Changes in DNA sequence that influence T2D treatment.
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Although there is no consensus in the contribution of genetic component to drug response, many studies from the 1970s have estimated that could be between 20 and 95% of the variability in drug disposition and effects [1]. The difficulty in reaching a consensus is because the contribution of environmental and genetic components to pharmacogenetics cannot be evaluated, through only one approach, that is, analyzing only one drug or group of drugs, or only a SNP or a group of SNPs; we have to talk about PK, PD and related outcomes. In this context, there are a variety of studies focused on PK, or PD, but the convergence of all these concepts has been difficult, so the translation to the clinical practice has been challenging. Along with these barriers are additional factors, such as gene–environment interactions and gene–gene interactions [2]. Moreover, the different responses among ethnicities are another factor to add to this complex phenomenon.
The knowledge on which the participation of genetics in response to the action of drugs in an individual or group of individuals has been generated through various studies, applying different strategies such as those described below. In this regard, in past decades, different laboratories in four countries carried out twin studies with different drugs to determine the contribution of genetic and environmental factors to interindividual variations. The results from all studies converged in that PK variation were similar between monozygotic twins and was preserved within dizygotic twins, and even as similar as the monozygotic twins [3]. Researchers from these laboratories conclude that genetic factors primarily controlled interindividual variations in the metabolism of a wide range of drugs [3, 4, 5, 6, 7, 8]. In the field of heritability of antidiabetics drug response, the studies are scarce, but one classic example is tolbutamide. In this context, an intravenous administration to 42 nondiabetic subjects, eight of their relatives, and to five sets of twins, the authors observed a monogenic control of tolbutamide revealed by a heritability value of 0.995 (this value means that considering a trait with 1.0 heritability, such as a Mendelian trait, the genetic factors have a great or complete influence in phenotype; in contrast, a trait with 0.0 heritability will not be influenced by genetic factors) [9]. In a more recent study by Gjesing et al., they found high heritabilities estimations for acute insulin secretion subsequent to glucose stimulation (0.88 ± 0.14), for insulin sensitivity (0.26 ± 0.12), disposition index (0.56 ± 0.14) and disposition index after tolbutamide administration (0.49 ± 0.14) in 284 non diabetic family members of patients with T2D after an intravenous injection of tolbutamide [10]. In another study of genome-wide complex trait analysis in patients in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) study, the heritability of glycaemic response to metformin varied by response phenotype, with a heritability of 34% (p = 0·022) for the absolute reduction in HbA1c in 2085 individuals in treatment with metformin [11]. Hence, these studies clearly show that the response to different types or classes of drugs is modulated by the individual’s genetics and can be passed on to their descendants showing a clearly genetic component.
Diabetes has become a health problem (by 2030, the number of individuals with diabetes is estimated to rise to 578 million and 700 million by 2045) [12]. Approximately, 90–95% of cases of diabetes correspond to T2D. T2D is a chronic metabolic disease characterized by hyperglycemia, resulting from insulin resistance and reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia [13].
The great prevalence of T2D impacts both direct and indirect costs. In 2019, the International Diabetes Federation estimated that total diabetes-related health spending reached $ 760 billion. By the years 2030 and 2045, spending is forecast to reach $ 825 billion and $ 845 billion, respectively [12]. Moreover, approximately the 32% of annual costs per diabetic patient is destined to treatment [14]. Furthermore, approximately 50% of T2D patients have good glycemic control considering HbA1c < 7%, which means that ∼50% have poor glycemic control [15]. Besides, as consequence of adverse drug reactions (approximately 20–30%) there is a high prevalence of treatment abandonment [16, 17, 18] All these facts denote the need for new drugs or strategies to improve glycemic control. Current treatment to control diabetes is aimed at specific key targets in glucose metabolism such as: adipose and muscle tissue to reduce insulin resistance, or act on the liver to inhibit glucose production, as well as stimulate the pancreas to release insulin. However, it is necessary to go beyond lowering glucose levels. In clinical practice it is often observed that T2D patients who receive identical antidiabetic regimens have significant variability in drug response, hence interindividual variation may be caused by numerous factors, such as genetic factors, physical inactivity, hypertension, age, gender and others [19]. Particularly, the genetic variability of therapy response was recently shown in several independent studies for the common drugs used for T2D treatment. Therefore, identification of genetic variants and their impact in drug response may improve our knowledge in the field, in order to be able of translate it into clinical practice. This could help in decision making on the therapeutic approach, reducing the rates of side effects and improving the adherence to treatment. Thus, the present chapter aims to collect all the available data about genetic variations in pharmacogenes affecting drug response in T2D and integrate them with their effect on gene expression, and to elucidate their impact on pharmacological efficacy.
In order to cover the objective, we compile all the available information about pharmacogenetics and epigenetics in T2D. We carried out a literature search using PubMed and Google Scholar. For this purpose, search words used were the following: diabetes + pharmacogenetics (826 studies); type 2 diabetes + pharmacogenetics (421 studies), diabetes + pharmacogenomics (1,184 studies); type 2 diabetes + pharmacogenomics (456 studies). When we added the words “drug response” the result was 338 and 267 papers, for pharmacogenomics and pharmacogenetics, respectively; or when we added the words “personalized medicine” in the search, we retrieved 152 and 114 papers, for pharmacogenomics and pharmacogenetics, respectively. Table 1 shows all the studies considered significantly associated with antidiabetics drug response. Regarding the Epigenetics section, this was covered with a literature search using the words diabetes + drug response + epigenetics. Table 2 shows the reports of epigenetics variations that influence drug response in T2D treatment. All the studies were chosen taking into account glycemic control and significance.
Drug group | Gene (Encoded protein) | dbSNP ID | Aminoacid change | Population | Effect | References |
---|---|---|---|---|---|---|
Biguanides (Metformin) | rs12208357 | Arg61Cys | European | Association with metformin intolerance | [20, 21, 22] | |
rs72552763 | Met420del | |||||
rs34059508 | Gly465Arg | |||||
rs34130495 | Gly401Ser | |||||
Lower decrease in HbA1c | ||||||
rs1867351 | Ser52Ser | Asian | Reductions in PPG and ΔHbA1c | [23] | ||
rs622342 | Intron A > C | South Indian | Less response to metformin | [24] | ||
European | Decreased reduction in HbA1c levels | [25] | ||||
Mexican | High ΔHbA1c values | [26] | ||||
rs36056065 | Indel GTAAGTTG | European | Association with metformin side effects | [27] | ||
rs628031 | Val408Met | Mexican | High ΔHbA1c values | [26] | ||
Chinese | Reduction in ΔHbA1c and ΔFPG | [23] | ||||
European | Association with metformin side effects | [27] | ||||
rs594709 | 597 A > G | Mexican | Increase in HbA1c values | [26] | ||
Chinese | Increase in FINS decrease in HOMA-IS and in QUICKI | [28] | ||||
rs145450955 | Thr201Met | Iranian | High HbA1c values | [29] | ||
rs316019 | Ala270Ser | Chinese | Higher incidence of hyperlactacidemia | [30, 31, 32] | ||
South Indian | Better response | |||||
rs3119309 | Intergenic | European | Association with metformin inefficiency | [33] | ||
rs7757336 | ||||||
rs2481030 | ||||||
rs2252281 | g. − 66 T → C | European African American | Enhanced response | [34] | ||
rs2289669 | g. − 130G → A | European | Association with reduction in HbA1c levels | [35] | ||
rs12943590 | Gly211Val | Reduced response | [34] | |||
South Indian | Better response | [31] | ||||
rs34399035 | Gly393Arg | European | Lower decrease in HbA1c | [22] | ||
rs8192675 | Intron C > T | European American African American Asian American Latino | Reduction in HbA1c values | [36, 37] | ||
Reduction in blood glucose | ||||||
rs11212617 | Intron C > A | European | Association with treatment success | [38] | ||
rs2162145 | UTR variant T > A /C/G | European African American | Better response | [39] | ||
rs254271 | Intron T > A /C/G | Worse response | ||||
rs2075604 | Intron G > T | Chinese | Better therapeutic efficacy | [32] | ||
CAPN10 (CAN10) | rs3792269 | Arg197Gly | European African American | Association with less treatment success and with smaller reduction in HbA1c | [40] | |
rs784892 | Intron G > A | European American African American Asian American | Association with decreased efficacy | [41] | ||
rs7541245 | Intron C > A | Not provided | Association with decreased glycemic response (decrease response to metformin) | [42] | ||
rs2076828 | C > G | European African American | Association with reduced response | [43] | ||
Sulfonylureas | rs1799853 (*2) | Arg144Cys | European | Greater response to sulfonylureas | [44, 45] | |
rs105791o (*3) | Ile359Leu | |||||
Mexican | Association with good glycemic control | |||||
rs757110 | Ser1369Ala | Chinese | Association with FPG, 2 h plasma glucose and HbA1c decrease | [46, 47] | ||
Association with therapeutic efficacy | ||||||
rs1799854 | Intron C > T | European | Lower HbA1c concentration | [48] | ||
rs1799859 | Arg1273Arg | |||||
rs1801261 | Thr759Thr | Chinese | Less reduction in FPG and HbA1c levels | [49] | ||
rs5219 | Glu23Lys | European Chinese | Better response | [50, 51] | ||
Mexican | Lower response | [52] | ||||
rs5210 | UTR G > A | Chinese | Association with FPG decrease | [46] | ||
rs163184 | C > G | European | Lower FPG response | [53] | ||
rs2237892 | Intron C > T | Chinese | Association with treatment success | [54] | ||
rs2237895 | Intron A > C, T | |||||
