*Review* **Research Advances on Health Effects of Edible** *Artemisia* **Species and Some Sesquiterpene Lactones Constituents**

**Antoaneta Trendafilova 1,\*, Laila M. Moujir 2, Pedro M. C. Sousa 3 and Ana M. L. Seca 4,5,\***

**Abstract:** The genus *Artemisia*, often known collectively as "wormwood", has aroused great interest in the scientific community, pharmaceutical and food industries, generating many studies on the most varied aspects of these plants. In this review, the most recent evidence on health effects of edible *Artemisia* species and some of its constituents are presented and discussed, based on studies published until 2020, available in the Scopus, Web of Sciences and PubMed databases, related to food applications, nutritional and sesquiterpene lactones composition, and their therapeutic effects supported by in vivo and clinical studies. The analysis of more than 300 selected articles highlights the beneficial effect on health and the high clinical relevance of several *Artemisia* species besides some sesquiterpene lactones constituents and their derivatives. From an integrated perspective, as it includes therapeutic and nutritional properties, without ignoring some adverse effects described in the literature, this review shows the great potential of *Artemisia* plants and some of their constituents as dietary supplements, functional foods and as the source of new, more efficient, and safe medicines. Despite all the benefits demonstrated, some gaps need to be filled, mainly related to the use of raw *Artemisia* extracts, such as its standardization and clinical trials on adverse effects and its health care efficacy.

**Keywords:** *Artemisia*; clinical trials; health effects; adverse effects; anticancer; antiparasitic; artemisinin; santonin; achillin; tehranolide


**1. Introduction**

Environmental pollution and the increasing awareness of limited resources have been a major driver in finding renewable alternatives to replace traditional fossil-based plastics, with bio-based materials (for ex., biocomposites) derived from carbon-neutral feedstocks [1]. Natural fibres have various advantages, including good mechanical properties, no emission of toxic substances, and reduction in cost [2]. Additionally, natural fiber-reinforced biocomposites have attracted increasing attention due to several beneficial properties, e.g., low-cost, good mechanical properties, and lightweight.

Poly (lactic) acid (PLA) is a promising biopolymer which has been introduced commercially as a renewable alternative to fossil-based polymers [3,4]. A number of promising PLA-based products are presently found commercially, such as automotive parts [5]. PLA provides good mechanical properties and relatively easy melt-processability. However, PLA is relatively expensive and some properties (e.g., brittleness) limit the utilization of PLA in some applications [6]. Therefore, additional polymers can be used in PLA blends in order to tailor the properties of the final products [7]. Moreover, some alternatives have been suggested to improve e.g. the mechanical and thermal properties, including the addition of fibre or filler materials [8] and cellulose nanofibres [9].

Lignin as the second most abundant renewable bio-resource, next to cellulose, is considered as a waste product in several industrial processes. Attempts for lignin valorisation have been published in a vast number of papers and reviews over the last years [10–12].

The notable properties of lignin, such as highly abundance, low-cost and biodegradability, high carbon content, high aromaticity, and reinforcing capability make it a good candidate as a potential component for biocomposites [13]. Each year, over 50 million tons of lignin are produced worldwide as a side product from biorefineries, of which 98% are burned to generate energy. Only 2% of the lignin has been used for other purposes, mainly in applications such as dispersants, adhesives, and fillers [14–17]. The commercial lignin is mainly lignosulfonates from sulphite pulp mills (about 1 mill. tons/year) and less than 100,000 tons/year of kraft lignin [18]. Since lignin has lower energy content than coal and because lignin-rich side streams are wet, the energy value is limited to 50 US Dollar/dry ton [19]. Thus, cost-efficient valorisation of lignin into value-added products offers a significant opportunity to enhance operational efficiency and generates additional revenue so that the production of bioethanol or other products from the hydrolysed carbohydrates becomes more competitive. However, lignin properties (for ex., high heterogeneity and complex structure), make it difficult to predict how the lignin loading will affect the properties of a given biocomposite. Recent reviews summarized the research done on lignin-reinforced thermoplastic biocomposites [20,21].

Lignin can be used as a component in biocomposites, with or without modification, depending on the target application. Gordobil et al. [22] acetylated kraft lignin to improve the affinity with PLA. However, incorporation of kraft lignin decreased the tensile strength properties of the PLA with increasing lignin loading of 10 wt % and 20 wt %. Furthermore, when acetylated lignin was blended with a thermoplastic the tensile strength was improved [21,22]. Without modification, lignin can be directly incorporated into a polymeric matrix, such as UV-light stabilizer, antioxidant, flame retardant, plasticizer, and flow enhancer to reduce production cost, reduce plastic, and potentially improve material properties [23–26].

Lignin can also be used as a coupling agent in natural fibre biocomposites. Lignin can act as a compatibilizer between the hydrophilic fibres and hydrophobic matrix polymer, thus strengthening the fibre matrix interface [27–29]. Lignin treatments of hemp fibres [28] and flax fibres [27] have been shown to improve compatibility between fibres and the thermoset matrix, thus also improving the mechanical properties of the biocomposites. Graupner [29] reported increased tensile properties of compression-moulded PLA-cotton composites when the fibres were treated with lignin.

In our study, lignin was extracted by a soda process. Soda pulping pre-treatment is similar to that of alkaline pulping process, which uses alkali (e.g., NaOH, Ca(OH)2) to solubilize or depolymerize lignin, and make lignin extractable from biomass matrix [30]. Soda pre-treatment disrupts the lignin structure and breaks the aryl-ether, ester, and C-C linkages among the lignin and hemicelluloses and hence open up the lignocellulose structure [31]. This process has mainly been studied on herbaceous biomass and to some extent hardwood [12,32,33]. The main difference of this process compared to the chemical pulping process is the moderate treatment severity, separating lignin with low condensation structure [19]. The soda process for obtaining lignin has some essential advantages from the environmental point of view in comparison with the sulphate process, namely, the soda cooking liquor has a lower content of low molecular products of wood degradation, which get to waste water, and the formation of the unpleasant sulphur organic compound odorants is prevented [34]. Soda lignin has found application in multiple areas: the production of phenolic resins [35,36], animal nutrition [37], dispersants [38], and synthesis of polymers [39]. A major difference between soda lignin compared with kraft lignin and lignosulphonates is that soda lignin is sulphur-free, without odour and with a chemical composition closed to pure lignin [38,39]. Additionally, soda lignin derived from non-wood plants contains a larger fraction of carboxyl groups and p-hydroxyl units [39].

Three-dimensional (3D) printing has evolved rapidly in recent years. This technology allows the production of unique, complex and customized structures by digitized and computer assisted processes, reducing production time and costs [40]. In addition, less waste in production and lower chemical

consumption is required by this technique in comparison with the traditional processing manufacturing. Fused deposition modelling (FDM) is one of the most used 3D printing technologies, which consists in the melting of thermoplastic materials at high temperature, which are solidified when cooling. Currently, there is great interest in the use of biomass and biomass components for use in 3D printing by FDM. However, unlike petroleum-derived thermoplastic compounds, lignocellulosic components are di fficult to melt for the extrusion and injection moulding processes. Therefore, the development of new materials from biomass suitable for 3D printing is a challenge [41–43]. The production of pure lignin composites is limited by its high thermal transition temperature and high flow resistance [40]. For this reason, lignin is mixed with other polymers that favour its melting behaviour and flow. Recently, organosolv hardwood lignin [40] and kraft softwood lignin [44] have been applied to manufacture filaments for FDM, based on acrylonitrile-butadiene-styrene and PLA polymers, respectively.

The purpose of this study was to demonstrate the suitability of PLA/soda lignin biocomposite filament for 3D printing. A motivation for selecting soda lignin is that it is sulphur-free. Soda lignin was thus expected to reduce the typical smell that is experienced when melt-processing biocompounds containing kraft lignin or lignosulfonates. Thus, samples with varying PLA/soda lignin weight ratios were manufactured and the mechanical (tensile testing), thermal (TGA, DSC analysis), morphological (SEM), FTIR, X-ray di ffraction, and antioxidant properties were assessed.

#### **2. Materials and Methods**

## *2.1. Raw Materials*

The lignin used in this study is a softwood lignin extracted from cooking liquor, using a soda cooking process of Norway spruce chips, collected from Norske Skog, Skogn, Norway. The PLA used in this study was a commercial grade for 3D printing (Ingeo PLA 3D850, NatureWorks LCC, Minnetonka, MN, USA).


