*2.1. Study Region*

Forests make up the dominant land cover type within the study domain, which covers a region with a total land surface area of approximately 167,500 km2 (Figure 1, inset). As such, preserving a similar proportion of forest area between the model training and validation regions was the main criterion when partitioning the domain into the training and validation subsets. Most of the forests within the full domain may be considered part of the boreal forest belt that extends almost continuously around the upper northern hemisphere. Forests are dominated by Norway spruce (*Picea abies* H. Karst.), Scots pine (*Pinus sylvestris* L.) and two birch species (*Betula pendula* Roth and *B. pubescens* Ehrh.), with the understory vegetation typically dominated by ericoid dwarf shrubs (*Vaccinium* spp.) and various herb communities [30].

**Figure 1.** Study domain split into model training and validation regions. "CRO" = croplands; "PAS" = pasture; "O-v" = Open, vegetated; "O-pv" = Open, partly vegetated; "O-sp" = Open, sparsely vegetated; "PB-f" = Peat bog, forested; "PB-nf" = Peat bog, non-forested; "O-nv" = Open, non-vegetated; "U&T" = Urban & transport; "S&G" = Snow & glacier; "FW" = freshwater; and "FOR" = forest.

The eastern parts of the region experience continental climates that are characterized by long cold winters, short mild summers and moderate, seasonally distributed precipitation. Forests in the northwestern coastal regions are more influenced by an oceanic climate, which is characterized by greater amounts of precipitation, warmer temperatures during winter, and cooler temperatures during summer. Snow covers the ground from December through late March/early April in the lowland regions (< 400 m). At higher elevations (> 600 m), permanent snow cover may commence in November and can persist through early May (Norwegian Meteorological Institute, 2013b).

#### *2.2. Spectral Unmixing Regression Analysis*

Satellite retrievals of the surface albedo are often provided at a spatial resolution that is too coarse for direct attribution to individual forest stands and other fine-scale features of the landscape. For instance, the nominal spatial footprint of the MODIS albedo product employed in this study (described in Section 2.5) is 25 hectares (250,000 m2), whereas the footprint of the typical even-aged forest stand in Norway rarely exceeds 1–2 hectares (< 20,000 m2) [31]. Linear spectral unmixing techniques based on the ordinary least squares regression are increasingly employed to overcome this spatial mismatch challenge (e.g., refs. [32–34]). Unlike conventional spectral unmixing techniques based on linear mixture models [35] in which the endmember spectral signatures are known *a priori* and the goal is to determine endmember fractions within any given pixel, the known endmember fractions in the present study are obtained from the land cover dataset, which are used to estimate their unique spectral signatures (albedos).

Under the premise that the surface albedo (or rather the surface reflectance) signal registered by the satellite spectroradiometer represents a linear combination of the individual albedos (reflectances) of all endmembers (land covers/forest stands) within its footprint, the linear unmixing model may be described [32] as:

$$\mathfrak{a} + \varepsilon\_{\mathfrak{a}} = \sum\_{i=1}^{n} \left( ef\_i (\mathfrak{a}\_i + \varepsilon\_i) \right) \tag{1}$$

where *α* is the albedo of the grid cell (described in Section 2.5), *e fi* is the fractional coverage of endmember type *i* within the pixel size (Section 2.3), *αi* is the albedo of endmember *i*, *εα* is the residual error of the pixel, and *εi* is the standard error of the estimator (*αi*). In Equation (1), the endmember albedo *αi*is essentially the slope that minimizes the sum of squared *εα*.

Endmember albedos *αi* are highly sensitive to the presence of snow. Equation (1) is therefore modified following Bright *et al*. [34] where *α* is described as a weighted combination of the mixed endmember albedos under snow-free and snow-covered conditions, with the weights determined by snow cover:

$$\mathfrak{A} = \mathrm{SC} \sum\_{i=1}^{n} \, \_{i}ef\_{i}(\mathfrak{a}\_{\mathfrak{s}\mathfrak{c},i}) + [1 - \mathrm{SC}] \sum\_{i=1}^{n} \, \_{i}ef\_{i}(\mathfrak{a}\_{\mathfrak{s}f,i}) \tag{2}$$

where *α* is the albedo of the grid cell (described in Section 2.5), *SC* is the snow cover of the grid cell (described in Section 2.6), and *αsc*,*i* and *αs f* ,*i* are the albedos for endmember *i* under snow-covered and snow-free conditions, respectively. This model form is used in some climate models [36] and has been found to perform consistently well over large spatial domains at high latitudes [34,37]. Unlike in Bright et al. [34], however, the model employed here is further modified to capture additional variation in endmember-dependent albedos—*αsc*,*i* and *αs f* ,*i*—owed to important local differences in vegetation structure and other environmental factors as described below.

For the vegetated endmembers and in particular forests, both *αsc*,*i* and *αs f* ,*i* are influenced by the structure of the vegetation. In Fennoscandic boreal forests, *αsc*,*i* and *αs f* ,*i* at the stand level have been found to be negatively correlated with canopy cover [38], leaf area index [38,39], aboveground biomass [38,40], volume [41], height [41] and age [27,33]. Because forest canopies are rarely fully buried by snow, ground masking by forest canopies is particularly influential as a control of surface albedo during the snow season [16,18,42], although the snow intercepted and held by forest canopies can be important during the coldest and calmest winter months [43–45].

