Characteristics of studies about genetic polymorphism at codon 399 of DNA repair gene XRCC1 and risk biomarker for DNA repair capacity (namely HCC risk)
\r\n\tThis book aims to expose the recent advances in the research and development of chemical and biochemical processes to obtain bio-based chemical compounds and fuels from glycerol.
\r\n\r\n\tChapters dealing with the synthesis and characterization of catalysts (single and mixed hydroxides and oxides, supported catalysts, zeolites, heteropolyacids, pillared-clays, and metal-organic frameworks) and biocatalysts (novel microbial and fungi cultures, immobilized cells, immobilized enzymes, and nanobiocatalysts) to carry out the conversion of glycerol, as well as their testing in discontinuous and continuous stirred reactors, fixed-bed, fluidized-bed, trickle-bed, bubble column, airlift and membrane (bio)reactors are welcome.
\r\n\r\n\tThe book will comprise, but will not be limited to, the homogeneous and heterogeneous chemical reactions of glycerol such as dehydration, hydrogenolysis, partial oxidation, steam- and dry-reforming, glycerol to hydrocarbon fuels and aromatics, (trans)esterification, etherification, halogenation, ammoxidation, as well as supercritical, and photocatalytic processes.
\r\n\r\n\tAdditionally, we hope to cover the bioprocessing of glycerol, including microbial and fungal fermentation and enzymatic reactions to obtain C2-C4 alcohols, diols, hydrogen, methane, organic acids, dihydroxyacetone, biopolymers, and others.
\r\n\tThe book will also deal with the engineering aspects of glycerol processing, such as chemical equilibrium of glycerol reactions, reaction kinetics, (bio)reactor modeling, as well as process simulation and optimization of process variables and reactors.
Aflatoxin B1 (AFB1) is an important aflatoxin produced by some strains of the moulds Aspergillus parasiticus and Aspergillus flavus [1-3]. This aflatoxin was discovered as a contaminant of human and animal food, especially peanuts (ground nuts), core, soya sauce, and fermented soy beans in tropical areas such as the Southeastern China as a result of fungal contamination during growth and after harvest which under hot and humid conditions in the late 1950s and early 1960s [1-4]. Increasing evidences have shown that AFB1 exposure levels are consistent with hepatocellular carcinoma (HCC) risk values [1, 2, 4-7]. DNA damage by AFB1 plays the central role of carcinogenesis of HCC-related to this toxin in the toxic studies [2, 8-10]. Today, AFB1 has been classified as a known human carcinogen by the International Agency for Research on Cancer [1, 2, 5, 10, 11]. However, more and more epidemiological evidence has exhibited that although many people are exposed to the same levels of AFB1, only a relatively small proportion of exposure person develop HCC [6, 12-23]. This indicates individual DNA repair capacity related to AFB1-induced DNA damage might be associated with HCC carcinogenesis [4].
This study attempts to briefly review currently available data on genetic polymorphisms of DNA repair genes and DNA repair capacity related to AFB1-induced DNA Damages, with emphasis on: (1) DNA damage types, (2) DNA repair pathways, (3) the role of DNA repair genetic polymorphisms in the repair process of DNA damage by AFB1, and (4) the elucidation of corresponding DNA repair capacity. Additionally, we summarized the association between genetic polymorphisms of DNA repair genes and AFB1-related DNA repair capacity via a meta-analysis based on published data.
In 1963, Asao
Biotransformation pathways for AFB1. AFB1, mainly produced by the moulds Aspergillus parasiticus (right upper figure) and Aspergillus flavus (right under figure), is metabolized by cytochrome P450 enzymes to its reactive form, AFB1-8,9-epoxide (AFB1-epoxide). AFB1-epoxide covalently binds to DNA strands and results in the formation of AFB1-DNA adducts (including AFB1-N7-Gua adduct and AFB1-FAPy adduct).
Several previous reviews have significantly summarized the DNA toxicity of AFB1 [1, 2, 8]. Generally, the severity of DNA toxic effects in human or animals vary with exposure levels, exposure years and nutritional status [1, 2, 26]. For large doses of exposure, this agent can induce acute damage of DNA such as inhabiting DNA synthesis, decreasing DNA-dependent RNA polymerase activity, and restraining messenger RNA (mRNA) and protein synthesis, and subsequently resulting in the lethal changes of liver cells: hepatocellular severe degeneration and necrosis [1, 2].
For long-times and low-levels exposure mainly induces chronic DNA damage [1, 2]. This damage can result in neoplasia, primarily HCC, in many animals or human. Chronic DNA damages induced by AFB1 include AFB1-DNA adducts, oxidative DNA damage, DNA strand break damage, and gene mutation [1, 2, 4].
AFB1-DNA adducts, including 8,9-di-hydro-8-(N7-guanyl)-9-hydroxy–AFB1 (AFB1-N7-Gua) adduct and formamidopyridine AFB1 (AFB1-FAPy) adduct (Fig. 1), is the main type of AFB1-induced DNA damage [1-4, 25-39]. Among these AFB1-DNA adducts, AFB1-N7-Gua adduct is the most common type identified and confirmed in vivo researches [2, 25]. This type adduct is formed from two pathways: (1) Binding reaction of AFB1-epoxide with DNA; and (2) enzymatic oxidation of AFP1, AFM1, and others with unsaturated in the 8,9-position [2, 25]. In the first pathway, the formations of AFB1-N7-Gua adduct proceeds by a precovalent intercalation complex between double-stranded DNA and the highly electrophilic, unstable AFB1-epoxide isomer. After that, the induction of a positive charge on the imidazole portion of the formed AFB1-N7-Gua adduct gives rise to another important a DNA adduct, a ring-opened AFB1-FAPy adduct. Accumulation of AFB1-FAPy adduct is characterized by time-dependence, non-enzyme, and may be of biological basis of genes mutation because of its apparent persistence in DNA. Another pathway only gives rise to minor AFB1-DNA adducts [1, 2, 25]. Additionally, some other DNA-adducts types, ex. covalent binding of AFB1 to adenosine or cytosine in DNA, has also been reported, however, needing more evidences to support this adducts [2].
Although AFB1-DNA adducts are mainly produced in liver cells, they are also found in the peripheral blood white cells [2]. Recent studies have shown that the levels of AFB1-DNA adduct of the peripheral blood white cells are positively and lineally correlated with that of liver cells, implying analysis of AFB1-DNA adducts in the peripheral blood white cells may substitute for the elucidation of tissular levels of adducts [40].
In the process of agent AFB1 metabolism, this agent can induced reactive oxygen species (ROS) [2]. Especially, the metabolic particulate phases, including I and II phase involved by detoxicate enzymes such as CYP and glutathione S-transferase (GST), is postulated to contain long-lived ROS that can lead to oxidative DNA damage [2, 4]. Nowadays, ROS have also been suggested to be involved in the progression of chronic liver disease and the occurrence of HCC; whereas its’ subsequent Oxidative DNA damage is generally regarded as a significant contributory cause of cancer from environmental exposures such as AFB1 exposure [41]. Of oxidative DNA damage, 8-oxodeoxyguanosine (8-oxodG), a kind of especial DNA adduct, is found as a sensitive marker of the DNA damage due to hydroxyl radical attack at the C8 of guanine [2, 4, 25, 42]. This adduct, different from the aforementioned AFB1-DNA adducts, is the most abundant endogenous DNA lesion caused by ROS, and has been classified as a biomarker of oxidative DNA damage [2, 10, 43, 44].
Previous studies have shown that in vitro treatment of hepatocytes with AFB1 resulted in a dose-dependent increase in ROS formation [45]; whereas exposure of rats to AFB1 produced a time- and dose-dependent increase in 8-oxodG in hepatic DNA [46, 47]. In 2007, Wu,
Previous reviewed adducts are capable of forming subsequent repair-resistant adducts, depurination, or lead to error-prone DNA repair resulting in single-strand breaks (SSBs) and double-strand breaks (DSBs). SSBs and DSBs are two kinds of important DNA damage types by AFB1 exposure. For SSBs, there are three pathways to produce this type DNA damage under the AFB1 exposure conditions: direct attack by ROS, through base hydrolysis, and enzymatic consequence of the repair of spontaneous base damage and base loss (such as resulting from abasic AP. sites arising spontaneously or from the action of glycosylases in the process of BER pathway) [49-51]. As the most abundant lesion occurring in cellular DNA, SSBs can play havoc with replication and transcription if not efficiently eliminated. However, they might cause other DNA damage such as genic mutations, DSBs, or carcinogenesis of cells [51, 52]. While DSBs is rare and severe DNA damage type among DNA damage induced by AFB1 exposure [25], mainly produced under the high-dose AFB1 exposure conditions. This damage can lead to chromosomal rearrangements at the first mitosis after exposure to the DNA strand-breaking agent [53].
