Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
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This achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
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We are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
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Thank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
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\n
1. Introduction
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The liver is a complex organ at the anatomical and physiological level, associated with numerous vital functions, including protein and urea synthesis, and regulation of the energy metabolism. It is also the main organ responsible for xenobiotics metabolism, the reason why it is often the first to contact with their metabolic products and most of the toxins, being one of the main targets of the toxicity caused by those drugs. Indeed, drug-induced liver injury (DILI) is responsible for nearly 60% of the cases of acute liver failure [1]. Despite the increased awareness for DILI, its absolute frequency is not decreasing demonstrating the need for evaluating drugs’ hepatotoxicity and for smarter in vitro tools to increase predictivity and to represent the patients at a population level within the drug development process [2].
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Traditional in vitro models for hepatotoxicity studies include monolayer cell cultures (2D) and suspensions of human hepatoma cell lines or primary hepatocytes [3] (Table 1). The primary cultures of human hepatocytes present the most representative phenotypic and functional profile, but exhibit a short-term viability, with a quick loss of several cellular functions within the first days in culture [3], including a loss in CYP-dependent monooxygenase activities, significant downregulation of phase I and phase II enzymes, stress-related upregulation of acute-phase-response enzymes and delocalization of transporter proteins. Rat primary hepatocytes, on the other hand, have also the disadvantage of presenting interspecies differences on the biotransformation of xenobiotics [4]. To overcome such limitations, different human hepatoma cell lines have been established. These can provide a high quantity of human cells and are cost-effective. However, those benefits are often surpassed by a number of other limitations, namely their disease-like state, lower metabolizing capacity and incomplete biotransformation profile [5]. As a result, the drawbacks of the currently available models sustain the need for relevant human in vitro hepatotoxicity models that better resemble the in vivo microphysiology.
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Model
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Advantages
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Limitations
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Ref.
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\n\n\n
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Isolated hepatocytes
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Obtained from whole livers or biopsies Functions close to those of hepatocytes in vivo\n Enable interspecies and pharmacogenomics studies Representative of different lobular subpopulations
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Viability: 2–4 h No bile canaliculus Low availability of human tissue Interspecies differences
Obtained from whole livers or biopsies Functions close to those of hepatocytes in vivo\n Longer viability than isolated tissue Induction/inhibition of drug-metabolizing enzymes Enable interspecies and pharmacogenomics studies
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Viability: 2–4 days Early phenotypic changes Altered bile canaliculi Difficult recovery of cells and maintenance of function upon cryopreservation Low availability of human tissue Interspecies differences
Advantages and limitations of traditional in vitro models for hepatotoxicity studies.
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Stem cell-based hepatic models represent an important alternative to the conventional hepatic in vitro systems. This chapter integrates the state of the art of human umbilical cord matrix (UCM-MSCs) or blood (UCB-MSCs) hepatic differentiation and its role as an in vitro alternative model for biotransformation and hepatotoxicity studies.
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1.1 Umbilical cord-derived mesenchymal stem cells as an alternative stem cell source for generating hepatocyte-like cells
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Recent developments in stem cell technology have paved the way for identifying novel candidate sources of cells as an attempt to increase the availability of functional human liver-like cells, as well as improving the reliability and the accuracy of drug screening in vitro [10, 11]. In fact, stem cells (SCs) are of human origin and possess the ability to self-replicate and differentiate into all cell types in the body. Regarding the liver, the differentiation strategies to derive hepatocyte-like cells (HLCs) from stem cells are mostly based on mimicking the development of hepatocytes in vivo and include the addition of soluble medium factors, the reconstruction of the cell-matrix and the intercellular interactions through the use of alternative cell culture strategies and the assessment of cell fate via genetic modifications and epigenetic modulation [12]. Yet, the major challenges on producing stem cell-derived HLCs in vitro are still the immature phenotype of the HLCs [13], the lack of defined endpoints of hepatic differentiation and maturation [14], the absence of relevant positive controls [15] and defining the best stem cell source.
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Several approaches have been developed for deriving HLCs from human embryonic stem cells (hESCs) [7, 16, 17], induced pluripotent stem cells (iPSCs) [7, 18, 19, 20], bipotent liver progenitor cells [21] and mesenchymal stem cells (MSCs) [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]. hESCs display various advantages for clinical applications when compared to immortalized cell lines and primary cell cultures, since they are genetically normal (diploid) and do not possess the high donor-dependent variability observed in primary cells [43]. The use of these cells raises, however, various ethical, technical and legal concerns [44]. Other types of SCs, like iPSCs and adult stem cells, do not give rise to those ethical issues. Nevertheless, there is some evidence suggesting that iPSC therapy has the risk of leading to tumor formation, raising safety concerns that should be addressed by researchers to ensure the viability of this therapy [44]. iPSCs and hESCs also reveal a high risk for teratoma formation in vivo [45], exhibiting high genomic instability, through the accumulation of mutations [46], a concern that is not raised by neonatal MSCs [47]. MSCs, on the other hand, reveal many advantages over the other SCs, which make them suitable for toxicological and regenerative medicine applications. They can be isolated from non-controversial sources at a relatively low cost, do not require feeder layers and high serum conditions, reveal a satisfactory proliferative capacity in vitro and are less immunogenic [23, 26, 34, 48, 49, 50, 51]. Interestingly enough, iPSC-derived MSCs have also been reported as less immunogenic [52].
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MSC classification is still controversial, being commonly defined as adult, fetal or neonatal MSCs depending on its origin. Independently of their origin, MSCs are characterized according to the International Society for Cellular Therapy (ISCT) criteria [53]. The position paper published by the ISCT states that the isolated cells must display: (a) plastic adherence when maintained in standard two-dimensional (2D) culture; (b) specific surface protein expression, typically confirmed by flow cytometry where a minimum of 95% of the cell population must portray the expression of surface markers CD105, CD73 and CD90, whereas the markers CD45, CD34, CD14 or CD11b, CD79α or CD19 and HLA-DR should show less than 2% expression among the isolated cells; and (c) tri-lineage differentiation capacity of the isolated cells, that is, these cells must be shown to differentiate to osteoblasts, adipocytes and chondroblasts using standard in vitro tissue culture-differentiating conditions [53].
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MSCs are pluripotent stem cells that can be obtained from adult tissues like adipose tissue, brain, bone marrow and pancreas [54], but can also be isolated from neonatal tissues, like fetal-blood, amniotic sac and fluid, placenta [55] and extra-embryonic tissues such as the umbilical cord (UC-MSCs) [56]. The umbilical cord, in particular, represents a source of MSCs that is readily available as it is discarded as a medical waste after birth [57]. Herein, MSCs can be isolated from the blood (UCB-MSCs) or from the matrix (UCM-MSCs) through several isolation processes, namely by enzymatic, explants or mixed enzymatic-explant digestion methods [58, 59] that result in different yields [60, 61, 62].
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Depending on their origin, MSCs may present variations in morphology, proliferation potential, growth rates and differentiation capacity as well as their regenerative potential. A significant advantage of the MSCs derived from neonatal and extra-embryonic tissues over their adult counterparts is their availability, extraction using non-invasive procedures, higher isolation yields and the absence of ethical concerns [16]. Nevertheless, other advantages have been linked to those cells. Several studies have reported superior cell biological properties such as less variability resulting from the epigenetic marks related to the donor’s lifestyle as well as high proliferative capacity, increased lifespan and, importantly, enhanced potency of the UC-MSCs over the other MSCs obtained from adult tissues (Figure 1). Indeed, in contrast to BM-MSCs, UC-MSCs maintain a significant expansion potential of 2.5 population doublings per week up to passage 22 (P22) keeping all MSC traits and genomic stability and without reaching senescence [63, 64]. Moreover, along with the adipogenic, chondrogenic and osteogenic lineages, UC-MSCs demonstrated differentiation ability into the mesodermal lineage originating from myoblasts and cardiomyocytes [65]; into the ectodermal lineage leading to neurons [66]; and into the endodermal lineage cells, giving rise to insulin-producing cells [51] and HLCs [22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]. Besides, UC-MSCs can be obtained from donors with diverse pharmacogenetic profiles allowing for inter-individual pharmacogenomic studies and development of personalized therapies.
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Figure 1.
Main advantages of human umbilical cord MSCs (hUC-MSCs) over other MSC sources.
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2. Hepatocyte-like cell differentiation
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2.1 Mimicking liver development by cytokines and growth factors supplementation
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The underlying mechanisms inducing hepatocyte polarity and functional maturation in vitro remain largely elusive. Liver cells in vivo reside within a dynamic microenvironment in which biomechanical and biochemical properties of the extracellular matrix (ECM), dynamical cell-ECM and cell-cell interactions, pressure gradients (oxygen and nutrients) and growth factor signaling are critical for the differentiation and maturation of hepatocytes. The relative importance of these various factors changes during liver development and maturation. This makes developing liver models enormously challenging.
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Liver development has been studied using animal models, such as mouse [67], chicken [68], zebra fish [69] and Xenopus [70]. The knowledge of other species’ developmental biology contributed significantly to the progress and set up of protocols, which mimic the in vivo liver development, for deriving HLCs from human stem cells in vitro. As shown in Figure 2, the hepatogenesis process and the subsequent in vitro mimicking of liver development include several steps:
Initially, gastrulation and endoderm specification are activated by Nodal, bone morphogenetic protein (BMP) and Wnt signaling. Signaling by Nodal initiates endoderm and mesoderm formation in a concentration-dependent manner, in which high Nodal concentrations originate the definitive endoderm [71]. The endoderm induction step has been tested in vitro on ESCs through cell exposure to Activin A, a growth factor from the TGF-β family, which binds the same receptors as Nodal and therefore mimics its activity [72, 73].
Gradients of fibroblast growth factor (FGF), Wnt, BMP and retinoic acid secreted from the adjacent mesoderm are responsible for patterning of endoderm [70, 74, 75] to generate the midgut, foregut and hindgut. Each domain expresses a specific transcription factor: HHEX in the foregut, PDX1 in the midgut and CDX in the hindgut. Activation of the HHEX gene expression is essential to foregut formation and therefore its development into the liver. In vitro, this step is mimicked by exposing cells to growth factors such as FGF and EGF, once these activate the HHEX gene [74, 76].
After endoderm commitment and foregut induction, the foregut receives signals from the developing heart and septum transverse mesenchyme (STM), which release FGF and BMP respectively, and regulate hepatic specification to generate hepatoblasts [71, 77]. After hepatic specification, cells start expressing hepatic markers, such as α-fetoprotein (AFP), albumin (ALB), transcription factors as CEBPA and HNF4A, and change their morphology from cuboidal to pseudostratified columnar epithelium, forming the liver bud [78]. STM and hepatic mesenchyme secrete FGF, BMP, Wnt, retinoic acid and hepatocyte growth factor (HGF), which promote hepatoblast proliferation and survival [74, 75, 79, 80]. This step is generally mimicked in vitro using FGF to simulate the signals sent by the developing heart and STM, which induce a transformation in cell disposal and morphology [77, 79], mediating early hepatic differentiation [21]. Herein, HGF stimulates a mid-late hepatic phenotype and is commonly used to promote hepatoblast formation; however, it does not induce functional maturation [21]. FGF and HGF, as well as cell culture supplements like insulin-transferrin-sodium selenite (ITS) and nicotinamide, synergistically affect the hepatic driving pathway [34, 80].
Finally, hepatoblasts, which are bipotent cells, can differentiate into hepatocytes or biliary epithelial cells. Initially, hepatoblasts express genes associated with both adult hepatocytes (HNF4A, ALB, CK18) and biliary epithelial cells (CK19), as well as fetal liver genes such as AFP [71]. Additionally, these cells express CK-14, DLK1, E-cadherin, EPCAM and CD133 and undergo proliferation and differentiation into hepatocytes and cholangiocytes [71]. One factor responsible for the induction of hepatoblast differentiation into hepatocytes and induction of metabolic maturation is oncostatin M (OSM), secreted by hematopoietic cells in the liver [81]. Indeed, several in vitro models for hepatocyte differentiation use dexamethasone, HGF [22, 40, 41], OSM [25, 34, 40] and TNF-α factors [21, 71] to induce hepatocyte maturation. Moreover, the use of a collagen coating [21, 22, 23, 34] improves the in vitro environment to promote hepatogenic differentiation by mimicking in vivo ontogeny.
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Figure 2.\n
Hepatogenesis and the respective inducing factors for in vitro differentiation of MSCs into HLCs. The addition of a combination of soluble factors to the culture, at defined time points, to mimic (i) endoderm commitment and (ii) foregut induction (EGF and FGF), followed by (iii) hepatoblast and liver bud formation (FGF, HGF and ITS) and finally (iv) hepatocyte differentiation and maturation (OSM, dexamethasone and ITS) have been shown to allow hepatic differentiation to some extent, mimicking the in vivo ontogeny. AFP, α-fetoprotein; ALB, albumin; BMP, bone morphogenetic protein; CK, cytokeratin; EGF, epidermal growth factor; FGF, fibroblast growth factor; bFGF, basic fibroblast growth factor; HGF, hepatocyte growth factor; HNF, hepatocyte nuclear factor; ITS, insulin-transferrin-selenium; MAPK, mitogen-activated protein kinase; OSM, oncostatin M.\n
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The protocols, to differentiate MSC into functional hepatocytes, based on the in vivo liver development process can be categorized into two groups: cocktail and sequential. The cocktail methodology is based on one single step, whereas the sequential and time-dependent procedures are based on four, three, or two steps. Campard et al. [22] study was one of the first described studies using a three-step-based protocol for deriving UCM-MSCs into HLCs. Herein, UCM-MSCs (also designated as Wharton’s jelly cells) have been isolated by an orthodox method, involving complex vein and arterial excisions, and the authors departed from a mixed, heterogeneous population of cells. Nevertheless, after the differentiation procedure, HLC derived from UCM-MSCs exhibited a hepatocyte-like morphology, the presence of several hepatic markers (CK18, ALB, AFP and connexin 32), had glycogen storage ability, produced urea and revealed an inducible CYP3A4 activity. Still, the absence of some hepatic markers in the differentiated UC-MSCs, such as HepPar1 or HNF4A, suggested that a fully mature hepatocyte phenotype was not achieved. In another study, Zhao et al. [37], after hepatic differentiation of UC-MSC, prompted by a two-step protocol with HGF and bFGF, HLCs exhibited hepatocyte-like morphology and specific functions including albumin secretion, low-density lipoprotein uptake and urea production. In contrast, Zhang and colleagues [36], using a simpler cocktail induction protocol (with HGF and FGF-4), successfully differentiated UC-MSCs into HLCs with the same hepatic features.
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Overall, those studies indicate that UC-MSCs are capable of generating hepatocyte-like cells with essential hepatic specific functions displaying an exciting potential venue toward cell-based therapeutics, human liver development studies and disease models for liver failure disorders. Yet, the weak characterization of the cells in terms of biotransformation ability has delayed their implementation for in vitro hepatotoxicity studies.
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2.2 Epigenetic modifiers for improving HLC phenotype
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Stepwise addition of factors such as EGF, FGF, HGF, nicotinamide, ITS, dexamethasone or OSM to the culture medium is used in the majority of the studies to differentiate MSCs [23, 26, 34, 35, 41]. Although the addition of these factors seems to lead to hepatic differentiation, a full mature hepatic cell has not yet been achieved. As such, the search for additional differentiation-inducing factors to induce a mature hepatic phenotype persists [34].
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The normal function of cells is controlled by epigenetics, in which a combination of signaling pathways controls the balance between growth and differentiation. Therefore, besides mimicking the in vivo extracellular communication pathways by the use of soluble molecules, such as growth factors, cytokines, hormones and glucocorticoids, one of the strategies for controlling lineage-specific gene expression to induce a mature hepatic phenotype is by the use of chromatin remodeling agents, such as epigenetic modifiers (EM) as HDAC inhibitors (HDACi), DNMT inhibitors (DNMTi) and microRNA (miRNA).
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Epigenetic modifiers change gene expression without changing the underlying DNA sequence, at the chromatin level, by modulation of its architecture between heterochromatin (transcriptionally inactive) and euchromatin (transcriptionally active) [82]. Epigenetic modulation allows to silence pluripotency transcription factors or to activate the transcription of genes of a specific lineage contributing to the improvement of the HLC phenotype [34]. These mechanisms are mainly regulated by DNA methylation, histone modifications and miRNA [82] as presented in Figure 3. Indeed, different strategies for hepatic differentiation based on epigenetic modification have been described so far and those include DNA methylation, histone modification and the use of microRNAs.
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Figure 3.
