**Li Cui 1,\*, Zhibo Peng 1, Xiaokun Yuan 1, Dingyong He 1 and Li Chen 2**

Received: 29 October 2018; Accepted: 20 November 2018; Published: 23 November 2018

**Abstract:** Autogenous laser welding of 5A90 Al–Li alloy sheets in a butt-joint configuration was carried out in this study. The microstructure characteristics of the weld metal and base metal in the horizontal surface and the transverse section of the welded joints were examined quantitatively using electron back scattered diffraction (EBSD) technique. The results show that the weld metal in the horizontal surface and the transverse section exhibits similar grain structural features including the grain orientations, grain shapes, and grain sizes, whereas distinct differences in the texture intensity and misorientation distributions are observed. However, the base metal in the horizontal surface and the transverse section of the joints reveals the obvious different texture characteristics in terms of the grain orientation, grain morphology, predominate texture ingredients, distribution intensities of textures, and grain boundary misorientation distribution, resulting in the diversity of the microhardness in the base metal and the softening of the weld metal. However, the degree of the drop in the hardness of the weld metal is highly correlated to the microtexture developed in the base metal.

**Keywords:** Al–Li alloys; laser welding; weld metal; base metal; grain orientation; texture


*3.2.1 Analysis of scopes of higher impact*

With the term "scope," we refer to the topics on which each study focuses on contributing to the area of IoT systems applied to ehealth and telemedicine. After the analysis, we have found studies whose scope is related to the provision of a health service, proposing models, system designs, and/or implementations of a complete system or a component of an IoT system. On the other hand, scopes focused on improving some characteristic of IoT systems that are relevant when applied to healthcare have also been identified.

**Figure 2** illustrates the scopes in the analysis. It can be seen that the majority of studies focus on providing solutions for the field of monitoring. The reader should know that a division has been made in this scope, distinguishing between studies that explicitly indicated or from which the character of real-time monitoring could be clearly inferred. The total number of studies that fit this domain was 83. These data

**Figure 1.** *Publications with more impact per country (N = 186).*

*Perspective Chapter: Internet of Things in Healthcare – New Trends, Challenges and Hurdles DOI: http://dx.doi.org/10.5772/intechopen.104946*

#### **Figure 2.**

show that the main purpose of the application of IoT to healthcare is to monitor patients, ubiquitously or integrated into rooms, for better control of vital signs or physiological parameters. This result is consistent with the main use for which IoT systems are used. Continuing with the analysis focused on areas of application, the next most common are those related to diagnosis. The creation of models that help the medical professional to give a diagnosis stands out mainly Machine Learning models that can be integrated into the system, sometimes complemented with architectures equipped with resources to apply Fog computing, as well as with the decentralization of processing with computing at the edge, trend that is currently increasing with the optimization of hardware and AI frameworks for model integration and consumption reduction [195]. Additionally, the applications are not restricted to the field of healthcare in the personal context, but also in the workplace [196]. To a lesser extent, we also find the use of IoT to facilitate the remote diagnosis of the patient. This last result may be related to the existing limitations to provide appropriate resources to remote centers or isolated areas that allow establishing reliable connections with sufficient transmission quality. The least relevant areas currently are self-care and remote rehabilitation. The first of these two areas mentioned was the one that had the greatest impact at the beginning of the use of IoT for healthcare, currently being on the slope of enlightenment or plateau of productivity in the hype-cycle curve. The low frequency of appearance of rehabilitation as a field of study may be due to the difficulty in carrying out rehabilitation tasks remotely.

Focusing on areas related to the improvement of system features, studies focused on maintaining the security of the IoT system are more frequent, that is, on avoiding transmission failures, network hacks, or data corruption. Additionally, we find studies focused on providing encryption protocols to ensure the authenticity and privacy of the patient. These last two scopes are often intrinsically related to system security. These results reveal the great challenges that exist in the integration of IoT systems in the Electronic Health Records of health systems: to be able to relate the data to the patient without compromising their privacy, as well as to manage the enormous amount of information collected avoiding losses, falsification information, and other security breaches. Very close in relevance we find the improvement of the performance of the system, that is, looking for better response times in the transmission and processing of information. Again, it is a challenging topic, especially in combination with equipping the system with authentication, privacy, and security protocols, which slows down IoT systems, which must be addressed for this type of system to be useful in terms of practicality.

#### **Figure 3.**

*Scope trends. At top, classification grouped by year analyzed in the study. At left, scopes related to the system's application approach. On the right, scopes focused on improving the characteristics of the IoT system.*

In the results, we also observe that the studies related to the study of interoperability and the analysis of usability, user experience, and degree of acceptance have very little impact. These types of studies are not frequent, and yet, they address determining aspects in the adequacy of IoT systems to the health environment; its correct application depends on the fact that the implemented system is practical and perceived as useful. The little research on these issues may be the greatest limitation of these systems in the future.

**Figure 3** shows the trend of these areas in the years considered for the analysis. Although a drop in the number of papers is perceived in 2021, this may be due to the fact that there has not yet been a stabilization in the number of citations on studies that contribute novelties to the field of research. Both graphs show how in recent years there has been a decrease in the impact of research aimed at providing solutions with IoT systems, and instead, there has been an increase in interest in research that focuses on improving some characteristics of the system architecture, mainly in security and privacy. This result again reveals indications of the situation of these systems in the hype-cycle curve, seeing reduced interest in deepen for new applications and consolidating their use by focusing on the greatest limitations that this set of technologies has, that is, aspects of security, privacy, and performance.

#### *3.2.2 Interest in applied technologies*

Paying attention to communication technologies, the charts in **Figure 4** reveal a varied set of alternatives. In these graphs, only those studies that have used and revealed the technologies applied in the implementation of IoT systems are taken into consideration. As a result, 87 articles were considered. The charts highlight the use of Bluetooth technology, in both its older versions and BLE, and Wi-Fi. Despite being a technology adapted to IoT, the use of LoRa is not frequent. GSM and GPRS technologies continue to be used, mainly because they have a greater network infrastructure for these technologies and because they are more in line with the user profile that

*Perspective Chapter: Internet of Things in Healthcare – New Trends, Challenges and Hurdles DOI: http://dx.doi.org/10.5772/intechopen.104946*

#### **Figure 4.**

*Most common communication technologies in studies that carry out an implementation of an IoT system (N = 87). Top-right chart considers only those studies whose sensing acquisition devices are wearable (N = 36).*

these systems are aimed at, mainly older people or those who are not familiar with new technologies.

Among the studies that reveal the communication technologies used, only 36 focus on the use of systems with exclusively wearable devices for data acquisition. In these studies, a lower use of MQTT is revealed in favor of the use of technologies such as Zigbee. Wi-Fi technology is still the most frequently used; however, there is a remarkable decrease.

The most frequent technologies identified in the analyzed studies include Machine Learning and Deep Learning for the fields of monitoring and diagnostic support. In the fields of security, privacy, and authentication, the use of Blockchain stands out. On the other hand, Fog computing and edge computing are the technologies for which the greatest interest is shown in the field of performance improvement. This is one of the most current trends, driven by systems equipped with more specialized hardware processing units [197].


*3.3.1 The "seed and soil" in bone tissue adaptation*

Breast cancer cells migration to bone is innately related to the molecular and cellular components provided by the pre-metastatic niche, in sequential and distinct phases [137, 172, 176]. In fact, in the nineteenth century, Stephen Paget proposed that tumor cells ("seeds") only grow in specific and permissive microenvironments ("fertile soil") [177]. Of note, BM is a fertile microenvironment, composed of hematopoietic cells, MSCs, endothelial cells, OBs, OCs, molecules secreted by breast primary tumor, either as soluble or contained in extracellular vesicles (EVs) or exosomes, and immune migrating cells [137, 175]. However, how and when these factors, produced locally or systemically, regulate the crucial mechanisms behind the establishment of this site remains less clear [175].

Recent studies suggest that bone pre-metastatic niche exists prior to metastatic colonization; however, disseminated breast cancer cells are detectable in BM prior to clinically detectable bone metastases [175, 178]. Interestingly, patients without any metastases harbored disseminated breast cancer cells with less genetic heterogeneity compared with the primary tumor or those disseminated cells isolated from bone metastatic patients [175, 178].  Based on these *Perspective Chapter: Breast-Tumor-Derived Bone Pre-Metastatic Disease – Interplay... DOI: http://dx.doi.org/10.5772/intechopen.107278*

findings, we can speculate that bone/BM stromal cellular and molecular components probably play roles in supporting these mutations, for further licensing and selection of the best "seeds" to adapt in the pre-metastatic niche, until their overt bone colonization.

Additionally, a recent study identified LOX-derived by hypoxia condition, a factor significantly associated with bone tropism and relapse. LOX induces an intense osteoclastogenesis, through NFATc1, before, and independent of breast tumor cells arrival at BM [174]. Therefore, this study identified a previous step in bone metastases development, triggered by these osteolytic lesions, opening new opportunities for therapeutic intervention [174]. In fact, in a previous study using an intracardiac mouse model of breast-cancer-derived bone metastases, animals treated with a nonspecific LOX inhibitor—β-aminopropionitrile—reduce bone colonization when administered at the time of tumor inoculation [182].

As mentioned in the last section, recent evidence suggests that breast-cancerderived miRNAs play key roles in tumor development and progression via exosomes transfer, regulating the outgrowth and metastases of breast cancer [183, 184]. Of note, it was described that miR-21, a highly conserved oncomicro RNA, is expressed in serum of breast cancer patients, significantly higher as compared with healthy controls [185]. Moreover, it was demonstrated that miR-21 induces OCs differentiation, by directly binding programmed cell death 4 (PDCD4), upregulation of NFATc1, and suppression of c-Fos transactivation [186, 187]. Indeed, it was showed that breast cancer cell–secreted exosomes containing miR-21 lead to an exacerbated osteoclastogenesis, which contributes to the generation of a pre-metastatic niche and further enhancing bone metastases development [188]. Importantly, the expression level of miR-21 was detected at higher level in serum exosomes of breast cancer patients with bone metastases, as compared with patients without bone metastases [188].

