Strain and curvature due to body and surface waves [9].
\r\n\tHomeostasis is brought about by a natural resistance to change when already in the optimal conditions, and equilibrium is maintained by many regulatory mechanisms. All homeostatic control mechanisms have at least three interdependent components for the variable to be regulated: a receptor, a control center, and an effector. The receptor is the sensing component that monitors and responds to changes in the environment, either external or internal. Receptors include thermoreceptors and mechanoreceptors. Control centers include the respiratory center and the renin-angiotensin system. An effector is a target acted on to bring about the change back to the normal state. At the cellular level, receptors include nuclear receptors that bring about changes in gene expression through up-regulation or down-regulation and act in negative feedback mechanisms. An example of this is in the control of bile acids in the liver.
\r\n\tSome centers, such as the renin-angiotensin system, control more than one variable. When the receptor senses a stimulus, it reacts by sending action potentials to a control center. The control center sets the maintenance range—the acceptable upper and lower limits—for the particular variable, such as temperature. The control center responds to the signal by determining an appropriate response and sending signals to an effector, which can be one or more muscles, an organ, or a gland. When the signal is received and acted on, negative feedback is provided to the receptor that stops the need for further signaling.
\r\n\tThe cannabinoid receptor type 1 (CB1), located at the presynaptic neuron, is a receptor that can stop stressful neurotransmitter release to the postsynaptic neuron; it is activated by endocannabinoids (ECs) such as anandamide (N-arachidonoylethanolamide; AEA) and 2-arachidonoylglycerol (2-AG) via a retrograde signaling process in which these compounds are synthesized by and released from postsynaptic neurons, and travel back to the presynaptic terminal to bind to the CB1 receptor for modulation of neurotransmitter release to obtain homeostasis.
\r\n\tThe polyunsaturated fatty acids (PUFAs) are lipid derivatives of omega-3 (docosahexaenoic acid, DHA, and eicosapentaenoic acid, EPA) or of omega-6 (arachidonic acid, ARA) and are synthesized from membrane phospholipids and used as a precursor for endocannabinoids (ECs) mediate significant effects in the fine-tuning adjustment of body homeostasis.
\r\n\t
\r\n\tThe aim of this book is to discuss further various aspects of homeostasis, information that we hope to be useful to scientists, clinicians, and the wider public alike.
A seismic ground motion poses a threat to urban infrastructure as well as human life. Individuals have a limited understanding of underground structures’ seismic resistance. Because of smaller deformations under the condition of encompassing rock or soil constraints, it is widely agreed that an underground structure is much more stable than a ground structure. Several communities have emerged in the United States of America to explain seismic behavior of underground opening under severe conditions since the 1990s. Numerous destructive seismic events, such as the Kobe, Chi-Chi, Kocaeli and Wenchuan earthquakes, have occurred since the 1990s, causing genuine harm to tram stations and tunnels, indicating that underground structures are still vulnerable to damage under intense seismic motions. A characteristic example of broad damage due to ground shaking and permanent displacements is the Hanshin earthquake caused liquefaction that contributed to the collapse of numerous underground structures in 1995, counting a tram station in Kobe, Japan, damages to highway tunnels during 1999 Chi- Chi and the collapse of the twin Bolu under construction tunnels, during the 1999 Kocaeli earthquake [1].
Owen and Scholl [2] characterized the deformation sorts of underground structures due to seismic excitation as axial compression/extension; longitudinal bending, ovaling, and racking deformations (Figure 1). Shear deformation of tunnels initiated by the vertically propagating shear waves has been broadly investigated by a number of researchers [3, 4], and it has been demonstrated to be the basic mode of deformation for tunnels under seismic loading. Ovaling and racking deformations are related to normal or nearly normal propagation of shear waves with respect to tunnel axes which cause distortion of tunnel cross section. Simplified seismic design approaches for tunnels are often favored by experts. They should be able to assess the general response of a tunnel system that has been subjected to seismic loading. As a result, simpler methods for measuring maximum shear strain (γmax) in the tunnel depth are used [1].
