Functional evaluation of initial population.
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IntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
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\\n\\nLaunching 2021
\\n\\nArtificial Intelligence, ISSN 2633-1403
\\n\\nVeterinary Medicine and Science, ISSN 2632-0517
\\n\\nBiochemistry, ISSN 2632-0983
\\n\\nBiomedical Engineering, ISSN 2631-5343
\\n\\nInfectious Diseases, ISSN 2631-6188
\\n\\nPhysiology (Coming Soon)
\\n\\nDentistry (Coming Soon)
\\n\\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\\n\\nNote: Edited in October 2021
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\n\nDesigned to cover fast-moving research fields in rapidly expanding areas, our Book Series feature a Topic structure allowing us to present the most relevant sub-disciplines. Book Series are headed by Series Editors, and a team of Topic Editors supported by international Editorial Board members. Topics are always open for submissions, with an Annual Volume published each calendar year.
\n\nAfter a robust peer-review process, accepted works are published quickly, thanks to Online First, ensuring research is made available to the scientific community without delay.
\n\nOur innovative Book Series format brings you:
\n\nIntechOpen Book Series will also publish a program of research-driven Thematic Edited Volumes that focus on specific areas and allow for a more in-depth overview of a particular subject.
\n\nIntechOpen Book Series will be launching regularly to offer our authors and editors exciting opportunities to publish their research Open Access. We will begin by relaunching some of our existing Book Series in this innovative book format, and will expand in 2022 into rapidly growing research fields that are driving and advancing society.
\n\nLaunching 2021
\n\nArtificial Intelligence, ISSN 2633-1403
\n\nVeterinary Medicine and Science, ISSN 2632-0517
\n\nBiochemistry, ISSN 2632-0983
\n\nBiomedical Engineering, ISSN 2631-5343
\n\nInfectious Diseases, ISSN 2631-6188
\n\nPhysiology (Coming Soon)
\n\nDentistry (Coming Soon)
\n\nWe invite you to explore our IntechOpen Book Series, find the right publishing program for you and reach your desired audience in record time.
\n\nNote: Edited in October 2021
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"644",leadTitle:null,fullTitle:"Chlamydia",title:"Chlamydia",subtitle:null,reviewType:"peer-reviewed",abstract:"Nowadays, Chlamydia still represents a redoubtable pathogen. Among its consequences, the blindness in children and severe impairment of reproductive health in adults are the most mutilating. Worldwide, it is estimated that six million of people suffer from post-trachoma blindness and almost 90 million become sexually infected each year. Due to its silent evolution and sexually transmission, the chlamydial infection can occur in anyone. The book “Chlamydia - A Multifaceted Pathogen” contains an updated review of all-important issues concerning the chlamydial infection. It comprises 18 chapters grouped in four major parts dealing with etiology and pathogenicity, clinical aspects, diagnosis and prevention. The new molecular data about the pathogenicity and the exhaustive presentation of clinical findings bring novelty to the book and improve our knowledge about Chlamydia induced diseases.",isbn:null,printIsbn:"978-953-51-0470-4",pdfIsbn:"978-953-51-6952-9",doi:"10.5772/1153",price:139,priceEur:155,priceUsd:179,slug:"chlamydia",numberOfPages:372,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"2630ab6bb67a91d15fff4592599268d3",bookSignature:"Mihai Mares",publishedDate:"March 30th 2012",coverURL:"https://cdn.intechopen.com/books/images_new/644.jpg",numberOfDownloads:48751,numberOfWosCitations:9,numberOfCrossrefCitations:4,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:12,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:25,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 8th 2011",dateEndSecondStepPublish:"April 5th 2011",dateEndThirdStepPublish:"August 10th 2011",dateEndFourthStepPublish:"September 9th 2011",dateEndFifthStepPublish:"January 7th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"88785",title:"Prof.",name:"Mihai",middleName:null,surname:"Mares",slug:"mihai-mares",fullName:"Mihai Mares",profilePictureURL:"https://mts.intechopen.com/storage/users/88785/images/system/88785.jpg",biography:"Dr. Mihai Mareș received his Ph.D. degree in Microbiology at Gr. T. Popa University of Medicine and Pharmacy from Iași-Romania (2005) and had postgraduate training at University VII Denis-Diderot, Pasteur Institute, Pitié-Salpêtrière Hospital, École du Val-de-Grâce - Paris (France), Complutense University – Madrid (Spain), Instituto de Salud Global - Barcelona (Spain), Karolinska Institute – Stockholm (Sweden), and Danish Technical University - Lyngby (Denmark). His areas of interest are medical mycology, antimicrobial resistance, mycobacteria, food microbiology, biofilms, microbial induced infertility, and bio-medical applications of plasma discharges and cold plasma activated water. Currently, Dr. Mareș is a Professor of Microbiology and Head of the Antimicrobial Chemotherapy Laboratory at Ion Ionescu de la Brad University – Iași (Romania). Also, he is a member of the EUCAST Antifungal Susceptibility Testing Subcommittee and ESCMID Study Group for Veterinary Microbiology. 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Patil and Prakash Rao",coverURL:"https://cdn.intechopen.com/books/images_new/3547.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"164249",title:"Dr.",name:"Yogesh",middleName:"Bhagwan",surname:"Patil",slug:"yogesh-patil",fullName:"Yogesh Patil"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}}},ofsBook:{item:{type:"book",id:"11867",leadTitle:null,title:"Echocardiography",subtitle:null,reviewType:"peer-reviewed",abstract:"\r\n\tAlthough the diagnosis and overall survival of patients with various cardiac diseases have improved in the last years, there still remains a significant proportion of patients with unfavorable prognoses. The evaluation of these patients necessitates effective imaging techniques in both diagnosis and long-term follow-up. Even though Cardiac Magnetic Resonance imaging is currently the imaging modality of choice for tissue characterization, advanced echocardiography represents a modern alternative. Speckle tracking echocardiography can be used to assess myocardial deformation at both segmental and global levels. Since distinct myocardial pathologies affect deformation differently, information about the underlying tissue can be offered by strain imaging. Echocardiography advances also show promising results in the improvement of diagnostic accuracy, management, and follow-up and a major advantage of echocardiography over other imaging modalities is the ability to use it in real-time, in the cardiac catheterization laboratory, allowing for the performance of imaging immediately before, during, and after interventional procedures. Furthermore, the prevalence of adult congenital heart disease continues to grow due to advances in surgical and diagnostic techniques. Echocardiography has proven to be a useful tool in the diagnosis and follow-up of these patients, both after percutaneous and surgical procedures, and its utility has expanded significantly due to the development of better technology. In addition, stress echocardiography could be useful in the evaluation of several cardiac diseases and should be preferred over other imaging modalities due to the lower cost, wider availability, and radiation-free nature.