Association with treatment success | ||||||
rs7903146 | Intron C > T | European | Lower effect of gliclazide | [55] | ||
Association with therapeutic failure | [56, 57] | |||||
rs12255372 | Intron G > T | |||||
rs10494366 | Intron G > C/T | Less effectiveness of treatment | [58] | |||
rs1801278 | Gly972Arg | African | Association with increased risk for secondary failure | [59, 60] | ||
European | ||||||
rs9282541 | Arg230Cys | Mexican | Association with decreased response to treatment | [61] | ||
Thiazolidinediones | rs1801282 | Pro12Ala | Chinese | Association with better response | [62, 63] | |
Higher ΔFPG | ||||||
rs880663 | Intron A > G | Mexican American | Association with response to troglitazone | [64] | ||
rs4135263 | Intron T > C | |||||
rs1152003 | G > C | |||||
rs6806708 | G > T | |||||
rs13065455 | C > A/G | |||||
rs13088205 | T > G | |||||
rs13088214 | T > C | |||||
rs13073869 | Intron G > A/C | |||||
rs8192678 | Gly482Ser | Chinese | Reduced ΔFPG and ΔFINS | [65] | ||
rs2970847 | Thr394Thr | Reduced ΔPINS | ||||
rs659366 | −866 G/A | Chinese | Smaller attenuated PINS and greater attenuated HbA1c | [66] | ||
rs10509681 (*3) | Lys399Arg | European | Association with reduced glycemic response | [67] | ||
rs4149056 | Val174Ala | European | Association with enhanced glycemic response | [67] | ||
rs2237892 | Intron C > T | Chinese | Larger augmentation in Δ2h glucose | [54] | ||
rs2237895 | Intron A > C/T | Greater decrement in ΔHbA1c | ||||
rs266729 | −11377 C > G | Attenuated rosiglitazone effect | [68] | |||
rs2241766 | GLy15Gly | Attenuated ΔFINS | ||||
Greater decrease in HbA1c and association with pioglitazone treatment | [69] | |||||
rs1501299 | SNP + 276 G > T | Korean | Smaller reductions in FPG and HbA1c | [70] | ||
rs182052 | −10068 G > A | Chinese | Increased reduction in HbA1c | [71] | ||
rs1862513 | −420 C > G | Japanese | Correlation with reduction of HbA1c | [72] | ||
rs7799039 | G-2548A | Chinese | High differential values of FINS and PINS | [73] | ||
rs1800629 | G-308A | Lower values of FINS | ||||
rs17584499 | Intron C > T | Higher ΔPPG | [63] | |||
DPP-4 inhibitors | rs7903146 | Intron C > T | European African Asian | Lower reduction of HbA1c | [74] | |
rs2285676 | UTR A > G/T | Asian | Association with better response | [75] | ||
rs7202877 | T > C/G | European | Smaller decrease of HbA1c | [76] | ||
rs163184 | Intron T > C/G | Association with a reduced glycemic response | [77] | |||
rs3765467 | Arg131Gln | Korean | Association with HbA1c reduction | [78, 79, 80] | ||
rs6923761 | Gly168Ser | European | ||||
rs2909451 | Intron C > T | Not Provided | Association with DPP-4 activity | [81] | ||
rs759717 | Intron G > C | |||||
rs6733162 | Intron G > C/A | |||||
rs57803087 | Intron A > G | Taiwanese | Association with DPP-4 inhibitor response | [82] | ||
rs1128503 | Gly412Gly | Asian | Association with response to therapy | [83] | ||
rs7754840 | Intron C > G | Japanese | Association with HbA1c reduction | [84] | ||
rs7756992 | Intron A > G | |||||
GLP-1 receptor agonists | GLP1R | rs10305420 | Pro7Leu | Chinese | [85] | |
rs7903146 | Intron C > T | Brazilian | Association with PINS | [86] | ||
rs761386 | Intron C > G/T | Taiwanese | Association with changes in the standard deviation of plasma glucose | [87] | ||
rs1416406 | A > G/T | Chinese | Association with FINS | [88] | ||
rs1049353 | Thr453Thr | European | Association with improvement of insulin resistance | [89] | ||
SGLT2 inhibitors | rs72551330 | Met33Thr | Not Provided | Higher AUC (26%) | [90, 91] | |
rs9934336 | Intron G > A | European | Association with reduced 30-min plasma glucose | [92] |
Changes in DNA sequence that influence T2D treatment.
OR: Odd ratio; BG: Blood glucose; FINS: Fasting serum insulin; PINS: Postprandial serum insulin; PPG: Postprandial plasma glucose; HOMA-IS: Insulin sensitivity by homeostasis model assessment; HOMA-IR: Insulin resistance by homeostasis model assessment; HOMA-BCF: homeostatic index of percentage of β-cell function; FBG: fasting blood glucose; FG: fasting glucose; AUC: Area under the curve. The gray cells indicate a haplotype associated with metformin intolerance in the study of Dujic et al. in 2015 [21].
Drug group | Gene /miRNA (Encoded protein) | CpG site | Effect | References |
---|---|---|---|---|
Biguanides (Metformin) | CFAP58 (CFA58) | cg03529510 | Association with glycemic metformin response | [93] |
OR4S1 | cg05402062 | |||
GPHA2 | cg16704073 | |||
SAP130 (SP130) | cg16240962 | |||
SEPT11 (SEP11) | cg01070242 | |||
LRRN2 | cg05151280 | |||
CSTT | cg07511259 | |||
SCYL1 | cg27553780 | Association with metformin intolerance | ||
FOXA2 (HNF-3B) | cg12356107 | |||
PGM1 | cg02994863 | |||
FAM107A (F107A) | cg08148545 | |||
SLC22A1 (OCT1) | cg24864413 | Lower DNA methylation and lower glucose levels | [94] | |
SLC22A3 (S22A3) | cg06295784 | |||
cg07883823 | ||||
SLC47A1 (MATE1) | cg01530032 | |||
cg07829432 | ||||
cg12550399 | ||||
miR-192 | N. A. | Decreased fasting glucose and HbA1c | [95, 96] | |
miR-140-5p | ||||
miR-222 | ||||
Sulfonyulureas | KCNJ11 (KCJ11) | N.R.. | 26.2% vs. 27.2% | [97] |
ABCC8 | 0% vs. 7.2% | |||
SGLT2 inhibitors | miR30e-5p | N. A. | Upregulated | [98] |
miR199a3p | Downregulated |
Epigenetics variations that influence T2D treatment.
N.R. Not reported.
SNPs, are modifications in the DNA sequence, that implies changes in single nucleotides, which are the most common variations and the main source of interindividual diversity [99]. Interindividual variability could be explained in part by SNPs in genes encoding drug-metabolizing enzymes, transporters, receptors and molecules involved in drug metabolism. In this context, many SNPs related with the metabolism of antidiabetic drugs have been described. In the following section we described the most significant SNPs associated with drug response, specifically glycemic control, with antidiabetics treatment.
First-line drugs in T2D therapy are biguanides, however, when the patient is not obese, the sulfonylureas group is usually prescribed and the response to treatment will be evaluated after 3 months [100]. Guidelines from the American Diabetes Association/European Association for the Study of Diabetes (ADA/EASD) and the American Association of Clinical Endocrinologists/American College of Endocrinology (AACE/ACE) recommend early initiation of metformin as a first-line drug for monotherapy and combination therapy for patients with T2D [101]. Approximately 30% of patients with T2D do not respond to metformin and about 20 to 30% experience intolerable side effects [102]. There is considerable variability in the glycemic response and PK characteristics of metformin. In terms of PK, metformin is not metabolized, and is excreted unchanged in the urine, with a half-life of roughly 5 h. In particular, mean plasma concentrations of metformin fluctuate between 0.4 and 1.3 mg/L at a dose of 1,000 mg twice daily [103].
The disposition of metformin includes elimination and tissue distribution, which in turn involves organic transporters (OCTs) and multidrug and toxin extrusion proteins (MATEs); both may contribute to the wide variation in metformin PK. Metformin response variability is important, in fact >30% of patients receiving metformin are classified as poor responders [102]. This drug is a polar molecule largely eliminated by the kidney without undergoing hepatic metabolization. The processes of uptake and secretion of metformin are highly dependent on membrane transporters, among which are solute carrier family 22A members 1 and 2 (SLC22A1/OCT1 and SLC22A2/OCT2, respectively), multidrug and toxin extrusion proteins MATE1 (SLC47A1) and MATE2 (SLC47A2) and the plasma membrane monoamine transporter PMAT (SLC29A4/hENT4). Therefore, impacting variants in any of these transporters may have an influence in metformin efficacy and adverse effects (Table 1). In this context, the most studied genes are SLC22A1/OCT1, SLC22A2/OCT2, SLC47A1/MATE1 and SLC47A2/MATE2. Genetic variants in SLC22A1/OCT1 are responsible for the adverse gastrointestinal effects experienced by many patients with T2D diabetes who use metformin. Dujic et al. found that 47% of participants with T2D, incident users of metformin, experienced gastrointestinal adverse effects. In the study the number of SLC22A1/OCT1 reduced-function alleles was highly correlated with over two-fold risk of gastrointestinal side effect development [20]. Consequently, the gastrointestinal adverse effects and in some cases intolerance to metformin could lead to treatment abandonment. In this same gene other variants associated to metformin response have been reported. As it can be seen in Table 1, most of the reported variants are related to a decrease in the effect of metformin, reflected in the less reduction in HbA1c levels (high concentration of HbA1c). In contrast variant rs316019 in SLC22A2/OCT2 is associated with lactic acidosis and better response to metformin, due to the evidence that this variant is related to a reduced level of metformin clearance [30, 104]. Therefore, patients with these variants may benefit receiving alternative therapy instead metformin.
The studies that evaluated the role of SLC47A1/MATE1 and SLC47A2/MATE2 SNPs in PK and PD in patients receiving metformin revealed that promoter variants in MATE1 (g.-66 T → C, rs2252281; g.-130G → A, rs2289669) are associated with a greater response to the drug in T2D patients [34, 35]. Interestingly, it is also reported that the MATE1 variant affects the PD but not the PK of metformin, a very important finding that reveals that the distribution of drugs occurs in response to the organ-specific location of the various transporters [34]. Most studies have associated variants in SLC47A2/MATE2 with contradictory effects. Concerning rs12943590, it was related to a reduced response in European populations and a better metformin response in South Indian populations; whilst rs34399035 was associated with a reduced response to metformin in European populations [31, 34]. It is important to mention that the studies were carried out in different populations, and that investigations in other ethnicities had not found associations between these variants and metformin response [105, 106]. In a recent meta-analysis by Dujic et al. there was no association between rs12943590 and glycemic response [107]. Nonetheless, it is important to note that SNP-drug interactions and SNP-SNP interactions cannot be ruled out, since the presence of other SNPs also modulate the response to drugs and are different in each individual, thus, genotyping of these SNPs should be considered if it is desired apply personalized medicine in diseases such as T2D [34].
