinomycin, sulfonamides, bleomycin, hygromycin, kanamycin, neomycin, or gentamicin, evaluates the uptake engineered plasmid to bacterial cell [8].
Disarmed Ti-plasmid is difficult to be manipulated in vitro due to its large size. Since the virulence genes may act in trans on the T-DNA sequences in the same cell, it was transferred to small independently plasmid that has origin of replication for Agrobacterium, called “helper vector.” In addition, the elimination of virulence gene causes the Ti-plasmid to accommodate longer transgene. Furthermore, scientist constructs the binary vector, so called because it is designed to be replicate in multiple host (E. coli and A. tumefaciens). The binary vector consist of left and right borders, origin of replication for multiple host, selectable marker genes, and gene(s) of interest. This engineered plasmid is now used in plant genetic transformation.
AMT is a general method for genetic modification in many plant species. It is because it allows efficient insertion of stable, un-rearranged, single-copy sequences into plant genome. Two critical points for successful transformation were indicated: the use of actively dividing embryonic callus cells derived from the scutella of mature seeds as the starting material and the addition of a phenolic compound, acetosyringone, in the cocultivation steps [44, 45]. Moreover, Cheng et al. reported that there is no significant difference in the transformation efficiencies between immature embryos, pre-cultured ones, and embryogenic callus [46].
Several protocols of AMT have been reported either in Monocotyledoneae or Dicotyledoneae plants. In general, Agrobacterium-based method was used for transgenic plant. The protocol consists of seven steps, which can be briefly summarized as follows: stage (I) preparation of sterilize seed or samples and inoculum; stage (II) explant preparation, infection, and cocultivation with A. tumefaciens; stage (III) selection; stage (IV) regeneration; stage (V) acclimatization and molecular identification of T0; stage (VI) cultivation and self-crossing of T0; and stage (VII) T1 plant analysis (Figure 7).
Figure 7.
The protocol of Agrobacterium-mediated transformation.
2.3.2.1 Preparation of sterilize seed or samples and inoculum
Immature embryo was a common sample that is used for transformation. Some experience reported that transformation efficiencies depend on the genotype or variety [47, 48]. To obtain the immature embryo, seed is planted in sterile media (such as husk, compost, mixed soil, etc.) and grown in environmentally controlled growth rooms. Immature embryo is harvested after pollination, but it depends on the species. On the other hand, callus is also produce from hypocotyl or cotyledon explants.
Inoculum is prepared by culture A. tumefaciens strain that contains appropriate antibiotics. The bacteria are grown with a loop and suspend in specific media such as LB, LS-inf-AS medium. Inoculum should be prepared fresh. In some cases, the growth of A. tumefaciens in liquid culture before transformation is not necessary. On the other hand, the A. tumefaciens preparation and plasmid construction are able to follow the commercial plasmid and A. tumefaciens preparation.
2.3.2.2 Explant preparation, infection, and cocultivation with A. tumefaciens
The embryonic, immature embryo or callus is able to be used as the explants. The explant should be sterilized before the infection or transformation process. Both of the suspension of the embryos and bacteria are transferred to the new plate or empty petri dish. After wrapping the petri dish, the cocultivation step follows by incubating in the dark at 24–29°C for 2–7 days, depending on the species. The A. tumefaciens concentration and the infection time were found to be important factors in preventing explant turning necrosis and improving transformation efficiency. We can follow some recommendation from several protocols for specific species.
2.3.2.3 Selection
Selection is one of the critical factors in the success of transformation. The process of selection can be occurred after the stage of transformation, regeneration, or on T0 and T1 plant. Moreover, antibiotic selection is one of the methods to check the successful transformation. In addition to antibiotic selection, PCR should be used to confirm the presence of the targeted transgene in each transformant at each generation.
2.3.2.4 Regeneration
Regeneration of transformed plants occurred after the proliferation. The shoots grown out from the proliferation explants is pulled out and placed in a new medium. Generally, the regeneration stage is following the in vitro propagation methods which are divided into shoot regeneration and selection, cut and recut shoot regeneration, and root regeneration.
2.3.2.5 Acclimatization and molecular identification of T0
The acclimatization of T0 can occur after the roots grow strongly. The transgenic T0 plant can be grown directly in a soil or mixed media under the environmental controlled or green house.
2.3.2.6 Cultivation and self-crossing of T0
The primary transformant (T0) was obtained by A. tumefaciens transformation. After the study of transgene inheritance in successive generation, T1 seeds are produced by self-crossing pollination of the primary transformant (T0). The process of cultivation occurred in the greenhouse. The seed of primary transformant (T0) is harvested from T0 plant.
2.3.2.7 T1 plant analysis
T1 plant is the plant that obtained from the harvested seed of T0 plant. The analysis of T1 plant are referring to the morphological or physiological expression of the specific gene which is inserted.
3. Conclusions
Currently, AMT become a common tool for genetic engineering. The mechanism of AMT was affected by several factors and also depends on the species. On the other hand, several Agrobacterium and plasmid have been commercialized, and it was accelerating plant breeding technology. This chapter gave brief information related to AMT mechanism, including the history of crown gall disease caused by A. tumefaciens, the natural pathogenesis of A. tumefaciens, and the general protocol of Agrobacterium-mediated transformation in plants.
\n',keywords:"Agrobacterium tumefaciens, crown gall disease, natural pathogenesis, plant transformation, plant breeding technology",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/71943.pdf",chapterXML:"https://mts.intechopen.com/source/xml/71943.xml",downloadPdfUrl:"/chapter/pdf-download/71943",previewPdfUrl:"/chapter/pdf-preview/71943",totalDownloads:1550,totalViews:0,totalCrossrefCites:3,totalDimensionsCites:3,totalAltmetricsMentions:0,introChapter:null,impactScore:1,impactScorePercentile:54,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"October 21st 2019",dateReviewed:"January 10th 2020",datePrePublished:"April 26th 2020",datePublished:"October 7th 2020",dateFinished:"April 26th 2020",readingETA:"0",abstract:"Agrobacterium-mediated transformation (AMT) heavily relies on the capability of bacterial pathogen Agrobacterium tumefaciens in transferring foreign genes into a wide variety of host plants. Currently, AMT is the most commonly used method for generating transgenic plants. On the other hand, A. tumefaciens was very useful for plant breeding. It also accelerated the technology of plant breeding to obtain specific characters. Gene transfer from bacteria to plants is a complex mechanism that involves several functional steps. This chapter will give brief information related to AMT mechanism, including the history of crown gall disease, the natural pathogenesis of A. tumefaciens, and the general protocol of AMT.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/71943",risUrl:"/chapter/ris/71943",book:{id:"9712",slug:"genetic-transformation-in-crops"},signatures:"Risha Amilia Pratiwi and Muhammad Imam Surya",authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Agrobacterium-mediated transformation mechanism",level:"1"},{id:"sec_2_2",title:"2.1 History of crown gall disease",level:"2"},{id:"sec_3_2",title:"2.2 The natural pathogenesis of A. tumefaciens",level:"2"},{id:"sec_3_3",title:"2.2.1 Signal recognition",level:"3"},{id:"sec_4_3",title:"2.2.2 T-DNA processing",level:"3"},{id:"sec_5_3",title:"2.2.3 T-DNA traveling",level:"3"},{id:"sec_6_3",title:"2.2.4 T-DNA integration",level:"3"},{id:"sec_7_3",title:"2.2.5 T-DNA expression",level:"3"},{id:"sec_9_2",title:"2.3 Agrobacterium-mediated transformation",level:"2"},{id:"sec_9_3",title:"2.3.1 The engineered A. tumefaciens Ti-plasmid",level:"3"},{id:"sec_10_3",title:"2.3.2 Agrobacterium-mediated transformation protocol",level:"3"},{id:"sec_10_4",title:"2.3.2.1 Preparation of sterilize seed or samples and inoculum",level:"4"},{id:"sec_11_4",title:"2.3.2.2 Explant preparation, infection, and cocultivation with A. tumefaciens",level:"4"},{id:"sec_12_4",title:"2.3.2.3 Selection",level:"4"},{id:"sec_13_4",title:"2.3.2.4 Regeneration",level:"4"},{id:"sec_14_4",title:"2.3.2.5 Acclimatization and molecular identification of T0",level:"4"},{id:"sec_15_4",title:"2.3.2.6 Cultivation and self-crossing of T0",level:"4"},{id:"sec_16_4",title:"2.3.2.7 T1 plant analysis",level:"4"},{id:"sec_20",title:"3. 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Cibodas Botanical Garden – Research Center for Plant Conservation and Botanic Gardens, Indonesian Institute of Sciences, Sindanglaya, Cipanas-Cianjur, Indonesia
Cibodas Botanical Garden – Research Center for Plant Conservation and Botanic Gardens, Indonesian Institute of Sciences, Sindanglaya, Cipanas-Cianjur, Indonesia
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Borisov and Igor A.\nTikhonovich",authors:[{id:"73360",title:"Dr.",name:"Alexey",middleName:"Y.",surname:"Borisov",fullName:"Alexey Borisov",slug:"alexey-borisov"},{id:"81134",title:"Dr.",name:"Vladimir",middleName:null,surname:"Zhukov",fullName:"Vladimir Zhukov",slug:"vladimir-zhukov"},{id:"81139",title:"Dr.",name:"Oksana",middleName:"Yurievna",surname:"Shtark",fullName:"Oksana Shtark",slug:"oksana-shtark"},{id:"81142",title:"Prof.",name:"Igor",middleName:null,surname:"Tikhonovich",fullName:"Igor Tikhonovich",slug:"igor-tikhonovich"}]},{id:"44504",title:"Opium Poppy: Genetic Upgradation Through Intervention of Plant Breeding Techniques",slug:"opium-poppy-genetic-upgradation-through-intervention-of-plant-breeding-techniques",signatures:"Brij Kishore Mishra, Anu Rastogi, Ameena Siddiqui, Mrinalini\nSrivastava, Nidhi Verma, Rawli Pandey, Naresh Chandra Sharma and\nSudhir Shukla",authors:[{id:"156649",title:"Dr.",name:"Sudhir",middleName:null,surname:"Shukla",fullName:"Sudhir Shukla",slug:"sudhir-shukla"}]},{id:"44016",title:"Castor Breeding",slug:"castor-breeding",signatures:"Máira Milani and Márcia Barreto de Medeiros Nóbrega",authors:[{id:"74313",title:"M.Sc.",name:"Maira",middleName:null,surname:"Milani",fullName:"Maira Milani",slug:"maira-milani"},{id:"156611",title:"Dr.",name:"Márcia",middleName:null,surname:"Barreto De Medeiros Nóbrega",fullName:"Márcia Barreto De Medeiros Nóbrega",slug:"marcia-barreto-de-medeiros-nobrega"}]},{id:"41024",title:"Participatory Plant Quality Breeding: An Ancient Art Revisited by Knowledge Sharing. The Portuguese Experience",slug:"participatory-plant-quality-breeding-an-ancient-art-revisited-by-knowledge-sharing-the-portuguese-ex",signatures:"Maria Carlota Vaz Patto, Pedro Manuel Mendes-Moreira, Mara Lisa\nAlves, Elsa Mecha, Carla Brites, Maria do Rosário Bronze and Silas\nPego",authors:[{id:"70071",title:"Prof.",name:"Maria",middleName:null,surname:"Bronze",fullName:"Maria Bronze",slug:"maria-bronze"},{id:"160017",title:"Dr.",name:"Maria Carlota",middleName:null,surname:"Vaz Patto",fullName:"Maria Carlota Vaz Patto",slug:"maria-carlota-vaz-patto"},{id:"160020",title:"MSc.",name:"Pedro",middleName:null,surname:"Mendes-Moreira",fullName:"Pedro Mendes-Moreira",slug:"pedro-mendes-moreira"},{id:"160021",title:"Dr.",name:"Carla",middleName:null,surname:"Brites",fullName:"Carla Brites",slug:"carla-brites"},{id:"160022",title:"Dr.",name:"Silas",middleName:null,surname:"Pego",fullName:"Silas Pego",slug:"silas-pego"},{id:"166078",title:"MSc.",name:"Mara Lisa",middleName:null,surname:"Alves",fullName:"Mara Lisa Alves",slug:"mara-lisa-alves"},{id:"166079",title:"MSc.",name:"Elsa",middleName:null,surname:"Mecha",fullName:"Elsa Mecha",slug:"elsa-mecha"}]}]}],publishedBooks:[{type:"book",id:"6627",title:"Brassica Germplasm",subtitle:"Characterization, Breeding and Utilization",isOpenForSubmission:!1,hash:"f11a68d95e239f899f787ef2ecd31466",slug:"brassica-germplasm-characterization-breeding-and-utilization",bookSignature:"Mohamed Ahmed El-Esawi",coverURL:"https://cdn.intechopen.com/books/images_new/6627.jpg",editedByType:"Edited by",editors:[{id:"191770",title:"Dr.",name:"Mohamed A.",surname:"El-Esawi",slug:"mohamed-a.-el-esawi",fullName:"Mohamed A. 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1. Introduction
There has been much debate about whether microwave irradiation acts as heat in chemical synthesis or whether it has a nonthermal effect [1, 2, 3, 4, 5, 6]. This problem has been discussed in many cases based on changes in the reaction rate and in the selectivity of the difference between the results with and without the application of microwaves. What is particularly important here is whether the temperatures of the two conditions to be compared are exactly the same. In microwave irradiation, it is difficult to use a general thermometer such as a metal thermocouple or an alcohol thermometer. This is because the distribution of the electromagnetic field changes significantly due to the insertion of a metal material (thermocouple or mercury thermometer), or because the indicator material (alcohol) itself is heated. As an alternative, an indirect method such as measuring the temperature from radiation on the surface of the vessel is used. In the comparison between microwave irradiation and non-irradiation, if the measurement does not correctly indicate the internal temperature, the difference may be due to the microwave irradiation condition being higher than the non-irradiation condition.