\r\n\tThis book intends to provide the reader with a comprehensive overview of the current state-of-the-art novel imaging techniques by focusing on the most important evidence-based developments in this area.
Saliva is a aqueous, transparent and odorless liquid produced and secreted by the major and minor salivary glands, which combined with the gingival crevicular fluid, cellular debris, upper airway secretions and microorganisms of the oral cavity, makes up the total human saliva [1, 2].
The saliva is responsible for maintaining the homeostasis of the oral cavity and its pH normally lies around 6-7, which makes it slightly acidic. Initially, it shows up isotonic, becoming hypotonic as it passes through the network of ducts [3].
The daily average flow of total saliva in healthy people varies between 500 and 1500 mL, and the mean volume of saliva in the oral cavity is approximately 1 mL; however, there is always a great variability in individual rates of salivary flow [3]. This flow provides important information about the health quality not only oral but also systemic [4, 5].
The main constituent of saliva is water, which accounts for 99% of its composition. Solid components, which are characterized by organic and inorganic molecules, are dissolved in the aqueous medium. The salivary composition has significant changes from one individual to another and in the same individual under different circumstances; however, the rate of salivary flow is considered the main factor affecting its composition [6].
Saliva is composed of a number of inorganic ions, including sodium, potassium, chloride, calcium, magnesium, bicarbonate, phosphate, sulfate, thiocyanate and fluoride, which are responsible for osmotic balance, buffering capacity and dental remineralization [7]. Humphrey and Williamson (2001), [3] consider that bicarbonate, phosphate and urea act as pH modulators being responsible for salivary buffering capacity.
The salivary organic components are represented by immunoglobulins, proteins, enzymes, mucins, and nitrogen products such as urea and ammonia. The salivary proteins (amylase, lipase, proteases, nucleases, mucins and gustin) act assisting in the digestive process, with antibacterial properties for hydrolysis of cellular membranes (lactoferrin, lysozyme and lactoperoxidase) besides inhibiting the adherence of microorganisms (immunoglobulins) [7].
The saliva keeps the oral health and creates a proper ecological balance. Among its functions (Figure 1) are the protection and lubrication of oral tissues, acting as a barrier against irritants, with buffering and cleaning action, maintaining the integrity of the teeth and antibacterial activity, besides acting improving the taste and starting the digestive process [8]. The saliva’s lubricity capacity is provided mainly by mucins, they are secreted by the minor salivary glands, having low solubility, high viscosity, high elasticity and strong adhesiveness [6, 9, 10].
Saliva functions
Saliva was used for a long time as a method to monitor the caries risk, being used as biological environment extremely useful as buffering capacity and microbiological evaluation. Today, it is an object of detailed study for the diagnosis of systemic diseases that affect the function of the salivary glands and saliva composition, for example, Sjögren\'s syndrome, alcoholic cirrhosis, cystic fibrosis, sarcoidosis, diabetes mellitus and adrenal cortex diseases [11, 12]).
According to [13], saliva is a valuable source of clinically relevant information, since its many components, besides protecting the oral tissues integrity, act as biomarkers of diseases and systemic conditions of the individual. The qualitative changes in the composition of these biomarkers have been used to identify patients with increased susceptibility to some diseases, identification of sites with active disease, prediction of sites with greater disease activity in the future and / or serving as a tool for monitoring effectiveness of therapies.
There have been significant advances in techniques for detection of biomarkers in the oral cavity in recent years, especially by ELISA for proteins and PCR for RNA and DNA. With these advances in biotechnology, it has become possible to use saliva as a diagnostic mean for different conditions such as caries and periodontal disease, infectious and autoimmune diseases, genetic and psychological disorders, malignancies, legal issues, among others (Figure 2).
Major diseases with possibility of salivary diagnostics.
Caries [14] and periodontal disease [15]) are the most occurring diseases in the oral cavity. Both considered infectious diseases and primarily responsible for tooth loss in adults. In recent years, remarkable achievements have been made in the field of oral microbiology, especially with regard to diagnosis. Techniques have been sought to predict the availability of patients to certain diseases; and this is not different with caries. The counts of bacteria present in saliva associated with other factors, such as diet and systemic conditions, may provide an estimate of the risk of caries in the individual. The increased number of lactobacilli and
The human salivary buffer systems consist of an important natural defense against tooth decay [18]. The saliva’s buffer capacity varies with glandular activity. The bicarbonate raises the pH of saliva and its buffering capacity, especially during stimulation [19]). Thus, the levels of bicarbonate and other important ions showing abnormalities can also suggest a predisposition to dental caries.
There has been an association between periodontal disease and increased levels of aspartate aminotransferase (AST) and alkaline phosphatase (ALP). The salivary AST can be used as a marker for monitoring periodontal disease. In addition, lower uric acid levels and albumin in saliva were associated with periodontitis and diabetes [20]. The development of new devices for periodontal monitoring probably would require less training and fewer resources than current diagnostic tests and may lead to better use by properly trained professionals for simpler and less intensive treatment, and may result in the provision of health care at low cost [21]. For determination of periodontal disease, it would be necessary a large body of research previously focused on fluid gingival biomarkers that provide the local disease status, but represents a technically difficult approach to implement in the clinical area [13, 17].
Currently, it is possible to use saliva tests for evaluating the microbiota associated with periodontal diseases, regardless of the degree of periodontal impairment of the patient. PCR tests can detect DNA of periodontal bacteria in oral fluids, such as
In addition to exercising extremely important functions for the organism’s homeostasis, saliva is currently an important tool for the diagnosis of infectious diseases. Besides the usual microorganisms in oral cavity, saliva may contain viruses and/or bacteria responsible for systemic diseases that can be identified by PCR. Another way to diagnose infectious disease by the salivary examination is through monitoring the presence of antibodies to the organisms [23].
Today, it is possible to identify, for example, the herpes virus associated with Kaposi\'s sarcoma and the presence of bacteria such as
The disease that generates more discussion regarding the use of saliva for diagnostic procedures is undoubtedly the Acquired Immunodeficiency Syndrome (AIDS). Until recently, oral HIV transmission through saliva of infected individuals during dental treatment or as a result of biting or contact stemmed by cough or kiss droplets has been considered less likely than vaginal or rectal transmission [27]. However, concerns about the way of transmission have increased. Studies have shown that these tests based on specific salivary antibodies are equivalent in reliability as compared to those in the serum, therefore being useful in the clinical use and epidemiological studies [28]. In recent years, researchers have shown that salivary tests for detection of antibodies to HIV [29] represents a non-invasive alternative for quantification of antibodies in blood to monitor the effectiveness of antiretroviral therapy and progression of Acquired Immunodeficiency Syndrome [30].