Almost 20 years ago, a pioneer study challenged the molecular basis for bone metastases. Using human breast cancer cell lines with elevated metastatic activity, it was determined a breast-cancer-derived bone metastases gene signature, which included genes involved in: (i) BM homing (CXCR4); (ii) extracellular matrix alteration (Matrix Metallopeptidase 1 (MMP1), ADAM metallopeptidase with thrombospondin type 1 motif 1 (ADAMTS1), and proteoglycan-1); (iii) angiogenesis (Fibroblast growth factor 5 (FGF5), and Connective tissue growth factor (CTGF); and osteoclastogenesis (IL-11) [189]. Moreover, the overexpression of this gene set is superimposed on a poor prognosis already present in the parental breast cancer population, suggesting that metastases require a set of functions beyond those underlying the emergence of the primary tumor [189]. Thereafter, several other bone metastases gene signatures were proposed, such as Src-dependent [190] or Irf7-regulated genes [191]. To date, it remains unclear the clinical significance and applicability of these gene signatures described, either by tumor heterogeneity in primary and secondary sites or by differences in tumor sources.


**1. Introduction**

Pharmaceuticals are used in large quantities around the world. In many cases, they are used not only to prevent disease or for treatment in humans, but also in animals [1,2]. Some of them, for example, natural and synthetic estrogens, are classified also to the group of endocrine disrupting compounds (EDCs). Over the last two decades, the presence of pharmaceuticals and EDCs in the aquatic environment has been confirmed many times [3–6]. They have been found in treated wastewater [7], sewage sludge [8], marine waters [9], and in living organisms [10]. They are extensively introduced into the environment via wastewater and in consequence by wastewater treatment plants (WWTPs) because the classical methods of wastewater treatment in WWTPs (mechanical, biological, chemical) do not completely remove pharmaceuticals and EDCs from the wastewater stream [11–14].

In recent years, some advanced technologies, such as advanced oxidation process (AOP), electrochemical oxidation, activated carbon adsorption, membrane techniques, and membrane bioreactors have been introduced for the removal of pharmaceuticals from wastewater [15–18]. However, these advanced processes are very expensive, and they are often unprofitable in technological systems. Therefore, the choice of cheaper, less complicated but very e ffective techniques for wastewater treatment with regard to pharmaceutical residues is well-aimed.

One of the options is to combine conventional WWTPs with hydroponic cultures called constructed wetlands (CWs). The basis of this is the use of plants such as macrophytes in the process of biological wastewater treatment [19]. In most cases, CWs are characterized based on water position and flow direction, and they are divided into surface flow (SF) systems, horizontal subsurface flow systems (H-SSF), and vertical subsurface flow systems (V-SSF). In the first case, sewage flows along a pool with growing plants. The root zone and part of the plants are located under the sewage stream. In H-SSF and V-SSF systems, sewage is introduced into a porous medium (generally gravel) in which macrophytes grow [20]. In most cases, constructed wetlands are a separate element of a sewage treatment plant. CWs act as a primary step (raw influent goes to the CW), secondary step (raw influent goes to primary treatment and afterwards to the CW), and tertiary step (raw influent goes to primary treatment, followed by secondary treatment and finally to the CW). This has been clearly and understandably described by Verlicchi et al. [20].

In recent years, constructed wetlands have been reported to be highly e fficient in the removal of conventional pollutants from domestic sewage, agricultural sewage, industrial wastewater, mine drainage, leachate, contaminated ground water, and urban runo ff [21–26]. Based on the literature, it is known that the mechanisms of pollution removal in CWs can be classified into biotic processes (e.g., microbiological degradation, root, and plant uptake) and abiotic processes like evaporation, photodegradation, oxidation, hydrolysis, retention, or sorption [27]. The e fficiency of the removal of a pollutant depends also on such factors as seasonality, weather, and humidity. On the other hand, the use of constructed wetlands to remove pharmaceuticals and EDCs from wastewater is still not fully understood [28]. Most of the research concerning the uptake of pharmaceuticals and EDCs by plants in CWs refers to so-called microcosm, or pilot-scale laboratory systems, as opposed to real systems in WWTPs (Table S1, Supplementary Materials). In addition, only a few scientific papers have examined the actual uptake of emerging environmental pollutants by plants (Table S1, Supplementary Materials). Moreover, in most cases, the removal e fficiency of the target compounds from wastewater is determined based only on determining their concentrations in raw and treated wastewater without the examination of their presence in plant tissues [29]. For this reason, it is di fficult to assume the influence and mechanism of the removal of EDCs from wastewater by plants, as well as to establish which plants are the best for this purpose.

In this study, in order to obtain the most reliable data, we decided to evaluate the possibility of using hydroponic cultivation for the removal of pharmaceuticals and endocrine disrupting compounds in municipal sewage treatment, both with the application of real WWTP conditions as well as with the determination of the analytes studied in plant materials.

For this reason, the main objectives of this work were as follows: (1) to determine the selected pollutants in raw and treated sewage; (2) to develop an analytical method for determining selected pharmaceuticals and endocrine disrupting compounds in plant materials; (3) to assess the bioaccumulation of the mentioned pollutants in hydroponically cultivated plants; (4) to evaluate which of the tested plant species best meets this purpose.

According to literature data [30–33] and information included in Table S1 in Supplementary Materials, for the isolation of pharmaceuticals and EDCs from plant materials, extraction techniques such as Microwave Assisted Extraction (MAE) [34], QuEChERS (Quick, Easy, Cheap, E ffective, Rugged, and Safe) procedures [35,36], Accelerated Solvent Extraction (ASE) [27], Solid-Liquid Extraction (SLE) under gentle mixing [32], as well as Ultrasound-Assisted Extraction (UAE) [33] are used. In this study, we decided to check the usefulness of an ASE-Solid-Phase Extraction (SPE) technique for the isolation of target compounds from plant materials, because in none of the published papers, such investigations have been performed for the same target compounds and with the application of the same plants.

#### **2. Results and Discussion**

#### *2.1. Determination of Selected Pharmaceuticals and Endocrine Disrupting Compounds in Treated and Untreated Sewage*

The method for the determination of pharmaceuticals and EDCs in untreated and treated sewage was described in Section 3.4. The identification of each analyte was based on retention time, quantitative ion, and conformation ion/s, the quantification analysis on the area peak of quantitative ion (details are presented in Section 3.4). The mass spectra of target compounds with the MS fragments assignation are included in Figure S1 in Supplementary Materials. The determined concentrations of fifteen target compounds in untreated and treated sewage from a municipal wastewater treatment plant (MWWTP) are presented in Table 1.

**Table 1.** Concentrations of target compounds in untreated and treated sewage samples collected from a municipal wastewater treatment plant (MWWTP), determined using the Solid-Phase Extraction (SPE)-GC-MS(SIM) method (*n* = 3).

Imipramine, diclofenac, and nadolol were not found in both types of samples (concentrations below the method detection limit (MDL) values). The concentrations of the analyzed NSAIDs (ibuprofen, naproxen) in untreated sewage were the highest among the investigated drugs (2695 ± 916 ng/L, 3420 ± 342 ng/L, respectively), which positively correlated with their large consumption and easy availability [6]. Amitriptyline, one of the measured antidepressant drugs, was found in a high concentration in untreated sewage (1676 ± 184 ng/L), and its concentration after wastewater treatment was still significant (613 ± 38 ng/L). Antidepressant drugs were identified in this area in 2014, and also in the Utrata River to which treated sewage is discharged [37].

In this study, for first time in this part of Europe, concentrations of estrogenic hormones in sewage derived from a wastewater treatment plant supported by constructed wetlands were investigated. E1, E2, E3, and synthetic EE2 were found in both types of sewage in concentrations ranging from 52 ± 3 ng/L to 1662 ± 260 ng/L in untreated sewage, and from 4 ± 0 ng/L to 122 ± 18 ng/L in treated sewage. The concentration of EE2 was the highest among the investigated estrogenic hormones, both in untreated and treated sewage (Table 1).

The concentrations of target compounds in untreated and treated sewage determined in this study were in the range presented by other authors for full-scan systems (Table S1, Supplementary Materials). For example, the concentrations of 86 pharmaceuticals, e.g., diclofenac, ibuprofen, ketoprofen, naproxen, EE2, E2, and E3 in untreated water were in the range from 1 ng/L to 1,000,000 ng/L, and in treated sewage to 901,618 ng/L [32].

However, for the first time, fifteen pharmaceuticals and EDCs were determined in untreated and treated sewage derived from a wastewater treatment plant supported by constructed wetlands working in a temperate climate zone.

#### *2.2. Evaluation of the Analytical Method for Determining Target Compounds in Plant Materials*

As previously mentioned, understanding the impact of individual plant species on the removal of pharmaceuticals and EDCs from wastewater requires an assessment of the uptake of these compounds by plants, for which an analytical procedure is required. In none of the published papers ([30–33], Table S1, Supplementary Materials), such investigations have been performed for the same target compounds and with the application of the same plants. For this reason, our investigations began from an evaluation of the analytical method for determining 15 target compounds in plant materials.

We decided to check the usefulness of the ASE technique for this purpose. ASE technique has been used only once for the isolation of 18 analytes [27]. In the work, among the tested analytes, were 7 pharmaceuticals (ibuprofen, ketoprofen, naproxen, diclofenac, salicylic acid, ca ffeine, carbamazepine), which were determined in *Typha angustifolia* and *Phragmites australis* plants (only roots) during an investigation of the behavior of pharmaceuticals and personal care products in mesocosm-scale constructed wetland compartments. A mixture of acetone/hexane (1:1; *v*/*v*), a temperature of 104 ◦C and two extraction cycles of 13.5 min were applied for ASE. A clean-up step was performed using a florisil column with di fferent elution of the neutral/acidic fractions. In other studies based on other extraction procedures, for the isolation of pharmaceuticals from plant materials, di fferent solvents such as methylene chloride:MeOH (2:1 *v*/*v*) and MTBE (Methyl *tert*-butyl ether):MeOH (1:1 *v*/*v*) [34], hexane:ethyl acetate (1:1, *v*/*v*) [35], 0.1 M HCl:ACN (1:1, *v*/*v*) [36], ACN with 0.5% formic acid (*v*/*v*) [32], and anhydrous sodium sulfate and MeOH [33] were applied.

In this study, the usefulness of three new extraction solvents: MeOH:H2O (1:1, *v*/*v*), EtOH:H2O (1:1, *v*/*v*), ACN:H2O (1:1, *v*/*v*), which were used at two temperatures: 50 ◦C and 80 ◦C for the isolation of target compounds by ASE was studied. Moreover, the e ffect of the acidification of the obtained extracts prior to SPE purification (pH ~ 2) was investigated (Figure 1).