**3. The hijab as an invitation**

substance, while to receive something is to receive a part of someone's spiritual essence' [3]. The process of gifting and counter-gifting involves not mere economic exchange but rather 'a pattern of spiritual bonds between things which are to some extent parts of persons' [3]. As the spiritual presence of the person who originally gave the gift resides within and lingers around it, then the gift received is owned by the receiver, 'but the ownership is of a particular kind', for the gift retains strong traces of the personal charisma of the person who first offered it. For Mauss, this shows that the gift is a complex of different properties which modern, Western thought usually separates from each other: it is simultaneously both 'property and a possession, a pledge and a loan, an object sold and an object bought', among

In other words, a received gift is not a mere object; it is a powerful reminder of someone else, and most likely of the social group that stands behind them too. Wearing such an object, then, is a potent and embodied reminder of the desires of the donor and of the group to which s/he belongs. To wear a gift garment is to acquiesce, at least to some degree, in the intentions of the donor and their social group. By wearing such a garment, I start to resemble, to some degree, the image that the donor and their group have of me, or the image which they want

Any object can potentially take on the special qualities of a gift; it just must be given to a recipient in the spirit of gift exchange. As Mauss puts the point, 'everything is stuff to be given away and repaid … [thus becoming] a perpetual interchange of what we may call spiritual matter' [3]. So deeply can objects be invested with special significance by both donors and receivers, that for those in a gift-giving chain these objects can come to seem to have 'a virtue of their own which [itself seems to] cause … them to be given and [in turn] compels the making of counter-gifts' [3]. In essence, once objects become gifts, those 'things have personality', [3] and are felt to have a special sort of resonance and charisma. They possess both the traces of the personality of the individual donor, and of the group to which s/he belongs. For example, a Bible given by a grandmother to a grand-daughter resonates with the personality not only of the esteemed elderly relative but also, because it is an explicitly religious object of the Christian church, community and belief system to which the grandmother belongs and subscribes. The Bible-gift seeks to pull the child into the ambit of the religious community of

We can note here that some authors have pointed to the especially strong bonds between women, whether as relatives or as friends, that can be created through gift-giving processes [14]. We can add that certain objects will be defined by particular groups as being especially worthy of being given as gifts. Weiner's extension and critique of Mauss's original formulations notes that hand-made objects, especially those made by donors themselves, operate as particularly powerful gifts, as they very deeply embed the personality of the maker-donor into the material fabric of the object. Objects that are not made by donors, but which are framed by donors as having been very carefully selected and sought out by them for the

Objects that a given community regards as especially spiritual are also likely to operate as particularly potent gifts. An object already defined as somehow spiritually *special* is particularly

which the more senior woman feels herself to be part and representative of.

recipient, can also take on strong traces of the donor's personality [15].

other things [3].

160 Socialization - A Multidimensional Perspective

me to have.

Aisha2 , a Finnish woman in her mid-20s, converted to Islam at the age of 18. Having grown up in a small Finnish town, she now lives in Helsinki, the capital city, and studies at a university. Soon after her conversion, she arranged her marriage to an Arab man through her religious community, and they now have one child. Aisha's views and dress choices – a full-length khimar3 and previously also the niqab4 – reflect a conservative interpretation of Islam, and she regularly visits a mosque that some other Finns consider 'Salafi-influenced'. Aisha is very articulate and critical of what she considers the cultural and commercial objectification of the female body in Finland and in 'the West' more generally.

2 All names of the interviewees have been changed.

3 Khimar refers to a head-covering, initially worn by both women and men. By the 1980s, khimar had come to mean 'a headcover that covers the hair and extends low to the forehead, comes under the chin to conceal the neck, and falls down over the chest and back'. [17] Khimars come in different lengths: below the hips, down to the knees, and full-length with sleeves.

4 Niqab is an Arabic face-veil, 'a free-flowing piece of black cloth of various lengths that covers the lower part of the face'. [18] It typically leaves the eyes visible, although there are niqabs that can be used to cover the eyes as well. More recently, niqabs have been available in a variety of colours.

Aisha told the interviewer how she, after reading the Qur'an and believing it to be 'the truth', learned more about the practicalities of Islam. Through an internet discussion forum, she made the acquaintance of a Somali Muslim woman of her own age, and learned more about everyday life as a Muslim.

interviewer visited his wife. Nura wears the long khimar and the niqab, and believes that others should do so too. While she stressed that the wearing of the hijab should be everyone's own personal choice, she also stated that she is 'advising' her younger sister to conform to more conservative dress styles, which the sister apparently resists. This kind of pressure was fairly common in this community, and was not considered to be in any sort of conflict with the

The Hijab as Gift: Mechanisms of Community Socialisation in the Muslim Diaspora

http://dx.doi.org/10.5772/intechopen.74649

163

In this regard, garment gifts may also serve the purpose of encouraging the wearing of a certain kind of hijab, and thus fostering the 'right' kind of representation of the religious and ethnic community. Such gifts are given under specific conditions, and usually follow the receiver's desire to change her dress (and the giver's desire to support her decision), rather

*Just this summer I gave up a scarf I've worn for many, many years. It was very dear to me… But… in my opinion it was useless to leave it in the closet; I got a migraine and I couldn't [wear it]. Someone else wanted to start [wearing] the [khimar], which is a great thing if another Muslim wants to cover herself*

Thus, giving away a garment to which she had an emotional bond was justified for Nura for two reasons: her inability to wear it (negative reason), and the other woman's need for it (positive reason – it encourages a deeper level of Islamic observance). Here, she practices a certain level of sacrifice, which is discussed in more detail below. The gift signified her encouragement and acceptance of the other woman's choice to 'cover more', as well as materially making that more possible and more likely. Such gifts are not simply about linkages between individuals, but are also about the expressing, forging and maintaining of networks within the ethnic/religious community [3]. The gift works as an invitation for a particular woman to be included in a particular group of veiling women, which in turn pulls her into the orbit of the religious norms of the broader community to which that particular group

Miriam, a Finnish woman in her late 20s, had a very different conversion story. She also dresses very differently from Aisha, preferring long skirts, long-sleeved tops and a small scarf that covers her hair but not her neck. Converted 2 years prior to the time of the interview, she had no connection to any local Muslim communities, and her only Muslim contacts were her Arab husband and his family, who live abroad. Miriam has one child, and is practically a single mother in her husband's absence. She tells the history of her scarf-wearing as follows:

*In Finland, I've worn this kind of a scarf [a small scarf covering most of the hair and the ears but not the neck] since the spring… It was actually because in 2010 we visited Jordan and I wore there for the first time the full scarf and the family saw me wearing it… Then [my husband's] brother came to visit [Finland]… and when I heard he's coming and thought that they've seen me with the scarf and I kind of can't appear with them without the scarf so I started wearing this… I couldn't imagine myself any*

requirement that wearing the hijab be 'freely chosen'.

*more. I was very glad [and] I gave it to her.*

**4. The hijab as connection-maker**

*more without a scarf in front of the family.*

subscribes.

than as a general encouragement for veiling. As Nura explained,

*I visited her a couple of times and she showed me how to pray and gave me a scarf and then an abaya. … So, I actually started to wear them and pray before I had said Shahada [the declaration of belief].*

As Muslim women are required to veil when praying, such garment gifts have a practical value for the new convert when she learns to pray and to integrate her new religion into her daily life routines. The gift serves the purpose of encouraging her to veil and operates as a welcome to the community.

Such gifts are often easily given and considered neither too personal nor too valuable to accept. They are typically bought cheaply from sources outside Finland, and as commodities operate in the cheaper end of globalised fashion systems. However, as Mauss reminds us, a gift is normally given and received under obligation, and in the process of gift-giving, it turns from mere commodity into something more spiritual and socially meaningful. In this case, the scarf and the abaya can be seen as a covert attempt to convert someone (or at least to encourage their conversion), and one of the gift's purposes is to bind the receiver, if not to the gift-giving individual per se, then to the Muslim community as a whole through a sense of gratitude and obligation to return the favour. New converts who are on the receiving side are expected to contribute back to the community, which the original donor represents, later on. Rather than creating a bond between two individuals, the gift therefore aims to create a bond between an individual and the community, imposing certain expectations with regard to appearance and behaviour onto the potential convert woman.

There has been a significant shift in Somali interpretations of Islam as the Somali diaspora has spread across the world. While many of the older generation are Sufist, many of the younger generation are influenced by trends of the global Islamic revival, and particularly those actively marketed by Saudi Arabia [19]. Many young Somalis are also involved in Da'wah ('calling to Islam'). This is a form of missionary work, which targets both non-Muslims and also Muslims deemed to be not the 'right' kind of believers and religious practitioners. Popular among various Arab populations and, in the US especially, black converts to Islam, Da'wah work is sometimes associated with conservative (or even radical) views of Islam. In Aisha's case, the presumed intention of the original donor bore fruit: Aisha is now a moral leader with conservative religious views, and lectures to other young Finnish converts to Islam. She has been successfully socialised into a religious community, and the original garment gifts she received some years ago played an important role in this regard.

The following story exemplifies the nuances within the Finnish Somali community with regards to interpretations of Islam. Nura is a Somali Muslim woman in her mid-20s. She arrived in Finland as a teenager and is married to a Somali man from her own clan. The marriage was arranged by their families, and both spouses share Salafi-influenced views of their religion. The interviewer was passed leaflets to that effect from the husband when visiting their home, but never actually met him in person as he firmly stayed in his room when the female interviewer visited his wife. Nura wears the long khimar and the niqab, and believes that others should do so too. While she stressed that the wearing of the hijab should be everyone's own personal choice, she also stated that she is 'advising' her younger sister to conform to more conservative dress styles, which the sister apparently resists. This kind of pressure was fairly common in this community, and was not considered to be in any sort of conflict with the requirement that wearing the hijab be 'freely chosen'.