The heat source in microwave irradiation is the loss of electromagnetic wave energy, i.e., loss of the electric or the magnetic fields due to undulation of the molecule itself. Therefore, the movement behavior varies depending on the molecular species of the irradiated material. A different momentum obtained for each molecule means that it is not in a thermal equilibrium state, meaning that it does not match the definition of temperature, which requires an isotropic equilibrium motion.
The aforementioned is an inductive argument that discusses differences due to microwave irradiation, such as changes in reaction rates and in selectivity. A lot of data are reported every year, but the interpretations are diverse, and there are cases where it is “both hard to explain and hard to ignore” [1].
On the other hand, in this review, the original physical meaning is examined based on the dielectric relaxation phenomenon and how the material behaves under microwave irradiation. Based on this, we will discuss deductions about what action should be generated if there is an effect other than heat based on principles, rather than data.
2. Material properties (relaxation properties)
2.1 Permittivity and refractive index
When an object is heated by irradiation with microwaves, the microwave energy is attenuated inside the object [7]. The Beer–Lambert law in optics can also be applied in the microwave region. The refractive index, n, and the attenuation factor, k, can be combined as a complex refractive index n*, as shown by Eq. (1):
n∗=n−jk,E1
where j is the square root of −1. When the wave has a cosine signal s(t, x) as a function of time t and position x, the n and k correspond to the propagation and attenuation velocities in the phasor formula (Eq. (2)) as shown in Figure 1:
Figure 1.
Undulation and complex refractive index at t = 0.
sxt=Acosn∗x+ωt=ReAe−jn−jkxe−jωt.E2
Physical properties in the microwave region are indicated by the complex permittivity ε* [F/m] and complex permeability μ* [H/m]. The meanings of these terms can be explained by definition of the values of basic physical constants. The speed of light propagation through the vacuum (c = 2.99792458 × 108 m/s) is defined value. After May 20, 2019, the magnetic constant μ0 changed from the defined value (4π × 10−7 H/m) to the experimentally determined value (1.25663706212 (19) × 10−6 H/m) [8]. The electric constant ε0 is derived from these constants (Eq. (3)):
ε0=1μ0c2.E3
When Eq. (3) is transformed to Eq. (4), c represents the reciprocal of the square root of ε0 and μ0:
c=1ε0μ0.E4
To be precise, vacuum is not a material, but electromagnetic waves propagate through it. Since the same relationship applies to materials, they can be treated equally well in terms of mathematical expressions. The velocity v [m/s] of the electromagnetic wave propagating through a material is the reciprocal of square root of the product of the material’s permittivity ε [F/m] and permeability μ [H/m] (Eq. (5)):
v=1εμ.E5
Therefore, the refractive index n is obtained by Eq. (6):
n=cv=εμε0μ0=εrμrwhereε=ε0εr,μ=μ0μr.E6
Here, the relative permittivity εr [nd] and the relative permeability μr [nd] are coefficients based on ε0 and μ0, and n is dimensionless. In the following, the dimensionless value is expressed as [nd].
When attenuation of electromagnetic waves occurs in a material, the complex relative permittivity εr* [nd] and the complex relative permeability μr* [nd] are used. Therefore, the relationship with n* is as follows (Eq. (7)):
n∗=εr∗μr∗whereεr∗=εr′−jεr″,μr∗=μr′−jμr″.E7
The superscripts ‘and “indicate a real part and an imaginary part, respectively.
Discussions dealing only with dielectrics generally introduce important assumptions here. Since dielectrics often do not exhibit magnetism, the permeability is considered to be the same as that of vacuum, and μr * is set to 1−j0. Devices that measure permittivity (actually complex relative permittivity) often base their calculations on this assumption, so one should be careful when measuring materials with magnetism or high conductivity. Under this assumption, Eq. (7) is approximated by Eqs. (8) and (9):
n∗=εr∗,E8
n−jk2=εr′−jεr″.E9
Here, Eq. (1) is reviewed again. Since n is the ratio of the propagation velocity in the material to that in the vacuum, it can be regarded as the ratio of the wavelength λ0 [m] in the vacuum to the wavelength λ [m] in the material (Eq. (10)):
n=cv=λ0λ.E10
On the other hand, since attenuation does not occur in a vacuum, it is difficult to understand k as a ratio. Therefore, a distance δ [m] at which an electric field intensity E [V/m] becomes 1/e = 36.8% is used. Here, e is the Napier number and ω [rad / s] is the angular frequency. δ is called the skin depth and has dimensions of length. As δ decreases, the amount of attenuation increases, indicating a large k (Eq. (11)):
From these equations, n and k are obtained from the εr* of the material. When n is large, the microwave that has progressed is greatly refracted. In particular, a cylindrical vessel collects power at the center as in the case of a lens, and heating may proceed locally. Figure 2 shows an example simulating the electromagnetic field distribution of water in a cylindrical container. When the water temperature is uniform, the power loss density (PLD) is concentrated in the center [9].
Figure 2.
Simulation of the electromagnetic field of water in a cylindrical vessel in an oven-type furnace. A: Oven shape. B: PLD of 25°C water. C: PLD of 100°C water.
2.2 Penetration depth and skin depth
When the same material is irradiated with electromagnetic waves having the same frequency, the applied power intensity P [W/m3] is proportional to the square of the electric field intensity E [V/m]. When the attenuation is large, the microwave may not reach the deep part of the vessel. Although the skin depth, δ, has been described earlier, there is a penetration depth L [m] as a similar index [7]. The distance at which the power intensity P becomes 1/e due to the loss during propagation is expressed as L1/e [m]. In this case, penetration depth L1/e is half of the skin depth, δ. Microwaves are not absent beyond this depth.
There are two methods for describing L1/e, as shown in Eqs. (14) and (15):
L1e=λ04π2εr′1+εr″/εr′2−11/2,E14
L1e=λ02πεr′tanδ.E15
The δ in Eq. (15) is not a skin depth, but a value indicating dielectric loss in a narrow definition as tan δ (Eq. (16)):
tanδ=εr″εr′.E16
Eq. (15) can be obtained from a modification in which the second and subsequent terms are ignored in the Maclaurin expansion when tan2δ → 0 in Eq. (14). Therefore, when using Eq. (15), it is assumed that tan δ → 0. On the other hand, during microwave heating, the material of tan δ → 0 does not heat, as will be described later. Therefore, if the target is not tan δ → 0, it is necessary to pay attention to whether the value based on the latter formula deviates from the premise.
2.3 Plotting on bode and Nyquist diagrams
The correlation with the horizontal axis representing frequency and the vertical axis representing complex permittivity is called a Bode diagram. The Bode diagram of the water is shown in Figure 3, indicating that the dielectric constants εr′ and εr″ are functions of the (angular) frequency [10]. This is represented by the Eq. (17):
Figure 3.
Nyquist diagram and bode diagram of water (200 MHz–14 GHz).
ε=ε0εr∗ω=ε0εr′ω−jεr″ω.E17
When the complex permittivity at each frequency is plotted on a Nyquist diagram with a real part on the horizontal axis and an imaginary part on the vertical axis, they draw a semicircular locus as shown in Figure 3. Such behavior is called Debye relaxation. Debye relaxation is a behavior commonly found in nonionic liquid materials. Examples that cannot be applied include cases where the relaxation frequency is not single, and those where a conductive material is included (described at 2.10 and 2.11).
2.4 Relationship between the Debye relaxation formula and the bode/Nyquist diagram
In the previous section, we described how many liquids show a characteristically semicircular geometric locus due to Debye relaxation. We will return to the basics to explain why and what information can be gleaned below. The characteristic behavior in the microwave band is called dielectric relaxation. The deformation of electron clouds and molecular structures is a response in the UV and IR bands and is faster than in the microwave band. These contributions are prompt responses to undulated fields.
On the other hand, molecular orientation is a phenomenon based on rotation of an electric dipole. A large moment like a molecule causes a time delay in orientation with respect to field changes. The time delay referred to here is a phase delay and does not vibrate at a different period from that of the applied external field. Since the molecule cannot rotate if the external field vibration is too fast, but it can follow a too-slow external field vibration without time delay, the behavior is distributed around a specific vibration frequency [11, 12, 13, 14]. The prompt response is only a propagation delay and does not contribute to the loss. This is expressed as εr (∞) only in the real part. At the current time t, the application of an external electric field E(t) generates an electric flux density D(t) in the material.
The part of the electric flux density in the material Dp(t) (p: prompt) pertaining to prompt response is expressed by Eq. (18):
Dpt=ε0εr∞Et.E18
On the other hand, the contribution of the delayed response includes not only the electric field E (t) at the current time t but also the influence of the electric field E (u) at the previous time u. Therefore, the electric flux density Dd (t) (d: delayed) of the dielectric following the delay is expressed by Eq. (19), integrated from start time 0 to the current time t:
Ddt=∫0tEuft−udu.E19
In Eq. (19), f (t-u) represents a response function in terms of the previous time u and the current time t. From Eqs. (18) and (19), the electric flux density D (t) of the dielectric at the current time t is expressed by Eq. (20):
Dt=ε0εr∞Et+∫0tEuft−udu.E20
D(t) in Eq. (20) can also be expressed as the product of the applied electric field E(t) and the dielectric constant ε*(ω) of the material. Therefore, Eq. (21) can be obtained:
Dt=ε0εr∗ωEt.E21
Substituting Eq. (21) into Eq. (20) and rewriting the response function to f (x) yields Eq. (22):
ε0εr∗ω−εr∞=∫0∞e−jωxfxdx.E22
Next, an appropriate expression is set for a response function. In Debye-type relaxation, Eq. (23) is used as a response function to Eq. (7):
fx=ε0εr0−εr∞e−x/ττ.E23
Here, τ [s/rad] is the relaxation time, which is the reciprocal of the angular frequency ω0 [rad/s] at which the vibration phase is delayed by π/2 (90 degrees). A very slowly undulating field is effectively the same as a static field. Therefore, the complex relative dielectric constant is also only the real part, and this is represented by εr(0). As shown in the Nyquist diagram of Figure 3, εr′(ω), which is the real part of εr*(ω), is between εr(0) and εr(∞). Therefore, f (x) can be interpreted as having a proportional coefficient of εr(0)-εr(∞), which is the difference between the real parts.
When Eq. (23) is substituted into Eq. (22) and transformed, εr*(ω) is expressed by Eqs. (24)–(26). These are Debye’s dispersion equations:
εr∗ω=εr∞+εr0−εr∞1+jωτ;E24
εr′ω=Reεr∗ω=εr∞+εr0−εr∞1+ω2τ2;E25
εr″ω=Imεr∗ω=εr0−εr∞ωτ1+ω2τ2.E26
Eliminating ωτ from Eqs. (25) and (26) leads to the relationship of Eq. (27). Therefore, when εr′(ω) is on the horizontal axis and εr″(ω) is on the vertical axis, a semicircle is drawn as shown in Figure 3:
εr′ω−εr0+εr∞22+εr″ω2=εr0−εr∞22.E27
From the aforementioned, if the measured values are plotted on a semicircle, it indicates that the material has a response that can be explained by Debye relaxation theory and is not in a special state.
2.5 Three angles on the semicircle: φ, θ, and δ
The dielectric loss is also written as tan δ. This is caused by the phase delay angle δ of the voltage and current when an alternating electric field is applied to the dielectric; it is defined by Eq. (16). The complex dielectric constant is calculated by measuring the loss and the propagation delay. The physical meaning of this value is a tangent, where δ is the angle between the horizontal axis and the line segment from the origin to the circumference (Figure 4).
