FFR latency values using syllable /da/of 40-ms duration performed on babies with normal hearing (silent background) [19].
\r\n\tNot all mixtures of particles and liquids can be considered slurries. A slurry has its character quite different from the carrying liquid (sometimes referred to as the vehicle). A Newtonian liquid has its shear stress directly proportional to its rate of deformation, but this is seldom the case for a slurry. In general, slurries are referred to as non-Newtonian liquids and ways of dealing with them are important threads in this text.
\r\n\r\n\tPipe blockages and pipe wear cause high costs to industry, in both maintenance and loss of production. This waste, and environmental damage which comes with it, can be shown to be reduced by careful application of slurry technology. This book will welcome recent research efforts to understand slurries related to the above-mentioned topics.
",isbn:"978-1-80356-669-6",printIsbn:"978-1-80356-668-9",pdfIsbn:"978-1-80356-670-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"a3de73ad02868797334aa3024ec3f018",bookSignature:"Dr. Trevor Jones",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11907.jpg",keywords:"Slurry Rheology, Non-Newtonian Flows, Wastewater Treatment, Blood Rheology, Slurry Measurement, Slurry Tomography, Pipeline Pigs, Pipeline Cleaning, Wear, Swirl Induction, Electrical Resistance Tomography, Electrical Capacitance Tomography",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 22nd 2022",dateEndSecondStepPublish:"May 25th 2022",dateEndThirdStepPublish:"July 24th 2022",dateEndFourthStepPublish:"October 12th 2022",dateEndFifthStepPublish:"December 11th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"6 hours",secondStepPassed:!1,areRegistrationsClosed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Jones is a world-leading expert in naturally-occurring particle products - slurries, sludges, coal, ore, and gravel. 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These insights lead in turn to “innovation” and new technologies [1]. However, in many instances, such an insight cannot be obtained purely from current experiments. The required fundamental theory has been available for some time. The more recent development of computational methodologies and the dramatic increase in computer power made computational methods an additional and competitive tool to describe chemical phenomena [2]. This field is broadly known as “modeling.” In “molecular modeling,” the premise is that the interatomic and intermolecular interactions can be known [3]. DFT has become the dominant tool for the purpose of determining such interactions [4]. In particular, in solid-state chemistry and physics, it has become increasingly popular since appropriate functionals and basis sets [5] were designed to provide a viable balance between the reliability of the numerical results and the computational costs.
Metal-organic frameworks (MOFs), also known as porous coordination polymers (PCPs) [6, 7, 8], are a class of hybrid organic-inorganic materials with high surface area, a permanent porosity with large internal pore volume and tunable pore sizes. They have a wide range of potential applications such as gas storage [9] and separation [10], catalysis [11], and many others [12, 13, 14]. MOFs are constructed by interlinking metal ions or, more generally, metal-containing units with organic moieties (carboxylates, azolates, imidazolates, pyridyl, etc.) through coordination bonds, thus creating crystalline frameworks. Due to the variety of the structural and chemical elements, some MOFs show unexpected characteristics, which sometimes cannot be fully assessed experimentally. Theoretical approaches have been intensively employed in this particular case to investigate the systems at the atomic level. Beyond the analysis of observed phenomena, the prediction of unknown attributes has been attempted.
In this book-chapter, we review and discuss the current status and challenges of DFT studies of MOFs. We focus in particular on aspects relevant to catalysis at the metal centers found in these structures.
One of the main issues of DFT calculations is that a compromise between the dependability of the results and computational costs must be found, especially for large and complex systems [15]. A primary issue is how to select a functional suitable for the investigated system [16]. Different functionals, based on different approximations, may give different (even opposite) results. It is thus important to choose the functionals wisely. No functional devised up to now has proven to be suitable for all systems. Therefore, the validation of any selected functional is crucial.
MOFs are crystalline materials with extended frameworks. This needs, in some instances, to be taken into account when, for catalytic applications of MOFs, DFT is used to investigate the reaction mechanism. The reaction enthalpy can be obtained approximately from the energy at 0 K by including a zero-point energy correction calculated from (possibly scaled) vibrational frequencies. To compute the entropy, harmonic or anharmonic low-frequency modes can be used. The temperature-dependent free and activation energies can be calculated by adding thermal enthalpic and entropic effects. The so-obtained free energies of reaction are used to calculate temperature-dependent equilibrium constants. Note that the kinetics of a reaction can also be investigated, e.g., by transition state theory (TST) [17]. However, this is beyond the scope of this chapter.
Since the properties of MOFs depend not only on their chemical composition but also their structures, atomistic structural characterization is essentials. Generally, the structure of a newly synthesized MOF is characterized by single-crystal X-ray diffraction (SC-XRD). If the quality of the single crystals is not sufficient, the structure can be inferred from powder diffraction patterns [18] which often remains incomplete because of the complicated molecular system, large unit cell, and low symmetry. Molecular modeling methods must thus complement these experiments [19].
The periodic structure of an MOF can be studied by DFT: properties such as cell parameters and elastic properties can be obtained from periodic calculations. However, such calculations consume large amounts of computational resources due to the typically large unit cell of MOFs. Simple functionals such as local-density approximation (LDA) or generalized gradient approximations (GGA) are, however, often sufficient in this case [20]. Studying catalytic effects requires more advanced “hybrid” functionals, e.g., BP86 [21], B3-LYP [22], or M06 series [23].
Molecular mechanics (MM) is a much cheaper computational method to study large systems. The reliability of these calculations depends on the quality of the force fields used to describe the interactions between the atoms in the investigated system. Some high-accuracy force fields for MOFs, such as BTW-FF [24], MOF-FF [25], Quick-FF [26], and others [27, 28], were parametrized from DFT calculations. They were successfully used to determine and predict the periodic structures [29, 30], as well as to examine phase transformations [31, 32, 33], guest diffusion in the pores and other mechanical properties such as bulk moduli [34], elastic constants [35] and mechanical stability [36]. Note that MM calculations cannot describe electronic structures. Bond breaking and forming cannot be accounted for in such calculations. Thus, it is not possible to study reaction mechanisms using conventional MM methods [37].
In summary, for structurally well-defined and small enough systems, DFT calculations are a cogent approach especially in the field of localized catalytic reactions. We aim here to outline the suitability of DFT techniques to study catalysis in MOFs materials through examples from the recent literature.
MOFs have well-defined crystal structures with high concentrations of metal centers organized at topical distances, and large pore volumes between these centers. Even though MOFs are less able to withstand high temperatures compared to some other catalytic porous materials, their undeniable qualities such as large internal surface areas and uniform pore and cavity sizes make them attractive for various applications [38]. The pore size/shape in the framework can be tuned for selectivity for a particular reaction. In contrast, the small pore windows of other nanoporous materials, such as zeolites, commonly limit the catalytic transformation of large molecules [39].
In principle, various types of active sites can be incorporated into MOFs. Coordinatively unsaturated metal sites (CUSs) and functional groups on the organic linkers (usually acid/base sites) are the main catalytic sites. In addition, even though the MOF framework itself does not contain active sites, the catalytic reactivity can be enhanced by (a) postsynthetic functionalized modification [40] and (b) encapsulation of catalytic species [41]. The pore volume of MOFs is able to accommodate organic molecules, inorganic nanoparticles, metal complexes, and enzymes to conduct catalytic reactions. Here, we focus only catalytic reactions taking place on one CUS.
It is because of these functionalities [39] that MOFs were originally proposed for applications in catalysis. From this point of view, one tends to focus on the design and synthesis of MOFs with large pore sizes. The purpose is to allow the reactant to diffuse easily into the framework reaching the catalytic centers. Suitable synthetic techniques make it possible to choose the linkers and the metal-containing nodes to construct MOF suitable for particular reaction. Such a well-designed MOF catalyst should be highly reactive, selective, and stable. In order to approach this goal, some understanding of the reaction mechanisms is essential. In many cases, the reactants and resulting products tend to be well localized, for a sufficiently long time, in the framework due to host-guest interaction. The catalytic site can thus often be separated from the framework and investigated independently, making it easier to follow the reaction mechanisms [42].
We focus in this brief overview, mostly through a series of examples, on such local analyses of the activity of single-site catalysts. Selected examples of work based on cluster, or truncated, models of reactions catalyzed by metal centers, metal substitutions, and deposited metal complexes are succinctly reviewed.
As mentioned above, MOFs are built up from metal ions or metal-containing clusters as the inorganic building node and organic ligands as linkers. In some MOFs, coordinatively unsaturated metal sites (CUSs) have a catalytic effect. The sites are spatially well separated and, ideally, structurally identical. Thus, to investigate the reaction mechanism with DFT methods, truncated structures can often be used to represent the entire MOFs.
MOFs with CUSs provide identical active metal sites, which are spatially isolated from each another. The sites are structurally well-characterized, without coupling to their neighbors. In typical dense heterogeneous catalyst, the reaction takes place on the outer surface [43]. One way to enhance the catalytic effect is to increase the accessible surface area. In MOFs, reactions occur not only on the outer surface, easily accessible active sites inside the framework also contribute.
Maihom et al. investigated the epoxidations of ethylene over Fe3(BTC)2 (BTC = 1,3,5-benzenetricarboxylate) using N2O as oxidant [44].
