Strongly abridged summary of information from studies on characteristics of Oribatid communities. (↑=increases or greater; ↓=decreases or lower)
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They can be found in most terrestrial microhabitats: in soil, leaf litter, moss, underwood, foliage and in aquatic habitats as well (Behan-Pelletier, 1999). They can be found mostly in great species richness and abundance in their habitats (Behan-Pelletier, 1999). They play a significant role in decomposition processes because they fragment the organic matter and influence the biomass and species composition of fungi and bacteria (Wallwork, 1983; Seastedt, 1984; Yoshida and Hijii, 2005). As this group plays a significant role in soil processes, it is necessary to get to know its spatial pattern and the causes of pattern generation, which can be used later for indication (Behan-Pelletier, 1999).
Applicability of Oribatid mites as an indicator group has been emphasized by researchers for several decades. These organisms possess such kind of extraordinary characteristics by which (considered even separately or as a whole) they are able to indicate different changes in their environment. These characteristics have been summarized in several reviews, most thoroughly in the works of Lebrun and van Straalen (1995), Behan-Pelletier (1999) and Gulvik (2007).
Oribatid mites can be found in almost every kind of habitats worldwide: on land, water and most importantly in the layers of soil containing organic materials, but they also conquered several other kind of microhabitats (e. g. lichen, moss, treebark etc.). Apart from the diversity of habitats, their excessive adaptational ability is also shown by great abundance and species richness. In most habitats, they constitute the largest proportion of microarthropods. These characteristics mentioned above can be primarily used in the application of coenological methods.
Oribatid mites consume mainly living or dead parts of plants or fungi, however there are some predators and scavengers to be mentioned as exceptions (Behan-Pelletier, 1999). As a consequence, they consume variuos kinds of food, and as such, they participate in numerous ways in the structure of the food web (Lebrun and van Straalen, 1995). Thus they are in strong interaction with their microenvironment (e. g. Ca-storage, heavy metal accumulation (Norton and Behan-Pelletier, 1991, Behan-Pelletier 1999), play an important role in the forming of soil structure and decomposition processes (Behan-Pelletier, 1999). These features can be applied for indicating the effects of chemical or heavy metal pollutions, and disturbances in the succession of decomposition processes (Lebrun and van Straalen, 1995).
The reproduction biology and life cycle of Oribatid mites can be considered extraordinary among arthropods from several aspects. There are some species/populations with sexual and asexual reproduction, and the proportion of species with obligate thelytokous parthenogenesis is very high – around 10% (Lebrun and van Straalen, 1995). Iteroparity and multiannual life cycle are also quite prevalent among the species, especially in moderate and cold climate zones (Norton, 1994, Luxton, 1981, Behan-Pelletier, 1999). The slow development, low fecundity and long larval stage of Oribatid mites can help indicating long-term disturbances. Their low dispersion ability (Lebrun and van Straalen, 1995) is also quite important, since these mites can hardly flee from sites affected by some kind of stress. Oribatid mites are classified as a „K-selected” group; this can be lead back to their slow metabolism according to Norton (1994). Based on the characteristics listed above, many researchers think that this group is quite promising since it can be used for various indication purposes.
Nowadays there are several methods to describe the natural state of a habitat; the focus is mainly on the measuring of biodiversity. However, uncertainty can arise when measuring biodiversity, as several questions can be raised already as to the explanation of the term, starting from which level it should be considered on (genetic, taxon, ecological diversity), to – if the taxon level has been chosen – the decision on which taxon the focus should be.
The main goal of this study is to set up a comparison scale based on genus-level presence-absence lists of oribatid mite communities (Acari: Oribatida) of habitats examined on different spatial and temporal scales. The secondary goal – and this time the precondition as well – is to get a reliable picture of the indication strength of the distances to be used, i.e. the information content included.
The indication suitability of the order of oribatid mites for describing the state of their habitat is justified by the special characteristics of the group. Oribatid mites can be found in almost all kinds of habitats: on land and in water; first of all in soil layers containing organic matter as well, however, they have penetrated into different other microhabitats, too (e.g. lichens, moss, bark etc.), which is mainly due to their indeed various food sources (e.g. organic debris, fungi, other mites etc.). Besides the diversity of habitats, their high adaptation ability is shown by their enormous abundance and species richness as well. The above characteristics can be mainly used in the case of coenological methods (Lebrun and van Straalen, 1995; Behan-Pelletier, 1999; Gulvik, 2007; Gergócs and Hufnagel, 2009).
The choice of the genus level can be explained by different aspects. In the analysis by Caruso and Migliorini (2006) it was shown that there were not any significant changes in data examining anthropogenic disturbance on oribatid mites when switching from species level to genus level. Our study has a similar goal as we would like to show potential habitat changes with our method. Podani (1989) had a similar observation in case of plants, according to which switching to genus level does not mean a significant change when comparing the examined habitats. Osler and Beattie (1999) carried out a meta-analysis similar to ours, which confirmed their expectation that taxonomic levels above species are more suitable for comparing habitats. This research showed further that habitats can be chosen on family level in case of oribatid mites, therefore our study covers besides the genus level the family level as well. There were also some other arguments for our decision, namely that the number of databases used could be considerably extended in this way, in addition, taxonomical processing became faster and more reliable in our field studies as well. Genus-level identification of oribatid mites is solved on the basis of the work by Balogh and Balogh (1992) on a global scale, too. However, species-level identification is only possible in case of some zoogeographical regions and only some taxa on a global scale as the related literature is not properly synthesized yet (e.g. Balogh and Mahunka, 1983; Olsanowski, 1996).
Research into oribatid mites goes back to the 1880s, the work of A. Berlese, who invented the Berlese funnel and made it possible to extract and examine soil mesofauna more precisely. His lifework was carried on by several renowned taxonomists, such as Grandjean, Hammer, Beck, Aoki, Wallwork, Engelbrecht, Corpus-Raros, Lee, Pérez-Inigo, Baggio, Bhattacharia and Haq (Balogh et al., 2008) with taxonomical descriptions of oribatid mites covering the bigger part of terrestrial habitats. Due to the above researches, nowadays it has become possible to examine oribatid mites from different indication aspects on community level.
One part of the studies on indication possibilities compares natural habitats. In these studies the goal is to reveal spatial and temporal pattern generation characteristics of habitats. Temporal change is examined in few studies (Irmler, 2006) and in case of spatial examinations different approaches are used: on substrate level (e.g. Fagan et al., 2006; Lindo and Winchster, 2006), examining altitudinal zonation of mountains (Migliorini and Bernini, 1999; Reynolds et al., 2003; Jing et al., 2005) and only seldom on the level of habitat types (Balogh et al., 2008). These studies do not always yield consistent results, however, the examinations prove that patterns exist.
These examinations try to explore what properties of habitats play a role in pattern generation, among which spatial and temporal changes can be distinguished. Observations on seasonality have not yielded considerable results (Reynolds et al., 2003, Noti et al., 1996, Badejo et al., 2002, Moldenke and Thies, 1996). Habitats and sampling frequencies are quite different and hardly comparable. Currently we do not possess any satisfying results on seasonal dynamics. A number of studies (Reynolds et al., 2003) surveying temporal changes measured the total abundance of the community. Measuring the changes in the number of individuals of larger groups does not mean thorough examination. It is worth to survey the temporal structures of the entire community on such places where seasons are well discernible. One of the most important studies has been made by Irmler (2006), who studied the seasonal changes of an Oribatid community living in the OL and OF layer of a beech forest. It was found that only the annual mean temperature had significant effect on the structure of the community. The study yielded more results when Irmler surveyed the seasonal dynamics of individual species. Mainly the amount of precipitation affected the abundance of certain species, but some species had been affected more significantly by temperature (primarily by the mean temperature in January). The significance of species-level examination was confirmed by the fact that certain species reacted differently on the surveyed parameters.
Spatial comparisons applied different scales; part of them compared soil and foliage of forests. These studies revealed that Oribatids of the soil showed greater α-diversity and species richness, but β-diversity proved to be greater in the foliage, which means difference among samples taken from individual trees has been greater than that of the samples collected from the soil (Lindo and Winchster, 2006, Fagan et al., 2006).
Comparison of elevations above sea level attracted great attention: primarily the abundance and species richness of Oribatids have been studied in zones of different altitudes. However, obtained data are not concordant: according to Migliorini and Bernini, (1999) and Fagan et al., (2006) the abundance of Oribatids decreased with altitude, but Jing et al., (2005) and Reynolds et al., (2003) observed an opposing tendency. Fagan et al., (2006) pointed out a decrease in species richness, Migliorini and Bernini, (1999) observed a growth in diversity as a function of increasing altitude. It has to be mentioned by these contradictory results that altitudes of sampling and habitats are hardly comparable, and even if they were, this would not guarantee consistent results. This has been pointed out by Andrew et al., (2003) in an extended series of studies conducted on different altitudes in Australia and New Zealand.
Beside altitude, vegetation also changes greatly when progressing upwards on a hill. Studies mentioned above did not lay an emphasis on vegetation. The work of Balogh et al.(2008) however demonstrates altitude as a difference in the type of vegetation: rainforest, moss forest and paramo. Samples were taken from the mountains of Brazil, Costa-Rica and New-Guinea. This work showed that the structure of Oribatid mite communities was primarily determined by the type of vegetation and not by the distance of several thousand kilometres, which means that climate and ecological conditions have stronger effects than zoogeographical connections (Balogh et al., 2008).
Studies examining Oribatid communities almost always measure which Oribatid species and in what quantity are present in samples taken from the given area. Species composition, abundance, total abundance, species richness, diversity and the uniformity of the community can be calculated from these data. In most cases, changes in the communities are examined using these variables.
When given the same climate, abundance, species richness and diversity of the Oribatids are greater in natural areas (forest or habitats not strongly affected by human activity) than in areas affected by agriculture (e.g. plant production or animal husbandry) or forestry (e.g. clear-felling, burning etc.) (Bedano
Decrease in abundance can be caused by hard frost (Sulkava and Huhta, 2003) and serious heavy metal pollution (Seniczak et al., 1995). According to Osler et al. (2006), mainly the number of individuals is lower in the initial state of succession. Decrease in abundance could be pointed out primarily as a result of water deficiency (O’Lear and Blair, 1999, Lindberg et al., 2002), but contradictory results had been also obtained (O’Lear and Blair, 1999, Melamud et al., 2007). Lindberg and Bengtsson, (2006) showed that community regeneration following drought can not be satisfactorily measured by the sole application of total abundance. Decrease in the abundance of Oribatids can also be caused by ash treatment of sour, acidic soils (Liiri et al., 2002). In Japanese coniferous forests it has been shown that the abundance of Oribatids was greater in mixed litter (litter of several tree species) than in litters consisting of only one tree species (Kaneko and Salamanca, 1999). Kovács et al., (2001) explored positive correlation between the nutrient content of the soil and abundance, but it was contradicted by several other studies (e.g. Osler and Murphy, 2005).