If the central angle φ is determined at an arbitrary point on the semicircle when εr(0) is φ = 0°, εr(∞) shows φ = 180° [15]. Therefore, φ indicates a phase delay of molecular motion in the delayed response. The tan φ at an arbitrary frequency is obtained geometrically by the following equation:
tanφ=εr″ωεr′ω−εr0+εr∞2.E29
Substituting Eqs. (25) and (26) into Eq. (29) eliminates εr(0) and εr(∞), as shown in Eq. (30). Therefore, the influence of φ upon temperature change means that it is based only on the change of the dielectric relaxation time τ when the frequency is constant:
tanφ=2ωτ1−ω2τ2=−1sinhlnωτ=−cschlnωτ.E30
As shown in Figure 4, if θ is defined as an angle formed by a straight line extending from the left intersection of the semicircle and the horizontal axis toward the measurement point and the horizontal axis, then θ is a circumferential angle of φ. Here, tan θ is expressed by Eq. (31):
transforming it yields Eq. (33) for relaxation time τ [s/rad]:
τ=1ωtanθ=1ωεr″ωεr′ω−εr∞.E33
When calculating τ, in a region far from θ = 45°(φ = 90°), even if ω changes logarithmically, φ does not change significantly, and the calculation of τ has a large error. On the other hand, in the vicinity of φ = 90°, εr*(ω) changes sharply with respect to ω. Therefore, when calculating τ using Eq. (31), it is preferable to perform evaluation with a measurement point in the vicinity of 2θ = φ = 90°.
From Eq. (32), εr″ (ω) is maximum at ω = 1/τ. In actual measurements, the function to be swept is often denoted by f[Hz] instead of ω[rad/s]. It should be noted that in many references, τ is sometimes written in terms of the reciprocal of the relaxation frequency fc which is defined in Eq. (58). In this case, the unit of the derived τ is [s], which is 2π times τ[s/rad]. In Table 1, the unit of τ is written in [s] instead of [s/rad].
Entry
fc [GHz]
τ [ps]
εr(0)
εr(∞)
εr*_(2.45 GHz)
εr*_(5.8 GHz)
Calcd.
Found
Calcd.
Found
1
H2O
16.8
59.4
79.8
4.8
78.2−j10.7
78.9−j10.8
71.8−j23.1
72.0−j23.3
2
ProC
3.5
287
66.2
7.4
46.7−j27.6
46.5−j27.8
23.0−j26.0
22.9−j26.2
3
DMSO
7.7
130
47.6
7.9
44.0−j11.5
44.2−j11.1
33.2−j19.1
33.6−j19.0
4
DMAc
8.6
116
40.5
6.2
37.9−j9.0
37.8−j9.2
29.8−j15.9
29.7−j16.1
5
MeNO2
32.3
31.0
37.1
11.0
37.0−j2.0
37.4−j2.3
36.3−j4.5
36.4−j5.1
6
DMF
13.9
72.0
37.6
8.2
36.7−j5.0
36.9−j5.2
33.2−j10.5
33.0−j10.8
7
MeCN
39.2
25.5
35.6
12.2
35.5−j1.5
35.4−j1.8
35.1−j3.4
35.0−j4.4
8
Me-Im
5.0
198
38.0
5.5
31.8−j12.8
31.8−j12.6
19.5−j16.1
19.7−j16.2
9
NMP
6.8
148
33.4
6.0
30.2−j8.8
30.2−j8.7
21.8−j13.5
22.0−j13.7
10
PhNO2
3.5
285
35.0
4.5
25.0−j14.3
24.6−j14.3
12.7−j13.5
12.2−j13.4
11
MeOH
3.0
338
33.7
6.1
22.5−j13.6
22.2−j13.2
11.8−j11.2
11.6−j11.1
12
PhCN
4.5
223
26.0
4.4
21.1−j9.1
21.4−j8.7
12.5−j10.5
12.7−j10.6
13
Me2CO
44.4
22.5
21.2
5.8
21.2−j0.8
21.0−j1.0
21.0−j2.0
21.1−j2.4
14
MEK
24.2
41.3
18.7
9.0
18.6−j1.0
18.6−j1.1
18.1−j2.2
18.0−j2.4
15
PhCHO
5.2
191
18.9
4.0
16.2−j5.7
16.2−j5.7
10.7−j7.4
10.8−j7.5
16
DCE
15.4
65.1
10.4
5.2
10.2−j0.8
10.2−j0.9
9.7−j1.7
9.7−j1.9
17
CH2Cl2
—
—
9.3
8.5
—
9.3−j0.1
—
9.1−j0.5
18
EtOH
0.9
1100
25.8
4.6
7.2−j7.0
7.5−j7.0
5.1−j3.3
5.3−j3.4
19
MeI
17.9
55.9
7.3
5.7
7.3−j0.2
7.2−j0.2
7.2−j0.5
7.1−j0.6
20
AcOEt
13.0
76.6
6.3
4.6
6.2−j0.3
6.2−j0.3
6.0−j0.6
6.0−j0.7
21
PhCl
10.4
96.3
5.8
3.2
5.7−j0.6
5.7−j0.6
5.2−j1.1
5.2−j1.1
22
PhF
13.8
72.6
5.8
4.0
5.7−j0.3
5.7−j0.3
5.5−j0.6
5.5−j0.6
23
PhBr
7.5
134
5.8
3.1
5.6−j0.8
5.5−j0.7
4.8−j1.3
4.9−j1.3
24
CHCl3
11.1
89.9
5.1
3.9
5.0−j0.2
5.1−j0.0
4.8−j0.5
4.9−j0.4
25
PhI
5.2
192
5.0
3.0
4.7−j0.8
4.7−j0.7
3.9−j1.0
3.9−j1.0
26
Et2O
—
—
4.5
4.1
—
4.5−j0.1
—
4.4−j0.2
27
2-PrOH
0.4
2730
20.1
3.4
3.8−j2.4
4.1−j2.7
3.5−j1.0
3.6−j1.3
28
CPME
27.8
36.0
4.0
2.3
4.0−j0.1
3.9−j0.3
3.9−j0.3
3.9−j0.4
29
1-BuOH
0.3
3170
16.3
3.4
3.6−j1.6
3.9−j2.0
3.4−j0.7
3.5−j1.1
30
2-BuOH
0.3
3540
15.4
3.2
3.3−j1.4
3.6−j1.6
3.2−j0.6
3.3−j0.9
31
i-BuOH
0.2
4070
16.1
3.1
3.3−j1.3
3.5−j1.6
3.2−j0.5
3.2−j0.9
32
t-BuOH
0.3
2910
11.6
2.9
3.1−j1.2
3.3−j1.5
2.9−j0.5
3.0−j0.8
33
PhMe
—
—
2.5
2.4
—
2.5−j0.1
—
2.4−j0.1
34
PhH
—
—
2.4
2.3
—
2.4−j0.1
—
2.4−j0.0
35
c-Hex
—
—
2.2
2.1
—
2.1−j0.1
—
2.1−j0.0
36
n-Hex
—
—
2.0
1.4
—
2.0−j0.0
—
2.0−j0.0
Table 1.
Physical property values of several liquids at room temperature. [19].
The propagation of the electromagnetic wave energy of the microwave is propagation of electromagnetic field vibration. Specifically, this vibration is caused by continuously and repeatedly converting the electric field energy into magnetic field energy and vice versa. The propagation equations are shown as follows (Eqs. (34)–(38)):
rotH=i+∂D∂t;E34
B=μH;E35
rotE=−∂B∂t;E36
D=εE;E37
i=σE.E38
Here, E, H, D, B, and i are the electric field intensity [V/m], magnetic field intensity [A/m], electric flux density [C/m2], magnetic flux density [Wb/m2], and current density [A/m2], all of which are vector quantities. In addition, the physical property coefficient of the material is transferred as a permittivity ε [F/m], a conductivity σ [S/m], and a permeability μ [H/m]. The loss of propagation energy means that the vector quantity has been lost when converted to the other field. This loss is mainly regarded as a conversion to heat. The loss equation calculated based on the physical property values is derived below [11, 12, 16].
The applied E is expressed by using a phasor as follows:
E=E0ejωt.E39
D in the dielectric produced by aligning the directions of the dielectric molecules undulates with a phase shift (delay) of δ. δ is a value expressed by Eq. (16) and is not φ, which is an undulation phase delay of the molecule:
D=D0ejωt−δ.E40
From Eq. (37), the product of E, ε0, and εr* gives D. Therefore, the phase delay of D can also be expressed by the complex permittivity (Eq. (41)):
Next, the energy consumption per unit volume when the electric flux density of the dielectric changes by dD is determined as dU. This dU is obtained by the product of E and dD. When dD is integrated over one period of vibration (1 / f = 2π / ω), the energy consumed by the dielectric during one period is obtained as w,
Since w is repeated f times per second (= ω/2π times), the energy W received by the dielectric from the electric field per unit volume / unit time is expressed by Eq. (49):
W=ω2πw=12ωε0εr″E02=πfε0εr″E02.E49
Rewriting Eq. (49) yields Eq. (50). Here, when E0 is rewritten to |E|, the electric field loss equation is obtained. In this paper, the dielectric loss based on ε obtained by Eq. (50) is defined as Pε_loss [W/m3]:
Pε_loss=12ωε0εr″E2.E50
When the frequency is very low and the change in the electric field is very slow, the molecules align their dipole moments in a direction that cancels the electric field without delay in proportion to the electric field strength, and this flux density can follow without delay. Since φ → 0 and δ → 0, εr″ → 0 from Eq. (43), Pε_loss → 0 from Eq. (50), and the electromagnetic wave energy loss is small. On the other hand, if the frequency is very high and the change in the electric field is very fast, the movement of the molecules cannot respond to the alternating electric field, and the application direction reverses before aligning the dipole moments. As a result, since φ → π and δ → 0, εr″ → 0, so Pε_loss→ 0 and the electromagnetic wave energy loss is small.
2.7 Difference between tan δ and εr″ in loss
If the target frequencies are the same, ω may be regarded as a constant. According to the aforementioned equation, the loss appears to be proportional to εr″, but the actual loss is not determined solely by the difference in εr″. The meaning of Eq. 50 indicates that if E is constant, the amount of power loss per unit volume is proportional to εr″. However, the propagation speed of electromagnetic waves decreases with the refractive index n, which varies with ε (and μ).
Figure 5 shows a model in which microwaves pass through media in the order of air, water, and air. Here, for the sake of simplicity, the electric flux is indicated by a straight arrow, and the reflected wave at the boundary is not considered. Wavelength reduction is considered first [17]. The electric flux density in air is D1 [C/m2], and that in water is D2 [C/m2]. Since wavelength shortening occurs in water with a large εr′, the interval (density) of arrows in D2 increases to (εr)0.5 times in D1 according to Eq. (8). Next, the electric field strength is considered. The electric field strength in air is E1 [V/m], and that in water is E2 [V/m]. In water where εr′ is large, the dipole of water cancels the applied electric field so that the intensity decreases to 1/εr according to the constitutive Eq. (37). Combining these two effects, the electric field strength E2 in water attenuates to 1 / (εr)0.5 times the electric field strength E1 in air as shown in Eq. (51):
Figure 5.
Model structure of heating considerations. Area 1:Air, area 2:Water, area 3:Air.
D2=εr′D1D1=ε0E1D2=ε0εr′E2thereforeE2=1εr′E1.E51
In actual examinations, it is difficult to measure the electric field strength inside the irradiation target. Therefore, irradiation with a predetermined irradiation power is performed. Thus, the following interpretation is derived:
Eq. (52) indicates that the loss is proportional to εr″ when the applied electric field is constant:
Pε_loss=12ωε0εr″E22.E52
Eq. (53) indicates that the loss is proportional to tan δ when the applied power is constant:
Pε_loss=12ωε0εr″E1εr′2=12ωε0tanδE12.E53
The applied electric field and applied power referred to here are the net electric field and power applied to the materials. As will be described later, not all irradiation power is always applied. The irradiated and reflected powers can be measured in area 1. The passing through power can be measured in area 3.