(a) Truncated model of [Fe2(H2BTC)4] and (b) energy profile of reactants, intermediates, and transition states involved in the formation of ethylene oxide (solid line) and the acetaldehyde (dash line) over the Fe paddle wheel. Adapted from Ref. [
An investigation of the epoxidation of propylene using Cu3(BTC)2 and Fe3(BTC)2 was recently carried out by the same group [45]. As mentioned, truncated clusters, [Cu2(H2BTC)4] and [Fe2(H2BTC)4], are suitable for these calculations, carried out at the M06-L/6-31G(d,p) level. As expected, the calculations showed that Fe3(BTC)2 is more active than Cu3(BTC)2 due to a larger charge transfer from the CUS to the oxidant O2. It was found that the production of propylene oxide is favored over that of carbonylic products (propanal and acetone). Propanal and acetone were formed on the Fe-MOF cluster via the formation of a C▬O bond. Then, the propyleneoxy intermediates and acetone are formed via a 1,2-hydride shift.
The M-MOF-74 series (M2(DOBDC), where DOBDC = 2,5-dioxidoterephthalate and M = Mg, Ni, Co, Cu, and Zn) has been proposed as good catalysts for several reactions, owing to their reactive CUSs and large 1D channels, beneficial for the reactants’ access to the active site. They are also thermally and chemically very stable [46, 47, 48]. Valvekens et al. [49] used MOF-74 with various metal ions, i.e., Mg (II), Ni (II), Co (II), Cu (II), and Zn (II) as Lewis acid catalysts to promote Knoevenagel condensations and Michael additions.
DFT calculations were performed on truncated models cut from the periodic geometries (Figure 2) optimized at the PBE-D2 level. The catalytic activities of M2(DOBDC) systems with respect to the Knoevenagel condensation and Michael additions were examined. The calculations at the B3LYP level with a 6–31 g(d) basis showed that Ni-MOF-74 is the most active catalyst for both reactions. In addition, it was found that the phenolate groups coordinated with the CUSs substantially increase the catalytic performance. The phenolate oxygen proved to be a stronger base than the carboxylate oxygen, resulting in more acidic CUSs, enhancing the catalytic activity.
Periodic structure of M2(DOBDC) optimized at the PBE-D2 level of theory (left), and the cluster model M9(DOBDC)9, truncated from the periodic structure (right). Adapted from Ref. [
Llabrés i Xamena et al. [50] demonstrated that Cu(2-pymo)2 and Co(PhIM)2 (2-pymo and PhIM are 2-hydroxypyrimidinolat and phenylimidazolate, respectively) promote the aerobic oxidation reaction converting tetralin hydrocarbon to ketone and alcohol derivatives. The tetralin was first oxidized to hydroperoxides under oxygen condition and then decomposed to ketone and alcohol under the influence of the Lewis acid sites Cu(II) and Co(II). Ryan et al. [51] studied the mechanism of the hydroperoxide decomposition over three different complexes possessing copper or cobalt CUSs, i.e., Co(imidazolate)4, Cu2(2-hydroxypyrimidinolat)4, and Cu2(acetate)4, as illustrated in Figure 3.
The metal cluster models taken from (a) Co(imidazolate)4, (b) Cu2(2-hydroxypyrimidinolat)4, and (c) Cu2(acetate)4.
From DFT calculations (B3LYP/TZVP/6-31G(d,p)), the access of hydroperoxide to the CUSs of Cu2(2-hydroxypyrimidinolat)4 and of Co(imidazolate)4 was found to be blocked by this bulky ligand. As a consequence, no decomposition of hydroperoxide was observed for the two systems. On the other hand, for Cu2(acetate)4, i.e., without the bulky ligands, the decomposition should occur. However, the calculations revealed that Cu2(acetate)4 was not active for the decomposition of tetralin. The energy barrier of the O▬O bond cleavage over Cu2(acetate)4 (35.6–36.8 kcal/mol) was almost identical with that of the cleavage in the gas phase without catalyst (36.0–36.7 kcal/mol). The external surface was then considered as the active sites.
A complex consisting of Cu coordinated by three organic linkers and one water molecule was modeled representing the edge or outer surface of the framework (Figure 4a). The energy barrier of the hydroperoxide decomposition on the new model complex decreased to 25.3 kcal/mol, which was considerably lower than the value of the gas-phase reaction without MOFs as shown in Figure 4b.
(a) Model of a cluster representing the exterior of a Cu2(2-hydroxypyrimidinolat)3 with one water molecule, (b) Gibbs free energy along the reaction coordinate for the proposed reaction cycle over the Cu2(2-hydroxypyrimidinolat)3 with one water molecule (blue) and oxygen▬oxygen bond cleavage without catalyst (green). All energies are in kcal/mol. Figure adapted from Ref. [
Vanadium-based MIL-47(V), [VO(BDC)] (BDC = benzene-1,4-dicarboxylate), is an active catalyst for the liquid-phase cyclohexene oxidation-reaction using tert-butyl hydroperoxide (TBHP) as an oxidant [52]. MIL-47(V) is built up from linear V-(μ2-O)-V chains interconnected by terephthalate linkers to form a 3D framework possessing 1D rhombic channels. Each V(IV)-center in this chain coordinates to six oxygen atoms—four from carboxylate and two from μ2O. Typically, MIL-47(V) does not provide CUSs. However, CUSs can be created from structural defects obtained by partially breaking the V▬OCOO bonds and from the hydrolysis of the V▬OCOO bonds.
The main products of the cyclohexene oxidation reaction are cyclohexene oxide, cyclohexane-1,2-diol, tert-butyl-2-cyclohexenyl-1-peroxide, and 2-cyclohexen-1-one with a conversion of about 80%. It was found that the catalytic performance of MIL-47(V) was comparable with that of typical homogeneous catalyst, VO(acac)2. Note that no leaching of V(IV) was observed when the oxidant was dissolved in the solution. The structures of the MIL-47(V) were maintained intact until the end of reaction. Leus and Vandichel et al. [52] proposed a reaction pathway from DFT calculations on finite clusters of MIL-47(V) (Figure 5).
Simulated model of V-MIL-47.
The results were in good agreement with EPR and NMR measurement that are interpreted in terms of the existence of (at least) two different catalytic pathways, described as the “direct” and “radical” pathways [52]. The first step of both pathways was the formation of a vanadium hydroperoxide species from TBHP. For the direct pathway, cyclohexene was directly converted to cyclohexene oxide, while the oxidation state of vanadium (V(IV)) did not change during the reaction. In the case of the radical pathway, V(IV) was oxidized to V(V), which further reacted with the oxidant TBHP to give an active species of the cyclohexene epoxidation. Finally, the catalyst was regenerated by interacting with TBHP again. At the B3LYP-D3 and 311 + g(3df,2p) level of theory, the reaction free energy for epoxidation reaction was 37 kJ/mol for the more favorable radical route.
Moreover, Matthias et al. [53] studied the cyclohexene oxidation using MIL-47(V)-functionalized linkers (with the functional groups ▬OH, ▬F, ▬Cl, ▬Br, ▬CH3, and ▬NH2) by means of experimental and theoretical works. Different catalytic conversions were observed depending on the functionalization of the linkers. DFT calculations on truncated clusters of MIL-47(V) and its derivatives were performed as in the abovementioned example for the radical pathway. The results showed that, compared to the parent MIL-47(V), the catalytic efficiency significantly increased due to the functional groups. Among these, the ▬OH-functionalized structure showed the largest improvement (lowest activation energy), which was in good agreement with the experimental results. This is because of a strong hydrogen bond between the ▬OH and the alkylperoxo group possibly stabilizing the transition state.
Partial substitution of metal ions while maintaining the structural integrity and the porosity is a promising strategy enabling some otherwise inactive MOFs to show a catalytic activity [54]. The metal substitution usually involves the cleavage and regeneration of coordination bonds between metal ions and organic ligands. The atomic-level understanding of this process is difficult, making room for molecular modeling. Here, we show examples of theoretical studies on the catalytic activity of metal-substituted MOFs.
Xiao et al. [55] reported the oxidation reaction of ethane to ethanol over magnesium-diluted Fe0.1Mg1.9(DOBDC), MOF-74, in which 5% of the redox-inactive Mg(II) were substituted by the active Fe(II). This framework provides wide hexagonal channels beneficial for an easy access of the reactants to the site-isolated open Fe-CUSs. Nitrous oxide (N2O) was used as the oxidant, generating highly reactive Fe(IV)-oxo intermediates, which could further activate strong C▬H bonds of alkanes, yielding ethanol and acetaldehyde. Owing to the short lifetime of Fe(IV)-oxo, it could neither be isolated nor characterized by conventional experiments.
Shortly afterward, Verma el al. [56] applied DFT calculations to confirm whether the Fe(IV)-oxo species are formed and act as active centers for ethane hydroxylation to ethanol. They modeled the Fe sites in magnesium-diluted Fe2(DOBDC) by replacing 1 Mg atom with Fe atom in cluster models comprising 88 atoms of Mg-MOF-74. The oxidation of ethane to ethanol over this magnesium-diluted MOFs using N2O as oxidant was proposed to proceed via a two-step consecutive reaction (Figure 6): the formation of the Fe(IV)-oxo unit via N2O decomposition and the hydroxylation of ethane to ethanol over the Fe(IV)-oxo complex. It is found that the first step is the rate-determining step with an activation energy of 82 kJ/mol. Compared to the uncatalyzed reaction, where nitrous oxide directly oxidizes the ethane to ethanol, it was found that the reaction requires an activation barrier of 280 kJ/mol. This suggests that the Fe(IV)-oxo species is indeed an active center for the oxidation of ethane to ethanol.