Removal of winter snow cover lead to a decrease in species richness, since the mesofauna of the soil has been exposed to greater fluctuation of temperature (Sulkava and Huhta, 2003). Response of species to heavy metal pollution varied greatly, sometimes even moderate pollution resulted in the highest species richness (Skubala and Kafel 2004). Drought generally decreased species richness (Tsiafouli et al., 2005), but there were several examples for growth as well (Melamud et al., 2007). Ash treatment lowered abundance and also species richness (Liiri et al., 2002). In mixed litter, both species richness and abundance were higher (Kaneko and Salamanca, 1999). Fagan et al., (2006) found in Canadian coniferous forests that species richness of Oribatids in the soil had been greater when comparing Oribatid communities of the foliage and soil.
Diversity data can be found primarily in agricultural and forestry studies. It has been pointed out that irrigation (enhancing the moisture content of the soil) increased the diversity of Oribatid communities, because it raised the individual numbers of rare species (Tsiafouli et al., 2005). Drought had a detrimental effect on diversity (Lindberg et al., 2002). Studies of Taylor and Wolters (2005) pointed out that Oribatid diversity had been greater in a more decomposed beech litter than in fresh litter. Seniczak et al., (2006) concluded that Oribatid diversity can be increased by increasing the number of ponds of forest habitats, since this means more ecotones and leads to the presence of such kind of species which prefer humid habitats and are normally absent from forest habitats. Age of temperate deciduous forests did not affect diversity (Erdman et al., 2006). Growth in the diversity of tree species did not increase the diversity of Oribatids living in the soil of these forests (Kaneko et al, 2005. However, growing diversity of the litter not only increased abundance and species richness, but diversity as well (Coleman 2008).
artificial disturbance↓ | artificial disturbance↓ | artificial disturbance↓ |
hard frost↓ | snow cover removal↓ | irrigation↑ |
drought↓ | drought↓ | drought↓ |
early stage of succession ↓ | ash↓ | number of ecotones↑ |
diverse litter mix↑ | diverse litter mix↑ | diverse litter mix↑ |
ash treatment↓ | soil "/> foliage | |
heavy metal pollution↓ | ||
organic mater content↑ |
Strongly abridged summary of information from studies on characteristics of Oribatid communities. (↑=increases or greater; ↓=decreases or lower)
With the overview of available studies, it can be clearly explored how various characteristics of Oribatid communities are modified due to changes in moisture, temperature, heavy metal concentration, organic matter content and level of disturbance. The most important question concerning the application of Oribatids as indicators is to clarify what kind of information content does natural Oribatid coenological patterns possess from the aspect of bioindication. Most of the variables listed above can be directly measured, since rapid methods are available to quantify temperature, heavy metal content etc. of the soil. Responses of Oribatids are worth to study in a more complex approach. Even now we have an expansive (but far from satisfactory) knowledge on how communities change due to modifications of different factors. These pieces of information necessitate the elaboration of such methods which render Oribatid communities suitable for the task to prognosticate what extent the given site can be considered near-natural or degraded, based on the Oribatid composition of a single sample taken from the given area. Raising further questions will be possible only after obtaining the answer for this problem. However, answering this problem needs extensive and coordinated work: approriate reference sites need to be appointed to clarify the concept of naturality, sampling and processing methods need to be standardized internationally – in conformity with the given environmental conditions – and the field of data processing methods also has to be developed. Definition and testing of Oribatid-based (or mesofauna-based in a broader sense) coenological indicators are also undoubtedly needed. The usefulness of Oribatid characteristics summarized in the introduction had been recognized long ago, now it is time to conduct research in a way that enables to explore and exploit the actual advantages Oribatid mites provide.
By setting up the spatial and temporal scales, we expected that the order based on the genus lists later should correspond to the real spatial and temporal scales, either the farther and qualitatively the more different habitats our lists originate from, the greater difference there should be among similarities inside the given categories. However, if data originate from the same site, the difference among the examined samples should be greater in case of the lists which are farther in time from each other.
The main goals of the present study are the following:
Developing a spatial and temporal scales reference based on the genus -level taxon lists with the help of similarity functions.
Examining the degree of distances in the similarity order used for indication.
Our analysis related to the notion that the genus level does not mean great data loss compared to the species level was carried out based on the databases by Marie Hammer. The work of Hammer was chosen due to the homogeneity and very extensive geographical cover of the databases. The series originate from two different sites of six different countries accordingly (Hammer, 1952, 1958, 1961, 1962, 1966, 1972). Besides the species and genus level the family level was analyzed as well, according to the taxonomical classification in the work by Balogh and Balogh (1992).
For our examination comparisons on genus level are sufficient as switching from species level to genus level did not cause a significant change regarding the distance and position of habitats according to the results of the ordinations. On family level inconsistency is caused by losing information. Using species-level data would be impractical due to taxonomical uncertainty on the one hand and lack of reliable databases on the other hand, and thirdly, due to unjustified increase in distance caused by genera with large number of species.
In order to be able to determine to which spatial and temporal distance the oribatid mite genus lists of two samples/sites examined by us correspond, different categories had to be defined. The categories were set up considering which combination of the given spatial and temporal scales the examined genus list pairs originate from. Regarding the time (Ti), differences between 0, 2, 12, 24 and 52 weeks and due to a study (Melamud et al., 2006(2007) were able to consider six years i.e. 312 weeks, too. In space the smallest distinguishable unit was the different substrate (S), then the different types of habitats/sites (H), the different topographicums (T) follow, and finally the largest unit was the zoogeographic kingdom (K). Substrate is the lowest vegetation level such as soil, förna, leaf litter, moss, bark etc. Site means habitat types such as rainforest, mossy forest, páramo etc. Topographicum is practically a country such as Papua New Guinea or Chile. When differentiating between zoogeographic kingdoms, six kingdoms found in the work by Balogh and Balogh (1992) were considered: Holarktis, Neotropis, Aethiopis, Orientalis, Australis (there Notogea) and Archinotis (there Antarctis), which is the modified version of Müller’s system (1980).
Genus lists of the different categories were collected from various sources. The first category means the similarity between genus lists of samples collected from the same zoogeographic kingdom (SaK), the same topographicum(SaT), the same type of site (SaH), the same substrate (SaS) and at the same time (Ti-0) (SaK/SaT/SaH/SaS/Ti-0). One part of these genus lists was obtained from our own research. From the soil of a dry oak forest in Törökbálint (Hungary), 9×300 cm3 förna sample was collected and the mesofauna was extracted from it, the oribatid mites were sorted out and identified to genus level according to the works by Balogh (1965); Balogh and Balogh (1972, 1992); Balogh and Mahunka (1980, 1983) and Olsanowski (1996). Further data for this category were collected by studying the scientific legacy of the late János Balogh, member of the Hungarian Academy of Sciences.
Data for the following four categories were also collected from our research. Samples were collected in 2005 and 2006 in a given quadratof 100 m2 in a dry oak forest in Törökbálint, Hungary (N 47°25’38” E 18°54’16”) and they were surveyed every two weeks. Every time samples were obtained from three types of substrates: from 500 cm3 leaf litter, 300 cm3 förna (from under the leaf litter) and 0.5 dm2 hypnum moss (Hypnum cupressiforme) living on tree trunks. Oribatid mites were extracted with the help of a Berlese-Tullgren funnel (Coleman et al., 2004) and identified on genus level. This examination made it possible to set up categories on pattern levels meaning a distance of two, 12, 24 and 52 weeks, in which substrate (S), site (H), topographicum (T) and zoogeographic kingdom (K) were the same (Sa). Abbreviations of these categories are: SaK/SaT/SaH/SaS/Ti-2, SaK/SaT/SaH/SaS/Ti-12, SaK/SaT/SaH/SaS/Ti-24 and SaK/SaT/SaH/SaS/Ti-52. A study by Melamud et al. (2007) was implied as well, in which samples were collected at different altitudes of Mount Carmel in Israel from the same sites with a difference of six years (312 weeks) (SaK/SaT/SaH/SaS/Ti-312).
Regarding spatial differences, the smallest change in scale is the difference in the substrate: SaK/SaT/SaH/DS/Ti-0, i.e. the substrate is different (D), however, there is no change in time (Ti-0). Genus lists belonging to this category originate from our own database and the above mentioned manuscripts by Balogh. Databases of three further studies were used as well (Behan-Pelletier and Winchester, 1998; Fagan et al., 2006; Lindo and Winchester, 2006).
In case of the following seven categories, only spatial scales “above” substrate change, substrate and time are not differentiated any more so they are marked “X”. Abbreviation of the same type of sites which can be found in the same zoogeographic kingdom and in the same topography is SaK/SaT/SaH/XS/Ti-X. Genus lists belonging to this category were obtained from the manuscripts by János Balogh, the study by Migliorini et al., (2005) and the studies by Hammer (1958, 1961, 1962, 1966). Abbreviation of the category of different sites is SaK/SaT/DH/XS/Ti-X. Sources of the series belonging to this category are: studies by Noti et al. (1996); Migliorini et al. (2002); Osler and Murphy (2005); Skubala and Gulvik (2005); Arroyo and Iturrondobeitia (2006); Osler et al. (2006), manuscripts by János Balogh, published series by János Balogh (Balogh et al., 2008) and studies by Hammer (1958, 1961, 1962, 1966). A series belonging here originates from samples collected by Levente Hufnagel in Australia (2006, Australia: QLD, Cairns)
In case of genus lists originating from different topographicums, we considered the point if they originate from the same (SaK/DT/SaH/XS/Ti-X) or different sites (SaK/DT/DH/XS/Ti-X) and if the two topographicums can be found in the same or different zoogeographic kingdoms (DK/DT/SaH/XS/Ti-X, DK/DT/DH/XS/Ti-X). These series come from studies by János Balogh and Marie Hammer.
