Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
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We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
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Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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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",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"6",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"981",title:"Molecular Biology",slug:"biomedicine-molecular-biology"}],chapters:[{id:"74620",title:"Molecular Mechanisms of Distinct Diseases",doi:"10.5772/intechopen.95114",slug:"molecular-mechanisms-of-distinct-diseases",totalDownloads:456,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Molecular medicine describes molecular structures and mechanisms and this chapter focuses on molecular and genetics errors of diseases. 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Drug discovery/invention can be achieved by collaborative efforts of biotechnologists and pharmacists for identifying potential candidates and successfully turn them into medicine for improving the healthcare system. Although molecular medicine for disease intervention is still in its infancy, however, significant research works and successful trials in short span of time have made it broadly accepted among the scientific community. This chapter identifies different molecular medicine approaches for dealing with parasites that have been coming up on the horizon with the new technological advances in bioinformatics and in the field of omics. With the better understanding of the genomics, molecular medicine field has not only raised hopes to deal with parasitic infections but also accelerated the development of personalized medicine. This will provide a targeted approach for identifying the druggable targets and their pathophysiological importance for disease intervention.",signatures:"Bhawana Singh",downloadPdfUrl:"/chapter/pdf-download/71751",previewPdfUrl:"/chapter/pdf-preview/71751",authors:[{id:"315192",title:"Dr.",name:"Bhawana",surname:"Singh",slug:"bhawana-singh",fullName:"Bhawana Singh"}],corrections:null},{id:"72009",title:"New Perspectives in Personalization of Therapy for Hematological Cancers",doi:"10.5772/intechopen.91957",slug:"new-perspectives-in-personalization-of-therapy-for-hematological-cancers",totalDownloads:504,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"A progress in treatment of hematological cancers was achieved. Unfortunately, some youngsters, because of rare genetic alterations that are not easy to detect, as well as heavily pretreated old patients, because of coexisting diseases that lead to changes in patient metabolism, do not respond to therapy. Moreover, sometimes familiar diversities and alterations on genetic or epigenetic level that could be transferred on diversities in metabolism or cell signaling might be a reason why patients do not respond to therapy. Interestingly, for older patients a resistance to therapy could also occur as a reason of drug cross-reactivity. For designing of effective anticancer therapy for patient with chronic lymphocytic leukemia before drug administration, patient’s leukemic cell response to anticancer drug(s) should be checked. Moreover, for patient response to treatment, also drugs prescribed previously by other medical doctors or even patients’ diet could be important for achieving therapeutic success of therapy. Therefore it is important to choose the effective drugs before their administration to patient that will improve treatment efficacy and exclude resistance to therapy. It must be stated that the special attention for personalized therapy tests should be focused on patients previously resistant to therapy, more sensitive to drugs or heavily pretreated.",signatures:"Małgorzata Rogalińska",downloadPdfUrl:"/chapter/pdf-download/72009",previewPdfUrl:"/chapter/pdf-preview/72009",authors:[{id:"314832",title:"Associate Prof.",name:"Malgorzata",surname:"Rogalinska",slug:"malgorzata-rogalinska",fullName:"Malgorzata Rogalinska"}],corrections:null},{id:"71908",title:"Genetic Risk Factors and Lysosomal Function in Parkinson Disease",doi:"10.5772/intechopen.91850",slug:"genetic-risk-factors-and-lysosomal-function-in-parkinson-disease",totalDownloads:360,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Parkinson disease is a complex disease that has multiple genetic and environmental factors. To achieve the early diagnosis and to be able to modify the disease progression, efforts are being made to identify individuals at risk. 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Since the contribution of LINE1 (L1) and human endogenous retrovirus (HERV) has been suspected to cause human cancers, their regulations and putative molecular functions have been investigated in diverse types of cancer. Their diagnostic, prognostic, and therapeutic potentials have been incessantly proposed using cancer associated or specific properties, such as hypomethylation, increased transcripts, and reverse transcriptase, as well as cancer-associated antigens. 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\r\n\tNext-generation textiles represent an exciting and interesting topic within the textiles sector. They are an intersection set between life science (for example medicine, microbiology, and comfort or strain) and technical applications (textile chemistry, engineering, and testing and certification). Developments in one of these areas affect the other one; for example, the invention of superabsorbent and gel-forming materials affected the production of a new type of baby diapers. Next-generation textiles can also be considered an important part of technical textiles, being used for different purposes such as chemical and biohazard protection. They present an important aspect from an economic point of view and the necessity for their production has been increasing; for example, a huge necessity for smart medical textiles comes from the increase of the elderly population in developed countries. In the last few decades, the rapid development of command cotton fabrics also occurred. This affects all textile sectors, for example, biodegradable fibers for implantations, three-dimension spacer fabrics, and reduction of bacterial growth by using silver ion-based textiles finishing. In this and other ways, the fields concerning the next-generation textiles have been growing rapidly and are becoming a more complex area to understand.
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He supervised 8 PhD and M.Sc. thesis, and participated in 14 national and international projects dealing with organic and environmental chemistry, hazardous wastes, medical textiles, nanotechnology, and electrospun nanofibers formation. He has expertise in applied chemistry and technology of organic chemistry, especially in carbohydrates, polymers, pollution prevention, preparation, and applications of nanoparticles (polymer chemistry, chemistry of chitosan, chitosan modification, nanoparticles preparation, and electrospinning technique). He built this model after years of research and teaching at university and research centers. He was the Egyptian National Representative of the Chemistry and Human Health Division Committee (VII) at the International Union of Pure and Applied Chemistry (IUPAC) in 2018-2019, and is currently a member of several national committees of pure and applied chemistry. 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\n
1. Introduction: cell membranes and lipid membranes
\n
Cell membranes are complex systems composed by lipids and proteins [1, 2]. They have structural and functional properties that are essential for life. The lipid bilayer is the backbone of cell membranes and is mostly composed by amphiphilic molecules such as phospholipids, cholesterol and glycolipids among others [3, 4, 5, 6, 7] (Figure 1).
\n
Figure 1.
(A) Electronic microscopic of cells; (B) cell membrane backbone is the lipid bilayer (a) which is formed by amphiphilic compounds such as lipids (single phospholipid) dispersed in water (b) facing the polar head group to water and segregating the acyl chains.
\n
A qualitative step in describing the membrane properties in terms of the lipid composition was the isolation and purification of lipids and its stabilization in water (Figure 1-Part B). After Bangham’s discovery in the 1960s [8, 9], lipids were found to form closed particles (liposomes) that are able to trap in controlled conditions such as ions, macromolecules and polar molecules of different nature in the inner aqueous space (Figure 2). With this information, it was thought reliable the possibility to modulate such trapping properties by changing membrane composition and to orient filled liposomes to specific organ targets. The changes were in the direction to modulate the surface properties, the excluded aqueous volume, the water permeability and the mechano-elastic properties of the particles.
\n
Figure 2.
Organized water around the acyl chains is displaced promoting aggregation by an increase in entropy of the system (upper part). Lipids self-aggregate in water due to the hydrophobic interaction of the nonpolar chains forming closed particles such as liposomes (lower part).
\n
In addition, different methodologies have been designed, afterwards, in order to obtain suspension of homogeneous size distribution of different magnitudes [10, 11, 12]. With this wide range of possibilities, it was immediate to infer that liposomes and its different versions of covered or uncovered unilamellar vesicles would be the ideal tools to trap, vehiculate specific compounds to drive them to specific targets and deliver drugs to organs and tissues, specifically for human beings pathologies (Figure 3).
\n
Figure 3.
Liposomes are one of the most attractive biomimetic systems because its preparation is done with lipids extracted from cells. In addition, other biomimetic nanoparticles can include lipids in its matrix.
\n
However, there are a number of difficulties for the direct use of these preparations that are mostly derived by limited knowledge of the physicochemical properties of the lipid bilayers. These include the presence of water as a major component in the membrane matrix; the thermodynamic properties derived from it in relation to the response from physicochemical stimuli and the interphase properties.
\n
The purpose of this chapter is to analyze these points in order to propose new strategies for designing biomimetic lipid particles more efficiently.
\n
\n
\n
2. Lipid hydration and bilayer stabilization
\n
When dry phosphatidylcholines (PCs) of chain length above 12 hydrocarbon atoms are dispersed in water above their transition temperature as described in Figure 2, they form lamellar onion-like structures in which bilayers are separated by aqueous spaces that are available to trap the compounds of interest to vehiculize and deliver (Figure 4).
\n
Figure 4.
(A) Electronic microscopic traditional image of multilamellar liposomes; (B) the diffraction pattern illustrates the separation between bilayers; (C) water solution trapped in between bilayers is schematically represented.
\n
After Bangham, Luzzati and others [13, 14, 15] determined the thickness of lipid bilayers by SAXS. Different thermal profiles were obtained according to the lipid features and head group structure was found [16, 17, 18]. Lipids stabilize differently according to its geometry. Phosphatidylcholines, that have similar areas in the head group region and the acyl chain, form bilayers by stacking molecules in cylindrical shape. In contrast, phosphatidylethanolamine (PE) forms hexagonal phases due to the conical shape of molecules [19, 20].
\n
The process of lipid hydration that derives the formation of liposomes consists of different stages as described in Figure 5.
\n
Figure 5.
Hydration of lipids and swelling of liposomes.
\n
The hydration step consists of the increase in area and decrease in thickness up to around 20% c.a. 22–24 water molecules per lipid. After this stage, area and thickness remain constant and the swelling of liposomes starts by the increase of water in the interlamellar space. This description of lipid swelling illustrates about several structural and physicochemical properties of the bilayers. The first observation is that there is a defined number of water molecules per lipid that determines the area per lipid and the bilayer thickness. This number is around 7–8 below the phase transition temperature and 22–24 above as derived by DSC [17, 18, 21, 22]. Thus, water is a component of the structure of the lipid bilayer, determining its thermodynamic stability.
\n
At least four features deserve discussion. At equilibrium in fully hydrated state, the membrane thickness is composed by the excluded volume of the lipid molecules and the excluded volume of the water organized by them (the hydration number denoted above). Thus, the barrier properties do not only merge with the head group and the acyl chain region per se but also of the packing and arrangement of water molecules in the hydration shell of the phospholipids. This means that for any solute, to overcome the bilayers, that is, releasing the trapped solute or incorporating some of them must permeate or alter the hydration shell. This can, in principle, be done by some of these mechanisms: insertion in the water network removing or replacing water molecules in the hydration shell or changing the area per lipid by expansion or compression.