For this class of diseases, the most studied in parameters of salivary diagnostics is the Sjogren\'s syndrome. It is an autoimmune disease characterized by decreased secretion of the salivary and lacrimal glands, associated with endocrine disorders. The sialochemistry (analysis of saliva’s chemical components) offers great value for the diagnosis of this syndrome. Increased immunoglobulin levels, inflammatory mediators, albumin, sodium and chloride and, decreased phosphate level are indicative of Sjögren\'s syndrome. Analysis of proteins in saliva showed increased level of lactoferrin, beta 2 microglobulin, lysozyme C, and cystatin C. However, levels of salivary amylase and carbonic anhydrase showed reduced [31, 32]. Thus, these references of protein chemical analysis associated with detailed history may show effectiveness for an accurate diagnosis.
Salivary changes that may reveal the presence of multiple sclerosis, an inflammatory disease characterized by loss of myelin and scarring caused due to failure in producing cells by the immune system have also sought. However, no significant changes were found except for a reduction in the production of IgA, which is inconclusive to suggest the diagnosis [33].
Sarcoidosis is an autoimmune and inflammatory disease, which affects the lymph nodes, lungs, liver, eyes, skin, or other tissues. Salivary diagnostics has demonstrated a decreased amount of saliva secretion associated with reduced activity of the enzyme alpha-amylase and kallikrein in most patients carrying the disease. However, there was no correlation between the decrease in enzyme activity and the volume of secretion, which complicates the understanding of salivary changes and possible diagnosis [34].
The total salivary flow and its characteristics had already been correlated with xerostomia, symptoms of anxiety, depression, Burning Mouth Syndrome and aphthous stomatitis [35, 36, 37]. The salivary cortisol levels may represent an important biological marker of stress. The salivary cortisol concentration increases after 20 the beginning of a stressful situation, besides increased pH and protein levels. However, there are no indications of changes in concentrations of fluoride under conditions of acute mental stress [38, 39].
The sialochemistry evaluation reveals significant elevation in the levels of phosphate, chloride and potassium in subjects with BSA symptoms, and also differences in expression pattern of salivary proteins of low molecular weight compared to healthy individuals. Levels of phosphate, potassium and chloride are increased in individuals with intense activity of the sympathetic nervous system, something common in situations of emotional stress [40].
The salivary alpha-amylase has its release regulated by the sympathetic autonomic nervous system, and has importance in the psychobiology of stress. The levels of salivary alpha-amylase in humans increase under various conditions of physical and psychological stress before any other clinical signs can be perceived [37, 41, 42]. Therefore, the salivary alpha-amylase may act as effective biomarker which can be used alternatively non-invasive way to evaluate psychological and metabolic stress, or including diseases whose etiology just seems to be related to stress.
Results are controversial and not always enlightening. For aphthous stomatitis significant changes in the levels of TCD4+ and TCD8+ lymphocytes have been associated and abnormal cytokine cascade arising from the oral mucosa. It is known that for aphthous stomatitis there are 41 genes expressed differently and increased activity of lymphocytes T-helper 1 (Th1), responsible for the production of interferon-gamma, interleukin 2 (IL-2) and alpha tumor necrosis factor (TNF-α). The levels of IL-2 are higher in patients with aphthous stomatitis compared with control subjects and may serve as markers in immunodiagnoses [43, 44, 45, 46, 47].
The secretory immunoglobulin A (IgA-s) can be used as the oral mucosa immune status parameter. It acts as a barrier to infectious agents, environmental allergens and carcinogens, as well as it participates in innate protection mechanisms. IgA deficiency is the most common humoral immune defect in humans and causes, in a large proportion, gastrointestinal and respiratory infections [48, 49, 50, 51].
The identification of exogenous genetic material in saliva may have forensic significance, or in cases of sexual assaults. The genetic material shared after a kiss is present and can be detected up to an hour after the kiss [52].
Cystic fribose, an autosomal recessive genetic disease caused by a disturbance in salivary glands secretions. Cystic fibrosis affects the chromosome 7, which is responsible for the production of a protein which will regulate the passage of sodium and chloride throuh cell membranes. The effects of this regulation can be analyzed through saliva. The Sodium and Potassium elements showed higher levels, while the trace elements vanadium, chromium, selenium and arsenic have lower levels in individuals with cystic fibrosis [53].
There is a growing interest worldwide for the saliva analysis through genomics, transcriptomics and proteomics, since this is a non-invasive source of rich genetic information. In the case of saliva, two main aspects of cancer diagnosis must be distinguished - one being the diagnosis of oral cancer (which has direct contact with saliva) and other the cancer diagnoses in other locations. Mouth cancer in advanced stages can usually be detected by inspection of the oral cavity. On the other hand, initial oral carcinomas are not visible and cannot be diagnosed and treated on time. The salivary proteomecan also be used for tumor detection [54].
The study of Streckfus et al. (2000) [55], demonstrated the role of saliva in the diagnosis of breast cancer, in which salivary tests for markers of disease were studied combined with mammography. From the analysis in saliva, the soluble fragment of the oncogene c-erbB-2, a prognostic marker for breast cancer, as well as the antigen for cancer were significantly higher in the saliva and serum of women diagnosed with cancer than that observed in a control group of healthy women and patients with benign tumors group, indicating that the saliva test for this oncogene is sensitive and reliable, and it is potentially useful in the early detection and monitoring of screening for breast cancer [56].
Additionally, the use of saliva test may be important in monitoring the levels of c-erbB-2 in patients undergoing chemotherapy and/or surgery, so that serves as an assessment of therapy effectiveness in question, and may be useful in preservation [57].
Franzmann et al. (2005) [58], evaluated the soluble CD44 in saliva as a potential molecular marker for head and neck cancer and concluded that the test can be effective to detect this cancer at all stages.
In the past, biomarkers were used primarily as prognostic indicators for patients with tumors of the head and neck. More recently, the role of biomarkers has been greatly expanded to cover all aspects of patient care, from early cancer detection to the more accurate tumor staging and even the selection of those patients most likely to benefit from specific therapies to post-treatment tumor surveillance. One of the most promising avenues regarding the early diagnosis of cancer has been the ability to use saliva as a substrate for the evaluation of biomarkers [59].