In this regard, garment gifts may also serve the purpose of encouraging the wearing of a certain kind of hijab, and thus fostering the 'right' kind of representation of the religious and ethnic community. Such gifts are given under specific conditions, and usually follow the receiver's desire to change her dress (and the giver's desire to support her decision), rather than as a general encouragement for veiling. As Nura explained,

*Just this summer I gave up a scarf I've worn for many, many years. It was very dear to me… But… in my opinion it was useless to leave it in the closet; I got a migraine and I couldn't [wear it]. Someone else wanted to start [wearing] the [khimar], which is a great thing if another Muslim wants to cover herself more. I was very glad [and] I gave it to her.*

Thus, giving away a garment to which she had an emotional bond was justified for Nura for two reasons: her inability to wear it (negative reason), and the other woman's need for it (positive reason – it encourages a deeper level of Islamic observance). Here, she practices a certain level of sacrifice, which is discussed in more detail below. The gift signified her encouragement and acceptance of the other woman's choice to 'cover more', as well as materially making that more possible and more likely. Such gifts are not simply about linkages between individuals, but are also about the expressing, forging and maintaining of networks within the ethnic/religious community [3]. The gift works as an invitation for a particular woman to be included in a particular group of veiling women, which in turn pulls her into the orbit of the religious norms of the broader community to which that particular group subscribes.


**1. Introduction**

[17] Adewole SO, Salako AA, Doherty OW, Naicker T (2007). Effect of melatonin on car‐ bon tetrachloride-induced kidney injury in Wistar rats. Afr*. J. Biomed*. *Res.,* 10:

[18] Arun K and Balasubramanian U (2011).Comapartive study on hepatoprotective ac‐ tivity of *phyllanthus amarus* and *eclipta prostrata* against alcohol induced in albino rats.

[19] Gnanadesigan M, Ananad M, Ravikumar S, Maruthupandy M, Syed Ali M, Vijaya‐ kumar V, Kumaraguru AK (2011).Antibacterial potential of biosynthesized silver

[21] Krithika R and VERMA R J (2009). Ameliorative potential of phyllanthus amarus against carbon tetrachloride-induced hepatotoxicity. Acta Poloniae Pharmaceutica ñ

[22] Snedecor GW, Cochran, WG (1989).Statistical method.8th edition Ames,IA:Affiliated

[23] Rajeshkumar NV, Joy KL, Kuttan G, Ramsewak RS, Nair MG, Kuttan R (2002). Anti‐ tumour and anticarcinogenic activity of Phyllanthus amarus extract. J Ethnopharma‐

[24] Narah M, Kalita JC, Kotoky J (2012). Medicinal plants with potential anticancer activ‐

ities: a review. International Research Journal of Pharmacy.3 (6)

nanoparticles using *Avicennia marina* mangrove plant, Applied Nanoscience.

International journal of environmental sciences volume 2:1.

[20] Gao H, Zhou YW (2005).World. J. Gastroenterol.11, 3671.

Drug Research, 66(5)-579-583.

294 Pharmacology and Nutritional Intervention in the Treatment of Disease

east-West Press;217-36.

col.81(1):17-22.

153-164.

Cancer is the leading cause of death in economically developed countries and the second leading cause of death in developing countries (WHO)1 . It is extraordinarily complex with novel mutations and phenotypes that are often unique to an individual. It is a disease of the chromosomes and the problem is, in almost all cancers, it isn't just one mutation but may be much more. Cancer may be regarded as a complex metabolic deficiency disease [9, 10, 11, 12, 13, 14]

Cancer diet is also used as a complementary approach to cancer that involves the use of special nutritional supplements. Selenium (Se) and cancer is a term that can be referred to the approach or associations between cancer and nutrition that is to lower an individual's risk of cancer. Selenium was first recognized as having some nutritional importance almost six decades ago [15]. Selenium is found in food as selenoamino acids or selenoproteins, and as selenide, selenite, or selenate [16]. Selenium is a critical cofactor in the activity of gluthathione peroxidase and is also important in the management of peroxynitrite. The selenium content of food depends upon soil content and varies regionally and nationally, with soil levels relatively low in most European countries [17, 18, 19]. Soil conditions have been associated with clinical selenium toxicity in animals (selenosis) in some areas with very high selenium content, and with selenium deficiency syndromes in animals and humans in areas of low soil selenium [17].

Selenium is essential nutrient that act as cofactor in enzyme oxidation–reduction reactions (e.g. iodothyronine deiodinase and glutathione peroxidases) [20]. It maintains the specific config‐ uration of proteins, is incorporated into the structure of hormones, and plays a structural and catalytic role in gene expression and transcriptional regulation. The trace element selenium is contained in soil and drinking water varies from area to area, which determines the variation in intake seen in different communities and the amount and chemistry of dietary constituents

© 2014 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

eaten with the this element affect the absorption efficiency of the selenium is said be 'the only trace element to be specified in the genetic code' [21].

of redox signalling, redox being a term used for reduction and oxidation. Healthy cells and also malignant ones benefit from intact Keap1/Nrf2 signalling, making a dysregulated hydroperoxide signaling a plausible explanation for the increased cancer risk in selenium deficiency [42]. Therefore, a research agenda to investigate the synergistic operation of such

The Pharmacology and Biochemistry of Selenium in Cancer

http://dx.doi.org/10.5772/58425

297

Cancer is a generic term for a large group of diseases that can affect any part of the body and it can exist in many different forms and types, some of which are brought on by the destructive choices people make while others are less predictable and are not the result of destructive decisions. It can be broadly grouped into different types (Carcinomas, Sarcomas, Lymphomas and Leukaemia's), depending on which tissues they come from [43, 44]. Cancer develops when cells multiply in the presence of oxidation and other damage. According to micro-evolutionary models, cells become damaged and change their behaviour, growing uncontrollably, and act like the single-celled organisms from which they originally evolved. The cancer cells' indi‐ vidualism overwhelms the cooperative control processes that are essential to a complex multicellular organism [45, 46]. As cancers become malignant, they exhibit incredible genetic diversity.  At this late stage, some (but not all) antioxidants can indeed promote cancer cell growth. Thousands of different cell types coexist: cooperating, competing, and struggling to survive. A consequence of the anaerobic conditions that prevail during the early development of a malignancy is that cancer cells differ from healthy cells, in that they have been selected for the way they generate energy (i.e. anaerobically, using glucose) [47, 48].

The sulfhydryl group is the most sensitive to the oxidizing effects of ROS among the amino acid side chains in protein; it is often involved in the intracellular transduction machinery of redox signals in response to physiological and oxidative stimuli. In fact, a variety of biological functions, not directly related to peroxidase activity, have also been reported for the Prx family [49]. Oxidative damage in DNA can cause cancer. Several antioxidant enzymes such as superoxide dismutase, catalase, glutathione peroxidase, glutathione reductase, glutathione Stransferase etc. protect DNA from oxidative stress. It has been proposed that polymorphisms in these enzymes are associated with DNA damage and subsequently the individual's risk of

Nutrition and physical activity and major lifestyle changes can reduce the risk of cancer [51, 52]. Antioxidants are becoming an increasingly common choice as a hopeful cancer prevention agent. Importantly, antioxidants limit oxidative damage and thus inhibit early benign cancer growth, preventing cancer from developing. Selenium has received publicity over the past decades based on some confusing and contradictory research about whether low-selenium diets are implicated in cancer risk. To date, this is still a question without a clear answer. However, selenium is required for the proper activity of a group of enzymes collectively called glutathione peroxidase. Each of these enzymes helps to turn toxic hydrogen peroxide into

substances in cancer treatment is required.

**3. Cancer and oxidation**

cancer susceptibility [50].

Selenocysteine is a vital component of 35 or more selenoproteins, some of which are important enzymes [22]. Selenium functions as a redox centre, an example of which is the reduction of hydrogen peroxide and lipid and phospholipid hydroperoxides to nondamaging water and alcohols by the glutathione peroxidases [23]. Functions of this kind help maintain membrane integrity, and protect prostacyclin production. Prevention of the oxidative chain reactions in this way prevents further damage to lipids, lipoproteins, and DNA; hence its antioxidant function helps prevent atheroma and cancer, among other things [24, 25, 26].


*Article* **Comparative Assessment of the Stability of AHP and FAHP Methods**

**Irina Vinogradova-Zinkeviˇc 1 , Valentinas Podvezko 2 and Edmundas Kazimeras Zavadskas 3,\***

**Abstract:** Mathematical models describing physical, technical, economic, and other processes can be used to analyze these processes and predict their results, providing that these models are stable and their results are stable relative to the model parameters used. Small changes in the values of the model parameters correspond to small changes in the results. Multicriteria decision-making models need to check the results' stability against the models' main components: the values of the criteria weights and the elements of the decision matrix. In this article, we study the stability of models associated with the calculation of criteria weights. For the analysis, the most commonly used models are taken—the Analytic Hierarchy Process (AHP) method and the fuzzy Analytic Hierarchy Process (FAHP) method, in which fuzzy numbers are used under conditions of data uncertainty. Both mathematically well-based methods verify the consistency of the expert evaluations. The method of statistical simulation (Monte Carlo) is the basis for studying the results' stability. The study checks the experts' provided evaluations' consistency, calculates the criteria weights, and evaluates their relative errors after a slight change in the estimates of the pairwise comparisons of the criteria provided by the experts. The matrix of comparisons of the FAHP method is constructed based on the entire expert group's assessments. It estimates the boundaries of variance in the fuzzy criteria weights. This paper estimates the stability of the criteria' weights associated with the mathematical methods themselves and the experts' estimates. The results are useful to study the stability of specific MCDM methods when ranking alternatives.