\n
The second feature of lipid bilayers is derived from the first one. The interbilayer space consists of water not bound to the membrane, that is, it can be displaced by changing the osmotic gradient between the inner spaces and the outer media of the liposome. Water can permeate the lipid bilayer with certain facility depending on the phase state of the lipids, the presence of double bonds or ramifications in the acyl chains [23, 24]. In contrast, membrane is completely or partially impermeable to some solutes, such as sugars, ions, depending on its size and molecular structure. The differences in permeation rates between water and any of these solutes means that at least in the beginning of the process, a gradient of water chemical potential can be built with a difference in solute concentrations between the two sides of the bilayer. Let us consider the interbilayer space described in Figure 5. If solute is more concentrated between the bilayers, water will be driven to enter due to a difference in osmotic pressure and them the spacing (and hence the trapped volume) will be larger. An opposite effect can be caused, if the solute is concentrated in the outer media of the liposomes. In this case, liposomes shrink and the interbilayer space decreases.
\n
The third feature is represented by an area per lipid for a membrane thickness of 60 Å, when lipids hydrate with 22–24 water molecules per lipid. Thus, any change in the number of these water molecules will affect thickness and area with concomitant effect on permeability.
\n
Finally, the fourth feature is defined by the limit of the volume decrease. This is given by the steric repulsion of the groups in the surface of the bilayer, in which water plays a significant role. Water associated with the lipids is oriented at the bilayer surface constituting an electrical potential that hinder bilayers approach. This repulsive force is named as dipole potential or hydration forces [24, 25, 26, 27] (Figure 6).
\n
Figure 6.
(A) The limit of approach of lipid bilayers, (B) water organized at the interphase determining the repulsion forces, (C) dipole potential at the lipid interphase. This potential makes the bilayer interior positive and has important consequences in the binding and penetration of charged peptides and proteins.
\n
It is immediate to derive that the presence of these forces hinders the adhesion or fusion of membranes with different kinds of surfaces (inorganic and organic materials, other membranes, proteins, tissues, etc.). On the other way round, those processes will be feasible if water of hydration is totally or partially removed. This point is essential to understand the role of water in terms of membrane response to biologically relevant effectors.
\n
Entering details of the dynamic properties of membranes in relation to water, we may again inspect Figure 5. The equilibrium point corresponding to an area per molecule of 75 Å and 20 water molecules per lipid could be modified by the inclusion or exclusion of water molecules. So, the question is which perturbations can trigger changes in hydration that can be dominated in order to promote controlled changes in permeation. In this direction, let us focus on the mechanical and chemical forces at constant temperature. By mechanical forces, we refer to processes that led the membrane to expand or contract and by chemical forces, the competition with water by membrane sites of compounds may form hydrogen bonds. To analyze these points, previous considerations about water as a component of membranes must be done.
\n
\n
\n
3. The bilayer structure and the water ratio
\n
The understanding of the structural role of water in lipid membranes received considerable attention after Luzzatti et al. and efforts were addressed to give a defined location to water and to determine the appropriated values for area per lipid molecule [22, 27, 28]. Today, it is generally accepted that PCs admit up to a limit of around 22–24 water molecules per lipid above the phase transition temperature to stabilize in a bilayer with an area per lipid of 64 Å2 and a thickness of around 40 A [29, 30]. In the first stages of the hydration process, the water molecules interact with the phosphate group and, at a second step, with the carbonyl groups [31, 32, 33]. The formation of hydrogen bonds between these groups and water molecules can be monitored by observing the frequency shift of their stretching frequencies [34, 35]. It is expected that upon hydrogen-bonding, these frequencies decrease as a consequence of the elongation of the chemical bonds in the relative functional groups. Furthermore, the conformation of the acyl chains changes with the hydration [36].
\n
At least three regions of differential hydration can be identified according to the rate of exchange between membrane phase and the aqueous environment: the phosphate group, the carbonyl groups and the hydrocarbon chains. Each of them has different level of water organization in regard to coordination water by H bonding [30]. From them, CO and acyl chains seem to be important to evaluate the role of water in regulatory and functional response [37, 38].
\n
Figure 7 shows the lipid bilayer denoting the water region (upper part figure) and the profile of water distribution along the lipid bilayer (lower part).
\n
Figure 7.
The lipid bilayer considering the water interphases. In the lower diagram, it is observed that the water profile (blue line) penetrates up to the region of the carbonyl groups (red solid and dashed lines), being phosphates (orange line) and cholines (green line) groups completely covered by water.
\n
It is observed that water covers all the phosphate and choline regions and partially the carbonyl groups. Moreover, it is also observed that water may penetrate beyond the carbonyl region, that is, the first methylene groups of the hydrocarbon chains. This denotes that different arrangements of water can be found along the membrane thickness each of one with a different energetic profile, that is, the ability to react with polar or ionic solutes. This reactivity can be ascribed to the residual capacity the water molecules have to form H bonds depending on the surface groups with which its interacts.
\n
In Figure 8, water populations are visualized using infrared spectroscopy. Water bands at different frequencies denote the presence of non bonded to tetracoordinated waters [35, 39].
\n
Figure 8.
Water bands in the adjacencies of lipid membranes in the gel (red line) and in the liquid crystalline state (blue line). Dotted lines denote the populations of water with none, one, two, three and four H-bonds. Central band at approximately 3500 cm−1 (red solid line) corresponds to bulk water without lipids.
\n
A closer analysis by molecular simulation allows to explain that the broad bands can be ascribed to subpopulations of water molecule in four of the five groups described (Figure 9) [30].
\n
Figure 9.
Distributions of subpopulations of water forming none, one, two, three and four H bonds. Numbers correspond to water (w), carbonyl (C) and phosphate (P). Thus, 2 1 0 means two H-bonds with water, one with carbonyl, none with phosphates.
\n
Hence, in a population of molecules with three hydrogen bonds, the following combinations can be possible: www, ppp, ccc, wwp, wwc, wpp, wcc, wcp, ppw, ppc, etc. This means that the water distribution and the energy of the surface are extremely heterogeneous and hence a great versatility in reaction can be expected, even more if we consider that these combinations have a mean life time. Hence, the sites can be modified by fluctuations and these can in turn affect the presence of solute from the media and the lateral interaction at different lateral pressure of the bilayer. In this regard, the presence of proteins can alter this picture.
\n
For a better understanding of the influence of the lateral pressure on the membrane properties, we first deal with thermodynamic aspects of lipid monolayer. We will connect these properties with bilayer in the last part of the next section.
\n
\n
\n
4. Stability and membrane response: a dynamic picture
\n
The thermodynamic stabilization of the lipids in water to form bilayers as a consequence of the hydrophobic interaction between acyl chains has been discussed in several previous paper and will not be analyzed here [40, 41, 42].
\n
Instead, the thermodynamic aspects of the bilayer as a reactive surface considering its mechanical properties will specifically be discussed. This approach is based on the proposals presented earlier by Damoradan et al., Cevc, Disalvo et al. [37, 38, 43, 44, 45]. In terms of interfacial properties, it is important to consider lipid interphases results that may give complementary information to present a more rigorous picture in terms of thermodynamic response. This implies to focus on the interfacial properties of the lipid arrangements both in bilayers and monolayers in which water is a component of the structure. For this reason, some general properties of lipid monolayers will be discussed to relate them in response with lipid bilayers of liposomes and vesicles to have a general formalism that can explain the behavior of both systems.
\n
The main property inherent to membrane stabilization as a bilayer or as a monolayer is the surface tension of water. In the formation of bilayers, the surface tension between the acyl chain and water as described in Figure 2 is the main force driven the hydrophobic interaction. The increase in entropy is expressed by the decrease in the surface tension, that is, of the surface free energy. Hence the process is spontaneous.
\n
When lipids spread on the air-water surface (Figure 10), monolayers are formed spontaneously by the same reason: decrease of the surface tension with respect to that of pure water (γ0) [46]. This is generally expressed as thesurface pressure (Π) which is given by:
\n
Figure 10.
The addition of lipids to the air water surface in a Langmuir though at constant area increases the surface pressure (Π) by decreasing the water surface tension (γο) until a limit value is reached. From this point, the area per lipid molecule can be calculated.
\n
\n\nΠ\n\n=\n\n\nγ\n0\n\n−\nγ\n\nE1
\n
Once the monolayer is stabilized at different lateral pressures (i. e. different surface excess of lipids), the response to perturbations promoted by solutes in the aqueous subphase can be tested (Figure 11).
\n
Figure 11.
(A) Kinetic of surface pressure changes after the injection of the effector to the subphase. The extent of the change reflects the affinity of the effector by the monolayer, (B) surface pressure increase versus initial pressure plot used for determining the exclusion pressure of the lipid monolayer.
\n
As observed in Figure 12, the exclusion pressure or cut off, that is, the surface pressure at which no further effect on the monolayer is observed depends on the head group region for a given acyl chain length. DMPE (mean hydration ratio, 7 water molecules per lipid) shows a lower exclusion pressure (cut off), than DMPC (water ratio 22–24 water per lipid), although the slope of the curves remains constant. Thus, in the whole range of pressure, PE monolayers are less reactive than those of PC in the same conditions [47].
\n
Figure 12.
The effect of a soluble protease on the surface pressure of pure DMPC (black full triangles) and DMPE (red empty triangles).
\n
In addition, the magnitude of the surface pressure increase is also dependent on the hydrocarbon composition for similar head group regions. In Figure 13, it is observed that the response at a given pressure increases with the unsaturation or ramification of the acyl chains and decreases with the presence of cholesterol [47, 48].
\n
Figure 13.
Effect on the magnitude of the surface pressure response to a soluble protease of (A) unsaturation of the acyl chains in phosphatidylcholines, (B) inclusion of cholesterol in phosphatidylcholine monolayers.
\n
The surface pressures below the critical cut off (Πc) are those states of the membrane interphase with propensity to react when chased by an effector in the subphase. These states correspond to different water/lipid ratio and hence different surface tension of water in the lipid matrix. The decrease in surface pressure Πc − Π is related to the increase of water beyond the hydration water (confined water) which part of it is distributed along the hydrocarbon chains. This can be followed by frequency changes in the methylene region by FTIR spectroscopy (Figure 14) [49, 50].
\n
Figure 14.
Dehydration produces a decrease in confined water between acyl chains.