**Figure 1.** Selection of the optimal Accelerated Solvent Extraction (ASE)-SPE conditions for the isolation of target compounds from plant materials.

The results of the optimization of the ASE procedure are presented in Table 2. As can be seen, among the tested ASE conditions, the best recoveries of target pharmaceuticals (ranging from 49 ± 6 to 111 ± 9%), were obtained during the application of a mixture of MeOH:H2O (1:1, *v*/*v*) and a temperature of 50 ◦C (Table 2). Only the recoveries of tri-cyclic antidepressant drugs (amitriptyline and clomipramine) were lower. It should be highlighted that these two compounds were not subjected to the derivatization procedure and the e fficiency of ionization of these two compounds in an ion source

during the GC-MS(SIM) analysis was high. In effect, the sensitivity of the proposed analytical method for the determination of these analytes was enough despite low recovery results.

**Table 2.** Recoveries (mean ± SD) of fifteen analytes using different conditions of the ASE procedure (*n* = 3, conc. 1000 ng/g d.w.).

The analyzed pharmaceuticals and EDCs contain polar functional groups (pKa are presented in Table S2), therefore the acidification of ASE extracts prior to SPE purification could reduce or stop the dissociation of weak acids and increase the dissociation of weak bases. Oasis HLB cartridges used in the SPE procedure are stable from pH 0–14, and they are useful for the isolation of acidic, basic, and neutral analytes. However, modifications of the pH of the loaded sample could strongly influence the recovery data. For this reason, the effect of the acidification of ASE extracts to pH 2 prior to SPE purification on the recovery of analytes was also evaluated. Such studies were performed for the most effective extraction mixture (MeOH:H2O 1:1, *v*/*v*; Table 2) which was tested at two temperatures: 80 ◦C and 50 ◦C. The results are shown in Figure 2.

As we can see (Figure 2), in most cases, the acidification of ASE extracts led to a decrease in recoveries, both at 80 ◦C and 50 ◦C. It was observed for weak acids such as naproxen, difunisal, diclofenac), and weak bases (paracetamol, terbutaline, amitriptyline, clomipramine and nadolol; Table S2). In case of acidification of the ASE extracts obtained at 80 ◦C (Figure 2A) the extraction efficiencies increased for ibuprofen, imipramine, estrone (E1), 17β-estradiol (E2), 17α-ethinylestradiol (EE2), and estriol (E3). However, when the ASE procedure was performed at 50 ◦C, these values decreased significantly for all mentioned compounds (Figure 2B). The extraction efficiencies of polar drugs: paracetamol (logP 0.46), terbutaline (logP 0.90), and nadolol (logP 0.81), decreased significantly where the ASE extracts obtained at 50 ◦C were subjected to acidification prior SPE (Figure 2B). Similar results were observed in our previous study concerning the development of a method for determining NSAIDs and natural estrogens in the mussel *Mytilus edulis trossulus* [38]. In summary, based on the obtained results, the application of the mixture of MeOH:H2O (1:1, *v*/*v*) at 50 ◦C without the acidification of the ASE extract prior to SPE purification was chosen as the most optimal ASE-SPE conditions for the isolation of target compounds from plant material.

In order to compare the recovery data obtained in this work with those presented by other scientists for pharmaceuticals and EDCs isolated from plants used in constructed wetlands, we tried to find the necessary information in all the cited papers [27,33–36]. Unfortunately, the recovery data were presented only in one of them [35], and only for triclosan, methyl-triclosan, and triclocarban. Nuel and coworkers [32] stated that drug detection and quantification methodologies had been fully described

in their paper submitted to the journal Science of the Total Environment (Nuel et al. (2018)), but this paper was not published (based on data from Scopus; 31.10.2019).

**Figure 2.** Impact of the acidification of ASE extracts prior to SPE purification on the recoveries of analytes, carried out at 80 ◦C (**A**) and 50 ◦C (**B**), respectively.

#### *2.3. Validation Parameters of the Proposed ASE-SPE-GC-MS(SIM) MetHod for Determining Target Compounds in Plant Materials*

The ASE-SPE-GC-MS(SIM) methodology for the determination of target pharmaceuticals in plant samples has been validated in accordance with the guidelines described in Section 3.6. The determined validation parameters are presented in Table 3.

**Table 3.** Selected validation parameters of the ASE-SPE-GC-MS(SIM) method for determining target compounds in plant samples (analytical range from method quantification limit (MQL) to 2500 ng/g). Precision and accuracy were determined for three concentrations from analytical range (78 ng/g d.w., 625 ng/g d.w., and

The coe fficient of determination (R2) was in the range of 0.9760–0.9997; the intermediate precision measurement in the range of 0.05–21.60%. Mean recoveries were between 80% and 102% (Table 3). The lowest MDL value was recorded for ibuprofen, flurbiprofen, naproxen, diflunisal, diclofenac, and EE2 – 0.4 ng/g d.w.; the highest value of 2 ng/g d.w. was calculated for clomipramine and amitriptyline. Matrix e ffects were not significant for most of the analyzed compounds, apart from naproxen (ME 43%). The highest suppression of signals was observed for terbutaline (ME −31%) and flurbiprofen (ME −20%). Generally, matrix e ffect values were similar to those presented in our previous studies for the same target pharmaceuticals isolated from environmental matrices [39].

A comparison of the obtained matrix e ffect data with those presented by other authors was not possible because matrix e ffect values were not included in the cited papers [27,32–36]. The method quantification limit (MQL) and MDL values were similar to those we presented (Table S1 in Supplementary Materials).

#### *2.4. Assessment of Bioaccumulation of Selected Pollutants in Hydroponically Cultivated Plants*

The determined concentrations of target compounds in three species of hydroponically cultivated plants (in ng/g dry weight) and the elimination e fficiency of pharmaceuticals and EDCs in an MWWTP with constructed wetlands are presented in Table 4. The elimination e fficiency (EE) was calculated according to Equation (6) described in Section 3.8.

**Table 4.** Results of determining target compounds in three species of hydroponically cultivated plants from an MWWTP using the developed ASE-SPE-GC-MS(SIM) method (*n* = 3), and the elimination efficiency of these compounds from wastewater in an MWWTP supported by constructed wetlands.

1 if drug concentrations were below the MDL value in both untreated and treated wastewater, the elimination efficiency (EE) was not calculated.

Among the 15 investigated analytes, three NSAIDs (ibuprofen, flurbiprofen, diflunisal), two antidepressants (amitriptyline, imipramine), and one synthetic hormone (EE2) were found in Papyrus (*C. Papyrus*) (Table 4). In the case of the Yellow pimpernel (*L. nemorum*) species, terbutaline (β2-agonists), naproxen, and diflunisal as well amitriptyline and EE2 were found. The tissue of the European spindle (*E. europaeus*) plant contained ibuprofen, diflunisal, amitriptyline, and EE2. The highest concentrations were observed for diflunisal and terbutaline determined in Yellow pimpernel (*L. nemorum*) (5569 ± 1298 and 5323 ± 1869 ng/g d.w., respectively). The concentrations of other target compounds were below the MDL value (Table 4). Among three determined estrogenic hormones, only EE2 was found in all the investigated plant species; its concentration was the highest in Papyrus (*C. Papyrus*) (4126 ± 821 ng/g dry weight); E1 and E2 (natural hormones occurring in living organisms) were not detected in any plant tissues. Example chromatograms with marked SIM ions, recorded in this study for real plant samples, are presented in the Supplementary Materials (Figures S3–S5).

Few studies directly point to the transport or uptake of pharmaceuticals by plants in constructed wetlands (Table S1 in Supplementary Materials). For example, 0.2% of the initial amount of diclofenac (1 mg/L) was detected in the roots and leaves of *Typha latifolia* during one week of exposure (laboratory system) [36]. Hijosa-Valsero et al. [27] investigated the possibility of the uptake of 18 selected analytes, including ibuprofen, ketoprofen, naproxen, diclofenac, salicylic acid, caffeine, and carbamazepine by *Typha angustifolia* and *Phragmites australis* plants in constructed wetlands (mesocosm-scale). Ibuprofen, salicylic acid and caffeine were detected in plant tissues, whereas ketoprofen, naproxen, diclofenac and carbamazepine were not found in these species. The main substance detected in root tissues was salicylic acid (123–2560 ng/g). The authors confirmed that *T. angustifolia* is more suitable for the removal of the investigated pollutants than *Phragmites australis* [27]. In another study, performed by Nuel et al. [32], ibuprofen was found in all the investigated plant samples (*Salix alba*, *Iris pseudacorus*, *Juncus e*ff*usus*, *Callitriche palustris*, *Carex caryophyllea*) used in constructed wetlands. According to Wang et al. [33] the bioconcentration factors (BCFs) in *Typha angustifolia* of 8 compounds, e.g., caffeine, carbamazepine, ibuprofen, fluoxetine, gemfibrozil ranged between 60 and 2000. Concentrations of the determined compounds in plant tissue were up to several hundred ng/g for caffeine. This confirms that the results obtained in this study are in agreement with the literature data. However, for the first time, such investigations were performed for Papyrus (*Cyperus papyrus*), European spindle (*Euonymus europaeus*) and Yellow pimpernel (*Lysimachia nemorum*) taking into account this selected group of pharmaceuticals and EDCs.

In the study, the obtained elimination efficiency (EE) of the investigated compounds from wastewater was in the range of 35.8% for diflunisal to above 99.9% for paracetamol, terbutaline and flurbiprofen (Table 4). For comparison, the literature EE data for ibuprofen, presented in Table S1**,** are as follows: 5–88% [40], 96% [41–43], 44–77% [44], 94% [45], 52–85% [46], >99% [47], 51–54% (winter), 85–96% (summer) [48], 42–99% [49]. In our study, this was 99.7%, which confirms that the elimination efficiency of ibuprofen was comparable or higher than that calculated for other studies. Similar the EE data for pharmaceuticals is shown also in papers [50–52]. Thus, the obtained results proved the uptake of the investigated micropollutants by plants allowed an increase in the effectiveness of their removal from wastewater in such a system.

