*Article* **Cropmarks in Aerial Archaeology: New Lessons from an Old Story**

**Zoltán Czajlik 1,\*, Mátyás Árvai 2, János Mészáros 2, Balázs Nagy 3, László Rupnik 4 and László Pásztor 2**

**Abstract:** Cropmarks are a major factor in the effectiveness of traditional aerial archaeology. Identified almost 100 years ago, the positive and negative features shown by cropmarks are now well understood, as are the role of the different cultivated plants and the importance of precipitation and other elements of the physical environment. Generations of aerial archaeologists are in possession of empirical knowledge, allowing them to find as many cropmarks as possible every year. However, the essential analyses belong mostly to the predigital period, while the significant growth of datasets in the last 30 years could open a new chapter. This is especially true in the case of Hungary, as scholars believe it to be one of the most promising cropmark areas in Europe. The characteristics of soil formed of Late Quaternary alluvial sediments are intimately connected to the young geological/geomorphological background. The predictive soil maps elaborated within the framework of renewed data on Hungarian soil spatial infrastructure use legacy, together with recent remote sensing imagery. Based on the results from three study areas investigated, analyses using statistical methods (the Kolmogorov–Smirnov and Random Forest tests) showed a different relative predominance of pedological variables in each study area. The geomorphological differences between the study areas explain these variations satisfactorily.

**Keywords:** cropmarks; empirical knowledge; alluvial sediments; geomorphological/pedological background; soil spatial infrastructure; statistical methods

#### **1. Introduction**

In June 1998, one of the most prolific aerial archaeologists of the second half of the 20th century, René Goguey, arrived in Budapest from Paris on an Air France scheduled flight. While still at the airport, he commented that from an altitude of 20,000 feet it was clear to him that research into cropmarks on the Little Plain (Rába interfluve) should begin immediately. Despite the previous several years' lack of success, work was recommenced in this region, and a large number of good quality archaeological features visible as cropmarks were identified [1].

To understand the significance and the complexity of cropmarks in aerial archaeology, a brief summary of traditional ways of investigating them and a short presentation of the factors affecting their formation are required. Alluvial fans are ideal for studying the role of the different soils in the formation of cropmarks, and therefore, this introduction will also contain the geographical background of the alluvial fans and the relevant results of soil mapping in Hungary.

**Citation:** Czajlik, Z.; Árvai, M.; Mészáros, J.; Nagy, B.; Rupnik, L.; Pásztor, L. Cropmarks in Aerial Archaeology: New Lessons from an Old Story. *Remote Sens.* **2021**, *13*, 1126. https://doi.org/10.3390/rs13061126

Academic Editors: Geert Verhoeven, Dave Cowley and Arianna Traviglia

Received: 31 December 2020 Accepted: 9 March 2021 Published: 16 March 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### *1.1. Cropmarks in Aerial Archaeology*

What has been long recognized is the correlation between variations in vegetation on arable land (and, under certain conditions, on grazed and mowed areas) and the presence of traces of past human activities (along with many natural phenomena). Although there were indications of an understanding that vegetation might reveal the past in this way as early as around 1540 (John Leland), it was the work of O. G. S. Crawford in the UK beginning in 1914 that definitively linked variations in crop growth to the presence of buried archaeological features [2]. By the 1920s, this was already being applied in his research [3]. The development of aviation and aerial photography then led to similar insights in continental Europe, too. In Hungary, Sándor Neogrády, another experienced World War I aviator, was an aerial photographer and cartographer who started to collect what he termed "unnatural phenomena" from the 1920s [4]. Pioneer researchers began to organize them systematically, so Neogrády also described the role of darker, denser vegetation, which grows over filled-in ditches/pits, and the sparser, lighter vegetation over buried walls, introducing the distinction between positive and negative cropmarks as basic categories [4].

In addition to variations in color, differences in the height of crops and vegetation are also important (Figure 1), as illustrated in various studies [5,6]. Many cultivated plant species indicate anomalies very early in their growing season, but it is in the course of ripening that the greater part of variations may be detected [7,8].

**Figure 1.** Dabas—Öreg Országúti-d ˝ul˝o (Pest County, Hungary) aerial archaeological site. The image is dominated by the positive cropmarks showing the color variations (marks of a green circular ditch and small pits) in yellow wheat. On the right side, mostly due to the barley's late harvest period, some further pits are visible (cf. Figure 2) owing to shadow effect of the cropmarks (Oblique aerial photograph, 12 June 2015, Zoltán Czajlik).

From the 1950s, first in France and Germany, later in Austria and Italy, and finally in the 1990s in Switzerland and the former socialist countries, the importance assigned to the identification of the cropmarks has grown. This, together with data gathered using traditional, analog aerial photography in archaeology, was summarized by Irwin Scollar in his work on archaeological prospection, which is still relevant today [9].

Beginning in the 2000s, the use of digital cameras and GPS for positioning images and navigation has greatly increased the efficiency of traditional aerial archaeological data collection. Images with reference points can be quickly rectified, and the interpretation and creation of photomaps has become much easier. Thanks to digital technology, it is now possible to collect information not only from the visible spectrum, but also from the NIR and NUV domains, which (in a way similar to infrared films in the analog era) can increase the contrast between normal and stressed crops and improve the visibility of cropmarks following data enhancement [10].

**Figure 2.** Rectified oblique aerial photographs at Dabas—Öreg Országúti-d ˝ul˝o (Pest County, Hungary, cf. Figure 1). Aerial photo polygons are generally related to the parcel-system. The "normal"/late harvest cropmarks are marked in different colors. Source: Zoltán Czajlik, 12 June 2015 and GE-imagery.

Nowadays, archaeological aerial photography has become part of airborne and spaceborne remote sensing (ASRS), in addition to those mentioned above, as well as the multiand hyperspectral applications [11]. The programmed use of the latest UAV platform—as with non-traditional ASRS—makes (semi) automatic photography also possible. Thus, traditional aerial archaeology remains one of the last remote sensing techniques requiring an observer, so its overhaul is certainly justified [12,13]. However, this does not lead to the undervaluing or discarding of the experience and benefits that come from the observer being not only part of the learning process, but also being constantly present during data collection and influencing its quality and efficiency through decisions; all this represents a resource to be exploited. This is especially true in the case of such a complex phenomenon as cropmarks, which are to this day still understood on the basis, more or less, of empirical knowledge [14].

#### *1.2. Factors Affecting the Formation of Cropmarks*

As summarized above, the experiences of pioneers in this field show that what character and what quality of cropmarks become visible depends on when a photo is taken. Some of these factors are connected to agricultural activity: in which way the soil is cultivated, and above all, what species are grown, and in what proportion [15]. The significance of barley (*Hordeum vulgare*), wheat (*Triticum aestivum*), winter rape (*Brassica napus*) and alfalfa (*Medicago sativa*) in this area of research is well-documented. To varying degrees, maize (*Zea mays* L.), pea (*Pisum sativum* L.) and sun-flower (*Helianthus annuus* L.) may also reveal archaeological features [16]. On the basis of the personal experience of the authors of the present paper, triticale (Triticale) and poppy (*Papaver somniferum* L.) also have important regional roles [17]. The explanation for these observations is mainly related to

the sowing distance, structure (e.g., normal root length) and drought tolerance/resistance to high amounts of precipitation of the plants [18,19].

One of the most difficult natural factors to calculate is the weather, and the personal experience of both the aerial photographer-archaeologist and the pilot still plays an important role in dealing with this. As a general rule, droughts caused by dry weather can dramatically increase the number of detectable cropmarks, which is what happened in England in 1976. Too much rainfall, on the other hand, yields few cropmarks, while a lot of rain in early summer can ruin even what had earlier been regarded as promising cropmark development—this is what happened in Hungary in 2019, for example.

Taking all the above into account, the investigation of the correlation between infiltration/evaporation data and cropmarks requires the detailed analysis not only of data sets for late spring/early summer but also of long-term sets [20–23]. Furthermore, it should be noted here that while the analysis of precipitation-related factors is important, it is not in itself sufficient; temperature and even, in some cases wind, may also be of significance [24].

Among the geological factors, the role of gravel-rich subsurface layers or gravel covers and fluvial-dominated fan surfaces is of extraordinary importance [25,26]. On the basis of data from Bavaria, it would appear that even in moderately rainy years, good results can be achieved by researching these areas [5]. In Central Bohemia, in the Elbe Basin, 75% of the cropmarks identified between 1993 and 2009 are in gravel/sandy areas, and a further 22% in territories underlain by loess bedrock [16]. Such areas can be successfully investigated in Hungary as well, though in this case, the difference in favor of gravel/sand areas is not as remarkable [17,23].

While soil conditions are, naturally, not independent of the underlying geology, alluvial areas may, nonetheless, present a very diverse picture, making it difficult to recognize correlations with soil types. The effects of sub-soil archaeological features on the growth of crops and the related question of within-plot variability in soil properties has been studied in Central European agricultural landscapes by Czech researchers. Hejcman et al. (2013) [27] were able to demonstrate that variations in soil pH and nutrient availability were attributable to prehistoric settlement activities. They recorded substantially higher contents of organic matter, higher pH, and concentrations of plant-available P, Ca, Mg, Cu, and Zn in the sub-soil layer in cropmarks identified on spring barley as compared to their surroundings. In the arable layer, pH and concentrations of P, Ca and Mg were generally higher. Cropmarks were characterized by barley plants that grew to twice the height of those in the control group, and with significantly higher Ca, Mg and P concentrations. In Bohemia, the cropmarks were most visible on sandy soils, as the soil texture, water holding capacity, and nutrient availability between filled-in archaeological features and the surrounding sub-soil layers showed the greatest contrast. The soil properties differ significantly in areas with clayey soils, which may explain the almost complete absence of cropmarks in these zones [16,28,29]. According to Gojda and Hejcman, positive cropmarks may appear particularly noticeable above graves due to the phosphorus from the bodies [19]. On the basis of the experiences of the current authors, it should be noted that the identification of graves through cropmarks is more sensitive to weather/precipitation than is the case with other archaeological phenomena.