Following Kuusinen et al. [33], we modeled the forest endmember albedos as functions of stand structure. Although the models of Kuusinen et al. [33] were fit separately for different seasons, it was possible to obtain universal endmember models that were not specific to individual months or seasons by including snow cover as an environmental state predictor. The albedo of an endmember under snow-covered conditions (*αsc*,*i*) is largely determined by the albedo of snow, which depends on the effective snow grain area and snow water content [46–49]. These are two physical properties that exhibit strong relationships with air temperature [50,51]. Furthermore, given the importance of air temperature as a control over vegetation phenology [19,52,53] and canopy snow dynamics (i.e., snow slippage and melt) [39,44,45,54], we included air temperature as an additional environmental state predictor.

For the forest endmembers, a model function was chosen that gives identical predictions for a zero structure forest—or when the structural predictor (i.e., volume, biomass, age and so on) equals zero. In other words, the forest endmember models have common y-intercepts. For snow-covered conditions, the functional form of the forest endmember model is given as:

$$\mathfrak{a}\_{\mathfrak{sc},i}(\mathbf{x}\_i, T) = (\mathfrak{a}\_{0, \mathfrak{sc}} + \rho\_{0, \mathfrak{sc}}T) - (\beta\_{\mathfrak{sc},i} + \rho\_{\mathfrak{sc},i}T) \left[1 - e^{\lambda\_{\mathfrak{sc},i}\mathbf{x}\_i}\right] \tag{3}$$

where *T* is the air temperature (in ◦C) of the grid cell (Section 2.7), *α*0,*sc* is the y-intercept (albedo) for forests with zero structure and when air temperature equals zero, *ρ*0,*sc* is a temperature sensitivity parameter for forests with zero structure, *βi* is the difference between *α*0,*sc* and the minimum albedo (i.e., the asymptote) for forest endmember *i* when air temperature equals zero, *ρsc*,*i* is a temperature sensitivity parameter unique to the forest endmember *i*; *λsc*,*i* is a shape parameter unique to the forest endmember *i;* and *xi* is the grid cell mean stand structural attribute for the forest endmember *i* (Section 2.4). Here, separate fits are performed using either the mean stand volume (*x* = *Volume*; m3 ha−1) or mean stand aboveground biomass (*x* = *Biomass*; t ha−1) as structural predictors.

The same function represented as Equation (3) was applied to estimate the forest endmember albedos under snow-free conditions:

$$\mathbf{a}\_{sf,i}(\mathbf{x}\_{i\prime},T) = \left(\mathbf{a}\_{0,sf} + \rho\_{0,sf}T\right) - \left(\beta\_{sf,i} + \rho\_{sf,i}T\right)\left[1 - e^{\lambda\_{sf,i}\mathbf{x}\_i}\right] \tag{4}$$

where the subscript "*sf* " denotes snow-free conditions.

In Equations (3) and (4), the zero-structure y-intercept parameter *α*0 shared by all forest endmembers was based on the mean of the forest endmember-specific zero-structure y-intercept parameters obtained from an initial regression analysis (i.e., *α*0 = ∑*ni*=1 *α*0,*i*/*n*).

Air temperature modifiers were also included for the non-forested endmembers given its importance as a control over seasonal phenology (i.e., vegetation dynamics) and snow physical processes (i.e., snow albedo):

$$\begin{cases} \boldsymbol{a}\_{s\mathbf{c},i}(T) = \boldsymbol{a}\_{0,\mathbf{s}\mathbf{c},i} + \rho\_{s\mathbf{c},i}T\\ \boldsymbol{a}\_{sf,i}(T) = \boldsymbol{a}\_{0,sf,i} + \rho\_{sf,i}T \end{cases} \tag{5}$$

where the intercepts *α*0,*sc*,*i* and *α*0,*s f* ,*i* are the surface albedos for endmember *i* under snow-covered and snow-free conditions when air temperature equals zero, respectively, while *ρsc*,*i* and *ρs f* ,*i* are air temperature modifiers for endmember *i* (i.e., slopes of the albedo–air temperature relationship).

Separate models were fit for both intrinsic albedos (black-sky/directional hemispherical and white-sky/bidirectional hemispherical) at the local solar noon and for each broad spectral band: visible (VIS; 300–700 nm), near infrared (NIR; 700–5000 nm) and the entire shortwave broadband (SW; 300–5000 nm).

### *2.3. Land Cover Data*

Endmember (land cover) mapping employed in model fitting was based on the high resolution land resource database "AR5", which employs a standardized Norwegian land cover classification system [55]. Although AR5 is a national seamless database, detailed information about land resources is only available for areas below the treeline. As a result, a recent mapping campaign for areas above the treeline was recently undertaken, resulting in a complimentary database "AR-Fjell" [56]. Furthermore, an additional campaign to improve the mapping of agricultural resources was more recently carried out, resulting in the database "FJB-AR5" [57]. These products, which were all produced at a scale of 1:5000, were merged and re-projected to a MODIS sinusoidal grid with a resolution of 16 m × 16 m.

