\r\n\tIt has been established that energy/nutrient depletion, calcium flux injury, or oxidative stress disrupt endoplasmic reticulum homeostasis and even induce accumulation of misfolded/unfolded proteins leading to endoplasmic reticulum stress. Under endoplasmic reticulum stress conditions, an adaptive mechanism of coordinated signaling pathways, defined unfolded protein response (UPR), is activated to return the endoplasmic reticulum to its healthy functioning state. The aging causes a decrease of the protective adaptive response of the UPR and an increase of the pro-apoptotic pathway together with endoplasmic reticulum ultrastructural injury. Controlling endoplasmic reticulum stress response, maintaining the appropriate endoplasmic reticulum ultrastructure and homeostasis, and retaining mitochondria interplay are crucial aspects for cellular health.
\r\n
\r\n\tThis book presents a comprehensive overview of endoplasmic reticulum, including, but not limited to, endoplasmic reticulum ultrastructural anatomy, MAMs, endoplasmic reticulum stress, and their implication in health and diseases. Additionally, identifying perturbations in the endoplasmic reticulum stress response could lead to early detection of age-related disease and may help develop therapeutic approaches.
",isbn:"978-1-80356-228-5",printIsbn:"978-1-80356-227-8",pdfIsbn:"978-1-80356-229-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"5d7d49bd80f53dad3761f78de4a862c6",bookSignature:"Dr. Gaia Favero",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11674.jpg",keywords:"Metabolism, Aging, Neurodegenerative Diseases, Endoplasmic Reticulum, Microscopy, Metabolic Stress, Ultrastructural Anatomy, Cellular Stress, Contactology, Mitochondria, Cellular Stress, Endoplasmic Reticulum Response",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 9th 2022",dateEndSecondStepPublish:"May 6th 2022",dateEndThirdStepPublish:"July 5th 2022",dateEndFourthStepPublish:"September 23rd 2022",dateEndFifthStepPublish:"November 22nd 2022",remainingDaysToSecondStep:"17 days",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Human anatomy researcher involved in crucial topics on morphology, anatomy, and molecular medicine - working on innovative approaches to aging-related pathopsychological processes at the University of Brescia.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"238047",title:"Dr.",name:"Gaia",middleName:null,surname:"Favero",slug:"gaia-favero",fullName:"Gaia Favero",profilePictureURL:"https://mts.intechopen.com/storage/users/238047/images/system/238047.jpg",biography:'Dr. Gaia Favero is a prominent scientist in the field of life sciences. She is currently engaged as a researcher for the Scientific-Disciplinary Sector BIO/16 Human Anatomy at the Anatomy and Pathophysiology Division, Department of Clinical and Experimental Sciences, University of Brescia (Italy).\r\nDr. Favero focuses on aging-related morphological dysfunctions as the prelude to various pathophysiological processes in her research programs. The central hypothesis is that natural antioxidants and, in particular, melatonin may act as molecular "switches" that modulate cells and tissues by suppressing, at various levels, oxidative stress and inflammatory signalling cascades. These research approaches represent powerful tools for developing innovative preventive strategies and identifying novel prognostic biomarkers for several diseases. 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1. Introduction
Surfactants are surface-active agents that reduce water–oil, liquid–gas, and solid–liquid or solid–gas medium surfaces and interfacial tension [1, 2]. The surface energy is reduced by the presence of hydrophilic and hydrophobic sections of the same surfactant molecule owing to preferred interactions at surfaces and interfaces. In aqueous solution, surfactant molecules arrange themselves at the interface, where the hydrophobic part is in the air (or oil) and the hydrophilic part is in water, while at high concentration or concentrations above the critical micelle concentration (CMC), surfactant molecules self-assemble into micelles (Figure 1). Not only are they widely used as cleaning agents, but also other beneficial properties, such as foaming, emulsification, and particle suspension, make surfactants known for their wetting ability and effectiveness such as emulsifiers and stabilizers. Due to this characteristic, surfactants are found in a variety of products that we use every day, including food, pharmaceuticals, toiletries, detergents, automotive fluids, paints, and coatings [2]. Surfactants have steadily grown in popularity since their debut in the early twentieth century, and they are now among the most widely used synthetic compounds on the planet [3, 4].
Figure 1.
(a) Simplified surfactant molecule, (b) arrangement of surfactant monomers at the water surface, and (c) micelle formation above critical micelle concentration (CMC).
Petrochemical and renewable sources are the two primary feedstock groups used in the manufacture of surfactants [5, 6]. The development of petrochemical processing led to the acquisition of hydrophobic structures of surfactant molecules through polymerization of alkenes, such as ethylene or propylene. Although ethylene has been employed as a carbon chain-building block, its increased applicability in industrial production has resulted from the production of an intermediate or precursor, ethylene oxide [7]. Natural surfactants are usually derived from triglycerides found in vegetable oils or animal fats. The surfactant industry was focused on the saponification of oils and fats prior to petrochemical processing [8, 9]. Surfactants infiltrate water bodies after usage, where they can create issues if they remain for a long time, resulting in the buildup of potentially toxic or otherwise hazardous substances causing significant environmental concerns [10, 11, 12]. Synthetic surfactant-related water contamination has increased in recent years because of its widespread usage in domestic, agricultural, and other cleaning activities. This occurrence has caused global concern, forcing establishment of a series of new rules governing its usage and disposal [13, 14]. In addition, experts relate the production of petrochemical-based surfactants to the high net output of CO2, a greenhouse gas linked to climate change and global warming. By switching to renewable feedstock, this rate can be minimized. A previous study shows that using renewable resources instead of petrochemicals for surfactant synthesis would cut CO2 emissions by 37% in the EU [15]. Beside environmental concerns and regulations, growing consumer awareness and market pressures have prompted considerable R&D into bio-based surfactants as potential substitutes for synthetic surfactants.
The term “bio-based surfactant” refers to a surfactant produced by a chemical or enzymatic process that uses renewable substrates as raw materials [16, 17]. According to ISO/DIS 21680, a bio-based surfactant is defined as a surfactant wholly or partly derived from biomass (based on biogenic carbon) [18]. Most applications need further processing of bio-based feedstocks to incorporate functional groups that can give the surfactant’s functional characteristics, resulting in a variety of anionic, cationic, nonionic, and amphoteric products. Many of these processes require the use of petroleum-based feedstocks or moieties that are not always environmentally friendly. The European Commission of Standardization has created categories for biosurfactants, including >95% completely bio-based, 50–94% majority bio-based, 5–49% minority bio-based, and 5% non-bio-based to assist in analyzing the bio-based surfactants’ sustainability criteria (Table 1) [19].
Surfactant class
Bio-based carbon content X% (m/m)
Wholly bio-based surfactant
≥95
Majority bio-based surfactant
95 ≥ X > 50
Minority bio-based surfactant
50 ≥ X ≥ 5
Non-bio-based surfactant
X < 5
Table 1.
Bio-based surfactant classes according to CEN/TS 17035 [19].
The hydrophobe, hydrophile, or both, which are derived from natural sources, can be used in the production of bio-based surfactants. Plant oil, fatty acids, and animal fat are examples of natural hydrophobes, while glycerol, glucose, sucrose, and amino acids (aspartame, glutamic, lysine, arginine, alanine, and protein hydrolysates) are examples of natural hydrophiles. They can be either directly utilized in their original form or produced from complicated sources, such as vegetable oil, sugarcane, sugar beets, and starch-producing crops. As for biosurfactants, they consist of hydrophilic sugar or peptide component and hydrophobic saturated or unsaturated fatty acid chains that are naturally produced by bacteria, yeast, and fungi. Hence, a biosurfactant is classified as a wholly bio-based surfactant since all its raw materials are considered natural [20, 21, 22].
The hydrophobic part of bio-based and biosurfactant feedstock is mostly from fatty acyl groups. The fatty acyl groups are generally obtained from oilseeds in the form of triacylglycerol, but they may also be derived from oleochemical by-products such as free fatty acid or phospholipids. Fatty acyl groups are generally utilized as lipophilic building blocks for surfactants in the form of free fatty acids or fatty acyl esters, which are produced via hydrolysis or alcoholysis of triacylglycerol [23, 24]. This fatty acyl group conjugates hydrophilic and lipophilic compounds via an ester bond. This bond makes the fatty acid-based surfactants suitable for foods, cosmetics, personal care, and pharmaceutical product applications, but not for laundry detergents since the ester bonds are unstable. More stable bonds, such as ether, amides, and carbonate bonds, can be produced by converting the fatty acid groups to fatty alcohols, fatty amines, or fatty acid chloride [25, 26, 27].