#### *1.3. Geographical Background*

The interior of the Carpathian Basin is dominated by lowlands derived from alluvial fans. The watercourses reaching the basin from the mountainous surroundings formed their vast alluvial fans with lengths of 10 km to 100 km, stretching out towards the deep-lying part of the giant basin during the Pleistocene [30]. The alluvial fans—representing a total area of more than 50,000 km2—are separated by low mountains and gentle hills. Elsewhere, however, interlinked alluvial fans underwent significantly different Late Pleistocene and Holocene development histories; in these cases, due to both tectonic and climatic processes, the watercourses gradually "slid down" (migrated) from the alluvial fans with gravel bases and silty and sandy sediment dominated upper layers [31].

On some of the alluvial fans—e.g., on the remnants of an alluvial fan flanked by a terraced valley edge—the movements of wind-blown sand and loess formation became dominant. The sand-formed topography is dominated by large blowout-residual ridgehummock form assemblages that are extensive and adapt to the runoff direction(s) of the former alluvial fan surface.

In other cases, the tectonic fragmentation of former alluvial fans with thick loess and sand cover formed a tectonically controlled valley network. Their streams sharply divided the alluvial fan bodies: alluvial valleys were formed, with steep marginal slopes, above which extended flat plateaus with a geological past as alluvial fans but subsequently were covered with loess and/or sand.

At the edges of the alluvial fans, the rivers that migrated there formed wide floodplains. After their strong alluvial fan erosion activity, during the accumulation phase-which is also characteristic of the Holocene—they partially covered the marginal areas with their sediments, or they could even cover the entire surface of the smaller alluvial fan.

#### *1.4. Soil Mapping*

The upper, weathered, solid mantle of the Earth, the pedosphere, results from the complex interplay of several soil forming factors and soil forming processes in the zone of interaction between the lithosphere, atmosphere, hydrosphere and biosphere. Soil is a multifunctional natural resource [32], one of its main functions is the conservation of natural and human heritages.

The goal of soil mapping is to reveal and visualize the spatial relationships of thematic knowledge concerning the soil mantle. Soil maps are thematic maps, whereby a theme is determined through specific information related to the soils [33]. These can be primary or secondary (derived), quantitative, or qualitative properties. There are two basic and apparently contradictory but in fact complementary concepts employed in the characterization of spatial variability in soils [34]. One approach essentially builds on similarity, and represents the soil mantle via the mapping of units of homogeneous composition. Its cartographic realization is classic soil maps, of which there is an extensive tradition [34]. The other approach emphasizes the continuous spatial variation of soil properties, and the mapped soil property is predicted using cells and the spatial resolution is determined by the cell size.

In Hungary, large amounts of soil information have been collected through soil surveys, observation and mapping. The goals and methodology of successive soil mapping projects differed, and as a consequence, very often it was dissimilar soil features that were highlighted. The maps were compiled at various scales, from farm to national level. Smaller scale, synthesized maps provide national coverage, while larger scale ones cover only parts of the country [35].

Recently, predictive soil maps in the form of digital soil maps have come to be considered the most effective representation of specific features of the soil mantle [36]. The evolution of digital soil mapping is closely related to the rising availability of spatially exhaustive, relatively low-cost data available in the form of satellite imagery covering wide time scales and spectra, and also digital elevation models originating from remote sensing, both of which provide efficient representations of various soil forming factors and processes [37]. In Hungary, the very recently elaborated DOSoReMI.hu is a collection of spatial soil information in the form of unique digital soil map products compiled to optimize the identification of specific soil features at the regional scale [38]. A significant part of these had never been mapped before, even nationally, at a high (~1 ha) spatial resolution. The new digital soil maps are compiled from specific spatial predictions based on (i) measured soil observation data, (ii) spatially exhaustive, environmental auxiliary variables, and (iii) sophisticated geostatistical and data mining methods for inferring the spatial and temporal variations of soil features. The inherent vagueness of spatial prediction is explicitly expressed through a proper accuracy assessment, and the newly produced

digital soil information and maps are therefore supplied with an estimation of the degree of both local and global uncertainty or reliability.

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

Studying cropmarks requires a special mixture of knowledge, as besides the technical factors, its efficiency depends on experience of the local setting, archaeological and geomorphological knowledge, and on environmental factors which are permanently changing with respect to one another. Among these dynamic factors, the role of precipitation is decisive, and the weather during the early summer time window can influence the results for better or for worse to a great extent. In the light of this, it is clear why methods may vary greatly in heritage management, but the greater the researcher's experience and the longer the research timescale, the greater the progress which can be made in reducing the impact of seasonal differences.

The primary spatial unit of the traditional archaeological approach is the archeological site. Official geoinformatics-based records rely on the sites being some kind of polygon clearly delimited in an area using field survey data. In the case of aerial archaeological sites, the greater part of the data concerns the archaeological features. This allows a much more detailed interpretation than the information from a field survey. Thanks to the detailed interpretation of aerial photos, defining the archaeological site boundaries is not necessary [39]. However, in aerial archaeology research, sites can be defined as territorial units reshaped by the imposition of modern borders, divisions, and changes in designation and use. Nevertheless, the density of aerial archaeological sites are usually marked on integrated maps with the help of simple coordinates/GPS tracks determined during flights or later in laboratory, meaning that there is no spatial data showing their true extent in most databases [8,17,40–42]. One important exception is the system operated by the University of Vienna for years, as they use both coordinates and polygons [26,29]. The method—in some aspects similar to the Austrian one—employed by the current authors is, with a few exceptions, adapted to the growth of cultivated field crops. In the presentation it is not aerial photograph coordinates which are used, but polygons. Aerial photo polygons do not show the boundaries of archaeological sites, but the plots planted with the same species, and any archaeological phenomena thus revealed. So, these are units which, thanks to the presence of homogenous conditions, theoretically all the important archeological phenomena should be visible.

Herein, the term cropmark plot (CMP) will be used for the areas covered by each polygon. In the absence of CMPs, the extent of all archaeological aerial photo sites should be determined in order to obtain comparable spatial data. Meanwhile, there may be often several, in some cases even 8–10 aerially identifiable archaeological sites within the area of a CMP (Figure 2).

The opposite is, of course, also true. Maps of various archaeological sites can be put together, just like pieces of a puzzle, based on aerial archaeological prospection conducted on different dates. In other words, the number of puzzle pieces—and the average size of the CMPs—depends on the pattern of land use. To meet these conditions, the CMPs are formed on the basis of the polygons determined by the parcel boundaries at the time when the photo is taken. As a result of further photography, CMPs can be merged or resized if the documented area expands.

The aim of the current research was to compare the pedological features of cropmark plots (CMP) and non-cropmark plots (nCMP) in order to identify demonstrable differences between them. For this purpose, the spatial soil information on primary soil properties provided by DOSoReMI.hu was employed. To compensate for the inherent vagueness of spatial predictions, together with the fact that the definition of CMPs and nCMPs adopted here is somewhat indefinite, the comparisons were carried out using data-driven, statistical approaches.

#### *2.1. Study Areas*

To examine the utility of this method, areas subject to increased systematic research from 1993 onwards were selected, and 2017 was the last year processed. This does not, however, mean that the regular aerial archaeological prospecting of the areas has ceased. The sample areas also represent examples of all three characteristic alluvial fan evolution types (1, 2, 3). These distinct environment types also demonstrate different patterns in terms of cropmark appearance (Figure 3).

**Figure 3.** Location of the study areas. Cropmark plots (CMPs) are displayed in yellow.

1. The alluvial fan of the Danube-Tisza interfluve (Study area 1)

This is a remnant of a huge alluvial fan of the paleo-Danube aligned in a NW-SE direction, and from which the river—for tectonic reasons—migrated to the West. In this new location, the Danube has created a wide floodplain extending 30–50 m below the top of the former alluvial fan. On the surface of the inactive alluvial fan there is a gravelrich alluvial plain in the North but going southwards it is dominated by loess and sandy sediments, and due to aeolian processes (which were extremely significant in the Holocene as well), by sand ridges, hollows and dunes. A near-surface gravel presence occurs at the neck of the alluvial fan and on the terraces of the Danube as it cuts into its western margin.

#### 2 Sió-Sárvíz valley (Study area 2)

The Carpathian Basin has been divided by fluvial activity (the paleo-Danube) and controlled by tectonic processes. This loess and sand region is markedly separated from the wide floodplain of the Danube due to its Pleistocene migration and even from the sandy surface of the wide alluvial fan of the Danube-Tisza interfluve. In the Sió-Sárvíz valley, which deepens into a tectonically divided terrain, significant valley widening and slope erosion took place. The area's classification as a lowland can be explained by the flat surface of the extensive loess and sandy plateaus that dominate the region.

3 Rába interfluve (Study area 3)

The alluvial fans of the section of the paleo-Danube entering the Carpathian Basin and of the watercourses (e.g., Rába) coming from the eastern edge of the Alps developed into one of the sub-basins of the Carpathian Basin-in the direction of the Gy˝or Basin. The graveldominated alluvial fans were built on top of each other in this lowland depression. Their floodplain sedimentary cover also significantly thickened during the Holocene, covering the alluvial fan-derived basement.

