*3.5. BrHSP18.2s Promoters and Their Possible Control*

The induction of *Arabidopsis HSP18.2* (*Hsp18.1-CI*/AT5G59720) expression by HSFA2, a major thermotolerance HSF [24,26,31], is related to the role of HSFA2 in sustaining H3K4 methylation [24]. The promoter activity of *ArabidopsisHSP18.2* is highest at 35 ◦C [55]. This promoter contains eight HSE modules between −97 and −53 bp; the deletion of two modules maintains promoter activity, but a deletion of six modules causes a dramatic reduction in promoter activity [26]. All *BrHSP18.2* promoters contain seven HSE modules, implying that there is no difference in BrHSFA2 binding among the three *BrHSP18.2* promoters. In other organisms, at least two nGAAn units arranged head-to-head (nGAAnnTTCn) or tail-to-tail (nTTCnnGAAn) are required in the promoters of *HSPs* for efficient HSF binding [25]. Four HSE units were found in all *BrHSP18.2s* promoters, one of which is overlapping (Figure S4), indicating that *BrHSP18.2A* to *C* contain sufficient numbers of HSEs for TF binding. The binding of HSFA2 with several target genes including *HSP18.2* has been assessed [26], showing that two modules of a TATA-proximal HSE (nGAAnnTTCn) are essential for transcriptional activation by HSFA2. These modules are also conserved in all *BrHSP18.2s* promoters, suggesting that the expression differences among *BrHSP18.2s* upon HT exposure or warming conditions might be due to the presence of different numbers of HSFs such as *BrHSFA2* (which is controlled by alternative splicing) and/or other factor(s).


**Author details**

metastasis. Thus, doxycycline selectively targets malignant tumors and reduces their meta‐

Apigenin is a naturally occurring compound with anti-inflammatory, antioxidant, and anticancer properties. We have investigated the effects of apigenin on migration and metastasis in experimental HCC cell lines in vitro and in vivo. Apigenin dose-dependently inhibits the proliferation, migration, and invasion of PLC and Bel-7402 human HCC cells. It also suppresses tumor growth in PLC cell xenografts without altering body weight, thereby prolonging survival. Apigenin reduces Snai1 and NF-κB expression, reversed increases in EMT marker levels, increases cellular adhesion, regulates actin polymerization and cell migration, and inhibits invasion and migration of HCC cells. Therefore, apigenin may inhibit EMT by inhibiting the NF-κB/Snail pathway in human HCC.  Some EMT inhibitors.

thymoquinone

Tao Sun\* , Yuan Qin and Wei-long Zhong

\*Address all correspondence to<EMAIL_ADDRESS>
State Key Laboratory of Medicinal Chemical Biology and College of Pharmacy, Nankai University , Tianjin, People's Republic of China


**Abbreviations**

The following abbreviations are used in this manuscript:

## **References**

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*


*1.2.3 Treatment with α-amylase of Bacillus subtilis (BAA)*

BAA synthesized using *Bacillus subtilis* is found to have an optimum pH value between 5.3 and 6.4, and an optimum temperature of 50°C [20]. Fogarty and Kelly [21] reported that with starch as substrate BAA produces limit dextrins. BAA enzyme produces limit dextrins that cannot be hydrolyzed using glucoamylase obtained from mold *A. niger* and starch degradation often remains incomplete BAA is unsuitable for SSF process which mainly uses glucoamylase enzyme. The BAA enzyme activity reaches a maximum for a pH between 5.8 and 6.8 and a temperature of 55–60°C, when corn is used a substrate [22, 23].

### *1.2.4 Treatment with α-amylase expressed by Bacillus licheniformis (BAB)*

BAB, a new technical enzyme produced with a genetically engineered strain of *B. licheniformis* (Liquozyme, NOVO Nordisk, Denmark) [24] for its tolerant even at low pH values down to 4.8–5. But BAB is used to liquefy cereal mashes and is very effective. This enzyme express it activity up to 90°C and is used in pretreatment step for liquefying substrate in SSF process.

## *1.2.5 Treatment with fungal α-amylase of Aspergillus oryzae (FAA)*

Fogarty and Kelly [21], reported that FAA contains only a few amino acid residues and is highly stable in acidic pH. The enzyme activity is maximum in a pH between 5.5–5.9 and at a temperature of 40°C. FAA can hydrolyze starch granules at a pH of 7.2 and temperature of 37°C and only 40% of starch was dextrinized in pretreatment step after 60 hour. The optimum pH ranges from 5.0 to 6.0 while corn is used as a substrate. The optimum temperature is reported between 50 and 57°C. FAA reduces the viscosity which is desirable for saccharification and is more effective in producing dextrins.

### *1.2.6 Enzymes for starch saccharification in SSF process*

Glucoamylase (EC <IP_ADDRESS>) enzyme, hydrolyzes α-1,4, α-1,6, and α-1,3 glycosidic linkages of starch molecules. Hydrolysis rate of starch is based upon the size and structure of the molecules [21].


**HUMAN MUSCULOSKELETAL BIOMECHANICS**

Edited by **Tarun Goswami**

**INTECHOPEN.COM**

http://dx.doi.org/10.5772/1547 Edited by Tarun Goswami

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Theodoros B. Grivas, Hu Huang, Hongwei Zhao, Zhichao Ma, Jiabin Ji, Antonia Bankoff, Sofia Brorsson, Vincent De Sapio, Richard Li-Yang Chen, Gyorgy L. Nadasy, Giuseppe Maida, Tarun Goswami

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First published in Croatia, 2012 by INTECH d.o.o. eBook (PDF) Published by IN TECH d.o.o. Place and year of publication of eBook (PDF): Rijeka, 2019. IntechOpen is the global imprint of IN TECH d.o.o. Printed in Croatia

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3.3.2. Parasite-Host Relationships

Parasitic platyhelminths establish a chemical dialogue with the host by taking elements from it and by sending molecules from the parasite, having a different impact in their relationship with the host. In addition to oxygen diffusion, this class of parasites must ensure access to the nutrients they need for their development, so the presence of a sophisticated recognition and acquisition system through the use of specific transporters (similar to those of the host) is not surprising [30,188]. However, the parasite-host relationship is not limited to that, as the parasite can use the metabolism of the host cells to its advantage [93],

Through proteomic analysis, the presence of intact and functional host proteins has been confirmed in the hydatid fluid of *E. granulosus* and in the vesicular fluid of various species of the genus *Taenia* [50]. Although the ratio of parasite/host proteins is specific to each organism, the composition of these fluids against the composition of the serum of the respective host has been analyzed [50,189–192]. Some of the most abundant host proteins reported are serum albumin and immunoglobulins [87,190]. In the case of the former, the parasite can use it to maintain internal osmotic pressure, whereas the latter could help to prevent antigen exposure of the immune system [192,193]. Surprisingly, it has been reported that these organisms can incorporate various host antioxidant proteins to their antioxidant repertoire, such as the SOD, Prxs, and CAT isoforms [81,87].

In parasitic flatworms, the presence of various families of transporters specialized in the removal of metabolites and drugs has been reported. Although this representation is not homogeneous in flatworms, its participation in detoxification processes has been demonstrated [194–201]. In a previous experiment, we inhibited the TGR enzyme activity of *T. crassiceps* cysticerci under in vitro conditions and observed the appearance of GSSG in the culture medium, which led to the proposition that the cestode expels GSSG excess as a mechanism to avoid the change of the redox environment inside [165]. By searching for a transporter capable of carrying out the translocation of this oxidized species, we were able to identify some multidrug resistance (MDR) transporters in the genome of *T. solium*, which may potentially be responsible for carrying out this function [165].

### **4. Conclusions**

Oxygen has a dual function in organisms. In aerobic organisms it works mainly as a final electron acceptor during respiration, which results in greater energy production through the catabolic pathways, and its presence is related to the generation of ROS resulting in the expression of antioxidant systems involved in redox homeostasis maintenance.

Among flatworms, trematodes and cestodes have life cycles that develop in environments with different oxygen tension, which determine the development of special characteristics that have allowed them to adapt to varied conditions, such as:

• Finally, the exposure of the tegument to a higher concentration of O2 implies a greater production of ROS in it, as indirectly demonstrated by a significant presence of antioxidant enzymes in this region (SOD, GPx, Prx).

These overall data provide more information on the type of metabolism that is performed in the parasite in relation to pO2. However, as Boyunaga comments [82], "one must be cautious when trying to relate this O2 tension where these parasites develop" with the type of energy metabolism they carry out, since the reports in the literature can be controversial. Thus, an important aspect that must be considered is the presence of both types of metabolism, aerobic and anaerobic, in the same organism and its relation to the size of the parasite, the stage of the life cycle, and the degree of purity of the mitochondrion (at least two mitochondrial types in these organisms). Having pure populations of mitochondria would make it possible to determine with greater certainty what type of energy metabolism occurs at what time in the life cycle and in what region of the parasite.

**Funding:** This work was supported by the research grant IN217920 from Dirección General de Asuntos del Personal Académico (DGAPA), at Universidad Nacional Autónoma de México (UNAM).

**Acknowledgments:** Authors want to thank Ingrid Helena Mascher Gramlich, for proofreading the English-language version of this manuscript. Authors want to thank Fashion Designer Juan Antonio Rocha-Santiago for redesign and elaboration of the figures used in this paper.