Control of gene transcription by epigenetic modifiers. Hypomethylated CpG islands and hyperacetylated histone tails at the chromatin level allow gene transcription. DNMT inhibitors (DNMTi), microRNA (miRNA) and HDAC inhibitors (HDACi) modulate the chromatin structure by creating an open, transcriptionally active euchromatin. Consequently, the enhanced accessibility of transcription complexes to chromatin leads to increased transcriptional activation of several epigenetically suppressed genes. 5-AZA, 5-azacytidine; DNMT, DNA methyltransferase; HAT, histone acetyltransferase; HDAC, histone deacetylase; NaBu, sodium butyrate; TSA, trichostatin A; VPA, valproic acid.\n
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2.2.1 DNA methylation
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DNA methyltransferases (DNMTs) introduce a methyl group, generally at CpG islands, into the DNA [82]. Decrease of DNMT1 [83] and increase of DNMT3 [84] expression have been shown to be associated with hepatic maturation. Hence, modulation of DNMTs may present a strategy for increasing liver-specific gene expression and consequently maintain a hepatic fate in HLCs [12]. 5-Azacytidine (5-AZA) is the most commonly used DNA methyltransferase inhibitor (DNMTi), whereas dimethyl sulfoxide (DMSO) emerges as a modulator of DNMTs [85].
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The alteration of the DNA methylation status occurs as 5-AZA mimics the cytidine base and thus is introduced into the newly synthetized DNA strain on the S phase of the cell cycle [86]. On the subject of hepatocyte differentiation, Rothrock and colleagues [87] administered 5-AZA in utero to 20 days gestational age rat fetus resulting in a quicker maturation of hepatocyte morphology, associated with higher activation of genes normally expressed later in liver development as TAT and ALB. In vitro, Yoshida et al. [25] evaluated various combinations of inducing factors, plus the addition or absence of 5-AZA, and verified that the 5-AZA combined with soluble factors was the most effective strategy for differentiating UCB-MSC that displayed a significantly higher ALB, CEBPA and CYP1A1/2 gene expression levels, PAS positive results and urea production after 21 days of differentiation. In another study, Cipriano et al. [23] used 5-AZA as a promoter of differentiation, in the hepatoblast-like stage of differentiation, and observed a significant increase in urea production and CYP activity on HLCs.
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DMSO has also been proposed as an epigenetic modifier. Although the mechanism by which DMSO induces hepatic differentiation is poorly understood, Iwatani et al. [85] suggested that it is by upregulation of the expression of DNMT3. This study was performed in mouse embryoid bodies. Yoon et al. [88], on the other hand, used trichostatin A (TSA) or DMSO treatment for the maturation steps within the hepatic differentiation procedure. Herein, TSA-treated MSCs showed higher EROD activity (human CYP450 1A1/1A2) and ammonia conversion than DMSO-treated cells. Conversely, Cipriano et al. [34] showed that, in addition to the sequential differentiation protocol, DMSO alone (in comparison to its combination with TSA) induced cellular modifications on UCM-MSCs, forming epithelial-like binucleated cells, and stimulated a homogeneous glycogen storage and improved HLC biotransformation activity. The introduction of DMSO for hepatic maturation also resulted in a significantly improved HLC phenotype and maintenance of the hepatocyte features up to 2 weeks in culture [34]. Hence, more studies are necessary in order to determine the effectiveness of DMSO on differentiation of MSCs.
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2.2.2 Histone modifications
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Histone deacetylases (HDCAs) remove the acetyl group from the histones and modulate chromatin to regulate cell proliferation, differentiation and growth [86]. The most commonly used histone deacetylase inhibitors (HDACi) are TSA, sodium butyrate (NaBu) and valproic acid (VPA).
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Similar to other HDACi, TSA reversibly and specifically inhibits HDAC leading to hyperacetylation of histones, but the exact role in hepatic differentiation and maturation is still unclear [88]. Exposure to TSA on primary rat hepatocytes culture revealed increased cell viability and albumin secretion and maintained CYP phase I enzymes’ capacity by controlling the expression of liver-enriched transcription factors (LETFs) and cell cycle arrest [89]. Yoon et al. [88] found that TSA-treated MSC presented higher activity than OSM- or DMSO-treated cells, showing an epithelial-like shape right after treatment and higher urea production and ammonia removal (compared to DMSO) on day 21, as well as the expression of late hepatic markers such as TAT gene expression and EROD activity. Although the expression of these markers and functions indicate a mature HLC phenotype, these values are still lower than in human primary hepatocytes. Likewise, Cipriano et al. [34] tested the effect of 100, 500 and 1000 nM of TSA on UCM-MSC differentiation and observed that 1000 nM of TSA resulted in cell detachment and cell loss, whereas 100 nM did not present relevant morphological changes from a fibroblastic morphology to a more epithelial morphology during the differentiation process. Conversely, 500 nM of TSA resulted in higher EROD and UGT activities, as well as CK18 presence and epithelial morphology [34], though, as referred in the above section, TSA-treated cells could not surpass the results with DMSO-treated cells [34].
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Several protocols for hepatic differentiation of SCs prime the cells with NaBu [90], in combination to Activin A [73] or bFGF and BMP4 [91], in order to induce the definitive endoderm prior to further maturation of HLC through, for instance, DMSO [92]. However, the translation of these studies to UC-MSC is still limited. To the best of our knowledge, only Panta et al. [26] showed that pre-treatment of UCM-MSCs with NaBu upregulated hepatoblast and hepatocyte markers and stimulated mature hepatic-associated functions, such as urea production, glycogen storage and G6P, CEBPA, and CYP2B6 activity, compared to non-treated differentiated cells.
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Finally, VPA, an antiepileptic and anticonvulsant drug, has demonstrated to improve stem cell hepatic differentiation when administered in low doses. An et al. [27] suggested that hepatic differentiation of UC-MSC is stimulated by VPA due to upregulation of endodermal genes such as AKT and ERK. Raut and Khana [28] also verified that pre-treatment of UCM-MSC with VPA enhanced the expression of hepatocyte-specific miRNAs typically upregulated during fetal liver development, such as miR-23b cluster (miR-27b-3p, miR-24-1-5p and miR-23b-3p), miR-30a-5p, miR-26a-5p, miR-148a-3p, miR-192-5p and miR-122-5p, which contributed to a more efficient hepatic transdifferentiation.
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2.2.3 microRNA (miRNA)
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MicroRNAs are critical regulators during the development of liver [93]. In humans, miR-122 is the most abundant miRNA expressed in the adult liver and is known to regulate hepatocyte differentiation [28, 93].
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Zhou et al. [50] validated that, besides miR-122, also miR-148a, miR-424, miR-542-5p and miR-1246 are essential for UC-MSC differentiation, given that omitting any of these five-miRNA combination prevented hepatic transdifferentiation. In addition, it was also demonstrated that HLCs transdifferentiated from those five microRNAs expressed high level of hepatic markers in only 7 days. Moreover, Khosravi et al. [94] studied the role of embryonic overexpressed miRNAs such as miR-106a, miR-574-3p and miR-451 and determined that upregulation of any of these three alone could not induce expression of hepatic genes, such as SOX17, FOXA2, HNF4A, ALB, AFP and CK18. However, the concurrent ectopic overexpression of the three miRNAs together could induce UC-MSC differentiation into functionally mature hepatocytes in an easier, faster and efficient way compared to conventional techniques [94].
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In summary, these results suggest that miRNAs have a role in hepatic differentiation and can rapidly and efficiently convert stem cells into functional HLC.
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2.3 Bioengineering tools for hepatic differentiation
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Hepatocytes need to be exposed to the native physiology of the liver and to have cell-cell interaction similar to the in vivo microenvironment in order to maintain its differentiated state [95]. Engineering tools, such as microfluidics, biomaterial scaffolds and bioprinting, have enabled greater control over the cellular microenvironment and, subsequently, cell response [96]. These strategies may set the ground for producing organs or tissues on demand to be used for animal-free drug development and personalized medicine. Moreover, optimizing cell-cell interactions using different bioengineering techniques, such as 3D liver spheroids and bioprinting, would allow a better mimic of the in vivo physiology and thus permit to analyze cells’ response to drugs and other stimuli more accurately.
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Different research groups reported various hepatic differentiation protocols by resorting to bioengineering tools. Table 2 gathers several strategies for deriving HLCs from different umbilical cord sections both in 2D and 3D systems.
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MSC source
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Induction factors
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Controls
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Functional analysis
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Hepatic markers
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Ref.
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Monolayer culture
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UCB
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HGF, ITS, OSM, dexamethasone
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MSC
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LDL uptake
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\nALB, AFP, CK-18, CK-19, GS, TAT HGF, c-Met, PEPCK, CPS\n
Within the umbilical cord, investigators seem to prefer using UCM-MSCs over UCB-MSCs to obtain HLCs, as shown in Table 2. This may be explained as UCM-MSCs are easier to isolate [97] and produce higher cell numbers with better proliferation capacities when compared to UCB-MSCs [98].
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2.3.1 3D cultures of UC-MSC-derived HLCs
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Animal models often fail to recapitulate human biology and are not appropriate to study tissue-specific mechanisms in a controlled fashion without the interference of other tissues [99]. Thus, creating a controlled human in vitro tissue using 3D culture techniques is a key strategy for producing reliable knowledge on drug toxicity and disease mechanisms [23, 29, 100]. Studies using HLCs differentiated from UC-MSC through 3D systems are still scarce. Nevertheless, Figure 4 illustrates several strategies of bioengineering for producing functional HLCs from MSCs.
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Figure 4.
2D and 3D culture strategies for the differentiation of MSCs into HLCs and potential clinical applications. Several strategies such as spheroid cultures, scaffolds, bioprinting and microfluidics have shown promissory results and represent good tools for future studies on drug screening, disease modeling and regenerative therapies using fully functional HLCs.
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Cipriano et al. [23] reported that by resorting to 3D spheroid cultures, the HLCs obtained from UCM-MSCs exhibited a higher glycogen stain and CYP3A4 induction when compared to the correspondent 2D cultures (Figure 5). On the other hand, HLCs cultured in hollow-fiber bioreactors favored diclofenac conversion and albumin production [23], a function mostly associated with the perivenous phenotype [101] that is also regulated by the blood flow-mediated shear stress [100]. Alternatively, Ong et al. [31] observed that MSC-derived HLCs cultured as spheroids in pellet culture endorsed expression of a subset of hepatic genes (CYP3A4 and HNF4A), secreted albumin and urea, stored glycogen and showed inducible CYP3A4 mRNA levels. Importantly, the culture conditions allowed stable cell anchorage, permitted the retention of ECM molecules produced by the cells, and when implanted into livers of hepatectomized rats also secreted human albumin into the bloodstream [31].
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Figure 5.
Immunohistochemical and PAS analysis of HLCs-derived UCM-MSCs cultured in 2D cultures, in spheroids and in bioreactors. Representative images show the presence of the plasma protein ALB, the efflux transporter MRP-2, the uptake transporter protein OATP-C and the biotransformation enzymes CYP1A2 and CYP3A4. Cell nuclei are stained with DAPI. Scale bar: 50 μm. ALB, albumin; CYP, cytochrome P-450; HLCs, hepatocyte-like cells; MRP-2, multidrug resistance protein-2; OATP-C, organic anion-transporting polypeptide C; PAS, Periodic acid–Schiff; UCM-MSC, umbilical cord matrix mesenchymal stem cells\n.
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In the region between the blood and the hepatocytes (space of Disse) lies a diffuse matrix composed mostly of collagen type I and fibronectin [102]. Collagen base scaffolds have demonstrated to improve the adult hepatocyte functions as they mimic the naïve hepatocyte niche [21, 22, 23, 34]. Talaei-Khozani et al. [103] and Khodabandeh et al. [104] compared 2D and 3D cultures of UCM-MSCs in collagen films and demonstrated a better hepatogenesis and increased expression of HNF4A on the 3D environment. Additionally, Aleahmad et al. [29] used a 3D bioprinted collagen and heparin scaffold and verified that heparinized 2D cultures mainly expressed early liver-specific markers (e.g., HNF4A, ALB, CK18 and CK19) in the presence of heparin, whereas the heparinized 3D cultures expressed both early and late liver-specific markers (e.g., G6P, CYP2B). In this study, HLCs showed a two-fold increase in albumin production compared to monolayer cultures [29]. These results infer that 3D culture conditions using collagen films can prevent loss of hepatocyte function and improve efficiency of hepatocyte differentiation.
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Scaffolds other than collagen matrixes have also been proposed to direct hepatic differentiation of UC-MSCs. Chitrangi et al. [30] observed that gelatin-vinyl acetate (GEVAC) stimulates the differentiation of UC-MSCs into hepatospheroids, resulting in a better maturation, higher urea production, expression of CYP3A4 and CYP2C9, higher percentage of albumin-positive cells and hepatic markers compared to 2D cultures. Hashemi et al. [33] also presented a protocol for seeding UC-MSCs on a poly(ε-caprolactone) (PCL) nanofiber scaffold to stimulate and then maintain hepatic differentiation.
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2.3.2 Microfluidic technologies
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The hepatic zonation corresponds to the different functions revealed by the hepatocytes according to their location in the hepatic lobule, which results from the gradient of concentration of the various nutrients and oxygen observed in the hepatic environment [7]. The 3D culture systems create a gradient that may stimulate the hepatic zonation and influence HLCs obtained. For instance, the 3D configuration may mimic the liver periportal environment by generating a gradient with higher oxygen, glucose and nutrients in cells closer to the capillaries in the culture system, for example, in the outer side of spheroids, leading to higher xenobiotic metabolism, urea production and glycogen synthesis [7]. The perivenous hepatocytes have less access to oxygen supplies and are characterized by a higher xenobiotic metabolism, being exposed to physiologic conditions similar to the ones observed around the inner cells [3, 7]. Moreover, hepatocytes are not the only cells present in the liver as they interact with mesenchymal cells, stellate cells, Küpffer cells, macrophages, and lymphocytes, and are exposed, in vivo, to a fluid perfusion [105]. Hence, in vitro liver function may be optimized by resorting to microfluidic technologies.
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Microfluidic culture devices (MD) permit to control the microenvironment and present the ability of continued delivery of medium, drugs and soluble molecules, allowing the study of drug metabolism and interactions [96]. The effect of medium flow on inducing albumin secretion was demonstrated by Prodanov et al. [100] using a human primary hepatocyte 3D microfluidic system. Likewise, McCarty et al. [106] demonstrated the creation of spatially-controlled zonation across multiple hepatocyte metabolism levels through the application of precise concentration gradients of exogenous hormones (insulin and glucagon) and chemical (3-methylcholanthrene) induction agents in a microfluidic device, using monolayer rat primary hepatocytes. Herein, a high concentration of insulin was directly correlated with a gradient in glycogen storage and urea production [106].
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Studies reporting the hepatic differentiation of MSCs are still limited, but two studies using bone-marrow-derived MSC cultured in MDs show already a cost-effective method for HLCs production in 3 [107] to 4 weeks [108]; however, the obtained HLCs were only characterized with regard to albumin and urea quantification and showed a low metabolic performance.
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3. Characterization of hepatocyte-like cells in vitro\n
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A great amount of work has been developed over the past years for generating human stem cell-derived hepatocyte systems for in vitro toxicity testing. However, the definition of what is considered a differentiated HLC is still not unanimous and largely depends on the authors and on the purpose for which the cells are to be used. Currently, a wide and variable range of parameters is used to demonstrate the acquisition of in vivo-like hepatic features, which often leads to an incomplete and inconsistent cell characterization. As such, the scientific community would benefit from the harmonization and definition of the number and type of performance criteria. Indeed, Vinken and Hengstler [14] propose an optimal characterization aiming at benchmarking of hepatocyte-based in vitro systems for toxicity testing. This proposal comprises critical elements such as cell viability, morphology, functionality and toxicological characterization, as follows:
Cell viability should be assessed using at least two methods that evaluate early and late key events of cytotoxicity. Moreover, a threshold of 90% viability should be adopted to discriminate between spontaneous cell death and cell death induced by toxicants.
In terms of cellular morphology, cells must be monitored closely in order to confirm the maintenance of the hepatic polygonal shape and the detection of structural polarity markers, essential for many hepatic functions.
Hepatocyte-specific functions, including secretion of albumin and blood coagulation factors, metabolism of carbohydrates and lipids, bile acid production and transport, as well as the detoxification of endobiotics and xenobiotics are some of the cells functionalities to be considered. This can be performed through measurement of albumin and urea production, of glycogen storage and of biotransformation enzyme activity. Other hepatic or liver-related markers, such as HNF-1/4A and PXR, should also be evaluated.
The toxicological characterization of hepatocyte-based in vitro systems is important to confirm their capacity to detect prototypical types of liver toxicity. This can be achieved by using hepatotoxicants capable of replicating human in vivo intrinsic drug-induced liver injury, namely paracetamol dose-dependent necrosis, microvesicular steatosis induced by valproic acid and cholestasis induced by cyclosporine A.
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However, a systematic interpretation of HLC-based in vitro systems with respect to their translation for the human in vivo situation remains a major challenge for future research.
