The main comparison between the characteristics of SMAs over SMPs [1, 8].
\\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\\nWe 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!
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased 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\nWe 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!
\n'}],latestNews:[{slug:"stanford-university-identifies-top-2-scientists-over-1-000-are-intechopen-authors-and-editors-20210122",title:"Stanford University Identifies Top 2% Scientists, Over 1,000 are IntechOpen Authors and Editors"},{slug:"intechopen-authors-included-in-the-highly-cited-researchers-list-for-2020-20210121",title:"IntechOpen Authors Included in the Highly Cited Researchers List for 2020"},{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"}]},book:{item:{type:"book",id:"6529",leadTitle:null,fullTitle:"Bismuth - Advanced Applications and Defects Characterization",title:"Bismuth",subtitle:"Advanced Applications and Defects Characterization",reviewType:"peer-reviewed",abstract:"Bismuth (Bi) is a post-transition metal element with the atomic number of 83, which belongs to the pnictogen group elements in Period 6 in the elemental periodic table. 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The use of ultrasound in regional anesthesia has shown the reduction of complications, which makes it mandatory to knowledge and acquire skills in all ultrasound-guided techniques.
\r\n\r\n\tUltrasound-guided regional blocks will be reviewed extensively, as well as intravenous regional anesthesia, thoracic spinal anesthesia. The role of regional anesthesia and analgesia in critically ill patients is of paramount importance. In addition, we will review the current role of regional techniques during the Covid-19 pandemic. Complications and malpractice is another topic that should be reviewed. Regional anesthesia procedures in some specialties such as pediatrics, orthopedics, cancer surgery, neurosurgery, acute and chronic pain will be discussed.
",isbn:"978-1-83969-570-4",printIsbn:"978-1-83969-569-8",pdfIsbn:"978-1-83969-571-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"264f7f37033b4867cace7912287fccaa",bookSignature:"Prof. Víctor M. Whizar-Lugo and Dr. José Ramón Saucillo-Osuna",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10708.jpg",keywords:"Regional Anesthesia, Ultrasound-Guided Regional Anesthesia, Local Anesthetics, Preventive Analgesia, Peripheral Blocks, Pediatric Regional Anesthesia, Intravenous Regional Anesthesia, Techniques, Complications, Adjuvants in Regional Anesthesia, Opioids, Alfa2 Agonists",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 23rd 2021",dateEndSecondStepPublish:"March 23rd 2021",dateEndThirdStepPublish:"May 22nd 2021",dateEndFourthStepPublish:"August 10th 2021",dateEndFifthStepPublish:"October 9th 2021",remainingDaysToSecondStep:"18 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Whizar-Lugo has published more than 100 publications on Anesthesia, Pain, Critical Care, and Internal Medicine. He works as an anesthesiologist at Lotus Med Group and belongs to the Institutos Nacionales de Salud as an associated researcher.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"169249",title:"Prof.",name:"Víctor M.",middleName:null,surname:"Whizar-Lugo",slug:"victor-m.-whizar-lugo",fullName:"Víctor M. Whizar-Lugo",profilePictureURL:"https://mts.intechopen.com/storage/users/169249/images/system/169249.jpg",biography:"Víctor M. Whizar-Lugo graduated from Universidad Nacional Autónoma de México and completed residencies in Internal Medicine at Hospital General de México and Anaesthesiology and Critical Care Medicine at Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán in México City. He also completed a fellowship at the Anesthesia Department, Pain Clinic at University of California, Los Angeles, USA. Currently, Dr. Whizar-Lugo works as anesthesiologist at Lotus Med Group, and belongs to the Institutos Nacionales de Salud as associated researcher. He has published many works on anesthesia, pain, internal medicine, and critical care, edited four books, and given countless conferences in congresses and meetings around the world. He has been a member of various editorial committees for anesthesiology journals, is past chief editor of the journal Anestesia en México, and is currently editor-in-chief of the Journal of Anesthesia and Critical Care. Dr. Whizar-Lugo is the founding director and current president of Anestesiología y Medicina del Dolor (www.anestesiologia-dolor.org), a free online medical education program.",institutionString:"Institutos Nacionales de Salud",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"5",totalChapterViews:"0",totalEditedBooks:"3",institution:null}],coeditorOne:{id:"345887",title:"Dr.",name:"José Ramón",middleName:null,surname:"Saucillo-Osuna",slug:"jose-ramon-saucillo-osuna",fullName:"José Ramón Saucillo-Osuna",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000033rFXmQAM/Profile_Picture_1611740683590",biography:"Graduated from the Facultad de Medicina de la Universidad Autónoma de Guadalajara, he specialized in anesthesiology at the Centro Médico Nacional de Occidente in Guadalajara, México. He is one of the most important pioneers in Mexico in ultrasound-guided regional anesthesia. Dr. Saucillo-Osuna has lectured at multiple national and international congresses and is an adjunct professor at the Federación Mexicana de Colegios de Anestesiología, AC, former president of the Asociación Mexicana de Anestesia Regional, and active member of the Asociación Latinoamericana de Anestesia Regional.",institutionString:"Centro Médico Nacional de Occidente",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"347258",firstName:"Marica",lastName:"Novakovic",middleName:null,title:"Dr.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"marica@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"6550",title:"Cohort Studies in Health Sciences",subtitle:null,isOpenForSubmission:!1,hash:"01df5aba4fff1a84b37a2fdafa809660",slug:"cohort-studies-in-health-sciences",bookSignature:"R. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"66443",title:"Future Prospects: Shape Memory Features in Shape Memory Polymers and Their Corresponding Composites",doi:"10.5772/intechopen.84924",slug:"future-prospects-shape-memory-features-in-shape-memory-polymers-and-their-corresponding-composites",body:'\nAs being a kind of smart materials, shape memory polymers (SMPs) and their composites (SMPCs) are significantly attracting consideration [1, 2]. An excellent type of polymers seems to have been disclosed to demonstrate shape memory attributes [2, 3, 4], however, the various characterizations or even analysis techniques of shape memory characteristics along with the changing circumstances among various scientists (see Figure 1), which they possess intention that the claimed characteristics of SMPs are not identical. Consequently, the correlation between shape memory characteristics and the structures is not entirely recognized for certain categories of SMPs. Thus, this can probably obstruct the growth and development of high-performance of SMPs. Aside from that, in comparison with the prompt boost of the variety of SMPs, the main uses of SMPs lags much behind. One among the key factors is certainly utilized the characterization of the SMPs is not going to produce the extensive properties for scientists. For that reason, the analysis of SMPs is vital for the enhancement as well as implantations of SMPs. Based on the Scopus database, a literature analysis was carried out through using the keywords of “Shape Memory Polymers” and/or “SMPs” and the analysis graphs are presented in Figure 1. This chapter presents a basic overview up to the date the main employed characterization of the shape memory characteristics of polymers.
\nShape memory polymer publications based on (a) document type, (b) subject area, and (c) country/territory. “Scopus source accessed on January, 2019”.
The shape memory effect in the shape memory alloys is typically execute based on the test temperature of the austenite ↔ martensite transformation temperature, in which it occurs with the deformation of the SMAs in the martensitic phase during the loading and unloading at temperatures below Mf. After heating these deformed alloys to a temperature above Af, the austenite phase forms, and thus, the original shape is recovered. In addition, these temperatures are typically will be indicated based on the type of alloys. There are three main based-types of shape memory alloys; Titanium-based, Copper-based and Iron-based SMAs. Figure 2(a) shows a typical loading path 1 → 2 → 3 → 4 → 1, wherein the property of SME is observed [5]. The parent phase transforms into the twined martensite (1 → 2) when it undergoes the cooling process. The stress induced detwinning and inelastic strains can occur when the materials are loaded (2 → 3). The maternsite phase is in the same state of the detwinned structure without obtaining any recovered inelastic strains even after the unloaded process (3 → 4). In the final step, the materials are returned to the original shape by recovering the inelastic strains after being heated above Af (4 → 1). On the other hands, there are two types of shape memory effects can be occurred in the SMAs, namely, one-way and two-way SME. On the contrary, the SME of SMPs (see Figure 2b) is mainly influenced by the presence of phases that linked to the coiled or cross-linked polymer structure. The SMPs is deformed at a temperature below the glass temperature (Tg), and the percentage of deformation is mainly depending on molecular chains of polymer, in which they are controlled by the chemical composition and physical cross-linked structure of SMPs. After preheating the deformed polymers, these molecular chains are able to return back to the original coiled-shape structure. The shape-memory transformation varies according to the apparatus in which polymer molecules transpose between the restricted together with random entangled conformations. As comparison with the SMAs, the SMPs are able to exhibited only one-way SME, whereby, the SMPs deformation at the called phase “soft” only along with the incorporation of the external force [6]. The main benefits of SMPs over SMAs is dependent mainly on their inherent attributes, for instance, they are lower cost and/or density, easier manufacturing process associated with higher percentage of strain [7]. Table 1 details the principal differences in the SMPs and SMAs characteristics, in which the SMPs are able to obtain up to 800% strain compared with the lower strain in the range of 0.1–20% for SMAs or other types of materials.
\nSchematic diagram of (a) stress-strain-temperature for the involved crystallographic changes during the phenomena of SME [5], (b) one-way SME for SMPs.
