**6. Conclusion**

Despite its contemporariness, Mozambique's Land Law is failing to guarantee secure tenure to land for its local communities, especially in areas perceived to be valuable for agriculture or biofuel production. This is primarily because of the government's inadequate political will to enforce the land law's statutes; ineffective civil society to protect communities against the booming private interest in land for investment in agribased businesses; blind loyalty of community members to their


**1. Introduction**

Esophageal cancer is one of the most fatal cancers worldwide as it was ranked ninth for cancer incidence and sixth for cancer death in 2013. In 2013, there were 442,000 new cases of esopha‐ geal cancer and 440,000 deaths [1]. There are two main histologic subtypes of esophageal cancer: squamous cell carcinoma and adenocarcinoma, each one of them is related to several risk factors. Among them, modifiable lifestyle factors, such as alcohol consumption, tobacco use, and nutrition should be considered as key points in order to prevent esophageal cancer.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2017 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Excess alcohol consumption and consumption of hot food and beverages increase the risk of esophageal squamous cell carcinoma, whereas many components of Western type diet, such as red and processed meat increase the risk of esophageal adenocarcinoma [2–4]. Moreover, obesity, especially central type, and gastroesophageal reflux disease are risk factors toward developing esophageal adenocarcinoma [5, 6]. On the other hand, healthy dietary habits could be a shield against some types of esophageal cancer [7], while nutritional support could be beneficial for the management of these patients after cancer diagnosis.

Esophageal cancer is commonly associated with malnutrition and impaired nutritional intake. Nutritional management of these patients may differ according to the type of therapy and stage of disease, in order to alleviate symptoms, ameliorate nutritional status, and improve quality of life. Furthermore, cancer cachexia affects a great percentage of esophageal can‐ cer patients emerging as a significant factor the multidisciplinary team should deal with [8]. Regarding the perioperative care, the proper type of feeding (i.e. enteral/parenteral nutrition (EN/PN), immunonutrition, oral supplements, etc.) as well as the right time of feeding is a matter of controversy due to lack of consistent evidence for patients undergoing esophagec‐ tomy [9]. Special nutritional needs in the long run are also of great significance for patients with both resectable and unresectble disease, bearing in mind that the majority of these patients strive to meet their caloric and protein needs. Considering the treatment approach, nutritional screening and assessment leads to early detection of malnourished patients in need of nutritional support. Taking into account patient's specific needs helps to choose the most suitable routes of delivering nutritional support (nutritional counseling and artificial nutrition). Personalized nutritional support could modify poor nutritional status resulting in reduced postoperative complications and improved survival. Moreover, the implementation of nutritional protocols could reduce toxicity of treatment regimens and in conjunction with nutritional monitoring could have impact on patients' daily living [10]. Therefore, nutritional therapy should be an essential part of a multidisciplinary approach in the clinical setting, in order to improve short‐ and long‐term outcomes.

The aim of the current review is to focus on the etiology of malnutrition, review the various methods of nutritional assessment, and analyze the aspects of nutritional management of esophageal cancer patients as a fundamental part of multimodality therapy.


**1. Introduction**

The analysis of transient regimes in electric networks is a complex problem due to great number of elements, some nonlinear, as well as, due to the nonsinusoidal variation of currents and voltages. Numerical simulation can solve properly such a problem

There are available a lot of simulation programs for transients. One of the first of them, dedicated to electro energetic systems, was initiated by H.W.Dommel. Electromagnetic Transient Program (EMTP) was bought by Bonneville Power Administration (USA) (Dommel, 1995). Later on, from this initial program were developed several versions, such as MicroTrans, EMTP-RV, ATP (Alternative Transients Program), PSCAD (Chuco, 2005; DeCarlo & Lin, 2001).

Comparing some of the main simulation programs is not very conclusive, because each one of them are used in some versions trying to solve a large group of problems (Iordache & Mandache, 2004; Istrate et al., 2009).

Interface becomes more and more friendly, the library becomes larger and the facilities for creating own models are simpler to use. The speed of calculations and the storage capacity do no more represent a problem. It is possible now to implement some complicated algorithms able to solve problems with high speed in the variation of variables, able to solve all kinds of nonlinearities or to handle eigenvalues highly distanced one from another (large stiffness ratio dynamical systems).

An important criterion for the selection is represented by the integration of complex dynamical systems like rotating electric machines, relays, power electronic devices, FACTS, controllers etc. in the simulation. Some of the programs, depending on the way that were conceived, allow a better integration of these subsystems.

© 2012 Toader et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Choosing one or other of the simulation programs depends on the previous experience of the user, as well as, on the manner the program responds to the specific demands (Chuco, 2005; Danyek et al., 2002; Foltin et al., 2006; Karlsson, 2005; Rashid & Rashid, 2006).

Numerical Methods for Analyzing the Transients in Medium Voltage Networks 443

Analyzing transient regimes in such networks is the same as the analysis of any other complex electric circuit (Dessaint, et al. 1999; Mandache & Topan, 2009; SIMULINK, 1997).

Generally, an electric circuit, no mater how complex it is, is described by an algebraic linear system of equations, obtained by applying the Kirchhoff's laws. This system of equations reflects the circuit's topology. To complete the model, the voltage-current equation at the

The inductors and the capacitors are described by constitutive relations in which are involved the derivatives of currents, respectively voltages. As a result, the mathematic model of an

In the electric circuit theory it is demonstrated that each current or voltage can be expressed as function of inductors currents and capacitors voltages. By other words if the inductors currents and the capacitors voltages are known, all remaining currents and voltages are

The state-variable equations are obtained by elimination of the algebraic equations in the

The modelization of an electric circuit made using state-equations has several important

First of all, electric circuits can be integrated with other dynamic systems, of completely different physical nature, as long as the last ones are described also by state-equations.

By the other hand, the procedures for integrating state-equations have a well-established theoretic support, being the domain of interest for quite a long period of time for famous

Finally, but not last, the method can be applied to linear circuits, as well as, to nonlinear

Of course there is a price to be paid for all these advantages: a certain difficulty in the

In order to give an example for the basics of the state-variable method, we will analyze the simple RLC series connection circuit supplied by an ideal voltage source *u*(*t*). The Kirchhoff

>

*RLC*

*RLC*

*it it it ut u t u t u t u t Ri t*

*R*

*ut L*

*it C*

*L*

*C*

,

(1)

( ) ( ) ( ),

*L*

*dt du t*

*di t*

*C*

*dt*

,

,

.

equations and the constitutive relations for such a circuit are, respectivelly:

terminals of each element of circuit (called also constitutive relations) must be added.

electric circuit consists of a system of algebraic and differential equations (DAE).

uniquely determined and because of this they are called state-variables.

elimination of the algebraic equations from the system.

initial DAE.

advantages.

mathematicians.

circuits.

No mater what program is used, the numerical analysis of transients eventually must be able to solve a set of differential – algebraic equations that models the physical system. By accounting the stage the numerical integration takes place at, there are two main classes of simulation programms.

One class consists of those programs that make the integration at element level, meaning that for each step of time discretization the differential equations associated to dynamic elements are transformed in finite difference relations. Several ways of approximation can be used, more frequently the trapeze rule being used. All these algebraic relations are then assembled and as a result an algebraic system of equations is obtained and consequently solved using specific algorithms. This procedure is repeated at each iteration step, the parameters involved in the equations being modified by the results obtained at the previous step. Usually the integration step is fixed, but if this is required by a lack of convergence, the integration step can be split in half and the computation process is resumed. This method is known under the name of the implicit integration method and is used in programs such as SPICE and EMTP (Blume, 1986).

