Impact of organic farming on biodiversity based on the literature review.
\r\n\tWith the discovery of more unconventional heavier crude and alternative hydrocarbon sources, primary upgrading or cracking of the oil into lighter liquid fuel is critical. With increasing concern for environmental sustainability, the regulations on fuel specifications are becoming more stringent. Processing and treating crude oil into a cleaner oil with better quality is equally important. Hence, there has been a relentless and continuous effort to develop new crude upgrading and treating technologies, such as various catalytic systems for more economical and better system performance, as well as cleaner and higher-quality oil.
\r\n\r\n\tThis edited book aims to provide the reader with an overview of the state-of-the-art technologies of crude oil downstream processing which include the primary and secondary upgrading or treating processes covering desulfurization, denitrogenation, demetallation, and evidence-based developments in this area.
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These types of farming practices also caused several negative environmental impacts such as decreasing biodiversity, including the farm bird index, where a decline has been observed in Slovenia since 2008. Many farms intensified their activities and became highly mechanized, whilst those unable to do so became increasingly marginalized and were sometimes forced to abandon their land, causing equally devastating consequences for biodiversity [1]. Today, it is globally imperative that the growing demand for food be met in a manner that is socially equitable and ecologically sustainable over the long term. It is possible to design farming systems that are equally productive and that maintain or enhance the provisioning of ecosystem services (i.e., biodiversity, soil quality, nutrient management, water-holding capacity, control of weeds, diseases and pests, pollination services, carbon sequestration, energy efficiency and reducing global warming potential, as well as resistance and resilience to climate change and crop productivity) and thus agroecosystem resilience and sustainability [2].
Organic agriculture refers to a farming system that enhances soil fertility by maximizing the efficient use of local resources, while foregoing the use of agrochemicals, genetically modified organisms and the many synthetic compounds used as food additives. The high quality of organic food and its added value relies on a number of farming practices based on ecological cycles, and aims at minimizing the environmental impact of the food industry, preserving the long term sustainability of soil and reducing to a minimum the use of non-renewable resources [3].
Organic farming practices have been promoted as reducing the environmental impacts of agriculture. The results of meta-analysis of studies that compare the environmental impacts of organic and conventional farming in Europe show that organic farming practices generally have positive impacts on the environment per unit of area, but not necessarily per product unit. Significant differences between the two farming systems include soil organic matter content, nitrogen leaching, nitrous oxide emissions per unit of field area, energy use and land use. Most of the studies that compared biodiversity in organic and conventional farming demonstrated lower environmental impacts from organic farming [4]. Furthermore, organic farming appears to perform better than conventional farming and also provides other important environmental advantages such as halting the use of harmful chemicals and their spread in the environment and along the trophic chain, and reducing water use [3]. A life cycle analysis approach calculating the ecological footprint of different productions systems confirmed, respectively, 8.5 and 5.9 times better environmental performance of organic farming practices, compared to their conventional counterparts in winter wheat and spelt production [5].
Biodiversity loss and the degradation of ecosystems have important implications for the environment and are costly for society as a whole [6]. In Europe, loss of plant biodiversity is primarily reflected in the decline of many species of plants and in the disappearing of local and old plant varieties. In 2011, the European Parliament adopted the European Union (EU) Biodiversity Strategy to 2020 with aim of preventing biodiversity loss and the degradation of ecosystems. The strategy includes combating invasive alien species that jeopardize biodiversity and aims also at enhancing the positive contribution of European agriculture, forest and fishery sectors to biodiversity conservation and sustainable use, and to increase by 2020 the EUs contribution to drawing attention to global biodiversity loss [1]. The World Trade Organization notes a crop variety loss of 75% during the past 100 years, even of 90% in the EU. Only 17% of species and habitats assessed under the Habitats Directive have been deemed to be in good status and the degradation and loss of natural capital is jeopardizing efforts for attaining the EUs biodiversity and climate change objectives [7, 4], which did not reach its 2010 biodiversity target [1].
Organic farming is a production method that preserves or even enrich biodiversity at the field level, at the farm level and in the ecosystem as per its regulatory demands, where the objectives of organic farming in EU regulation 834/2007 is noted thus: that organic farming shall pursue to establish a sustainable management system for agriculture with respect to nature\'s systems and cycles, and sustain and enhance the health of soil, water, plants and animals and the balance between them, and to contribute to a high level of biological diversity [5]. Organic farming systems generally harbour larger floral and faunal biodiversity, more so than conventional systems; however, when properly managed, the latter can also improve biodiversity. Importantly, the landscape surrounding farmed land also appears to have the potential to enhance biodiversity in agricultural areas [3]. However, the benefits of organic farming to biodiversity in agriculture landscapes are still being discussed.
Agrobiodiversity is an important aspect of biodiversity that is directly influenced by different production methods, especially at the field level. It can also supply several ecosystem services to agriculture, thus reducing environmental externalities and the need for off-farm inputs. Organic farming is considered an environmentally-friendly agriculture practice and a holistic approach encompassing several demands and bans from a regulatory point of view [8], and receives primarily from European countries additional agri-environmental payments for ecosystem services, including biodiversity. In some countries, payments are available as single biodiversity measures (i.e., hedgerows, insectary strips, crop rotation, or the retention of semi-natural areas) in agri-environmental programmes that are also aimed at conventional agriculture.
The aim of this paper is to establish whether organic farming fulfils the promise of protecting biodiversity better than conventional farming, based on the review of recent publications emphasizing the importance of precisely quantifying the effect of organic vs. conventional farming. Additional to an extensive review, data from the University of Maribor regarding the effects of different production systems on the earthworm population [9] and the biodiversity of weed species from field experiments in the north east of Slovenia [10] were compared with other findings.
The reader is kindly referred to previously mentioned sources [5, 9, 10, 36] for a detailed description of differences between farming systems. For a better general understanding, some details are explained. Earthworms were collected in October 2009, 2010 and 2011 using a mustard aqueous solution as a non-toxic irritant that drove deep burrowing earthworm species to the surface [11]. After measurements were taken, earthworms were returned back to the soil. Analyses were carried out using the Statgraphics Centurion XV statistical program [12]. The biodiversity of weed species [9] was measured using two methods: (i) above-ground weed population sampling; (ii) seedbank sampling. The size of the weed seedbank was determined within the 0 to 0.2 m soil layer of each plot using the greenhouse emergence method [13]. The in situ number of the above-ground weed population per m2 was measured at the end of June or at the beginning of July 2009, 2010 and 2011, after mechanical control and the use of herbicides. Weeds were counted in four 0.25 m2 quadrates randomly located in the centre of each plot, parallel to the working direction of machinery. The weed species were determined when a 2/3 population was at the stages of 2 to 3 true leaves and 1/3 was at the stages of 4 to 5 true leaves. Species diversity was calculated for both seedbank and weed communities using H’ [14].
Results of several research studies and published scientific articles showed that organic farming benefits to the environment, including biodiversity. Comparison of biodiversity in organic and conventional farms has shown that organic farming generally had positive impacts on many species [15]. Results of meta-analyses that compared biodiversity in organic and conventional farms found that organic farms generally have 30% higher species richness and 50% higher abundance of organisms than conventional farms. However, there are wide variations between different studies, which have to be discussed; for example, 16% of studies found a negative effect of organic farming on species richness. Additionally, it was also found that the effect of organic farming on species richness was larger for intensively managed landscapes than for diverse landscapes with many non-crop biotopes [16]. In 327 out of 396 relevant results [17], a higher degree of biodiversity in organic farming was found when compared to conventional farming. In 56 papers (14 %), no difference was verified and in 13 contributions (3%), organic farming yielded less biodiversity (seven of them for soil invertebrates). Significantly, the positive effect of organic farming on biodiversity compared to conventional farming was noticed in 80% of cases; in 16%, differences were unclear and less biodiversity was found in 4% of comparisons (Table 1).
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Rahmann [17] | \n\t\t\t343 | \n\t\t\t10 | \n\t\t\t327 | \n\t\t\t56 | \n\t\t\t13 | \n\t\t
Hole et al. [15] | \n\t\t\t76 | \n\t\t\t9 | \n\t\t\t66 | \n\t\t\t25 | \n\t\t\t8 | \n\t\t
Pfiffner [18] | \n\t\t\t44 | \n\t\t\t7 | \n\t\t\t49 | \n\t\t\t5 | \n\t\t\t1 | \n\t\t
Sum | \n\t\t\t\n\t\t\t | \n\t\t\t | 442 | \n\t\t\t86 | \n\t\t\t22 | \n\t\t
Share (%) | \n\t\t\t\n\t\t\t | \n\t\t\t | 80 | \n\t\t\t16 | \n\t\t\t4 | \n\t\t
Impact of organic farming on biodiversity based on the literature review.
1 Multiple citations of used studies are possible due to different conclusions for different species or multiple answers; 2 biodiversity indicators i.e., flora, weeds, soil biota, earthworms, pollinators, birds, etc.
On average, organic farming increased species richness by about 30%. This result has been robust over the past 30 years of published studies. Organic farming had a greater effect on biodiversity as the percentage of arable fields of the landscape increased, that is, it is higher in intensively farmed regions [19]. Thus, it may be concluded that organic farming produces more biodiversity. Research gaps still exist for the understanding of functional biodiversity and ecosystem impact, which comprise soil biota, landscape (ecosystem and habitat) and genetic biodiversity on agricultural land in natural habitats [17]. The majority of current studies are from Northern and Western Europe and North American agriculture practices, while other regions with large areas of organic farming have been poorly investigated. Comparison between paired organic and conventional fields in India assessed a wide range of taxa (plants, soil microbes, earthworms, butterflies, dragonflies and other arthropods, reptiles, molluscs, amphibians/frogs and birds) trough different methods that showed similar trends. Habitat area, composition and management of organic fields were likely to favour higher levels of biodiversity by supporting higher numbers of species, dominance and abundance across most taxa. Organic fields are systems that are less dependent on external inputs to restore and rejuvenate the environment, resulting in higher biodiversity that promotes higher sustainable production on a long-term basis [20]. The effects of time since conversion to organic farming on species richness and abundance have been poorly researched. Plant and butterfly species richness was 20% higher on organic farms and butterfly abundance was about 60% higher, compared to conventional farms. Time since conversion to organic farming affected butterfly abundance gradually over a 25-year period, resulting in a 100% increase; however, no effect was found on plant or butterfly species richness, indicating that the main effect took place immediately after the conversion to organic farming [21].
Three recent multiregional studies from Europe have also demonstrated the negative effects of both agricultural intensification (increased use of synthetic fertilizers and pesticides combined with the reduced use of diversified farming system techniques) and landscape simplification on components of biodiversity [2]. The EU Biodiversity Strategy to 2020 also focuses on sustainable farming and forestry as the focus of one of six targets in the form of improving the integration of biodiversity conservation into key policies for agriculture and forestry. Combined, these two sectors include almost 72% of land in the EU and play a major role in Europe’s biodiversity [1].
Crop rotation brings biodiversity in the time scale. It is mandatory on organic farms and is stated as a method to maintain and increase the fertility and biological activity of the soil, and means the prevention of damage caused by pests, diseases and weeds [8]. Due to more diverse crop rotation and the use of green manure and intercroppings on organic farms, there is also greater biodiversity. Furthermore, using domestic populations of seed varieties preserves biodiversity, but the production of alternative crops (rare, underutilized, disregarded, neglected or new) increase biodiversity at the filed level [22].
The biodiversity of weed communities in agro-ecosystems provides several valuable ecological functions [23]. Conventional and integrated production systems tend to be similar in both intensity of management and within-field biodiversity, but organic production tends to support greater density, species number and biological diversity in comparison with other investigated production systems [24]. At the field level, species richness was the greatest on organic farms where there was a greater abundance of weeds [24-27, 31; organic production system had the highest biodiversity of weed species [28-31]. Organic agricultural practices yielded more weed species in root crops, red clover/grass mixtures and in winter triticale. Weed species richness was reduced in red clover/grass stands, while root crops and spring barley undersown with red clover and grasses decreased weed species diversity, which is also important for achieving higher yields in an organic production system. The species composition and in particular the quantitative structure of weeds were affected more by crop species and cultivation regime, compared to different agriculture practices (organic vs. integrated). Weed communities of crops grown using organic and integrated farming systems were more similar in terms of species composition than quantitative structure [30].
The maintenance of a diverse weed community is one step towards the sustainability of an agro-ecosystem through improved nutrient cycling and pest control, improved soil chemical and physical properties, and the reduction of soil erosion. An important aspect in the evaluation of the environmental impact of production systems is the biodiversity index for weed species (Table 2). Using the Shannon-Weaver diversity index for weeds of different production systems (conventional, integrated, organic) growing white cabbage and red beet showed that the biodiversity index was significantly higher in organic systems (0.86 in organic vs. 0.66 in conventional systems for cabbage and 0.81 in organic vs. 0.59 in conventional for red beet). Using ecological footprint calculation for the evaluation of different production systems showed that organic farming had the lowest impact on the environment. In the case of white cabbage and red beet production, ratio in ecological footprint between organic and conventional production was 1 to 3.5 [10].
The emerged weed flora is more affected by recent agrochemical inputs than the seedbank, which is buffered by the persistence of weed seeds in the soil. The seedbank is more strongly influenced by soil characteristics, such as the percentage organic carbon and percentage total nitrogen than by management [26]. The same weed species were in the seedbank and at field counted as germinated weeds, totalling 29 weed species in the survey (Table 2). The accumulated number of observed species pooled over fields was highest in the organic production of white cabbage and red beet, with 29 and 28 species, respectively. Within the conventional crop rotations, 18 species were observed in the cabbage field and 17 in the red beets field, while 20 and 19 were observed in the integrated crop rotation for cabbage and red beets. The differences in the number of weed species between conventional and integrated fields for cabbage were not significantly different; however, the difference when comparing organic and conventional fields was significantly different for both vegetables. For red beet, differences among all production systems were significant, which is contrary to the findings of [30], where weed communities of crops grown under organic and integrated farming systems were similar with regard to species composition but not quantitative structure. Different farming practices (described as organic, integrated and conventional) appeared to exert selection pressure on the species composition of the seedbank, building up different communities under the three farming systems over time [26]. These effects were scale dependent. At a within-field scale, species richness was greatest in organic farms, where there was a greater abundance of weeds; this was similar to our results and those of many others [24-31]. These results suggest that weed species diversity can be promoted by using organic cropping practices [31].