Enthalpy profile, ΔH298.15 (in kJ/mol), for the intermediates and transition states of the catalytic cycle. The key bond distances are given in Å (color code: orange = Fe, red = O, blue = N, gray = C, and white = H). Reproduced from Ref. [
In the meantime, Hirrao et al. [57] also carried out combined quantum and molecular mechanics (QM/MM) calculations for the hydroxylation of ethane, in analogy to Mg-MOF-74. This methodology treats the active site by QM and the rest of the system is treated by MM. The accuracy of QM/MM methods certainly depends on the choice of the QM theory level and the set of MM parameters, also on the treatment of electrostatics at the interface between the QM and MM regions. One of three Mg(II) ions was substituted by Fe(II) in the QM region, as in the model suggested by Verma et al. [56]. In the ONIOM [58] scheme, the MM region was treated at the B3LYP/[SDD(Fe),6-31G(d)(others)] level while the UFF interaction model [59] was used for the MM region. The 6–311 + G(df,p) basis set was used for single-point reference calculations. This work also suggested that the spin state (S = 2) of the Fe(IV)-oxo species does not change during the reaction.
Interestingly, Liao et al. [60] then improved based on Verma et al. model [56] the understanding on the activity of Fe open sites for the oxidation of ethane reaction. They studied MOF-74 with different linkers, in particular, ▬CH3, NH2, ▬COOH, ▬CN, ▬OH, ▬OCH3, ▬N(CH3)2, and 4-pyridyl functionalized groups on different linkers such as using methanol, pyridine, formate, benzoate anion, and the imidazole anion. The authors concluded that the population of the d-orbital was significantly influenced by the coordination ligand field. The 3d orbital energy of Fe correlated with the electron-donating strength of the functional groups on the linkers. The results reveal that linkers with ▬NH2 groups reduce the enthalpic barrier for the most endothermic step in the ethane oxidation pathway. This study illustrates the use of simple models to understand complicated and computationally intensive systems. The activity of CUSs thus might be optimized by selecting suitable ligand environments, which might be useful for upgrading certain hydrocarbon process.
The design of Fe(IV)-oxo complexes in MOFs was further reported by Impeng et al. [61]. In this work, we demonstrated the possibility of designing Fe-oxo complexes in MOFs for the activation of alkane C▬H bond by incorporating an Fe ion into a Zn-based cluster derived from Zn4O(BDC)6, known as MOF-5 [62], and generating the Fe-O unit through N2O dissociation on an Fe-substituted Zn-based cluster (Fe-Zn3O(pyrazole)6). The calculations with B3LYP-D3 showed that both steps are feasible and that the catalytic activity of Fe-Zn3O(pyrazole)6 for N2O decomposition is on a par with the Fe sites in magnesium-diluted Fe2(DOBDC). Concerning ethane C▬H bond activation, in addition to σ and π pathways on triplet and quintet surfaces, an alternative unusual pathway, called δ, is also observed on the triplet surface. The σ pathway on the quintet surface
Reaction profile for ethane C▬H bond activation over the FeO-Zn3O(pyrazole)6 cluster. The inserted numbers are the relative energies ΔE, together with the enthalpies ΔH298K in parentheses. Energies are given in kcal/mol and distances are expressed in Å. The notations ADS, TS, and INT refer to the adsorption, transition, and intermediate steps, respectively. Superscripts 3 and 5 refer to the triplet and quintet spin states, respectively.
In this section, we discuss systems possessing metal-complexes/ions anchored on the inorganic building nodes of the framework, which can be achieved by postsynthetic techniques such as metalation [63], cation exchange [64], or atomic layer deposition [65]. Zr-based MOFs consist of Zr6O8 as a primary node linked with carboxylate linkers. The Zr6O8 nodes connected by 12 linkers result in the UiO-66 series, while the partial connection with 8 and 6 carboxylates produces NU-1000 and MOF-808, respectively. The catalytic reactivity can be enhanced through such modifications. This was often employed for Zr-based MOFs, which are remarkable because of their appealing chemical and thermal stability [40]. Well-known Zr-based MOFs such as MOF-808 [Zr6(μ3-O)4(μ3-OH)4(OH)6(H2O)6(BTC)2], NU-1000 [Zr6(μ3-O)4(μ3-OH)4(OH)4(H2O)4(TBAPy)2] (TBAPy = tetratopic 1,3,6,8-tetrakis(p-benzoate)pyrene) and UiO-66, known as NU-1000 and [Zr6(μ3-O)4(μ3-OH)4(BDC)6], known as UiO-66 have been studied intensively [66, 67].
Ortuño et al. [68] reported on a computational screening of the first row of divalent transition metals (i.e., Fe(II), Co(II), Ni(II), Cu(II), and Zn(II)) supported on NU-1000 (Figure 8) for acceptorless alcohol dehydrogenation. The author proposed the reaction taking place via a three-step reaction mechanism, composed of (i) a proton transfer, (ii) β-hydride elimination, and (iii) H▬H bond formation. The Fe(II), Co(II), and Ni(II) complexes, consistent with weak-field oxide ligands, had high-spin ground electronic states as quintet, quartet, and triplet, respectively. The Cu(II) and Zn(II) species were predicted to have doublet and singlet ground states, respectively. It was found that the Co(II) and Ni(II) supported NU-1000 were the two most promising catalysts for the acceptorless alcohol dehydrogenation with an activation free energy of 28.5 and 26.5 kcal/mol, respectively.
The “top” and “side” views of a 12-, 8-, and 6-connected Zr6 oxide node. The arrows indicate the unsaturated 8- and 6-connected nodes, which have potential anchoring points. Reproduced from Ref. [
Later, the same group also studied Ni(II) and Co(II) deposited on Zr-NU-1000 as a catalyst for ethylene dimerization, which converts ethylene to 1-butene and 2-butene [69]. For the structure optimization, the DFT level of theory (M06-L) and def2-TZVPP basis set were employed, whereas complete active space self-consistent field (CASSCF) and second-order perturbation theory (CASPT2) were used for the electronic structure characterization of the reactive species. The NU-1000 models were used as the same as in the previous example (Figure 8). The grafted Ni and Co were terminated with active ▬OH and ▬OH2 groups.
The Cossee-Arlman mechanism was found as the energetically preferable pathway. Ethylene insertion into the existing metal-ethyl bond was the rate-determining step. Concerning the spin state of the two catalysts, the Co(II) species can have doublet or quartet states and the Ni(II) can have singlet or triplet states. Based on these calculations, Ni(II)-modified NU-1000 (with an activation energy of 15.6 kcal/mol) presents a greater reactivity than the Co(II)-modified system (with an activation energy of 24.1 kcal/mol) for the ethylene insertion into the metal-carbon bond. The energetics of ethylene dimerization for the Ni(II) and Co(II) complexes are shown in Figure 9. From the most relevant CASSCF molecular orbitals (MOs), the 3
Reaction coordinate and calculated enthalpy ΔH298.15K for stationary points along the reaction coordinates for ethylene dimerization catalyzed by M(II)-NU-1000 (M = Co and Ni). Reproduced from Ref. [
The oxidative dehydrogenation mechanism of propane on an active Co(II)-oxygen cluster anchored on the inorganic node of Zr-NU-1000 [70] was also explored by DFT with the M06-L functional and def2-TZVPP. A highly selective propane dehydrogenation at low temperature (230°C) has been found in experiments. Li et al. [70] found a computed propene formation in line with experimental results. DFT cluster calculations allowed to study the reaction and showed the influence on the reaction of adding Co(II) cations as a secondary metal. The computed enthalpies for the equilibrium structures are shown in Figure 10.
Computed enthalpies, ΔH503K (kcal/mol), for propane oxidative dehydrogenation. Reproduced from Ref. [
In more detail, the reactive Co(III)▬O˙ moiety was generated by the catalyst regeneration reaction with O2 having a strong interaction with the propane molecules, promotes the propane dehydrogenation, and forms isopropyl at the Co(III) active site. The abstraction of the terminal C-H bond by the Co(III)▬O˙ intermediate is the rate-determining step, yielding Co(II)▬OH and isopropyl radicals, which are converted into propene. The energy required for the H abstraction producing propene (15.8 kcal/mol) was significantly lower than that for the isopropyl migration (23.1 kcal/mol), the propene formation path is thus preferable.
Gates et al. [71] showed that Rh(I) and Ir(I) diethylene complexes can be anchored on the Zr-NU-1000, Hf-NU-1000, and Zr-UiO-67 to catalyze ethylene hydrogenation and dimerization. They also used DAY zeolite as supporting material to compare the catalytic performance. DFT calculations with M06-L and def2-TZVPP were employed. The optimized geometries were in good agreement with the data analyzed from IR spectra and X-ray absorption fine structure (EXAFS) results. The ethylene insertion to the ethyl▬Rh bond (rate-determining step) significantly depended on the nature of the supporting MOF. The catalytic activity was compared between Zr- and Hf-nodes and DAY zeolites. The calculated enthalpies for the ethylene hydrogenation and dimerization were shown in Figure 11. The calculations reveal a lower energy barrier of the DAY zeolite as supporting material than Zr-NU-1000, Hf-NU-1000, and Zr-UiO-67 for the hydrogenation and dimerization. This is opposite to the experiments which show a better catalytic activity of the DAY zeolite than the MOFs materials. The authors proposed that this might be because of the spillover effect rather than a direct electronic effect on the Rh(I) complex.
Calculated enthalpy, ΔH298.15K (kcal/mol), for ethylene hydrogenation to ethane and dimerization to 1-butene catalyzed by supported metal complexes initially present as Rh(C2H4)2 on NU-1000, UiO-67, or DAY zeolites. Reproduced from Ref. [
We focus in this brief overview on theoretical studies of the catalytic activity of single-site catalytic MOFs. DFT-based approaches can provide a detailed, if only local, description of the chemistry occurring in various environments encountered in such MOFs. This not only helps in the interpretation of experiment data; the abilities of DFT calculations are a crucial characterization method toward a deeper molecular perspective. This technique is now powerful and reliable enough to predict and guide the synthesis of materials.
There are, however, several problems which need to be overcome:
To find a link between a predicted structure and its syntheses still a challenge.