**Keywords:** Analytic Hierarchy Process; fuzzy Analytic Hierarchy Process; symmetric and asymmetric fuzzy numbers; uncertainty; stability


**Author details**

Paulo Santos1,2,6\*, Pedro Teixeira3,4,6, Helena Beça5,6 and Alberto Hespanhol1,2,6

1 Department of Medicine of Community, Information and Health Decision Sciences, Faculty of Medicine, University of Porto, Portugal

2 CINTESIS, Center for Health Technology and Services Research, University of Porto, Portugal

3 ICVS/3B's, PT Government Associate Laboratory, Life and Health Sciences Research Institute (ICVS), Portugal

4 School of Medicine, University of Minho, Portugal

5 Family Health Unit of Espinho, ACeS Espinho-Gaia, Portugal

6 Ethics Committee of the Administração Regional de Saúde do Norte, ARS Norte, Portugal

\*Address all correspondence to<EMAIL_ADDRESS>
© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**103**

2019

*Evaluation of the Research Protocol by Ethical Committee*

[11] Santos P, Hespanhol A. Informed

consent for case reports—An ethical perspective. Acta Bioethica.

[12] Teixeira PM. p-Hacking—A call for ethics. Pulmonology.

[13] Cain DM, Detsky AS. Everyone's a little bit biased (even physicians).

[14] Dekking SA, van der Graaf R, van Delden JJ. Strengths and weaknesses of guideline approaches to safeguard voluntary informed consent of patients within a dependent relationship. BMC

2017;**23**(2):271-278

2018;**24**(3):207-208

JAMA: The Journal of the American Medical Association. 2008;**299**(24):2893-2895

Medicine. 2014;**12**:52

[15] Jamrozik K. Research ethics

Série I de 2018-10-15; 2018

paperwork: What is the plot we seem to have lost? BMJ. 2004;**329**(7460):286-287

[16] Estabelece os princípios e regras aplicáveis às comissões de ética que funcionam nas instituições de saúde, nas instituições de ensino superior e em centros de investigação biomédica que desenvolvam investigação clínica. Decreto-Lei n.° 80/2018. Sect. 198/2018.

*DOI: http://dx.doi.org/10.5772/intechopen.92265*

[1] Hipocratis opera vera at adscripta. Vol. Quartus. Lausanne; 1771.

[2] Trials of War Criminals before the Nuernberg Military Tribunals under Control Council Law n. 10. Volume II:

Recommendations guiding doctors in

[5] McGee G, Caplan AL, Spanogle JP, Asch DA. A national study of ethics committees. The American Journal of

[6] WMA Declaration of Helsinki— Ethical principles for medical research involving human subjects; 2018

[7] Sikes P, Piper H. Ethical research, academic freedom and the role of ethics committees and review procedures in educational

research. International Journal of Research & Method in Education.

[8] Beauchamp TL, Childress JF.

[9] Grady C. Chapter 2—Ethical principles in clinical research. In: Gallin JI, Ognibene FP, Johnson LL, editors. Principles and Practice of Clinical Research. 4th ed. Boston: Academic Press; 2018. pp. 19-31

[10] Kemp P, Dahl RJ. The

2008;**23**(2):239-251

Barcelona declaration. Towards an integrated approach to basic ethical principles. Synthesis Philosophica.

Principles of Biomedical Ethics. 8th ed. New York: Oxford University Press;

2010;**33**(3):205-213

[4] Sims JM. A brief review of the Belmont report. Dimensions of Critical Care Nursing. 2010;**29**(4):173-174

pp. 197-199

**References**

The medical case; 1949

clinical research; 1964

[3] Declaration of Helsinki:

Bioethics. 2001;**1**(4):60-64

*Evaluation of the Research Protocol by Ethical Committee DOI: http://dx.doi.org/10.5772/intechopen.92265*


**6. Conclusion**

**4. Time for orthodontic bonding and force application**

usage may begin after orthodontic wire was placed.

arches at first orthodontic appointment after surgery.

were reported to affect stability in SFA cases [59].

fixation.

150 Current Approaches in Orthodontics

**5. Relapse in SFA**

On the basis of simulated model surgery setup, surgical guidance splint is prepared. Before the surgery, orthodontic bracket bonding/banding is placed but no arch wire is used. Bonding orthodontic bracket was reported as immediately before surgery [26, 47, 48], 1 week before surgery [16, 26, 38], and 1–2 months before surgery [50]. Some studies reported the usage of passive archwire before the surgery [49, 50, 52, 53, 55]. Passive arch can be used 1–3 days before the surgery [17, 35]. In some cases, the orthodontist can prefer minimal orthodontic preparation during 6 months [49] before the surgery, and then, they are continuing the orthodontic treatment after the surgery. Intermaxillary fixation of jaws during the surgery can be done by bony screws following the surgical guidance splints placements in cases without arch wires [47, 50, 51]. Kim et al. maintained intermaxillary fixation without surgical splint for 2 weeks but used intermaxillary elastic [50]. The osteotomized bones are fixed by rigid

Postoperatively, surgical splint is left for 2–4 weeks [34, 50, 53], and intermaxillary elastics

There is no definitive consensus about postsurgical orthodontic force application time. But generally, the orthodontic treatment in SFA begins in 1 or 2 weeks after surgery. The surgical splint and inter-maxillary fixation were removed for the tooth movement. Liao et al. reported that postsurgical orthodontics begun immediately after surgery [17]. This is beneficial to shorten the orthodontic treatment time due to the regional accelerated phenomena. The studies showed that the orthognathic surgery triggers a 3- to 4-month period of higher osteoclastic activity, serum findings, and metabolic changes and that in the dentoalveolar bone postoperatively [15, 56]. Archwire changes took place every 2–3 weeks. Arch coordination may be managed with transpalatal elastics or active transpalatal arch. In segmental surgery patients, passive continuous arches which were placed before surgery are changed with sectional

The short- and long-term relapse rates in SFA have been investigated, and the results are good by comparison with the conventional surgical approach with a maximum follow-up of 3 years [19, 57–59]. Without presurgical orthodontics, the patients may have likely to develop unstable occlusion after surgery leading to relapse. However, some of the comparative studies between conventional and surgery first approach showed no statistical differences in relapse and almost equal for those achieved using the more traditional orthodontics-first approach [17, 19, 51, 53, 59–63]. Advancement of fixation system enabled more stabilized results due to more stable fixation of bony segments. On the other side, based on one research and on the meta-analysis, SFA showed more relapses than in the conventional approach [57, 64]. Larger overbite, a deeper curve of Spee, a greater negative overjet, and a greater mandibular setback The surgery first approach is an alternative method that may be more satisfying for orthodontists and patients by minimizing the treatment time required for orthodontic treatment compared to conventional approach.


*Article* **Composition and Statistical Analysis of Biophenols in Apulian Italian EVOOs**

#### **Andrea Ragusa 1,2,\* , Carla Centonze 3, Maria Elena Grasso 3, Maria Francesca Latronico 3, Pier Francesco Mastrangelo 3, Francesco Paolo Fanizzi 3 and Michele Maffia 3,\***

Received: 26 September 2017; Accepted: 16 October 2017; Published: 18 October 2017

**Abstract:** Extra-virgin olive oil (EVOO) is among the basic constituents of the Mediterranean diet. Its nutraceutical properties are due mainly, but not only, to a plethora of molecules with antioxidant activity known as biophenols. In this article, several biophenols were measured in EVOOs from South Apulia, Italy. Hydroxytyrosol, tyrosol and their conjugated structures to elenolic acid in different forms were identified and quantified by high performance liquid chromatography (HPLC) together with lignans, luteolin and α-tocopherol. The concentration of the analyzed metabolites was quite high in all the *cultivars* studied, but it was still possible to discriminate them through multivariate statistical analysis (MVA). Furthermore, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were also exploited for determining variances among samples depending on the interval time between harvesting and milling, on the age of the olive trees, and on the area where the olive trees were grown.

**Keywords:** HPLC; EVOO; biophenols; antioxidants; hydroxytyrosol; oleuropein; multivariate statistical analysis; OPLS-DA

#### **1. Introduction**

The nutritional and health-promoting properties of extra-virgin olive oils (EVOOs) are well-known and they have been extensively studied over recent decades. In particular, it has been demonstrated that phenolic derivatives in olive oils, also known as biophenols, have strong antioxidant activity which, apart from being responsible of the product shelf life, it also confers on EVOOs anti-inflammatory, chemopreventive, and anti-cancer effects, among others, yielding a product with very important nutraceutical properties [1].

