**Abbreviations**

*Time Domain Performance Evaluation of UWB Antennas DOI: http://dx.doi.org/10.5772/intechopen.94546*

is presented in this work. Temporal characterizations of the two antennas

are no changes in the phase center of the antenna.

*Innovations in Ultra-WideBand Technologies*

funding the facilities for simulation and measurement.

The authors declare no conflict of interest.

FCC Federal Communication Commission

FWHM Full Width Half Maxima IFFT Inverse Fast Fourier Transform RMA Rectangle Monopole Antenna SQMA Square Monopole Antenna

UWB Ultra Wide-band

**Acknowledgements**

**Conflict of interest**

**Abbreviations**

**124**

open.com/page/authorship-policy.

performed by the method outlined here reveal a close correspondence between the geometry of the antenna with its performance in the time domain. From the study, it is concluded that for good time-domain performance, excitation of multiple modes within the operating band of the UWB antennas has to be taken care of during the designing of the antennas itself and its physical dimension has to remain to a minimum. The first condition minimizes internal reflections and the subsequent cancelations in the antenna geometry while the second one ensures that there

Simulations and measurements of the present work were done at the Govt. Victoria College, Palakkad and Cochin University of Science and Technology, Cochin. The authors acknowledge DST SERB, DST-FIST, UGC and KSCSTE for

The authorship criteria are listed in our Authorship Policy: https://www.intech


Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy

*Ali K. Refai*

### **Abstract**

The spectrum of patients' needs for dental implant treatment ranges between healthy individuals to those with complex diseases and compromised jaw bones. The aim of this review chapter is to introduce the application of personalized dental medicine to dental implant field as a therapeutic strategy that is best suited to individualized patient's genetic makeup "Implantogenomics" to enhance their longevity and clinical outcomes. The ultimate goal of personalized medicine and dentistry is tailoring targeted treatment to the patient's individual genetic makeup and having predictive outcomes. This approach will transfer the traditionally known "one size fits all" to an actionable model, tailoring therapy to individuals in a homogenous stratified group. In this review chapter, in analogy to pharmacogenomics, personalized dental implant and its implantogenomics concept have been proposed as a novel application of personalized dentistry. It is conceivable that the actionable model that integrates genomics and materiomics will accelerate the production of personalized implantable biomaterials and biomedical devices. Moreover, the convergence of multi-disciplines including biological sciences, material sciences, and computational tools may underpin the application of personalized dental implant therapy in the future. This approach will unleash the potential of advancing technologies to tailor dental implants targeting different subpopulations. Despite this optimistic goal, challengeable remains ahead of us where the conduction of well-directed scientific and clinical research is needed.

**Keywords:** osseointegration, personalized dental implant therapy, omics, materiomics, implantogenomics

#### **1. Introduction**

For more than 50 years, dental implants were employed for the treatment of patients who are both partly and wholly edentulous. This treatment modality has been shown to improve the quality of life of large populations and demonstrated to perform very well, clinically, functionally, and esthetically [1–3]. Osseointegration is an essential factor in the success rates of dental implant-supported prostheses. The first known use of the term "osseointegration" was in the 1970s when Branemark defined it as a "Direct structural and functional link between organized, live bone tissue and the surface of a load-carrying artificial implant at the resolution level of the light microscope" [4]. At the bone-implant interface, osteoinduction and osteoconduction events are necessary for osseointegration to occur. The biological

#### **Table 1.** *Shows the main terminologies used throughout the review.*

*Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

mechanisms defining the three concepts are known to be connected yet distinct from one another [5].

Although osseointegration was defined as a time-dependent healing process, whereby clinically asymptomatic rigid fixation of alloplastic materials is achieved and maintained in bone during functional loading, osseointegration, a novel definition has emerged recently [6]. Albrektsson et al. defined "osseointegration as a foreign body reaction where interfacial bone is formed as a defense reaction to shield off the implant from tissues" [7]. Understanding both the old definition and the new one necessitate conceptualizing osseointegration beyond its definitions.

To achieve such goal, this review chapter proposed an actionable model integrating various fields. The convergence of scientific disciplines including advancements in molecular biology in terms of "multi-omics data," bioengineering in the term "materiomics and biomaterialomics," and proper computational tools that will hasten the production of personalized implantable medical devices. Thus, the formulation of this strategic approach is critical toward personalized dental implant as a target future therapeutics. Moreover, the introduction of osseointegration's new concept "implantogenomics" demonstrates patient-specific implants whereby reliable dental implant therapy is tailored based on the genetically unique individual. **Table 1** shows the main terms used throughout the review.

#### **2. Synopsis of wound healing around dental implants**

The process of osseointegration involves a cascade of complex physiological mechanisms similar to intramembranous ossification and direct fracture bone healing [8]. After an implant is inserted into an osteotomy site, immediately protein serum is adsorbed onto the implant surface and forms conditioning layer. It is well known that the characteristics of implant surface determine the biological and molecular profile of the adsorbed protein layer. At the micro-environment between bone and implant surface, cells interact with this layer rather than with the implant surface itself [9, 10].

The protein adsorption stage is followed by coordinating and sequentially overlapping biological events. These biological events include mesenchymal and non-mesenchymal cellular interactions (i.e., recruitment, attachment, proliferation, and differentiation), soluble proteins and growth factors secretions, osteogenic cells proliferation and differentiation, osteoid production and matrix calcification, and bone formation and remodeling [11–14].

The principal factors that regulate the biological events of endosseous wound healing are the cells dominating the osteotomy site. Cells populate each stage of the healing process and are found to coordinate and communicate with each other by producing a myriad of signaling molecules including; cytokines, chemokines, growth factors, extracellular matrix proteins, hormones, and ions, which orchestrated the osseous healing process at biointerface. The secretion of the signaling molecules is well controlled by the sequential activation of corresponding typical genes [14, 15]. In fact, the decisive underlying cellular and molecular mechanisms that regulated endosseous wound healing and osseointegration are yet to be fully understood [15, 16]. **Figure 1** summarizes the biological events and the cellular and molecular mechanism of osseointegration.