#### *2.4. Forest Cover and Structure Data*

The forest species composition and structure employed in model fitting were based on the forest resource map "SR16", which was developed using photogrammetric and LiDAR point cloud data with ground plots from the Norwegian National Forest Inventory (NFI) [58]. The forest cover in SR16 is based on updating the forest cover in AR5 with object-based image analysis methods [59]. Stand attributes, such as tree species, tree height (Lorey's), biomass, and volume are predicted with generalized linear models at a resolution of 16 m × 16 m with an accuracy (normalized RMSE) of 50% [58]. The forests in SR16 are classified as one of four classes: (1) newly clear-cut; (2) spruce; (3) pine; and (4) deciduous broadleaf. Pixels that were classified as newly clear-cut comprised ~1% of all forested pixels in the training dataset and were thus re-classified as spruce since spruce was the most abundant tree species of the model training region.

After fitting the models (Section 2.2), they were applied to reconstruct the monthly mean surface albedos in the validation region (Figure 1). Because the SR16 product used in the fitting did not yet extend to this region of Norway, an alternative product "SAT-SKOG" [60] was instead used in order to provide information about the forest cover and structure. The SAT-SKOG product is based on a *k*-nearest neighbor algorithm, which combines the spectral information from Landsat5&7 with information from permanent NFI plots [60,61]. The structural variables in the SAT-SKOG product are limited to stand volume and height; thus, only the forest models fit using the stand volume as the structural predictor (i.e., *xi*) were applied in the validation exercise. The forest area in AR5 and SAT-SKOG are identical so only the species information in SAT-SKOG was used to update the AR5 classification for forests. The SAT-SKOG forest classification differs from SR16 in that it includes a "mixed evergreen needleleaf" and a "mixed needleleaf-broadleaf" classification. For the former, we weighted the pine and spruce endmember predictions evenly while for the latter, we weighted predictions for all three species (spruce, pine, birch) evenly.


*Schizophrenia: Early Recognition and Prevention DOI: http://dx.doi.org/10.5772/intechopen.88537*

*Neurodevelopment and Neurodevelopmental Disorder*

several times a week within the last 3 months.

based on the APS and BLIPS criteria [51].

catatonic behaviour" [1].

education or work-related difficulties.

further progression of the illness [54].

**17. Early intervention and prevention**

ity is also an important treatment goal [1].

disorder and/or pre- or perinatal complications".

• The absence of attenuated or transient psychotic symptoms [1].

odd thinking or speech; suspiciousness or paranoid ideation".

The LIPS criterion attempts to identify those at more immediate risk and is

• The presence of at least one of the following attenuated positive symptoms (APS) present within the last 3 months, appearing several times per week for a period of at least 1 week, but no longer in the same severity than 1 year: "ideas of reference; odd beliefs or magical thinking; unusual perceptual experiences;

• "Brief limited intermittent psychotic symptoms (BLIPS), defined as appearance of one of the following frank psychotic symptoms for less than 1 week (interval between episodes at least 1 week) and resolving spontaneously: hallucinations; delusions; formal thought disorder; gross disorganized or

This two-stage prodromal state guides the treatment approach, that is, psychological or pharmacological therapy [51–53]. LIPS criteria denote an imminent risk of transition to psychotic disorder within the next 12 months, so an antipsychotic medication—second generation—appeared justified. Psychological interventions were crisis intervention, psychoeducation, family counseling, and assistance with

In EIPS group the psychological intervention (cognitive behavioral therapy (CBT) or the supportive control condition) appeared successful in preventing

Early intervention may be able to delay or even prevent onset of psychosis in the UHR or prodromal stage. Both antipsychotic medication (risperidone 1–2 mg/day, olanzapine 5–15 mg/day) and psychological interventions (cognitive behavioral therapy (CBT), case management, supportive therapy, problem-solving strategies) might have a role in treating the difficulties and problems that UHR young people experience, as well as in reducing the rate of transition to psychosis and in reducing symptomatology. Deterioration in psychosocial functioning and persistent disabil-

Therapeutic strategies must be personalized and correlated with the first psychotic episode stages. Treatment for young people who meet ARMS criteria should

The onset of the symptoms has occurred at least a year ago, with a frequency of

• Decrease in "the Global Assessment Functioning Score" (DSM-V) of at least 30 points in the past year which add one of the following risk factors: "first-degree relative with a lifetime diagnosis of schizophrenia or a schizophrenia spectrum

**16.2 Derealization**

**16.3 The LIPS criteria**

**42**

not only focus on the symptoms that constitute the ARMS criteria but also address the range of difficulties which the young person might present.

 Extrapyramidal side effects such as tardive dyskinesia, which is often irreversible, are less common with the newer, atypical antipsychotics [58, 59]. Evidence also suggests that certain antipsychotics (haloperidol) reduced gray matter volume in the brains of patients with a first episode of psychosis [60]. In contrast the newer second-generation antipsychotic medications, in fact, have neuroprotective qualities.

Antipsychotic drugs are potentially useful in the latter phases of the prodromal period when attenuated psychotic symptoms are evident and the individual is on the edge of a conversion to full psychosis.

Psychological interventions are useful in earlier and less symptomatic stages of the prodrome, to manage the stress, depression, anxiety, sleep disturbance, and decline in functioning.

Psychological treatments may be not only necessary but sufficient for some of these putatively prodromal patients [1].

Further researches are required to determine which treatment strategies are most effective and how long they should be continued.