\n\t\t\t | \n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t | ||
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t
Control Conventional Organic Integrated Biodynamic | \n\t\t\t0.38d 0.66c 0.86a 0.74b - | \n\t\t\t14c 18b 29a 20b - | \n\t\t\t0.32d 0.59c 0.81a 0.64b - | \n\t\t\t13c 17b 28a 19b - | \n\t\t\t11.58b 11.25b 22.41a 13.00b 24.00a | \n\t\t
Shannon-Weaver diversity index (H\') and the frequency of occurrence (O) of weed species from the 30 species present in white cabbage and red beet in different production systems [10],3 and the influence on earthworm population [9, 36].
a-d Mean values followed by different letters within a column are significantly different (Duncan, α=0.05)
Organic farming systems are generally associated with increased biological activity and increased below-ground biodiversity. The main impacts on biological fertility do not result from the systems per se, but are related to the amount and quality of the soil organic matter that is used in the farming system, as well as the disruptions of soil habitat using different tillage tools. Even within the constraints of organic farming practices, it is possible for farmers to make changes to management practices using less tillage, which will tend to improved soil biological quality [32]. An important part of soil biodiversity is arbuscular mycorrhizal fungi, which can provide several benefits to plants and ecosystems. Organic farming enhances arbuscular mycorrhizal fungi, communities of which are similar in organically managed fields and in semi-natural species-rich grasslands; however, significantly less communities are found in conventionally managed fields. Their richness increased significantly over time since conversion to organic agriculture [33]. Soil microorganisms and other parts of soil biota including earthworms are also important drivers of soil fertility. Organic farming is based on the principle of the maintenance and enhancement of soil life and natural soil fertility, soil stability and soil biodiversity for preventing and combating soil compaction and soil erosion, and for the nourishing of plants primarily through the soil ecosystem [8]. Furthermore, our research results investigating the number and mass of earthworms as an indicator of soil biodiversity confirmed the effects of different production systems (conventional, integrated, organic, biodynamic) on the population of earthworms following the harvesting of different crops [9].
The studied production systems significantly influenced total earthworm population (Table 2) and small earthworms [36]. Both were shown to be higher in number in the biodynamic and organic production systems compared to the control, conventional and integrated production systems. When compared to control plots, as well as those managed without fertilizers and plant protection agents, there were roughly 2.7 and 2.5 times more small earthworms in biodynamic and organic production systems, respectively. In the same manner, the total earthworm population in the biodynamic production system was 207% and in the organic production system, 193% of this was counted for the control treatments. Similarly, the beneficial effect of organic farming on earthworms has been emphasized by other investigations [34, 35]. The abundance of earthworms, as well as their total body mass, was affected by plant species occurring in crop rotation. Oil pumpkins were revealed to have a beneficial effect on earthworms. There was also a significant production system and plant species interaction concerning the population of small earthworms [36]. In addition to a production system, tillage is also a major driver for altering communities of earthworms and microorganisms in arable soils. The use of reduced tillage provides an approach for eco-intensification by enhancing inherent soil biota functions in organic arable farming [37].
Biodiversity, as one of the most important ecosystem services of organic farming, is firmly connected to biocontrol and pollination services [2]. While the field of organic crop production has increased globally, the potential interactions between pest management in organic and conventionally managed systems have to date received little attention [38]. Organic agriculture improves biodiversity at the field level, but potential interactions with the surrounding landscape and the potential effects on ecosystem services are less well known. Predation of aphids was the highest in organic fields in mixed landscapes and lower in more uniform surroundings. The results of comparing 153 farms from five countries showed that organic agriculture improved the biodiversity of plants and birds in all landscapes, but only in more diverse surroundings did it improve the potential for biological control. Contradictory results showed the necessity for taking into consideration production methods (organic vs. conventional) and regional landscape complexity for developing agri-environmental schemes for the future [39]. Organic farming is one of the most successful agri environmental schemes, as humans benefit from high quality food and farmers from higher prices for their products; additionally, this approach often successfully protects biodiversity. Based on the assessment of 30 triticale fields (15 organic vs. 15 conventional) and the comparison of five conventional fields that were treated with insecticides and 10 non-treated conventional fields, it was found out that organic fields had five times higher plant species richness and about 20 times higher pollinator species richness compared to conventional fields. In contrast, the abundance of cereal aphids was five times lower in organic fields, while predator abundances were three times higher and predator-prey ratios 20 times higher in organic fields, indicating a significantly higher potential for biological pest control in organic fields [40]. Aphid density was also significantly lower in organic wheat fields compared to conventional fields, based on the assessment of 216 wheat fields during a two-year study [41]. Another positive impact of crop genetic diversity where wheat is concerned was found on below (collembola) and aboveground arthropod (spiders and predatory carbides) diversity at the field scale, which may be the result of a wider variety of food resources or more complex crop architecture. Increasing crop genetic diversity can therefore be an easy-to-implement scheme for benefiting farmland biodiversity [42].
Despite decades of European policy to ban harmful pesticides, the negative effects of pesticides on wild plant and animal species are nonetheless present and can be observed through losses pertaining to biodiversity. Chemical pesticides minimize opportunities for biological pest control. If there is an aim for biodiversity to be restored in Europe, opportunities should be created for crop production utilizing biodiversity-based ecosystem services such as biological pest control; what is needed is a Europe-wide shift towards farming employing the minimal use of pesticides over large areas, not only on organic farming areas [43]. Insecticide treatment in conventional fields had only a short-term effect on aphid densities, while later in the season, aphid abundances were even higher and predator abundances lower in treated compared to untreated conventional fields. Preventative insecticide application in conventional fields has only short-term effects on aphid densities but long-term negative effects on biological pest control. Therefore, conventional farmers should restrict insecticide applications to situations where thresholds for pest densities have been reached. Organic farming increases biodiversity, including important functional groups like plants, pollinators and predators, which in turn enhance natural pest control [40].
Biodiversity supplies multiple ecosystem services to agriculture. In addition to the potential for biological pest control, pollination problems are a topic now also being addressed in EU agriculture policy [43]. Declines in insect-pollinated plants and their pollinators have been reported as a result of agricultural intensification [44]. Reducing farming intensity with conventionally managed leys does not seem to be as effective as organic farming for delivering crop pollination services [45]. The abundance of pollinators was more than 100 times higher on organic fields. Plant and pollinator species richness, as well as predator abundances and predator-prey ratios, were higher at field edges compared to field centres, highlighting the importance of field edges for ecosystem services [40].
Pollination systems within intensive grassland communities may be different from those in arable systems. Results from comparing plant community composition among 10 pairs of organic and conventional dairy farms indicate that organic management increases plant richness in field centres, but that landscape complexity exerts a strong influence on both organic and conventional field edges. Insect-pollinated forb richness showed positive relationships to landscape complexity, reflecting what has been documented for bees and other pollinators [44].
Hedges provide important nesting, feeding and sheltering sites for birds in agricultural areas, while organic farming also enhances the environments of farmland birds [15, 18, 46]. However, little is known about how the interaction of (the amount of) hedges and variables pertaining to the organic management of the landscape scale affects birds. Birds were surveyed in the fields and in the adjoining hedges on conventional and organic winter wheat fields and meadows. More bird species occurred in organic than in conventional fields, regardless of land-use type. Hedge length had a much stronger effect on bird richness than organic farming practice. The interaction of landscape complexity and hedge length was found to be connected. Hedge length enhanced bird richness only in the case of simple landscapes. In more complex landscapes, the local effect of hedge length levelled off, because bird richness was high even without local hedges. Adding hedges or introducing organic farming practices should be primarily promoted in simple landscapes, where it particularly makes a difference for biodiversity [46].
The effect of organic farming differs depending on the scale of uptake of a particular landscape. The local effect of organic farming was found to be consistently strong, with higher diversity in borders adjoining organic fields, most likely due to the lack of herbicides used on organically managed farmland. In addition to the proportion of semi-natural habitat, which is important for farmland biodiversity, the management practice of cropland can also influence diversity in semi-natural habitats. Forb richness, which was evaluated as an agri-environmental indicator for biodiversity was also higher within borders situated in landscapes with a high proportion of organic land, irrespective of local management; this was possibly as a result of the dispersal of primarily annual plant species from the organically managed fields into the borders (mass effect). Farming practice at a local and a landscape scale can independently influence plant species richness, indicating that organic farming can also influence diversity at larger spatial scales, as well as outside organically managed land [47]. Organic farming enhances species richness and the abundance of many common taxa, but its effects are often species specific, as well as trait or context dependant. Landscape enhances or reduces the positive effects of organic farming, or acts through interactions where the surrounding landscape affects biodiversity differently on organic and conventional farms [48].
Around the world, small farms are those that practice high-diversity agriculture. Small farmers often choose to cultivate several varieties of the same crop; additionally and perhaps more importantly, different farmers in a given locality often cultivate different varieties. On the other hand large farms usually sow a single variety over a wide area [49]. Small farms may in this way have an indirect, positive effect on biodiversity, since these farms normally have smaller land parcels and thus more field edges, which are relatively species-rich. Although the average organic farm is bigger in the EU than its conventional counterparts [50] and in some cases is “conventionalized”, organic farming is nonetheless generally viewed as small farms. The world\'s majority of food is produced by smallholder farmers who grow over 70% of all our food. Organic farming on small farms leads to an increase in food production and to greater benefits for the ecosystem by improving soil organic matter, reducing erosion and increasing biodiversity. At the same time, organic farming also allows farmers to receive higher prices for their value-added produce and provide them with opportunities to export to markets niche [51]. The report of a study focusing on farming systems in Africa showed that it is possible to set broad priorities for agricultural intensification based on the organic principles of health, ecology, fairness and caring for the earth. Ecological principles and technologies can be used to support farmers in obtaining food security and improving their livelihoods without destroying the local indigenous biodiversity [52].
Agricultural intensification has caused significant declines in biodiversity, while the profound intensification of European agricultural practices in the past number of decades continues. This is due to decreasing crop diversity, simplification of cropping methods, the use of fertilizers and pesticides and the homogenization of landscapes, all of which have negative effects on biodiversity in agricultural areas. Agricultural management practices can have a substantial positive impact on the conservation of the EUs wild flora and fauna. Agri-environmental schemes including organic farming are thought to benefit biodiversity. Agri-environmental payments are part of Common agriculture policy, which promotes the multifunctional role of farming as a provider of food products and a steward of diverse landscapes, as well as the cultural and natural heritage of rural areas. Furthermore, in the future, according to the EU regulation 1305/2013, each member state has to introduce agri-environmental measures for enhancing biodiversity and the preservation of high nature value farming and forestry systems [53]. Ecosystem services payments must be based on a standardized and transparent assessment of the goods and services provided. This is especially relevant in the context of EU agri-environmental programmes, but also for organic-food companies that foster environmental services on their contractor farms [54].
Agri-environmental schemes have been introduced to minimize the effects of agricultural intensification and enhance farmland biodiversity, but evaluations have produced inconsistent results [47]. Biodiversity is in different countries supported by different measures (i.e., strips and hedges, crop rotation, autochthone varieties, Nature 2000 measures), as is organic farming, which enhances the species richness and abundance of above and below soil taxa [15-20]. Traditional farming contributes to the safeguarding of certain natural or semi-natural habitats. Many valuable habitats and the presence of species have a direct interdependence with agriculture (e.g., many bird species nest and feed on farmland). Two major changes have contributed to upsetting the delicate balance between agriculture and biodiversity: (i) specialization and intensification of certain production methods (such as the use of more chemicals and heavy machinery); (ii) marginalization or abandonment of traditional land management, a key factor in preserving certain habitats and site-specific biodiversity. In some EU member states, land abandonment and the withdrawal of traditional management may become a threat to biodiversity on farmland. Therefore, preventing these processes is a key action for halting the loss of biodiversity. The Common agricultural policy addresses the preservation of habitats and biodiversity by specific rural development measures targeted at the preservation of habitats and biodiversity (agri-environmental and Nature 2000 payments), as well as requirements included in the scope of cross compliance for birds and habitats [55].
Agri-environmental payments to farmers for the conversion from conventional to organic farming or remaining inorganic should encourage them to participate in schemes, thereby responding to the increasing demand by society for the use of environmentally-friendly farm practices and also for high standards of animal welfare, as is the case in organic farming. In order to increase synergy in biodiversity and the benefits delivered by the organic farming, other measures should also be promoted and supported among organic farmers in order to cover larger areas or other protected areas, e.g., Nature 2000 [53].
In agricultural landscapes, farmers have a large impact on biodiversity through the management decisions and agricultural practices that are used on their farms. Farmers\' perceptions of biodiversity and its different values influence their willingness to apply biodiversity-friendly farming practices. Organic and conventional farmers\' perceptions of the different values of biodiversity were analysed across three European countries. Farmers\' perceptions of biodiversity were strongly connected to their everyday lives and linked to farming practices. In addition to recognizing the importance of variety, species and habitat diversity, farmers also acknowledged wider landscape processes and attached value to the complexity of ecological systems. It was found that organic farmers tended to have a more complex and philosophical approach to biodiversity, with little differences being observed between these farmers; conventional farmers, on the other hand, exhibited more differences among themselves. Furthermore, ethical and social values were important for all farmers, but economic value was more important for conventional farmers, which has an impact on their behaviour [56].
Based on a survey among organic and conventional farmers, it was concluded that they had similar attitudes to farming results and to the environment; however, organic farmers were better informed about environmental issues and carried out more environmentally-friendly practices and behaviours. More biodiversity was found on environmentally-friendly orientated farms and less on high production-orientated farms. Organic farmers with more positive attitudes to the environment and who were better informed about environmental topics had higher biodiversity on their farms compared to others. Although there were disparities between attitudes and actual behaviours in relation to the environment among organic farmers sharing similar attitudes to conventional farmers, they were more prepared to inform themselves about and carry out environmentally-friendly farming. Results of the comparison study showed that biodiversity benefitted more from organic farming and environmentally- oriented farmers, and that there is an important link between farmers\' environmental attitudes and knowledge and the beneficial effects of organic farming on biodiversity [57].