Other SNPs in candidate genes such as SLC2A2/GLUT2 (solute carrier family 2/Glucose transporter 2) have been associated with reduction in HbA1c or treatment success, together with rs11212617 in
Sulfonylureas are a class of oral antidiabetic agents widely used for the management of T2D [108]. They are chosen in the first line of treatment if the patient does not present with obesity or with insulin resistance or if there is intolerance or contraindication to metformin. Also, they are used in the second line in combination with other oral hypoglycemic agents, such as metformin [109]. According to the 2003–2016 National Health and Nutrition Examination Survey (NHANES), sulfonylurea monotherapy decreased from 33–8%, nonetheless, the combination with insulin or metformin was used in 50% of patients in the mentioned period [110]. Patients with a short duration of diabetes with residual beta cell function (high C-peptide levels) are likely to be most responsive to sulfonylurea therapy [111]. The mechanism of action of sulfonylureas consists of promoting insulin secretion via binding to sulfonylurea receptor 1 (SUR1), an element of the ATP-sensitive K+ (KATP) channel. The link between sulfonylurea and SUR1 inhibits the K-ATP channel, depolarizing the β cells, increasing intracellular Ca2+, and consequently insulin granule exocytosis [112]. The rise of insulin levels regulates postprandial glycemia, stimulating peripheral glucose utilization [113]. Despite, sulfonylureas have a relatively short half-lifes (3 to 5 hours); they can cause hypoglycemia, which affects the quality of life and adherence to therapy in patients with T2D [114]. Two studies have reported hypoglycemia had occurred in 16–39% of patients treated with sulfonylureas [115, 116]. As a consequence, it has been estimated that 10–20% of individuals treated with sulfonylureas do not attain adequate glycemic control and 5–10% initially responding to sulfonylurea subsequently lose the ability to maintain normal glycemic level [117].
The most commonly used sulfonylureas, including the second-generation: glyburide, glipizide, and glimepiride are mainly metabolized through the cytochrome P450 (CYP) 2C9 enzyme. CYP2C9 belongs to the cytochrome P450 gene family and is the enzyme most abundantly expressed in liver. Indeed, CYP2C9 accounts for approximately 20% of total hepatic P450 protein, based on mass spectrometry quantitation [118]. It contributes to the metabolism of approximately 15% of all drugs that are subject to P450-catalyzed biotransformation, and it is responsible for >25% of metabolic clearance of oral hypoglycemic agents, such as chlorpropamide, glibenclamide, gliclazide, glimepiride, nateglinide and tolbutamide [119, 120]. Although CYP2C9 is highly polymorphic, however, only two polymorphisms have shown impact in enzyme expression and function, both allelic variants CYP2C9*2 (Arg144Cys, rs1799853) and CYP2C9*3 (Ile359Leu, rs1057910), encode proteins with less enzymatic activity for the metabolism of several substrates compared with the wild-type allele CYP2C9*1 (Arg144/Ile359). CYP2C9*2 and CYP2C9*3 are generally associated with more than 80% reduction in CYP2C9-mediated intrinsic clearance, while the effect of CYP2C9*2 is generally slightly smaller and varies considerably, depending on the substrate [120]. In both cases patients present more drug event reactions. Some studies have shown that CYP2C9 loss-of function alleles CYP2C9*2/*3 are associated with higher sulfonylurea levels and greater response to sulfonylureas. In the Go-DARTS study, patients with two copies of a loss-of-function allele were 3.4 times more probable to reach good glycemic control compared with patients with two wild-type CYP2C9 alleles, corresponding with a 0.5% greater reduction in HbA1c [44, 45]. In several pharmacokinetic studies the two variants rs1799853 and rs1057910 in CYP2C9 have been associated with hypoglycemic events, suggesting identification of these variants as a tool to predict adverse effects of these drugs in the patients with T2D [121].
Polymorphisms in KCNJ11, ABCC8, NOS1AP, TCF7L2, CYP2C8, KCNQ1, and IRS1 genes have been associated with altered therapeutic response to sulfonylureas, which will be described below [122]. ABCC8 and KCNJ11 encode K-ATP channel proteins SUR1 and Kir6.2, respectively, both form the K-ATP channel, which controls glucose-dependent insulin secretion in pancreatic β-cells [123, 124]. It has been reported that 50% of cases of neonatal diabetes are caused by mutations in KNJ11 or ABCC8 (SUR1) [125]. Therefore, genetic variants in ABCC8 and KCNJ11 genes could influence K-ATP channel function of beta cells, leading to changes in depolarization of the cell membrane and impact insulin secretion. Most studied SNPs in the ABCC8 gene include rs757110 (Ser1369Ala), rs1799854 (intronic variant) and rs1799859 (Arg1273Arg). Feng et al. demonstrated the association of the Ser1369Ala variant in the ABCC8 gene with fasting plasma glucose test (FPG) and two-hour plasma glucose after oral glucose tolerance test decreases after 8 weeks of gliclazide therapy. Additionally, the authors found a nominal association of the variant with levels of HbA1c, suggesting a role of this SNP on antidiabetic efficacy of gliclazides [46]. Several authors have attempted to associate this variant with insulin secretion; however, the findings have been contradictory. A study in the Diabetes Prevention Program population that includes Caucasian, African Americans, Hispanic Americans, American Indians and Asian Americans, found an association with a significantly lower insulin index, nevertheless, other studies failed to replicate this association [126, 127, 128]. Despite these data, it is interesting to mention that variant Ser1369Ala has been related with progression to diabetes [126]. Nikolac et al., found that rs1799854 and rs1799859 in the ABCC8 gene were associated with sulfonylurea efficacy in Caucasians, evidenced by significantly lower HbA1c concentrations in carriers compared with noncarriers [48].
As mentioned above, the KCNJ11 gene encodes the Kir6.2 subunit; four pore forming subunits assemble with four regulatory subunits of SUR1 to form the K-ATP channel of the β-cell [129]. Two SNPs have been associated with sulfonylureas response, rs5219 and rs5210. The rs5219 (Lys23Glu, p.E23K) A allele plays an important role in insulin secretion through reduction of ATP sensitivity of the K-ATP channel and suppression of insulin secretion. Previous studies, have demonstrated that carriers of a common variant, E23K, with normal glucose tolerance showed up to 40% reduction in glucose-stimulated insulin secretion [130, 131]. However, the mechanism of action of this locus in the insulin secretion pathway is still not completely understood. Although early observations have reported that E23K carriers exhibit higher predisposition to secondary failure when treated with sulfonylureas, other investigations have associated this variant with a better response to sulfonylureas [50, 51, 132, 133]. Additionally, some studies have suggested that the presence of the E23K variant is related to the severity of hypoglycemia in patients with sulfonylureas therapy or with lower response [52, 133]. Regarding rs5210, it has been reported that the G allele acts as a potential target for miR-1910, which is implicated in T2D; however, the mechanism of action of this miRNA in the development of T2D is unknown [134]. Moreover, variant rs5210, has been associated with gliclazide response, revealed by decreased levels of FPG test in carriers of this SNP [46].
The KCNQ1 gene belongs to a large family of voltage-gated K+ channels [135]. Although KCNQ1 is mainly expressed in the tissues or cells in the heart, it is also expressed in other tissues or organs such as pancreas islets [136]. Blockading the channels with KCNQ1 inhibitors, might stimulate secretion of insulin in pancreas, suggesting the association of KCNQ1 with the regulation of insulin secretion, specifically with reduced insulin secretion [137]. The intronic SNPs rs2237892 and rs2237895 were shown to increase gliclazide efficacy, whereas the intronic variant rs163184, was reported to lower-sulfonylureas effects on FPG levels [53, 54].
The transcription-factor-7-like-2 (TCF7L2) gene encodes the transcription factor 7 like-2 [138]. TCF7L2 can act through GLP-1 protein (Glucagon Like Peptide 1), which plays a central role in glucose homeostasis and is involved in the regulation of insulin secretion [139]. Several studies have suggested that TCF7L2 stimulates the proliferation of β-cells in the pancreas and facilitate the production of GLP-1 in intestinal cells. In this context, it is postulated that the SNP rs7903146 could decrease the expression levels of TCF7L2 in the pancreas and lead to lower secretion of insulin due to the decreased levels of GLP1. However, the association between TCF7L2 and T2D is more complex and is not limited to the decrease in GLP1, but also to alterations in other processes regulated by TCF7L2 such as the differentiation of pancreatic beta cells, in the normal metabolism of cholesterol and in the production of other incretins [140]. Pearson et al. determined the association of two genetic variants rs1225372 and rs7903146 in TCF7L2 with the treatment success of sulfonylurea therapy in T2D patients. It was shown that 12% of the diabetic population are homozygous carriers of SNP rs1225372 and were twice as unlikely to achieve good glycemic control within 1 year of treatment initiation compared to 42% of the population with wild type [56]. These findings were replicated in Indian and European populations among others [57, 141]. Therefore, carriers of these variants are at high risk of therapy failure with sulfonylureas.
The rest of SNPs that were associated with decreased response to sulfonylurea treatment and are found in the following genes: nitric oxide synthase 1 adaptor protein
Regarding rs1801278 in the ISR-1 gene, this variant has been associated with increased risk for secondary failure in African an European populations [59, 60]. In case of rs9282541, T2D patients carriers of variant needed a higher dose of glyburide in order to achieve the same glucose lowering effect that persons with the wild type variant [61].
Thiazolidinediones (TZDs) are pharmacologic agents that specifically treat insulin resistance. TZDs are effective at lowering HbA1c by ∼1–1.25% on average [146]. Despite durability in action, TZDs show weight gain which has limited their clinical utility [147, 148]. For every 1% reduction in HbA1c, an estimated 2–3% weight gain is reported [149]. TZDs are transported into the liver by OATP1B1 (encoded by
TZDs decrease insulin resistance directly through activation of peroxisome proliferator-activated receptors-γ (PPARγ) receptors, which facilitate differentiation of mesenchymal stem cells into adipocytes, promote lipogenesis in peripheral adipocytes, decrease hepatic and peripheral triglycerides, decrease activity of visceral adipocytes, and increase adiponectin. These primary effects of TZDs markedly ameliorate insulin resistance and decrease insulin requirements [153, 154]. Individuals differ in drug response, and ∼ 20–30% of diabetic patients fail to respond to thiazolidinediones [155]. To date, numerous case–control studies have been conducted to identify the possible relationship between PPARG gene polymorphisms with the risk of T2D in various ethnic populations [156]. The most common variant is located at exon-2 of PPARG, rs1801282, and consists of a non-synonym change Pro12Ala. This substitution leads to a change in the structure of PPARγ protein, which in turn decreases the binding effect of target genes, and reducing transcriptional activity [157]. PPARγ is also the target of antidiabetic TZD drugs, which have a unique and powerful insulin-sensitizing effect [158].
Dipeptidyl peptidase-4 inhibitors (DPP-4 inhibitors) are enzyme inhibitors that inhibit the enzyme dipeptidyl peptidase-4 (DPP-4). Inhibition of the DPP-4 enzyme prolongs and enhances the activity of incretins which play an important role in insulin secretion and blood glucose regulation [159]. DPP-4 is a 766 amino acid transmembrane glycoprotein, which is also known as adenosine deaminase or CD26, is a ubiquitously expressed glycoprotein of 110 kDa, which was first characterized by Hopsu-Havu and Glenner [160].