#### *2.5. Assessment of the Usefulness of Hydroponically Cultivated Plants for Removing Target Compounds from Sewage Stream*

According to the literature data, due to the considerable size of rhizomes and roots, the most frequently hydroponically cultivated plants are *Typha sp.* and *Phragmites sp.* (Table S1 in Supplementary Materials). In this study, the possibility of using three plants: *Cyperus papyrus* (Papyrus), *Lysimachia nemorum* (Yellow pimpernel), and *Euonymus europaeus* (European spindle) for this purpose was examined for the first time. These plant species are very well adapted to growth in MWWTPs and exhibit the strongest growth during the growing season. In order to assess the usefulness of these species for removing pharmaceuticals and EDCs from the sewage stream, the sum of the masses of all the target compounds taken by the tested species was established and the obtained values are presented in Table 5.

**Table 5.** The sum of the uptake of selected pharmaceuticals and endocrine disrupting compounds (EDCs) in ng/g dry weight by tested plant species grown in an MWWTP.

Therefore, the highest concentration of all target compounds was observed for *the Lysimachia nemorum* (Yellow pimpernel) plant (16,849 ng/g d.w.), followed by *Cyperus papyrus* (Papyrus) (12,439 ng/g d.w.), and the lowest for *Euonymus europaeus* (European spindle) (2525 ng/g d.w.). Taking into account the summary uptake of target pharmaceuticals and EDCs by tested plants, the *Lysimachia nemorum* (Yellow pimpernel) species is the best for this purpose. The differences in the uptake of target compounds by these plants are connected to their morphological structures. *Euonymus europaeus* (European spindle) has a significant number of woody stems and rhizomes, which means that the uptake of target compounds by this plant is much lower than by the green parts of the two other tested species. Thus, the determination of target compounds in untreated wastewater and treated wastewater, as well as in plant tissues, allowed for establishing which hydroponic cultivation system supported the wastewater treatment process the most significantly (Tables 3–5).

#### **3. Materials and Methods**

#### *3.1. Chemicals and Materials*

Pure standards (>98%) of ibuprofen, paracetamol, flurbiprofen, naproxen, diflunisal, diclofenac sodium salt, nadolol, terbutaline, amitriptyline, imipramine, clomipramine, estrone (E1), 17β-estradiol (E2), 17α-ethinylestradiol (EE2), and estriol (E3), as well as the derivatization reagent *N,O*-bis(trimethylsilyl)trifluoroacetamide (BSTFA) containing 1% of trimethylchlorosilane (TMCS) and pyridine (99.8%) were purchased from Sigma-Aldrich (Steinheim, Germany). Solvents: methanol (MEOH), ethanol (EtOH), acetonitrile (ACN) were supplied by POCH (Gliwice, Poland), ethyl acetate (EtOAc) by Sigma-Aldrich, while 37% hydrochloric acid (HCl) for the acidification of extracts was provided by Chempur (Piekary Sl ˛ ´ askie, Poland). Solid-phase extraction (SPE) was performed using Oasis HLB cartridges (6 mL, 200 mg, Waters Corporation, Miliford, USA).

Standard stock solutions of target compounds (1 mg × mL−1) were prepared in methanol. All the stock solutions were stored at –20 ◦C. Working calibration standard solutions were prepared by diluting the standard stock solutions in the appropriate amount of methanol, and they were stored in the dark at –20 ◦C.

#### *3.2. MWWTP and Constructed Wetlands Characteristic*

The research was carried out at the municipal wastewater treatment plant (MWWTP) in Sochaczew (Mazowieckie Voivodeship, Poland). In Sochaczew MWWTP, macrophyte cultures are introduced in combination with an oxygen biological reactor. The efficiency of removing conventional pollution in Sochaczew MWWTP is high, as presented in Table 6.

**Table 6.** List of sewage test results in the Municipal Wastewater Treatment Plant in Sochaczew (average values from 2017).

BOD5 biochemical oxygen demand (for 5 days). CODCr Chemical Oxygen Demand (using Potassium Dichromate).

Sochaczew MWWTP consists of the following elements: 1◦ mechanical wastewater treatment (grates with a throughput of 515 m3/h, aerated sand traps with degreasers, aerated at 1.91 m3/min), 2◦ biological wastewater treatment (flow reactor with activated sludge with throughput at 6000 m3/d and secondary settling tank with active capacity at 1142 m3), sediment trap settling tanks with a diameter of 21 m, excessive sludge dewatering station, and lime treatment. The wastewater treatment plant was designed for 55,925 equivalent number of inhabitants with a maximum daily volume of sewage at 11,636 m3/d.

Constructed wetlands have been implemented in the second stage of wastewater treatment (biological) as a wastewater polishing treatment system. Wastewater mixed with activated sludge flows around plants. Contact between the plants and wastewater occurs only in the rhyzophytic zone (Figure S2, Supplementary Materials). In this way, the green parts do not have contact with the walls and the benefits are the lack of dieback of the shoots, and faster acclimatization. The plants used in the constructed wetlands are as follows: Papyrus (*Cyperus papyrus*), Reed (*Phragmites australis* (Cav.) Trin. ex Steud, 1841), Spathiphyllum (*Spathiphyllum Adans.*), Grey willow (*Salix cinerea*), Rushes (*Juncus tenageia* Ehrh.), Sweet flag (*Acorus calamus*), Yellow iris (*Iris pseudacorus*), European spindle (*Euonymus europaeus*), Yellow pimpernel (*Lysimachia nemorum*), and Summer lilac (*Buddleja davidii* Franch).

#### *3.3. Sampling Sewage and Plants from Constructed Wetland*

The samples of untreated and treated sewage were collected in November 2017 into 2.5 L amber glass bottles. Raw sewage samples were taken before mechanical treatment, and treated sewage samples were collected at the outlet to the Utrata River. In the laboratory, the sewage samples were filtered under pressure using a 0.45 μm nylon filter and frozen at −20 ◦C until analysis. A list of the monitored pharmaceuticals and EDCs with physical and chemical properties is included in the Supplementary Materials in Table S2.

At the same time, samples of the plants used in the constructed wetlands were collected. Only parts which had no contact with sewage were collected to confirm the migration of pharmaceuticals to green tissue. The plants were washed under tap water, separated and dried for 3 days at room temperature (~23 ◦C). Finally, the plants were dried at 60 ◦C for 3 hrs in a heating oven (Pol-Eko Apparatures sp.j., Wodzisław Sl ˛ ´ aski, Poland). The dried plants were homogenized using a mechanical blender (Kenwood, Havant, UK), and frozen at −20 ◦C until analysis. The average water content in *Cyperus papyrus*, *Lysimachia nemorum* and *Euonymus europaeus*, determined based on the weight of the sample before and after desiccation, was 75.4%, 64.7%, and 68.5%, respectively.

#### *3.4. Determination of Selected Pharmaceuticals and Endocrine Disrupting Compounds in Treated and Untreated Sewage*

Pharmaceuticals and endocrine disrupting compounds were extracted from treated and untreated sewage using SPE on Oasis HLB cartridges (3 mg, 6 mL) according to a previously optimized and validated procedure [53]. Each cartridge was preconditioned with 3 mL of EtOAc, 3 mL of MeOH, and 3 mL of distilled water adjusted to pH 2 with 1 M HCl. A liquid sample (250 mL of wastewater adjusted to pH 2 with 1 M HCl) was passed through a cartridge at a flow rate of ~5 mL min−1 using a vacuum manifold. After loading the sample, the cartridge was flushed with 10 mL of an MeOH:H2O (1:9, *v*/*v*) mixture and subsequently air-dried under a vacuum for 30 min. The adsorbed analytes were eluted with 6 mL of MeOH and dried completely under nitrogen gas in order to be derivatized. Derivatization was carried out using 100 μL of a mixture of 99% BSTFA/1% TMCS and pyridine (1:1, *v*/*v*) [53]. After shaking for 30 s, the reaction vials were placed in a heating block for 30 min at 60 ◦C. The standards of pharmaceuticals were derivatized using the same procedure. The samples were analyzed using the GCMS-QP 2010 SE Shimadzu System (Shimadzu, Kyoto, Japan) with an AOC-5000 autosampler. The separation of analytes was done using a Zebron ZB-5MSi fused-silica capillary column (30 m, 0.25 mm I.D., 0.25 μm film thickness, Phenomenex). The injection port temperature was 300 ◦C and 1 μL samples were injected in the splitless mode (1 min). The carrier gas was helium (100 kPa). The oven temperature programme was: 120 ◦C for 1 min, from 120 ◦C to 300 ◦C at 6 ◦C/min, and finally, 4 min at 300 ◦C (total 35 min). The transfer line was held at 300 ◦C. The scan time was 0.3 s. The parameters used for identifying analytes: retention time, quantitative ions, and conformation ions, and applied time windows for selected analytes are shown in Table 7.

**Table 7.** Retention parameters (time allowed change ± 0.15 min), time windows, and SIM ions for trimethylsilyl (TMS)-derivatives of target compounds (quantitative ions are marked in bold; confirmation ions with intensity relative to quantitative ions (%)).

#### *3.5. Development of the Analytical Method for Determining Target Compounds in Plant Materials*

An Accelerated Solvent Extraction (ASE) technique with purification of the obtained extracts by SPE was applied for extracting the pharmaceuticals and EDCs from plant tissues. The ASE extraction was performed using a DIONEX ASE 350 (Dionex Corp., Sunnyvale, CA, USA). Three solvent mixtures (MeOH:H2O 1:1 *v*/*v*; EtOH:H2O 1:1 *v*/*v*: ACN:H2O 1:1 *v*/*v*) were applied at two different temperatures (50 ◦C and 80 ◦C) for the ASE extraction of the analytes. Moreover, the obtained extracts, prior to SPE purification, were acidified to pH ~2 as well as being investigated without acidification. In each tested condition, the concentration of the target pharmaceuticals and EDCs in spiked plant samples was 1000 ng/g d.w.

A cellulose filter (19.8 mm, Dionex Corp.) was placed on the bottom of a 33-mL stainless steel extraction cell. The cell was filled with 3 ± 0.01 g of diatomaceous earth (on the cellulose filter). Then, 1 ± 0.01 g of spiked and non-spiked homogenous plant tissues was added. Next, the dead volume of the cell was filled with diatomaceous earth. Each extraction was carried out at constant parameters: heating time 5 min, static time 3 min in 3 cycles, and a 10% purge of 50 s. The extraction pressure was set to 1500 psi. The total extraction time was 18.5 min and the extraction volume was 26 ± 0.1 mL. A total of 5 mL of ASE extract was dissolved in deionized water and subjected to purification using SPE under the conditions presented in Section 3.4. A minimum of three samples for each tested parameter were prepared, and each sample was analyzed a minimum of three times.