A second class of programs uses a two step procedure. In the first step the mathematic model is expressed as a system of first order differential equations, known as the system's state equations. During the next step this system of equations is integrated using algorithms with fixed step or with variable steps, depending on the systems particularities. The advantage of this method, called the state variables method, is to treat in the same way, in a unitary manner, electric networks, electric machines, drives, control devices or any other device that allows state equations. A representative of this method is SimPowerSystemsTM which is an extension of Simulink® with tools for modeling and simulating of electrical power systems. It provides models of many components used in these systems, including three-phase machines, electric drives, and libraries of application-specific models such as Flexible AC Transmission Systems (FACTS) and wind-power generation. Harmonic analysis, calculation of Total Harmonic Distortion (THD), load flow, and other key power system analyses are automated (Mathworks®).

The precision of the results obtained by integration of the equations describing the simulated system is quite remarkably high. It is obvious that none of the simulation programs, no mater which of the methods is using, cannot be more precise than the mathematic models used for the simulated components. The accuracy of the values of the parameters of these models is of high importance.


4.1.5. Effects on Diuresis

The evaluation of the effects of Jaburetox on diuresis was one of the first investigations carried out to understand the mechanism of action of the toxin. In 2009, Stanisçuaski et al. [81] conducted studies on *R. prolixus*' Malpighian tubules to explore, in vitro, the effects of Jaburetox on serotonin-induced diuresis. The authors demonstrated that Jaburetox and also JBU are capable of interacting with membrane factors that end up inhibiting diuresis by triggering different signaling cascades. While JBU effect is mediated by the activation of the eicosanoid cascade and is dependent on Ca++ ions, the antidiuretic effect of Jaburetox is mediated by an increase in cyclic guanosine monophosphate (cGMP) levels. This increment leads to the interruption of ion transport by blockage of the apical V-ATPase and disruption of the transepithelial potential across the tubule's membrane through an unknown pathway, leading (directly or indirectly) to the inhibition of water secretion and consequent impairment of diuresis [81].


*3.3. Calculation of Excitation Winding Parameters*

Another parameter to be calculated is the excitation time constant, which is closely related to the resistance and inductance of the excitation winding. Figure 9 shows the excitation window and its size, which is used for the assembly of excitation windings.

**Figure 9.** Excitation window and excitation winding. (**a**) Excitation window and its size. (**b**) Excitation winding.

The resistance of the excitation winding can be expressed as:

$$r\_f = \frac{\rho\_{\text{Cu}} N\_f \pi D\_f}{S\_{\text{cf}}} \tag{19}$$

where *ρCu* is the conductivity of copper, *Nf* is the turn of excitation winding, *Df* is the excitation coil diameter and *Scf* is the cross-sectional area of the excitation coil.

Under the excitation current alone, the magnetic density of a one-sided air gap between the HTR and the squirrel-cage rotor can be expressed as:

$$B\_{dcl}(\theta) = \frac{N\_f I\_f}{2} k\_m \sum\_{n=0}^{\infty} \lambda\_n \cos \, n\theta \tag{20}$$

Therefore, the average air gap flux density at one side of the machine can be expressed as:

$$B\_{\rm av} = \frac{1}{2\pi} \int\_0^{2\pi} B\_{\rm dcl}(\theta) d\theta = \frac{N\_f I\_f}{2} k\_{\rm m} \lambda\_{\rm dcl}^\* \Lambda\_B \tag{21}$$

The main flux linkage of excitation winding is:

$$
\psi\_{\mathcal{Y}} = N\_f B\_{\text{av}} S\_\delta = I\_f N\_f^2 \pi R\_H (I\_1 + 2\delta) k\_m \lambda\_{dc0}^\* \Lambda\_B \tag{22}
$$

where *Sδ* represents the total area of a one-sided air gap between HTR and the squirrel-cage rotor, *RH* is the radius of the HTR, and *l*1 is the single length of the HTR.

The main inductance of the excitation winding is:

$$L\_{\sharp\overline{f}} = \frac{\Psi\_{\overline{f}\overline{f}}}{I\_f} = N\_f^2 \pi R\_H (l\_{\perp 1} + 2\delta) k\_m \lambda\_{dc0}^\* \Lambda\_B \tag{23}$$

Moreover, (23) shows that the main self-inductance of the excitation winding only contains the dc component, because in the same pole magnetic field structure, the selfinductance parameters of the excitation winding are determined by the overall magnetic circuit state and have nothing to do with the details of the air gap flux density waveform.

The excitation time constant can be expressed by:

$$\mathbf{t}\_f = \frac{\mathbf{L}\_{\text{ff}}}{r\_f} = \frac{N\_f \pi R\_H (l\_1 + 2\delta) k\_m \lambda\_{dc0}^\* \Lambda\_B}{\rho\_{\text{Cu}} \pi D\_f} S\_{cf} \tag{24}$$

In the design of an HTR-ASD, the excitation winding time constant *tf* is expected to be as small as possible. On the one hand, it can reduce the excitation establishment time and improve the system mobility. On the other hand, it can make it easier to adjust the flux linkage of the excitation winding in the process of speed regulation, in order to strengthen the dynamic response ability of the system in the process of speed regulation.


**3. Contents of the including and excluding criteria and questions in detail**

#### **3.1 Inclusion and remission criteria**

EAT26 ≤ 9, healthy eating behavior, ability to do ordinary activities without difficulties, working for the members of the society to some extent, having no other psychotic disorders, having not irregular menstruation: For AN patients, normal menstruation,weight increase was not always necessary.

### **3.2 Exclusion criteria**

EAT26 ≥ 9, Complication suffering from other psychotic disorders, such as depression and addiction, serious dependency or obsession with food, preoccupation with thinness, afraid of being fat seriously, having irregular menstruation.

*The Outcome of Eating Disorders: Relapse, Childbirth, Postnatal Depression, Family Support DOI: http://dx.doi.org/10.5772/intechopen.95452*

#### **3.3 Interview questions during pregnancy and after delivery**

We asked the patients if they had panic, depressed about being mother, always preoccupied with food, unsatisfied with their body weight and shape,and if they have an urge to binge or vomit. Using the structured interview according to DSM-4 [14]. Once a month, their husbands were also asked if their spouse had an abnormal eating attitudes or obsessive compulsive thinking for eating etc.

We interviewed the patients every 2 weeks both during gestation period and after birth.

#### **3.4 Postnatal depression**

We used the JEPDS. In JEPDS, Usually scored >12 were diagnosed as depression, though, we interviewed those who scored>9.because they could have postnatal depression [13].

#### **3.5 Relapse group (TRED group)**

In hyperemesis symptoms or pregnancy sickness, pregnant women experienced nausea overeating and vomiting. These symptoms were very similar to those of ED symptoms. However, if the patients were motivated to reduce their weight to become thinner these thoughts were dissimilar from those suffered from hyperemesis. Thus, we decided those who had vomit and binge and feelings above mentioned was given name as the relapse group. In our cases, their symptoms disappeared during pregnancy, they were given name as the temporary relapse group during pregnancy. (TRED group).TRED group recovered within 3 mon of pregnancy. Also non-relapse participants during pregnancy was given name as non-relapsing group (NRED group).

#### **3.6 Statistical analyses**

We conducted t-test to determine the statistical difference between means of two different groups.

We compared the results of the TRED group and NRED group while pregnant and postnatally. Moreover, we examined the results of the postnatal depression and the non-depression group for 3 months following childbirth. A p value of, ≦0.05 was considered significant, and a p value of ≤0.1 was considered marginally significant.

#### **4. Results**

#### **4.1 Patients characteristics**

The characteristics of interviewed women who were recovering from EDs,assessed during their pregnancy and after childbirth are showed in **Table 1**. Sixteen patients (67%)had temporary ED relapse. We made the **Figure 1** to highlight these results clearly after **Table 1**.

We have previously reported that characteristics of women who have recovered from EDs in detail [1].