The DPP4 gene encodes a serine aminopeptidase enzyme, which inactivates GLP-1, GIP and other proteins via dipeptide cleavage of the N-terminal amino acid. Other DPP-4 substrates include peptides containing proline or alanine, such as growth factors, chemokines, neuropeptides, and vasoactive peptides [161].
Inhibitors of DPP-4 reversibly inhibit the hydrolysis of endogenous incretins, which increases plasma levels of GIP and GLP- 1, producing an increase in insulin response and a decrease in glucagon secretion. Therefore, the increase in the concentration of GLP-1 in plasma is the pharmacological effect of DPP-4 inhibitors, which increases insulin synthesis in β cells of the pancreas, stimulates the growth of these cells and prevents apoptosis [162]. Hence, DPP4 inhibition leads to greater exposure to incretins and therefore prolongs the half-life of insulin action. Because of this, DPP4 became a major target for the treatment of T2D [163].
However, it has recently been reported that some patients taking DPP-4 inhibitors are at increased risk of heart failure. It has been suggested that DPP-4 polymorphisms could potentially lead to a change in gene expression in renal cells in patients with T2D; these changes would be related to the renin-angiotensin-aldosterone system causing cardio-renal damage or myocardial hypertrophy, however further studies are needed to clarified the impact of these polymorphisms in DPP-4 inhibitors response [164].
Sodium-glucose cotransporter inhibitors are adjunctive medications in the treatment of T2D. These drugs decrease HbA1c concentrations in diabetic patients, with few adverse effects seen to date. In a healthy adult, the kidneys filter approximately 180 g of glucose per day, this is almost entirely reabsorbed into the circulation and less than 1% of glucose is excreted in the urine filtered. This reabsorption is possible thanks to the action of a family of transmembrane proteins called sodium-glucose cotransporters (SGLT, sodium glucose co-transporter) [165]. So far, seven types of sodium-glucose transporters have been identified. Particularly, type 2 (SGLT2) is responsible for glucose renal reabsorption; and is mainly found in the epithelial cells of the proximal convoluted tubule.
Glycosuria, which was initially observed as an etiopathogenic component of some renal and urinary complications in patients with T2D, has been proposed as a means to lower glucose concentrations through the pharmacological use of SGLT2 inhibitors [166]. Some SGLT-2 inhibitors can be glucuronidated by UGT enzymes (UDP-glucuronosyltransferase), thereby polymorphisms like UGT1A9*3 allele (rs72551330), in the genes encoding these drug-metabolizing enzymes could potentially influence its response. Despite, higher values of area under the curve (AUC) of canaglifozina in carriers if UGT1A9*3, the studies have not found clinical implications [90, 91]. Recently Zimdahl et al. found that common genetic variants in the SLC5A2 gene do not affect diabetes-related metabolic traits and they do not have a clinically relevant impact on response to treatment with the SGLT2 inhibitor empagliflozin [167]. Nonetheless, a study in a Caucasian population showed that rs9934336 carriers presented increased 30-min glucose concentrations after oral glucose tolerance test [92]. Studies on these drugs are few, because SGLT2 inhibitors are relatively recent. Thus, the efficacy and safety evaluation of these drugs in various clinical settings has not yet been fully established.
Despite, the major contribution in drug response can be attributed to genetic components, common genetic polymorphisms explain only less than half of this genetically encoded variability, thus it is important to address other factors of drug response, such as pharmacoepigenomics [168].
Pharmacoepigenomics combines the analysis of genetic variations and epigenetic modifications in an effort to advance personalized medicine [169]. Epigenetic modification refers to processes that modify DNA or chromatin structure in a manner that alters the level of expression of genes but not the DNA sequence itself. Chemical processes that fall into the realm of epigenetics include DNA methylation and post-translational modifications of histones such as the addition of methyl, phosphate, and acetyl groups. These modifications influence the overall chromatin structure and the availability of gene regulatory regions to transcription machinery [170].
On the other hand, regulatory processes involve molecules such as miRNas. Although miRNAs do not directly interact with DNA, they inhibit mRNA translation, therefore it is considered as having epigenetic effects [158].
Specific genes can be expressed or silenced depending on specific stimulators, such as hormone levels, dietary components or drug exposure, and can also accommodate gene-expression changes in response to gene–environment interactions [171]. Although, the cellular machinery responsible for the secretion of miRNA is not fully understood yet, it is recognized that miRNAs are packaged into microvesicles, exosomes, lipid drops and apoptotic bodies by a broad range of cell types and can be found in various types of body fluids, such as serum, plasma, and urine [172]. The miRNAs participate as negative regulators in post-transcriptional processes inhibiting mRNA translation or degrading the mRNA via the seed sequence region at the 5′ end of the miRNA, which allows the binding to its 3-´untranslated region (3 -UTR) of mRNA. miRNAs are estimated to affect approximately 30% of the process of protein coding genes [173]. A single miRNA is responsible for the expression of hundreds of proteins, and a protein-coding gene can be modulated by more than one miRNA, this is therefore a highly complex mechanism, but its results largely contribute to inter-individual variability in response to drugs. Although the study of miRNAs has focused on their involvement in the genesis of some complex diseases [174, 175] there is some evidence about their participation in the response to treatment in T2D. Interestingly the treatment with dapagliflozin (an inhibitor of sodium-glucose co-transporter 2, SGLT2), but not with hydrochlorothiazide (useful in treating high blood pressure), significantly up-regulated miR30e-5p and downregulated miR199a-3p (P < 0.05). These miRNAs are involved in the pathophysiology of heart failure and suggest a cardioprotective effect of SGLT2 inhibitor response [165].
Metformin can also interfere with the levels of miRNAs in the blood, which results in a change in the expression of the genes that are controlled by these. Ortega et al. have shown that increasing the dose of metformin modifies the levels of circulating miRNAs (started at a 425 mg/day and increased progressively during the first week to reach 1,700 mg/day), increased miR-192 (49.5%; P = 0.022) and decreased miR-140-5p (−15.8%; P = 0.004), and miR-222 (−47.2%; P = 0.03), in parallel to decreased fasting glucose and HbA1c. Revealing the response of circulating miRNAs to metformin therapy [95].
The information generated on miRNAs and their molecular actions place these molecules as innovative applications in the industry. Among the most promising prospects is the use of miRNA in medical therapy. Future studies of miRNAs that allow the generation of knowledge about their probable role in the modulation of pharmacogene expression will undoubtedly contribute to personalizing the treatment of T2D. miRNA-based therapies offer advantages over other nucleic acid therapies, because miRNAs are efficient silencers and, in contrast to plasmid DNA or synthetic oligonucleotides, miRNAs are naturally found in the bloodstream. As they target multiple mRNAs, the resulting synergistic effects could be positive for therapy, however, there are still multiple aspects that must be addressed before application to clinical trials in various human pathologies, among them, to identify the best miRNA candidates of miRNA targets for each disease type, the design of more efficient vehicles for the targeted delivery of oligonucleotides to specific organs, as well as avoiding potential toxicities and off-target effects. Low toxicity and good tolerance in patients treated with antagomiR a 15-nucleotide locked nucleic acid–modified antisense oligonucleotide whose action is sequestering mature miR-122 in a highly stable heteroduplex, thereby inhibiting its function avoiding the stability and propagation of hepatitis C virus (HCV), supporting the beneficial role of miRNAs in therapy [176]. miRNAs are naturally endogenous regulators of cell processes that are often dysregulated in diabetes restoration of any given miRNA function to normal levels will be the ultimate therapeutic goal. Several miRNAs appear to affect the function of the differentiated state of the pancreatic β-cell, while miRNAs in skeletal muscle, the liver, and adipose tissue constitute sets of different miRNAs, which is why the choice of the best molecules to treat this disease becomes very complex. Several challenges will need to be overcome in the field of pharmacotherapy with miRNA in the control of diabetes, but they will undoubtedly contribute to personalizing the treatment of this disease.
It has been suggested that epigenomics may act synergistically with pharmacogenomics towards optimization of drug therapy [177]. In addition, epigenomic somatic alterations represent an emerging class of biomarkers that hold promise for personalized therapy particularly to overcome drug resistance [178].
Regarding methylation, García-Calzón et al. evaluated the potential blood epigenetic markers associated with metformin glycemic and intolerance response. They analyzed DNA methylation in blood from newly diagnosed patients with T2D after 1.5 years of metformin treatment. According to the authors, the methylation risk scores explain 68–73% of the variation in glycemic response to metformin. In addition, the methylation risk scores explain 50–51% of the variation in metformin tolerance. In the same study, the researchers also assessed whether any of 26 SNPs previously associated with metformin response were associated with DNA methylation of any of the identified epigenetic markers. They identified one significant association between a SNP in SCL22A1 (rs628031) and DNA methylation of cg05151280 (P = 0.001, q = 0.028). The A/A genotype carriers had lower methylation (83.6 ± 2.3%) compared to carriers of the G/G (85.3 ± 1.9%, P = 0.002) and G/A (85 ± 1.8%, P = 0.006) genotypes in 132 participants from the discovery and replication cohorts. Lower methylation of this CpG site was associated with a better glycemic response to metformin (Table 2) [93]. In previous work from the same group, they assessed the DNA methylation in OCT1 encoded by
Methylation in KCNJ11 and ABCC8 gene promoters in T2D patients receiving sulfonylurea therapy have been assessed by Karaglani et al., their results show that epigenetic changes such as methylation influence interindividual variability in treatment with sulfonylureas. They considered hypoglycemia as an outcome of the treatment. KCNJ11 methylation was detected in 21.6% of hypoglycemic individuals and in 27.7% of non-hypoglycemic patients (P = 0.353) in this study, while ABCC8 methylation in 7.2% of non-hypoglycemic and none of the hypoglycemic patients (P = 0.012). These findings suggest that ABCC8 methylation is associated with hypoglycemic events in sulfonylurea-treated T2D patients [97].
The interindividual variability in the response to a drug is the consequence of various factors, including pharmacokinetic causes: absorption, distribution, metabolization and excretion of the drug that affects the intensity and duration of the response, or to pharmacodynamic causes in drug-receptor interaction. Each of these PK and PD factors is different in each individual due to genetic, environmental or pathological determinants, and also depends on the severity or intensity of the disease to be treated.
One of the main obstacles to transferring findings from pharmacogenetics to the clinic is the impact of ethnicity on genetic variation. The highly significant associations between SNPs and the response modulated by pharmacogenetics can differ considerably between populations, which has a direct impact on drug use and dosage decisions. It is necessary then that the studies to evaluate pharmacological efficacy and pharmacogenetics, have uniformity in research designs, dosage regimens, study populations, and analytical methods.