\n
\n
\n
5. Bilayer barrier properties: permeation and controlled release
\n
The studies in lipid monolayers allow to conclude that the response of the membrane to stimuli is due to the excess of surface tension due to the increase of water beyond the hydration shell, mostly in the acyl chain region. This excess is produced in monolayers by increasing the area per lipid, that is, reducing the surface pressure. In terms of bilayers, the expansion can be achieved by submitting liposomes to a hypotonic swelling. In this condition, membrane expands and liposomes become leaky of solute trapped in the liposome interior in isotonic conditions. Hence, the modulation of the mechanical properties of the bilayer by lipid composition, for instance, by including different cholesterol ratios, would allow to have a controlled release. The plots in Figure 13 help to understand this response. At a given surface pressure, the response decreases with the increase in cholesterol, which can be related to an increase in the membrane rigidity and lower water ratio [16, 51].
\n
Thus, permeability (i.e. the ratio between trapped and released solute) depends on the extent of water in the acyl region and in the second shell of phosphate groups. An important derivation of these results is that the properties of permeability can no longer be described by a model that assumes that the membrane is composed of three slabs: a low dielectric region (the hydrocarbon chains) and the two aqueous interphases, where the polar groups are located (Figure 7). This view predicts that solute permeating the membrane would be those that can partition in a non-polar media [52]. However, polar amino acids and hydrophilic compounds such as glycerol, erythritol and urea permeate easily the lipid bilayer. In addition, when swelling is taken place, ions and large molecules such as sucrose trapped in liposomes in isotonic conditions can permeate when they osmotically swell [53, 54].
\n
Therefore, solute permeation involved in the release of trapped solutes is a more complex phenomenon than a simple partition process. In terms of water participation at the membrane interphase and in the acyl chain region, the mechanism would involve water reorganization and hence structural changes. To put this complexity into relevance, the interaction of polyarginines (Arg 9) with bilayers of lipids differing in hydration such as phosphatidylcholines and phosphatidylethanolamines will be discussed. In Figure 15, the adsorption isotherm of Arg 9 on liposomes composed by PC and PE are shown. Both present typical curves of saturation, denoting a limited number of sites with the affinity to bind Arg 9 are present in each surface [55]. They can be described by Eq. (2):
\n
Figure 15.
Adsorption of Arg 9 on DMPC and DMPE liposomes (A) change in zeta potential (ζ) of DMPC \n\n\n and DMPE \n\n\n liposomes with addition of increasing concentrations of Arg 9. θ is calculated by ζ − ζ0/ζ∞ − ζ0, where ζ is the value at a given Arg 9 concentration, ζ0 corresponds to liposomes in the absence of Arg 9 and ζ∞ the value at saturation. (B) Degree of coverage as calculated from part A versus Arg 9 concentration.
\n
\n\n
\nE2
\n
where θ is the degree of coverage of the liposome by Arg 9, K the dissociation constant and n is a stoichiometric coefficient of the binding. In the present case, θ has been calculated by the change in the surface potential at each Arg 9 concentration measured by electrophoretic mobility from plots as shown in part A of Figure 15.
\n
The fitting of the curves of part B gives an affinity constant for DMPC at 18°C, K = 0.54 × 103 ± 44 M−1 and a value n = 1. For DMPE at 18°C, K = 2 × 103 ± 189 M−1 and n = 0.74 ± 0.06. According to these results, the affinity of Arg 9 is higher in DMPC than in DMPE. In addition, the interaction of Arg 9 with DMPC is well described by a Langmuir isotherm, since n = 1. In contrast, the value of n is different from 1 for Arg 9 in DMPE suggesting different mechanisms of interaction. The strong difference in affinity between PE and PC membrane can be explained recalling the monolayer results. The cut off described in Figure 12 is much lower in PE than in PC, that is, at pressure above 32 mN/m at which PE is not affected, PC monolayer is still reactive. This can be explained by the strong interaction between the polar head groups of the PE molecules that restrict the water excess and hence decreasing responsiveness.
\n
\n
\n
6. Topological effects of osmotic shrinkage. Defects in packing
\n
As described above, liposomes and vesicles, as well as cells, respond to osmometers [54]. That is, their volumes increase or decrease as a consequence of the entrance or exit of water driven by osmotic gradients. In the previous section, we show that in swelling conditions, bilayer expansion produces changes in its permeability, that is, osmosis does not only affect the liposome volume but also the membrane density. Now we will see that it also affects the surface properties.
\n
In hypertonic media, liposomes shrink, that is, they expulse the free water in the internal volume. However, the volume decrease has a limit due to the repulsive forces put in evidence at short distance as described in Figure 6. The overcoming of this repulsive barrier derives in adhesion or fusion of the surfaces and implies water elimination from the interphase. The compression process due to osmotic shrinkage in bilayers can be compared with the decrease in area in monolayers. In this system, at high pressures (i.e. low areas), monolayer collapses and lipids are lost. In bilayers, the compression has different consequences due to the impossibility to extrude lipids from the bilayer.
\n
Bilayers are soft and dynamic material [56, 57], and as a result, they can bend and deform in response to different stimuli such as dehydration and molecules that may compete with water. So, compression induced by osmotic shrinkage may result in topological changes giving place to regions (domains) of high curvature (invaginations or vesiculations) [58, 59, 60]. Thus, bilayer deformation can allow transient defects, when exposed to osmotic gradients (Figure 16). These curvature domains have important consequences in the interfacial behavior in the absorption or penetration of peptides composed by different types of amino acids. Many simulation studies showed that defect formation can determine the free energies of many membrane processes [61, 62].
\n
Figure 16.
Defects induced by osmotic shrinkage enhance Phe insertion into lipid bilayers.
\n
When DPPC LUVs were subjected to hypertonic stress, defects caused by dehydration have more affinity for lytic compounds and amino acids such as phenylalanine [63, 64, 65, 66]. The presence of defects in the membrane packing determines the binding and stabilization of peptides containing Arg and Phe motifs [67, 68, 69]
\n
The disruption of the water network around the phenyl group and the membrane defect has been invoked to explain the negative free energy of the formation a PC-Phe (phosphocholine-phenylalanine) complex in the presence of water. An important observation was that a dipole potential decrease was produced in this interaction which was explained by the orientation of the carboxylate opposing to the CO of the lipids [66, 70].
\n
As described in Figure 9, carbonyl groups are one of the hydration centers in which interfacial water is distributed. The formation of high curvature surfaces is related to changes in the CO arrangements [39] (Figure 17).
\n
Figure 17.
Orientation of CO groups at the bilayer interphase in relation to curvature.
\n
The curvature domains, in fact, increases the bilayer free energy surface by exposing hydrophobic region and carbonyl configuration as observed in part B of Figure 17. The stabilization of peptides or amino acid is the result of the decrease of free energy at expense of the bending modulus, that is, the energy cost of topological changes [67, 71, 72]. This last quantity is an important parameter that governs a membrane’s tendency for defect formation. Many kinds of defects may be formed, including vesicle budding and fusion, depending on the presence of non-bilayer lipid phases, cholesterol and interactions between lipid bilayers and other biomolecules [19, 73].
\n
\n
\n
7. Concluding remarks: design and modulation
\n
The lipid matrix in cell membranes presents a variety of lipids. As shown in Figure 18, all of them present a diacyl glycerol structure with acyl chains differing in saturation and length, a phosphate group in position 3 linked to a proton, choline, ethanolamine, glycerol, serine or inositol residues. It is difficult to accept that within the economicity principle of biology, this wide variation does not play a role in functional properties of the membrane.
\n
Figure 18.
Protrusion of the groups esterified to the phosphate in the surface of the membrane promotes different water organization.
\n
It must be noticed that all lipids may be aligned along a plane containing the glycerol backbone and the carbonyl groups. On one side of this plane, the hydrocarbon region can vary in terms of chain length, saturation and ramification. Each of these variations may give a complex matrix in which water cannot be excluded and constitute a media of a wide range of dielectric properties. On the other, polar groups protrude into the aqueous phase at different magnitudes. Importantly, also these groups are able in different extents to form hydrogen bonds between its lipid neighbors and with water. In conclusion, it is an oversimplification to reduce the bilayer structure in which lipids organize facing the polar groups to water and segregating the nonpolar chains.
\n
The lack of details in these regions in relation to their emergent properties is a major limitation in the design of biomimetic systems that, as liposomes and vesicles, may be used for biotechnological and medical purposes. As a consequence, literature is saturated with works in which only “try and error” strategies are employed.
\n
In this chapter, we have briefly discussed that:
the interface is a bidimensional solution of hydrated polar groups.
excess water beyond the hydration shell has solvent properties for additives in the bulk water phase and confers free energy that is excess for binding of amino acids and peptides.
Dissolution in the water membrane phase changes the water activity (aw) and affects the surface pressure.
\n
These studies indicate a deeper understanding of the role of lipid bilayers in cellular biology and support the development of future lipid-based biotechnology that should necessarily include the role of water as a membrane dynamic component.