2.8 Maximum of tanδ
From the Nyquist diagram, the maximum value of tan δ is the tangent point through the origin. Therefore, it is obtained from Eq. (54):
tanδmax=εr0−εr∞2εr0εr∞.E54
Furthermore, εr′(ω) and εr″(ω) when tan δ is maximal are represented by Eqs. (55) and (56):
εr′tanδmax=2εr0εr∞εr0+εr∞,E55
εr″tanδmax=εr0−εr∞εr0+εr∞εr0εr∞.E56
The tan θ when tan δ becomes maximum is defined as tan θtanδmax. This is geometrically determined from Figure 4. The angular frequency ωtanδmax at this time is given by Eq. (32). When both are combined, Eq. (57) is derived:
tanθtanδmax=ωtanδmaxτ=εr0εr∞.E57
The frequency at which εr″ is maximized is defined as fc. Since tanθ is 1 at fc, 2πfcτ is equal to 1 from Eq. (32) and Figure 4. Therefore, Eq. (57) becomes Eq. (58) by ftanδmax and fc:
ftanδmax=εr0εr∞fc.E58
The semicircle in the Nyquist diagram shows that the maximum values of εr″ and tan δ do not match. For example, water has a maximum value of εr″ at 18 to 22 GHz, but the maximum value of tan δ is on the higher frequency side. Since 2.45 GHz is much smaller than these, it appears to be less efficient at heating water. However, when the amount of absorption is large, attenuation occurs rapidly in the surface and does not penetrate into the inner side. Therefore, it cannot be said that a larger loss is always effective for heating the inside to a wide area.
2.9 Changes in εr* with temperature
The complex dielectric constant according to Debye relaxation can be generalized by obtaining εr(0), εr(∞), and τ by measuring in a wideband and fitting to a semicircle. From this relationship, it can be seen that the temperature, frequency, and complex permittivity have the following relationship:
When the temperature rises, the molecule becomes disturbed. As a result, the external response amount εr′(ω) decreases. This also applies to εr(0).
When the temperature rises, the intermolecular bond becomes weaker and the relaxation time τ becomes shorter. As a result, the peak value of εr″(ω) shifts to the high frequency side.
If the dielectric loss is based on the response-phase difference φ, εr′(ω) and εr″(ω) are linked by the Kramers-Kronig relations and are not independent.
As shown in Figure 6, the Bode diagrams of εr′(ω) and εr″(ω) shift from 1 → 2 → 3 with temperature rising [18]. Therefore, in the Nyquist diagram, the central angle φ indicated by the irradiation frequency fi can be classified into six types depending on the position [11, 12, 13].
Figure 6.
Area division of the bode diagram. Left: area division; Right: temperature rising.
Type I is the case where the relaxation frequency fc of the irradiated material before heating is much larger than fi, and the φ of the irradiated material before heating is in the vicinity of 0π/8 to 2π/8. As the temperature rises, φ approaches 0 and the amount of loss decreases.
Type II is the case where fc is slightly larger than fi, and φ indicates 2π/8 to 4π/8. Since εr″(ω) is large, the temperature rises rapidly. However, as the temperature becomes high, φ decreases and the temperature rise rate greatly decreases.
Type III is when fi is close to or slightly smaller than fc, and φ is in the vicinity of 4π/8 to 5π/8. Since εr″(ω) is large as a whole, the temperature rise rate is high and εr″(ω) rises until φ becomes π/2 and then falls.
Type IV is when fc is smaller than fi, and φ indicates 5π/8 to 7π/8. The tan δ is a large region, and as temperature rises, φ approaches 4π/8, so εr″(ω) further increases. Thermal runaway due to uneven heating may occur.
Type V is the case where fc is much smaller than fi, and φ indicates 7π/8 to 8π/8. Although it has the property that the temperature rises due to irradiation and the amount of absorption increases, there is a case where the irradiation frequency is too high, such that there is a lot of transmission and heating is not sufficient.
Type 0 is not shown in this figure. This corresponds to the case where contributions to the original dielectric loss, such as that from nonpolar molecules, are very small.
When the irradiated fi is considerably smaller than fc, the change in εr′ (ω) and εr″(ω) due to temperature rising is classified as type I, but when it irradiates a considerably larger fc, it becomes a V type. Therefore, this classification also means that the classification changes depending on the irradiation frequency, even for the same material. As an example, the physical property values of several liquids and the value of τ calculated from a semicircle are shown in Table 1.
2.10 Liquid mixture
For the relaxation time τ in the system to show only one value, it is necessary for the entire material to be in a uniform state. This occurs when there is only one kind of electric dipole that controls the dielectric constant, and the surrounding molecules that control the relaxation time are also uniform. This means that τ is distributed according to the δ function [20]. In the mixed liquid, there are various types of molecules exhibiting dielectric loss and various types of surrounding molecules. Therefore, the relaxation time is not always one. In the model, when the εr*(ω) of a system having the same εr(0) and εr(∞), different τ is calculated. Figure 7 shows that wideband complex permittivity plot is separated into two semicircles when the difference between the two τ is large. On the other hand, when the difference in τ is not large, the distortion of the semicircle is small. In the case of simple two-component mixing, the trajectory shown in the Nyquist diagram is considered to be similar to any in Figure 7. However, there is little distortion in the measurement range as shown in Table 1, and there is almost a single semicircle. This can be regarded as a response in which εr(0), εr(∞), and τ show one average value. Furthermore, when τ is evaluated with respect to the mixing ratio, it continuously changes according to the composition, but it is not always shown on the straight line in terms of arithmetic mean. However, there is also a behavior that protrudes upward and downward.
Figure 7.
Nyquist diagrams with two τ. Line 1: zero difference in τ, Line 2: small difference in τ ∼ Line 6: large difference in τ.
Figure 8 shows the Argan diagram as a complex relative permittivity at 2.45 GHz by the reflection probe method [21, 22, 23]. One line indicates the nine mixtures made with a volume ratio of 9:1 to 1:9 between two pure liquids. If the εr* obtained in the mixed sample obeys the additive property, the connection should be a straight line, but in many cases a curve is shown. This is because εr(0), εr(∞), and τ change due to the mixing of the two materials, such that εr′ and εr″ do not always attain a single arithmetic average value.
A plot of the responses at other frequencies on the Argan diagram is also shown in Figure 8. Apparently, these figures have changed greatly. However, as shown in point A, ethanol:water = 4:6 mixed solution, acetonitrile:propylene carbonate = 2:8 mixed solution, and acetone:propylene carbonate = 2:8 mixed solution had close εr* values, regardless of frequency. Similar intersection points were also observed in Group B (acetone:propylene carbonate = 9:1, cyclopentyl methyl ether:acetonitrile = 3:7) and Group C (ethanol:propylene carbonate = 7:3, methanol = 10). This means that if the average εr(0), εr(∞), and τ obtained by mixing are close, εr*(ω) matches, and therefore the same εr* is shown at different frequencies. Thus, when the liquid mixture characteristic is shown as a “train map,” the intersection corresponding to the “transfer station” does not change even if the frequency does.
2.11 Involvement of conductivity σ
The conductive material is heated by the conductive loss [10, 24, 25, 26, 27]. This property agrees with the dielectric loss in that it is proportional to the square of the electric field strength. These are losses to the electric field and not to the magnetic field. Since ω is not included in the conduction loss equation, it occurs even when the frequency is zero. Conduction loss is a phenomenon in which materials with a single charge, that is, positive and negative ion atoms (or molecules), are accelerated in opposite directions by application of an electric field. An increase in the distance between the counterions means that the electrostatic potential of the material is increased. Also, if ions that should linearly move with constant acceleration are decelerated to constant speed, this means that resistance has made ions motion isotropic, or the surrounding molecules have received the kinetic energy of ions. This means that the current has been converted to Joule heat. It is clear that such a conduction loss differs from dielectric loss in which the charge distance in the molecule is constant. Therefore, in the partial dielectric including conductivity, the conductive and dielectric losses appear separately. For example, the Nyquist diagrams of 0.1-mol/L = NaCl aqueous solution are shown in Figure 9. Comparing to Figure 3, it is shown that the locus is changed by adding NaCl due to conductive loss.
Figure 9.
Nyquist and bode diagrams of 0.1-Mol/L NaCl aqueous solution.
In many cases, only one parameter σ is used for the discussion of conductive loss. However, in the Nyquist diagram, σ must be a complex number with real and imaginary parts. If these parts have the same value, the low-frequency part shown in Figure 9 should be a straight line with a 45° slope, but the measured value is not. Therefore, from this figure, when discussing losses in the microwave band, conductivity must also be considered to have a complex value.
The power density w* [J/m3] of one cycle can be calculated from the current density i(t) = i0 sinωt with amplitude i0 [A/m] and the electric field intensity E(t) = E0 sinωt with amplitude E0 [V/m]. From the definition of the complex conductivity σ* [S/m] = σ′−jσ″, Eq. (38) is deformed as Eq. (59):
Since w* is repeated f times per second, the energy W received by the conductive material from the electric field per unit volume/unit time is expressed by Eq. (61):
W∗=12σ∗E02.E61
Here, σ* is a complex value and describes mobility and loss at the same time. When the real part is mobility and the imaginary part is loss, the conduction loss can be described in the same way as Eq. (50), and Eq. (62) is obtained:
Pσ_loss=12σ″E2.E62
Comparing Eqs. (50) and (64), it can be seen that σ″ and ωε0εr″ have the same dimensions. Therefore, the loss equation of the combined electric field is Eq. (63):
PE_loss=12σ″+ωε″E2.E63
The apparent relative permittivity measured in Figure 9 is the sum of the permittivity term and the conductivity term. This response is represented by ψr * (ω). Here, since σr* has the same dimension as ωεr*, ψr*(ω) is expressed by the following Eq. (64):
ψr∗ω=σ∗ωωε0+εr∗ω=σr∗ωω+εr∗ω.E64
When the complex conductivity σ* [S/m] = σ′−jσ″ is determined in the same manner as the complex conductivity ε* [F/m] = ε′−jε″, the complex relative permittivity εr* [nd] = ε*/ε0, the complex relative conductivity is derived as σr* = σ*/ε0 = σr’ − jσr″. Here, σr* has the same dimensions as ωεr*, [rad/s]. Although the international annealed copper standard (IACS) is defined as 58 MS/m as a standard for conductivity, σr* indicates a ratio to ε0, rather than IACS.
In the previous diagram of the NaCl aqueous solution, the Nyquist diagram shows a semicircle in the high-frequency band, so this region has dielectric properties. On the other hand, in the low-frequency region, a locus different from a semicircle based on the movement of ions is shown. This means the loss due to the phase delay is small and mainly due to the motion of the ionic molecules. Whether the heat generation behavior at the irradiated frequency is mainly caused by dielectric or conductive loss cannot be distinguished by measurement at one frequency. Unless it is a Nyquist or Bode diagram, the contribution ratio of the dielectric and conductive losses cannot be separated from the locus.
3. Extraordinary microwave effect
In many discussions of microwave chemistry, temperature and heat are very important. It is shown that the loss of electromagnetic energy is based on the imaginary part, i.e. εr″ or σr″, as shown in Eq. (65). On the other hand, it is stated that energy is accumulated in a material with a large real part because propagation delay occurs, and substantial loss can be obtained by the tan δ term as shown in Eq. (53). Since microwave energy penetrates the material, the amount of energy on the spot can be increased without changing the amount of material. Therefore, it must be remembered that there is a high energy in the field, even if there is no conversion to heat. From this viewpoint, we considered what behavior should be taken if there is a nonthermal effect when microwave energy is applied. This section discusses deductions based on principles, not induction based on data [28, 29].
3.1 Classification of microwave effects
When the chemical reaction field under microwave irradiation is different from the non-irradiation condition, its form can be classified into four types.
Fast reaction rate (acceleration);
Slow reaction rate (deceleration);
Different products (selective production);
Different consumptions (selective consuming).
The first is an example in which the reaction speed increases when microwave energy is applied, and as a result, the reaction’s end time is shortened. Since the reaction rate can be significantly accelerated by increasing the temperature, one can always discuss whether the temperature was accurately measured or whether the actual reaction field temperature was high. The second is an example opposite to the first. This phenomenon appears when the actual reaction field temperature is low, but this case has little detailed discussion. If phase transition is included in the category, supercooling and overheating phenomena correspond to this. The third is an example in which products differ depending on the presence or absence of microwave irradiation when multiple products are considered. This happens when there are multiple reaction paths, one of which is particularly accelerated. This includes cases where only intermediates are obtained in a multistep reaction. The fourth is an example of a case with multiple substrates, and a reaction of the specific substrates is prioritized. In any of these cases, the reaction rate is considered to have changed due to the application of microwave energy. That is,
The target reaction speed increased;
The inhibition reaction speed increased;
The reaction speed for obtaining target products increased;
The reaction speed for consuming specific substrates increased.
All four of these interpretations mean that the specific reaction rate was increased by the application of microwave energy. From the aforementioned, when the chemical reaction under microwave irradiation is different from that in the non-irradiation case, if it is not a thermal effect, an equation for changing the reaction rate must be derived even if the temperature T is constant. The following describes the possibility of such an expression.