For genes mutations induced by AFB1 exposure, the experimental and theoretical researches are briefly on the p53 gene [54-56]. Reaction with DNA at the N7 position of guanine preferentially causes a G:C > T:A mutation in codon 249 of this gene, leading to an amino acid substitution of arginine to serine [54-56]. In high AFB1-exposure areas, this mutation is present in more than 40% of HCC and can be detected in serum DNA of patients with preneoplastic lesions and HCC. While codon 249 transversion mutations are either very rare or absent in low or no AFB1-exposure areas [4]. Using the human p53 gene in an in vitro assay, codon 249 has been exhibited to be a preferential site for formation of AFB1-N7-Gua adducts evidence consistent with a role for AFB1 in the mutations observed in HCC [57-65]. Therefore, the codon 249 mutation of p53 gene has been defined as the hot-spot mutation of p53 gene (TP53M) resulting from AFB1 and has become the molecular symbol of HCC induced by AFB1 exposure. The frequency of TP53M is also regarded as the molecular biomarker of AFB1-related DNA repair capacity [4].
A wide diversity of DNA damage induced by AFB1 exposure, if not repaired, may cause chromosomal aberrations, micronuclei, sister chromatid exchange, unscheduled DNA synthesis, and chromosomal strand breaks, and can be converted into gene mutations and genomic instability, which in turn results in cellular malignant transformation [4]. Nevertheless, human cells have evolved surveillance mechanisms that monitor the integrity of genome to minimize the consequences of detrimental mutations [9]. AFB1-induced DNA damage can be repaired through the following pathways: nucleotide excision repair (NER), base excision repair (BER), single-strand break repair (SSBR), and double-strand break repair (DSBR) [4, 25].
NER pathway, a major DNA repair pathways in human cells featuring genomic DNA damage, can remove structurally such diverse lesions as pyrimidine dimers, irradiative damage, and bulky chemical adducts, and DNA damage from carcinogens and some chemotherapeutic drugs [66]. To date, the mechanism of this pathway is well understood and has been reconstituted in vitro. It consists of several sequential steps: lesion sensing, opening of a denaturation bubble, incision of the damaged strand, displacement of the lesion-containing oligonucleotide, gap filling, and ligation [66, 67]. In the fibroblast cells with the deficiency of xeroderma pigmentosum A (XPA) gene, conversion of the initial AFB1-N7-Gua adduct to the AFB1-FAPy adduct has been found to be more extensive. This suggests that NER should be a major mechanism for enzymatic repair of AFB1 adducts. Its defects lead to severe diseases related AFB1 exposure, including liver injury and HCC [4].
Of the oxidative DNA damage resulting from AFB1 exposure, the formation of 8-oxodG is thought to be important due to being abundant and highly mutagenic and hepatocarcinogenesis [4, 25]. The 8-oxodG lesions are repaired primarily through the BER pathway. The BER pathway facilitates DNA repair through two general pathways: a. the short-patch BER pathway, leading to a repair tract of a single nucleotide; b. the long-patch BER pathway, producing a repair tract of at least two nucleotides [68, 69]. In these two repair sub-pathways, DNA glycosylases play a central role because they can recognize and catalyze the removal of damaged bases [68, 69]. This suggests that the defect of DNA glycosylases should be related to the decreasing capacity of the BER pathway and might increase the risk of such toxicity as AFB1 [4, 25].
SSB is a relative severe type of DNA damage produced by AFB1 exposure. If not repaired, it can disrupt transcription and replication and can be converted into potentially clastogenic and/or lethal DSBs [51]. This DNA damage is repaired via SSBR pathway. SSBR pathway includes four basic steps: a. SSB detection and signaling, through poly (ADP-ribose) polymerase (PARP); b. DNA break end processing, through the role of polynucleotide kinase (PNK), AP endonuclease-1 (APE1), DNA polymerase β (Pol β), tyrosyl phosphodiesterase 1 (TDP1), and flap endonuclease-1 (FEN-1); c. gap filling, involving in multiple DNA polymerases; d. DNA ligation, involving in multiple DNA ligases [49, 50, 52]. This pathway mainly plays an important role in the repair process of SSBs induced AFB1.
DSBs, although only make up a very small proportion of AFB1-induced DNA damage, are critical lesions that can result in cell death or a wide variety of genetic alterations including large- or small-scale deletions, loss of heterozygosity, translocations, and chromosome loss [70]. This type damage is repaired DSBR consisting of non-homologous end-joining (NHEJ) and homologous recombination (HR) [71, 72]. There are several decades DNA repair genes involve in DSBR pathway and the defects in these genes cause genome instability and promote tumorigenesis [71-77]. During the process of damage removed by aforementioned repair pathways, DNA repair genes play a central role, because their function determines DNA repair capacity [4]. It has been shown that reduction in DNA repair capacity related to DNA repair genes is associated with increasing frequency of genic mutation, levels of DNA adducts, and risk of cancers [8, 78]. Thus, genetic polymorphisms in DNA repair genes might be correlated with AFB1-related DNA repair capacity.
As shown in the previous review, two main characteristics of AFB1-induced DNA damage are AFB1-DNA adducts and the hot-spot mutation of tumor suppressor gene p53 at codon 249 (TP53M) [4, 25]. Thus, DNA repair capacity related to this type DNA damage might be elucidated using the analysis of AFB1-DNA-adducts levels and TP53M frequency in the liver tissues or other tissues. For AFB1-DNA adducts, many researchers in the relative fields regard AFB1-FAPy adduct as a validated biomarker of AFB1 exposure based on as following reasons: (1) that AFB1-FAPy adduct is the imidazole ring-opened product of AFB1-N7-Gua adduct, also the stable of form of the later adduct, and may play an important role in the development of HCC. Moreover, the accumulation of this adduct is time-dependent and non-enzymatic, and may have potential biological importance because of its apparent persistence in DNA; (2) that AFB1-N7-Gua adduct is unstable and easily lost from DNA. Increasing evidences have exhibited that AFB1-FAPy-adducts levels in the liver or placenta tissues are lineally correlated with AFB1 exposure levels and HCC risk [79, 80], suggesting this adduct should be regarded as a biomarker for DNA repair capacity related to AFB1-induced DNA damage. Remarkably, the monoclonal antibodies recognizing AFB1-FAPy adduct have been developed by several research groups. These types of antibodies are not only used to orientationally and semi-quantitatively test AFB1-DNA adduct information in the tissue specimens through immunochemistry (IHC), but to quantitatively analyze the levels of this adduct using a competitive enzyme-linked immunosorbent assay (ELISA) in human liver and placenta tissue specimens. Additionally, a quantitative indirect immunofluorescence method using monoclonal antibody 6A10 has also been developed to measure AFB1-DNA adducts in liver tissues. In 2009, Long
As regard of the mutations of p53 gene, because AFB1 exposure results in G to T transversion in both bacteria and human cells and AFB1 preferentially binds to codon 249 of p53 gene, as previous mentioned, AFB1 mainly induces the transversion of G → T in the third position at codon 249 of TP53M. The frequent value of TP53M is more persistent biomarker and more directly represents DNA repair capacity compared with AFB1-DNA adducts. In the studies from higher AFB1 exposure areas, researchers have found TP53M frequency associates with AFB1 exposure levels and HCC risk. Thus, this mutation is the selective elucidative marker for DNA repair capacity correlated with AFB1-induced DNA damage as well as AFB1-DNA adducts.
Additionally, HCC is the most common malignant tumors caused by AFB1 exposure. More and more epidemiological studies have shown AFB1-related HCC risk is related to different DNA repair capacity [4, 8, 15, 22, 40, 78, 81-90], suggesting that tumor risk value might be regard as a selective elucidative marker for DNA repair capacity correlated with AFB1-induced DNA damage.