\n
\n\n',keywords:"lipid bilayers, hydration, osmotic stress, responsive membranes, curvature, defects",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/66763.pdf",chapterXML:"https://mts.intechopen.com/source/xml/66763.xml",downloadPdfUrl:"/chapter/pdf-download/66763",previewPdfUrl:"/chapter/pdf-preview/66763",totalDownloads:1090,totalViews:0,totalCrossrefCites:1,totalDimensionsCites:4,totalAltmetricsMentions:0,impactScore:1,impactScorePercentile:57,impactScoreQuartile:3,hasAltmetrics:0,dateSubmitted:"November 15th 2018",dateReviewed:"March 13th 2019",datePrePublished:"June 18th 2019",datePublished:"September 4th 2019",dateFinished:"April 16th 2019",readingETA:"0",abstract:"The lack of details in the hydration properties of lipid bilayers hinders the design of biomimetic systems that, as liposomes and vesicles, may be used for biotechnological and medical purposes. In this chapter, studies indicate water as a membrane dynamic component determining the affinity and response of lipid membranes to amino acids, peptides and others stimuli. Based on thermodynamic analysis in lipid monolayers and its comparison with swelling shrinkage processes in liposomes and vesicles, it is concluded that: (1) the interphase of a lipid bilayer in a bidimensional solution of hydrated polar groups imbibed in labile water can be exchanged with the media by osmosis and or expansion-compression. (2) Excess water beyond the hydration shell (confined water) has solvent properties for additives in the bulk water phase and confers free energy that is in excess for binding of amino acids and peptides. (3) Dissolution in the water membrane phase changes the water activity (aw) and affects the surface pressure. (4) Defects may be formed by the compression of bilayers in which carbonyl groups organized water differently. These studies indicate that a deeper understanding of the role of lipid bilayers in cellular biology and support the development of future lipid-based biotechnology that should necessarily include the role of water as a membrane dynamic component.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/66763",risUrl:"/chapter/ris/66763",book:{id:"8095",slug:"liposomes-advances-and-perspectives"},signatures:"Anibal Disalvo and Maria de los Angeles Frias",authors:[{id:"285313",title:"Ph.D.",name:"Anibal",middleName:null,surname:"Disalvo",fullName:"Anibal Disalvo",slug:"anibal-disalvo",email:"disalvoanibal@yahoo.com.ar",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"298166",title:"Dr.",name:"Maria",middleName:null,surname:"Frias",fullName:"Maria Frias",slug:"maria-frias",email:"marafrias@hotmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction: cell membranes and lipid membranes",level:"1"},{id:"sec_2",title:"2. Lipid hydration and bilayer stabilization",level:"1"},{id:"sec_3",title:"3. The bilayer structure and the water ratio",level:"1"},{id:"sec_4",title:"4. Stability and membrane response: a dynamic picture",level:"1"},{id:"sec_5",title:"5. Bilayer barrier properties: permeation and controlled release",level:"1"},{id:"sec_6",title:"6. Topological effects of osmotic shrinkage. Defects in packing",level:"1"},{id:"sec_7",title:"7. Concluding remarks: design and modulation",level:"1"}],chapterReferences:[{id:"B1",body:'Robertson JD. Membrane structure. The Journal of Cell Biology. 1981;91:189\n'},{id:"B2",body:'Bernardino de la Serna J, Schütz GJ, Eggeling C, Cebecauer M. There is no simple model of the plasma membrane organization. Frontiers in Cell and Development Biology. 2016;4:106\n'},{id:"B3",body:'Benson A. On the orientation of lipids in chloroplast and cell membranes. 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Nature. 2005;438:590\n'},{id:"B61",body:'Baumgart T, Capraro BR, Zhu C, Das SL. Thermodynamics and mechanics of membrane curvature generation and sensing by proteins and lipids. Annual Review of Physical Chemistry. 2011;62:483-506\n'},{id:"B62",body:'MacCallum JL, Bennett WD, Tieleman DP. Distribution of amino acids in a lipid bilayer from computer simulations. Biophysical Journal. 2008;94:3393-3404\n'},{id:"B63",body:'Senisterra GA, Disalvo EA, Gagliardino JJ. Osmotic dependence of the lysophosphatidylcholine lytic action on liposomes in the gel state. Biochimica et Biophysica Acta. 1988;941:264-270\n'},{id:"B64",body:'Cutro A, Disalvo E. Phenylalanine blocks defects induced in gel lipid membranes by osmotic stress. The Journal of Physical Chemistry B. 2015;119:10060-10065\n'},{id:"B65",body:'Frias MA, Nicastro A, Casado NM, Gennaro AM, Diaz SB, Disalvo EA. Arbutin blocks defects in the ripple phase of DMPC bilayers by changing carbonyl organization. Chemistry and Physics of Lipids. 2007;147:22-29\n'},{id:"B66",body:'Rosa AS, Cutro AC, Frias MA, Disalvo EA. Interaction of phenylalanine with DPPC model membranes: More than a hydrophobic interaction. The Journal of Physical Chemistry. B. 2015;119:15844-15847\n'},{id:"B67",body:'Nuscher B, Kamp F, Mehnert T, Odoy S, Haass C, Kahle PJ, et al. α-Synuclein has a high affinity for packing defects in a bilayer membrane a thermodynamics study. Journal of Biological Chemistry. 2004;279:21966-21975\n'},{id:"B68",body:'Mitchell DJ, Steinman L, Kim D, Fathman C, Rothbard J. Polyarginine enters cells more efficiently than other polycationic homopolymers. The Journal of Peptide Research. 2000;56:318-325\n'},{id:"B69",body:'Griffith EC, Perkins RJ, Telesford D-M, Adams EM, Cwiklik L, Allen HC, et al. Interaction of L-phenylalanine with a phospholipid monolayer at the water-air interface. The Journal of Physical Chemistry B. 2014;119:9038-9048\n'},{id:"B70",body:'Cutro AC, Hollmann A, Cejas J, Maturana P, Disalvo EA, Frias MA. Phenylalanine interaction with lipid monolayers at different pHs. Colloids and Surfaces. B, Biointerfaces. 2015;135:504-509\n'},{id:"B71",body:'Ziegler A, Li Blatter X, Seelig A, Seelig J. Protein transduction domains of HIV-1 and SIV TAT interact with charged lipid vesicles. Binding mechanism and thermodynamic analysis. Biochemistry. 2003;42:9185-9194\n'},{id:"B72",body:'Gonçalves E, Kitas E, Seelig J. Binding of oligoarginine to membrane lipids and heparan sulfate: Structural and thermodynamic characterization of a cell-penetrating peptide. Biochemistry. 2005;44:2692-2702\n'},{id:"B73",body:'Marsh D. Intrinsic curvature in normal and inverted lipid structures and in membranes. Biophysical Journal. 1996;70:2248-2255\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Anibal Disalvo",address:"disalvoanibal@yahoo.com.ar",affiliation:'
Applied Biophysics and Food Research Center, Centro de Investigaciones en Biofísica Aplicada y Alimentos, CIBAAL, National University of Santiago del Estero and CONICET, Santiago del Estero, Argentina
'},{corresp:null,contributorFullName:"Maria de los Angeles Frias",address:null,affiliation:'
Applied Biophysics and Food Research Center, Centro de Investigaciones en Biofísica Aplicada y Alimentos, CIBAAL, National University of Santiago del Estero and CONICET, Santiago del Estero, Argentina
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1. Introduction
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Cervical degenerative disc disease is one of the most common diagnoses for patients suffering from neck and back pain. These symptoms may present with various conditions, such as radiculopathy or myelopathy, involving compression of the nerve root and spinal cord, respectively [1]. Patients may suffer from pain, lack of function, immobility and sensory loss. Initial treatments often include anti-inflammatory medicine, immobilization, and physical therapy [1]. However, when conservative treatment options fail, a surgical approach such as anterior cervical discectomy and fusion (ADCF) may be warranted. This anterior approach involves excising the affected disc(s), removing osteophytes, and decompressing the nerve root or spinal cord. Following disc removal, the residual vertebral space is typically implanted with a bone or synthetic graft, with or without the additional support of plates and screws. Robinson and Smith described this technique in 1955 [2]. Their approach involved implantation of a horseshoe-shaped bone graft harvested from iliac crest, followed by immobilization. Patients treated with this technique demonstrated promising clinical outcomes [2]. In 1958, Cloward described a similar technique, however, it included decompression of the neural structures and implantation of a bone dowel in the interbody space [3]. Regardless of the approach, a graft was used as a spacer to restore disc height, provide stability, and help promote bone fusion. Autograft, generally taken from the iliac crest, is often considered to be the gold standard for interbody fusion [4]. The use of autograft has led to high fusion rates and clinical success, although there are several disadvantages, such as extended operating time, donor site pain, limited supply, and variable quality depending upon the patient’s health [5, 6, 7, 8]. In an effort to avoid the complications seen with autografts, there has been a decades-old shift towards the use of alternative interbody spacers for treatment of degenerative disc disease [9, 10]. Two of the most common choices have been structural allograft bone or synthetic cages manufactured using polyetheretherketone (PEEK) [10]. Here, a comparison of the material properties and clinical performance of structural allografts and conventional PEEK cages is provided.
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2. Bone graft substitutes as intervertebral spacers in ACDF
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Structural bone allografts have been used successfully in a broad range of clinical applications including ACDF procedures [11, 12, 13]. Although lacking direct osteogenic potential, structural allografts have similar osteoconductive properties to autograft while avoiding complications such as donor site morbidity [14]. Furthermore, studies have shown similar clinical outcomes when comparing the use of allograft to autograft in ACDF procedures [15, 16]. Other commonly used implants include interbody cages made of various materials, including metals, ceramics, and polymers. Metal implants have been widely used as spinal cages for ACDF procedures. In particular, titanium implants offer mechanical strength, maintenance of vertebral disc height, and are available in various forms including mesh and box implants [4]. However, there are concerns regarding the use of titanium implants due to their mismatched mechanical properties compared to native bone. The difference in elastic modulus between bone and titanium can cause stress shielding, weakening the surrounding bone and increasing risk of peri-prosthetic fractures [17]. Bioactive ceramics serve as an attractive alternative due to their demonstrated biocompatibility, osteoconductive potential, and availability [9]. Despite these advantages, varying porosity of ceramics can lead to brittleness, thus making them less ideal implants for load-bearing applications [18]. Finally, various polymers are used in biomedical applications due to their biocompatibility, chemical and mechanical stability, and wide ranging compositions. However, some polymers are not ideal for orthopedic implants due to their malleable nature and weak mechanical properties [19]. One polymer with desirable mechanical properties is polyetheretherketone (PEEK). Compared to autograft, PEEK cages offer shorter operating time and reduced donor site morbidity [4]. This chapter will focus on the properties of structural allograft bone compared to conventional PEEK implants due to their similar mechanical properties and common use. Pre-clinical studies examining mechanical properties, osteoconduction and osseointegration, and clinical fusion rates in the cervical spine will be presented.
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2.1 Structural allograft
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Allograft bone, sourced from deceased human donors, is readily available and commonly used [20]. Allogenic bone grafts come in various forms, shapes, and sizes, based on clinical need, and can be either structural or non-structural. The bone is typically processed by physical and chemical means to ensure safety, biocompatibility and clinical suitability. Processing steps can include physical shaping and resizing of the graft for a specific clinical purpose (e.g., an intervertebral body spacer), disinfection and sterilization, and preservation to increase shelf life and simplify storage.
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Allograft use in bone grafting procedures dates back many decades, as evidenced by a nineteenth century publication from the Scottish surgeon William Macewen [21, 22]. He successfully reconstructed an infected humerus of a 4 year-old child using allograft tibial segments obtained while treating effects of rickets. Early in the twentieth century, Fred Albee published a book on bone graft applications, laying the foundation for a surge in bone transplantation procedures that is ongoing [23]. Allograft bone is now widely used for spinal, orthopedic, dental, and trauma applications. Notably, allograft usage in the treatment of degenerative cervical disc disease has increased from 14% in 1999 to 59% in 2008 [24]. Of particular interest here, the use of structural allografts in ACDF procedures dates back as early as 1958. Cloward described the use of frozen allograft bone in 46 patients undergoing ACDF [3]. A cylindrical iliac dowel, commonly known as the Cloward dowel, was implanted into the empty interbody space. Forty-four patients demonstrated complete interbody fusion at 3–4 months post-operative. Numerous studies have since been published discussing the use of various structural allografts in ACDF procedures [18]. Structural allografts continue to be used as interbody spacers due to their ability to support mechanical loads and resist failure. Such structural allografts are comprised of either cortical, cancellous or a combination of both cortical and cancellous bone. Cortical bone is more rigid and provides greater structural support, while cancellous bone confers less mechanical strength, but is more porous, providing an osteoconductive scaffold for neovascularization and osseointegration.