In the last category only the zoogeographic kingdom can be interpreted as the complete genus lists of the six zoogeographic kingdoms were compared in it according to the work by Balogh and Balogh (1992) (DK/XT/XH/XS/Ti-X).
The lists created from the Hammer-databases were analysed with Ochiai, Jaccard and Sørensen distance functions and non-metric ordination using the software Syn-tax 2000 (Podani, 2001).
From the other databases we did not consider all possible list combinations which fit the category, only the ones having at least nine genera. After our complete genus list database was set up, the number of genera of the two lists and the number of the common genera were determined considering the genus list pairs in each category. As we had only presence-absence data and the value “d” of the contingency table was not considered in case of the genus list pairs, the Ochiai and Jaccard functions were used as distance functions (Podani, 1997). The similarity data of each category was calculated from the means of the values of the distance functions for the genus list pairs.
As our data were not always independent within a category, it was determined with a complex method to what extent the means of the categories differ from each other. We had several distance function values within each category as we. We had 106 genus list pairs within one category on average. From among the distance function values of each category fifteen values were chosen randomly with the help of a random number generator in the Excel software. It was carried out ten times in case of each category. In this way we got 10 series containing 15 values for each category. Series of the data table containing 10×15 values in case of each of the 14 categories were now independent and since normal distribution could not be observed within each category, the data were analysed with the Kruskal-Wallis statistical test. Each of the 14 series were analysed with the Mann-Whitney post hoc test as well, so we got ten tables containing 14×14 post hoc test results. One table was made out of these ten, which shows 95% confidence interval of the appropriate values of the ten tables. Based on this we were able to decide which categories differ from each other significantly. These statistical tests were carried out using PAST software (Hammer et al., 2001).
As we got nearly the same results using both distance functions (Ochiai and Jaccard), only the results calculated with the help of the Ochiai function are discussed further. Fig. 2 displays intervals with defined standard error around the Ochiai distance means in case of each category.
Average distance within genus list categories using Ochiai function. Next to the category codes, the number of genus list pairs used for calculating the average can be seen in brackets. Remarkable code parts are highlighted
In Fig. 2 it can be seen that the largest similarity between samples can be observed in the category where all criteria are the same (SaK/SaT/SaH/SaS/Ti-0) i.e. where the samples were collected at the same time and from the same substrates. Similarities of genus lists originating from different time but the same substrates are the next: first the two-week-difference, then the 12-, 24- and finally the 52-week-difference. Among comparisons on sample level the last one marked with yellow colour is the similarity of genus lists originating from different types of substrates.
As expected, within the same topographicum there is larger similarity between genus lists coming from the same type of sites than between those coming from different sites. This is where the sample series meaning six-year-difference (SaK/SaT/SaH/SaS/Ti-312) turn up. This considerable difference is amazing within one given habitat.
Among the last five there are the four categories in which the difference between lists originating from different topographicums(DT) is measured. Regarding the order of these four categories it is remarkable that the same type of site shows larger similarity than different sites, irrespective of the fact whether the different topographicums are in the same or different zoogeographic kingdoms. This corresponds with the results of a former study conducted with other methods (Balogh et al., 2008). The category DK/XT/XH/XS/Ti-X fits in the above mentioned categories in the order. Using the Jaccard distance function this is the only category position that changes places with the category DK/DT/SaH/XS/Ti-X.
The order set up with the help of genus lists based on the complete database met our expectations, so it can be definitely an appropriate reference in indication researches.
The significance of distances between genus list categories was tested by a Mann-Whitney tests. Our first remarkable result is that the average distances between genus lists originating from the same substrate but from different dates within a year does not differ from each other significantly. According to our former assumptions time difference could have been detected regarding a one-year-difference, however, it could not be detected from the substrates of the temperate dry oak forest studied. Consequently, if genus lists of the complete habitat type were examined with time lags less than a year, no change could be detected on site level, either. Irmler (2006) had a similar result on species level in a long-term European study.
The difference between oribatid mite communities originating from different substrates (DS/Ti-0) can be significantly larger in case of certain distance functions than the difference between communities coming from the same type of substrate (SaS/Ti-0). Besides, there is no large difference between samples collected within a year from a given type of substrate. It follows from these two statements that if genus lists originate from different types of substrates, there is larger difference between them than if samples are collected within a year from the same type of substrate. Consequently, the quality of substrate in a given habitat type is a more important factor in the composition of the oribatid mite community than time changes within a year.
Similarity between oribatid mite genus lists of the same types of sites (SaK/SaT/SaH/XS/Ti-0) differs significantly from the similarity between genus lists originating from the same type of substrate (SaK/SaT/SaH/SaS) if samples were collected with a time lag of maximum 24 weeks in the latter case. At the same time, the distance between genus lists coming from different types of substrates is similar to the distance between oribatid mite genus lists of the same or different habitats in a given topographicum, i.e. the type of substrates plays a similarly important role in the quality of the oribatid mite community as habitat types in a given topographicum.
The distance between genus lists originating from the same or different types of substrate is much smaller than the distance between genus lists of different topographicums (XK/DT/...), independently of the fact if sites in the same or different zoogeographic kingdoms are compared. More remarkable is the fact that the similarity of genus lists coming from the same sites in the same topographicumsdoes not differ significantly from the similarity of genus lists originating from the same sites in different topographicums. It means that oribatid mite communities of the same types of habitats resemble each other nearly in the same way no matter if they originate from the same or different topographicums.
Several researches have already been done to detect the pattern and composition of oribatid mite communities and their exact causes. However, it is hidden to date by which mechanisms the structure and functioning of the individual communities are affected.
Climatic factors belong to the most determinant ones. The above statement is reflected by the number of researches as well, because most of the studies on oribatid mite communities investigate how the communities react to the meteorological factors changing naturally or artificially, especially to temperature and the amount of precipitation (Gergócs and Hufnagel, 2009). First it is worth investigating the effect of the natural changes of the climatic factors, and the most appropriate way to do this is to study the seasonal changes of the communities. The mistake in most of these studies is that the research on seasonality is conducted over a maximum of a year (e.g. Schenker, 1984), so it cannot be determined whether the observed phenomena occur similarly each year. The most significant research on this topic was conducted by Irmler (2006) in a beech forest in Germany. He investigated monthly changes of ground-dwelling oribatid mite communities over a seven-year period and found that there are no important changes among the communities.
Our research is similar to his one, however, it differs as well because we collected samples every two weeks and not once a month, and we investigated not one but three microhabitats over a one and a half year period in an oak forest in Hungary.
The other difference is that data on oribatid mites were recorded on genus level and not on species level. The decision on the genus level can be justified by several factors. The analysis of Caruso and Migliorini (2006) showed that there were not any important changes in the data when studying human disturbance on oribatid mites and changing from species level to genus level. Podani (1989) found a similar result in case of plants, namely, changing to genus level does not mean a significant difference when comparing the studied habitats. Osler and Beattie (1999), Hammer and Wallwork (1979) and Norton et al. (1993) concluded according to their studies that the many widespread genera and families indicate that the similarity between oribatid mite communities should be studied above species level. In their meta-analyses their assumption was confirmed that taxonomical levels above the species level are more suitable to compare habitats. According to this we also compared the data series recorded with time difference on genus level.
The aim of our study was to explore which seasonal changes occur in oribatid mite communities living in three types of microhabitats in an oak forest and what role the most important climatic factors that is the amount of precipitation and temperature have in these changes.
Samples for our study were collected in 2005 and 2006 in a given quadrate of 100 m2 in a dry oak forest near Törökbálint, Hungary (47°25’38” N, 18°54’16” E). In the sampling quadrate the most common tree species is turkey oak (Quercus cerris), common trees are field maple (Acer campestre), common ash (Fraxinus excelsior) and wild service tree (Sorbus torminalis). The most important herbaceous plants are broad-leafed Solomon\'s seal (Polygonatum latifolium) and garlic mustard (Alliaria petiolata). Samples were collected every two weeks from 15th March till 1st December 2005 and from 26th March till 30th July 2006. Every time samples were collected randomly from three types of substrate within the quadrate: from 500 cm3 leaf litter, 300 cm3 foerna (from under the leaf litter) and 0.5 dm2 hypnum moss (Hypnum cupressiforme) living on tree trunks. So we obtained altogether 19 moss samples and 18 leaf litter and 18 foerna samples in 2005 (the first time no leaf litter and foerna samples were collected); in 2006 we collected 10 leaf litter, 10 moss and 9 foerna samples (the tenth sample could not be analyzed for technical reasons). Components of the mesofauna were extracted with the help of a modified Berlese-Tullgren funnel (Coleman et al., 2004) and conserved in isopropyl alcohol, then they were sorted into larger groups, and finally oribatid mites were identified on genus level. For the identification the works of Balogh (1965), Balogh and Balogh (1992, 1972), Balogh and Mahunka (1980), Olsanowski (1996) and Hunt et al. (1998) were used.
The samples were analyzed based on oribatid mite communities with the help of multivariate computer aided methods using the software Syn-tax 2000 (Podani, 2001). The size difference between the samples from the three types of substrate was compensated by comparing the ratio and presence-absence data of the oribatid mite genera with the help of non-metric multidimensional scaling and classification method using several distances. Monte Carlo method was used to check these analyses. The means of the genus proportion of the substrate types were calculated, each mean was multiplied by a number created by a random generator twenty times, then these new values were divided by the sum of the random numbers. This way twenty data series were generated per substrate. These were compared using classification and ordination. Correspondence analysis and PCA analysis were used to identify the genera which are responsible for possible differentiations. The difference of the genera in specimen number and proportion was checked using Mann-Whitney test between the substrate types. The average diversity and the genus number were calculated in case of each substrate type.
In order to recognize seasonality patterns, each season was marked (in winter no sampling was conducted), and the changes in genus diversity and total abundance during a period of the study were displayed separately in case of the three substrate types. The relationship between the pattern changes of the communities and meteorological factors was analyzed with the help of data series from the meteorological station in Pestszentlőrinc (47°25’53” N, 19°10’57” E). This station can be found 21 air km eastwards from our sampling point. In the case of precipitation the total precipitation amount of the sampling day and that of the preceding 5 and 10 days, and the standard deviation of the precipitation amount of the preceding 5, 10, 15, 20, 25 and 30 days were considered. In the case of temperature minimum and maximum values of the given days were available in our database, so in our analyses the means of these two values were considered. As for temperature data, the mean temperature of the sampling day and that of the preceding 5 and 10 days, and the standard deviation of temperature of the preceding 5, 10, 15, 20, 25 and 30 days were involved in our analyses. A redundancy analysis was conducted for all substrates first and then separately. In order to make the relationships more exact, the correlation between certain genera and meteorological factors was studied based on Spearman’s analysis.