#### **4.2 TRED group and NRED group**

Sixteen (67%)showed temporary relapse within 3 mon of pregnancy. All the infants in the NRED group were male. With respect to ED relapse after childbirth,

#### **Table 1.**

*A summary of the characteristics of women who have recovered from EDs and who were interviewed during pregnancy and after childbirth. We made new tables different from previous report [1].*

#### **Figure 1.**

*The rate of the ED relapse: patients with relapse after 3mon of delivery tended to relapse afterbirth.*

there was a significant difference between RED group and NRED group. **Figure 2** shows the comparison of these two groups. **Figure 3** shows the infant sex ratio afterbirth between two groups.

No statistical difference could be seen between RED group and NRED group with regard to family support (**Table 2**).

#### **4.3 TRED group and NRED group were compared after childbirth**

All NRED group had a vaginal delivery, and most of them gave birth to male infants. However, for the postpnatal depression rate, these two groups were the same. There was a significant difference between age at remission, and age at pregnancy (P ≤ 0.05); further, difference for ED relapse during pregnancy reached statistical significance (P ≤ 0.05) between these two groups (**Table 3**).

No significant difference could be seen between RED group and NRED group with respect to postnatal depression and family support.

*The Outcome of Eating Disorders: Relapse, Childbirth, Postnatal Depression, Family Support DOI: http://dx.doi.org/10.5772/intechopen.95452*

**Figure 2.**

*Showed ED relapse after delivery between two groups. (RED means NRED).*

#### **Figure 3.**

*Showed the infant sex afterbirth between two groups.*

#### **Table 2.**

*Characteristics of women with RED group and NRED group.*

### **4.4 A comparison between patients with postnatal depression and those who did not develop depression afterbirth**

The infant body weight was found to be the only difference (**Table 4**).

#### **Table 3.**

*Comparison between TRED group and NRED group after childbirth.*

**Table 4.**

*A comparison between postnatal depression and patients who did not develop depression following childbirth.*

#### **4.5 Complications among mothers**

Our research exhibited a variety of complications such as diabetes mellitus in 5 patients, anemia in 3, threatened miscarriage in 2, kidney stones in 2, nephrosis in 1, eclampsia in1, hypertension in 1, placenta previa in 1, miscarriage in 1, cesarean sections in 5, Although the sample size was small, We detected various complications.

*The Outcome of Eating Disorders: Relapse, Childbirth, Postnatal Depression, Family Support DOI: http://dx.doi.org/10.5772/intechopen.95452*

### **4.6 Main summary of the results**

#### *4.6.1 The relapse rate of EDs during pregnancy*

67% of the patients relapsed after delivery and of them were belong to RED group.

#### *4.6.2 Relapse of EDs afterbirth*

50% of the participants relapsed.

*4.6.3 What kind of the participants experienced relapse of EDs afterbirth*

The group relapsed during pregnancy (TRED group) tended to be relapsed afterbirth.

#### *4.6.4 Infants sex*

50%of the infants in the TRED group had male infants, while 100% of the infants in the NRED group were male.

#### *4.6.5 Postnatal depression*

50% of the participants had postnatal depression.

## **5. Discussions**

We hypothesized that Ex-ED patients were vulnerable to relapse ED during body transition period such as pregnancy and giving birth. In addition, after birth, they tended to be anxious and depressed with their body image and weight, leading to have possibility to suffer from postnatal depression. Our results may supported our hypothesis.

Further we anticipated that family support played an important role in preventing relapse and postnatal depression. However, our result was not supported by our anticipation.

As per the literature, partners attitudes to EDs could help prevent ED relapse [15] and postpartum depression [16].

In our samples, all the supporters were partners and not mothers. Ikuno [17] reported there was problematic relationship between mother and daughter; daughter used her thinness as a weapon to draw her mother's attention, and involved her mother in her frustration. This is the problematic relationship of mother and daughter, that had not overcomed for a long time, as a result they hate each other. Owing to this problematic relation, mother might not support her daughter and daughter do not want to be supported by her mother.

We believed that the supporters for patients with EDs are very sensitive and some cases their behavior might worsen the symptoms of ED.

We investigated pregnant women recovered from EDs completely. Keel et al. [18] showed that among the patients who recovered from EDs, relapse rate was 36% in AN patients, and 35% in BN patients. Compared to these results, our rate of TRED group was 67%. Thus, Pregnancy was a crucial event for relapse for patients with ED. Our data showed that the TRED group improved within the first 3mon of pregnancy.

We found the in spite of the relapse, mothers and infants complications were not different compared to NRED group.

Nevertheless, the prevalence of postnatal depression was lower and the infant body weight was greater in the NRED group. Following childbirth, we found that the rate of postnatal depression and complications were similar in the RED and the NRED group. Further, we showed that the infants belonging to the postnatal depression group had a lower body weight than those in the non-depression group.

Angela [19] showed that patients with ex-EDs commonly experienced relapse;in AN 36%, in BN 35%, the figure was similar to that reported by Keel et at al [18]. Hetman et al. [20] showed that ED patients experienced relapse when they go to start to school or to go to college, or to start a new job, to be pregnant, and to have a baby.

Our data (67% of the patients relapsed during pregnancy and 50% of the patients relapsed ED after childbirth.) showed that pregnancy and childbirth represented the transition period for EDs, and postnatal term. Patients had been treated from the time of diagnosis up until the time of giving birth and postnatal period. We treated them twice a month, and we taught them how to coping with their eating attitudes and negative feelings.

A study out of Kelty Mental Health Center in British Columbia, Canada. [21] suggested that ED relapse could be averted by encouraging a support system for EDs, such as teaching them how to eat healthier,and control their unstable feelings. The Authority also taught EDs how to cope with their negative influences; to identify disease triggers, to create personal coping strategies, and to eat meals regularly. Our attitudes to them was that we encouraged them continuously to change their eating attitudes promoting self-control and encouraging the development of healthy relationships with the others, particularly their spouses and close family members. Our strategy may be equivalent to that of Kelty. Therefore, that we should followed -up the ED patients for a long term was the one of the strategies to prevent ED relapse. We think this is also appropriate even for pregnant women with EDs.

Hetman et al. [20] stated that pregnancy was risk factor for ED relapse. Especially AN patients wanted to be thinner seriously, leading to reducing their food, tended have a higher risk of relapse even when they are pregnant, regardless of their desire to be pregnant. They did not want to eat an adequate amount of food. In a similar way, Mancini [22] stated that it was usual that even pregnant healthy women had body image dissatisfaction. Our results suggested that having a prior history of an EDs with body image unsatisfaction was serious risk factors for relapsing for EDs.

Our patients had many complications during gestation. In EKeus et al. [23], it was reported that BN women experienced an increased risk of miscarriage. Similarly, our findings demonstrated that a woman who had a history of BN experienced a miscarriage. In Koubaa et al. [24], they reported that the fetus among AN mothers grew less efficiently in the intrauterine environment, leading to lower body weight infants. The Japanese Nikkei Health [25] describes that an average infants' body weight in Japan, where a male infants' average weight should be 2980 g and a female infants' weight should be 2910 g. Our findings showed an average body weight of 2928 ± 540 g infants, which was comparable to Nikkei Health Report.

However, our RED group regained during the first 3 months of gestation. The mechanism for this change remains unclear. The body weight of infants in the RED group was lower than that infants weight in the NRED group. Nevertheless, the final body weight of infants measured in this study was similar to the average body infant weight in Japan. Thus, the first 3 mon of pregnancy may not be important for the infant growth. Middle ages patients, such as hypertension, the presence of coronary heart disease, and non- insulin-dependent diabetes mellitus can be caused by intrauterine growth restriction, leading to lower birth weight [26]. Thus, low body

#### *The Outcome of Eating Disorders: Relapse, Childbirth, Postnatal Depression, Family Support DOI: http://dx.doi.org/10.5772/intechopen.95452*

weight infants should be followed -up for a long duration, which can be important to prove for Barker's hypothesis. Our data showed that all subjects in the NRED group gave birth to male infants. However, the underlying reason remains still unclear.