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


*2.4. Protein Extraction and Quantification*

Proteins of wt and of the two mutant lines, untreated and treated (80 mg L−1 CdS QDs), were extracted. Frozen samples were ground to powder in liquid nitrogen using a mortar and pestle; 1 g aliquot was suspended in 6 mL of extraction buffer: 700 mM sucrose, 500 mM Tris-HCl, pH 7.5, 50 mM ethylenediaminetetraacetic acid (EDTA), 100 mM KCl, 2% dithiothreitol (DTT), 0.1% Protease Inhibitor Cocktail (Sigma-Aldrich), vortexed and mixed for 10 min on ice. An equal volume of 500 mM Tris-HCl buffered phenol was added, and the solution was mixed at room temperature for 10 min [30,31]. The samples were

centrifuged for 10 min at 5500× *g* and at 4 ◦C. The phenolic phase was collected in a new tube and back-extracted with 3 mL of extraction buffer. Proteins were precipitated from the phenolic phase overnight at −20 ◦C by adding five volumes of 0.1 M ammonium acetate (J.T. Baker, Deventer, The Netherlands) saturated in methanol. Precipitated proteins were centrifuged for 30 min at 5500× *g* and at 4 ◦C, the pellet was washed with cooled methanol and then with cooled acetone. After each washing step, the sample was centrifuged for 5 min at 5500× *g* and at 4 ◦C. Finally, the pellet was dried using a Speed Vac Concentrator 5301 (Eppendorf AG, Barkhausenweg, Hamburg, Germany).

The pellet was dissolved in 300 μL of isoelectofocusing (IEF) buffer containing 9 M urea, 4% 3-[(3-cholamidopropyl) dimethylamino]-1-propanesulfonate (CHAPS), 50 mM DTT, 0.001% protease inhibitor cocktail, 1% carrier ampholyte mixtures (pH 3–10, BioRad, CA, USA). Protein quantification was evaluated according to a modified Bradford assay [32] based on the acidification of the sample buffer with 20 mM HCl. Bovine serum albumin (BSA) was used as standard.

## *2.5. 2D Gel Electrophoresis*

The proteins mixtures were resolved by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). For proteins separation in the first dimension (IEF), 400 μg of proteins of each sample were loaded onto 11-cm ReadyStrip pH 5-8 IPG strips (BioRad, CA, USA) which had been rehydrated overnight with 250 μL IEF buffer containing the sample. Proteins were focused by PROTEAN® i12™ IEF System (BioRad, CA, USA) applying 250 V (60 min), 1000 V (60 min), 8000 V (2 h) and 8000 V up to 35,000 V/h.

After IEF, the strips were incubated 15 min in 3 mL of reducing buffer containing 6 M urea, 2% *w*/*v* DTT, 0.375 M Tris-HCl (pH 8.8), 20% *w*/*v* glycerol, 2% *w*/*v* SDS and for 15 min in 3 mL of alkylating buffer containing 6 M urea, 2.5% w/v iodoacetamide, 0.375 M Tris-HCl (pH 8.8), 2% *w*/*v* glycerol. The second dimension (SDS-PAGE) was performed using a CriterionTM Dodeca™ cell (BioRad, CA, USA) and 12% Criterion™ XT Bis-Tris gels (BioRad, USA) in 1 M MOPS (3-(N-morpholino)-propanesulfonic acid) buffer (1 M Tris, 20 mM EDTA and 2% *w*/*v* SDS).

2D gels were stained with QC Colloidal Coomassie G-250 (BioRad, CA, USA) and were scanned with a ChemiDocTM Imaging System (BioRad, CA, USA). Gel analysis was performed using PDQuest software (BioRad, CA, USA). Spot detection and matching between gels were performed automatically, followed by manual verification. The spot densities were normalized by local regression method and followed by a calculation against the whole gel densities. The percentage density of every spot was averaged over three replicate gels, and Student's *t*-test analysis (*p* < 0.05) was carried out to find statistically significant differences in protein abundances. Statistically significant spots were then excised from the gels using an EXQuest Spot Cutter (BioRad, CA, USA), destained by soaking the pieces of acrylamide in a 1:1 solution of 100 mM ammonium bicarbonate/acetonitrile for 30 min, and the proteins were hydrolyzed with trypsin at 37 ◦C overnight [33].


*5.1. Imbalanced Multi-Label Classification Performance*

Tables 2 and 3 show the performance of all the methods in terms of Micro-F1 and Macro-F1. The results are presented as the mean of ten repeated experiments. Based on these results, we reached the following conclusions:

of the two strategies works the best. As supporting evidence, **SORAG***F* is the best performer in 5/6 tasks and the second-best performer in the remaining task.

**Table 2.** Imbalanced multi-label classification comparison in terms of Micro-F1. The first and second best results are boldfaced and underscored, respectively.

**Table 3.** Imbalanced multi-label classification comparison in terms of Macro-F1. The first and second best results are boldfaced and underscored, respectively.


(c) Mosaicism

**Figure 2.** Karyotype 45,XX,rob(13;22)(q10;q10)—Robertsonian translocation.

446 Congenital Anomalies - From the Embryo to the Neonate

**Figure 3.** Karyotype 46,XY,t(1;15)(p36.3;q26.1)—reciprocal translocation.

Generally, mosaicism cases have the lowest frequency contributions to the total of the trisomies. Mosaicism can occur de novo in the offspring, but parental germ line mosaicism contributes to the recurrence risk [15]. Reduced mosaic [16], meaning low percentage of modified cell lines, or partial trisomy [17], equivalent with duplication, generally has a better prognosis by comparison with a homogenous complete trisomy, but this is not a rule [18].

The couple must be informed that there is no prophylaxis or treatment to correct the aneuploidy, but genetic counseling can provide the support for medically informed decisions to guide the management of the case.

If the couple wishes to keep a pregnancy with chromosomal disorder, they must be informed on the obstetrical complications that may arise, the life expectancy, and the natural history of the disease neonatally and into adulthood.

A trisomy prenatal case, especially 13 or 18, may present with different obstetrical challenges: miscarriage and stillbirth are more frequent than compared to the general population. Structural anomalies of the fetuses lead to a negative prognosis after birth and low life expectancy [19].

Screening and diagnosis limitations for trisomy 13 lead to underdiagnosis of this aneuploidy. Genetic counseling should bring into discussion the viable fetuses in the second trimester (60% of the cases), when life expectancy is very hard to predict and there is no longer the alternative to terminate the pregnancy. It is crucial to inform the parents on the neonatal procedures for resuscitation, possibilities to correct certain defects so that the couple is prepared to face the trauma of having a child with lethal defect [20].

established, then the recurrence risk can be calculated. Probability of inheritance based on Mendel's principles and conditional probability (also known as Bayesian analysis, based on

Prenatal Genetic Counseling in Congenital Anomalies http://dx.doi.org/10.5772/intechopen.74394 449

The risk of expressing a monogenic disease is dependent not only on the pattern of inheritance, but also on other factors such as the incidence of the disease, the presence of other affected members, the penetrance and variable expressivity, ethnicity, and the influence of environmental factors.

An autosomal dominant disease is a condition expressed in both heterozygous, carrying one copy, and homozygous individuals, carrying two copies one from each parent. The disease is caused by a single gene defect located on an autosome. The affected individuals are usually heterozygous, and the homozygous genotype is associated with more severe features or can be lethal. Females and males exhibit the trait in approximately equal proportions and severity of clinical signs is similar between the two sexes. Both sexes are equally likely to transmit the mutation to their offspring. Mostly, the affected offsprings are descendants of an affected heterozygous and a normal parent. On average, half of the children will be heterozygous and express the disease and half will not. Rarely, homozygous are seen in autosomal dominant diseases. This status can be due to a higher frequency of a gene with mild effects, late onset (e.g. Huntington disease) or when both parents are affected (e.g. achondroplasia). Unusually, an affected homozygous parent will transmit the disease to all of his children. On the pedigree, a vertical transmission pattern is observed (**Figure 4**), and the disease phenotype is usually seen in one generation after another. The disease does not skip generations: if an individual has an autosomal disease, in most of the cases, one parent must also have it [1, 2].

Frequently, autosomal dominant disorders involve different organs and systems of the body; however, dominant conditions affecting one organ have been described (e.g., congenital cataract). The capacity of a single gene to affect unrelated organs is called *pleiotropy* (e.g., Marfan syndrome can affect the skeletal, ocular, and cardiovascular systems; some affected individuals have all features, whereas others may have almost none). In addition, the clinical features in autosomal dominant disorders can show remarkable variation between patients, even between the members of the same family. This difference between individuals is referred to as *variable expressivity* (e.g., in autosomal dominant polycystic kidney disease, some affected individuals develop renal failure in early adulthood, whereas others have just a few renal cysts that do not significantly influence renal function). Occasionally, the heterozygous and

homozygous individuals express identical phenotype (complete dominance) [2, 23].

Sometimes, a dominant mutation is inherited, but the condition it determines is not expressed. In these cases, the gene has *reduced (incomplete)penetrance.* The term penetrance is used in monogenic inheritance to indicate the probability of a gene to influence the phenotype. A number of autosomal dominant diseases show an incomplete penetrance (e.g., polydactyly), meaning that a person has the mutation but shows no evidence of a disease. A gene is *completely penetrant* if each individual who inherited the mutation expresses clinical

Bayes' theorem on probability) are used to calculate genetic risk [1].

**3.1. Autosomal dominant inheritance**

features (e.g., neurofibromatosis type I) [3].

For trisomy 18, only 10% of the neonates survive longer than 1 year. Diagnosing this trisomy though genetic testing is essential for decision-making during the neonatal life, where critical emergency interventions and choosing invasive treatments are often required [21].

Trisomy 21 has a life expectancy of almost 60 years. Following up, the patient asks for collaborations with multiple medical specialties: cardiological, ENT, ophthalmology, endocrinology, to assess possible complications. During their pediatric life, other interventions are generally symptomatic and similar to their euploid peers [22]. The parents must be prepared though through genetic counseling for the possible difficulties due to motor and cognitive delay. Support in the patient's lifestyle can also come from nongovernmental associations and patient support groups, e.g., Down Syndrome International (https://ds-int.org/ down-syndrome-your-country).


**5.1 YOLO**

YOLO is a detection algorithm based on a single-stage CNN architecture that can detect multiple objects in an image in real-time. The main idea is to predict bounding boxes and confidence values for grid cells into which an image or frame is divided. In the cases when an object is spread across more than one grid cell, the holder of its prediction will be the center cell.