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4. In vitro toxicological applications of HLCs
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Drug attrition is a major expense in the drug development process and the use of advanced in vitro models will likely contribute to its reduction [109]. Detection of hepatotoxicity often occurs late in the drug development process and contributes to drug attrition, withdrawn in a post-market scheme and restriction of therapeutic indications [110]. Animal-based testing is currently the base for translating in vitro studies to clinical trials but often do not correlate with human toxicity data [99], mainly due to interspecies differences in drug metabolism [4]. In vitro models cannot directly replace animal models but may occupy a new space in which, in the future, animal models will become obsolete (Figure 6). In vitro models provide tissue-specific mechanistic insights and allow to study a high number of conditions with the same cells, by means of, for example, miniaturization and higher throughput [111]. However, current in vitro application of differentiated HLCs in drug metabolism studies and disease modeling is still in its infancy.
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Figure 6.
Potential of mature, fully functional HLCs on drug discovery and drug development. Conventional drug development pipelines involve preclinical in vitro and in vivo research in animal models followed by clinical trials on humans. In vitro toxicology models such as fully functional HLCs may shorten the way by performing a more similar to human toxicology screen and overcome limitations associated with poor correlation, interspecies differences and ethical concerns when using animal models.
\n
Numerous studies have been published on HLCs obtained from UC-MSCs [25, 27, 34, 35, 40] as shown in Table 2, but few were able to demonstrate cells’ biotransformation capacity, as follows: Xue et al. [49] showed that HLCs from UCM-MSCs were capable of metabolizing midazolam through CYP3A4 activity. As mentioned earlier, using a three-step protocol for UCM-MSC differentiation, Campard et al. [22] obtained HLCs that expressed important hepatic features (ALB, G6P, TDO, AAT, TAT and AFP markers, glycogen accumulation and urea production) and exhibited CYP3A4 activity. However, the absence of markers of hepatic maturation such as CYP2B6 induction after exposure to phenobarbital suggested that a relevant phenotype was not fully achieved [22]. On the other hand, Cipriano et al. [34], in contrast to the results observed when comparing HepG2 and primary human hepatocytes (PHH), obtained a comparable expression of genes involved in drug transport, amino acid metabolism and proliferation of hepatocytes between UCM-MSC-derived HLCs and PHH, indicating that HLCs are a better model for drug screening than low-metabolizing cell lines. In another study, using HLCs derived from UCM-MSC in 3D spheroids culture, Cipriano et al. [23] also observed that diclofenac was effectively converted by CYP2C9 into its hepatotoxic metabolite, 4-OH-diclofenac, and was also metabolized to a lesser extent by CYP3A4 and UGTs. Furthermore, the determined IC50 felt in the range of what is found on the literature for primary hepatocytes, indicating that differentiated MSCs had similar dose-response characteristics to mature primary hepatocytes for this hepatotoxicant. Diclofenac is one of the most prescribed nonsteroidal anti-inflammatory drugs (NSAIDs) worldwide [112]. As such, these results permit the future use of these HLCs on drug testing and potential hepatotoxicity screening, which is often dependent of bioactivation.
\n
Acetaminophen (APAP) is an over-the-counter antipyretic and analgesic drug widely used in several pharmacological formulations. However, in toxic doses, APAP causes liver injury by saturation of its main inactivation pathway and shifts to the transformation, by CYP2E1, CYP2D6, CYP1A2 and CYP2A6, of APAP into its hepatotoxic metabolite N-acetyl-p-benzoquinone imine (NAPQI) [113]. Chitrangi et al. [30] used hepatospheroids derived from UC-MSCs as an in vitro model for studying the metabolism and toxicity of APAP. CYP3A4 and CYP1A2 were induced in HLCs by APAP as well as reactive oxygen species (ROS) cell damage, which lead to cytoskeletal disorganization, both in HLCs and primary hepatocytes.
\n
Hepatocytes derived from SCs may also represent a platform for drug discovery trough disease modeling, in which in vivo cell functions and mechanisms involved in pathological processes on disease onset and progression may be analyzed [114]. There are already several liver diseases successfully modeled in vitro using iPSC-derived hepatocytes as, for instance, familial hypercholesterolemia [115], hemophilia A [116], hepatitis C [117] and drug-induced hepatotoxicity [118]. One of the first studies to use human UC-MSCs to define a disease was Paganelli et al. [119], who developed an in vitro disease model to study the mechanisms underlying hepatitis B virus (HBV) infection by differentiating UC-MSCs into HLCs and infecting them with HBV. Results showed a higher susceptibility of HBV infection on HLCs rather than on undifferentiated MSCs. Despite low replication efficiency on HLCs, viral entry was as efficient as in primary hepatocytes and mimicked appropriately the in vivo-restricted HBV host range [119]. These similarities between the in vivo, in vitro gold standard and UC-MSCs lead, once again, to a promising opportunity for future development of in vitro models for drug discovery as human UC-MSCs represent a unique, human, easily available, non-transformed in vitro model.
\n
\n
\n
5. Conclusion and future perspectives
\n
This chapter provides insights into the potential use of human umbilical cord MSCs for obtaining a mature HLC phenotype suitable for in vitro toxicological studies. As primary hepatocytes present limited capacity to expand ex vivo, the possibility of obtaining comparable hepatocyte-like cells from MSCs may alleviate the low cell availability of human primary hepatocytes. Moreover, the use of MSCs in a physiologically relevant microenvironment that generates fully functional HLCs would allow an integrated approach to study xenobiotics biotransformation and mechanisms of action (MoA) or toxicity (MoT).
\n
The differentiation process of MSCs into HLCs and their potential toxicology application are still in their infancy and, in the following years, there are still major challenges to resolve before their relevant application. Firstly, improvement of the efficiency of hepatic induction in vitro and in vivo still requires further investigation on the hepatic transdifferentiation mechanisms of UC-MSCs. Secondly, the differentiation process is long and the generation and maintenance of high numbers of HLCs are still difficult to achieve. The definition of the most relevant endpoints of hepatic differentiation and maturation is of extreme importance. Thirdly, the use of relevant positive controls such as human primary hepatocytes is essential for benchmarking HLCs and its absence represents a major issue in evaluating most of the published studies.
\n
As such, further studies will be required to allow the use of HLCs derived from UC-MSCs in the drug development process, but the strategies described in this chapter represent the first step toward the establishment of a relevant human in vitro hepatic model for toxicological studies. Exploring the full potential of UC-MSCs by the introduction of mechanistic models for toxicity testing, including in vitro disease models and hepatotoxicity models, at the pipeline of drug discovery and development will significantly reduce compound attrition rate and progressively substitute current animal models by selecting safer and more efficacious lead molecules.
\n
\n
Acknowledgments
\n
This work was funded by FCT (Portugal) through the research grants TUBITAK/0003/2014 and PTDC/MED-TOX/29183/2017.
\n
Conflict of interest
The authors declare no conflict of interest.
\n
Appendices and Nomenclature
\n
\n\n\n2D\n\n
two-dimensional
\n\n\n\n3D\n\n
three-dimensional
\n\n\n\n5-AZA\n\n
5-azacytidine
\n\n\n\nAAT\n\n
α1 anti-trypsin
\n\n\n\nAFP\n\n
α-fetoprotein
\n\n\n\nALB\n\n
albumin
\n\n\n\nBMP\n\n
bone morphogenetic protein
\n\n\n\nCEBP\n\n
CCAAT enhancer-binding protein
\n\n\n\nCK\n\n
cytokeratin
\n\n\n\nCYP\n\n
cytochrome P450
\n\n\n\nDILI\n\n
drug-induced liver injury
\n\n\n\nDMSO\n\n
dimethyl sulfoxide
\n\n\n\nDNMTi\n\n
DNA methyltransferase inhibitors
\n\n\n\nEGF\n\n
epidermal growth factor
\n\n\n\nEROD\n\n
7-ethoxyresorufin-O-deethylase
\n\n\n\nFGF\n\n
fibroblast growth factor
\n\n\n\nG6P\n\n
glucose-6-phosphatase
\n\n\n\nGS\n\n
glutamine synthetase
\n\n\n\nHDACi\n\n
histone deacetylase inhibitors
\n\n\n\nhESCs\n\n
human embryonic stem cells
\n\n\n\nHGF\n\n
hepatocyte growth factor
\n\n\n\nHLC\n\n
hepatocyte-like cell
\n\n\n\nHLCs\n\n
hepatocyte-like cells
\n\n\n\nHNF\n\n
hepatocyte nuclear factor
\n\n\n\nhnMSC\n\n
human neonatal mesenchymal stem cell
\n\n\n\nhnMSCs\n\n
human neonatal mesenchymal stem cells
\n\n\n\nhUCB-MSCs\n\n
human umbilical cord blood mesenchymal stem cells
\n\n\n\nhUCM-MSCs\n\n
human umbilical cord matrix mesenchymal stem cells
\n\n\n\nhUC-MSC\n\n
human umbilical cord-derived mesenchymal stem cell
\n\n\n\nIGF\n\n
insulin-like growth factor
\n\n\n\niPSCs\n\n
induced pluripotent stem cells
\n\n\n\nITS\n\n
insulin-transferrin-selenium
\n\n\n\nLDL\n\n
low-density lipoprotein
\n\n\n\nMD\n\n
microfluidic culture device
\n\n\n\nMiR\n\n
microRNA
\n\n\n\nMSC\n\n
mesenchymal stem cells
\n\n\n\nNaBu\n\n
sodium butyrate
\n\n\n\nOSM\n\n
oncostatin M
\n\n\n\nPAS\n\n
periodic acid Schiff’s
\n\n\n\nSCs\n\n
stem cells
\n\n\n\nTAT\n\n
tyrosine aminotransferase
\n\n\n\nTDO\n\n
tryptophan-2,3-dioxygenase
\n\n\n\nTSA\n\n
trichostatin A
\n\n\n\nUGT\n\n
uridine 5′-diphosphate glucuronosyltransferase
\n\n\n\nVPA\n\n
valproic acid
\n\n\n\n
\n
\n',keywords:"human neonatal mesenchymal stem cells, umbilical cord mesenchymal stem cells, hepatocyte-like cells, hepatic differentiation, liver development, epigenetic modifiers, bioengineering, in vitro alternative models, in vitro toxicology",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/71523.pdf",chapterXML:"https://mts.intechopen.com/source/xml/71523.xml",downloadPdfUrl:"/chapter/pdf-download/71523",previewPdfUrl:"/chapter/pdf-preview/71523",totalDownloads:414,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:1,totalAltmetricsMentions:0,impactScore:1,impactScorePercentile:54,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"October 21st 2019",dateReviewed:"February 17th 2020",datePrePublished:"June 24th 2020",datePublished:"April 14th 2021",dateFinished:"March 20th 2020",readingETA:"0",abstract:"The in vitro toxicology field seeks for reliable human relevant hepatic models for predicting xenobiotics metabolism and for the safety assessment of chemicals and developing drugs. The low availability and rapid loss of the phenotype or low biotransformation activity of primary hepatocytes urged the stem cell differentiation into hepatocyte-like cells (HLCs). Umbilical cord-derived mesenchymal stem cells (UC-MSC), in particular, offer a highly available cell source, with few ethical issues and higher genetic stability. However, the dynamic and complex microenvironment of liver development, including the cell-ECM and cell–cell interactions, pressure gradients (oxygen and nutrients) and growth factor signaling that are critical for the differentiation and maturation of hepatocytes, challenges the progress of in vitro hepatic models. Promising strategies like (i) cytokine and growth factor supplementation mimicking the liver development; (ii) epigenetic modification; and (iii) bioengineering techniques to recreate the liver microphysiological environment are gaining increasing importance for the development of relevant in vitro liver models to address the need for higher predictivity and cost efficiency. In this context, this chapter reviews the existing knowledge and recent advances on the approaches for deriving HLCs from UC-MSC and their application for in vitro toxicology.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/71523",risUrl:"/chapter/ris/71523",book:{id:"9021",slug:"novel-perspectives-of-stem-cell-manufacturing-and-therapies"},signatures:"Ana Sofia Martins Serras, Madalena Zincke dos Reis Fernandes Cipriano, Pedro Miguel da Graça Silva and Joana Paiva Gomes Miranda",authors:[{id:"313888",title:"Prof.",name:"Joana P.",middleName:null,surname:"Miranda",fullName:"Joana P. Miranda",slug:"joana-p.-miranda",email:"jmiranda@ff.ul.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"313889",title:"MSc.",name:"Ana",middleName:null,surname:"Serras",fullName:"Ana Serras",slug:"ana-serras",email:"ana.serras@edu.ulisboa.pt",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"313891",title:"Dr.",name:"Madalena",middleName:null,surname:"Cipriano",fullName:"Madalena Cipriano",slug:"madalena-cipriano",email:"madalena.cipriano@igb.fraunhofer.de",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"318079",title:"BSc.",name:"Pedro",middleName:null,surname:"Silva",fullName:"Pedro Silva",slug:"pedro-silva",email:"pedrom.g.silva@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_1_2",title:"1.1 Umbilical cord-derived mesenchymal stem cells as an alternative stem cell source for generating hepatocyte-like cells",level:"2"},{id:"sec_3",title:"2. Hepatocyte-like cell differentiation",level:"1"},{id:"sec_3_2",title:"2.1 Mimicking liver development by cytokines and growth factors supplementation",level:"2"},{id:"sec_4_2",title:"2.2 Epigenetic modifiers for improving HLC phenotype",level:"2"},{id:"sec_4_3",title:"2.2.1 DNA methylation",level:"3"},{id:"sec_5_3",title:"2.2.2 Histone modifications",level:"3"},{id:"sec_6_3",title:"2.2.3 microRNA (miRNA)",level:"3"},{id:"sec_8_2",title:"2.3 Bioengineering tools for hepatic differentiation",level:"2"},{id:"sec_8_3",title:"2.3.1 3D cultures of UC-MSC-derived HLCs",level:"3"},{id:"sec_9_3",title:"2.3.2 Microfluidic technologies",level:"3"},{id:"sec_12",title:"3. Characterization of hepatocyte-like cells in vitro\n",level:"1"},{id:"sec_13",title:"4. In vitro toxicological applications of HLCs",level:"1"},{id:"sec_14",title:"5. Conclusion and future perspectives",level:"1"},{id:"sec_15",title:"Acknowledgments",level:"1"},{id:"sec_18",title:"Conflict of interest",level:"1"},{id:"sec_15",title:"Appendices and Nomenclature",level:"1"}],chapterReferences:[{id:"B1",body:'\nLee WM. Drug-induced acute liver failure. Clinics in Liver Disease. 2013;17(4):575-586\n'},{id:"B2",body:'\nAndrade RJ, Aithal GP, Björnsson ES, Kaplowitz N, Kullak-Ublick GA, Larrey D, et al. EASL clinical practice guidelines: Drug-induced liver injury. Journal of Hepatology. 2019;70(6):1222-1261\n'},{id:"B3",body:'\nGerets HHJ, Tilmant K, Gerin B, Chanteux H, Depelchin BO, Dhalluin S, et al. Characterization of primary human hepatocytes, HepG2 cells, and HepaRG cells at the mRNA level and CYP activity in response to inducers and their predictivity for the detection of human hepatotoxins. 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Cytotherapy. 2006;8(4):315-317\n'},{id:"B54",body:'\nda Silva ML, Chagastelles PC, Nardi NB. Mesenchymal stem cells reside in virtually all post-natal organs and tissues. Journal of Cell Science. 2006;119(Pt 11):2204-2213\n'},{id:"B55",body:'\nde la Torre P, Jesús Pérez-Lorenzo M, Flores AI. Human placenta-derived mesenchymal stromal cells: A review from basic research to clinical applications. In: Stromal Cells - Structure, Function, and Therapeutic Implications. IntechOpen; 2019\n'},{id:"B56",body:'\nSecunda R, Vennila R, Mohanashankar AM, Rajasundari M, Jeswanth S, Surendran R. Isolation, expansion and characterisation of mesenchymal stem cells from human bone marrow, adipose tissue, umbilical cord blood and matrix: A comparative study. Cytotechnology. 