Types of deformations on tunnels under seismic actions (a) compression extension, (b) longitudinal bending deformation, (c) compression of tunnel section [
Many researchers proposed analytical solutions to estimate the seismic internal forces of tunnel linings under certain assumptions and conditions, such as elastic response of the soil and tunnel lining, and seismic loading simulation in semi-static construction, among others. Analytical solutions are useful, moderately fast, and easy to use for fundamental seismic design of tunnels, despite the fact that they are formed using relatively strict assumptions and simplifications. As a result, they’re commonly used in the early stages of design. With the improvement in technology and computer science, and consequently in numerical analysis of material deformation and stability, several methods are used for analysis of underground structures such as finite element, finite difference and discrete element method. Analyzing of axial and bending deformations can be best performed using 3-D models. In finite difference or finite element models, the tunnel is discretized spatially and the surrounding soil is either discretized or models by springs. Several computer codes perform these type of analysis such as FLAC, ABAQUS and so on [1].
The seismic design of tunnels is based on two approaches: (1) soil-structure interaction and (2) free field approach. In the first approach, the soil shear strains are affected by the deformation of the nearby underground structures and will conform to the structure strains. A reduction in the total mass of the soil and structure at the soil cavity may have a significant effect on the shear strain. In this case, shear strain of soil in the vicinity of structure will be greater than the free-field approach. In the free-field approach, the interaction between soil and structure is neglected and it is expected that structures accommodate the forced deformations from encompassing ground. These deformations are a function of maximum shear strain [1, 5]. The direct measurement of strains is not possible so it is correlated to other strong-motion parameters such as Peak Ground Velocity (PGV) [6, 7]. Newmark considered one-directional propagation of the harmonic wave in a homogeneous, isotropic, and elastic unbounded medium. According to Newmark, relationship between the maximum particle velocity (Vmax) and (γmax) is.
Where C is the apparent wave velocity [8].
C cannot be estimated straightforward and is depended on wave type, the angle of incidence, and material property [9]. To calculate this parameter, some formulas are proposed. For instance, O’Rourke and Elhmadi [10] proposed a relation for calculation of longitudinal deformation on buried pipes:
Where Ø is angle of the incidence at the ground surface and Vs is the shear wave velocity of the top layer. C is variant at different geological situations [10, 11, 12]. Ovaling and racking deformations are correlated with γmax on a vertical plane, so C is close to Cs, which is the incident horizontal shear-wave velocity in geological layers. The consequent structural deformations are basically related to γmax in the imperforated ground as shown in Figure 2 [13, 14, 15].
Ovaling and racking deformation on buried structures [
Wang [13] considering ovaling deformation related C to effective shear modulus, G, and the mass density of the medium, ρ by.
In the case of replacement of Eq. (3) in Eq. (1) some problems may arise such as the indeterminacy in the definition of deep depth or application of this formula for layered strata. Considering all these issues, they are still adopted by most of the available technical guidelines [6, 7, 12].
St. John and Zahrah [9] developed Newmark’s formula and proposed relationships to estimate longitudinal, normal and shear strains in the free field which is depicted in Table 1.
Wave Type | Axial Strain | Shear Strain | Curvature | |
---|---|---|---|---|
P-wave | ||||
S-wave | ||||
R-wave | Compressional Component | |||
Shear Component | ||||
where: | ||||
VP = soil particle velocity caused by P-waves | ||||
aP = soil particle acceleration caused by P-waves | ||||
CP = apparent propagation velocity of P-waves | ||||
VS = soil particle velocity caused by S-waves | ||||
aS = soil particle acceleration caused by S-waves | ||||
CS = apparent propagation velocity of S-waves | ||||
VR = soil particle velocity caused by R-waves | ||||
aR = soil particle acceleration caused by R-waves | ||||
CR = propagation velocity of R-waves | ||||
1/p = curvature |
Strain and curvature due to body and surface waves [9].
If the shear waves propagate vertically in a uniformly elastic half space, γmax for a specific ground motion is a function of d/Vs, the ratio of depth below free boundary to shear-wave velocity in medium [16]. In layered medium, the equivalent travel-time concept proposed by Imai et al. [17] for estimation of maximum shear-stress (τmax) may be used. Consequently, γmax, can be calculated by dividing τmax by the secant shear modulus of material Gsec, representing the average stiffness in a range of shear strain.
For calculation of ovaling deformation, vmax is frequently assumed to be equal to the Peak Ground Velocity (PGV) in free field [10, 18]. A reduction coefficient (rd) is proposed to reduce the ratio of ground motion at tunnel depth to motion at ground surface as it is shown in Table 2. This correlation is based on earthquake databases gathered from accelerograms [6, 7].