The epidemic of T2D has forced the use of drugs that aim at glycemic control and avoid secondary complications that cause very high medical costs and decrease the quality of life of patients. However, it has been observed that even though many patients carefully follow medical guidelines, the glycemic control so desired is not achieved. Thus, with the advent of pharmacogenomics, various studies are carried out to achieve personalized medicine in this field having an impact on a better quality of life and also reducing the costs of treatment of this disease by the Health services.
In this review, the main drugs used for the treatment of T2D were analyzed and the implications that the various SNPs have on their target genes, which will affect their pharmacological response. All this opens the way for us to apply these genomic findings in daily clinical practice, in search of personalized medicine that impacts adequate glycemic control in patients with T2D in search of a better quality of life.
Large scale hazard indication maps of avalanche protection provide an overview of areas potentially endangered by snow avalanches [1]. Such hazard maps serve in Switzerland also as a basis to define the extent of avalanche protection forests [2]. The first available hazard indication maps of avalanche protection at the beginning of the 21st century [2, 3] were based on a relatively coarse 25-m digital elevation model and simple forest vs. non-forest scenarios. In the meantime, we have increasingly advanced remote sensing data such as airborne LiDAR data and, in particular, highly resolved digital elevation models [4, 5], and additional and refined knowledge on avalanche-forest interactions [6, 7]. In this contribution we outline how we can take advantage of newly available process knowledge, refined spatial data and numerical modeling to improve avalanche protection forest maps, related applications and visualizations.
The main effects of avalanche protection forests are that avalanches do generally not release in sufficiently dense forest and that smaller avalanches can be slowed down or stopped by forest [6, 7, 8]. These effects are not only influenced by the forest structure but also by topographical factors and the properties and thickness of the snow cover. Critical thresholds for the spontaneous release of avalanches can be different inside the forest compared to the open field. For example, avalanches in forests mainly occur on slopes with an inclination of at least 35° [9], whereas in open areas, they may also occur in less steep terrain below 30° [10]. The surface roughness of the terrain is a crucial factor, at least as long as the snow cover thickness in the forest does not exceed the effective height of the dominant objects such as trees, root plates, logs or deposited rocks [11].
There are essentially four physical processes that contribute to the stabilization of the snow cover in forests: (1) Interception of falling snow: Snow is partly intercepted on branches and sublimated back into the atmosphere [12]. Intercepted snow, which is not sublimated, enters the snowpack in the form of snow lumps or meltwater [13]. (2) More balanced radiation regime: The duration of solar radiation and the long-wave radiation during the night are reduced in forests compared to open field [14, 15]. (3) Reduced wind speeds: Within the forest, near-surface wind speeds are lower than in the open [16]. (4) Direct mechanical support: Standing trees, but also lying dead wood, stumps, and root plates help to stabilize the snow cover with their reinforcing effect and increase the roughness of the terrain [6, 17].
As a result of these four processes, crown coverage, gap sizes and slope angle are considered the most essential characteristics for avalanche prevention in forests (see also chapter [18] of this book). Critical thresholds can be estimated from the retro analysis of events in relation to the topographical factors and snow properties [19, 20]. Based on such studies, critical lengths of forest gaps in the fall line are usually given in the range between 25 and 60 m, depending on slope inclination [18, 21]. Some authors also propose to use the height of the trees for defining the length and width of these gaps [22]. The size of gaps is also decisive in determining whether a small-medium scale avalanche (< 10′000 m3) that starts in the forest can potentially develop into a large avalanche (≥10′000 m3). The minimum gap width required to form avalanches is generally smaller in deciduous forests (approx. 5–10 m) than in evergreen forests (approx. 15–20 m), with considerable variation depending on steepness, terrain roughness and snow conditions. Smaller avalanches, which start in the forest or 100–200 m above the forest line, can come to a stop depending on the forest structure, topography and snow characteristics in the forest. The braking effect of the forest is a consequence of various interactions between avalanches and trees [6, 7] but is for large-scale hazard mapping usually simplified and modeled with a friction approach [8].
In order to create large-scale and applicable maps of forests with a protective effect and/or protective function (protection forest maps), it is necessary to deduce criteria from existing process knowledge and combine them with appropriate remote sensing and other available GIS-Data. For a hazard indication mapping project in the Canton of Grisons (eastern Switzerland) we consequently aimed at the following criteria for the delineation of avalanche protection forest (Figure 1 and Table 1):
Based on existing data: We used data on 150 avalanches released in forested terrain of the Swiss Alps and deduced a logistic regression model to quantify the effect of topographical and forest structural variables ([19, 20], Table 1).
Comprehensive and automatized: We aimed for a completely automatized and comprehensible delineation of the protection forest for the whole area of the Canton Grisons. Thus, it is necessary that all variables and criteria used to delineate the forest with an avalanche protective function and effect could be spatially deduced from newly available remote sensing data and/or additional GIS data, which are available for the whole Canton of Grisons and can potentially be repeated later with updated forest data.
Verified and optimized: The delineation of the avalanche protection forest had to be verified and further adapted by knowledge from scientists and local natural hazard and forest experts. In order to verify the effect of the forest structure on avalanche runout, an additional optimization loop had to be conducted after the simulation with the avalanche simulation software RAMMS [8, 23].
Schematic structure of the model for calculating the spatial extend of avalanche protection forest. The core of the disposition model is a logistic model based on avalanche releases in forested terrain [
Considered variables and threshold | Definition |
---|---|
Crown cover | The higher the crown cover, the lower the likelihood of an avalanche release. The crown cover is calculated based on a percentual proportion of pixels with a higher VHM value than the crown cover threshold. This procedure is done within a 5 m and 25 m environment, and the arithmetical mean is calculated. |
Gap width | Pixels that have a lower VHM value than the Gap-threshold (see definition below) are considered as a gap. If multiple gap pixels are adjacent to each other, a polygon is drawn, which represents the gap. The gap polygon is intersected with the contour lines to extract gap width. The length of the contour line represents the width of the gap. Gaps smaller than 500 m2 were neglected after verification of avalanche runout with RAMMS simulations To get homogeneous results, the mean over a 10 m environment is calculated. |
Slope angle | The angle of the slope was calculated based on a 10-m DTM. Values lower than 28° and higher 48° are considered as constant. In the range within 28 and 48° an increase of inclination is expected to lead to a higher potential for an avalanche release. |
Forest cover-threshold | In order to take into account the coverage at different spatial scales and to optimize the detection of trees, especially in a critical range between 3 and 5 m, the following VHM limits have been set.
|
Gap-threshold | The local snow depth for a 100-years event was calculated according to [28] and corrected by a factor of 0.85 for frequent and 1.14 for rare events. The calculated snow heights multiplied by the factor 1.5 according to Protect-Bio [29] result in the respective tree height limit. To compensate for underestimations of tree heights within the VHM, a constant height was subtracted from the VHM raster value. |
Surface roughness | The surface roughness influences on the likelihood of an avalanche release, especially when the snow height is low. The roughness was calculated with the “Vector Ruggedness Measure” (VRM) according to [27] based on a 2-m DTM (SwissAlti3D) and a moving window of 5 × 5 m. Based on empirical comparisons, areas with a value > 0.02 are considered as rough. For rough areas that do not show lateral convex curvature an increase of 10% of the avalanche disposition is accounted for. |
Shrub forest | Shrub forests tend to protect less against an avalanche release. Trees such as green alder |
Avalanche disposition | Statistically deduced disposition of each pixel to be part of an avalanche release area, given as a value from 0 to 1 according to a logistic model with following formula: Logit(release 1/0) = −6.17 + 0.18 * slope angle [Degrees] – 0.03 * crown cover [%] – 0.05 * gap width [m]. |
Protection forest index | Index calculated from avalanche disposition and additional parameters (roughness, shrub forest) (may have values from −10 to 110) |
Protection forest-threshold | The threshold for the protection forest index, based on validation in well-documented areas. Threshold values for fulfilled protective effect were:
|
Variables, threshold values and definitions for delineating avalanche protection forest for a frequent (ca. 10–30 years event) and extreme (ca. 100–300 years event).
A central component within this framework is the logistic regression model calculated with the most important variables “slope inclination”, “percentage of crown cover” and “gap width”, adapted from [20]. Those variables were implemented within a GIS approach. The algorithm is described in detail in Table 1. Based on spatial input data sets (e.g., vegetation height model [VHM] and digital terrain model [DTM]) [24] and various GIS operations, we calculated an “avalanche disposition” between 0 (no disposition) and 100% (very high avalanche release probability). To minimize the calculation time, a forest mask was used to delimit the calculation domain of the model. This forest mask consists of a combination of forest areas defined by the Federal Office of Topography (Swisstopo) and the Swiss National Forest Inventory, NFI [4, 25]. We defined different threshold values for tree heights to assign forest gaps (“Gap-threshold”) and forest cover (“Forest cover-threshold”) for different avalanche scenarios (frequent scenario vs. extreme scenario according for regionally expected snow-heights according to [28]). Additionally, we accounted for two factors which could not be quantitatively deduced from the original logistic model, but which turned out to be of additional relevance and for which spatial data were available for the whole canton: (1) a scrub forest area layer [26] helped to assign an adequately higher avalanche disposition to areas covered by shrubs. (2) We delineated areas with a high surface roughness from a high resolution DTM, and which do not show lateral convex curvature. With this combined requirement, we could exclude vertical gullies with high terrain roughness, as they are known for frequent avalanche release. Based on (1) and (2), we assigned higher values to the protection forest index for areas with considerable terrain roughness and lower values for areas that are covered by shrub forests (Figure 1). The resulting “protection forest index” builds the basis for the protection forest maps. The exact threshold values defining a sufficient protection forest index for frequent (ca. 10–30 years return period), and extreme (ca. 100–300 years return period) scenarios could then be defined in an iterative process after validating avalanche simulations with former avalanche events and after discussing different scenarios (with and without forests) together with the responsible regional natural hazard experts [31].
The avalanche protection forest map for the Canton of Grisons (Figure 2) is thus the result of an iterative process starting with an empirical statistical model of avalanche releases in forested terrain and was subsequently improved in several working and validation loops. The iterative process allowed us, for example, to better account for the stopping behavior of small and very small avalanches in forested terrain and how these processes are simulated with the avalanche dynamics software RAMMS [8]. In the applied model, the turbulent friction ξ (Xi) is set to a very high value, simulating the braking effect of the forest. Other adaptations introduced after validation loops included a stronger representation of surface roughness, leading to an increase in the protection forest index of forests with high surface roughness and may shift the categorization for some forests with a relatively open forest structure but a high surface roughness. Additionally, we considered differences between actual tree heights and how these tree heights were assessed with the available vegetation height models [3, 30]. Besides validating the forest cover map after the simulation of avalanches and besides the feedback of regional experts, it was also essential to validate the delineation of the avalanche protection forest maps specifically in well-investigated areas with known tree heights and avalanche history.