2015;67(5):793-807\n'},{id:"B57",body:'\nNekanti U, Mohanty L, Venugopal P, Balasubramanian S, Totey S, Ta M. Optimization and scale-up of Wharton’s jelly-derived mesenchymal stem cells for clinical applications. Stem Cell Research. 2010;5(3):244-254\n'},{id:"B58",body:'\nVaraa N, Azandeh S, Khodabandeh Z, Gharravi AM. Wharton’s jelly mesenchymal stem cell: Various protocols for isolation and differentiation of hepatocyte-like cells; narrative review. Iranian Journal of Medical Sciences. 2019;44(6):437-448\n'},{id:"B59",body:'\nHassan G, Kasem I, Soukkarieh C, Aljamali M. A simple method to isolate and expand human umbilical cord derived mesenchymal stem cells: Using explant method and umbilical cord blood serum. International Journal of Stem Cells. 2017;10(2):184-192\n'},{id:"B60",body:'\nZeddou M, Briquet A, Relic B, Josse C, Malaise MG, Gothot A, et al. The umbilical cord matrix is a better source of mesenchymal stem cells (MSC) than the umbilical cord blood. Cell Biology International. 2010;34(7):693-701\n'},{id:"B61",body:'\nSingh TP, Sherpa ML, Pradhan A, Singh TA. Neonatal derived mesenchymal stem cells can Be isolated from human umbilical cord Wharton’s jelly but not from human umbilical cord blood. Journal of Evolution of Medical and Dental Sciences. 2019;8(12):849-854\n'},{id:"B62",body:'\nGanchas Soares RI, Baptista Coelho MC, Silva Santos JM, Martins JP, Basto VA, Estilita Monteiro Da Cruz P, et al. Optimised and defined method for isolation and preservation of precursor cells from human umbilical cord. WO/2009/044379. Portugal; 2009\n'},{id:"B63",body:'\nSantos JM, Camões SP, Filipe E, Cipriano M, Barcia RN, Filipe M, et al. Three-dimensional spheroid cell culture of umbilical cord tissue-derived mesenchymal stromal cells leads to enhanced paracrine induction of wound healing. Stem Cell Research & Therapy. 2015;6(1):1-19\n'},{id:"B64",body:'\nMartins JP, Santos JM, Almeida JM, Filipe MA, de Almeida MVT, Almeida SCP, et al. Towards an advanced therapy medicinal product based on mesenchymal stromal cells isolated from the umbilical cord tissue: Quality and safety data. Stem Cell Research & Therapy. 2014;5(1):9\n'},{id:"B65",body:'\nGrabowska I, Streminska W, Janczyk-Ilach K, Machaj EK, Pojda Z, Hoser G, et al. Myogenic potential of mesenchymal stem cells - the case of adhesive fraction of human umbilical cord blood cells. Current Stem Cell Research & Therapy. 2013;8(1):82-90\n'},{id:"B66",body:'\nChen S, Zhang W, Wang JM, Duan HT, Kong JH, Wang YX, et al. Differentiation of isolated human umbilical cord mesenchymal stem cells into neural stem cells. International Journal of Ophthalmology. 2016;9(1):41-47\n'},{id:"B67",body:'\nJung J, Zheng M, Goldfarb M, Zaret KS. Initiation of mammalian liver development from endoderm by fibroblast growth factors. Science. 1999;284(5422):1998-2003\n'},{id:"B68",body:'\nFukuda-Taira S. Hepatic induction in the avian embryo: Specificity of reactive endoderm and inductive mesoderm. Journal of Embryology and Experimental Morphology. 1981;63:111-125\n'},{id:"B69",body:'\nWilkins BJ, Pack M. Zebrafish models of human liver development and disease. Comprehensive Physiology. 2013;3(3):1213-1230\n'},{id:"B70",body:'\nMcLin VA, Rankin SA, Zorn AM. Repression of Wnt/β-catenin signaling in the anterior endoderm is essential for liver and pancreas development. Development. 2007;134(12):2207-2217\n'},{id:"B71",body:'\nGordillo M, Evans T, Gouon-Evans V. Orchestrating liver development. Development. 2015;142(12):2094-2108\n'},{id:"B72",body:'\nHay DC, Fletcher J, Payne C, Terrace JD, Gallagher RCJ, Snoeys J, et al. Highly efficient differentiation of hESCs to functional hepatic endoderm requires ActivinA and Wnt3a signaling. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(34):12301-12306\n'},{id:"B73",body:'\nZhou M, Li P, Tan L, Qu S, Ying QL, Song H. Differentiation of mouse embryonic stem cells into hepatocytes induced by a combination of cytokines and sodium butyrate. Journal of Cellular Biochemistry. 2010;109(3):606-614\n'},{id:"B74",body:'\nCalmont A, Wandzioch E, Tremblay KD, Minowada G, Kaestner KH, Martin GR, et al. An FGF response pathway that mediates hepatic gene induction in embryonic endoderm cells. Developmental Cell. 2006;11(3):339-348\n'},{id:"B75",body:'\nWang Z, Dollé P, Cardoso WV, Niederreither K. Retinoic acid regulates morphogenesis and patterning of posterior foregut derivatives. Developmental Biology. 2006;297(2):433-445\n'},{id:"B76",body:'\nShen MM. Nodal signaling: Development roles and regulation. Development. 2007;134(6):1023-1034\n'},{id:"B77",body:'\nAmeri J, Ståhlberg A, Pedersen J, Johansson JK, Johannesson MM, Artner I, et al. FGF2 specifies hESC-derived definitive endoderm into foregut/midgut cell lineages in a concentration-dependent manner. Stem Cells. 2010;28(1):45-56\n'},{id:"B78",body:'\nBort R, Signore M, Tremblay K, Barbera JPM, Zaret KS. Hex homeobox gene controls the transition of the endoderm to a pseudostratified, cell emergent epithelium for liver bud development. Developmental Biology. 2006;290(1):44-56\n'},{id:"B79",body:'\nRossi JM, Dunn NR, Hogan BLM, Zaret KS. Distinct mesodermal signals, including BMPs from the septum, transversum mesenchyme, are required in combination for hepatogenesis from the endoderm. Genes & Development. 2001;15(15):1998-2009\n'},{id:"B80",body:'\nZorn AM. Liver Development. In: StemBook. Harvard Stem Cell Institute: Cambridge (MA); 2008\n'},{id:"B81",body:'\nKamiya A, Kinoshita T, Miyajima A. Oncostatin M and hepatocyte growth factor induce hepatic maturation via distinct signaling pathways. FEBS Letters. 2001;492(1-2):90-94\n'},{id:"B82",body:'\nMortada I, Mortada R. Epigenetic changes in mesenchymal stem cells differentiation. European Journal of Medical Genetics. 2017;61(2):114-118\n'},{id:"B83",body:'\nKaji K, Factor VM, Andersen JB, Durkin ME, Tomokuni A, Marquardt JU, et al. DNMT1 is a required genomic regulator for murine liver histogenesis and regeneration. Hepatology. 2016;64(2):582-598\n'},{id:"B84",body:'\nLee CW, Huang WC, Huang HD, Huang YH, Ho JH, Yang MH, et al. DNA methyltransferases modulate hepatogenic lineage plasticity of mesenchymal stromal cells. Stem Cell Reports. 2017;9(1):247-263\n'},{id:"B85",body:'\nIwatani M, Ikegami K, Kremenska Y, Hattori N, Tanaka S, Yagi S, et al. Dimethyl sulfoxide has an impact on epigenetic profile in mouse embryoid body. Stem Cells. 2006;24(11):2549-2556\n'},{id:"B86",body:'\nEl-Serafi AT. Epigenetic modifiers and stem cell differentiation. Cancer Stem Cells. 2012;8:147-154\n'},{id:"B87",body:'\nRothrock R, Lee KL, Isham KR, Kenney FT. Changes in hepatic differentiation following treatment of rat fetuses with 5-azacytidine. Archives of Biochemistry and Biophysics. 1988;263(2):237-244\n'},{id:"B88",body:'\nYoon HH, Jung BY, Seo YK, Song KY, Park JK. In vitro hepatic differentiation of umbilical cord-derived mesenchymal stem cell. Process Biochemistry. 2010;45(12):1857-1864\n'},{id:"B89",body:'\nHenkens T, Papeleu P, Elaut G, Vinken M, Rogiers V, Vanhaecke T. Trichostatin A, a critical factor in maintaining the functional differentiation of primary cultured rat hepatocytes. Toxicology and Applied Pharmacology. 2007;218(1):64-71\n'},{id:"B90",body:'\nYan Y, Zhong B, Qi W, Song Y, Wu Y, Fan Y, et al. In vitro differentiation of mouse embryonic stem cells into functional hepatocytes by sodium butyrate, hepatocyte growth factor and dexamethasone under chemically defined conditions. African Journal of Biotechnology. 2011;10(46):9493-9500\n'},{id:"B91",body:'\nCao J, Shang CZ, Lü LH, Qiu DC, Ren M, Chen YJ, et al. Differentiation of embryonic stem cells into hepatocytes that coexpress coagulation factors VIII and IX. Acta Pharmacologica Sinica. 2010;31:1478-1486\n'},{id:"B92",body:'\nHay DC, Zhao D, Fletcher J, Hewitt ZA, McLean D, Urruticoechea-Uriguen A, et al. Efficient differentiation of hepatocytes from human embryonic stem cells exhibiting markers recapitulating liver development in vivo. Stem Cells. 2008;26(4):894-902\n'},{id:"B93",body:'\nDeng XG, Qiu RL, Wu YH, Li ZX, Xie P, Zhang J, et al. Overexpression of miR-122 promotes the hepatic differentiation and maturation of mouse ESCs through a miR-122/FoxA1/HNF4a-positive feedback loop. Liver International. 2014;34(2):281-295\n'},{id:"B94",body:'\nKhosravi M, Azarpira N, Shamdani S, Hojjat-Assari S, Naserian S, Karimi MH. Differentiation of umbilical cord derived mesenchymal stem cells to hepatocyte cells by transfection of miR-106a, miR-574-3p, and miR-451. Gene. 2018;667:1-9\n'},{id:"B95",body:'\nProctor WR, Foster AJ, Vogt J, Summers C, Middleton B, Pilling MA, et al. Utility of spherical human liver microtissues for prediction of clinical drug-induced liver injury. Archives of Toxicology. 2017;91(8):2849-2863\n'},{id:"B96",body:'\nUnderhill GH, Khetani SR. Bioengineered liver models for drug testing and cell differentiation studies. Cellular and Molecular Gastroenterology and Hepatology. 2018;5(3):426-439.e1\n'},{id:"B97",body:'\nReinisch A, Bartmann C, Rohde E, Schallmoser K, Bjelic-Radisic V, Lanzer G, et al. Humanized system to propagate cord blood-derived multipotent mesenchymal stromal cells for clinical application. Regenerative Medicine. 2007 Jul;2(4):371-382\n'},{id:"B98",body:'\nAraújo AB, Salton GD, Furlan JM, Schneider N, Angeli MH, Laureano AM, et al. Comparison of human mesenchymal stromal cells from four neonatal tissues: Amniotic membrane, chorionic membrane, placental decidua and umbilical cord. Cytotherapy. 2017;19(5):577-585\n'},{id:"B99",body:'\nOlson H, Betton G, Robinson D, Thomas K, Monro A, Kolaja G, et al. Concordance of the toxicity of pharmaceuticals in humans and in animals. Regulatory Toxicology and Pharmacology. 2000;32(1):56-67\n'},{id:"B100",body:'\nProdanov L, Jindal R, Bale SS, Hegde M, Mccarty WJ, Golberg I, et al. Long-term maintenance of a microfluidic 3D human liver sinusoid. Biotechnology and Bioengineering. 2016;113:241-246\n'},{id:"B101",body:'\nJungermann K, Keitzmann T. Zonation of parenchymal and nonparenchymal metabolism in liver. Annual Review of Nutrition. 1996;16:179-203\n'},{id:"B102",body:'\nHansen LK, Wilhelm J, Fassett JT. Regulation of hepatocyte cell cycle progression and differentiation by type I collagen structure. Current Topics in Developmental Biology. 2006;72(05):205-236\n'},{id:"B103",body:'\nTalaei-Khozani T, Khodabandeh Z, Jaberipour M, Hosseini A, Bahmanpour S, Vojdani Z. Comparison of hepatic nuclear factor-4 expression in two and three-dimensional culture of Wharton’s jelly-derived cells exposed to hepatogenic medium. Romanian Journal of Morphology and Embryology. 2015;56(4):1365-1370\n'},{id:"B104",body:'\nKhodabandeh Z, Vojdani Z, Talaei-Khozani T, Jaberipour M, Hosseini A, Bahmanpour S. Comparison of the expression of hepatic genes by human Wharton’s jelly mesenchymal stem cells cultured in 2D and 3D collagen culture systems. Iranian Journal of Medical Sciences. 2016;41(1):28-36\n'},{id:"B105",body:'\nKryou C, Leva V, Chatzipetrou M, Zergioti I. Bioprinting for liver transplantation. Bioengineering. 2019;6(4):95\n'},{id:"B106",body:'\nMcCarty WJ, Usta OB, Yarmush ML. A microfabricated platform for generating physiologically-relevant hepatocyte zonation. Scientific Reports. 2016;6:26868\n'},{id:"B107",body:'\nYen MH, Wu YY, Liu YS, Rimando M, Ho JHC, Lee OKS. Efficient generation of hepatic cells from mesenchymal stromal cells by an innovative bio-microfluidic cell culture device. Stem Cell Research & Therapy. 2016;7:120\n'},{id:"B108",body:'\nJu X, Li D, Gao N, Shi Q , Hou H. Hepatogenic differentiation of mesenchymal stem cells using microfluidic chips. Biotechnology Journal. 2008;3(3):383-391\n'},{id:"B109",body:'\nFranzen N, van Harten WH, Retèl VP, Loskill P, van den Eijnden-van Raaij J, IJzerman M. Impact of organ-on-a-chip technology on pharmaceutical R&D costs. Drug Discovery Today. 2019;24(9):1720-1724\n'},{id:"B110",body:'\nWilke RA, Lin DW, Roden DM, Watkins PB, Flockhart D, Zineh I, et al. Identifying genetic risk factors for serious adverse drug reactions: Current progress and challenges. Nature Reviews. Drug Discovery. 2007;6(11):904-916\n'},{id:"B111",body:'\nVan Den Berg A, Mummery CL, Passier R, Van der Meer AD. Personalised organs-on-chips: Functional testing for precision medicine. Lab on a Chip. 2019;2:198-205\n'},{id:"B112",body:'\nMcGettigan P, Henry D. Use of non-steroidal anti-inflammatory drugs that elevate cardiovascular risk: An examination of sales and essential medicines lists in low-, middle-, and high-income countries. PLoS Medicine. 2013;10(2):e1001388\n'},{id:"B113",body:'\nMazaleuskaya LL, Sangkuhl K, Thorn CF, Fitzgerald GA, Altman RB, Klein TE. PharmGKB summary: Pathways of acetaminophen metabolism at the therapeutic versus toxic doses. Pharmacogenetics and Genomics. 2015;25(8):416-426\n'},{id:"B114",body:'\nCaddeo S, Boffito M, Sartori S. Tissue engineering approaches in the design of healthy and pathological in vitro tissue models. Frontiers in Bioengineering and Biotechnology. 2017;5:40\n'},{id:"B115",body:'\nCayo MA, Mallanna SK, Di Furio F, Jing R, Tolliver LB, Bures M, et al. A drug screen using human iPSC-derived hepatocyte-like cells reveals cardiac glycosides as a potential treatment for hypercholesterolemia. Cell Stem Cell. 2017;20(4):478-489.e5\n'},{id:"B116",body:'\nJia B, Chen S, Zhao Z, Liu P, Cai J, Qin D, et al. Modeling of hemophilia a using patient-specific induced pluripotent stem cells derived from urine cells. Life Sciences. 2014;108(1):22-29\n'},{id:"B117",body:'\nSa-ngiamsuntorn K, Wongkajornsilp A, Phanthong P, Borwornpinyo S, Kitiyanant N, Chantratita W, et al. A robust model of natural hepatitis C infection using hepatocyte-like cells derived from human induced pluripotent stem cells as a long-term host. Virology Journal. 2016;13(59):1-18\n'},{id:"B118",body:'\nChoudhury Y, Toh YC, Xing J, Qu Y, Poh J, Huan L, et al. Patient-specific hepatocyte-like cells derived from induced pluripotent stem cells model pazopanib-mediated hepatotoxicity. Scientific Reports. 2017;7:41238\n'},{id:"B119",body:'\nPaganelli M, Dallmeier K, Nyabi O, Scheers I, Kabamba B, Neyts J, et al. Differentiated umbilical cord matrix stem cells as a new in vitro model to study early events during hepatitis B virus infection. Hepatology. 2013;57(1):59-69\n'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Ana Sofia Martins Serras",address:null,affiliation:'
Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Portugal
'},{corresp:null,contributorFullName:"Madalena Zincke dos Reis Fernandes Cipriano",address:null,affiliation:'
Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Portugal
Fraunhofer Institute for Interfacial Engineering and Biotechnology IGB, Germany
'},{corresp:null,contributorFullName:"Pedro Miguel da Graça Silva",address:null,affiliation:'
Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, University of Lisbon, Portugal
Industry 4.0 has both expanded the possibilities of digital transformation and increased its importance to manufacturing, with an emphasis on globalization, international trade, and foreign direct investments. Industry 4.0 combines and connects digital and physical technologies including artificial intelligence, the Internet of Things, additive manufacturing, robotics, cloud computing, and others to drive more flexible, responsive, and interconnected enterprises capable of making more informed decisions [1]. The infusion of digital technologies in the value chain processes of research and development, design, production, marketing, distribution, and customer services will drive efficiency in production, thereby increasing the ambits of international trade.