Franco et al. [27] showed that most women with active EDs had normal progress during gestation period, and the newborn babies were healthy. Our results are in line with those reported by Franco et al.; Further, the patients in our research did not have active EDs; thus their babies were more likely to be normal weight than those from mothers with active EDs.

Bennet et al. [28] demonstrated that in ED patients, half developed postnatal depression and the rate of postnatal depression among healthy women was about 13%. Our results agree with this report. Nasreen et al. also [29] reported that low birth weight infants was strongly related to postnatal depression. Moreover, our results demonstrated that following birth infants in whose mothers' developed depression, had a decreased infant body weight, when compared to those whose mothers did not develop depression. Our results supported Bennet and Narsreen.

Because of the small sample size, we did not reached the result that BN patients had a higher chance for developing postnatal depression. Nevertheless, since about half of BN patients developed postnatal depression, BN has possibility to increase the risk of having postnatal depression. Moreover, within the AN patients group, 75% of the patients developed postnatal depression. However, the underlying reason remains unclear. Mazzeo et al. [30] demonstrated that patients with a history of EDs were at increased risk of relapse during gestation period, which lead to an increased incidence of postnatal depression and anxiety. Chan et al. [31] demonstrated that a higher level of disordered eating during pregnancy was related to an increased incidence of postnatal depression. However, in contrast, our findings did not demonstrate a higher rate of postnatal depression in RED group compared to the NRED group. Therefore, when considering pregnant women who have a history of ED, there may be a higher risk of postnatal depression and long-term follow-up should be considered. In the current study, we demonstrate that approximately half of the patients with pre-existing EDs relapsed within 1 y of delivery. Morgan et al. [32] reported that among mothers with pre-existing EDs 66% of experienced binging and vomiting after childbirth. However, we do not have detect the patients' types precisely about the type of EDs relapse experienced after childbirth. Thus, we are not able to confirm the findings of Morgan. Patients were seen in our outpatient clinic every 2 wk. and we counseled them about the management of their stress coping and anxiety etc., that might helped EDs to prevent relapse.

There are some limitations of this study. Sample size was smaller. An increase in the sample size would have strengthened the statistical power of our study and made us to compare between groups with EDs. Our findings supported our hypothesis that suggested that women with pre-existing EDs were vulnerable to relapse during pregnancy and after childbirth as well as suffering from postnatal depression. Another limitation was that we included only women with AN and BN. Our samples were limited to the following two groups: women with AN and women with BN. As such other subtypes of EDs such as binge eating disorder etc. were not included, and should be examined to verify our results. The most important limitation in our current study was the lack of a control that included healthy women, who did not have any EDs.

In order to anticipate the risk of postnatal depression, we need to consider various questions, including the patients' social support system, and their feeling of becoming a mother and how they perceive their body shape and weight, because Chan et al. [31] demonstrated a relationship between postnatal anxiety, irritability, and depressive symptoms for 6 mon afterbirth had a serious relationship with body dissatisfaction, leading to postnatal depression.


**FIGURE 1 | Symptoms in rice caused by RGSV infection. (A)** Rice plants at 28 days and **(B)** 60 days after RSGV inoculation and mock inoculation. **(C)** Leaf yellowing of RGSV-infected plants at 60 days after inoculation.

**Table 1 | Numbers of DEGs in gene ontology groups overrepresented or underrepresented in RGSV-infected plants.**

*aBased on Rice Genome Annotation Project database Osa1 (rice.plantbiology.msu.edu).*

*bNumbers in bold (or underlined) text indicate that the corresponding ontology groups are overrepresented (or underrepresented) based on a* χ2*-test between the actual ratio of DEG (the number of DEGs/the number of expressed genes belonging to the corresponding ontology group) and the expected ratio of DEG [the number of total DEGs (8204)/the number of the total expressed genes (24,911)].*

*cFrom the* χ2*-test.*

cellular processes, DEGs involved in stress responses and secondary metabolism were overrepresented in the plants infected with RGSV (**Table 1**). For DEGs categorized in stress responses, the number of induced genes was significantly greater than that of suppressed genes, whereas the number of induced genes involved in secondary metabolism was not significantly different from that of suppressed genes. On the other hand, expression of genes involved in translation process and nucleic acid metabolism was less influenced by RGSV infection than genes in other categories (**Table 1**). These results indicated that genes involved in development of cell structures, secondary metabolisms, and stress responses were noticeably affected by RGSV infection, and might be associated with RGSV-induced symptoms.

#### **Table 2 | Continued**

*aBased on Rice Genome Annotation Project database Osa1 (rice.plantbiology. msu.edu).*

*bLog*2*-based differential expression ratio (signal intensity in RTSV-infected plant/signal intensity in mock-inoculated plant).*

*cU (D): Significantly induced (suppressed) by RGSV infection.*

## *Cell wall-related genes*

The expression of genes related to cell wall components was affected by RGSV infection (**Table 2**). The expression of genes for cellulose synthase (-like) and arabinogalactan proteins associated with cell wall formation was predominantly suppressed by RGSV infection (**Table 2**). The genes encoding expansin proteins involved in cell elongation by loosening cell wall components (Choi et al., 2003) were also predominantly suppressed by RGSV infection (**Table 2**). These results indicate that RGSV infection suppressed both cell wall formation and cell elongation in rice.

### *Genes associated with tillering*

One of the major symptoms caused by RGSV infection is excessive tillering. The genes *RCN1* (*REDUCED CULM NUMBER 1*; Yasuno et al., 2009), *SPL14* (*SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 14*; Miura et al., 2010), and *Ostill1* (*ORYZA SATIVA TILLERING 1*; Mao et al., 2007) were reported to promote shoot branching. RGSV infection induced the expression of *RCN1*and *Ostill1*, but suppressed that of *SPL14* (**Table 2**), suggesting that activation of *RCN1* and *Ostill1* alone may contribute to the development of excess tillers in RGSV-infected plants.

*(Continued)*

**metabolisms in RGSV-infected plants that are up- or down-regulated.** Responses of genes for **(A)** Calvin-Benson cycle, and **(B)** chlorophyll metabolism. Enzymes catalyzing reactions are shown in the table below:

## *Genes functioning in chloroplast*

Expression of many genes functioning in chloroplasts was affected by RGSV infection (**Supplementary Material 1**). Eight genes functioning in the Calvin-Benson cycle were induced by RGSV infection, whereas 8 genes including those encoding ribulose bisphosfate carboxylase (Rubisco) large and small subunits were suppressed (**Figure 2A**). Among 35 genes involved in the photosynthesis system whose expression was affected by RGSV, 34 were suppressed in RGSV-infected plants (**Supplementary Material 1**). The chlorophyll is a photoreceptor in the chloroplast. Among 14 genes for chlorophyll metabolism whose expression was affected by RGSV infection, 12 genes were suppressed and 2 genes were induced (**Figure 2B**). The suppressed genes were those involved in chlorophyll synthesis and conversion. The two induced genes were *Staygreen* (*Sgr*) and the gene encoding red chlorophyll catabolite reductase, both of which are associated with chlorophyll degradation (Park et al., 2007). Thus, it is likely that RGSV infection inhibits the carbon fixation and chlorophyll synthesis, and promotes degradation of chlorophyll.

## **EXPRESSION OF GENES ASSOCIATED WITH PLANT HORMONE METABOLISM AND SIGNALING**

We examined the expression patterns of genes involved in plant hormone biosynthesis and signaling processes. Rice genes for

hormone biosynthesis and signaling and their orthologous genes in *Arabidopsis* are described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa et al., 2010).