Accumulating evidences have implied that genetic polymorphisms in NER genes are associated with DNA repair capacity related to AFB1-induced DNA damage. Molecular epidemiology studies in this field are mainly from high AFB1 exposure areas such as in China. To date, two genes involved in NER pathway, namely xeroderma pigmentosum C (XPC) and xeroderma pigmentosum D (XPD), have been investigated in the DNA repair capacity analysis.
XPC gene (Genbank accession NO. AC090645), consisting of 16 exons and 15 introns, spans 33kb on chromosome 3p25. This gene encodes a 940-amino acid protein, an important DNA damage recognition molecule which plays an important role in NER pathway. XPC protein binds tightly with another important NER protein HR23B to form a stable XPC-HR23B complex, the first protein component that recognizes and binds to the DNA damage sites [91-98]. XPC-HR23B complex can recognize a variety of DNA adducts formed by exogenous carcinogens such as AFB1 and binds to the DNA damage sites [4, 91, 99]. Therefore, it may play a role in the process of DNA repair of DNA damage related to AFB1 exposure.
Some recent studies have showed that defects in XPC have been related to many types of malignant tumors [99-114]. Transgenic mice researches have also exhibited predisposition to many kinds of neoplasms in mice model with XPC gene knockout [115]. Moreover, pathological and cellular studies have shown that increasing expression of this gene is associated with hepatocarcinogenesis [116]. Together, these studies suggest the genetic polymorphisms localizing at conserved sites of XPC gene might modify the risk of HCC induced by AFB1 exposure and decrease DNA repair capacity related to AFB1-related DNA damage. Recently, four studies from high AFB1-exposure areas have supported abovementioned hypothesis [84, 89, 101, 117].
The first study conducted by Cai
The other three studies, from Guangxi Zhuang Autonomous Region which is the most common of high AFB1 exposure area all over the world [4, 118], directly investigated the modifying effects of genetic polymorphisms XPC on AFB1-related DNA repair capacity and HCC risk based on hospitals via molecular epidemiological studies [84, 89, 101]. Their results showed XPC codon 939 Gln alleles increased about 2-times risk of HCC and decreased AFB1-related DNA repair capacity. Furthermore, Wu,
Additionally, Long,
As a result, these data suggest that genetic polymorphism at codon 939 of XPC gene is not only a genetic determinant in the DNA repair process of DNA damage induced by AFB1 exposure, and a risk and prognostic factor influencing HCC developing, but also is an independent genetic factor of evaluating DNA repair capacity related to AFB1-caused DNA damage. A possible reason is that this genetic polymorphism down-regulates XPC expression [84] and decrease the repair function of XPC protein [116].
However, Li
XPD protein, a DNA-dependent ATPase/helicase encoded by DNA repair gene XPD (also called excision repair cross-complementing rodent repair deficiency complementation group 2 (ERCC2), COFS2, EM9, or TTD.) (Genbank ID. 2068) which spans about 20 kb on chromosome 19q13.3 and contains 23 exons and 22 introns is one of seven central proteins in the NER pathway [119-122]. This protein is associated with the TFIIH transcription-factor complex, and plays a role in NER pathway [66, 67, 119-121, 123-125]. During NER, XPD participates in the opening of the DNA helix to allow the excision of the DNA fragment containing the damaged base [119-122].
There are four described polymorphisms that induce amino acid changes in the protein: at codons 199 (Ile to Met), at codon 201 (His to Tyr), at codon 312 (Asp to Asn) and at codon 751 (Lys to Gln) [123]. To date, the first two polymorphisms have not investigated because they are quite rare (~0.04%) in most population, whereas the latter two polymorphisms in conserved region of XPD have been extensively studied [123]. Several groups have done genotype-phenotype analyses with these two polymorphisms and have shown that the variant allele genotypes are associated with low DNA repair ability [126, 127]. Recent studies have showed the polymorphisms at codon 312 and 751 of XPD are correlated with DNA-adducts levels, p53 gene mutation, and cancers risk [86, 123, 128-131]. In a hospital-based case-control study conducted in a high AFB1 exposure area [40], Long,
Together, these results suggest the genetic polymorphisms at conserved sequence of XPD gene such as at codon 751 may have potential effect on AFB1-related HCC susceptibility. This supports different AFB1-related DNA repair capacity might be modified by genetic polymorphisms at codon 751 in DNA repair gene XPD. However, the study from AFB1-exposure areas shows that the genetic polymorphism at codon 312 in XPD polymorphism is not significantly correlated with DNA repair capacity related AFB1-induced DNA damage [4, 40].
As previous described, DNA glycosylases play a central role in the BER pathway because they can recognize and catalyze the removal of damaged bases [68, 69]. Among having been reported genetic polymorphisms of DNA glycosylases, only human 8-oxoguanine DNA glycosylase (hOGG1) correlates with DNA repair capacity [132-143]. This gene (Genbank ID# 4968), also called HMMH, OGG1, MUTM, OGH1, 8-hydroxyguanine DNA glycosylase, AP lyase, DNA-apurinic or apyrimidinic site lyase, and N-glycosylase/DNA lyase, consisting of 7 exons and 6 introns, spans 17 kb on chromosome 3p26.2 (PubMed). This gene encodes a 546-amino acid protein, a specific DNA glycosylase that catalyzes the release of 8-oxodG and the cleavage of DNA at the AP site [142]. Genetic structure study has shown the presence of several polymorphisms within hOGG1 locus [136]. Among these polymorphisms, the polymorphism at position 1245 in exon 7 causes an amino acid substitution (namely Ser to Cys) at codon 326, suggesting this polymorphism may glycosylase function and decrease DNA repair capacity [136].
In the past twenty years, increasing epidemiological evidences have validated aforementioned the hypothesis [132-144]. In 2003, Peng,
As a result, these findings suggested the genetic polymorphism at codon 326 of DNA repair gene hOGG1 should modify AFB1-related DNA repair capacity. However, another case-control study from Japan shows this genetic polymorphism is not associated with HCC risk. This might result from lower AFB1 exposure in this area and not showing the relative low DNA repair capacity related to AFB1-induced DNA damage.
SSBR pathway involves in several central DNA repair genes such as XRCC1, poly (ADP-ribose) polymerase-1 (PARP-1), APE (or DNA glycosylase), DNA ligase III, Pol β, and so on [49-51]. Of these DNA repair genes, only XRCC1 is investigated to correlate with AFB1-related DNA repair capacity. This gene, also called RCC, spans about 32 kb on chromosome 19q13.2 and contains 17 exons and 16 introns is one of three submits of DNA repair complex in the SSBR pathway (Gene dbase from PubMed). Its’ encoding protein (633 amino acids), consists of three functional domains: N-terminal domain (NTD), central breast cancer susceptibility protein-1 homology C-terminal (BRCT I), and C-terminal breast cancer susceptibility protein-1 homology C-terminal (BRCT II) [4, 51, 145-151]. This protein is directly associated with Pol β, DNA ligase III, and PARP, via their three functional domains and is implicated in the core processes in SSBR and BER pathway [4, 51, 145, 150-152]. Mutant hamster ovary cell lines that lack XRCC1 genes are hypersensitive to DNA damage agents such as ionizing radiation, hydrogen peroxide, and alkylating agents [4, 51]. Furthermore, this kind of cells usually faces increasing frequency of spontaneous chromosome aberrations and deletions. Three single nucleotide polymorphisms in the coding region of XRCC1 gene that lead to amino acid substitution have been described and investigated [25]. Among these polymorphisms, the codon 399 polymorphism is of special concern, because this polymorphism resides in functionally significant regions (BRCT II) and may be related to decreasing DNA repair capacity [85, 153-179].