Antioxidants in EVOOs can be mainly grouped in two categories depending on the solubility of the phenolic compounds in either organic or aqueous solvents [2]. Lipophilic phenols in EVOOs are mainly constituted by tocopherols, and in particular, their α-homologue, the most biologically active form of vitamin E, which represents over 90% of their total composition [3]. On the other hand, lignans and secoiridoids represent the mayor constituents of hydrophilic phenols in EVOOs, with the latter being only found in plants belonging to the family of *Oleaceae*. Among secoiridoids, *o*-diphenols, such as 3,4-DHPEA and its derivatives 3,4-DHPEA-EDA and 3,4-DHPEA-EA, were reported to have a higher antioxidant activity compared to *p*-HPEA and α-tocopherol (see Figure 1 for names and structures of these compounds) [4]. Nevertheless, all these molecules, together with other minor

compounds, such as carotenoids, and thanks to a well-balanced unsaturated-to-saturated fatty acid ratio, contribute to the high quality of EVOOs and its fundamental role in the Mediterranean diet.

**Figure 1.** Chemical structures of the antioxidant molecules studied.

EVOOs from Apulia have been already studied in quite significant detail over recent years, also because they represent almost 40% of the total Italian production [5]. However, most of the studies examine *cultivar* from the central area of Apulia and only few investigate the southern part, that is, Salento. Back in 1999, Caponio et al., studied the phenolic composition of Ogliarola and Coratina EVOOs and correlated its variation to different technological variables [6]. They later investigated the influence of decanter working parameters on the quality of the oils [7]. Longobardi and colleagues classified Apulian olive oils based on their chemical composition, i.e., free acidity, peroxide value, spectrophotometric indexes, chlorophyll content, sterol, fatty acid, and triacylglycerol, and on the NMR profile combined with multivariate statistical analysis [8,9]. Gambacorta et al., also inspected the phenolic composition and the antioxidant activity of Collina di Brindisi oils and found out that the maturity degree of olives had a major influence on the phenol composition, followed by the extraction

system and the place of growth [10]. Over recent years Fanizzi and colleagues explored, in detail, the use of nuclear magnetic resonance (NMR) and used multivariate statistical analysis (MVA) to investigate various aspects of EVOOs from Apulia. They managed to correlate NMR spectra to genetic profile of the *cultivars*, to the characteristics of the soil where the trees were grown, to the age of the olive trees, as well as the production parameters employed and the weather influence over the years [11–14]. The NMR-based metabolomics was exploited to generate a comparable data set for fingerprinting olive oil *cultivars* from Apulia, thus allowing identification and traceability of commercial EVOOs [5,15–18]. They also applied the same technique to EVOOs from Salento, in particular to Ogliarola, Cellina, and blend samples [19]. Nevertheless, a detailed study regarding the phenolic composition in EVOOs from Salento has not been reported so far despite the commercial importance of these products.

We already reported the phenolic profile of several grape types from Salento and we now extend this study, by examining similar antioxidant molecules in local olive oils [20]. In this article, the total amount of biophenols, as well as the concentration of hydroxytyrosol and tyrosol and their derivatives conjugated to elenolic acid, lignans, luteolin, and α-tocopherol were quantified in several monovarietal *cultivars* and blend EVOOs. Furthermore, their concentrations were correlated to the type of *cultivar* and other agronomical parameters, such as the age of the trees and the areas they were located, as well as more technical variables, such as the interval time between harvesting and milling.

#### **2. Materials and Methods**

#### *2.1. Chemicals*

High performance liquid chromatography (HPLC)-grade *orto*-phosphoric acid (85% *v*/*v*) and reference standard of tyrosol, hydroxytyrosol, syringic acid, luteolin, and α-tocopherol were purchased from Sigma-Aldrich (Milan, Italy). HPLC-grade methanol, acetonitrile, isopropanol, and hexane were purchased from J.T. Baker (Deventer, The Netherlands). HPLC-grade water was purchased from Carlo Erba Reagenti (Milan, Italy).

#### *2.2. Samples*

Analysis was conducted on a total of 68 EVOO samples collected and produced between October and December 2013 by enterprises from Salento, a geographic region at the southern end of the region of Apulia, in South Italy (see Figure 2 for details). All samples were produced from olive trees grown locally and representing typical *cultivars* from Apulia, such as Ogliarola salentina (*n* = 25), Cellina di Nardò (*n* = 20), Leccino (*n* = 4), Frantoio (*n* = 2), Picholine (*n* = 2), and Cima di Melfi (*n* = 1). Furthermore, 14 blend samples, 9 of which composed of mixtures of Ogliarola and Cellina in different ratios (from 30 to 70%), and the other 5 same as the former with also a minor percentage (from 10 to 20%) of either Leccino, Frantoio, or Coratina, were also analyzed. The Protected Designation of Origin (PDO) *cultivars* were certified by the Chamber of Commerce of Lecce (IT), the competent Public Authority Control, while the non-PDO *cultivars* were assessed and certified based on the growers' declaration. Other technical info and production details were provided by the farmers and are reported in Table 1. When the sum of the number of samples in each category is lower to the total number of samples it means that not all the producers provided the corresponding information. All producers employed the same technical details additionally provided, such as the use of continuous crushers, malaxation at low temperatures (about 25 ◦C), and two-phases decanters, and as such they were not treated as variables. Samples were stored directly in dark glass bottles soon after production, and were kept as such in a cool, dark place until analyzed. All analyses were completed within 2014.

**Figure 2.** Map of Italy with a zoom on a southern Apulia region (Salento, in red). The colored shapes represent the sites of production of the extra-virgin olive oils (EVOOs) categorized according to their proximity either to the Adriatic (green circles) or Ionian Sea (red triangles), or to neither of them (blue squares).

**Table 1.** Technical info and production details about EVOO samples organized by type of *cultivar*. 1

1 Extra-virgin olive oils (EVOOs) data were provided by the farmers. When the sum of the number of samples for each category is lower than the total it means that not all the producers provided the corresponding information. 2 Protected Designation of Origin (PDO) "Terra d'Otranto" certification is valid only for EVOOs from Ogliarola salentina and Cellina di Nardò *cultivars*, present alone or in combination, in varying percentages and not less than 60%. The remaining 40% can consist of other minor *cultivars* present in the olive grove of the production area [21]. 3 Location of the olive trees according to their proximity either to the Ionian or Adriatic Sea, or to neither of them.

4 Samples in the ">12" category were milled between 12 and 24 h from harvesting.

#### *2.3. HPLC Analysis*

Separation and identification of phenolic compounds were carried out using an HPLC 1220 Infinity (Agilent Technologies, Palo Alto, CA, USA) equipped with an Eclipse Plus C18 (particle size 5 μm; 4.6 × 250 mm, Agilent) stationary phase column interfaced with a diode array detector (model G1315B DAD system; Agilent).

#### 2.3.1. Analysis of the Phenolic Compounds

Extraction and quantification of the phenolic compounds was carried out following an official methodology from the International Olive Council, see the original document for details and a representative spectrum [22]. Tyrosol and syringic acid in a methanol/water 80/20 (*v*/*v*) solution at a concentration of 0.030 and 0.015 mg/mL, respectively, were used as external standards. Syringic acid in a methanol/water 80/20 (*v*/*v*) solution at a concentration of 0.015 mg/mL was used as internal standard. The concentration of the biomolecules in the analyzed samples was expressed as mg/kg of tyrosol.

Before analysis, 2.0 g of olive oil were put into a 10 mL vial and 1 mL of the internal standard solution was added. The vial was shaken on an orbital shaker (New Brunswick Innova 2050, Eppendorf, Germany) for 30 s and then 5 mL of a methanol/water 80/20 (*v*/*v*) solution were added. The sample was shaken for 1 min and then sonicated for 15 min at room temperature. The sample was centrifuged (Eppendorf 5804R Centrifuge, Eppendorf, Germany) at 5000 rpm for 25 min and an aliquot was extracted from the upper layer and filtered over polyvinylidene fluoride (PVDF) membrane filters with 0.45 μm pore size (VWR International, Milano, Italy). The solution obtained was ready for HPLC analysis.