Sometime nonlocal phenomena such as a stimulus-responsive behavior of the catalytic site itself must be taken into account. Many works[ref] attempt to simulate larger models in order to describe such systems. This seems to require improved methodologies to limit the computational requirements.
The functionals: Since there is no “universal functional” DFT must be always used with a lot of caution. A lot of experience has been accumulated on the suitability of various approximations to investigate MOFs. Yet new, and costly, validations are still required whenever a “new” system is to be studied.
Last but not least, in some cases, a local view as described in this chapter may not be sufficient to catch the main features of a particular process. The overall outcome of the process under study may depend on many factors, in the worst case, none of which dominant. Various “local views” that may have been obtained could be combined as building blocks (e.g., by understanding the molecular motions between “sites”). This remains largely a task for theoretical improvements in the future.
The writing and publication of this book chapter was financially supported by Vidyasirimedhi Institute of Science and Technology and the Thailand Research Fund (TRF) (RSA6080068).
There are no conflicts to declare.
Until recently, electrophysiological evaluations were performed exclusively with nonverbal stimuli such as clicks and tone bursts which allow rapid and synchronous stimulation of neurons. However, the use of verbal stimuli, such as speech sounds, allows a more accurate analysis of the auditory system, especially if the aim is to investigate how the system decodes speech sounds involved in daily communication. Verbal and nonverbal stimuli are decoded in different ways and follow different trajectories through the central auditory nervous system.
\nHuman communication consists predominantly of verbal stimuli, and it is important to understand how verbal sounds are coded at various levels of the auditory system. The need to develop research methods that are objective and accurately represent daily listening led to the development early this century of electrophysiological tests for measuring how speech sounds are perceived [1, 2]. Subsequently, a number of research groups have focused their efforts on using complex stimuli such as speech for diagnostic purposes [3, 4, 5, 6, 7, 8, 9, 10].
\nThe initial studies were performed in animal models [11] aiming to evaluate how the temporal and spectral properties of verbal stimuli were coded, and later human responses were also analyzed [12]. Among the electrophysiological procedures for investigating the processing and coding of verbal sounds, we highlight the frequency following response (FFR).
\nAcquisition of an FFR is very similar to collecting an ABR with a click stimulus. However, interpretation of an FFR requires that the audiologist has a more sophisticated knowledge base. Speech stimuli allow a more complex analysis of the responses, such as their:
timing;
magnitude;
frequency content and magnitude;
frequency tracking;
phase consistency;
intrinsic factors; and
difference between individual responses.
An FFR evaluation can be performed on different clinical populations and age groups, and below we give details of how the procedure varies depending on the patient’s age. Because FFR is a relatively new procedure, initial work was done on adult subjects. Afterward, researchers turned their interest to the study of responses in infants and young children, children and adolescents, and the elderly.
\nIn order for an FFR assessment to be useful in identifying auditory disorders at an early stage, normative values using different equipment and recording parameters need to be established and compared with language acquisition markers.
\nThe distinctive features of FFRs in different age groups will be presented in three parts:
evaluation in infants;
evaluation in children and adolescents;
evaluation in adults and the elderly.
In clinical practice, a comprehensive hearing evaluation for infants and young children is essential, since the integrity of their auditory system is the basis for acquiring oral language. In this context, if one measures only the functioning of the peripheral auditory pathway, perhaps by recording and analyzing otoacoustic emissions and/or auditory brainstem evoked potentials, it significantly constrains one’s knowledge of the patient’s hearing status. Moreover, behavioral assessments of hearing in very young children are often inconclusive, considering the diversity of neuropsychomotor development in this age group.
\nThe perception of speech is important for the development of receptive and expressive language [13]. Through auditory experiences, infants and toddlers acquire and master the linguistic elements necessary for effective communication. The experiences are associated with information from the other senses, and together they allow the acquisition and development of oral language. Through listening, the subject understands oral language and creates concepts, finally inter-relating them and expressing them through speech [14]. Thus, the importance of hearing for the acquisition and development of language is vital, and any disturbance to the auditory pathway has implications for oral communication as a whole [14].
\nFFR testing can be used with infants and young children as a predictor of the extent of future language appropriation—in other words as a way of identifying children who are at risk of deficits in oral language acquisition [2, 15]. Assessment by FFR of infants and young children is relatively recent, and published studies of its potential have only been done over the last decade. Before discussing what is known about FFR in this population, it is first necessary to clarify an important factor: maturation of the auditory pathway.
\nIt is known that peripheral hearing is functional even before birth, whereas myelination and the organization of neural connections keep developing after birth [16, 17]. Indeed, the central structures, such as the subcortex and cortex, develop throughout the early years of human life. There is an ascending myelination of the auditory pathway, evidenced by magnetic resonance imaging. Up to the 13th week of life, there is an increase in myelination density of the cochlear nucleus, the superior olivary complex, and the lateral lemniscus, with the inferior colliculus demonstrating an increase in density around the 39th week of life [18]. This continuous process of myelination of the higher structures of the auditory pathway during the first year of life must be considered when evaluating the FFR, for it means that the lower the age of the evaluated subject, the greater the latency of the FFR waves [19, 20]. This increase in latency can also be seen in other auditory evoked potentials [21]. An FFR can be recorded from a neonate, but the responses only become readily apparent from the third month of age [15]. The existence of a series of FFR waves—V, A, C, D, E, F, and O—in neonates has been pointed out by several researchers [15, 19, 22, 23, 24, 25, 26]. FFR evaluations have been performed with the vowel /i/ [15, 24], the syllables /ba/ and /ga/ [26], and the syllable /da/ [23].
\nThe FFR has been studied in neonates of different nationalities (Chinese, American) during the first days after birth, and the FFRs were nearly the same. This finding makes it possible to infer that, independent of the mother tongue, there is an innate capacity for speech coding in neonates at the subcortical level [22].
\nThe evaluation of subcortical representation of speech coding was studied by evaluating FFRs in 28 healthy North American infants, 3–10 months of age. The study focused on the fundamental frequency (F0), the response time of the FFR, and the representation of harmonics. To analyze the data in the frequency domain, spectral amplitudes were calculated by fast Fourier transform (FFT) and divided into three frequency ranges: F0, 103–125 Hz; first formant (F1), 220–720 Hz; and high harmonics (HH), 720–1120 Hz. The F0 responses were more robust in infants 3 months of age and the amplitude of F0 did not show significant changes over the entire 6 months. For the F1 and HH frequencies, there was a rapid and systematic increase of amplitude from 3 to 6 months of age.
\nTo analyze the data in the time domain, the peaks were identified manually and confirmed by a second observer. Waves I, III, and V were first identified in response to a click, and then, in the FFR, the same peak and following valley (V and A), the peaks (D, E, and F), and the displacement peak (O). Non-detectable peaks were marked as missing data points and were excluded from analysis. The latencies and amplitudes (baseline to peak) were extracted from the identified waves. The time domain analysis demonstrated a decrease in neural conduction time and an improvement in amplitude with increasing age. The latencies of A and O, the time interval between A and O, and the slope between V and A were shown to have a negative correlation between latency and age. In addition, there was an improvement in the morphology of all waves as age increased. It was also observed that infants 3–5 months of age had longer latencies, smaller intervals between A and O, and a lower V/A slope compared to those 6–10 months of age. This negative correlation between the latencies and the age of the infants, as well as the decrease of slope in the smaller children, is due to a maturational process occurring in the subcortical auditory system and shows that there is less neural synchrony in younger infants [23]. The authors also note that these findings indicate that at approximately 6 months of age, the coding of speech characteristics, both spectrally and temporally, becomes more like those of an adult, although the changes continue through to school age. These findings indicate that FFR evaluation can detect early disorders in the perception of speech sounds.
\nThe researchers also investigated the development of subcortical speech processing in Chinese infants born in households in which the mother tongue was Mandarin. They recorded FFRs at two ages: 1–3 days of life and at 3 months. This prospective-longitudinal design study included only infants who had undergone auditory screening at birth, who had no obvious neurological disorders, and did not have any risk indicator for hearing loss. Initially, 44 newborns were tested by FFR during natural sleep. After that, the sample was divided into groups. For each group, the researchers selected different speech stimuli for the evaluation of FFR (monosyllables contrasting with Mandarin). Only 13 infants completed the follow-up protocol at the third month. The processing and tracking of the fundamental frequencies of human speech at the subcortical level, evidenced by the FFR, showed more robust responses when the babies were 3 months old. Researchers acknowledged the limitations of the study, including statistical analysis and data interpretation. A research weakness was the relatively low completion rate (i.e., 17/44 infants or 38.64%). This factor undermined the power of the conclusions and prevented the possibility of performing statistical analyses for each Mandarin tone used. Despite the limitations of the study, the findings fill a gap in understanding the developmental trajectory of subcortical processing during the first 3 months of life [25].
\nFrom the theoretical assumptions highlighted in the previous reference, it should be noted that the linguistic environment of a newborn has a substantial effect on the development of its speech perception. Even at birth, children are able to detect subtle differences in verbal sounds. Newborns can effectively differentiate all the features of human speech and most infants who participated in an FFR follow-up showed improvement in pitch tracking and response amplitudes at 3 months of age [25]. Such neural refinements observed by FFR are often highlighted in the literature for both infants [22, 24] and young infants [15, 23]. For example, in a longitudinal case report of one infant, the researchers obtained FFR records when the infant was 1, 3, 5, 7, and 10 months old. The results showed an evolving trajectory of development with a transition point of about 3 months [15].