3.2 Real and imaginary parts
Eq. (63) describes the attenuation of the energy of the electric field. Considering the propagation here, it is an expression in which the imaginary part is changed to a real part. This means that the propagation equation is derived as Eq. (65):
PE_prop=12σ′+ωε′E2.E65
Since the conductive material can be regarded as a special state of the dielectric, discussion of the material including σ will be omitted hereafter. Energy of electromagnetic waves vibrate between electric and magnetic fields as follows equations (Eqs. (66)–(69)). Herein, the magnetic field loss and the propagation energy PH are also expressed based on the complex permeability μ* = μ′−jμ″ [H/m]:
PE_prop=12ωε′E2;E66
PE_loss=12ωε″E2;E67
PH_prop=12ωμ′H2;E68
PH_loss=12ωμ″H2.E69
Therefore, propagation of electromagnetic waves occurs according to the following stages:
E-stage 1: Electric field energy given in the system is accumulated as propagation amount PE_prop, and loss amount PE_loss is converted into isotropic thermal motion of the molecules;
E-stage 2: Propagation amount PE_prop changes to magnetic field energy;
H-stage 1: The magnetic field energy given in the system is accumulated as propagation amount PH_prop, and the loss amount PH_loss is converted into isotropic thermal motion of the molecules;
H-stage 2: Propagation amount PH_prop changes to electric field energy.
These stages are repeated. What this equation indicates is transition of the electromagnetic wave energy, not a chemical reaction; thus, to consider the effect on the chemical reaction, one uses the following quantities:
PX_prop indicates the amount of energy present in the field acting on the reaction;
PX_loss indicates the amount of energy lost to the field affecting the reaction;
A combination of these.
Whether PX_prop is involved as a field that affects the reaction or PX_loss is involved as a result of affecting the reaction is not clearly determined now. In any case, however, it should be energy terms which affect the chemical reaction.
3.3 Interpretation of the Arrhenius equations
In the reaction kinetics, the activation energy theory described by Arrhenius (Eq. (70)), which originated from gas molecular kinetics, is discussed:
k=Ae−EaRT.E70
Strictly speaking, it cannot be applied theoretically except for the secondary reaction of two gas molecules, but it is useful as an empirical formula and can be used in a solution system. Here, k, A, Ea, and R are the reaction rate constant, A-factor, activation energy [J/mol], and molar gas constant [J/Kmol]. Ea is assumed to be a constant that does not change with the reaction temperature.
The Arrhenius equation can be interpreted as follows. The horizontal axis in Figure 10 shows the molecular velocity v in an arbitrary reaction coordinate system. The vertical axis φv represents the existence probability of the molecule with a normal distribution. In Figure 10, it is assumed that a molecule that thermally and isotropically exchanges kinetic energy at a temperature T has a normal velocity distribution according to Eq. (71):
Figure 10.
Relationship between molecular velocity v and existence probability φE. Line 1: small distribution ∼ Line 3: large distribution.
ϕv=Ae−mvx22RT.E71
Here, the mass per mol is m [kg/mol], the kinetic energy of the molecule is Ev = mv2/2 [J/ mol], and the horizontal axis is energy, E. If the range of E is 0 ≤ E < +∞, this frequency distribution φE is canonical, as shown in Figure 11.
Figure 11.
Reaction coordinate and energy distribution at temperature T.
ϕE=Ae−ERTE72
The progress of the reaction is assumed to occur when the motion of the original molecule coincides with the positive direction of the reaction coordinate system and its kinetic energy exceeds Ea. The reaction coordinate is shown on the left-hand side of Figure 11. Here, the substrate, transition state, and product are Sb, Tr, and Pd, respectively. The integrals of the region Ea < E < ∞ and of the whole region 0 ≤ E < ∞ are expressed by Eqs. (73) and (74):
∫Ea∞Ae−ERTdE=ARTe−EaRT;E73
∫0∞Ae−ERTdE=ART.E74
Therefore, the ratio of the region exceeding Ea to the entire region is represented by Eq. (75), indicating that A is irrelevant:
∫Ea∞Ae−ERTdE∫0∞Ae−ERTdE=e−EaRT.E75
The value obtained by Eq. (75) is the Boltzmann factor. In the Arrhenius equation, the reaction rate is proportional to the Boltzmann factor because of the occupation ratio of the high energy state.
Here, the temperature T of the heat bath is increased to T + ΔT. In gas molecule kinetics, the kinetic energy of a molecule increases with temperature, and this is expressed by (mBv2)/2 = 3kBT/2. Here, mB and kB are the mass of one molecule and the Boltzmann constant, respectively. Therefore, a temperature increase of ΔT is the same as one molecule receiving kBΔT/2 of energy as mBvx2/2, mBvy2/2, and mBvz2/2, respectively. Considering this at 1 mol, since R = NAkB (where NA is Avogadro’s number), the kinetic energy of the system is distributed to the x, y, and z components by RΔT/2, respectively.
When any one direction is taken as the reaction coordinate, the energy distribution is the same in any state from Sb to Pd in the reaction coordinate system. Therefore, as expected, Ea does not change, even if the temperature is raised. This is shown on the left-hand side of Figure 12. On the other hand, an increase in T corresponds to a decrease in the kurtosis of the Boltzmann distribution in the original molecule and an increase in the tail. As a result, the occupancy rate of molecules having an energy exceeding Ea increases, and the reaction rate k increases, as shown at right in Figure 12.
Figure 12.
Reaction coordinate and energy distribution at temperature T + ΔT.
Next, consider the supply of microwave energy instead of ΔT as an external energy supply. The Arrhenius equation presupposes that it is in thermal equilibrium, which indicates that energy can be exchanged quickly with an external heat bath. Therefore, if the rate at which the system releases heat to the outside matches the heating rate by microwaves, a constant temperature state can be maintained, and T can be regarded as constant. This means that there can be reaction systems with the same T and different microwave application intensities. Microwave energy is calculated as energy per unit time. On the other hand, the reaction kinetics discussed earlier calculate the change in the molar concentration of molecules as the reaction rate. Therefore, in order to align the units, the electromagnetic wave energy supplied to the volume per mole with respect to the concentration M [mol/m3] of the target reaction molecule is Eadd [J/mol]. Eadd is proportional to the oscillated energy EMW [J/mol], which is the product of power per mole and irradiation time, but not all energy works effectively.
Herein, the effective efficiency is defined by α and γ, and Eadd = αRT = γEMW. This means that αRT is added to the thermal potential RT that the field already has. Assuming that this added amount of external energy is incorporated into the canonical distribution in the same manner as RΔT, the potential distribution is derived in Eq. (76) by replacing RT in Eq. (72) with (1 + α)RT:
ϕE=A1e−E1+αRT=A1e−ERT+Eadd.E76
The coefficient A1 in Eq. (76) was introduced to consider the possibility that the A-factor changes depending on the presence or absence of external energy.
From the right-hand side of Figure 13, integration of the region Ea < E < ∞, integration of the whole region 0 ≤ E < ∞, and the ratio between both are obtained as Eqs. (77), (78), and (79):
Figure 13.
Reaction coordinate and energy distribution at temperature T under microwave irradiation.
From the aforementioned, it is apparent that the exponential form of the Boltzmann factor is maintained, and this expression is irrelevant to A1, just as was Eq. (75). Here, when the reaction rate constant under microwave non-irradiation is k0 and that under irradiation is k1, the Arrhenius equation is described as follows:
k0=A0e−EaRT;E80
k1=A1e−EaRT+Eadd.E81
Comparing both equations, k0 = k1 at Eadd = 0. Therefore, A0 = A1 is derived. Eq. (81) shows that the A-factor does not change under microwave irradiation.
3.4 Introduction of a nonthermal constant
Generalizing Eq. (81) under an applied microwave irradiation yields Eq. (82):
k=Ae−EaRT+γEMW.E82
EMW is an intensive property that can change the applied amount from the outside. Therefore, changing k by a variable independent of temperature T is not thermal, that is, a nonthermal effect. Therefore, the coefficient γ in Eq. (82) is a nonthermal constant. Here, if γ is a positive value, the group has the same T, but the variance of the canonical distribution widens, and the occupation ratio of Ea or higher is increased and k0 < k1.
Eq. (82) does not change Ea and A. Therefore, the reaction route is not changed. This is a reaction rate equation that can be applied, even when the microwave irradiation is 0, and the irradiation intensity of the microwave is variable. In this case, the population maintains a canonical distribution. If there is a nonthermal effect, it must be expressed by a reaction equation with a microwave intensity independent of temperature as a variable. Eq. (82) obtained by deduction meets this condition.
3.5 Working principle of a nonthermal constant
Eqs. (81) or (82) can be transformed into Eq. (83). Ea and A can be obtained without microwave irradiation. If Ea and A are not changed by microwave irradiation, Eadd, that is, γEMW can be obtained from k at T. Assuming that the volume of the irradiation target is same and EMW is proportional to the irradiation power, γ can be calculated from Eq. (83):
αRT=Eadd=γEMW=EalnA−lnk−RT.E83
If the effect of microwave irradiation is expressed by Eq. (81), the ratio r between Eqs. (81) and (80) indicates the efficiency of increase by microwave irradiation (Eq. (84)):
r=Ae−Ea1+αRTAe−EaRT=eα1+αEaRT.E84
When α is 0, there is no irradiation, so r = 1. The upper limit of r is considered when α is infinite. Therefore, the upper limit rmax of r is expressed by Eq. (85):
rmax=lima→∞eα1+αEaRT=eEaRT.E85
This equation suggests that in a system having an effective α, the effect of microwave irradiation appears more markedly as the reaction temperature T is lower and Ea is higher.
4. Conclusions
Microwave chemistry was described with a focus on the behavior of dielectrics. We discussed the relationship between physical properties such as dielectric constant, energy propagation in the material, and energy loss in the material. By discussing energy, if there is a special effect other than heat in microwave chemical reactions, we have derived a priori by mathematical formulas factors that are required. The “Arrhenius equation under microwave irradiation” proposed in this section is one model. In this equation, a microwave energy term is added.
In order to confirm the results of this deduction inductively, correct measurements are required. A simple method is a surface temperature measurement with a radiation thermometer, but the fact that there is a temperature difference from the inside has been investigated in various experiments, and unless this problem is solved, it will lead to incorrect measurement. The temperature and its distribution should be validated with multiple methods, such as internal radiation measurements using an optical fiber, a fiber-grating method that measures the local volume changes of the optical fiber, and temperature dependence of the lifetime of the fluorescent material at the tip [30, 31, 32].
As presented in this paper, understanding microwave effects algebraically in terms of energy theory is different from considering energy distribution geometrically. For example, the existence of nonequilibrium local heating, which is influenced by the structure of the irradiated object, has been reported [33]. This phenomenon, which can be explained as a peculiar heating method occurring in microwave heating, is due to the geometric intensity of the electromagnetic field distribution. In this example, the unique heat distribution structure gives “geometric” microwave effects rather than “algebraic” microwave effects.
Microwaves in the GHz band have a decimator wavelength. If the size of the reaction vessel is smaller than the wavelength, the result may vary greatly depending on the place of installation and the shape of the vessel, based on the microwave interference. Therefore, in chemical synthesis assisted by microwave heating, it is necessary to consider the shape of the electromagnetic field distribution in the apparatus. Otherwise, other conditions may change at the same time that the temperature, substrate, solvent, and scale are changed. If this unintended influence is ignored, it becomes difficult to clarify general trends in the condition search, or the result will lead to excessively good or bad evaluations. Thus, microwave chemistry seems to be complicated in terms of chemistry and electromagnetic field analysis. However, it can be expected that more efficient reaction control will be possible by fully utilizing the control as an external field and utilizing it highly. In addition to the algebraic interpretation based on energetics, if the structure of the irradiated object is geometrically controlled as a metamaterial, further microwave effects will be manifested. We believe that microwave chemistry will be a useful technique that can be used to manipulate chemical synthesis by applying external energy to a simple heating reaction.