A ternary gradient system with solvents (A) 0.2% H3PO4/H2O (*v*/*v*), (B) methanol, and (C) acetonitrile was used. The gradient parameters were: 96% (A), 2% (B), 2% (C) at 0 min; 50% (A), 25% (B), 25% (C) at 40 min; 40% (A), 30% (B), 30% (C) at 45 min; 0% (A), 50% (B), 50% (C) at 60 min; 0% (A), 50% (B), 50% (C) at 70 min; 96% (A), 2% (B), 2% (C) at 72 min; 96% (A), 2% (B), 2% (C) at 82 min. The solvent flow was maintained at 1.0 mL/min, the column temperature was set 25 ◦C, and the ultraviolet-visible (UV-Vis) detection wavelength was set at 280 nm. The ratio of the response factors between syringic acid and tyrosol, *RRFsyr/tyr*, was calculated before sample analyses to be sure that it was in the range 5.1 ± 0.4. The concentration of the phenol *X* was calculated according to the equation:

$$X \text{ (mg/kg)} = \text{((A}\_{x}\text{)} \times 1000 \times RRF\_{synlyr} \times P\_{syn}) / (\text{A}\_{syr} \times P\_{oil})\_r$$

where A*x* is the area of the corresponding phenol *X*, P*syr* is the weight in mg of the syringic acid utilized as internal standard, A*syr* is the area of the peak of syringic acid, and P*oil* is the exact weighted amount of oil utilized for the extraction. Obtained retention time for the identified phenols were: hydroxytyrosol, min 10.6; tyrosol, min 15.1; syringic acid, min 20.6; 3,4-DHPEA-EDA, min 31.7; 3,4-DHPEA-EA, min 34.4; *p*-HPEA-EDA, min 36.6; lignans, min 37.8; *p*-HPEA-EA, min 39.8; luteolin, min 40.9; 3,4-DHPEA-EA aldehydic and hydroxylic isomer, min 54.8; *p*-HPEA-EA aldehydic and hydroxylic isomer, min 57.7. The total amount of biophenols was calculated by integrating all the peaks in the spectrum in the range 9–59 min, i.e., those of the identified phenols plus other unidentified. The original raw data are available from the Multilab–Chamber of Commerce of Lecce—upon request at<EMAIL_ADDRESS>
#### 2.3.2. Analysis of α-Tocopherol

Before analysis, 0.1 g of olive oil was put into a 10 mL vial and 5 mL of methanol were added. The vial was shaken on an orbital shaker for 2 min and then centrifuged at 3000 rpm for 5 min. An aliquot was extracted from the upper layer and filtered over PVDF filters with 0.45 μm pore size (VWR International, Milano, Italy). The solution obtained was ready for HPLC analysis.

A calibration curve was prepared using standard solutions at increasing concentration of α-tocopherol in methanol and recording the corresponding peak area. Fitting of the data was performed through a linear equation with zero intercept (*R*2 > 0.99). The concentration in mg/kg of α-tocopherol in the analyzed sample was then calculated through interpolation of the corresponding peak area.

A binary gradient system with solvents (A) 0.5% isopropanol/hexane (*v*/*v*), (B) 10% isopropanol/hexane was used. The gradient parameters were: 100% (A), 0% (B) at 0 min; 100% (A), 0% (B) at 4 min; 60% (A), 40% (B) at 14 min; 40% (A), 60% (B) at 18 min; 100% (A), 0% (B) at 21 min; 100% (A), 0% (B) at 25 min. The solvent flow was maintained at 1.0 mL/min, the column temperature was set 25 ◦C, and the UV-Vis detection wavelength was set at 288 nm. Obtained retention time was 11.2 min.

#### *2.4. Statistical Analysis*

The amounts of phenols reported represent the mean values for a specific type of *cultivar*. The reported standard deviation represents the difference among different samples from the same

category. When just one sample for a specific type of *cultivar* was available, no standard deviation has been reported. Standard deviation relatively to replicates of the same sample was always <5%. Obtained values were rounded to one decimal place. Statistical analysis was performed using SIMCA 14.1 software (MKS Umetrics, Malmö, Sweden). Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were performed using the detected biophenols, their total amount, and α-tocopherol as variables (*n* = 12) while the qualitative information, such as *cultivar*, interval time between harvesting and milling, age of the trees, location of the trees, and PDO certification, as classes according to the data reported in Table 1. Strong outliers were removed from the computation to obtain a better fit. *R*2X(cum) and *R*2Y(cum) are the cumulative Sum of Squares (SS) of the variation of the X or Y variables, respectively, explained by the extracted components of the model. *Q*2(cum) is the cumulative variation of the X and Y variables predicted by the extracted components of the model. *R*2X(cum) and *R*2Y(cum) are parameters utilized for describing the goodness of the fit and their values are always between 0 and 1, the higher the better. *Q*2(cum) is a parameter used to describe the predictive ability of the model and its value is usually between 0 and 1, the higher the better.

#### **3. Results and Discussion**

The content of several biophenols and their total amount was quantified in several EVOOs from Salento, in Southeast Italy (Figure 2). All EVOOs were prepared from olive trees grown locally from monovarietal species of Ogliarola, Cellina, Leccino, Picholine, Frantoio, and Cima di Melfi. Furthermore, Ogliarola and Cellina were mixed in blend samples, in percentages from 30 to 70%, plus a few samples wherein small amounts of other *cultivar* were added (see Section 2.2 for details). Oils were produced in late 2013, between October and December, and additional agronomical and technical information are reported in Table 1.

All samples showed significant amounts of the investigated biophenols, as well as very high quantities of α-tocopherol, as shown in Figure 3. *orto*-Diphenols conjugated to the elenolic acid in various forms, i.e., the dialdehydic 3,4-DHPEA-EA, the decarboxylated dialdehydic 3,4-DHPEA-EDA, and 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form, were found to be the most abundant compounds, followed by their mono-hydroxy homologous (the *p*-HPEA derivatives). Nevertheless, significant amounts of their simple phenols hydroxytyrosol and tyrosol (3,4-DHPEA and *p*-HPEA, respectively) as well as lignans and luteolin were also found.

**Figure 3.** Histograms of the analyzed biophenols averaged for all samples. Bars represent standard deviations. A logarithmic scale was used on the Y axis.

#### *3.1. Analysis by Cultivar*

The average total amount of biophenols was about 452 mg/kg, with Frantoio being the *cultivar* with lowest quantity, as detailed in Table 2. On the other hand, Frantoio EVOOs had the highest concentration of hydroxytysosol and tyrosol (about 23 and 20 mg/kg, respectively), and lignans (about 43 mg/kg). Nevertheless, all the other biophenols were present in modest quantities compared to the other *cultivars*. Ogliarola showed quite high concentrations of total biophenols and *p*-HPEA-EDA, all other values being on average. Cellina also had quantities of phenols analogous to average values, with the only exception being the amount of α-tocopherol, the highest among all *cultivars*. As expected, blend samples showed a trend similar to that of Ogliarola and Cellina, being they constituted completely by mixtures in different percentages of those two *cultivars*, or at least for 80% by them also when mixed with other varieties, such as Leccino, Frantoio, or Coratina. The only significant difference was the concentration of α-tocopherol, much lower than that in the pure parent varieties. Small amounts of *p*-HPEA-EDA and *p*-HPEA-EA were detected in Leccino EVOOs, while Picholine had a low concentration of hydroxytyrosol but very high quantities of *p*-HPEA-EA in the aldehydic and hydroxylic form. Finally, Cima di Melfi EVOOs showed quite high concentrations of biophenols compared to average, especially of 3,4-DHPEA-EDA, 3,4-DHPEA-EA, and lignans, while lower quantities of α-tocopherol were detected. However, it must be considered that only two samples each of Frantoio and Picholine and one of Cima di Melfi were analyzed, hence those average values might be quite variable on a broader pattern.

In order to check the presence of dominant constituents among the *cultivars*, principal component analysis (PCA) was carried out on the Cellina and Ogliarola samples, for a total of 45 observations, using the 10 detected phenols, α-tocopherol, and the total amount of biophenols as variables. Blend samples were initially excluded from the analysis because of their intrinsic variability being mixtures of Cellina and Ogliarola in various ratios and, in some cases, also with other *cultivars*, as already stated. On the other hand, Leccino, Picholine, Frantoio, and Cima di Melfi EVOOs were omitted due to low number of available samples for each category (4, 2, 2, and 1, respectively). The first two components of the model could explain 50.3% of the total population, however the resulting score plot did not show any dominant variable but the samples were quite spread with a high degree of overlap among them, as shown in Figure 4.

**Figure 4.** PCA score plot (PC1 vs. PC2) for EVOO samples from Salento categorized by *cultivar* (blue squares = Cellina; purple triangles = Ogliarola).

Much better results were obtained when a supervised multivariate method was used. Partial least-squares discriminant analysis (OPLS-DA) improved significantly separation of the *cultivars*, as shown in Figure 5, with cumulative *R*2X and *R*2Y of 0.60 and 0.83, respectively, and a respectable *Q*2 of 0.66. The two groups were perfectly separated along the mayor component, while the variability among samples is probably responsible for their dispersion along the orthogonal component. According to the loadings, α-tocopherol and 3,4-DHPEA-EA contributed the most to the discrimination of Cellina EVOOs, while *p*-HPEA-EDA and *p*-HPEA-EA to that of Ogliarola samples.

Values are expressed as mean ± standard deviation relatively to the different samples of EVOO analyzed in each category. Only one sample was available for the *cultivar* Cima and no standard deviation has been reported.

**Figure 5.** (**a**) Orthogonal partial least-squares discriminant analysis (OPLS-DA) score plot for EVOO samples from Salento categorized by *cultivar* (blue squares = Cellina; purple triangles = Ogliarola); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols;2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 = Cellina; 14 = Ogliarola).

In order to check the predictive ability of the model, blend EVOOs were used as prediction dataset. As expected, samples did not aggregate in any region of the plot but they spread along PC1 between the two extremes marked by the pure *cultivars*, probably according to the different percentages of Cellina and Ogliarola in their composition, as shown in Figure 6.