Protection forest map for the Canton Grisons for a frequent avalanche scenario (corresponding to avalanche events with a 10–30-year return period, displayed in blue and red combined) and for an extreme snow cover scenario (corresponding to a ca. 100–300-year avalanche event, displayed in red).
While all these validation procedures improved the quality and applicability of our map, more progress is possible during the following years by applying the map in practice and by introducing additional spatial data sets on forest characteristics. Therefore, the map will be updated once (i) reliable tree species maps are available in order for better consideration of the protective capacity of different forest types (e.g., forests dominated by evergreen coniferous trees, deciduous conifers or broadleaved trees) or (ii) after an improved understanding of the effect and the assessment of different surface roughness categories.
Two-dimensional protection forest, hazard indication or risk maps are still the standard application in the administration and consulting offices. Nevertheless, modern cartographic visualization strategies go far beyond showing a static portray of reality at a given point in time. Especially new advances in web technologies and multimedia integration, known as “web mapping”, make it possible to create easily shareable, user-friendly and robust web applications via different (mobile) devices such as smartphones, tablets or personal computers.
As forests undergo permanent and often abrupt changes in time, protection forest maps should be updated when more data or better process knowledge is available and after relevant changes in the forest structure. Map updates are particularly important with expected changes due to climate change and important legacies of past land use and expected increases in the frequency and severity of natural disturbances [30]. The development from static, two-dimensional maps to dynamic, interactive maps in a 3-D environment with possibilities to regularly update the visualization of protective effects in response to different forest scenarios would not only be a logical response to the increasing availability of spatial data, cartographic capabilities and computing capacity, but also a response to increasing practical needs. Compared to existing maps, dynamic maps enable to track effects of changes to the forest cover due to natural disturbances and different management scenarios on the protective capacity and other forest functions.
Based on the avalanche protection forest layer presented in this contribution, the avalanche hazard indication map for the canton of Grisons [32] was compiled and mapped for the first time with an interactive visualization platform (maps.wsl.ch), which is currently being developed at the WSL Institute for Snow and Avalanche Research SLF in Davos, Switzerland. In a first step, the latest findings on protection forests, RAMMS simulations of various avalanche scenarios and topographical and asset data such as buildings or roads were combined into an interactive user experience.
For the implementation, basic criteria were defined for the cartographic representation and the functional scopes of the interactive maps. In addition to a traditional two-dimensional map view, the user is offered a three-dimensional, spatial form of representation. Within this 3-D representation, all functions of “traditional” web mapping and other functions beyond are available. This means that the map reacts directly to the user, attributes and geometric data are linked, and interactive legends and diagrams are available. This encompasses the well-known functions of zooming, panning, perspective, 3-D navigation and flights through digital elevation models and three-dimensional objects like buildings or snow avalanche release areas, selection, print or an extended search function. The latest functions include the individual selection of layers, the retrieval of information via pop-ups, the creation of own bookmarks for quick navigation, the measurement of distances and areas in three-dimensional space as well as the personal editing of certain layers and the integration of shapefiles. The integration of shapefiles allows the user to upload recorded field data, for instance, and thus to overlay this data with the map content for visual analysis or prints. The functionality and design of the application will be improved in the future depending on the needs of the users and the progress in avalanche modeling.
The development of interactive web maps can broadly be categorized into three parts: 1) data preparation and visualization, 2) user interface design, and 3) application development. Hence, the map itself is only one element in a more prominent programmatically framework of digital cartography. For the detailed analysis and necessary transformations of the geospatial data that will be part of the application (step 1), conventional GIS software is used. Most of the layers are also being visualized at this stage. In order to keep the application lightweight in storage, all map data is being uploaded to a cloud or, respectively, a hosting data server. The user interface design is carried out with HTML and CSS (step 2), while for most of the application development, including all the functional parts, the programming language JavaScript is the main component. Finally, the application has to be run through a web server (maps.wsl.ch) responsible for distributing all necessary files to the client’s web browser (step 3).
In addition to the existing range of functions, the interactive maps are made to be increasingly dynamic. This is an updating of the map contents, which the user can also do. For example, a forester may digitize, edit and upload areas where forest disturbances such as windthrow, insect outbreaks or forest fires occurred or where a forest intervention is planned or implemented. However, providing modeling software as RAMMS via web service is neither possible nor planned so far.
Drone images or other collected data such as forest inventory data or climate data can provide additional information on selected sites (hotspots). Such dynamic, interactive maps will not only allow a user-friendly way to represent different forest scenarios or changes in forests, natural hazards or resulting risk but can also be used as a tool for (forest) planning or for consulting issues as well as for teaching and research (Figure 3).
Insight into the interactive map platform, which is currently being developed at WSL (
Automatically produced protection forest maps (showing protective effects and functions of forests) based on a sound scientific framework and reliable spatial data are an important basis for prioritizing management interventions and for deducing hazard indication maps or even legally binding hazard maps. In view of further optimizing such maps and their application in different regions, it is important to carefully validate the mapping procedure after the simulation of avalanches with regional experts. Furthermore, as the technology to assess spatial data, and the forest cover and its ability to reduce avalanche risks are changing with time, it is necessary to regularly update such maps and calculate them for different scenarios. Thus, we propose and currently develop web-based interactive maps as a new planning and visualization tool.
The protection forest map of Grisons has been supported by the Cantonal office for forest and natural hazards of the canton of Graubünden (Grisons). Additional funding has been provided by the WSL research program Climate Change Impacts on Alpine Mass Movements – CCAMM (ccamm.slf.ch) and by the prevention foundation of the Swiss cantonal building insurance (KGV). We thank in particular Roderick Kühne, Stephan Wohlwend, Andreas Stoffel and Stefan Margreth for support and feedback which helped to improve the maps. The map is still in evaluation. We also thank Frank Graf, Michaela Teich, Frank Perzl and Frédéric Berger for valuable comments on an earlier version of the manuscript.
The authors declare no conflict of interest.
As this section deals with legal issues pertaining to the rights of individual Authors and IntechOpen, for the avoidance of doubt, each category of publication is dealt with separately. Consequently, much of the information, for example definition of terms used, is repeated to ensure that there can be no misunderstanding of the policies that apply to each category.
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\\n\\nIntechOpen only publishes manuscripts for which it has publishing rights. This is governed by a publication agreement between the Author and IntechOpen. This agreement is accepted by the Author when the manuscript is submitted and deals with both the rights of the publisher and Author, as well as any obligations concerning a particular manuscript. However, in accepting this agreement, Authors continue to retain significant rights to use and share their publications.
\\n\\nHOW COPYRIGHT WORKS WITH OPEN ACCESS LICENSES?
\\n\\nAgreement samples are listed here for the convenience of prospective Authors:
\\n\\nDEFINITIONS
\\n\\nThe following definitions apply in this Copyright Policy:
\\n\\nAuthor - in order to be identified as an Author, three criteria must be met: (i) Substantial contribution to the conception or design of the Work, or the acquisition, analysis, or interpretation of data for the Work; (ii) Participation in drafting or revising the Work; (iii) Approval of the final version of the Work to be published.
\\n\\nWork - a Chapter, including Conference Papers, a Scientific Article and any and all text, graphics, images and/or other materials forming part of or accompanying the Chapter/Conference Paper.
\\n\\nMonograph/Compacts - a full manuscript usually written by a single Author, including any and all text, graphics, images and/or other materials.
\\n\\nCompilation - a collection of Works distributed in a Book that IntechOpen has selected, and for which the coordination of the preparation, arrangement and publication has been the responsibility of IntechOpen. Any Work included is accepted in its entirety in unmodified form and is published with one or more other contributions, each constituting a separate and independent Work, but which together are assembled into a collective whole.
\\n\\nScientific Journal – Periodical publication intended to further the progress of science.
\\n\\nJournal Article/Scientific Article – Publication based on empirical evidence. It can support a hypothesis with original research, describe existing research or comment on current trends in a specific field.
\\n\\nIntechOpen - Registered publisher with office at 5 Princes Gate Court, London, SW7 2QJ - UNITED KINGDOM
\\n\\nIntechOpen platform - IntechOpen website www.intechopen.com whose main purpose is to host Monographs in the format of Book Chapters, Long Form Monographs, Compacts, Conference Proceedings, Scientific Journals and Videos.
\\n\\nVideo Lecture – an audiovisual recording of a lecture or a speech given by a Lecturer, recorded, edited, owned and published by IntechOpen.
\\n\\nTERMS
\\n\\nAll Works published on the IntechOpen platform and in print are licensed under a Creative Commons Attribution 3.0 Unported and Creative Commons 4.0 International License, a license which allows for the broadest possible reuse of published material.
\\n\\nCopyright on the individual Works belongs to the specific Author, subject to an agreement with IntechOpen. The Creative Common license is granted to all others to:
\\n\\nAnd for any purpose, provided the following conditions are met:
\\n\\nAll Works are published under the CC BY 3.0 and CC BY 4.0 license. However, please note that book Chapters may fall under a different CC license, depending on their publication date as indicated in the table below:
\\n\\n\\n\\n
LICENSE | \\n\\t\\t\\tUSED FROM - | \\n\\t\\t\\tUP TO - | \\n\\t\\t
\\n\\t\\t\\t Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) \\n\\t\\t\\t | \\n\\t\\t\\t1 July 2005 (2005-07-01) | \\n\\t\\t\\t3 October 2011 (2011-10-03) | \\n\\t\\t
\\n\\t\\t\\t Creative Commons Attribution 3.0 Unported (CC BY 3.0) \\n\\t\\t\\t | \\n\\t\\t\\t5 October 2011 (2011-10-05) | \\n\\t\\t\\tCurrently | \\n\\t\\t
\\n\\t\\t\\t Creative Commons 4.0 International (CC BY 4.0) – for Journal Articles \\n\\t\\t\\t | \\n\\t\\t\\t15 March 2022 | \\n\\t\\t\\tCurrently | \\n\\t\\t
The CC BY 3.0 and CC BY 4.0 license permits Works to be freely shared in any medium or format, as well as the reuse and adaptation of the original contents of Works (e.g. figures and tables created by the Authors), as long as the source Work is cited and its Authors are acknowledged in the following manner:
\\n\\nContent reuse:
\\n\\n© {year} {authors' full names}. Originally published in {short citation} under {license version} license. Available from: {DOI}
\\n\\nContent adaptation & reuse:
\\n\\n© {year} {authors' full names}. Adapted from {short citation}; originally published under {license version} license. Available from: {DOI}
\\n\\nReposting & sharing:
\\n\\nOriginally published in {full citation}. Available from: {DOI}
\\n\\nRepublishing – More about Attribution Policy can be found here.