Seasonal changes could not be detected in the communities of the three substrates. In Fig. 2 change in the Shannon diversity of the genera in the case of the three substrates, however, a seasonal pattern recurring the following year cannot be detected.
Change in the Shannon diversity of the genera in the case of the three substrates (2005-2006)
There is no relationships between the annual changes in precipitation amount and temperature and the composition and structure of Oribatid mite communities in leaf litter and foerna, however, in the case of moss there is. This can be caused by the genus Tectocepheus, which is one of the most frequent genera in moss samples (43% of the adult specimens on average), and its correlation is r=0.38 regarding the five-day mean temperature (Spearman’s correlation; p=0.043); and regarding the ten-day mean temperature its correlation is r=0.45 (Spearman’s correlation; p=0.014).
According to the research in seasonality during one and a half year we conclude that if any change occurs in the community during the year, it is not seasonal, i.e. neither genus-level diversity, nor abundance, nor the structure of the community have a recurring pattern in leaf litter, foerna and moss microhabitats. These results correspond with several previous data from the literature. Irmler (2004, 2006) observed oribatid mite communities in two different habitats over several years and he did not find any seasonal regularity either, except for some species. Those who interpreted their results in a way that seasonal change was found in oribatid mite communities drew a conclusion based on only one studied year or on the difference between two sampling months (Schenker, 1984; Stamou and Sgardelis, 1989; Askidis and Stamou, 1991; Clapperton et al., 2002). Such a hypothesis was, among others that important changes may occur between two temperate seasons in oribatid mite communities (Stamou and Sgardelis, 1989; Askidis and Stamou, 1991; Clapperton et al., 2002).(kétszer ugyanazok?) Although some of these studies were conducted in other types of habitats, i.e. not in temperate deciduous forests, a study covering a shorter period than a year is considered to be insufficient in the case of all habitats when observing regularities in seasonality. Schenker (1984) carried out a one year study around a turkey oak (Quercus cerris), a beech (Fagus sylvatica) and a Scots pine (Pinus sylvestris) in a moist deciduous forest in Switzerland. He found that annual change in abundance can be observed mostly around the beech and the pine, whereas it can hardly be observed around the oak, and species composition is not affected by seasonality, either. Oribatid mites occurred approximately in the same abundance further away from the oak trunks, than in the soil around it. For our study, data were collected in an oak forest. This may be the reason for the fact that we have not found any seasonal changes or changes in the genus composition, either. However, since Irmler (2006) conducted his studies in a beech forest and could not observe any seasonality either, and Schenker (1984) collected samples for only one year, it cannot be stated that the lack of seasonality is characteristic of oak forests.
If changes in communities do not occur seasonally, this can be brought into connection with micro- and macroclimatic effects. According to the results of Stamou and Sgardelis (1989) it could be concluded that the density of oribatid mites is largely influenced by temperature, although several later studies showed that temperature does not have the power to shape communities (Haimi et al., 2005). Irmler (2006) found that the structure of the community was in connection with the annual mean temperature only, and only some species showed significant correlation with some climatic factors. Webb et al. (1998) showed in the case of oribatid mite species living in polar areas that these species do not depend on seasonal changes, life cycle of the studied oribatid mite species is mainly influenced by temperature fluctuation. In our study proportional change correlating with temperature could be observed in the case of the genus Tectocepheus only and only in moss, however, no such connection can be found in the study of Irmler (2006), for example. Based on our results – just like based on those of Irmler (2006) – it can be concluded that the structure of oribatid mite communities is not affected by climatic factors in leaf litter and foerna substrates. In moss samples the connection with temperature was due to the genus Tectocepheus.
Seasonality can also be observed in the decomposition of plant material. Quantity and quality of the decomposing plant material change seasonally in the leaf litter and in the soil so it can be assumed that oribatid mite communities may change correspondingly during the year. However, the exact role of oribatid mites in the decomposition of the leaf litter is not completely clear till this day (Lindo and Winchster, 2007). The most important role of oribatid mites in the decomposition is the spreading of microbiota as they feed mainly on fungi and bacteria, and they are not in direct connection with the leaf litter input, accordingly (Maraun et al., 2001). This corresponds with the phenomenon observed by us, that the quantity of leaf litter may not have influenced the compositional changes of the communities.
Our result that leaf litter and foerna substrates differ from moss was not interpreted by other literature yet, however, there are observations regarding other types of substrates. A common result is for example that the oribatid mite community living in the foliage of the trees differs significantly from the one living in the soil under the trees (e.g. Yoshida and Hijji, 2005; Karasawa and Hijii, 2008). Karasawa and Hijii (2004) showed that the substrate of oribatid mite communities living in the soil, in the foliage, on the bark of the tree trunks and on the remnants of algae accumulating on soil significantly differ from each other in seaside forests. In our study the community living in hypnum moss was simpler than the one living in the soil in the forest. Communities of moss and lichen are always relatively simple (Gjelstrup, 1979; Gjelstrup and Søchtig, 1979; Smrz, 1992; Smrz and Kocourková, 1999; Smrz, 2006). The three frequent genera found in moss turned up in the observations of others as well. Zygoribatulaexilis is assumed to be a species living in moss (Gjelstrup, 1979), however, the Zygoribatula species found by us could be found on the forest ground as well. The genus Tectocepheus occurs everywhere from drier and more disturbed habitats to intact forests, accordingly it can also be found in moss in great quantities, especially because climatic fluctuation is larger in moss, what only some species can tolerate (Gjelstrup, 1979). A common epiphyte is Eremaeus oblongus (Smrz and Kocourková, 1999), in our study the genus Eremaeus could be found only in moss (except for only one foerna sample).
Therefore research showed that oribatid mite communities living in soil, leaf litter and hypnum moss, in Hungarian oak forests – similarly to those living in German beech forests – did not show seasonal changes. This result is important on the one hand because according to this, we are not bound to a season regarding sampling. However, besides that it would be important to detect the cause of the still occurring changes and patterns exactly. Furthermore it is unclear as well whether non-woody biocoenoses in the temperate zone or oribatid mite communities living in other climatic zones show seasonal changes.
Communities living in the soil differ from the oribatid mite community of moss living on tree trunks more significantly than from the community of the leaf litter. Oribatid mites in moss, especially the genus Tectocepheus, may be influenced by climatic factors to a large degree. In future it would be necessary to study oribatid mite communities of various microhabitats in order to detect exactly by which factors and to what degree their composition, changes and patterns are affected.
Oribatid mites of the tropical regions had been almost completely unknown for science before 1958. With the general use of the Berlese-funnel, systematic collections started at that time, which resulted in the collection of hundreds or thousands of species. However, the majority of these samples are unprocessed till these days. Professor J. Balogh and his fellow-workers had to realize, that the description of all the species living there is an impossible task.
And even if the recognizable morphological kinds of the samples will be described with decades of monumental work by the practices of formal describing taxonomy and according to the rules of nomenclature, the biological and coenological information content of these would still remain hidden. However the material extracted with the Berlese-Tullgren device informs us not only about the presence and morphological diversity, but also about the species’ abundance and dominance as well. Moreover it has become clear that this material together, as it was brought in front of us, contains a heap of such kind of information, which would be impossible to read from single species or from their constitutional characteristics. The samples collected this way are suitable for zoocoenological examinations. This observation led Humboldt to the recognition of „basic forms” (Grundformen) and later to the revelation of formations, which means the structure that can be found in plant associations without the exact knowledge of species. The emphasis here is on the „visibility” of the vegetation, because the recognition of biological communities began with the sight of the flora: vegetation is a „landscape element”. Animal communities – apart from some exceptions – live hidden in the vegetation. But the Berlese-device concentrates and makes them visible.
In this present section of our examinations, the objective is to clarify the methodological possibilities of biological indication and the information content of the coenological data matrices by an appropriately chosen indication case study. We also set the aim to apply univariate indicators and to exploit the possibilities of multivariate coenological pattern analysis.
In this study series, there is need to introduce the main Oribatid sinusia of tropical areas as per climatic, vegetation and elevation zones. According to the holistic approach, we start from the whole and proceed towards the smaller parts. As a first step, we examined the similarities between the Oribatid sinusia of the Neotropical Region and the Notogaea. Stemming from the fact that the vertical stratification of Oribatid fauna follows the vegetation zones, and took samples for examination from 3 elevation zones:
tropical rainforest
mossforest
paramo
In the study, we disregarded the mountain forest zone, which can be found between the zones of tropical rainforest and mossforest, because the determination of its borders is quite uncertain. To avoid transitions, Berlese-samples of tropical rainforest have been selected from 200 m elevation above sea level, close to the forest border. 2 ideal transects were set for representative sampling. The first one crosses Andes at Costa Rica, at the 10. degree of latitude, from coast to coast. The second one starts from Papua New-Guinea, from the valley of Fly River at the 4. degree of Southern latitude, and goes up to the 4000 m high ridge of Mt Wilhelm. As an amendment, samples were also taken near to the 23. degree of Southern latitude in an additional transect, crossing Serra do Mar and Serra do Mantiguera. This transect has been set because 200-300 years ago there’s been a belt of dense tropical rainforest – which even exceeded Amazonia in biodiversity – in the most densely populated area of Brazil, along the line marked by Sao Paulo and Rio de Janeiro. Almost 95 % of these forests have been devastated, but it could have been hoped that the rainforest spots reserved the original soil fauna – at least partially. 82 representative samples have been collected on 9 spots of the three transects. The spatial distribution of these samples and the abbreviation of individual sites can be seen in the next table:
Tropical rainforest | Mossforest | Paramo | ||
Costa Rica | RC: 10 | MC: 10 | PC: 10 | 30 |
Brazil | RB: 7 | MB: 6 | PB: 10 | 23 |
New-Guinea | RN: 10 | MN: 9 | PN: 10 | 29 |
27 | 25 | 30 | 82 |
The base table for our analyses was the 82 individual soil samples from the 9 examined habitat (3 habitat types of 3 areas) containing 111 Oribatid genera. For the various analyses, we created task-oriented assemblies from this base table.