Algae are another potential renewable source of fatty acids. It has been an active research area in recent years due to its potential for high oil production per acre and the ability to leverage on nonarable soil [28, 29, 30]. Previously, Unilever has partnered with Solazyme, a microalgae firm, with the aim of finding a palm-oil-free replacement for its soaps and surfactants. Solazyme used the advantage of its intellectual property in the areas of recombinant DNA expression in algae and algae bioprocessing to create oils with specific fatty acyl compositions [31]. Solazyme, later renamed as TerraVia, was acquired by Carbion in 2017 to focus on delivering innovative and high-value ingredients for food, personal care, and industrial applications [32]. Lignin has also been used as a feedstock in surfactant production due to its hydrophobic aromatic structure. Lignin-based surfactants are usually made by grafting hydrophilic groups or monomers onto the lignin to enhance its surface properties [33, 34, 35]. Extensive investigations are necessary to expedite the commercialization of lignin-based surfactants to the market since information on connecting performance and characteristics of lignin-based surfactants for their optimal usage is still lacking.
Among the most significant feedstocks for renewable hydrophile sources are vegetable oils (for glycerol), sugarcane and sugar beets (for sucrose), and starch-producing crops, such as maize, wheat, potato, and tapioca (for glucose) [4, 23, 36]. The use of glycerol as an alternative hydrophilic building block to replace ethylene oxide in the synthesis of nonionic surfactants is a feasible option. The major glycerol-based surfactants in the market are ester-based mono- and diglycerides, which are made by transesterifying triglycerides with excess glycerol and a base catalyst [4, 26, 37]. Carbohydrates, such as sugar and sucrose, are another useful biorefinery feedstock that make up as surfactant hydrophiles. The discovery of sucrose monoesters, or long-chain fatty acid esters, was one of the first major achievements of the Sugar Research Foundation (SRF) and led to their use as nonionic surfactants, food additives, and emulsifiers [38]. The global sucrose esters market amounted to $71.9 M in 2018 and is expected to reach $137.85 M by 2027 [39]. However, selectivity in the synthesis of these esters remains a challenge where acylation with a single fatty acid can yield many different isomers with various degrees of substitution [40]. One of the solutions to tackle the selectivity problem is by using lipases and proteases for regioselective sucrose ester production [41, 42]. Further improvement via lipase and protease protein engineering might increase the regioselectivity and yield of the catalysis processes. The biotransformation of sucrose to sucrose esters utilizing whole-cell fermentation methods might also give a new path to sucrose-based surfactant production.
Glucose is utilized as a hydrophile in the manufacture of a variety of surfactants, both directly and indirectly. It can react directly with fatty alcohol in a glycosidation process to produce alkyl polyglucosides (APGs), a nonionic surfactant class with growing production and popularity. Indirectly, glucose may be chemically converted to sorbitol, sorbitan, N-methyl glucamine, and O-methylglucoside, or enzymatically converted to amino, lactic, and citric acids, all of which can be leveraged to produce surfactants (Figure 2) [4].
Figure 2.
Simplified transformations pathway from glucose to several surfactant building blocks and surfactants.
Sugar-derived surfactants have a higher market demand than synthetic chemicals and surfactants due to their low toxicity, low cost, biodegradability, good cleaning and washing abilities, environmental compatibility, and high surface activity [43, 44]. However, if the demand for sugar surfactants grows in the long run, feedstock availability will become a concern. New methods that use bacteria and microorganisms to manufacture glucose are emerging; however, the issue of scalability has yet to be solved.
The creation of new amino acid-based surfactants may be influenced by advancements in biotechnological amino acid synthesis. Other than L-glutamic acid and L-lysine, which are the two most produced amino acids in the market, alanine, aspartic acid, glycine, and arginine, as well as protein hydrolysates, are also used in the manufacture of some commercial surfactants [45, 46, 47]. Another type of amino acid surfactant, sarcosine-based surfactants, has been in the market for decades. Even though sarcosine is a naturally occurring molecule, it is mostly synthesized on a large scale by combining chloroacetic acid with N-methylamine [48, 49, 50]. Betaine, another naturally occurring molecule, is also synthesized in large scale using petrochemical-based trimethylamine and chloroacetic acid. Most betaine surfactants use an oleochemical hydrophobe precursor obtained from tropical oils as the bio-based component [51]. Glycine betaine is a promising biosurfactant that can be commercially extracted from brown algae and sugar beet molasses [52, 53].
Glycolipids are a type of complex carbohydrate that contains both a glycan and a lipid component. They are usually the main lipids of bacterial and fungal cell walls. In an aqueous solution, glycolipids are amphiphilic substances that form stable micelles, and these molecules have the capacity to offer low interfacial tension [54, 55]. Rhamnolipids and sophorolipids are among the glycolipids that have been utilized the most as biosurfactants. Rhamnolipids are produced as one or two rhamnose sugar groups attached to one or two fatty acid chains by different bacterial species (i.e., Pseudomonas aeruginosa, Pseudomonas chlororaphis, Burkholderia pseudomallei) [4, 56]. Beside their favorable emulsifying, solubilizing, foaming, and antibacterial characteristics, the use of rhamnolipids is appealing due to their high production yields after relatively short incubation times [56]. Rhamnolipids are now available on a larger scale due to the optimized fermentation techniques and advanced extraction and concentration technologies. Sophorolipids, another extensively researched type of glycolipid, are biosynthesized by certain yeast strains such as Starmerella bombicola, Wickerhamiella domercqiae, and Candida batistae from sophorose sugar and hydroxylated fatty acid. Sophorolipids are commercially used in dish and vegetable detergents and in skin care formulations [57, 58, 59, 60].
2. Recent progress in R&D and industrial production
Regulations on the environmental impact and hazardous chemicals are highly stringent, particularly in Europe and North America, which are the two largest markets for surfactants, especially in the home and personal care sectors. As a result, the surfactant industry is commencing to develop biosurfactants, which have lower levels of toxicity and a more environmentally friendly manufacturing process. Apart from complying with environmental regulations, the industry is seeing bio-based surfactants to achieve a sustainable competitive edge. The advent of biotechnology in the twenty-first century promoted the creation of novel bio-based and biosurfactants along with their enhanced commercial and economic viability. Extensive and significant R&D has also enabled high-quality and high-functionality bio-based surfactant formulations to evolve from the lab scale to niche applications to commercial-scale production. Some of the bio-based surfactants that are commercially available in the market, their main manufacturers, and their applications are listed in Table 2.
Bio-based surfactants
Selected manufacturers
Fields of applications
Anionic
Lignosulfonate Methyl ester sulfonates Anionic derivatives of alkyl polyglucoside
Ajinomoto Co. Inc., Stepan, Zschimmer and Schwarz Clariant Schill+Seilacher
Personal care
Table 2.
Commercially available bio-based surfactants, their manufacturers, and their applications.
In the current development of novel surfactants, there is a growing trend of utilizing nontraditional naturally occurring branching hydrophobic chains [61, 62, 63]. Nonionic surfactants based on twin tail glycerol have been synthesized and they have good oil-in-water and water-in-oil emulsifying characteristics [64]. Other structural analogs of glycerol-based surfactants have recently been created by employing heterogeneous interfacial acidic catalysts to directly etherify glycerol and dodecanol. These surfactants have been shown to be comparable with commercially available surfactants in terms of physicochemical assessment and detergency ability [37]. Another class of amphiphilic compounds with a glycerol backbone is bio-based dialkyl glycerol ethers. These compounds have good solvo-surfactant characteristics and can function as solubilizers for hydrophobic dyes in aqueous media [65].
Natural edible flavor vanillin is used to create a cleavable vanillin-based polyoxyethylene nonionic surfactant. Because it contains cleavable acetal bonds that break down quickly under acidic circumstances, this environmentally beneficial surfactant is totally biodegradable in nature. The surfactant’s surface activity, wettability, and emulsifying and foaming properties are on par with nonylphenol ethoxylate surfactants, which are highly toxic to aquatic organisms and environment [66]. Several novel types of sustainable surfactant have been created in recent years by employing various types of terpenes, which are the major components of essential oils derived from a variety of plants and flowers [67, 68, 69, 70]. The terpenes were transformed to branched hydrophobic tail containing quaternary ammonium surfactants. Natural farnesol, a 15-carbon acyclic sesquiterpene alcohol found in neroli, lemongrass, tuberose, rose, citronella, and other plant species, was used to create a new form of terpene-based sustainable surfactant, which has demonstrated excellent surfactant performance [70]. Under the trade name ECOSURF, Dow Chemical Co. is now offering a range of sustainable oilseed-based nonionic surfactants. These surfactants are claimed to have minimal aquatic toxicity and are biodegradable in nature, making them suitable candidates for paints and coatings, as well as home, industrial, and institutional cleansers and textiles [71].