### *Genes related to auxin biosynthesis and signaling*

GH3 converts IAA into an inactive form by conjugating IAA to amino acids (Domingo et al., 2009; Zhang et al., 2009). Four genes encoding GH3 were activated by RGSV infection (**Figure 3A**). RGSV infection also affected the expression of genes for auxin transporters such as *AUX1/LAX1, PIN1*, and *ABCB* (**Figure 3A**, **Supplementary Material 1**). RGSV suppressed *AUX1/LAX1* genes, but activated *OsPIN1* genes. RGSV infection induced the genes for the regulator of auxin signaling such as *AUX/IAA* and *ARF* (*AUXIN RESPONSE FACTOR*) (Lau et al., 2008) (**Figure 3A**). The expression of *SAUR* (*SMALL AUXIN-UP RNA*) genes involved in regulation of auxin synthesis and transport (Kant et al., 2009) was also affected by RGSV infection, and the number of induced *SAUR* genes was similar to that of suppressed genes (**Figure 3A**). These results suggest that RGSV infection might have inhibited the accumulation of auxin in rice, but activates IAA signaling process.

## *Genes related to gibberellic acid (GA) biosynthesis and signaling*

Enzymes such as *ent*-kaurene synthase (KS), *ent*-kaurene oxidase (KO), and gibberellin 20-oxidase (GA20ox) catabolize the

production of bioactive GA precursor (Yang and Hwa, 2008, and references therein). Five genes encoding these enzymes were induced by RGSV infection (**Figure 3B**). RGSV infection also activated the expression of four genes encoding gibberellin 2-oxidase (GA2ox), which degrades bioactive GA. The expression of genes for GA metabolism is regulated by Dwarf 62 (D62) and YABBY1 transcription factors (Dai et al., 2007; Li et al., 2010). The genes encoding D62 and YABBY1 were induced and suppressed by RGSV infection, respectively (**Supplementary Material 1**). On the other hand, the expression of genes encoding GID1, DELLA, and GID2, which are involved in GA signaling (Itoh et al., 2008), was not affected by RGSV infection (**Supplementary Material 1**). These results suggest that RGSV infection might have induced both GA biosynthesis and GA degradation.

the table below: 1based on Rice Genome Annotation Project database Osa1 (rice.plantbiology.msu.edu), 2log2-based differential expression ratio (signal

## *Gene related to strigolactone (SL) biosynthesis and signaling*

SL was recently classified as a plant hormone. The expression of genes involved in SL biosynthesis such as those encoding Dwarf 17 (D17), D10, and D27 was not changed by RGSV infection (**Figure 4A**). We quantified 2 -epi-5-deoxystrigol, one of the major SLs n rice, in root exudates to examine intensity in RTSV-infected plant/signal intensity in mock-inoculated plant), and 3U (D): Significantly induced (suppressed) by RGSV infection. Boxes of red (or suppressed). Boxes of red/blue indicate that the number of the corresponding genes induced was similar to that of suppressed genes. →: Reaction and translocation of substrate →: Positive signaling : Negative signaling.

whether endogenous SL level was changed by RGSV infection. Quantification of 2 -epi-5-deoxystrigol was made on plant tissue at 42 dpi instead of 28 dpi, because the symptoms induced by RGSV infection were clearly observed at this stage. The amounts of 2 -epi-5-deoxystrigol were low in both RGSV and mock plants (**Figure 4B**), but it seemed that RGSV infection suppressed the strigolactone synthesis. *HTD2* (*HIGH TILLERING DWARF 2*) and *D3* are related to SL signaling (Umehara et al., 2010; Yamaguchi and Kyozuka, 2010). The expression of the two genes was suppressed by RGSV infection. These results suggest that SL synthesis and signaling in rice might have been suppressed by RGSV infection.

## **DISCUSSION**

We previously reported gene responses of rice to RSV and *Rice dwarf virus* (RDV) (Shimizu et al., 2007; Satoh et al., 2010, 2011). RSV is the type member of *Tenuivirus* and RDV belongs to the genus *Phytoreovirus*. Symptoms such as leaf stripe and stunting are common to plants infected with either virus. Symptoms caused by RSV infection are shown in **Supplementary Material 3**. The transcriptome analyses of plants infected with either virus commonly showed the predominant

suppression of genes involved in cell wall synthesis, GA synthesis and chloroplast function, implying strong associations of such gene responses with leaf stripes and stunting. We expected that the symptoms of leaf yellowing, stunting and excessive tillering caused by RGSV are also associated with specific gene responses in RGSV-infected plants. In this study, we focused on the responses of genes involved in cell wall formation, chloroplast function, and hormone biosynthesis and signal transduction since expression of these groups of genes were also significantly affected in rice plants infected with RDV and RSV (Shimizu et al., 2007; Satoh et al., 2010, 2011).

## **GENE EXPRESSION RESPONSES ASSOCIATED WITH STUNTING AND LEAF YELLOWING IN RGSV INFECTED PLANTS**

RGSV infection induces stunting of rice plants. Many cellulose synthase (-like) genes were suppressed in RGSV-infected plants (**Table 2**). The suppression of many cellulose synthase (-like) genes was also seen in RSV-infected plants, which exhibits stunting symptom (Satoh et al., 2010). Expansins mediate loosening of cell wall. Suppression of *OsEXP4*, one of the rice expansin genes, resulted in stunted growth (Choi et al., 2003). The expression of many expansin (-like) genes were suppressed by RGSV infection. The suppression of many expansin genes was also observed in RSV-infected plants (Satoh et al., 2010). Therefore, the suppression of cellulose synthase and expansin genes is one of the common gene responses associated with stunting of rice infected with tenuiviruses.

The expression of the Rubisco genes was suppressed by RGSV infection (**Figure 2A**). The suppression of the Rubisco genes was also observed in RSV-infected plants (Satoh et al., 2010). RGSV-infected plants show leaf yellowing (**Figure 1**), implying the chlorophyll contents may have been decreased by RGSV infection. The appearance of leaf chlorosis in RSV-infected plants is different from that in RGSV-infected plants. RSV-infected plant showed white stripes on leaves (Satoh et al., 2010). The difference in leaf chlorosis pattern may have resulted from the difference in influence by RGSV and RSV on chlorophyll synthesis and degradation processes. In RGSV-infected plants, the expression of genes involved in chlorophyll synthesis was suppressed, and the suppression of those genes was also detected in RSVinfected plants. This suppression indicates that RGSV-infected plants contain low chlorophyll content, and have lower photosynthesis activity than healthy plants. These suggest that decreased biomass accumulation such as cell wall synthesis and carbon fixation activity may account for stunting of the virus-infected plants.

The difference in leaf chlorosis pattern may be related to chlorophyll degradation process (**Figure 2B**). The degradation of chlorophyll is regulated by *Sgr* gene (Park et al., 2007). Overexpression of *Sgr* resulted in yellowing leaves which is similar to the disease symptoms of RGSV-infected plants (Park et al., 2007). The expression of *Sgr* gene was induced by RGSV infection (**Figure 2**). Thus, the activation of *Sgr* by RGSV infection may play a role to induce the leaf yellowing symptom. In RSV-infected plants, the expression of genes involved in chlorophyll degradation was also activated, but the expression of *Sgr* was not significantly changed (Satoh et al., 2010). Therefore, the difference in the appearance of leaf chlorosis between the plant infected with RGSV and that infected with RSV may be related to the activation of *Sgr*.

Cell elongation is controlled by plant hormones such as GA and IAA. The expression of genes for GA biosynthesis such as those for KS, KO, and GA20ox, and those involved in GA inactivation such as the genes for GA2ox increased in RGSVinfected plants (**Figure 3B**), whereas the expression of these genes decreased in plants infected with RSV (Satoh et al., 2010). It was reported that rice plants overexpressing *GA2ox* contained lower bioactive GA, and were shorter than the wild type (Lo et al., 2008). The expression of *GA2ox* increased in stunted rice plants after infection with RDV (Satoh et al., 2011). These observations, in total, suggest that there are multiple ways to reduce the bioactive GA content and produce stunted plants, and that for RGSV an induction of *GA2ox* may aid in producing the stunted plants. On the other hand, many genes for both GA biosynthesis and degradation were suppressed in plants infected with RSV, which may have caused a reduction in GA content. Sakamoto et al. (2004) reported that a GA-deficient mutant was stunted. Therefore, the stunting symptom of RSV-infected plants might be related to GA deficiency. These observations indicate that RGSV- and RSV-infected plants may contain low bioactive GA, though the pathways to the reduction may be different between the plant infected with RGSV and that infected with RSV.