Developed in Germany, currently, Industry 4.0 has become the most discussed issue in the industrial arena in the world. Both managers and policymakers from developed, emerging, and developing countries are debating this issue about how they can participate in this fourth industrial revolution as well as save them from the fallout of this advancement. The issue is still evolving, and experts from all spheres of industry and markets are debating on it. The objective of this chapter is to participate in this debate and explore how Industry 4.0 will evolve in the coming years and how it might affect international trade and the global value chain. We will take an in-depth look into what exactly is Industry 4.0 in our globalized context, what it brings to the table when it comes to international businesses and how international organizations can benefit from Industry 4.0 in their globalization strategies? As a matter of fact, Industry 4.0 outperforms the previous industrial revolutions we have gone through during the past centuries. The fourth industrial revolution is the result of the combination between the real and the virtual world, in which deep learning encourages and challenges human capacities and frontiers, particularly, with the increase of cyber-physical systems. Indeed, the new industrial revolution which develops deep learning is not limited to the use of automation systems based on machine learning, but autonomous ones that do not systematically depend on human beings and which can learn and act by themselves. Industry 4.0 refers to many concepts such as artificial intelligence, smart technologies, smart factories, smart automation, or smart management like the implementation of enterprise resource planning and automation of robotized processes. The global business environment has already started to enhance efficiency with futuristic and high-value-added technologies, from which we are not able to see the frontier clearly for now.
Firstly, we will undertake a brief literature review to explain how we structured our work. We will then be having a great detailed analysis of Industry 4.0 and its main components and how it is changing the way corporations do business in an increasingly connected world. Parallelly, we will explore the opportunities that the fourth industrial revolution brings as well as the challenges which emerged from this new revolution in order to counterbalance and give a realistic view of the latter. Finally, we will illustrate the major strategies that can enable the organization to avail opportunities emanated from Industry 4.0.
2. Opportunities and strengths of Industry 4.0
Industry 4.0 contributes to the virtualization of a physical production environment that facilitates connectivity and interaction between the machines as well as man and machines in real-time. The automation and connectivity as well as machine learning facilitate the inter-connectivity and improve the production process and bring several benefits to the organization. Some of them are presented in the following sections.
2.1 Generator of efficiency
Industry 4.0 is a generator of efficiency. Indeed, the great use of technologies within the different steps in the supply chain helps with optimizing the latter. It is, therefore, cost-effective, time-effective and it globally enhances productivity as well as flexibility and quality of outputs, which also raises the overall reliability of the firm and so the value of the company and its competitiveness. Industry 4.0 is not only about using high technology machines to produce more rapidly. There is indeed much more to that. Industry 4.0 can contribute to streamlining the value chain thanks to its transformation of every aspect of the production process from the logistics, passing through the managerial issues, to the networks, and more generally, the whole structure of firms in the network.
First of all, firms can benefit from advanced planning and controlling with relevant, real-time data [2]. Indeed, the collection and great use of data help with a greater inner and outer communication and organization, even from an international perspective: from a headquarter in Quebec City (Canada) to a manufacturer in Dhaka City (Bangladesh), for instance. Planning is simple and effective, and accessible for all employees who need to access it, and can be easily changed. The improvement of communication also implies a greater control of the organization thanks to easy access of the information, anywhere, anytime.
Data is the basis of all the improvements around artificial intelligence and the comprehension of the opportunities that can be taken in the organizations. Used correctly, data and communication tools can help firms to better respond to customers’ demands and allow a better accuracy of forecasts too. Data within the industry can help to see what should be improved in terms of production methods to gain efficiency. In that sense, they can also more easily identify bottleneck products which would result in better opportunity costs. Firms can also benefit from greater management and control thanks to adapted software within the firm. Data can be used to analyze production time and costs, as well as comparisons of portfolios of suppliers and materials to get the best of their interest. It allows a rapid reaction to changes and errors. It also allows a quick adaptation when it comes to stock levels, wherever it is from the production or the purchasing teams’ perspectives. Finally, data is the base of artificial intelligence. Thanks to machine learning, data is used to learn from mistakes and successes, which is crucial to be exponentially improving.
Thanks to data, programs are elaborated to improve the business networks such as suppliers with industries or with clients, or from clients to employees when they make a requirement for a change in the process of making an order. The communication is smoother, quicker, and easier to take action. Technologies also allow better safety of work conditions. The efficiency of new technologies allows companies to be more sustainable thanks to smart production facilities, which allows a better allocation of resources and vertical networking of smart production systems. The vertical networking of smart production systems can be defined as Smart factories and smart products, and the networking of smart logistics, production and marketing, and smart services, with a strong needs-oriented, individualized and customer-specific production operation [3]. Most firms affirm that Industry 4.0 and its innovations contribute to efficiency and profitability [4]. Industry 4.0 gives companies a better competitive advantage. This has a great impact on a company’s profitability. This is partially due to a reduction of costs from the efficient use of resources. On top of this, we can observe the benefits of Industry 4.0 through its four main components [3]:
The vertical networking of smart production systems: Vertically integrated Smart productions use deeply integrated data in order to rapidly orient the production in a customer-specific direction depending on the demand and the stock levels. The production is monitored by cyber-production systems (CPS) and smart sensor technologies (SST) that automatize the organization, making it autonomous. As a result, maintenance and management of production systems are optimized. All the processes at all stages and the resources that come with them are logged, which helps to perpetually update the fluctuations and adapt quickly to any movement of these factors. In a nutshell, the goal of this vertically integrated system is the efficiency of resources, and the satisfaction of specific, individual requirements of customers. These advanced systems allow firms to communicate in real-time with their supply chain partners across the globe, from producers to the clients and suppliers, and consequently to adjust their global supply chain on a continuous basis.
Horizontal integration via a new generation of global value chain networks: The horizontal integration is a new model of the value-creation network: optimized real-time networks that enable integrated transparency, offer a high level of flexibility to respond more rapidly to problems and faults, and facilitate better global optimization [3]. Similarly, to the previous model of integration, horizontal integration works via CPS, in order to log and meet all the logistics challenges continuously (the traceability, the accessibility, management of warehouses, and production). Processes are therefore more flexible in every step of the value chain. Modifications and adaptations following the customer’s requirement can be made at any level.
Through-engineering across the entire value chain: The third main characteristic of Industry 4.0 is cross-disciplinary through-engineering across the entire value chain and across the full life cycle of both products and customers [3]. It consists of the development of integrated and coordinated to product-life-cycle production systems that creates an optimization of the relation between the production systems and the product development. The key to this component of I4.0 is also the deep integration of data, used at every step of the value chain.
Acceleration through exponential technologies: The fourth main benefit of I4.0 is its impact on flexibility, individualization, and cost savings in terms of industrial processes thanks to its ever-growing set of innovative solutions.
Autonomy: Artificial Intelligence allows automation systems to be highly cognitive and autonomous thanks to advanced robotics and sensor technology that can perfect each individual production process.
Safety and quality: Nanomaterials and nano-sensors allow the close monitoring of production for better quality assessment and safer collaboration of humans with next-generation robots.
Automated logistics: The use of AI programmed machines like drones to make inventories, driverless vehicles in factories and warehouses to deliver components is particularly efficient thanks to their ability to function day and night under any weather conditions. These logistics solutions of smart factories allow for cost-cutting, flexibility, reliability, and time savings.
3D printing: Additive manufacturing (3D Printing) brings new functionalities and higher complexity of products without additional costs and new inventory management solutions thanks to delayed differentiation of products allowing for smaller stocks, and supply chain risk pooling between different factories. There are, however, still challenges to overcome before additive manufacturing can make an impact on manufacturing sectors given the fact that this technology is still expensive and unit cost of production is high, and do not follow economy of scale principles.
2.2 Customization
The most blatant of the effects of efficiency in this modern revolution is customer satisfaction. Indeed, thanks to the advanced technologies, customers demand is well – if not above expectations – aligned with the market’s needs and wants while remaining highly profitable for the firm.
Customization is an important issue in the global manufacturing industry, and its relevance is expected to even increase in the future. Customers want to customize the design of their products and by influencing the development and production processes at an early or even late stage. This tendency creates the need for manufacturing companies to move from the objective of better products for their customers to the objective of an individualized understanding of customer needs and specialized, industry-specific solutions [5]. That is to say, a major shift from an economy of scale to an economy of customization regardless of the location of production sites in the global value chain.
This ongoing change of customers’ needs results in more and more system complexity in system design as well as in assembly. Furthermore, commissioning can only be partially compensated by manufacturers’ standardization and modularization efforts. Nevertheless, end-to-end product data modeling from engineering to commissioning enables efficient production at locations with a global presence and supply chain, as well as, an efficient way to cope with the increasing product complexity resulting from the demand for customized system solutions [6]. One way to implement individualization in the production process is through assembly line production systems. Modern assembly line systems have the increasing ability to offer each customer a different product that is better suited to their needs and preferences. These assembly line systems are enormously profiting from the upcoming Industry 4.0 technologies. Moreover, this development enables the proposal of business models covering product customization, i.e., customers can change attributes of their product once production of the product has started. This business model requires manufacturing tools to be able to make decisions online and negotiate with the customer on the changes that can be made, depending on the workload flowing through the production system [7]. The ability to make changes online also reduces the disadvantages of the large geographical distance between the manufacturer and the customer caused by international business activities.
Assembly line production systems will also be affected by an increase in flexibility in production. Bortolini et al. [8] state that products produced in assembly lines will not only be able to be personalized but that late customization (i.e., after the order has been placed) will also be possible because real-time information on the status of the production process will be available. This means that customers will not only be involved in the definition and design of the product and its specifications, as is the case with mass customization products but will also be launched once in a late customization mode [9].
In contrast, mass-customized production facilities typically produce large volumes of products that share a common core but may be customized to a certain degree [9], creating production process sections with repetitive larger lots (e.g., automotive press shop) and sections of high product variance (e.g., final automotive assembly). The customers of mass-customized production factories typically customize their products based on a predefined set of configuration options, which can be integrated into a common modular architecture. Mass-customized production type factories are typical in the automotive industry, automotive Tier-1 suppliers, and, to some extent, in the truck, bus, agricultural, and construction equipment sectors. Industrial equipment manufacturers – where factories simultaneously have large production volumes and accommodate an ever-increasing number of variants – run mass- customized production type factories as well.
Therefore, the strategy of providing differentiated products leads to a paradigm change in manufacturing planning, posing new challenges for industrial activities. To satisfy the new kind of markets, industries had to adopt agile models, exploiting the competitive advantages of each organization [10]. These manufacturing models intend to face the uncertainty of the market by increasing the response capability of the organization in order to satisfy the customers with similar costs to mass-production industries [11]. Handling the production of large amounts of customized products presents a tough challenge since product differentiation hampers scale economies.
However, managing the production of personalized or customized goods will be quite demanding, given their different requirements. Finally, when late customization of the customer is possible to be accepted and when it is not, it depends on the production sequence in execution, and when it is possible to apply to re-sequence to incorporate the late customizations. Moreover, the advantages of late customization processes can be achieved only if the system is autonomous and can keep running the fabrication process. The customer needs real-time information about the evolution of the production of its personalized product [12]. And, as Kietzmann et al. [13] comment in the context of additive manufacturing, As with most disruptive technologies, it is likely that we will over-estimate the potential of 3-D printing in the short term while underestimating it in the long term [13]. In particular, for manufacturing companies, it can be concluded the widespread adoption of the constituent technologies has the potential to transform the location and organization of these production firms worldwide.
2.3 Big data analytics
Before Industry 4.0, companies used traditional data sources such as production records, internal accounts, and market research reports with a limited range for their decision-making process. The way of data sourcing is changing. Data is more and more generated from sources like sensor-generated data from smart products and data from search engines and social media sites. This technological shift offers multinational compagnies (MNC) the opportunity to access new worldwide business-relevant information. Additionally, technical progression regarding computing power and data storage costs is taking place. This results in the development of big data analytics [14, 15, 16].
To understand the innovational power of big data analytics, it is important to understand the changed concept about time in comparison to data analytics before Industry 4.0. Big data analytics is looking into the future and tries to generate existing and new data sources. The traditional role of information technology has been more backward-looking and concerned with monitoring processes and notifying management of anomalies. Firms that have adopted big data analytics report improvements in productivity and financial performance. For example, analysis of big data can enable managers to identify defects, faults, and shortcomings in the production process at an early stage, optimize automation processes and carry out trend analyses, use resources more efficiently and carry out predictive maintenance [17].
The potential implications of big data analytics for international business are several. In particular, firms will be able to monitor emerging trends and opportunities in overseas markets without the need to make substantial resource commitments in those local marketing affiliates, and they will be able to optimize more effectively their supply, production, and distribution activities around the world [18]. But there are two major drawbacks. The first is that the availability of good-quality big data may well be a source of value for firms, but successful firms will require a range of technical and governance capabilities to analyze and operationalize that data so as to realize the potential benefits [19, 20]. The second is that individuals’ privacy will be under threat from widespread big data applications. Like Facebook knows what we like, Google knows what we browse, and Twitter knows what is on our mind [21].
New data protection laws and/or stronger industry self-regulation will need to be formulated to safeguard the privacy of individuals and companies, and to put limits on what data can be accessed, stored, and transmitted both nationally and across borders [22]; Rose et al. [23]. It has to be discussed who will have legal title over what, and who will bear legal responsibility for, products that involve consumer-generated intellectual property [24] and how will these issues be handled in cross-border settings? Some form of (transnational) governance regime will be necessary to regulate this dilemma between the benefits of big data analytics described earlier and data privacy. Finally, this may influence or even determine the abilities of firms to maximize the commercial potential of big data analytics [25, 26].
2.4 Environmental impact: Energy sustainability
The optimization of production and logistics processes allowed by Industry 4.0 could have a major impact on the management of the environmental crisis. Indeed, the processes of Industry 4.0 that allow energy savings and waste reductions to cut costs for firms would be equally beneficial for the preservation of natural resources and biodiversity. The Sustainable Development Goals established by the United Nations include the improvement of energy efficiency and better management of waste. Therefore, the improvements brought by Industry 4.0 would be in adequation with government environmental policies and regulations, which will most probably become much stricter in the coming decades.
Industry 4.0 allows improved production management thanks to the production monitoring capabilities of Industry 4.0. Constant monitoring of production efficiency and intelligent quality control offer great opportunities in terms of production efficiency, waste reduction, and improved reliability. Consequently, firms would have a better energy efficiency [27]. Industry 4.0 allows firms to make informed decisions based on the data-mining possibilities brought by sensors and AI. Relevant statistics on production efficiency, product life cycle, and energy consumption will be available to the firms [28]. Industry 4.0 will also connect the consumer with its energy consumption thanks to the sharing of statistics made possible by smart data communication technologies [29]. Energy consumers will be informed on their consumption, and this will promote self-responsibilities.
However, these improvements could easily be counterbalanced by the fact that Industry 4.0 requires the collection and storing of massive quantities of data in data centers, which significantly contribute to global warming. But this is not a fatality, and firms should not be stopped by this challenge, as innovative solutions allow the heat produced by data centers to be reused as a heating source. This strategy is especially used in Nordic countries such as Finland or Sweden.
3. Evolution of Industry 4.0 and implications for global business
Research on Industry 4.0 is numerous and rapidly evolving. Many types of research have addressed the evolution of the Industry 4.0 (I4.0) phenomenon and its contribution to international business activities. Especially the major drivers of I4.0 that underlines its involvement to enhance current business practices by streamlining both the production and supply chain networks [30, 31]. Those developments in Industry 4.0 have huge implications on the way the current business activities both at home as well as across the globe (i.e., international trade) are being conducted. Mamad [2] has addressed how Industry 4.0 works and has made a broad illustration of the subject in detail through an exhaustive literature review. Deloitte [3] provided an overview of the beneficial application of Industry 4.0 to enhance organizational processes. McKinsey’s [6] study focused on customization and explained how Industry 4.0 has reshaped the manufacturing industry to fit customer demand and how companies can reap profit from these upcoming innovations by showing application opportunities. UNIDO [32] report has presented an impact analysis and showed how Industry 4.0 could contribute to environmental sustainability. Jayashree et al. [33] showed how Industry 4.0 could contribute to developing dynamic capabilities and realizing triple bottom line (TBL) sustainability. Bibby et al. [34] give some tools to assess the current level of Industry 4.0 maturity of businesses that want to transition to I4.0 and better approach the issue. Dhanpat [35] reminds us of the underlying dimensions of I4.0 as a growing need for learning capacities of smart technologies to cope with the new era of cyber-physical systems. Ahmadi et al. [36] addressed the main architecture models of value-chain structure in Industry 4.0.
3.1 Industry 4.0 and international trade
Industry 4.0 brings both enormous opportunities and challenges for the industry and international trade. It helps not only to modernize the production process and self-initiated execution but also allow the managers to undertake the management of the production process across the globe by creating a flexible global supply chain.
The fourth industrialization is changing the way we perform different kinds of business activities by drawing its main components and their contribution to the business environment. Industry 4.0 is the implementation of cyber-physical systems for creating smart factories by using the IoT, big data, cloud computing, artificial intelligence (AI), and communication technologies for information communication in real-time between the man-machine and machine to machine communication which is redefining the global value chain.