\n',keywords:"microwave chemistry, complex permittivity, Debye relaxation, nonthermal effect, Arrhenius equation",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/82958.pdf",chapterXML:"https://mts.intechopen.com/source/xml/82958.xml",downloadPdfUrl:"/chapter/pdf-download/82958",previewPdfUrl:"/chapter/pdf-preview/82958",totalDownloads:4,totalViews:0,totalCrossrefCites:0,dateSubmitted:"June 20th 2022",dateReviewed:"July 4th 2022",datePrePublished:"August 5th 2022",datePublished:null,dateFinished:"August 5th 2022",readingETA:"0",abstract:"We consider the application of microwave energy to a material. The effects of the electromagnetic field on the material and of the material on the electromagnetic field will be described, focusing on the dielectric relaxation phenomenon of the liquid. The dielectric permittivity of mixtures is discussed by extending Debye relaxation to explain how the material behaves with respect to an electric field. We will also consider the energy that the electric field imparts to the material, both thermally and nonthermally. We will develop this relation and describe what form it should take if there is a nonthermal effect in the chemical reaction field under microwave irradiation.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/82958",risUrl:"/chapter/ris/82958",signatures:"Sugiyama Jun-ichi, Sugiyama Hayato, Sato Chika and Morizumi Maki",book:{id:"11494",type:"book",title:"Electric Field in Advancing Science and Technology",subtitle:null,fullTitle:"Electric Field in Advancing Science and Technology",slug:null,publishedDate:null,bookSignature:"Prof. Hai-Zhi Song",coverURL:"https://cdn.intechopen.com/books/images_new/11494.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80356-678-8",printIsbn:"978-1-80356-677-1",pdfIsbn:"978-1-80356-679-5",isAvailableForWebshopOrdering:!0,editors:[{id:"196114",title:"Prof.",name:"Hai-Zhi",middleName:null,surname:"Song",slug:"hai-zhi-song",fullName:"Hai-Zhi Song"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Material properties (relaxation properties)",level:"1"},{id:"sec_2_2",title:"2.1 Permittivity and refractive index",level:"2"},{id:"sec_3_2",title:"2.2 Penetration depth and skin depth",level:"2"},{id:"sec_4_2",title:"2.3 Plotting on bode and Nyquist diagrams",level:"2"},{id:"sec_5_2",title:"2.4 Relationship between the Debye relaxation formula and the bode/Nyquist diagram",level:"2"},{id:"sec_6_2",title:"2.5 Three angles on the semicircle: φ, θ, and δ",level:"2"},{id:"sec_7_2",title:"2.6 Loss calculation formula",level:"2"},{id:"sec_8_2",title:"2.7 Difference between tan δ and εr″ in loss",level:"2"},{id:"sec_9_2",title:"2.8 Maximum of tanδ",level:"2"},{id:"sec_10_2",title:"2.9 Changes in εr* with temperature",level:"2"},{id:"sec_11_2",title:"2.10 Liquid mixture",level:"2"},{id:"sec_12_2",title:"2.11 Involvement of conductivity σ",level:"2"},{id:"sec_14",title:"3. Extraordinary microwave effect",level:"1"},{id:"sec_14_2",title:"3.1 Classification of microwave effects",level:"2"},{id:"sec_15_2",title:"3.2 Real and imaginary parts",level:"2"},{id:"sec_16_2",title:"3.3 Interpretation of the Arrhenius equations",level:"2"},{id:"sec_17_2",title:"3.4 Introduction of a nonthermal constant",level:"2"},{id:"sec_18_2",title:"3.5 Working principle of a nonthermal constant",level:"2"},{id:"sec_20",title:"4. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Ritter SK. Microwave chemistry remains hot, fast, and a tad mystical. Chemical & Engineering News. 2014;92(4):26-28'},{id:"B2",body:'Kappe A, Pieber B, Dallinger D. Effects in organic synthesis: Myth or reality? Angewandte Chemical International Edition. 2013;52:1088-1094. DOI: 10.1002/anie.201204103'},{id:"B3",body:'Rosana MR, Tao Y, Stiegman AE, Dudley GB. On the rational design of microwave-actuated organic reactions. Chemical Science. 2012;3:1240-1244. DOI: 10.1039/c2sc01003h'},{id:"B4",body:'Dudley GB, Stiegman AE, Rosana MR. Correspondence on microwave effects in organic synthesis. Angewandte Chemie, International Edition. 2013;52:7918-7923. DOI: 10.1002/anie.201301539'},{id:"B5",body:'Kappe CO. Reply to the correspondence on microwave effects in organic synthesis. Angewandte Chemie, International Edition. 2013;52:7924-7928. DOI: 10.1002/anie.201304368'},{id:"B6",body:'Nushiro K, Kikuchi S, Yamada T. Microwave effect on catalytic enantioselective Claisen rearrangement. Chemical Communications. 2013;49:8371-8373. DOI: 10.1039/c3cc44610g'},{id:"B7",body:'Sugiyama J. Heating principle of microwave from a viewpoint of the mathematical formula. In: Proceedings of the 4th JEMEA Symposium. Fukuoka. Tokyo: JEMEA; 2010. pp. 26-27'},{id:"B8",body:'The International System of Units. 9th ed. The International Bureau of Weights and Measures; 2019 ISBN 978-92-822-2272-0'},{id:"B9",body:'Sugiyama J. Change of complex permittivity and electromagnetic field accompanying with temperature rising. In: Proceedings of the JEMEA Safety/technology Seminar. Fukuoka. Tokyo: JEMEA; 2010. pp. 40-50'},{id:"B10",body:'Sugiyama J, Morizumi M, Sato C. Separation of conductivity sigma and permittivity epsilon in electrolyte solution. IEICE Technical Report. 2014;MW2014:1-6'},{id:"B11",body:'Sugiyama J. Development of the resonator to measure a complex permittivity at the wide temperature. IEICE Technical Report. 2009;MW2009-79:31-36'},{id:"B12",body:'Sugiyama J. Evaluation of the phase displacement delta by the complex permittivity measuring with resonators. IEICE Technical Report. 2010;MW2009:11-16'},{id:"B13",body:'Sugiyama J. Calculation of the relaxation time tau by resonators and thermal behavior in heating device. IEICE Technical Report. 2010;MW2010:13-18'},{id:"B14",body:'Sugiyama J. What is the microwave heating from a viewpoint of a material? JEMEA-Bulletin. 2017;3(1):15-18'},{id:"B15",body:'Sugiyama J. Heating principle of microwave from a viewpoint of the mathematical formula. In: Proceedings of the 7th JEMEA Symposium. Fukuoka. Tokyo: JEMEA; 2013. pp. 148-149'},{id:"B16",body:'Sugiyama J. Microwave heating from the viewpoint of materials. In: Proceedings of the 1st JEMEA Summer School. Takayama. Tokyo: JEMEA; 2016. pp. 35-80'},{id:"B17",body:'Sugiyama J. Microwave Course I, II, III. In: Proceedings of the 13th JEMEA Symposium. Tsukuba. Tokyo: JEMEA; 2019. p. 28'},{id:"B18",body:'Gabriel C, Gabriel S, Grant EH, Halstead BSJ, Mingos DMP. Dielectric parameters relevant to microwave dielectric heating. Chemical Society Reviews. 1998;27(3):213-223. DOI: 10.1039/a827213z'},{id:"B19",body:'Sugiyama J, Morizumi M, Sato C. Frequency dependence of the dielectric-relaxation of single liquid. In: Proceedings of the 7th JEMEA Symposium. Tokyo: JEMEA; 2013. pp. 188-189'},{id:"B20",body:'Sugiyama J, Morizumi M, Sato C. Frequency dependence of the dielectric-relaxation of blended liquid. In: Proceedings of the 7th JEMEA Symposium. Tokyo: JEMEA; 2013. pp. 190-191'},{id:"B21",body:'Sugiyama J, Sato C. Heating of small amount solution by a solid oscillator. In: Proceedings of the 10th JEMEA Symposium. Tokyo: JEMEA; 2016. pp. 160-161'},{id:"B22",body:'Sugiyama H, Sugiyama J, Sato C. Study of characteristic correlation for dielectric liquid mixture. In: Proceedings of the 13th JEMEA Symposium. Tokyo: JEMEA; 2019. pp. 162-163'},{id:"B23",body:'Sugiyama J, Morizumi M, Sato C. Mathematical analysis of the empirical relationship of the dielectric-relaxation. In: Proceedings of the 8th JEMEA Symposium. Kochi, Tokyo: JEMEA; 2014. pp. 74-75'},{id:"B24",body:'Miyamoto S, Sugiyama J. Microwave characteristics measurement of the liquid which has electrical conductivity sigma. IEICE Technical Report. 2011;MW2011:13-18'},{id:"B25",body:'Sugiyama J, Yamazaki T, Moriike T, Suzuki M, Segawa T, Kato Y, et al. Prototyping of large-scale circular microwave oven and its actual heating efficiency at complete evaporation of water. IEICE Technical Report. 2011;MW2010:51-56'},{id:"B26",body:'Nagashima I, Sugiyama J, Sakuta T, Sasaki M, Shimizu H. Efficiency of 2.45 and 5.80 GHz microwave irradiation for a hydrolysis reaction by thermostable β-glucosidase HT1. Bioscience, Biotechnology, and Biochemistry. 2014;78(5):758-760. DOI: 10.1080/09168451.2014.891931'},{id:"B27",body:'Sugiyama J, Morizumi M, Sato C. Evaluation of the real and imaginary part of complex conductivity. In: Proceedings of the 8th JEMEA Symposium. Kochi, Tokyo: JEMEA; 2014. pp. 198-199'},{id:"B28",body:'Sugiyama J. Proposition of theory on the quantitativity of non-thermal effects. In: Proceedings of the 13th JEMEA Symposium. Tsukuba, Tokyo: JEMEA; 2019. pp. 41-42'},{id:"B29",body:'Sugiyama J, Yoneya M. Simulation of molecular motion in the application of alternating electromagnetic fields in the microwave band. Computation of Chemical Japan. 2021;20(3):123-125. DOI: 10.2477/jccj.2021-0035'},{id:"B30",body:'Sugiyama J. Electromagnetic relationship between microwaves and flow reactor systems. Chemical Record. 2019;19:146-156. DOI: 10.1002/tcr.201800120'},{id:"B31",body:'Wada D, Sugiyama J, Zushi H, Murayama H. An optical fiber sensing technique for temperature distribution measurements in microwave heating. Measurement Science and Technology. 2015;26(085105):1-7. DOI: 10.1088/0957-0233/26/8/085105'},{id:"B32",body:'Wada D, Sugiyama J, Zushi H, Murayama H. Temperature distribution monitoring of a coiled flow channel in microwave heating using an optical fiber sensing technique. Sensors and Actuators B: Chemical. 2016;232:434-441. DOI: 10.1016/j.snb.2016.03.156'},{id:"B33",body:'Wada Y, Tsubaki S, Maitani MM, Fujii S, Kishimoto F, Haneishi N. Physical insight to microwave special effects: Nonequilibrium local heating and acceleration of Electron transfer. Journal of the Japan Petroleum Institute. 2018;61(2):98-105. DOI: 10.1627/jpi.61.98'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Sugiyama Jun-ichi",address:"sugiyama-j@aist.go.jp",affiliation:'
National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan
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However, some of these heavy metals in high doses can be harmful to the body while others such as cadmium, mercury, lead, chromium, silver, and arsenic in minute quantities have delirious effects in the body causing acute and chronic toxicities in humans. The focus of this chapter is to describe the various mechanism of intoxication of some selected heavy metals in humans along with their health effects. Therefore it aims to highlight on biochemical mechanisms of heavy metal intoxication which involves binding to proteins and enzymes, altering their activity and causing damage. More so, the mechanism by which heavy metals cause neurotoxicity, generate free radical which promotes oxidative stress damaging lipids, proteins and DNA molecules and how these free radicals propagate carcinogenesis are discussed. Alongside these mechanisms, the noxious health effects of these heavy metals are discussed.",book:{id:"7111",slug:"poisoning-in-the-modern-world-new-tricks-for-an-old-dog-",title:"Poisoning in the Modern World",fullTitle:"Poisoning in the Modern World - New Tricks for an Old Dog?"},signatures:"Godwill Azeh Engwa, Paschaline Udoka Ferdinand, Friday Nweke Nwalo and Marian N. Unachukwu",authors:[{id:"241837",title:"Mr.",name:"Godwill Azeh",middleName:null,surname:"Engwa",slug:"godwill-azeh-engwa",fullName:"Godwill Azeh Engwa"},{id:"274194",title:"BSc.",name:"Paschaline Ferdinand",middleName:null,surname:"Okeke",slug:"paschaline-ferdinand-okeke",fullName:"Paschaline Ferdinand Okeke"},{id:"286975",title:"Dr.",name:"Friday",middleName:null,surname:"Nweke Nwalo",slug:"friday-nweke-nwalo",fullName:"Friday Nweke Nwalo"},{id:"286976",title:"Dr.",name:"Marian",middleName:null,surname:"Unachukwu",slug:"marian-unachukwu",fullName:"Marian Unachukwu"}]},{id:"57717",doi:"10.5772/intechopen.71923",title:"In Vitro Cytotoxicity and Cell Viability Assays: Principles, Advantages, and Disadvantages",slug:"in-vitro-cytotoxicity-and-cell-viability-assays-principles-advantages-and-disadvantages",totalDownloads:14818,totalCrossrefCites:78,totalDimensionsCites:157,abstract:"Cytotoxicity is one of the most important indicators for biological evaluation in vitro studies. In vitro, chemicals such as drugs and pesticides have different cytotoxicity mechanisms such as destruction of cell membranes, prevention of protein synthesis, irreversible binding to receptors etc. In order to determine the cell death caused by these damages, there is a need for cheap, reliable and reproducible short-term cytotoxicity and cell viability assays. Cytotoxicity and cell viability assays are based on various cell functions. A broad spectrum of cytotoxicity assays is currently used in the fields of toxicology and pharmacology. There are different classifications for these assays: (i) dye exclusion assays; (ii) colorimetric assays; (iii) fluorometric assays; and (iv) luminometric assays. Choosing the appropriate method among these assays is important for obtaining accurate and reliable results. When selecting the cytotoxicity and cell viability assays to be used in the study, different parameters have to be considered such as the availability in the laboratory where the study is to be performed, test compounds, detection mechanism, specificity, and sensitivity. In this chapter, information will be given about in vitro cytotoxicity