Ethical considerations associated with treatment of young people who meet ARMS criteria have been widely debated [17, 28, 40, 41, 42, 45, 46]. Concerns about stigma associated with being identified as having a label of ARMS "false positives" and for how long should treatment be provided (in other words, how long is the period of risk) remain unresolved, and even clinical research into ARMS has now been conducted for over a decade.

*Neurodevelopment and Neurodevelopmental Disorder*


1. Introduction

Fracture toughness properties yield very essential information on the material behavior with the presence of the sharp crack. This information is in many cases crucial for design or decision about the further use or discarding the component from service. However in many such important cases, there is shortage of the experimental material, and thus assessment has to be done based on miniaturized specimen testing. Examples of the cases when shortage of the

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

experimental material is only available can be residual service life assessment of in-service components, when the experimental material only by semi-destructive approach can be obtained. Cases during development of new materials, generally preparation of the materials with limited volume such as severe plastic deformation processes for bulk nanomaterials preparation. Recently, also for the assessment of the parts produced by additive manufacturing techniques are application for small-size specimen testing.

This chapter is going to provide overview of reporting values of the results obtained with the use of miniaturized specimens with hints how can be small-size-based results related to the standard-sized specimen results. These techniques enable assessment of the fracture behavior from small material volumes allowing, for example, also local anisotropy assessment. In the first part of the chapter, some theoretical background for small-size specimen testing is provided for different fracture regime behaviors ranging from brittle up to full ductile behavior. Several mini specimens' geometries are demonstrated here that are subsequently applied on the experimental materials. Three materials are presented here, ferritic steel used for Master Curve-based assessment and then stainless steel and Ti-alloy produced by additive manufacturing technology. The results are summarized in order to provide inside into the facture behavior assessment with the use of miniaturized specimens providing background for practical application of these approaches.


**1. Introduction**

As per the American Diabetes Association, 2-3 million individuals in the United States have type 1 diabetes (www.medicinenet.com/script/main/art.asp?articlekey=159355), with 1 in every 400 to 600 children and adolescents affected by the disease in 2007. Furthermore, similar to other autoimmune diseases, allergies and asthma, the incidence of type 1 diabetes is on the increase at an alarming rate in industrialized countries for unknown reasons. Information released by the American Diabetes Association shows 23% and 21% increased rates of type 1 and 2 diabetes, respectively, from 2001 to 2009. The increase in incidence of type 1 diabetes is especially apparent in young children and has generated an urgent need for novel treatments that can safely control diabetes-causing inflammation, and alleviate the need for administra‐ tion of exogenous insulin. Indeed, type 1 diabetes has been treated for almost a century in the same fundamental manner using daily insulin injections. Although it is a life-saving treatment and one of the most remarkable accomplishments of medicine, administration of exogenous insulin is still not a cure because it does not address the underlying autoimmunity that targets insulin-secreting beta cells. Because it is currently impossible to mimic regulation of physio‐ logical insulin levels faithfully, many type 1 diabetic individuals receiving standard of care are exposed to acute and chronic complications that cause increased morbidity and mortality. As a result, there have been intense efforts to develop immunotherapies that can eliminate or at least alleviate the need for exogenous insulin. In this case the goal is to arrest pathological autoimmunity that destroys beta cells so that the cells can regain function, and possibly proliferate and regenerate.

Two major immunotherapeutic paths have been taken. The first path relies on different forms of systemic suppression of inflammation that inhibit effector T lymphocytes in a non-specific manner. Serious side effects associated with the use of systemic immunotherapies are in‐ creased risks of cancer and infection resulting from the decreased activity of effector cells involved in beneficial destructive immune responses against cancer cells and pathogens. These

© 2013 Li and Escher; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

side effects have been observed with broadly acting immunosuppressants used to prevent organ transplant rejection, which have been also investigated for treating type 1 diabetes [1, 2]. Serious side effects can also be seen, albeit to a lesser degree, with more specific agents like antibodies that target specific molecules involved in inflammation [3, 4]. In contrast, the second immunotherapeutic path is based on administration of a self-antigen synthesized by pancreatic beta cells that is a target of pathological autoimmunity, i.e., an autoantigen. This path is thought to be safer because it aims to induce a regulatory immune response that targets the inflamed islets. Here the goal is to manipulate endogenous immune mechanisms of homeostasis that can re-establish some form of tolerance to the chosen autoantigen, as well as to other neigh‐ boring beta cell autoantigens through a mechanism known as "by-stander suppression" [5]. Accordingly, it is anticipated that pathological autoimmunity and inflammation of islets can be stopped in an organ-specific manner that does not impair the immune system.

a DNA vaccine for treatment of melanoma delivered with gold particles into skin was found to be as efficacious as 1000 microgram injected intramuscularly [12]. These results illustrate the significant impact that choice of route and method of delivery of a DNA vaccine can have not only on efficacy, but also on cost of treatment. Other delivery routes like intravenous, nasal, and sublingual have also been investigated [13]. Post delivery, expression of coding sequences in plasmid DNA results in significant levels of protein production that may persist for six

DNA Immunotherapies for Type 1 Diabetes http://dx.doi.org/10.5772/55727 535

**Figure 1. Plasmid DNA Immunotherapy for Type 1 Diabetes.** Plasmid DNA immunotherapy for type 1 diabetes can be divided into two categories: DNA vaccines and gene therapies. Plasmid DNA can be delivered using different routes, for example, the intradermal and intramuscular routes. The therapies can induce tolerogenic dendritic cells (DC), T regulatory cells (Treg), and death/anergy of T effector cells (Teff) which are the main cause of pancreatic islet