RGSV infection suppressed the genes for IAA biosynthesis, and induced the genes for IAA inactivation (**Figure 3A**). This implies that IAA content decreases in plants infected with RGSV. In addition, RGSV infection increased the expression of *GH3* genes (**Figure 3A**). It is known that the activation of *GH3* genes inhibits plant growth by suppressing genes related to auxin biosynthesis and signaling, and those for expansin (Ding et al., 2008; Domingo et al., 2009). The activation of *GH3* genes was also observed in RSV-infected plants (Satoh et al., 2010). These observations suggest that stunting of plants infected with rice tenuiviruses is associated with a reduction in auxin content.

Overexpression of a SAUR gene resulted in various morphological changes in rice plants (Kant et al., 2009). The expression of a SAUR gene was conspicuously induced in *Arabidopsis thaliana* by *Beet curly top virus* (BCTV), and the induction of the SAUR gene was correlated with symptom development and tissuespecific accumulation of BCTV (Park et al., 2004). The expression of many SAUR genes was found to be regulated in the plants infected with RGSV (**Supplementary Material 1**, **Figure 3A**), RDV (Satoh et al., 2011), and RSV (Satoh et al., 2010). Among the regulated SAUR genes, *OsSAUR13*, *OsSAUR26,* and *OsSAUR33* were commonly activated by RGSV and RDV, whereas *OsSAUR8, OsSAUR30, OsSAUR44, OsSAUR46, OsSAUR53, OsSAUR57*, and *OsSAUR58* were commonly suppressed by RGSV, RDV and RSV. Consequences of the regulated expression of various SAUR genes in the RGSV-infected plant are not clear, but the SAUR genes commonly regulated by RGSV, RDV, and RSV may be associated with stunted growth of plants infected with these viruses.

#### **GENE ASSOCIATED WITH EXCESS TILLERING BY RGSV INFECTION**

Excess tillering (shoot branching) is RGSV-specific symptoms. Shoot branching is controlled by plant hormones (Dill and Sun, 2001; Ferguson and Beveridge, 2009; Shimizu-Sato et al., 2009). Auxin and SL inhibit shoot branching, whereas cytokinin promotes it. In RGSV-infected plants, genes related to IAA biosynthesis were suppressed and those related to IAA degradation were induced (**Figure 3A**), implying that the IAA content was decreased by RGSV infection. The suppression of genes involved in IAA synthesis genes and the induction of genes involved in IAA degradation genes were also observed in RSV-infected plants which do not show excess tillers. These indicate that the reduction in auxin content is not directly associated with the excess tillering of RGSV-infected plants. A rice plant overexpressing the *GH3-8* displayed phenotypes of dwarfism and excess tillering (Ding et al., 2008) which are similar to the symptoms of RGSV-infected plants. However, the activation of *GH3-8* was also observed in RSV-infected plants. Therefore, the induction of the *GH3* genes in RGSV-infected plants may not be related to excess tillering.

Rice genes *D10, D17/HTD1*, and *D27* are involved in SL biosynthesis, and *D3* and *D14/HTD2* are involved in SL signaling (Arite et al., 2009; Lin et al., 2009; Yamaguchi and Kyozuka, 2010). Rice mutants for these genes have more tillers than the wild type. The expression of *D3* and *D14*/*HTD2* was suppressed in rice plants infected with RGSV (**Figure 4**), implying that the SL signaling process is repressed by RGSV infection. In addition, endogenous SL was reduced by RGSV infection (**Figure 4**). The expression of *D17/HTD1* was also suppressed in RSV-infected plants. Thus, SL biosynthesis might have been suppressed by RSV infection. These results suggest that excessive tillering because of RGSV infection may be related to the repression of SL signaling, but not to the decrease in SL content in RGSV-infected plants.

A reduction in active GA also promotes the formation of axillary buds (Curtis et al., 2005; Lo et al., 2008). *GA2ox* is one of the key genes for GA degradation to produce inactive GA (Curtis et al., 2005; Lo et al., 2008). Overexpression of *GA2ox* in rice resulted in development of excess tillers, a decrease in bioactive GA, and an increase in inactive GA (Lo et al., 2008). RGSV infection induced *GA2ox* (**Figure 3B**). Thus, it is likely that RGSV infection decreases bioactive GA content and increase inactive GA content in rice plants. On the other hand, genes involved in biosynthesis and degradation of bioactive GA were suppressed by RSV infection (Satoh et al., 2010), indicating that GA content may have been decreased by RSV infection. Plants deficient in GA display stunted growth and reduced tillers (Margis-Pinheiro et al., 2005), which are similar to the symptoms caused by RSV. These observations suggest that excessive tillering because of RGSV infection is related to the accumulation of inactive GA, but not to the lack of bioactive GA.

Overall, excessive tillers induced specifically by RGSV infection might be a consequence from the additive actions of SL, GA, and the genes regulating shoot branching, such as *RCN1*and *Ostill1*. Examination for possible interactions between RGSV proteins and host proteins, and phenotypes of transgenic plants with RGSV genes may help to elucidate the molecular mechanism of excessive tillering caused by RGSV infection. Moreover, there could be modifications in gene expression that occur earlier than 28 dpi, and further studies will determine how such modifications influence the symptoms observed at 28 dpi.

## **ACKNOWLEDGMENTS**

We thank Dr. Bill Hardy for editing this manuscript and Ms. Setsuko Kimura and Hiromi Satoh for their support in the microarray and semi-quantitative RT-PCR experiments. This work was supported by a grant from the Program for Promotion of Basic Research Activities for Innovative Biosciences (PROBRAIN).

#### **SUPPLEMENTARY MATERIAL**

The Supplementary Materials for this article can be found online at: http://www.frontiersin.org/journal/10.3389/fmicb. 2013.00313/abstract

**Supplementary Material 1 | List of expressed genes and differentially expressed genes in RGSV-infected plants.**

**Supplementary Material 2 | Examination of expression of selected genes**

**by RT-PCR.** The numbers below DNA band images are average log2 (signal intensity of microarray data) for the corresponding genes in

mock-inoculated or RGSV-infected plants (Supplementary Material 1).

**Supplementary Material 3 | Symptoms in rice caused by RSV infection.** Rice plants at 60 days after RSV inoculation and mock inoculation.

## **REFERENCES**

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*ONE* 7:e43447. doi: 10.1371/journal.pone.0043447

I. R., et al. (2011). Relationship between symptoms and gene expression induced by the infection of three strains of *Rice dwarf virus*. *PLoS ONE* 6:e18094. doi: 10.1371/journal.pone.0018094

and exudation? *Planta* 235, 1197–1207. doi: 10.1007/s00425- 011-1568-8

Zhang, S. W., Li, C. H., Cao, J., Zhang, Y. C., Zhang, S. Q., Xia, Y. F., et al. (2009). Altered architecture and enhanced drought tolerance in rice via the down-regulation of indole-3-acetic acid by *TLD1/OsGH3.13* activation. *Plant Physiol.* 151, 1889–1901. doi: 10.1104/pp.109. 146803

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 15 May 2013; accepted: 29 September 2013; published online: 18 October 2013.*

*Citation: Satoh K, Yoneyama K, Kondoh H, Shimizu T, Sasaya T,* *Choi I-R, Yoneyama K, Omura T and Kikuchi S (2013) Relationship between gene responses and symptoms induced by Rice grassy stunt virus. Front. Microbiol. 4:313. doi: 10.3389/fmicb. 2013.00313*

*This article was submitted to Virology, a section of the journal Frontiers in*

*Microbiology. Copyright © 2013 Satoh, Yoneyama, Kondoh, Shimizu, Sasaya, Choi, Yoneyama, Omura and Kikuchi. This is* *an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

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**6. Discussion**

### *6.1. Measuring Factors Affecting EFs*

From the generating-presentation model we can conclude that EFs can be affected by different factors corresponding to different layers or sublayers through 15 approaches. For example, according to approach 1, EFs are directly affected by species life history or species behavior. According to approach 2, EFs can be affected by community structures and species life history or species behavior. Among the 15 approaches, 8 (approaches 5–12) are related to biodiversity. Based on the factors identified to affect BEF in recent research, various effect factors are incorporated into the generating-presentation model (Table 1). It should be noted that the generating-presentation model can incorporate not only factors affecting BEF but also those affecting EFs. In other words, biodiversity is identified as a common factor that affects EFs in the model.