Property | \nSMAs (Ti-based) | \nSMPs (Polystyrene) | \n
---|---|---|
Density/g.cm−3 | \n6–8 | \n0.9–1.1 | \n
Deformation strain (%) | \n<8 | \n≥800 | \n
Young Modulus at Temp.> Trans (GPa) | \n83 | \n0.01–3 | \n
Recovery speed (min) | \nBased on type of alloy | \n<0.1 min- several min | \n
Deformation stress (MPa) | \n50–200 | \n1–3 | \n
Thermal conductivity (W.m−1.K−1) | \n18 | \n0.15–0.3 | \n
Cost ($) | \n∼ 250 per pound | \n∼ 10 per pound | \n
To give details about the shape memory characteristics of polymers, a number of variables are essential. Initially, the variables can certainly reveal the characteristics of polymers. Following by the differentiation of them from other sorts of attributes of materials, shape memory capabilities are demonstrated by means of a variety of thermomechanical cyclic procedures. Consequently, the specifications must be able to describe the natural shape memory functions too. Finally, the structure of the variables must look into the prospective purposes. With taken the consideration of these kinds of aspects, a number of variables were presented and also quantified [9, 10, 11]. The variables are presented in the following subsections:
\nLike appears to have been explained in the foregoing parts, the shape memory behavior is initiated by heating the shape memory polymer to a temperature above the transformation temperature (Ttrans) [12], it could actually cultivate considerable deformations and this can be mainly predetermined by cooling the materials to a temperature below the Ttrans, whereby, this parameter was advocated to define the severity of a brief shape becoming fastened in a pattern of shape memorization [12, 13, 14]. It ought to be pointed out that the numerous perplexed utilizations as well as illustration appear in the characterization of SMPs. Regarding to the shape fixity, further sorts of capabilities for instance strain fixity [9] and also shape preservation [15, 16], stand for the exact same actual physical indication, in which the shape fixity (Rf) is comparable of the extension ratio of the predetermined deformation to the total deformation, which can be prearranged as:
\nFurthermore, the main mechanism of the shape fixity is attributed to the structure and thermomechanical conditions of the shape memory characteristics. The latter condition is significantly been implemented in shape fixity determination as well as the properties of shape memory materials. Wu et al. [17] shows the shape recovery of commercial ether-vinyl acetate copolymer (EVA) with a 300% of pre-stretching at the room temperature, as shown in Figure 3. It was revealed that as the number of cycles increased the strain recovery reduced, in which the residual strain starts from 136% and dropped to 112% after 20 min, and within the 9 h, it reaches to 94% and with increasing the time to 72 h, it ends up with 88%. It would be proven that as the time increased; the rapid creep turns to be gradual creep within the first 9 h. Therefore, a long term of the shape fixity ratio was described according to the value of residual strain. Julie et al. [18] demonstrated the shape fixity (Rf) of the epoxy network based on the torsion test, whereby the Rf was found based on the ratio of angle of torsion after unloading to the angle of torsion after loading. It was found that the shape fixity of epoxy within a dimension of 100 × 10 × 1 mm3 is about 95% at a deformation angle of 360o.
\nRelationship curve of stress-strain of EVA at the room temperature. Insets: (a) multiple cycles at different strains; (b) cyclic test [17].
Shape memory recovery (Rr) is mainly reflect the ability of any substance to recover the memorized shape after being deformed at low temperature and subsequently heated above the transformation temperature (Ttrans) [9, 12, 13]. It is significant to notice that, in a shape recovery event, the full strain energy is emitted by means of the two-recovery strain and stress. To a first approximation, nevertheless, the recovery stress to stain ratio is consistent for an identical material [19]. The stored strain energy, alternatively, ought to be influenced by the internal material energy needed in the deformation, despite the fact that the particular relationship is not recognized, in another words, the quantity of energy loss throughout the shape-fixing stage is not identified. Hence, there needs to be a minimum of a qualitative correlation between recovery stress together with deformation energy (or even input energy). Tobushi et al. [9] and Kim and coworkers [13] have performed the thermomechanical test with multi-cycles in purpose of evaluating the performance of SMPs and found the main determination of strain/shape recovery, in which can be calculated using the following interpretation:
\nWhile the shape recovery rate was determined by Li and Larock [20] after been utilized a bending test on SMPs and came with the following formula:
\nAccording the above-mentioned equations of (2) and (3), it can be proven that there are different mechanisms referring to the shape recovery in different perspectives. Julie et al. [18] obtained that the kinematic of the shape recovery of epoxy networks is a function of the applied deformation angle. It was found that a complete recovery (100%) was obtained and as the deformation increased the recovery ratio tends to decreased. They also found that the lower heating rate is able to attain a full recovery compared with the high heating rate. As both of two types of recovery are mainly related to the molecular mobility that been coincides with the variation of polymer viscoelasticity properties. They were also proven that the torsion test provides a useful interpretation on the molecular mobility with the glass transition when a uniformed deformation is applied. Moreover, the speed of recovery process and deformation of recovery speed were named by Li et al. [20] and Luo et al. [21], respectively, thereby, both terminologies were reflected the shape memory characteristics of polymers. The shape recovery process of different types of shape memory polymers was studies by Liu et al. [22] using video camera records within a rate of 20 frames per seconds. The results of their experiment revealed that the polymer was capable to obtain a full recovery after 0.7 s. Whilst, Luo et al. [21] found that the curve of shape recovery of SMPs as function of temperature and then the shape recovery speed was determined based on the following equation:
\nwhereas Vr is representing the shape recovery speed, dR/dT is the ratio of shape recovery Vs temperature, and dT/dt is the heating rate. On the other hands, Tobushi et al. [9], Takahashi et al. [23], and Kim [13] were performed the tensile test as thermomechanical cycling via a specially designed machine as shown in Figure 4a to study the shape memory characteristics of polymers, in which the tensile test process was isolated under a certain temperature and an extensometer was attached to record the stress–strain data and a programmable software was used to plot the final behavior of one or multicycle of relationship of stress versus strain versus temperature and then the shape recovery and memory effect were determined. Figure 4b shows the final curve behavior of shape memory effect, thereby the curve can be classified into four stages, as the first stage, the polymer sample is heated to a higher temperature (i.e. > transition temperature), which often temperature would be in range of 15–25°C. Second stage describes the strain behavior that maintained a constant strain (εm) followed with a cooling to a temperature lower than the transition temperature (room temperature) to obtain the permanent shape. The unloading process and the elastic recovery stress turns to reach a zero value at a certain strain (εu), as presented in stage 3. An external heating process was applied at a higher temperature to recover the original shape with a minimum value of residual strain (εp) as demonstrated in stage 1′ or 4 based on the type of polymer.
\n(a) Tensile test as thermomechanical cyclic machine; (b) shape memory effect curve [9, 13, 23].
Tobushi et al. [21] have demonstrated the shape recovery (Rr) of polymer at different temperatures and the Rr can be calculated based on the following equation:
\nThe Rr(N), εm, and εp are the shape recovery, residual strain, and plastic strain, respectively under a number of cycles (N), in which found that as the number of cycles increased, the shape recovery maintained to attain 100%. While, Kim and Lee [13] have found that the shape recovery using the following equation:
\nThereby, the shape recovery tends to decrease as the number of cycles increased and shown a stabilized behavior after a number of cycles. Another studies by Liu et al., [22] Lin and Chen [24] and Li and Larock [20] found that the employing of the bending test is much easier and more approachable than tensile test for the thermomechanical test. Figure 5 shows the mechanism of thermomechanical cycles using the bending test, whereas the shape memory polymer sample with a strip shape is bent to angle θmax at a higher temperature > transition temperature (Ttrans). The deformed sample followed by cooling process at a temperature < Ttrans, in which the sample been unloaded and shape recovery started to an angle represented by θfixed. However, with preheating the deformed sample, the original shape recovered gradually associated with number of θ(T) recorded. At the final stage, the sample turns to recover the final shape at angle of θfinal. Therefore, the shape recovery is determined using the following equation:
\nSchematic drawing of bending test as thermomechanical cycles test.
A compression test was also utilized to obtain the shape memory behavior of polyurethane shape memory polymer foam MF5520 at a nominal glass temperature of 63°C. The shape recovery behavior was obtained as the foams were compressed at T > Tg, then cool it to the room temperature, and finally the shape recovery SMP foam was investigated upon heating after different period time of hibernation. The results revealed that at 80 and 93.4% pre-strain and 1 N applied load, the recovery curves acquired the same trends without a full recovery as shown in Figure 6a and b, conversely, removing the applied load, the shape recovery was attained. On the other hands, the sample without hibernation displayed a reduction in the shape recovery as the load increased. Gall et al. [25] was investigated the shape recovery of the thermosetting polymer (CTD-DP7 SMP) along with their corresponding composites using a Dynamic Mechanical Analyzer (DMA). The prepared samples were placed in a three-point fixture and the tip of probe was in contacted to the inner surface of SMP sample. With fixed probe contact, the shape recovery was recorded as the temperature was increased.
\nExtension behavior representing the shape recovery SMP foams hibernated at different time for the pre-strain; (a) 80% and (b) 93.4%.
Lendlein and Kelch [12] described that the behavior of the shape memory for SMPs is not only linked to the polymer properties, but it is also mainly controlled by the structure and morphology associated with the manufacturing processes. Theretofore, the shape memory effect of any type of polymers is demonstrating the thermomechanical cyclic performance includes, shape recovery, deformation, and shape fixing and each of these processes associated with the condition of thermomechanical process are able to vary the shape memorization and thus affect the shape memory characteristics. Hence, it is essential for further development and advanced applications of SMPs to give a complete characterization. For instance, Wang et al. [26] have carried out the thermomechanical cyclic for SMP composite using the cyclic tensile test within 30 mm/min as displacement rate for 5 cycles, as shown in Figure 7a and b. They revealed in their results that there is a huge hysteresis between 1st and 2nd cycle, while these differences are attainment smaller from 2nd, 3rd, 4th and 5th cycles. These variations are mainly attributed to the existence of deformation, composite structure failure along with initial training effect for the 1st cycle. Figure 7b illustrates that the variation of residual strain at the room temperature versus the number of cycles, in which the residual strain tends to increased precipitously with final stabilization behavior as the number of cycles increased due to the resistance of the modified particles against the deformation, which will be explained in details in Section 3.2.