There have been four versions of YOLO since it was first published. In the original version, the network architecture has 24 convolutional layers with two additional fully connected layers. The purpose of the convolutional layers is the feature extraction, while for fully connected layers to calculate the bounding boxes predictions and probabilities. The bounding box predictions and class probabilities are associated with grid cells so that if an object occupies more than one cell, the center cell will be designated to be the holder of prediction for a particular object [11].

In the next version, YOLOv2 [12], five convolution layers were replaced with max-pooling layers, and instead of the fully connected layers, predefined anchor boxes are introduced. In the training phase, to define the anchor boxes, YOLOv2 uses k-means clustering on ground-truth bounding boxes where boxes translations are relative to a grid cell.

YOLOv3 [13] is the third version of the YOLO object detector. It consists of 53 convolutional layers of (3 × 3) and (1 × 1) filters with shortcut connections between layers (residual blocks) used for feature extraction. The last convolutional layer predicts the bounding boxes, the confidence scores, and the prediction class. It predicts possible bounding boxes at three different scales using a structure that is similar to feature pyramid networks. In this way three sets of boxes are predicted at each feature map cell for each scale, to improve the detection of objects of different sizes.

#### *5.1.1 Player detection with YOLO*

Player and ball detection performance of the YOLOv3 detector was tested on the handball dataset using two different models. The reference model, further marked as Y, is the pre-trained YOLOv3 model with 608 x 608 input image size with weights pre-trained on the COCO dataset and no additional training. The pre-trained model contains the person and sports ball among other classes from the COCO dataset. Transfer learning [14] was used to avoid training the models from the beginning.

**151**

**Table 1.**

*Evaluation of the object detector.*

**Figure 4.**

*Application of Deep Learning Methods for Detection and Tracking of Players*

The second model (YBP) was trained using transfer learning, on PBD-Handball part of the dataset. The input image resolution was increased to 1024 x 1024 from 608 x 608 of the original model and the model was trained for approximately 80 epochs. **Figure 4** shows an example of detection results for the

both classes and the mean average precision are used and shown on **Table 1**.

To evaluate the performance of a model, the average precision (AP) metric of

The best results for ball detection in terms of AP were achieved with the YPB model, which was trained on additional examples for both ball and person class and had an increased input image size. A small amount of training data can significantly improve detection results as can be seen in the example of ball detection which improved for 23%. The achieved results are satisfactory given the demanding environment but are not sufficient for commercial application, so the training dataset

Mask R-CNN [15] is a two-stage CNN that can not only detect and localize multiple objects simultaneously present in the image, but also provides a segmentation mask of the objects, that is, assigns a membership value to each of the pixels belonging to the object. The first stage of the network is a region proposal network that finds the regions of the image that are likely to contain objects (regions of interest, RoI) and proposes candidate object bounding boxes. A sliding window is applied to the feature map to examine the probability whether there is an object class or a background in the examined region. Then, bounding boxes and masks are

generated with the corresponding confidence values for all possible classes. In the second stage, there are two parallel branches of the network, a fully convolutional branch for predicting the segmentation masks and a fully connected branch used on each RoI for classification and for adjusting the proposed box size. There are similar networks like R-CNN, Fast R-CNN, Faster R-CNN [16] on

which Mask R-CNN is based to look up for object detection purpose.

*Player detections in handball scene with YOLOv3 (bounding boxes with confidences).*

**Model Ball AP Person AP mAP** Y 13.53 66.13 39.83 YPB 35.44 63.77 49.61

**PBD-Handball**

*DOI: http://dx.doi.org/10.5772/intechopen.96308*

"person" class.

should be increased.

**5.2 Mask R-CNN**


3.2.4. Color

It is crucial to control the color of mayonnaise samples to obtain the desired color that most affects the consumer's willingness to purchase or taste a new product. Therefore, values of lightness (L\*), redness (a\*) and yellowness (b\*) of the prepared vegan mayonnaise samples are listed in Table 6.

**Table 6.** Color of mayonnaises.

*n* = 5; SD—Standard Deviation; Different letters (a–f) within the same column indicate significant differences between color parameters (L\*—lightness; a\*—redness; b\*—yellowness) of aquafaba-based mayonnaise samples with blends of refined rapeseed oil and cold-pressed rapeseed oil (MRO), cold-pressed sunflower oil (MSO), cold-pressed linseed oil (MLO), and cold-pressed camelina oil (MCO); MT1—commercial egg yolk mayonnaise from producer 1; MT2—commercial egg yolk mayonnaise from producer 2; MV—commercial vegan mayonnaise (Tukey's post hoc test, *p* < 0.05).

The Tukey's post hoc test indicated that the color parameters for mayonnaises with blends of RRO and various cold-pressed oils significantly differ from each other. The highest lightness value (L\* = 48.7–47.7) had MRO, MT1 and MT2, respectively. It can be caused by the smaller OD sizes in these samples (Figure 3). Due to light scattering, mayonnaises with smaller OD sizes are whiter, and also the intensity of the yellow color is lower [56]. It is noteworthy that store-bought samples had higher redness values (a\* = 2.2–3.4) than the prepared aquafaba-based samples (a\* = −0.3–0.9). High yellowness values (b\* = 9.0–11.2) for commercial samples MT1 and MT2 containing a high egg yolk content can be preferable by consumers. The highest b\* value (11.3) for the MV sample was probably caused by the addition of carotenoids. High b\* values (6.7–10.9) and low a\* values (−0.3–0.9) for MRO, MSO, MLO and MCO samples with cold-pressed oils can be explained by the presence of natural pigments, mainly carotenoids and chlorophyll, in added press-cold oils.

For comparison, the a\* and b\* values of mayonnaises with different oil-to-aquafaba (O/A) ratios increased significantly for higher oil contents in mayonnaises (a\* = 3.5–4.1 and b\* = 36.5–39.9 for O/A = 80/15, while a\* = 2.6–2.9 and b\* = 30.5–31.8 for O/A = 70/25). Moreover, mayonnaise samples with smaller OD sizes had greater brightness values [23].


**1. Introduction**

Autonomous (also called self-driving, driverless, or robotic) vehicle operation is a significant academic as well as an industrial research topic. It is predicted that fully autonomous vehicles will become an important part of total vehicle sales in the next decades. The promotion of autonomous vehicles draws attention to the many advantages, such as service for disabled or elderly persons, reduction in driver stress and costs, reduction in road accidents, elimination of the need for conventional public transit services, etc. [1,2].

A typical autonomous vehicle system contains four key parts: localization, perception, planning, and controlling (Figure 1). Positioning is the process of obtaining a (moving or static) object's coordinates with respect to a given coordinate system. The coordinate system may be a local coordinate system or a geodetic datum such as WGS84. Localization is a process of estimating the carrier's pose (position and attitude) in relation to a reference frame or a map. The perception system monitors the road environment around the host vehicle and identifies interested objects such as pedestrians, other vehicles, traffic lights, signage, etc.

By determining the coordinates of objects in the surrounding environment a map can be generated. This process is known as Mapping.

Path planning is the step that utilizes localization, mapping, and perception information to determine the optimal path in subsequent driving epochs, guiding the automated

**Citation:** Zheng, S.; Wang, J.; Rizos, C.; Ding, W.; El-Mowafy, A. Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis. *Remote Sens.* **2023**, *15*, 1156. https://doi.org/10.3390/rs15041156

Academic Editors: Yuwei Chen, Changhui Jiang, Qian Meng, Bing Xu, Wang Gao, Panlong Wu, Lianwu Guan and Zeyu Li

Received: 27 October 2022 Revised: 6 January 2023 Accepted: 10 January 2023 Published: 20 February 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

vehicle from one location to another location. This plan is then converted into action using the controlling system components, e.g., brake control before the detected traffic lights, etc.

**Figure 1.** Functional components of an autonomous driving system.

All these parts are closely related. The location information for both vehicle and road entities can be obtained by combining the position, perception, and map information. In contrast, localization and mapping can be used to support better perception. Accurate localization and perception information is essential for correct planning and controlling.

To achieve fully automated driving, there are some key requirements that need to be considered for the localization and perception steps. The first is accuracy. For autonomous driving, the information about where the road is and where the vehicle is within the lane supports the planning and controlling steps. To realize these, and to ensure vehicle safety, there is a stringent requirement for position estimation at the lane level, or even the "wherein-lane" level (i.e., the sub-lane level). Recognition range is important because the planning and controlling steps need enough processing time for the vehicle to react [3]. Robustness means the localization and perception should be robust to any changes while driving, such as driving scenarios (urban, highway, tunnel, rural, etc.), lighting conditions, weather, etc.

Traditional vehicle localization and perception techniques cannot meet all of the aforementioned requirements. For instance, GNSS error occurs as the signals may be distorted, or even blocked, by trees, urban canyons, tunnels, etc. Often an inertial navigation system (INS) is used to support navigation during GNSS signal outages, to continue providing position, velocity, and altitude information. However, inertial measurement bias needs frequently estimated corrections or calibration, which is best achieved using GNSS measurements. Nevertheless, an integrated GNSS/INS system is still not sufficient since highly automated driving requires not only positioning information of the host vehicle, but also the spatial characteristics of the objects in the surrounding environment. Hence perceptive sensors, such as Lidar and Cameras, are often used for both localization and perception. Lidar can acquire a 3D point cloud directly and map the environment, with the aid of GNSS and INS, to an accuracy that can reach the centimeter level in urban road driving conditions [4]. However, the high cost has limited the commercial adoption of Lidar systems in vehicles. Furthermore, its accuracy is influenced by weather (such as rain) and lighting conditions. Compared to Lidar, Camera systems have lower accuracy but are also affected by numerous error sources [5,6]. Nevertheless, they are much cheaper, smaller in size, require less maintenance, and use less energy. Vision-based systems can provide abundant environment information, similar to what human eyes can perceive, and the data can be fused with other sensors to determine the location of detected features.