**Figure 6.** Predicted OPLS-DA score plot for blend EVOO samples from Salento with unknown percentages of Cellina/Ogliarola (blue squares = Cellina; purple triangles = Ogliarola, gray stars = blend predictions).

#### *3.2. Analysis by Interval Time between Harvesting and Milling*

It is well recognized that the amount of antioxidants in EVOOs is influenced, together with other factors, also by the interval time between harvesting and milling. In fact, it has been shown that the shorter this interval time the higher the concentration of biophenols and it is also the reason why, for example, PDO EVOOs are required to be processed by 48 h at the latest after being collected [21]. Samples were grouped in two classes, those which were milled by 12 h from harvesting and those for which that interval time was longer, and OPLS-DA was performed. Initially only Cellina EVOOs were considered to reduce the potential variability introduced by other *cultivars*, and the resulting score scatter plot is reported in Figure 7.

**Figure 7.** (**a**) OPLS-DA score plot for Cellina EVOO samples from Salento categorized by the interval time between harvesting and milling of the olives (green circles ≤ 12 h; blue squares > 12 h); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 ≤ 12 h; 14 > 12 h).

Discrimination was substantial and it could be observed from the loading plot that most variables contributed significantly to the separation of EVOOs with shorter interval time, especially the total concentration of biophenols, 3,4-DHPEA-EA, and α-tocopherol. On the other hand, only *p*-HPEA-EA appeared to give a slightly positive contribution to samples with an interval time longer than 12 h. However, this result is not surprising because it is known that degradation of antioxidant molecules starts soon after harvesting, and that is why a short interval time between harvesting and milling is a prerequisite for producing high quality EVOOs.

Performing the OPLS-DA on all EVOOs yielded a much worse model (*R*2X(cum) = 0.38, *R*2Y(cum) = 0.45, *Q*2X(cum) = 0.28) compared to that obtained with only Cellina samples (*R*2X(cum) = 0.56, *R*2Y(cum) = 0.73, *Q*2X(cum) = 0.54). This was expected given the randomness introduced by other variables, nevertheless a similar trend could be observed in the score scatter plot and in the loading column plot (Figure 8).

**Figure 8.** (**a**) OPLS-DA score plot for EVOO samples from Salento categorized by the interval time between harvesting and milling of the olives (green circles ≤ 12 h; blue squares ≥ 12 h); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 ≤ 12 h; 14 > 12 h).

#### *3.3. Analysis by the Age of the Olive Trees*

Salento is well-known for having a high number of secular olive trees, which have recently been regulated and surveyed because of their high historical value [23]. Furthermore, EVOOs from secular olive trees have been already studied and categorized by NMR due to their commercial importance [12]. We now tested if any statistical difference in the amount of biophenols could be detected between secular and younger olive trees. EVOOs were grouped depending on the age of their trees in >100 and <100-year-old classes and OPLS-DA was performed on Cellina samples. A quite good descriptive but not predictive model was obtained, as shown by the correlation coefficients (*R*2X(cum) = 0.48, *R*2Y(cum) = 0.70, *Q*2(cum) = 0.02). According to the loadings, EVOOs from younger trees were significantly discriminated by the total amount of biophenols and *p*-HPEA-EDA, although many other variables also contributed to the separation, as shown in Figure 9. On the other hand, only tyrosol gave a slightly positive contribution to the discrimination of secular trees.

**Figure 9.** (**a**) OPLS-DA score plot for Cellina EVOO samples from Salento categorized by the age of the olive trees (green circles ≤ 100 years; blue squares > 100 years); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 ≤ 100 years; 14 > 100 years).

The OPLSA-DA was repeated on all EVOOs yielding, despite the different *cultivars* utilized, a model with very good both descriptive (*R*2X(cum) = 0.74, *R*2Y(cum) = 0.79) and predictive (*Q*2(cum) = 0.65) ability, as shown in Figure 10. The reported loadings again confirmed that younger trees were richer of biophenols compared to secular ones, also emphasizing the role of 3,4-DHPEA derivatives and luteolin, while older ones were discriminated thanks to tyrosol and its derivatives conjugated to elenolic acid.

**Figure 10.** (**a**) OPLS-DA score plot for EVOO samples from Salento categorized by the age of the olive trees (green circles ≤ 100 years; blue squares > 100 years); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 ≤ 100 years; 14 > 100 years).

#### *3.4. Analysis by the Cultivation Area*

Climate and agronomical features are very important variables that influence noteworthy the final characteristics of olives and vegetables in general. Gambacorta et al., reported that olive maturity index and technology used had a greater influence with respect to the place of growth on the total amount of phenols [10]. Nevertheless, they found a variability of about 40% depending on the cultivation area. Similarly, we looked for any correlation between the area where the olive trees were grown and the concentration of the analyzed biophenols. OPLS-DA was performed on Cellina EVOOs grouped into 3 categories depending on the proximity of the trees either to the Adriatic or Ionian Sea, or to neither of them if in the central mainland. The EVOOs clustered quite nicely (*R*2X(cum) = 0.85, *R*2Y(cum) = 0.73) with samples from trees close to the Adriatic Sea being well separated on the positive axis because of most variables, especially luteolin, *p*-HPEA-EDA, lignans, and the total amount of biophenols, as shown in Figure 11. On the other hand, samples from the Ionian area and the central mainland reported both similar negative values along PC1, but were completely separated along PC2 mainly because of *p*-HPEA-EA the former and 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form the latter.

**Figure 11.** (**a**) OPLS-DA score plot for Cellina EVOO samples from Salento categorized by their proximity either to the Adriatic (green circles) or Ionian Sea (red triangles), or to neither of them (blue squares); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 = Adriatic area; 14 = central mainland; 15 = Ionian area).

OPLS-DA was also performed on Ogliarola EVOOs, but only samples from the Ionian Sea and the central mainland were considered, being only two those close the Adriatic area. A very good both descriptive (*R*2X(cum) = 0.65, *R*2Y(cum) = 0.89) and predictive (*Q*2(cum) = 0.75) model was obtained, with samples close to the Ionian Sea being richer of *p*-HPEA-EDA and *p*-HPEA-EA, while those from the central mainland of 3,4-DHPEA-EA and α-tocopherol, quite in agreement with Cellina EVOOs from similar cultivation areas (Figure 12).

**Figure 12.** (**a**) OPLS-DA score plot for Ogliarola EVOO samples from Salento categorized by their proximity either to the Ionian Sea (red triangles), or to the central mainland (blue squares); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 = central mainland; 14 = Ionian area).

#### *3.5. Analysis by PDO Certification*

Protected Designation of Origin (PDO) "Terra d'Otranto" accreditation is a certificate given to EVOOs from the province of Lecce and part of the provinces of Brindisi and Taranto which satisfy determined agronomic and production characteristics which should guarantee healthful properties, among which a high content of antioxidants. Ogliarola and Cellina are the most popular *cultivars* in Salento and they are the mayor components of PDO EVOOs [21,24].

Most of the analyzed EVOOs in this study were PDO certified, however none of the pure *cultivars* studied contained a significant number of both PDO and non-PDO samples to perform a multivariate statistical analysis. Nevertheless, OPLS-DA analysis conducted on all EVOOs could descript (*R*2X(cum) = 0.54, *R*2Y(cum) = 0.77) and predict (*Q*2X(cum) = 0.68) quite satisfactorily the two groups (Figure 13). The PDO samples were separated mainly because of a higher content of α-tocopherol and *p*-HPEA-EA in the mixed aldehydic and hydroxylic form, while smaller phenols, such as tyrosol and hydroxytyrosol, and *p*-HPEA-EA influenced the most the discrimination of samples without certification.

**Figure 13.** (**a**) OPLS-DA score plot for EVOO samples from Salento categorized by PDO certification (green circles = non-PDO; blue squares = PDO); (**b**) OPLS-DA loadings column plot for the first predictive component of the model (variables: 1 = total biophenols; 2 = hydroxytyrosol; 3 = tyrosol; 4 = 3,4-DHPEA-EDA; 5 = 3,4-DHPEA-EA; 6 = lignans; 7 = luteolin; 8 = *p*-HPEA-EDA; 9 = *p*-HPEA-EA; 10 = 3,4-DHPEA-EA in the mixed aldehydic and hydroxylic form; 11 = *p*-HPEA-EA in the mixed aldehydic and hydroxylic form; 12 = α-tocopherol; 13 = non-PDO; 14 = PDO).

#### **4. Conclusions**

Quantification of antioxidant molecules in EVOOs is of paramount importance because of their nutraceutical value, even though biophenols represent only minor constituents in olive oil. In this article, we quantified, by HPLC, the total amount of biophenols, several individual biophenols (i.e., tyrosol, hydroxytyrosol, and several more complex derivatives conjugated to elenolic acid in various forms), and α-tocopherol in a variety of pure *cultivars* and blend EVOOs from Salento, in South Apulia. Remarkable differences in the phenolic profile were evident among samples and a high variability was found within the *cultivars*, probably because of the influence of genotyping and other agro-climatic parameters. Nevertheless, all *cultivars* showed significant amounts of biophenols and supervised multivariate statistical analysis could detect differences between Cellina and Ogliarola EVOOs, and predict blend samples. Furthermore, the content of biophenols was correlated to production parameters, such the interval time between harvesting and milling, and to agronomical variables, such as the age of the olive trees and the area they were grown. OPLS-DA showed that shorter interval times lead to an increase in the total concentration of biophenols. Furthermore, it could distinguish between EVOOs from secular and from younger trees, and among samples from different cultivation areas, such as the proximity to the Adriatic or Ionian Sea, or to the central mainland. Eventually, these multivariate statistical analyses, besides yielding valuable information about the characteristics of the studied *cultivars*, could be exploited to improve the already beneficial properties of their EVOOs and to determine a metabolic profile that could be exploited, in combination with other parameters, to guarantee the originality and traceability of these products.