TegraSurf, a range of sustainable water-based surfactants developed for energy, mining, agricultural, water treatment, and other industrial applications, was released in July 2021 by Integrity BioChem (IBC), a technology-driven business producing next-generation biopolymers. TegraSurf is made of sustainable vegetal materials and is certified Readily Biodegradable by the OECD 301B guideline. After 90 days, it is no longer present in the environment, making it safer and healthier for local populations and allowing formulators to fulfill industry sustainability criteria [72]. BASF and Solazyme Inc. recently released Dehyton® AO 45, the first commercial microalgae-derived betaine surfactant made from microalgae oils as an alternative to conventional amidopropyl betaine surfactants [73]. Following the launch of sophorolipid-based surfactants in 2020, BASF formed an exclusive partnership with Holiferm Ltd. in the United Kingdom to focus on the development of glycolipids other than sophorolipids for personal and home care as well as for industrial uses [74].
Croda expanded its commercial-scale bio-based manufacturing capabilities and technology leadership in renewable raw materials by unveiling its 100% bio-based ethylene oxide production facility as an effort to make the world’s products greener. Ethylene oxide is the key raw material used to produce surfactants. Croda’s Atlas Point manufacturing plant in New Castle, Delaware, is the first of its type in the United States for the manufacture of 100% sustainable, 100% bio-based nonionic surfactants [75]. Ajinomoto is increasing to 60% of its global capacity for its Amisoft range of amino acid-based liquid surfactants by building a new plant in Brazil [76]. Sironix Renewables received $645,000 in investment from the University of Minnesota Discovery Capital Investment program and investors as well as a $1.15 million grant from the US Department of Energy Advanced Manufacturing Office, to help them scale up their Eosix® production. The new renewable oleo-furans-based surfactants are 100% plant-based that offer unique and adjustable characteristics in a wide range of areas, including cleaning products, cleaners, cosmetics and personal care, agriculture and inks, and paint and coatings [77].
3. Industrial challenge on bio-based surfactant
This section covers the market performance, demand drivers, and growth prospects of biosurfactants. The market trend on bio-based and biosurfactants is discussed for the different geographic regions and in terms of changing market trends for biosurfactants in various application areas. Analysis of the industrial challenges of biosurfactants, which include the growth-restraining factors and future opportunities, is provided.
3.1 The economy and market trend of bio-based surfactant
The worldwide surfactant industry, estimated to be worth $39 billion in 2019, is expected to expand at a rate of 2.6% per year over the following five years, reaching $46 billion in 2024. Surfactants are produced in total of 17 million metric tons per year [78]. In the EU, of the 3 million metric tons of surfactants produced in 2019, roughly 50% were bio-based [79]. A market study by Market Research Future [80] indicated that the global biosurfactants’ market value is around USD 2.1 billion in 2020 and predicted it to reach USD 2.8 billion by 2026, with a compound annual growth rate of over 5% from 2021 to 2026. The attractive performance of biosurfactants advances their high potential to substitute synthetic-based surfactants for drop-in applications and with unique properties that can overcome entry barriers for the emerging industrial areas. Major types of biosurfactants, such as sophorolipids, glycolipids, lipopeptides, polymeric biosurfactants, phospholipids and fatty acids, generally form the product demand application. Among biosurfactants, sophorolipids provide the largest global market demand with detergents and industrial cleaning applications. The leading demand drivers for biosurfactants comprise a growing consumer preference, increasingly stringent regulatory requirements, and rising awareness toward eco-friendly alternatives. By being environmentally compatible and with low toxicity, many studies have considered biosurfactants as the next generation of industrial surfactants [81, 82, 83]. In terms of end-user applications, biosurfactants are finding usage in household detergents, industrial and institutional cleaners, cosmetics, and personal care within the major markets in Europe and North America [80]. Recently, they have been gaining acceptance in the newer application areas such as in oil and gas as well as in agricultural industries.
Furthermore, the increasing consumer awareness of the benefits of biosurfactants and their wide range of application sectors form market drivers that increase their future growth potential. Higher growth of biosurfactants is seen in Asia-Pacific (APAC), especially in Southeast Asian countries that have slightly different demand factors that involve the increasing purchasing power of mass consumers, growing concern on environmental issues, and the generation of harmful chemical by-products. In terms of APAC market segmentation, the major sales revenue for biosurfactants resides within the home care and personal care applications, as rising urbanization becomes the dominant factor for surfactant growth. More importantly, a key growth enabler is in the innovative research on biosurfactants, especially when it can generate multifunctional and diversified products using renewable feedstock. This technological progress contributes to the desirable properties of biosurfactants to meet the changing consumer lifestyles in developing economies and consequently their increasing preference for usage in the end-user product formulation. As an example, within the home care detergent industry, the usage of biosurfactants as environmentally friendly products provides sustainable alternatives that are gaining a large market share [81, 84, 85].
The highest adoption of bio-based and biosurfactants is in Europe and North America, which dominate bio-based surfactant market share in terms of revenue and volume. Increasingly stringent regulatory requirements enable a wider acceptance of biosurfactants in the place of synthetic surfactants. For example, the imposed government regulations, such as CEN/TC-276, define the standards for surface-active agents and detergents to enhance the EU bio-based economy, detergent regulation (EC) No 648 that require surfactants used in detergents to be biodegradable under aerobic conditions as per OECD 301 test series. In addition, the COVID-19 pandemic results in a sharp increase in the bio-based surfactant product demand for household detergents, personal care, and industrial cleaners due to the rising trend for sanitation.
3.2 The industrial challenges of bio-based surfactant
Bio-based surfactants are synthesized via a chemical reaction, which is usually carried out under harsh conditions. The use of hazardous solvents and toxic acid or base catalysts sometimes creates undesired waste or by-products that are detrimental to the environment. Enzymes have the potential to play a significant role in the production of numerous bio-based surfactants, although they are not currently used on a large basis. Enzymes provide several advantages over chemical processing, notably in terms of improving process sustainability. The main drawbacks of enzymes are their relatively higher price compared to chemical catalysts as well as their slower reaction speeds. However, since energy costs are expected to rise, the need of sustainability (lower operating energy, less waste, and safer operating condition) is crucial. Despite the growing demand for bio-based surfactants, several challenges exist that restrain their further market growth and wider adoption. The main challenge is in the higher pricing of bio-based and biosurfactants as the biggest hurdle in meeting the requirement of priced sensitive Asian customers. Higher complexity and low-efficiency microbial fermentation process in biosurfactant manufacturing contribute to the high production cost and expensive capital cost investment. For example, the average price of sophorolipids is USD 34 per kilogram as compared to sodium dodecyl sulfate and amino acid surfactants that are priced at USD 1–4 per kilogram [86]. Nevertheless, a lower operating cost of USD 2530/ton for sophorolipids’ production is attainable through technological improvement such as integrated separation, which places sophorolipid surfactants at similar prices to other specialty surfactants [87]. Increased sustainability of biosurfactant alone without significantly higher performance is not well accepted, as the usual consumers will not be willing to pay a “green” premium for bio-based products. Therefore, lower cost improvement in biosurfactant manufacturing is fundamentally important to attain an economically sustainable process and assure future market continuity [85].
A second challenge is the dependency of biosurfactant demand on the volatility and economic downturn of downstream end-user industries. Industries that are applicable for biosurfactant applications, such as oil and gas, enhanced oil recovery, food industry, construction, textiles, paints, pharmaceutical, and detergents, are known to be susceptible to general macroeconomic performance. In addition, the COVID-19 pandemic further leads to disruption in the end-user industrial demand and sustainability concern on the raw material supply. The sustainability of raw materials is a major concern as these contribute up to 50% of the glycolipid production cost and 10–30% of the overall cost for other biosurfactant products. Purification accounts for 60% of the production cost, but this can be minimized for the case of biosurfactant application in crude forms, such as in an industrial environment [88]. However, for high-purity applications, improvement in downstream processing methods is needed to attain a competitive cost of production. Opportunity exists in developing a new technology solution that utilizes a low-cost raw material such as industrial wastes for biosurfactant production. However, this needs to consider the overall production impact factors that include the availability, stability, and variability of each component [88]. The economic viability criteria for biosurfactant production, therefore, include microorganism performance, bioreactor design, target market, purification process, product properties, production condition, fermentation cycle time, and production yield [89].
Additionally, several operation and control factors provide important handles to minimize biosurfactant production costs. Batch cycle optimization on the fermentation and purification process can reduce the idle time between batches and minimize chemical usage for equipment cleaning and energy use during sterilization. Productivity is the most important factor in the manufacturing economics of biosurfactant production at commercial scales [8]. Optimum batch-sequencing campaign minimizes startup and shutdown frequency to lower the production downtime that improves productivity. Lastly, biosurfactant product development will need to fulfill time-consuming and expensive legislative requirements, which restrain market growth [90]. These add a high cost of compliance to the product development cost that is incurred by biosurfactant manufacturers. Other market entry requirements include the biosurfactant products that are tested for long shelf life and the ability to maintain stable properties in the industrial environment [91].