A map with rich road environment information is essential for the aforementioned sensors to achieve accurate and robust localization and perception. Pre-stored road information makes autonomous driving robust to the changing environment and road dynamics. The recognition range requirement can be satisfied since an onboard map can provide timely information on the road network. Map-based localization and navigation have been studied using different types of map information. Google Map is one example as it provides worldwide map information including images, topographic details, and satellite images [7], and it is available via mobile phone and vehicle apps. However, the use of maps will be limited by the accuracy of the maps, and in some selected areas the map's resolution may be inadequate. In [8], the authors considered low-accuracy maps for navigation by combining

data from other sensors. They detected moving objects using Lidar data and utilized a GNSS/INS system with a coarse open-source GIS map. Their results show their fusion technique can successfully detect and track moving objects. A precise curb-map-based localization method that uses a 3D-Lidar sensor and a high-precision map is proposed in [9]. However, this method will fail when curb information is lacking, or obstructed.

Recently, so-called "high-definition" (HD) maps have received considerable interest in the context of autonomous driving since they contain very accurate, and large volumes of, road network information [10]. According to some major players in the commercial HD map market, 10–20 cm accuracy has been achieved [11,12], and it is predicted that in the next generation of HD maps, a few centimeters of accuracy will be reached.  The autonomous car can use the HD map to precisely locate the host-car within the road lane and to estimate the relative location of the car with respect to road objects by matching the landmarks which are recognized by onboard sensors with pre-stored information within the HD map.

Therefore, maps, especially HD maps, play several roles in support of autonomous driving and may be able to meet the stringent requirements of accuracy, precision, recognition ranging, robustness, and information richness. However, the application of the "map" for autonomous driving is also facilitated by techniques such as Simultaneous Localization and Mapping (SLAM). SLAM is a process by which a moving platform builds a map of the environment and uses that map to deduce its location at the same time. SLAM, which is widely used in the robotic field, has been demonstrated [13,14] as being applicable for autonomous vehicle operations as it can support not only accurate map generation but also online localization within a previously generated map.

With appropriate sensor information (perception data, absolute and dead reckoning position information), a high-density and accurate map can be generated offline by SLAM. When driving, the self-driving car can locate itself within the pre-stored map by matching the sensor data to the map. SLAM can also be used to address the problem of DATMO (detection and tracking of moving objects) [15] which is important for detecting pedestrians or other moving objects. As the static parts of the environment are localized and mapped by SLAM, the dynamic components can concurrently be detected and tracked relative to the static objects or features. However, SLAM also has some challenging issues when applied to autonomous driving applications. For instance, "loop closure" can be used to reduce the accumulated bias within SLAM estimation in indoor or urban scenarios, but it is not normally applicable to highway scenarios.

This paper will review some key techniques for SLAM, the application of SLAM for autonomous driving, and suitable SLAM techniques related to the applications. Section 2 gives a brief introduction to the principles and characteristics of some key SLAM techniques. Section 3 describes some potential applications of SLAM for autonomous driving. Some challenging issues in applying the SLAM technique for autonomous driving are discussed in Section 4. A real-world road test to show the performance of a multi-sensor-based SLAM procedure for autonomous driving is described in Section 5. The conclusions are given in Section 6.


**7. Generators**

In Nuclear Medicine environment, sometimes is useful to have a regular provision of radioisotopes for studies to be performed without the restrictions of providers time dependences, for example when studies has to be done anytime of the day in emergency conditions. If physician suspects an infection in a patient admitted in Emergency Room, it will be of utmost usefulness to have Nuclear Medicine images done with appropriate radiopharmaceuticals to solve the question about the most effective treatment to be offer to the patient. Either way, sometimes in Cardiology it is of high importance to know about percentage of isquemic muscle, but patient has not the luxury of time to undergo a catheterism, so it is more effective and quick to have Nuclear Medicine images and cine of the heart. In many cases like this, have a good availability of radiotracers make the differences between a correct and opportune answer or a misdiagnosis.

This is the reason why radioisotopes generators have become so popular beside the fact that in countries like Venezuela where there is no nuclear production, sometime become very hard to warranty a regular supply. A radioisotopes generator is a device in which you can contain a pair father/daughter in which the daughter is the product of interest for studies purposes and father only come to generate the full amount of daughter needed. Due to the short half life we need for the radioisotope to be safe handle in hospital conditions, it would be useful to find a pair father and daughter that warranty the in time provision of radioisotope needed. During the generator useful life father has to decay completely to the useful daughter so it can be easily recharged, disposed or returned to provider. Such pair must that accomplish some conditions like:

reactors is that in cyclotron you can use 98Mo enriched target to be activated by neutron irradiation in a (n,γ) reaction, while 99Mo coming from fission include very expensive production beside the complex regulations due to the highly enriched Uranium targets.

(CaNa399mTc)

Calcium Gluconate Lactobionate

Calcium Glucoheptonate

2,4 dimercaptosuccinic acid

Sodium Calcium Phytate

Albumin Macroagregates Microspheres (50μ)

(MDP) Metilendiphosphonate

HIDA (Hepatobiliary IminoDiacetic Acid)

99mTc HMPAO (HexaMethylPropileneAmineOxime)

Monofluorphosphate Diphosphonate Pirophospate

Microspheres (0.5-4 μ)

Tetracycline Citrate

**TARGET ORGAN 99mTc RADIOPHARMACEUTICALS Brain** DTPA (DiethylTriaminoPentacetic Acid)

**Kidneys** DTPA (DiethylTriaminoPentacetic Acid)

Manitol Dextrose Penicilamine

Sn Hidroxide Sodium Phytate

**Brain Perfusion** ECD (EthylCysteinate Dimer)

**Liver** 99mTc Sulphur

**Bone** Poliphosphate

**Dynamic Studies** Albumina

**Tumors** Bleomicine

**Spleen** Red Blood Cell Markers **Spleen and Bile** Vitamine B6 glutamic

Table 4. Radiuopharmaceuticals used with 99mTc for diagnostic studies.

**Blood Pool** 99mTc Albumina

**White Blood Cell or platelets (infection or inflammation)**

**Lungs** Inorganic Macroagregate

After radiochemist discover some pairs of father/daughter that accomplish this characteristics, some were built in a shielded container to be send to hospital to extract the daughter. It makes radiosotopes clinically useful and commercially available.

Medicine is not the only client for radioisotopes generator, also we will talk about some other uses of them that are increasing its popularity thru years. So let´s have a few words about their relationship. As in any father/daughter relationship there are different kinds, in radioactive "family" we can talk about two kind of equilibrium that this families reach, they are called transient and secular equilibrium. Equilibrium meaning when father and daughter exist in significant proportion to one another. Secular equilibrium is a condition that they can reach when father physical half life is 2 or 3 magnitude orders greater that daughter´s (100 to 1000 times greater). It means when daughter decay many times father seems no to be affected. While transient equilibrium is a condition that is reach when father physical half life is about 10 times daughter´s. It is, when daughter decay few times father can decay to its 50%, i.e a full half life. Note that if physical half life of the daughter is larger that the father equilibrium can never be reach because father will be ever alone.

#### **Secular Equilibrium Generators**

$$\begin{aligned} ^{68}G & \xrightarrow{\varepsilon, 275d} ^{68}Ga \xrightarrow{\beta^{+}, \varepsilon, \gamma, 1.14} ^{h} ^{68}Zr \\\\ ^{81}Rb & \xrightarrow{\beta^{+}, \varepsilon, 4.7h} ^{61m}Kr \xrightarrow{\gamma, 13s} ^{61}Kr \\\\ ^{82}Sr & \xrightarrow{\varepsilon, 25d} ^{62}Rb \xrightarrow{\beta^{+}, \varepsilon, \gamma, 75s} ^{62}Kr \\\\ ^{113}Sn & \xrightarrow{\varepsilon, 118d} ^{113m}In \xrightarrow{\gamma, 1.7h} ^{113}In \end{aligned}$$

#### **Transient Equilibrium Generators**

$$^{99}Mo \xrightarrow{\beta^{-} \cdot \chi, 67h} ^{99m}Tc \xrightarrow{\chi, 6 \cdot h} ^{99}Tc$$

$$^{198}W \xrightarrow{\varepsilon, 275d} ^{198}Rh \xrightarrow{\beta^{-}, 17 \cdot h} ^{198}Os$$

Although this last one has a promising future in metastatic disease pain reliever and as a monoclonal antibody marker, the most popular generator in Nuclear Medicine is the Mo/Tc one. It is Techenetium is highly biocompatible in the Nuclear Medicine fashion so it can be used in a large number of studies.

This Mo/Tc generators can be produced in cyclotrons or reactors and as in many radioisotope produced, the advantages of using that from cyclotron in front of that of

5. This separation must be passive in terms of no violent chemical reaction must be

6. The daughter must be eluted with a human compatible solution to warranty biological

7. The human intervention would be minimum to warranty the minimum exposure to

8. Radiation protection now is not the unique concern but chemical and biological

After radiochemist discover some pairs of father/daughter that accomplish this characteristics, some were built in a shielded container to be send to hospital to extract the

Medicine is not the only client for radioisotopes generator, also we will talk about some other uses of them that are increasing its popularity thru years. So let´s have a few words about their relationship. As in any father/daughter relationship there are different kinds, in radioactive "family" we can talk about two kind of equilibrium that this families reach, they are called transient and secular equilibrium. Equilibrium meaning when father and daughter exist in significant proportion to one another. Secular equilibrium is a condition that they can reach when father physical half life is 2 or 3 magnitude orders greater that daughter´s (100 to 1000 times greater). It means when daughter decay many times father seems no to be affected. While transient equilibrium is a condition that is reach when father physical half life is about 10 times daughter´s. It is, when daughter decay few times father can decay to its 50%, i.e a full half life. Note that if physical half life of the daughter is larger

involved in the process, to warranty the chemical safeness

9. The granddaughter must be of very long time as to be consider stable

daughter. It makes radiosotopes clinically useful and commercially available.

that the father equilibrium can never be reach because father will be ever alone.