In 2008, Long,
As regards of risk biomarker for DNA repair capacity namely AFB1-related HCC risk, a total of fourteen molecular epidemiological studies involving genetic polymorphism at codon 399 of DNA repair gene XRCC1 were found in PubMed database, Sprinker database, Ovid database, Wangfang Database, and Weipu database [22, 81, 83, 162, 164, 175, 180-186], summarized in Table 1. However, associations between this genetic polymorphism and DNA repair capacity have been reported in these case-control studies with the results being contradictory [172, 187]. Possible reasons are as follows: different study population, non-scientific design, the loss of matching methods or improper match, the loss of stratified analysis based on AFB1 exposure information, repeated data, and so on. To avoid above error and achieve more scientific results, we analyzed the possible causes of contradictory using meta-analysis method (Comprehensive Meta-Analysis Version 2, http://www.meta-analysis.com/). Fig. 2, 3, and 4 showed the meta-analysis results of the modifying effects of genetic polymorphism at codon 399 of XRCC1 gene on AFB1-related DNA repair capacity. Based on meta-analysis of overall studies including known published literature (Fig. 2), we found contradictive results; whereas we would observe significant modifying effects of genetic polymorphism at codon 399 of XRCC1 gene on DNA repair capacity related to AFB1-caused DNA damage if these possible repeated studies from the same researchers (Fig. 3) or adding these studies from low/no AFB1 exposure areas (Fig. 4) were excluded. Actually, although Yang,
\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t\t\n\t\t\t\t\t | \n\t\t\t
1 | \n\t\t\tYu | \n\t\t\t2003 | \n\t\t\tTaiwanese | \n\t\t\thigh | \n\t\t\tcase-control | \n\t\t\tage, sex | \n\t\t\t577 | \n\t\t\t389 | \n\t\t\t1.54 ( | \n\t\t
2 | \n\t\t\tHan et al.(2004) | \n\t\t\t2004 | \n\t\t\tQidongese | \n\t\t\thigh | \n\t\t\tcase-control | \n\t\t\tage, sex | \n\t\t\t69 | \n\t\t\t136 | \n\t\t\tabout 1 ( | \n
3 | \n\tKirk et al.(2005) | \n\t2005 | \n\tGimbia | \n\thigh | \n\tcase-control | \n\tage, sex | \n\t149 | \n\t294 | \n\t2.66 ( | \n
4 | \n\tLong et al.(2005) | \n\t2005 | \n\tGuangxiese | \n\thigh | \n\tcase-control | \n\tage, sex, HBV, HCV, race | \n\t140 | \n\t536 | \n\t2.18 ( | \n
5 | \n\tLong et al.(2006) | \n\t2006 | \n\tGuangxiese | \n\thigh | \n\tcase-control | \n\tage, sex, HBV, HCV, race | \n\t257 | \n\t649 | \n\t2.47 ( | \n
6 | \n\tRen et al.(2008) | \n\t2008 | \n\tBeijingese | \n\tlow | \n\tcase-control | \n\tage, sex | \n\t50 | \n\t92 | \n\t0.49 ( | \n
7 | \n\tBorentain et al.(2007) | \n\t2007 | \n\tFrench | \n\tlow | \n\tcase-control | \n\tage, sex | \n\t56 | \n\t61 | \n\t1.84 ( | \n
8 | \n\tKiran et al.(2009) | \n\t2009 | \n\tIndian | \n\tlow | \n\tcase-control | \n\tno | \n\t63 | \n\t142 | \n\t0.33-0.63 ( | \n
9 | \n\tKiran et al.(2009) | \n\t2009 | \n\tIndian | \n\tlow | \n\tcase-control | \n\tno | \n\t63 | \n\t142 | \n\t0.33-0.63 ( | \n
10 | \n\tSu et al.(2008) | \n\t2008 | \n\tLiaoningese | \n\tlow | \n\tcase-control | \n\tage, sex | \n\t100 | \n\t111 | \n\t2.95 ( | \n
11 | \n\tYang et al.(2004) | \n\t2004 | \n\tQidongese | \n\thigh | \n\tcase-control | \n\tage, sex | \n\t69 | \n\t136 | \n\tabout 1 ( | \n
12 | \n\tPan et al.(2012) | \n\t2012 | \n\tShangdongese | \n\tmedium | \n\tcase-control | \n\tage, sex | \n\t202 | \n\t236 | \n\t1.35-1.55 ( | \n
13 | \n\tLi et al.(2012) | \n\t2012 | \n\tShangdongese | \n\tmedium | \n\tcase-control | \n\tage, sex | \n\t150 | \n\t158 | \n\t1.69-1.78 ( | \n
14 | \n\tChen et al.(2005) | \n\t2005 | \n\tTaiwanese | \n\thigh | \n\tcase-control | \n\tage, sex | \n\t577 | \n\t389 | \n\t1.57 ( | \n
Characteristics of studies about genetic polymorphism at codon 399 of DNA repair gene XRCC1 and risk biomarker for DNA repair capacity (namely HCC risk)
a Defined by means of Ref Henry,
b AFB1-related DNA repair capacity is evaluated using risk biomarker AFB1-related HCC risk (
The meta-analysis of the relationship between genetic polymorphism at codon 399 (Arg/Gln) XRCC1 and AFB1-related HCC risk, a biomarker for DNA repair capacity correlated with AFB1-induced DNA damage, based on overall studies size. Compared with Arg/Arg genotype, Arg/Gln (A) genotype decreased AFB1-related DNA repair capacity. This effect was not observed in Gln/Gln genotype (B).
The meta-analysis of the relationship between genetic polymorphism at codon 399 (Arg/Gln) XRCC1 and AFB1-related HCC risk, a biomarker for DNA repair capacity correlated with AFB1-induced DNA damage, based on overall studies size excluded possible repeated studies. Compared with Arg/Arg genotype, Arg/Gln (A) and Gln/Gln (B) genotype decreased AFB1-related DNA repair capacity.
The meta-analysis of the relationship between genetic polymorphism at codon 399 (Arg/Gln) XRCC1 and AFB1-related HCC risk, a biomarker for DNA repair capacity correlated with AFB1-induced DNA damage, based on overall studies size excluded possible repeated studies and studies from low AFB1 exposure areas. Compared with Arg/Arg genotype, Arg/Gln (A) and Gln/Gln (B) genotype decreased AFB1-related DNA repair capacity.
These data support XRCC1 codon 399 Gln alleles decrease AFB1-related DNA repair capacity. Additionally, several studies have shown that the other two genetic polymorphisms (at codon 194 and codon 280) of XRCC1 also decrease DNA repair capacity related AFB1-induced DNA damage, with adjusted value 2.25-2.27 for codon 194 polymorphism and 4.95-6.27 for codon 280 polymorphism (
DSBR pathway involves a series of DNA repair genes. In published molecular epidemiological studies, only XRCC3 gene codon Thr241Met polymorphism and XRCC7 rs#7003908 polymorphism affect AFB1-related DNA repair capacity [8, 15, 78].
The product of the XRCC3 gene is one of identified paralogs of the strand-exchange protein RAD51 in human beings [188-192]. This protein correlates directly with DNA breaks and facilitates of the formation of the RAD51 nucleoprotein filament, which is crucial both for homologous recombination and HRR [188-192]. Previous studies have shown that a common polymorphism at codon 241 of XRCC3 gene (Thr to Met) modifies the function of this gene [193-205]. Two reports from high AFB1-exposure areas all of world supported above-mentioned conclusions [15, 90].
In the first frequent case-control study in Guangxiese [90], we observed that the genotypes with XRCC3 codon 241 Met alleles (namely Thr/Met and Met/Met) was significantly different between controls (33.01%) and HCC cases (61.48%,
DNA repair gene XRCC7, called DNA-dependent protein kinase catalytic subunit (DNA-PKcs), DNAPK, DNPK1, HYRC, HYRC1, or p350) (Genbank ID. 5591), spans about 197 kb on chromosome 8q11 and contains 85 exons and 86 introns (Gene dBase in PubMed). This gene encodes DNA-PKcs that constitutes the large catalytic subunit of the DNA-PK complex. When DNA-PKcs is recruited to the site of DSBs by the Ku70/Ku80 heterodimer, DNA-PK complex changes into its active form and subsequently initiates the non-homologous end joining (NHEJ) repair, an important DSBR pathway [206-213]. Murine mutants defective in the XRCC7 have non-detectable DNA-PK activity, suggesting that XRCC7 is required for NHEJ pathway protein. More than 20 polymorphisms have been reported in the XRCC7 gene, some of which are correlated with malignant tumors such as bladder cancer (dbSNP in NCBI Database). Of these genetic polymorphisms in XRCC7 gene, only two loci (rs7003908 and rs10109984) are investigated their modifying effects on AFB1-related DNA repair capacity [8].