4. Future outlook and prospect
The development of bio-based surfactants from renewable feedstocks is an attractive alternative to fossil-based surfactants with a significantly growing market attributed to their performance, biodegradability, biocompatibility, and nontoxicity [22, 33]. Additionally, advances in renewable technology, increased environmental concern, consumer awareness, and stringent regulatory requirements provide a continued push toward the demand of bio-based surfactants. Potential areas for use are growing fast, and valuable outcomes depend on whether the bio-based surfactants can be customized for specific applications along with if they can be produced at a price that will make them attractive alternatives to the fossil-based surfactants. The simultaneous design of bio-based surfactants for functional, economic, and environmental benefits will be taxing, but it will ensure the replacement of conventional fossil-based surfactants provided they can offer comparable or superior performance and a unique value proposition.
Presently, fossil-based surfactants are less expensive than bio-based surfactants [4, 92, 93]. However, this trend will likely change in the future, thereby increasing the prospects of bio-based surfactants. Feedstocks and how the bio-based surfactants are produced are the two key factors governing final product costs [4, 36, 94, 95]. To use renewable feedstock in the industry, they should be cost-effective, available in large quantities, and can effectively be converted to value-added surfactants [95]. Renewable feedstocks used as starting materials to produce surfactants usually face severe economic competition from their fossil-based counterparts. Surfactants comprised of hydrophilic head group and hydrophobic tail group, which are linked by a chemical bond generating an amphiphilic molecule that can be used directly or further modified. Surfactant design requires careful selection of the hydrophile and hydrophobe pair so that they can be easily synthesized with minimum purification and provide the desired properties for the intended application [4, 16, 92, 96]. Triglycerides, fatty acid methyl esters, fatty alcohols, fatty acids, and fatty amines are common examples of renewable hydrophobes used to produce bio-based surfactants. Sustainable hydrophilic headgroups can be designed using several molecules such as glycerol, carbohydrate feedstocks such as sucrose, glucose, organic acids, and amino acids [4, 36, 94, 95]. Additionally, the use of renewable feedstock for surfactant manufacturing also helps reduce CO2 emissions because once the bio-based surfactants degrade, they only release back the quantitative amount of the carbon used by the plant to produce the surfactants [36]. Other than the starting material mentioned above, the use of alternative substrates, such as agro-based industrial wastes or other suitable simple waste substrate, is gaining a lot of research interest and can lead to significant cost reduction [97].
Researchers are continually improving the cost-effectiveness of production methods as well as enhancing the current technologies with green manufacturing principles to convert renewable feedstocks into valuable and new biobased surfactants. Some of the key focus areas include developing biobased surfactants from cheaper feedstocks, higher performance catalysts, green solvents, optimized reaction processes, and effective downstream purification could entice the industry players and end-use customers to make the switch from fossil-based surfactants to biobased surfactants. Catalyst design is also crucial to ensure high selectivity of the processes to limit or eliminate the formation of by-products and to help push the reaction forward towards completion faster [98, 99, 100]. Other than that, researchers are looking into equipment miniaturization such as continuous reactors to help reduce the raw material consumption and effluent production. Process intensification is another aspect that could help to reduce the investment costs [99]. Research focusing on alternative or green solvents dedicated to the conversion of renewable feedstock to value-added products has led to several publications. Among those being researched include bio-based ionic liquids, deep eutectic solvents, bio-based solvents, CO2-switchable solvents and supercritical fluids [101, 102, 103].
In terms of market penetration of bio-based surfactants, customers tend to choose cost-effective surfactants. Despite much progress in technical knowledge, the large-scale production of bio-based surfactants using the methods described above is still limited. The commercial production of bio-based surfactants still faces many challenges that must be addressed for them to be economically viable. One major obstacle is the homogeneity and consistency of the feedstock, which can lead to inconsistency in the final bio-based surfactants. Variation in the surfactant properties and performance could lead to unsatisfactory properties. Thorough testing on the use of bio-based surfactants in place of fossil-based ones will also be needed to provide enough and convincing data on the merits of bio-based surfactants. It is hoped that these efforts will lead to broader use of bio-based surfactants in the future, offering enormous benefits such as excellent physicochemical properties, biodegradability, lower risk to human health, and minimum harm to the environment.
5. Conclusions
Surfactant manufacturers have introduced numerous new eco-friendly surfactant-based products to the market in the past few years. Increased consumer awareness, along with a responsibility for sustainable development, has resulted in the creation of several novel surfactant types based on renewable building blocks. These surfactants have improved biodegradation characteristics and low toxicity, making them a preferred alternative for innovative formulations in the industrial and consumer markets. However, these “drop-in” surfactant molecules, which aim to directly replace their petrochemical-based equivalents, face a huge challenge since prices must be as competitive as their fossil counterparts. Moreover, while several personal care and consumer product businesses have shown interest in 100% bio-based surfactants, only a few green premium products have been accepted into the market. More assessments and surveys need to be done to gauge consumer willingness to pay premium prices for other than commodity products. With increasing innovative formulations to meet consumer, legislative, and sustainability demands, it is obvious that the global demand for both petroleum- and bio-based surfactants will continue to grow, while manufacturers are challenged to balance cost-effective formulations with efficient performance.
\n',keywords:"bio-based surfactant, green surfactant, biosurfactant, renewable materials, sustainable surfactant",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80063.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80063.xml",downloadPdfUrl:"/chapter/pdf-download/80063",previewPdfUrl:"/chapter/pdf-preview/80063",totalDownloads:172,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:0,impactScoreQuartile:0,hasAltmetrics:0,dateSubmitted:"September 14th 2021",dateReviewed:"September 20th 2021",datePrePublished:"January 16th 2022",datePublished:null,dateFinished:"January 16th 2022",readingETA:"0",abstract:"Bio-based surfactants are surface-active compounds derived from oil and fats through the production of oleochemicals or from sugar. Various applications of bio-based surfactants include household detergents, personal care, agricultural chemicals, oilfield chemicals, industrial and institutional cleaning, and others. Due to the stringent environmental regulations imposed by governments around the world on the use of chemicals in detergents, as well as growing consumer awareness of environmental concerns, there has been a strong demand in the market for bio-based surfactants. Bio-based surfactants are recognized as a greener alternative to conventional petrochemical-based surfactants because of their biodegradability and low toxicity. As a result, more research is being done on producing novel biodegradable surfactants, either from renewable resources or through biological processes (bio-catalysis or fermentation). This chapter discusses the various types, feedstocks, and applications of bio-based surfactants, as well as the industrial state-of-the-art and market prospects for bio-based surfactant production. In addition, relevant technological challenges in this field are addressed, and a way forward is proposed.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80063",risUrl:"/chapter/ris/80063",book:{id:"10998",slug:null},signatures:"Nur Liyana Ismail, Sara Shahruddin and Jofry Othman",authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Recent progress in R&D and industrial production",level:"1"},{id:"sec_3",title:"3. Industrial challenge on bio-based surfactant",level:"1"},{id:"sec_3_2",title:"3.1 The economy and market trend of bio-based surfactant",level:"2"},{id:"sec_4_2",title:"3.2 The industrial challenges of bio-based surfactant",level:"2"},{id:"sec_6",title:"4. Future outlook and prospect",level:"1"},{id:"sec_7",title:"5. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Rosen MJ, Kunjappu JT. Surfactants and Interfacial Phenomena. 4th ed. 