**Figure 1.**

*Summary of the biological events and the cellular and molecular mechanisms of osseointegration.*

#### **3. Gene markers and genetic networks of osseointegration**

The biological processes of osseointegration (inflammo-immuno-angio-neuroosteogenesis processes) are directed by several genes expressed in an orderly sequence. Studies showed that gene expression profile after implant installation shifted from genes upregulated during immuno-inflammatory processes and cell proliferation to genes expression upregulated in favor of angiogenesis, osteogenesis, and neurogenesis processes [17, 18]. This alternation of biological processes may be attributed to the concept of "foreign body equilibrium." It has been proposed that osseointegration is the result of an immune system's reaction to a foreign body, which, at the right level of intensity, will balance itself out and allow osteogenesis to start on surface of the implant [19, 20].

Several in vitro and in vivo studies have demonstrated the influence of surface topography on gene expression of osseointegration. In brief, over the last two decades, the studies investigated the genetic basis of osseointegration have shown that the most observed genes were immunoinflammatory-related gene markers, extracellular matrix and osteoblast differentiation-related genes, bone formation, and remodelingrelated genes, transcriptional-whole genome-proteome profiles of osseointegration related to immune-inflammo-angio-neuro-skeletogenesis biological processes, micro RNAs and signaling pathways. These biomarkers recapitulated the reported

*Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

significant genetic markers and genetic networks associated with the biological processes of osseointegration [14, 16, 21–26].

Osseointegration encompasses a network of reactions that are dependent on a building system rather than a single pathway [20]. In this context, it is noteworthy that even though thorough studies have made significant progress in demonstrating the fundamental mechanisms underlying the molecular basis of osseointegration, as previously mentioned, the revolution of ongoing scientific research has highlighted the importance of other genetic networks related to osseointegration [25]. Whole genome microarray analyses have shown that the genetic networks that control osseointegration include other genes that function in coherent and/or independent pathways to complete the process of osseointegration around dental implants, in addition to the genes regulating osteogenesis and involving the expression of osteoblast marker genes. Other gene networks involved in the process of osseointegration include those that control the cross-linking of the bone collagen matrix, extracellular matrix-related genes associated with cartilage, and clock genes related to the peripheral circadian rhythm system. The modulation of those novel genetic networks was found to be topographical dependent and devoted to accelerate osseointegration [25, 27, 28].

#### **4. The effect of implant surface properties on osseointegration**

Implant surface properties including its topographical, chemical, mechanical, and physical are considered to be one essential factor to promote and maintain osseointegration. Since the foundation of osseointegration phenomenon, many bioengineering techniques have been developed to modify dental implant surface characteristics. These modification techniques have been classified into subtractive and additive treatments. Subtractive treatments include machining, Sandblasting, acid etching, and laser ablation. Additive treatments include anodization, fluoride surface treatment, nanoscale surface, plasma spraying, hydroxyapatite coating, electrophoretic deposition, biomimetic precipitation "peptides growth factors and ECM proteins", and drugs incorporated "bisphosphonates and statins" [29–33].

Recent reviews have shown that dental implant surface modifications were enormously studied aiming to promote osseointegration in the last decades [16, 26]. Mechanistically, implant surface properties are able to modulate osseous healing by influencing the cells-implant interactions and then producing several genes and proteins that serve as key regulators to inflammo-immuno-angio-neuro-osteogenesis processes [16, 26, 34].

Quit recently, new interesting approach is surface loading with cells potentially gaining more attention in the future [35]. However, this type of functionalization has not been extensively studied, as its clinical translation is more challenging due to the cell preparatory requirements and regulations. In tandem with the progression of cellbased therapy and personalized medicine, this approach may accelerate tissue repair in many clinical aspects [35].

#### **5. Personalized medicine and dentistry**

#### **5.1 Personalized medicine**

Personalized medicine is a contemporary evolving field in medicine and healthcare industries [36, 37]. Its aspirational goal is about tailoring medical treatment to the

patient's individual genomic, anatomical, and physiological characteristics in order to provide a better quality of life and prolong life expectancy. Though the concept of current personalized medicine as new medical innovation was laid in tandem with the successful completion of the Human Genome Project (HGP) in the USA, in 2003 [37, 38], the term personalized medicine was coined in the published works in 1999 [39]. **Figure 2** shows the main elements of personalized medicine and dentistry concept.

The Human Genome Project (HGP) along with further projects (International HapMap Project (2002–2010), and the 1000 Genomes Project (2008–2015) authorizing personalized medicine to grow steadily in the medical practice and pharmacotherapy [37]. Among the main project achievements were discovering 1800 disease-related genes, developing numerous molecule biomarker-based tests, identifying genetic variations which lead to an individual different response to environmental factors, as well as drugs and vaccines effectiveness [37, 38, 40–42]. Personalized medicine has been extensively reviewed in the pharmacogenetics "study of genetic causes of individual variations in drug response" and pharmacogenomics (impact of multiple mutations in the entire genome that may determine the patient's response to drug therapy [43, 44].

Both pharmacogenetics and pharmacogenomics testing is involved as novel approaches in drug development and future registered therapeutic for a specific disease. For example, the implication of using pharmacogenetics and pharmacogenomics in the fields of cardiovascular, pulmonary, oncological, and bone diseases and also feature the potential economic value of their development [44, 45].

For centuries, health care providers, namely physicians treated medical conditions based on identifying the signs and symptoms and prescribed drug therapy without a diagnostic pretest. This traditional approach is so-called "One Size-Fits-Alls," which is doomed to failure. The failure has been attributed to several factors including lack of patient stratification, existing of genetic variation and treatment drug reaction, identifying risk assessment, understanding factors involved in disease development

#### **Figure 2.**

*Personalized medicine and dentistry concept: Main components and its applications in medical and dental fields.*

*Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

"epigenetics" and taking in account patient's profile "age, sex and weight" [36, 37]. Collectively, such factors are the reason for extensive differences in response to medication.

The employing of pharmacogenetics and pharmacogenomics testing in personalized medicine will show which medication will have a positive effect and which one will have a negative effect. This approach will shift the paradigm from currently using "one size fits all" to individualizing drug target "a test and treat" approach. The consequence of such transformation is expanding the personalized medicine concept in the medical practice and healthcare industries [37, 46, 47].

Although there is no one uniform definition of personalized medicine because of lack of consensus on definitions and nomenclature, several agencies, institutes, and associations have provided a diverse range of definitions depending on the scope and the main elements of personalized medicine [37, 43]. Personalized medicine is a multifarious approach to patient care that not only improves our ability to diagnose and treat disease, but offers the potential to detect disease at an earlier stage, when it is easier to treat effectively. The full implementation of personalized medicine encompasses six domains (**Table 2**) [48].