Based on all of the individual samples, paired all samples with all other samples we created the similarity matrix of our data using multiple distance functions. In this current publication, Euclidean distance have been used.
Coenological similarity patterns can be analysed on multiple spatial scales (scale levels). We also analysed the similarity patterns of generic lists of different sites by NMDS with Euclidean distance, and hierarchical cluster-analysis. The two analytical results are shown projected onto each other (Figure 3). The multivariate similarity pattern of habitats’ Oribatid community gave the expected picture. It can be stated that differences originating from the habitats and continents can also be recognized in the similarity patterns of the generic lists of the examined habitats. However, it can seem surprising that despite the vast geographical distances the pattern generating role of habitats does not disappear, it seems perhaps even more important. In accordance with the real ecological conditions, mossforest plays a transitional role between rainforest and paramo. However, mossforests are the most similar to each other and they are positioned in the middle of the similarity pattern, while the rest of the sites are separated radially. It is clearly visible that Brazilian sites are much more similar to each other than the Costa-Ricans.
Comparison of the sites can be fine-tuned if we also examine the similarity pattern of the individual soil samples considering every sample as different objects independent from the sites. We analysed this similarity pattern also by applying NMDS and Euclidean distance (Figure 4). Analysing the collective similarity pattern of every individual sample it can be stated that the groupings of elementary samples reflect their relations to the sites. This justifies the methodological decision by which sites are considered the basic objects of the examination. It can be stated furthermore, that habitat-type is unambiguously more significant pattern-generating factor than geographical attribution. Rainforests, mossforests and paramos lying thousands of kilometers from each other are more similar than sites of other habitats at only a few kilometers distance. Following the results of these pattern analyses, exact examination of the observed phenomena with a regression model seems to be practical.
Similarity pattern of the examined sites in an NMDS ordination with the projection of the hierarchical cluster analysis results, applying Euclidean distance.
We pointed out that dissimilarities of habitats caused even by their type and also by the continent they originate from can be recognized in the similarity pattern of genus lists of the examined habitats. But if we analyze the overall similarity pattern of all the individual samples, it is quite conspicuous that the type of habitat is a much more significant pattern-generating factor than the geographical location. Rainforest, mossforests and paramos located many thousand kilometers from each other are more similar to each other than sites of other kind of habitats in only a few kilometers away.
The most important result of our case study is that the list of Oribatid genera as a coenological indicator, primarily characterizes the present ecological effects of the habitat and its climatically determined type of vegetation; and represents the effect of zoocoenological past in a much lesser extent. Thus, it can be concluded that a meritable scientific faunagenetical analysis should not be based upon geohistorical, but climatological grounds. This is why the ecological indication based on Oribatid genus lists provides unique possibilities for the purpose of climate change research.
Similarity pattern of elementary samples in an NMDS ordination by applying Euclidean distance.
It became obvious that if we had chosen species and not genera as the basis of our examination, we would not get results that were interpretable from bioindicational aspect. This is because the majority of the described species would have appeared only as local specifica, and they do not provide any meritable information on similarity patterns – unless we are thinking in a very small grade of space. Species-level indication studies would be only rational in the case if we would deal only with cosmopolite species, but their number and detectability would not be sufficient for the majority of examinations for practical tasks. Thus, our important conclusion is that under current circumstances, the recommended taxonomical unit for indicational ecological studies can only be the genus. This statement is also important because many authors (primarily species describing taxonomists) consider a serious problem of indicational research that a number of researchers classify individuals only to genus level (Gulvik 2007). However, based on the work of Caruso (2006), we know that human contamination, intervention and disturbance can be better detected if we examine larger taxonomical units. It is also clear that rapid changes can not be detected on species-, but on community level. From the same work, it is also known that the species data of Oribatid mites can be raised to genus- or family level, and this does not cause loss of data or sensitivity by multivariate methods. According to Osler (1999), it is possible that habitat preference is determined rather at family level. Furthermore it is also known that there is strong relation between species-level and higher taxon level diversity indicators.
At the same time, the standardization and quantification of current Oribatid-collection methods would be obviously necessary for the development of the bioindicational methodology in order to make the data from different authors comparable. The need for this is emphasized more and more in literature (Gulvik 2007). A criteria-system of classifying the collected individuals into genera (or into other optional morphological groups) can be considered as a part of the standardized method. The current identificational and taxonomical practice in oribatodology is almost completely unsuitable for the purposes of biological indication research. Till such methods are unavailable, case studies can be conducted only if the person doing field sample collection and taxonomical processing is identical, and furthermore, this is only true if the coenological matrices have been created with the greatest care.
During our examinations (Balogh et al 2008), we pointed out that by advancing vertically upwards in the tropical high mountains (from rainforests towards the paramo vegetation), the average species number of genera present, and the extent of Holarctic and/or Antarctic relations of present genera grow, which can be well interpreted with the conception system of geographical analogy based on climatic similarities. This indication adequately supports former studies on the role of vegetational similarities and on genera as taxonomical units suitable for indication. Many authors (Andrew 2003, Melamud 2007 state that advancing upwards on the mountains, elevation above sea level and exposure have significant influence on the diversity of Oribatids. Besides, it is known that Oribatid diversity grows from the Boreal region towards warmer climates, but it does not grow further towards the tropics (Maraun 2007).
Furthermore, we pointed out that from the aspect of similarity of individual samples, among the examined habitat types the mossforest is the most homogeneous habitat, and paramo is the most heterogeneous. This latter phenomenon can be well interpreted if we consider the uniform moss cover prevalent in the mossforest, and the role of stable microclimate created by the moss cover. In the paramo, the observed proportion of species with low constancy level and also the heterogeneity of habitats (tussocks with different size) are high, and the role of the resulting microclimatic variability is obvious.
The genus lists of oribatid mites provide a unique indication device for the research of climate change, based on their following characteristics:
Provide uncomparably simple, fast and effective sample collection opportunity in case of nearly any substrate type of nearly any habitat, all over the world.
Are easy and quick to indentify on a genus- level
Have well processed, synthetised scientific literature
Seasonal stability
Reflect the intrinsic, fundamental ecological characteristics of their biotops, which reflection overwrites the zoogeographical patterns
Extremely high information content of the distance functions of genus lists.
Category orders as results of the analyses mostly met our expectations, first of all in case of genus lists, i.e. larger distances between genus lists correspond to larger spatial scales. However, time difference within a year could not be pointed out to a considerable extent either on genus or on family level. The most important differences in the orders are the followings:
the difference between samples originating from the same and different types of substrate;
the difference between the distance of lists coming from the same type of substrate in a given site and the distance of genus lists originating from the same topographicumbut from different or the same types of site;
the difference between the distance of lists coming from the same or different types of substrate in a given site and the distance of lists originating from different topographicums;
the difference between the distance of lists coming from the same types of sites in a given topographicumand the distance of lists originating from different topographicums.
The analysis on family level differs from that of genus level that family lists of the zoogeographic kingdomsresemble each other as much as family lists originating from the same types of substrate.
Thus, compiled a reference list with the help of which it can be expressed to what spatial distances the similarity – shown with distance functions – of the genus or family lists of two oribatid mite communities originating from samples of unknown quality corresponds. Disturbed and transformed habitats can be compared with the help of oribatid mite communities based on an existing reference list.
We have to thank Prof. János Podani for his kind methodological help, Dr. Péter Balogh for his valuable professional help with the research of oribatid mites and for making the manuscripts from the Balogh-legacy available. We thank the “Adaptation to Climate Change” Research Group of the Hungarian Academy of Sciences and particularly the late Zsolt Harnos, who ensured the professional prerequisites of the research. Our research was supported by the Research Assistant Fellowship Support (Corvinus University of Budapest), „ALÖKI” Applied Ecological Research and Forensic Institute Ltd., the Landscape Architecture and Landscape Ecology PhD School of the Corvinus University of Budapest and the “Bolyai János” Research Fellowship (Hungarian Academy of Sciences, Council of Doctors). This work was supported by the research project of the National Development Agency TÁMOP 4.2.1.B-09/1/KMR-2010-0005.
More than 97% of all melanomas are diagnosed with a known primary site, most often on the skin [1, 2, 3]. Melanoma can also present within the eye or in the mucosae of internal organs [3]. In the rare cases in which it is diagnosed without an obvious primary site, it is referred to as melanoma of unknown primary (MUP) [3]. The predominant hypothesis to explain MUP involves the spontaneous regression of melanoma from a known primary site [3]. Metastatic melanoma could develop synchronously with a subclinical or otherwise unrecognized cutaneous, ocular, or mucosal melanoma.
Ultraviolet (UV) radiation is the most significant risk factor in the pathogenesis of melanoma, directly damaging DNA [1, 2, 3]. Multiple somatic and epigenetic alterations have also been implicated in the pathogenic process, along with the immune response and disturbances of immune tolerance [3].
There is a little evidence for early detection and risk stratification in malignant melanoma [4, 5]. The gold standard for melanoma diagnosis is still histopathological examination of tissues. Histopathological diagnosis involving the qualitative and quantitative assessment of biomarkers is susceptible to substantial interobserver variability, limiting its usefulness for individual patients. Specialized dermatopathologists are likely to be more consistent; however, their expertise is not widely available. Therefore, the standardization of the assessment is important [3].
Deep learning, an automated approach using labeled images to train a network with no other assumptions, has proven useful in many similar areas of digital pathology. In recent years, significant progress has been made in proteomics, metabolomics, and genomics. However, histopathological examination remains the gold standard for the diagnosis and prognosis of melanoma [3, 5, 6, 7].
The current World Health Organization (WHO) classification of skin tumors subdivides melanoma on the basis of solar elastosis assessed by dermal elastic fibers to measure cumulative sun damage (CSD) [3]. According to this WHO classification, there are currently three classes of melanomas: those associated with high CSD, those associated with low CSD, and those associated with nodular melanomas [3]. Solar elastosis is usually apparent in superficially spreading melanoma and lentigo maligna melanoma, the so-called high CSD melanoma. Desmoplastic melanoma is associated with increased solar elastosis. The most common subtype of high CSD melanoma is superficially spreading melanoma, which usually begins with early radial growth, followed by vertical growth and invasion of the dermis.
Acral, mucosal, uveal, and spitzoid melanomas are not associated with CSD or are characterized by low CSD. Nodular melanoma usually characterized as a low CSD type with early progression to vertical growth [3].