\\n\\nThe same principles apply to Works published under the CC BY-NC-SA 3.0 license, with the caveats that (1) the content may not be used for commercial purposes, and (2) derivative works building on this content must be distributed under the same license. The restrictions contained in these license terms may, however, be waived by the copyright holder(s). Users wishing to circumvent any of the license terms are required to obtain explicit permission to do so from the copyright holder(s).
\\n\\nDISCLAIMER: Neither the CC BY 3.0 license, CC BY 4.0, nor any other license IntechOpen currently uses or has used before, applies to figures and tables reproduced from other works, as they may be subject to different terms of reuse. In such cases, if the copyright holder is not noted in the source of a figure or table, it is the responsibility of the User to investigate and determine the exact copyright status of any information utilised. Users requiring assistance in that regard are welcome to send an inquiry to permissions@intechopen.com.
\\n\\nAll rights to Books and Journals and all other compilations published on the IntechOpen platform and in print are reserved by IntechOpen.
\\n\\nThe copyright to Books, Journals and other compilations is subject to separate copyright from those that exist in the included Works.
\\n\\nAll Long Form Monographs/Compacts are licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license granted to all others.
\\n\\nCopyright to the individual Works (Chapters) belongs to their specific Authors, subject to an agreement with IntechOpen and the Creative Common license granted to all others to:
\\n\\nUnder the following terms:
\\n\\nThere must be an Attribution, giving appropriate credit, provision of a link to the license, and indication if any changes were made.
\\n\\nNonCommercial - The use of the material for commercial purposes is prohibited. Commercial rights are reserved to IntechOpen or its licensees.
\\n\\nNo additional restrictions that apply legal terms or technological measures that restrict others from doing anything the license permits are allowed.
\\n\\nThe CC BY-NC 4.0 license permits Works to be freely shared in any medium or format, as well as reuse and adaptation of the original contents of Works (e.g. figures and tables created by the Authors), as long as it is not used for commercial purposes. The source Work must be cited and its Authors acknowledged in the following manner:
\\n\\nContent reuse:
\\n\\n© {year} {authors' full names}. Originally published in {short citation} under {license version} license. Available from: {DOI}
\\n\\nContent adaptation & reuse:
\\n\\n© {year} {authors' full names}. Adapted from {short citation}; originally published under {license version} license. Available from: {DOI}
\\n\\nReposting & sharing:
\\n\\nOriginally published in {full citation}. Available from: {DOI}
\\n\\nAll Book cover design elements, as well as Video image graphics are subject to copyright by IntechOpen.
\\n\\nEvery reproduction of a front cover image must be accompanied by an appropriate Copyright Notice displayed adjacent to the image. The exact Copyright Notice depends on who the Author of a particular cover image is. Users wishing to reproduce cover images should contact permissions@intechopen.com.
\\n\\nAll Video Lectures under IntechOpen's production are subject to copyright and are property of IntechOpen, unless defined otherwise, and are licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. This grants all others the right to:
\\n\\nShare — copy and redistribute the material in any medium or format
\\n\\nUnder the following terms:
\\n\\nUsers wishing to repost and share the Video Lectures are welcome to do so as long as they acknowledge the source in the following manner:
\\n\\n© {year} IntechOpen. Published under CC BY-NC-ND 4.0 license. Available from: {DOI}
\\n\\nUsers wishing to reuse, modify, or adapt the Video Lectures in a way not permitted by the license are welcome to contact us at permissions@intechopen.com to discuss waiving particular license terms.
\\n\\nAll software used on the IntechOpen platform, any used during the publishing process, and the copyright in the code constituting such software, is the property of IntechOpen or its software suppliers. As such, it may not be downloaded or copied without permission.
\\n\\nUnless otherwise indicated, all IntechOpen websites are the property of IntechOpen.
\\n\\nAll content included on IntechOpen Websites not forming part of contributed materials (such as text, images, logos, graphics, design elements, videos, sounds, pictures, trademarks, etc.), are subject to copyright and are property of, or licensed to, IntechOpen. Any other use, including the reproduction, modification, distribution, transmission, republication, display, or performance of the content on this site is strictly prohibited.
\\n\\nPolicy last updated: 2016-06-08
\\n"}]'},components:[{type:"htmlEditorComponent",content:'Copyright is the term used to describe the rights related to the publication and distribution of original Works. Most importantly from a publisher's perspective, copyright governs how Authors, publishers and the general public can use, publish, and distribute publications.
\n\nIntechOpen only publishes manuscripts for which it has publishing rights. This is governed by a publication agreement between the Author and IntechOpen. This agreement is accepted by the Author when the manuscript is submitted and deals with both the rights of the publisher and Author, as well as any obligations concerning a particular manuscript. However, in accepting this agreement, Authors continue to retain significant rights to use and share their publications.
\n\nHOW COPYRIGHT WORKS WITH OPEN ACCESS LICENSES?
\n\nAgreement samples are listed here for the convenience of prospective Authors:
\n\nDEFINITIONS
\n\nThe following definitions apply in this Copyright Policy:
\n\nAuthor - in order to be identified as an Author, three criteria must be met: (i) Substantial contribution to the conception or design of the Work, or the acquisition, analysis, or interpretation of data for the Work; (ii) Participation in drafting or revising the Work; (iii) Approval of the final version of the Work to be published.
\n\nWork - a Chapter, including Conference Papers, a Scientific Article and any and all text, graphics, images and/or other materials forming part of or accompanying the Chapter/Conference Paper.
\n\nMonograph/Compacts - a full manuscript usually written by a single Author, including any and all text, graphics, images and/or other materials.
\n\nCompilation - a collection of Works distributed in a Book that IntechOpen has selected, and for which the coordination of the preparation, arrangement and publication has been the responsibility of IntechOpen. Any Work included is accepted in its entirety in unmodified form and is published with one or more other contributions, each constituting a separate and independent Work, but which together are assembled into a collective whole.
\n\nScientific Journal – Periodical publication intended to further the progress of science.
\n\nJournal Article/Scientific Article – Publication based on empirical evidence. It can support a hypothesis with original research, describe existing research or comment on current trends in a specific field.
\n\nIntechOpen - Registered publisher with office at 5 Princes Gate Court, London, SW7 2QJ - UNITED KINGDOM
\n\nIntechOpen platform - IntechOpen website www.intechopen.com whose main purpose is to host Monographs in the format of Book Chapters, Long Form Monographs, Compacts, Conference Proceedings, Scientific Journals and Videos.
\n\nVideo Lecture – an audiovisual recording of a lecture or a speech given by a Lecturer, recorded, edited, owned and published by IntechOpen.
\n\nTERMS
\n\nAll Works published on the IntechOpen platform and in print are licensed under a Creative Commons Attribution 3.0 Unported and Creative Commons 4.0 International License, a license which allows for the broadest possible reuse of published material.
\n\nCopyright on the individual Works belongs to the specific Author, subject to an agreement with IntechOpen. The Creative Common license is granted to all others to:
\n\nAnd for any purpose, provided the following conditions are met:
\n\nAll Works are published under the CC BY 3.0 and CC BY 4.0 license. However, please note that book Chapters may fall under a different CC license, depending on their publication date as indicated in the table below:
\n\n\n\n
LICENSE | \n\t\t\tUSED FROM - | \n\t\t\tUP TO - | \n\t\t
\n\t\t\t Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0) \n\t\t\t | \n\t\t\t1 July 2005 (2005-07-01) | \n\t\t\t3 October 2011 (2011-10-03) | \n\t\t
\n\t\t\t Creative Commons Attribution 3.0 Unported (CC BY 3.0) \n\t\t\t | \n\t\t\t5 October 2011 (2011-10-05) | \n\t\t\tCurrently | \n\t\t
\n\t\t\t Creative Commons 4.0 International (CC BY 4.0) – for Journal Articles \n\t\t\t | \n\t\t\t15 March 2022 | \n\t\t\tCurrently | \n\t\t
The CC BY 3.0 and CC BY 4.0 license permits Works to be freely shared in any medium or format, as well as the reuse and adaptation of the original contents of Works (e.g. figures and tables created by the Authors), as long as the source Work is cited and its Authors are acknowledged in the following manner:
\n\nContent reuse:
\n\n© {year} {authors' full names}. Originally published in {short citation} under {license version} license. Available from: {DOI}
\n\nContent adaptation & reuse:
\n\n© {year} {authors' full names}. Adapted from {short citation}; originally published under {license version} license. Available from: {DOI}
\n\nReposting & sharing:
\n\nOriginally published in {full citation}. Available from: {DOI}
\n\nRepublishing – More about Attribution Policy can be found here.
\n\nThe same principles apply to Works published under the CC BY-NC-SA 3.0 license, with the caveats that (1) the content may not be used for commercial purposes, and (2) derivative works building on this content must be distributed under the same license. The restrictions contained in these license terms may, however, be waived by the copyright holder(s). Users wishing to circumvent any of the license terms are required to obtain explicit permission to do so from the copyright holder(s).
\n\nDISCLAIMER: Neither the CC BY 3.0 license, CC BY 4.0, nor any other license IntechOpen currently uses or has used before, applies to figures and tables reproduced from other works, as they may be subject to different terms of reuse. In such cases, if the copyright holder is not noted in the source of a figure or table, it is the responsibility of the User to investigate and determine the exact copyright status of any information utilised. Users requiring assistance in that regard are welcome to send an inquiry to permissions@intechopen.com.
\n\nAll rights to Books and Journals and all other compilations published on the IntechOpen platform and in print are reserved by IntechOpen.
\n\nThe copyright to Books, Journals and other compilations is subject to separate copyright from those that exist in the included Works.
\n\nAll Long Form Monographs/Compacts are licensed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license granted to all others.
\n\nCopyright to the individual Works (Chapters) belongs to their specific Authors, subject to an agreement with IntechOpen and the Creative Common license granted to all others to:
\n\nUnder the following terms:
\n\nThere must be an Attribution, giving appropriate credit, provision of a link to the license, and indication if any changes were made.
\n\nNonCommercial - The use of the material for commercial purposes is prohibited. Commercial rights are reserved to IntechOpen or its licensees.
\n\nNo additional restrictions that apply legal terms or technological measures that restrict others from doing anything the license permits are allowed.