Recently, Jiang et al. (2005)[60], reported increased content of mitochondrial DNA in saliva of patients with head and neck cancer. Multivariate analysis revealed a significant and independent association of SCC diagnosis of head and neck, age and smoking with increased content of mitochondrial or nuclear DNA. Salivary proteins such as CEA, defensin-1, TNF-alpha, IL-1, 6 and 8 and CD44 showed increase in their detection in patients with oral cancer.
Most of these studies relied on immunological assays of individual gene products 2,137. It is expected that proteomic biomarkers, when combined, increase the sensitivity and specificity of detection of human cancer [61, 62].
Increased levels of salivary defensin-1, CA15-3 cancer antigen, tumor marker proteins, such as c-erbB-2 or CA-125 and antibodies against tumor suppressor protein p53 are promising markers of oral malignant neoplasms and other cancers. In the future, a global proteomic profile of saliva with methods newly developed for proteome analysis is likely to result in other peptide sequences candidates for detection with high sensitivity [62, 54].
When compared to blood, saliva can express more sensitive and specific markers for certain local oral diseases. For example, saliva contains expressed proteins locally different from serum that can be best indicators of the oral disease. There are compelling reasons to use saliva as a diagnostic fluid to monitor the onset and progression of oral cancer. Saliva is the fluid that drains the lesions and there is increased RNA and proteins of oral cancer on it [63].
The forensic dentistry method is efficient for human identification, but is endowed with certain limitations: it suffers distortion from the moment of the bite until the act of expertise, especially when the mark is left on the skin. The salivary DNA emerges as a complement or even to replace the first, since it is a test of excellence [64]. However, the use of saliva in the identification was only feasible after the development of molecular biology techniques applied to forensic dentistry. In forensic uses, the PCR technique is the most used as it drastically increases the chances of DNA analysis, allowing determining the individual’s molecular profile. It was from then that saliva became a great focus on looking for traces, as they provide enough genetic material and excellent qualities for the exam in most cases [65].
The DNA can be degraded depending on the conditions of their preservation. Moisture, excessive heat, pH, enzymes and other are variables for its ideal preservation under the various surfaces that can be found [66].This being the object of several recent studies. In the study by [67], the authors concluded that saliva is able to provide genetic material, even when stored under conditions below those considered optimal.
The human salivary proteome (HSP), using 2D gel electrophoresis coupled to mass spectrometry, is able to identify approximately 100 different salivary proteins [68]. A significant number of spots on a typical 2-DE gel can capture fragments of abundant salivary proteins such as amylases, cystatins and immunoglobulins [69]. For the identification of less abundant salivary proteins, analysis by advanced techniques of mass spectrometry ensures a significant increase in resolution when compared to two-dimensional gel electrophoresis [70]. Generally, a pre fractionation of intact salivary proteins employing high resolution separation techniques is required to achieve a wide coverage of the human salivary proteome [71].
Human saliva stains can be found at crime scenes, alone or mixed with other biological fluids. The most common sites of occurrence are: the surface of objects such as envelopes [72], tissues cigarette butts, cups, sites near bites and often victims of rape [73].
For the salivary diagnosis become routine in clinical practice, it is necessary to know specific salivary biomarkers of disease states or health, besides technology necessary for their detection [74]. The genomics, epigenomics, transcriptomics, proteomics and metabolomics (Figure 3) approaches are currently being used to characterize these diagnostic biomarkers in saliva [75].
Study of omics to identify salivary biomarkers.
Biomarkers of DNA, mRNA, or protein biomarkers can provide useful diagnostic information that can identify the effect of disease or medication on salivary constituents. However, there is still not a complete characterization of the salivary proteome for disease biomarkers. Five hundred salivary proteins have been described, but this number is very small when compared to the more than 4,000 proteins listed for plasma [76].
The analysis of salivary genome and epigenoma allows identification of the presence of invading pathogens, as well as profiles transcription of anomalous genes that reflect genetic pathological processes such as cancer. The salivary genome consists of DNAs representing the individual’s genome and the oral microbiota. The quality and yield of DNA that can be obtained from saliva is relatively good compared to blood and urine, which can be used for genotyping, amplification or sequencing [54], and can be stored for a long time without significant degradation [77].Thus, the salivary DNA is an analyte suitable for diagnosis but limited to reflect the presence or absence of specific genes or alterations in the sequences (mutations) and also cannot provide information about upregulation and downregulation of gene expression.
Regarding the salivary transcriptome, mRNAs and miRNAs are secreted by cells into the extracellular medium and can be found in biofluids remote cellular sources [78, 79, 80]. In the disease state, the transcription of specific miRNAs and mRNAs has changed. Despite suffering some criticism initially, the use of salivary RNAs as diagnostic biomarkers, is now widely accepted [81]. However, the precise sources of salivary RNAs and other molecules remain unclear.
The standard procedures for the isolation and analysis of salivary mRNA require low temperatures, besides being expensive and time consuming, precluding its clinical application. Currently, simple methods of stabilization of mRNA in saliva samples have been developed, allowing for storage at room temperature without the use of stabilizers, and are so-called \'direct-saliva-transcriptomic-analysis\' [82]. However, this approach also involves centrifugation. An alternative method has been described [83], but it was based on the use of an expensive stabilizing agent (expensive). Thus, neither method is completely suitable for all applications. The mRNAs of saliva and plasma can be remarkably stable. The microarray technology is considered the gold standard for the identification of salivary transcripts. In this technique, the salivary transcriptome is determined using microarrays and is validated by means of qPCR. However, low concentrations of certain biomarkers, as well as small sample volumes require innovations in technology [84].
For proteins detection, the use surface - enhanced laser desorption/ionization time - of - flight (SELDI - TOF) mass spectrometry (MS), has been reported for several diseases. Recently, analysis of saliva for protein biomarker discovery has mainly been performed using two - dimensional difference gel electrophoresis (2D - DIGE) coupled with MS (which can identify around 300 proteins in a sample, and liquid chromatograpy - MS (LC - MS) based techniques (which can identify more than 1,050 proteins in a sample; reviewed in [85]. Thus, liquid chromatographic separation appears to resolve protein species more precisely than gel electrophoresis methods. A multiplex protein array was also employed, providing high - throughput analysis [86]; however, this method requires some prior knowledge of likely analytes. Despite these advances, the discovery and validation of protein salivary biomarkers still has some challenges. Proteins have short half-lives, making them unstable. Both the nature of peptides, as the oral environment makes them vulnerable to degradation. Thus, the diagnosis based on salivary protein requires immediate processing of samples, or the use of freezers and expensive protease inhibitors. In the clinical environment, these requirements are not easily circumvented.