According to Horvàth et al. [37], there are five key drivers of Industry 4.0: Digitalization, optimization, and customization of the production, automation, and adaptation, human and machines interactions, and collaborations, high value-added offers, and automatic exchanges of data and communication. The fourth industrialization has contributed to critical transformation to the international business environment in the different stages of an organization such as human resources, financial systems, management, organizational structure, or production processes.
Those key drivers are highly illustrated by the implementation of cyber-physical systems, the internet of things, smart factories, smart technologies, cloud computing, and big data. The latest architecture of industrialization pursues new objectives and faces completely different challenges that increase in a global perspective. Industry 4.0 offers an opportunity of restructuring declining manufacturing industry in the high-cost-country (HCC) and permit to maintain a strong industrial base in developed countries [38]. It could represent a great opportunity in the context of declining manufacturing in the developed markets. Industry 4.0 answers three key challenges: better competitiveness, flexibility, and agility by facing global offer end demand fluctuation and the regionalization of production [38]. To sum up, Industry 4.0 can be understood as multiple solutions built to change the international industrial sector to gain stronger competitive positions, market shares, especially within a risky business environment. This ambition should be realized by using smart technologies and factories that ensure efficient response to the variation of the global market by improving competitiveness and agile management, which will conduct the changes implied by Industry 4.0.
3.2 Industry 4.0 and implications for international businesses
Central to the fourth industrial revolution is an interconnected network. The internet enables many small firms to participate in global trade, thus, leading to more inclusion. It makes it possible for more products to be exported to more markets, often by newer and younger firms. A 10-percent increase in internet use in the exporting country is found to increase the number of products traded between two countries by 0.4 percent. A similar increase in internet use of a country pair increases the average bilateral trade value per product by 0.6 percent [39]. The transformation implied by the fourth industrialization, Industry 4.0, might lead to significant changes in existing business models allowing new ways to create value. These changes are expected to result in the transformation of traditional value chains. Industry 4.0 affects three elements of manufacturing small and medium enterprises (SMEs): value creation, value capture, and value offer [37].
The 4th industrialization will completely change global value chains by transforming its practices and objectives. The purpose is not limited to monetary rewards but includes new trends such as the willingness to gain efficiency, to create and sustain global competitive advantages, finding new ways of producing, generating innovations, stimulating automation and learning, or even increasing customer implications in the production processes.
Several opportunities generated by Industry 4.0 are transforming the current business levels and activities through its drivers. Multiple business models are flourishing in the Industry 4.0 era. One of the fast-emerging models of them is the expectation [40]. The expectation represents a combined model in which a firm built its expertise through the production processes of its general offer. This new trend led a company to create consulting services (about products or processes) or a new platform-based model. The platformization of the product refers to a company that uses its know-how and intensive capacities of production to create digital products that answer customer queries by using a cloud-based platform. The platformization of processes reflects the use of the smart factories’ concepts and internal processes to transform their capacities into a digital platform. The value created is the result of an integrated solution of digital products and related Information technologies services. The expectation gives us an illustration of how I4.0 changes our model to do business and how complex it is to put in place within an organization and will impact the current business activities. The major Industry 4.0 drivers will redefine business activities [30].
Internet of things (IoT) is retained as a pillar of I4.0. This type of technology provides access to the internet by using deep learning technologies. This equipment transforms machines into smart objects that could, for instance, detect wear, control the performance of the production process, plan the capacity or even manage stocks in real-time. Cloud computing allows interconnection between computers and the internet. It can solve many issues such as Big Data storage as well as the costs and capacities linked to this storage.
Cyber-physical systems (CPS) are mechanisms that allow Humans, software, and machines to interact. It implies an aggregate level of networking. The main purposes of this technique are, by creating such virtual interconnection, to exchange key information to make better strategic decisions. It establishes strong links between production processes, machines, and the virtual world, which work and communicate thanks to computation and the internet in real-time cooperatively. The machines and physical systems will be synchronized to software, and it will allow the control and assessment in real-time production efficiency, adjusting it and making the right strategic decisions easily. Also, CPS enhances the integration of autonomous machines and the collaboration between humans and cyber work.
Autonomous robots are created with deep learning capacities. Deep learning technological advances permit a robot endowed with artificial intelligence to adapt itself to its working environment, make adjustments that enhance its working environment, and take appropriate decisions when observing disruptive issues. This is one of the major pillars of I4.0 that is very challenging as it can replace Human works forward and generate greater benefit for a company. Enterprise resource planning (ERP) systems are considered the backbone for the Industry 4.0 [41]. ERP systems, for instance, the systems Applications and products in data processing (SAP) software, helps companies in various areas, to manage better their processes, and enhance their efficiency by integrating its operations to increase flows of information and collaboration between the company and its partners. ERP systems help companies in many areas starting from increasing better information sharing between departments, improving workflow, better supply chain management, integrating of data, processes, and technology in real-time across internal and external value chains, standardization of various business practices, improve orders management and accurate accounting information of inventory management [42].
The result of the use of the different drivers (IoT, CPS, Internet of Service, ERP) will lead to the creation of smart factories, which brings all the smart tools and models together in its production model. This integrated system will facilitate the globalization of production and expansion of global supply chain. It is true that some of manufacturing activities might be re-shored but at the same time, the new smart technology will allow firms to reconfigure their production network overlooking the national boundaries and distance. That is the reason why it is still in the pre-paradigmatic stage of Industry 4.0. implications it is a continuous process that conducts the transformation of our current or traditional methodologies to do business and conceive industrial purposes and processes. As a result, the production model of smart factories becomes cost-effective and flexible to market changes and sustainable, which would reflect the highest level of effectiveness feasible to achieve. This newfound technological prowess will modify drivers of global production networks (GPN), reduce the importance of physical distance as well as re-configure the global value chain (GVC). The new global division of labor (NGDL) is likely to emerge and re-distribute the manufacturing activities integrating different hubs from both the developed, emerging, and developing markets.
4. Challenging issues related to Industry 4.0
There are no doubts about the enormous challenges that Industry 4.0 will bring to the current practice of production, consumption, and global value chain (GVC). Firms and policymakers need to take into consideration adequate strategies to better implement the Industry 4.0 systems, re-organize business activities by taking into consideration of new context and take other caution for the long-term growth of the fourth industrial revolution and reap profit from it. We will define and analyze in this section the challenges raised by Industry 4.0, starting with implementation challenges, then the challenges surrounding the management of Human resources, then the risks to data security, then the Big Data challenges, and finally, the challenges concerning the environment.
4.1 Implementation challenges and inequalities
As we established earlier, the transition to Industry 4.0 brings countless opportunities for businesses to increase their efficiency and development. However, there are many barriers to the implementation of Industry 4.0, the most important lackings are the shortages of skill-sets that are required in the Industry 4.0 phenomenon. There is also a lack of experience and hindsight on the transition, the necessity to remodel the entire organization, and the coordination of data resources. Added to these challenges are the inequality between SMEs and MNCs in terms of resources, focus, and strategies in the transition to Industry 4.0. This section will present the three main difficulties faced by firms integrating Industry 4.0.
4.1.1 Lack of experience and established models
The lack of experience is certainly one of the biggest factors that hold back the businesses from transitioning to Industry 4.0. era. Indeed, the transformation of the companies is very costly, and no clear business case is available as a reference for companies. It is very difficult to justify such investments when there is no perspective, no pattern to follow, and no successful case to reproduce. Therefore, most frequently, companies will either fail in their transition (60% rate of failure) or simply lack the necessary courage to follow through the process of radically changing their organization and investing as much time and resources.
To tackle this challenge effectively, some interesting research in the field has started to emerge, building the first tools to approach the transition. According to Bibby et al. [34], firms should begin by assessing the current level of Industry 4.0 maturity in their specific context or supply network. This analysis will help them determine their strengths and weaknesses and focus their improvement on the right area. Few academic research has been done so far in this area, and many research are done by consulting firms. As an example, in order to assess the industry maturity level of firms, two Industry 4.0 assessment models have been developed in 2016 by consulting firms, IMPULS management consulting GmbH (IMPULS) and PWC. While the PWC model helps companies self-assess their level of maturity based on various criteria, the IMPULS model is focused on delivering improvement advice based on the company’s preparation. More of these models are currently developing, showing that the challenge of the lack of experience will likely be overcome with time as Industry 4.0 spreads across the manufacturing world.
4.1.2 The cost of restructuring the firms
The transition to Industry 4.0 from a traditional organization requires the restructuring of the entire organization, as tasks are automated and decision-making processes are programmed. Every firm that will adopt Industry 4.0 system. We will have to create new business models and define a new strategy. Indeed, this transition requires rethinking the whole organization and processes, interconnecting departments, buying new equipment or modernizing the existing one, re-assigning roles to employees, recruiting new operators, and many other disruptions of their current model. These major changes have a great cost for any business on many levels: financially, of course, but also in terms of time. Therefore, firms have to be especially careful when investing in these transitions in order to not fail its implementation of Industry 4.0.
4.1.3 Advanced coordination across the firms
Another challenge of the implementation of Industry 4.0 is how to connect all data efficiently. Industry 4.0 requires the cooperation of all organizational units, from manufacturing, R&D, IT, to sales and finance departments. Sometimes the walls separating these departments are very hard to break, adding to the difficulty of the transition. But the coordination of functions is only part of the issue: Industry 4.0 requires the management of the large quantities of data generated by diverse sources in the company. For example, production data will have to be processed and coordinated along with data from customer information systems. Data Integration is, therefore, a very difficult task, and the firms need to have the necessary talent from data scientists that will be able to process and model this data.
4.1.4 Inequalities for SMEs compared to large firms
More than 98% of firms in the developed markets are considered as SMEs, and they are increasingly participating in the global value chains and global trades of goods, services, and components. Introducing the new I4.0 paradigm may have varying levels of difficulty depending on the size and available resources of the targeted firms. Starting conditions between Small and Medium Enterprises (SMEs) and larger firms are obviously very different and bring different challenges. According to Matt et al. [43], SMEs need specific strategies to properly implement I4.0 to their business model.
Large companies will usually follow the higher maturity level in the technological domain faster and more easily than SMEs because of the resources. Indeed, they have more money, expertise, and time to invest in this project. As a consequence, I4.0 is spreading more quickly across large companies which are investing and working intensively on introducing and enabling the necessary technologies. SMEs, however, are lagging behind because they lack the financial and human resources to research into the risks and potential of implementing I4.0. These difficulties further enlarge the gap between SMEs and large multinational companies. However, SMEs have an advantage over large companies, which have a much more complex organizational structure and production processes. Therefore, it is much easier to implement the necessary changes to the organization and culture of SMEs.
4.2 Human resources challenges
According to the study made by Glass et al. [44], across 176 SMEs and 71 large enterprises, numerous barriers to Industry 4.0 must be underlined across business processes and models. The most important challenges include, of course, the multiple issues which arise from Industry 4.0 strategy modeling and the growing need for highly skilled workers with specific know-how, particularly oriented in high technologies, smart engineering, automation, and digitalization competencies and expertise, etc.
We can easily understand that, beyond such technical and future-oriented subjects applying to industries, which is already developed in multiple kinds of business corporations, human resources remain a major challenge for the spread of Industry 4.0 concepts, methodologies, models, and tools. For instance, Mubarak and Petraite [45] have raised a fundamental HR component of Industry 4.0 implementation: The concept of digital trust. Digital trust is situated between trust and Industry 4.0 implementation and implies HR issues. We can identify major human resources issues related to Industry 4.0 as the followings:
4.2.1 The dangers of the technocentric approach
When digital trust refers to a new working environment where technology and Humans interact for the welfare of a company and to answer the stakeholder’s needs, a danger of this approach would be the growth of technocentric businesses. In fact, in this model, the stakeholders will give more confidence to technologies, artificial intelligence, and automation to run their business activities and corporations rather than human beings. Indeed, The Deloitte reports questioned the preparedness of HR in an era of Industry 4.0 and the global value chain. Among the 32% of firms that are ready to face technological challenges, only 12% are ready to face the challenges emanating from the Industry 4.0 ecosystem [46]. This statistic illustrates the new trends for companies to focus on efficiency with the highest technological implementation rather than hiring people and maintaining their position through retention policies.
4.2.2 The digital transformation: The increase of ISHR, ARP systems, and ERP
The information systems of human resources (ISHR) illustrate the Industry 4.0 impact upon Human resource function. Indeed, the ISHR technologies permit to automate, standardize with the intervention of smart technologies, activities that belong to HR functions as the following ones: Administrative procedures, training, payrolls management, recruitments, talents management, or even career development of employees within a company [47, 48]. The different systems like automation of robotic processes (ARP) and enterprise resource planning (ERP) were conduct to rethink the HR function. Those different tendencies push HR workers to acquire new competencies geared towards smart technologies and which are transforming their workstation, and which are implying news risks. On the one hand, we can identify the complexity of adaptation to the rapid change of HR function but also the risks linked to the security of information systems and the possibility to lose sensitive data to the benefit of the competition. As a reminder, ISHR systems such as the one proposed by the SAP software can contain confidential data such as the wages, the positions, the personal data of each employee, their curriculum vitae, the annual reports, information posted on the different job board and the main partners of the company, etc.
4.2.3 The recruitment, retention, and attraction of new talents
The fourth revolution required a highly-skilled workforce to be implemented, developed, used and maintained. As a result, a wide range of industries needs a certain level of cooperation between machines and workers. If Industry 4.0 implies this tendency, it also underlines the growing trend of Google, Apple, Facebook, Amazon, Microsoft (GAFAM) to conquer traditional industries in which they have the necessary knowledge and capacities to become undisputable competitors in multiple fields [49]. As an example, we can remember the creation of the Google autonomous car, the collaboration between the Volkswagen group with Amazon web services to collect and analyze its industrial data and becoming a major global leader of the automotive industry, and even the collaboration between Apple and General Electric (GE) to create new applications for the internet of things (IoT) platforms that benefit to GE industries purposes thanks to IOS (exploitation system owned by Apple) opportunities. Industry 4.0 increases competition, in traditional industries and markets (but not only), which seems to be overwhelmed regarding the fast spread of the fourth industrial revolution. To overcome these challenges, companies must recruit high skilled workers, implementing continuous reskilling, learning, and training programs in their HR policies [44]. Besides, one of the major HR issues is constituted by the launch of retention practices which will reduce the diffusion of confidential business information and enhance efficiency and profitability by staying competitive at the same time. We can understand that the rise of high skilled workers’ demand would create a danger if it is not associated with HR policies to enhance workforce abilities to work in a new smart and autonomous workplace.
4.2.4 The adaptation to change
One major issue to face urgently for HR function is the resistance to change. According to Deloitte [50] report, 17% of their interviewees are ready to manage working environments composed of people, robots, and AI interacting together when 60–70% will fail because they do not manage the adaptation to change properly. Also, Dhanpat et al. [35] confirmed this problem. They have shown that some employees can be resistant to change by being afraid of losing their jobs and being replaced by machines. Bonekamp et al. [51] also agree on the fact that the introduction of Industry 4.0 led to the suppression of standardized tasks by smart and autonomous systems. As a consequence, strong pressure is put on HR managers who require highly skilled people, to train employees and manage to dismiss workers for whom their tasks will be replaced by smart technologies to gain efficiency and competitiveness in the global market. In 2016, The World Economic Forum (WEF) already raised awareness by making an announcement before the opening of the Davos forum: around 5 million jobs in 5 years will be suppressed within 5 years in the main global economies [52]. It is necessary for the HR function globally to answer and react to the exponential expectations of the fourth industrial revolution by taking into account its effect on the global workforce demand and its impact on the global economy and competitiveness.
4.3 Big data challenges (storage, RGPD, societal challenge)
The fourth industrialization reveals new challenges in business activities such as the management of Bigdata and cybersecurity. Multiple obstacles to Industry 4.0 remain redundant: The constraints are numerous because the digitization of the industry poses formidable problems of standardization and cybersecurity [52].
Indeed, through their researches, one of the major challenges implied by this concept in the working environment is the deployment of Big Data, which creates a growing need to provide a legal framework for the protection of personal data and private life. Among the different cyber issues reported in Industry 4.0, the Deloitte report [50] identifies the top 10 cyber threats and their major data protection concerns.
Indeed, if legal restrictions increase to manage big data challenges, the different issues persist. In terms of an international legal framework, the ISO norm ISO/IEC 27001 defines the data security management for sensitive subjects such as financial, intellectual proprietary, employees, or even data entrusted to another company in the context of business activities. This norm is also called “Management systems of Information security” [53]. In addition, the European Union has implemented the General Data Protection Regulation (GDPR) to mitigate different kinds of challenges affiliated with the management of Big Data. GDPR regulations refer to “imposing a legal framework on the processing of personal data” [54].
However, despite the willingness to build an international legal framework to reduce risk related to Big data cybersecurity, there are still a long-ways to go for a proper framework of Industry 4.0. For instance, Deloitte report has shown that one out of four firms is not developing, implementing, or documenting the industrial cybersecurity (ICS) specific policies and procedures, and more than 33% of manufacturers have not performed any cyber risk assessments specifically focused on the ICS operating on their shop floors, resulting in a potentially significant risk to their operations [55].