DNA vaccination was originally investigated to induce immunogenic responses to pathogens and cancer cells, but it has increasingly been applied to the induction of immune tolerance for treatment of autoimmune diseases like type 1 diabetes. DNA vaccines and other gene-based vaccines belong to a third generation of vaccines after live and attenuated whole organism vaccine and recombinant protein vaccines. These vaccines can be used to either prevent (prophylactic vaccine) or treat (therapeutic vaccine) disease depending on their potency, in which prevention is generally easier to achieve than treatment. Recent reports of beneficial results in different clinical trials using delivery of autoantigens indicate that DNA vaccination is reaching a stage where we are likely to see accelerated development of a therapeutic future for vaccines targeting a variety of autoimmune diseases. In the case of type 1 diabetes, early results using a DNA vaccine encoding insulin have shown promise in humans. In addition,

destruction.

weeks and longer without serious side effects in human patients [14, 15].

In this chapter, we will review how plasmid deoxyribonucleic acid (DNA) has been used as an immunotherapeutic vector platform to treat type 1 diabetes through each immunothera‐ peutic path. For the purpose of this review, we have called the first path "gene-based immu‐ notherapy", meaning that plasmid DNA does not encode a known autoantigen, and the second path "DNA vaccine immunotherapy" meaning that a beta cell autoantigen is encoded by plasmid DNA (Figure 1). In other words, gene-based immunotherapy relies on the inherent function of a product encoded by plasmid DNA that can in turn affect cell function. In contrast, DNA vaccine immunotherapy relies on the tolerogenic immune response induced directly by the autoantigen after its processing by immune cells. As we shall see, some DNA vaccine immunotherapies have also a gene-based immunotherapy component that acts as a molecular adjuvant to promote tolerogenic immune responses. Nevertheless, in all cases synthesis of the molecule encoded by plasmid DNA, which is almost always a protein, starts after delivery of the plasmid DNA and its uptake by cells.

Plasmid DNA has several notable advantages compared to other vectors and therapeutic molecules. For example, it consists of relatively low molecular weight circles of double stranded DNA that can be readily isolated from bacteria in a generic and cost-effective manner. In addition, plasmid DNA permits rapid turnaround when developing new candidate products, refrigeration-free storage, and synthesis over time of a chosen antigen in its native conformation. Furthermore, plasmid DNA can be given in repeat doses within short periods of time without inducing an immune response to vector and other side effects. This is in contrast with viral-based vaccines that can induce immune responses to vector and protein/ peptides that can cause anaphylaxis [6, 7].

Plasmid DNA can be delivered either as "naked" DNA or packaged into molecular scaffolds like liposomes, cationic lipids, virosomes, and polymer-based nano- and micro-particles to increase efficacy of delivery to cells [8]. Although they may sometime have pro-inflammatory properties that can be detrimental to controlling inflammation, these particles have been used to induce immune tolerance with plasmid DNA. For example, chitosan-DNA nanoparticles encoding an ovalbumin antigen are tolerogenic when delivered orally [9].

Indeed, route of delivery can play a significant role in the type and strength of immune responses induced by DNA vaccines in animal models [10, 11]. In humans, two microgram of a DNA vaccine for treatment of melanoma delivered with gold particles into skin was found to be as efficacious as 1000 microgram injected intramuscularly [12]. These results illustrate the significant impact that choice of route and method of delivery of a DNA vaccine can have not only on efficacy, but also on cost of treatment. Other delivery routes like intravenous, nasal, and sublingual have also been investigated [13]. Post delivery, expression of coding sequences in plasmid DNA results in significant levels of protein production that may persist for six weeks and longer without serious side effects in human patients [14, 15].

side effects have been observed with broadly acting immunosuppressants used to prevent organ transplant rejection, which have been also investigated for treating type 1 diabetes [1, 2]. Serious side effects can also be seen, albeit to a lesser degree, with more specific agents like antibodies that target specific molecules involved in inflammation [3, 4]. In contrast, the second immunotherapeutic path is based on administration of a self-antigen synthesized by pancreatic beta cells that is a target of pathological autoimmunity, i.e., an autoantigen. This path is thought to be safer because it aims to induce a regulatory immune response that targets the inflamed islets. Here the goal is to manipulate endogenous immune mechanisms of homeostasis that can re-establish some form of tolerance to the chosen autoantigen, as well as to other neigh‐ boring beta cell autoantigens through a mechanism known as "by-stander suppression" [5]. Accordingly, it is anticipated that pathological autoimmunity and inflammation of islets can

be stopped in an organ-specific manner that does not impair the immune system.

the plasmid DNA and its uptake by cells.

534 Type 1 Diabetes

peptides that can cause anaphylaxis [6, 7].