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Available from: https://www.cosmeticsandtoiletries.com/formulating/category/natural/How-Bio-Based-Surfactants-are-Turning-the-World-Green---570209271.html'},{id:"B75",body:'BASF Strengthens Its Position in Bio-Surfactants for Personal Care, Home Care and Industrial Formulators with Two Distinct Partnerships. BASF; 2021. Available from: https://www.basf.com/my/en/media/news-releases/global/2021/03/p-21-148.html'},{id:"B76",body:'Ajinomoto to Expand Amino Acid-Based surfactants [Internet]. Specialty Chemicals Magazine; 2019. Available from: https://www.specchemonline.com/index.php/ajinomoto-expand-amino-acid-based-surfactants'},{id:"B77",body:'Sironix Renewables Closes Seed Round to Scale Production of its Plant-Based Surfactant for Detergents, Cleaners & Shampoos [Internet]. GlobeNewswire; 2020. Available from: https://www.globenewswire.com/news-release/2020/09/16/2094579/0/en/Sironix-Renewables-Closes-Seed-Round-to-Scale-Production-of-its-Plant-based-Surfactant-for-Detergents-Cleaners-Shampoos.html'},{id:"B78",body:'Assessing the Sustainability and Performance of Green Surfactants [Internet]. IHS Markit; 2020. Available from: https://ihsmarkit.com/research-analysis/assessing-sustainability-and-performance-of-green-surfactants.html'},{id:"B79",body:'Bio-Based Chemicals—A 2020 Update. IEA Bioenergy Task 42 Report [Internet]. 2020. Available from: https://www.ieabioenergy.com/wp-content/uploads/2020/02/Bio-based-chemicals-a-2020-update-final-200213.pdf'},{id:"B80",body:'Market Research Future. 2021. Available from: https://www.reportlinker.com/p06081965/Biosurfactants-Market-Research-Report-by-Product-Type-by-Application-by-Region-Global-Forecast-to-Cumulative-Impact-of-COVID-19 [Accessed: 15 August 2021]'},{id:"B81",body:'Rocha e Silva NMP, Meira HM, FCA A, et al. Natural surfactants and their applications for heavy oil removal in industry. Separation and Purification Reviews. 2019;48(4):267-281. DOI: 10.1080/15422119.2018.1474477'},{id:"B82",body:'Drakontis CE, Amin S. Biosurfactants: Formulations, properties, and applications. Current Opinion in Colloid & Interface Science. 2020;48:77-90. DOI: 10.1016/j.cocis.2020.03.013'},{id:"B83",body:'Naughton PJ, Marchant R, Naughton V, et al. Microbial biosurfactants: Current trends and applications in agricultural and biomedical industries. Journal of Applied Microbiology. 2019;127(1):12-28. DOI: 10.1111/jam.14243'},{id:"B84",body:'Almeeida DG, Sores da Silva RCF, Luna JM, et al. Biosurfactants: Promising molecules for petroleum biotechnology advances. Frontiers in Microbiology. 2016;7:1718'},{id:"B85",body:'Silva RCFS, Almeida DG, Luna JM, et al. Applications of biosurfactants in the petroleum industry and the remediation of oil spills. International Journal of Molecular Sciences. 2014;15(7):12523-12542. DOI: 10.3390/ijms150712523'},{id:"B86",body:'Rodriguez-Lopez L, Rincon-Fontan M, Vecino X, et al. Extraction, separation and characterization of lipopeptides and phospholipids from corn steep water. Separation and Purification Technology. 2020;248. DOI: 10.1016/j.seppur.2020.117076'},{id:"B87",body:'Roelants S, Van Renterghem L, Maes K, Evaraert B, Vanlerberghe B, Demaeseneire S, et al. Mirobial biosurfactants: From lab to market. In: Press C, editor. Microbial Biosurfactants and Their Environmental and Industrial Applications. Boca Raton: CRC Press; 2019. DOI: 10.1002/9781315271767'},{id:"B88",body:'Singh P, Patil Y, Rale V. Biosurfactant production: Emerging trends and promising strategies. Journal of Applied Microbiology. 2019;126(1):2-13'},{id:"B89",body:'Santos DKF, Rufino RD, Luna JM, et al. Biosurfactants: Multifunctional biomolecules of the 21st century. International Journal of Molecular Sciences. 2016;17:401. DOI: 10.3390/ijms17030401'},{id:"B90",body:'Natural Surfactants Market. 2018. Available from: https://www.marketsandmarkets.com/Market-Reports/natural-surfactant-market-25221394.html [Accessed: 14 August 2021]'},{id:"B91",body:'Souza EC, Vessoni-Penna TC, De Souza Oliveira RP. Biosurfactant-enhanced hydrocarbon bioremediation: An overview. International Biodeterioration and Biodegradation. 2014;89:88-94. DOI: 10.1016/j.ibiod.2014.01.007'},{id:"B92",body:'Geys R, Soetaert W, Van Bogaert I. Biotechnological opportunities in biosurfactant production. Current Opinion in Biotechnology. 2014;30:66-72'},{id:"B93",body:'Marchant R, Banat IM. Microbial biosurfactants: Challenges and opportunities for future exploitation. Trends in Biotechnology. 2012;30(11):558-565'},{id:"B94",body:'Hayes DG. Fatty acids-based surfactants and their uses. In: Fatty Acids. Elsevier Inc.; 2017. pp. 355-384'},{id:"B95",body:'Bhadani A, Iwabata K, Sakai K, Koura S, Sakai H, Abe M. Sustainable oleic and stearic acid based biodegradable surfactants. RSC Advances. 2017;7(17):10433-10442'},{id:"B96",body:'Farias CBB, Almeida FCG, Silva IA, Souza TC, Meira HM, Soares da Silva RCF, et al. Production of green surfactants: Market prospects. Electronic Journal of Biotechnology. 2021;51:28-39. DOI: 10.1016/j.ejbt.2021.02.002'},{id:"B97",body:'Makkar RS, Cameotra SS, Banat IM. Advances in utilization of renewable substrates for biosurfactant production. AMB Express. 2011;1(1):1-19'},{id:"B98",body:'Marion P, Bernela B, Piccirilli A, Estrine B, Patouillard N, Guilbot J, et al. Sustainable chemistry: How to produce better and more from less? Green Chemistry. 2017;19(21):4973-4989'},{id:"B99",body:'Perathoner S, Centi G. Science and Technology Roadmap on Catalysis for Europe. Brussels: ERIC aisbl; 2016'},{id:"B100",body:'Lange JP. Renewable feedstocks: The problem of catalyst deactivation and its mitigation. Angewandte Chemie, International Edition. 2015;54(45):13187-13197'},{id:"B101",body:'Gu Y, Jérôme F. Bio-based solvents: An emerging generation of fluids for the design of eco-efficient processes in catalysis and organic chemistry. Chemical Society Reviews. 2013;42(24):9550-9570'},{id:"B102",body:'Jessop PG, Mercer SM, Heldebrant DJ. CO2-triggered switchable solvents, surfactants, and other materials. Energy & Environmental Science. 2012;5(6):7240-7253'},{id:"B103",body:'Eckert CA, Knutson BL, Debenedetti PG. Supercritical fluids as solvents for chemical and materials processing. Nature. 1996;383(6598):313-318'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Nur Liyana Ismail",address:"nurliyana.ismail@petronas.com.my",affiliation:'
PETRONAS Research Sdn. Bhd, Kajang, Selangor, Malaysia
PETRONAS Research Sdn. Bhd, Kajang, Selangor, Malaysia
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1. Introduction
Chronic hyperglycemia can lead to complications involving damage to the kidneys, retina, nervous system and cardiovascular system. In this chapter, we discuss the causes of hyperglycemia, including drug-induced hyperglycemia, highlighting the importance and approaches to prevention and management of hyperglycemia. We focus on the role and rationale for the use of metformin for the prevention of hyperglycemia, presenting the evidence that supports its use for this indication.
2. Hyperglycemia
Hyperglycemia, which literally means ‘high blood glucose’ levels, refers to the elevation of blood glucose concentrations above the normal range. Specifically, it refers to fasting blood glucose levels greater than 7.0 mmol/L (126 mg/dl) or 2-hour postprandial blood glucose levels greater than 11.0 mmol/L (200 mg/dl) [1].
2.1 Symptoms and complications
Mild, transient hyperglycemia is largely asymptomatic. However, prolonged uncontrolled hyperglycemia is associated with various symptoms including the classic hyperglycemic triad of polyuria, polydipsia, and polyphagia, as well as blurred vision, dehydration, weight changes (gain or loss), generalized fatigue, abdominal discomfort, nausea, vomiting and muscle cramps [1, 2]. Complications arise when the hyperglycemia is severe and/or persists over an extended period. Frequent infections, erectile dysfunction and poor wound healing are associated with prolonged hyperglycemia. Chronic hyperglycemia can also lead to many serious life-threatening complications involving damage to the kidneys (nephropathy), retina (retinopathy), nervous system (peripheral neuropathy) and cardiovascular system (myocardial infarction, stroke) [1, 2, 3, 4, 5].
2.2 Causes of hyperglycemia
Blood glucose levels reflect the dynamic balance between, on the one hand, dietary glucose absorption and hepatic glucose production and, on the other hand, glucose uptake and utilization by peripheral tissues. Except for dietary glucose absorption, these complex and interrelated processes are under the control of the hormone insulin and, to a lesser extent, other counter-regulatory hormones such as glucagon, catecholamines, cortisol and growth hormone [1, 6]. Hyperglycemia arises from an imbalance in these processes that determine blood glucose levels.
The greatest quantitative determinant for hyperglycemia is dysfunction in pancreatic islet cell activity which affects insulin release from the pancreas in response to. The pathophysiology of hyperglycemia also entails a resulting degree of insulin resistance and impairment in homeostatic glucose regulation. Insulin resistance results in decreased uptake of glucose by insulin-sensitive tissues as well as a consequential increase in endogenous glucose production. This all leads to hyperglycemia [7]. The elevation of blood glucose levels during the fasting state is directly proportional to the increase in hepatic glucose production while that of the postprandial state is connected to insufficient suppression of glucose output plus a defect in the stimulation of insulin hormone on recipient tissues like skeletal muscle [8].
The progression of this imbalance in blood glucose homeostasis over time leads to the development of diabetes, a chronic disease affecting glucose metabolism that occurs due to either insufficient production of insulin by the pancreas, or inadequate response by tissues to insulin [9]. The development of diabetes can be delayed or prevented by targeting the early prevention and/or reversal of hyperglycemia, as well as by inhibiting the development of hyperinsulinemia-induced insulin resistance [10]. This would also delay progression of prediabetic states to diabetes [11].