Tunnel Depth (m) | Ratio of Ground Motion at Tunnel Depth to Motion at Ground Surface (rd) |
---|---|
≤ 6 | 1.0 |
6 to 15 | 0.9 |
15 to 30 | 0.8 |
> 30 | 0.7 |
For tunnels with shallow burial depths, maximum shear stress can be estimated by the product of Peak Ground Acceleration (PGA) in ground surface and overburden pressure [7]. This product is corrected by an empirical depth-reduction factor (rd) due to the deformability of medium [19]. In this method, maximum shear stress (on a horizontal plane) at depth d is.
such that ρ is the density of the shallow geological formation, and d is the depth of interest. Then, maximum can be estimated by Eq. (3).
Penzien [20] also suggested closed-form solutions for seismic analysis of deep rectangular and circular tunnels, with the seismic loading being better replicated as a uniform shear-strain dissemination, τff, forced on the soil boundaries of the soil-tunnel system, away from the tunnel. Penzien’s solutions, on the other hand, ignore the impact of typical stresses generated during loading along the soil-tunnel interface. They decided that the deformation of the tunnel could be approximated by the deformations of a circular cavity (e.g. through significant consideration of parameter β in Figure 3). Huo et al. [21] proposed improved arrangements by considering the genuine deformation example of rectangular-molded cavities and representing both the ordinary and shear stresses at the the soil-tunnel interface.
Deformation of W × H rectangular cavity subjected to a uniform shear strain distribution γff: (a) with free-field shear stress distribution applied to cavity surface; (b) with free-field shear stress distribution removed from cavity surface [
Analytical solutions usually presume that the soil has a linear elastic behavior and therefore do not take into account the strain-dependent soil shear modulus. Bobet et al. [22] compensated for the reduction in shear modulus by iteratively adjusting the soil shear modulus as a function of shear strain magnitude before shear strain convergence was achieved. The analytical solution was then used to estimate the soil deformation using the compatible shear strain shear modulus [21]. The effect of soil saturation was overlooked in the production of all of the above closed-form solutions. Bobet [4] suggested circular tunnel solutions in saturated soil, assuming a non-slip interface. Bobet [23] went on to extend the previous solutions to look at the response of rectangular tunnels under no-slip and fully-slip interface conditions, as well as drained and undrained soil conditions. Park et al. [24, 25] looked over the previous solutions and proposed a new approach for considering future sliding along the soil-tunnel interface. The majority of the above-mentioned suggested analytical relationships are for shear S-waves propagating upward in the tunnel’s transverse direction. Kouretzis et al. [26, 27, 28, 29] proposed a set of relations for compressional P-wave tunnels as well.
The assumptions on which the analytical solutions are based limit their applicability (Table 3). Researchers started comparing the results of analytical solutions with the predictions of sophisticated numerical models after the rapid growth of computational power in the last two decades to recognize the shortcomings of these analytical solutions. For example, Kontoe et al. [15] compared four different analytical models (i.e. [13, 20, 23, 24]) and validated them against finite element simulations (FE). Tsinidis et al. [33] compared the results of analytical solutions (i.e. [13, 20, 24]) with numerical predictions for extreme lining flexibilities, i.e. very flexible or very rigid tunnels compared to the surrounding soil. Kontoe et al. [14] and Tsinidis et al. [33] found that the analytical solution of Penzien [20] underestimates the thrust added to the tunnel structure for a slip-free interface, which is consistent with previous findings [34]. As a result, using this solution for a rough soil-lining interface is not recommended.
Solution | Tunnel lining | Soil type | Saturation conditions | Soil layering | Soil-tunnel interface | Cross-section | ||
---|---|---|---|---|---|---|---|---|
Elastic | Elastic | Dry | Homogeneous | No slip | Frictional Slip | Full Slip | Circular | |
St.John C.M. and Zahrah T.F [9] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Wang, J.N., [13] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Penzien and Wu [31] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Penzien [20] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Bobet [4] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Hou, et al. [21] | Yes | Yes | Yes | Yes | Yes | No | Yes | No |
Park et al. [25] | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Bobet [32] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Kouretzis [27] | Yes | Yes | Yes | Yes | Yes | No | Yes | Yes |
Kouretzis [28] | Yes | Yes | Yes | Yes | No | No | Yes | Yes |
Kouretzis [29] | Yes | Yes | Yes | Yes | No | No | Yes | Yes |
Summary of assumptions and applicability of analytical solutions for the analysis of tunnels under ground shaking [30].