#### *3.6. Validation of the Proposed Method for Determining Target Compounds in Plant Species*

The validation of the analytical method for determining target compounds in plant species was carried out using the matrix-matched calibration solutions and working calibration standard solutions in accordance with the guidelines of the International Vocabulary of Metrology [54]. The matrix-matched calibration solutions were prepared by spiking samples with eight different concentrations of pharmaceuticals and endocrine disrupting compounds in a range of 19.5–2500 ng/g d.w. Calibration curves were based on the external method, and they were obtained by plotting the peak area for each analyte against its concentration. The linearity, correlation coefficient (R2), intermediate precision measurement (expressed by RSD, *n* = 3), and mean recovery (MR) were established according to procedures described in our previous paper [55]. Briefly, the mean recovery of the analytical method

was determined based on the known concentrations of target compounds in the tested samples (Cknown) and the concentrations determined by the analysis (Cdetermined) using Equation (1):

$$\mathbf{MR} = (\mathbf{C}\_{\text{determined}} / \mathbf{C}\_{\text{known}}) \times 100\% \tag{1}$$

The method quantification limit (MQL) was determined using Equation (2):

$$\mathbf{MQL} = (\mathbf{IQL} \times 100\%) / (\mathbf{CF} \times \mathbf{AR}) \tag{2}$$

whereas the method detection limit (MDL) using Equation (3):

$$\mathbf{MDL} = \mathbf{MQL}/3\tag{3}$$

where IQL is the instrumental quantification limit, CF is the concentration factor, and AR is the absolute recovery of analytes (%).

The matrix e ffect (ME) and absolute recovery (AR) were determined according to procedures described by Caban et al. [56] using Equation (4) and Equation (5), respectively:

$$\mathbf{ME} = ((\mathbf{B} - \mathbf{D}/\mathbf{A}) - 1) \times 100\% \tag{4}$$

$$\mathbf{AR} = ((\mathbf{C} - \mathbf{D})\mathbf{/A}) \times 100\% \tag{5}$$

where A is the peak area of the analyte recorded for the standard solution, B is the peak area of the analyte recorded for the sample spiked with the target compound after extraction, C is the peak area of the analyte recorded for the sample spiked with the target compound before extraction, and D is the peak area of the analyte recorded for the non-spiked sample (blank sample).

#### *3.7. Application of the Proposed Method for Determining Target Compounds in Hydroponically Cultivated Plants*

The optimized and validated ASE-SPE-GC-MS(SIM) method was used to determine 15 target compounds in 3 species of plants (Papyrus (*Cyperus papyrus*), European spindle (*Euonymus europaeus*), Yellow pimpernel (*Lysimachia nemorum*)) used in the constructed wetlands in Sochaczew MWWTP. These species were chosen due to their best adaptation to growth in the MWWTP. In addition, the mentioned plants exhibit the strongest growth during the growing season, which a ffects the transport of pollutants to plant tissues.

#### *3.8. Evaluation of the E*ff*ectiveness of Removing Pharmaceuticals and Endocrine Disrupting Compounds in MWWTP Sochaczew*

Concentrations of pharmaceuticals and EDCs in treated and untreated sewage were used to determine the elimination e fficiency (EE%) from the wastewater stream in the MWWTP. The elimination efficiency factor was calculated using Equation (6):

$$\text{EE\%} = (\text{C}\_{\text{untreated}} - \text{C}\_{\text{treated}}) / (\text{C}\_{\text{untreated}}) \times 100\% \tag{6}$$

where Cuntreated is the measured concentration of the pharmaceutical in untreated sewage samples, and Ctreated is the measured concentration of the pharmaceutical in treated sewage samples. This parameter allowed for establishing the e ffectiveness of removing pharmaceuticals in a municipal treatment plant supported by constructed wetlands.


**2. Viral metagenomics: understanding the evolutionary history of viruses**

There are many purposes that can be achieved through the use of metagenomics using NGS. Thomas et al. [2] described that this methodology can be a source of genetic information about the possible new biocatalysts or enzymes in cases of bioprospecting; can realize the genomic connections between the function and phylogeny of "non-cultivable" organisms; can identify the evolutionary profiles and associate the function and structure in microbial communities; and also can inference about the new hypotheses of microbial functions.

The Baltimore classification considers the virus taxonomy from seven groups: I (double-stranded DNA viruses), II (single-stranded DNA viruses), III (doublestranded RNA viruses, dsRNA), IV [positive-sense single-stranded RNA viruses, (+) ssRNA], V [negative-sense single-stranded RNA viruses, (−) ssRNA], VI (single-stranded RNA viruses with a DNA intermediate in their life cycle, ssRNA-RT), and VII (double-stranded DNA viruses with an RNA intermediate in their life cycle, dsDNA-RT). However, metagenomics approaches have contributed to understand the real universal viral taxonomy.

Since the RNA viruses are the most abundant to infect eukaryotes in general and all these viruses contain a specific gene, the RNA-dependent RNA polymerase (RdRp), responsible to produce the protein for their replication, it was possible to reconstruct their evolutionary history. Using 4617 different RdRps, they found five key subdivisions, two inclosing dsRNA and (−) ssRNA viruses, the other one containing + ssRNA and dsRNA, and two including only (+) ssRNA viruses. In these analyzes, it was showed that the (+) ssRNA viruses possibly have had a single ancestor and that the dsRNA viruses have emerged from (+) ssRNA in two independent events and the (−) ssRNA and could have emerged later from dsRNA. In addition, phylogenetic analysis including other genes showed the broad horizontal transference between the hosts remotely related, including between animals and plants. All these findings allow the continuous update of the viruses' arrangement by International Committee on Taxonomy of Viruses (ICTV) [3]. Considering this continuous host-change, also analyzed from diversity of data previously unavailable and now discovered by metagenomics assays, possibly, the evolution of RNA viruses is associated with the evolutionary history of the host, which dates from hundreds of millions of years ago, from the ocean to the terrestrial environment. In this sense, it should be imprudent to associate the origin of some RNA viruses' families of vertebrates from mosquitoes and ticks [4].

In general, when unrecognized zoonotic viral pathogens emerge from wildlife, it can induce a strong impact on the public health and generate a pandemic risk. In these cases, there are no molecular or serological diagnostic assays specific available for detecting them and the metagenomic appears like the strategy unique to start the developing of new diagnostic test. Temmam et al. [5], in a review paper, already suggested that to predict emerging zoonotic infections always have been an important challenge for public health. Furthermore, the viral metagenomics was pointed by them as the promising alternative to surveillance, especially to identify viromas in selected animals and arthropods closely in contact with humans.

**275**

*Metagenomics and Pandemic Viruses*

*DOI: http://dx.doi.org/10.5772/intechopen.93687*

perspective action from One Health.

ing diseases or even for emerging infectious diseases.

as real-time PCR and high-performance sequencing NGS.

amplification (LAMP), and conventional PCR, among others.

For the diagnosis of viral diseases, the gold standard test is the viral isolation. However, it has the disadvantage of being laborious, consuming many days, in addition to the biosecurity issues of handling in the laboratory. Since the 1980s, with the advent of molecular techniques of polymerase chain reaction (PCR) and sequencing, the scientific community has gradually adopted these tests for the investigation and pathogens diagnosis, mainly the emerging ones. The international scientific community's decision to sequence the human genome provided the rapid evolution of all molecular techniques and allowed the emergence of techniques such

Before the appreciation of metagenomics into the scientific community, the molecular diagnostic methods most common on the routine were practically performed using the PCR system and its variations and Sanger sequencing. Therefore, several commercial molecular diagnostic tests to detect viral, bacterial, and fungal pathogens were made available using real-time PCR, loop-mediated isothermal

These approaches are increasingly used to detect new viral pathogens as well as to generate complete genomes of non-cultivable viruses. The *in silico* identification of complete viral genomes from sequence data would allow a rapid phylogenetic characterization of these new viruses [6]. Thus, the methodology emerges as an alternative for the discovery of new viral agents in animals, allowing the expansion of knowledge of viral diversity as well as of potentially emerging zoonosis. The identified material can provide insights into the evolution and viruses phylogenies. These data, associated with studies on the biology of the hosts, can contribute to the understanding of the eco-epidemiology of several viruses that, through complementary analyzes, help in the identification of potentially pathogenic agents, a

Important advances in the knowledge of microbial diversity through metagenomic tools in several ecosystems have allowed to associate the sequence data with the complex biological characteristics of an ecosystem, be it the human intestine, for example, whether aquatic or terrestrial environmental. This can be an essential source to understanding the microbial ecology and biogeography. Different works of metagenomics have shown that the biogeography of viruses, in general, is associated with the characteristics of habitats. As such, similar viral biogeography can be found in similar habitats that can be geographically far. On the other hand, also was identified substantial sharing of the human viroma between unrelated population and widespread viral quasi-species distinctly dissimilar habitats [7]. So, is really important to implement the metagenomic assay in several places around the world in order to deepen the understanding of this complex ecological dynamic. There are many antibiotics and antiviral molecules produced in these ecosystems. To identify the biosynthetic origin of these drugs can improve treatment alternatives for exist-

Viromas of different animal species as well as different human organs have been obtained through this methodological approach. Brotman et al. [8] described the temporal relationship between vaginal microbiota and detection of human papilloma virus (HPV). A small DNA virus, the Torque Teno Virus (TTV), was unexpectedly found in samples from patients with ophthalmitis (negative bacterial and fungal cultures) [9]. Enteric metaviroma of shrews (genus *Crocidura*, one of nine genera of the shrew subfamily *Crocidurinae*), small insectivorous mammals similar to rodents, were determined and identified with new insect and virus viruses, including cyclovirus, picornavirus, and picorna-like virus. In addition, several cycloviruses, including human variants, were detected in wild shrews with a high prevalence rate. Complete or almost complete genomic sequences of these new viruses were determined and subjected to genetic characterization [10, 11].

#### *Metagenomics and Pandemic Viruses DOI: http://dx.doi.org/10.5772/intechopen.93687*

*Genetic Variation*

the pandemic time.