In this hospital-based case-control study conducted by Long,
Recently, great progress has been made in understanding the molecular mechanisms of the genetic susceptibility to DNA repair capacity related to AFB1-induced DNA damages. However, we are still far from a comprehensive view of the issue. The molecular mechanism about genetic polymorphisms in the DNA repair genes modifying DNA repair capacity related AFB1-induced DNA damages remains largely unknown. Although several reports have shown the spot mutation resulting from genetic polymorphisms may decrease DNA repair capacity via changing the structure of DNA repair proteins, downregulating expression of DNA repair genes or decreasing the function of DNA repair genes, more direct evidence is lost. Disclosing the roles of different genetic types of DNA repair genes in the different toxicity of AFB1 will greatly benefit our understanding of pathological mechanisms of the genetic polymorphisms in the DNA repair genes affecting DNA repair capacity related to AFB1-induced DNA damage, and will shed important light on the clinical therapy for these patients with risk types.
AFB1 is an important environment variation of DNA damage. This toxic variation is characterized by: (1) the attraction of specific organs, especially liver; (2) genotoxicity, mainly inducing the formation of AFB1-DNA adducts and the hot-spot mutation of p53 gene; and (3) carcinogenicity, primarily causing HCC. Among these chronic DNA damage characteristics, AFB1-DNA adducts play a central role because of their genotoxicity and interactions with genetic susceptive factors. In human, there are several repair pathways, including NER, BER, SSBR, and DSBR, is able to repair this type damage. Genetic polymorphisms in DNA repair genes might modify the expression and the functions of DNA repair proteins encoded by the relative genes and decrease the AFB1-correlated DNA repair capacity. Based on this knowledge, DNA repair capacity related to AFB1-induced DNA damage can be elucidated via the following three methods: testing the levels of AFB1-DNA adducts (mainly AFB1-FAPy adduct), analyzing the frequency of TP53M, and evaluating the risk of HCC by AFB1 exposure.
Numerous studies reviewed in this paper have demonstrated that the hereditary variations in DNA repair genes are associated with DNA repair capacity of DNA damage induced by AFB1. These molecular epidemiological studies have significantly contributed to our knowledge of the importance of genetic polymorphisms in DNA repair genes in the individual’s susceptibility to AFB1 exposure. It would be expected that genetic susceptibility factors involved in DNA repair genes for AFB1-induced DNA damage repair could serve as useful biomarkers for identifying at-low-DNA-repair-capacity individuals by AFB1 exposure and, therefore, targeting prevention of this toxicity-related malignant tumor.
However, there are several issues to be noted. The conclusions should first be drawn carefully, because of conflicting data existing in the same ethnic population in view of between some genotypes of DNA repair genes and the AFB1-related DNA damage repair capacity. Second, because of the fact that AFB1-related DNA repair is polygenic, no single genetic marker may sufficiently predict DNA repair capacity. Therefore, a panel of susceptive biomarkers is warranted to define individuals at low DNA repair capacity. Last, the corresponding molecular mechanisms of risk types modifying DNA repair capacity correlated with AFB1-induced DNA damages should be paid close attention.
We are grateful to Yuan-Feng Zhou for the collection and management of data. This study is partly supported by the National Nature & Science Foundation of China (NO. 81160255), the Science Foundation of Youjiang Medical College for Nationalities (NO. 2005 and 2008), and Guangxi Key Construction Project of Laboratory Room (NO. 2009).
AFB1, Aflatoxin B1; AFB1-epoxide, AFB1-8,9-epoxide; AFB1-N7-Gua, 8,9-di-hydro-8-(N7-guanyl)-9-hydroxy–AFB1; AFB1-FAPy, ring-opened formamidopyridine AFB1; AFF, aflatoxins family; APE1, AP endonuclease-1; BER, base excision repair; CI, confidence interval; DNA-PKcs, DNA-dependent protein kinase catalytic subunit; DSB, double-strand break; DSBR, double-strand break repair; HBV, hepatitis virus B; HCV, hepatitis virus C; HCC, hepatocellular carcinoma; hOGG1, Human oxoguanine glycosylase 1; NER, nucleotide excision repair; OR, odds ratio; 8-oxodG, 8-oxodeoxyguanosine; PARP, poly (ADP-ribose) polymerase; PLC, Primary liver cancer; PNK, polynucleotide kinase; Pol β, DNA polymerase β; ROS, reactive oxygen species; SSB, single-strand break; SSBR, single-strand break repair; XPA, xeroderma pigmentosum A; XPC, xeroderma pigmentosum C; XPD, xeroderma pigmentosum D; XRCC1, x-ray repair cross complementary 1; XRCC3, x-ray repair cross complementary 3; XRCC4, x-ray repair cross complementary 4; XRCC7, x-ray repair cross complementary 7.
The impacts of climate change (CC) will be channeled primarily through the water cycle [1], with consequences that could be large and uneven particularly on the agricultural sector. Ref. [1] also entails that some regions could see their growth rate decline by as much as 6% of GDP by 2050 as a result of water-related losses in agriculture, health, income, and property. For the Mediterranean countries, reduction of freshwater availability is predicted to attain more than 40% by the end of this century along the coastal areas [2]. The North African region is one of the regions which will be affected the most by CC, as anticipated by different climate models [3]. The region is already experiencing low rainfall characterized by its high variability, which is influencing agricultural production systems and changing their determinants. Climate model simulations are providing converging results concerning the decreasing trends of rainfall with 10–20% across North Africa [4], with average median decrease reaching 12% [5]. For Tunisia, this rainfall trend will result in a decline of water availability with up to 28% in 2030 [6, 7]. Ref. [1] also reports that water management policies can exacerbate the adverse growth impacts of CC, while good policies can go a long way toward neutralizing them. While CC is one of the major challenges facing humanity nowadays, adaptation frameworks to its, reversible and irreversible, impacts on the natural and human systems have emerged as an urgent need. It is expected to intensify risks related to natural resources availability, particularly in areas where water scarcity is already a concern [8]. In most countries, freshwater scarcity is increasing, forest fires are more frequent because of high temperature, drought is omnipresent and persistent, and desertification rates are growing [9]. Previous reports and analysis have described the Mediterranean region as a CC “hot spot” [10] including the Intergovernmental Panel on Climate Change (IPCC). Agriculture is a climate-sensitive sector subject not only to adverse impacts of CC on natural resources but also on social and economic contexts. Changes in precipitation and warming patterns are witnessed having occurred during the last century [11]. All year round widespread warming and reduction in rainfall are predicted by scientific literature for the twenty-first century [10]. Reduction in precipitation in addition to an increase in evapotranspiration would lead to water shortages particularly in regions where resources are already at a critical level and irrigated cropping areas are increasing. CC is thus contributing to narrowing the gap between water supply and demand [12] which entails more complexity on water resources management in agriculture [8]. CC is reshaping not only agriculture activity patterns but also driving human existence standards, which requires a restructuration of an institutional framework and a policy plan that could be able to mitigate and adapt to CC impacts. Therefore, exploring adaptive pathways [13] and climate policy is becoming a cross-scale central focus for decision and policy makers [14]. Ref. [15] demonstrated the role of regional, national, and global policies and institutions in highlighting adaptation options and tools [16] and that the development of CC adaptation as a policy field is considered as a relevant application context for the establishment of the agriculture policy [17]. In order to assess the implications of potential policy actions and to assist stakeholders in developing adequate measures to improve resilience to CC, [17] prevailed that cost-benefit analysis is a useful assessment tool; bio-economic models are more useful for an ex-ante evaluation of policy interventions by simulating agents’ (farmers’) behavior on the farm level. However, analyzing CC impacts on agriculture (economic, social, and environmental) requires an approach that is able to provide a detailed picture of the sector, its constituents, and the interactions within it. Agricultural models, can be built on micro-level; bio-economic models or macro-level; studies entailing the whole agricultural sector such as agricultural supply models. Agricultural supply model (ASM) provides a presentation of the agricultural sector by a sequence of behavioral equations whose objective is to maximize regional income subject to technological, environmental, and institutional constraints [17, 18, 19]. They treat a wide range of issues in agriculture; ASM has been used to predict and assess the impacts of Europe’s Common Agricultural Policy (CAP) or to estimate economic value of water and land [20]. Assessing CC impacts on Tunisian agricultural sector is a propitious research field; hence, by means of an agricultural supply model, it is possible to assess the impact of water scarcity, engendered by CC, on the agricultural sector in the country.