Since the soil response is often assumed to be linearly elastic, the solutions are usually more reliable only when the soil undergoes minor deformations, such as for very rigid clays and rocks at low shaking levels, with the exception of Bobet et al. [22]. The solutions for the transverse earthquake response are derived in the plane strain condition and therefore cannot be used for complex ground plans. In most cases, the contact interface is limited to two extreme states, full or no slip, while the lining is assumed to be continuous; therefore, a suitable representation of the segmental lining by an equivalent continuous lining is mandatory.
Random vibration theory (RVT) relates the statistical properties of the random behavior of a dynamical system to the system properties or those of the random excitation. Therefore, RVT can be used to statistically estimate the random response of a system by representing the ground motion by a power spectral density (PSD) function.
Simplified theoretical conclusions are possible by assuming that ground motion is a stationary (i.e., the statistical properties of the motion are constant in time) Gaussian process. Although earthquake excitations are not stationary, the strong phase of such motions can be assumed to be stationary [35]. In this approach, the excitation is first defined by a PSD. The response PSD is either expressed theoretically or calculated using transfer functions. Then the statistical properties of the response are estimated using its PSD.
A well- known example of the use of RVT for the development of theoretical solutions is the Complete Quadratic Combination (CQC) method, which is useful for estimating peak displacements or forces within a structure [36]. CQC is also used for analyzing the nonstationary random responses of complex structures that are in an inhomogeneous stochastic field [37]. The analysis of the seismic response of linear multicolumn structural systems can be formulated by RVT, which takes into account the multicolumn input [38]. The steady-state filtered white noise model proposed by Kanai and Tajimi [39, 40] provides a well-known PSD in the field of earthquake engineering. White noise is a stationary random process that has a mean of zero and a constant spectral density for all frequencies. In the Kanai-Tajimi spectral model, the rock acceleration is assumed to be white noise and the overlying ground deposits are simulated by a linear one-degree-of-freedom system. Modified Kanai-Tajimi models are also proposed in the literature [41]. Therefore, RVT can be used to generate simple theoretical solutions. On the other hand, these simple solutions are limited to linear systems.
The theorems of random oscillation can be used to derive theoretical relationships between the parameters of dynamic response and ground motion. The theoretical analysis of the random response can be simplified by two assumptions. The first is that the excitation is statistically stationary in a broad sense. The second assumption is that the probability distribution of the excitation is Gaussian, so that each linear operation on this random process produces a different Gaussian process [42]. Although the properties of transient seismic motions obviously contradict these assumptions, the simplification can lead to reasonable theoretical functions that reflect the characteristic properties of dynamical systems. The applications concerning the combination of maximum modal displacements in structural dynamics [36, 43] and transfer functions for kinematic soil-structure interaction [44, 45] are well-known examples.
Analytical methods are implemented for analyzing underground structures by a numerous researchers. Though these methods have some shortcomings because of simplifying the design conditions, they provide a good approximation for preliminary analysis of such structures. Analytical methods are divided into two main categories: (a) soil-structure interaction and (b) free-field methods. In this chapter, free-field method, which ignores interaction between structure and encompassing soil, is being studied and its development has been discussed. For the practitioner, the simplified techniques are useful tools for preliminary studies. They make it simple to identify the variables that influence the severity of the prejudices, providing insight into the structure’s actions. Furthermore, the simplified approach and its solutions are invaluable in better understanding the relationship between dynamic loads, viscoelastic foundations, and tunnel structures, defining the most important parameters for the problem, and providing preliminary estimates or even a design. They also have the advantage of being able to conduct sensitivity analyses with little effort. The simplified approach may not be able to capture the responses and damage in structural specifics, components, or positions of possible failure due to the simplified assumptions for the tunnel layout and soil-tunnel interaction.
No potential conflict of interest was reported by the author.