\n(a) Stress-strain curves of SMP composite under different loading-unloading cycles; (b) residual strain versus number of cycles of the reinforced SMP with different percentage of chopped carbon fiber [26].
Pieczyska et al. [27] have been studied the thermomechanical properties of polyurethane theoretically and experimentally under different mechanical loadings at temperature of 20°C above and below Tg at a strain rate of 2 per second within a strain range of 0.6/s. It was observed that when the temperature been slightly dropped, the thermoelastic effect stepped affected. On the other hands, the thermal images (see in Figure 8) are referring to the variations in the strain vales during the loading-unloading process, whereby the uniform distribution of the temperature replicated the deformation process in a macroscopically homogenously presented.
\nTrue stress-strain curve during loading and unloading of PU-SMP along with thermal images that represented different values of strain [27].
The design of SMPs and SMPCs thermomechanical behavior can be vary based on the changes in the polymer molecular structure and/or addition of functional particles or fillers in purpose of forming multi-phases composite SMPs. The reinforcement categorization for the SMP composite can be inserted under the particle/filler according to the type of applications. There are various types of particles can be incorporated with SMP, for instance, Silicon carbide (SiC), carbon nanotubes (CNT), nickel, carbon black (CB), clay, and Fe3O4 [28, 29, 30, 31] along with some others different fibers based on the application requirements [32, 33]. Thus, these types of additions or reinforcements are trigger to enhance the electrical and mechanical properties of SMPs.
\nThermally induced shape memory polymers have been characterized as a remarkable substance with a high recovery and shape memory effect is required, however, their mechanical properties such as modulus and strength are still low. Therefore, the incorporation of carbon nanotube (CNTs) with different types of polymer is essential and their inadequate properties are able to improve after a certain modification been considered [8, 34, 35]. On the other hands, the carbon nanotubes have the presented a potentially implementation the nanoelectronics devices, for example, electrochemical energy storage and artificial muscles. According to the above-mentioned deliberations, Kai Yu et al. [36] have studied the effect of carbon nanotubes on the shape memory effect of SMPs after being exposure to microwave radiation. It was found that the CNTs particles have been absorbed the electromagnetic radiation and converted to be an internal heating source, thus lead to induce a shape recovery for SMCs, as shown in Figure 9. Furthermore, increasing the frequency of radiation and/or amount of CNTs lead to enhance the shape recovery, whereas the SMPs composite within 3 and 5 wt.% of carbon nanotubes have shown a fully recovery in their shape, while, the SMPs within 1 wt.% addition has a lowered recovery with 80% less than high amount and the unrecovered shape has been resulted due to the insufficient amount of radiation to overcome the caused friction between the CNTs and polymer matrix. From the same point of view, another research was conducted poly(vinyl alcohol) (PVA) filled by CNTs, in which the results revealed that there is a wide boarding in the glass transition temperature and the initiated stress during the recovery was almost double value compared with the conventional polymer [37]. Conversely, Raja et al. [38] found that there no apparent for the shape recovery of PU/PVDF polymer blend nanocomposites after been deformed in “U” shape and preheated using a hot water with a temperature of 60°C for 2 h and followed by a direct quenching in cold water, as demonstrated in Figure 10a. An external heating source using a DC controller with a 40 V was attached to the ends of modified polymer strips to activate/initiate the shape recovery. In spite of this, the modified PU/PVDF nanocomposites with CNTs fillers, namely as PUPF-NTM10 has been recovered after 15 s and others samples filled with pristine CNT, namely as PUPF-NTP10 has been recovered the complete shape after 30 s with the external applying of electrical impulse. It was also found that repeating the shape memory test (i.e. increase the number of cycles) led to reduce the shape memory ratio as depicted in Figure 10b.
\nSequence of the shape recovery process of the SMP composites under microwave radiation (2.45 GHz): (a) deformation process and (b) modified SMP/CB/CNT sample shape recovery and temperature distributions.
(a) SME of unmodified PUPF-NTP10 pristine and CNT modified PUPF-NTS10 filled with PU/PVDF nanocomposites; (b) recovery ratio versus number of cycles [38].
The influence of multi-walls CNTs on the shape memory effect of epoxy nanocomposites was deliberate by Abishera et al. [39] as implementation in the self-healing systems applications under different programming conditions. It was revealed that the changing in the programming conditions obtained an excellent shape memory behavior, as well as, the incorporation of the multi-walls of CNTs has indicated an improvement in the young modulus, strength, recovery speed and shape fixity of epoxy associated with drops in the failure strain. Qi et al. [40] have investigated the shape memory properties of polylactide (PLA)/thermoplastic poly(ether)urethane (TPU) composites after been reinforced with carbon black (CB) nanoparticles within the blending ratio of 70:30 by weight. Due to the continuous phase of thermoplastic poly(ether)urethane (TPU), an outstanding shape memory behavior was acquired for the novel ternary structure of PLA70/TPU30/CB, wherein it resulted in the occurrence of the persuasive recovery driving force. In addition, the addition of CB with different percentages displays a slight improvement in the shape fixing ratio (Rf) of 90% (see in Figure 11), this may relate to the elongated TPU phase retraction, in which resulted in a total rigid of polylactide phase at 25°C. As the temperature increased more than Tg, the amorphous chains of PLA started to move and thus release constrained TPU phase. The principal contributor in the enhancement of shape recovery ratio (Rr) is the strong pliability of TPU phase and addition of CB, as it was shown only 59% for the binary phase of PLA70/TPU30 and increased to 80.2% as the CB was added, as shown in Figure 11a and b. Moreover, the increment in the heating time under a consistent 30 V led to increase the shape memory ratio of the ternary phases of PLA70/TPU30/CB6 and PLA70/TPU30/CB8, as shown in Figure 11c. The fastest shape recovery response for PLA70/TPU30 after 8 wt.% addition of CB with 90% ratio in 80 s, on the other hands, the PLA70/TPU30 with 6 wt.% of CB approached the same ratio in 150 s, as illustrated in Figure 11d. Haibao Lu et al. [41] presented the shape memory behavior of shape memory polymer nanocomposite (SMPs) after carbon nanotube and boron nitride additions using a bending testing with an Infrared light-induced as heating source. A full recovery 100% in 60 s was recorded for the modified SMP with 4 wt.% boron nitride and CNTs, as shown in Figure 12(a-c), in which the unmodified sample was obtained shape recovery lower than 80% in the same exposure heating time, as shown in Figure 12d. This kind of improvements is mainly attributed to the particle of boron nitride that have been improved the thermal conductivity through the facilities of the heat transfer in the composite polymers [44, 45], and thus, CNTs and boron nitride additions have been drastically superior the infrared light-induced shape recovery.
\nRepresentation design of the shape recovery of (a) binary blends of PLA70/TPU30 and (b) ternary blends of PLA70/TPU30/CB5; (c) recovery ratio (Rr) versus CB contents and (d) shape fixing (Rf) versus time PLA70/TPU30/CB6/8 [40].
Optical shape recovery of (a) pristine SMP, (b) nanocomposite SMP reinforced with 4 wt.% of BN, (c) nanocomposite SMP reinforced with 4 wt.% of BN and CNTs, and (d) shape recovery ratio versus time for pristine SMP with and without BN/CNT reinforcements [41].
The effects of the nanosized noble metals-based, such as gold (Au) and silver (Ag) nano-particles/wires on the structure and properties of SMPs have shown a great interest for the researchers and scientists as a multi-responsive shape memory polymer in composite form [8, 42, 43]. Due to the large surface and high plasmonic resonance, these nanosized metals been offered a structure that able to absorb the specific wavelength and convert it into heat energy, thus produce a remarkable type of polymer with high shape actuation and wavelength activation.
\nThe cross-link structure between the polymer and ion-metals as ligand coordination have shown a promising method to produce shape memory polymers with noteworthy properties. An isonicotinate-functionalized polyester (PIE) was studied by Wang et al. [44], which they described the effect of silver (Ag) addition to the coordination of the polymer network structure to produce the strip specimens. The shape memory effect was measured based on the DMA test, whereas the strips was heated to 50°C for 1 min, followed by bending process into spiral shape. The shape fixation was carried out by frozen the deformed strips at 0°C for 1 min. Lastly, the strips were recovered the initial shape after being heated to 40°C using hot air. It was found that the modified strip was shown an excellent shape recovery at 37°C for 60 s, as shown in Figure 13. Another study on producing a film by Lu et al. [45], the shape memory behavior was investigated using bending test, where the sample was bent in U-like shape at 160°C and cooled to the room temperature (which it was about 22°C). it was found that the sample contains the Ag particles decorated GO has recovered 100% after 36 s within an electric power of 3.87 Watt, as shown in Figure 14.
\nShape memory effect of Ag–PIE in PBS at 37°C [44].
Shape memory effect of SMPs composite induced by joule heating based on (a) trend scale of temperature, (b) reinforcement of carbon fiber grafted with graphene oxide, (c) reinforcement of carbon fiber grafted with nanoparticles of Ag associated with GO decoration [45].