\nIn this chapter, we suggest to look to strategic structural adjustments needed in terms of land use and irrigation in Tunisia to deal with future water scarcity. Structural change in agriculture is defined as being the adjustment of the agricultural sector to the changing conditions of demand and supply [21]. This complex and dynamic process constitutes a reallocation of land use and farm specialization, as well as repositioning of the agricultural sector as compared to other sectors of the economy [21, 22, 23]. Within this general framework, the objective of this paper is to simulate the scope of future water scarcity scenarios on the agricultural sector of Tunisia and to provide recommendations on how to reduce its effects through a CC adaptive policy plan. For the following sections, we particularly refer to structural change as being the reallocation of land use and crop specialization among different regions in Tunisia, as well as upon rain-fed and irrigated conditions. A regionally disaggregated agricultural supply model for Tunisia (ASMOT) was developed and used to simulate the effects of declining irrigation water availability on the development of the agricultural sector in different regions of Tunisia. Implications in terms of regional agricultural value added as well as employment in both irrigated and rain-fed sectors were assessed under different water-related scenarios. To our knowledge, ASMOT is the first attempt of disaggregated sector modeling in Tunisia which we aim to further develop and validate in the coming years.
\nAgriculture is an important sector in Tunisia contributing to 8.7% of the national GDP and employing around 16.2% of the total employment in the country [24]. Major crops, in terms of cultivated area, are tree crops (especially olives and dates) followed by cereals. While tree crops are strategic for exports (Tunisia is among the top 5 world exporters of olive oil and dates), cereals remain very important for human and livestock domestic consumption. Tunisia is also characterized by low rainfall and limited renewable water resources. It is influenced by the arid and semiarid climate that covers more than three-fourths of its area [25]. The agricultural sector is also highly dependent on water resources since it consumes more than 75% of total water use in the country [26, 27]. Climate variability has major effects on agricultural production in Tunisia which results on highly variable yields along years. Other sectors might also be affected but certainly with much less extent. In fact, according to the Tunisian regulation, urban, industrial, and touristic sectors are prioritized in terms of water use during shortage periods. As an example of this fluctuation, total cereal production went from 2.9 million tons in 1996 to 0.5 million tons in 2002 and again to 2.9 million tons in 2003 [26]. This trend is observed for all cereal crops where the yield of durum wheat varies between 0.5 and 2 tons/ha, soft wheat yield ranges between 0.5 and 2.5 tons/ha, and barley yield is between 0.4 and 1.5 tons/ha. Not only yields are variable, but the cereal and fodder cropped areas are also depending stochastically on the climate conditions. For the expected “bad” years, farmers usually avoid planting cereals which engenders a decrease of both areas and yields. As strategic response to climate variability, the country has started since the early 1970s to expand its irrigated areas in order to ensure more reliable supply of agricultural commodities over the years [28]. This strategy partly succeeded in developing around 450,000 ha of irrigated areas representing around 8% of total agricultural area in the country. Although irrigated area share is low, it reflects the highest surface that can be irrigated by the available water resources, given the current levels of irrigation water use efficiency (IWUE). However, despite their low share in total agricultural land, irrigated areas in Tunisia are producing 35% of the agricultural value added, and they are contributing up to 20% of total agricultural exports and 27% of agricultural employment [26]. Around 48% of these irrigated areas are irrigated from groundwater sources, including both superficial and deep aquifers, allowing the irrigation of 48% of the total irrigated area [28]. Overall water resources in the country are estimated to be only around 4700 million m3 [7] including 650 million m3 of nonrenewable resources (13.8% of the total water resources). Surface water is estimated to 2700 million m3. Another major problem of the agricultural sector in Tunisia is the small farms’ size. In fact, average farm size in Tunisia in 2005 was only about 10.2 ha [27]. Total farm number is 516,000 farms, managing an area of 5.3 million ha. According to the same source, in 2005, 54% of these farms have a size lower than 5 ha, and 75% of farms have a size lower than 10 ha indicating the main structural problem facing the modernization of the agricultural sector and the irrigated areas. In this regard, the stabilization of agricultural yields and the decrease of the sector dependency to climate variations are thus necessary for enhancing food security and agricultural trade balance in Tunisia. Many solutions have been proposed including the improvement of farmers’ skills, financing, mechanization, intensification, and the extension of the irrigated areas. A structural change, however, is a broader concept that permits the adjustment of agricultural sector not only upon market features but also a more sustainable management of natural resources, land and water, to reinforce resilience to climate variability and food insecurity. This paper actually aims to determine which national structural readjustments are relevant for a more efficient reallocation of resources using a country- and context-specific agricultural supply model and scenarios. The following sections explain in details the model structuring and also present and discuss the outcomes of the study.
\nThe ASMOT model is an agricultural supply model that is built based on primary and secondary data of farming inputs and outputs for different crops, regions, and systems (rain-fed and irrigated). ASMOT is the first regionally disaggregated ASM developed for Tunisia. The model includes 21 of the most strategic crops of the country (including the most important cereals, trees/fruits, and vegetables). It also includes a representation of 67% of the total agricultural areas of Tunisia (around 3.34 million ha) and 78% of the total irrigated areas (around 352,000 ha). The ASMOT model is built based on regional disaggregated data, including 24 governorates of Tunisia. These governorates have been aggregated into five regions (North West (NW), North East (NE), Center West (CW), Center East (CE), and South (SO)) based on bioclimatic homogeneity (Figure 1).
\nDifferent bioclimatic regions in Tunisia.
The model was calibrated through Positive Mathematical Programming (PMP) [29] and using official 2011 data about observed crop areas by region and system (irrigated/rain-fed) as recorded by the Ministry of Agriculture, Hydraulic Resources and Fisheries of Tunisia [30]. Regional irrigation water availability was also included into the model based on official secondary data about existing water reservoirs in the different regions of the country.
\nRegional agricultural value added are optimized by ASMOT and aggregated into a national domestic agricultural value added. Various types of biophysical and economic constraints are considered in parallel to this optimization process. These can be found in the next section presenting the main mathematical structure of the model. The model also considers crop evapotranspiration and their respective effect on yield gaps. The different crops and regions included in the ASMOT model are shown in Table 1.
\nCrops | \nGovernorates and aggregated regions | \n
---|---|
Durum wheat, soft wheat, barley, olive, almond, palm date, citrus, grape, peach, apple, pear, grenade, tomato, potato, pepper, onion, garlic, artichoke, melon, watermelon, strawberry | \nNorth West (NW) (Bizerte, Beja, Seliana, Le Kef, Jendouba) North East (NE) (Nabeul, Ariana, Manouba, Ben Arous, Zaghouan) Center West (CW) (Sidi Bouzid, Kasserine, Kairouan, Gafsa) Center East (CE) (Sfax, Mahdia, Monastir, Sousse) South (SO) (Tozeur, Kebili, Tataouine, Médenine, Gabes) | \n
Different crops and regions considered by the ASMOT model.
The aggregated agricultural supply (Eq. (1)) of the model calculates the aggregated gross value of agricultural supply (AS) in Tunisia as the sum of regional agricultural gross production values (RAS). Eq. (1) can be read as follows:
where ASc,s is the total agricultural supply of different crops (c) and systems (s). Systems can either be rain-fed (rai) or irrigated (irr). RASr,c,s indicates the regional agricultural supply by region (r), crop (c), and system (s). Pc is the producer price of crop c; Y is the yield expressed by region, crop, and system; and ∆Y is the variation of yields which can be due to water stress (higher temperatures and evaporations). AC is the average cost of crop production excluding water costs. AC is expressed by region and system. WP is the irrigation water price in different regions. Finally, Xc,r,s is the positive variable of the total area for crop (c) under system (s) and in region (r). Observed Xc,r,s of the year 2011 was used for the calibration of Eq. (1). Once calibrated, X becomes variable and can be optimized under different scenarios. Yield variation ∆Y is calculated as follows:
\nwhere
Constraint 3 is a land constraint, indicating that the total cultivated areas in each region should not, in the short term, exceed the currently observed agricultural areas (Ar):
\nConstraint 4 indicates that the sum of crop irrigated areas in each region should not exceed the total irrigable areas (IAr) available in that region:
\nConstraint 5 bounds the annual tree area expansion to the observed annual growth rates of these areas in Tunisia during the last two decades which is about 5%. This constraint is also set at the regional level, where TAr is the current tree area in region r and γ is the annual growth rate of tree areas which is set to be equal to 5%:
\nConstraint 6 indicates that the sum of water requirement of all crops cultivated under different systems in a given region (Wr,c,s) should not exceed the water availability in that region (WAr):
\nFinally, constraint 7 is a calibration constraint which was used in the first PMP step in order to estimate the cost function calibration coefficients (αr,c,s and βr,c,s). The average cost AC function is a nonlinear expression (Eq. (8)) estimated using two main calibration coefficients (\n
Eq. (8) was replaced by Eq. (1) which will generate a calibrated nonlinear objective function. To validate the calibrated model, we optimize Eq. (1) under all constraints while excluding the initial calibration in Eq. (7). If the resulting model will generate the same land allocation observed during the base year, then we can assume that our model is well validated and can be used for scenario simulations. ASMOT validation and calibration performances are presented in the result section.