ሱۛۛۛሮ ܩܽ ఉశǡఌǡఊǡଵǤଵସ ሱۛۛۛۛۛۛۛۛሮ ܼ݊ ଼ ଼ ଼

ሱۛۛۛۛۛሮ ݎܭ ఊǡଵଷ௦ ሱۛۛሮ ݎܭ ଼ଵ ଼ଵ ଼ଵ

ሱۛۛሮ ܴܾ ఉశǡఌǡఊǡହ௦ ሱۛۛۛۛۛۛሮ ݎܭ ଼ଶ ଼ଶ ଼ଶ

ሱۛۛۛሮ ܫ݊ ఊǡଵǤ ሱۛۛۛሮ ܫ݊ ଵଵଷ ଵଵଷ ଵଵଷ

ሱۛۛۛۛۛሮ ܶܿ ఊǡ ሱۛሮ ܶܿ ଽଽ ଽଽ ଽଽ

ሱۛۛۛሮ ܴ݄ ఉషǡଵ ሱۛۛۛۛሮ ଵ଼଼ ଵ଼଼ ܱݏ ଵ଼଼ Although this last one has a promising future in metastatic disease pain reliever and as a monoclonal antibody marker, the most popular generator in Nuclear Medicine is the Mo/Tc one. It is Techenetium is highly biocompatible in the Nuclear Medicine fashion so it can be

This Mo/Tc generators can be produced in cyclotrons or reactors and as in many radioisotope produced, the advantages of using that from cyclotron in front of that of

ܩ݁ ఌǡଶହௗ

ܴܾ ఉశǡఌǡସǤ

ఌǡଶହௗݎܵ

ܵ݊ ఌǡଵଵ଼ௗ

ܯ

ܹ ఌǡଶହௗ

ఉషǡఊǡ

safeness

radiation

protection is also very critical

**Secular Equilibrium Generators**

**Transient Equilibrium Generators**

used in a large number of studies.

reactors is that in cyclotron you can use 98Mo enriched target to be activated by neutron irradiation in a (n,γ) reaction, while 99Mo coming from fission include very expensive production beside the complex regulations due to the highly enriched Uranium targets.

Table 4. Radiuopharmaceuticals used with 99mTc for diagnostic studies.

• Stability

• Target effectiveness • Activation effectiveness

• Area monitorization • Personal dosimetry • Activation control • Airborne debris • Chimney

• Shielding

**accounting to:**

• Output dose and exposition

• Area classification and signs

• Personnel Medical Check up:

• Radiation Safety Committee

• Radioisotope Production

• Possible emergency

• Pre-start conditions

• Decay rate • Free release dates

• Fractionation doses

• Beam Energy • Output flux

• Mechanical movements of inner and outer doors

**8.1.3 Radiation Safety aspects to be under control are:**

• Previous to begin working in the facility

• Posterior to end laboral relationship with the facility

**<IP_ADDRESS> In radioisotope production it must be carefully checked:**

• Area and ventilation ducts monitoring during cyclotron is on • Activation and contamination control after cyclotron is turn off

• Radioactive waste disposal entry and release record

**<IP_ADDRESS> Radioactive material handling for diagnostic studies**

**8.1.4 Daily journey: Also three aspects need to be controlled step by step,**

• Annual (prevocational) check up

• Handling radioactive material for studies

• Fractionation residues and contamination

• Total activity produced in a cyclotron run

• Patient injection site and procedure

• Pre and post Hot Cell monitoring

• Radioactive waste disposal • Place design • Waste classification


*Space Radiation-Induced Hematopoietic Stem Cell Injury DOI: http://dx.doi.org/10.5772/intechopen.88914*

*Beyond LEO - Human Health Issues for Deep Space Exploration*

contribute to γ-irradiation-induced ROS production in HSCs [66], which was supported by increasing NOX4 expression, rather than other isoforms of NOXs in γ-ray irradiated HSCs [66]. Diphenyliodonium (a selective NOX inhibitor) treatment can partially restore the functional impairment in γ-ray irradiated HSCs by decreasing irradiation-induced ROS production in HSCs [66]. For space radiation circumstance, the higher level of NOX4 expression was observed in proton-irradiated HSCs than that in unirradiated HSCs. These data indicated that NOX enzyme, especially NOX4, might be involved in the induction of ROS production in proton-irradiated HSCs. The importance of ROS production in space radiation-induced HSC injury should further be assessed by using NOX4 inhibitor or other antioxidants, such as N-acetylcysteine and gamma-tocotrienol in future studies. There are some other potential unanswered questions including (1) whether these chronically oxidativestressed HSCs induced by proton radiation experience senescence, (2) whether these space-irradiated HSCs have chromosomal instability, and (3) whether the chromosomal aberrant HSCs after space radiation result in the leukemia development,

which was evidenced in mice after γ-irradiation exposure [38, 65, 68].

risk of loss self-renewal of HSCs.

antioxidants, which should be investigated in the future.

**4. Oxygen radiation and hematopoietic stem cells**

One of HSC properties is its self-renewal ability, which is sustained via its slow cycling and quiescence. By using BrdU-chasing assay and H2B-GFP mice model, it has been shown that dominant HSCs divide only once every 145 days, which ensures self-renewal capacity along with providing whole life blood homeostasis and avoiding HSC exhaustion [69]. It was reported that loss of FOXO3a resulted in increasing ROS production and accelerating HSC cycling, which is along with the defect of HSC self-renewal capacity and the exhaustion of HSCs. N-acetylcysteine (NAC), an antioxidant, can protect FOXO3a mutant HSCs from oxidative stress and restore HSC dormancy. The same phenotype was also seen in the case of loss of Bmi-1 and TSC1 in mice [70–72], which is due to increasing ROS production and cycling in HSCs. Upon proton radiation, data have shown that there were far fewer HSCs in G0 phase and higher numbers of HSCs in G1 phase than nonirradiated controls. Proton radiation-induced HSC cycling is consistent with upregulation of positive cell cycle regulators cyclin D1 and cyclin D3. Although HSC proliferation might compensate for the decreased number of HSCs after proton radiation, it will be at

Additionally, it has demonstrated that the persistent increase of DNA damage in proton-irradiated HSCs, but not in HPCs, was associated with proton radiationinduced ROS production in HSCs. Unrepaired DNA damage in proton-irradiated HSCs might negatively affect HSC self-renewal, proliferation, and differentiation, leading to long-term functional damage in HSCs. Taken together, these findings provide strong evidence showing that proton TBI induces not only acute hematopoietic injury but also long-term BM suppression and HSC damage. These detrimental effects of proton radiation on hematopoietic cells are closely related to the induction of oxidative stress in irradiated HSCs. The proton exposure-induced acute and long-term hematopoietic damage might be ameliorated through using

As we discussed above, GCR contains various HZE particles including 56Fe, 28Si, 16O, and 12C, which have more detrimental effects on normal tissues than do photon and proton radiations during spaceflight. Oxygen (16O) radiation has relatively high-charge and high-linear energy transfer (LET), leading to a high relative biological effectiveness. In this section, we will mainly discuss the biological negative

effects of 16O on hematopoietic stem cells in long-duration space missions.

**86**

Hematopoietic cells in the body are the most radiosensitive cells to radiation [73, 74]. Exposure to γ-irradiation causes both acute and long-term damage in hematopoietic stem and progenitor cells (HSPCs), which is due primarily to radiation-induced cellular apoptosis and senescence in HSPCs [37–39, 65]. Using porcine and mice model, it has documented that proton radiation induced both acute and long-term hematopoietic damage. We have described the acute and residual effects of proton radiation on hematopoietic stem cells showing that numbers and function of bone marrow HSCs in mice were detrimentally affected. The negative effects of proton radiation mainly contribute to increasing the production of oxidative stress and DNA damage in irradiated HSCs [53]. 56Fe radiation causes significant alterations in the expression of repetitive elements and DNA methylation, and 0.1-0.4 Gy of 56Fe radiation resulted in significant epigenetic changes in hematopoietic stem and progenitor cells in a mouse model [75]. Using cultured human hematopoietic stem and progenitor cells, it was found that 12C radiation induced chromosome aberrations and cellular apoptosis [76]. 0.3–0.9 Gy of 28Si radiation triggers a significant increase of cellular apoptosis in irradiated mice HSCs at 4 weeks after the exposure, which results in the deficiency of numbers and clonogenic function of irradiated HSCs [77]. These findings indicate that GCR, including different forms of ionizing radiation, induces acute and residual injury in hematopoietic stem cells. However, it remains elusive whether 16O radiation induces acute and long-term hematopoietic effects and what main factors are involved in the negative effects on HSCs under 16O exposure.

In one of our experiments, C57BL/6 J mice were exposed to 0.1, 0.25, and 1.0 Gy 16O (600 MeV/n) total-body irradiation (TBI) and analyzed the effects of 16O radiation on peripheral blood and BM 2 weeks after the exposure [51] (**Table 3**). Since hematopoietic cells are known to be radiosensitive, it is not surprising that a significant decrease was observed in peripheral WBC and platelet counts in mice exposed to 1.0 Gy of 16O. In comparison to 16O radiation, peripheral blood cell counts, including numbers of WBCs and platelets, were almost recovered to normal levels at 2 weeks after 1.0 Gy of γ-ray radiation in BALB/c mice [78]. This might due to (1) different animal species used and (2) different biological effectiveness of 16O and γ-ray radiation along with high LET properties of 16O. 16O TBI causes cellular apoptosis in hematopoietic progenitors but not hematopoietic stem cells at 2 weeks postexposure. To monitor how fast HPCs recover from 16O TBI, apoptotic assay was performed at 3 months after 0.1, 0.25, and 1.0 Gy of 16O TBI, showing that the apoptotic levels in HPCs and HSCs after the exposure are similar to those in nonirradiated mice. These data suggest that HPCs have a slower recovery than HSCs after 16O TBI.