The behavior of the electro-response shape recovery of the surface modified of SMP with Ag nanowires layer was investigated by Luo et al. [46]. The recoded data of shape recovery versus time as shown in Figure 15a, the results exhibited that the Ag modified samples were not only able to recover the full initial shape but also with fastest speed recovery in shorten time compared with un-modified samples. It was also found that the higher addition of Ag led to reduce the shape recovery, and therefore, the external heating source was essential. As the heating increase, the thermal transition was occurred and consequently the shape recovery developed. Figure 15b shows that with the applied external heat of 5 volt, the bent angle turns to be change within 3 s, this because the presence of nanofillers is capable of conductive network reduction and subsequently increase the resistivity of the strain sensitivity and conductivity [47].
\n(a) Shape recovery ratio versus exposure time under a voltage of 5 V; (b) shape recovery demonstration under different exposure times [46].
A semi-crystalline PEO20K polymer was prepared by Zhang et al. [42] using a cross-linked loaded with nano-particles, whereas found that the gold addition is not utilized to obtain/control the shape memory effect, however, it has also enhanced the properties of self-healing of SMPs. An exceptional concern in such a form of substances is the fact that SMPs necessitate an everlasting system structure (characteristically cross-linked) that could be in confrontation with the substantial a string movability and also inter-diffusion intended for the manufacturing of self-healing properties (SHP) polymers. Within this purpose, the configuration of the SHP it can be more suitable to develop materials upon one single-polymer with the two light-controlled shape-memory and optical recovery features. It was found that the addition of small amount of AuNPs of 0.003 wt.% to the cross-linked poly (ethylene oxide) (PEO) films was sufficient enough to deliberate the main shape memory properties of produced films. The shape memory effect of the produced films is shown in Figure 16.
\nOptical healing/recovery procedure of a film made from a cross-linked PEO/AuNP using light controlled as a source of heating: (a) Original film, (b) temporary shape obtained by folding the film along the lines a1, a2, a3 at 80 ?C followed by cooling to room temperature; then two cuts were made as indicated by red arrows (b1 and b2 in photo a), (c) the b1 cut was healed by exposing the crack to laser (12 W/cm2) for 5 s; (d) the first unbending after 10 seconds laser scanning along the fold a1 at a power of 6 W/cm2, followed by the second unbending under the same condition along the fold a2; (e) the other cut b2 remained in the film of an intermediate temporary shape; (f) the cut b2 was optically healed under the same condition as for the cut b1; (g) the third light-triggered unbending along the fold a3 completed the permanent shape recovery.
In 2009, Hribar et al. [48] have been developed a modified polymer network, namely β-amino esters, whereas the modified nanocomposites SMPs has demonstrated shape memory effect using IR light as heating source within a temperature above glass transition temperature (Tg). The results exhibited that the prompt shape recovery was spotted until the transformation turn out the path of the beam associated with a thermal transition in the polymer from glassy ⇒ rubbery networks. There are new perspectives for the actuated and functional shape memory polymer that recently been used in different application, for examples: dry adhesives, panels of light-tracking solar, light-guided for smart windows and even actuators. Zheng et al. [49] have been produced a light responsive SMPs as micropillar with a diameter of 10 μm mixed with 0.1–0.2 mol% of AuNRs in a hexagonal array using poly(dimethylsiloxane) mold as replica molding. To obtain a temporary shape, the pillars were bent at different angles (θ = 30, 45, and 60°) at a temperature above the glass transition temperature (i.e., T = 20°C) and then following by cooling process to the room temperature, as shown in Figure 17a and b. A heating source was applied using a green laser with a wave-length of 532 nm for different period of times and the shape recovery was monitored by optical microscopy. The results revealed that within 0.08 W, as a laser power, the pillars need 40 s to recovery their temporary shape, however, with raising the laser power to 0.3 W, they grabbed the original shape within only 5 s. It was also found that when the pillars are ground to be collapsed, the shape recovery will not be able to obtain a full recovery (i.e.,100%), and this may attribute to the large force of adhesion between the substrate and pillars, in which it has particularly a higher value than the stored elastic energy of the deformed pillars.
\nRecovery time versus (a) bending angle and (b) laser power, of the reinforced SMPs with AuNRs at 45o pillar angle [49].
A cross-linked poly(ethylene oxide) (PEO) loaded with 0.5 wt.% AuNPs was experienced to bending loading and unloading along with an exposure to a laser source within a wave-length of 532 nm and power of 0.15 W [50]. The deformation process involved a stretching of the modified PEO/AuNPs to 90% (approximately 200% strain) at 80°C above the Tm, followed by cooling to the room temperature. The top surface of the film was exposure to the laser in purpose of maintaining the anisotropic relaxation in the polymer chains, followed by cooling a temperature below Tm and consequently, resulted in fixing the temporary shape, as shown in Figure 18(a–f), in which the main principles of the technology to exploited the unique shape memory effect property in numerous types of photothermal based shape memory polymers. On the other hands, the adaption of the light polarization has also shown a significant effect on the shape memory property, in which it led to control the photo-based thermal effect, as shown in 2013 study by Zhang et al. [51], whereas the cross-linked network polymer of PVA containing of 0.02 wt.% AuNRs film was stretched and heated to a temperature of 80°C, i.e., above the Tg to maintain the shape permanent transformation, as shown in Figure 19(a–c). A laser in a linear polarization featured with a wave-length of 785 nm and 0.2 W/cm2 was applied. The results revealed that there is no shape recovery was obtained when the polarization was perpendicular to the deformed film, even after 2 minutes of exposure. Whilst, the deformed shape was fully recovered in 10 s when the polarization turned to be in parallel direction aligned with stretching direction. The reason behind the directional effects can be elucidated that there was no longitudinal absorption in the perpendicular direction, thus resulted with no heat released. However, with the parallel direction, the longitudinal absorption reached to the maximum, and subsequently, the temperature increased above the glass transition temperature (Tg) that lead to reactivate the shape recovery.
\nOptical observation of the shape transformation of cross-linked PEO film reinforced with AuNPs using a laser as a temperature source; (a) original film, (b) deformed sample at 80 °C, (c) large-out of plane bending, (d) gradient chain relaxation and (e,f) shape recovery after applying the laser heating source.
Shape memory characteristics of PVA/0.02 wt.% AuNR with the light polarization-dependent at the room temperature; (a) optical images of the shape memory behavior; (b) recovery angle verse exposure time under different period of times in two directions, parallel and perpendicular; (c) relationship curve of recovery angle and polarization angle in 1 minute exposure using a light polarization [51].
Generally, the enhancement in the shape memory polymer mechanical properties is still limited and their reinforcement with short fibers and/or particles is irrationally to be proposed as structural substances [52]. Therefore, the reinforcement with continuous fiber has been attentionally employed to improve the mechanical properties of SMPs [53, 54]. Due to the highly potentialized SMPs, their usages are widely fulfilled for various advanced applications, such as solar arrays, trusses and antennas, which they essential with no moving segments [32]. Furthermore, the majority of researches with regards to SMPs composites are involved in thermoplastic SMPs resins such as polyurethane SMPs. Nevertheless, the comparatively inadequate thermal together with mechanical properties, for instance, moisture, temperature and/or chemical resistance of thermoplastic SMPs are not able to fulfill sensible demands [2]. Thermosetting SMPs, in spite of this, established a marked improvement in the latter characteristics which enable it to be extremely popular for many practical and or structural resources. The development of the fabricated polyurethane SMPs reinforced with carbon-based fiber was implemented for the industrial applications [55, 56, 57], a larger ratio of the bending recovery was exhibited in the reinforced polymers compared with pure SMPs sheets, from the same point of view, the epoxy-based SMCs namely EMC (Elastic Memory Composite) was potentially executed for the structure of spacecraft applications, as this EMC was developed in the early 1990s by Composite Technology Development (CTD) [58, 59]. Gall et al. [60] have been investigated the deformation micro-mechanisms of EMC and highlighted the development interaction reinforcement between the epoxy EMC laminate as shape memory polymers resins and fibers and found that because of the changing in the surface of the neutral-strain and micro-buckling effects, the reinforced SMP was able to produce a large value of compression strain compared with the traditional resin composite. Furthermore, the development of composite of thermosetting styrene-based reinforced with fiber was studied by Leng et al. [61], and found due to the good strain capabilities and their relative properties, these types of reinforced-polymers have been potentially chosen to take a part of the structure’s applications. From the same perspectives, as a comparison with the pure SMPs, the carbon-based fibers present better thermomechanical properties, and thus been proposed to be use as multi-functional materials [32, 62]. The reinforcement of the glass and kevlar fibers SMPs composite have obtained a superior improvement in the stiffness associated with decrement in the recoverable strain, has been premeditated by Liang et al. [52]. On the other hands, the chopped glass fibers were added to the thermoplastic SMPs and their influences on the shape memory characteristics were examined by Ohki et al. [55]. It was found that the reinforcement by 50 wt.% glass-fiber entertains increment in the failure stress to 140% and reduced the recovery rate to 62%. Another study by Wang et al. [26] demonstrated the shape memory effect of TPI SMPCs under the effect of different mass fraction of the chopped carbon-fibers at three experimental temperatures of 299, 319, and 339 k, as shown in Figure 20a. it was found that both experimental variables; temperatures and fibers reinforcement have been remarkable affected the shape memory effect of TPI polymers. The shape recovery ratios tend to rapidly increased as the applied temperatures increased and reinforcement ratio of carbon fiber decreased (see Figure 20b), which can be justified these variations that as the cross-linked structure are getting dense, their movements are required more energy and the chain segment movements would be required a higher free space. Therefore, as the temperatures increased, the chain segments will have enough energy to release and thus perform the shape recovery.