The concept of personalized medicine [49] has been designated by many names in the literature [37, 50]; including precision medicine [51, 52], individualized medicine [53], network medicine [54], predictive medicine [55], stratified medicine [56] as well as P4 medicine [57]. These terms have a similar meaning with some slight differences between them and used interchangeably as alternative and synonyms terms [37, 50].

#### **5.2 Personalized dentistry**

Like medicine, there is a growing attention toward personalized/precision dentistry. The personalized dentistry branches from personalized medicine as an emerging concept, a multifaceted, individualized data-driven approach to oro-cranio-facial care environment. The personalized dentistry will act as an actionable model in dentistry that represents a paradigm shift in dental practice from the one size fits all approach to tailoring therapy to individuals in a homogenous stratified group. Each group of individuals sharing similar risk factor data includes but is not limited to genomic, environmental, e-health record, and lifestyle [50, 58–62].

#### **Table 2.**

*Domains of personalized medicine adapted from Reference [48].*

Nowadays, the advances in personalized oral health focus on the creation of new digital technologies and medical devices, conceptualizing complex process align with understanding system biology, improving patient's stratifications, identifying biomarkers as diagnostic and prognostic factors related to disease development and progression. In to aforementioned, personalized oral health concentrates on developing proper treatment planning and early disease detection as preventive strategies. In fact, the main goal of personalized dental medicine is tailoring treatment taking into account its application, dosing, and response to treatment according to individual characteristics [50, 63, 64].

Bartold explained the importance of implementing personalized dentistry as a custom dental management model for the future of dental practice in two folds. First, this approach will bring the field of dentistry in tandem with current medical practice. Second, personalized dentistry stressing on patient-centered care and improving patient health outcomes [65].

In the last decade, several researchers have been investigating the application of personalized dentistry concept to various branches of dentistry. Some examples of these studies include, head and neck cancer [66, 67], periodontics [68–70], restorative [71–73], pedodontic [74–76], orthodontic [77, 78], TMJD [79], Public health and preventive care [80–84], prosthodontic [85], dental implant [16, 86–88], and oral rehabilitation and regenerative medicine [89].

In the context of advanced healthcare research in the medical field, personalized medicine is escalating, whereas, in dentistry, personalized dentistry is still in its infancy. Several challenges have been attributed to delay implementations of personalized dentistry in the practice environment. According to Polverini, these challenges include gaps in education of the current knowledge related to the basis of personalized dental medicine, addressing issues such as reimbursement for preventive dental procedures, insufficient an integrated electronic health record, difficulty in protecting patient genetic information, and differences in access to genomic medicine by certain populations. However, the dental profession should act in tandem with medical profession to pace toward innovation and harness advanced technologies to ensure the development and progression of personalized healthcare environment [62, 90].

#### **6. Personalized dental implant therapy: Introducing Implantogenomics Concept**

The emergence of advanced technologies underpins the application of personalized dental implant therapy as a novel dental approach to providing precise patient's care. In fact, the presence of a broad spectrum of patients with various conditions include systemic diseases, special needs, and syndromic and elderly with compromised jaws necessitate patient's stratifications who share similar risk factors. Having such homogeneous groups and subgroups will help in developing proper protocol, treatment decision and prediction and tailoring precise patient-centered treatment strategy.

In 2020, we have proposed the personalized dental implant along with its new concept implantogenomics [16]. The current opinion review wishes to introduce the new concept to more audience in both medical and dental fields. In analogy to pharmacogenomics, implantogenomics should accurately achieve three major components

#### *Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

prior to be implemented as a future personalized therapeutic strategy in the realm of implantology. First, stratifying individuals into subgroups based on a person's unique genome, second, identifying specified prognostic and predictive biomarkers which characterized endosseous wound healing of each subpopulations, and third, applying genomic information to design dental implant suit each subpopulation.

It is conceivable that the actionable model which integrates multiple advancement technologies will leverage the development of new medical devices including dental implants in favor of regenerative medicine and dentistry. These include but is not limited to multi-omics data, advanced material science, biotechnologies, and contemporary bioinformatics tools along with artificial intelligence. It is suggested that the joining of bioinformatics and artificial intelligence will handle high throughput genetic data more precisely in terms of defining, categorizing and analyzing [91, 92]. The ultimate goal of personalized dental implant therapy is to have the four Rights. (1) Right treatment in terms of implant design and legitimate protocols, (2) Right patient in terms of patient stratification and minimal biological complication outcomes, (3) Right time in terms of bio-physiological events, and (4) Right Positioning in terms of Jaw status. **Figure 3** elucidates an actionable model of personalized dental implant therapy.

More recently, Albrektsson et al. proposed that personalized dental implant therapy and its implantogenomics concept may accelerate the development of genetic diagnostic tests as a target future therapeutic for residual ridge resorption (RRR) in elderly [16, 93]. In this regard, it should be mentioned that the application of personalized dental medicine to the realm of dental implant requires innovative leadership to direct wide-spectrum of scientific and clinical research as well as multidisciplinary and multicenter collaborations. Thus, the application of personalized dental medicine in the field of dental implant remains challengeable.

#### **Figure 3.**

*An actionable model. The personalized dental implant therapy- the convergence of multiple disciplines.*

#### **7. Conclusions**

The Integration of multi-disciplines including biological sciences, material sciences, and computational tools in actionable model may underpin the application of personalized dental implant therapy in the future. This approach will unleash the potential of advancing technologies to tailor dental implants targeting different subpopulations with more predictive outcomes. Despite this optimistic goal, challengeable remain ahead of us where conduction of well-directed scientific and clinical research is needed.

#### **Author details**

Ali K. Refai College of Dentistry, King Saud University, Riyadh, Kingdom of Saudi Arabia

\*Address all correspondence to<EMAIL_ADDRESS><EMAIL_ADDRESS>
© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

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[67] Polverini P, D'Silva N, Lei Y. Precision therapy of head and neck squamous cell carcinoma. Journal of Dental Research. 2018;**97**(6):614-621

[68] Divaris K. Searching deep and wide: Advances in the molecular understanding *Implantogenomic: Conceptualizing Osseointegration toward Personalized Dental Implant Therapy DOI: http://dx.doi.org/10.5772/intechopen.109159*

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[70] Bartold PM, Ivanovski S. P4 medicine as a model for precision periodontal care. Clinical Oral Investigations. 2022 Sep;**26**(9):5517-5533

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## **Chapter 14**


**Abstract**

The need for cleaner sources of energy has become a serious need now more than ever due to the rising effects of fossil fuels on the environment. Technological advancement in society today has necessitated the need for fast and robust materials that will match the speed at which society is moving forward. Hydrogen as an alternative source, has garnered a lot of attention due to its zero emission characteristic. In this chapter, a background on hydrogen storage and its impact on the 'envisaged green environment' is discussed. Graphene and borohydrides hydrogen storage materials are reviewed extensively and the kinetic models thereof. Furthermore, the reaction mechanism of graphene nanocomposites is also discussed.