and viability assays, these assays will be classified and their advantages and disadvantages will be emphasized. The aim of this chapter is to guide the researcher interested in this subject to select the appropriate assay for their study.",book:{id:"6310",slug:"genotoxicity-a-predictable-risk-to-our-actual-world",title:"Genotoxicity",fullTitle:"Genotoxicity - A Predictable Risk to Our Actual World"},signatures:"Özlem Sultan Aslantürk",authors:[{id:"211212",title:"Dr.",name:"Özlem Sultan",middleName:null,surname:"Aslantürk",slug:"ozlem-sultan-aslanturk",fullName:"Özlem Sultan Aslantürk"}]},{id:"66259",doi:"10.5772/intechopen.85270",title:"Antioxidant Compounds and Their Antioxidant Mechanism",slug:"antioxidant-compounds-and-their-antioxidant-mechanism",totalDownloads:7594,totalCrossrefCites:58,totalDimensionsCites:152,abstract:"An antioxidant is a substance that at low concentrations delays or prevents oxidation of a substrate. Antioxidant compounds act through several chemical mechanisms: hydrogen atom transfer (HAT), single electron transfer (SET), and the ability to chelate transition metals. The importance of antioxidant mechanisms is to understand the biological meaning of antioxidants, their possible uses, their production by organic synthesis or biotechnological methods, or for the standardization of the determination of antioxidant activity. In general, antioxidant molecules can react either by multiple mechanisms or by a predominant mechanism. The chemical structure of the antioxidant substance allows understanding of the antioxidant reaction mechanism. This chapter reviews the in vitro antioxidant reaction mechanisms of organic compounds polyphenols, carotenoids, and vitamins C against free radicals (FR) and prooxidant compounds under diverse conditions, as well as the most commonly used methods to evaluate the antioxidant activity of these compounds according to the mechanism involved in the reaction with free radicals and the methods of in vitro antioxidant evaluation that are used frequently depending on the reaction mechanism of the antioxidant.",book:{id:"8008",slug:"antioxidants",title:"Antioxidants",fullTitle:"Antioxidants"},signatures:"Norma Francenia Santos-Sánchez, Raúl Salas-Coronado, Claudia Villanueva-Cañongo and Beatriz Hernández-Carlos",authors:[{id:"143354",title:"Dr.",name:"Raúl",middleName:null,surname:"Salas-Coronado",slug:"raul-salas-coronado",fullName:"Raúl Salas-Coronado"},{id:"148546",title:"Dr.",name:"Norma Francenia",middleName:null,surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez"},{id:"193718",title:"Dr.",name:"Beatriz",middleName:null,surname:"Hernández-Carlos",slug:"beatriz-hernandez-carlos",fullName:"Beatriz Hernández-Carlos"},{id:"278133",title:"Dr.",name:"Claudia",middleName:null,surname:"Villanueva-Cañongo",slug:"claudia-villanueva-canongo",fullName:"Claudia Villanueva-Cañongo"}]},{id:"40253",doi:"10.5772/50486",title:"Lipid Nanoparticulate Drug Delivery Systems: A Revolution in Dosage Form Design and Development",slug:"lipid-nanoparticulate-drug-delivery-systems-a-revolution-in-dosage-form-design-and-development",totalDownloads:11293,totalCrossrefCites:22,totalDimensionsCites:105,abstract:null,book:{id:"2509",slug:"recent-advances-in-novel-drug-carrier-systems",title:"Recent Advances in Novel Drug Carrier Systems",fullTitle:"Recent Advances in Novel Drug Carrier Systems"},signatures:"Anthony A. 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Among these heavy metals, a few have direct or indirect impact on the human body. Some of these heavy metals such as copper, cobalt, iron, nickel, magnesium, molybdenum, chromium, selenium, manganese and zinc have functional roles which are essential for various diverse physiological and biochemical activities in the body. However, some of these heavy metals in high doses can be harmful to the body while others such as cadmium, mercury, lead, chromium, silver, and arsenic in minute quantities have delirious effects in the body causing acute and chronic toxicities in humans. The focus of this chapter is to describe the various mechanism of intoxication of some selected heavy metals in humans along with their health effects. Therefore it aims to highlight on biochemical mechanisms of heavy metal intoxication which involves binding to proteins and enzymes, altering their activity and causing damage. More so, the mechanism by which heavy metals cause neurotoxicity, generate free radical which promotes oxidative stress damaging lipids, proteins and DNA molecules and how these free radicals propagate carcinogenesis are discussed. Alongside these mechanisms, the noxious health effects of these heavy metals are discussed.",book:{id:"7111",slug:"poisoning-in-the-modern-world-new-tricks-for-an-old-dog-",title:"Poisoning in the Modern World",fullTitle:"Poisoning in the Modern World - New Tricks for an Old Dog?"},signatures:"Godwill Azeh Engwa, Paschaline Udoka Ferdinand, Friday Nweke Nwalo and Marian N. Unachukwu",authors:[{id:"241837",title:"Mr.",name:"Godwill Azeh",middleName:null,surname:"Engwa",slug:"godwill-azeh-engwa",fullName:"Godwill Azeh Engwa"},{id:"274194",title:"BSc.",name:"Paschaline Ferdinand",middleName:null,surname:"Okeke",slug:"paschaline-ferdinand-okeke",fullName:"Paschaline Ferdinand Okeke"},{id:"286975",title:"Dr.",name:"Friday",middleName:null,surname:"Nweke Nwalo",slug:"friday-nweke-nwalo",fullName:"Friday Nweke Nwalo"},{id:"286976",title:"Dr.",name:"Marian",middleName:null,surname:"Unachukwu",slug:"marian-unachukwu",fullName:"Marian Unachukwu"}]},{id:"49459",title:"Pharmacokinetics of Drugs Following IV Bolus, IV Infusion, and Oral Administration",slug:"pharmacokinetics-of-drugs-following-iv-bolus-iv-infusion-and-oral-administration",totalDownloads:15480,totalCrossrefCites:16,totalDimensionsCites:24,abstract:null,book:{id:"4491",slug:"basic-pharmacokinetic-concepts-and-some-clinical-applications",title:"Basic Pharmacokinetic Concepts and Some Clinical Applications",fullTitle:"Basic Pharmacokinetic Concepts and Some Clinical Applications"},signatures:"Tarek A. Ahmed",authors:[{id:"175649",title:"Dr.",name:"Tarek A",middleName:null,surname:"Ahmed",slug:"tarek-a-ahmed",fullName:"Tarek A Ahmed"}]},{id:"29240",title:"Oral Absorption, Intestinal Metabolism and Human Oral Bioavailability",slug:"oral-absorption-intestinal-metabolism-and-human-oral-bioavailability-",totalDownloads:27175,totalCrossrefCites:28,totalDimensionsCites:58,abstract:null,book:{id:"672",slug:"topics-on-drug-metabolism",title:"Topics on Drug Metabolism",fullTitle:"Topics on Drug Metabolism"},signatures:"Ayman El-Kattan and Manthena Varma",authors:[{id:"85539",title:"Dr.",name:"Ayman",middleName:null,surname:"El-Kattan",slug:"ayman-el-kattan",fullName:"Ayman El-Kattan"},{id:"88221",title:"Dr.",name:"Manthena",middleName:null,surname:"Varma",slug:"manthena-varma",fullName:"Manthena Varma"}]},{id:"66259",title:"Antioxidant Compounds and Their Antioxidant Mechanism",slug:"antioxidant-compounds-and-their-antioxidant-mechanism",totalDownloads:7587,totalCrossrefCites:58,totalDimensionsCites:152,abstract:"An antioxidant is a substance that at low concentrations delays or prevents oxidation of a substrate. Antioxidant compounds act through several chemical mechanisms: hydrogen atom transfer (HAT), single electron transfer (SET), and the ability to chelate transition metals. The importance of antioxidant mechanisms is to understand the biological meaning of antioxidants, their possible uses, their production by organic synthesis or biotechnological methods, or for the standardization of the determination of antioxidant activity. In general, antioxidant molecules can react either by multiple mechanisms or by a predominant mechanism. The chemical structure of the antioxidant substance allows understanding of the antioxidant reaction mechanism. This chapter reviews the in vitro antioxidant reaction mechanisms of organic compounds polyphenols, carotenoids, and vitamins C against free radicals (FR) and prooxidant compounds under diverse conditions, as well as the most commonly used methods to evaluate the antioxidant activity of these compounds according to the mechanism involved in the reaction with free radicals and the methods of in vitro antioxidant evaluation that are used frequently depending on the reaction mechanism of the antioxidant.",book:{id:"8008",slug:"antioxidants",title:"Antioxidants",fullTitle:"Antioxidants"},signatures:"Norma Francenia Santos-Sánchez, Raúl Salas-Coronado, Claudia Villanueva-Cañongo and Beatriz Hernández-Carlos",authors:[{id:"143354",title:"Dr.",name:"Raúl",middleName:null,surname:"Salas-Coronado",slug:"raul-salas-coronado",fullName:"Raúl Salas-Coronado"},{id:"148546",title:"Dr.",name:"Norma Francenia",middleName:null,surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez"},{id:"193718",title:"Dr.",name:"Beatriz",middleName:null,surname:"Hernández-Carlos",slug:"beatriz-hernandez-carlos",fullName:"Beatriz Hernández-Carlos"},{id:"278133",title:"Dr.",name:"Claudia",middleName:null,surname:"Villanueva-Cañongo",slug:"claudia-villanueva-canongo",fullName:"Claudia Villanueva-Cañongo"}]},{id:"66742",title:"Introductory Chapter: Alkaloids - Their Importance in Nature and for Human Life",slug:"introductory-chapter-alkaloids-their-importance-in-nature-and-for-human-life",totalDownloads:4130,totalCrossrefCites:16,totalDimensionsCites:32,abstract:null,book:{id:"6828",slug:"alkaloids-their-importance-in-nature-and-human-life",title:"Alkaloids",fullTitle:"Alkaloids - Their Importance in Nature and Human Life"},signatures:"Joanna Kurek",authors:[{id:"214632",title:"Dr.",name:"Joanna",middleName:null,surname:"Kurek",slug:"joanna-kurek",fullName:"Joanna Kurek"}]}],onlineFirstChaptersFilter:{topicId:"19",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"83076",title:"Treatments for the Infection by SARS-CoV-2",slug:"treatments-for-the-infection-by-sars-cov-2",totalDownloads:4,totalDimensionsCites:0,doi:"10.5772/intechopen.106232",abstract:"In late 2019, pneumonia cases from unknown origin were detected in Wuhan, China. The cause was a new coronavirus. The World Health Organization (WHO) named the virus SARS-CoV-2 and COVID-19 the associated disease. In the first months of 2020, this disease became a pandemic with a high lethality reported. Since then, the search for treatments began. We started by searching among treatments previously approved for human use that were not designed for COVID-19 and were considered to treat this condition. We continued searching on the therapeutics guidelines published by the WHO for the management of infection by SARS-CoV-2. Based on these results, we searched for the literature in PubMed to obtain further evidence on the drugs against SARS-CoV-2. The treatments presented in this chapter are Ivermectin, Hydroxychloroquine, Nitazoxanide, Azithromycin, Molnupiravir, Casirivimab-Imdevimab, Ritonavir-Nirmatrelvir, Ritonavir-Lopinavir, Remdesivir, and Favipiravir. Two years ahead of the start of the COVID-19 pandemic, a plenty of options for treatment have been investigated. Only a few of them have been shown to be efficient and safe. According to the WHO, Ritonavir-Nirmatrelvir outperforms other proposed therapeutics.",book:{id:"11690",title:"COVID-19 Drug Development - Recent Advances, New Perspectives, and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/11690.jpg"},signatures:"Nicolás Padilla-Raygoza, Gilberto Flores-Vargas, María de Jesús Gallardo-Luna, Efraín Navarro-Olivos, Francisco Javier Magos-Vázquez and Daniel Alberto Díaz-Martínez"},{id:"83054",title:"Pulsatory Liposome: A Possible Biotechnological Device",slug:"pulsatory-liposome-a-possible-biotechnological-device",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.106347",abstract:"A unilamellar liposome filled with an osmotic solution is introduced into a hypotonic aqueous environment. Because of the mechanical tension induced by the osmotic flow, the vesicle swells up to a critical size, when suddenly a transbilayer pore appears and the vesicle relaxing stage starts. A part of the intracellular material leaks out through this pore, and the liposome membrane relaxes and finally recovers. The swelling begins again and the liposome experiences a periodical process. For this reason, we have named it a pulsatory liposome. The swelling of the liposome is described by a differential equation. All the processes which contribute to the vesicle relaxing and its coming back to the initial size are described by three differential equations. The pulsatory liposome can be programmed to work a number of cycles, established before. The activity of a pulsatory liposome can be characterized by the following parameters: (a) number of cycles, the length time of each cycle, and liposome activity life; (b) the length time of the swelling stage and the relaxation stage for each cycle; (c) the amount of solute leaked out through the pore in each cycle. The pulsatory liposome may be regarded as a two-stroke engine.",book:{id:"11814",title:"Liposomes - Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/11814.jpg"},signatures:"Dumitru Popescu and Alin Gabriel Popescu"},{id:"82962",title:"Pluralism Medical Treatment, Prevention, and Control of COVID-19 Infection and Its Long-Sufferings among the Older Adults in the Northeast