Farmers strongly acknowledged ethical and social biodiversity values. This suggests that soft policy tools can also foster biodiverse-sensitive farming methods that are complementary to mainstream monetary incentives [55]. As farmers receive a majority of agri-environmental payments, they can be more involved in data generation and conservation management. Farm size is very important in terms of the amount of payments that are provided per hectare and for improving biodiversity on a bigger scale. A standardized model for measuring on-farm biodiversity does not yet exist in practice. Performance indicators should be focused on and farmers should be included in generating this information. A framework is needed for assessment of the results and for management measures that can be employed on farms. Another requirement is ease of application, which encompasses the simplicity of gathering input data and its clarity to those farmers who will apply it [54]. Conservation-oriented thinking and better environmental education among farmers should be encouraged for those who already participate in an agri-environmental scheme and even more so amongst newcomers. In this way, the benefits of the agri-environmental schemes for the environment can be maximized [57].
An open source farm assessment system was prepared for the assessment of biodiversity including biotopes, species, biotope connectivity and the influence of land use. Interviews with the test farmers showed that the assessment methods can be implemented on farms and that they were understood by farmers [54].
The analysed data showed that in the past decades, the specialization and intensification of agriculture production methods have had negative effects on biodiversity. The future holds the challenge of designing more sustainable farming systems that are productive and maintain or enhance the provision of ecosystem services, including biodiversity. The significantly positive effect of organic farming on biodiversity compared to conventional farming was noticed in 80% of cases; in 16%, differences were unclear and less biodiversity was found in 4% of comparisons [15, 17, 18], where seven to 10 biodiversity indicators were taken into account. Small farms in particular may have an indirect positive effect on biodiversity. These farms generally have smaller land parcels and thus more field edges, which are relatively species-rich.
We can conclude that the benefits of organic farming on biodiversity are as follows:
Organic farming increased species richness by about 30% and had a greater effect on biodiversity, as the percentage of the landscape consisting of arable fields increased. It was found that organic fields had up to five times higher plant species richness compared to conventional fields. For example, plant and butterfly species richness was up to 20% higher on organic farms and butterfly abundance was about 60% higher. After the conversion from conventional to organic farming abundance of butterflies was increased for 100%. Organic farming enhanced arbuscular mycorrhizal fungi and its communities. This was similar in organically managed fields and in semi-natural species rich grasslands, but significantly fewer communities were found in conventionally managed fields. Their richness increased significantly over time from the point of a conversion to organic agriculture.
The occurrence of weed species was significantly higher in the organic production of white cabbage and red beet compared to integrated and conventional production. The biodiversity index was significantly higher in organic production compared to the conventional method, 0.86 vs. 0.66 for cabbages and 0.81 vs. 0.59 for red beets. Conventional and integrated production systems tended to be similar both in terms of the intensity of management and regarding within-field biodiversity; however, organic production tended to support greater density, species number and biological diversity compared to other investigated production systems.
Earthworms were more abundant on organically managed fields. In organic and biodynamic farming plots, the number of earthworms was on average two times higher compared to integrated, conventional and control plots.
Biodiversity as one of the most important ecosystem services of organic farming is firmly connected to biocontrol and pollination services, which are enhanced when using no or less chemicals. The abundance of cereal aphids was five times lower in organic fields, while predator abundances were 20 times higher in organic fields, indicating a significantly higher potential for biological pest control in organic fields. Organic fields had 20 times higher pollinator species richness compared to conventional fields. Pollinators and predator abundance was higher at field edges compared to field centres, highlighting the importance of field edges for ecosystem services. Edges provide important nesting, feeding and sheltering sites for birds in agricultural areas. Thus, organic farming enhances farmland birds.
Overall, organic agriculture appears to perform better than conventional farming and provides important environmental advantages such as halting the use of harmful chemicals and their spread in the environment and along the trophic chain, reducing water use, as well as reducing carbon and ecological footprints. As we have underscored, organic farming fulfils the promise to protect biodiversity better than conventional farming. However, in the European commission document, The EU Biodiversity Strategy to 2020 [1], organic farming is not even mentioned, while in the European Parliament resolution regarding the strategy [6], organic farming is mentioned only once in the context of a call for a strengthening of Pillar II and for drastic improvements to the environmental focus of that pillar, and to the effectiveness of its agri-environmental measures. Supporting farmers to convert their properties to organic land and to maintain organic farming within the scope of agri-environmental schemes as a part of Common agriculture policy can have a significant impact on biodiversity as a result of management decisions farmers apply to their agricultural land.
The results presented in this paper are in part an output of the national research project J4-9532: "The quality of food dependent on the agricultural production method", funded by the Ministry of Higher Education, Science and Technology of the Republic of Slovenia and Slovenian Research Agency.
Cancer is the world’s second leading cause of death and accounts for around 1 in 6 deaths worldwide. A projected 18.1 million new cancer-related cases and 9.6 million cancer-related deaths were recorded in 2018, according to the 2018 GLOBOCAN study. Lung cancer is the most frequently diagnosed cancer for both sexes with 11.6% of the total cases of cancer and is also the leading cause of cancer death with 18.4% of the total cancer deaths. Cancer, a cellular overgrowth disorder, involves cellular transformation, apoptotic dysregulation, uncontrolled proliferation, invasion, angiogenesis, and metastasis [1]. A significant correlation between chronic infection, inflammation, and certain forms of cancer have been suggested in clinical and epidemiological research, with inflammation frequently occurring in and around tumors [2].
Recent studies have shown that chronic inflammation that regulates the microenvironment of the tumor is involved in the initiation of the tumor and is a critical component of tumor promotion and progression [3]. The insistent inflammatory microenvironment contributes to increased promotion of the tumor, accelerated progression, invasion of the surrounding tissues, angiogenesis, and eventually metastasis [4]. The tumor microenvironment has a vast abundance of cytokines as well as other inflammatory mediators which impact immunosuppression, cancer growth, tissue remodeling, and angiogenesis [5]. Cytokines are a heterogeneous group of glycoproteins or small soluble polypeptides (secreted or membrane-bound) chiefly produced by the immune cells which under normal conditions are produced in response to specific stimuli exerting pleiotropic and redundant effects thereby altering the behavior of the identical or different cells by regulating the growth, differentiation, and activation of normal cells especially immune cells [6]. Depending on the microenvironment, cytokines may either have pro- or anti-inflammatory or may even have immunosuppressive activity [7]. In response to both antigen-specific and nonspecific stimuli, the development of multiple cytokines by immune cells plays a crucial role in the outcome of inflammatory immune responses [8]. They are either released in response to a variety of cellular stresses, including carcinogen-induced injury, infection, inflammation, and immunity that inhibits tumor growth and progression, or are host-derived cytokines that cause cancer cells to promote growth, reduce apoptosis, aid invasion and metastasis. The role of cytokines in subsequent settings is to cause a host response aimed at controlling cellular stress and reducing cell damage. Although critical insult control encourages tissue repair, failure to control the injury can lead to the insistent development of cytokines, leading to further aggravation of tissue damage. Depending on several stages of cancer development and progression, host responses to cellular stress may influence it inherently [9]. Therefore, the cytokine mixture produced in the tumor microenvironment plays an important role in the pathogenesis of cancer [10]. The molecular and cellular changes that eventually lead to cancer stimulate changes in the local cytokine environment, stimulate immune cell intrusions, and release additional cytokines that function in an autocrine or paracrine manner [11]. In addition, pro-inflammatory cytokines are associated with anorectic and cachectic disease in patients with progressive cancer, pain in the form of both algia and dynia, toxicity, and resistance to treatment. Physical exercise can, however, alter cytokine levels and decrease fatigue in cancer patients, and may also increase their prognosis [7].
Cytokines provide a key molecular link between inflammation, tumor promotion, and progression which mainly include the interferons (IFNs), the interleukins (ILs), the tumor necrosis factor super family (TNFs), the transforming growth factor super family (TGFs), and Colony Stimulating Factors (CSFs) [12].
Genetic variations in the human genome can govern the risk of cancer development, symptoms, treatment, and its outcome [7]. In recent years, within cytokine gene sequences, many single nucleotide polymorphisms (SNPs) and a small number of microsatellite polymorphisms have been reported, mainly within their promoter regions [13] Indeed the most common variations in the genome are the SNPs [14]. Some suggest that the differences in SNPs may also help explain cancer disparities among the various ethnic groups [15]. Differential levels of gene transcription, including TNF -308 and IL-10-10822 can be associated with some of these polymorphisms [16]. Several genetic studies have attempted to associate these cytokine polymorphisms with cancers; however, the studies are still limited, but increasingly evolving. The link between TNF alpha-SNPs and specific cancers, including oral carcinoma, has been documented in several studies [17] and non-Hodgkin’s lymphoma [18], but most of these associations are refuted by others. IL-1 gene polymorphisms that provide increased expression of this pro-inflammatory cytokine are associated with an increased risk of cancers, mainly of gastric origin [19]. The association between IL-1B/IL-1RN polymorphisms and the development of gastric adenocarcinoma following
IL-6 is a major inflammatory pleiotropic cytokine that is considered a main growth-promoting factor [21]. Several IL-6 target genes are involved in the progression of the cell cycle and apoptosis suppression, which emphasizes the significance of IL-6 in tumorigenesis [22]. Many polymorphic IL-6 studies have shown that it is associated with breast cancer risk and prognosis. A study indicates that IL-6 is a predisposing genetic factor that contributes to the prognosis of breast cancer, with a G/C polymorphism associated with high levels of IL-6 production within the promoter region of the IL-6 gene correlating with a worse prognosis. While few studies have been published to date on polymorphisms within the IL-6 gene cluster and breast cancer [23], there is still controversy about the evidence on 174 G/C IL-6 polymorphism in breast cancer. The presence of IL-6 polymorphism was associated with an improved outcome in high-risk breast cancer, reported by DeMichele et al. [24]. Iacopetta et al. [25] found that the IL-6 polymorphism was predictive of the phenotype of aggressive breast cancer
IL-10 is an immunosuppressive and anti-angiogenic multifunctional cytokine that can have both tumor-promoting and inhibiting properties [26]. The IL-10 gene promoter has been recognized to have a significant number of polymorphisms (primarily SNPs) [27]. As a consequence, promoter polymorphisms have been the most scrutinized, particularly with regard to possible gene transcription and protein production influences. Many studies on the interactions between genotypes of IL-10 and breast cancer have been published. One small breast cancer study confirmed that the low-expression 21082 AA genotype was associated with a high risk of disease [28]. In comparison, a larger case-control study found a correlation between the 2592 AA genotype and the reduced risk of breast cancers [29] but did not associate with any clinical parameters.
Interferon-γ (IFN-γ) is the cytokine that likely has a vital role in carcinogenesis. Several combined epidemiological studies have shown that IFN-γ can function as a major risk factor for breast cancer development and progression, primarily due to genetic polymorphisms of IFN-γ [30]. Interestingly, genetic polymorphisms in the IFN-γ gene are likely to affect the degree of IFN-γ expression, leading to impaired function or decreased IFN-γ activity; subsequent low IFN-γ expression levels would encourage tumor development, which can contribute to can susceptibility to breast cancer [31]. In order to be more precise, many common IFN-γ gene polymorphisms have been found to increase the risk of breast cancer, such as rs20697 (−1615C/T) and rs2430561 (+874T/A) [30, 32, 33]. Contradictory findings have also been reported recently, although several studies have also suggested that IFN-γ genetic polymorphisms can play a critical role in breast cancer pathogenesis [30, 31]. Gene polymorphisms, with low levels of IFN-γ, can alter the function and expressions of IFN-γ. The rs2430561 A>T polymorphism was revealed by Liu et al. in intron 1 of IFN-γ [34]. The gene can transform its transcription functionally and lead to susceptibility to breast cancer [35]. Another meta-analysis shows that genetic polymorphisms within the IFN-γ gene were significantly associated with an increased risk of breast cancer, especially the polymorphism of 2430561 T>A. No connection was, however, identified between rs2069705 C>T polymorphism and breast cancer susceptibility. Genetic polymorphisms and the risk of breast cancer in Asians, but not among Caucasians, suggest that ethnic differences may affect the susceptibility of individuals to breast cancer [36].
TNF-α is an essential pro-inflammatory cytokine for human cancer growth and progression [37] by stimulating the development of genotoxic molecules (NO, ROS) that can lead to DNA damage and mutations, TNF-α can promote tumor initiation and progression. The increased risk of many cancers, including breast cancer, is associated with genetic polymorphisms that boost TNF-α development [33].
Increasing evidence has shown that a SNP in the promoter region of the TNF-α gene (−308G>A, rs1800629) induces genetic susceptibility in many forms of tumors like BC [38]. The TNF-α-308A allele tends to have a higher constitutive and inducible expression, as the −308G>A mutation affects the AP-22020 consensus binding site [39]. The results on the association of –308 (G/A) TNF-α polymorphism with breast cancer development are rather contradictory [40]. A rise in homozygous (−308AA) TNF-α genotype frequency was significantly associated with the development of breast cancer and poor prognosis in Tunisian women [40]. No link between the homozygous (−308AA) TNF-α genotype and breast cancer risk was identified in Holland. The association of allele (−308A) TNF-α with tumor vascularization has, however, been shown to be [41]. Where the majority of studies found no link between-308 (G/A) TNF-α polymorphism and the occurrence of breast cancer [42, 43]. Two recent meta-analyses have confirmed that the genotypes TNF-α-308GA and AA were significantly associated with a reduced risk of breast cancer in Caucasians [14, 16, 44, 45]. The allele frequencies in the controls of some studies [42, 46] did not show compliance with Hardy-Weinberg (HW) in the meta-analyses. In addition, Yang et al meta-analysis included one study comparing the frequencies of various genotypes of TNF-α-308 polymorphism in patients with benign breast disease and controls, and another study that did not have frequencies for each genotype [14, 16, 44, 45]
IL-1 α and IL-1β are pro-inflammatory and potent cytokines. It has been stated that the genes of this family are highly polymorphic that modulate the expression of IL-1β. IL-1β −511T/C, −31C/T, and +3593C/T are the most studied SNPs of the IL-1 gene family, in addition to 86bp of VNTR in intron 2 of the IL-1RN gene with 5 different alleles [47]. IL-1β-31C/T is associated with increased transcription initiation factor binding that has been shown to participate in hepatic carcinogenesis [48]. In the presence of IL-1β (−511CC and −31TT) genotypes, allele 2 was known to be a risk for HBV-related hepatocellular carcinoma (HCC). The IL-1β-511C allele was found to be an IL-1RN risk with no HCCC risk [49]. On the other hand, there was no connection between the IL-1β-511C allele and HCC in several studies. In the Wang et al. analysis [50], the IL-1β-31TT genotype and the IL-1β-511/−31CT haplotype were associated with an increased risk of HCC-related HCC and the risk factor was not the IL-1RN VNTR polymorphism.