In terms of internal management, other issues can arise when a company starts using big data analytics in order to grow. The challenges to take into account include the lack of proper understanding of big data, and therefore, proper usage of the latter; data growth issues, or, “what do I do with this much information?” because the collection of such an amount of data must be useful for something. But what, exactly? Another issue is the confusion when selecting a Big Data tool. There is an increasing number of tools available on the market for firms to have reports and data concerning their businesses. However, it is often not very precise and easy when one is not really aware of what is best for them. This last point brings us to another issue which is the lack of professional expertise in the field of Big Data. Indeed, more and more companies are recruiting professionals and experts in the field of data, such as data scientists, engineers, and analysts. These professions are rare, and as the demand and supply rule confirms, it is quite costly for a firm to recruit, though it is a must when expecting to grow, especially in our current globalized market.
5. Strategies of Industry 4.0 implementations
Concerning the international strategies of Industry 4.0 applied to firms, we can find key references in terms of Smart Manufacturing architectures: Reference Architecture Model or Industry 4.0 (RAMI 4.0), Smart manufacturing ecosystem (SME), Intelligent manufacturing system architecture (IMSA). In Smart manufacturing, the architecture corresponds to the designing of the arrangement and connectivity of the organizational structure. The Smart manufacturing ecosystem (SME) provides a standard overview of Smart Manufacturing Systems (SMS). It has three dimensions: product, production, and business. It allows information circulation, in order to follow the production of products through its entire life-cycle. It focuses on the entire value chain and the interaction between the three dimensions. Each dimension comes into play in the vertical integration of enterprise systems (ERP), manufacturing operations management (MOM), and cyber-physical production system (CPPS) [36]. The IMSA is a 3D intelligent manufacturing system framework, consisting of life cycles, system hierarchy, and intelligent functions. It takes into account the standards and features of all intelligent manufacturing systems to a framework with key dimensions: Lifecycle, to represent the chain integration; system hierarchy, to control, workshop, enterprise, and cooperation levels; and finally, Intelligent Functions which illustrate resources, integration, interconnection, information fusion, and new business patterns, [36].
According to a BGC report on Industry 4.0, related to the German manufacturing industry, Industry 4.0 will be used by an increasing number of firms and generate significant productivity gains of this industry sector (90 to 150 billion EUR). The productivity will improve by 15 to 25%. If material costs are considered, productivity upgrades of 5 to 8% are realistic. Individual effect size depends on the specific manufacturing industry. E.g. industrial component manufacturers will see the largest productivity gains (20 to 30%), while automotive manufacturers may assume 10 to 20% [56]. Furthermore, Industry 4.0 will impact the revenue growth of the German industry. Need from manufacturers for improved devices and new data applications, as well as customer demand for a greater range of increasingly customized products, will provide further revenue growth of around 30 billion euros per year, equivalent to around 1% of German GDP.
The BCG study predicts that the growth and productivity increase described above will also positively impact the employment growth of 6% over the next decade. The need for mechanical engineering workers could increase even more – by up to 10 percent over the same period. In the next few years, the automation trend will replace some low-skilled workers in repetitive and monotonous tasks. However, the increasing use of big data analytics will increase the demand for workers with ICT skills. This shift of needed skills transformation is one of the most important challenges of future growth and innovation. Making the mandatory steps to be economically successful in the world of Industry 4.0 will cost manufacturers about 1 to 1.5 percent of their sales in absolute value over the next decade. Finally, it can be concluded that Industry 4.0 will transform the global value chain, labor market, and logistics.
6. Conclusion
Global trades are going through lots of volatility from geopolitical instability and natural disasters. The current situation requires businesses to develop their strategic goals for growth, risk management, and global supply chain for the short term, mid-term as well as long term. Manufacturing firms need to develop multi-pronged and multi-disciplinary approaches to address challenges facing current and future supply chain disruptions. The use of advanced technologies like artificial intelligence (AI) and Business analytics can be helpful to analyze large-scale data and keep track of supply chain movements in real-time and develop the ability to re-configure the Supply chain on short notice. A firm’s ability to succeed in global markets will depend on the capacity of the industry to adapt to a rapidly changing business landscape.
To sum up, Industry 4.0 seems to have reached heights when it comes to the organization of enterprises at a global level. We described how international organizations could benefit from Industry 4.0 doing international business. We explained how the components of Industry 4.0 had enhanced many aspects of SMEs and MNCs, by analyzing the evolution of the different phases of the historical context to come to such a strong, advanced stage. We, therefore, defined the industry and its key components to explain its contribution to the organization.
Managers need to develop the ability to identify the opportunities and the strengths brought up by this industrial revolution. We took a look into its efficiency features, and opportunities to satisfy the varied demands thanks to capabilities of customization, and the power of the use of Big Data Analytics, as well as the great impact that this evolution has on the environment. Nevertheless, all these benefits do not come without some challenges. Indeed, Industry 4.0 has full of potentialities of innovation and quite complex transformations to simplify and adapt organizations, especially in terms of human resources because robotics and automation will have huge a repercussion on the social aspect. Most especially, developing and emerging countries that participate in the global value chain by offering advantageous manufacturing production locations will face stiff competition between Industry 4.0 based technologies with those of cheap and abundant labor force in those countries. There is no option other than up-grading the workforce and integrating into the 4.0 era to face these new challenges in the era of Industry 4.0. Finally, as valuable as Big Data can be for the industry, we have found out that it is still a domain that requires particular attention since its use remains quite laborious.
Nonetheless, this modern revolutionary phase is not the last of its category. In fact, the very recent rise of Industry 5.0, a solution provider for people and the planet has flipped the script. Indeed, the new revolution of Industry 5.0 puts an emphasis on the well-being of the workers and captures all the added-value components of Industry 4.0 with the aim of prosperity in the new industry as an ambition for a better future.
\n',keywords:"industry 4.0, cyber-physical system (CPS), global value chain (GVC), global supply chain (GSC), big data",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80058.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80058.xml",downloadPdfUrl:"/chapter/pdf-download/80058",previewPdfUrl:"/chapter/pdf-preview/80058",totalDownloads:163,totalViews:0,totalCrossrefCites:0,dateSubmitted:null,dateReviewed:"November 25th 2021",datePrePublished:"January 16th 2022",datePublished:"April 28th 2022",dateFinished:"January 16th 2022",readingETA:"0",abstract:"Industry 4.0 is the natural consequence of the techno-industrial development of the last decades. It has the huge potentiality to change the way globalization of manufacturing and consumption of goods and services that take place in the global markets. This chapter will focus on the evolution of Industry 4.0 and how this new technological framework will create values for firms and consumers, and how we can use it for a firm’s competitiveness and save them from the fallout of its development. An extensive literature review shows that the multi-faceted technology will hugely impact the global value chain, global supply chain, and new global division of labor (NGDL). It will reconfigure and re-distribute the business activities in the developing, emerging, and developed country markets and small and medium sizes firms and MNCs. The rapid development of technological and human capabilities can allow firms to reap benefits from this technology. At the same time, there are many challenges related to skill shortages, technological issues, business ethics, and values that need to be overcome to reap a profit from this new technological advancement.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80058",risUrl:"/chapter/ris/80058",signatures:"Muhammad Mohiuddin, Md. Samim Al Azad, Selim Ahmed, Slimane Ed-Dafali and Mohammad Nurul Hasan Reza",book:{id:"9544",type:"book",title:"Global Trade in the Emerging Business Environment",subtitle:null,fullTitle:"Global Trade in the Emerging Business Environment",slug:"global-trade-in-the-emerging-business-environment",publishedDate:"April 28th 2022",bookSignature:"Muhammad Mohiuddin, Jingbin Wang , Md. Samim Al Azad and Selim Ahmed",coverURL:"https://cdn.intechopen.com/books/images_new/9544.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83969-147-8",printIsbn:"978-1-83969-146-1",pdfIsbn:"978-1-83969-148-5",isAvailableForWebshopOrdering:!0,editors:[{id:"418514",title:"Dr.",name:"Muhammad",middleName:null,surname:"Mohiuddin",slug:"muhammad-mohiuddin",fullName:"Muhammad Mohiuddin"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"418514",title:"Dr.",name:"Muhammad",middleName:null,surname:"Mohiuddin",fullName:"Muhammad Mohiuddin",slug:"muhammad-mohiuddin",email:"muhammad.mohiuddin@fsa.ulaval.ca",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038UqSfQAK/Profile_Picture_2022-05-13T10:39:03.jpg",institution:{name:"Université Laval",institutionURL:null,country:{name:"Canada"}}},{id:"465884",title:"Dr.",name:"Md. Samim",middleName:null,surname:"Al Azad",fullName:"Md. Samim Al Azad",slug:"md.-samim-al-azad",email:"dummy+141321254235241342342346983@intechopen.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"465885",title:"Dr.",name:"Selim",middleName:null,surname:"Ahmed",fullName:"Selim Ahmed",slug:"selim-ahmed",email:"dummy+1413435212254235241342342346983@intechopen.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"465886",title:"Dr.",name:"Slimane",middleName:null,surname:"Ed-Dafali",fullName:"Slimane Ed-Dafali",slug:"slimane-ed-dafali",email:"dummy+1413213512542352441342342346983@intechopen.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"465887",title:"Dr.",name:"Mohammad",middleName:null,surname:"Nurul Hasan Reza",fullName:"Mohammad Nurul Hasan Reza",slug:"mohammad-nurul-hasan-reza",email:"dummy+141321543254237325241342342346983@intechopen.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Opportunities and strengths of Industry 4.0",level:"1"},{id:"sec_2_2",title:"2.1 Generator of efficiency",level:"2"},{id:"sec_3_2",title:"2.2 Customization",level:"2"},{id:"sec_4_2",title:"2.3 Big data analytics",level:"2"},{id:"sec_5_2",title:"2.4 Environmental impact: Energy sustainability",level:"2"},{id:"sec_7",title:"3. Evolution of Industry 4.0 and implications for global business",level:"1"},{id:"sec_7_2",title:"3.1 Industry 4.0 and international trade",level:"2"},{id:"sec_8_2",title:"3.2 Industry 4.0 and implications for international businesses",level:"2"},{id:"sec_10",title:"4. Challenging issues related to Industry 4.0",level:"1"},{id:"sec_10_2",title:"4.1 Implementation challenges and inequalities",level:"2"},{id:"sec_10_3",title:"4.1.1 Lack of experience and established models",level:"3"},{id:"sec_11_3",title:"4.1.2 The cost of restructuring the firms",level:"3"},{id:"sec_12_3",title:"4.1.3 Advanced coordination across the firms",level:"3"},{id:"sec_13_3",title:"4.1.4 Inequalities for SMEs compared to large firms",level:"3"},{id:"sec_15_2",title:"4.2 Human resources challenges",level:"2"},{id:"sec_15_3",title:"4.2.1 The dangers of the technocentric approach",level:"3"},{id:"sec_16_3",title:"4.2.2 The digital transformation: The increase of ISHR, ARP systems, and ERP",level:"3"},{id:"sec_17_3",title:"4.2.3 The recruitment, retention, and attraction of new talents",level:"3"},{id:"sec_18_3",title:"4.2.4 The adaptation to change",level:"3"},{id:"sec_20_2",title:"4.3 Big data challenges (storage, RGPD, societal challenge)",level:"2"},{id:"sec_22",title:"5. Strategies of Industry 4.0 implementations",level:"1"},{id:"sec_23",title:"6. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Tim Y, Pan SL, Bahri S, Fauzi A. Digitally enabled affordances for community‐driven environmental movement in rural Malaysia. Information Systems Journal. 2018;28(1):48-75'},{id:"B2",body:'Mamad M. Challenges and benefits of industry 4.0: An overview. International Journal of Supply and Operations Management. 2018;5(3):256-265'},{id:"B3",body:'Deloitte AG. Industry 4.0: Challenges and solutions for the digital transformation and use of exponential technologies; 2014'},{id:"B4",body:'Kasim T, Haracic M, Haracic M. The improvement of business efficiency through business process management, economic review. Journal of Economics and Business. 2018;16(1):31-43'},{id:"B5",body:'Lasi H, Fettke P, Kemper HG. Industry 4.0. Business and Information Systems Engineering. 2014;6:239-242'},{id:"B6",body:'McKinsey. 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Laval University, Canada
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Although this chapter cannot provide a comprehensive account of the state of knowledge regarding plant saponins, we hope that it will help make saponins the focus of ongoing international cooperation.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Dorota Kregiel, Joanna Berlowska, Izabela Witonska, Hubert\nAntolak, Charalampos Proestos, Mirko Babic, Ljiljana Babic and\nBolin Zhang",authors:[{id:"179443",title:"Associate Prof.",name:"Dorota",middleName:null,surname:"Kregiel",slug:"dorota-kregiel",fullName:"Dorota Kregiel"},{id:"197451",title:"MSc.",name:"Hubert",middleName:null,surname:"Antolak",slug:"hubert-antolak",fullName:"Hubert Antolak"},{id:"198329",title:"Dr.",name:"Joanna",middleName:null,surname:"Berlowska",slug:"joanna-berlowska",fullName:"Joanna Berlowska"},{id:"198330",title:"Prof.",name:"Izabela",middleName:null,surname:"Witonska",slug:"izabela-witonska",fullName:"Izabela Witonska"},{id:"198333",title:"Dr.",name:"Charalampos",middleName:null,surname:"Proestos",slug:"charalampos-proestos",fullName:"Charalampos Proestos"},{id:"198334",title:"Prof.",name:"Mirko",middleName:null,surname:"Babic",slug:"mirko-babic",fullName:"Mirko Babic"},{id:"198335",title:"Prof.",name:"Bolin",middleName:null,surname:"Zhang",slug:"bolin-zhang",fullName:"Bolin Zhang"},{id:"204881",title:"Prof.",name:"Ljiljana",middleName:null,surname:"Babic",slug:"ljiljana-babic",fullName:"Ljiljana Babic"}]},{id:"55368",doi:"10.5772/intechopen.68755",title:"Multifunctional Gemini Surfactants: Structure, Synthesis, Properties and Applications",slug:"multifunctional-gemini-surfactants-structure-synthesis-properties-and-applications",totalDownloads:4432,totalCrossrefCites:23,totalDimensionsCites:46,abstract:"Gemini cationic surfactants are compounds which are composed of two hydrophilic head groups and two hydrophobic tails linked by a spacer at the head groups or closed to them. The spacer can be either hydrophobic or hydrophilic. It can be rigid or flexible. The neutral charge of the molecule is retained by the presence of organic or inorganic counterions. Critical micelle concentrations (CMCs), surface tension (γ) and minimal inhibitory concentration (MIC) are dozen times lower than corresponding parameters of monomeric surfactants. The unique properties of gemini surfactants with a wide range of hydrophilic-lipophilic balance (HLB) make them a very useful, innovative material in detergents, cosmetics, personal care products, additives for paints and coatings, biocides, material science, organic synthesis, pharmacy, textiles, enhanced oil recovery, nanotechnology, petroleum and many other branches of life. A large number of papers concerning gemini surfactants have been published so far. This review presents a synthetic look at current work devoted to structure, synthesis and applications of gemini surfactants.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Bogumil E. Brycki, Iwona H. Kowalczyk, Adrianna Szulc, Olga\nKaczerewska and Marta Pakiet",authors:[{id:"197271",title:"Prof.",name:"Bogumil E.",middleName:null,surname:"Brycki",slug:"bogumil-e.-brycki",fullName:"Bogumil E. Brycki"},{id:"207547",title:"Dr.",name:"Iwona",middleName:null,surname:"Kowalczyk",slug:"iwona-kowalczyk",fullName:"Iwona Kowalczyk"},{id:"207548",title:"Dr.",name:"Adrianna",middleName:null,surname:"Szulc",slug:"adrianna-szulc",fullName:"Adrianna Szulc"},{id:"207549",title:"Dr.",name:"Olga",middleName:null,surname:"Kaczerewska",slug:"olga-kaczerewska",fullName:"Olga Kaczerewska"},{id:"207550",title:"Dr.",name:"Marta",middleName:null,surname:"Pakiet",slug:"marta-pakiet",fullName:"Marta Pakiet"}]},{id:"54704",doi:"10.5772/67977",title:"Amino Acid-Based Surfactants for Biomedical Applications",slug:"amino-acid-based-surfactants-for-biomedical-applications",totalDownloads:3160,totalCrossrefCites:9,totalDimensionsCites:20,abstract:"The growing demand for surfactants worldwide has a profound impact on the environment and public health. The quest for environmentally friendly “green” surfactants has driven research toward bio-based surfactants from renewable sources with improved performances and low toxicity. Amino acid-based surfactants (AAS) are a promising class of biocompatible and biodegradable surfactants for biomedical applications due to their improved safety profiles that meet the requirements of both physiological and ecological compatibility. Natural amino acids are chiral compounds and important raw materials for production of AAS. The amino acid pool allows the synthesis of multifunctional surfactants with chiral properties that can be tailored for specific technological and/or biomedical applications. The nature of the amino acid residue, the chirality, and the ability for hydrogen bond formation strongly influences the surface active properties and self-assembly behavior of AAS. This review summarizes recent developments in AAS structure-property relationships providing valuable information for modulation of the surface active and biological properties of AAS to meet specific biomedical applications. The interaction of AAS with biointerfaces and biological molecules is also addressed concerning cellular toxicity and potential therapeutic applications of AAS as antimicrobial agents, drug delivery vehicles, and a promising alternative to viral vectors in gene therapy.