In addition to diabetes, there are a myriad of other causes of hyperglycemia, i.e., non-diabetic hyperglycemia. Disorders that compromise pancreatic function (pancreatic cancer, cystic fibrosis, chronic pancreatitis, etc.) or affect the glucose counter-regulatory hormones (pheochromocytoma, acromegaly, Cushing syndrome) cause hyperglycemia. Transient hyperglycemia may arise consequent to abnormally high carbohydrates in the diet, dextrose infusion and total parental nutrition. Acute or serious illness or injury may also bring about transient hyperglycemia referred to as stress hyperglycemia or hospital-related hyperglycemia [1, 12].
Medicines may also induce hyperglycemia [1, 6, 13].
2.3 Drug-induced hyperglycemia
Drug-induced hyperglycemia refers to the clinically relevant elevation of blood glucose levels caused by drugs [13]. Whereas drug-induced hyperglycemia is often mild and asymptomatic, severe hyperglycemia may occur particularly in predisposed patients, such as those with pre-existing pancreatic dysfunction or insulin resistance. Drug-induced hyperglycemia can occur in adults and children alike, and certain patient factors are known to increase the risk of drug-induced hyperglycemia, such as obesity, sedentary lifestyle, stress, illness, history of gestational diabetes, or a family history of diabetes [6, 14].
Many classes of drugs have been implicated in causing hyperglycemia via various mechanisms. Some drugs cause hyperglycemia by reducing insulin production/secretion (glucocorticoids, β-receptor antagonists, thiazide diuretics, calcium-channel blockers, phenytoin, pentamidine, calcineurin inhibitors, protease inhibitors), including by direct damage to pancreatic cells (glucocorticoids, pentamidine, statins). Glucocorticoids, β-receptor antagonists and thiazide diuretics also promote hepatic glucose production and reduce insulin sensitivity. Other classes of drugs that reduce peripheral tissue sensitivity to insulin include atypical antipsychotics, antidepressants, oral contraceptives, statins, nucleoside reverse transcriptase inhibitors and protease inhibitors [1, 6, 14, 15, 16]. Hyperglycemia is one of the common adverse effects of the anticancer agent L-asparaginase, which inhibits insulin synthesis by depleting available asparagine in pancreatic cells in addition to impairing insulin receptor activity and promoting peripheral tissue resistance to insulin [14]. Monoclonal antibodies such as nivolumab and pembrolizumab may cause severe hyperglycemia by triggering the autoimmune-mediated destruction of pancreatic cells [17, 18]. β2-receptor agonists cause hyperglycemia by promoting hepatic and muscle glucose production [19]. The various mechanisms of drug-induced hyperglycemia and the classes of drugs implicated are shown in Figure 1.
Figure 1.
Mechanisms of drug-induced hyperglycemia and implicated classes of drugs.
The overall occurrence of drug-induced hyperglycemia is not known and would obviously vary between individual drugs. There is a lack of data on the burden of drug-induced hyperglycemia for specific drugs, and a few studies have attempted to address this gap. For example, the incidence of corticosteroid-related hyperglycemia in patients treated with high dose corticosteroids has been estimated to be in excess 50% [20, 21]. Comparably high prevalence has been reported for clozapine [22]. These and other similar findings strongly suggest that the risk of drug-induced hyperglycemia (alongside the risk of new-onset diabetes) is real.
The onset of drug-induced hyperglycemia varies on the medication administered. At the time of or shortly after initiating corticosteroids, blood glucose levels may be altered, whereas patients on hydrochlorothiazide may not experience altered levels for weeks or longer, depending on the dose given. In regard to second generation antipsychotics (SGAs), a consensus statement developed by the American Diabetes Association (ADA) in conjunction with other medical organizations recommends monitoring fasting blood glucose for 12 weeks after initiation of therapy and annually thereafter in those without diabetes. However, cases involving hyperglycemic crises have been reported within weeks of starting SGAs [23].
3. Prevention and management of hyperglycemia
The common medical occurrence of hyperglycemic states has yet to be given the due attention it deserves, considering the numerous consequences it bears to patients and the healthcare fraternity. The existing reality of numerous patients suffering from hyperglycemia of varied cause provides an overwhelming patient load, unmatched by the number of specialized providers. However, the management of hyperglycemia has continually posed a great challenge mainly from a lack of standardized protocols [24]. Currently, lack of knowledge and consensus on strategies of management play a significant role in its mismanagement.
Insulin resistance and the resulting compensatory hyperinsulinemia is considered to preclude the development of type 2 diabetes. Hyperglycemia prophylaxis is thus highly attractive based on the numerous socio-economic benefits it confers to patients and the healthcare system. Several studies have demonstrated the advantages gained from preventing elevations of blood glucose levels across a divergent patient portfolio. Research has broadly focused on management of hyperglycemia regardless of the cause, which underlies the common pathways involved in the development of hyperglycemia.
3.1 The role of insulin
The primary strategy employed in hyperglycemia management is insulin [25]. Consensus arrived at by ADA and European Association for the Study of Diabetes (EASD) outline the management of hyperglycemia in type 2 diabetes patients. These guidelines have also been adopted in the prevention of hyperglycemia from other causes, including drug-induced hyperglycemia. The guidelines recommend the use of insulin in all hospitalized patients, with discontinuation of oral hypoglycemic medication [26, 27]. Stoppage of the drugs is on the basis that majority of hospitalized patients present with concurrent conditions and/or physiological dysfunctions that tend to contraindicate continued use of these medications if already prescribed. The pharmacokinetics of oral medication, which tend to have a slow onset of action, disallows for rapid dose adjustment to changing patient needs [28]. Therefore, it is recommended that critically ill patients be treated with a continuous insulin infusion while non-critically ill patients are initiated on subcutaneous (SC) insulin. An individualized dose adjustment for insulin is advised across major studies [26, 29]. Resumption of oral diabetic agents (ODA) when transitioning from inpatient to outpatient setting, with careful consideration given to previous insulin dosing, is advised upon successful treatment. A study involving patients without diabetes recommended the administration of intravenous (IV) insulin infusion in patients with serum blood glucose level values of greater than 10 mmol/L, with a target of achieving serum blood glucose levels of 7.8–10 mmol/L in non-critical settings and less than 7.8 mmol/L in an outpatient setting [30].
Despite numerous recommendations, challenges faced by providers during insulin administration cannot be overlooked. The biggest impediment to insulin use in management of drug-induced hyperglycemia in the affected population is the unavoidable side effect of hypoglycemia [31]. Unfortunately, insulin treatment is the most common risk factor for inpatient hypoglycemia. The incidence of hypoglycemia is approximately 30% in elderly patients, in spite of using low dose insulin and oral diabetic agents [28]. This is associated with increased mortality rate and prolonged hospital stays. Hence, constant monitoring of blood glucose levels is necessary.
Dose adjustments using patients’ weight is perceived to be safe and effective as long as close monitoring is done. However, this is not always feasible, let alone practical with many patients. So too is the recommendation of individualizing glycemic targets for patients based on clinical status, risk of hypoglycemia and patient comorbidities, no matter the benefit it confers. This is because the number of patients with drug-induced hyperglycemia cannot be matched to the number of specialized health care workers required to meet this need.
Herein lies the difficulty as many patients are unable to achieve the close monitoring desired, let alone manage the expected side effects in a home-based set up. Even in hospitalized patients, lack of protocols for dose adjustment poses a hindrance in adequate control of elevated blood glucose levels. Hypoglycemia presents a consequential effect that should be carefully considered in hyperglycemia management. Any chosen medication, in addition to lifestyle interventions, should ideally be one that is safe, effective, economical and with minimal side effects.
3.2 The role of oral antidiabetic medications
Non-insulin medications provide a practical alternative to achieving glycemic control. These agents may also confer a non-glycemic benefit whilst regulating the fluctuations in blood glucose levels. Alternatives among non-insulin medication include metformin, sulphonylureas, glinides, thiazolidinediones, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium–glucose cotransporter2 (SGLT2) inhibitors.
However, the side effects of each of these agents must also be considered. For example, SGLT2 inhibitors reduce blood glucose levels by preventing proximal tubular reabsorption in the kidney. This has been shown to effectively reduce glycated hemoglobin A1c (HbA1c) levels by 0.6–1.0%. They are also associated with a low risk of hypoglycemia. However, the dehydration side effects make these agents contraindicated in renal dysfunction. They also bear an increased risk of urinary and genital tract infections and are related with the development of diabetic ketoacidosis among diabetic patients [32]. Such a profile tends to limit the use of these agents. Metformin use is contraindicated in the presence of any possible indication for iodinated contrast media and in renal insufficiency while thiazolidinediones are associated with fluid retention. On the other hand, sulfonylureas and glinides result in hypoglycemia in most patients while GLP-1 receptor antagonists can cause nausea and hence need to be withheld in critical patients. In spite of the many side effects of oral diabetic agents and the recommendation of using insulin as first line, recent studies have leaned towards the adoption of the oral diabetic agents. The drug most endorsed based on clinical evidence has been metformin [33].