The development of melanoma is closely related to somatic and epigenetic changes. Different mutations have been implicated in its pathogenesis and evolution. Recent genomic classification subdivides melanoma into four subtypes based on the pattern of the most prevalent significantly mutated genes: BRAF, RAS and NF1 mutants, and triple-WT (wild type) [3, 5].
BRAF, CDKN2, and NRAS mutations are the most important and clinically relevant. The advent of novel personalized treatment for melanoma based on BRAF inhibitors and immunotherapy has reduced the mortality rate over the last decade, but advanced and metastatic melanomas remain difficult to treat [8, 9, 10]. Immune tolerance mechanisms are also important in the progression of melanoma.
Germline mutations in the cyclin-dependent kinase inhibitor 2A gene (CDKN2A) are frequently identified in familial melanoma; in 20–50% of such cases, three or more family members are diagnosed with melanoma [11]. Germline mutations in CDKN2A have also been associated with familial atypical multiple mole melanoma (FAMMM) syndrome, an autosomally dominant condition exemplified by a family history of melanoma and large numbers of atypical nevi [3, 11],
Immune responses are important in the pathogenesis of melanoma. Programmed cell death protein 1 ligand 1 (PDL1) and PDL2 are usually expressed by melanoma cells, T cells, B cells, and natural killer cells. This observation led to the development of specific antibodies against programmed cell death protein 1 (PD1) for the personalized treatment of melanoma (for example, nivolumab and pembrolizumab). Combinations of different targeting treatments that influence immune response mechanisms had beneficial effects on melanoma treatment, including PDL1 and CTLA4 targeting and immunotherapy with oncolytic viruses [8, 9, 10, 11, 12].
Clinicopathological characteristics, such as tumor size, tumor type, tumor invasiveness (Breslow thickness, Clark level, lymphovascular invasion, and neurotropisms), ulceration, and tumor mitotic activity, are significant prognostic factors for the development and progression of melanoma [3, 11]. In addition, it has been demonstrated that tumor-infiltrating lymphocytes can stratify melanoma into low- and high-risk progression types [13, 14, 15].
Diagnostic and therapeutic molecular markers have been increasingly used to assist in the histopathological assessment of melanoma [16]. These markers are helpful not only for diagnosing the condition, but also for distinguishing certain subtypes that could otherwise be difficult to identify [17, 18, 19, 20, 21, 22, 23, 24]. BRAF-mutated melanoma is mostly associated with superficial spreading melanoma, younger patients, and non-CSD skin, whereas NRAS mutational melanoma is a nodular subtype associated with CSD skin [20, 25].
Generally, NRAS mutations are independent of BRAF mutations, but dual expression has been reported [25]. The association of NRAS mutations with the degree of solar elastosis suggests that NRAS is closely related to the mutations induced by UV irradiation. Previous studies showed that NRAS mutation is also associated with decreased immune responses in peritumoral melanoma tissue and a more advanced tumor stage [26]. However, the prognostic value of NRAS mutation is still controversial, especially in early-stage melanoma.
At present, the histopathological examination of melanoma is based on the current WHO classification and the College of American Pathologists (CAP) guidelines [3]. Such criteria as tumor type, ulceration, peritumoral lymphocytes, Clark invasion level, Breslow invasion level, lymphovascular invasion, neurotropism, regression, and mitotic activity are routinely assessed. In addition, the excision lines and distance from the tumor are recorded. The pathological tumor node metastasis (pTNM) staging is determined on the basis of histopathological assessment. Table 1 summarizes the histopathological characteristics for assessing invasive melanoma.
Characteristics | |
Tumor site | Head and neck, arms, back, trunk, limb |
Tumor size | |
Histological type, Invasive melanoma | Invasive melanoma Superficial spreading melanoma (low-cumulative sun damage (CSD) melanoma) Lentigo maligna melanoma Desmoplastic melanoma Pure desmoplastic melanoma Mixed desmoplastic melanoma Acral melanoma Melanoma arising in a blue nevus (blue nevus-like melanoma) Melanoma arising in a giant congenital nevus Spitz melanoma (malignant Spitz tumor) |
Ulceration | Present/Absent |
Tumor Regression | Not identified Present, involving less than 75% of lesion Present, involving 75% or more of lesion |
Maximum Tumor (Breslow) Thickness | mm |
Anatomic (Clark) Level | Clark I-V level |
Mitotical activity | Mitoses/mm2 |
Solar elastosis | 0–3 |
Microsatellite(s) | Present/Absent |
Lymphovascular Invasion | Present/Absent |
Neurotropism | Present/Absent |
Tumor-Infiltrating Lymphocytes | The lymphocyte distribution score 0 = absence of lymphocytes within the tissue, 1 = presence of lymphocytes occupying <25% of the tissue, 2 = presence of lymphocytes occupying 25 to 50% of the tissue, and 3 = presence of lymphocytes occupying >50% of tissue |
Margins | Distance from Invasive Melanoma to Peripheral Margin, mm Distance from Invasive Melanoma to Deep Margin, mmm |
Regional lymph nodes status | Total Number of Lymph Nodes Size of Largest Nodal Metastatic Deposit, mm Extranodal involvement Total Number of Lymph Nodes with Tumor Sentinel Lymph Nodes with Tumor |
Distant metastasis | Not identified Site |
pTNM |
The protocol for routine clinical examination of melanoma.
Since Breslow thickness is of particular importance for TNM staging, digital slide analysis could provide better evidence for the measurement of invasions, especially in borderline cases. During recent years, digital pathology has been extensively used not only in research but also in clinical practice. Slide digitalization, scanning, and analysis by artificial intelligence have been suggested as a comprehensive tool to help pathologists construct a final report [27].
Figure 1 shows superficial spreading melanoma. The slide was stained with hematoxylin and eosin, magnification ×100. The tumor cells are located in the epidermis and papillary dermis, with moderate cellular pleomorphism, epidermotropism, and asymmetry. There is prominent peritumoral lymphocyte infiltration.
Representative photomicrograph demonstrated superficial spreading melanoma. Hematoxylin-eosin staining method, magnification: ×100, and scale bar: 20 μm.
Melanomas with an amelanotic appearance are more difficult to diagnose. Immunohistochemical staining positive for S100, SOX-10, HMB-45, Melan-A, Mart-1, and tyrosinase supports a diagnosis of melanoma [3].
Some melanomas, especially if regressed and metastatic, can cease to express HMB-45, Melan-A, and tyrosinase. In such cases, the immunohistochemical assessment of melanoma is straightforward; usually, only S-100 and vimentin expression is characteristic.
Figure 2A demonstrates S-100 expression in melanoma immunohistochemically. The arrow indicates positively stained cells. Note cytoplasmic biomarker expression. Figure 2B demonstrates SOX-10 expression in melanoma tissue immunohistochemically. The arrow indicates positively stained cells. Note the positive nuclear staining of melanoma cells.
Representative photomicrograph of biomarker expression melanoma. A. S-100, B. SOX-10. Immunohistochemical staining method, magnification: ×200, and scale bar: 50 μm.
Recently, it has been shown that p16 expression in melanoma is significantly lower than nevus [28]. PRAME has also been demonstrated as an immunohistochemical marker to aid the diagnosis of malignant melanoma [29].
Artificial intelligence (AI) and its subdisciplines of machine learning (ML) and deep learning (DL) are emerging as key technologies in healthcare with the potential to change lives and improve patient outcomes in many areas of medicine. While there is considerable promise for AI technologies in health, there are challenges ahead. These include recognition that it will be extremely difficult for AI to achieve full automation in the diagnostic/clinical pathway. Most efforts to date have focused on the development of neural network architectures to enhance the performance of different computational pathology tasks. U-Net has been used in several applications.
Recently, a deep learning network called MVPNet—multiviewing path deep learning neural networks for magnification invariant diagnosis in breast cancer—has been proposed for the digital analysis of breast cancer. MVPNet has significantly fewer parameters than standard deep learning models and combines local and global features.
During the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable patients to be selected and stratified for treatment.
In the global market, there is a high demand for digital pathology and artificial intelligence software for consultations and automated data analysis. Recently, the Food and Drug Administration (FDA) approved the first digital pathology software for automated prostate cancer assessment.
The possibility of digitizing whole-slide images of tissue has led to the advent of artificial intelligence and machine learning tools in digital pathology, which enable subvisual morphometric phenotypes to be mined and could ultimately improve patient management [30].
Tumor-infiltrating lymphocytes (TILs) are considered a manifestation of the host immune response to the tumor [13, 14, 15].
Cell membrane-bound antigens different from those of normal cells are characteristic of tumor cells. These antigens are recognized as nonself by antigen-presenting cells, with subsequent activation of cellular and humoral immune responses. The key cells for cytotoxic immune responses are CD4, CD8, and NK cells; for humoral responses, they are B lymphocytes and plasma cells. However, a tumor can escape immune surveillance by unmasking its antigens and inducing apoptosis in the immune cells. The key characteristic of tumor immunity is the presence of peritumoral and intratumoral inflammatory cells. Tumor-infiltrating lymphocytes (TILs) arise from different inflammatory cells, mainly CD4 and CD8 T cells, plus CD20 B lymphocytes and NK cells. These cells have been extensively described in antitumor immunity. T-regulatory lymphocytes, which form the key cell population of peritumoral and intratumoral lymphocytes, have immunoregulatory features. They suppress the immune response and commonly express FOXP3, CD4, and CD25 [13, 14, 15].
It has been shown that peritumoral lymphocyte infiltration (TIL) is valuable for melanoma prognosis. It is also closely associated with tumor metastasis to lymph nodes. Patients with increased TIL infiltrate have a better prognosis [13]. Furthermore, increased TIL infiltration is a sign of longer progression-free survival and overall survival, and a lower mortality rate [31].
However, American Joint Committee for Cancer (AJCC) manuals have not included the assessment of TIL for tumor staging and prognosis, and some pathology guidelines do not require peritumoral lymphocyte infiltration to be assessed [3]. The College of American Pathologists (CAP) and the Royal College of Pathologists of Australasia (RCPA) protocols suggest that peritumoral lymphocyte infiltration be assessed as brisk and nonbrisk infiltration. The association of TIL with an improved prognosis for melanoma remains controversial [32, 33, 34]. Previous studies have shown that an increased TIL infiltrate is associated with more favorable survival outcomes [13, 30, 31].