Polymorphisms of TNF-α (−1031T/C, −863C/A, −857C/T, −308G/A and −238G/A) are found to alter TNF-α development [51]. A critical risk factor for HCCC is regarded as TNF-α −308G/A [45], but TNF-α-238G/A is engineered to play a passive role in the risk of HCC [52]. On the other hand, several other studies indicated an increased risk of HCC for the allele TNF-α-308A [51]. The association between TNF-α promoter alleles such as TNF-α-308A and TNF-α-238A and various TNF-α-238A expressions is indicated in several studies [39].
In order to counteract inflammatory reactions, IL-6 is a key factor in viral infections. In the promoter area, the most studied genetic polymorphisms in the IL-6 gene are located downstream (−597G/A, −572G/C, −174G/C, and −373A/T), and have an effect on IL-6 development levels at the transcriptional stage [52]. These are reported to be associated with chronic hepatitis, where IL-6-572G/C was found to be associated with the risk of HCC-related HBV [53].
There are three associated genes in the IL1 cluster: IL1-A, IL-1B, and IL-1RA that encode the signal proteins IL-1, IL-1, and their receptor, IL-1RA, respectively. The association between IL-1B and IL-1RA gene polymorphisms and the development of gastric cancer (GC) has been identified in numerous studies [47]. Polymorphisms of IL-1 are located in positions-511 (CT, rs16944), -31 (TC, rs1143627), and 3954 (CT, rs1143634) that affect the expression of IL-1. The majority of studies classify the IL1β-511 polymorphism T allele as normal among Caucasian individuals with non-cardiac GC but preferably for cancer of the intestinal subtype. It is, therefore, feasible to propose this SNP as a possible GC predictive marker. Even after numerous meta-analyses have been carried out, investigations of the IL1B-31 TATA-box polymorphism appear to be controversial. Around 14 studies [54] reported a slight non-significant correlation between the C variant allele and GC risk in comparison with TT homozygotes. Again, in contrast with Hispanic or Caucasian cultures, there was no correlation between Asian groups. A modest increase in the intestinal GC subtype among C allele carriers in Caucasian populations was suggested by histologic stratification, but this statement was not true for the diffuse GC subtype. Wang et al. also found that the +3954 gene polymorphism T allele contributes to the GC risk. A lack of interaction between the +3954 polymorphism and GC was stated by Xue et al. [55]. A limited number of studies were conducted on the IL-1β-+3954 C/T polymorphism [55].
In the differentiation of CD41-positive T cells into Th1 and Th2 effector subsets, IL-2 effectively controls the immune response and plays an important role. IL-2 leads to the activation and transmission of immune responses that are inflammatory, including
IL-6 appears to be involved in gastric oncogenesis, as serum IL-6 levels show an increase in the gastrointestinal cells and mucosa of patients suffering from GC [60]. The data collected indicated that the polymorphism of IL6-174G/C was related to the risk of GC in the West. The suppression of tumor necrosis factor-α and IL-11 could explain the carcinogenic properties of IL-6 [61]. In 2009, Kang et al. showed a strong negative association among HP-positive cases and controls between the IL6-572G/C polymorphism GG genotype and duodenal ulcer risk. The effect of the G allele on the rate of synthesis of proteins has not been determined to date, and the role of this SNP remains unclear.
IL-8 improves the proliferation and migration of cells and serves as a chemical attractor and mediates chronic inflammatory processes [62]. In contrast, mucosal levels of IL-8 were found to be elevated in GC patients, and the prognosis was significantly lower in patients with high expression of IL-8 compared to patients with moderate levels of this protein [63]. IL-8 can induce Reg protein expression in stomach cells, which intensifies gastric mucosal cell proliferation and may indirectly promote the initiation of GC [64]. In the IL-8 gene locus, fifteen functional polymorphisms occur, and some can alter gene expression [65]. Several IL8- case-control studies on 251A/T (rs4073), IL8 +396T/G (rs2227307), and IL8+ 781C/T (rs2227306) were conducted in which IL8-251A/T, A allele was associated with increased GCC [66]. Kang et al. [67] also found that higher GC risk is correlated with the AA genotype of HP-positive individuals. Due to conflicting findings, the role of IL-8 gene polymorphisms in GC remains unclear. The −251 polymorphism of the gene, however, seems to play a major role in the development of GC and needs further study. In this region, the +396 and +781 SNPs are almost unexplored.
IL-17A and IL-17F, synthesized by activated T cells, are characterized as pro-inflammatory. Five variants of this cytokine are known which differ in properties and sites of expression from the founding member IL-17A. Several studies have shown that IL-17 leads to gastric carcinoma growth and progression [68]. It has recently been suggested that a low IL-17 tumor expression rate can imply a poor prognosis in GC patients. Wu et al. reported that in comparison with the mutant AA genotype, the GA and GG genotypes of +7488 SNP were correlated with an increased GC risk and also reported the absence of a link between IL17-197G/A polymorphism and GC risk [69].
One of the pro-inflammatory cytokines strongly expressed in
The relation between the risk of IL-1 family polymorphisms, including IL-1A, IL-1B, and IL-1RN and prostate Cancer (PCa), has been less studied. There was no important correlation between PCa risk and IL-1B/IL-1RN polymorphism in several studies. In a recent meta-analysis, IL-1A, IL-1RN (rs315951 and rs3087263), and IL-1B+3953 (rs1143634) polymorphisms were not significantly correlated with the risk of PCa. In homozygote and recessive models, IL-1B-511 (rs16944) polymorphism was significantly associated with PCa risk, and in the heterozygote model, the allele comparison IL-1B-31 (rs1143627) polymorphism was also marginally significantly associated with PCa risk. Therefore, the meta-analysis indicated that IL-1B-511 (rs16944) and IL-1B-31 (rs1143627) sequence variants were significantly associated with PCa risk. This result presents more new evidence that pro-inflammatory cytokines and inflammation play an important role in the etiology of PCa [77].
Interleukin 6 (IL 6) plays a crucial role in the inflammatory phase among the cytokines involved in inflammation. Mandić et al., found that IL-6-174 SNP differs between ethnicities and that single polymorphic cytokine variants most likely have little effect on the susceptibility of PCa [78]. The study by Pierce et al. showed that circulating IL- 6 and its gene polymorphism did not affect the risk of PCa [79]. Whereas Mandal et al. had a contrary view [80]. Another meta-analysis of 11 independent studies, including 10,745 cases and 13,473 controls based on several recently published studies which indicated an inconsistent conflicting and inconsistent trends of association between IL- 6 (174 G/C) and PCa. IL- 6 (174 G/C) polymorphism has been found not to be a risk factor for prostate cancer in the general population [81].
IL-6 (interleukin-6) is a pro-inflammatory peptide that is actively involved in tumorigenesis [82]. The effect of IL-6 and IL-6 receptors (IL-6R) on the prognosis of esophageal cancer (EC) has been identified [83]. Systemic and/or local IL-6 therefore appears to be a central molecule in the stimulation of ESCC progression. Different studies have shown an association between various IL-6 polymorphisms and cancers. Polymorphism of IL-6-634G>C and prognosis after EC esophagectomy revealed that when EC patients were treated surgically, those with the IL-6-634G/G or G/C genotype had a 3-fold poorer prognosis than those with the C/C genotype. In comparison, IL-6R polymorphism and IL-6 tumor expression are not associated with prognosis [84]. With respect to EC, Oka et al. [85] stated that poor survival was associated with high serum IL-6 levels. Buraczyn et al., on the other hand, stated that in the presence of inflammatory stimulation, patients carrying the G allele and to an even greater extent the G/G genotype showed higher IL-6 output at position −634 in the IL-6 promoter region than patients carrying the C allele [86]. Kitamura et al. also reported that the 634 G allele is associated in vitro with increased IL-6 production in peripheral mononuclear blood cells [87]. While IL-6 levels are associated with different cancers, the relationship between IL-6 and EC polymorphisms requires further evaluation because less studies are available [88].
The pro-inflammatory cytokine family is the Interleukin 12 (IL-12) family, which is essential for host tumor resistance [89]. A few studies have determined whether polymorphisms and serum levels of the IL-12 family (IL-12A gene rs568408, IL-12Bgene rs3212227, IL-27 gene rs153109, rs17855750, rs181206) and its family receptor (IL-12Rb1, 378 C/G) gene are correlated with EC. Studies that revealed polymorphisms of IL-12 rs568408, rs3212227, and IL-12Rb1 gene 378 C/G and serum levels of IL-12p40 and IL-27p28 were significantly associated with the risk of EC [90]. IL-12Rb1 gene Codon 378 C to G causes a transition in amino acid (glycine to arginine), which may further weaken the transcript’s subsequent biological activity and is linked to many malignancies such as leiomyoma [91].
Interleukin-18 (IL-18) is another cytokine that is mainly involved in the inflammatory immune response and is a potent factor triggering IFN-γ. Genetic IL-18 gene polymorphisms have recently been observed to have a significant effect on the vulnerability of a number of inflammatory diseases and various malignancies, including EC [92]. Different SNPs have been identified in the promoter region of the IL-18 gene and are likely to influence gene activity [93]. In the promoter region of the same gene, three SNPs were found at distinct positions −137, 607, and 656 relatives to the transcriptional start site. A study conducted by Ye et al. in the Chinese population investigated 137 G/C and 607 C/A polymorphisms of the IL-18 gene in EC patients. The 137 GC and CC genotypes were associated with a significantly increased risk of ESCC as compared with the −137 GG genotypes as G to C substitution at position 137 abolishes a histone4 transcription factor-1(H4TF-1) nuclear factor-binding site and hence has an impact on IL-18 activity. Nevertheless, in EC patients, the genotype and allele frequencies of IL-18 promoter 607 C/A polymorphism were not substantially different from those in healthy controls. The results, therefore, indicate that IL-18 137 G/C polymorphism could be used as an ESCCC genetic susceptibility marker [94].
Tumor necrosis factor-alpha (TNF-α) is a pro-inflammatory cytokine that plays a major role in host defense and inflammatory responses but also induces cell death and tissue degradation in some instances [95]. There have been reports of dysregulated expression of TNF-α associated with a number of tumors, including EC, [96]. A number of SNPs of TNF-α gene have been found, which include TNF-α-238 G/A (rs361525), TNF-α-308G/A (rs1800629), TNF-α-857C/T (rs179972), TNF-α-863C/A (rs1800630), TNF-α-509C/T (rs1800469) and TNF-α-1031T/C (rs1799964) [83]. Among these, the most common TNF-α polymorphisms occur at position 308 in the promoter region and are extensively studied, showing a strong association with increased TNF-α production [97]. Many studies have focused on the association between TNF-α-308 G>A (rs1800629) and EC risk [98]. Deans et al. have found that the genotype AA TNF-α 308 is associated with an adverse prognosis of gastroesophageal cancer [99]. In contrast, the results of the Cui et al. study found that TNF-α-308G/A polymorphism was not associated with EC risk [100]. In addition, Guo et al. did not find a significant difference between EC patients and controls in the overall genotypic distribution of TNF-α-308G/A polymorphism [101]. In addition, few meta-analyzed studies report that TNF-α-308 G>A (rs1800629) is poorly associated with an increased risk of EC [102]. Conclusions on the role of TNF-α -308G/A gene polymorphism in the risk of EC have, therefore, been inconsistent.
The cytokine produced against viral and intracellular bacterial infections in the human body is Interferon-gamma (IF-γ). Many polymorphisms have been investigated mostly in IFN-gamma, which are significantly associated with many complications such as susceptibility to many infections [103]. It has been stated that a risk factor for EC may be the IFN-γ + 874AT genotype. The study by Du et al. has shown that IFN-γ + 874, T allele may predispose for EC [104]. Another research found that an important association existed between the genetic polymorphism of INF-γ 874A>T and infectious complications following esophagectomy in a cohort of EC patients [105].
Interleukin 1b (IL1b), a central IL-1b gene-encoded pro-inflammatory cytokine, has been associated with chronic inflammation and plays an important role in inflammatory pancreatic diseases, including pancreatic cancer [106]. In the production of pNETs, the functions of IL-1b −511C/T and +3954 C/T genotypes remain unclear. PNETs are a heterogeneous group with different biology and prognosis of tumors; they can occur as solitary tumors, and up to 15% of pNETS are part of hereditary syndromes. The findings of Maja et al. [107] showed a significant correlation between the IL-1b −511C/T genotype and CTCT −511/+3954 genotype combination and susceptibility to functional pNET growth, and the risk of non-functional pNET development were associated with patients with CTCC −511/+3954 genotype combination. All of these findings indicate IL-1b participation in the growth of pNET [107].