Graft-versus-host disease (GVHD) is a debilitating complication that can determine the prognosis of allogeneic hematopoietic stem cell transplantation (HSCT) and subject 40–60% of HSCT recipients to a risk of death and disability [1]. GVHD is composed of acute GVHD (aGVHD) and chronic GVHD (cGVHD). For the classification of the 2 types of GVHD, the classifier should be clinical manifestations instead of time after HSCT [2]. However, in many cases, aGVHD appears within 100 days after HSCT and causes severe inflammation mostly in the skin, gastrointestinal tract, and liver [3]. cGVHD generally occurs systemically 6 months or later after HSCT, and its symptoms are similar to those of autoimmune diseases [4]. Complex interactions between donor and host immune cells are implicated in the pathogenesis of GVHD. It is thought that aGVHD is induced primarily by donor T cells’ cytotoxic responses against host tissues through recognition of host polymorphic histocompatibility antigens [5]. On the other hand, the mechanisms of cGVHD are more complicated and still poorly understood [6]. Although the use of corticosteroids alone or in combination with immunosuppressive agents is the recommended first-line strategy for the treatment of GVHD, its efficacy is not satisfactory [3, 7]. The prevalence of allogeneic HSCT for the treatment of hematologic diseases has increased the need for the development of efficacious second-line therapies which can mitigate symptoms of GVHD without compromising a graft-versus-leukemia effect, where donor T cells eliminate host leukemia cells. To date, various signaling pathways and pathogenic events in the context of GVHD have been intensively investigated. As a result, several FDA-approved drugs for GVHD have recently emerged. This chapter concisely summarises therapeutic targets and newly emerging drugs for the 2 forms of GVHD with the goal to facilitate the development of novel GVHD treatments for human use.
aGVHD can occur after the engraftment of donor-derived cells in the transplant recipient [8]. Symptoms of aGVHD can develop within weeks after the transplantation [9]. It has been believed that aGVHD can primarily affect the skin, gastrointestinal (GI) tract, and/or liver [10]. HSCT recipients can manifest rash, increased bilirubin, diarrhea, and vomiting [11]. Most recently, mounting evidence suggests that other organs such as the central nervous system, lungs, ovaries and testis, thymus, bone marrow, and kidney can be susceptible to aGVHD [12].
Clinical manifestations of cGVHD are different from those of acute GVHD. The onset of chronic GVHD can be divided into the following 3 cases: (1) occurring when aGVHD is present, (2) emerging after a period of resolution from aGVHD, and (3) developing de novo [13]. Immune dysregulation and absence of functional tolerance are characteristic of cGVHD, and symptoms of cGVHD are reminiscent of those of autoimmune disorders [13]. Clinical presentations of cGVHD can be as follows: (i) rash, raised or discolored areas, skin thickening or tightening, (ii) dry eye or vision changes, (iii) dry mouth, white patches inside the mouth, (iv) diarrhea and weight loss, (v) shortness of breath due to lung disorders and (vi) abnormal liver function [14]. It was challenging for clinicians to reach an agreement on the diagnosis, the timing of treatment, and how to grade cGVHD [15]. In order to overcome these difficulties, the National Institute of Health (NIH) consensus created diagnostic criteria for cGVHD in 2005 and revised the criteria in 2014 [16, 17]. The authors considered the severity of involvement of the skin, mouth, eyes, gastrointestinal tract, liver, lungs, joint fascia, and genital tract in order to define manifestations of cGVHD in its target organs and establish a scoring system.
Corticosteroids are used with or without immunosuppressive drugs as the first-line therapy for aGVHD and cGVHD in clinical settings [3, 7, 18, 19]. However, approximately 50% of patients who receive steroid therapy will be resistant to it, although mechanisms of steroid resistance remain to be elucidated [3, 7, 18, 19]. In addition, corticosteroid therapies also cause various undesired effects such as diabetes, obesity, osteoporosis, hypertension, glaucoma, and liver damage [20]. Thus, medical settings are in need of effective treatments of steroid-refractory aGVHD and cGVHD [3, 7, 18, 19].
GVHD has a complex pathophysiology, which initially begins with damage to host tissues by chemotherapy and radiation therapy before allogeneic HSCT (Figure 1) [21]. Due to this, damage-associated molecular patterns (DAMPs), pathogen-associated molecular patterns (PAMPs), and inflammatory cytokines are released [22]. These stimuli activate host dendritic cells (DCs), leading to the expression of major histocompatibility complex class I (MHC-I) and class II (MHC-II) on the host DCs [22]. The mature host DCs activate donor-derived T cells in the graft [22]. The activated donor T cells migrate to aGVHD-susceptible organs and promote the excessive production of pro-inflammatory cytokines such as interferon (IFN)-γ and interleukin (IL)-17 [23, 24]. It results in abnormal inflammation and tissue damage [23, 24]. While it is believed that donor-derived CD4+ and CD8+ T cells play a pivotal role in mediating aGVHD [25], several other types of immune cells are reportedly involved in the pathogenic process of aGVHD [26]. Neutrophils contribute to the development of intestinal aGVHD [27]. A previous report suggests that neutrophils in the ileum migrate to mesenteric lymph nodes, presenting antigens on their MHC-II and promoting T cell expansion [28]. Donor monocyte-derived macrophages with potent immunological functions are implicated in the pathophysiology of cutaneous aGVHD by secreting chemokines, stimulating T cells, and mediating direct cytotoxicity [29, 30]. In contrast, regulatory T cells (Tregs) are thought to serve a suppressive role in aGVHD without significantly reducing the graft-versus-leukemia (GVL) effect [31, 32]. Recent reports suggest that donor-derived natural killer (NK) cells can have an inhibitory effect in aGVHD by promoting the depletion of allo-reactive T cells while showing the GVL effect [33]. A recent study indicates that the occurrence and severity of aGVHD could be associated with the disordered reconstitution of CD56high NK cells [34].