The metabolome is the set of small metabolites and changes continuously, reflecting the gene and protein expression. Metabolomics investigations can generate quantitative data to elucidate metabolic dynamics related to disease and exposure to drugs [87]. However, a metabolomics limitation comparative to genomics, transcriptomics and proteomics is the inability to identify differentially the metabolites expressed [88, 89, 90].
In recent years, many important biological questions have been answered by the study of the "omics" (genomics, transcriptomics, proteomics, metabolomics, etc.), allowing the discovery of various salivary biomarkers. However, few of these markers have exceeded the identification phase. The transfer of scientific knowledge of salivary biomarkers for clinical applications is a challenging process that rarely has resulted in clinical implementation. Its successful application in clinical practice will depend on collaborative studies including physicians, epidemiologists, molecular biologists and bioinformaticians with a relevant clinical question and with well-defined parameters of recruitment and characterization of patients and samples. Thus, the use of saliva as a diagnostic fluid will be increasingly accepted, allowing for enhanced systemic and oral health.
Darwin’s principle of evolution says that the existence of any creature is based on the law “strongest creature survives.” Before computers have entered the human world, in the 50s, knowledge to apply Darwinian principles for automated problem solving was invented. Darwin also proved that the survival of any organism can be maintained with genetic inheritance, such as reproduction, crossover, and mutation. Thus, Darwin’s evolution theory was deployed by computational optimization algorithm to search for a solution to any real-world optimization problem in a natural way [1].
In the 60s, three various interpretations of this idea were introduced at different places. Evolutionary programming was developed by Lawrence J. Fogel in the USA when John Henry at Holland started his methodology as a genetic algorithm, stimulated by Darwin’s evolutionary concepts. Similarly, Ingo Rechenberg and Hans-Paul Schwefel have invented evolution strategies in Germany. Following this fourth one had emerged as genetic programming, in the early 90s. These four different terminologies are seen as different representatives of one technology called evolutionary algorithms (EAs), which denote the whole field by considering evolutionary programming, evolution strategies, genetic algorithms, and genetic programming as sub-areas and is well depicted in Figure 1 [1, 2].
Evolutionary algorithms and their subtypes.
Real-world has many optimization scenarios. Optimization, by definition, is a methodology of making the decision as fully perfect as possible to achieve the maximum possible goal, in an engineering system. Nature is a very good optimizer. An optimization problem can be stated as follows [2, 3].
Any engineering system can be represented with a set of quantities. Certain quantities are usually fixed called as pre-assigned constants. Remaining quantities can be treated as decision variables in the optimization process,
In real-world engineering problems, the objective function is discontinuous, nonlinear, non-convex, and multi-modal. Also, the problems are multi-dimensional as the number of design variables are more and they are mixed in type like integer, real, discrete, binary. Hence, the search space is not smooth. It may require accessing look-up table data for objective function evaluation. The constraint functions are very complex and the amount of violation of each constraint does not cover the same range, which requires normalization [4].
In general, the optimization problems are categorized based on the existence of constraints, nature of the decision variables, permissible values of the design variables, nature of the equations involved, deterministic nature of the variables, separability of the functions, number of objective functions, etc. Some of them are static optimization problem, dynamic optimization problem, linear programming problem, convex programming problem, nonlinear programming problem, geometric programming, quadratic programming problem, separable programming problem, multi-objective optimization problem, single-variate optimization problem, multi-variate optimization problem [5].
Two different techniques to find the solution for optimization problems are mathematical programming techniques and meta-heuristic techniques. When derivative-based mathematical programming methods are applied in solving nonlinear programming problems, there are several shortcomings. Traditional optimization methods:
Yields results that are caught at premature convergence, that is, local optima often, due to the search space with multi-modality.
Requires mathematically well-defined objective and constraint functions.
Requires existence of derivatives for objective function and constraint functions.
Find difficulty to handle mixed variables.
For a real-world optimization problem, the surface plot obtained even for optimizing two design variables gives greater number of local minima/maxima. Figure 2 depicts the surface plot obtained for the design optimization of the distribution transformer problem with two decision variables, width of the core leg, height of the core window, by minimizing the transformer lifetime cost (TLTC) of the transformer. It is very clear from Figure 2 that the real-world problem is very complex with its multi-modal search space [3].
Search space for minimization of TLTC objective optimizing two decision variables.
Of course, when it is a multi-dimensional engineering problem, which requires optimization of more decision variables, the multi-modality cannot be imagined. So, the conventional derivative-based mathematical programming technique cannot handle such complex nature of the optimization problem, accurately. It may yield a feasible design; however, it will not be an optimal solution. If there is no knowledge or little knowledge about the behavior of the objective function related to the presence of local minima, location of feasible region, infeasible region in the multi-dimensional parameter space, it is advisable to start the meta-heuristic technique, which is a stochastic strategy [2, 3].
Of all the meta-heuristic techniques, evolutionary algorithms (EAs) are especially effective in the solution of high-complexity, non-convex, nonlinear, multi-dimensional, mixed variable, multi-objective, constrained optimization problems, for which a traditional mathematical model is difficult to build, where the nature of the input/output relationship is neither well defined nor easily computable. The stages of EAs have not yet been investigated in detail steps with illustration, despite their performances are better in terms of convergence, consistency in obtaining the solution, and computational speed in solving any multi-modal problems.
Hence, this chapter discusses in detail the step-by-step evolutionary process that happens behind the optimization algorithm. It highly helps to find solution for any multi-modal real-world engineering optimization problem, by optimizing design objective, while satisfying simultaneously various constraints imposed by international standards and user specifications.
Evolutionary optimization algorithms minimize or maximize an objective function and they are search algorithms. The algorithm checks all the way through a large search space of possible solution set for the optimal best solution. In day-to-day practical life as well as professional life, there are numerous activities that seek optimization. Some of the common well-known real-world optimization problems are the traveling salesman problem, classification problem, economic power dispatch, base station location problem, antenna design, scheduling problem, etc.
In traveling salesman problem, a salesman wants to visit all the towns, with information of list of towns and distances between all the towns. The constraint is that each town has to be visited only once. The optimization problem statement is searching for the optimum shortest distance/route that the salesman travel and visits each town exactly only once and returns to the place where he started [6].
Base station location problem is setting radio and optimizing maximum coverage. Given a set of spots for installing base stations, feasible configurations for every base station, antenna tilt, maximum power, antenna height, sectors orientation, etc. along with the information of traffic and strength of the signal propagation, the optimization algorithm is to choose the right location and appropriate configuration of the base station such that the installation cost is minimum while meeting the traffic demand simultaneously [7].