All the three study areas were preprocessed for the analysis in four steps:

#### *2.2. Spatial Soil Information*

Traditionally, the spatial knowledge of soils is summarized chiefly in the form of soil type maps based on an appropriate classification system [44]. Generally, these maps are simply called soil maps, which in fact reflects their importance. Historically, soil mapping was done based on soil typology, and soil types have strong didactic significance. Soil type maps have also been created on different levels and according to different classification systems. In present study, the cartographically prepared (raster-vector transformed and generalized) version of the newly compiled nationwide soil type map (with harmonized legend and spatially consistent predictivity [45], was used for the identification of the location of CMPs along main soil types.

In the quantitative investigations, optimized primary soil property maps with 1 ha spatial resolution were tested for their ability to reveal differences between CMPs and nCMPs. As with soil type, rooting depth refers to the whole soil profile (pedon), while particle size fractions (clay, sand and silt content), bulk density (BD), soil organic matter content (SOM), CaCO3 content (CC), and pH are mapped for subsequent soil layers according to various partitions (Table 1). Each target variable was modelled using a sequence of spatial inference approaches (altering either methods or the reference and predictor data), which were always accompanied by a detailed accuracy assessment for the determination of the best performing set of soil data, method and auxiliary covariables for the given target variable [38]. The map products are published on the www.dosoremi.hu website and are serviced in two different ways. The maps elaborated according to GSM specifications represent the Hungarian contribution to the GlobalSoilMap.net project.

**Table 1.** Summary of the primary soil property maps used for the comparison of the pedological features of CMPs and nCMPs.

#### *2.3. Statistical Methods*

To identify their pedological differences, the two types of area underwent (i) testing using a traditional, non-parametric statistical test, namely the Kolmogorov–Smirnov (KS) homogeneity test and (ii) modelling using a recently "popularized" data mining method, namely Random Forest (RF). Despite their inherent differences, both methods are appropriate for revealing the hypothesized differences in the two types of areas on the basis of the available data.

#### 2.3.1. Kolmogorov–Smirnov Homogeneity Test

The two-sample Kolmogorov–Smirnov (KS) homogeneity test is used to test whether two samples come from the same distribution by comparing the cumulative distributions of the two data sets. A great advantage of this non-parametric test is that it does not assume that data are sampled from normal distributions. The null hypothesis is that both groups were sampled from populations with identical distributions. The KS test reports the maximum difference (D) between the two cumulative distributions and calculates a *p* value from that and the sample sizes. The *p* value shows what the chances are that the value of the Kolmogorov–Smirnov D statistic is as large, or larger than observed. If the *p* value is small, the two groups are sampled from populations with different distributions.

The distribution of raster values for the two sample populations was compared by KS for each soil property independently for the three pilot areas. The two distributions were considered statistically different at a 95% confidence level, then the soil properties with *P* < 0.05 were ranked according to their D values. The higher the D value, the greater degree to which CMPs and nCMPs differ in their tested soil property.

#### 2.3.2. Random Forests

Random Forests (RF) are an ensemble data mining method for classification and/or regression. The RF algorithm depending on its settings and on the type of the dependent variable, generates a number of regression or classification trees. The model relies on averaging the result of the trees, which are grown independently of each other [46]. In the course of RF modelling, the number of trees was set at 500, the number of variables available for splitting at each tree node (mtry) was set at 7 (501/2). RF models provide a variable rank, reflecting which co-variables play a more important role in the prediction model. According Hengl et al. (2017) [47], the main advantages of random forest over linear regression are: (i) it has no requirements in terms of the probability distribution of the target variable; (ii) it can fit complex non-liner relationships in k+1-dimensional space (where k is the number of environmental covariates); and (iii) the correlation between the environmental covariates is not a limiting factor.

In the present study, the prediction of CMPs and nCMPs was tested using RF modelling. The test dataset was set up by using all raster values for each study areas, and a binary classification was carried out for the identification of CMPs and nCMPs. The variable degrees of importance provided by RF were used for the ranking of soil properties in the discrimination. RF was carried out once on genetic soil type and once only with merely quantitative predictors.

#### **3. Results**

Differences in geological/geomorphological background alone do not explain all anomalies. It was presumed that the recent state of soil formation, expressed by genetic soil type, water absorption and water holding as well as nutrition supply capacity, would play an essential role, too.

#### *3.1. Distribution of CMPs along Main Genetic Soil Types*

As witnessed in the study areas, Chernozem and Meadow type soils are remarkably helpful in the formation of cropmarks, while the suitability of sandy soils is limited.

The eastern part of study area 1 (Figure 4, first panel) is dominated by an alluvial fan covered with sandy soils, and the amount of the detected CMPs decreases. Furthermore, in the case of the area derived from the fan, the CMPs were not recognizable on salt-affected soils. Only rarely do a few cropmarks show up on alluvial soils close to the riverbanks.

**Figure 4.** *Cont.*

**Figure 4.** (**panel 1–3**). Distribution of CMPs on the soil type map for the study areas.

Study area 2 (Figure 4, second panel) is the most geomorphologically determined area of the three study areas. The cropmarks fit in the typical soil types of valley floors, and in the vast majority of cases, the CMPs occur on Chernozem soils. As with previous study areas, only a few CMPs could be detected on sandy soils. Study area 3 (Figure 4, third panel) is the most heterogeneous area in relation to the distribution of soil types. The majority of CMPs occur on Meadow and Chernozem type soils. It is suggested that the detection of CMPs depends mainly on the weather and seasons.

#### *3.2. Differences between Pedological Characteristics of CMPs and nCMPs as Revealed by the Kolmogorov–Smirnov Test*

In the light of the two-sample Kolmogorov–Smirnov homogeneity tests, the three pilot areas display significant differences. The ranked soil properties are listed in Table S1. For each study area, the histogram of the raster cell values for the two data sets (CMPs and nCMPS) in the case of the most discriminating soil properties are displayed in Figure 5.

In the Rába interfluve study area, CMPs and nCMPs mostly differ in the carbonate content of the upper layers. Particle size fractions (clay, sand and silt content) in subsoil (under 1m) and near-surface soil organic carbon also seem to be strong discriminating factors. As can be seen in Figure 5, the carbonate content of the 15–30 cm layer is shifted towards higher values in CMPs, with the distribution reaching a maximum in the 6- 8% range; however, a second, local maximum is similarly situated for both data sets at about 13%.

In the Sió-Sárvíz study area CMPs and nCMPs differ mostly in the particle size fractions (clay, sand and silt content) of all layers; carbonate and soil organic matter content lag behind and seem to be rather weak discriminating factors. Despite the significant test result, the histograms in Figure 5 do not seem to differ to any great extent, except for the fact that for CMPs the maximum close range sand content of the 5–15 cm layer is wider, and at over 40% is still almost as high as at 30%.

**Figure 5.** The histograms of the raster cell values for the two data sets (CMPs and nCMPS) in the case of the most discriminating soil properties for the three study areas.

In the Danube-Tisza interfluve study area, CMPs and nCMPs also differ to a large extent in particle size fractions (clay, sand and silt content). However, deeper layers occur later in the ranking; carbonate and soil organic matter content even lag behind and seem to be rather loose discriminating factors. The two histograms in Figure 5 for the silt content of the 0–60 cm layer look rather different, while for CMPs the maximum is located at the lowest values and the overall distribution shows only slight fluctuations. For nCMPs the maximum is close to 30% and only one mode is visible.

It is an interesting fact that for all the three study areas rooting depth showed very weak discriminating power, while pH and bulk density did not provide any statistically valid test results despite their presupposed higher significance.

For all three study areas, the use of RF with genetic soil type as qualitative predictor provided the same results in relation to the importance of soil type, ranking it in the hindmost position. As a consequence, the result and discussion of the models excluding soil type alone form the focus of the discussion. Variable ranks are listed in Table S2. They are also displayed graphically for each study area in Figure S1 [48].

In the Rába interfluve study area the most important soil properties in the prediction of CMPs and nCMPs are the soil organic matter content of the deeper layers, rooting depth, pH of the subsoil (under 1 m) and bulk density of the topsoil (0–30 cm).

In the Sió-Sárvíz valley study area, the most important soil properties in the prediction of CMPs and nCMPs are rooting depth, soil organic matter content of the deeper layers, pH of the subsoil (under 1 m), bulk density of the topsoil (0–30 cm).

In the Danube-Tisza interfluve study area the most important soil properties in the prediction of CMPs and nCMPs are bulk density of the topsoil (0–30 cm), soil organic matter content of the topmost layers (0–5 and 5–15 cm), rooting depth, pH of the subsoil (under 1m), the soil organic matter content of the deeper layers.

It is an interesting point that particle size fractions (clay, sand and silt content) lag behind in all three study areas, while in KS they were top ranked, and the least discriminating properties provide by KS became the determining factors in the RF based prediction of CMPs (Figure 6).

**Figure 6.** Importance of soil property covariates for predicting the indicators of CMPs and nCMPs. Abbreviations: BD: bulk density, SOM: soil organic matter content.