A recent study showed that melanoma patients with high TIL grade had significantly better progression-free survival than patients with low TIL grade [15]. The authors recommend incorporating the assessment of TIL into a scoring system, for example from 0 to 3, by estimating the percentage cellular infiltration of the tissue. The scoring system was defined as follows: 0 = absence of lymphocytes from the tissue, 1 = lymphocytes occupying <25% of the tissue, 2 = lymphocytes occupying 25–50% of the tissue, and 3 = lymphocytes occupying >50% of tissue. Low TIL infiltration was defined as scores of 0 and 1. High TIL infiltration was defined as scores of 2 and 3 [15]. This scoring system correlated significantly with progression-free survival and showed perfect concordance among pathologists; therefore, it could be recommended for routine clinical practice.
The BRAF gene is located on the seventh chromosome and encodes BRAF protein, one of the signaling kinases in the MAPK pathway. BRAF mutations are the most common genetic alterations in cutaneous melanoma. The prevalence of BRAF mutations among the different melanoma subtypes and populations ranges from 40% to 60% of cases [16, 17, 18, 19, 25]. BRAF mutations lead to the constitutive activation of the MAPK pathway. The most common BRAF mutation (80% of all alterations in the gene) is V600E [20]. V600K and V600R mutations are other examples [21].
Previous studies have shown that the BRAF V600E mutation is associated with the superficial spreading melanoma subtype, solar elastosis, younger patients, and melanoma localization on the extremities and back. In contrast, BRAF V600K mutations are correlated with skin sites with high CSD, such as the head and neck, and with older patients [14, 15, 16, 17, 18, 19, 35, 36, 37, 38, 39, 40].
Recently, whole-genome sequencing of benign melanocytic nevi revealed BRAF mutations in addition to NRAS mutations, the mutational load being positively correlated with UV exposure. The mutational loads in congenital nevi were lower [23].
A recent study revealed associations between BRAF V600 mutational status and younger patient age, Clark invasion level, Breslow thickness, lymphovascular invasion, female gender, and TIL [15].
The importance of NRAS mutations for the progression of melanoma is controversial. Some studies have shown associations between NRAS mutation and melanoma prognosis, while others found that NRAS mutations have no value for assessing the prognosis [3, 11, 41, 42].
The RAS gene family includes genes that encode the G proteins responsible for cell growth and cell cycle regulation. Three major members of the RAS gene family are NRAS, KRAS, and HRAS. NRAS-mutant melanomas often have dysregulated cell cycles, characterized by the upregulation of cyclin D1 and loss of the tumor suppressor p16INK4A [43].
The NRAS gene is most frequently mutated at hotspots in exon 2 (codons 12 and 13) and exon 3 (codon 61) [42, 44, 45, 46, 47]. Mutations of NRAS have previously been associated with the nodular subtype of the primary tumor and localization in sun-damaged skin [45].
Some studies have shown that NRAS mutation is associated with a favorable prognosis [46]. In contrast, others have demonstrated that this mutation is associated with a worse prognosis [48, 49], and some found no significant association at all between NRAS mutation and a prognosis of melanoma [45, 50, 51].
Recent evidence showed that in up to 20–30% of cases, NRAS mutations coexisted with BRAF mutations. Patients with both BRAF and NRAS mutations had worse prognoses than those with BRAF mutant melanoma alone [25, 26]. Since the prognosis for co-mutations is worse, routine NRAS assessment of all the primary melanoma cases would seem to be beneficial.
The assessment of NRAS mutation in melanoma, especially in BRAF-wild-type melanoma, is beneficial since targeted treatment is considered for NRAS mutant melanoma [52]. Immune checkpoint inhibitors (anti-CTLA4 and/or anti-PD1) are the standard treatment in these cases. However, a recent clinical trial also showed promising results from targeted treatments of PI3K-AKT-mTOR, MEK, and CDK4/6.
In recent years, the direction of personalized medicine, which is based on disease-specific targeting therapy, along with the early diagnosis of tumors and identification of high-risk individuals, has developed rapidly around the world.
The gold standard for melanoma diagnosis is histopathological investigation and routine evaluation of, e.g., tumor type and tumor invasiveness. Histopathological slide digitalization seems to be beneficial for standardizing the assessment of histopathological characteristics. In addition, the assessment of peritumoral lymphocyte infiltration and BRAF and NRAS mutation status in early-stage melanoma has proved to be of significant value for the risk stratification of disease progression and for personalized treatment.
The assessment of BRAF and NRAS mutations in melanomas is important not only for personalized targeting treatment, but also for prognosis and surveillance strategy. BRAF and NRAS mutations correlate with primary tumor type and disease stage. NRAS mutant melanoma has a significantly worse prognosis than BRAF mutant melanoma, and an active surveillance strategy should be applied to patients with this condition.
The study was supported by project “Strengthening of the capacity of doctoral studies at the University of Latvia within the framework of the new doctoral model” identification No. 8.2.2.0/20/I/006. The assistance of BioMedES UK (www.biomedes.biz) in the final drafting of this chapter is acknowledged.
The authors declare no conflict of interest.
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It functions as a redox buffer which can reduce, and thereby neutralize, reactive oxygen species. It is a cofactor for enzymes involved in regulating photosynthesis, hormone biosynthesis, and regenerating other antioxidants; which also regulates cell division and growth, is involved in signal transduction, and has roles in several physiological processes, such as immune stimulation, synthesis of collagen, hormones, neurotransmitters, and iron absorption, has also roles in detoxifying the body of heavy metals. Severe deficiency of vitamin C causes scurvy, whereas limited vitamin C intake causes symptoms, such as increased susceptibility to infections, loosening of teeth, dryness of the mouth and eyes, loss of hair, dry itchy skin, fatigue, and insomnia. In contrast, vitamin C can also act as a prooxidant, especially in the presence of transition metals, such as iron and copper, starting different hazardous radical reactions. Vitamin C can both act as a strong, efficient, and cheap antioxidant agent and, at the same time, behave as a radical promoter. Further investigations are needed to illuminate the dual roles of vitamin C",book:{id:"5940",slug:"vitamin-c",title:"Vitamin C",fullTitle:"Vitamin C"},signatures:"Fadime Eryılmaz Pehlivan",authors:[{id:"200567",title:"Dr.",name:"Fadime",middleName:null,surname:"Eryılmaz Pehlivan",slug:"fadime-eryilmaz-pehlivan",fullName:"Fadime Eryılmaz Pehlivan"}]},{id:"56440",doi:"10.5772/intechopen.70162",title:"Vitamin C: Sources, Functions, Sensing and Analysis",slug:"vitamin-c-sources-functions-sensing-and-analysis",totalDownloads:6442,totalCrossrefCites:15,totalDimensionsCites:28,abstract:"Vitamin C is a water-soluble compound found in living organisms. It is an essential nutrient for various metabolism in our body and also serves as a reagent for the preparation of many materials in the pharmaceutical and food industry. In this perspective, this chapter can develop interest and curiosity among all practicing scientists and technologists by expounding the details of its sources, chemistry, multifunctional properties and applications.",book:{id:"5940",slug:"vitamin-c",title:"Vitamin C",fullTitle:"Vitamin C"},signatures:"Sudha J. Devaki and Reshma Lali Raveendran",authors:[{id:"187911",title:"Associate Prof.",name:"Sudha",middleName:null,surname:"J Devaki",slug:"sudha-j-devaki",fullName:"Sudha J Devaki"},{id:"204937",title:"Mrs.",name:"Reshma",middleName:null,surname:"Laly Ravindran",slug:"reshma-laly-ravindran",fullName:"Reshma Laly Ravindran"}]},{id:"50921",doi:"10.5772/63712",title:"Menaquinones, Bacteria, and Foods: Vitamin K2 in the Diet",slug:"menaquinones-bacteria-and-foods-vitamin-k2-in-the-diet",totalDownloads:3333,totalCrossrefCites:10,totalDimensionsCites:22,abstract:"Vitamin K2 is a collection of isoprenologues that mostly originate from bacterial synthesis, also called menaquinones (MKs). Multiple bacterial species used as starter cultures for food fermentation are known to synthesize MK. Therefore, fermented food is the best source of vitamin K2. In the Western diet, dairy products are one of the best known and most commonly consumed group of fermented products.",book:{id:"5169",slug:"vitamin-k2-vital-for-health-and-wellbeing",title:"Vitamin K2",fullTitle:"Vitamin K2 - Vital for Health and Wellbeing"},signatures:"Barbara Walther and Magali Chollet",authors:[{id:"184784",title:"Dr.",name:"Barbara",middleName:null,surname:"Walther",slug:"barbara-walther",fullName:"Barbara Walther"},{id:"188194",title:"Mrs.",name:"Magali",middleName:null,surname:"Chollet",slug:"magali-chollet",fullName:"Magali Chollet"}]},{id:"66098",doi:"10.5772/intechopen.84445",title:"Golden Rice: To Combat Vitamin A Deficiency for Public Health",slug:"golden-rice-to-combat-vitamin-a-deficiency-for-public-health",totalDownloads:3388,totalCrossrefCites:12,totalDimensionsCites:17,abstract:"Vitamin A deficiency (VAD) has been recognised as a significant public health problem continuously for more than 30 years, despite current interventions. The problem is particularly severe in populations where rice is the staple food and diversity of diet is limited, as white rice contains no micronutrients. Golden Rice is a public-sector product designed as an additional intervention for VAD. There will be no charge for the nutritional trait, which has been donated by its inventors for use in public-sector rice varieties to assist the resource poor, and no limitations on what small farmers can do with the crop—saving and replanting seed, selling seed and selling grain are all possible. Because Golden Rice had to be created by introducing two new genes—one from maize and the other from a very commonly ingested soil bacterium—it has taken a long time to get from the laboratory to the field. Now it has been formally registered as safe as food, feed, or in processed form by four industrialised counties, and applications are pending in developing countries. The data are summarised here, and criticisms addressed, for a public health professional audience: is it needed, will it work, is it safe and is it economic? Adoption of Golden Rice, the next step after in-country registration, requires strategic and tactical cooperation across professions, non-governmental organisations (NGOs) and government departments often not used to working together. Public health professionals need to play a prominent role.",book:{id:"7978",slug:"vitamin-a",title:"Vitamin A",fullTitle:"Vitamin A"},signatures:"Adrian Dubock",authors:[{id:"273220",title:"Ph.D.",name:"Adrian",middleName:null,surname:"Dubock",slug:"adrian-dubock",fullName:"Adrian