Previous studies have demonstrated that the functional defect of mouse HSCs was observed under either radiation or chemotherapeutic drug treatment. For example, the reconstitution capacity of mouse HSCs has detrimental effects under 1.0 Gy of total-body γ-ray radiation along with apparent myeloid bias differentiation [78, 79]. One dose of 5-fluorouracil treatment significantly decreased the numbers and engraftment ability of mouse HSCs at day 10 after the exposure [80]. To investigate the effects of low doses of 16O TBI on HSC function, in vitro colonyforming assays using bone marrow cells were performed at 2 weeks after 0.1–1.0 Gy doses of 16O exposure. It shows that low doses of 16O TBI not only decreases numbers of HSCs but also abates the in vitro colony-forming abilities, such as decreased numbers of BFU-E, CFU-GM, and CFU-GEMM from irradiated bone marrow cells. These data suggest that the function of HSC after 16O TBI was negative affected despite low doses of 16O used. Using in vitro cell culture model, previous studies have shown that 16O radiation has more dramatic effects on chromosomal aberrations, micronuclei formation, cell survival, and apoptosis than photon radiation [81, 82]. It has been documented that 6.5 Gy total-body γ-irradiation decreased the numbers of bone marrow HSCs up to 50% at 2 weeks postexposure, which was observed at 2 weeks after 1.0 Gy of total-body 16O radiation [38]. These results indicate that 16O radiation has a higher RBE than photon radiation.

To explore long-term effect of 16O TBI on hematopoietic cells, 0.05, 0.1, 0.25, and 1.0 Gy 16O (600 MeV/n) radiations were used to irradiate C57BL/6 J mice. Irradiated mice were analyzed for the long-term effects of 16O radiation on peripheral blood cells and bone marrow cells 3 months postexposure [83]. Although there are the same numbers of peripheral blood cells at 3 months after 0.05 to 1.0 Gy of 16O TBI as nonirradiated controls, numbers of HPC and HSCs from irradiated mice were significantly lower than those from nonirradiated controls. The changes of peripheral blood cell counts after oxygen radiation are similar to the effects of other types of ionizing radiation, such as 0.5 and 1.0 Gy of γ-TBI [84, 85]. Peripheral blood cell counts were back to normal levels 2 months after sublethal doses of γ-ray exposure [86]. Recovery of peripheral blood cell counts may neglect the effects of irradiation on bone marrow HSCs [84], which will result in overlooking the longterm bone marrow suppression after radiation.

We have demonstrated that 0.1 to 1.0 Gy of 16O TBI, but not 0.05 Gy dose, resulted in a dramatic impairment in both numbers and function of bone marrow HSCs in mice at 3 months after exposure. Comparing to 16O TBI, exposure of mice to 0.5 and 1.0 Gy of γ-TBI did not negatively affect the numbers and function of HSC in mice at 3 months after exposure. The phenotype from 16O- and γ-TBI might be related to their RBE along with higher RBE levels of 16O TBI than γ-TBI [81]. The long-term detrimental effects of 16O TBI on bone marrow hematopoietic stem cells have also been seen in 6.5 Gy sublethal doses of γ-rays and 1.0 Gy low dose of proton radiation, showing a reduction in HSC reserves and a defect in HSC function [48, 85, 87, 88]. When comparing the effects of different radiation sources on HPCs, we have shown that acute exposure to low doses of 16O TBI triggered a significant reduction in numbers of HPCs at 2 weeks after exposure. However, numbers of HPCs in irradiated mice recovered back to normal levels 2 weeks after either γ-ray or proton exposure [51]. These data indicate that 16O-irradiated HPCs have a slower recovery than proton- and photon-irradiated HPCs.

We have previously demonstrated that exposure of mice to 1.0 Gy of 16O TBI leads to an increased rate of apoptosis at 2 weeks postexposure in irradiated HPCs but not HSCs. This is consistent with HPC colony-forming ability assay, showing lower numbers of BFU-E, CFU-GM, and CFU-GEMM when compared to those in nonirradiated controls [51]. When we further examined HPC colony-forming abilities at 3 months after same dose of 16O TBI, it showed that numbers of various

**89**

**Table 4.**

*Space Radiation-Induced Hematopoietic Stem Cell Injury*

colonies were still much lower than those in nonirradiated controls [83]. Notably, the decreased colony-forming abilities after 16O TBI were in a dose-independent manner, which suggests "hit and damage." These data suggest that oxygen irradiation has features with a high-linear energy transfer and strong relative biological

A cobblestone area-forming cell (CAFC) assay is a surrogate in vitro hematopoietic stem cell functional assay. We measured HSC in vitro CAFC-forming ability at 3 months after 0.1, 0.25, and 1.0 Gy of 16O radiation, showing that irradiated mice HSCs had a significant reduction of CAFC numbers independent of radiation doses (**Table 4**). These unusual dose-response curves have also been seen in the studies of 28Si radiation, such as effects of 28Si radiation on synaptic plasticity and contextual fear memory [89, 90]. However, when mice were exposed to 0.05 Gy of 16O TBI, numbers of CAFC were comparable to nonirradiated controls, indicating that HSC function was not affected after exposure to 0.05 Gy 16O TBI [83]. These long-term negative effects of 16O TBI on HSCs are also observed in other different types of ionizing radiation [53, 63, 91]. Mice were exposed to 1.0 Gy of proton total-body irradiation, leading to a significant decrease in the CAFC-forming ability in HSCs at 22 weeks postexposure [53]. 6.5 Gy of γ-ray total-body irradiation caused a reduction in HSC colony-forming ability 2 months postexposure [38]. As we discussed previously, peripheral blood cell counts were back to normal levels at 3 months after low-dose 16O TBI, while the numbers and function of bone marrow HSCs were significantly decreased after exposure. Proliferation of progenitors (such as myeloid, lymphoid, and erythroid progenitors) might contribute to the recovery of peripheral blood cells after radiation. These results suggest that low doses of ionizing radiation can induce long-term HSC suppression, while 16O TBI has stronger abilities to induce

the long-term HSC suppression than other types of ionizing radiation.

*Induction of cellular apoptosis, ROS, and DNA damage after oxygen irradiation.*

Cellular apoptosis and ROS production are crucial mediators in irradiationinduced cell damage. We exposed mice to 1.0 Gy of 16O, and it triggered an aberrant increase in ROS production in HPCs and HSCs 2 weeks after exposure [51]. Meanwhile, increasing levels of apoptosis were significant in irradiated HPCs, but not LSK cells and HSCs, when compared to nonirradiated controls. Whether the different acute responses of HPCs and HSCs to 16O TBI are related to ROS production has yet to be determined. Induction of ROS production persisted up to 3 months after 16O TBI [83], which is congruent with the decreased expression of the antioxidant genes GPX2 and SOD3 in 1.0 Gy 16O-irradiated HSCs when compared to nonirradiated HSCs. Previous studies utilized proton and γ-ray radiation to prove that HSC functional impairment might be attributable to the accumulation of residual ROS [53, 63, 92, 93]. This is evidenced by a decrease in in vivo

*DOI: http://dx.doi.org/10.5772/intechopen.88914*

effectiveness.

*Beyond LEO - Human Health Issues for Deep Space Exploration*

indicate that 16O radiation has a higher RBE than photon radiation.

term bone marrow suppression after radiation.

recovery than proton- and photon-irradiated HPCs.

To explore long-term effect of 16O TBI on hematopoietic cells, 0.05, 0.1, 0.25, and 1.0 Gy 16O (600 MeV/n) radiations were used to irradiate C57BL/6 J mice. Irradiated mice were analyzed for the long-term effects of 16O radiation on peripheral blood cells and bone marrow cells 3 months postexposure [83]. Although there are the same numbers of peripheral blood cells at 3 months after 0.05 to 1.0 Gy of 16O TBI as nonirradiated controls, numbers of HPC and HSCs from irradiated mice were significantly lower than those from nonirradiated controls. The changes of peripheral blood cell counts after oxygen radiation are similar to the effects of other types of ionizing radiation, such as 0.5 and 1.0 Gy of γ-TBI [84, 85]. Peripheral blood cell counts were back to normal levels 2 months after sublethal doses of γ-ray exposure [86]. Recovery of peripheral blood cell counts may neglect the effects of irradiation on bone marrow HSCs [84], which will result in overlooking the long-

We have demonstrated that 0.1 to 1.0 Gy of 16O TBI, but not 0.05 Gy dose, resulted in a dramatic impairment in both numbers and function of bone marrow HSCs in mice at 3 months after exposure. Comparing to 16O TBI, exposure of mice to 0.5 and 1.0 Gy of γ-TBI did not negatively affect the numbers and function of HSC in mice at 3 months after exposure. The phenotype from 16O- and γ-TBI might be related to their RBE along with higher RBE levels of 16O TBI than γ-TBI [81]. The long-term detrimental effects of 16O TBI on bone marrow hematopoietic stem cells have also been seen in 6.5 Gy sublethal doses of γ-rays and 1.0 Gy low dose of proton radiation, showing a reduction in HSC reserves and a defect in HSC function [48, 85, 87, 88]. When comparing the effects of different radiation sources on HPCs, we have shown that acute exposure to low doses of 16O TBI triggered a significant reduction in numbers of HPCs at 2 weeks after exposure. However, numbers of HPCs in irradiated mice recovered back to normal levels 2 weeks after either γ-ray or proton exposure [51]. These data indicate that 16O-irradiated HPCs have a slower

We have previously demonstrated that exposure of mice to 1.0 Gy of 16O TBI leads to an increased rate of apoptosis at 2 weeks postexposure in irradiated HPCs but not HSCs. This is consistent with HPC colony-forming ability assay, showing lower numbers of BFU-E, CFU-GM, and CFU-GEMM when compared to those in nonirradiated controls [51]. When we further examined HPC colony-forming abilities at 3 months after same dose of 16O TBI, it showed that numbers of various