**viruses**

directly from samples without previous amplification—is able to reveal the hidden microbial diversity. Metagenomes' work aims to contribute to the facilitation of epidemiological studies through the adoption of simple effective strategies for the pathogens' identification, understanding the evolutionary dynamic of them before

**2. Viral metagenomics: understanding the evolutionary history of**

inference about the new hypotheses of microbial functions.

understand the real universal viral taxonomy.

There are many purposes that can be achieved through the use of metagenomics using NGS. Thomas et al. [2] described that this methodology can be a source of genetic information about the possible new biocatalysts or enzymes in cases of bioprospecting; can realize the genomic connections between the function and phylogeny of "non-cultivable" organisms; can identify the evolutionary profiles and associate the function and structure in microbial communities; and also can

The Baltimore classification considers the virus taxonomy from seven groups: I (double-stranded DNA viruses), II (single-stranded DNA viruses), III (doublestranded RNA viruses, dsRNA), IV [positive-sense single-stranded RNA viruses, (+) ssRNA], V [negative-sense single-stranded RNA viruses, (−) ssRNA], VI (single-stranded RNA viruses with a DNA intermediate in their life cycle, ssRNA-RT), and VII (double-stranded DNA viruses with an RNA intermediate in their life cycle, dsDNA-RT). However, metagenomics approaches have contributed to

Since the RNA viruses are the most abundant to infect eukaryotes in general and all these viruses contain a specific gene, the RNA-dependent RNA polymerase (RdRp), responsible to produce the protein for their replication, it was possible to reconstruct their evolutionary history. Using 4617 different RdRps, they found five key subdivisions, two inclosing dsRNA and (−) ssRNA viruses, the other one containing + ssRNA and dsRNA, and two including only (+) ssRNA viruses. In these analyzes, it was showed that the (+) ssRNA viruses possibly have had a single ancestor and that the dsRNA viruses have emerged from (+) ssRNA in two independent events and the (−) ssRNA and could have emerged later from dsRNA. In addition, phylogenetic analysis including other genes showed the broad horizontal transference between the hosts remotely related, including between animals and plants. All these findings allow the continuous update of the viruses' arrangement by International Committee on Taxonomy of Viruses (ICTV) [3]. Considering this continuous host-change, also analyzed from diversity of data previously unavailable and now discovered by metagenomics assays, possibly, the evolution of RNA viruses is associated with the evolutionary history of the host, which dates from hundreds of millions of years ago, from the ocean to the terrestrial environment. In this sense, it should be imprudent to associate the origin of

some RNA viruses' families of vertebrates from mosquitoes and ticks [4].

in selected animals and arthropods closely in contact with humans.

In general, when unrecognized zoonotic viral pathogens emerge from wildlife, it can induce a strong impact on the public health and generate a pandemic risk. In these cases, there are no molecular or serological diagnostic assays specific available for detecting them and the metagenomic appears like the strategy unique to start the developing of new diagnostic test. Temmam et al. [5], in a review paper, already suggested that to predict emerging zoonotic infections always have been an important challenge for public health. Furthermore, the viral metagenomics was pointed by them as the promising alternative to surveillance, especially to identify viromas

**274**

For the diagnosis of viral diseases, the gold standard test is the viral isolation. However, it has the disadvantage of being laborious, consuming many days, in addition to the biosecurity issues of handling in the laboratory. Since the 1980s, with the advent of molecular techniques of polymerase chain reaction (PCR) and sequencing, the scientific community has gradually adopted these tests for the investigation and pathogens diagnosis, mainly the emerging ones. The international scientific community's decision to sequence the human genome provided the rapid evolution of all molecular techniques and allowed the emergence of techniques such as real-time PCR and high-performance sequencing NGS.

Before the appreciation of metagenomics into the scientific community, the molecular diagnostic methods most common on the routine were practically performed using the PCR system and its variations and Sanger sequencing. Therefore, several commercial molecular diagnostic tests to detect viral, bacterial, and fungal pathogens were made available using real-time PCR, loop-mediated isothermal amplification (LAMP), and conventional PCR, among others.

These approaches are increasingly used to detect new viral pathogens as well as to generate complete genomes of non-cultivable viruses. The *in silico* identification of complete viral genomes from sequence data would allow a rapid phylogenetic characterization of these new viruses [6]. Thus, the methodology emerges as an alternative for the discovery of new viral agents in animals, allowing the expansion of knowledge of viral diversity as well as of potentially emerging zoonosis. The identified material can provide insights into the evolution and viruses phylogenies. These data, associated with studies on the biology of the hosts, can contribute to the understanding of the eco-epidemiology of several viruses that, through complementary analyzes, help in the identification of potentially pathogenic agents, a perspective action from One Health.

Important advances in the knowledge of microbial diversity through metagenomic tools in several ecosystems have allowed to associate the sequence data with the complex biological characteristics of an ecosystem, be it the human intestine, for example, whether aquatic or terrestrial environmental. This can be an essential source to understanding the microbial ecology and biogeography. Different works of metagenomics have shown that the biogeography of viruses, in general, is associated with the characteristics of habitats. As such, similar viral biogeography can be found in similar habitats that can be geographically far. On the other hand, also was identified substantial sharing of the human viroma between unrelated population and widespread viral quasi-species distinctly dissimilar habitats [7]. So, is really important to implement the metagenomic assay in several places around the world in order to deepen the understanding of this complex ecological dynamic. There are many antibiotics and antiviral molecules produced in these ecosystems. To identify the biosynthetic origin of these drugs can improve treatment alternatives for existing diseases or even for emerging infectious diseases.

Viromas of different animal species as well as different human organs have been obtained through this methodological approach. Brotman et al. [8] described the temporal relationship between vaginal microbiota and detection of human papilloma virus (HPV). A small DNA virus, the Torque Teno Virus (TTV), was unexpectedly found in samples from patients with ophthalmitis (negative bacterial and fungal cultures) [9]. Enteric metaviroma of shrews (genus *Crocidura*, one of nine genera of the shrew subfamily *Crocidurinae*), small insectivorous mammals similar to rodents, were determined and identified with new insect and virus viruses, including cyclovirus, picornavirus, and picorna-like virus. In addition, several cycloviruses, including human variants, were detected in wild shrews with a high prevalence rate. Complete or almost complete genomic sequences of these new viruses were determined and subjected to genetic characterization [10, 11].

Metagenomic analyzes have shown that bats can be reservoirs to several species of RNA viruses. Many of these viruses are highly pathogenic and exhibit broad cell tropism, being able to infect a wide variety of cells and hosts (Hendra virus, HEV; Nipah virus, NIV; Ebola virus, EBOV; Meddle East Respiratory Syndrome virus, MERS; Severe Acute Respiratory Syndrome Coronavirus type 1, SARS-CoV; Severe Acute Respiratory Syndrome Coronavirus type 2, SARS-CoV-2). Viruses such as HEV, rabies virus (RABV), and NIV show high genomic conservation within their bat hosts, which suggests that they are under strong selective restrictions [7].

Considering that bats can be host a great viruses diversity and that little is known about their viroma, Dacheux et al. [12] determined the viral diversity of five different French insectivorous bats species (nine specimens). They detected viruses from many viral families that infect bacteria, plants, fungi, insects, and vertebrate animals and mammals (Retroviridae, Herpesviridae, Bunyaviridae, Poxviridae, Flaviviridae, Reoviridae, Bornaviridae, and Picobirnaviridae). They described new mammalian viruses, including rotavirus, gammaretrovirus, bornavirus, and bunyavirus, as well as the first nairovirus identification in bats.

Bat metaviroma from Myanmar (China) revealed the presence of new mammalian viruses. The analysis was conducted using organs of 853 bats of six species, identifying known sequences belonging to 24 viral families. Of the viral contigs (2% of the total sequences), 45% were related to vertebrate viruses, 28% to insect viruses, 27% to phages, and 95 contigs to plant viruses. The validation performed by PCR followed by phylogenetic analyzes led to the discovery of some new bat viruses of the genera *Mamastrovirus*, *Bocavirus*, *Circovirus*, *Iflavirus*, and *Orthohepadnavirus* [13].

In African fruit bats populations (*Eidolon helvum*), it was identified by metagenomics a great abundance and diversity of new herpes and papillomavirus. The authors also described a new adenovirus and detected, for the first time in Chiroptera, sequences of a poxvirus closely related to contagious mollusk [14].

Herman Tse et al. [15], carrying out studies of 156 apparently healthy rectal swab samples from bats also using a metagenomic approach, discovered a new Papillomavirus strain, *Miniopterus schreibersii Papillomavirus type 1* (MscPV1), with a 7.5 kb long genome. In addition to the new agent characterization, the researchers also carried out several phylogenetic studies that allowed us to infer that MscPV1 and *Erethizon dorsatum* papillomavirus (EdPV1) are more closely related, with an approximate divergence of 60.2–91.9 million years.

He and collaborators (2014) identified hundreds of sequences related to alpha and Betacoronavirus sequencing 268 rectal swabs from 68 bats from four counties in Yunnan province. They also reported the complete genome of a new SARS-CoV (LYRa11) containing 29,805 nucleotides in length, 13 ORFs, 91% nucleotide identity with human and civet SARS CoVs, 89% similarity to another bat SARS-CoV-like. One of the most interesting reports was obtained through recombination analyzes. Such analyzes indicated that LYRa11 is a probable recombinant descendant of parental strains evolved from SARS-CoVs-like bats.

An outbreak of respiratory infection of unknown origin began to manifest in many people in Wuhan-Hubei-China in late 2019. Difficulties in controlling the disease by conventional methods of treatment suggested a new infectious disease with viral characteristics and effective transmission of person to person. A short time later and with the support of the international scientific community, it was confirmed that the new disease called Coronavirus Disease 2019 (COVID-19) was caused by a new coronavirus initially called 2019 Novel Coronavirus (2019-nCoV). It is not the first time that a human coronavirus has caused a major disease with risk of global spread. Severe Acute Respiratory Syndrome Coronavirus type 1 (SARS-CoV-1) and, in 2013, Middle East Respiratory Syndrome (MERS-CoV) emerged,

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*Metagenomics and Pandemic Viruses*

SARS-CoV-1.

for preventing a pandemic.