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Infection due to allograft transplantation remains a risk, albeit rare. A report released by the Centers for Disease Control and Prevention (CDC) in 2005 estimated an overall allograft-associated infection rate of 0.0004%, emphasizing the unlikely event of allograft-associated disease transmission [25]. This number was developed before additional advanced tissue processing methods, including terminal sterilization, were implemented by many tissue providers. Organizations, such as the American Association of Tissue Banks (AATB) and the Food and Drug Administration (FDA), maintain standards for tissue banking, including donor acceptance criteria, tissue procurement and processing methods, and allograft storage [26, 27]. Additionally, FDA published the Current Good Tissue Practice (CGTP) Final Rule, effective in 2005, setting requirements aimed at “preventing the introduction, transmission and spread of communicable diseases” [28]. AATB and FDA guidelines ensure that human allograft tissues are both clinically suitable and safe. Through the combination of rigorous donor screening and tissue processing, risk of disease transmission is virtually eliminated.
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2.2 Synthetics: polyetheretherketone (PEEK) cages
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Polyetheretherketone (PEEK) is a non-absorbable, semicrystalline polymer processed through a variety of techniques including extrusion, or injection and compression molding [29, 30]. Chemically, PEEK is made up of an aromatic backbone, interconnected by ketone and ether functional groups [30]. The chemical structure of PEEK gives it distinct qualities such as: stability at high temperatures, resistance to chemical and radiation damage, strength and stiffness. PEEK is available in several configurations including neat (unfilled) and carbon-reinforced PEEK (CRPEEK). The addition of composite fillers, such as carbon fiber, provides those forms of PEEK with increased mechanical strength [30].
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Developed in 1978, PEEK was initially commercialized for industrial applications such as aircraft and turbine blades due to its high chemical and mechanical resistance [29, 31]. However, in the late 1980s, it emerged as a potential biomaterial for surgical implantation and rapidly gained acceptance as a medical device. In the late 1990s, PEEK was introduced as a spinal cage implant and has also been used for other orthopedic and dental applications [19]. PEEK cages have become a popular choice due to inherent biocompatibility and favorable mechanical properties compared to traditional metal-based cages. PEEK has undergone numerous biocompatibility and cytotoxicity tests in accordance with both FDA and ISO 10993 standards. Morrison et al. evaluated the response from mouse fibroblasts and rat osteoblasts in vitro and found PEEK to display excellent biocompatibility [32]. Rivard et al. demonstrated that PEEK particles implanted in New Zealand white rabbits elicited no apparent necrosis or swelling, leading the authors to suggest that it is “harmless” to the spinal cord [33].
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Compared to other synthetic implants such as titanium cages, PEEK has an elastic modulus similar to that of native bone, thus reducing the potential impact of stress shielding on the bone healing process [19, 34]. Another advantage of PEEK is radiolucency which allows for radiographic assessment of fusion [35]. Furthermore, due to its ability to resist radiation damage, PEEK is able to be sterilized by electron beam or gamma irradiation. Despite noted advantages, several concerns have been raised due to how PEEK’s inert nature and low-surface energy might affect the body’s biological response. Adsorption of water at the implant surface plays an important role in protein-surface interactions, and thus cell-surface interactions, which can determine the success of an implant [36]. The hydrophobic nature of PEEK can potentially limit cellular adhesion. This undesirable property has been recently reported in studies finding that conventional smooth PEEK implants have limited osteoconductive properties and limited bone fixation at the implant interface [29, 37]. For example, Phan et al. described a case in which a patient underwent anterior lumbar interbody fusion (ALIF) with a PEEK implant [38]. The authors found evidence of poor integration between the implant and surrounding bone causing the “halo-effect” on CT scans.
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These issues have led to several modifications in an attempt to increase PEEK’s bioactivity, including surface coating with synthetic osteoconductive material such as titanium, increasing surface roughness and porosity through chemical modifications, and incorporating bioactive particles [34, 39]. Despite these promising modifications, conventional PEEK is still commonly used and is the focus in this chapter.
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3. Engineering studies of PEEK and allograft
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Interbody spacers require appropriate mechanical properties to be clinically effective. One important property is elastic modulus, the measure of resistance to deformation in response to applied stress. Mismatches in the elastic modulus between the surrounding vertebral bodies and an implant may lead to issues such as subsidence and stress shielding [40]. Clinically, these issues can cause complications such as pseudarthrosis and non-unions. Thus, it is ideal for an implant to have a similar elastic modulus as native bone. Heary et al. measured the elastic modulus and stiffness of various spinal interbody implants including neat and carbon-reinforced PEEK and cancellous and cortical bone [40]. The authors found that the elastic modulus of neat PEEK was similar to cancellous allograft bone, 3.84 and 3.78 GPa, respectively (Figure 1). Similarly, carbon-reinforced PEEK demonstrated a comparable elastic modulus to cortical allograft bone, 17.94 and 14.64 GPa, respectively. The study demonstrates the similar elastic modulus of allograft and PEEK implants and contrasts with the stiffer stainless steel, titanium, and cobalt-chrome materials.
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Figure 1.
Elastic modulus of all materials (*p < 0.05; **p < 0.01). Reprinted with permission from Heary et al. [40].
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The success of a spinal fusion procedure depends, in part, on the mechanical strength of the interbody spacer. Failure of the spacer can lead to graft subsidence and non-union. Native vertebral bodies have been reported to withstand average compressive strengths up 2400 N for cervical and 8600 N for lumbar joints [41, 42]. It is desirable for interbody spacers to withstand a compressive strength comparable to that of the relevant autologous bone in that surgical procedure (e.g., cervical vs. lumbar). Since structural allografts are typically processed to disinfect or sterilize, and to preserve for storage before use, these methods have the potential to alter clinically relevant properties. The biomechanical strength of several configurations of structural bone allografts was assessed following disinfection using one such method, the proprietary Allowash® process (United States Patents 5,556,379; 5,820,581; 5,977,034; 6,024,735). In addition, samples were tested with or without a sterilizing dose of gamma irradiation performed at ultra-low temperatures (Figure 2). The results indicate that bone grafts can be disinfected and retain a strength greater than that of pertinent vertebral bodies, but can also be sterilized under controlled conditions without negative impact on the clinically relevant characteristics of the bone. Additionally, it has been separately demonstrated that moderate doses of irradiation (up to 28.5 kGy) performed at ultra-low temperatures do not alter the compressive strength or elastic modulus of structural allografts compared to non-irradiated controls [43].
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Figure 2.
Compressive strength of disinfected and irradiated vs. disinfected only structural bone allografts used in spinal fusion procedures. Compressive strength was defined as the maximum load that the graft could withstand before graft failure. Disinfected structural allografts were divided into either non-irradiated or irradiated groups, with a targeted absorbed dose of 15 kGy. Irradiation did not significantly alter the compressive strength of any of the structural allografts.
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Likewise, storage conditions can potentially alter properties of structural bone allografts before use. Traditionally, bone grafts have been provided frozen, with storage at −20°C, or freeze-dried, which allows for storage at room temperature. Frozen grafts require special shipping and storage, and must be thawed prior to use. Freeze-dried allografts can be stored at room temperature, but require rehydration, which may not restore the native biomechanical properties of the graft. More recently, a glycerol-based preservation solution was developed to allow storage of grafts at room temperature [44]. The flexural strain (i.e., elasticity) and compressive strength of various structural bone allografts preserved by either freezing, freeze-drying, or glycerol-based preservation were evaluated. The results demonstrate that the frozen and glycerol-preserved groups were not significantly different, but did display significantly greater flexural strain compared to freeze-dried tissue, even after the freeze-dried bone was rehydrated up to 60 minutes (Figure 3A). The compressive strengths of different structural allografts that were either freeze-dried or glycerol-preserved (Figure 3B) were found to be unaltered by the preservation method for each type of graft. These results demonstrate that the processing of allograft bone, including disinfection, sterilization by irradiation and varying preservation methods, does not significantly impair clinically relevant characteristics, notwithstanding the increased brittle nature of freeze-dried bone.
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Figure 3.
Biomechanical properties of structural allografts preserved by different methods. Different types of disinfected structural bone allografts were preserved by either freezing, freeze-drying or glycerol preservation, followed by irradiation with a targeted absorbed dose of 15 kGy. Panel (A) shows the average flexural strain of cortical bone allografts preserved by the different approaches. The glycerol-preservation and frozen groups were not significantly different, but both demonstrated significantly greater average maximum flexural strain compared to the freeze-dried group. Modified and reprinted with permission from Samsell et al. [44] according to the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/legalcode). (B) Average compressive strength of structural allografts that were either freeze-dried or preserved using a glycerol-based solution. The compressive strength was not different between the freeze-dried and glycerol-preserved groups for all three graft types.
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4. Pre-clinical literature review: in vivo models
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In addition to testing mechanical properties, it is also important to evaluate the biocompatibility of bone graft substitutes. Animal models are a common and useful tool to evaluate the in vivo response to implantable materials prior to clinical application. Animal studies have demonstrated fibrous tissue growth and lack of osseointegration related to the use of PEEK implants.
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In a technical note, Phan et al. described PEEK’s poor integration with the surrounding bone, producing a “PEEK-Halo” effect [38]. This phenomenon is represented by a halo appearance between the implant and bone graft on a CT scan. The authors placed conventional PEEK (c-PEEK) and Ti-sprayed PEEK implants in cortical bone and cancellous bone of adult sheep tibia. Histological analysis of the c-PEEK implant showed a fibrous tissue layer and a gap on the PEEK-bone interface (Figure 4). The authors suggest this may be due to inflammatory factors and/or the interaction between PEEK and osteoblastic differentiation. In a cervical interbody fusion model in adult sheep, authors compared the bone-implant interface of conventional PEEK (c-PEEK) and Hydroxyapatite coated PEEK (HA-PEEK) [37]. Micro-CT analysis demonstrated less new bone formation in the c-PEEK group at 6 weeks post-implantation. Furthermore, histological analysis showed a fibrous tissue interface between bone and c-PEEK implants at 6 and 12 weeks post-implantation. Walsh et al. likewise compared the mechanical and histologic properties of conventional PEEK and Ti-PEEK at the bone-implant interface in a sheep model [45]. Sites implanted with c-PEEK appeared static with no bone response. While, encouragingly, Ti-PEEK exhibited in-growth of bone, that is not the focus of this chapter. PEEK-bone implant interface contained a fibrous tissue layer and a gap at 4 and 12 weeks. Direct bone contact for the c-PEEK implants in cancellous bone was minimal at 4 weeks (4.8%) and improved at 12 weeks, but only reached 11.5%. This in vivo study is yet another example of fibrous tissue seen at the PEEK interface.