Previous studies have demonstrated that the functional defect of mouse HSCs was observed under either radiation or chemotherapeutic drug treatment. For example, the reconstitution capacity of mouse HSCs has detrimental effects under 1.0 Gy of total-body γ-ray radiation along with apparent myeloid bias differentiation [78, 79]. One dose of 5-fluorouracil treatment significantly decreased the numbers and engraftment ability of mouse HSCs at day 10 after the exposure [80]. To investigate the effects of low doses of 16O TBI on HSC function, in vitro colonyforming assays using bone marrow cells were performed at 2 weeks after 0.1–1.0 Gy doses of 16O exposure. It shows that low doses of 16O TBI not only decreases numbers of HSCs but also abates the in vitro colony-forming abilities, such as decreased numbers of BFU-E, CFU-GM, and CFU-GEMM from irradiated bone marrow cells. These data suggest that the function of HSC after 16O TBI was negative affected despite low doses of 16O used. Using in vitro cell culture model, previous studies have shown that 16O radiation has more dramatic effects on chromosomal aberrations, micronuclei formation, cell survival, and apoptosis than photon radiation [81, 82]. It has been documented that 6.5 Gy total-body γ-irradiation decreased the numbers of bone marrow HSCs up to 50% at 2 weeks postexposure, which was observed at 2 weeks after 1.0 Gy of total-body 16O radiation [38]. These results

**88**

colonies were still much lower than those in nonirradiated controls [83]. Notably, the decreased colony-forming abilities after 16O TBI were in a dose-independent manner, which suggests "hit and damage." These data suggest that oxygen irradiation has features with a high-linear energy transfer and strong relative biological effectiveness.

A cobblestone area-forming cell (CAFC) assay is a surrogate in vitro hematopoietic stem cell functional assay. We measured HSC in vitro CAFC-forming ability at 3 months after 0.1, 0.25, and 1.0 Gy of 16O radiation, showing that irradiated mice HSCs had a significant reduction of CAFC numbers independent of radiation doses (**Table 4**). These unusual dose-response curves have also been seen in the studies of 28Si radiation, such as effects of 28Si radiation on synaptic plasticity and contextual fear memory [89, 90]. However, when mice were exposed to 0.05 Gy of 16O TBI, numbers of CAFC were comparable to nonirradiated controls, indicating that HSC function was not affected after exposure to 0.05 Gy 16O TBI [83]. These long-term negative effects of 16O TBI on HSCs are also observed in other different types of ionizing radiation [53, 63, 91]. Mice were exposed to 1.0 Gy of proton total-body irradiation, leading to a significant decrease in the CAFC-forming ability in HSCs at 22 weeks postexposure [53]. 6.5 Gy of γ-ray total-body irradiation caused a reduction in HSC colony-forming ability 2 months postexposure [38]. As we discussed previously, peripheral blood cell counts were back to normal levels at 3 months after low-dose 16O TBI, while the numbers and function of bone marrow HSCs were significantly decreased after exposure. Proliferation of progenitors (such as myeloid, lymphoid, and erythroid progenitors) might contribute to the recovery of peripheral blood cells after radiation. These results suggest that low doses of ionizing radiation can induce long-term HSC suppression, while 16O TBI has stronger abilities to induce the long-term HSC suppression than other types of ionizing radiation.

Cellular apoptosis and ROS production are crucial mediators in irradiationinduced cell damage. We exposed mice to 1.0 Gy of 16O, and it triggered an aberrant increase in ROS production in HPCs and HSCs 2 weeks after exposure [51]. Meanwhile, increasing levels of apoptosis were significant in irradiated HPCs, but not LSK cells and HSCs, when compared to nonirradiated controls. Whether the different acute responses of HPCs and HSCs to 16O TBI are related to ROS production has yet to be determined. Induction of ROS production persisted up to 3 months after 16O TBI [83], which is congruent with the decreased expression of the antioxidant genes GPX2 and SOD3 in 1.0 Gy 16O-irradiated HSCs when compared to nonirradiated HSCs. Previous studies utilized proton and γ-ray radiation to prove that HSC functional impairment might be attributable to the accumulation of residual ROS [53, 63, 92, 93]. This is evidenced by a decrease in in vivo

**Table 4.**

*Induction of cellular apoptosis, ROS, and DNA damage after oxygen irradiation.*

engraftment capacity and in vitro colony-forming ability using bone marrow cells after radiation. The importance of ROS overproduction on functional HSCs was not only supported under radiation stress condition but also supported by other genetic animal models. Deletion of Foxo3, ATM, TSC1, and Bmi-1 in mice leads to the impairment of numbers and function of HSCs along with increasing ROS production. Application of antioxidants, such as N-acetyl cysteine (NAC), on these mutant mice significantly ameliorated the HSC functional deficiency [71, 94–96]. We have provided data showing 16O-irradiated HSCs had higher levels of ROS production than nonirradiated animals in both acute and long-term studies. It is well accepted that mitochondrial oxidative phosphorylation and NADPH oxidases are two main sources to produce ROS in mammalian cells. Because HSCs reside in hypoxic environmental niche in the bone marrow and have higher expression of HIF1α in response to hypoxia, HSCs produce ROS mainly through glycolysis and NOX enzyme. We have previously shown that proton and γ-ray radiation induced significantly upregulation of NOX4 in irradiated HSCs [53, 66]. The NOX4 inhibitor diphenyliodonium can partially protect functional HSCs from γ-irradiationinduced long-term damage. Therefore, antioxidants, such as NOX4 inhibitors and NAC, should be further tested whether inhibiting ROS production can decrease 16O TBI-induced ROS production to accelerate the functional recovery of HPCs and HSCs after 16O irradiation exposure.

Under radiotherapy and chemotherapy stress conditions, dominant HSCs might be activated from quiescent status to provide the need for stressed hematopoietic system. However, frequent HSC activation might cause its loss of self-renewal ability, differentiation, and death with bone marrow failure syndrome [69, 97]. We have shown that proton and γ-irradiation can efficiently activate quiescent HSCs [53, 65], leading to the redistribution of different cell cycle phases and stem cell functional defects. Data from genetic mice models, such as depletion of FOXO3a and Lkb1, showed that HSCs had fast cycling with loss of HSC self-renewal ability and HSC exhaustion [94, 98–100]. There are fewer numbers of HSCs in G0 and higher numbers in G1/G2SM at 2 weeks after 16O TBI [51]. Additionally, we observed that around 15% of irradiated HSCs had more than two γH2AX foci per cell 2 weeks after 16O exposure [51], which is positively correlated with the increased ROS production in 16O TBI HSCs. Taken together, all of ROS production, DNA damage, and HSC cycling after 16O TBI might contribute to HSC defect induced by oxygen radiation, which will be tested in our future studies.

Note:

**91**

*Space Radiation-Induced Hematopoietic Stem Cell Injury*

high-energy charged particle radiation.

and HZE particle exposure on the hematopoietic system.

China (Grant No. 81460110, 81660123, and 81860026),

The authors declare no conflicts of interest.

, Mengzhen Yue1

\*Address all correspondence to<EMAIL_ADDRESS>
provided the original work is properly cited.

1 Medical College of Nanchang University, Nanchang, China

**5. Conclusion**

**Acknowledgements**

**Conflict of interest**

**Author details**

Huihong Zeng1

Nanchang, China

3.The protons and oxygen nuclei in the studies described here were all delivered within a few minutes, and most charged particle exposures during space flight occur at a very low-dose rate and/or are fractionated. Though we acknowledge that the high-dose rates we used are a limitation of our studies, low-dose rate exposures were not possible because of practical constraints. Future studies with low-dose rate or fractionated exposures should provide further insight into dose-rate dependence of hematopoietic stem/progenitor cell response to

In summary, proton and oxygen space radiation have detrimental effects on the hematopoietic system even with at low doses, which will have potential implications for health outcomes during long-duration space missions. Increasing ROS production might be a major mediator on space radiation-induced HSC damage. Knowledge gained from this chapter could aid in planning countermeasure strategies to protect against hematopoietic effects of radiation exposure during space travel. To minimize the health negative effects of deep-space travel, decreasing oxidative stress might be a good approach to mitigate the adverse effects of proton

The study was in part supported by the National Natural Science Foundation of

and Lijian Shao1,2\*

2 Jiangxi Provincial Key Laboratory of Preventive Medicine, Nanchang University,

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

*DOI: http://dx.doi.org/10.5772/intechopen.88914*

*Space Radiation-Induced Hematopoietic Stem Cell Injury DOI: http://dx.doi.org/10.5772/intechopen.88914*

3.The protons and oxygen nuclei in the studies described here were all delivered within a few minutes, and most charged particle exposures during space flight occur at a very low-dose rate and/or are fractionated. Though we acknowledge that the high-dose rates we used are a limitation of our studies, low-dose rate exposures were not possible because of practical constraints. Future studies with low-dose rate or fractionated exposures should provide further insight into dose-rate dependence of hematopoietic stem/progenitor cell response to high-energy charged particle radiation.


*3.7. Dielectric Loss Tangent*

Dissipation of energy is measured with respect to alternating external field which is recorded in terms of dielectric loss. The variation in dielectric loss as a function of frequency for varying Zn concentration in hematite is shown in Figure 11.

*Crystals* **2020**, *10*, x FOR PEER REVIEW 14 of 19

**Figure 11.** Variation of dielectric loss with frequency of pure Fe2O3, Zn 2%, Zn 4% and Zn 6% nanoparticles. **Figure 11.** Variation of dielectric loss with frequency of pure Fe2O3 , Zn 2%, Zn 4% and Zn 6% nanoparticles.