\nUsing FFR evaluation in preterm infants may also be an alternative for the early diagnosis of auditory disorders in this population related to the perception of speech sounds. Premature babies are at high risk of developing language disorders, so using FFR may be a way of measuring immature neural activity and predicting possible changes in the processing of verbal sounds. In order to do so, one study evaluated 12 premature Indian infants through FFR with the aim of exploring how an immature auditory system responds to complex acoustic stimuli such as speech [27]. Peaks V, A, C, D, E, and F were detected in almost all babies and with latencies and amplitudes similar to those reported in the literature. The waves could be replicated. The authors conclude that FFR may be a way of understanding how the human brain-stem receives speech signals and that such an assessment might be important for all high-risk babies. Although the findings of this study cannot be generalized, mainly due to the limited data (small sample and absence of a controls, among others), they point out the potential of FFR in evaluating infants from neonatal intensive care units.
\nMore recently, studies that record FFRs in the presence of background noise have been published. It is known that competing noise can make speech comprehension more difficult in people of all ages. Speech-in-noise tests are clinically available but cannot be given to infants. Thus, the use of FFRs in noise may be an alternative for evaluating impaired speech perception in young children who are unable to respond to behavioral tests.
\nIn this context, with the objective of examining the electrophysiological responses in the presence of noise, researchers have evaluated the FFR in 30 children with typical development under conditions with and without noise (a signal-to-noise ratio of +10 dB in the former) [28]. Babies were divided into two age groups: 7–12 and 18–24 months. For all infants, frequency analysis of the FFR with a Fourier transform was performed, analyzing the latency and amplitude of waves V, A, D, E, and F, and correlation tests were carried out. In both groups, the mean latency of all recorded waves was higher in the presence of noise. According to the authors, this suggests that, at least for infants up to 24 months, the presence of noise causes a delay in the appearance of FFR waves independent of age. In addition, they observed a greater amplitude of F0 in the noise condition in the group of older babies; this difference was not seen in the silent condition. Thus, the authors point out that, at 2 years of age, infants are less vulnerable to the degrading effects of noise compared to children younger than 12 months.
\nThe development of phase lock and frequency representation has also been evaluated in infants. This was the focus of a study that included an initial sample of 56 typical babies, aged between 2 and 12 months, and evaluated the FFR with /ba/ and /ga/ stimuli presented in the right ear using the SmartEP equipment from Intelligent Hearing Systems [26]. These responses were also obtained in young adults to provide a reference for the course of development of neural synchrony (represented by phase lock) and response amplitude (represented by spectral magnitude). The results obtained in this study demonstrate that the strength of phase-lock in the fine structure at CV transition is higher in young adults compared to infants. However, phase lock for F0 was equivalent between adults and infants. The frequency of F0 was found to be higher in older infants compared to younger infants and adults. Thus, these data demonstrate that speech coding can be evaluated in infants from 2 months of age and that such data are of value in a clinical setting, since it is known that performing electrophysiological evaluation of hearing in young children is difficult because they are less able to remain still during a test. The data indicate that the FFR may be a way of testing babies who are at risk of developing a language disorder, examining the auditory coding mainly of the midbrain, but also reflecting contributions from the auditory nerve, brain stem, and cortex.
\nThe most commonly used parameters in FFR evaluations are: monoaural stimulus, right ear stimulation, intensity of 80 dB SPL, syllable /da/ speech stimulus, alternating polarity, presentation rate of 10.9 stimuli per second, vertical placement of electrodes, insert headphones, and the subject sitting distracted or awake during recording [29].
\nRegarding the latency parameters, when FFR is done with the Navigator Pro AEP System (Natus Medical, Inc.) and a syllable stimulus, one group of researchers [19] pointed out that in 23 normal-hearing babies (0–12 months) the wave latencies were on average: V = 7.22 ms, A = 8.22 ms, D = 23.14 ms, E = 31.5 ms, F = 39.91 ms, and O = 49.64 ms. FFR wave latencies were also investigated in 53 children aged 3–5 years (Tables 1 and 2).
\nWaves | \n||||||
---|---|---|---|---|---|---|
\n | V | \nA | \nD | \nE | \nF | \nO | \n
\n | Lat | \nLat | \nLat | \nLat | \nLat | \nLat | \n
∑ | \n7.22 | \n8.22 | \n23.14 | \n31.51 | \n39.91 | \n49.64 | \n
SD | \n0.42 | \n0.43 | \n0.66 | \n0.49 | \n0.45 | \n1.32 | \n
Detect (%) | \n86.9 | \n86.96 | \n91.30 | \n91.30 | \n82.61 | \n65.22 | \n
FFR latency values using syllable /da/of 40-ms duration performed on babies with normal hearing (silent background) [19].
∑: average (ms), SD: standard deviation, Detect: the percent detectability for each peak.
Sample: 23 babies (0–1 years old).
Waves | \n||||||
---|---|---|---|---|---|---|
\n | V | \nA | \nD | \nE | \nF | \nO | \n
\n | Lat | \nLat | \nLat | \nLat | \nLat | \nLat | \n
∑ | \n6.59 | \n7.56 | \n22.36 | \n30.90 | \n39.34 | \n48.14 | \n
SD | \n0.26 | \n0.35 | \n0.38 | \n0.37 | \n0.32 | \n0.42 | \n
Detect | \n100 | \n100 | \n88.67 | \n98.11 | \n100 | \n90.57 | \n
FFR latency values using syllable /da/ of 40-ms duration performed in children with normal hearing (in silence) [19].
∑: average (ms), SD: standard deviation, Detect: the percent detectability for each peak.
Sample: 53 children (3–5 years old).
Parameters of FFR evaluation in infants and young children used in the Hearing Electrophysiology Service of the Federal University of Santa Maria, Brazil, are presented in Table 3.
\nPresentation parameters | \nSetting | \n
---|---|
Equipment | \nSmartEP, Intelligent Hearing Systems (IHS) | \n
Transducer | \nInsert phones | \n
Electrodes | \nFz; Fpz; M1; M2 or Cz, M1, M2 | \n
Stimulation | \nRight ear | \n
Stimulus | \nSyllable /da/ | \n
Duration of stimulus | \n40 ms | \n
Presentation rate | \n10.9/s | \n
Window | \n80–100 ms | \n
Filter | \nLow pass of 100 Hz and high pass of 2000 Hz Low pass of 100 Hz and high pass of 3000 Hz | \n
Polarity | \nAlternating | \n
Intensity | \n80 dBnHL | \n
Number of stimuli | \n6000 | \n
Reproducibility | \n2 × 3000 stimuli | \n
Condition of evaluation | \nAwake and quiet | \n
Impedance | \n3k Ohms | \n
Artifact rejection | \nAcceptance if <10% | \n
Parameters of FFR in infants and young children.
ms, millisecond; s, second; Hz, hertz; dB, decibel; HL, hearing level.
The early identification of hearing disorders through FFR evaluation allows a speech-language pathologist to intervene, lessening the damage that this disorder can have on the development of speech skills in early childhood [2, 20, 22, 31]. This assertion can be understood by appreciating the relationship between language development and the presence of stimulating auditory experiences in the first few months of life.
\nFuture studies evaluating FFRs in infants will no doubt benefit from interdisciplinary collaboration which seeks to deepen understanding of the underlying mechanisms involved in the typical and atypical development of the auditory system during early childhood.
\nAuditory impairment is almost invariably associated with language and communication deficits. Learning a spoken language depends on assimilating the acoustic and phonetic elements of a language [32]. The development of the central auditory nervous system begins in intrauterine life and continues until adolescence, over which time hearing abilities become more complex and elaborate.
\nBecause of the close relationship between hearing, language, and learning, it is extremely important to monitor hearing over the course of life. Especially in children, be it pre-school or school age, the aim should be to monitor auditory function, either through behavioral or electrophysiological assessments. The ideal would be a combination of both behavioral and electrophysiological methods, so that with numerous evaluations there are crosschecks which allow a more accurate diagnosis to be made.
\nThe electrophysiological procedure traditionally used in clinical practice is the click ABR. However, in evaluating children with language deficits, this type of sound stimulus is not ideal for making diagnoses. Assessments using verbal sound stimuli, such as used in FFR, appear to be more effective and reliable in cases of learning problems or school difficulties [6]. Evaluation via an FFR allows a detailed analysis of how verbal stimuli are encoded in the central auditory nervous system to be done.
\nThe FFR allows fine-grained auditory processing deficits associated with real-world communication skills to be identified. As well as being used for the early identification of auditory processing, it can also be used to assess hearing across different clinical populations [33, 34]. This electrophysiological procedure can provide reliable and objective information about acoustic patterns such as timing, pitch, and timbre [35]. These three elements can be evaluated using different parts of the FFR, as follows:
timing—via analysis of the onset and offset portions;
pitch—by analysis of the fundamental frequency (F0);
timbre—from analysis of the harmonics of F0.
Simplistically, it can be said that the FFR helps in understanding which speech sounds were spoken (their timing and harmonic cues) and who said it (pitch cues) [36]. In addition, an FFR test can be performed under two conditions: (i) in silence (presentation of verbal stimuli only), and (ii) in noise (presentation of verbal stimuli plus background noise).
\nIn children and adolescents, studies have shown that FFRs change in latency as age increases. FFRs of children aged around 5 years appear to be very similar to the responses of children aged 8–12. However, the FFR pattern of children under 5 years has a somewhat different morphology and latency. According to Johnson et al. [33], the differences in children younger than 3 years are more evident in the initial portion of the responses (the onset), while in older children the change is more evident in the final portion (the offset) [3, 37].