The job of optimal generator maintenance scheduling problem is to find out the optimum period for which, the generator units must be taken offline for maintenance over the stipulated time horizon, so that the operating costs involved are minimized, meeting the maintenance constraints during the considered time period such as load demand, maintenance window, maintenance duration and manpower availability [8].
Previous research works have applied only machine learning techniques for the prediction and classification of any disease/tumor. However, nowadays due to the capability of evolutionary algorithms, such classification problems have been stated as an optimization problem and solved using the integrated machine learning-optimization technique. Thus, optimal classification problem aims to select optimum elite features from intelligent liver and kidney cancer diagnostic systems of huge data sets, by filtering the redundant features, minimizing the error rate, in order to improve the quality of heart disease classification [9].
Economic power dispatch is a vital optimization problem in power system planning. The aim of the economic dispatch is to schedule the optimum power output for the available generator units of the power system such that the production cost is minimum and power demand is met [10].
EA handles a population of possible random solutions. Each solution is represented through a chromosome. The fitness of each chromosome is calculated to call for a competition among the chromosomes. Competition results in the selection of those better chromosomes/solutions (with high fitness value) that are suited for the environment. The process of the first level of filtration based on the fitness value is called parent selection [3]. The selected individuals, that is, parents act as seeds for creating children through genetic inheritance, that is, recombination and mutation. These genetic operators aid the necessary diversity. Few pairs of chromosomes from the parent pool are chosen based on the random probability to undergo crossover for forming offspring. The resulted offspring individuals obtained after crossover are allowed to take up mutation randomly. Different regions of the search space are explored for identifying possible optimal individuals through “recombination and mutation” operation known as “exploration.” The new individuals/children thus formed have their fitness evaluated to compete for survival in the next generation. As an end to an iteration, in a replacement stage, 80% worst solutions of the initial random population are substituted by the best offspring children filtered after survival selection process based on the evaluated fitness value. Over time and several iterations, “natural selection” operation, which is called exploitation leads to the identification of an individual in the population as global optimum. The complete working of the evolutionary algorithm is pictured in Figure 3 [11]. The major steps involved in the process of optimization in an evolutionary algorithm are as follows [1, 3].
Solution representation
Random population generation
Fitness function evaluation
Parent selection
Reproduction—(crossover, mutation)
Survival selection
Replacement
Stopping criteria
Working of evolutionary algorithms.
To define problem statement:
Consider an equality function,
Formulate objective function:
The objective/aim is to
Identify decision variables/type: In this equity problem, there are four decision variables [
Find problem dimension:
Total number of decision variables is the problem dimension = 4.
Representation:
A solution generated by an evolutionary algorithm is called a chromosome/individual, which is made up of genes [1]. After selecting the decision variables, and problem dimension, choice of suitable type for these variables is another important task. The nature of the decision variables is completely problem dependent and thus in this example, [
Impose boundary constraint:
This range selection for setting the search space is more often done on a trial basis, in case the problem dimension is high. On contrary, if the objective function is very simple, clear, and possesses straight relationship (mathematical equation) with lesser number of decision variables, then the search space can be decided by inspection [2]. For this example, it is very clear that the integer values of decision variables [
To illustrate solving a minimization type optimization problem using EA, integer type for decision variables, six for population size, single-point method for crossover, and roulette wheel for selection are assumed. The various stages involved in the process of optimization are given for one iteration in this section [13, 14, 15].
Four genes [
Initial random population | Feval [ | Remarks | ||||
---|---|---|---|---|---|---|
Solution [1] | 12 | 05 | 23 | 08 | 93 | |
Solution [2] | 02 | 21 | 18 | 03 | 80 | |
Solution [3] | 10 | 04 | 13 | 14 | 83 | |
Solution [4] | 20 | 01 | 10 | 06 | 46 | |
Solution [5] | 01 | 04 | 13 | 19 | 94 | |
Solution [6] | 20 | 05 | 17 | 01 | 55 |
Functional evaluation of initial population.
All the chromosomes of random population will then go through a process known as fitness evaluation to measure the quality of the solution created by EA. Evaluation of fitness value of chromosome/solution is carried out by calculating the objective function value as Feval = Modulus[
Feval [1] = mod [(12 + 10 + 69 + 32) − 30] = 93. Similarly, the solutions of entire population can be calculated and tabulated as under in Table 1. It is found that Chromosome 4 has the least objective function value 46.
The chromosomes are selected from the initial population to act as parent for reproduction, based on the fitness of the solution/individual. The selection procedure tells how to choose individuals in the population that will create offspring for the next generation. The fittest solution will have a higher probability to be selected as a parent. Two-step selection process is discussed as follows [13, 15].
To compute the probability of selection: Prob[
where,
(to avoid undefined divide by zero error, which may encounter for the optimal solution, it is advisable to add 1 with Feval).
Fit [1] = 1/(1 + Feval [1]) = 1/94 = 0.0106 and so on, till
Total fitness = 0.0845 (refer Table 2).
Prob [1] = 0.0106/0.0845 = 0.1254
To select the parent pool: Roulette-wheel (RW) selection process:
Initial population | Feval [ | Fit [ | Prob [ | Cum [ | |||
---|---|---|---|---|---|---|---|
12 | 05 | 23 | 08 | 93 | 0.0106 | 0.1254 | 0.1254 |
02 | 21 | 18 | 03 | 80 | 0.0123 | 0.1456 | 0.2710 |
10 | 04 | 13 | 14 | 83 | 0.0119 | 0.1408 | 0.4118 |
20 | 01 | 10 | 06 | 46 | 0.6639 | ||
01 | 04 | 13 | 19 | 94 | 0.0105 | 0.1243 | 0.7882 |
20 | 05 | 17 | 01 | 55 | 0.0179 | 0.2118 | 1 |
Total fitness | 0.0845 |
Selection probability computation.
Parent selection is vital for the convergence of optimization algorithm as efficient parents force solutions/individuals to optimality. There are different methods in the process of selecting parents such as stochastic universal sampling, fitness proportionate selection, tournament selection, rank selection, and random selection. In this chapter, roulette wheel selection has been implemented for identifying the right parent pool.
Consider a wheel that is split into ‘6’ pies. Pie refers to the individual in the population. Each solution occupies a portion of the wheel, proportional to its fitness value. It is clear that a fitter solution takes a larger pie on the wheel and has larger probability chance of being selected as a parent when the wheel is made to spin ‘6’ times. Hence, the probability of choosing a chromosome depends on its fitness only. The steps involved in the roulette wheel selection process are:
Compute cumulative probability values for all the solutions—Cum[
Allot pie in sequence for all the ‘6’ individuals, based on the cumulative probability. That is, Chromosome 1 has occupied light blue pie with cumulative probability ranging between [0–0.1254]. Chromosome 4 which has the highest fitness value ‘0.0213’ has the highest probability ‘0.2521’ among all the solutions of the population. Naturally, it will take larger sized pie, which is yellow in color on the wheel. It is clearly explained in Figure 4, and Tables 3 and 4.