In this chapter, we will review how plasmid deoxyribonucleic acid (DNA) has been used as an immunotherapeutic vector platform to treat type 1 diabetes through each immunothera‐ peutic path. For the purpose of this review, we have called the first path "gene-based immu‐ notherapy", meaning that plasmid DNA does not encode a known autoantigen, and the second path "DNA vaccine immunotherapy" meaning that a beta cell autoantigen is encoded by plasmid DNA (Figure 1). In other words, gene-based immunotherapy relies on the inherent function of a product encoded by plasmid DNA that can in turn affect cell function. In contrast, DNA vaccine immunotherapy relies on the tolerogenic immune response induced directly by the autoantigen after its processing by immune cells. As we shall see, some DNA vaccine immunotherapies have also a gene-based immunotherapy component that acts as a molecular adjuvant to promote tolerogenic immune responses. Nevertheless, in all cases synthesis of the molecule encoded by plasmid DNA, which is almost always a protein, starts after delivery of

Plasmid DNA has several notable advantages compared to other vectors and therapeutic molecules. For example, it consists of relatively low molecular weight circles of double stranded DNA that can be readily isolated from bacteria in a generic and cost-effective manner. In addition, plasmid DNA permits rapid turnaround when developing new candidate products, refrigeration-free storage, and synthesis over time of a chosen antigen in its native conformation. Furthermore, plasmid DNA can be given in repeat doses within short periods of time without inducing an immune response to vector and other side effects. This is in contrast with viral-based vaccines that can induce immune responses to vector and protein/

Plasmid DNA can be delivered either as "naked" DNA or packaged into molecular scaffolds like liposomes, cationic lipids, virosomes, and polymer-based nano- and micro-particles to increase efficacy of delivery to cells [8]. Although they may sometime have pro-inflammatory properties that can be detrimental to controlling inflammation, these particles have been used to induce immune tolerance with plasmid DNA. For example, chitosan-DNA nanoparticles

Indeed, route of delivery can play a significant role in the type and strength of immune responses induced by DNA vaccines in animal models [10, 11]. In humans, two microgram of

encoding an ovalbumin antigen are tolerogenic when delivered orally [9].

**Figure 1. Plasmid DNA Immunotherapy for Type 1 Diabetes.** Plasmid DNA immunotherapy for type 1 diabetes can be divided into two categories: DNA vaccines and gene therapies. Plasmid DNA can be delivered using different routes, for example, the intradermal and intramuscular routes. The therapies can induce tolerogenic dendritic cells (DC), T regulatory cells (Treg), and death/anergy of T effector cells (Teff) which are the main cause of pancreatic islet destruction.

DNA vaccination was originally investigated to induce immunogenic responses to pathogens and cancer cells, but it has increasingly been applied to the induction of immune tolerance for treatment of autoimmune diseases like type 1 diabetes. DNA vaccines and other gene-based vaccines belong to a third generation of vaccines after live and attenuated whole organism vaccine and recombinant protein vaccines. These vaccines can be used to either prevent (prophylactic vaccine) or treat (therapeutic vaccine) disease depending on their potency, in which prevention is generally easier to achieve than treatment. Recent reports of beneficial results in different clinical trials using delivery of autoantigens indicate that DNA vaccination is reaching a stage where we are likely to see accelerated development of a therapeutic future for vaccines targeting a variety of autoimmune diseases. In the case of type 1 diabetes, early results using a DNA vaccine encoding insulin have shown promise in humans. In addition, DNA vaccines encoding human heat shock protein 60 and glutamic acid decarboxylase 65 have also shown efficacy in preclinical trials and are reviewed in this chapter.

the severity of insulitis at 13 weeks of age was not improved, the incidence of diabetes was markedly reduced to 50% at 35 week old compared to 90% with control mice. These results show that the progression of autoimmune disease in mice can effectively be suppressed by intramuscular DNA injection coding for anti-inflammatory cytokines alone. When the same interleukin-10 encoded plasmid DNA was combined with a cationic polymeric carrier, systemic administration could reduce the severity of insulitis in NOD mice markedly (15.7%) compared with that of naked DNA injection (34.5%) and non-treated controls (90.9%),

DNA Immunotherapies for Type 1 Diabetes http://dx.doi.org/10.5772/55727 537

Another report investigating the immune effects of interleukin-10 DNA showed that systemic intramuscular administration of 200 microgram interleukin-10 plasmid DNA could alleviate blood glucose and insulitis in a streptozotocin induced diabetic mouse model up to day 28 post injection [24]. In this model, pancreatic interleukin-1b and tumor necrotic factor-alpha gene expression, serum interferon-gamma concentration, and the numbers of CD4+ and

 lymphocytes were decreased on day 28. A similar interleukin-10 construct was modified by introducing nuclear factor kappa-B (NF-kB) binding sites into plasmid DNA to facilitate nuclear transport of the plasmid after delivery into the cell [25]. A single injection of 50 microgram of the plasmid using polyethylenimine as a gene carrier in 5 week old mice reduced the degree of insulitis and serum glucose levels in 100% of mice compared to 40% of the control mice at 32 weeks of age. These results illustrate how plasmid DNA can be easily modified in

As mentioned previously, nanoparticle technology has been used to condense plasmid DNA into nanometer-size complexes to improve delivery. An interleukin-10 encoding plasmid DNA was assembled into a cationic nanoparticle complex, and a single dose of 50 microgram DNA was delivered intramuscularly into streptozotocin-induced diabetic mice [26]. Animals showed higher serum levels of interleukin-10, suppression of interferon-gamma level, reduction of islet insulitis, and lower blood glucose levels compared to those treated with interleukin-10 plasmid alone or the nanoparticle alone up to week 6 post injection. Histology of muscle showed that nanoparticles were biocompatible and did not cause a chronic inflam‐