Dubock"}]},{id:"62836",doi:"10.5772/intechopen.79350",title:"The Role of Thiamine in Plants and Current Perspectives in Crop Improvement",slug:"the-role-of-thiamine-in-plants-and-current-perspectives-in-crop-improvement",totalDownloads:1567,totalCrossrefCites:7,totalDimensionsCites:11,abstract:"Current research is focusing on selecting potential genes that can alleviate stress and produce disease-tolerant crop variety. The novel paradigm is to investigate the potential of thiamine as a crop protection molecule in plants. Thiamine or vitamin B1 is important for primary metabolism for all living organisms. The active form, thiamine pyrophosphate (TPP), is a cofactor for the enzymes involved in the synthesis of amino acids, tricarboxylic acid cycle and pentose phosphate pathway. Recently, thiamine is shown to have a role in the processes underlying protection of plants against biotic and abiotic stresses. The aim of this chapter is to review the role of thiamine in plant growth and disease protection and also to highlight that TPP and its intermediates are involved in management of stress. The perspectives on its potential for manipulating the biosynthesis pathway in crop improvement will also be discussed.",book:{id:"6709",slug:"b-group-vitamins-current-uses-and-perspectives",title:"B Group Vitamins",fullTitle:"B Group Vitamins - Current Uses and Perspectives"},signatures:"Atiqah Subki, Aisamuddin Ardi Zainal Abidin and Zetty Norhana\nBalia Yusof",authors:[{id:"240031",title:"Dr.",name:"Zetty-Norhana Balia",middleName:null,surname:"Yusof",slug:"zetty-norhana-balia-yusof",fullName:"Zetty-Norhana Balia Yusof"},{id:"261167",title:"Mr.",name:"Aisamuddin Ardi",middleName:null,surname:"Zainal Abidin",slug:"aisamuddin-ardi-zainal-abidin",fullName:"Aisamuddin Ardi Zainal Abidin"},{id:"261169",title:"Ms.",name:"Atiqah",middleName:null,surname:"Subki",slug:"atiqah-subki",fullName:"Atiqah Subki"}]}],mostDownloadedChaptersLast30Days:[{id:"56440",title:"Vitamin C: Sources, Functions, Sensing and Analysis",slug:"vitamin-c-sources-functions-sensing-and-analysis",totalDownloads:6442,totalCrossrefCites:15,totalDimensionsCites:28,abstract:"Vitamin C is a water-soluble compound found in living organisms. It is an essential nutrient for various metabolism in our body and also serves as a reagent for the preparation of many materials in the pharmaceutical and food industry. In this perspective, this chapter can develop interest and curiosity among all practicing scientists and technologists by expounding the details of its sources, chemistry, multifunctional properties and applications.",book:{id:"5940",slug:"vitamin-c",title:"Vitamin C",fullTitle:"Vitamin C"},signatures:"Sudha J. Devaki and Reshma Lali Raveendran",authors:[{id:"187911",title:"Associate Prof.",name:"Sudha",middleName:null,surname:"J Devaki",slug:"sudha-j-devaki",fullName:"Sudha J Devaki"},{id:"204937",title:"Mrs.",name:"Reshma",middleName:null,surname:"Laly Ravindran",slug:"reshma-laly-ravindran",fullName:"Reshma Laly Ravindran"}]},{id:"56013",title:"Vitamin C: An Antioxidant Agent",slug:"vitamin-c-an-antioxidant-agent",totalDownloads:7829,totalCrossrefCites:27,totalDimensionsCites:60,abstract:"Vitamin C or ascorbic acid (AsA) is a naturally occurring organic compound with antioxidant properties, found in both animals and plants. It functions as a redox buffer which can reduce, and thereby neutralize, reactive oxygen species. It is a cofactor for enzymes involved in regulating photosynthesis, hormone biosynthesis, and regenerating other antioxidants; which also regulates cell division and growth, is involved in signal transduction, and has roles in several physiological processes, such as immune stimulation, synthesis of collagen, hormones, neurotransmitters, and iron absorption, has also roles in detoxifying the body of heavy metals. Severe deficiency of vitamin C causes scurvy, whereas limited vitamin C intake causes symptoms, such as increased susceptibility to infections, loosening of teeth, dryness of the mouth and eyes, loss of hair, dry itchy skin, fatigue, and insomnia. In contrast, vitamin C can also act as a prooxidant, especially in the presence of transition metals, such as iron and copper, starting different hazardous radical reactions. Vitamin C can both act as a strong, efficient, and cheap antioxidant agent and, at the same time, behave as a radical promoter. Further investigations are needed to illuminate the dual roles of vitamin C",book:{id:"5940",slug:"vitamin-c",title:"Vitamin C",fullTitle:"Vitamin C"},signatures:"Fadime Eryılmaz Pehlivan",authors:[{id:"200567",title:"Dr.",name:"Fadime",middleName:null,surname:"Eryılmaz Pehlivan",slug:"fadime-eryilmaz-pehlivan",fullName:"Fadime Eryılmaz Pehlivan"}]},{id:"69402",title:"Vitamin D Deficiency and Diabetes Mellitus",slug:"vitamin-d-deficiency-and-diabetes-mellitus",totalDownloads:1610,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"Vitamin D (VD) is a molecule that can be synthesized directly in the humans’ body or enter the organism with food in the form of inactive precursors. To exert its biological action, VD undergoes two-stage hydroxylation (at the 25th and 1st position) catalyzed by cytochromes P450, the presence of which has already been shown in almost all tissues of the human body. The product of hydroxylation is hormone-active form of vitamin D–1,25(OH)2D. 1,25(OH)2D binds to specific vitamin D receptor (VDR) and regulates the expression of genes involved in bone remodeling (classical function) and genes that control immune response, hormone secretion, cell proliferation, and differentiation (nonclassical functions). VD deficiency is prevalent around the globe and may be one of the key factors for diabetes development. The direct association between vitamin D deficiency and type 1 (T1D) and type 2 (T2D) diabetes has been proven. Detection of VDR in pancreas and adipose tissue, skeletal muscles, and immune cells allowed implying the antidiabetic role of vitamin D by enhancing insulin synthesis and exocytosis, increasing the expression of the insulin receptor, and modulating immune cells’ functions. This chapter summarizes data about relationship between VD insufficiency/deficiency and development of T1D and T2D, and their complications.",book:{id:"7038",slug:"vitamin-d-deficiency",title:"Vitamin D Deficiency",fullTitle:"Vitamin D Deficiency"},signatures:"Ihor Shymanskyi, Olha Lisakovska, Anna Mazanova and Mykola Veliky",authors:null},{id:"76108",title:"Vitamin D Metabolism",slug:"vitamin-d-metabolism",totalDownloads:504,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"Vitamin D plays an important role in bone metabolism. Vitamin D is a group of biologically inactive, fat-soluble prohormones that exist in two major forms: ergocalciferol (vitamin D2) produced by plants in response to ultraviolet irradiation and cholecalciferol (vitamin D3) derived from animal tissues or 7-dehydrocholesterol in human skin by the action of ultraviolet rays present in sunlight. Vitamin D, which is biologically inactive, needs two-step hydroxylation for activation. All of these steps are of crucial for Vitamin D to show its effect properly. In this section, we will present vitamin D synthesis and its action steps in detail.",book:{id:"10631",slug:"vitamin-d",title:"Vitamin D",fullTitle:"Vitamin D"},signatures:"Sezer Acar and Behzat Özkan",authors:[{id:"29878",title:"Dr.",name:"Behzat",middleName:null,surname:"Özkan",slug:"behzat-ozkan",fullName:"Behzat Özkan"},{id:"348287",title:"Dr.",name:"Sezer",middleName:null,surname:"Acar",slug:"sezer-acar",fullName:"Sezer Acar"}]},{id:"50754",title:"Medicinal Chemistry of Vitamin K Derivatives and Metabolites",slug:"medicinal-chemistry-of-vitamin-k-derivatives-and-metabolites",totalDownloads:1923,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"Vitamin K acts as a cofactor for γ‐glutamyl carboxylase. Recently, various biological activities of vitamin K have been reported. Anti‐proliferative activities of vitamin K, especially in vitamin K3, are well known. In addition, various physiological and pharmacological functions of vitamin K2, such as transcription modulators as nuclear steroid and xenobiotic receptor (SXR) ligands and anti‐inflammatory effects, have been revealed in the past decade. Characterization of vitamin K metabolites is also important for clinical application of vitamin K and its derivatives. In this chapter, recent progress on the medicinal chemistry of vitamin K derivatives and metabolites is discussed.",book:{id:"5169",slug:"vitamin-k2-vital-for-health-and-wellbeing",title:"Vitamin K2",fullTitle:"Vitamin K2 - Vital for Health and Wellbeing"},signatures:"Shinya Fujii and Hiroyuki Kagechika",authors:[{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika"},{id:"180529",title:"Dr.",name:"Shinya",middleName:null,surname:"Fujii",slug:"shinya-fujii",fullName:"Shinya Fujii"}]}],onlineFirstChaptersFilter:{topicId:"379",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},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:11,numberOfPublishedChapters:91,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:333,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:11,numberOfPublishedChapters:144,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:126,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:113,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:23,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:13,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:"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"}}}},{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"}}}}]},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 17th, 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:"Rosa María Martínez-Espinosa is a Full Professor of Biochemistry and Molecular Biology at the University of Alicante, Spain, and has been the vice president of International Relations and Development Cooperation at this university since 2010. She created the research group in applied biochemistry in 2017 (https://web.ua.es/en/appbiochem/), and from 1999 to the present has made more than 200 contributions to Spanish and international conferences. Furthermore, she has around seventy-five scientific publications in indexed journals, eighty book chapters, and one patent to her credit. Her research work focuses on microbial metabolism (particularly on extremophile microorganisms), purification and characterization of enzymes with potential industrial and biotechnological applications, protocol optimization for genetically manipulating microorganisms, gene regulation characterization, carotenoid (pigment) production, and design and development of contaminated water and soil bioremediation processes by means of microorganisms. This research has received competitive public grants from the European Commission, the Spanish Ministry of Economy and Competitiveness, the Valencia Region Government, and the University of Alicante.",institutionString:"University of Alicante",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. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!0,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. 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