*DOI: http://dx.doi.org/10.5772/intechopen.93687*

both in two different places, of zoonotic origin and evolved from bats having intermediary animals as hosts, the civets and camelids, respectively. Using metagenomics approaches, in a few days, the scientific community has managed to obtain the complete genome of this virus. Based on genetic, evolutionary and molecular studies, the 2019-nCoV virus was named Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), a Sarbecovirus, Betacoronavirus, brother of

However, it is an important question without conclusive answer: what is the real reservoir for SARS-CoV-2? Until now, no virus isolation was successful from the none animal source but Lam et al. [16], by metagenomics approaches, identified several pangolin coronavirus lineages suggesting that these animals could be considered as possible hosts in the emergence of new coronaviruses and must be

In the COVID-19 pandemic, until August 2020, more than 20,000,000 people were infected and almost 800,000 death in more than 190 countries that detected the virus [17]. Peddu et al. [18] described the metagenomic analysis as a good alternative to investigate and to response to this and future viral pandemics; they evaluated, by metagenomic sequencing, positive and negative samples from Seattle, WA. Part of these samples showed superinfection or colonization with human parainfluenza virus 3 or *Moraxella* species, emphasizing to be essential to conduct molecular testes using a viral respiratory panel. In addition, negative samples for SARS-CoV-2 by RT-PCR were positive for Rhinovirus A and C, showing that the metagenomic analysis of these SARS-CoV-2 negative samples was able to identify

Did we learn from the past epidemics? Are we prepared for the worst? Gonzalez et al. [19] stablished these key questions related our learning from the humanity history. According to them, the ultimate goal should be develop a resilient global health infrastructure; like the bio-surveillance using geographic information systems (GIS) and metagenomics to trace the molecular changes in pathogens during their emergence, and mathematical models to assess risk should be "critical point"

**3. Epidemiological surveillance in bats by metagenomic approaches:**

In recent years, emerging and serious infectious diseases have caused worldwide fear. It is also known that many of these diseases are caused by viruses from bats, such as Ebola, Marburg, SARS coronavirus (SARS-CoV), MERS coronavirus (MERS-CoV), Nipah (NIV) and Hendra (HEV) [20], and nowadays, SARS-CoV-2. The growing recognition of the bats importance as reservoirs for new diseases is due to the fact that they constitute 20% of known mammal species, have unique and diverse lifestyles, including the ability to fly, often presenting gregarious social structures achieving incredible abundance and densities (some cave bats reaching

As more information has been obtained regarding the factors or causes of emergence, there has been an expectation that it is possible to predict the emergence of new pathogens. These and other factors have significantly increased the demand for new viral pathogens, especially at the human-animal interface in

With the exception of studies focusing on lyssavirus, most viruses' investigations in bats have been limited to one particular zoonotic agent involved in an outbreak of geographically localized disease [23]. COVID-19 showed the need to form an

**a powerful tool for conducting large-scale studies**

up to 500 individuals per square meter) and long life [21].

species of wild and domestic animals [22].

removed from wet markets to prevent zoonotic transmission.

candidate etiological agents for the respiratory signs in those patients.

#### *Metagenomics and Pandemic Viruses DOI: http://dx.doi.org/10.5772/intechopen.93687*

*Genetic Variation*

*Orthohepadnavirus* [13].

Metagenomic analyzes have shown that bats can be reservoirs to several species of RNA viruses. Many of these viruses are highly pathogenic and exhibit broad cell tropism, being able to infect a wide variety of cells and hosts (Hendra virus, HEV; Nipah virus, NIV; Ebola virus, EBOV; Meddle East Respiratory Syndrome virus, MERS; Severe Acute Respiratory Syndrome Coronavirus type 1, SARS-CoV; Severe Acute Respiratory Syndrome Coronavirus type 2, SARS-CoV-2). Viruses such as HEV, rabies virus (RABV), and NIV show high genomic conservation within their bat hosts, which suggests that they are under strong selective restrictions [7]. Considering that bats can be host a great viruses diversity and that little is known about their viroma, Dacheux et al. [12] determined the viral diversity of five different French insectivorous bats species (nine specimens). They detected viruses from many viral families that infect bacteria, plants, fungi, insects, and vertebrate animals and mammals (Retroviridae, Herpesviridae, Bunyaviridae, Poxviridae, Flaviviridae, Reoviridae, Bornaviridae, and Picobirnaviridae). They described new mammalian viruses, including rotavirus, gammaretrovirus, bornavirus, and

bunyavirus, as well as the first nairovirus identification in bats.

approximate divergence of 60.2–91.9 million years.

parental strains evolved from SARS-CoVs-like bats.

Bat metaviroma from Myanmar (China) revealed the presence of new mammalian viruses. The analysis was conducted using organs of 853 bats of six species, identifying known sequences belonging to 24 viral families. Of the viral contigs (2% of the total sequences), 45% were related to vertebrate viruses, 28% to insect viruses, 27% to phages, and 95 contigs to plant viruses. The validation performed by PCR followed by phylogenetic analyzes led to the discovery of some new bat viruses of the genera *Mamastrovirus*, *Bocavirus*, *Circovirus*, *Iflavirus*, and

In African fruit bats populations (*Eidolon helvum*), it was identified by metagenomics a great abundance and diversity of new herpes and papillomavirus. The authors also described a new adenovirus and detected, for the first time in Chiroptera, sequences of a poxvirus closely related to contagious mollusk [14]. Herman Tse et al. [15], carrying out studies of 156 apparently healthy rectal swab samples from bats also using a metagenomic approach, discovered a new Papillomavirus strain, *Miniopterus schreibersii Papillomavirus type 1* (MscPV1), with a 7.5 kb long genome. In addition to the new agent characterization, the researchers also carried out several phylogenetic studies that allowed us to infer that MscPV1 and *Erethizon dorsatum* papillomavirus (EdPV1) are more closely related, with an

He and collaborators (2014) identified hundreds of sequences related to alpha and Betacoronavirus sequencing 268 rectal swabs from 68 bats from four counties in Yunnan province. They also reported the complete genome of a new SARS-CoV (LYRa11) containing 29,805 nucleotides in length, 13 ORFs, 91% nucleotide identity with human and civet SARS CoVs, 89% similarity to another bat SARS-CoV-like. One of the most interesting reports was obtained through recombination analyzes. Such analyzes indicated that LYRa11 is a probable recombinant descendant of

An outbreak of respiratory infection of unknown origin began to manifest in many people in Wuhan-Hubei-China in late 2019. Difficulties in controlling the disease by conventional methods of treatment suggested a new infectious disease with viral characteristics and effective transmission of person to person. A short time later and with the support of the international scientific community, it was confirmed that the new disease called Coronavirus Disease 2019 (COVID-19) was caused by a new coronavirus initially called 2019 Novel Coronavirus (2019-nCoV). It is not the first time that a human coronavirus has caused a major disease with risk of global spread. Severe Acute Respiratory Syndrome Coronavirus type 1 (SARS-CoV-1) and, in 2013, Middle East Respiratory Syndrome (MERS-CoV) emerged,

**276**

both in two different places, of zoonotic origin and evolved from bats having intermediary animals as hosts, the civets and camelids, respectively. Using metagenomics approaches, in a few days, the scientific community has managed to obtain the complete genome of this virus. Based on genetic, evolutionary and molecular studies, the 2019-nCoV virus was named Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), a Sarbecovirus, Betacoronavirus, brother of SARS-CoV-1.

However, it is an important question without conclusive answer: what is the real reservoir for SARS-CoV-2? Until now, no virus isolation was successful from the none animal source but Lam et al. [16], by metagenomics approaches, identified several pangolin coronavirus lineages suggesting that these animals could be considered as possible hosts in the emergence of new coronaviruses and must be removed from wet markets to prevent zoonotic transmission.

In the COVID-19 pandemic, until August 2020, more than 20,000,000 people were infected and almost 800,000 death in more than 190 countries that detected the virus [17]. Peddu et al. [18] described the metagenomic analysis as a good alternative to investigate and to response to this and future viral pandemics; they evaluated, by metagenomic sequencing, positive and negative samples from Seattle, WA. Part of these samples showed superinfection or colonization with human parainfluenza virus 3 or *Moraxella* species, emphasizing to be essential to conduct molecular testes using a viral respiratory panel. In addition, negative samples for SARS-CoV-2 by RT-PCR were positive for Rhinovirus A and C, showing that the metagenomic analysis of these SARS-CoV-2 negative samples was able to identify candidate etiological agents for the respiratory signs in those patients.

Did we learn from the past epidemics? Are we prepared for the worst? Gonzalez et al. [19] stablished these key questions related our learning from the humanity history. According to them, the ultimate goal should be develop a resilient global health infrastructure; like the bio-surveillance using geographic information systems (GIS) and metagenomics to trace the molecular changes in pathogens during their emergence, and mathematical models to assess risk should be "critical point" for preventing a pandemic.


**Longitudinal Displacement Behavior and Girder End Reliability of a Jointless Steel-Truss Arch Railway Bridge during Operation**

#### **Hanwei Zhao 1, Youliang Ding 1,\*, Satish Nagarajaiah 2 and Aiqun Li 3**

Received: 4 May 2019; Accepted: 28 May 2019; Published: 30 May 2019

**Abstract:** The long length and complex service load form conflicts with the low limits of longitudinal and transverse displacements of jointless bridge design. The longitudinal displacements of the Nanjing Dashengguan Yangtze River Bridge, a jointless steel-truss arch railway bridge, and its girder end reliability are investigated in this article. The time–frequency characteristics of the longitudinal displacements of bearings and expansion joints are analyzed using the empirical wavelet transform. The long-term characteristics of the longitudinal displacements of bearings and expansion joints in the operation period are explored. Furthermore, the relative transverse displacements of the bridge girder end are calculated using longitudinal displacement monitoring data. The mechanical behaviors of the expansion device under relative transverse displacements are studied. The reliability of expansion devices and crossing trains under the effects of relative transverse displacements is studied using kernel density estimation. The main results demonstrate that: (1) The longitudinal displacements of bearings and expansion joints are mainly influenced by environmental temperature. (2) The maximum relative transverse displacement of the expansion joint is close to 1 mm in long-term bridge operation, with the transverse rail deflection at the expansion device approaching 1 mm, which reduces the stability of cross high-speed trains.