\nInitial studies have focused on understanding the FFRs in children and adolescents under silent conditions and in subjects who have normal hearing and typical development. For the benefit of clinical audiologists, some of these studies are summarized below (Tables 4
Source | \nLatency (ms) | \nAmplitude (μV) | \nVA measures | \n|||
---|---|---|---|---|---|---|
\n | ∑ | \nSD | \n∑ | \nSD | \n∑ | \nSD | \n
V | \n6.61 | \n0.25 | \n0.31 | \n0.15 | \n\n | \n |
A | \n7.51 | \n0.34 | \n0.65 | \n0.19 | \n\n | \n |
C | \n17.69 | \n0.48 | \n0.36 | \n0.09 | \n\n | \n |
F | \n39.73 | \n0.61 | \n0.43 | \n0.19 | \n\n | \n |
Slope VA (μV/ms) | \n\n | \n | 0.13 | \n0.05 | \n||
Area VA (μV × ms) | \n\n | \n | 1.70 | \n1.23 | \n
FFR latency and amplitude values using the syllable/da/of 40-ms duration, performed in children with normal hearing on the right ear (silent conditions) [12].
∑: average, SD: standard deviation.
Sample: 36 and 38 children and adolescents (8–12 years old) with normal hearing.
Waves | \n|||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | \n | V | \nA | \nC | \nD | \nE | \nF | \nO | \n|||||||
\n | Sex | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \n
∑ | \nM | \n6.53 | \n0.10 | \n7.53 | \n0.19 | \n18.43 | \n0.08 | \n22.29 | \n0.17 | \n30.86 | \n0.21 | \n39.31 | \n0.17 | \n48.02 | \n0.13 | \n
F | \n6.49 | \n0.13 | \n7.43 | \n0.23 | \n18.33 | \n0.12 | \n22.28 | \n0.15 | \n30.81 | \n0.29 | \n39.27 | \n0.24 | \n47.95 | \n0.21 | \n|
Med | \nM | \n6.49 | \n0.10 | \n7.53 | \n0.18 | \n18.28 | \n0.07 | \n22.24 | \n0.09 | \n30.86 | \n0.21 | \n39.28 | \n0.7 | \n48.11 | \n0.13 | \n
F | \n6.49 | \n0.12 | \n7.37 | \n0.22 | \n18.37 | \n0.09 | \n22.11 | \n0.13 | \n30.78 | \n0.22 | \n39.11 | \n0.24 | \n47.86 | \n0.21 | \n|
SD | \nM | \n0.19 | \n0.05 | \n0.32 | \n0.04 | \n0.44 | \n0.05 | \n0.32 | \n0.07 | \n0.53 | \n0.07 | \n0.44 | \n0.08 | \n0.45 | \n0.07 | \n
F | \n0.22 | \n0.07 | \n0.35 | \n0.90 | \n0.44 | \n0.11 | \n0.67 | \n0.09 | \n0.58 | \n0.35 | \n0.56 | \n0.26 | \n0.75 | \n0.28 | \n
FFR latency and amplitude values for males and females using syllable /da/ of 40-ms duration performed in children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, M: male, F: female.
Sample: 40 children and adolescents (8–16 years old).
\n | \n | Complex VA | \n|
---|---|---|---|
\n | Sex | \nSlope VA (ms/μV) | \nArea VA (ms × μV) | \n
∑ | \nM | \n0.31 | \n0.29 | \n
\n | F | \n0.39 | \n0.34 | \n
Med | \nM | \n0.29 | \n0.31 | \n
\n | F | \n0.36 | \n0.31 | \n
SD | \nM | \n0.11 | \n0.09 | \n
\n | F | \n0.14 | \n0.14 | \n
Complex VA (slope and area) values for males and females using syllable/da/of 40-ms duration performed in children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, M: male, F: female.
Sample: 40 children and adolescents (8–16 years old).
Waves | \n|||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | \n | V | \nA | \nC | \nD | \nE | \nF | \nO | \n|||||||
\n | Ear | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \n
∑ | \nR | \n6.50 | \n0.12 | \n7.46 | \n0.22 | \n18.33 | \n0.10 | \n22.21 | \n0.14 | \n30.89 | \n0.30 | \n39.37 | \n0.24 | \n48.00 | \n0.21 | \n
L | \n6.51 | \n0.11 | \n7.48 | \n0.21 | \n18.41 | \n0.11 | \n22.36 | \n0.13 | \n30.78 | \n0.23 | \n39.20 | \n0.19 | \n47.95 | \n0.16 | \n|
Med | \nR | \n6.45 | \n0.12 | \n7.45 | \n0.21 | \n18.33 | \n0.08 | \n22.12 | \n0.14 | \n30.86 | \n0.23 | \n39.24 | \n0.19 | \n47.99 | \n0.15 | \n
L | \n6.53 | \n0.11 | \n7.41 | \n0.21 | \n18.33 | \n0.09 | \n22.28 | \n0.11 | \n30.78 | \n0.21 | \n39.07 | \n0.18 | \n48.03 | \n0.15 | \n|
SD | \nR | \n0.21 | \n0.06 | \n0.33 | \n0.09 | \n0.42 | \n0.08 | \n0.66 | \n0.09 | \n0.50 | \n0.39 | \n0.55 | \n0.29 | \n0.75 | \n0.30 | \n
L | \n0.21 | \n0.06 | \n0.36 | \n0.07 | \n0.46 | \n0.10 | \n0.44 | \n0.08 | \n0.61 | \n0.09 | \n0.47 | \n0.09 | \n0.54 | \n0.12 | \n
FFR latency and amplitude values for right and left ears using syllable/da/of 40-ms duration performed on children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, R: right, L: left.
Sample: 40 children and adolescents (8–16 years old).
Complex VA | \n|||
---|---|---|---|
\n | Ear | \nSlope VA (ms/μV) | \nArea VA (ms × μV) | \n
∑ | \nR | \n0.37 | \n0.33 | \n
\n | L | \n0.34 | \n0.31 | \n
Med | \nR | \n0.32 | \n0.31 | \n
\n | L | \n0.32 | \n0.31 | \n
SD | \nR | \n0.14 | \n0.13 | \n
\n | L | \n0.13 | \n0.13 | \n
Complex VA (slope and area) values for right and left ears using syllable/da/of 40 ms duration performed on children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, R: right, L: left.
Sample: 40 children and adolescents (8–16 years old).
Waves | \n|||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | \n | V | \nA | \nC | \nD | \nE | \nF | \nO | \n|||||||
\n | Age range | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \nLat | \nAmp | \n
∑ | \n8–11 | \n6.53 | \n0.12 | \n7.44 | \n0.22 | \n18.37 | \n0.11 | \n22.26 | \n0.15 | \n30.80 | \n0.25 | \n39.34 | \n0.21 | \n47.95 | \n0.17 | \n
12–16 | \n6.46 | \n0.11 | \n7.51 | \n0.21 | \n18.36 | \n0.10 | \n22.32 | \n0.10 | \n30.89 | \n0.28 | \n39.19 | \n0.21 | \n48.02 | \n0.21 | \n|
Med | \n8–11 | \n6.53 | \n0.11 | \n7.45 | \n0.21 | \n18.37 | \n0.09 | \n22.20 | \n0.14 | \n30.78 | \n0.23 | \n39.28 | \n0.20 | \n47.95 | \n0.15 | \n
12–16 | \n6.45 | \n0.12 | \n7.45 | \n0.17 | \n18.28 | \n0.08 | \n22.20 | \n0.09 | \n30.86 | \n0.20 | \n39.11 | \n0.15 | \n48.03 | \n0.13 | \n|
SD | \n8–11 | \n0.23 | \n0.06 | \n0.32 | \n0.10 | \n0.46 | \n0.09 | \n0.53 | \n0.08 | \n0.62 | \n0.19 | \n0.56 | \n0.11 | \n0.75 | \n0.14 | \n
12–16 | \n0.17 | \n0.06 | \n0.37 | \n0.07 | \n0.41 | \n0.08 | \n0.63 | \n0.45 | \n0.43 | \n0.22 | \n0.42 | \n0.32 | \n0.46 | \n0.33 | \n
FFR latency and amplitude values for various age ranges using syllable/da/of 40-ms duration performed on children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, R: right, L: left.
Sample: 40 children and adolescents (8–16 years old).
Table 10 shows the parameters used in children and adolescents at the Electrophysiology Department of the State University of Campinas using Biologic equipment and BioMARK software.
\nParameter | \nSettings | \n
---|---|
Equipment | \nBiologic Navigator Pro | \n
Software | \nBioMARK | \n
Electrode montage | \nCz, M1, and M2 | \n
Stimulated ear | \nRight ear | \n
Stimulus | \nSpeech | \n
Stimulus type | \nSyllable /da/ | \n
Stimulus duration | \n40 ms | \n
Stimulus polarity | \nAlternating | \n
Stimulus intensity | \n80 dB SPL | \n
Stimulus rate | \n10.9/s | \n
Number of sweeps | \n6000 | \n
Replicability | \nTwice for 3000 sweeps | \n
Transducer | \nInsert | \n
Assessment condition | \nWatching a movie | \n
Impedance | \n1k Ohms | \n
Window 85.33 ms | \n85.33 ms | \n
Filter | \n100–2000 Hz | \n
Artifact rejection | \n>10% | \n
Parameters of FFR in children and adolescents.
Cz: vertex, M1: left mastoid, M2: right mastoid, ms: millisecond, dB: decibel, SPL: sound pressure level, s: second, Hz: hertz.
Because FFR is a new procedure, unstudied pathologies are gradually being added and, little by little, we are gaining new information about what effects the pathologies have on the responses of affected children and adolescents.