**Keywords:** hydrogen storage, hydrides, kinetics, graphene, nanocomposites

#### **1. Introduction**

The generation of the 21st century has had to deal with the effects of centuries of environmental mismanagement due to industrialization and modernization. To put things into perspective, approximately 6587 billion metric tons of carbon dioxide, a main contributor to climate change, were emitted into the atmosphere in 2015 through the use of fossil fuels [1]. In 2017, these numbers increased and they are continually increasing every year (**Figure 1**).

As such, the implementation of green systems and processes has become a priority in order to try and mitigate the damages to the environment. The remedial actions implemented to reduce the effects on the environment include the institution of legislations that fine high carbon emitters, green technologies and green alternatives to support energy and electricity demands. Hydrogen is amongst the green alternative researched as a substitute for fossil fuels. However, it is acknowledged that the transition from fossil fuels or carbon based sources is not going to be an easy one because of the demand and the complexity of introducing a different system. The United States of America has already started introducing the hydrogen fuelled cars and currently, there is about 6558 hydrogen fuelled cars. This number is expected to surge in the coming years, in 2027 it is expected that there demand would increase to 70,000 units [2].

The implementation of the hydrogen economy is driven by the Department of Energy in the United States. The DoE set the standards and requirements for hydrogen storage materials for practical application in hybrid cars (**Figure 2**).

Various hydrogen storage materials have been synthesized and tested for hydrogen storage applications. However most of these materials have not met the

#### **Figure 2.**

*2020 hydrogen storage requirements for hybrid cars (Department of Energy, United States).*

requirements for applicable hydrogen storage. In this book chapter, the synthesis and first principles studies thereof of new classes of materials will be reviewed, their kinetics will also be reviewed in great details.

An immense effort has been put towards finding novel material for hydrogen storage that will have optimum conditions as indicated by the D.o.E. A great number of light-weight nanostructures consisting of nitrogen, carbon and boron have received favorable attention due to their large volume-to- surface ratio and lightweight characteristic [3]. These materials have been studied intensely and recent works, depicts an improvement and a ray of light in terms of practical applicable hydrogen storage in them.

The interest in these materials was instigated by their unique characteristics. Boron based nanostructures have similar porous structural characteristics with carbon based materials however, boron based materials are much more lighter [3] making them an interesting candidate for practical hydrogen storage. Boron based materials are synthesized using various methods such as hydrolysis and pyrolysis of chemical hydrides.

### **Hydrolysis:**

Hydrolysis is the liberation of hydrogen gas through the reaction of water with a hydride. The overall reaction is summed up as follows:

$$\text{MHx} + \text{xH}\_2\text{O} \rightarrow \text{M(OH)}\_\text{x} + \text{xH}\_2\tag{1}$$

$$\text{MXH}\_4 + 4\text{H}\_2\text{O} \rightarrow 4\text{H}\_2 + \text{MOH} + \text{H}\_3\text{XO}\_3 \tag{2}$$

Where x is the valence number of the metal, M is the metal and X is a trivalent group III element.

### **Pyrolysis:**

Pyrolysis is the breakdown of a substance due to heating. The overall pyrolysis reaction is summed up as follows:

$$\text{2M} + \text{xH}\_2 \rightarrow \text{2MHx} + \text{HEAT} \tag{3}$$

Where M is an alloy or a metal.

Boron hydrides are interesting chemical H2 storage materials that have high hydrogen capacity however the kinetics and thermodynamics of these materials have limited their practical use for hydrogen storage. Different approaches have been employed to decrease the kinetics and thermodynamics of these materials. Popular boron hydrides include LiBH4 (Lithium borohydride) and NH3BH3 (ammonia borane) [1]. The reaction mechanism with boron hydrides can be summed up into four main steps: 1. the decomposition or breakdown of the material through heating to generate hydrogen (Pyrolysis), 2. The interaction of the material with water to release hydrogen (pyrolysis), 3. Improvement of the kinetics through the addition of boron to the electrodes on the metal hydride battery, 4. The storage of hydrogen via the boron nitride nanotubes which can also release the hydrogen when heating [4]. A lot of remedial actions have been employed to improve the kinetics of these materials however the research still continue.


*2.6. Molecular Dynamics Simulations*

The possible conformations for the CDR3 were investigated with molecular dynamics (MD) simulations, starting from representative of the six different clusters including all the best 18 energy-minimized structures from PONDEROSA C/S modeling. All simulations show an initial increase of the RMSD from the first structure of the specific NOE-restrained cluster, followed by rather stable equilibration at the value of about 2.5 Å (Figure 8a). During the simulation, most of the structures fluctuate about an average conformation with lower RMSD with respect to the initial structure, as witnessed by the much lower residue root mean square fluctuations (RMSFs) on the superimposed residues (Figure 8b). Large RMSF values are observed at loops and in the region 100–120 encompassing the CDR3. This is observed in most simulations, although in one of the simulations the region 50–70 is also showing large fluctuations.

**Figure 8.** (**a**) RMSD with respect to the lowest energy structure of the NOE−restrained clusters as a function of time of the six MD simulations that were carried out starting from the minimized representative structures from the six clusters of the NOE−restrained PONDEROSA C/S models of Nb23. Black trace = cluster 1 (11 members); red trace = cluster 2 (2 members); green trace = cluster 3 (2 members); blue trace = cluster 4 (1 member); orange trace = cluster 5 (1 member); pale brown trace = cluster 6 (1 member). (**b**) RMSF in the same six MD simulations as in panel (**a**), as a function of the residue number of Nb23. The color code of the traces is the same as in panel (**a**).

MD confirms the proximity of Arg50 and Tyr104 sidechains in all of the simulations originating from the different clusters of PONDEROSA C/S energy-minimized conformers, with a geometry of either cation–π or π–stacking interaction in the snapshots of the simulation concerning the NOE-restrained best cluster.