#### **4. Discussion**

Although in the selection of the study areas, the aim was to match as many criteria as possible, it should be noted that it is not yet possible to guarantee the same level of analysis of the areas, and they thus cannot be compared with a perfect level of consistency in terms of cropmark formation conditions. This is primarily due to the weather factor, which shows considerable variations every year for the three study areas. While in the area of the Danube-Tisza interfluve cropmarks can be detected every year, there are years when their discovery is not possible in the Rába interfluve. The Sió/Sárvíz valley falls somewhere in between these two, as there are no completely unsuccessful years, but truly good ones are rare as well. A further weather-related observation is that the periods ideal for identifying cropmarks—the cropmark time-windows—are not of the same length in the case of each study area. In the Danube-Tisza interfluve study area, there may be a relatively long period of up to two months, whereas this period is noticeably shorter in the Sió / Sárvíz valley, and only 1–2 weeks long in the Rába interfluve. A further complicating factor in the case of the Sió / Sárvíz valley is that the maize/sunflower/rape trio plays a noticeably greater role in field crop production than in the other areas. This means that barley/wheat are grown less frequently in crop rotation than in the other two study areas. Finally, it should be noted that the research of the Danube-Tisza interfluve is much cheaper due to its proximity to the bases of the researchers. Thus, even in the years of scarce funding, flights were guaranteed, while good years—like 2012—may have been missed in the other two areas (Table 2).

Also due to these differences, the proportion of areas covered by CMP is significantly higher in the Danube-Tisza interfluve than in the other two study areas. It is possible that further flights will reduce the differences in representativeness between the study areas, eventually making the results of the statistical analyses more coherent regardless of the study areas.

Although all three sample areas have alluvial fan origins, their sediment accumulation and surface evolution show distinct features. Their geologic and geomorphologic diversity makes it difficult to specify factors that influence the cropmark appearance clearly. Because of the different appearance of geomorphological/sedimentological fragmentation, determining soil-parameters can still be used to boost the effectiveness of identifying cropmarks.

Regarding the occurrence of CMP-nCMP, the topsoil bulk density and the grain-size composition can be definitive on areas of fluvially determined low angle fans with a complex recent geomorphologic history. On these surfaces diverse landforms are built up from sediments differing greatly in their water-balance, resulting in a mosaic of sand regions, wet meadows, terrace surfaces and floodplains (e.g., the Danube-Tisza interfluve). As sand movement and fluvial land-forming have been active processes during the Holocene, [49] both the subsurface sediments and the topsoil display great spatial variability.

The situation/picture/ is different in areas where during the Late Quaternary surface evolution was governed by shallow valleys cutting into alluvial fans (e.g., the Sió-Sárvíz valley): in the dual fluviatile system of floodplains and flood-free relief areas, the topsoil bulk density is also an important factor. But the dominant component yielding sediment and forming surfaces is sediment accumulation related to the recent flooding of active streams. This therefore results in significantly higher organic material and carbonate content as CMP-nCMP markers.

Regarding the CMP-nCMP analyses, the most problematic areas are completely flat plains with origins as alluvial fan. Considering sedimentation and buried paleo-landforms together, the area must be considered fragmented. These terrains covered in thick, alluvial sediments partially Holocene in origin are characterized by invariable reliefs [50]. The majority of paleochannels are completely buried by now (e.g., in the Rába interfluve). As today's surface does not reflect the earlier, rougher terrain, and because of its covering alluvial sediment, higher organic material and carbonate content seem to be even more dominant factors in defining CMP and nCMP areas.

Pedological differences between CMPs and nCMPs can be detected by all the three approaches. The statistically identified differences, however, differ to a fair degree between the various approaches. Differences in the distribution of specific soil property values for CMPs and nCMPs (as opposed to the variable importance provided by RF for the prediction of the two types of areas) result in significantly different rankings of soil properties. This might be caused by the problem of representative sampling in the study areas.

In contrast to results for the Czech Republic [16,19], those presented here do not show the dominance of sandy soils in cropmarks.

The role of soil chemical properties in cropmarks revealed by Hejcman et al. (2013) [27] are, however, supported by the result in the present study that organic matter and carbonate as well as pH are important variables in RF models. However, nutrients available to plants have not been mapped in the frame of DOSoReMI.hu due to their dynamic nature and the lack of available observational data. Thus, their role in cropmarks is not considered in the present work. Nevertheless, the approach employed can reveal the more static pedological background where the spatial differences in nutrient status due to archeological sources may result in stronger effects on crop development, thus making plots more suitable for cropmarks.

#### **5. Conclusions**

The analyses of the factors behind the formation of cropmarks gave rather complex results, despite the fact that only the fixed elements of the system were examined. The importance of alluvial fans has also been prospected in Southern Germany, Switzerland, Austria, and the Czech Republic. However, the differences in cropmark between alluvial fan sub-types have been explained by analyzing Hungarian soil data. At the same time, this method could prove useful in the future for the analysis of areas with significantly

different geomorphological conditions—bearing in mind the important role of loess areas in the Czech Republic.

Based on the detailed statistical analysis of both the aerial archaeological and pedological data, different factors seem to be relevant to each study area. However, these differences can be sufficiently explained by the slightly different formation and landscape evolution processes of study areas with similar bedrock. While cropmarks correlate well with the results of traditional soil mapping, much more complex processes underlie the formation of cropmarks. This is probably due to the fact that in previous analyses, the role of some important factors (e.g., sandy soils) seems to have been more subordinate.

Since the 1990s, Hungary has been considered highly suitable for the prospection of cropmarks, thanks chiefly to the presence of large field monoculture grain corn production and also to early summer weather suitable for aerial archaeological research. Among a number of other factors, the favorable conditions can certainly be linked to a high-quality soil mantle. It is worth noting that by increasing the representativeness of archaeological prospecting, an even more accurate picture may hopefully be created in the future. One important objective of the methodological developments presented here is the creation of a predictive model in order to start mapping cropmarks during flights over micro-regions not previously researched, but in which the geomorphological / soil conditions seem to be favorable.

We also plan to explore the roles of changeable factors. The above described features' influence on cropmarks might be enhanced, decreased, or—in years of extreme weather completely altered by weather conditions, especially by the amount of precipitation.

The use of cropmarks in aerial archaeology helps primarily the identification and the geomorphological analyses of sites, as well as the mapping of archaeological data. However, in order to understand the complex factors of cropmark formation better, new methods were needed. Asked in 2000 how much experience he needed truly to understand the nature and the research opportunities of cropmarks, René Goguey's answer was: "After 30 years work, I've started to realize". Now, 20 years later, progress seems possible on the basis of an approach which makes cropmark data suitable for statistical processing, together with analyses related to soil data systems based on remote sensing data sources and interpreted from a geomorphological point of view. It is the hope of the authors that the methodological experiments detailed here may make the technology of aerial archaeological prospecting, which has been somewhat sidelined in the last 10 years, more predictable, plannable and thereby more effective.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/2072-4 292/13/6/1126/s1, Table S1: Rank of primary soil property maps used for the comparison of the pedological features of CMPs and nCMPs in the case of the three study areas. The higher the D value, the greater the degree to which CMPs and nCMPs differed in their tested soil properties. Table S2: Variable importance rank of primary soil properties used in Random Forest modelling of CMPs and nCMPs in the case of the three study areas. The higher the importance value, the more informative is the given soil property in the discrimination of CMPs and nCMPs. Figure S1: Variable importance rank of primary soil properties used in Random Forest modelling of CMPs and nCMPs in the case of the three test sites.

**Author Contributions:** Conceptualization, Z.C. and L.P.; methodology, Z.C., B.N. and L.P.; software, M.Á. and J.M.; validation, Z.C., B.N. and L.P.; formal analysis, Z.C.; investigation, Z.C. and L.P.; resources, Z.C. and L.P.; data curation, M.Á., J.M. and L.R.; writing—original draft preparation, Z.C. B.N. and L.P.; writing—review and editing, Z.C., B.N. and L.P.; visualization, M.Á., J.M. and L.R.; supervision, Z.C. and L.P.; project administration, Z.C.; funding acquisition, Z.C. and L.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by National Research Development and Innovation Office (Hungary), grant numbers NN-111058, K-131820 and SNN 134635, by the Higher Educational Institutional Excellence Program / the Thematic Excellence Program of the Eötvös Loránd University, and Momentum Mobility research project (Institute of Archaeology, Research Centre for the Humanities), granted by the Momentum Program of the Hungarian Academy of Sciences.

**Data Availability Statement:** The digital soil maps used in the present study were compiled in the "Digital Optimized Soil Related Maps and Information" framework and are published on the www.dosoremi.hu website. The maps were elaborated according to GSM specifications, thus they also represent the Hungarian contribution to the GlobalSoilMap.net project. The CMPs are sensitive data containing archaeological site information indirectly.

**Acknowledgments:** The authors thank Á. Marton for his indispensable contribution. We are grateful to the editors and the six anonymous reviewers who provided valuable suggestions regarding the manuscript.

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

#### **References**

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Tel: +41 61 683 77 34 Fax: +41 61 302 89 18


**4. Research**

This research uses learning tools with collaborative opportunities with the main campus of Texas A&M in Second Life using private cloud to improve student success in engineering calculus.

It will bridge the gap in knowledge, using interactive games and social networking in the context of success in mathematics conceptual knowledge and skills necessary to be successful in Engineering, and Mathematics.