In T cell-dependent immunity, IL-2 is a potent pro-inflammatory cytokine and a central regulatory cytokine. Several SNPs) have been found to alter IL-2 production in the promoter region and to be associated with inflammation-based cancer [58]. The G-allele in the IL-2 promoter at the −330 position seems to correlate with higher IL-2 output [108]. It has been shown that during the cell cycle, dividing cancer cells release IL-2 in various concentrations and that IL-2 promotes cancer development [109]. Hofsli and collaborators found that GEP-NET carcinogenesis growth factors downregulate the IL-2 receptor, presenting proof of an additional mechanism through which neuroendocrine cancer cell growth is promoted [110]. It was found that G-allele raises the expression of IL-2 at the −330 position and that individuals homozygous for the G-allele have three times higher IL-2 values [108].
In the inflammatory etiology of pancreatic cancer, TNF-α plays a very crucial role. The risk factor for various forms of cancer, such as hepatocellular carcinoma, gastric cancer, and breast cancer, has been identified as TNF-α-308 polymorphism [111, 112, 113], while previous studies have reported that polymorphisms in the TNF-A-308 A/G gene are not linked to pancreatic cancer [78].
IL6 is an inflammatory pleiotropic cytokine released by different types of lymphoid/non-lymphoid cells [114]. Immune response, cell survival, proliferation, and apoptosis are critical for [113]. In the IL-6 promoter region, numerous polymorphic variants have been identified that are associated with IL-6 transcription activity [115] which indicates a connection to cancer [116].
IL-6 polymorphism has been shown to modulate changes in its expression to cause cancer risk, including bladder cancer. Association studies of IL-6 gene polymorphisms conducted in India and globally confirm the risk of several CC genotype and C allele cancers, especially BCC allele cancers [117, 118]. Fishman et al. have stated that IL-6-174 G/C polymorphic variation affects transcription and IL-6 protein expression [119]. Conversely, several studies from other parts of the Indian and Caucasian population indicated that conflicting findings were present [120, 121]. The variant genotype IL-6-174 G/C was shown to be significantly associated with an increased risk of BC [122] but no BC risk association was found by other authors [123]. In addition, there was no proven association between IL-6-572 G/C, -596 A/G polymorphisms, and BC risk [118].
A major inflammatory cytokine is the tumor necrosis factor-alpha (TNF-α) gene, which mediates a connection to all steps involved in tumor growth and development. TNF-α gene polymorphisms and their receptors have conceptualized the understanding of the genetic effects of inflammatory consequences [124]. Polymorphic sequence differences are mainly documented in association studies of various cancers like BC, with some studies refuting and other studies showing the association for cancer risk, mostly single nucleotide changes in TNF-α promoter [125, 126]. This contentious link between TNF-α polymorphisms and UBC is due to the race, sample size, and technical aspects involved. Of the 7 variants of the TNF-α gene studied by Marsh et al., 859T and +488A polymorphisms were significantly linked to BC risk [127]. Another research investigates 3 TNF-al-1031 T>C polymorphism SNPs where high risk was identified for controls of BC cases [128]. Similarly, experiments on TNF-al-308 G>A polymorphism have also reported controversial results [129, 130]. Although TNF-α-308 A variant alleles with a major risk relationship to BC risk were observed by Lima et al. [131].
Research by Brenner et al. found that the polymorphism of IL-4 (rs2243248, −1098T>G) was substantially correlated with the overall risk of glioma [132]. Another study showed that IL-4 induced aberrant Stat3 activation in glioblastoma cells but not in normal human astrocytes, and hypothesized that aberrant Stat3 activation induced by IL-4 could contribute to the pathogenesis of GBM cells [133].
IL4R encodes the interleukin-4 receptor alpha chain that can connect interleukin 4 and interleukin 13 to regulate the development of IgE [134]. In 2013, TianboJin et al. reported that rs1801275 in the IL-4R gene can predict the over-dominant model of Glioma susceptibility by 2.29-fold [135]. Furthermore, another article also stated that rs1801275 could increase the risk of studying glioblastoma [136]. However, an important link between mutant IL-4R alpha rs1801275 and gliomas was not found by Ruan et al. [137].
Many SNPS, like 1188A/C, in the IL-12 gene will affect its levels of expression and are associated with several tumors such as nasopharyngeal carcinoma [138] and breast cancer [139]. This SNP might influence the susceptibility of individuals to glioma. Haidar et al. stated that neither mutant (hetero or homozygous) genotypes nor mutant IL-12p40 1188A/C variant allele appears to be associated with gliomas [140]. In line with a meta-analysis review, this outcome [141]. The stratification by cancer type showed that the variant only represents a risk factor for cervical and nasopharyngeal cancer, although these authors found a substantial association of the variant with overall cancer.
IL-13 plays an important role in allergies and is essential for the suppression of tumor immune surveillance through an immune regulatory pathway [142]. SNPs, including rs25041, rs1800925, and rs1295686, found in the IL-13 gene, are closely linked to IL-13 expression. In human malignant glioma cell lines and in primary tumor cell cultures, IL-13 has been shown to be over-expressed [143]. The serum immunoglobulin E (IgE) level could be significantly increased by the rs20541 A allele (glutamine (Gln, Q) form) in different populations [144]. Evidence has also been established by previous research that IgE levels in patients with glioma were lower than in people without glioma [136]. It is very fair to expect the IL-13 gene rs20541 polymorphism to exert some effect on glioma susceptibility due to its important roles in immune surveillance and serum IgE level modulation. A recent meta-analysis review, however, indicates that the IL-13+rs1800925 genotype could be a risk factor for gliomas and that IL-13+rs20541 contributes to cancer [145] (Table 1).
Activity | Cancer type | Cytokines | Polymorphisms | Association | Allele | References | |
---|---|---|---|---|---|---|---|
Pro-inflammatory | Solid tumors | Breast | IL-6 | −174 G/C | High grade tumor | −174 CC | [25] |
IL-10 | 21082 G>A | Worst prognosis | −21082 AA | [28] | |||
High risk | −21082 AA | [29] | |||||
IFN-γ | +874T/A | Increased risk | +874 AA | [36] | |||
−1615C/T | No | — | [36] | ||||
TNF-α | −308G/A | Poor prognosis | −table308GA, AA | [40] | |||
No | — | [43] | |||||
HCC | TNF-α | 1031T>C | No | 1031T>C | [146] | ||
863C>A | Yes | 863C>A | [146] | ||||
857C>T | No | 857C>T | [146] | ||||
308G>A | Yes | 308G>A | [146] | ||||
IFN- γ | +874T>A | Risk factor | +874T>A | [147] | |||
IL-18 | 607A>C | Risk factor | 607A>C | [148] | |||
137C>G | Risk factor | 137C>G | [149] | ||||
148G>C | Risk factor | 148G>C | [150] | ||||
IL-16 | rs11556218T>G | Risk factor | rs11556218T>G | [151] | |||
rs4072111C>T | Risk factor | rs4072111C>T | [151] | ||||
rs4778889 | Risk factor | rs4778889 | [152] | ||||
IL-12A | rs3212227A>C | Risk factor | rs3212227A>C | [153] | |||
IL-12B | rs2243115T>G | Risk factor | rs2243115T>G | [147] | |||
Gastric | TNF-α | TNF-α 307 | Race sp. asso. | [150] | |||
TNF-α 307, 1031, 863, 857, and 238 | Not favoring | [154] | |||||
[75] | |||||||
TNF-α 307 | Not favoring | [155] | |||||
IL-1β | IL1β –31 T/C | Slight non sig | C allele | [155] | |||
IL1β –511C/T | Significant association | TT | [94] | ||||
Association | T allele | [156] | |||||
Association | T allele | [55] | |||||
IL1β +3954 C/T | Lack of association | T allele | [55] | ||||
Association | T allele | [156] | |||||
IL-6 | Il-6 −174 G/C | Association | GG | [157] | |||
IL-6 −572 G/C | Negative association | GG | |||||
IL-6 −597 G/A | Lack of association | G allele | [158] | ||||
IL-8 | IL8 –251A/T, | Lack of association | TA | [158] | |||
IL8 +396T/G, | Lack of association | GG | [158] | ||||
IL8+781C/T | Lack of association | CT | [157] | ||||
IL-2 | IL-2 -330 | Sig reduced risk | T allele | [57] | |||
Non-sig association | T allele | [159] | |||||
Sig association | TT genotype | [58] | |||||
IL-2 −384G/T, +114G/T | Non-sig association | [59] | |||||
IL17A and IL17F | –197G/A | Lack of association | AG | [4] | |||
+7488A/G | Association | GG | [4] | ||||
Prostate | IL-6 | IL-6 −174 | Least association | [78] | |||
IL-1 | IL-6 | No. assoc. | [79] | ||||
IL-6 | Association | [80] | |||||
IL-6 −174 G/C | No association | [81] | |||||
IL-1α/IL-1RN/ILβ +3953 | No association | [77] | |||||
IL-1β-511/IL-1β-31 | Association | [77] | |||||
Esophageal | IL-6 | −634 | Poor prognosis | −634GG | [84] | ||
IL-12A | rs568408 G>A | Susceptibility | rs568408 GA,GG | [160] | |||
IL-12B | rs3212227A>C | Significant risk | rs3212227AC,CC | [160] | |||
IL-12Rb1 | −378 | Susceptibility | −378 GG | [160] | |||
IL-18 | −137 G/C | Increased risk | −137 CC, | [94] | |||
−607 C/A | No | −607 C/A | [94] | ||||
TNF-α | −308 | Adverse prognosis | −308 A/A | [99] | |||
IFN-γ | +874A>T | Protective | +874AT,TT | [104] | |||
Pancreatic | IL-1β | −511C/T, −511/+3954 | Favouring | CT genotype | [106] | ||
IL-2 | Favouring | CT genotype | [107] | ||||
TNF-α-308 | IL-2 −330 | Favouring | G allele | [108] | |||
A/G | TNF-α-308 A/G | Not favouring | AG | [69] | |||
Bladder cancer | TNF-α | 1031T>C | No | 1031T>C | [161] | ||
−857C>T | Yes | −857C>T | [161] | ||||
−308G>A | Yes | −308G>A | [161] | ||||
IFN-γ | IFN-γ +874 | Yes | IFN-γ +874 | [162] | |||
IL-1β | −511C>T | No | −511C>T | [123] | |||
IL1-RN | VNTR | Yes | — | [163] | |||
Glioma | IL-4 | −588C>T | Suggestive association | −588TT | [132] | ||
−1098T>G | −1098GT,GG | [132] | |||||
IL-4R | +828A>G | Overall risk | +828A>G | [164] | |||
Overall risk | — | [137] | |||||
IL-12 | −1188A>C | No | — | [140] | |||
IL-13 | +2044A>G | No susceptibility | +2044AA,AG | [136] |
A meta-data of different pro-inflammatory cytokine polymorphisms and their association in various solid tumors.
In the proliferation of T cells, Il-4 and Il-5 play a key role. The study of the relationship between SNPs was chosen from the main immunological genes of cytokines and NHL in several studies. This represents a pathway-based approach to the investigation of common genetic variants in the cytokine network of Th1 and Th2. Common genetic variants of the Th2 cytokine genes have been observed and are associated with NHL risk. SNPS has been shown to be substantially associated with an increased risk of NHL in the TH2 genes IL-4 (−1098T>G) and IL-5 (−745C>T) [165].
While monocytes are the main source of IL-6, many cells, including dendritic cells, lymphocytes, neutrophils, mast cells, mesenchymal cells, and tumor cells, may produce it. IL-6 rs1800797 (IL-6 rs1800795G>C, rs1800796G>C, rs1800797G>A) was the only SNP to demonstrate substantial survival outcomes, with DLBCL co-dominant model (GG/AG/AA) and recessive model (AA genotype versus combined GG/GA genotype) subjects having worse overall survival. The correlation between polymorphism of the IL-6 gene promoter and the risk of lymphomas, however, shows inconsistent results. A common case-control study conducted by the International Lymphoma Epidemiology (Inter Lymph) consortium in 2006 to examine the relationship between gene polymorphisms and the risk of lymphoma showed that there is no correlation between IL-6 promoter polymorphism (174G>C rs1800795) and the risk of NHL [166].
A number of studies have evaluated the association between specific polymorphisms of IL-10 genes and the risk of non-Hodgkin lymphoma but fewer studies analyzed the impact of IL-10 polymorphisms on the prognosis of patients with DLBCL. There is clear evidence that in hematologic malignancies, immune-regulatory cytokines play a major role. The relationship of seven single nucleotide polymorphisms (SNPs) in two selected cytokines (IL-6 rs1800795 G C, rs1800796 G>C, rs1800797 G>A, IL-10 rs1800871 G A, rs1800872 G>T, rs1800890 A>T, rs1800896 T>C) to risk and overall survival was examined in different studies [167].
The proliferation of T, B, and NK cells is encouraged by IL-15, a pro-inflammatory cytokine. Some studies have previously shown that IL-15 can protect hematologic tumors from drug-induced in vitro apoptosis, and high expression of IL-15 is associated with childhood ALL CNS disease. Several minimal residual diseases (MRD)-related IL-15 SNPs have been shown to have a link to increased in vitro transcription/translation efficiency of IL-15. As found by the GWAS scan, there are 5 SNPs in the IL-15 locus that are significantly correlated with childhood ALL therapy response. In the most recent study, polymorphisms of the IL-15 rs10519612 CC genotype have been shown to be associated with adult ALL1 [69]. Polymorphisms of IL-1β (rs16944) and IL-18 (rs1946518) have been shown to predict the prognostic consequences and manage ALL. The impact of the rs1884444 sequence variant on relapse rate and connection of rs10889677 AA genotype with favorable prognostic factors recommend the influence of the investigated SNPs on ALL response to treatment and outcome.
Polymorphisms of IL-1β (rs16944) and IL-18 (rs1946518) have been shown to predict the prognostic consequences and manage ALL care. In cytokine genes, several SNPs have been identified, indicating that certain alleles may lead to alterations in cytokine production [168]. It is, therefore, hypothesized that variants of the cytokine gene can influence the expression of genes and may be associated with leukemia pathogenesis.