In addition to their use alone, delivery of both interleukin-4 and interleukin-10 DNA has also been investigated. Combined delivery into nonobese diabetic mice of the two plasmid DNA constructs encoding interleukin-4 and interleukin-10 (25 μg each) was done intravenously using a degradable, cationic polymeric carrier, poly (alpha-(4-aminobutyl)-L-glycolic acid) [27]. Overexpression of the two cytokine messenger RNAs was confirmed in the liver of mice 5 days after delivery. Six weeks after injection, 75% of observed islets were intact compared with less than 3% in the control group, and development of diabetes was prevented in 75% of treated animals at 30 weeks of age, compared to 20% in control mice receiving plasmid DNA coding for a single cytokine or vector control alone. The results indicated that the interleukin-4 and interleukin-10 plasmid DNAs had synergistic effects on the prevention of autoimmune diabetes. A report from the same research group showed that a 'chimeric' plasmid expressing both of the interleukin-4 and interleukin-10 under controls of two CMV promoters could also

suggesting an increased protective effect of the polymeric carrier in vivo [23].

a generic manner to improve therapeutic efficacy.

reduce insulitis in the same system [28].

CD8+

matory response.

In contrast to DNA vaccine immunotherapy, gene-based immunotherapy involves delivery of genetic material by a plasmid vector into a cell, tissue or organ with the aim of improving the clinical status using the function of the encoded product, instead of its properties as an antigen. Gene-based immunotherapy includes delivery of anti-inflammatory cytokines, chemokines, and other factors to modulate the activity of immune cells [16, 17].


**Author details**

However, the mechanism by which the host's immune system develops the tolerance (healthy reaction) or sensitization (allergy) against a food has been partially elucidated. A subtype of

system tune against the food allergens, leading the immune responses either toward a tuned (healthy) or a false response (allergy). DCs sample the food allergens thorough the epithelial cell barrier of the gut. Other antigen presenting cells such as macrophages help the DCs for antigen sampling. Then these antigen activated DCs migrate from the lamina propria toward a secondary lymphoid tissue and there prime the naïve T lymphocytes to differentiate into

T cell to polarize into FOXP3−

called type 1 regulatory T cells (Tr1 cells). Tr1 cells have also critical role in dampening the immune response against food antigens. The DC-mediated polarized T cells contribute in suppressing the immune reaction against food allergens and induce the IgA production by

toward a cascade of responses directed by TH2 cells. In sensitized patients, the food allergens trigger inflammatory responses mediated by gut epithelial cells via producing the thymic stromal lymphopoietin (TSLP), IL-25, and IL-33. These cytokines affect the DCs, empowering them to deviate the polarization of naïve T cells toward the TH2 cells rather than the TH1 cells. Then TH2 cells induce the class-switching of B cells to produce allergen-specific IgE followed by subsequent responses by effector cells (mast cells, basophils) which is end in the food

There have been a series of diagnostic methods, some of them developed decades ago but until recently have been remained reliable enough although in some cases they give false positive or false negative result. However, the medical history and physical examination are the first line approach for medical diagnosis of food allergy in which some disorders such as the history of an atopic disease can guide the physician toward a proper diagnosis. In addition, a method based on step-by-step removing the nonallergic food from the dietary regimen until reaching the food causing the allergic response is the only fully reliable method of identifying the original cause of the food allergy. An accurate and generally accepted variant of the method called oral food challenge (OFC) has been developed but it could not be used extensively thus far due to requirement of intensive laboratory resources, its time-consuming procedures and the risk of undergoing anaphylactic reactions. The serologic tests such as measuring the total IgE and allergen-specific IgE, skin tests such as skin prick test, intradermal skin test, and atopy patch test can also help for diagnosis, though these tests indicate only the sensitization not a clinical food allergy. There are also two novel highly accurate diagnostic tests including the component-resolved diagnosis and basophil activation test although yet

The management and treatment methods for food allergy are mostly based on avoidance or elimination of the allergenic food from the dietary regimen. Currently, the only method whose effect can last for long time is known as the allergen-specific immunotherapy (SIT). In the SIT method, the allergen food is usually administered orally to the patient in a controlled manner in order to relieve the food allergy, which is called antigen desensitization. However,

cells responsible for tolerance against food allergens. In addition, CD103+

B cells. In contrast, during the sensitization process, CD103+

are being in the developing process in research settings.

regulatory T (Treg) cells. These primed and antigen-specific Treg cells are main immune

DCs are the key cells concerting the immune

DCs also involved

, IL-10-secreting T cells which are

DCs shift the immune system

dendritic cells (DCs) classified as the CD103+

FOXP3+

4 Allergen

allergy.

in triggering the naïve CD4+

Seyyed Shamsadin Athari1 \*, Ghasem Vahedi2

\*Address all correspondence to<EMAIL_ADDRESS>and<EMAIL_ADDRESS>
1 Department of Immunology, Faculty of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran

2 Research Center for Food Hygiene and Safety, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

**Provisional chapter**


*2.14. Statistical Analyses*

Analyses were performed in triplicate, and the results were expressed as mean and standard deviation (SD). Experimental data were subjected to one-way analysis of variance (ANOVA) after checking the normality and homoscedasticity to find significant differences. For post hoc analysis, the Tukey technique with a 95% confidence interval was used; *p* < 0.05 was deemed statistically significant. Minitab 18 software was used to perform the statistical analysis.