An interesting observation is that the simulations starting from different minimized conformers of the PONDEROSA C/S clusters sample different regions of the conformational space, as can be seen by comparing the average RMSD at each residue for the ensemble of MD snapshots from each pair of simulations and for the ensemble of the pooled snapshots. An example is provided in Figure S4 with the pooling (dashed curve) of two of the MD snapshot ensembles depicted in Figure 8B. The large increase in RMSD upon pooling the two ensembles is indicative of large differences in the conformations about which the two MD simulations are fluctuating (see Figure S4).


**1. Introduction**

The determination of when and how genes are "turned on and off" is a challenge in posgenomic era. Differences between two species are closer to gene expression and regulation than to gene structures (Howard & Benson, 2002). The first and key step in gene expression is promoter recognition by RNA polymerase enzyme (RNAP). The promoter sequences can be defined as cis-acting elements located upstream of the transcription start site (TSS) of open reading frames (ORF). To make an analogy, genes represent the "computer memory" and promoters represent the "computer program" which acts on that memory. The study about promoters can assist in providing new models about the constitution of the computer program and how it operates (Howard & Benson, 2002).

The proper regulation of transcription is crucial for a single-cell prokaryote since its environment can change dramatically and instantly (Huffmann & Brennan, 2002). In face of this, the detailing of the principals and the organization of transcriptional process is helpful for understanding the complexity of biological systems involved, for instance, cellular responses to environmental changes or in the molecular bases of many diseases caused by microbes (Janga & Collado-Vides, 2007).

While several sequenced genomes have their protein-coding gene repertoire well described, the accurate identification and delineation of cis-regulatory elements remain elusive (Fauteux et al., 2008). At this moment, the challenges are to analyze the available sequences and to locate TSS, promoters and other regulatory sequences (Askary et al., 2009). The purpose of this review is to provide a brief survey of promoter sequences characteristics and the advances of computer algorithms for their analysis and prediction. This chapter is organized in two main sections. The established knowledge about biological features of the

© 2012 Silva and Echeverrigaray, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 Silva and Echeverrigaray, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

promoters will be described in the first section, focusing in their genetic role and sequence content constitution. This is an important topic for understanding the intrinsic difficulties in the *in silico* promoter prediction approaches. The second section is devoted to give a reasonably concise background of the most used methodologies for *E. coli* promoter prediction and recognition, presenting their applications, as well as their limitations.

Bacterial Promoter Features Description

Region Reference

Helmann & Chamberlin,

1987

1985

1999

al.,2006

Margalit, 1993

and Their Application on *E. coli in silico* Prediction and Recognition Approaches 243

sequences of the promoters can affect the level of expression of the gene(s) they control, without altering the gene products themselves (Lewin, 2008). The canonical consensus and the number interspacing nucleotides recognized by the most important σ are presented on

Region Separation -10 consensus

Response CCCTTGAA 13-15pb CCCGATNT Cowing et al.,

Metabolism CTGGNA 6pb TTGCA Barrios et al.,

Response GGAACTT 15pb GTCTAA Rhodius et

A comprehensive study of the promoter content information was carried out by Schultzaberger et al. (2006). The authors have used the Claude Shannon's information theory and have built a promoter model by aligning and refining of 559 sequences upstream of TSS. The results for the promoter motifs showed, among others, two interesting results: *(i)*  the difference of TSS prokaryotic information (0.39+-0.06 bits) in opposite to eukaryotic TSS (~3bits) and, (*ii)* the notorious high degree of conservation of the last nucleotide (T) in the -10 region. Another important discussion described in the paper is about the -10 extended region. According to Hook-Barnard et al. (2006), some promoters are functional without the -35 region and this missing information is compensated by four nucleotides upstream of the -10 element. Its consensus sequence is TRTG (according to IUPAC code, the letter R represents A or G). About this issue, the authors suggest that in prokaryotes the extended - 10 may be an evolutionary predecessor to the modern bipartite promoter or vice versa.

Response TTGACA 16-18pb CTATACT Typas et al., 2007

Table 1. Just for σ54, the consensual region is located in the -12 and -24 nucleotides.

70 rpoD Housekeeping TTGACA 16-18pb TATAAT Lisser &

**Table 1.** *E. coli* σ factors and their promoter sequences binding sites (LEWIN, 2008).

However, the second possibility does not explain the origin of bipartite promoter.

and incorrect assignments (de Avila e Silva et al., 2011).

As it has been related so far, the promoter motifs are not strictly conserved within a set of promoters recognized by a given σ factor and also differ according to the σ factor which recognizes them. The structure of bacterial promoters limits the efficacy of prediction by a global analysis approach. A limited analysis of a putative promoter sequence by comparison with the σ70 promoter consensus motif can lead to an unacceptable rate of false negatives

28 fliA Flagellar genes CTAAA 15 pb GCCGATAA

σ

Factor Gene Cellular

32 rpoH Heat shock

38 rpoS Starvation

54 rpoN Nitrogen

24 rpoE Heat shock

Uses


**3. Thermal performance-enhancing techniques**

It is clear from the studies in the literature that MCHS has an eminent future in the field of thermal management of electronic equipment. The work performed on the micro-channel heat sink by Tuckerman and Pease [9] attracted the researchers towards the MCHS. Researchers and scientists have been working on MCHS to develop new ways to enhance heat transfer in micro-channels. The details of the few thermal performance-enhancing techniques developed for MCHS are produced in this section.

#### **3.1 Geometric improvements**

*Heat Transfer - Design, Experimentation and Applications*

method (DMLS) for manufacturing of two MCHS models, PMM (permeable mem-

The analysis method implemented for the study of MCHS is also plays a key role in the accuracy of the study. Initially, researchers and scientists depended on expensive experimental methods only for their research but the development of numerical methods has upturned the studies on microfluidics. Novel computational fluid dynamic (CFD) techniques have been developed for accurate analysis of the MCHS. 3-dimensional simulation models give an accurate result than 2-dimensional simulation models but computational time is less for a 2-dimensional model. Similar outcomes were found in the 2D and 3D simulation model studies conducted on the

brane MCHS) and MMC (manifold MCHS) heat-sinks shown in **Figure 3**.