The purpose is to investigate different online e-technology methods used in Mathematics classes at Texas A&M University at Qatar to accelerate learning and detecting the best practice in using them in education. Five different software applications and class management systems used in Calculus I and Calculus II for Engineers which are: Turning Point System for students' attendance, 3D online system (Second life) for conducting help

interactive games have had positive effects on interest and motivation in mathematics (Su, Marinas, & Furner, 2010; Ahmad, Shafie, Latif, 2010; Kebritchi, Hirumi, & Bai, 2010; Jones,

3. provides opportunities for collaborative work (Jones, 2009; Bourke, 2009; Cheong, 2010; Lucia, Rancese, Passero, & Tortora, 2009). Second Life information is generally freely available to all residents (Jones, 2009), although the client uploading content for a virtual classroom pays a fee for upload access. Second Life has the capability to support not only asynchronous distance learning products but can also support synchronous lectures and increase interaction and communication opportunities between teachers

After conducting interviews at a variety of public and private co-ed schools, all-girls schools and all boys schools it was noticed that "the real variables affecting a girl's performance seems to have more to do with class size, and the expectations of society and the family. The size of the group, affects their ability to speak out and to feel comfortable in expressing themselves. Adding to that the problems of discipline that may arise in the class and it's easy to understand why quieter students, or those who lack confidence, might be

Moreover more studies in the literature cited that the popular belief that girls will do better academically at single-sex schools is not sustained by the data. School type does not appear to be an important factor in attempts to improve the performance levels of girls in mathematics and science however the Mathematics anxiety and lack confidence does. Finally, it is already established in the literature the need of graduates to have skills working with the digital communications tools as well as having long life learning skills in the real and the virtual environment. Moreover, accreditation criteria include the problem solving and team shearing particularly in Engineering is required by utilizing a variety of technologies.

This research uses learning tools with collaborative opportunities with the main campus of Texas A&M in Second Life using private cloud to improve student success in engineering

It will bridge the gap in knowledge, using interactive games and social networking in the context of success in mathematics conceptual knowledge and skills necessary to be

The purpose is to investigate different online e-technology methods used in Mathematics classes at Texas A&M University at Qatar to accelerate learning and detecting the best practice in using them in education. Five different software applications and class management systems used in Calculus I and Calculus II for Engineers which are: Turning Point System for students' attendance, 3D online system (Second life) for conducting help

2009).

intimidated.

**4. Research**

calculus.

**3.2 Second Life environment**

Second Life is an online 3D virtual environment that

**3.3 Cultural difference in coeducational school**

successful in Engineering, and Mathematics.

1. allows participants to engage directly and interactively, 2. provides an opportunity for rich social networking, and

and students [Lucia, Rancese, Passero, & Tortora, 2009).

sessions and student meetings, WebCT for posting class notes, grads and notices, WebAssign for online quizzes and practice, and Pod casting for posting solved homework problems and using iTunesU.

The general idea is to produce an intelligent program, called agent, through a process of learning using Reinforcement Learning (RL) which is a Machine Learning technique that has become very popular in recent days. The technique has been applied to a variety of artificial domains, such as game playing, as well as real-world problems. In principle, a Reinforcement Learning agent learns from its experience by interacting with the environment. The agent is not told how to behave and is allowed to explore the environment freely. However once it has taken its actions, the agent is rewarded if its actions were good and punished if they were bad. This system of rewards and punishments teaches the agent which actions to take in the future, and guides it towards a better outcome. The basic idea is the visual perception of the ability to be familiar with the environment visually.

Data mining tools used to predict future trends (Neel, 2011). It predicts the future and the hidden information in the database. Data mining tools can answer questions that traditionally were very time consuming to resolve and experts may miss because it lies outside their expectations. The most commonly techniques used in data mining are artificial neural networks, decision trees, and clustering which used in this research.


**A Multi-Domain Spectral Collocation Approach for Solving Lane-Emden Type Equations**

Motsa Sandile Sydney, Magagula Vusi Mpendulo, Goqo Sicelo Praisegod, Oyelakin Ibukun Sarah and Sibanda Precious

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/63016

#### **Abstract**

[29] K. Diethelm, The analysis of fractional differential equations, Springer, Berlin, Germa‐

[30] K. Diethelm, N. J. Ford, A. D. Freed, A predictor-corrector approach for the numerical solution of fractional differential equations, Non-Linear Dynamics, 29, 3–22, 2002. [31] K. Diethelm, N. J. Ford, A. D. Freed, Detailed error analysis for a fractional Adams

[32] S. Ma, Y. Xu, W. Yue, Numerical solutions of a variable order fractional financial

[33] K. Diethelm, N. J. Ford, A. D. Freed, Yu. Luchko, Algorithms for the fractional calculus: a selection of numerical methods, Comput. Methods Appl. Mech. Energy, 194, 743–773,

[34] R. Boonstra, C. J. Krebs, N. C. Stenseth, Population cycles in small mammals: the

[35] A. J. Sami, A. R. Shakoor, Cellulase activity inhibition and growth retardation of associated bacterial strains of Aulacophora foviecollis by two glycosylated flavonoids

[36] M. Okamoto, K. Hayashi, Frequency conversion mechanism in enzymatic feedback

[38] G. Chen, T. Ueta, Yet another chaotic attractor, Int. J. Bifurc. Chaos, 9, 7, 1465–1466,

[39] G. Chen, Comments on "Chen's attractor exists if Lorenz repulse exists: The Chen

[40] C. Li, G. Peng, Chaos in Chen's system with a fractional order, Chaos, Solitons and

[41] S. Bhalekar, V. Daftardar-Gejji, P. Gade, Dynamics of fractional ordered Chen system

system is a special case of the Lorenz system", CHAOS, 23, 033108, 2013.

isolated from Magnifier indicia leaves, J. Med. Plants Res., 5, 2, 184–190, 2011.

[37] N. E. Lorenz, Deterministic non-periodic flow, J. Atmos. Sci., 20, 1, 130–141, 1963.

problem of explaining the low phase, Ecology, 79, 1479–1488, 1998.

ny, 2010.

2005.

1999.

Fractals, 22, 443–50, 2004.

method, Numer. Algor., 36, 1, 31–52, 2004.

142 Numerical Simulation - From Brain Imaging to Turbulent Flows

systems, J. Theoret. Biol., 108, 4, 529–537, 1984.

with delay, PRAMANA-J. Phys., 79, 1, 61–69, 2012.

system, J. Appl. Math., 2012, 14, 2012 (Article ID 417942).

In this work, we explore the application of a novel multi-domain spectral collocation method for solving general non-linear singular initial value differential equations of the Lane-Emden type. The proposed solution approach is a simple iterative approach that does not employ linearisation of the differential equations. Spectral collocation is used to discretise the iterative scheme to form matrix equations that are solved over a sequence of non-overlapping sub-intervals of the domain. Continuity conditions are used to advance the solution across the non-overlapping sub-intervals. Different Lane-Emden equations that have been reported in the literature have been used for numerical experimentation. The results indicate that the method is very effective in solving Lane-Emden type equations. Computational error analysis is presented to demonstrate the fast convergence and high accuracy of the method of solution.

**Keywords:** Multi-domain, Lame-Emden, Spectral Relaxation method, Collocation, As‐ trophysics


**Author details**

*Oncogenes and Carcinogenesis*

cell cycle adjustments.

to be tumor-prone [9].

**Acknowledgements**

basis of cancer chronotherapy.

**10. Conclusion**

[69, 70]. In this scenario, increasing levels of oxygen-free radicals during the daytime may be a decisive factor in relegating the anabolic processes of mitosis, growth, and consolidation to the dark hours. Thus, it is reasonable that cellular signaling cascade mediated by ROS is utilized in the regulation of the circadian clocks and that common regulatory pathways mediate both cellular responses to photooxidative stress

In addition to the photooxidative stress derived from sunlight, the UV component of it is major source of harm to organisms [51, 52]. In zebrafish, the light induces expression of PHRs which repair UV-damaged DNA in a light-dependent manner (**Figure 2**) [49, 71]. Importantly, this light induction of *DNA Phr* expression appears to be mediated by photooxidative stress [68, 72]. These observations are consistent with the idea that photooxidative stress may be utilized as a signal to activate DNA repair enzymes that can protect the organism's DNA from UV-induced damage. The fact that ROS, a well-known inducer of oxidative stress, can activate *zCry1a* transcription in zebrafish cells [66], together with the finding that *zCry1a* and *DNA Phr* are governed by shared light-induced signaling pathways [49], strongly suggests that, at least in zebrafish, the light entrainment of the circadian clock reflects a long-standing cellular response to photooxidative stress (**Figure 2**). The zCRY1a protein interacts directly with the CLOCK (NPAS2):BMAL complexes and regulates its transcriptional capacity [67, 73]. The complexes regulate a variety of key genes involved in cellular stress responses, DNA repair, and cell cycle regulation [14, 74]. Thus, the circadian clock protein zCRY1a may be the key integrator of oxidative stress that controls the core circadian machinery to regulate the transcription of genes responsible for DDR and

Many studies have identified a link between the circadian clock and tumorigenesis [8, 12]. The core of the circadian clock mechanism is the cell-autonomous and self-sustained transcriptional machinery called the cellular clock. Importantly, the cellular clocks have been reported to regulate transcription of tumor suppressors and cell cycle regulators [6, 12]. In addition, circadian proteins appear to play roles in cell cycle control, acting as tumor suppressors [9]. For example, it has been hypothesized that a core circadian regulator, CLOCK, directly interacts with key checkpoint proteins, leading to the acetylation of these proteins and thereby modulating their activities. In support of this idea, *Clock* mutant mice have been reported

Cancer chronotherapy relies on the asynchrony that exists in cell proliferation and drug sensitivities between normal and malignant cells [8, 12]. The administration of cancer therapy based on circadian timing has had encouraging results, but still lacks a strong mechanistic foundation. Thus, identification of detailed molecular links between the circadian clocks and tumorigenesis will provide the functional

This work was supported in part by the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research [16K08521 and 18KT0068

(J.H.)]. This work was also supported by grant from Komatsu University

and the light-dependent regulation of the circadian clocks (**Figure 2**).

**20**

(J.I. and J.H.).