A report by *Iwauchi et al.* [43] showed that conduction hopping and dielectric behavior are

strongly correlated. The dielectric loss is high at lower frequencies, due to the grain boundary behaving as an insulating interface, as the charge carriers undergo space charge polarization [44]. Diamagnetic dopant and organized growth of domains have a major impact on decrease of loss tangent at small frequencies. The loss factor decreases at higher frequencies, due to the mismatch of electrons with applied field frequency, as discussed above. Loss is dependent on various factors, such as ferric and ferrous content, the stoichiometry of material and heterogeneous domain wall geometry. It can be observed that loss tangent has a relaxation peak for α-ZnxFe2−xO3, which is consistent with earlier reports [45,46]. According to Rezlesque model [47], a peak in dielectric loss is expected when the hopping frequency of electrons between Fe2+ and Fe3+ states is in resonance with the external applied electric field's frequency. The maxima in dielectric loss can be expressed as a relation ωτ = 1, where ω is the angular frequency of field and τ is relaxation time for hopping mechanism. The increase in peak height, as well as shifting in peak position with doping of Zn shows the variation in hopping probability of electrons between Fe2+ and Fe3+ states, and this is influenced by the number of Fe3+ ions in the octahedral site [48]. *3.8. AC Conductivity*  To study the hopping mechanism, ac conductivity (σac) versus logf of Zn doped hematite at room temperature is plotted (Figure 12a). At lower frequencies, conductivity seems to be constant and A report by Iwauchi et al. [43] showed that conduction hopping and dielectric behavior are strongly correlated. The dielectric loss is high at lower frequencies, due to the grain boundary behaving as an insulating interface, as the charge carriers undergo space charge polarization [44]. Diamagnetic dopant and organized growth of domains have a major impact on decrease of loss tangent at small frequencies. The loss factor decreases at higher frequencies, due to the mismatch of electrons with applied field frequency, as discussed above. Loss is dependent on various factors, such as ferric and ferrous content, the stoichiometry of material and heterogeneous domain wall geometry. It can be observed that loss tangent has a relaxation peak for α-ZnxFe2−xO3, which is consistent with earlier reports [45,46]. According to Rezlesque model [47], a peak in dielectric loss is expected when the hopping frequency of electrons between Fe2+ and Fe3+ states is in resonance with the external applied electric field's frequency. The maxima in dielectric loss can be expressed as a relation ωτ = 1, where ω is the angular frequency of field and τ is relaxation time for hopping mechanism. The increase in peak height, as well as shifting in peak position with doping of Zn shows the variation in hopping probability of electrons between Fe2+ and Fe3+ states, and this is influenced by the number of Fe3+ ions in the octahedral site [48].

#### using log σac versus logf as shown in Figure 12b. In large polaron model, ac conductivity decreases, while in the small polaron model, ac conductivity increases with rise in frequency. In the present *3.8. AC Conductivity*

study, conductivity shows almost linear behavior with increases in frequency that indicates conduction hopping is followed by small polaron mechanism, as evident from Figure 12b. Conductivity is more affected by grain boundaries at lower frequencies, while grains have more impact on conduction at high frequencies [49]. The increase in frequency enhances the hopping of charge carriers between ferric and ferrous ions that leads to increase in conductivity. Low conductivity is observed at lower frequencies which is due to the blocking effects at grain boundaries. To study the hopping mechanism, ac conductivity (σac) versus logf of Zn doped hematite at room temperature is plotted (Figure 12a). At lower frequencies, conductivity seems to be constant and increases with rise in frequency. The type of polarons involved in hopping mechanism was estimated using log σac versus logf as shown in Figure 12b. In large polaron model, ac conductivity decreases, while in the small polaron model, ac conductivity increases with rise in frequency. In the present study, conductivity shows almost linear behavior with increases in frequency that indicates conduction hopping is followed by small polaron mechanism, as evident from Figure 12b. Conductivity is more affected by grain boundaries at lower frequencies, while grains have more impact on conduction at high frequencies [49]. The increase in frequency enhances the hopping of charge carriers between ferric and ferrous ions that leads to increase in conductivity. Low conductivity is observed at lower frequencies which is due to the blocking effects at grain boundaries.

increases with rise in frequency. The type of polarons involved in hopping mechanism was estimated

The relation between frequency and ac conductivity can be depicted as [50],

$$
\sigma\_{ac} = 2\pi f \varepsilon\_0 \varepsilon' \tan \delta \tag{15}
$$

where, f is frequency in Hz. The conductivity decrement with Zn dopant concentration could be described by the microstructures of the material, the probability of hopping and hopping duration of the electrons. This may arises due to the reduction of Fe3+ ions in octahedral site and creation of Fe3+ vacancies by substitution of Zn2+ ions. *Crystals* **2020**, *10*, x FOR PEER REVIEW 15 of 19

**Figure 12.** (**a**) Frequency dependency AC conductivity of pure Fe2O3, Zn 2%, Zn 4% and Zn 6% nanoparticles and (**b**) Linear plot of log σac versus logf. **Figure 12.** (**a**) Frequency dependency AC conductivity of pure Fe2O3 , Zn 2%, Zn 4% and Zn 6% nanoparticles and (**b**) Linear plot of log σac versus logf.

#### The relation between frequency and ac conductivity can be depicted as [50], *3.9. Modulus Properties*

*3.9. Modulus Properties*

ᇱߝߝ݂ߨ2 = ߪ (15) ߜܽ݊ݐ where, f is frequency in Hz. The conductivity decrement with Zn dopant concentration could be described by the microstructures of the material, the probability of hopping and hopping duration of the electrons**.** This may arises due to the reduction of Fe3+ ions in octahedral site and creation of Fe3+ The electric modulus plays an important role in the study of conduction and relaxation behavior of materials, and also, in detecting the impedance sources like grains, grain boundary conduction effect, electrode polarization and electrical conductivity. The real (M') and imaginary (M") components of electric modulus can be obtained using dielectric constant (ε 0 and ε") [51]:

$$M^\* = \frac{\varepsilon'}{\varepsilon'^2 + \varepsilon''^2} + i \frac{\varepsilon'}{\varepsilon'^2 + \varepsilon''^2} = M' + iM''. \tag{16}$$

The electric modulus plays an important role in the study of conduction and relaxation behavior of materials, and also, in detecting the impedance sources like grains, grain boundary conduction The real component (M') of electric modulus represents the energy given to the system, and the imaginary component (M") represents the dissipated energy during the conduction process.

effect, electrode polarization and electrical conductivity. The real (M') and imaginary (M") components of electric modulus can be obtained using dielectric constant (ε′ and ε″) [51]: ఌᇱ∗ = ܯ ఌᇱమାఌ"మ + ݅ ఌᇱ ఌᇱమାఌ"మ = ܯᇱ + ݅ܯ".) 16 ( The real component (M') of electric modulus represents the energy given to the system, and the imaginary component (M") represents the dissipated energy during the conduction process. The frequency dependence of electric modulus (M', M") at room temperature is shown in Figure 13. It is observed that at lower frequencies M' is very small nearly to be zero and a continuous dispersion with frequency increases having a tendency to saturate at a maximum value for all the samples at higher frequencies due to the relaxation process. These observations implies the lack of restoring force for flow of charge carriers under the action of steady electric field. The small value of M' at low frequency supports the long range mobility of charge carriers. While, in higher frequencies, M' increases rapidly with frequency, indicating that the conduction mechanism, which may be due to the short range mobility of charge carriers.

**Figure 13.** Frequency dependence (**a**) real component (M') and (**b**) Imaginary component (M") of electric modulus of pure Fe2O3, Zn 2%, Zn 4% and Zn 6% nanoparticles. The imaginary part of electrical modulus M" shows an increasing trend compared to frequency with relaxation peaks for all samples. The frequency region below peak frequency represents the frequency range by which ions drift to long distance, i.e., performing successful hopping from one site to neighboring site. Whereas, the high frequency region above the peak shows that the carriers are confined to their potential wells and can make localized motion inside the well. The occurrence of peak in electrical modulus M" indicates the transition from long range to short range mobility of charge carriers with rise in frequency. The behavior of the modulus spectrum is indicative of hopping type mechanism for electrical conduction in the system. The broadening of the peaks is the consequence of the distributions of relaxation time arise from the non-Debye type of the material. Further, it is observed that the peaks shift towards the higher frequency side, with Zn doping and the obtained relaxation peaks having resonance peaks, where the oscillating dipoles frequency matches the applied field frequency.

**Figure 12.** (**a**) Frequency dependency AC conductivity of pure Fe2O3, Zn 2%, Zn 4% and Zn 6%

ᇱߝߝ݂ߨ2 = ߪ

where, f is frequency in Hz. The conductivity decrement with Zn dopant concentration could be described by the microstructures of the material, the probability of hopping and hopping duration of the electrons**.** This may arises due to the reduction of Fe3+ ions in octahedral site and creation of Fe3+

The electric modulus plays an important role in the study of conduction and relaxation behavior of materials, and also, in detecting the impedance sources like grains, grain boundary conduction effect, electrode polarization and electrical conductivity. The real (M') and imaginary (M")

The real component (M') of electric modulus represents the energy given to the system, and the

(15) ߜܽ݊ݐ

ఌᇱమାఌ"మ = ܯᇱ + ݅ܯ".) 16 (

The relation between frequency and ac conductivity can be depicted as [50],

components of electric modulus can be obtained using dielectric constant (ε′ and ε″) [51]:

ఌᇱమାఌ"మ + ݅ ఌᇱ

imaginary component (M") represents the dissipated energy during the conduction process.

ఌᇱ∗ = ܯ

nanoparticles and (**b**) Linear plot of log σac versus logf.

vacancies by substitution of Zn2+ ions.

*3.9. Modulus Properties*

**Figure 13.** Frequency dependence (**a**) real component (M') and (**b**) Imaginary component (M") of electric modulus of pure Fe2O3, Zn 2%, Zn 4% and Zn 6% nanoparticles. **Figure 13.** Frequency dependence (**a**) real component (M') and (**b**) Imaginary component (M") of electric modulus of pure Fe2O3 , Zn 2%, Zn 4% and Zn 6% nanoparticles.