\nThe FFRs of children diagnosed as poor readers frequently present as alterations in the timing and magnitude of timbre components [38]. The perception of the duration of a sound stimulus is essential for proficient reading, and the FFR can evaluate or monitor a decline in temporal and spectral precision. Children and adolescents with dyslexia commonly have difficulty perceiving speech sounds either in silence or in competing noise backgrounds. If a child has difficulty in perceiving speech sounds, their reading can be severely impaired [39]. Recently, Sanfins et al. [6] highlighted the importance of FFR as a biological marker in scholastic difficulties.
\nFFR evaluation in children who have suffered from secretory otitis media in the first 6 years of life, and who have undergone myringotomy for bilateral ventilation tube placement, exhibit changes in their FFR compared to normal children [5]. This study found that evaluating the FFR seems to be a promising method of identifying changes in the coding of speech stimuli in these children which might be undetected using traditional electrophysiological evaluation. The changes in their electrophysiological responses might serve as an alert to parents and educators, who can then adopt strategies to minimize the negative consequences on language development and academic achievement.
\nAnother possibility for using FFR assessment may be in monitoring an auditory training program or even tracking the effect of therapeutic interventions. Studies have shown that children with learning disabilities can benefit from an auditory remediation program, and it might therefore be usefully accompanied by FFR examinations (because FFRs have good repeatability in test and retest) [40, 41]. In addition, bilingual children can also be monitored through FFR assessment. Researchers have confirmed that neural perception of speech seems to be more consistent in bilinguals than in monolinguals [42, 43]. Bilingual experience during childhood may favor plasticity in the neuronal coding of sound and improve fundamental frequency perception (F0).
\nRecently, the neurophysiological aspects of speech perception have been investigated in cases of autism spectrum disorder (ASD). The results showed that children with ASD tend to have changes in the sensation of pitch (frequency), which might explain a withdrawal from speech reception. The fundamental frequency (F0) and its harmonics contain speech information which is essential in conveying affect [44], so changes in FFRs are consistent with a defect in perceiving prosody. The inference is that prosody deficits in some ASD patients may derive from an inability to encode and transmit auditory information in the brainstem [45].
\nTraditionally, FFR testing is done by presenting verbal stimuli through an insert earphone with a silent background. However, the perception of speech in a noisy background is a much discussed topic. In the presence of noise, normally hearing individuals need to make constant adjustments in their central auditory nervous system to satisfactorily understand and process speech information. Of course, there are others who, in the presence of competing noise, experience great difficulty in understanding speech [46].
\nThe evaluation of FFR in the presence of noise can be effectively used to diagnose children with learning disabilities [47]. Thus, identification of such children could lead to improvements in their reading and writing skills and in daily communication.
\nIn the adult and elderly population, the need for detailed audiological investigation increases when the patient complains of hearing difficulties, even if auditory thresholds appear normal.
\nThe evaluation of the FFR first involves time and prosody recordings, which provide important information about consonant and vowel discrimination and also aid in the perception of intonation [48]. For adults, but especially in the elderly, participation in these sorts of tests can assist in rehabilitation, either using a hearing aid or auditory training (or both).
\nThe clinical usefulness of the FFR in gauging how well auditory information is being processed is unquestionable. In adults and the elderly, many studies have already been done to identify how the FFR can help in diagnosing complaints related to central auditory processing, thereby allowing better rehabilitation.
\nThe latencies (mean and standard deviation) for adults and the elderly are presented in Table 11. The values come from Skoe et al. [19] who used Biologic and Navigator Pro equipment. In this study, subjects aged between 18 and 72 years and distributed in 6 age brackets were used. In the case of adults, the authors list values for subjects aged 21–30 years (
Complex VA | \n|||
---|---|---|---|
\n | Age range | \nSlope VA (ms/μV) | \nArea VA (ms × μV) | \n
∑ | \n8–11 | \n0.38 | \n0.31 | \n
\n | 12–16 | \n0.33 | \n0.34 | \n
Med | \n8–11 | \n0.37 | \n0.31 | \n
\n | 12–16 | \n0.28 | \n0.31 | \n
SD | \n8–11 | \n0.12 | \n0.11 | \n
\n | 12–16 | \n0.16 | \n0.16 | \n
Complex VA (slope and area) values for age range using syllable/da/of 40-ms duration performed in children with normal hearing (silent conditions) [30].
∑: average, Med: median, SD: standard deviation, R: right, L: left.
Sample: 40 children and adolescents (8–16 years old).
In Table 12 the maximum values of each wave are listed by adding two standard deviations to those in Table 13. Assuming the distribution is Gaussian means that this measure will cover 95% of the population.
\nAge (years) | \nNumber | \nLatencies (maximum in milliseconds + 2 SD) | \n|||||
---|---|---|---|---|---|---|---|
\n | \n | V | \nA | \nD | \nE | \nF | \nO | \n
17–21 | \n54 | \n7.04 | \n8.15 | \n23.21 | \n31.9 | \n39.50 | \n48.94 | \n
21–30 | \n143 | \n7.17 | \n8.28 | \n23.4 | \n32.54 | \n40.84 | \n49.79 | \n
30–40 | \n32 | \n7.27 | \n8.39 | \n23.64 | \n32.09 | \n40.38 | \n49.13 | \n
40–50 | \n11 | \n7.05 | \n8.22 | \n24.26 | \n31.86 | \n39.93 | \n49.6 | \n
50–60 | \n26 | \n7.5 | \n8.77 | \n24.5 | \n32.97 | \n41.46 | \n50.72 | \n
60–73 | \n24 | \n7.68 | \n8.81 | \n24.27 | \n32.47 | \n40.60 | \n50.02 | \n
Age | \nNumber | \nLatency ∑ (mean in milliseconds) | \nStandard deviation | \n||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
\n | \n | V | \nA | \nD | \nE | \nF | \nO | \nV (SD) | \n% | \nA (SD) | \n% | \nD (SD) | \n% | \nE (SD) | \n% | \nF (SD) | \n% | \nO (SD) | \n% | \n
117–21 | \n54 | \n6.58 | \n7.53 | \n22.41 | \n31.02 | \n39.50 | \n48.26 | \n0.23 | \n100 | \n0.31 | \n96.30 | \n0.40 | \n92.6 | \n0.44 | \n94.44 | \n0.46 | \n98.15 | \n0.34 | \n98.15 | \n
221–30 | \n143 | \n6.65 | \n7.60 | \n22.60 | \n31.12 | \n39.61 | \n48.33 | \n0.26 | \n100 | \n0.34 | \n100 | \n0.67 | \n95.8 | \n0.71 | \n100 | \n0.62 | \n99.30 | \n0.73 | \n97.90 | \n
330–40 | \n32 | \n6.61 | \n7.53 | \n22.52 | \n31.09 | \n39.54 | \n48.21 | \n0.33 | \n100 | \n0.43 | \n100 | \n0.56 | \n96.88 | \n0.50 | \n96.88 | \n0.42 | \n96.88 | \n0.46 | \n93.75 | \n
440–50 | \n11 | \n6.67 | \n7.64 | \n22.84 | \n31.26 | \n39.49 | \n48.30 | \n0.19 | \n100 | \n0.29 | \n100 | \n0.71 | \n90.90 | \n0.30 | \n100 | \n0.22 | \n100 | \n0.65 | \n90.90 | \n
550–60 | \n26 | \n6.86 | \n7.89 | \n23.08 | \n31.57 | \n39.92 | \n48.72 | \n0.32 | \n92.31 | \n0.44 | \n92.31 | \n0.71 | \n76.92 | \n0.70 | \n96.15 | \n0.77 | \n92.31 | \n1.00 | \n88.46 | \n
660–73 | \n24 | \n6.92 | \n7.89 | \n23.05 | \n31.37 | \n39.68 | \n48.84 | \n0.38 | \n91.67 | \n0.46 | \n91.67 | \n0.61 | \n83.33 | \n0.55 | \n83.33 | \n0.46 | \n83.33 | \n0.59 | \n100 | \n
FFR latency values for syllable /da/ of 40-ms duration, (silence) performed in adults and the elderly with normal hearing [19].
∑: Average (ms), SD: standard deviation, %: percent detectability for each peak.
Undoubtedly, the largest number of FFR studies have been performed using the Navigator Pro model from Biologic. Researchers tend to use this equipment together with the Intelligent Hearing Systems and SmartEP software [7, 49, 50].
\nOne study aimed to assess the processing of auditory information in those with hearing loss through an evaluation of eight individuals, aged 46–58 years, with hearing loss [7]. FFRs (collected by SmartEP) were correlated with results from two auditory processing behavioral tests—the masking level difference test and the random gap detection test. No correlation was found between FFR and these tests. The researchers found that the generation of this potential is extremely complex and could encompass several functions and does not depend on just temporal resolution or selective attention [7]. Also seeking to correlate FFRs with hearing loss, Peixe et al. [49] evaluated 11 individuals, aged 23–59 years, with moderately severe hearing loss. They concluded that hearing loss may cause an increase in the FFR wave latency, but the waves are still present so long as the stimulus intensity is adjusted. In other words, the presence of FFR waves is related to the audibility of the signal.
\nAnother interesting study was conducted with 30 young Indian adults aged 18–25 years [50]. The evaluation was carried out with the SmartEP equipment, and FFRs were present in all subjects evaluated. The latency and amplitude values of the analyzed elements were: wave V (lat = 6.81 ms and amp = 0.19 μV), wave C (lat = 16.82 ms and amp = 0.24 μV), wave D (lat = 24.75 ms and amp = 0.32 μV), wave E (lat = 31.36 ms and amp = 0.37 μV), and wave F (lat = 40.04 ms and amp = 0.29 μV).
\nWorldwide, there is a large increase in the number of elderly people. This entails providing better care for the elderly in all aspects of their health. With aging, there are structural changes in the peripheral and central auditory system which can lead to a decline in hearing. This, in turn, causes complaints of difficulty in understanding speech, especially in unfavorable environments [51, 52]. These impairments have a great impact on the life of the elderly, since in addition to causing social isolation, it can also lead to a depression and reduce cognitive function [53].