\n(a) Shape memory effect behavior with the reinforced SMP along with (b) the shape recovery ratio [26].
Figure 21a and b displays the epoxy-based SMPs reinforced of carbon fibers with four percentages ratio of 16, 23, 30, and 37% were designed by Li et al. [63]. The designed composites have demonstrated an excellent shape recovery at 120°C within a ratio of 90% and obtained a full recovery 100% after 20 min at the same temperature. The recovery ratio behaved proportionally with the mass fraction of fibers and inverse proportional with the partial load level. Extensive researches were carried out on different types of SMPs matrix and various fiber reinforcements because of the increasing demands for different applications as been summaries in Table 2.
\n(a) Stress recovery curves for four percentages of fiber reinforcement; (b) recovery ratio of the reinforced SMP composites with 23 and 37% mass fraction within different partial loads [63].
Summary of various types of fibers and their shape memory effect.
Shape memory polymers (SMPs) and their composite (SMPCs) have exhibited exceptional features that led to proposed them to be implemented as advanced materials for the current and potential applications. However, the traditional shape memory characteristics and features are quite limited to due to their abilities of recovering the original shape using the heating source only. Therefore, the reinforcements with micro/nano-fillers and particles or fibers are essentially important to be considered to meet the needed functions and performances. Furthermore, the reinforced SMPs and SMPCs are not only demonstrated a significant mechanical and shape memory properties, but also obtained noble features after being exposure to any electro-or-thermal heating source. Based on the previous researchers, the foreseeable future concepts of SMPs and SMPCs may well-rely on how to adopt the benefits of this kind of properties, in addition to, exceptional attributes as advanced alternatives. On the positive front, the practical applications probability of SMPs and SMPCs are found extensively when displayed in the remarkably distinct application principles which may have seemed in the recent peer-reviewed publications and also patents. Moreover, we believe that the investigation of the advanced features of these types of materials is still in development of new design and/or incorporations. The actual vital, hence, can be found in the finding of substantial beneficial functions wherefore SMPs and SMPCs are enablers or even no less than tremendously excellent substitutes.
\nThe author(s) would like to thank the Management and Science University (MSU) for providing the research support under the Seed Research Grant No. SG-451-0518-ISE.
\nThe authors declared without any conflict of interest.
Lipids are a very heterogeneous group of biological molecules. Some of the most studied lipids are built from the fatty acids (FAs) or isoprenyl groups. FAs are carboxylic acids composed by an even number of carbon atoms connected by single or double bonds with a methyl group end. FAs can be classified into very long (>20 carbons), long (14–20 carbons), medium (6–12 carbons), and short (up to 6 carbons)-chain FAs, as well as saturated (no double chains), monounsaturated (1 double bond), and polyunsaturated (PUFAs, >1 double bond) FAs. Furthermore, unsaturated fatty acids can receive its omega (n) assignment according to the first double-bond position from the end methyl group. Biosynthetically, endogenous FAs have been made from acetyl-CoA/malonyl-CoA [1, 2, 3].
FAs represent a class of lipids on their own and do not make part of all lipids [4]. Some lipids, which are not formed from FAs but are biosynthetically related to them, are the polyketides, formed from the acetyl units. Other unsaponifiable lipids are built from isoprene units, molecules with five carbons with a branch structure and alternated double bonds. Isoprenes have their biosynthesis in mevalonate (vegetables) or deoxyxylulose phosphate (animals) pathways. They can form sterols and prenols [2]; some sterols can also have FAs in their structure [3].
Actually, lipids comprise eight main classes within different chemical characteristics: fatty acids (1), glycerolipids (2), glycerophospholipids (3), sphingolipids (4), sterols (5), prenols (6), saccharolipids (7), and polyketides (8) (Figure 1) [3]. These classes show a high diversity of molecules and are grouped into several subclasses. Lipid classification based on their chemical information, described by the headgroup and the type of a linkage between the head group and aliphatic chains [5, 6] is the most used among biochemists. Investigators have estimated the presence of ~180,000 lipid species in nature and ~40 common fatty acids as building blocks [7]. At the moment, 43,109 structurally distinct lipids are already registered at the Lipid MAPS consortium.
Biosynthetic lipid network. Acetyl-CoA: fatty acids-FAs (class 1) are synthetized, enabling the production of other lipid classes: 2 (glycerolipids-GLs), 3 (glycerophospholipids-GPs), 4 (sphingolipids-SPs), and 7 (saccharolipids-SLs), as well the class of eicosanoids. Acetyl-CoA can also generate the class 8 (polyketides-PKs) and isopentenyl diphosphate molecule, through mevalonate. On the other side, isoprenyl is used as starting substrate for producing lipid classes 6 (prenols-PRs) and 5 (sterols-STs). Figure was inspired on Quhenberger et al. [4].
The high diversity of lipids reflects their multiple biological functions and can be attributed to the wide variety of their building blocks and numerous possible permutations [6, 8]. In the human body, lipids serve as: substrates for the synthesis of energy (9.3 kcal/g), steroid hormones, inflammatory lipid mediators, vitamins or liposoluble vitamins transportation, and structural elements of cell and organelle membranes [9, 10, 11]. As a part of the cell membrane, lipids can influence the distribution of surface proteins, protein signaling (as part of lipid rafts or as second messengers), and consequently, the activation of transcriptional factors [12, 13]. This means that besides their recognized biological functions, lipids can influence protein signaling and synthesis.
In a cell, lipids show different compositions, tens of thousands to hundreds of thousands of compounds, and concentrations from a mol/mg to nmol/mg of protein [5]. Facing the biological relevance of lipids, it is not surprising that the human organism has sophisticated machineries for the FA synthesis when its dietary supply flaws. Saturated and monounsaturated FAs can be endogenously generated from glucose and amino acids through enzymatic elongation (by adding units of two carbons) and desaturation (by forming new double bonds) reactions. However, a pitiful lack of the desaturating enzymes ∆-12 and ∆-15 desaturases preclude humans to add double bonds before the ninth carbon at the end of the methyl extremity for the synthesis of the polyunsaturated fatty acids (PUFAs) n-linoleic acid (C18:2 n-6, LA) and alpha-linolenic acid (C18:3 n-3, ALA). Consequently, LA and ALA are obtained exclusively from diet and, then, called as essentials. After ingestion, LA and ALA compete for sequential enzymatic processes of elongation and desaturation until their conversion into longer chain PUFAs: arachidonic acid (C20:4 n-6, ARA) from LA and eicosapentaenoic acid (C20:5 n-3, EPA) or docosahexaenoic acid (C22:6 n-3, DHA) from ALA [14].
ARA, EPA, and DHA have a high clinical interest once they influence the composition and steady-state of cell membranes. Also, they are precursors of the lipid mediators named eicosanoids involved in the activation of the inflammatory response. While ARA is a precursor of pro-inflammatory, immunosuppressive, and pro-thrombotic eicosanoids, EPA competes with ARA for lipoxygenase (LOX) and cyclooxygenase (COX) enzymes to generate functionally less intense and antithrombotic mediators [10]. Furthermore, EPA and DHA are precursors of resolvins and DHA is a precursor of protectins and maresins. These lipid mediators are collectively called as specialized pro-resolving mediators and have a relevant role in the inflammation resolution and homeostasis restoring [15]. In conjunction, these observations traduce an anti-inflammatory and pro-resolving potential of EPA and DHA (Figure 2).
Synthesis of lipid mediators from eicosapentaenoic (C20:2 n-6, EPA), docosahexaenoic (C22:6 n-3, DHA), and arachidonic (C20:4 n-6, ARA) acids. EPA, DHA, and ARA are previously synthetized from n-3 and n-6 fatty acid families in reactions mediated by enzymes: 1—desaturase, 2—elongase, 3—peroxisomal fatty acyl-CoA oxidase, 4—lipoxygenase (LOX), and 5—cyclooxygenase (COX). The cellular bioavailability of EPA decreases the production of ARA-produced eicosanoids, which include prostaglandins (PG)E2, thromboxane (TX)A2, and leukotriene (LT)B4. These eicosanoids have a higher pro-inflammatory potential than those contra parts produced from EPA (PGE5, TXA3, and LTB5) in promoting vasodilation and leukocyte chemotaxis and adhesion, events that stimulate the migration of neutrophils into the damaged tissue. As part of the neutrophil-monocyte sequence of inflammation, eicosanoids are no longer produced to initiate the synthesis of resolvins, protectins and maresins, lipid mediators from EPA and DHA. Other fatty acids shown are: linoleic acid (C18:2 n-6, LA), gamma-linolenic acid (C18:3 n-6, GLA), dihomo-gamma-linolenic acid (C20:3 n-6, DGLA), adrenic acid (C22:4 n-6), tetracosatetraenoic acid (C24:4 n-6), tetracosapentaenoic acid (C24:5 n-6), docosapentaenoic acid (C22:5 n-6), oleic acid (C18:1 n-9), octadecadienoic acid (C18:2 n-9), alpha-linolenic acid (C18:3 n-3, ALA), stearidonic acid (C18:4 n-3, SDA), eicosatrienoic acid (C20:3 n-3, ETE), eicosatetraenoic acid (C20:4 n-3, ETA), docosapentaenoic acid (C22:5 n-3, DPA), tetracosapentaenoic acid (C24:5 n-3), and tetracosahexaenoic acid (C24:6 n-3).