Yoshimi Okamoto-Uchida1 , Junko Izawa2 and Jun Hirayama2 \*

1 Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan

2 Department of Clinical Engineering, Faculty of Health Sciences, Komatsu University, Ishikawa, Japan

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


**2. Post liver transplantation**

262 Immunodeficiency

levels (47).

important predictor of survival (49).

Institutes of Health multi-center trial guidelines for LT in HIV positive patients with chronic

The Model for End-Stage Liver Disease (MELD) score has been adopted by transplant centers across Europe and North America to ensure the appropriate allocation of organs to those at the highest risk of death (45). Although MELD has been well validated in the HIVnegative patients, there have been mixed reports on its sensitivity in HIV-positive patients with ESLD (46). One prospective study reported similar MELD scores at the initial LT assessment for HIV-positive and HIV negative patients despite those with HIV having a significantly shorter cumulative survival time (880 versus 1427 days, p=0.04) (47). Another observation made by the same study was that the MELD score did not differentiate between survivors and non-survivors (13 versus 15, p = 0.6). Two more recent studies, both prospective, however have suggested that the MELD score may actually be a sensitive predictor of patient outcome (47, 48). Multivariate analysis of predictive factors of mortality demonstrated that the MELD score was independently associated with death (HR per 5-U increase 1.53, p<0.001). The MELD score also remained predictive of death on subgroup analysis of HIV/HCV patients (without HCC) and on comparison with HIV negative historical controls, the mortality rates were significantly higher for HIV-positive patients in each MELD category (48). In the second study, which matched 167 HIV-positive patients with 792 HIV-negative patients the baseline MELD score was the only significant predictor of pre-LT mortality in HIV-positive patients after controlling for CD4+ counts and HIV RNA

Optimal control of HIV disease is an important prerequisite for HIV-positive patients undergoing consideration for LT. In patients with portal hypertension, splenic sequestration of T lymphocytes can lead to a fall in the CD4+ T cell count. In such cases a CD4+ cell count > 100 cells/uL is acceptable. A fall in the CD4+ cell count can also be precipitated by the use of pegylated interferon. In our opinion, CD4+ T cell percentages may represent a more sensitive indicator of immune reconstitution in HIV-positive patients with portal hypertension. HIV-positive patients undergoing evaluation for LT also require an undetectable HIV viral load (< 50 copies/mL) except for those that presently acutely. The inability to achieve an undetectable HIV RNA viral load before LT has been associated with an increased mortality rate (HR 3.5, p<0001)(48). In addition to good therapeutic options available in the pre-transplant period, HIV-positive patients require future cART options based upon their previous regimens and HIV phenol- genotype resistance testing. It is not inconceivable that certain HIV-positive patients may not be able to tolerate cART medications pre-LT due to brittle liver synthetic function. This group should not be automatically excluded from LT as long as HIV control is deemed possible post LT by the multidisciplinary team. cART intolerance post-LT, however has been identified as an

A thorough knowledge of past opportunistic infections is required. A distant history of an opportunistic infection in a patient that was not taking cART is not a contraindication to LT unless there is no effective treatment available for possible recurrence post-LT. Absolute

liver disease are listed in Table 2. UK guidelines have similar requirements.

Standard surgical techniques with conventional arterial, venous and biliary anastomosis are recommended. One concern highlighted is the possible risk of transmission of HIV to the surgical team. The risk of HIV however is low and is substantially lower than the risk of transmission of HBV and HCV (50). In the event of HIV exposure, current regimens provide effective prophylaxis (51). As HIV infection is associated with a pro-thrombotic state, concerns have been raised regarding an increased risk of vascular complications post transplantation (52). Recent data from our Institution demonstrated an increased an increased incidence of hepatic artery thrombosis compared to HIV negative patients (12% vs. 3.2%, p=0.016) (53). Given the increased pro-thrombotic risk, the introduction of prophylactic subcutaneous heparin (5000 units every 8 hours) is recommended once the international normalised ration (INR) is below 1.5 and the platelet count is greater than 50 x 109 cells/L.

Immunosuppression should be tailored to the individual taking into account aetiology of liver disease, renal function, risk factors for the metabolic syndrome and specifically to HIV patients the possible interactions with combined anti-viral therapy (cART) medications. Dual immunosuppression with calcineurin inhibitors (CNIs) and cortico-steroids is recommended post-LT. Target trough levels in the first 3 months should be the same as HIV negative patients (cyclosporin, 100-250 ng/ml; tacrolimus, 8-10ng/ml). Utilising data from HCV mono-infected patients post-LT, rapid withdrawal of cortico-steroids should be avoided due to the association of a more severe recurrence of HCV (54). We therefore recommend that prednisolone, which is usually commenced at 20mg daily, be withdrawn by a slow taper at 3 months. Anti-fungal prophylaxis (fluconazole 50mg daily) should be given for a minimum of 3 months post-LT. Episodes of acute cellular rejection (ACR) should also be managed as one would in HIV negative patients namely moderate-severe episodes be treated with a 3-day course of intravenous methylprednisolone (1g daily). Consideration of the introduction of mycophenalate mofetil (MMF) after the 2nd episode of ACR is recommended.

Both tacrolimus and cyclosporin are metabolised via the P450 cytochrome. In addition, nonnucleoside reverse-transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs), which are commonly part of cART regimens, are also metabolised by the same pathway, therefore increasing the risk of drug – drug interactions. NNRTIs (e.g. efavirenz) decrease serum CNI concentrations by induction of the P450 cytochrome whilst PIs (e.g. ritonavir and lopinavir) are inducers resulting in increased CNI concentrations (55). We have used tacrolimus doses as low as 1mg per week in certain individuals. Raltegravir, a novel HIV-1 integrase inhibitor, is not metabolised via the P450 cytochrome and has been used successfully post transplantation in combination with nucleoside reverse-transcriptase inhibitors and

standard CNI doses (56). Meticulous monitoring and surveillance is required to reduce the possibility drug-drug interactions and toxicity.

The Role of Liver Transplantation in HIV Positive Patients 265

Recurrence of HCV post-LT is universal but an accelerated disease course is well recognised in HIV/HCV co-infected patients (62, 64). HCV recurrence, especially the aggressive severe fibrosing cholestatic variant of recurrent hepatitis C (FCH) and sepsis are the leading causes of death post-LT amongst HIV/HCV co-infected patients (61, 62, 65-68). Although no reliable markers are available to identify patients who will develop FCH, higher HCV viral loads immediately after LT at week 1 and week 2 may be an indicator for those at risk (69). A French study highlighted the rapid fibrosis progression rates in HIV/HCV co-infected patients (2.4 versus 1.4 score, p=0.01) at 24 months post-LT (62). The likelihood of progression to a fibrosis score ≥ 2 was also significantly higher in HIV/HCV co-infected

Re-treatment of HCV recurrence post-LT is associated with an increased side-effect profile and poorer treatment outcomes compared to HCV patient's pre-LT. Pegylated interferon and ribavirin remain the 'standard of care' for a minimum of 48 weeks irrespective of viral genotype. Treatment for recurrent HCV post-LT in our institution is instigated when histological disease is demonstrable (F≥2) although some groups have commenced treatment within 90 days of LT (70, 71). The concurrent use of didanosine and ribavirin is not recommended due to increased risk of mitochondrial toxicity (72). cART regimens that contain abacavir should also be avoided due to the impairment of ribavirin phosphorylation

Patients co-infected with HBV and non-viral aetiologies including those that present with acute liver failure, have excellent short and long-term outcomes post LT. Reported median survival at 1 year ranges between 75-100% and 100% at 5 years (74)(75). The largest prospective study to date in HIV/HBV co-infected patients was conducted in 21 patients for

The key difference between HIV/HBV and HIV/HCV co-infected patients is the presence of highly potent anti-viral agents against HBV in the therapeutic armamentarium. Patients coinfected with HBV and receiving cART will undoubtedly be receiving an oral nucleoside/nucleotide analogue that will have anti-viral actions against both HIV and HBV. Tenofovir in conjunction with emtricitabine (Truvada) is recommended (76, 77). The use of these highly efficacious, potent oral agents results in the majority of patients undergoing LT with an undetectable HBV viral load. Immuno-prophylaxis with Hepatitis B Immunoglobulin (HBIg) is also recommended in the post LT period indefinitely. Reported data on the use of HBIg and oral anti-viral agents has demonstrated that this combination is highly effective at preventing HBV recurrence even in those who have a detectable HBV viral load at the time of LT (78). Data on patients with HIV and non-viral liver disease undergoing LT is limited. Our experience suggests that these patients have similar survival

**2.3. Hepatitis B co-infection and non-viral aetiologies**

a median of 42 months with no patient suffering graft loss (76).

rates as HIV negative patients (74).

patients (p<0.0001).

(73).

#### **2.1. Outcomes post liver transplantation**

Initial case series of HIV positive patients undergoing liver transplantation were associated with poor outcomes (57, 58). It is important to note that this was before the introduction of cART regimens. Retrospective data since has however demonstrated an increasing understanding of the complexities faced by this unique patient cohort. To date, the largest study analysed data provided by the US United Network for Organ Sharing LT database (1997-2006) and identified 138 HIV-positive patients (59). Overall survival rates were inferior in the HIV positive cohort compared to a comparative HIV negative cohort (n = 30.520) at 2- and 3-years post transplant (70% and 60% vs 81% and 77%, p < 0.047). Considerable data however was missing from the HIV cohort raising the possibility that HIV infection may not have been optimally treated prior to LT.