To arrange the order of chromosomes (6) in the parent pool, equivalent to spinning the wheel ‘6’ times, generate random number ‘6’ times, ‘rand[i]’ < 1, six.
rand [place 1] = 0.2; rand [place 2] = 0.285; rand [place 3] = 0.098;
rand [place 4] = 0.812; rand [place 5] = 0.397; rand [place 6] = 0.50.
Fit the random number of each place in the respective range of cumulative probabilities and fetch the color of the pie. For example, rand [place 2] = 0.285,which is between Cum [2] and Cum [3]. So, the gray pie which is individual/chromosome [3] will occur in place2 of the parent/mating pool.
Roulette wheel—Parent selection process.
Position | Chromosome | Initial population | ||||
---|---|---|---|---|---|---|
Place 1 | I | Solution [1] | 12 | 05 | 23 | 08 |
Place 2 | II | Solution [2] | 02 | 21 | 18 | 03 |
Place 3 | III | Solution [3] | 10 | 04 | 13 | 14 |
Place 4 | IV | Solution [4] | 20 | 01 | 10 | 06 |
Place 5 | V | Solution [5] | 01 | 04 | 13 | 19 |
Place 6 | VI | Solution [6] | 20 | 05 | 17 | 01 |
Place and position of solution—Before RW selection process.
Position | Chromosome | Population after selection | |||
---|---|---|---|---|---|
Place 1 | II | 02 | 21 | 18 | 03 |
Place 2 | III | 10 | 04 | 13 | 14 |
Place 3 | I | 12 | 05 | 23 | 08 |
Place 4 | VI | 20 | 05 | 17 | 01 |
Place 5 | III | 10 | 04 | 13 | 14 |
Place 6 | IV | 20 | 01 | 10 | 06 |
Chromosomes in the MATING POOL after RW selection process.
The crossover operation involves three steps: (A) selecting mating chromosomes, (B) determining cut point for crossover, and (C) updating the population.
In this operation pairs of parents are chosen and many children/off-springs are generated using the information available in the gene of the parents. Usually, crossover operation is deployed in EA with high probability(
To select chromosome:
Population after selection | Population after crossover | ||||||
02 | 21 | 18 | 03 | 02 | 05 | 17 | 01 |
10 | 04 | 13 | 14 | 10 | 04 | 13 | 14 |
12 | 05 | 23 | 08 | 12 | 05 | 23 | 08 |
20 | 05 | 17 | 01 | 20 | 04 | 13 | 14 |
10 | 04 | 13 | 14 | 10 | 04 | 18 | 03 |
20 | 01 | 10 | 06 | 20 | 01 | 10 | 06 |
Population after and before crossover operation.
Parent chromosome from parent pool that undergoes the mating process is randomly selected and the number of mate solutions is decided using crossover rate,
rand [1] = 0.19; rand [2] = 0.249; rand [3] = 0.750; rand [4] = 0.005
rand [5] = 0.149; rand [6] = 0.320
Thus, for the generated random numbers, three chromosomes/solutions [1, 4, 5] are selected for crossover operation. Hence, the number of crossovers becomes 3, that is, 3 pairs.
Solution [1] >< Solution [4] --- First Crossover
Solution [4] >< Solution [5] --- Second Crossover
Solution [5] >< Solution [1] --- Third Crossover
To determine cut point:
Followed by mating chromosome selection, the next phase is to determine the position of the crossover point. The steps involved are:
Generate random numbers between 1 to (Problem dimension—1) in order to get the crossover point. That is, between 1 and 3. Assume, Cut [1] = 1; Cut [2] = 1; Cut [3] = 2
Parent individuals get cut at the crossover point and their genes are interchanged. For first, second, and third crossovers, parents’ genes are cut at positions 1, 1, and 2, respectively.
First Crossover: New Chromosome [1] = Solution [1] >< Solution [4]
Second Crossover: New Chromosome [4] = Solution [4] >< Solution [5]
Third Crossover: New Chromosome [5] = Solution [5] >< Solution [1]
C. To update the population after crossover:
Mutation operation is a small random sharp change in the chromosome necessary to obtain a new solution. Mutation is used to sustain population diversity and it generally has a low probability,
Calculate the total number of genes in the population = 24 genes.
Calculate number of mutable genes.
Number of solutions that undergo mutations in a population is decided by mutation rate
Calculate gene positions.
Generate two random numbers below 24, say 12 and 18. Mutable genes and chromosomes are Chromosome [3]-gene 4 and Chromosome [5]-gene 2. This process is seen in Table 6.
The value of mutable genes at the mutation point is substituted with random number, satisfying the boundary constraint of decision variables/genes. That is, between 0 and 30; Say 02, 05.
Population after selection | Population after crossover | Population after mutation | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
02 | 21 | 18 | 03 | 02 | 05 | 17 | 01 | 02 | 05 | 17 | 01 |
10 | 04 | 13 | 14 | 10 | 04 | 13 | 14 | 10 | 04 | 13 | 14 |
12 | 05 | 23 | 08 | 12 | 05 | 23 | 08 | 12 | 05 | 23 | 02 |
20 | 05 | 17 | 01 | 20 | 04 | 13 | 14 | 20 | 04 | 13 | 14 |
10 | 04 | 13 | 14 | 10 | 04 | 18 | 03 | 10 | 05 | 18 | 03 |
20 | 01 | 10 | 06 | 20 | 01 | 10 | 06 | 20 | 01 | 10 | 06 |
Population after and before mutation operation.
After mutation operation one iteration/generation of EA is over. Functional evaluation is again performed on the offspring for survival selection. From the functional evaluation of population after mutation, it is evident that the objective function value of the best solution is reducing—37 in comparison with the minimum objective value—47 of initial random population, as shown in the table. Hence the minimization objective,
To execute the iteration process continuously, population is to be revised at the end of each iteration, as a final process, which is referred to as replacement mechanism. In each iteration end, 80–90% of best solutions from offspring population (4–5 best children) and 20–10% best solutions from the initial population (2–1 random solution) are selected to form new population for next generation [15]. Chromosomes of the next generation will then become as shown in Tables 7 and 8.