The relation between the polymorphism of IFNγ +874T>A (rs2430561) and the risk of CML [169] or earlier, CLL was assessed. Various studies have suggested that the IFNγ+874T>A polymorphism leads to the susceptibility of CML and CLL [168]. No association between TGFβ1 rs1800470 polymorphism and leukemia was identified in earlier studies. Nursal et al., on the other hand, found that variants of the genes TNF-α rs361525, IL-10 (−1082G>A rs1800896, −819C>T rs1800871, −592C>A rs1800872) and TGF-β1 (codon 25) may have a significant association with AML etiopathogenesis [170]. The relation between TNF-α 308G>A, IL-10 (−592T>G, −819T>C, −1082T>C), IFN-γ +874T>A and TGF-β1 (codons 10 and 25) was not identified to confer any risk to CML [169].
IL-1 is a potent cytokine that is pro-inflammatory and functions as an endogenous pyrogen. IL-1 has two cytokines formed by two diverse genes, IL-1 alpha, and IL-1β. Cytokine plays a crucial role in the development, differentiation, and function of different immune cells in cells. An important interaction between IL-1 alpha-889C>T and IL-1β-3737C>T and the risk of MM was shown to have an association with polymorphisms of IL-1 [171].
As a proliferative factor for multiple myeloma (MM), IL-6, a cytokine with broad inflammation and immunity functions, is identified. Some myeloma cells and bone marrow stromal cells may produce IL-6 and can restrain apoptosis in myeloma [172]. Previous studies have shown that IL-6 expression can be partly genetically modulated in the promoter region of IL-6 by polymorphisms located at the rs1800795 location. Recent studies have shown that the association of IL-6 rs1800795 polymorphism with MM risk is negligible.
Gene polymorphisms of TNF-α may also be essential for its functional variation. Research has shown that a TNF-α allele (−308) has been expressed at lower levels in MM subjects, indicating that an allele can have a protective effect against disease [173]. However, the GG genotype of TNF-α (−238) was shown to be correlated to early progression in MM in another study [174].
IL-12 is a cytokine that stimulates immunity that is both innate and adaptive. This induces cytotoxicity of Th1 cells and has been shown to have effective immunomodulatory and anti-tumor activities [175]. However, while IL-12 is an inflammatory cytokine, protection from neoplastic disease appears to be the prevalent activity of the cytokine in this case. There is no clear link between IL-12 (rs1801131) (A>C), polymorphism, and the risk of MM in recent studies [176] (Table 2).
Activity | Cancers type | Cytokines | Polymorphisms | Association | Allele | References | ||
---|---|---|---|---|---|---|---|---|
Pro-inflammatory | Hematological cancers | Lymphomas | HL | IL-1 | +4345 T>G | Significant | −TG | — |
IL-6 | −174 G>C | Significant | 174 GC | [177] | ||||
TNF-α | −863/308 C>A/G>A | Not significant | −863/308 CA,GA | [177] | ||||
NHL | IL-6 | rs1800795 G> C | Not significant | −174GC | [166] | |||
rs1800796 G>C | Significant | −598GA | ||||||
TNF-α | rs1800629 G>C | Significant | −308GA | [157] | ||||
TNF-β | rs909253 A>G | Significant | −252AG | [178] | ||||
IL-4 | rs2243250T>G | Significant | −1098TG | [178] | ||||
IL-5 | rs2069812 C>T | Not significant | −745CT | |||||
Leukemias | ALL | IL-1β | rs16944 G>A | Significant | TT | [179] | ||
IL-18 | rs1946518 | Significant | TT | [180] | ||||
IL-15 | rs10519612 | Significant | CC | [181] | ||||
IL-6 | 174G/C | Significant | rs1800795 GC | [182] | ||||
IL-4 | 590C/T | Not significant | rs2243250 CT | [170, 183] | ||||
AML, CML, CLL | IL-1α | 889C>T- | Significant | 889CT | ||||
IL-1β | 3737C>T | Significant | 3737CT | [184] | ||||
IL-2 | rs1800795 G>C | Significant | 174/52GC | [185] | ||||
IL-6 | rs1801131C>G rs361525G>A | Not Significant | CG | [184] | ||||
TNF-α | rs2430561T>A | Significant | -308/238 GA | [186] | ||||
IFN-γ | 889C>T- | Significant | +874T TA | |||||
Myelomas | IL-1 α | 889C>T | Highly significant | CT | [187] | |||
IL-1β | 3737C>T | Highly significant | CT | [187] | ||||
IL-6 | 174/52G>C | Significant | rs1800795 GC | [188] | ||||
IL-12 | rs1801131 A>C | Not significant | rs1801131AC | [185] | ||||
TNF-α | −308/238 G>A | Significant | rs1800629-308/238 GG | [189] |
A meta-data of different pro-inflammatory cytokine polymorphisms and their association in various liquid cancers.
A variety of cell types, including monocytes, macrophages, and epithelial cells, are formed by interleukin-1β (IL-1β) belonging to the IL-1 family and have multiple biological effects [190]. IL-1β induces the expression of pro-inflammatory genes that may play a key role in the early stages of carcinogenesis, such as cyclooxygenase type 2, inducible nitric oxide synthase, and other cytokines/chemokines. A number of studies have documented the association of IL-1β polymorphisms with the risk of breast cancer, establishing the important role of IL-1β in its development. The findings are contradictory due to the relatively small sample size of the study. Ito et al. [191] first recorded that rs1143627 is significantly correlated with the risk of breast cancer (CC vs. TT: OR = 1.82). The correlation in the Chinese population was followed by another case-control analysis by Liu et al. (CC vs. TT: adjusted OR=1.72). All the studies for rs1143627 included in the meta-analysis were conducted in Asian populations, suggesting that rs1143627 could contribute to the risk of breast cancer, especially in Asians [34].
A multifunctional cytokine that is important for maintaining homeostasis involving bone and muscle differentiation, immune response, and tumor suppression is the transforming growth factor beta-1(TGFβ-1). Increased TGFβ-1 development occurs in different tumor types and is associated with tumor grade severity [192]. There is evidence that when the proliferative inhibition effect of the TGFβ-1 signaling pathway has been overridden by other oncogenic mutations, TGFβ-1 functions as a suppressor of tumor initiation but as a promoter of tumor progression [193]. The 29T/C transformation that generates a Leu10Pro replacement in the TGFβ-1 precursor signal peptide has been reported to be associated with TGFβ-1 secretion of the protein and thus may have altered the risk of breast cancer. In the published clinical trials, Dunning et al. [194] concluded that in studies (20,837 patients and 22,879 controls) from European countries, TGFβ-129T/C T polymorphism was strongly correlated with breast cancer risk (C/C versus T-carrier, 1.21; 95% CI 1.05–1.37); Hishida et al. [195] found that the C/C genotype was substantially correlated with a decreased risk of breast cancer relative to the T/T genotype (OR = 0.45, 0.20–0.98); polymorphisms are not likely to be associated with major increases in the overall risk of breast cancer among Caucasian women in the promoter region of TGFβ-1. Another meta-analysis review indicated that the 29T/C polymorphism did not contribute to breast cancer risk in both recessive, dominant, and other genetic models [196].
During chronic viral infections, IL-10, an immune suppressor cytokine, plays a vital role in the weakened host immune response, where its secretion is stated to be genetically regulated [197]. The most studied SNPs that have an influence on IL-10.1 development are IL-10 (−1082G/A, −819T/C, and −592A/C). The reports suggested that −1082 G allele and GCC haplotype are correlated with high IL-10 expression, where less expression association is shown by ATA haplotype. On the other hand, studies have shown that IL-10GCC and IL-10 haplotype AAGCC (−3575, −2763, −1082, −819, and −592) are associated with lower IL-10 haplotype concentration [198].
In addition to +869T/C (Codon 10), +915G/C (Codon 25) and +788C/T (codon 263), TGF-β1 polymorphisms are identified in TGF-β1-988C/A, -800G/A, -509C/T and in insertion/deletion [199, 200]. Several SNPs are identified in TGF-β1 (+869T/C and +915G/C) [201] while TGF-β1 +869T allele was found to be correlated with high TGF-β11 expression [202].
IL-4 is also recognized as a pro-inflammatory cytokine suppressor and an enhancer of anti-inflammatory cytokine synthesis [203]. The polymorphism of the promoter IL4-590C/T (rs2243250) is widely studied because the mutant T allele has been documented to increase IL-4 expansion compared to the C allele [204]. In contrast with the TT genotype, Wu et al. found an increased risk of developing diffuse form and cardiac GC for the CT/CC genotype in 2003. It is also proposed that lower IL-4 levels in the gastric mucosa favor the growth of GC. The genetic polymorphism IL4-168T/C (rs2070874) tested by Wu et al. [205] stated that a reduced GC risk among the Chinese population was correlated with mutant C allele.
As an immune suppressor and anti-inflammatory mediator, IL-10 typically acts. From the transcriptional start site, there are 3 functional promoters SNPs at-1082 (A to G, rs1800896), -819 (C to T, rs1800871), and -592 (A to C, rs1800872) pairs in the IL10 locus. Studies of IL10-1082A/G, IL10-592A/C, and IL10-819C/T polymorphisms indicate the absence of major discrepancies in the distribution of genotypes between GC patients and healthy controls [206, 207, 208].
The most studied cytokine for PCa risk is IL-10. Controversial findings have emerged in this regard, where various studies show conflicting results and the latest meta-analysis showed that IL-10 (rs1800871) polymorphism was not correlated with PCa danger [209]. On the contrary, another meta-analysis indicated that polymorphic variants of IL-10 (rs1800871) and IL-10 (rs1800872) reinforce the idea that these may be moderately correlated with advanced PCa and thus affect disease progression [210]. The 2011 study by Shao et al found no substantial evidence suggesting variations in allele frequency or genotype distribution between PCa patients and control subjects for any of the three SNPs IL-10-1082 A>G, -819 C>T and -592 C>A.
In cell proliferation and apoptosis, interleukin 1β (IL1β) is involved which is an essential mediator of inflammatory response. IL1β induces COX-2 expression, inducible synthase nitric oxide, and other cytokines/chemokines, which can function significantly in the early stages of carcinogenesis. Many cancers such as gastric cancer and inflammatory bowel disease are associated with IL1β polymorphisms [211]. One of the polymorphisms associated with IL1β levels in the promoter area is rs16944 G>A [212]. According to Liang et al., IL1ß rs16944 GA variant heterozygotes had a substantially decreased chance of ESCC rather than IL1ß rs16944 AA homozygotes, in line with the Thai population study showing that IL1ß rs16944 GG genotype was found to be more common in patients with gastric cancer [213, 214]. However, minimal studies have been performed that can provide us with clear proof of the functionality in the risk of ESCC of IL1ß rs16944 G>A polymorphism.
Two main components of TGF-β signaling that play an important role in carcinogenesis are the transforming growth factor β1 (TGF-β1) and its TGF-β1RII receptor. Several functional polymorphisms were observed in TGF β1 and TGF β1 RII and were correlated with elevated TGF-β1 serum or plasma levels and increased TGFβ1RIII transcription activity. Epidemiological evidence has shown that two transforming growth factor-beta 1 (TGF-β1) gene polymorphisms (namely rs1800468G>A and rs1800471G>C) could be involved in the production of cancer. Their function in the carcinogenic process of esophageal squamous cell carcinoma (ESCC) has, however, been less well described. In recent studies, two polymorphisms of this gene (namely rs1800468G>A and rs1800471G>C) have been shown to be associated with TGF-β1 dysfunction and increased tumor risk [215, 216]. Several evidence indicates that ESCC risk may be increased by the genotypes with rs1800471 C alleles and rs1800471G>C polymorphism may play an important role in ESCCC tumorigenesis [217]. There were some drawbacks to this analysis, however. In contrast to the above findings, several studies have shown that RS#1800468 polymorphism is not associated with an increased risk of ESCC, but with a reduction in the survival of this tumor, consistent with other studies of various cancers [216, 218].
TGF-β functions not only as a powerful epithelial, endothelial and hematopoietic cell proliferation inhibitor but also acts as an effective pro-inflammatory cytokinetic cell proliferator. In cellular proliferation, angiogenesis, differentiation, migration, and apoptosis, TGF-β pathway has important roles. TGF-β expression levels have been reported to correlate with the period of postoperative survival in various malignancies [219]. A study by Zhang et al. [220] showed the TT genotype to be more common in patients with leakage of pancreatic anastomosis in TGF-β. In addition, TT genotype cases had an increased level of bilio-digestive anastomosis leakage.
Interleukin-6 (IL6), a pleiotropic inflammatory cytokine released by different types of lymphoid/non-lymphoid cells, is important for immune response, survival of cells, proliferation, and apoptosis [113]. In the IL-6 promoter region, different polymorphic variants have been identified that are associated with IL-6 transcription activity [115], IL-6 influences the release of acute-phase proteins in the acute inflammatory response and regulates the anti-inflammatory cytokines, thereby influencing the strength of inflammatory response. IL-6 is active in multiple cancer growth pathways and promotes neo-angiogenesis. IL-6 polymorphism has been shown to modulate changes in its expression to induce cancer risk, like bladder cancer. Association studies of IL-6 gene polymorphisms conducted in India and globally support the risk of CC genotype and C allele in many cancers, especially BC. Fishman et al. have stated that IL-6-174 G/C polymorphic heterogeneity affects transcription and IL-6 protein expression. The variant genotype of IL-6-174 G/C has been shown to be substantially associated with an increased risk of BC but other authors have not identified any risk association. In addition, there was no proven association between IL-6-572 G/C, -596 A/G polymorphisms, and BC susceptibility [117].
Interleukin-4 (IL-4), an anti-inflammatory cytokine produced mainly by activated CD4+T cells, plays a significant role in the production of Th2 to examine and destroy distorted cells and eradicate extracellular pathogens [221]. The risk conferred by IL-4-590 C/T polymorphism in different cancers has been substantiated by studies from different quarters [222]. In order to modulate the incidence of BC, a polymorphic variance of IL-4-590 C/T was found and another analysis similarly observed a substantial difference in variant allele distribution between cases and controls [223].