4. Metformin for the prevention of hyperglycemia
4.1 Introduction and rationale
The pathophysiology of hyperglycemia entails a degree of insulin resistance and results in decreased uptake of glucose by insulin-sensitive tissues as well as a consequential increase in endogenous glucose production [7]. Dysfunction in the activity of pancreatic islet cells affects insulin release in response to rising blood glucose levels. Targeting the prevention and/or reversal of dysglycemia and insulin resistance is the principal behind preventing the development of hyperglycemia [11]. Any agent used in prevention of hyperglycemia must therefore target these pathways, thereby partially or completely eliminating its development.
Metformin can rightfully be considered for hyperglycemia prevention and treatment in cases of insulin resistance. Metformin is a first-line agent in treatment of type 2 diabetes mellitus. Recent studies have shown it confers a greater benefit to patients than the other oral diabetic agents, which has led to its recommendation for use in the prevention of hyperglycemia and prediabetes in at risk patients [34, 35, 36].
4.2 Mechanisms of action/pharmacodynamics
Metformin prevents hyperglycemia by hastening the clearance of glucose [37, 38]. It causes a reduction in hyperglycemia and hyperinsulinemia [39]. This facilitates a consequent decline in high insulin and high blood glucose levels, with no effect on insulin secretion. The primary mechanism involved in lowering blood glucose levels is through improving hepatic and peripheral tissue sensitivity to insulin [40]. It inhibits the production of glucose by the liver whilst enhancing uptake of circulating glucose and its utilization in peripheral tissues such as muscle and adipose tissue.
Hepatic gluconeogenesis is an energy-demanding process in which synthesis of one molecule of glucose from lactate or pyruvate requires four molecules of ATP and two molecules of GTP. Metformin suppresses hepatic gluconeogenesis by causing a reduction of cellular ATP levels [41]. Molecularly, metformin appears to inhibit mitochondrial respiration. The resulting shift in cellular energy balance increases the activity of AMP-activated protein kinase (AMPK), which promotes the action of insulin and reduces hepatic gluconeogenesis [42]. AMPK acts as a cell energy sensor: it plays a role in energy balance at the cellular and body level by adapting to changes in the concentration of AMP/ADP relative to ATP [43]. Upon activation by a decrease in cellular energy levels, AMPK initiates a change from anabolic to catabolic pathways that consume ATP. This stimulates the uptake and use of glucose and oxidation of fatty acids, in addition to the suppression of hepatic glucose production. Metformin’s’ inhibition of the mitochondrial complex is the basis of its effect as observed through the change in the ratios of AMP/ATP or ADP/ATP after its administration [44]. Multiple studies have demostrated that one of the mechanisms of action of metformin is the disruption of mitochondrial complex I [45, 46].
Metformin may also modulate the gut-brain-liver axis through the activation of a duodenal AMPK-dependent pathway, as has been demonstrated in rats. This effect involves activation of protein kinase A (Pka) by GLP-1 in duodenal enterocytes, and results in suppression of hepatic glucose production [47]. It has been shown that glucocorticoid therapy leads to changes in the activation of AMPK in Cushing’s syndrome patients and in vitro in human adipocytes, effects that were reversed with metformin in human adipocytes. These indicate the likelihood of converse effects of steroids and metformin in the AMPK signaling pathway, as well as the overriding of steroid effects by metformin [44, 48]. Supporting studies demonstrate that steroid-related increase in glucose levels can be prevented with an AMPK activator [49].
Another postulated mechanism of action for metformin is by causing an increase in circulating cyclic adenosine monophosphate (cAMP) which in turn opposes the hyperglycemic action of glucagon [42, 50]. Metformin has also been postulated to increase the concentration of Glucagon-like peptide-1 (GLP-1) by enhancing site production as well as subsequently decreasing its degradation in circulation and specific tissues via inactivation of the enzyme dipeptide peptidase-4 (DPP-4). Additionally, metformin may induce up regulation of GLP-1receptors on beta cell surfaces of the pancreas. This can aid in ameliorating the beta cell dysfunction associated with hyperglycemia via the enhancement of the role of GLP-1 on glucose dependent release of insulin [11].
4.3 Metformin prevents hyperglycemia and hyperinsulinemia
Metformin can rightfully be considered for hyperglycemia prevention and treatment in cases of insulin resistance. Metformin has been identified as a first line agent in treatment of type 2 diabetes mellitus. Recent studies have shown that it confers a greater benefit to patients than the other oral diabetic agents, which has led to its recommendation for use in the prevention of prediabetes in at risk patients [34, 35, 51]. Presently though, only a few nations have formally adopted this proposal such as Poland, Philippines and Turkey but many may adopt it in the near future based on the emerging evidence [11]. Metformin overrides most of the factors that contribute to poor glycemic management like inaccessibility to medicine and fear of developing hypoglycemia. This improves patient perception on its use regardless of the minimal side effects. In addition, it has been demonstrated to confer long term benefit to those who use it prophylactically. A study that followed up patients from a diabetes prevention program after 15 years found that the metformin treatment arm had a 17% lower incidence for developing type 2 diabetes than the placebo arm. This was determined using the HbA1c parameter, in which 36% of the patients had a risk reduction for diabetes development [34].
In a prospective observational study in persons with normal glucose tolerance and hyperinsulinemia, a dose of 2.55 ± 0.2 g/day of metformin restored physiological insulin secretion by decreasing fasting and post-glucose load hyperinsulinemia in the oral glucose tolerance test (OGTT). Over the observation period, the effect of metformin on the reduction of hyperinsulinemia increased over time, peaking after 1 year of treatment. The ability to lower fasting blood glucose levels also improved with time. Fasting blood glucose levels reached normoglycemic range at 3 months and remained so until the end of the 1 year observation period, with no development of hypoglycemia [39]. A substantial decrease in hyperinsulinemia from high blood glucose levels has also been reported in metformin-treated patients based on an increase in the uptake of glucose [52]. The enhancement of insulin action reduces the load on the beta cells in insulin secretion thus can aid in ameliorating the beta cell dysfunction to an extent; this confers an advantage to patients predisposed to developing hyperglycemia.
In addition, a randomized controlled study showed that there was no significant difference in blood glucose levels between critically ill patients receiving 1000 mg of metformin daily versus a similar spectrum of patients receiving 50 International Units (IU) of regular insulin. Furthermore, metformin-treated patients had blood glucose levels subside to near-normal range [40]. The targeted desired blood glucose levels were achieved with metformin after three days while insulin failed to do the same.
4.4 Metformin for drug-induced hyperglycemia
In acute lymphoblastic leukemia patients with drug-induce hyperglycemia, metformin monotherapy controlled blood glucose in 12 out of 17 patients, without the need for insulin using a median dose of 1000 mg/day for a median of 6 days. Blood glucose levels never exceeded 11.1 mmol/L in 8 of the 12 patients. The one patient who developed hyperglycemia during relapse re-induction for leukemia treatment was effectively controlled using metformin alone [53]. Three of the patients given insulin therapy due to high blood glucose levels were eventually weaned off insulin to metformin alone. Additionally, in a controlled trial consisting of non-diabetic patients on glucocorticoids, metformin prevented an increase of 2-hour glucose AUC with, signifying glucose tolerance preservation. No changes in baseline and after 4 weeks metformin treatment was seen with the 2-hour glucose AUC whereas this parameter increased in the placebo group [54].
Similarly, the effect of metformin on prednisone-induced hyperglycemia (PIH) was observed on fasting and 2-hour post prandial glucose levels in hematological cancer patients. The fasting blood glucose readings indicated a proportion of prednisone-induced hyperglycemia of 72.7% and 14.3% in the control and treatment groups respectively. The proportion was slightly lower while using the 2-hour post prandial glucose, in which 54.5% of participants in the control group developed prednisone-induced hyperglycemia while none developed prednisone-induced hyperglycemia in the treatment group. Patients in the control group had 16 (95% CI 1.3–194.6) times the odds of developing prednisone-induced hyperglycemia compared to patients in the treatment group. Double daily dosing (1700 mg twice daily) was more effective in preventing prednisone-induced hyperglycemia [21]. This is supported by other studies that show that that a daily dose of metformin 1500 mg contributes to 80–85% glucose lowering effects [55].