**286**

**Figure 4.**

**Figure 3.**

*Schematic of various studies on micro-channel heatsinks (MCHS) [15].*

*Images of the (a, c) manifold MCHS and (b, d) permeable membrane MCHS [29].*

The microchannel geometry has a major impact on its heat transfer and fluid flow performance. The improvement of the microchannel geometry is a possible technique to decrease the pressure drop with a significant increase of the heat transfer. Various cross-sectional shapes of micro-channels used for the analysis are presented in **Figure 5**. Microchannel with a Trapezoidal-shaped cross-section has a good thermal performance than the rectangular channel [41]**.** The effect of the different parameters like aspect ratio (AR) [42], hydraulic diameter, channel spacing [31], channel width, channel height, etc., on the heat transfer behavior of microchannel, were also studied.

An experimental analysis performed on the rectangular microchannel with the working fluids FC770 and water proved that the critical Reynolds number (Re) increases to 2400 from 1700 with a reduction of aspect ratio (AR) to 0.25 From 1 [43]. The reduction of friction factor with increasing the AR was also noticed initially, and then it started increasing. The increase of both the Nusselt number (Nu) and the pressure loss with the channel height reduction was observed in the numerical study on MCHS with transfer channels [44]**.** The flow channel size shows a noticeable effect on the hydraulic performance as it was decreasing from the macro scale to the microscale. The effect on the hydraulic behavior of the microchannel was negligible as the space between the micro-channels decreases from 50 μm to 0.5 μm [31]**.** The Nu and Poiseuille number are found to be raised with rising the AR and side angle [45].

Some studies on MCHS have introduced the ribs, internal fins into the flow channels and changes the shape of the passage so that the area of heat transfer increased. A considerable decrease of pressure drop was noticed when the rectangular-shaped ribs and the sinusoidal cavities are provided to the MCHS [46]. In the various category of offset ribs on the channel sidewalls, the best performance was observed with the forward triangular ribs and the rectangular ribs showed the worst behavior at the Re

**Figure 5.** *Various cross-sections of micro/mini channels used for studies [40].*

less than 350 [47]**.** The increase of heat transfer was also observed by providing the internal fins with the increase of pressure drop, as a cumulative effect, the microchannel performance was increased. The proximity from the wall of the large row of pin fins showed the greatest effect on the velocity field, distribution of flow, temperature distribution, and streamline structure. As the gap between the pin-fins increases, the heat transfer is noticed to increase first and then decrease. The fin structured microchannel with equal gap and diameter shows better thermal performance [48]. A schematic model of finned MCHS is produced in **Figure 6**. The effect of proximity from the sidewall on the thermal performance is represented in **Figure 7**.

**289**

**Figure 9.**

**Figure 7.**

**Figure 8.**

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks…*

The large heat transfer (HT) enhancement was found in the periodically converg-

ing and the diverging and periodically expanded and constrained MCHS. 46.8– 160.2% improvement in HT was noticed in the converging and the diverging MCHS (**Figure 8**) [49]**.** 50–117% improvement of heat transfer was found in the periodically expanded and constrained MCHS (**Figure 9**) in the range of Re from 150 to 820 [50]**.** An experimental study on periodic jetting and throttling MCHS (**Figure 10**) has concluded that the mean temperature and maximum temperature in the throttling

*The influence of proximity from the sidewall on the thermal performance of MCHS [48].*

*Physical model of periodic converging–diverging microchannel [49].*

*Design of the periodic expanded and constrained MCHS [50].*

*DOI: http://dx.doi.org/10.5772/intechopen.97087*

**Figure 6.** *Schematic model of finned MCHS,* **(a)** *physical model and* **(b)** *boundary conditions [48]***.**

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks… DOI: http://dx.doi.org/10.5772/intechopen.97087*

#### **Figure 7.**

*Heat Transfer - Design, Experimentation and Applications*

*Various cross-sections of micro/mini channels used for studies [40].*

less than 350 [47]**.** The increase of heat transfer was also observed by providing the internal fins with the increase of pressure drop, as a cumulative effect, the microchannel performance was increased. The proximity from the wall of the large row of pin fins showed the greatest effect on the velocity field, distribution of flow, temperature distribution, and streamline structure. As the gap between the pin-fins increases, the heat transfer is noticed to increase first and then decrease. The fin structured microchannel with equal gap and diameter shows better thermal performance [48]. A schematic model of finned MCHS is produced in **Figure 6**. The effect of proximity

from the sidewall on the thermal performance is represented in **Figure 7**.

*Schematic model of finned MCHS,* **(a)** *physical model and* **(b)** *boundary conditions [48]***.**

**288**

**Figure 6.**

**Figure 5.**

*The influence of proximity from the sidewall on the thermal performance of MCHS [48].*

The large heat transfer (HT) enhancement was found in the periodically converging and the diverging and periodically expanded and constrained MCHS. 46.8– 160.2% improvement in HT was noticed in the converging and the diverging MCHS (**Figure 8**) [49]**.** 50–117% improvement of heat transfer was found in the periodically expanded and constrained MCHS (**Figure 9**) in the range of Re from 150 to 820 [50]**.**

An experimental study on periodic jetting and throttling MCHS (**Figure 10**) has concluded that the mean temperature and maximum temperature in the throttling

**Figure 8.**

*Physical model of periodic converging–diverging microchannel [49].*

**Figure 9.** *Design of the periodic expanded and constrained MCHS [50].*

#### **Figure 10.**

*Physical model of* **(a)** *jetting MCHS* **(b)** *throttling MCHS [51].*

MCHS are less than the jetting MCHS with huge pressure loss [51]. The heat transfer rate in the trapezoid cross-sectional MCHS with grooved structure was noticed to be improved by 28% because of the breaking and regeneration of the thermal and hydrodynamic boundary layer [41]**.**

Huan-ling Liu et al. [52] developed new annular MCHS designs, MRNH and MRSH presented in **Figure 11,** and concluded that the consistency of the substrate temperature of the interleaved structure was better than the sequential structure. The increase of the total thermal resistance was noticed with rising the slant angle in the MRSH design. The variation of the average Nu with the pumping power is represented in **Figure 12**.