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Figure 4.
Histology of PEEK/bone interface at 4 weeks post-implantation into a sheep tibia model. (A) Presence of fibrous tissue (white arrow) between the PEEK implant and adjacent bone—the rim of fibrous tissue results in the halo effect seen on CT imaging. (B) Titanium (Ti)-PEEK/bone interface demonstrating on-growth and ingrowth of bone at the Ti-PEEK/bone interface, with no radiolucent rim evident on CT imaging. Reprinted with permission from Phan et al. [38].
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The use of structural allografts in ACDF procedures is well documented, with reported fusion rates similar to that of autologous bone [15, 16]. In vivo osseointegration of bone was assessed using a calvarial defect model in athymic rats [44]. A portion of the rat’s skull was removed to create a critical size defect, which cannot close on its own. Following creation of the defect site, the investigators implanted human cortical and cancellous bone discs that were preserved by either freezing, freeze-drying, or glycerol-based preservation. At 1 week post-implantation, there was apparent soft tissue infiltration in all experimental groups, consistent with an early post-operative response. These findings support the biocompatibility of the bone grafts. Additionally, at 6 weeks post-implantation, the authors observed areas of osseointegration similar to autograft (Figure 5).
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Figure 5.
(a) Glycerol-preserved cancellous bone in a tight-fit rat calvarial defect. The scale is 500 μm. (b) Freeze-dried cortical bone in a tight-fit rat calvarial defect at 6 weeks. The scale is 500 μm. Black arrows mark complete bone bridge formation. Blue arrows indicate soft tissue infiltrate. Green arrows mark osseointegration. H, host bone; I, implant bone. Reprinted with permission from Samsell et al. [44] according to the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/legalcode).
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5. Clinical data: fusion, nonunion, and pseudarthrosis rates
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Both PEEK and allograft spinal implants have a long history of use in ACDF procedures. While mechanical and pre-clinical results can help predict clinical performance, this is ultimately determined through clinical outcomes. Many studies rely upon radiographic fusion to determine clinical success. According to Zdeblick and Phillips, “most published reports use the ‘fusion’ criteria required by the FDA, including motion of less than 5° on flexion-extension radiographs and an absence of lucencies around the cages or cage migration” [46]. Some studies also include pseudarthrosis rates. In the following section, we will compare clinical outcomes for allograft and PEEK implants.
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Historically, autograft has been considered the gold standard for spinal fusion procedures, and therefore, it is used as the control to which structural allografts or PEEK implants have been compared. In a retrospective review, investigators evaluated radiographic fusion in 66 patients who underwent one-level ACDF with autograft (n = 31) or frozen tricortical iliac crest allograft spacers (n = 35), both with anterior plate fixation [16]. Radiographic outcomes were assessed at an average of 12 months follow-up. One hundred percent of patients in the allograft group demonstrated fusion compared to the 90% of patients in the autograft group, although the difference was not statistically significant. Three patients in the autograft group showed evidence of non-union. The authors suggested that the use of allograft can achieve high fusion rates, while avoiding complications associated with autograft, such as donor site pain. In a similar study, radiographic fusion was assessed in 80 patients who underwent multi-level ACDF procedures using autologous (n = 45) or allogeneic (n = 35) tricortical iliac crest grafts [15]. Radiographic outcomes were assessed in all patients at an average follow-up of 16 months. Successful bone fusion occurred in 100 and 94% of patients in the autograft and allograft group, respectively. Pseudarthrosis occurred in two patients in the allograft group, but was not statistically significant. The authors concluded that allograft can produce solid bone fusion similar to autograft without the associated donor site pain. Finally, in a prospective study, Cho et al. compared the radiographic outcomes of PEEK cages filled with autologous iliac bone marrow vs. autologous iliac crest graft only in 80 patients who underwent ACDF, with the number of levels ranging from 1 to 3 [47]. The study revealed 93% fusion in the autograft only group and 100% fusion rate in autograft filled PEEK cage group at an average follow-up of 10 months. It should be noted that the high fusion rate demonstrated by the PEEK group could potentially be associated with inherent bone healing properties of autograft within the cage.
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Structural allografts have been used for decades to treat degenerative cervical disc disease. Numerous studies have evaluated radiographic fusion rates following use of structural bone allografts in ACDF procedures. Abla et al. prospectively evaluated 74 patients who were diagnosed with clinically significant cervical spinal stenosis or spondylosis and required ACDF surgery [48]. The investigators used a corticocancellous composite interbody spacer allograft (Figure 6) combined with cervical plate fixation. One-level fusion was performed in 34 patients, two levels in 23 patients, three levels in six patients, and four levels in one patient. Early fusion (at 1–3 months post-operative) was seen in 53% of the patients and by 12 months, 100% of the patients had fusion (Figure 6). The authors reported no graft failures, and an overall patient satisfaction of 90% at 12 months follow-up.\n
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Figure 6.
(A) Structural interbody spacer with cancellous bone sandwiched between two plates of cortical bone. (B) Lateral X-ray 6 months after ACDF was performed in a 47-year old woman from C4-C5 using the structural interbody spacer shown. Complete fusion and good alignment were achieved. Modified and reprinted with permission from Abla et al. [48].
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Another study, conducted by Graham et al. prospectively compared fusion rates using either freeze-dried or glycerol-preserved Cloward dowel allografts in ACDF procedures [49]. The study evaluated 86 patients with random assignment to either freeze-dried (n = 39) or glycerol-preserved (n = 47) groups (82 and 100 levels, respectively). Radiographic assessment at 6 months follow-up confirmed an overall fusion rate of >95% at all levels. Similarly, Rodway and Gander compared the use of glycerol-preserved vs. frozen interbody corticocancellous composite allografts in 67 patients undergoing ACDF procedures, with the number of levels ranging from 1 to 4 and a 1-year minimum follow-up [50]. Radiographic results demonstrated fusion in 38% of glycerol-preserved and 42% of frozen allografts at 3 months follow-up, and 100% fusion in both groups at 12 months (Table 1). Of note, the structural allografts used in each of these studies were sterilized by a low dose of gamma irradiation at ultra-low temperatures. Therefore, the combined results demonstrate the clinical effectiveness of structural allografts in ACDF surgery, regardless of method of preservation or treatment with a sterilizing dose of irradiation.
\n
Table 1.
Fusion rates by number of patients*. Source: “Reprinted with permission from Rodway and Gander [50], according to the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/legalcode)”.
\n
In a separate retrospective study, Muzevic et al. evaluated 154 patients who underwent a first-time ACDF surgery for treatment of cervical degenerative disc disease over a 3-year period [51]. One-level fusion was performed in 48 patients, two-level in 56 patients, three-level in 47 patients, and four-level in three patients using either cortical or corticocancellous structural allografts, along with demineralized bone matrix and cervical plating. Solid fusion was achieved in 98% of patients at a mean follow-up of 6 months, with improved overall treatment outcomes in 82% of patients. Finally, Yue et al. reviewed clinical and radiological outcomes in 71 patients who had ACDF surgery performed using structural freeze-dried fibular allografts an average of 7.2 years prior to the review [52]. The authors found that symptoms remained resolved in more than 82% of patients. They observed fusion in 93% of disc spaces, which was comparable to reported fusion rates for autograft [15, 16, 47, 53, 54]. While approximately 17% of the patients required revision surgery, the authors state that this rate is comparable to that following ACDF performed with autograft. Therefore, they attribute this revision rate to be a reflection of “normal” degeneration with age and not to use of allograft.
\n
Several studies have assessed the clinical outcomes of ACDF procedures with the use of PEEK cages. In a prospective study, investigators assessed bone fusion in 52 patients who underwent anterior cervical discectomy with empty PEEK cages. One-level surgery was performed in 44 patients and 2-level surgery in eight patients [55]. Based on radiographic analyses, the authors confirmed bone fusion at 43 treated levels (72%) at an average of 16 months. The authors note the low fusion rates of empty PEEK cages, but stated that the lack of fusion did not affect clinical outcomes. Similarly, Suess et al. evaluated the clinical and radiographic outcomes of 292 patients who received empty PEEK cages for single-level ACDF procedures [56]. PEEK demonstrated radiographic fusion in 126 patients (43%) at 6 months, 214 patients (73%) at 12 months, and 241 patients (83%) at 18 months. The authors noted that slow and incomplete radiographic fusion could be attributed to the use of empty PEEK cages, and therefore did not recommend their use. Furthermore, they suggest this incomplete fusion may lead to reduced improvement in pain and possible disability. Finally, Kim et al. retrospectively evaluated 68 patients who underwent two and three-level ACDF with PEEK packed with demineralized bone matrix [57]. At an average follow-up of 28 months, PEEK demonstrated 81% overall fusion rate, which is less than reported levels for both autograft and structural allograft.
\n
In a retrospective review, Krause et al. looked at 127 patients who underwent one-level ACDF with structural allograft (composite (61/71), cortical (8/71), or cancellous (2/71)) or PEEK cages to examine the incidence of pseudarthrosis as determined by radiography [58]. Fifty six patients (44%) received PEEK implants while 71 (56%) received structural allografts. All PEEK cages were filled with allogeneic demineralized bone matrix (DBM) or local autograft. The PEEK cohort demonstrated a higher rate of radiographic pseudarthrosis at one or more years after follow-up compared to the allograft cohort, 52 vs. 10% (p < 0.001), respectively (Figure 7). The investigators concluded that there was a five-fold higher incidence of pseudarthrosis in patients with PEEK cages, and almost double the rate of subsequent revision. Furthermore, the investigators suggested PEEK’s inability to integrate with organic bone is due to its bio-inertness.
\n
Figure 7.
Sagittal X-ray films obtained in a patient with a PEEK interbody graft and pseudarthrosis (left) and a patient with a structural allograft implant (right) healed 1 year after surgery. Reprinted with permission from Krause et al. [58].