\nThe data used for the ASMOT model was of different types and thus collected from various sources. Specific crop input and output levels for different regions and systems were collected through farmer questionnaires which were conducted for the season 2012–2013, in all regions of Tunisia in the framework of the Eau Virtuelle et Sécurité Alimentaire en Tunisie(EVSAT, funded by the IDRC) research project. Many focus groups with regional experts in crop production were conducted afterward in order to revise the average input and output values in respective regions and systems for all considered crops. Some coefficients of the model, such as the annual growth rates of tree crops, were calculated using FAO data [40]. Other secondary data regarding water availability, initial crop area distribution, irrigated areas, etc. were collected from official national datasets, especially available at the level of [30]. Water requirements in addition to evapotranspiration coefficients of different crops in different regions and systems were measured by the EVSAT research team through field experimentations.
\nIn relation to the overall objective of the chapter, our scenario development considers the current water scarcity situation faced by Tunisia, where water availability is expected to decrease by 28% at the end of the next decade [6]. Based on this, our first scenario suggests a cut of water availability by 25%, while second and third scenarios will consider improvements of IWUE and producers’ prices as possible options to deal with this shortage and offer market incentives to enhance farmers’ adaptation capacities. Only 69% of the total irrigated areas in Tunisia are fitted with water-saving technologies, thus leading to an average water use efficiency of about 55% at the national level [41]. This shows a wide scope to improve IWUE through appropriate investments in the farmer’s skills and modernization of the irrigation networks. On the other side, it is well known that better integration of farmers along commodity value chains may offer enhanced producer prices [42], which can be considered as market incentives allowing farmers to enhance their technical investments and adaptation capacities [43, 44]. Based on these arguments, scenarios which were simulated using the ASMOT model can explicitly be read as follows:
Scenario 1. Cutting total fresh water availability by 25%. This reduction is supposed to be the same across all regions of the country.
Scenario 2. Cutting total fresh water availability by 25% and improving IWUE by 10%. The improvement of IWUE is interpreted in our modeling as a decrease of water volumes applied for different crops by 10%.
Scenario 3. Cutting total fresh water availability by 25%, in addition to an increase of IWUE with 10% and higher producer prices offered to farmers. The suggested increase of producer prices are as follows: +5% for cereal prices and +10% for fruits and vegetable prices.
After calibrating the model using real 2011 data and by estimating the calibration coefficients of the average cost function (Eq. (8)), the model was validated by running a status quo scenario and checking for consistency of the results compared to the observed values of land use. The result of this test showed that deviations of simulated land use variables (
Percentage deviation of simulated vs. observed crop areas in different regions included in the ASMOT model.
This validation test shows that ASMOT is performing well and can thus be used for scenario simulation. The next step is to reformulate and modify appropriate equations in the model in order to be able to simulate the scenarios presented in Section 2.3. Economic, social, and environmental outcomes of these scenarios are presented in the following sections.
\nAs discussed earlier, ASMOT optimizes the national agricultural value added and provides optimal regional land allocations for different crops and systems. These needed changes of land use in Tunisia allowing for optimal agricultural performances under a situation of water scarcity were purely calculated based on economic incentives corresponding to crop yields, costs, and incomes in the different regions and systems of Tunisia (Table 2). Results in Table 2 show the overall trend of land use under different scenarios (SC1, SC2, and SC3).
\nType of crops | \nRegions | \nPercentage deviations compared to the status quo situation | \n||
---|---|---|---|---|
SC1 | \nSC2 | \nSC3 | \n||
Cereal crops | \nNW | \n−0.28 | \n−0.06 | \n−0.75 | \n
NE | \n2.21 | \n0.77 | \n−1.39 | \n|
CW | \n−8.25 | \n−3.37 | \n−6.69 | \n|
CE | \n−0.01 | \n0.03 | \n−0.14 | \n|
SO | \n0.52 | \n0.26 | \n0.59 | \n|
Olives and almond | \nNW | \n−0.8 | \n−0.4 | \n1.6 | \n
NE | \n3.8 | \n2.1 | \n3.3 | \n|
CW | \n2.2 | \n1.0 | \n1.5 | \n|
CE | \n−0.1 | \n0.0 | \n−0.1 | \n|
SO | \n1.7 | \n0.3 | \n0.0 | \n|
Irrigated fruit trees | \nNW | \n6.2 | \n1.4 | \n8.7 | \n
NE | \n−8.0 | \n−3.8 | \n0.2 | \n|
CW | \n−5.2 | \n−3.4 | \n2.7 | \n|
CE | \n0.7 | \n−0.6 | \n3.4 | \n|
SO | \n−11.7 | \n−2.3 | \n−1.8 | \n|
Vegetable crops | \nNW | \n8.0 | \n2.9 | \n4.8 | \n
NE | \n−17.0 | \n−7.3 | \n−5.4 | \n|
CW | \n−4.1 | \n−2.7 | \n−0.6 | \n|
CE | \n7.5 | \n2.7 | \n7.5 | \n|
SO | \n4.6 | \n2.2 | \n8.1 | \n
Percentage change, compared to baseline situation, of the main crop areas under different scenarios (aggregated changes of rain-fed and irrigated systems).
Table 2 shows that trends of SC1 and SC2 are consistent but in most cases different from trends suggested under SC3. For the case of cereals, both SC1 and SC2 suggest important cuts of cereal areas in NW and CW and an increase of these areas in NE and SO regions. However, cereal areas are suggested to be reduced in all areas (except SO) under SC3. The same scenario 3 is also more favorable for expanding olives, almond, irrigated fruit trees, and vegetable areas in the different aggregated regions. The highest area reductions recorded under SC1 and SC2 are these of cereals in CW; irrigated fruit trees in NE, CW, and SO; and vegetable crops in the NE. Under SC3, the highest area reductions were however recorded for cereals in CW and vegetable crops in NE.
\nTotal water use for irrigation under different scenarios in Tunisia was estimated based on optimal changes of land use as suggested in Table 2 (see Figure 3). In the baseline scenario, around 2086.6 million m3 of water is used for the total irrigated area considered in ASMOT (78% of the total irrigated areas, around 352.9 thousand ha) with an average use of 5912.1 m3/ha (Figure 3). Under the first, second, and third scenario, total water consumption, respectively, decreases to 1876.5, 1818.1, and 1833 million m3. By considering the new irrigated areas under each scenario, these decreases led to average water consumptions of 5949, 5349.7 , and 5385.8 m3/ha. Total water saving under the second scenario is about 268.5 million m3, which corresponds to around 13% of the total water use in the baseline situation. These numbers are showing that effective water management in the irrigated areas in Tunisia can mitigate the effect of water scarcity and even generate agricultural economic growth if accompanied by appropriate economic incentives.
\nTotal water use for irrigation under different scenarios.
ASMOT provides information about the total value added of its respective agricultural land area as the most aggregated results calculated based on optimization of these values at regional levels. This result can be calculated and presented for separate scenarios. For our particular case, the optimization process shows that Tunisia can overcome the problem of water scarcity (Figure 4) through specific structural changes of land use among crops, systems, and regions, as suggested in Table 2. Figure 4 shows that agricultural value added in Tunisia will decrease with only 0.76 and 0.16%, respectively, under SC1 and SC2. However, these slight changes can only be possible if structural adaptations of the Tunisian agricultural sector, based on specific land use reallocations, are adopted as shown in Table 2.