Some of the researchers [53–55] investigated the effect of the channel surfaceroughness on the thermal performance of MCHS. Their work disclosed that the HT in MCHS was augmented for rough-surfaced channels and its effect is very significant at high Re. Yan Ji et al. [56] analyzed the low Knudsen number (Kn) gas

**291**

**Figure 13.**

*Variation of nu with the relative roughness [56].*

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks…*

flow in rough channels and observed a decrease of local heat flux with increasing the relative roughness for rarefied and compressible flow. The variation Nu with the

Secondary flow in MCHS is an effective method to reduce the pressure drop, which is a major limitation in the above-discussed models. One of the secondary flow MCHS models is shown in **Figure 14**. The maximum enhancement in heat transfer in secondary flow MCHS was obtained by optimizing the ratio of the parameters of secondary channel width to the main channel width (), the ratio of secondary channel half-pitch to the main channel width (), and tangent value of

*DOI: http://dx.doi.org/10.5772/intechopen.97087*

roughness is shown in **Figure 13**.

**Figure 12.**

the angle of the secondary channel () [57].

*The variation average nu with pumping power at three slant angles [52].*

**Figure 11.** *Schematic design of MCHS, (a) MRNH (b) MRSH configuration [52].*

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks… DOI: http://dx.doi.org/10.5772/intechopen.97087*

**Figure 12.** *The variation average nu with pumping power at three slant angles [52].*

flow in rough channels and observed a decrease of local heat flux with increasing the relative roughness for rarefied and compressible flow. The variation Nu with the roughness is shown in **Figure 13**.

Secondary flow in MCHS is an effective method to reduce the pressure drop, which is a major limitation in the above-discussed models. One of the secondary flow MCHS models is shown in **Figure 14**. The maximum enhancement in heat transfer in secondary flow MCHS was obtained by optimizing the ratio of the parameters of secondary channel width to the main channel width (), the ratio of secondary channel half-pitch to the main channel width (), and tangent value of the angle of the secondary channel () [57].

**Figure 13.** *Variation of nu with the relative roughness [56].*

*Heat Transfer - Design, Experimentation and Applications*

hydrodynamic boundary layer [41]**.**

*Physical model of* **(a)** *jetting MCHS* **(b)** *throttling MCHS [51].*

**Figure 10.**

MCHS are less than the jetting MCHS with huge pressure loss [51]. The heat transfer rate in the trapezoid cross-sectional MCHS with grooved structure was noticed to be improved by 28% because of the breaking and regeneration of the thermal and

Huan-ling Liu et al. [52] developed new annular MCHS designs, MRNH and MRSH presented in **Figure 11,** and concluded that the consistency of the substrate temperature of the interleaved structure was better than the sequential structure. The increase of the total thermal resistance was noticed with rising the slant angle in the MRSH design. The

Some of the researchers [53–55] investigated the effect of the channel surfaceroughness on the thermal performance of MCHS. Their work disclosed that the HT in MCHS was augmented for rough-surfaced channels and its effect is very significant at high Re. Yan Ji et al. [56] analyzed the low Knudsen number (Kn) gas

variation of the average Nu with the pumping power is represented in **Figure 12**.

**290**

**Figure 11.**

*Schematic design of MCHS, (a) MRNH (b) MRSH configuration [52].*

**Figure 14.** *Design of* **(a)** *secondary flow MCHS* **(b)** *computational domain [57].*

A novel MCHS model namely, permeable membrane MCHS (PMM) and manifold microchannel heatsink (MMC) manufactured by Direct metal laser sintering method using an aluminum alloy was studied experimentally and noticed the better performance of the PMM heat sink [29]. **Figure 3** shows the images of PMM and MMC heat sinks.

#### **3.2 Jet impingement arrangement**

A microchannel heat sink with a jet impingement arrangement is an active heat sink with high heat transfer coefficients. Jet impingement in the flow of a fluid using liquid coolants produces very high heat transfer coefficients and it is more significant in the stagnation region [58–60]. Substantial work has been performed on the jet impingement, with various working fluids, at various nozzle configurations, standoff distances, and lengths. Jet impingement in heat sinks shows uniform temperature distribution for both micro-scale and macroscale applications. Microscale jet impingement is most suitable for dissipating the heat from high-powered electronic systems [61]. Hybrid MCHS with micro jet impinging developed for photovoltaic solar cell cooling was enhanced the solar cell electrical efficiency by 39.7% [62]**.** The numerical study conducted on the hybrid MCHS with a slot-jet module and various channel cross-sections revealed that the trapezoidal channel shows the better cooling effect [63]**.** The decreasing order of the pressure drop in the various channels at the fixed flow rate was circular cross-section, a trapezoidal cross-section, and rectangular cross-section. The rectangular channel was not favorable for impingement jet to produce vorticities, so it has a low-pressure loss. Afzal Husain et al. [64] modeled a new hybrid MCHS with impingement and pillars (**Figure 15**). It was noticed that the MCHS model with the low jet pitch to diameter ratio produces a greater heat transfer coefficient. The hybrid MCHS design with the ratio of standoff (distance between jet impingement surface and nozzle exit) to the diameter of the jet close to 2 and 3 results in low thermal resistance and pumping power.

P. Naphon et al. [65] applied the ANN model (**Figure 16**) of the Levenberg– Marquardt Backward propagation (LMB) training algorithm and Computational

**293**

**Figure 16.**

**Figure 15.**

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks…*

fluid dynamics to study the jet impingement of Nanofluids in the MCHS. The maximum deviation of the predicted results from the measured data was found to be 1.25%. With increasing the nozzle level, the heat transfer from the heat sink module to Nanofluid was tended to decrease, which causes the high fins tip temperature. Generally, there are two different jet impingement arrangements: the free-surface and submerged jet-arrays [66]**.** The schematic model of the free surface

The heat transfer was also enhanced effectively by introducing various shapes of dimples on the HT surface with impinging jets [67]**.** Convex dimple arrangement

and submerged jet arrays are produced in **Figure 17**.