\n
In a similar study, Teton et al. compared pseudarthrosis rates of 62 consecutive patients who underwent multi-level ACDF with structural allograft or PEEK cages, with at least 1 year follow-up [59]. Of 62 patients, 31 received PEEK implants, and 31 received structural allograft. Within the PEEK group, 20 (65%) patients demonstrated radiographic evidence of pseudarthrosis, compared to six (19%) patients implanted with structural allograft (p < 0.001), demonstrating over three-fold higher incidence of pseudarthrosis rates with PEEK. Furthermore, four patients implanted with PEEK required re-operation due to pseudarthrosis (13%), compared to zero patients with allograft (p = 0.014). Additionally, in a retrospective database review, authors analyzed 6130 patients who underwent ACDF with allograft (4063 patients) or intervertebral cages (2067 patients) to compare nonunion rates after 1 year post-operative [60]. Cages were unable to be stratified by type and may have been “PEEK, titanium, mesh, or porous.” Patients were stratified by the number of levels treated, tobacco use, and diabetic conditions. Overall nonunion rates were significantly higher in the cage group (5.32%) than in allograft group (1.97%) (p < 0.0001). Notably, patients receiving intervertebral cages showed higher rates of nonunion regardless of other factors such as, levels treated, tobacco use, and diabetes (Table 2).
\n
Table 2.
Nonunion Rates Between Structural Allograft and Cages*. Source: Reprinted with permission from Pirkle et al. [60].
*PEEK, titanium, mesh, or porous (unstratified due to nature of data base).
\n
\n
\n
6. Summary
\n
While autograft use is common for bone grafting procedures, it is associated with limitations, including donor site morbidity, limited quantities, and unsatisfactory biological activity. For ACDF, autograft use has steadily declined in favor of alternatives, primarily structural bone allografts and PEEK cages [18, 30]. Favorably, each has mechanical properties similar to autograft, with comparable elastic modulus and sufficient strength for intended applications. However, in vivo models demonstrate lack of osseointegration for PEEK, as well as fibrous tissue growth. Poor integration can lead to graft subsidence and pseudarthrosis, and ultimately pain, immobility and sensory loss. In contrast, structural allografts act as an osteoconductive scaffold demonstrating osseointegration in a rat model and have a long history of successful clinical use. These differences are reflected in clinical outcomes, as detailed in this chapter and summarized in Table 3. As shown, fusion rates when using PEEK cages were generally lower than when structural allografts were used. Moreover, the use of PEEK cages, and cages in general, in ACDF surgery presented a significantly higher rate of pseudarthrosis vs. structural allografts, leading to a greater rate for the need for subsequent revision surgery.
Clinical fusion and pseudarthrosis rates following ACFD using autograft, structural allograft, or PEEK cages.
\n
Due to lack of osseointegration of PEEK reported both pre-clinically and clinically, researchers have modified its surface or sought other materials in attempt to improve clinical outcomes. There are promising advances in porous and titanium coatings and clinical efficacy is being assessed.
\n
In conclusion, although conventional PEEK cages have similar elastic modulus as structural allografts and autografts, they display poorer osseointegration characteristics compared to human bone implants. Comparative clinical analyses indicate that structural allografts yield higher fusion rates and lower incidence of pseudarthrosis than conventional PEEK cages in ACDF procedures.
\n
\n
Acknowledgments
\n
We would like to thank Julie B. McLean, PhD, for editorial assistance.
\n
\n
Conflicts of interest
\n
NC, ECG, and MAM are employees of LifeNet Health, a nonprofit organization.
\n
\n',keywords:"polyetheretherketone (PEEK), structural bone allograft, anterior cervical discectomy and fusion (ACDF), cervical degenerative disc disease, synthetic cage, allograft, irradiation",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/68131.pdf",chapterXML:"https://mts.intechopen.com/source/xml/68131.xml",downloadPdfUrl:"/chapter/pdf-download/68131",previewPdfUrl:"/chapter/pdf-preview/68131",totalDownloads:866,totalViews:0,totalCrossrefCites:0,dateSubmitted:"April 1st 2019",dateReviewed:"June 17th 2019",datePrePublished:"July 16th 2019",datePublished:"February 10th 2021",dateFinished:"July 16th 2019",readingETA:"0",abstract:"Cervical degenerative disc disease (CDDD) can lead to radiculopathy and myelopathy, resulting in pain, lack of function, and immobility. Anterior cervical discectomy and fusion (ACDF) is a common surgical treatment modality for advanced CDDD. ACDF involves removal of the affected disc(s) followed by replacement with a bone or synthetic graft. Historically, autograft has been considered the gold standard for interbody fusion. However, it is often associated with limitations, including donor site morbidity and limited quality and supply, prompting surgeons to seek alternatives. Two of the most common alternatives are structural bone allografts and polyetheretherketone (PEEK) synthetic cages. Both, advantageously, have similar mechanical properties to autologous bone, with comparable elastic modulus values. However, a lack of osseointegration of PEEK cages has been reported both pre-clinically and clinically. Reported fusion rates assessed radiographically are higher with the use of structural bone allografts compared to PEEK cages, while having a lower incidence of pseudarthrosis. This book chapter will discuss in detail the pre-clinical and clinical performance of structural allografts in comparison to conventional PEEK cages.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/68131",risUrl:"/chapter/ris/68131",signatures:"Nigeste Carter, Elena C. Gianulis and Mark A. Moore",book:{id:"9406",type:"book",title:"Clinical Implementation of Bone Regeneration and Maintenance",subtitle:null,fullTitle:"Clinical Implementation of Bone Regeneration and Maintenance",slug:"clinical-implementation-of-bone-regeneration-and-maintenance",publishedDate:"February 10th 2021",bookSignature:"Mike Barbeck, Nahum Rosenberg, Patrick Rider, Željka Perić Kačarević and Ole Jung",coverURL:"https://cdn.intechopen.com/books/images_new/9406.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78985-832-7",printIsbn:"978-1-78985-831-0",pdfIsbn:"978-1-78984-398-9",isAvailableForWebshopOrdering:!0,editors:[{id:"204918",title:"Dr.",name:"Mike",middleName:null,surname:"Barbeck",slug:"mike-barbeck",fullName:"Mike Barbeck"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"300414",title:"Dr.",name:"Mark A.",middleName:null,surname:"Moore",fullName:"Mark A. Moore",slug:"mark-a.-moore",email:"mark_moore@lifenethealth.org",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"307867",title:"Ms.",name:"Nigeste",middleName:null,surname:"Carter",fullName:"Nigeste Carter",slug:"nigeste-carter",email:"nigeste_carter@lifenethealth.org",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"307870",title:"Dr.",name:"Elena C.",middleName:null,surname:"Gianulis",fullName:"Elena C. Gianulis",slug:"elena-c.-gianulis",email:"elena_gianulis@lifenethealth.org",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Bone graft substitutes as intervertebral spacers in ACDF",level:"1"},{id:"sec_2_2",title:"2.1 Structural allograft",level:"2"},{id:"sec_3_2",title:"2.2 Synthetics: polyetheretherketone (PEEK) cages",level:"2"},{id:"sec_5",title:"3. Engineering studies of PEEK and allograft",level:"1"},{id:"sec_6",title:"4. Pre-clinical literature review: in vivo models",level:"1"},{id:"sec_7",title:"5. Clinical data: fusion, nonunion, and pseudarthrosis rates",level:"1"},{id:"sec_8",title:"6. Summary",level:"1"},{id:"sec_9",title:"Acknowledgments",level:"1"},{id:"sec_9",title:"Conflicts of interest",level:"1"}],chapterReferences:[{id:"B1",body:'\nWhitecloud TS 3rd. Modern alternatives and techniques for one-level discectomy and fusion. Clinical Orthopaedics and Related Research. 1999;359:67-76\n'},{id:"B2",body:'\nRiley LH Jr, Robinson RA, Johnson KA, Walker AE. The results of anterior interbody fusion of the cervical spine. Review of ninety-three consecutive cases. Journal of Neurosurgery. 1969;30(2):127-133\n'},{id:"B3",body:'\nCloward RB. The anterior approach for removal of ruptured cervical disks. Journal of Neurosurgery. 1958;15(6):602-617\n'},{id:"B4",body:'\nSong KJ, Choi BY. Current concepts of anterior cervical discectomy and fusion: A review of literature. Asian Spine Journal. 2014;8(4):531-539\n'},{id:"B5",body:'\nBhadra AK, Raman AS, Casey AT, Crawford RJ. Single-level cervical radiculopathy: Clinical outcome and cost-effectiveness of four techniques of anterior cervical discectomy and fusion and disc arthroplasty. European Spine Journal. 2009;18(2):232-237\n'},{id:"B6",body:'\nShen FH, Samartzis D, Khanna N, Goldberg EJ, An HS. Comparison of clinical and radiographic outcome in instrumented anterior cervical discectomy and fusion with or without direct uncovertebral joint decompression. The Spine Journal. 2004;4(6):629-635\n'},{id:"B7",body:'\nSuchomel P, Barsa P, Buchvald P, Svobodnik A, Vanickova E. Autologous versus allogenic bone grafts in instrumented anterior cervical discectomy and fusion: A prospective study with respect to bone union pattern. European Spine Journal: Official Publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society. 2004;13(6):510-515\n'},{id:"B8",body:'\nRussell JL, Block JE. Surgical harvesting of bone graft from the ilium: Point of view. Medical Hypotheses. 2000;55(6):474-479\n'},{id:"B9",body:'\nChau AM, Mobbs RJ. Bone graft substitutes in anterior cervical discectomy and fusion. European Spine Journal. 2009;18(4):449-464\n'},{id:"B10",body:'\nChen F, He W, Mahaney K, Noeller J, Mhanna N, Viljoen S, et al. Alternative grafts in anterior cervical fusion. Clinical Neurology and Neurosurgery. 2013;115(10):2049-2055\n'},{id:"B11",body:'\nMcKoy BE, Wingate JK, Poletti SC, Johnson DR 2nd, Stanley MD, Glaser JA. Fibular allograft after anterior cervical corpectomy: Long term follow-up. The Iowa Orthopaedic Journal. 