\nOnly a few studies have focused on FFR in the elderly, with the most reported population being young adults [54]. Some researchers have pointed to the clinical applicability of FFR in different populations and with different pathologies [7, 19, 37, 55].
\nThe effects of presbycusis on FFRs have been investigated in 18 individuals aged 61–78 years with hearing loss at frequencies of 2, 4, and 8 kHz (and compared with the responses of a control group of 19 young adults aged 20–26 years with normal hearing) [37]. The elderly group had lower amplitudes and increased latencies compared to the control group, demonstrating that the FFR can be affected by aging as well as hearing loss, but in different ways.
\nThe effects of hearing loss on FFRs were described in a sample of 30 elderly individuals aged 60–71 years who were divided into two groups matched by gender and intelligence quotient: (i) normal hearing, and (ii) mild to moderate hearing loss [35]. With ABR clicks, all subjects had normal responses. FFR testing indicated that individuals with hearing loss could be assessed with this procedure, but there were changes in the frequency responses. In the elderly with hearing loss, there was a breakdown in the perception of the speech signal, which resulted in differences in signal parameters compared to the group with normal thresholds. This breakdown in neural synchrony may explain the greater difficulty subjects with hearing loss have in speech perception.
\nThe evaluation of FFR in noisy environments is becoming more widespread, Thus, one study was carried out with 111 individuals between 45 and 78 years of age (mean 61.1 years) with normal to moderate hearing loss [56]. All subjects presented values within normal limits for the Montreal Cognitive Assessment (MoCA) and click ABR. In addition, they were tested on the SSQ (Speech, Spatial, and Qualities of Hearing Scale) which relates to auditory quality, as well as to the Quick Speech-in-Noise test (QuickSIN), in which phrases are presented binaurally with a verbal background babble. The FFR assessment demonstrated an increase in O-wave latency associated with speech comprehension difficulty in competing noise environments.
\nSupporting the observation that FFR traces are affected by increasing age, research on 34 individuals aged 22–77 years with normal hearing [57] found a decrease of the amplitude was associated with an increase in latency (Figures 1 and 2).
\nFFRs of an infant 13 days old. Authors’ data with FFR performed using SmartEP.
FFRs of two 9-year-old-children. The top trace represents a normal response and the second represents an abnormal response. Authors’ data using BioMARK software and Biologic equipment.
Figure 3 shows an FFR done on an adult aged 25 and on one aged 70. The shape of the FFR is similar in both, but there is an increase in latencies and some waves appear to be absent.
\nFFRs of an adult aged 25 years (top) and another aged 70 (bottom). Note the increase in latency of the waves. Authors’ data using SmartEP equipment.
In these FFR tracings, it can be seen that the elderly subject had an increase in latency of all waves compared to the younger adult. Aging causes a progressive loss of structure or functioning of neurons, which can be seen as decreased auditory evoked potentials. Through the FFR, it is seen that there is also a reduction in the speed of neural activation from brainstem to cortical structures.
\nOur FFR evaluation in adults and the elderly used IHS equipment and the parameters are shown in Table 14.
\nPresentation parameters | \nSetting | \n
---|---|
Equipment | \nSmartEP Intelligent Hearing Systems (IHS) | \n
Transducer | \nInsert phones | \n
Electrodes | \nFz, Fpz, M1, M2 or Cz, M1, M2 | \n
Stimulation | \nRight ear | \n
Stimulus | \nSyllable /da/ | \n
Stimulus duration | \n40 ms | \n
Presentation rate | \n10.9/s | \n
Window | \n80–100 ms | \n
Filter | \nLow pass of 100 Hz and high pass of 2000 Hz Low pass of 100 Hz and high pass of 3000 Hz | \n
Polarity | \nAlternating | \n
Intensity | \n80 dBnHL | \n
Number of stimuli | \n6000 | \n
Reproducibility | \n2 × 3000 stimuli | \n
Condition of evaluation | \nawake and quiet | \n
Impedance | \n3k Ohms | \n
Artifact rejection | \n>10% | \n
Parameters of FFR in adults and the elderly.
FFR evaluations can be included as an extra examination in diagnostic testing and have an important role in crosschecking the results. It can also greatly assist making differential diagnoses in different clinical populations. However, each age group has FFRs with specific characteristics, so it is important that the audiologist has access to good normative values for the different age groups (infants and toddlers, young children, children and adolescents, adults and the elderly).
\n\n a standard system for electrode location auditory brainstem response auditory evoked potential. Evoked potential when using an auditory stimulus Biological Marker of Auditory Processing is software that compares responses from a click to those from a synthetic syllable (usually /da/) central auditory nervous system central auditory processing central auditory processing disorder central nervous system a phoneme produced by a consonant and a vowel frequency following response the first part of an FFR that reflects the consonant Scale of Auditory Behavior, a questionnaire for monitoring auditory processing skills the second part of an FFR that reflects the vowel Synthesized speech Artificial human speech produced by a computer
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His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. 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He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. 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Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. 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He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals.",institutionString:null,institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"28",type:"subseries",title:"Animal Reproductive Biology and Technology",keywords:"Animal Reproduction, Artificial Insemination, Embryos, Cryopreservation, Conservation, Breeding, Epigenetics",scope:"The advances of knowledge on animal reproductive biology and technologies revolutionized livestock production. Artificial insemination, for example, was the first technology applied on a large scale, initially in dairy cattle and afterward applied to other species. Nowadays, embryo production and transfer are used commercially along with other technologies to modulate epigenetic regulation. Gene editing is also emerging as an innovative tool. This topic will discuss the potential use of these techniques, novel strategies, and lines of research in progress in the fields mentioned above.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/28.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11417,editor:{id:"177225",title:"Prof.",name:"Rosa Maria Lino Neto",middleName:null,surname:"Pereira",slug:"rosa-maria-lino-neto-pereira",fullName:"Rosa Maria Lino Neto Pereira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9wkQAC/Profile_Picture_1624519982291",biography:"Rosa Maria Lino Neto Pereira (DVM, MsC, PhD and) is currently a researcher at the Genetic Resources and Biotechnology Unit of the National Institute of Agrarian and Veterinarian Research (INIAV, Portugal). She is the head of the Reproduction and Embryology Laboratories and was lecturer of Reproduction and Reproductive Biotechnologies at Veterinary Medicine Faculty. She has over 25 years of experience working in reproductive biology and biotechnology areas with a special emphasis on embryo and gamete cryopreservation, for research and animal genetic resources conservation, leading research projects with several peer-reviewed papers. Rosa Pereira is member of the ERFP-FAO Ex situ Working Group and of the Management Commission of the Portuguese Animal Germplasm Bank.",institutionString:"The National Institute for Agricultural and Veterinary Research. Portugal",institution:null},editorTwo:null,editorThree:null,series:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517"},editorialBoard:[{id:"90066",title:"Dr.",name:"Alexandre",middleName:"Rodrigues",surname:"Silva",slug:"alexandre-silva",fullName:"Alexandre Silva",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRt8pQAC/Profile_Picture_1622531020756",institutionString:null,institution:{name:"Universidade Federal Rural do Semi-Árido",institutionURL:null,country:{name:"Brazil"}}},{id:"176987",title:"Ph.D.",name:"María-José",middleName:"Carrascosa",surname:"Argente",slug:"maria-jose-argente",fullName:"María-José Argente",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9vOQAS/Profile_Picture_1630330499537",institutionString:null,institution:{name:"Miguel Hernandez University",institutionURL:null,country:{name:"Spain"}}},{id:"321396",title:"Prof.",name:"Muhammad Subhan",middleName:null,surname:"Qureshi",slug:"muhammad-subhan-qureshi",fullName:"Muhammad Subhan Qureshi",profilePictureURL:"https://mts.intechopen.com/storage/users/321396/images/system/321396.jpg",institutionString:null,institution:{name:"University of Agriculture",institutionURL:null,country:{name:"Pakistan"}}},{id:"183723",title:"Dr.",name:"Xiaojun",middleName:null,surname:"Liu",slug:"xiaojun-liu",fullName:"Xiaojun Liu",profilePictureURL:"https://mts.intechopen.com/storage/users/183723/images/system/183723.jpg",institutionString:null,institution:null}]},onlineFirstChapters:{},publishedBooks:{paginationCount:3,paginationItems:[{type:"book",id:"8545",title:"Animal Reproduction in Veterinary Medicine",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/8545.jpg",slug:"animal-reproduction-in-veterinary-medicine",publishedDate:"January 20th 2021",editedByType:"Edited by",bookSignature:"Faruk Aral, Rita Payan-Carreira and Miguel 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Animals",editors:[{id:"251314",title:"Dr.",name:"Juan Carlos",middleName:null,surname:"Gardón",slug:"juan-carlos-gardon",fullName:"Juan Carlos Gardón",profilePictureURL:"https://mts.intechopen.com/storage/users/251314/images/system/251314.jpeg",institutionString:"Catholic University of Valencia San Vicente Mártir, Spain",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null},{type:"book",id:"7233",title:"New Insights into Theriogenology",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7233.jpg",slug:"new-insights-into-theriogenology",publishedDate:"December 5th 2018",editedByType:"Edited by",bookSignature:"Rita Payan-Carreira",hash:"74f4147e3fb214dd050e5edd3aaf53bc",volumeInSeries:1,fullTitle:"New Insights into Theriogenology",editors:[{id:"38652",title:"Prof.",name:"Rita",middleName:null,surname:"Payan-Carreira",slug:"rita-payan-carreira",fullName:"Rita 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