Moreover, EPA, DHA, and their metabolites can exert anti-inflammatory and metabolic effects by modulating the activity of transcriptional factors, such as nuclear kappa B factor (NFκB), nuclear factor E2-related factor 2 (Nfr2), peroxisome proliferator-activated receptor (PPAR), and sterol regulatory element-binding proteins (SREBP). Due to their abilities, EPA and DHA can influence the transcription of genes enrolled in inflammation, cell survival, oxidative stress, and in carbohydrate and lipid metabolism [16]. Some of the EPA and DHA functions arise from the capacity of these n-3 PUFAs (mainly DHA) to interfere in protein receptors signaling by disrupting lipid rafts, membrane microdomains rich in saturated FAs (mainly cholesterol) who confer a rigidity needed for some protein dimerization through the fluid cell membrane [17, 18].
Due to biological properties, the importance of EPA and DHA for human health has been highly discussed and investigated by basic, translational, and epidemiologic scientists. However, studies on lipids and their biological relevance are not limited to n-3 PUFAs or other individual lipids, but also include the analysis of all lipid species from a biological sample—the lipidome. Because lipids are intermediates and even signaling molecules of metabolic pathways, the lipidomic response (change of the lipidome pattern of a biological sample) to nutritional, pharmacological, or any intervention (i.e., surgery, exercise) treatments can reflect their biological effects [5]. Studies on lipidome can also add to the knowledge on the lipid content of a nutritional source (i.e., fish) aiming to found ones with the high n-3 PUFAs, for instance. These are examples of many applications of lipid analysis in biological systems.
There are several tools available for the study of individual lipids and lipidome (the total lipid content in a cell or an organism), all with their advantages and limitations (Figure 3). Understanding these points is essential for the application of that most appropriate techniques to answer a scientific question on lipids within a biological model. Often little familiarity with these analytical resources may limit the validity of the results. This chapter aims to present and discuss different tools available for different applications in the study of lipids aiming to assess biological hypothesis, with focus on nutrition and metabolism aspects.
The most common analytical techniques used in analyses of lipids and lipidomes are gas chromatography (GC), mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. These techniques show some vantages and weaknesses and could be used in combination with other techniques in so-called hyphenated bioanalytical methods. All enable qualitative and quantitative analyses of lipids, but GC needs additional step in sample preparation as to increase the volatility of the compounds; thus, not all lipids could be analyzed by GC. Also, GC requires greater sample quantities when compared to MS, which is most sensitive. MS analyses require the use of ionization techniques, such as electron and chemical ones for gas samples, while electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) are usually applied for liquid and solid samples. NMR is the only nondestructive technique and allows the noninvasive lipid analysis in intact cells and tissues, and enables to investigate changes in lipid and dynamic structures in biochemical cell functionalization, but it is not sufficiently sensitive and universal when compared to MS.
According to the principles of chromatographic techniques, the gas chromatography (GC) is applied when aimed to separate organic compounds from a mixture in the gas form. For this purpose, the GC uses interaction among the sample components and the stationary phase and the mobile gas phase. After lipid extraction, the samples (lipid mixture) are usually liquids and must be exposed to a high temperature at the gas chromatograph entrance (injector). Vaporized, the samples are carried by a gas, which is usually a nonheavy and inert gas (i.e., hydrogen, helium), through a long capillary column containing a high or low polarity material (stationary phase) [19].
The gaseous compounds generated from the vaporized sample interact with the stationary phase what allows each compound to elute/separate at a different time (retention time). Because GC considers both chemical and physical properties of the vaporized compounds, those with more chemical affinity to the stationary phase will take longer time to be removed from the column and the temperature will influence the overall process. This explains why the column stays in an oven, which is programmed to work at different temperature ranges (i.e., temperature programming) in which the compounds are carried out by the gas according to their boiling point until they get to an electronic detector [20].
At the end of GC analysis, the electronic detector generates a chromatogram based on retention time by intensity. This allows a qualitative identification of the lipid compounds by comparing their retention times with certified standard using the flame ionization detector (FID) or by deduction of spectra information using a mass spectrometer as detector. Lipid quantification can also be performed using analytical procedures of external or internal certified standard in GC analysis [21].
Main points to be considered when assessing FAs by GC analysis are the carrier gas flow rate, column length, and the temperature because these can influence the order or retention time of the lipid compounds and then must be precisely standardized [22]. The column length of the stationary phase influences the resolution of the analytes, once the number of theoretical plates (hypothetical zone in which two phases establish an equilibrium with each other) is respectively high in longer column. As fat and oils have high boiling points not supported by the stationary phase, a previous derivatization reaction step is required after lipid extraction from the biological sample, in which triacylglycerol and free fatty acids are transformed into their respective free fatty esters with lower boiling points (transesterification/esterification reaction) [23]. Several methods are available for FAs derivatization [24], and the most applied ones are described in the 969.33 AOAC’s method [25].
Particularly for cholesterol analysis, the samples preparation must consider a derivatization reaction. This allows to block protic sites of steroids obtained after an unsaponifiable lipid extraction [26] had been performed, and also, to diminish dipole-dipole interactions, to increase the volatility of the compounds, and to generate products with reduced polarity. Cholesterol derivatization is usually achieved by using trimethylsilyl compounds as reagents (silylation reaction). A common method for this purpose is described by Bowden and collaborators [27], in which N,O-bis(trimethylsilyl-trifluoroacetamide/trimethylchlorosilane)—BSTFA/TMCS is used.
Nowadays, other more modern analytical tools than GC (next-generation techniques) do not require sample derivatization for lipid analysis. Needed lipid derivatization can be then consider a quite limitation step of the technique. In comparison with next-generation techniques, GC also implies in using greater sample quantities. This may be the main limitation in biological assays, which usually lead with restricted sample amounts. Nevertheless, by using certified standard and a powerful detector as FID, GC has the advantage to allow a precise and complete (by burning every compound, no one is lost in the detection) quantification of lipid compounds from biological samples, not always achieved by the other analytical techniques. In this context, GC continues to be accepted as an efficient and simple technique for FA and sterol analyses, mainly when combined with mass spectrometry (MS, detailed later in this chapter).
In biological issues, GC is largely applied to assess the FA and cholesterol contents in animal models or human fluids and tissues, as biological markers of FA ingestion and cell incorporation. The technique is a powerful tool in studies assessing the effect of FA supplementation on a specific biologic response. For instance, the endogenous synthesis of EPA and DHA from ALA is low in humans, who have in the ingestion, oily fishes as the most relevant source. Therefore, studies on n-3 PUFAs have been focused on the effect of fish ingestion or fish oil/EPA/DHA supplementation in several clinical conditions, and cell and disease models. In such studies, the treatment compliance or effectiveness can be reflected by the cell or circulate contends of n-3 PUFAs [28]. Furthermore, GC can be applied to validate data generated by other lipidomic techniques.
A practical example in using GC for treatment compliance is the study of Nogueira et al. [29] assessing the effect of n-3 PUFAs supplementation in patients with nonalcoholic steatohepatitis against placebo (mineral oil). In this study, GC highlighted a similar increase in n-3 PUFAs plasma in both n-3 PUFAs- and placebo-treated patients. Because the authors have controlled compliance of n-3 PUFAs, they were able to discover off-protocol intake of PUFAs by some patients from the placebo group. When studying biochemical markers of lipid intake and cell incorporation, the biological sample nature matters. For instance, plasma and red blood samples can reflect periods of weeks and months of FAs ingestion and their effects, respectively, while the adipose tissue is the reference method, once it reflects such variables for years [28].
The study of Ravacci et al. [30] can illustrate the use of GC to assess treatment compliance. Applying this technique, the authors were able to demonstrate that the treatment of a lineage of breast cancer cell overexpressing HER-2 with DHA increased its availability in the cell membrane and was associated with the disruption of surface lipid rafts that sustained cell signal for survival. Regarding the use of GC for data validation, a practical example is the study of Ouldamer et al. [31], which applied the technique to validate the fatty acid information generated by the 1H NMR analysis on the PUFAs n-3 DHA and EPA content in the adipose tissue of mammary tumor model in rats exposed to controlled dietary intake of lipids.
Modernization of MS used for lipid analysis raised the concept of lipidomics. Lipidomics is an emerging science that aims to analyze the total lipid content found in a cell or tissue (lipidome) through the application of analytical chemistry principles and techniques. As a part of the omics sciences, the processes applied in the lipidomic analysis are analogous to those applied in other life-building macromolecules, such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and proteins, called as genomics, transcriptomics, and proteomics, respectively [32].
The basic principle of the MS technique is founded on the detection of the abundance of ions by their mass/charge ratio (m/z). To allow the analysis, such ions of compounds are generated by suitable methods and ions are separated according to their m/z. Ionization techniques can break some sample’s molecules into charged fragments and are chosen according to the physical state of the sample. Also, the efficiency of various ionization mechanisms for the unknown species might help when picking the most appropriate ionization technique. The most common ones for gaseous samples are the electron and chemical ionizations, while for liquid and solid samples, the electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) are usually applied [33].
Advances in ESI-MS and MALDI-MS have greatly facilitated lipidomic analysis [34] and enabled a great progress in lipid metabolic discoveries. This is because ESI is one of the softest ionization techniques, in which some complex dimers and solvent adducts can also be detected at the end. The efficiency of lipid ionization in ESI is incomparably higher than achieved by other traditional MS ion sources. MALDI-MS counts on a good solubility of analytes (lipids) and a matrix (for example, 2,5-dihydrobenzoic acid) in organic solvents, and provides excellent signal-to-noise ratio and reproducibility [32].