2002;22:42-46\n'},{id:"B12",body:'\nNovell J, Novell-Costa F, Ivorra C, Farinas O, Munilla A, Martinez C. Five-year results of implants inserted into freeze-dried block allografts. Implant Dentistry. 2012;21(2):129-135\n'},{id:"B13",body:'\nRichards CJ, Garbuz DS, Pugh L, Masri BA. Revision total knee arthroplasty: Clinical outcome comparison with and without the use of femoral head structural allograft. The Journal of Arthroplasty. 2011;26(8):1299-1304\n'},{id:"B14",body:'\nMiller LE, Block JE. Safety and effectiveness of bone allografts in anterior cervical discectomy and fusion surgery. Spine. 2011;36(24):2045-2050\n'},{id:"B15",body:'\nSamartzis D, Shen FH, Goldberg EJ, An HS. Is autograft the gold standard in achieving radiographic fusion in one-level anterior cervical discectomy and fusion with rigid anterior plate fixation? 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American Association of Tissue Banks; 2016\n'},{id:"B27",body:'\nRegulatory Considerations for Human Cells, Tissues, and Cellular and Tissue-Based Products: Minimal Manipulation and Homologous Use. 2017\n'},{id:"B28",body:'\nUS Food and Drug Administration (FDA). Guidance for Industry Current Good Tissue Practice (CGTP) and Additional Requirements for Manufacturers of Human Cells, Tissues, and Cellular and Tissue-Based Products (HCT/Ps); 2011\n'},{id:"B29",body:'\nToth JM, Wang M, Estes BT, Scifert JL, Seim HB 3rd, Turner AS. Polyetheretherketone as a biomaterial for spinal applications. Biomaterials. 2006;27(3):324-334\n'},{id:"B30",body:'\nKurtz SM, Devine JN. PEEK biomaterials in trauma, orthopedic, and spinal implants. Biomaterials. 2007;28(32):4845-4869\n'},{id:"B31",body:'\nEschbach L. Nonresorbable polymers in bone surgery. Injury. 2000;31(Suppl 4):22-27\n'},{id:"B32",body:'\nMorrison C, Macnair R, MacDonald C, Wykman A, Goldie I, Grant MH. In vitro biocompatibility testing of polymers for orthopaedic implants using cultured fibroblasts and osteoblasts. Biomaterials. 1995;16(13):987-992\n'},{id:"B33",body:'\nRivard CH, Rhalmi S, Coillard C. In vivo biocompatibility testing of peek polymer for a spinal implant system: A study in rabbits. Journal of Biomedical Materials Research. 2002;62(4):488-498\n'},{id:"B34",body:'\nMa R, Tang T. Current strategies to improve the bioactivity of PEEK. International Journal of Molecular Sciences. 2014;15(4):5426-5445\n'},{id:"B35",body:'\nRao PJ, Pelletier MH, Walsh WR, Mobbs RJ. Spine interbody implants: Material selection and modification, functionalization and bioactivation of surfaces to improve osseointegration. Orthopaedic Surgery. 2014;6(2):81-89\n'},{id:"B36",body:'\nKasemo B, Lausmaa J. Material-tissue interfaces: The role of surface properties and processes. Environmental Health Perspectives. 1994;102(Suppl 5):41-45\n'},{id:"B37",body:'\nWalsh WR, Pelletier MH, Bertollo N, Christou C, Tan C. Does PEEK/HA enhance bone formation compared with PEEK in a sheep cervical fusion model? Clinical Orthopaedics and Related Research. 2016;474(11):2364-2372\n'},{id:"B38",body:'\nPhan K, Hogan JA, Assem Y, Mobbs RJ. PEEK-Halo effect in interbody fusion. Journal of Clinical Neuroscience. 2016;24:138-140\n'},{id:"B39",body:'\nAlmasi D, Iqbal N, Sadeghi M, Sudin I, Abdul Kadir MR, Kamarul T. Preparation methods for improving PEEK’s bioactivity for orthopedic and dental application: A review. International Journal of Biomaterials. 2016;2016:8202653\n'},{id:"B40",body:'\nHeary RF, Parvathreddy N, Sampath S, Agarwal N. Elastic modulus in the selection of interbody implants. Journal of Spine Surgery. 2017;3(2):163-167\n'},{id:"B41",body:'\nPrzybyla AS, Skrzypiec D, Pollintine P, Dolan P, Adams MA. Strength of the cervical spine in compression and bending. Spine. 2007;32(15):1612-1620\n'},{id:"B42",body:'\nMosekilde L, Mosekilde L. Iliac crest trabecular bone volume as predictor for vertebral compressive strength, ash density and trabecular bone volume in normal individuals. Bone. 1988;9(4):195-199\n'},{id:"B43",body:'\nBalsly CR, Cotter AT, Williams LA, Gaskins BD, Moore MA, Wolfinbarger L Jr. Effect of low dose and moderate dose gamma irradiation on the mechanical properties of bone and soft tissue allografts. Cell and Tissue Banking. 2008;9(4):289-298\n'},{id:"B44",body:'\nSamsell B, Softic D, Qin X, McLean J, Sohoni P, Gonzales K, et al. Preservation of allograft bone using a glycerol solution: A compilation of original preclinical research. Biomaterials Research. 2019;23:5\n'},{id:"B45",body:'\nWalsh WR, Bertollo N, Christou C, Schaffner D, Mobbs RJ. Plasma-sprayed titanium coating to polyetheretherketone improves the bone-implant interface. The Spine Journal. 2015;15(5):1041-1049\n'},{id:"B46",body:'\nZdeblick TA, Phillips FM. Interbody cage devices. Spine. 2003;28(15 Suppl):S2-S7\n'},{id:"B47",body:'\nCho DY, Liau WR, Lee WY, Liu JT, Chiu CL, Sheu PC. Preliminary experience using a polyetheretherketone (PEEK) cage in the treatment of cervical disc disease. Neurosurgery. 2002;51(6):1343-1349. Discussion 9-50\n'},{id:"B48",body:'\nAbla AA, El Kadi H, Bost J, Maroon JC, Wert M. Allograft composite cortical and cancellous bone graft for anterior cervical fusion. Contemporary Neurosurgery. 2005;27(8):1-6\n'},{id:"B49",body:'\nGraham RS, Samsell BJ, Proffer A, Moore MA, Vega RA, Stary JM, et al. Evaluation of glycerol-preserved bone allografts in cervical spine fusion: A prospective, randomized controlled trial. Journal of Neurosurgery. Spine. 2015;22(1):1-10\n'},{id:"B50",body:'\nRodway I, Gander J. Comparison of fusion rates between glycerol-preserved and frozen composite allografts in cervical fusion. International Scholarly Research Notices. 2014;2014:960142\n'},{id:"B51",body:'\nMuzevic D, Splavski B, Boop FA, Arnautovic KI. Anterior cervical discectomy with instrumented allograft fusion: Lordosis restoration and comparison of functional outcomes among patients of different age groups. World Neurosurgery. 2018;109:e233-ee43\n'},{id:"B52",body:'\nYue WM, Brodner W, Highland TR. Long-term results after anterior cervical discectomy and fusion with allograft and plating: A 5- 1-year radiologic and clinical follow-up study. Spine. 2005;30(19):2138-2144\n'},{id:"B53",body:'\nGeisler FH, Caspar W, Pitzen T, Johnson TA. Reoperation in patients after anterior cervical plate stabilization in degenerative disease. Spine. 1998;23(8):911-920\n'},{id:"B54",body:'\nSchneeberger AG, Boos N, Schwarzenbach O, Aebi M. Anterior cervical interbody fusion with plate fixation for chronic spondylotic radiculopathy: A 2- -year follow-up. Journal of Spinal Disorders. 1999;12(3):215-220. Discussion 21\n'},{id:"B55",body:'\nPechlivanis I, Thuring T, Brenke C, Seiz M, Thome C, Barth M, et al. Non-fusion rates in anterior cervical discectomy and implantation of empty polyetheretherketone cages. Spine. 2011;36(1):15-20\n'},{id:"B56",body:'\nSuess O, Schomaker M, Cabraja M, Danne M, Kombos T, Hanna M. Empty polyetheretherketone (PEEK) cages in anterior cervical diskectomy and fusion (ACDF) show slow radiographic fusion that reduces clinical improvement: Results from the prospective multicenter “PIERCE-PEEK” study. Patient Safety in Surgery. 2017;11:12\n'},{id:"B57",body:'\nKim YS, Park JY, Moon BJ, Kim SD, Lee JK. Is stand alone PEEK cage the gold standard in multilevel anterior cervical discectomy and fusion (ACDF)? Results of a minimum 1-year follow up. Journal of Clinical Neuroscience. 2018;47:341-346\n'},{id:"B58",body:'\nKrause KL, Obayashi JT, Bridges KJ, Raslan AM, Than KD. Fivefold higher rate of pseudarthrosis with polyetheretherketone interbody device than with structural allograft used for 1-level anterior cervical discectomy and fusion. Journal of Neurosurgery. 2018;30(1):46-51\n'},{id:"B59",body:'\nTeton Z, II BC, Ahmed Raslan M, Khoi Than M. Use of Polyetheretherketone Interbody Devices for Multi-Level Anterior Cervical Discectomy and Fusion Results in a Three-Fold Higher Rate of Pseudarthrosis Compared to Structural Allograft. American Association of Neurological Surgeons; 2019\n'},{id:"B60",body:'\nPirkle S, Kaskovich S, Cook DJ, Ho A, Shi LL, Lee MJ. Cages in ACDF are associated with a higher nonunion rate than allograft: A stratified comparative analysis of 6130 patients. Spine. 2019;44(6):384-388\n'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Nigeste Carter",address:null,affiliation:'
LifeNet Health, Virginia Beach, VA, USA
'},{corresp:null,contributorFullName:"Elena C. Gianulis",address:null,affiliation:'
LifeNet Health, Virginia Beach, VA, USA
'},{corresp:"yes",contributorFullName:"Mark A. Moore",address:"mark_moore@lifenethealth.org",affiliation:'
LifeNet Health, Virginia Beach, VA, USA
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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}},{id:"351158",title:"Prof.",name:"David W.",middleName:null,surname:"Anderson",slug:"david-w.-anderson",fullName:"David W. Anderson",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Calgary",country:{name:"Canada"}}}]}},subseries:{item:{id:"11",type:"subseries",title:"Cell Physiology",keywords:"Neurodevelopment and Neurodevelopmental Disease, Free Radicals, Tumor Metastasis, Antioxidants, Essential Fatty Acids, Melatonin, Lipid Peroxidation Products and Aging Physiology",scope:"
\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/11.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11407,editor:{id:"133493",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",profilePictureURL:"https://mts.intechopen.com/storage/users/133493/images/3091_n.jpg",biography:"Prof. Dr. Angel Catalá \r\nShort Biography Angel Catalá was born in Rodeo (San Juan, Argentina). He studied \r\nchemistry at the Universidad Nacional de La Plata, Argentina, where received aPh.D. degree in chemistry (Biological Branch) in 1965. From\r\n1964 to 1974, he worked as Assistant in Biochemistry at the School of MedicineUniversidad Nacional de La Plata, Argentina. From 1974 to 1976, he was a Fellowof the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor oBiochemistry at the Universidad Nacional de La Plata, Argentina. 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