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Lídia Pinheiro and Célia Faustino",authors:[{id:"199931",title:"Dr.",name:"Lidia",middleName:null,surname:"Pinheiro",slug:"lidia-pinheiro",fullName:"Lidia Pinheiro"},{id:"201447",title:"Dr.",name:"Celia",middleName:null,surname:"Faustino",slug:"celia-faustino",fullName:"Celia Faustino"}]},{id:"54753",doi:"10.5772/67998",title:"Recent Advances in Catanionic Mixtures",slug:"recent-advances-in-catanionic-mixtures",totalDownloads:1955,totalCrossrefCites:8,totalDimensionsCites:18,abstract:"Most surfactant mixtures display synergistic physicochemical properties, which have led to their extensive application in various technologies. Aqueous mixtures of two oppositely charged surfactants, so‐called catanionic surfactant mixtures, exhibit the strongest synergistic effect, which is manifested as high surface activity, enhanced adsorption and a low critical aggregation concentration. In addition, catanionic systems display rich phase behavior and a range of nano and microstructures, including small spherical micelles, rod‐like micelles as well as open and closed bilayers (vesicles). The spontaneous formation of catanionic vesicles is of special interest due to their various applications in nanotechnology and pharmaceutical formulations. In this chapter, the properties of catanionic mixtures of amphiphilic molecules with advantageous properties are discussed. Since numerous papers dealing with catanionic mixtures of monomeric surfactants already exist, the aim of this chapter is to summarize recent progress in mixtures of structurally different surfactants. At the end of the chapter, special emphasis is placed on applications of catanionic mixtures.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Darija Domazet Jurašin, Suzana Šegota, Vida Čadež, Atiđa Selmani\nand Maja Dutour Sikirć",authors:[{id:"30822",title:"Dr.",name:"Maja",middleName:null,surname:"Dutour Sikiric",slug:"maja-dutour-sikiric",fullName:"Maja Dutour Sikiric"},{id:"169636",title:"Dr.",name:"Darija",middleName:null,surname:"Domazet Jurašin",slug:"darija-domazet-jurasin",fullName:"Darija Domazet Jurašin"},{id:"199044",title:"Dr.",name:"Suzana",middleName:null,surname:"Šegota",slug:"suzana-segota",fullName:"Suzana Šegota"},{id:"199045",title:"Dr.",name:"Vida",middleName:null,surname:"Čadež",slug:"vida-cadez",fullName:"Vida Čadež"},{id:"199046",title:"Dr.",name:"Atiđa",middleName:null,surname:"Selmani",slug:"atidja-selmani",fullName:"Atiđa Selmani"}]},{id:"54922",doi:"10.5772/68020",title:"The Versatile Dioctadecyldimethylammonium Bromide",slug:"the-versatile-dioctadecyldimethylammonium-bromide",totalDownloads:1548,totalCrossrefCites:2,totalDimensionsCites:12,abstract:"Dioctadecyldimethylammonium bromide (DODAB) is a quaternary ammonium surfactant (Quat) with interesting properties and applications. In this chapter, DODAB characteristics as compared to other Quats emphasize its self-assembly in aqueous solutions and the novel applications involving this useful cationic lipid so easily combined with biomolecules and interfaces to yield a wide range of novel uses in many fields such as delivery of drugs, vaccines and genes, design of nanoparticles, modification of interfaces, and many others yet to come.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Ana Maria Carmona-Ribeiro",authors:[{id:"5978",title:"Prof.",name:"Ana Maria",middleName:null,surname:"Carmona-Ribeiro",slug:"ana-maria-carmona-ribeiro",fullName:"Ana Maria Carmona-Ribeiro"}]}],mostDownloadedChaptersLast30Days:[{id:"54735",title:"Saponin-Based, Biological-Active Surfactants from Plants",slug:"saponin-based-biological-active-surfactants-from-plants",totalDownloads:6691,totalCrossrefCites:28,totalDimensionsCites:72,abstract:"Plants have the ability to synthesize almost unlimited number of substances. In many cases, these chemicals serve in plant defense mechanisms against microorganisms, insects, and herbivores. Generally, any part of the plant may contain the various active ingredients. Among the plant, active compounds are saponins, which are traditionally used as natural detergents. The name ‘saponin’ comes from the Latin word ‘sapo,’ which means ‘soap’ as saponins show the unique properties of foaming and emulsifying agents. Steroidal and triterpenoid saponins can be used in many industrial applications, from the preparation of steroid hormones in the pharmaceutical industry to utilization as food additives that exploit their non‐ionic surfactant properties. Saponins also exhibit different biological activities. This chapter has been prepared by participants of the Marie Sklodowska‐Curie Action—Research and Innovation Staff Exchange (RISE) in the framework of the proposal ‘ECOSAPONIN.’ Interactions between the participants, including chemists, physicists, technologists, microbiologists and botanists from four countries, will contribute to the development of collaborative ties and further promote research and development in the area of saponins in Europe and China. Although this chapter cannot provide a comprehensive account of the state of knowledge regarding plant saponins, we hope that it will help make saponins the focus of ongoing international cooperation.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Dorota Kregiel, Joanna Berlowska, Izabela Witonska, Hubert\nAntolak, Charalampos Proestos, Mirko Babic, Ljiljana Babic and\nBolin Zhang",authors:[{id:"179443",title:"Associate Prof.",name:"Dorota",middleName:null,surname:"Kregiel",slug:"dorota-kregiel",fullName:"Dorota Kregiel"},{id:"197451",title:"MSc.",name:"Hubert",middleName:null,surname:"Antolak",slug:"hubert-antolak",fullName:"Hubert Antolak"},{id:"198329",title:"Dr.",name:"Joanna",middleName:null,surname:"Berlowska",slug:"joanna-berlowska",fullName:"Joanna Berlowska"},{id:"198330",title:"Prof.",name:"Izabela",middleName:null,surname:"Witonska",slug:"izabela-witonska",fullName:"Izabela Witonska"},{id:"198333",title:"Dr.",name:"Charalampos",middleName:null,surname:"Proestos",slug:"charalampos-proestos",fullName:"Charalampos Proestos"},{id:"198334",title:"Prof.",name:"Mirko",middleName:null,surname:"Babic",slug:"mirko-babic",fullName:"Mirko Babic"},{id:"198335",title:"Prof.",name:"Bolin",middleName:null,surname:"Zhang",slug:"bolin-zhang",fullName:"Bolin Zhang"},{id:"204881",title:"Prof.",name:"Ljiljana",middleName:null,surname:"Babic",slug:"ljiljana-babic",fullName:"Ljiljana Babic"}]},{id:"55124",title:"Environmental Impact of the Use of Surfactants and Oxygenates in the Petroleum Industry",slug:"environmental-impact-of-the-use-of-surfactants-and-oxygenates-in-the-petroleum-industry",totalDownloads:2179,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"The role of surfactants and hydrophilic additives in gasoline fuel was demonstrated. The impact of anionic surfactant sodium bis‐(2‐ethylhexyl)sulfosuccinate (AOT) and hydrophilic oxygen containing additives, such as alcohols (methanol, ethanol, propan‐2‐ol, butanol, 2‐methylpropanol) and methyl t‐butyl ether (MTBE) on solubility of water, electrolytic conductivity in gasoline and interfacial tension in the water/gasoline system was studied. Small amounts of amphiphilic components improve the solubility of water in gasoline as a result of the occurrence of association phenomena with the formation of reverse micelles. The formation of surfactant aggregates and droplet clusters results in an increase in the solubility of water in gasoline, electrolytic conductivity, and a decrease in interfacial tension. The changes depend on concentration of the surfactant and type of applied biocomponents. Gasoline fuel in the form of microemulsion has a positive impact on the natural environment. The presence of water causes the almost complete combustion of hydrocarbons to the low toxic gases and the absence of carbon black among combustion products reduces fuel consumption, enhances engine power and decreases its temperature, reduces emissions of volatile organic compounds (VOCs), NOx, SO2, CO, and particulate matter. The alternative fuel may have a potential use in spark‐ignition engines in the future.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Tomasz Kalak",authors:[{id:"197816",title:"Dr.",name:"Tomasz",middleName:null,surname:"Kalak",slug:"tomasz-kalak",fullName:"Tomasz Kalak"}]},{id:"55368",title:"Multifunctional Gemini Surfactants: Structure, Synthesis, Properties and Applications",slug:"multifunctional-gemini-surfactants-structure-synthesis-properties-and-applications",totalDownloads:4432,totalCrossrefCites:23,totalDimensionsCites:46,abstract:"Gemini cationic surfactants are compounds which are composed of two hydrophilic head groups and two hydrophobic tails linked by a spacer at the head groups or closed to them. The spacer can be either hydrophobic or hydrophilic. It can be rigid or flexible. The neutral charge of the molecule is retained by the presence of organic or inorganic counterions. Critical micelle concentrations (CMCs), surface tension (γ) and minimal inhibitory concentration (MIC) are dozen times lower than corresponding parameters of monomeric surfactants. The unique properties of gemini surfactants with a wide range of hydrophilic-lipophilic balance (HLB) make them a very useful, innovative material in detergents, cosmetics, personal care products, additives for paints and coatings, biocides, material science, organic synthesis, pharmacy, textiles, enhanced oil recovery, nanotechnology, petroleum and many other branches of life. A large number of papers concerning gemini surfactants have been published so far. This review presents a synthetic look at current work devoted to structure, synthesis and applications of gemini surfactants.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Bogumil E. Brycki, Iwona H. Kowalczyk, Adrianna Szulc, Olga\nKaczerewska and Marta Pakiet",authors:[{id:"197271",title:"Prof.",name:"Bogumil E.",middleName:null,surname:"Brycki",slug:"bogumil-e.-brycki",fullName:"Bogumil E. Brycki"},{id:"207547",title:"Dr.",name:"Iwona",middleName:null,surname:"Kowalczyk",slug:"iwona-kowalczyk",fullName:"Iwona Kowalczyk"},{id:"207548",title:"Dr.",name:"Adrianna",middleName:null,surname:"Szulc",slug:"adrianna-szulc",fullName:"Adrianna Szulc"},{id:"207549",title:"Dr.",name:"Olga",middleName:null,surname:"Kaczerewska",slug:"olga-kaczerewska",fullName:"Olga Kaczerewska"},{id:"207550",title:"Dr.",name:"Marta",middleName:null,surname:"Pakiet",slug:"marta-pakiet",fullName:"Marta Pakiet"}]},{id:"55934",title:"SAXS and SANS Techniques for Surfactant Characterization: Application in Corrosion Science",slug:"saxs-and-sans-techniques-for-surfactant-characterization-application-in-corrosion-science",totalDownloads:1980,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"This chapter presents advances in the characterization of surfactants and detergents using small angle X‐ray scattering (SAXS) and small angle neutron scattering (SANS) techniques. Surfactant molecules have been extensively used for corrosion prevention as part of commercial corrosion‐inhibitor formulations. It is generally established that the interactions between surfactant molecule and metallic substrate play a key role in the formation of a corrosion‐protective film. It is therefore essential to develop understanding about the nature of surfactant and detergent molecules in bulk solutions prior to formation of a surface film, as well as the mechanisms of their interactions with metallic substrates. These properties and interactions determine the properties of the surface film, including its persistency, and in turn define its protectiveness against corrosion. X‐ray and neutron reflectivity methods are important investigating tools that could be used to characterize surfactant interactions with metallic substrates. These techniques have recently been utilized to investigate adsorption energies and contact angles between molecules or particles and variable substrates. This chapter addresses basic principles of these techniques and discusses their application for surfactant and detergent studies in corrosion science. Several case studies are presented and provide outlook for future prospects in this field of science.",book:{id:"5840",slug:"application-and-characterization-of-surfactants",title:"Application and Characterization of Surfactants",fullTitle:"Application and Characterization of Surfactants"},signatures:"Deepak Dwivedi and Kateřina Lepková",authors:[{id:"197497",title:"Ph.D.",name:"Katerina",middleName:null,surname:"Lepkova",slug:"katerina-lepkova",fullName:"Katerina Lepkova"},{id:"207546",title:"Dr.",name:"Deepak",middleName:null,surname:"Dwivedi",slug:"deepak-dwivedi",fullName:"Deepak Dwivedi"}]},{id:"56940",title:"Phase Transition effect on the Parametric Instability of Liquid Crystals",slug:"phase-transition-effect-on-the-parametric-instability-of-liquid-crystals",totalDownloads:1118,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"We review advances in the last few years on the study of the Faraday instability onset on thermotropic liquid crystals of nematic and smectic A types under external magnetic fields which have been investigated with a linear stability theory. Especially, we show that thermal phase transition effects on nematics of finite thickness samples produce an enhanced response to the instability as a function of the frequency of Shaker’s movement. The linear stability theory has successfully been used before to study dynamical processes on surfaces of complex fluids. Consequently, in Section 1, we show its extension to the study of the instability in the nematics, which set the theoretical framework for its further application to smectics or other anisotropic fluids such as lyotropic liquid crystals. We present the dispersion relationships of both liquids and its dependence on interfacial elastic parameters governing the surface elastic responses to external perturbations, to the sample size and their bulk viscosities. Finally, we point out the importance of following both experimental and theoretical analysis of various effects that needs to be incorporated into this model for the quantitative understanding of the hydrodynamics behavior of surface phenomena in liquid crystals.",book:{id:"6070",slug:"liquid-crystals-recent-advancements-in-fundamental-and-device-technologies",title:"Liquid Crystals",fullTitle:"Liquid Crystals - Recent Advancements in Fundamental and Device Technologies"},signatures:"Martin Hernández Contreras",authors:[{id:"207318",title:"Dr.",name:"Martin",middleName:null,surname:"Hernandez Contreras",slug:"martin-hernandez-contreras",fullName:"Martin Hernandez Contreras"}]}],onlineFirstChaptersFilter:{topicId:"514",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"23",title:"Education and Human Development",doi:"10.5772/intechopen.100360",issn:null,scope:"
\r\n\tEducation and Human Development is an interdisciplinary research area that aims to shed light on topics related to both learning and development. This Series is intended for researchers, practitioners, and students who are interested in understanding more about these fields and their applications.
",coverUrl:"https://cdn.intechopen.com/series/covers/23.jpg",latestPublicationDate:"June 25th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"280770",title:"Dr.",name:"Katherine K.M.",middleName:null,surname:"Stavropoulos",slug:"katherine-k.m.-stavropoulos",fullName:"Katherine K.M. Stavropoulos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRdFuQAK/Profile_Picture_2022-05-24T09:03:48.jpg",biography:"Katherine Stavropoulos received her BA in Psychology from Trinity College, in Connecticut, USA. Dr. Stavropoulos received her Ph.D. in Experimental Psychology from the University of California, San Diego. She completed her postdoctoral work at the Yale Child Study Center with Dr. James McPartland. Dr. Stavropoulos’ doctoral dissertation explored neural correlates of reward anticipation to social versus nonsocial stimuli in children with and without autism spectrum disorders (ASD). She has been a faculty member at the University of California, Riverside in the School of Education since 2016. Her research focuses on translational studies to explore the reward system in ASD, as well as how anxiety contributes to social challenges in ASD. She also investigates how behavioral interventions affect neural activity, behavior, and school performance in children with ASD. She is also involved in the diagnosis of children with ASD and is a licensed clinical psychologist in California. She is the Assistant Director of the SEARCH Center at UCR and is a Faculty member in the Graduate Program in Neuroscience.",institutionString:null,institution:{name:"University of California, Riverside",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:2,paginationItems:[{id:"89",title:"Education",coverUrl:"https://cdn.intechopen.com/series_topics/covers/89.jpg",isOpenForSubmission:!1,editor:{id:"260066",title:"Associate Prof.",name:"Michail",middleName:null,surname:"Kalogiannakis",slug:"michail-kalogiannakis",fullName:"Michail Kalogiannakis",profilePictureURL:"https://mts.intechopen.com/storage/users/260066/images/system/260066.jpg",biography:"Michail Kalogiannakis is an Associate Professor of the Department of Preschool Education, University of Crete, and an Associate Tutor at School of Humanities at the Hellenic Open University. He graduated from the Physics Department of the University of Crete and continued his post-graduate studies at the University Paris 7-Denis Diderot (D.E.A. in Didactic of Physics), University Paris 5-René Descartes-Sorbonne (D.E.A. in Science Education) and received his Ph.D. degree at the University Paris 5-René Descartes-Sorbonne (PhD in Science Education). His research interests include science education in early childhood, science teaching and learning, e-learning, the use of ICT in science education, games simulations, and mobile learning. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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