#### **2.2. Hepatitis C co-infection**

The present literature clearly demonstrates that outcomes in HIV/HCV co-infected patients is suboptimal when compared to other aetiologies. Studies to date have only described small numbers from single centres. Survival rates have ranged between 64-88% at 1 year and 33- 51% at 5 years (49, 60-62). The only prospective cohort study of 89 HIV/HCV co-infected patients and 235 HCV mono-infected controls performed at 17 US centers which was recently published, warrants further analysis (63). The authors evaluated the 2 cohorts for a median 2.7 years and 2.4 years respectively (ref). Compared to HCV controls, HIV/HCV coinfected patients were younger (49 vs. 54 years, p<0.0001), had lower BMI at listing (25 vs. 28 kg/m2, p<0.0001), more HBV co-infection (6% vs. 1%, p=0.02), were more likely to receive a non-heart beating graft (17% vs. 4%, p = 0.0002), longer median warm ischaemia time (41 vs. 21 minutes, p =0.001) and less use of tacrolimus-based (versus cyclosporine) initial immunosuppression (58% vs. 80%, p<0.0001). 1- and 3-year patient survival rates were 76% and 60% in HIV/HCV cohort compared to 92% and 79% in the HCV cohort (p<0.001). Graft loss was also significantly higher in the HIV/HCV cohort (p<0.001). Multivariate analysis identified HIV infection as the only baseline factor associated with increased risk of death (HR 2.3, p = 0.002) and graft loss (HR 1.9, p = 0.01). Analysis of the HIV/HCV co-infected cohort only identified that receipt of a combined kidney-liver transplant (HR 3.8, p=0.003), BMI<21 kg/m2 at enrolment (HR = 3.2, p=0.01), receipt of an anti-HCV positive donor (HR 2.5, p=0.03), and older donor age (HR 1.3 per decade, p=0.04) were significant predictors of reduced graft survival. A previous study identified a MELD score > 20, intolerance of cART post transplantation and high post-transplant HCV viral loads as predictors of mortality post-LT (49). The cumulative incidence of acute cellular rejection (ACR) requiring treatment was significantly higher in HIV/HCV patients compared to HCV-mono-infected patients (39% vs. 24% at year 3, HR 2.1, p=0.01)(63). 50% of the cases of ACR occurred within the first 21 days following LT.

Recurrence of HCV post-LT is universal but an accelerated disease course is well recognised in HIV/HCV co-infected patients (62, 64). HCV recurrence, especially the aggressive severe fibrosing cholestatic variant of recurrent hepatitis C (FCH) and sepsis are the leading causes of death post-LT amongst HIV/HCV co-infected patients (61, 62, 65-68). Although no reliable markers are available to identify patients who will develop FCH, higher HCV viral loads immediately after LT at week 1 and week 2 may be an indicator for those at risk (69). A French study highlighted the rapid fibrosis progression rates in HIV/HCV co-infected patients (2.4 versus 1.4 score, p=0.01) at 24 months post-LT (62). The likelihood of progression to a fibrosis score ≥ 2 was also significantly higher in HIV/HCV co-infected patients (p<0.0001).

Re-treatment of HCV recurrence post-LT is associated with an increased side-effect profile and poorer treatment outcomes compared to HCV patient's pre-LT. Pegylated interferon and ribavirin remain the 'standard of care' for a minimum of 48 weeks irrespective of viral genotype. Treatment for recurrent HCV post-LT in our institution is instigated when histological disease is demonstrable (F≥2) although some groups have commenced treatment within 90 days of LT (70, 71). The concurrent use of didanosine and ribavirin is not recommended due to increased risk of mitochondrial toxicity (72). cART regimens that contain abacavir should also be avoided due to the impairment of ribavirin phosphorylation (73).

#### **2.3. Hepatitis B co-infection and non-viral aetiologies**

264 Immunodeficiency

possibility drug-drug interactions and toxicity.

**2.1. Outcomes post liver transplantation**

**2.2. Hepatitis C co-infection**

21 days following LT.

HIV infection may not have been optimally treated prior to LT.

standard CNI doses (56). Meticulous monitoring and surveillance is required to reduce the

Initial case series of HIV positive patients undergoing liver transplantation were associated with poor outcomes (57, 58). It is important to note that this was before the introduction of cART regimens. Retrospective data since has however demonstrated an increasing understanding of the complexities faced by this unique patient cohort. To date, the largest study analysed data provided by the US United Network for Organ Sharing LT database (1997-2006) and identified 138 HIV-positive patients (59). Overall survival rates were inferior in the HIV positive cohort compared to a comparative HIV negative cohort (n = 30.520) at 2- and 3-years post transplant (70% and 60% vs 81% and 77%, p < 0.047). Considerable data however was missing from the HIV cohort raising the possibility that

The present literature clearly demonstrates that outcomes in HIV/HCV co-infected patients is suboptimal when compared to other aetiologies. Studies to date have only described small numbers from single centres. Survival rates have ranged between 64-88% at 1 year and 33- 51% at 5 years (49, 60-62). The only prospective cohort study of 89 HIV/HCV co-infected patients and 235 HCV mono-infected controls performed at 17 US centers which was recently published, warrants further analysis (63). The authors evaluated the 2 cohorts for a median 2.7 years and 2.4 years respectively (ref). Compared to HCV controls, HIV/HCV coinfected patients were younger (49 vs. 54 years, p<0.0001), had lower BMI at listing (25 vs. 28 kg/m2, p<0.0001), more HBV co-infection (6% vs. 1%, p=0.02), were more likely to receive a non-heart beating graft (17% vs. 4%, p = 0.0002), longer median warm ischaemia time (41 vs. 21 minutes, p =0.001) and less use of tacrolimus-based (versus cyclosporine) initial immunosuppression (58% vs. 80%, p<0.0001). 1- and 3-year patient survival rates were 76% and 60% in HIV/HCV cohort compared to 92% and 79% in the HCV cohort (p<0.001). Graft loss was also significantly higher in the HIV/HCV cohort (p<0.001). Multivariate analysis identified HIV infection as the only baseline factor associated with increased risk of death (HR 2.3, p = 0.002) and graft loss (HR 1.9, p = 0.01). Analysis of the HIV/HCV co-infected cohort only identified that receipt of a combined kidney-liver transplant (HR 3.8, p=0.003), BMI<21 kg/m2 at enrolment (HR = 3.2, p=0.01), receipt of an anti-HCV positive donor (HR 2.5, p=0.03), and older donor age (HR 1.3 per decade, p=0.04) were significant predictors of reduced graft survival. A previous study identified a MELD score > 20, intolerance of cART post transplantation and high post-transplant HCV viral loads as predictors of mortality post-LT (49). The cumulative incidence of acute cellular rejection (ACR) requiring treatment was significantly higher in HIV/HCV patients compared to HCV-mono-infected patients (39% vs. 24% at year 3, HR 2.1, p=0.01)(63). 50% of the cases of ACR occurred within the first

Patients co-infected with HBV and non-viral aetiologies including those that present with acute liver failure, have excellent short and long-term outcomes post LT. Reported median survival at 1 year ranges between 75-100% and 100% at 5 years (74)(75). The largest prospective study to date in HIV/HBV co-infected patients was conducted in 21 patients for a median of 42 months with no patient suffering graft loss (76).

The key difference between HIV/HBV and HIV/HCV co-infected patients is the presence of highly potent anti-viral agents against HBV in the therapeutic armamentarium. Patients coinfected with HBV and receiving cART will undoubtedly be receiving an oral nucleoside/nucleotide analogue that will have anti-viral actions against both HIV and HBV. Tenofovir in conjunction with emtricitabine (Truvada) is recommended (76, 77). The use of these highly efficacious, potent oral agents results in the majority of patients undergoing LT with an undetectable HBV viral load. Immuno-prophylaxis with Hepatitis B Immunoglobulin (HBIg) is also recommended in the post LT period indefinitely. Reported data on the use of HBIg and oral anti-viral agents has demonstrated that this combination is highly effective at preventing HBV recurrence even in those who have a detectable HBV viral load at the time of LT (78). Data on patients with HIV and non-viral liver disease undergoing LT is limited. Our experience suggests that these patients have similar survival rates as HIV negative patients (74).

#### **2.4. Hepatocellular carcinoma**

Studies specifically evaluating outcomes of LT in HIV positive patients with HCC have been limited. One such study compared 21 HIV positive patients with 65 HIV negative patients (79). The authors demonstrated a trend towards a higher drop-out rate on the waiting-list amongst HIV positive patients (23% vs 10%, p = 0.08) with 16 HIV positive and 58 HIV negative patients eventually undergoing LT. HIV positive patients were younger at the time of LT (50 versus 58 years, p<0.002) and following LT, observed survival was comparable at 1 and 3 years (81% and 74% versus 93% and 85%, p=0.07). HCC recurred in 5 HIV positive patients (31%) and in 9 HIV negative patients (15%) at a median time of 11 and 18 months respectively. Predictive factors for HCC recurrence before LT included Child Pugh C (p=0.003), being outside the Milan criteria radiologically (p=0.0008) and AFP progression > 15 ug/L per month on the waiting list (p=0.005). Factors predictive of HCC recurrence post LT which took into account pathological factors included those outside the Milan criteria (p=0.01), those outside the UCSF criteria (p=0.03) and those with evidence of satellite nodules (p=0.03) and microscopic (p=0.005) or macroscopic vascular invasion (p=0.001). Further studies are required to evaluate the influence of HIV infection on the impact of HCC post-LT but this indication in the HIV population will become more relevant.