**Table 1.** The approaches to express the effects of factors on ecosystem functions (EFs) in generatingpresentation model.

The generating-presentation model provides a useful reference system for EFs or ecosystem services research. In future BEF research, the approaches of effects of biodiversity on EFs or ecosystem services can be clearly presented by this model. For instance, some recent BEF studies cited in this article can be grouped in approaches 5–12 (Table 1).

### *6.2. Integrating Factors Affecting BEF with the Generating-Presentation Model*

In general, the ultimate goal of BEF research is to evaluate the state of EF. In some cases, the correlation between biodiversity and EF has been described as involving a cascade process [72]. On one hand, as expressed by the approaches illustrated in the generatingpresentation model, this cascade process indicates that biodiversity, which is affected by species, can influence the community structures and compositions of ecosystems. On the other hand, as Isbell et al. [72] showed in their research, because of cascade processes, the impacts of human activities on BEF may increase at larger spatial and longer temporal scales. Furthermore, community structures and compositions can affect ecosystem processes, which can in turn further lead to a variety of EFs. However, as a dynamic and open system, the natural ecosystem has a typical dissipative structure whose factors have complex sources. As a result, the separation of biodiversity and EFs from the ecosystem without considering integrated features is not appropriate for BEF-related research.

Biodiversity decline has drawn attention to the effects of biodiversity loss on EFs [2,73]. However, biodiversity is only a factor that affects EFs. Thus, when the research object is to evaluate the state of EF, not only biodiversity but other factors must be studied—especially when the main effect factors do not include biodiversity (approaches 1–4 and 13–15 of the generating-presentation model). However, when the research objective is to evaluate the state of biodiversity, factors related to biodiversity, such as land-use change, may be considered [74]. These two research objectives are relatively independent of each other, though relationships between biodiversity and EFs have been found in numerous studies. Therefore, research on BEF may not be relevant in reference to certain areas, as relationships between biodiversity and EFs are not always significant in certain regions.

### **7. Conclusions**

As a new avenue for research in ecology, BEF research generally focuses on the effects of biodiversity loss on EF. However, other factors, with the exception of biodiversity, also affect EF and play an important role in BEF-related studies. In this work, the different factors that affect BEF have been reviewed and summarized, and a new conceptual model, the generating-presentation model, accounting for the links between effect factors and EF has been built to provide a systematic means of understanding how different factors affect BEF. The model shows that correlations between biodiversity and EF can be described as involving a cascade process and that the separation of biodiversity and EFs from the ecosystem without considering integrated features is not appropriate for BEF-related research. The generating-presentation model thus comprehensively reveals the effects of different factors on EFs and thus has key theoretical and applied implications. It is suggested that the integration of effect factors in BEF could allow us to greatly advance our knowledge of BEF.

**Author Contributions:** Conceptualization, writing—original draft, J.H.; writing—review and editing, H.F.; investigation, M.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the National Key Research and Development Program of China [no. 2016YFC0500802].

**Institutional Review Board Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors would like to thank anonymous referees for their constructive suggestions.

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

### **References**


**SOYBEAN – GENETICS AND NOVEL TECHNIQUES FOR YIELD ENHANCEMENT**

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**4.2** *Bacillus subtilis* **ICDH**

322 Current Trends in X-Ray Crystallography

The crystal structure of *Ec* ICDH determined with its substrates revealed that the malate moiety of isocitrate, namely 1-carboxyl and 3-carboxyl groups and 2-hydroxyl group, is recognized by three arginine, three aspartate, one lysine, and one tyrosine residues of ICDH, which are the residues conserved between the enzymes (Hurley et al., 1990). As shown in Fig. 9, in the substrate binding site, the α-carboxyl group of isocitrate is bound to three arginine residues, Arg-119, Arg-129, and Arg-153. The β-carboxylate group is bound to Arg-153 and Tyr-160. The α-position of isocitrate forms hydrogen bonds with the Lys-230', and Asp-283' residues of the other subunit of the dimer (Doyle et al., 2001; Mesecar et al., 1997).

Large domain

Fig. 8. Diagram of *Ec* ICDH monomer with isocitric acid. (PDB ID: 1P8F). The large domain containing the N and C termini, the small domain, and the clasp domain are indicated.

(www.rcsb.org/pdb/home/home.do) and imaged using PyMol (The PyMOL Molecular

Mesecar and Koshland Jr. have made precisely explanation as to the mechanism for stereospecificity, that is, to distinguish between the two enantiomers on the basis revealed by electron density maps of the crystal structures of ICDH with L- and D-isomer isocitrate (Mesecar & Koshland Jr., 2000). In the metal-free crystal of ICDH with a racemic mixture of isocitrate, only the L-isomer (2S,3R) is seen bound to the enzyme. When enzyme crystals are

Atomic coordinates were obtained from the RCSB Protein Data Bank

C

Graphics System, version 0.99, DeLano scientific, LLC).

Small domain

N

Isocitric acid

Clasp domain

Recently, the crystal structure of *Bs* ICDH has been reported and discussed on the difference between *Ec* ICDH. Both have very similar 3-D structures not only because *Bs* ICDH is 67% identical to *Ec* ICDH but also that both are 100% identical in the primary sequence around the phosphorylation site (Singh et al., 2001). The tertiary structure of *Bs* ICDH monomer A is illustrated in Fig. 10, and the *Bs* ICDH dimer is shown in Fig. 11. Each subunit is composed of 15 α-helices and 13 β-strands. Although *Bs* ICDH is a homodimer, interestingly, the crystal structures of the individual monomers are not identical. In the dimerization*,* socalled clasp domain is formed where constituent of two β-strands and connecting α-helix of each subunit interlock forming a hydrophobic core. The manner of intersubunit interactions in *Bs* ICDH dimer is reported the same for the most part with *Ec* ICDH. There are several reported differences between *Bs* ICDH and *Ec* ICDH, suggesting the robustness of the enzyme in preserving the principle function.

Crystallization, Structure and Functional Robustness of Isocitrate Dehydrogenases 325

Fig. 12. Amino acid sequence alignment of *Tth* ICDH, *Ec* ICDH, and *Bs* ICDH. The shaded and boxed sequences represent those identical to *Tth* ICDH sequence, and boxed ones

represent those in similar to *Tth* ICDH sequence.

Fig. 10. Cα trace of *Bs* ICDH monomer (monomer A) with citric acid. (PDB ID: 1HQS). Overall folding manner of the monomer resembles that of *Ec* ICDH, but has several differences in the secondary structures.

Fig. 11. Diagram of *Bs* ICDH dimer. Each of monomer A, and monomer B having slightly different conformation are related by dimerization mediated through expansive portion of small and clasp domains. (PDB ID: 1HQS).

Citric acid

N

C

C N

differences in the secondary structures.

C

N

small and clasp domains. (PDB ID: 1HQS).