4.5 Metformin for hyperglycemia: risks and benefits
The limitations attached to the full exploitation of metformin use include its relative contraindications in many hospitalized patients who present with comorbidities like renal insufficiency or unstable hemodynamic status. Metformin is contraindicated if serum creatinine is ≥133 mmol/L in men or ≥ 124 mmol/L in women. Emerging evidence shows that the established cut-off points for renal safety may be overly restrictive [56]. It has been argued that there is a need to relax these cut-offs and policies to allow use of this drug to patients with stable chronic kidney disease characterized by mild–moderate renal insufficiency [57, 58, 59].
The associated risk of lactic acidosis tends to deter the use of metformin in majority of the comorbid patients on drugs that predispose to the development of hyperglycemia. However, the studies that made such recommendations used a small percentage of the patient population, thus limiting the extrapolation of these recommendations to the greater public [60]. Fortunately, the incidence of metformin-induced lactic acidosis is rare and can be significantly reduced in at-risk patients by observing the necessary precautions [27, 56]. Other factors may also play a greater role in in being predictors of acidosis, such as dehydration, severe heart and renal failure. Thus, its benefits for use outweigh the potential risk of lactic acidosis.
Supporting evidence on avoidance of metformin use in certain cases is poor and inconsistent such as in patients undergoing radio-contrast imaging which theoretically predisposes patients to media-induced nephropathy, increasing the risk of lactic acidosis [56].
The benefits of metformin in the prevention of hyperglycemia are unmatched despite its list of contraindications. This has facilitated its expanded use based on its well-founded glycemic effects as well as numerous benefits conferred such as the beneficial effect on reduction of development of cardiovascular risk factors [61]. It confers good glycemic management that yields a substantial and enduring decrease in the onset and progression of micro vascular complications [60].
Moreover, large based clinical trials and systematic reviews have shown its beneficial effect of enhancing weight loss, even the weight loss associated with medicaments like antipsychotic agents [62, 63].
5. Conclusions
In summary, the suppression of glucose production by metformin’s direct effect plus the enhancement of hepatic insulin signaling will curb the development of drug-induced hyperglycemia. Metformin has been shown to reduce the incidence of hyperglycemia-related complications such as diabetes and risk factors for cardiovascular disease in patients with impaired glucose tolerance and fasting blood sugar [11, 64, 65]. This has led to its endorsement of use in patients with high risk of developing the aforementioned conditions [36].
\n',keywords:"hyperglycemia, hyperinsulinemia, insulin, metformin, glucose",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/78058.pdf",chapterXML:"https://mts.intechopen.com/source/xml/78058.xml",downloadPdfUrl:"/chapter/pdf-download/78058",previewPdfUrl:"/chapter/pdf-preview/78058",totalDownloads:137,totalViews:0,totalCrossrefCites:0,dateSubmitted:"July 3rd 2021",dateReviewed:"July 9th 2021",datePrePublished:"October 4th 2021",datePublished:"December 15th 2021",dateFinished:"August 12th 2021",readingETA:"0",abstract:"Hyperglycemia is the elevation of blood glucose concentrations above the normal range. Prolonged uncontrolled hyperglycemia is associated with serious life-threatening complications. Hyperglycemia arises from an imbalance between glucose production and glucose uptake and utilization by peripheral tissues. Disorders that compromise pancreatic function or affect the glucose counter-regulatory hormones cause hyperglycemia. Acute or serious illness or injury may also bring about hyperglycemia, as can many classes of drugs. Metformin lowers blood glucose levels by inhibiting the production of glucose by the liver whilst enhancing uptake of circulating glucose and its utilization in peripheral tissues such as muscle and adipose tissue. Metformin suppresses hepatic gluconeogenesis by inhibiting mitochondrial respiration and causing a reduction of cellular ATP levels. Metformin may also modulate the gut-brain-liver axis, resulting in suppression of hepatic glucose production. Metformin also opposes the hyperglycemic action of glucagon and may ameliorate pancreatic cell dysfunction associated with hyperglycemia. Metformin is therefore recommended for use in the prevention of hyperglycemia, including drug-induced hyperglycemia, in at risk patients. The benefits of metformin in the prevention of hyperglycemia are unmatched despite its contraindications.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/78058",risUrl:"/chapter/ris/78058",signatures:"Lucy A. Ochola and Eric M. Guantai",book:{id:"10735",type:"book",title:"Metformin",subtitle:"Pharmacology and Drug Interactions",fullTitle:"Metformin - Pharmacology and Drug Interactions",slug:"metformin-pharmacology-and-drug-interactions",publishedDate:"December 15th 2021",bookSignature:"Juber Akhtar, Usama Ahmad, Badruddeen and Mohammad Irfan Khan",coverURL:"https://cdn.intechopen.com/books/images_new/10735.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83969-606-0",printIsbn:"978-1-83969-605-3",pdfIsbn:"978-1-83969-607-7",isAvailableForWebshopOrdering:!0,editors:[{id:"345595",title:"Prof.",name:"Juber",middleName:null,surname:"Akhtar",slug:"juber-akhtar",fullName:"Juber Akhtar"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"418482",title:"Dr.",name:"Lucy A.",middleName:null,surname:"Ochola",fullName:"Lucy A. Ochola",slug:"lucy-a.-ochola",email:"lucyochola@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"420882",title:"Dr.",name:"Eric M.",middleName:null,surname:"Guantai",fullName:"Eric M. Guantai",slug:"eric-m.-guantai",email:"eguantai@uonbi.ac.ke",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Nairobi",institutionURL:null,country:{name:"Kenya"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Hyperglycemia",level:"1"},{id:"sec_2_2",title:"2.1 Symptoms and complications",level:"2"},{id:"sec_3_2",title:"2.2 Causes of hyperglycemia",level:"2"},{id:"sec_4_2",title:"2.3 Drug-induced hyperglycemia",level:"2"},{id:"sec_6",title:"3. Prevention and management of hyperglycemia",level:"1"},{id:"sec_6_2",title:"3.1 The role of insulin",level:"2"},{id:"sec_7_2",title:"3.2 The role of oral antidiabetic medications",level:"2"},{id:"sec_9",title:"4. Metformin for the prevention of hyperglycemia",level:"1"},{id:"sec_9_2",title:"4.1 Introduction and rationale",level:"2"},{id:"sec_10_2",title:"4.2 Mechanisms of action/pharmacodynamics",level:"2"},{id:"sec_11_2",title:"4.3 Metformin prevents hyperglycemia and hyperinsulinemia",level:"2"},{id:"sec_12_2",title:"4.4 Metformin for drug-induced hyperglycemia",level:"2"},{id:"sec_13_2",title:"4.5 Metformin for hyperglycemia: risks and benefits",level:"2"},{id:"sec_15",title:"5. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Mouri Mi, Badireddy M. Hyperglycemia. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2021 [cited 2021 Jun 17]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK430900/'},{id:"B2",body:'Utiger RD. 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Evidence that metformin exerts its anti-diabetic effects through inhibition of complex 1 of the mitochondrial respiratory chain. Biochem J [Internet]. 2000 Jun 7;348(3):607-14. Available from: https://doi.org/10.1042/bj3480607'},{id:"B47",body:'Duca FA, Côté CD, Rasmussen BA, Zadeh-Tahmasebi M, Rutter GA, Filippi BM, et al. Metformin activates a duodenal Ampk–dependent pathway to lower hepatic glucose production in rats. Nat Med [Internet]. 2015;21(5):506-11. Available from: https://doi.org/10.1038/nm.3787'},{id:"B48",body:'Christ-crain M, Kola B, Lolli F, Fekete C, Seboek D, Feltrin D, et al. AMP-activated protein kinase mediates glucocorticoid- induced metabolic changes : a novel mechanism in Cushing’ s syndrome. 22(6):1672-83'},{id:"B49",body:'Nader N, Sin S, Ng M, Lambrou GI, Pervanidou P, Wang Y, et al. 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Use of metformin in the setting of mild-to-moderate renal insufficiency. Diabetes Care. 2011;34(6):1431-7'},{id:"B60",body:'Davies MJ, D’Alessio DA, Fradkin J, Kernan WN, Mathieu C, Mingrone G, et al. Management of hyperglycemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the european association for the study of diabetes (EASD). Diabetes Care. 2018;41(12):2669-701'},{id:"B61",body:'Strack T. Metformin: a review. Drugs Today (Barc). 2008 Apr;44(4):303-14'},{id:"B62",body:'Diabetes N, Clearinghouse I. Diabetes Prevention Program (DPP)'},{id:"B63",body:'Björkhem-Bergman L, Asplund AB, Lindh JD. Metformin for weight reduction in non-diabetic patients on antipsychotic drugs: a systematic review and meta-analysis. J Psychopharmacol. 2011 Mar;25(3):299-305'},{id:"B64",body:'Temprosa M. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. 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. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). 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:"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:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{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:null},{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:"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:"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:"357085",title:"Mr.",name:"P. 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He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. 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His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). 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Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. 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/332100",hash:"",query:{},params:{id:"332100"},fullPath:"/profiles/332100",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)}()