The overview of aGVHD pathogenesis. The preconditioning regimen causes tissue damage. It generates DAMPs, PAMPs and proinflammatory cytokines such as TNFα, IL-1β and IL-6, which activates host APCs. The activated APCs present antigens to donor T cells, and the activated T cells infiltrate aGVHD target organs and produce an excessive amount of IFNγ and IL-17, leading to abnormal inflammation and tissue damage. This figure is created with BioRender.
While mechanisms of cGVHD are still incompletely understood, recent evidence suggests that there are several observations characteristic of cGVHD (Figure 2) [35]. The thymus is damaged due to the conditioning regimen and/or the prior occurrence of aGVHD, leading to impaired negative selection of alloreactive CD4+ T cells [36]. Alloreactive T cells are activated by antigen-presenting cells (APCs), resulting in their expansion and polarization toward type 1, type 2, and type 17 helper T (Th1, Th2, and Th17) cells [35]. These immune deviations lead to the production of proinflammatory and profibrotic inflammatory cytokines such as IFNγ, IL-6, IL-17, IL-4, and transforming growth factor β (TGFβ), which skew macrophages and fibroblasts towards proinflammatory and/or profibrotic phenotypes [35]. Consequently, inflammation and fibrosis are induced in cGVHD target organs [37]. The damaged thymic epithelial cells (required for the generation of Tregs as well as the negative selection) also cause a decrease in the number of Tregs [38]. Furthermore, the dysregulation of B cells causes autoreactive B cells to arise and produce autoreactive antibodies [39]. The emergence and activation of autoreactive B cells presumably stem from B cell exhaustion induced by aberrant levels of B cell-activating factor (BAFF) in the lymphoid microenvironment [40, 41].
Overview of cGVHD pathogenesis. The thymus is damaged due to the preconditioning regimen and/or aGVHD. Due to the damage, the negative selection of alloreactive T cell is impaired. Alloreactive T cells are polarised into Th1, Th2 or Th17 cells. Th1 cells produce IFNγ, which drives macrophages to an M1-like phenotype to promote inflammation. IL-4, IL-10 and TGFβ produced by Th2 cells facilitate macrophage differentiation into an M2-like phenotype. Activation and proliferation of tissue fibroblasts are induced by (i) TGFβ from Th2 cells, (ii) PDGFα and TGFβ from M2-like macrophages and (iii) IL-6 and IL-17 from Th17 cells, leading to collagen production and fibrosis. B cells are activated by IL-6 and IL-17 from Th17 cells, and the alloreactivity of B cells is presumably induced by an excessive amount of BAFF. As a result of the above events, systemic inflammation and fibrosis are induced, and autoimmune-like manifestations are observed. This figure is created with BioRender.
When the T cell receptor (TCR) interacts with an MHC-antigenic peptide complex, it induces molecular and cellular changes in T cells [42]. A wide range of signal transduction pathways in T cells is stimulated due to this interaction, leading to the activation of a variety of genes [43]. Effector enzymes such as kinases, phosphatases, and phospholipases are involved in the TCR signaling pathways, which are integrated by non-enzymatic adaptor proteins acting as a scaffold for interactions between proteins [42]. These intracellular signaling pathways can determine the features of immunity mediated by T cells [44].
The B cell receptor (BCR) complexes on inactivated B cells act as self-inhibiting oligomers [45]. The BCR signaling pathways are initiated, when BCR is bound to an antigen and induces actin-mediated nanoscale recombination of receptor clusters [46]. Due to this event, the BCR oligomers are opened and the ITAM domains are revealed, resulting in the transduction of intracellular signals which are crucial for B cell development, activation, proliferation, differentiation, and antibody production in health and disease [47].