Fig. 10. Cα trace of *Bs* ICDH monomer (monomer A) with citric acid. (PDB ID: 1HQS). Overall folding manner of the monomer resembles that of *Ec* ICDH, but has several

Subunit A Subunit B

Clasp region Fig. 11. Diagram of *Bs* ICDH dimer. Each of monomer A, and monomer B having slightly different conformation are related by dimerization mediated through expansive portion of

Fig. 12. Amino acid sequence alignment of *Tth* ICDH, *Ec* ICDH, and *Bs* ICDH. The shaded and boxed sequences represent those identical to *Tth* ICDH sequence, and boxed ones represent those in similar to *Tth* ICDH sequence.

Crystallization, Structure and Functional Robustness of Isocitrate Dehydrogenases 327

Fig. 14. Diagram of *Tth* ICDH dimer. (A) Monomer A is shown in blue with its 141 extra residues at the C terminus region in red. Monomer B is shown in pale-green. (B) in the view,

Although more than 40 structures including many mutants of homo-dimeric ICDH are available from Protein Data Bank (RCSB PDB), there are few structures with as clearly drawn electron density as the nicotinamide ribose moiety for example. It is understood that there lies the difficulty due to disorder, hence, further structural information is still requisite to elucidate the catalytic mechanism. Observation by AFM of the surface of the crystal form II of *Tth* ICDH suggested that the crystals consisted of huge ellipsoidal bodies of a homocomplex of ICDH, of which long axis' diameter was 18.6 nm and short one was 10.9 nm. The

*Tth* ICDH has been rotated ~180° around the axis indicated in (A). (PDB ID: 2D1C).

**A**

**B**

**5. Conclusion**

#### **4.3** *Thermus thermophilus* **ICDH**

Between *T. thermophilus* and *E. coli* ICDHs, the residues of 37% are identical and those of 51% show similarity. The typical difference in the primary structure between the two enzymes is the presence of 141 extra residues at the C terminus in *Tth* ICDH. The region may contribute to the folding of the enzyme and the acquired thermostability of the enzyme (Miyazaki et al., 1992). Between *Tth* ICDH and *Bs* ICDH, the residues of 35% are identical and those of 50% have similarity. The primary sequence alignment of *Tth* ICDH, *Ec* ICDH, and *Bs* ICDH is shown in Fig. 12. Enzymes from thermophiles are often highly homologous to the mesophilic counterparts and the catalytic mechanisms are usually identical. The thermophilic enzymes have to be stable enough to withstand denaturation at elevated temperature where the thermophile optimally grows and possess simultaneously the flexibility required for enzymatic activity. Comparison among these enzymes of functions and structural similarities suggest functional robustness. The crystal structure of *Tth* ICDH is shown in Fig. 13. The overall core structure resembles those of *Ec* ICDH and *Bs* ICDH. As shown in Fig. 14, it can be seen that the string of the extra residues constitutes clasp domain, and it appears playing a role in the formation of a stable dimer.

Fig. 13. Cα trace of *Tth* ICDH monomer with citric acid. (PDB ID: 2D1C). Although there is a string of the extra sequence at the C terminus region, overall folding manner is quit similar to *Ec* ICDH and *Bs* ICDH. It may the reflection of functional robustness of the protein.

Although the preliminary X-ray study and crystallization of *Tth* ICDH were already reported by Ohzeki et al. (1995), and quite recently the crystal structure was determined by Lakonath & Kunishima (2006), we have described the other two curious crystal forms (crystal form I, and II) obtained for *Tth* ICDH under different crystallization conditions. Observation on the surface of one of the crystal forms (form II) by AFM motivated extended analysis on the possibility of *Tth* ICDH molecule taking the form of a supramolecular architecture under the condition and crystallization state. Study in this line leads to the important subject which concerns polymorphism of protein crystals, and has focused on the importance of spontaneous hierarchical construction with supramolecular assemblies as a block towards nano-composites.

Fig. 14. Diagram of *Tth* ICDH dimer. (A) Monomer A is shown in blue with its 141 extra residues at the C terminus region in red. Monomer B is shown in pale-green. (B) in the view, *Tth* ICDH has been rotated ~180° around the axis indicated in (A). (PDB ID: 2D1C).


Preface

**Section 4 Macromolecules and Food Quality 115**

**VI** Contents

José Luis Rivera Armenta

**Quality and Safety 137** Yankun Peng and Wenxiu Wang

Chapter 7 **Evaluation of Crosslinking Reaction in Adhesive Based Styrene-Butadiene Elastomers Using Infrared Spectroscopy 117** Beatriz Adriana Salazar Cruz, Ana María Mendoza Martínez, Alejandro Esquivel de la Garza, Sergio Moctezuma Espiricueto and

Chapter 8 **Application of Near-infrared Spectroscopy for Assessing Meat**

In this book you can find studies on Infrared Spectroscopy and Near Infrared Spectroscopy, Anharmonicity of biomolecules (proteins), biopolymers food quality and safety as well as Infrared Spectra of human tissues from diseases like Down syndrome tooth disorders and metastatic cancer of bones.

The book contains four sections:

#### **1) Introduction**

**2) Anharmonicity in protein vibrations and biopolymers.** The two chapters in this section are skillfully describing the calculation of anharmonicities for signature bands of proteins and the molecular cross-linking of a biopolymer.

**3) Food quality.** In this section one can find applications of MIRS and NIRS in food industry and research. These include quality control of food, e.g. the structure and dynamics of caro‐ tenoid and chlorophyll triplets in photosynthetic light-harvesting complexes in fruits and in farms in order to determine the amounts of carbon and nitrogen at a farm scale.

**4) Medical applications.** This section contains 3 chapters of MIRS and NIRS on medical ap‐ plications including the role of β-antagonists on the structure of human cancerous bone and characterization of bone-based graft materials; brain-computer interface in rehabilitation and brain oxygenation; and tooth disorders found in Down syndrome. Overall they provide a review of FT-IR on biomedical research in cells and biopolymer modifications in biomedi‐ cal applications.

> **Theophile Theophanides** Emeritus Professor of Chemical Engineering National Technical University of Athens Chemical Engineering Department Greece

**Section 1**


*3.3. Di*ff*erential Scanning Calorimetry (DSC)*

According to the data obtained in the coarse-grained state, during direct martensitic transformation (DMT), one distinct exothermal peak appears on the DSC curves. During the reverse martensitic transformation (RMT), an endothermic peak is observed associated with the appearance of the high-temperature austenitic phase B2 from the martensitic phase B19 . After thermal cycling with *n* = 100 cycles, a peak was observed from the intermediate R phase during direct martensitic transformation and a decrease in the temperatures of martensitic transformations (Ms, Af). After the maximum number of cycles, a multidirectional change in temperatures was observed, including a slight decrease in the temperatures of the beginning of the direct conversion (Ms) and the end of the reverse (Af), and an increase in the temperatures of the end of the direct conversion (Mf) and the beginning of the reverse (As) (Table 3). In the ultrafine-grained state, a decrease in martensitic temperatures was observed with an increase in the number of cycles from 0 to 250; at the same time, in this state, a transformation with the formation of an intermediate R phase proceeded without thermal cycling, and thermal cycling reduces temperatures—Rs (the temperature of the start of R transformation with direct MT) and Rf (the temperature of the end of the R transformation with direct MT). In this case, the decrease in the temperatures of direct martensitic transformation in the ultrafine-grained state was lower than that in the coarse-grained state. The graphs of the DSC curves of Ti-50.8 at.%Ni alloy are plotted according to Table 3 (Figure 12).

**Table 3.** Results of differential scanning calorimetry (DSC) of the Ti-50.8 at.% Ni alloy.

Af R = Temperature of the end of the reverse transformation with an intermediate R phase.

**Figure 12.** DSC curves of the Ti-50.8 at.% Ni alloy in CG (**a**) and UFG (**b**) states.