of Thailand from 2019 to 2022",slug:"pluralism-medical-treatment-prevention-and-control-of-covid-19-infection-and-its-long-sufferings-amo",totalDownloads:49,totalDimensionsCites:0,doi:"10.5772/intechopen.106339",abstract:"COVID-19 in 2019 has brought both changes and challenges to the world. This global pandemic has an impact on people of all age levels, especially older adults. In Thailand, older persons are at high risk of COVID-19 infection. They are included in the so-called 608 groups. The objective of this review article was to synthesize and present medical pluralism, the development of drugs from herbs, and projects conducted to treat, prevent, and control the infection and long sufferings of COVID-19. The review covers 10 studies, three projects produced at Mahasarakham University, Chaiyaphum Rajabhat University, and Khon Kaen University that were reviewed, synthesized, and analyzed. The results of the synthesis indicate that modern and Thai traditional medicine can help reduce the severity of the infection and long sufferings of COVID-19. The medical pluralism between modern and Thai traditional medicine is needed to remedy COVID-19 cases among the older adults in the Northeast of Thailand.",book:{id:"11690",title:"COVID-19 Drug Development - Recent Advances, New Perspectives, and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/11690.jpg"},signatures:"Pissamai Homchampa, Khemika Napattaradechanon, Parichat Yatniyom, Thawalrat Ratanasiri, Piyaporn Sansila, Thanawan Sirisuk, Thawalwong Ratanasiri and Amornrat Ratanasiri"},{id:"82353",title:"Pharmacovigilance of Biological Drugs",slug:"pharmacovigilance-of-biological-drugs",totalDownloads:7,totalDimensionsCites:0,doi:"10.5772/intechopen.105520",abstract:"The use of biological drugs has significantly increased over the past decades and has allowed for the treatment of many life-threatening and chronic diseases. The patent expiration of biological innovative medicines enables copies of these drugs called biosimilars. The availability of biosimilars enhances competition, with the potential to improve patient access to biological medications and contribute to the financial sustainability of the healthcare systems. Unlike equivalent drugs, biosimilars are not identical but similar to their innovator products because of the differences in the manufacturing process, which is a biological process. However, they are considered comparable to their originators in safety, quality characteristics, biological activity, and efficacy. The regulatory procedures used for generic drugs cannot be applied for biosimilars, so they are subjected to rigorous characterization as well as comparative clinical studies. Since they are highly complex molecules produced from living cells, even small change in the production process can have major implications on their safety and effectiveness profile, causing a potential risk of immune-based adverse reactions. For all these reasons, for biological drugs, a robust long-term pharmacovigilance system is necessary. It is desirable that in the future, there are further guidance and resolution of the ongoing discussions on biosimilar labeling, naming, pharmacovigilance and interchangeability/substitution, to ensure the appropriate use of these drugs in clinical practice.",book:{id:"11679",title:"Pharmacovigilance and Regulations",coverURL:"https://cdn.intechopen.com/books/images_new/11679.jpg"},signatures:"Simona Guerzoni, Flavia Lo Castro, Carlo Baraldi, Giuliana Colella and Luca Pani"},{id:"82868",title:"Recent Strategies for Ocular Drug Delivery: Promises and Challenges",slug:"recent-strategies-for-ocular-drug-delivery-promises-and-challenges",totalDownloads:9,totalDimensionsCites:0,doi:"10.5772/intechopen.106335",abstract:"Ocular diseases include various anterior and posterior segment diseases. Due to the unique anatomy and physiology of the eye, efficient ocular drug delivery is a great challenge to researchers. The emerging nanoscience is playing an important role in the development of novel strategies for ocular disease management. Various active molecules have been designed to associate with nanocarriers to overcome ocular barriers and interact with certain ocular tissues. In this chapter, highlights will be made on barrier to intraocular delivery, general pathways for ocular absorption, and factors affecting intraocular bioavailability. The recent attempts of nanotechnology for treating anterior and posterior ocular diseases will be explored. This will include nanomicelles, nanoparticles, nanosuspensions, vesicular systems, in situ gel, dendrimers, contact lenses, implants, microneedles, and cell-based delivery systems. In addition, gene-based ocular delivery systems will be discussed. 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Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. 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She is a member of the Coordination and Scientific Committees of the doctoral program “Tropical Knowledge and Management” (NOVA), Master in Biotechnology (UEM), and Master in Conservation Biology (GNP); and a national expert for Food and Nutrition Security and Sustainable Agriculture - High-Level Policy Dialogue EU-Africa. 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He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. 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Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"426586",title:"Dr.",name:"Oladunni A.",middleName:null,surname:"Daramola",slug:"oladunni-a.-daramola",fullName:"Oladunni A. Daramola",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Federal University of Technology",country:{name:"Nigeria"}}},{id:"357014",title:"Prof.",name:"Leon",middleName:null,surname:"Bobrowski",slug:"leon-bobrowski",fullName:"Leon Bobrowski",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Bialystok University of Technology",country:{name:"Poland"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"354126",title:"Dr.",name:"Setiawan",middleName:null,surname:"Hadi",slug:"setiawan-hadi",fullName:"Setiawan Hadi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Padjadjaran University",country:{name:"Indonesia"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"332603",title:"Prof.",name:"Kumar S.",middleName:null,surname:"Ray",slug:"kumar-s.-ray",fullName:"Kumar S. Ray",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Statistical Institute",country:{name:"India"}}},{id:"415409",title:"Prof.",name:"Maghsoud",middleName:null,surname:"Amiri",slug:"maghsoud-amiri",fullName:"Maghsoud Amiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Allameh Tabataba'i University",country:{name:"Iran"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}}]}},subseries:{item:{id:"3",type:"subseries",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11399,editor:{id:"205604",title:"Dr.",name:"Tomas",middleName:null,surname:"Jarzembowski",slug:"tomas-jarzembowski",fullName:"Tomas Jarzembowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKriQAG/Profile_Picture_2022-06-16T11:01:31.jpg",biography:"Tomasz Jarzembowski was born in 1968 in Gdansk, Poland. He obtained his Ph.D. degree in 2000 from the Medical University of Gdańsk (UG). After specialization in clinical microbiology in 2003, he started studying biofilm formation and antibiotic resistance at the single-cell level. In 2015, he obtained his D.Sc. degree. His later study in cooperation with experts in nephrology and immunology resulted in the designation of the new diagnostic method of UTI, patented in 2017. He is currently working at the Department of Microbiology, Medical University of Gdańsk (GUMed), Poland. Since many years, he is a member of steering committee of Gdańsk branch of Polish Society of Microbiologists, a member of ESCMID. He is also a reviewer and a member of editorial boards of a number of international journals.",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorTwo:{id:"484980",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Garbacz",slug:"katarzyna-garbacz",fullName:"Katarzyna Garbacz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003St8TAQAZ/Profile_Picture_2022-07-07T09:45:16.jpg",biography:"Katarzyna Maria Garbacz, MD, is an Associate Professor at the Medical University of Gdańsk, Poland and she is head of the Department of Oral Microbiology of the Medical University of Gdańsk. She has published more than 50 scientific publications in peer-reviewed journals. She has been a project leader funded by the National Science Centre of Poland. Prof. Garbacz is a microbiologist working on applied and fundamental questions in microbial epidemiology and pathogenesis. Her research interest is in antibiotic resistance, host-pathogen interaction, and therapeutics development for staphylococcal pathogens, mainly Staphylococcus aureus, which causes hospital-acquired infections. Currently, her research is mostly focused on the study of oral pathogens, particularly Staphylococcus spp.",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorThree:null,series:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188"},editorialBoard:[{id:"190041",title:"Dr.",name:"Jose",middleName:null,surname:"Gutierrez Fernandez",slug:"jose-gutierrez-fernandez",fullName:"Jose Gutierrez Fernandez",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"University of Granada",institutionURL:null,country:{name:"Spain"}}},{id:"156556",title:"Prof.",name:"Maria Teresa",middleName:null,surname:"Mascellino",slug:"maria-teresa-mascellino",fullName:"Maria Teresa Mascellino",profilePictureURL:"https://mts.intechopen.com/storage/users/156556/images/system/156556.jpg",institutionString:"Sapienza University",institution:{name:"Sapienza University of Rome",institutionURL:null,country:{name:"Italy"}}},{id:"164933",title:"Prof.",name:"Mónica Alexandra",middleName:null,surname:"Sousa Oleastro",slug:"monica-alexandra-sousa-oleastro",fullName:"Mónica Alexandra Sousa Oleastro",profilePictureURL:"https://mts.intechopen.com/storage/users/164933/images/system/164933.jpeg",institutionString:"National Institute of Health Dr Ricardo Jorge",institution:{name:"National Institute of Health Dr. Ricardo Jorge",institutionURL:null,country:{name:"Portugal"}}}]},onlineFirstChapters:{paginationCount:2,paginationItems:[{id:"82936",title:"Soil Degradation Processes Linked to Long-Term Forest-Type Damage",doi:"10.5772/intechopen.106390",signatures:"Pavel Samec, Aleš Kučera and Gabriela Tomášová",slug:"soil-degradation-processes-linked-to-long-term-forest-type-damage",totalDownloads:3,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Forest Degradation Under Global Change",coverURL:"https://cdn.intechopen.com/books/images_new/11457.jpg",subseries:{id:"94",title:"Climate Change and Environmental Sustainability"}}},{id:"82124",title:"Assessment of Diversity, Growth Characteristics and Aboveground Biomass of Tree Species in Selected Urban Green Areas of Osogbo, Osun State",doi:"10.5772/intechopen.104982",signatures:"Omolara Aremu, Olusola O. Adetoro and Olusegun Awotoye",slug:"assessment-of-diversity-growth-characteristics-and-aboveground-biomass-of-tree-species-in-selected-u",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Forest Degradation Under Global Change",coverURL:"https://cdn.intechopen.com/books/images_new/11457.jpg",subseries:{id:"94",title:"Climate Change and Environmental Sustainability"}}}]},publishedBooks:{paginationCount:2,paginationItems:[{type:"book",id:"9525",title:"Insights Into Drug Resistance in Staphylococcus aureus",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/9525.jpg",slug:"insights-into-drug-resistance-in-staphylococcus-aureus",publishedDate:"December 8th 2021",editedByType:"Edited by",bookSignature:"Amjad Aqib",hash:"98bb6c1ddb067da67185c272f81c0a27",volumeInSeries:10,fullTitle:"Insights Into Drug Resistance in Staphylococcus 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\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
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The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment"},{id:"5",title:"Parasitic Infectious Diseases",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. Therefore, it is important to conduct studies that examine parasitic infections in the context of the coronavirus pandemic for the benefit of all communities to help foster more informed decisions for the betterment of human and animal health.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/5.jpg",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology"},{id:"6",title:"Viral Infectious Diseases",scope:"The Viral Infectious Diseases Book Series aims to provide a comprehensive overview of recent research trends and discoveries in various viral infectious diseases emerging around the globe. The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",keywords:"Novel Viruses, Virus Transmission, Virus Evolution, Molecular Virology, Control and Prevention, Virus-host Interaction"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:null,selectedSubseries:null},seriesLanding:{item:null},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"profile.detail",path:"/profiles/14212",hash:"",query:{},params:{id:"14212"},fullPath:"/profiles/14212",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)}()