The Role of Liver Transplantation in HIV Positive Patients 267

• **Viral:**

**CMV HSV**

• **Non-viral: Alcohol**

**assay)**

**3. Conclusion**

**Immune reconstitution**

**Opportunistic infections**

**Table 1.** Causes of liver disease in HIV-positive individuals

**opportunistic complications).**

• **Absence of AIDS-defining illness**

• **The criteria for liver transplantation are met**

**Table 2.** Criteria for Liver Transplantation in HIV-positive individuals

**Hepatitis A, Hepatitis B, Hepatitis C, Hepatitis D, Hepatitis E**

cART, combined anti-retroviral therapy; CMV, cytomegalovirus; HSV, herpes simplex virus; NNRTI, non-nucleoside

• **CD4+ cell count > 100 cells/uL (> 200 cells/uL with a previous history of**

• **HIV viral load < 50 copies/mL ( using ultrasensitive Amplicor Monitor PCR**

• **Absence progressive multi-focal leukoencephalopathy, chronic intestinal**

HIV-positive patients established on cART are expected to have good long-term outcomes. Given the success of cART, more patients are likely to present with the long-term sequelae of ESLD. In an era of organ/donor shortage, more of these patients are likely to present as potential candidates for liver transplantation. Our understanding of the issues faced by this patient cohort both pre- and post-liver transplantation continues to improve but challenges remain in the management of HIV-HCV coinfection. The data discussed in this article certainly represents a learning curve of the experience of this patient cohort. Liver transplantation in HIV-positive patients is a viable option and should be considered for

reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor

**cryptosporidiosis (> 1 month) or primary CNS lymphoma**

carefully selected patients in transplant units with multi-disciplinary expertise.

**cART induced liver injury (e.g. NNRTI, NRTI, PI)**

**Non-alcohol related fatty liver disease Non-cirrhotic portal hypertension**

#### **2.5. HIV disease post transplant**

At present no standardised cART regimen is utilised, but instead is tailored to the individual patient reflecting known resistance and mutations. The re-introduction of cART post-LT also varies between individual centers, with some continuing cART throughout the transplant period whilst others re-introduce the medication between 4-14 days. We recommend that cART medication should be re-introduced once liver graft function has normalised thereby avoiding the possibility of confusion with the other causes of graft dysfunction immediately post-LT.

In a recent study of HIV/HCV patients bacterial infections were identified as the principal aetiological agents of post-LT infections and viral infections were secondary to uncomplicated herpes simplex virus (HSV) infections (80). Risk factors associated with severe infections included a pre-LT MELD score of > 15 ( HR 3.5, 95% CI 1.7-7.1, p = 0.001), history of category C AIDS-defining events (HR4.0, 1.9-8.6, p<0.001) and non-tacrolimus based immunosuppression (HR 2.5, 1.3-4.8, p=0.006). The same study also suggested that opportunistic infections namely CMV disease, disseminated HSV, invasive fungal infections and tuberculosis were increased in HIV positive patients, affecting 11% of their cohort. It is important to note these 'opportunistic' infections however can occur in HIV negative patients post LT. This study also did not have a HIV negative comparative group therefore not allowing the authors to be able to demonstrate that these deemed opportunistic infections were due to HIV infection only. Reassuringly reported data from other studies fails to demonstrate a higher incidence of opportunistic infections in comparison to HIV negative patients (81).

cART, combined anti-retroviral therapy; CMV, cytomegalovirus; HSV, herpes simplex virus; NNRTI, non-nucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor

**Table 1.** Causes of liver disease in HIV-positive individuals

**Table 2.** Criteria for Liver Transplantation in HIV-positive individuals

#### **3. Conclusion**

266 Immunodeficiency

**2.4. Hepatocellular carcinoma**

**2.5. HIV disease post transplant**

dysfunction immediately post-LT.

negative patients (81).

Studies specifically evaluating outcomes of LT in HIV positive patients with HCC have been limited. One such study compared 21 HIV positive patients with 65 HIV negative patients (79). The authors demonstrated a trend towards a higher drop-out rate on the waiting-list amongst HIV positive patients (23% vs 10%, p = 0.08) with 16 HIV positive and 58 HIV negative patients eventually undergoing LT. HIV positive patients were younger at the time of LT (50 versus 58 years, p<0.002) and following LT, observed survival was comparable at 1 and 3 years (81% and 74% versus 93% and 85%, p=0.07). HCC recurred in 5 HIV positive patients (31%) and in 9 HIV negative patients (15%) at a median time of 11 and 18 months respectively. Predictive factors for HCC recurrence before LT included Child Pugh C (p=0.003), being outside the Milan criteria radiologically (p=0.0008) and AFP progression > 15 ug/L per month on the waiting list (p=0.005). Factors predictive of HCC recurrence post LT which took into account pathological factors included those outside the Milan criteria (p=0.01), those outside the UCSF criteria (p=0.03) and those with evidence of satellite nodules (p=0.03) and microscopic (p=0.005) or macroscopic vascular invasion (p=0.001). Further studies are required to evaluate the influence of HIV infection on the impact of HCC

post-LT but this indication in the HIV population will become more relevant.

At present no standardised cART regimen is utilised, but instead is tailored to the individual patient reflecting known resistance and mutations. The re-introduction of cART post-LT also varies between individual centers, with some continuing cART throughout the transplant period whilst others re-introduce the medication between 4-14 days. We recommend that cART medication should be re-introduced once liver graft function has normalised thereby avoiding the possibility of confusion with the other causes of graft

In a recent study of HIV/HCV patients bacterial infections were identified as the principal aetiological agents of post-LT infections and viral infections were secondary to uncomplicated herpes simplex virus (HSV) infections (80). Risk factors associated with severe infections included a pre-LT MELD score of > 15 ( HR 3.5, 95% CI 1.7-7.1, p = 0.001), history of category C AIDS-defining events (HR4.0, 1.9-8.6, p<0.001) and non-tacrolimus based immunosuppression (HR 2.5, 1.3-4.8, p=0.006). The same study also suggested that opportunistic infections namely CMV disease, disseminated HSV, invasive fungal infections and tuberculosis were increased in HIV positive patients, affecting 11% of their cohort. It is important to note these 'opportunistic' infections however can occur in HIV negative patients post LT. This study also did not have a HIV negative comparative group therefore not allowing the authors to be able to demonstrate that these deemed opportunistic infections were due to HIV infection only. Reassuringly reported data from other studies fails to demonstrate a higher incidence of opportunistic infections in comparison to HIV

HIV-positive patients established on cART are expected to have good long-term outcomes. Given the success of cART, more patients are likely to present with the long-term sequelae of ESLD. In an era of organ/donor shortage, more of these patients are likely to present as potential candidates for liver transplantation. Our understanding of the issues faced by this patient cohort both pre- and post-liver transplantation continues to improve but challenges remain in the management of HIV-HCV coinfection. The data discussed in this article certainly represents a learning curve of the experience of this patient cohort. Liver transplantation in HIV-positive patients is a viable option and should be considered for carefully selected patients in transplant units with multi-disciplinary expertise.


**Contents**

## **About the Special Issue Editors**

**Antonio Gil** (Full Professor of Chemical Engineering, Universidad Publica de Navarra, Spain): ´ Professor Gil earned his BS and MS in Chemistry at University of Basque Country (San Sebastian) ´ and his PhD in Chemical Engineering at University of Basque Country (San Sebastian). He did ´ postdoctoral research at the Universite catholique de Louvain (Belgium) working on Spillover and ´ Mobility of Species on Catalyst Surfaces.

**Miguel A. Vicente** (Full Professor of Inorganic Chemistry, Universidad de Salamanca, Spain): Professor Vicente earned his BS and MS in Chemistry at Universidad de Salamanca, and his PhD in Inorganic Chemistry at UNED University (Madrid). He carried out postdoctoral research at the Universite Pierre et Marie Curie (Paris, France) and at the Universit ´ e catholique de Louvain ´ (Belgium).

*Communication*


*4.2. Transmission Electron Microscopy (TEM)*

TEM analysis was performed as described by Shih et al. [3]. Green and yellow sectors of leaves were cut into small cubes in the field and placed in a fixation solution containing 2.5% glutaraldehyde and 4% paraformaldehyde in 0.1 M sodium phosphate buffer (pH 7.0). Samples underwent 20 min of rinsing three times and were post-fixed in 1% osmium tetroxide for 2 h. After being dehydrated through an ethanol series, samples were infiltrated and embedded in Spurr's resin and then polymerized at 70 ◦C for 8 h. Ultrathin sections (~70–90 nm) were collected and stained with ethanol uranyl acetate and lead citrate. The morphology of plastids was observed with Tecnai F20S TEM (The Thermo Scientific™, Waltham, MA, USA) at 200 kV.

#### *4.3. Measurement of Physio-Biochemical Parameters*

A total of 50 mg fresh leaves were used to extract chlorophyll. The total chlorophyll content (ChlT, mg g−1FW) and carotenoids content (Ca, mg g−1 FW) were determined as described by Wellburn [77]. The net photosynthetic rate (*Pn*, µmol m−2 s −1 ), intercellular CO2 concentration (*Ci*/ppm) and transpiration rate (*Tr*, mmol.m−2 s −1 ) were determined with a portable L-6400XT (LI-COR, Lincoln, NB, USA). The measurements of photosynthetic parameters were taken at the

saturation irradiance with an incident photosynthetic photo flux density (PPFD) of 1200 µmo m−2 s −1 and an airflow rate at 500 µmol s−1 . The enzymatic activities of superoxide dismutase (SOD, U g−1 ), catalase (CAT, U g−1 .min−1 ), peroxidase (POD, U g−1 .min−1 ) and the content of malonaldehyde (MDA, µmol g−1 ) were calculated by following the manufacturer's instructions (Biological Engineering Institute of Nanjing Jiancheng, China). Means from three replicates were used for statistical analysis.