### **3. Results and Discussion**

### *3.1. The Phytochemical Profiles of the Kiwi Extracts*

In order to have a comprehensive view of kiwi byproducts' phytochemical content, selected solvents were used in order to obtain extracts enriched in hydrophilic and lipophilic compounds, such as polyphenols, flavonoids, and carotenoids. The phytochemical profile and antioxidant activity are shown in Table 1.

**Table 1.** Phytochemical characterization and antioxidant activity of kiwifruit pomace and peels.

Means in the same row that do not share a letter (a,b) are significantly different based on Tukey's method with 95% confidence.

As expected, the kiwi peels showed higher contents of polyphenols, flavonoids, and carotenoids, leading to significantly higher antioxidant activity. Our results support the hypothesis of the accumulation of bioactives in the outer layer of fruits. Wang et al. [32] suggested that most phenolic compounds, such as protocatechuic acid, chlorogenic acid, caffeic acid, rutin, p-hydroxybenzoic acid, and quercitin, are found in different parts of kiwifruit, with higher contents in the peels. These authors reported higher concentrations of flavonoids and polyphenols in kiwi peels, up to 8.13 mg gallic acid/g, compared with values ranging from 2.89 to 6.91 mg gallic acid/g in kiwi pulp.

As expected, the carotenoid content had the same trend, with β-carotene and lycopene contents of 4.23 ± 0.027 mg/g DW and 1.06 ± 0.027 mg/g DW, respectively, in kiwi peels. Our results are consistent with the hypothesis that the carotenoid content in kiwifruits is due to the cumulative content of β-carotene and chlorophylls [33]. As regards antioxidant activity, the kiwi peel extracts showed higher values for both DDPH and ABTS radical scavenging activities, which were correlated with the higher contents of polyphenols and carotenoids. Antioxidant activity is often associated with the prevention or inhibition of processes that lead to cellular degradation, caused mainly by the effects of free radicals. Using multivariate correlation analysis, Zhang et al. [34] established that different groups of polyphenolic compounds are mainly responsible for antioxidant activity.

### *3.2. The Phytochemical Profiles and Cell Viability of Inoculated Freeze-Dried Kiwi Powders*

In order to valorize the kiwi pomace and peels as added-value ingredients, the fresh materials were enhanced with different flours in order to improve additional properties, such as color, prebiotic activity, enhanced antioxidant activity, etc. Therefore, four variants of inoculated kiwi-based powders containing *L. casei* 431® were obtained. The phytochemical profiles of the four variants are given in Table 2.

**Table 2.** Phytochemical characterization of freeze-dried samples.

KPO—kiwi pomace with *L. casei* 431®; KPB—kiwi pomace with buckwheat flour and *L. casei* 431®; KBR—kiwi pomace with black rice flour and *L. casei* 431®; KP—kiwi peels and *L. casei* 431®. Means in the same row that do not share a letter (a–d) are significantly different based on Tukey's method with 95% confidence.

It is well known that fruits and vegetables are rich in polysaccharides. Kiwifruits contain large amounts of pectin and dietary fiber, which have been found to improve the immune system and chronic diseases associated with constipation. Therefore, it is fair to consider that kiwifruits confer prebiotic effects on the intestinal microbiota [35]. These authors suggested that kiwifruit can act as a prebiotic in the selective intensification of the growth of lactic acid bacteria (*Lactobacillus* and *Bifidobacterium*) while inhibiting *Clostridium* and *Bacteriodes* ssp.

Table 2 gives the number of colony-forming units in each sample before and after freeze-drying. The variant based on kiwi pomace (KPO) showed an initial cell concentration of 10.63 log CFU/g DW, while after freeze-drying, a decrease to 7.89 log CFU/g DW was observed. In the case of the variant based on kiwi peels (KP), the initial probiotic load (10.64 log CFU/g DW) slightly decreased to 9.46 log CFU/g DW, whereas for the variants with black rice and buckwheat flour addition, a prebiotic effect was observed, with a higher value for the KPB variant. Although the freeze-drying process is considered a friendly preservation method with a low rate of biologically active compound degradation, a decrease in the viable counts of *L. casei* 431® was observed to different extents in all samples. It can be inferred that the higher survival rate observed in samples based on peels with flour addition is due to the prebiotic effects of the fiber, vitamins, and bioactives. For example, Xie et al. [36] suggested a link between polyphenolic compounds in kiwi byproducts and the viable counts of lactic acid bacteria cells. The survival rate of lactic acid bacteria ranged from 73% to 88%. Based on these results, it is fair to attribute a probiotic character to all of the kiwi-based variants, given the suggested minimum concentration of viable cells of log 6 CFU/g.

The polyphenolic content of the samples was highly influenced by the particular formulation. The kiwi byproduct-based formulations showed a polyphenolic content varying from 10.56 ± 0.30 mg AGE/g DW to 13.16 ± 0.33 mg AGE/g, whereas the flavonoid content was influenced by the type of flour added (Table 2). No significant differences were found in antioxidant activity values. Table 2 shows the carotenoid contents of the samples, highlighting the higher contents of β-carotene and lycopene in the KPO sample (0.90 ± 0.07 mg/g DW and 0.57 ± 0.05 mg/g DW, respectively).