**Keywords:** structural health monitoring; jointless bridge; high-speed railway; bearing; expansion device; displacement analysis


**4.2 Calcium-channel blockers**

Topical application of calcium-channel blockers has been proven to effectively heal anal fissures with a lower risk of side effects [17]. Topically applied 0.5% nifedipine has been found to have healing rates of 93% in a duration of 19-month follow-up [18]. Also, Khan et al. have proved significantly higher healing rates (80.4%) with 2% topical diltiazem compared to GTN application [19]. Similarly, 0.5% topical minoxidil has been shown as equally effective as diltiazem [20].

#### **4.3 Botulinum toxin**

Botulinum toxin is an exotoxin produced by *Clostridium botulinum,* and its injection prevents the release of acetylcholine from the presynaptic nerve terminals, thus results resulting in temporary muscle paralysis. The first use of botulinum toxin in treating anal fissure was described in 1993 by Jost and Schimrigk [21, 22].

Although there is no standardized treatment with botulinum toxin regarding the dose and injection site, it is commonly injected directly into the internal anal sphincter on either side of the midline, with doses varying from 5 to 100 units [23, 24]. Pilkington et al. have revealed no significant differences between unilateral and bilateral injections in healing and fissure pain relief in a randomized prospective study [25]. In a retrospective review of patients who have been treated with high-dose (80–100 IU) and low-dose (20–40 IU) botulinum toxin, recurrence rates have been found significantly lower in a high-dose group during a mean follow-up of 25 months [26]. However, a meta-analysis has demonstrated no dose-dependent efficiency [27].

Several comparative studies have investigated the healing rates and symptomatic relief after botulinum toxin and topical agents [28–32]. Sajid et al. have shown that botulinum toxin injection has had similar healing rates with GTN but fewer side effects [33]. Also, another study has demonstrated that overall cure rates have been similar between diltiazem (53%), GTN (54%), and botulinum toxin (51%) [34]. A guideline published in 2017 has stated that botulinum toxin injection has similar results with topical agents as first-line therapy and modest improvement in healing rates as second-line therapy following treatment with topical agents [10].

The significant drawbacks of botulinum toxin injection are the risk of incontinence and its temporary effectiveness that usually lasts 3–6 months [35, 36]. Moreover, there are still unanswered questions: the following step when botulinum toxin fails if the second injection should be performed, the interval for repeat

*Sphincterotomy is the Gold-Standard Treatment of Chronic Anal Fissure: But How Should it be… DOI: http://dx.doi.org/10.5772/intechopen.104109*

injection, and the timing of surgery. A recent study has discussed some of those issues among colorectal surgeons on practice parameters of botulinum toxin treatment [37]. It has been shown that more than half of the clinicians perform the second injection in case of persistence of symptoms and recurrence, and the interval for repeat injection has usually been more than 2 months.


**6. Conclusions**

Solid mining wastes including host rocks and tailings must be managed during the whole period of operation. Some of them can be utilized for construction and other activities; however, some of them may also cause severe environmental impacts. Moreover, unexpected occasions can be happened individually even routine monitoring program has been carried out during all time of the operation. Therefore, all concerns must be taken into account since mining plan is developed initially. All mining wastes generated from each step of operation should be tested and put into the long term monitoring plans. Besides, all types of top soil and host rock must be sampled systematically for analyses of AMD and heavy metals prior to waste categorization and placement design. Dealing with natural materials, both rock and top soil in this case, variety of chemical composition may lead to complexity. Many of these chemicals are stable and unable to leaching out; however, just in case of some leachable form exiting, it may turn to harmfulness and difficulty of operation. Protection and prevention should therefore be planned well to keep mining operation moving smoothly and clearly to be inspected.

Regarding to rock waste and top soil, both AMD and heavy metal have become the most concerns for mining and environmental management. Some materials are unlikely to cause AMD but they contain high amounts of heavy metals that seem to be well leachable. These materials must be placed away from AMD potential wastes. Otherwise, mixing up of both types can threaten the surrounding area leading to widely land contamination. Neutralizer should be provided during the placement process. Limestone has been used as natural neutralizer which is easy to find and quite cheap. Liners should also be provided particularly for waste materials trending to have potentials of acid generation and/or heavy metal contaminants. Both natural and artificial materials can be used in individual cases, based on nature of the site and characteristics of mining waste. Cares must be taken very well during operation as well as monitoring program must be carried out regularly. It would also be notified that unexpected events can occur all the time; therefore, detailed investigations have to be initiated anytime whenever unusual signature is reveled either by regular monitoring or accident finding.


**1.7 Comparing different management approaches**

When viewed on a spectrum, all three water management approaches – supply management, demand management, and the soft path – represent incremental steps toward sustainability. However, far from being a simple progression some key characteristics distinguish them. The most significant difference is the view of the limits of water available for human use and of the nature of the choices that should determine how we manage water. Figure 2 is an idealized sketch of the different paths that will result from following each of the three approaches.

Water demand management seeks primarily water efficiency, and is often focused on the implementation of cost-effective ways to achieve the same service with less water. Demand management options have been known for years, but with water prices kept artificially low, little incentive existed for widespread adoption (Brandes et al, 2005).

Though demand management has always been part of how water system operate, it is typically treated as a secondary or temporary measure needed until additional supplies are secured. Changing our water management paradigm requires that demand management become the primary focus. With rampant growth and the uncertainty of climate change, reducing the demand for water is our best "source" of "new" water (Brandes et al, 2005).

The soft path approach changes the conception of "water." Instead of being viewed simply as an end product, water becomes the means to accomplish specific tasks, such as sanitation or agricultural production. Conventional demand management asks the question "How" –

4. The soft path requires water agency or company personnel to interact closely with water users and to effectively engage community groups in water management. Users need help determining how much water of various qualities they need, and to capture low-cost opportunities. In contrast, the hard path is governed by an engineering

5. The soft path recognizes that ecological health and the activities that depend on it (e.g., fishing, swimming, tourism, delivery of clean raw water to downstream users) are water-based services demanded, at least in part, by their customers, not just third parties. Water that is not abstracted, treated, and distributed is being used productively to meet these demands. Water is part of a natural infrastructure that stores and uses water in productive ways. The hard path, by ignoring this natural infrastructure, often reduces the amount and quality of water available for use. The hard path defines infrastructure as built structures, rather than separating it into built and natural

6. The soft path recognizes the complexity of water economics, including the power of economies of scope. The hard path looks at projects, revenues, and economies of scale. An economy of scope exists when a combined decision-making process would allow specific services to be delivered at lower cost than would result from separate decisionmaking processes. For example, water suppliers, flood control departments, and landuse authorities can often reduce the total cost of services to their customers by accounting for the interactions that none of the authorities can account for alone. This requires thinking about landuse patterns, flood control, and water demands in an

When viewed on a spectrum, all three water management approaches – supply management, demand management, and the soft path – represent incremental steps toward sustainability. However, far from being a simple progression some key characteristics distinguish them. The most significant difference is the view of the limits of water available for human use and of the nature of the choices that should determine how we manage water. Figure 2 is an idealized sketch of the different paths that will result from following

Water demand management seeks primarily water efficiency, and is often focused on the implementation of cost-effective ways to achieve the same service with less water. Demand management options have been known for years, but with water prices kept artificially low,

Though demand management has always been part of how water system operate, it is typically treated as a secondary or temporary measure needed until additional supplies are secured. Changing our water management paradigm requires that demand management become the primary focus. With rampant growth and the uncertainty of climate change, reducing the demand for water is our best "source" of "new" water (Brandes et al, 2005).

The soft path approach changes the conception of "water." Instead of being viewed simply as an end product, water becomes the means to accomplish specific tasks, such as sanitation or agricultural production. Conventional demand management asks the question "How" –

little incentive existed for widespread adoption (Brandes et al, 2005).

mentality that is accustomed to meeting generic needs.

components.

integrated, not isolated, way.

each of the three approaches.

**1.7 Comparing different management approaches**

How can we get more from each drop of water? Water soft paths also ask the question "Why" – Why should we use water to do this at all? (Brandes et al, 2005).

Fig. 2. Planning for the future with a soft path approach. (Brandes et al, 2005)

### **1.8 One continuing gap in soft path analyses**

Probably the most legitimate criticism of energy soft path studies was that they neglected issues of equity. This led to many comments about the need to introduce environmental justice as an explicit element of policy, regardless of the nature of the policy. If that criticism was true of energy, it is even more so of water. The inequities in water and land distribution around the world are sizable and, as a result of misguided policies that promote centralization and privatization, they seem to be growing. As it is, poor people in urban areas commonly pay 10 times as much per litre for water of questionable quality as do richer people for water of good quality; and poor subsistence farmers sometimes (especially if they are women) get no water at all when commercial farms are adequately supplied (Webb et al , and Koppen et al in Brooks et al 2004). Though it is almost unquestionably true that water soft paths would improve the situation for poor people around the world, water soft paths by themselves are not sufficient. As emphasized by staff at the International Water Management Institute (IWMI) in Sri Lanka, water policies must be explicitly "pro-poor" and "pro-women". Urban water systems in developing countries are notoriously leaky if one compares the difference between water put into the system and water that reaches registered consumers. Some of those leaks are true losses, but some (highly indeterminate) portion is "stolen" or redirected to illegal taps, which may serve hundreds of poor residents. Fixing the "leaks," another common recommendation, should be undertaken only if coupled with additional, and possibly free, taps in low-income neighborhoods. In short, greater efficiency for water needs to be tempered with concern for equity, and this concern must be introduced explicitly in soft path analyses.

Water Soft Path Analysis – Jordan Case 295

Fig. 3. Spatial distribution of rainfall in Jordan (National Water Master Plan, 2004)

featured as a high priority in the National Agenda.

by Beautmont (2002) as follows:

The water challenge in Jordan stands as a major threat confronting human development and poverty alleviation. For this reason, the enhancement of water resource management is

A description of how serious the water situation is in Jordan is presented in a paper written

Of all the countries in the Middle East it is Jordan which faces the greatest water problems (Salameh & Bannayan,; Beaumont in Beautmont, 2002). To meet its predicted urban water demand of 832 million cubic meters by 2025 would require 113% of its current irrigation use (1990s). In other words even if it reallocates all the irrigation water which was being used in the 1990s there would not be sufficient water to meet the expected demand. When figures on renewable water resources are examined the position becomes even more serious. It can be seen that Jordan has an internal renewable water resource base of 680 million cubic meters and a total natural water resource base of 880 million cubic meters. Yet in the 1990s withdrawals were 984 million cubic meters, which is well in excess of the total natural water