Mass spectrometers are made from three components: the ion source (1), which converts a sample into ions that are targeted through the mass analyzer (2) and run into the detector (3). The mass analyzer acts as ions organizer (classifier) using ion m/z ratios. This component accelerates ions as they face a strong electromagnetic field. The detector measures charged particles, such as an electron multiplier [35], and the abundances of each ion present in a sample are reported.
An advantage of MS is its high sensibility. A detection limit, expressed in concentration units, goes from a mol L−1 to as low as fmol L−1 and surely shall improve as the instruments modernize. For example, the instrument response factor for any individual molecular species detected is essentially identical within experimental error after 13C deisotoping if the analysis is performed properly [34]. Also, MS ion source can act as a separation device if set to selectively ionize just a certain lipid class. Thus, it is feasible to analyze different classes of lipids and individual molecular species with high efficiency without prior chromatographic separation. Nevertheless, depending on the analysis aims, MS can also be combined with a chromatography system, as GC (early mentioned) and liquid chromatography (LC) [35].
Data obtained by MS are displayed as spectra of the relative abundance of detected ions as a function of the corresponding m/z. By correlating the known masses (e.g., an entire molecule) to the identified masses, or through the compounds deposited characteristic fragmentation pattern, MS are used to identify compounds. The MS are also used to determine the elemental or isotopic signature of a sample, the masses of particles and molecules, and to elucidate the chemical structures of molecules [36]. Database platforms, such as LIPIDMAPS, LIPID Bank, LIPIDAT, Cyberlipids, and Lipidomics expertise platform, can help to identify the lipid molecules. Then, interpretation of MS-obtained lipid data must be conducted in accordance with the literature [7].
When assessing the entire lipidome profile, i.e., lipidomics by MS or nuclear magnetic resonance (NMR, detailed later in this chapter), big-data information is generated. Therefore, lipidomics require multistatistic tools for data interpretation. The additional information to MS lipidomics is mapping of the lipid pathway. For example, diacylglycerol is an essential precursor for glycerophospholipid and glycerolipid synthesis in eukaryotes [5].
Manual data interpretation using publicly available databases (i.e., KEGG pathways and the LipidMAPS databases) may add in to lipidomic results and provide meaningful biological context to data understanding from biological point of view. Indeed, using bioinformatics software platform, one can understand the changes in lipid composition and content, and understand adaptive or pathological changes in lipid metabolism. Lipids form networks, which are used to build their inter-relationships and connect them based on known metabolic pathways. Also, these relationships and the determined quantities of lipids are used to calculate the possible contributions to the production of a particular lipid class in the network, and the masses calculated are compared with the masses determined from the lipidomic MS data.
Several parameters involving the metabolic pathways can then be derived from computational simulation, such as those associated with enzymatic activities, as those analyzed by a lipid expertise, i.e., known principles of lipid biochemistry to calculate indexes of fatty acid unsaturation, fatty acyl chain length, or fatty acid precursor/product ratios to gain insight into the function of fatty acid remodeling or other relevant lipid metabolic pathways [5, 37]. Some useful tools that can be used for this purpose are the public platforms MetaboAnalyst (available from
Once lipids have a high discrepancy of m/z within their categories and are susceptible to ion cleavage, the main disadvantage of MS in lipid analysis is that some compounds from a mixture may be determined as the same ion and incorrectly identified. Furthermore, lipid quantification by MS may be weakened by the loss of ion information due to the random collision of lipid molecules that may preclude that all of these get to the detector, the differing abilities of lipid species to form ions and hence varying signal intensity, and the ion-quenching phenomena. The last can occur when the signal from poor ionizing lipids is quenched by more easily ionized species (therefore suppressing the former signal), which is quite avoided by prior separation of lipid species for accurate quantitation or the use of specialized MS [38]. Altogether, these factors result in a loss of sensitivity for some nonpolar lipid metabolites.
It is worth to note that the limitations in identification and quantification of lipid species by MS described above have been minimized with advances of the technique (i.e., target MS). Currently, this analytic tool is considered accurate for characterization of lipids and the most efficient one to assess lipidomes.
In biological assays, lipidomics-MS analysis is highly applied to generate information related to metabolism and biological responses, once several known pathways from metabolic networks in eukaryotes involve lipids as metabolic intermediates (mainly sphingolipids, glycerophospholipids, glycerolipids, and nonesterified fatty acids [NEFAs]) or signaling molecules (mainly oxysterols) [5]. For instance, changes of a lipidome profile can be identified by MS, allowing the interpretation of biological responses to external interferences (i.e., by comparing the lipidome before and after a medication) or enrolled in the pathophysiology of diseases (in comparison with healthy status) [5, 32, 39].
The ionization technique applied is a relevant point to be considered when designing studies for lipid assessment in biological samples using MS. For instance, MALDI can be used to analyze changes of lipid and their metabolites in single genetically identical cells from the RAW264.7 lineage after lipopolysaccharide (LPS) stimulation, using a Fourier transform ion cyclotron resonance mass spectrometer (FTICR MS). MALDI analysis was chosen because single cells on a plate using a histology-directed workflow can increase the number of cells analyzed. Furthermore, the speed of MALDI-IMS enables high spatial resolution and high-throughput single-cell analysis. Combined with the high sensitivity of FTICR MS, hundreds of lipids can be measured from a large population of single cells (>100) in a few hours.
Tandem MS measurements (i.e., through precursor ion scanning and neutral loss scanning experiments) are useful for biological assays requiring the identification of all lipid molecular species. These methodologies are usually better than full scan MS because they apply sequential analyzers and are often associated with a target analysis (i.e., aiming to study a molecule species). This allows high sensitivity and enhanced signal/noise ratio, facilitating the characterization of minor but biologically relevant lipid species [40].
One example of the tandem analysis application is the work of Slatter et al. [41]. By using LC-MS/MS (tandem MS), they were able to characterize the lipidomic network of human platelets, where nearly 200 oxidized species were identified. These minacious data provided by the methodology allowed to display a direct link between innate immunity and mitochondrial bioenergetics in human platelets. Procedures enabling to achieve this conclusion from generated data included the selection of lipids upregulated under thrombin activation and the analysis on temporal dynamics of their generation, monitoring precursor-to-product ion transitions in multiple reaction monitoring (MRM) modes.
Also, through tandem MS, Morgan et al. [42] have proposed a novel role for 12/15-lipoxygenase in regulating autophagy. They have used LC/ESI/MS/MS in a target approach to determine the levels of 1,2-dimyristoyl-sn-glycero-3-phosphoethanolamine (DMPE), 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), 1,2-dimyristoyl-sn-glycero-3-phosphate (DMPA), and 1,2-dimyristoyl-sn-glycero-3-phospho-(1′-rac-glycerol) (DMPG), using comparison technique with internal standards. In addition, the 1,2-dimyristoyl-sn-glycero-3-phosphoserine (DMPS) was determined by product ions and the analysis of cholesteryl esters was performed.
Along with other analytical tools available for lipidome investigations, NMR spectroscopy allows identification of characteristic signals from the different classes of lipids and provides their successful quantification [43, 44]. The technique facilitates the analysis of hundreds of metabolites in a single sample with great advantage because there is no need for a previous sample treatment [8].
The principle of NMR spectroscopy is based on the physical resonance phenomenon in which spin-active nuclei in a strong static magnetic field respond to a perturbation (radiofrequency waves) by producing an electromagnetic signal with a characteristic frequency, which matches magnetic field observed by a given nucleus. This process of resonance happens when the oscillation frequency matches the intrinsic frequency of the nuclei, which depends on the strength of the static magnetic field, the chemical environment, and the magnetic properties of the isotope involved [45].
In a practical way, NMR spectroscopy provides information of the number (integrals) of magnetically distinct atoms (chemical shift of the resonance frequencies and peak splitting due to the coupling constants J or dipolar couplings between nuclear spins in the sample) of the studied isotope and provides all necessary information for determination of the structure of unknown molecules. Several nuclei can be studied by NMR techniques, but the most commonly available ones are hydrogen-1 and carbon-13. The most common experiments for lipid analysis by NMR are 1H, 13C, 31P, and the bidimensional experiments involving 1H-1H and 1H-13C [45].
Usually, an NMR experiment starts with insertion of a liquid sample into the magnet, then, short radio-frequency pulses (from an electronic device named probe) are applied, and all emitted frequencies from the same type of nuclei are registered and reported as signals with a given chemical shift, multiplicity, and intensity. Also, multidimensional NMR as well as solid-state NMR has emerged to provide additional and relevant information on sample composition [45].
Also, the exact ratio of specific fatty acids in the lipid samples and their iodine values could be calculated considering integral values corresponding to characteristic peaks with the help of the corresponding spectral information and the existing references [46]. This type of experiment works as a relative quantification. Absolute and relative quantification experiments by NMR are possible; however, it is necessary to take care of some precautions. Direct quantitative information by NMR is due to the fact that the signal intensity of each resonance in the NMR spectrum is directly proportional to the number of spins associated with the particular resonance [38]. Thus, no standard with chemical similarity to the studied compounds is required as in other analytical methods; however, one certified standard must be used. This can be performed through relative quantification using ERETIC. For absolute quantification also, a certified standard is required now as an internal standard in a known concentration. For both methods, the pulse sequence needs to be calibrated to 90° to be sure that the spectral response is completely real, and it means that the longitudinal relaxation time (T1) of spins is entirely returned [38]. Typically, this is achieved by waiting five times the longest T1 (at five times T1 approximately 99.3% of the equilibrium value is re-established) between two scans.