TGF-β1 is the most abundant type of TGF-β, which includes numerous polymorphic variants that regulate the expression of TGF-β1 proteins. The risk association of TGF-β1 polymorphisms in a number of cancers has been verified. TGF-β1 was shown to be associated with the possibility of BCC in 41 SNPs. In comparison, 3 polymorphisms in TGF-β1 and 4 in the TGFβR1 gene showed no correlation yet another study reported comparable outcomes of negligible interaction with BC [210]. Gautam et al., on the other hand, observed an important association between TGF-β1 c.29 C/T and the risk of BCF [118].
TGF-β functions as an oncogenic factor that contributes to the growth and invasion of cells and lowers host tumor immune responses [224]. The −509C/T TGF-β1 gene polymorphism can theoretically control the transcription of TGF-β1. The 869T/C polymorphism may have decreased cancer survival in patients carrying the −509C/T T allele and in patients with the 869T/C C allele, as both of these alleles are associated with elevated levels of TGF-β1. In comparison, TT genotype-carrying glioma patients and CC genotype patients have longer average survival. Therefore, in patients with glioma, the TT genotype of the −509C/T polymorphism and the CC genotype of the 869T/C polymorphism have the ability to be used as predictors of improved survival.
IL-10 has pleiotropic effects on inflammation and immunoregulation and can facilitate carcinogenesis [54]. In gliomas, several IL-10 gene polymorphisms have been shown to influence disease susceptibility and severity [134]. The association of the IL-10 rs1800871 C/T genotype with increased survival in low-grade glioma patients was confirmed by Mingjun et al. [225]. Another research found an important protective interaction of variant IL-10 (−1082A/G) G allele inst glioma whereby It has been shown to induce an increase in the development of IL-10 In 2012, Tanikawa et al. [226] noted that high serum IL-10 levels increased tumor-specific immune response and decreased tumor growth. The exact role of IL-10 in glioma is unclear; further studies are needed to elucidate the mechanisms underlying the relationship between IL-10 polymorphisms and the prognosis of glioma patients (Table 3).
Activity | Cancer type | Cytokines | Polymorphisms | Association | Allele | References | |
---|---|---|---|---|---|---|---|
Anti-inflammatory | Solid tumors | Breast | IL-1β | −511C>T | High risk | −511 CC | [23] |
TGFβ1 | Codon 29T>C | Significant risk | 29TT | [194] | |||
No | — | [196] | |||||
HCC | IL-1β | 511T>C | Risk Factor | 511T>C | [49] | ||
IL1-RN | Intron 286bp | Risk Factor | Intron 286bp | [47] | |||
Allele 2 VNTR | Allele 2 VNTR | [227] | |||||
TGF-β1 | 509C>T | Risk Factor | 509C>T | [228] | |||
IL-4 | 2590C>T | Risk Factor | 2590C>T | [229] | |||
233C>T | Risk Factor | 233C>T | [230] | ||||
IL-6 | −597G>A | No | −597G>A | [231, 232] | |||
−572G>C | Risk factor | −572G>C | [54] | ||||
−174G>C | Risk factor | −174G>C | [233] | ||||
IL-10 | −1082G>A | Risk factor | −1082G>A | [156] | |||
−819T>C | Risk factor | −819T>C | [156] | ||||
Gastric | IL-4 | IL-4 –590C/T | Asso | T allele | [234] | ||
IL-4–168T/C | Neg assoc | C allele | [234] | ||||
IL-10 | IL-10–1082 A/G | Lack of assn | AA | [206] | |||
IL-10–819 C/T | Lack of assn | TC | [235] | ||||
IL-10–592 A/C | Lack of assn | AC | [207] | ||||
Prostate | IL-10 | IL-10 (rs1800871) | Not favouring | [209] | |||
IL-10rs1800871)/(rs1800872) | Favouring | [210] | |||||
IL-10 −1082 A/G | No association | [210] | |||||
−819 C/T | No association | ||||||
−592 C/A | No association | ||||||
Esophageal | IL-1β | rs16944 G>A | Protective | rs16944 GA | [213] | ||
TGFβ1 | rs1800468G>A +915G>C | Significant risk | rs1800468AA | [216] | |||
Significant risk | +915 CC | [227, 236] | |||||
Pancreatic | TGFβ | TGF-β | Association | TT genotype | [237] | ||
Glioma | TGFβ1 | −509C/T,869T/C | Better prognosis | −509TT,869CC | [238] | ||
IL-10 | −819 C>T | Improved survival | −819 CC | [225] | |||
−1082A/G | Protective role | −1082GG | [239] |
A meta-data of different anti-inflammatory cytokine polymorphisms and their association in various solid tumors.
Studies regarding the role of interleukin gene polymorphisms in Hodgkin’s Lymphoma have revealed anti-inflammatory functions of IL-1R and IL-10 [240, 241].
In cancer growth and progression, interleukin-10, a pleiotropic cytokine serves as an immune stimulant factor. In ALL IL-10 SNP rs1800896 was correlated with the progression of the disease and also affect the cytokine expression. Many experiments, however, studied IL-10 rs100896 T/C polymorphism to determine the relevant relationship with susceptibility and prognosis.
In response to similar stimuli that induce IL-1 release, the IL1-Receptor Antagonist (IL-lRa) is developed and released. According to Liang Zheng et al., carriers of IL1B rs16944 GA variant heterozygotes had a slightly reduced chance of multiple myeloma compared to IL-1B rs16944 AA homozygotes, had a slightly reduced [213].
IL-10 suppresses immune responses as an immunosuppressive cytokine by functioning simultaneously on the innate and the adaptive immune system. IL-10 can also inhibit pro-inflammatory cytokine secretion, antigen presentation, and cell growth. In the pathogenesis of hematological disorders, both IL-10 and IL-10R SNPs are involved. IL-10-592G/A and IL-10-1,082G>A SNPs, -592(C) or -1,082(G) are considered to be correlated with a strong IL-10 expression and a low -592(A) or -1,082(G) expression (A). However, studies have shown, that the C allele of IL10-592 has no clear interaction with MM [242].
TGF-β is an active regulatory cytokine with divergent hemopoietic cell effects. Usually, TGF-β serves to reduce the release of immunoglobulin by B cells. Studies have shown that TGFβ1 genotypes with rs1800471 C alleles may raise the risk of MM and rs1800471G>C polymorphism may play a significant role in MMM tumorigenesis [217].
Germline constitutional mutations or changes in the polymorphic sequence are key instruments used as molecular tools to predict the susceptibility of a person to risk numerous cancers. Cytokines are also thought to be essential molecules that have a dual face due to pro-inflammatory as well as anti-inflammatory mechanisms in carcinogenesis. These molecules regulate the development of cancer when involved in the activation of the immune response, while their recurrent inflammatory reaction will envisage the development of malignancy and tumor formation. Any differences in the polymorphic sequence of cytokine genes cause heterogeneity in their expression to deregulate genetic regulation, which eventually makes a person vulnerable to multiple cancers. As stated in the t segment, considerable evidence that links cytokine gene susceptibility polymorphism with various cancers has materialized their position as important bimolecular genetic cancer susceptibility and prognosis determinants. In studying candidate genes implicated in particular pathways for specific cancer; we conclude there is a desperate need for more case-control association studies involving additional variables haplotypic gene-gene associations and clinical-pathological features to unearth factual association for cancer. Because cytokine polymorphisms play a crucial role in immunological processes in which a rich supply of inflammatory cytokines are produced by various intensities of inflammation and cancer microenvironment, research into genetic polymorphisms in cytokine genes and their reaction to chemo-radiotherapy is believed to assist patients with cancer treatment and management.
The authors declare no conflict of interest.
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However, it can only be activated under ultraviolet light irradiation due to its wide bandgap, high recombination, and weak separation efficiency of carriers. Doping is an effective method to extend the light absorption to the visible light region. In this chapter, we will address the importance of doping, different doping modes, preparation method, and photocatalytic mechanism in TiO2 photocatalysts. Thereafter, we will concentrate on Ti3+ self‐doping, nonmetal doping, metal doping, and codoping. Examples of progress can be given for each one of these four doping modes. The influencing factors of preparation method and doping modes on photocatalytic performance (spectrum response, carrier transport, interfacial electron transfer reaction, surface active sites, etc.) are summed up. The main objective is to study the photocatalytic processes, to elucidate the mechanistic models for a better understanding the photocatalytic reactions, and to find a method of enhancing photocatalytic activities.",book:{id:"5139",slug:"semiconductor-photocatalysis-materials-mechanisms-and-applications",title:"Semiconductor Photocatalysis",fullTitle:"Semiconductor Photocatalysis - Materials, Mechanisms and Applications"},signatures:"Fei Huang, Aihua Yan and Hui Zhao",authors:[{id:"178389",title:"Dr.",name:"Fei",middleName:null,surname:"Huang",slug:"fei-huang",fullName:"Fei Huang"},{id:"185126",title:"Dr.",name:"Aihua",middleName:null,surname:"Yan",slug:"aihua-yan",fullName:"Aihua Yan"},{id:"185127",title:"Ms.",name:"Hui",middleName:null,surname:"Zhao",slug:"hui-zhao",fullName:"Hui Zhao"}]},{id:"17184",doi:"10.5772/17039",title:"Polymer Nanocomposites: From Synthesis to Applications",slug:"polymer-nanocomposites-from-synthesis-to-applications",totalDownloads:17338,totalCrossrefCites:33,totalDimensionsCites:70,abstract:null,book:{id:"1045",slug:"nanocomposites-and-polymers-with-analytical-methods",title:"Nanocomposites and Polymers with Analytical Methods",fullTitle:"Nanocomposites and Polymers with Analytical Methods"},signatures:"S. 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This chapter aimed at providing some basic and fundamental properties of ceria, the importance of oxygen vacancies in this material, nano‐size effects and various synthesis strategies to form diverse structural morphologies. Finally, some key applications of ceria‐based nanostructures are reviewed. We conclude this chapter by expressing personal perspective on the probable challenges and developments of the controllable synthesis of CeO2 nanomaterials for various applications.",book:{id:"5510",slug:"functionalized-nanomaterials",title:"Functionalized Nanomaterials",fullTitle:"Functionalized Nanomaterials"},signatures:"Adnan Younis, Dewei Chu and Sean Li",authors:[{id:"191574",title:"Dr.",name:"Adnan",middleName:null,surname:"Younis",slug:"adnan-younis",fullName:"Adnan Younis"}]},{id:"17194",doi:"10.5772/21694",title:"Properties of Nanofillers in Polymer",slug:"properties-of-nanofillers-in-polymer",totalDownloads:20422,totalCrossrefCites:9,totalDimensionsCites:57,abstract:null,book:{id:"1045",slug:"nanocomposites-and-polymers-with-analytical-methods",title:"Nanocomposites and Polymers with Analytical Methods",fullTitle:"Nanocomposites and Polymers with Analytical Methods"},signatures:"Damien M. 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Nanotechnology is widely considered to constitute the basis of the next technological revolution, following on from the first Industrial Revolution, which began around 1750 with the introduction of the steam engine and steelmaking. Nanotechnology is defined as the design, characterization, production, and application of materials, devices and systems by controlling shape and size of the nanoscale. The nanoscale itself is at present considered to cover the range from 1 to 100 nm. All samples prepared in thin film forms and the characterization revealed their nanostructure. The major exploitation of thin films has been in microelectronics, there are numerous and growing applications in communications, optical electronics, coatings of all kinds, and in energy generation. A great many sophisticated analytical instruments and techniques, largely developed to characterize thin films, have already become indispensable in virtually every scientific endeavor irrespective of discipline. Among all these techniques, electrodeposition is the most suitable technique for nanostructured thin films from aqueous solution served as samples under investigation. The electrodeposition of metallic layers from aqueous solution is based on the discharge of metal ions present in the electrolyte at a cathodic surface (the substrate or component.) The metal ions accept an electron from the electrically conducting material at the solid- electrolyte interface and then deposit as metal atoms onto the surface. The electrons necessary for this to occur are either supplied from an externally applied potential source or are surrendered by a reducing agent present in solution (electroless reduction). The metal ions themselves derive either from metal salts added to solution, or by the anodic dissolution of the so-called sacrificial anodes, made of the same metal that is to be deposited at the cathode.",book:{id:"4718",slug:"electroplating-of-nanostructures",title:"Electroplating of Nanostructures",fullTitle:"Electroplating of Nanostructures"},signatures:"Souad A. M. Al-Bat’hi",authors:[{id:"174793",title:"Dr.",name:"Mohamad",middleName:null,surname:"Souad",slug:"mohamad-souad",fullName:"Mohamad Souad"}]},{id:"54226",title:"Localized Surface Plasmon Resonance for Optical Fiber-Sensing Applications",slug:"localized-surface-plasmon-resonance-for-optical-fiber-sensing-applications",totalDownloads:2311,totalCrossrefCites:2,totalDimensionsCites:6,abstract:"It is well known that optical fiber sensors have attracted the attention of scientific community due to its intrinsic advantages, such as lightweight, small size, portability, remote sensing, immunity to electromagnetic interferences and the possibility of multiplexing several signals. This field has shown a dramatic growth thanks to the creation of sensitive thin films onto diverse optical fiber configurations. In this sense, a wide range of optical fiber devices have been successfully fabricated for monitoring biological, chemical, medical or physical parameters. In addition, the use of nanoparticles into the sensitive thin films has resulted in an enhancement in the response time, robustness or sensitivity in the optical devices, which is associated to the inherent properties of nanoparticles (high surface area ratio or porosity). Among all of them, the metallic nanoparticles are of great interest for sensing applications due to the presence of strong absorption bands in the visible and near-infrared regions, due to their localized surface plasmon resonances (LSPR). These optical resonances are due to the coupling of certain modes of the incident light to the collective oscillation of the conduction electrons of the metallic nanoparticles. The LSPR extinction bands are very useful for sensing applications as far as they can be affected by refractive index variations of the surrounding medium of the nanoparticles, and therefore, it is possible to create optical sensors with outstanding properties such as high sensitivity and optical self-reference. In this chapter, the attractive optical properties of metal nanostructures and their implementation into different optical fiber configuration for sensing or biosensing applications will be studied.",book:{id:"5721",slug:"nanoplasmonics-fundamentals-and-applications",title:"Nanoplasmonics",fullTitle:"Nanoplasmonics - Fundamentals and Applications"},signatures:"Pedro J. Rivero, Javier Goicoechea and Francisco J. Arregui",authors:[{id:"69816",title:"Dr.",name:"Javier",middleName:null,surname:"Goicoechea",slug:"javier-goicoechea",fullName:"Javier Goicoechea"},{id:"188796",title:"Dr.",name:"Pedro J.",middleName:null,surname:"Rivero",slug:"pedro-j.