*Optimal ANN model proposed by P. Naphon et al. [65].*

*DOI: http://dx.doi.org/10.5772/intechopen.97087*

*Schematic model of the hybrid MCHS with pillars and jet impingement [64].*

*Recent Advancements in Thermal Performance Enhancement in Microchannel Heatsinks… DOI: http://dx.doi.org/10.5772/intechopen.97087*

#### **Figure 15.**

*Heat Transfer - Design, Experimentation and Applications*

*Design of* **(a)** *secondary flow MCHS* **(b)** *computational domain [57].*

A novel MCHS model namely, permeable membrane MCHS (PMM) and manifold microchannel heatsink (MMC) manufactured by Direct metal laser sintering method using an aluminum alloy was studied experimentally and noticed the better performance of the PMM heat sink [29]. **Figure 3** shows the images of PMM and

A microchannel heat sink with a jet impingement arrangement is an active heat sink with high heat transfer coefficients. Jet impingement in the flow of a fluid using liquid coolants produces very high heat transfer coefficients and it is more significant in the stagnation region [58–60]. Substantial work has been performed on the jet impingement, with various working fluids, at various nozzle configurations, standoff distances, and lengths. Jet impingement in heat sinks shows uniform temperature distribution for both micro-scale and macroscale applications. Microscale jet impingement is most suitable for dissipating the heat from high-powered electronic systems [61]. Hybrid MCHS with micro jet impinging developed for photovoltaic solar cell cooling was enhanced the solar cell electrical efficiency by 39.7% [62]**.** The numerical study conducted on the hybrid MCHS with a slot-jet module and various channel cross-sections revealed that the trapezoidal channel shows the better cooling effect [63]**.** The decreasing order of the pressure drop in the various channels at the fixed flow rate was circular cross-section, a trapezoidal cross-section, and rectangular cross-section. The rectangular channel was not favorable for impingement jet to produce vorticities, so it has a low-pressure loss. Afzal Husain et al. [64] modeled a new hybrid MCHS with impingement and pillars (**Figure 15**). It was noticed that the MCHS model with the low jet pitch to diameter ratio produces a greater heat transfer coefficient. The hybrid MCHS design with the ratio of standoff (distance between jet impingement surface and nozzle exit) to the diameter of the jet close to 2 and 3 results in low thermal resistance and

P. Naphon et al. [65] applied the ANN model (**Figure 16**) of the Levenberg– Marquardt Backward propagation (LMB) training algorithm and Computational

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pumping power.

MMC heat sinks.

**Figure 14.**

**3.2 Jet impingement arrangement**

*Schematic model of the hybrid MCHS with pillars and jet impingement [64].*

fluid dynamics to study the jet impingement of Nanofluids in the MCHS. The maximum deviation of the predicted results from the measured data was found to be 1.25%. With increasing the nozzle level, the heat transfer from the heat sink module to Nanofluid was tended to decrease, which causes the high fins tip temperature. Generally, there are two different jet impingement arrangements: the free-surface and submerged jet-arrays [66]**.** The schematic model of the free surface and submerged jet arrays are produced in **Figure 17**.

The heat transfer was also enhanced effectively by introducing various shapes of dimples on the HT surface with impinging jets [67]**.** Convex dimple arrangement

**Figure 17.** *Schematic model of* **(a)** *free-surface jet-arrays and* **(b)** *submerged jet-arrays [66].*

has superior overall performance among the three arrangements studied and it has a high heat transfer rate and lowest pressure loss. The single nozzle with a convex dimple arrangement is presented in **Figure 18**.


**1. Introduction**

The history of dyes began over 4000 years ago, and for many years, dyes were extracted from natural sources, such as flowers, vegetables, wood, insects, and roots, among others [1]. The synthetic dye industry began with the synthesis of mauveine, by researcher William Henry Perkin, in 1865. This dye, which until then was extracted from coal tar, was synthesized by Perkin while the researcher was looking for a new synthetic route for quinine, a drug used to treat malaria [2]. Perkin's discovery marked the creation of a new generation of dyes [3].

Synthetic dyes are organic compounds that are produced from raw materials of petrochemical origin. Such compounds may or may not be soluble in water, are generally easily absorbed, and quickly impart color to substrates [1]. Structurally, dyes

contain three essential groups: the chromophore, which is the active site of dyes where atoms interacting with visible electromagnetic radiation are located [2]; auxochrome, which has functional groups that introduce the chromophore, increase the fiber's affinity to color, and decrease its solubility in water [4] and conjugated aromatic structures, such as benzene, anthracene and perylene rings [2]. Dyes are classified according to their chemical structure and application mode. Thus, according to the chemical structure of the dye, this is classified into azo, anthraquinone, sulfur, phthalocyanine, and triarylmethane [2]. Depending on its method of application, the dye is classified as reactive, direct, dispersed, basic, and by vat dyeing [5].

The chemical composition of the dye reflects in its pigmentation (formation of its color), being also responsible for the lighter or darker tone of each dye. The coloring is due to the absorption of light of a certain wavelength in the visible range of the electromagnetic spectrum, that is, the dye is a molecule capable of absorbing certain light radiations and then reflecting the complementary colors [6]. **Table 1** brings together the main classes of dyes used in the textile industry, the types of fiber or substrates to which the dyes of each class are applied, the types of interaction between dye and fiber or substrate, and the methods of application or dyeing.

Dyes are materials of great importance in different industrial sectors, such as fabric production, papermaking, plastics, cosmetics, as well as in medicine and biology [8]. Currently, the world production of dyes is about 800 tons a year and most of the dyes produced, about 70 million tons a year, are used in the textile industry [1].

With high world production, the textile industry occupies the second place among the industrial sectors that most pollute since during the dyeing stage a large amount

#### **Table 1.**

*Main classes of dyes used in the textile industry, types of fiber to which the dyes of each class are applied, types of interaction between dye and fiber, and methods of application or dyeing [7].*

#### *Enzymatic Bioremediation of Dyes from Textile Industry Effluents DOI: http://dx.doi.org/10.5772/intechopen.103064*

of dyes is released into the environment due to the nonadhesion of the dye to the substrate to be dyed [2]. Therefore, the search for economically viable and ecologically sustainable alternatives for the treatment of effluents containing textile dyes is of extreme importance and interest, whereupon bioremediation is a process that can help to solve this industrial problem.

This chapter brings together the main and most recent information reported in the scientific literature on the enzymatic bioremediation of dyes from textile industry effluents. In this context, the negative impacts of dyes used in this industrial segment on human and animal health are discussed, as well as methods conventionally used for the treatment of industrial effluents containing dyes, the principles of enzymatic bioremediation, the enzymes used in this process, and their by-products.


*3.2. Annotation of Carbohydrate-Active Enzymes*

The carbohydrate-active enzymes and carbohydrate-binding modules were annotated using the dbCAN2 Meta server (version 9.0) with default settings [24]. Predictions by at least one of the three algorithms integrated within the server (DIAMOND, HMMER, and Hotpep) were considered sufficient for CAZy family assignments. The relative abundances of CAZymes and PLs were visualized by stacked bar plots and heat maps using the ggplot2 (version 3.3.3) and pheatmap (version 1.0.12) packages in RStudio (version 1.3.1093) with R (version 4.0.3, R Foundation for Statistical Computing) [35,36].