Proton magnetic resonance spectroscopic imaging (1H-MRSI) has a major role in lipid assays, mainly used in the medical area with extreme importance for in vivo sampling. Both profiling and ratio quantifications are possible by the obtained spatial resolved spectra. The presence of so many compounds in living biological samples may require water or other signal suppression experiments to be performed in order to obtain better resolution on the target metabolites. The same approach is used in NMR samples but with greater implications due to lack of sample pretreatment [47].
Compared to the MS method, NMR technique is less sensitive and limited by the overlapping of signals in either, 1H NMR or 31P NMR, and also by the low natural abundance of 13C for 13C NMR. On the other hand, NMR is a nondestructive sample technique that allows a high analytical reproducibility, an easy identification of molecular moieties, and with relatively easy to get information on molecular dynamics [8, 38]. Furthermore, NMR does not require a standard curve or molecule species for quantitative measuring. Therefore, this technique has been emerging as a promising approach for more accurate and faster quantitative analysis of lipids than other analytical methods [38]. Also, the sensitivity improvement of cryogenic probe in an equipment of 800 MHz LC-NMR is very promising in analysis of a trace amount of lipids in a faster experiment, once it is able to acquire 1H NMR spectrum of approximately 1 μg sample within 30 min, whereas the current 500 MHz NMR needs 20 h or longer [38].
A wide variety of NMR experiments (e.g., HSQC, HMBC, TOCSY, etc.) besides the classics 1H, 13C, and 31P NMR are being used to solve a variety of biological issues where biofluid samples such as serum, plasma, urine, cerebrospinal fluid (CSF), etc., are being investigated. More commonly used are 1H, 13C, and 31P NMR experiments, which bring rich information on lipid profiling, for example, molecular identification of fatty acid chains and phospholipid structures. Furthermore, heteronuclear and multidimensional experiments can be used to elucidate lipid profiling information by signal interpretation and also using comparisons with databases. The 13C NMR is also a complementary tool that can be used for fatty acyl residue identification [38].
Once NMR allows the noninvasive lipid analysis in intact cells and tissues, the technique prevents losses of chemical information in the analyte environment. This fact, together with the high sensibility of NMR to molecular dynamics (in timescales from picoseconds to seconds), enables to investigate changes in lipid and dynamic structures in biochemical cell functionalization. The experiment used for this application is the diffusion ordered spectroscopy (DOSY), which enables to separate signals according to their diffusion coefficients and then add chromatography-like capabilities to NMR [38, 48].
Lipoproteins consist mainly from cholesterol esters and triacylglycerols surrounded by a hydrophilic layer, which comprehend phospholipids, cholesterol, and proteins [8]. Lipoproteins perform the lipid transportation in blood circulation through the exogenous (dietary lipids) and the endogenous (liver-synthetized lipids) channels. The endogenous transportation begins in the liver through the production of a very low-density lipoprotein (VLDL). After being secreted into the bloodstream, VLDL interacts with other lipoproteins, through collisions, in which the contact with the high-density lipoprotein (HDL) is highlighted.
Kostara et al. [49] have found how blood lipoproteins influence the progression of coronary heart disease (CHD) by comparing the lipid profiles of atherogenic (non-HDL) and atheroprotective (HDL) lipoproteins from patients with CHD with those from patients with normal coronary arteries (NCA). They analyzed the lipid extracts of these lipoproteins using 1H NMR experiments and statistical analysis and identified the potential target-lipid biomarkers for the early evaluation of the CHD onset. Furthermore, Lopes et al. [50] were able to find that circulating HDL increases, and LDL and VLDL decrease in obese patients after bariatric surgery by using DOSY experiments to monitor these lipoproteins. Notably, lipoprotein investigations and quantitative analysis of lipids can be performed using NMR of the same sample [51].
Also, selective recoupling of dipolar and chemical-shift interactions removed by magic-angle spinning NMR in the solid state allows the characterization of regulatory interactions, dynamics, and ion channels within biological membranes [52].
In this scenario, the NMR application has contributed to obtaining of important data on the structure and turnover of lipid species and the composition of lipids in cells, and to characterize pathways enrolled in lipid synthesis/transport and degradation [53, 54]. Also, the high-resolution magic-angle spinning NMR (HR-MAS NMR) has been applied to global lipidomic studies [52].
Besides the identification of lipid species and dynamics, NMR can be used for reliable quantification of lipid mixtures obtained from tissues, body fluids, and cell cultures [40, 55]. It can be allied to the bioinformatic tools available to a better quantitative analysis of lipid profiles [56]. For instance, using 1H NMR and 31P NMR, Fernando et al. [57] were able to identify an over-accumulation of lipids associated with the pathophysiology of ethanol-induced liver steatosis accompanied by mild inflammation.
Also, quantification can be used in magnetic resonance imaging (MRI) experiments as Vafaeyan et al. [47] have shown. They have used a time-domain quantification method namely as subtract-QUEST-MRSI algorithm to quantify alterations of the biomarkers, i.e., lipids and other metabolism molecules species such as choline, creatine, N-acetyl aspartate, lactate, myo-inositol, and glutamine in multiple sclerosis subjects in comparison with control group. This research aimed to know how lesion biomarker ratios in multiple sclerosis have affected human brains, through the imaging of different brain areas, which could present lesions.
Other MRI works have found that on brain imaging, lipids tend to be an almost undesired artifact, and consequently, scientists may use the approach of selective signal suppression pulses such as adiabatic frequency selective, spatial-spectral lipid suppression, or broadband outer volume suppression bands [58]. Trauner et al. [59] have used a dynamic saturation transfer technique in MRI experiments to assess dynamic Pi-to-ATP exchange parameters in nonalcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) aiming to report alterations of hepatic lipid, cell membrane, and energy.
Lipids per se exert several relevant biological functions making the single knowledge of the lipidome profile from a biological sample highly informative by itself. For instance, sphingolipids and glycerophospholipids are important components of the cell membrane and then can affect several cellular functions. Disorders of sphingolipid metabolism are associated with lysosomal storage diseases and of lysoglycerophospholipid by phospholipase A2 activation are associated with lipotoxicity and inflammation. Accumulation of triacylglycerol (a glycerophospholipid) is associated with lipotoxicity and insulin resistance, and the NEFA profile is a useful indicator of lipid metabolism and can add to understanding on molecular mechanisms underlying the metabolic syndrome [5].
Therefore, lipidomic tools are particularly useful to identify and understand changes in metabolic pathways and the underlying mechanisms enrolled in the pathophysiology of human health, such as metabolic diseases. One practical example is data from Meikle et al. [60] study that measured 259 lipid species in plasma samples from prediabetic, diabetic and normal glucose tolerant patients, including sphingolipids, phospholipids, glycerolipids, and cholesterol ester. The authors used electrospray ionization-tandem mass spectrometry in previous precursor ion and neutral loss scans on control plasma extracts, MRM experiments for the major species of each lipid class identified in plasma, and quantification using internal standards. These approaches highlighted that metabolic pathways altered in type 2 diabetes include a deregulation of lipid homeostasis, characterized by abnormal plasma-free fatty acids accumulation.
In lipidomic studies, beyond the care of equipment calibration and accuracy of the experiments, special cares of analytical procedures must be planned to have accurate information of data. The statistical recourses are necessary to process the data, but, also lipid knowledge is required for correct interpretation in all cases. The choice of the most suitable lipidomic tool to be used for a specific biological assay is closely linked to the study aim. Next-generation techniques (MS and NMR) can provide detailed lipid information to assess more elaborated scientific questions. However, thousands of individual lipid molecular species are present in cells implying that no single technique can effectively study all the lipid species [38]. When possible, combining techniques can be the best choice, because one can compensate for the limitation of the other, and bring complementary information and/or can validate the previous analysis data.
Usually, combined lipidomic techniques are applied for data validation. For instance, data obtained by shotgun lipidomics (direct infusion MS) can be validated using LC-MS-based analyses and vice versa. Other methods, including NMR, or chromatography-based analysis might be used to validate the total lipid content of a lipid class [5]. However, the combined use of lipidomic techniques can also be useful to improve the data information on the lipids from biological samples. For instance, to assess lipid changes during the response of hypoxia stress to a treatment in cervical cancer-derived cells (HeLa cells), Yu et al. [40] applied NMR technique for the phospholipid profile analysis and MS for phospholipids characterization. Also, Whiley et al. [61] investigated the plasma phosphatidylcholine metabolism using NMR and MS to obtain a fingerprint of three phosphatidylcholines (PC) molecules that significantly decrease in individuals with Alzheimer’s disease compared to healthy controls. Then, LC-MS and NMR were used for phosphatidylcholine and fatty acyl side chain validation and for total plasma choline validation, respectively. The study of Whiley et al. [61] illustrates the scientific value in combining different lipidomic tools to obtain complementary information and reinforce validation of the obtained data.
In conclusion, all available tools for lipidomic studies in biological samples have several advantages and limitations that can be overcome when combining more than one technique. Because this practice involves the availability of complex technologies and skilled labor, it is not always possible. In this scenario, the use of mass spectrometry alone can be the best alternative currently available when technique combination is impossible. However, NMR has a high potential and, in the future, may be expected to answer issues that MS is quite limited to do.
This research counted on grant received from the Brazilian agency—Fundação de Amparo à Pesquisa do Estado de São Paulo—FAPESP (Sao Paulo Research Foundation, grant number 2018/06510-4).
Authors declare no conflict of interests.
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