In 2017, FDA approved ibrutinib, which targets B cells and T cells, for the treatment of cGVHD. Ibrutinib was the first FDA-approved drug for steroid-refractory cGVHD, and it was a significant milestone for GVHD research [48]. Ibrutinib is reported to modulate the functions of B cells and T cells by potently inhibiting Bruton’s Tyrosine Kinase (BTK) and IL-2 Inducible T-cell Kinase (ITK) [49], which are involved in the B cell signaling and T cell signaling pathways, respectively. Treatment of cGVHD-affected recipients with ibrutinib resulted in decreased serum-autoantibodies and B-cell proliferation [50]. Data from the clinical trials show that symptoms of cGVHD improved in 67% of patients treated with ibrutinib [48].
The Purinergic signaling pathways play a crucial role in a range of physiological systems including the immune system. In the purinergic signaling pathways, extracellular purine nucleosides and nucleotides such as adenosine and adenosine triphosphate (ATP) are used as signaling molecules that mediate the communication between cells through the activation of purinergic receptors [51]. There are four types of P1 (adenosine) receptors (A1, A2A, A2B, and A3). P2 receptors are subdivided into P2X and P2Y [52]. P2X receptors have seven subtypes (P2X1, P2X2, P2X3, P2X4, P2X5, P2X6, and P2X7), and P2Y receptors have 8 subtypes (P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, P2Y13, and P2Y14) [52].
As demonstrated by several studies using mouse models of aGVHD, extracellular ATP is augmented in aGVHD-affected mice, and purinergic signaling is implicated in the pathogenic process of aGVHD (Figure 3) [53]. The conditioning regimens prior to allo-HSCT can induce tissue damage, leading to the release of DAMP molecules including ATP, which activates purinergic signaling [53]. The involvement of extracellular ATP is evidenced by the fact that the injection of the soluble ATP diphosphohydrolase (ATPDase) can reduce inflammation in aGVHD target organs and the serum level of IFNγ [53, 54].
Link between GVHD and the therapeutically targetable purinergic signaling pathways. In aGVHD, ATP is produced due to tissue damage. Host APCs and donor T cells can be activated by the P2X7 receptor, which results in the progression of aGVHD. The activation of donor Tregs can also be induced by the ATP-activated P2X7 receptor, which leads to the reduction of Treg survival and the progression of aGVHD. CD39 and CD73 on donor Tregs can degrade ATP to adenosine. Adenosine can activate the A2A receptor on donor T cells, which culminates in the decrease in the number of CD4+ and CD8+ T cells and the reduction of aGVHD. In cGVHD, ATP is also released because of tissue damage and may promote fibroblast-to-myofibroblast transition through the ATP-activated P2X7 receptor, leading to the augmented collagen production and the progression of tissue fibrosis. In contrast, the ATP-activated P2Y14 receiptor may prevent cellular senescence in macrophages and mitigate cGVHD. This figure is created with BioRender.
Evidence suggests that; (i) P2X7 is a crucial P2X receptor in the development of aGVHD after the release of extracellular ATP, (ii) the expression of the P2X7 receptor is elevated in PBMCs in aGVHD patients, (iii) the liver, spleen, skin, and thymus in aGVHD-affected mice show the increased expression of the P2X7 receptor, (iv) the ATP-induced the activation of the P2X7 receptor on host APCs can facilitate the stimulation, proliferation, and survival of donor T cells during aGVHD and (v) the P2X7 activation on host APCs may be associated with the expression of microRNA mir-155 [53, 55, 56, 57].
While the host P2X7 receptor is shown to play an integral role in the development of aGVHD, the donor P2X7 receptor is also a contributor to this disease. Evidence suggests that (i) the activation and proliferation of donor CD4+ T cells and (ii) the metabolic fitness of donor CD8+ T cells are also enhanced by the activated donor P2X7 receptor [58, 59]. In addition, the activation of P2X7 on donor Tregs can reduce their suppressive ability and stability of Tregs, promoting their conversion to Th17 cells [60].
Inhibition of the P2X7 receptor is reported to mitigate aGVHD in conventional and humanised mouse models of aGVHD. Treatment of allogeneic HSCT recipient mice with the P2X7 inhibitor pyridoxalphosphate-6-azophenyl-2′,4′-disulfonic acid (PPADS) can increase the survival rate and the number of Tregs, and reduce the serum level of IFNγ and histological aGVHD [53, 54]. Administration of the P2X7 inhibitor brilliant blue G (BBG) to allogeneic HSCT recipient mice can also prevent weight loss and reduce inflammation in the liver and the production of inflammatory cytokines [56]. Furthermore, a crystal structure of the P2X7 receptor in complex with the inhibitor AZ10606120 has been reported (PDB: 5U1W) [61], and this structural information could be useful for the design and synthesis of novel P2X7 inhibitors which can be used in clinical settings.