Population after mutation | Feval | Remarks | |||
---|---|---|---|---|---|
02 | 05 | 17 | 01 | ||
10 | 04 | 13 | 14 | 77 | Survive in next generation |
12 | 05 | 23 | 02 | 47 | Survive in next generation |
20 | 04 | 13 | 14 | 93 | Rejected solution |
10 | 05 | 18 | 03 | 56 | Survive in next generation |
20 | 01 | 10 | 06 | 46 | Survive in next generation |
Survival selection.
Population after mutation | Next generation initial population | Feval | Remarks | ||||||
---|---|---|---|---|---|---|---|---|---|
02 | 05 | 17 | 01 | 02 | 05 | 17 | 01 | ||
10 | 04 | 13 | 14 | 10 | 04 | 13 | 14 | 77 | |
12 | 05 | 23 | 02 | 12 | 05 | 23 | 02 | 47 | |
20 | 04 | 13 | 14 | 20 | 01 | 10 | 06 | 47 | Replaced solution |
10 | 05 | 18 | 03 | 10 | 05 | 18 | 03 | 56 | |
20 | 01 | 10 | 06 | 20 | 01 | 10 | 06 | 46 |
Replacement-population for the next iteration.
The optimization process is repeated until when objective function value or decision variables values become stagnant, that is, have no/very little change for a greater number of iterations. Thus, over period, the solution will get converge to the final best minimum optimal solution and the optimization process will be stopped, based on any stopping criteria such as the maximum number of iterations, or maximum number of functional evaluations, etc.
The basic processes that occur behind an evolutionary algorithm have been explained and illustrated in this chapter with steps covering solution representation, population generation, functional evaluation, parent selection, genetic operations, offspring evaluations, survival selection, and stopping criteria for a simple optimization problem. This knowledge can be extended very well by researchers across any discipline, working in the field of optimization and for applying evolutionary algorithms to solve any complex engineering problem using computers. Although the process behind EA may appear to be simple, the details of the optimization process form the base and are very much necessary in applying the learned concepts for modifying the existing evolutionary concepts and evolving into better optimization methods in the research level.
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In all cases, cyclical ups and downs depend not only on internal system cyclical processes and their factors in countries but also on the consequences of intercountry interaction. The ability to measure and predict business cycles, taking into account their mutual influence, is a prerequisite for the development of an adequate business policy of countries and their associations.",book:{id:"6703",slug:"statistics-growing-data-sets-and-growing-demand-for-statistics",title:"Statistics",fullTitle:"Statistics - Growing Data Sets and Growing Demand for Statistics"},signatures:"Elena Zarova",authors:null},{id:"60246",title:"Statistical Research of Investment Appeal of Russian Regions",slug:"statistical-research-of-investment-appeal-of-russian-regions",totalDownloads:1014,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, the methodological results directed on realization statistical research of investment appeal of Russian regions are offered. 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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. 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He also obtained an MSc in Molecular and Genetic Medicine, and a Ph.D. in Clinical Immunology and Human Genetics from the University of Sheffield, UK. He also completed a short-term fellowship in Pediatric Clinical Immunology and Bone Marrow Transplantation at Newcastle General Hospital, England. Dr. Rezaei is a Full Professor of Immunology and Vice Dean of International Affairs and Research, at the School of Medicine, Tehran University of Medical Sciences, and the co-founder and head of the Research Center for Immunodeficiencies. He is also the founding president of the Universal Scientific Education and Research Network (USERN). Dr. Rezaei has directed more than 100 research projects and has designed and participated in several international collaborative projects. He is an editor, editorial assistant, or editorial board member of more than forty international journals. He has edited more than 50 international books, presented more than 500 lectures/posters in congresses/meetings, and published more than 1,100 scientific papers in international journals.",institutionString:"Tehran University of Medical Sciences",institution:{name:"Tehran University of Medical Sciences",country:{name:"Iran"}}},{id:"180733",title:"Dr.",name:"Jean",middleName:null,surname:"Engohang-Ndong",slug:"jean-engohang-ndong",fullName:"Jean Engohang-Ndong",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180733/images/system/180733.png",biography:"Dr. Jean Engohang-Ndong was born and raised in Gabon. After obtaining his Associate Degree of Science at the University of Science and Technology of Masuku, Gabon, he continued his education in France where he obtained his BS, MS, and Ph.D. in Medical Microbiology. He worked as a post-doctoral fellow at the Public Health Research Institute (PHRI), Newark, NJ for four years before accepting a three-year faculty position at Brigham Young University-Hawaii. Dr. Engohang-Ndong is a tenured faculty member with the academic rank of Full Professor at Kent State University, Ohio, where he teaches a wide range of biological science courses and pursues his research in medical and environmental microbiology. Recently, he expanded his research interest to epidemiology and biostatistics of chronic diseases in Gabon.",institutionString:"Kent State University",institution:{name:"Kent State University",country:{name:"United States of America"}}},{id:"188773",title:"Prof.",name:"Emmanuel",middleName:null,surname:"Drouet",slug:"emmanuel-drouet",fullName:"Emmanuel Drouet",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/188773/images/system/188773.png",biography:"Emmanuel Drouet, PharmD, is a Professor of Virology at the Faculty of Pharmacy, the University Grenoble-Alpes, France. As a head scientist at the Institute of Structural Biology in Grenoble, Dr. Drouet’s research investigates persisting viruses in humans (RNA and DNA viruses) and the balance with our host immune system. He focuses on these viruses’ effects on humans (both their impact on pathology and their symbiotic relationships in humans). He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. Dr. Aqib joined the Department of Clinical Medicine and Surgery at UAF for one year as an assistant professor where he developed a research laboratory designated for pathogenic bacteria. Since 2018, he has been Assistant Professor/Officer in-charge, Department of Medicine, Manager Research Operations and Development-ORIC, and President One Health Club at Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Pakistan. He has nearly 100 publications to his credit. His research interests include epidemiological patterns and molecular analysis of antimicrobial resistance and modulation and vaccine development against animal pathogens of public health concern.",institutionString:"Cholistan University of Veterinary and Animal Sciences",institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"333753",title:"Dr.",name:"Rais",middleName:null,surname:"Ahmed",slug:"rais-ahmed",fullName:"Rais Ahmed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333753/images/20168_n.jpg",biography:null,institutionString:null,institution:{name:"University of Agriculture Faisalabad",country:{name:"Pakistan"}}},{id:"62900",title:"Prof.",name:"Fethi",middleName:null,surname:"Derbel",slug:"fethi-derbel",fullName:"Fethi Derbel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62900/images/system/62900.jpeg",biography:"Professor Fethi Derbel was born in 1960 in Tunisia. He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). 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