-rivero",fullName:"Pedro J. Rivero"},{id:"197277",title:"Dr.",name:"Francisco",middleName:null,surname:"Arregui",slug:"francisco-arregui",fullName:"Francisco Arregui"}]},{id:"25297",title:"Nanofabrication of Metal Oxide Patterns Using Self-Assembled Monolayers",slug:"nanofabrication-of-metal-oxide-patterns-using-self-assembled-monolayers",totalDownloads:3473,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"860",slug:"nanofabrication",title:"Nanofabrication",fullTitle:"Nanofabrication"},signatures:"Yoshitake Masuda",authors:[{id:"12385",title:"Dr.",name:"Yoshitake",middleName:null,surname:"Masuda",slug:"yoshitake-masuda",fullName:"Yoshitake Masuda"}]},{id:"77225",title:"Piezoelectricity and Its Applications",slug:"piezoelectricity-and-its-applications",totalDownloads:639,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"The piezoelectric effect is extensively encountered in nature and many synthetic materials. Piezoelectric materials are capable of transforming mechanical strain and vibration energy into electrical energy. This property allows opportunities for implementing renewable and sustainable energy through power harvesting and self-sustained smart sensing in buildings. As the most common construction material, plain cement paste lacks satisfactory piezoelectricity and is not efficient at harvesting the electrical energy from the ambient vibrations of a building system. In recent years, many techniques have been proposed and applied to improve the piezoelectric capacity of cement-based composite, namely admixture incorporation and physical. The successful application of piezoelectric materials for sustainable building development not only relies on understanding the mechanism of the piezoelectric properties of various building components, but also the latest developments and implementations in the building industry. Therefore, this review systematically illustrates research efforts to develop new construction materials with high piezoelectricity and energy storage capacity. In addition, this article discusses the latest techniques for utilizing the piezoelectric materials in energy harvesters, sensors and actuators for various building systems. With advanced methods for improving the cementations piezoelectricity and applying the material piezoelectricity for different building functions, more renewable and sustainable building systems are anticipated.",book:{id:"10511",slug:"multifunctional-ferroelectric-materials",title:"Multifunctional Ferroelectric Materials",fullTitle:"Multifunctional Ferroelectric Materials"},signatures:"B. Chandra Sekhar, B. Dhanalakshmi, B. Srinivasa Rao, S. Ramesh, K. Venkata Prasad, P.S.V. Subba Rao and B. Parvatheeswara Rao",authors:[{id:"335022",title:"Dr.",name:"B. Chandra",middleName:null,surname:"Sekhar",slug:"b.-chandra-sekhar",fullName:"B. Chandra Sekhar"},{id:"422021",title:"Dr.",name:"B.",middleName:null,surname:"Dhanalakshmi",slug:"b.-dhanalakshmi",fullName:"B. Dhanalakshmi"},{id:"422022",title:"Dr.",name:"B.Srinivasa",middleName:null,surname:"Rao",slug:"b.srinivasa-rao",fullName:"B.Srinivasa Rao"},{id:"422023",title:"Dr.",name:"S.",middleName:null,surname:"Ramesh",slug:"s.-ramesh",fullName:"S. Ramesh"},{id:"422024",title:"Dr.",name:"K.Venkata",middleName:null,surname:"Prasad",slug:"k.venkata-prasad",fullName:"K.Venkata Prasad"},{id:"422025",title:"Dr.",name:"P.S.V",middleName:null,surname:"Subba Rao",slug:"p.s.v-subba-rao",fullName:"P.S.V Subba Rao"},{id:"422026",title:"Dr.",name:"B.Parvatheeswara",middleName:null,surname:"Rao",slug:"b.parvatheeswara-rao",fullName:"B.Parvatheeswara Rao"}]}],onlineFirstChaptersFilter:{topicId:"1169",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"79274",title:"Molecular Simulation of Cholesteric Liquid-Crystal Polyesteramides: Conformational and Structure Analysis by Rietveld Refinement",slug:"molecular-simulation-of-cholesteric-liquid-crystal-polyesteramides-conformational-and-structure-anal",totalDownloads:77,totalDimensionsCites:0,doi:"10.5772/intechopen.100388",abstract:"Molecular modeling techniques are applied to polyesteramides designed as PNOBDME (C34H38N2O6)n and PNOBEE (C26H22N2O6)n, synthesized and characterized as cholesteric liquid crystals -through the condensation reaction between 4 and 4′-(terephthaloyl- diaminedibenzoic chloride (NOBC) and racemic glycol: DL-1,2 dodecanediol, or DL-1,2-butanediol, respectively, being chemical modifications of precursor multifunctional cholesteric LC polyesters, adding new properties but holding their helical macromolecular structures. Although the starting raw materials were racemic, these cholesteric LC polymers exhibit unexpected optical activity and chiral morphology. For that reason, conformational analysis is studied on the monomer models of PNOBDME and PNOBEE. Four helical conformers models, experimentally observed by NMR, are proposed for each cholesteric polyesteramide: Rgg, Rgt, Sgg, Sgt. Polymerization of the monomeric conformers, with minima energies, have been simulated and used to reproduce the crystalline fraction observed by x-ray diffraction. Three orders of chirality are observed in the structure of the polymer chains: One due to the asymmetric carbon atoms, a second chirality due to the two successive rotations of the benzene groups, along the main chain, within the monomer which implies the formation of helical molecules, for both R and S chirality and still, a third chirality corresponding to the twisting of the rigid/semirigid cholesteric LC polymer chains. All these factors contributing to the net optical activity observed in these materials. Crystal packing is simulated in triclinic primitive P1cells, with molecular chains oriented parallel to the z-axis (c lattice parameter equal to the pitch length of each simulated polymer helix) and parameters a, b, α, β and γ, obtained by Pawley refinement from the known structures of precursor polyesters. The simulated x-ray diffraction patterns of the proposed crystal models fit, after successive Pawley and Rietveld refinement cycles, the experimental WAXS. Powder Quantitative Phase Analysis applied to an ideal mixture with the four possible helical conformers, for each degree of polymerization, allows to refine their relative weight and determine the major phase relative amount. These results would confirm the theory of a preferable recrystallization, among the four possible helical diastereoisomers, depending on the synthetic conditions.",book:{id:"10957",title:"Liquid Crystals",coverURL:"https://cdn.intechopen.com/books/images_new/10957.jpg"},signatures:"Mercedes Pérez Méndez, José Fayos Alcañiz and Marc Meunier"},{id:"80636",title:"The LCD Interfacing and Programming",slug:"the-lcd-interfacing-and-programming",totalDownloads:202,totalDimensionsCites:0,doi:"10.5772/intechopen.102408",abstract:"This chapter will discuss 10 subchapters that will make it more detailed and easier for the reader to master and implement them in their project. Before discussing the subchapters in detail the author discusses the wide use of LCD in various equipment that needs display and the superiority of it compared to the conventional existing displays especially in the low energy consumption of it compare to the rest of the displays, then the author ended this general discussion by mentioning the type of LCD known in the market right now (passive matrix and active matrix). After discussing the LCD in general, the author starts discussing the detailed 10 subchapters. The 10 subchapters are 1. 2 × 16 LCD; 2. LCD controller; 3. LCD instructions; 4. LCD initialization; 5. More instructions; 6. LCD initialization subroutine; 7. Displaying a character on the LCD; 8. Displaying more than 1 character on the LCD; 9. A 4-bit mode 2 × 16 LCD module. To give the readers with a succinct overview of important details or interesting information, the author provides the summary of this chapter in subchapter 10. The author also provided the glossary to enable the readers to quickly study the general terms used in this chapter. Finally, the author provides some questions to enable the reader to test their own knowledge of this chapter. The references is also provided to enable the readers to refer to some articles as the sources of this subchapter and to enable them to enrich their knowledge of this chapter.",book:{id:"10957",title:"Liquid Crystals",coverURL:"https://cdn.intechopen.com/books/images_new/10957.jpg"},signatures:"Dahlan Sitompul and Poltak Sihombing"},{id:"80473",title:"Overview of Liquid Crystal Research: Computational Advancements, Challenges, Future Prospects and Applications",slug:"overview-of-liquid-crystal-research-computational-advancements-challenges-future-prospects-and-appli",totalDownloads:93,totalDimensionsCites:0,doi:"10.5772/intechopen.101417",abstract:"Liquid crystal (LC) is a fascinating state of matter that combines order and mobility at multiple hierarchical levels, spanning from nanoscale to the macroscale, or from molecular to the macroscopic, and is composed of molecules and layers as thin as of a few nanometer in size. This unique combination allows such a system to adapt to a wide range of external stimuli, including temperature, magnetic field, electric field, mechanical stress, light, chemical reaction, and electrochemical response, by determining a new lowest energy configuration. Liquid crystalline nanostructures efficiently transmit and amplify information and attributes over macroscopic sizes due to their dynamic nature. The responsiveness and diversity of LCs provide enormous potential and challenges for fundamental scientific insights as well as opening the door to countless applied applications. Recent breakthroughs in nanotechnology have boosted the discipline, both in terms of theoretical simulations and the ability to fabricate nanoscale structures such as sub-wavelength gratings, nanoporous materials, and nanoparticles. Because LC materials are switchable, a new family of active plasmonic and nanophotonic devices is emerging, describing fascinating basic research processes as well as the creation of upgraded devices. This chapter discusses the fundamentals, computational advances, future prospects and challenges, as well as potential applications of LCs.",book:{id:"10957",title:"Liquid Crystals",coverURL:"https://cdn.intechopen.com/books/images_new/10957.jpg"},signatures:"Maria Malik, Muhammad Aamir Iqbal, Wajeehah Shahid, Syed Zaheer Ud Din, Mujtaba Ikram, Nadia Anwar, Samiah Shahid and Faryal Idrees"},{id:"80010",title:"Phase Transitions and Structure of Liquid Crystalline Cellulose Ether Solutions in a Magnetic Field and in Its Absence",slug:"phase-transitions-and-structure-of-liquid-crystalline-cellulose-ether-solutions-in-a-magnetic-field-",totalDownloads:94,totalDimensionsCites:0,doi:"10.5772/intechopen.101451",abstract:"The results of research studies of a magnetic field effect on structure and phase transitions of liquid crystalline polymer systems are described. Influence of intensity of the magnetic field, molecular weight, and concentration of polymers in solutions on the phase diagrams is analyzed. The dependences of boundary curves on the chemical structure of polymers and solvents are discussed. Results of theoretical researches of the magnetic field effect on the diamagnetic macromolecule orientation in solutions are described. The shift of boundary curves of liquid crystalline cellulose derivative systems is compared with the energy of magnetic field stored by solutions.",book:{id:"10957",title:"Liquid Crystals",coverURL:"https://cdn.intechopen.com/books/images_new/10957.jpg"},signatures:"Sergey Vshivkov and Elena Rusinova"},{id:"78941",title:"High Precision Optical Wavefront Generation Using Liquid Crystal Spatial Light Modulator (LC-SLM)",slug:"high-precision-optical-wavefront-generation-using-liquid-crystal-spatial-light-modulator-lc-slm-",totalDownloads:180,totalDimensionsCites:0,doi:"10.5772/intechopen.100379",abstract:"LC-SLM provides a flexible way to modulate the phase of light with the help of a grayscale pattern loaded on it. Nevertheless, the modulated phase profile is of relatively low accuracy due to the nonlinear and nonuniform response of the liquid crystal layer in the SLM. To improve the performance of LC-SLM on the wavefront generation, the nonlinear and nonuniform phase response needs to be calibrated and compensated effectively. In this chapter, we present some state-of-art methods to measure the phase modulation curve of the LC-SLM. Some methods to measure the static aberration caused by the backplane of the LC-SLM are then presented. Last but not the least, the future development of the LC-SLM in phase modulation is also presented.",book:{id:"10957",title:"Liquid Crystals",coverURL:"https://cdn.intechopen.com/books/images_new/10957.jpg"},signatures:"Zixin Zhao"}],onlineFirstChaptersTotal:5},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:139,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:122,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:21,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"August 2nd, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:33,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:42,paginationItems:[{id:"82914",title:"Glance on the Critical Role of IL-23 Receptor Gene Variations in Inflammation-Induced Carcinogenesis",doi:"10.5772/intechopen.105049",signatures:"Mohammed El-Gedamy",slug:"glance-on-the-critical-role-of-il-23-receptor-gene-variations-in-inflammation-induced-carcinogenesis",totalDownloads:9,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Chemokines Updates",coverURL:"https://cdn.intechopen.com/books/images_new/11672.jpg",subseries:{id:"18",title:"Proteomics"}}},{id:"82875",title:"Lipidomics as a Tool in the Diagnosis and Clinical Therapy",doi:"10.5772/intechopen.105857",signatures:"María Elizbeth Alvarez Sánchez, Erick Nolasco Ontiveros, Rodrigo Arreola, Adriana Montserrat Espinosa González, Ana María García Bores, Roberto Eduardo López Urrutia, Ignacio Peñalosa Castro, María del Socorro Sánchez Correa and Edgar Antonio Estrella Parra",slug:"lipidomics-as-a-tool-in-the-diagnosis-and-clinical-therapy",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82440",title:"Lipid Metabolism and Associated Molecular Signaling Events in Autoimmune Disease",doi:"10.5772/intechopen.105746",signatures:"Mohan Vanditha, Sonu Das and Mathew John",slug:"lipid-metabolism-and-associated-molecular-signaling-events-in-autoimmune-disease",totalDownloads:17,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82483",title:"Oxidative Stress in Cardiovascular Diseases",doi:"10.5772/intechopen.105891",signatures:"Laura Mourino-Alvarez, Tamara Sastre-Oliva, Nerea Corbacho-Alonso and Maria G. 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