**Acknowledgments:** This research was supported by the project "Caratterizzazione, valorizzazione ed effetti salutistici dell'olio extravergine di oliva del Salento" funded by MultiLab—Chamber of Commerce of Lecce (Italy). We would like to thank Giuseppe Potenza for his technical assistance and fruitful discussion.

**Author Contributions:** A.R. and M.M. conceived and designed the experiments; A.R., C.C., M.E.G., M.F.L., and P.F.M. performed the experiments; A.R., F.P.F., and M.M. analyzed the data; A.R., F.P.F., and M.M. wrote the paper.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


**4. Proposed procedure**

184 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

The ability to estimate the probability density functions, based on training patterns, is fundamental to the use of Eq. (8). Frequently, a priori probabilities can be known or estimated, and the loss functions require subjective evaluation. However, if the probability densities of the categories patterns to be separate are unknown, and all that is known is a set of training patterns, then, these patterns provide the only clue to the estimation of that unknown probability density. A particular estimator that can be used is (Specht, 1990):

1 1 ( )( ) ( ) exp 2

Where *i* is the pattern number, *m* is the total number of training patterns, *ai x* is the i-th

( ) *Af x* is simply the sum of small Gaussian distributions centered at each training sample.

The probabilistic neural network is basically a Bayesian classifier implemented in parallel. The PNN, as described by Specht (Specht, 1988), is based on estimation of probability density functions for the various classes established by the training patterns. A schematic diagram for a PNN is shown in Figure 5. The input layer *X* is responsible for connecting the input pattern to the radial basis layer. *X xx x* 1 2 ,,, *M* is a matrix containing the

*xx xx f x m*

*m T*

1 2

*n i*

(2 )

*A n*

*A* , and

Fig. 5. Schematic diagram of a Probabilistic Neural Network

**3.2 Structure of the Probabilistic Neural Network**

training pattern of category

vectors to be classified.

2

*ai ai*

(10)

is the smoothing factor. It should be noted that

The proposed procedure is shown schematically in Figure 6. The real data file contains phases A-B-C voltages and currents waveforms, as well as digital signals that indicate the statuses of protective devices, as relays and circuit breakers, acquired by DDR and IED installed in the electrical system substations. These raw data are coded in the COMTRADE format for power systems (IEEE Standard Common Format for Transient Data Exchange), (IEEE Std C37.111, 1999). So, to obtain the voltages and currents signals it is firstly necessary to decode the COMTRADE data, and select the desired waveforms to be analyzed.

Fig. 6. Schematic diagram representing the proposed processing procedure.

Before inputting the voltages waveforms to the processing stage, a pre-processing routine is accomplished to standardize the raw data due to the different voltage levels that are

Application of Wavelet Transform and Artificial Neural Network to

level 1 to level 3, and (e) level 3 approximation.

the previously selected decomposition level:

the number of samples; ˆ ( ) *s d n* is the new value of ( ) *s d n* ;

coefficients *s*.

Where:

The

Extract Power Quality Information from Voltage Oscillographic Signals in Electric Power Systems 187

Fig. 7. Signal decomposition in 3 levels. In (a) original signal. From (b) to (d) details from

The wavelet transform performance to detect disturbances in electrical signals is substantially improved if a procedure for reducing noise level is applied to the decomposition level coefficients to be used in the detection process. This feature is highlighted in (Yang et al, 1999; 2000 & 2001). So, to better characterize the disturbance location in the signal, it is applied the following algorithm presented in (Misiti et al, 2000), to

ˆ () () () () 0

*n N* 1,2, , is the number of the decomposition level *s*, ( ) *s d n* , coefficient and *N* is

*s sss s s*

*d n d n if d n and d n if d n*

*sss s s*

*d n if d n and d n*

0 ( )

coefficients considered, as proposed in (Santoso et al, 1997).

() () () 0

  (12)

*s s*

*s* is a threshold based on the maximum absolute value of the decomposition level

*s* value used was 10% of the maximum absolute value of the decomposition level

A voltage waveform containing voltage sag is shown in Figure 8(a). In (b) it is presented the details level used to detect the disturbance beginning and (c) presents new details values after the noise reduction algorithm is applied. In (c) it can be observed smaller coefficients magnitudes over the entire signal which improves the algorithm performance used to detect the disturbance.

encountered in the power system topology. In the case study presented here, the power transmission system presents 230 kV and 500 kV voltage levels. The standardization is performed by converting the phase voltages to per unit (p.u.) values considering the voltage peak value as base voltage.

## **4.1 Processing stage**

In the processing stage, the wavelet transform is applied to the voltage waveforms to obtaining signals patterns that characterize short duration voltage variations (SDVV) and transient variations (TV) due to system faults. These obtained patterns are used as inputs to two Probabilistic Neural Networks for SDVV classification (PNN1), as well as to classify the fault type that has occurred (PNN2). The classification results will form a database which can be used to evaluate power quality indices for the electrical system.


**1. Introduction**

Atherosclerotic cardiovascular disease is a group of disease which contains coronary artery disease, carotid artery disease, upper and lower extremity disease, and renal arterial diseases. The main cause of atherosclerotic cardiovascular diseases is the atherothrombotic process that occurs with atherosclerotic plaque rupture. Atherosclerosis is a chronic lipid-associated inflammatory disease concomitant with intimal thickening, especially involving bifurcation regions where endothelial damage is particularly high. Hypertension, hyperlipidemia,

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

diabetes, and smoking are the main risk factors for atherosclerosis. Fibrinogen, hsCRP, and interleukin-6 (IL-6) which are markers for inflammation have been found elevated in atherosclerosis. Atherosclerotic diseases are also common with systemic inflammatory diseases such as lupus and rheumatoid arthritis.

**4. Atherosclerosis and cholesterol hypothesis**

hyperlipidemia and atherosclerosis [2, 5, 6].

**5. LDL and total cholesterol**

small dense LDL.

The hypothesis of cholesterol suggests that lipids play a major role in the development of atherosclerosis. The 4S trial (Scandinavian Simvastanin Survival Study) showed that while there was significant reduction in total cholesterol level, LDL cholesterol level, and decrease in major coronary events, HDL cholesterol level was elevated in simvastatin receiving group [4]. After 4S study, REVERSAL, ASTEROID, and SATURN studies revealed that parallel plaque regression was observed with aggressive lipid-lowering therapy and reduction in major cardiovascular events was achieved. These similar studies have proven the relationship between

Role of Cholesterol as a Risk Factor in Cardiovascular Diseases

http://dx.doi.org/10.5772/intechopen.76357

97

Statins reduce macrophages and extracellular lipid accumulation in atherosclerotic plaque region and increase the content of collagen in the extracellular matrix which result in intimal calcification. Statins also stabilize inflammation and coagulation cascade after plaque rupture.

LDL is the particle that is responsible for transporting cholesterol to tissues. Cholesterol transportation is achieved by binding of the LDL receptor and apoB. There are three separate fractions of LDL: LDL (large/floating), IDL, and small dense LDL. The most atherogenic LDL is

In the WOSCOP trial and the AFCAPS/TeXCAPS trial which used pravastatin and lovastatin, respectively, the effect of hyperlipidemic therapy on the primary prevention of coronary artery disease was shown [7, 8]. The ASCOT-LLA study was terminated early in hypertensive individuals because atorvastatin significantly reduced nonfatal MI and CAD-induced mortality [9]. Similarly, the CARDS study was terminated early in diabetic individuals because

LIPID study compared low-dose and high-dose atorvastatin in patients with stable coronary artery disease and mortality was similar in both groups, but there was a significant decrease in major cardiovascular events in the high-dose atorvastatin group. The HPS study has shown that statin therapy protects high-risk patients with LDL cholesterol levels below 116 mg/dL [11]. CARE study with pravastatin in acute MI and MIRACLE study with atorvastatin in

In the ASTEROID trial, high-dose statin therapy (rosuvastatin 40 mg/day) was shown to reduce 53% LDL cholesterol, 15% increase in HDL cholesterol, and regression in 78% atheroma [5].

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors inhibit the PCSK9 protein, which is effective in LDL receptor synthesis and provide 50–70% reduction in LDL-C levels.

In the ACCELERATE study, it was shown that the CETP inhibitor (Evacetrapib) did not

reduce major cardiovascular events despite a 39% reduction in cholesterol level [14].

atorvastatin decreased 37% in major cardiovascular events and 48% in stroke [10].

USAP or MI have shown early initiation of statins have a positive affect [12, 13].