\nEffect of water scarcity scenarios on the national agricultural value added.
Scenario 2 shows that with 10% increase of IWUE, the cut of water availability can be effectively mitigated, with an agricultural value added remaining almost equal to the status quo situation. If producer prices will further be supported (+5% for cereal crops and +10% for fruits and vegetable crops), the agricultural value added in Tunisia can even be 13% higher than the baseline situation, despite the sharp water cut considered. This higher value added of SC3 is not only due to the suggested price inflation but also to the restructuring of land use and the decrease of total water use under this scenario. In fact, irrigated areas will decrease the most under SC3, and the average water use by hectare of irrigated land will also be 9.5% lower than SC1. Furthermore, the average price inflation considered under SC3 is only about 7.5%, with a maximum of 10% for vegetables and fruits. This price increase generated a higher and nonproportional increase of the value added (+13%), showing a relevant and positive and environmental effect of this price instrument.
\nFigure 5 shows a geographical distribution of changes in total agricultural value added among the considered regions, under different scenarios. It also shows the respective trends of these values among rain-fed and irrigated sectors. The figure shows that irrigated agriculture in Center West and North East of Tunisia is mostly affected by water scarcity. However, the contribution of the rain-fed agriculture in these two regions is also expected to grow which will partly overcome the negative effects of the decrease of irrigation value added.
\nChanges of regional agricultural value added under different scenarios in Tunisia (million TND).
In this section we provide an overview of changes in labor demand under different scenarios compared to the baseline situation. Figure 6 shows that despite the optimization of land use and agricultural value added, agricultural labor demand will still be negatively affected under both SC1 and SC2, with respective decreases of 0.7 and 0.18% compared to the baseline situation. The same figure shows that this decrease of labor demand is exclusively recorded for irrigated areas and can reach–5.91% in these areas under the first scenario. The third scenario shows however that overall agricultural labor demand in Tunisia can increase with about 1.06% (around 8500 employment), despite the water scarcity situation. It is important to notice that, in opposite to SC1 and SC2, labor demand will increase under SC3 for the irrigation sector despite the decrease of the irrigated areas under this scenario (−3.6%).
\nEffect of different scenarios on regional agricultural labor demand (percentage changes compared to baseline).
Similar to the agricultural value added, labor demand in agriculture will disproportionally be affected along the different regions of Tunisia. Figure 7 captures most of these regional effects for both rain-fed and irrigated sectors. Despite the negative trend of labor demand in the irrigated sector, the restructuring of irrigated areas in the North West and Central East of Tunisia may generate slightly higher employment while at the same time maximize the value added of this sector. Furthermore, results show that labor demand in irrigated areas of South Tunisia will be decreasing even under the third optimistic scenario.
\nEffect of different scenarios of regional agricultural employment under different scenarios (percentage change compared to baseline).
The scope of enhanced IWUE was proven through our analysis to be highly effective in mitigating the effects of water scarcity in the different regions of Tunisia. Better IWUEs (SC2) are allowed for lower decrease of irrigated areas than the no IWUE scenario (SC1). In the NE region, these decreases were, respectively, −15 and −6% under SC1 and SC2. At the national level, irrigated areas decreased with −10.6 and −3.7%, respectively, under SC1 and SC2. This is showing a wide scope of IWUE to improve irrigation performances and sustain irrigation. However, IWUE can be defined at different scales including user/scheme and basin levels. Through our modeling framework, we only captured benefits of IWUE in terms of water saving. However, in addition to the benefits captured by our model in terms of water saving, physical efficiency at the user/scheme level will also be translated into increased water productivity (or economic efficiency) [45]. Mechanisms to reallocate saved water elsewhere in the water economy will further be necessary to enhance basin-level efficiency. On the other hand, only improvement of IWUE through better technology and management can generate real water savings [45]. Hence, in order to improve IWUE, some measures could be considered such as assisting farmers by providing enhanced knowledge about better irrigation scheduling of optimal amounts of applied water. Another measure would be related to better management of irrigation systems at the field and the landscape levels.
\nWithout substantial improvement in the productivity of rain-fed agriculture, and despite a considerable expansion of cropped area, irrigated area would have to increase close to 500 million ha globally to meet the expected food demand, entailing a doubling of water use [46]. However, it is unlikely that suitable natural resources for such expansion might be available and the increase of agricultural productivity in both rain-fed and irrigated agriculture is necessary to meet such a global food demand. In Tunisia, our results show that rain-fed agriculture might be a good alternative for mitigating the effects of future water scarcity. In fact, value added of this sector was stable over the different scenarios, and it also showed a good potential for absorbing unemployment from the irrigated sector.
\nThe overall effect of the water shortage scenarios on employment is negative, but this negative effect can widely be mitigated and improved if producer prices can be increased. Increased producer prices do not necessarily entail higher consumer prices but can simply be implemented through enhanced management, regulation, and control of agri-food value chains. This is in line with the suggestion that better integration of farmers along commodities value chains may offer enhanced and more equitable producer prices [42], which can in turn be considered as a type of market incentive for farmers and can be used to promote specific agricultural productions [43, 44].
\nIn this chapter, we used an agricultural supply model to simulate the effect of water scarcity on agricultural production in Tunisia. We simulated three scenarios related to (i) cutting irrigation water availability, (ii) cutting irrigation water availability accompanied by relative improvement of irrigation water use efficiency, and (iii) scenario 2 in addition to enhanced producer prices for farmers. Results were overall showing that mitigating a shortage of irrigation water in Tunisia is possible through readjustment of irrigated and rain-fed areas and better allocation of crops among regions and systems (irrigated vs. rain-fed). Results also show that the best scenario which has a significant effect on agricultural value added is the third one. Under this scenario, agricultural employment in the overall agricultural sector can even increase. We strongly recommend that the “national agricultural map” already developed by the Tunisian government could be revised using further socioeconomic data and applied for an optimal allocation of crop areas across the country. We further recommend that more work should be done on better performing the structure and the functioning of the strategic agri-food value chain in Tunisia, allowing better marketing margins for farmers which will thus be translated into higher adaptation capacities of farmers to climate change and water scarcity.
\nThis work was undertaken as part of, and funded by, the CGIAR Research Program on Policies, Institutions, and Markets (PIM) led by the IFPRI. Authors acknowledge the support of the Arab Fund for Economic and Social Development. The data used in this work was collected in the framework of the “Eau Virtuelle et Sécurité Alimentaire en Tunisie” project funded by the IRDC. The authors also acknowledge helpful funding from the European Union Horizon 2020 programme, under Faster project, grant agreement N°[810812].
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\n\nThe first step in obtaining funds for your Open Access publication begins with your institution or library. IntechOpen’s publishing standards align with most institutional funding programs. Our advice is to petition your institution for help in financing your Open Access publication.
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\n\nPlease consult our Open Access Funding page to explore some of these funding opportunities and learn more about how you could finance your IntechOpen publication. Keep in mind that this list is not definitive, and while we are constantly updating and informing our Authors of new funding opportunities, we recommend that you always check with your institution first.
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She is now a lecturer at the University of Witwatersrand, South Africa, and a principal researcher at the Health Economics and Epidemiology Research Office (HE2RO), South Africa. Dr. Moolla holds a Ph.D. in Psychology with her research being focused on mental health and resilience. In her professional work capacity, her research has further expanded into the fields of early childhood development, mental health, the HIV and TB care cascades, as well as COVID. She is also a UNESCO-trained International Bioethics Facilitator.",institutionString:"University of the Witwatersrand",institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"355660",title:"Dr.",name:"Anitha",middleName:null,surname:"Mani",slug:"anitha-mani",fullName:"Anitha Mani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"355612",title:"Dr.",name:"Janani",middleName:null,surname:"Karthikeyan",slug:"janani-karthikeyan",fullName:"Janani Karthikeyan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"334400",title:"Dr.",name:"Suvetha",middleName:null,surname:"Siva",slug:"suvetha-siva",fullName:"Suvetha Siva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}}]}},subseries:{item:{id:"90",type:"subseries",title:"Human Development",keywords:"Neuroscientific research, Brain functions, Human development, UN’s human development index, Self-awareness, Self-development",scope:"