\n\nThe CC BY-NC 4.0 license permits Works to be freely shared in any medium or format, as well as reuse and adaptation of the original contents of Works (e.g. figures and tables created by the Authors), as long as it is not used for commercial purposes. The source Work must be cited and its Authors acknowledged in the following manner:
\n\nContent reuse:
\n\n© {year} {authors' full names}. Originally published in {short citation} under {license version} license. Available from: {DOI}
\n\nContent adaptation & reuse:
\n\n© {year} {authors' full names}. Adapted from {short citation}; originally published under {license version} license. Available from: {DOI}
\n\nReposting & sharing:
\n\nOriginally published in {full citation}. Available from: {DOI}
\n\nAll Book cover design elements, as well as Video image graphics are subject to copyright by IntechOpen.
\n\nEvery reproduction of a front cover image must be accompanied by an appropriate Copyright Notice displayed adjacent to the image. The exact Copyright Notice depends on who the Author of a particular cover image is. Users wishing to reproduce cover images should contact permissions@intechopen.com.
\n\nAll Video Lectures under IntechOpen's production are subject to copyright and are property of IntechOpen, unless defined otherwise, and are licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license. This grants all others the right to:
\n\nShare — copy and redistribute the material in any medium or format
\n\nUnder the following terms:
\n\nUsers wishing to repost and share the Video Lectures are welcome to do so as long as they acknowledge the source in the following manner:
\n\n© {year} IntechOpen. Published under CC BY-NC-ND 4.0 license. Available from: {DOI}
\n\nUsers wishing to reuse, modify, or adapt the Video Lectures in a way not permitted by the license are welcome to contact us at permissions@intechopen.com to discuss waiving particular license terms.
\n\nAll software used on the IntechOpen platform, any used during the publishing process, and the copyright in the code constituting such software, is the property of IntechOpen or its software suppliers. As such, it may not be downloaded or copied without permission.
\n\nUnless otherwise indicated, all IntechOpen websites are the property of IntechOpen.
\n\nAll content included on IntechOpen Websites not forming part of contributed materials (such as text, images, logos, graphics, design elements, videos, sounds, pictures, trademarks, etc.), are subject to copyright and are property of, or licensed to, IntechOpen. Any other use, including the reproduction, modification, distribution, transmission, republication, display, or performance of the content on this site is strictly prohibited.
\n\nPolicy last updated: 2016-06-08
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This chapter presents a methodology for detecting common security flaws. The methodology is put in practice using an open-source RFID platform (Proxmark 3), and it is tested in different fields, such as public transportation or animal identification. The results obtained show that the consistent application of the methodology allows researchers to perform security audits easily and detect, mitigate, or avoid risks and possible attacks.",book:{id:"5368",slug:"radio-frequency-identification",title:"Radio Frequency Identification",fullTitle:"Radio Frequency Identification"},signatures:"Tiago M. Fernández-Caramés, Paula Fraga-Lamas, Manuel Suárez-\nAlbela and Luis Castedo",authors:[{id:"186818",title:"Dr.",name:"Tiago M.",middleName:null,surname:"Fernández-Caramés",slug:"tiago-m.-fernandez-carames",fullName:"Tiago M. 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However, despite the existing belief, there is no universal RFID system on the commercial market that could be used in all user applications. All components of a developed solution should be carefully selected or designed according to the specification of objects being recognized and characteristics of their environment. In order to determine parameters of propagation or inductively coupled system, especially when it is dedicated to uncommon applications, a multiaspect analysis has to be taken into consideration. Due to complexity, the problem is reduced to analytical or experimental determination of RFID system operation range and a “trial and error” method is mostly used in the industry practice. In order to cope with the barriers existing in the RFID technology, the authors give the review of latest achievements in this field. They focus on the definition, comprehensive characteristics and determination of the antenna parameters. They also pay attention to the 3D interrogation zone (IZ) that is the main parameter in which multitude technical aspects of the RFID systems are gathered simultaneously, as regards the theoretical synthesis as well as market needs.",book:{id:"5368",slug:"radio-frequency-identification",title:"Radio Frequency Identification",fullTitle:"Radio Frequency Identification"},signatures:"Piotr Jankowski-Mihułowicz and Mariusz Węglarski",authors:[{id:"5982",title:"Associate Prof.",name:"Piotr",middleName:null,surname:"Jankowski-Mihułowicz",slug:"piotr-jankowski-mihulowicz",fullName:"Piotr Jankowski-Mihułowicz"}]},{id:"66114",doi:"10.5772/intechopen.85075",title:"Combined Deep Learning and Traditional NLP Approaches for Fire Burst Detection Based on Twitter Posts",slug:"combined-deep-learning-and-traditional-nlp-approaches-for-fire-burst-detection-based-on-twitter-post",totalDownloads:826,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The current chapter introduces a procedure that aims at determining regions that are on fire, based on Twitter posts, as soon as possible. The proposed scheme utilizes a deep learning approach for analyzing the text of Twitter posts announcing fire bursts. Deep learning is becoming very popular within different text applications involving text generalization, text summarization, and extracting text information. A deep learning network is to be trained so as to distinguish valid Twitter fire-announcing posts from junk posts. Next, the posts labeled as valid by the network have undergone traditional NLP-based information extraction where the initial unstructured text is converted into a structured one, from which potential location and timestamp of the incident for further exploitation are derived. Analytic processing is then implemented in order to output aggregated reports which are used to finally detect potential geographical areas that are probably threatened by fire. So far, the part that has been implemented is the traditional NLP-based and has already derived promising results under real-world conditions’ testing. The deep learning enrichment is to be implemented and expected to build upon the performance of the existing architecture and further improve it.",book:{id:"8511",slug:"cyberspace",title:"Cyberspace",fullTitle:"Cyberspace"},signatures:"Konstantinos-George Thanos, Andrianna Polydouri, Antonios Danelakis, Dimitris Kyriazanos and Stelios C.A. Thomopoulos",authors:null},{id:"66610",doi:"10.5772/intechopen.85362",title:"Text Mining to Facilitate Domain Knowledge Discovery",slug:"text-mining-to-facilitate-domain-knowledge-discovery",totalDownloads:1079,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"The high-precision observation and measurement techniques have accelerated the rapid development of geoscience research in the past decades and have produced large amounts of research outputs. Many findings and discoveries were recorded in the geological literature, which is regarded as unstructured data. For these data, traditional research methods have limited functions for integrating and mining them to make knowledge discovery. Text mining based on natural language processing (NLP) provides the necessary method and technology to analyze unstructured geological literature. In this book chapter, we will review the latest researches of text mining in the domain of geoscience and present results from a few case studies. The research includes three major parts: (1) structuralization of geological literature, (2) information extraction and visualization for geological literature, and (3) geological text mining to assist database construction and knowledge discovery.",book:{id:"8511",slug:"cyberspace",title:"Cyberspace",fullTitle:"Cyberspace"},signatures:"Chengbin Wang and Xiaogang Ma",authors:null}],mostDownloadedChaptersLast30Days:[{id:"68505",title:"Research Design and Methodology",slug:"research-design-and-methodology",totalDownloads:24839,totalCrossrefCites:7,totalDimensionsCites:16,abstract:"There are a number of approaches used in this research method design. The purpose of this chapter is to design the methodology of the research approach through mixed types of research techniques. The research approach also supports the researcher on how to come across the research result findings. 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Then, the chapter will discuss three aspects of 5G which are, namely, (1) Regulations, (2) security, and (3) the 5 enabling Technologies. Then, the chapter will discuss the real-life case of South Korea mobile carrier.",book:{id:"8511",slug:"cyberspace",title:"Cyberspace",fullTitle:"Cyberspace"},signatures:"Evon Abu-Taieh, Issam H. Al Hadid and Ali Zolait",authors:null},{id:"68561",title:"Cyberspace and Artificial Intelligence: The New Face of Cyber-Enhanced Hybrid Threats",slug:"cyberspace-and-artificial-intelligence-the-new-face-of-cyber-enhanced-hybrid-threats",totalDownloads:1236,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"While, until recently, cyber operations have constituted a specific subset of defense and security concerns, the synergization of cyberspace and artificial intelligence (AI), which are driving the Fourth Industrial Revolution, has raised the threat level of cyber operations, making them a centerpiece of what are called hybrid threats. The concept of hybrid threat is presently a key concern for the defense and security community; cyber-enabled and cyber-enhanced hybrid operations have been amplified in scope, frequency, speed, and threat level due to the synergies that come from the use of cyberspace and machine learning (ML)-based solutions. In the present work, we address the relevance of cyberspace-based operations and artificial intelligence for the implementation of hybrid operations and reflect on what this cyber dimension of hybrid operations implies for the concept of what constitutes a cyberweapon, the concept of hybrid human intelligence (hybrid HUMINT) and possible responses to the hybrid threat patterns.",book:{id:"8511",slug:"cyberspace",title:"Cyberspace",fullTitle:"Cyberspace"},signatures:"Carlos Pedro Gonçalves",authors:[{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves"}]},{id:"52156",title:"Case Study: Installing RFID Systems in Supermarkets",slug:"case-study-installing-rfid-systems-in-supermarkets",totalDownloads:2471,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Radio frequency identification technology (RFID) is considered as the reference technology for wireless identification and item traceability. Supermarkets are one of those scenarios where the RFID potential can be harnessed. In theory, RFID in supermarkets shows several advantages compared with traditional barcode systems, offering real‐time inventory, stock control, cash queues, among others. In practice, its massive and global implementation is still being delayed due to the high quantity of factors that degrade the RFID system performance in these scenarios, causing uncontrolled items and identification losses and, at the end, economical losses. Some works in the scientific literature studied a single or a set of problems related to RFID performance, mostly focused on a specific communication layer: antennas and hardware design, interferences at physical layer, medium access control (MAC) protocols, security issues, or middleware challenges. However, there are no works describing in depth the set of factors affecting RFID performance in a specific scenario and contemplating the entire communication layer stack. The first challenge of this chapter is to provide a complete analysis of those physical and environmental factors, hardware and software limitations, and standard and regulation restrictions that have a direct impact on the RFID system performance in supermarkets. This analysis is addressed by communication layers, paying attention to the point of view of providers, supermarket companies, and final customers. Some of the most feasible and influential research works that address individual problems are also enumerated. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:229,paginationItems:[{id:"318170",title:"Dr.",name:"Aneesa",middleName:null,surname:"Moolla",slug:"aneesa-moolla",fullName:"Aneesa Moolla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/318170/images/system/318170.png",biography:"Dr. Aneesa Moolla has extensive experience in the diverse fields of health care having previously worked in dental private practice, at the Red Cross Flying Doctors association, and in healthcare corporate settings. 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:"39",type:"subseries",title:"Environmental Resilience and Management",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices",scope:"\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
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