The P2Y2 receptor is also reported to contribute to the pathogenesis of aGVHD [22, 57]. Evidence indicates that the number of cells expressing the P2Y2 receptor is increased in the intestinal tract in aGVHD-affected mice and that the increased P2Y2 expression enhances the severity of intestinal aGVHD [62]. Of note, knock-out allogeneic HSCT recipient mice of the P2Y2 receptor show an increased survival rate and decreased cytokine levels [62]. However, in the case where the P2Y2 receptor in donor cells is knocked out, no such improvement is observed [62]. In contrast, literature precedent suggests that the activation of the P2Y2 receptor can promote the migration of Tregs to sites of inflammation and thereby mitigate aGVHD [63]. Due to the dual functions of the P2Y2 receptor, targeting the P2Y2 receptor for the treatment has been challenging and there have been no reports about systemic injection of P2Y2 inhibitors/activators for the treatment of aGVHD [64].
While ATP is released in damaged tissues in allogeneic HSCT recipients and promotes inflammation, it is also degraded to adenosine by CD39 and CD73 [53]. In particular, a murine study indicates that CD39 and CD73 are highly expressed on CD150high Tregs [65]. As shown by a study using a mouse model of aGVHD, inhibition of CD39 and CD73 with adenosine 5′-(α,β-methylene)diphosphate (APCP) leads to the increase in the number of splenic CD4+ and CD8+ T cells, the serum levels of IFNγ and IL-6, and the mortality rate [66]. These data suggest that CD39 and CD73 play an alleviatory role in aGVHD. Evidence demonstrates that the production of adenosine by CD39 and CD73 results in the activation of the adenosine A2A receptor [66, 67, 68]. The activated A2A receptor can induce the expansion of donor Tregs and thereby mitigate aGVHD-induced inflammation [66, 67, 68]. The blockade of A2A with the antagonist SCH58261 exacerbates aGVHD by elevating the levels of TNFα, IFNγ, and IL-6 and the number of CD4+ and CD8+ T cells in sera [66]. In agreement with this report, the A2A agonist ATL-146e reduced weight loss and mortality in aGVHD-affected mice by (i) increasing serum IL-10 and reducing serum IFN-γ and IL-6, (ii) precluding the activation of splenic CD4+ and CD8+ T cells, and the infiltration of T cells into GVHD target organs [67]. Other A2A agonists, ATL-370 and ATL-1223, are reported to exert similar therapeutic effects on aGVHD [68]. Moreover, a crystal structure of the A2A receptor in complex with the activator ZM241385 has been reported (PDB: 5WF5) [69], and this structural information could facilitate the creation of novel A2A activators which can enter the clinic.
Although there are few to no reports about a link between purinergic signaling and cGVHD pathogenesis, activation of the P2X7 receptor is reported to promote fibroblast-to-myofibroblast transformation and contribute to the development of fibrosis [70]. The activation of the P2X7 receptor enhances Ca2+ influx and skews fibroblasts towards a fibrogenic phenotype, leading to augmented collagen production [70]. Considering fibrosis is a significant hallmark of cGVHD, the investigation into a correlation between purinergic signaling and fibroblast activity in cGVHD could open up a new window for the elucidation of mechanisms of cGVHD and the development of novel drugs for cGVHD (Figure 3). Furthermore, stress-induced cellular senescence in immune cells is reported to play a detrimental role in the pathogenesis of ocular cGVHD [71, 72], and a murine study indicates that the P2Y14 receptor modulates stress-induced cellular senescence in hematopoietic stem/progenitor cells [73]. Given these findings, the P2Y14 receptor may be a regulator of stress-induced cellular senescence in cGVHD, and development of agonists of the P2Y14 receptor could benefit cGVHD patients.
The Janus kinase/signal transducer and activator of transcription (JAK/STAT) signaling pathways are regarded as a central communication junction for the immune system [74]. In the JAK/STAT signaling pathways, the cytoplasmatic kinase JAKs interact with the transcription factor STATs, and more than 50 cytokines and growth factors are involved in the JAK/STAT signaling pathways [75]. Mammals have 4 JAKs (JAK1, JAK2, JAK3, JAK4) and 7 STATs (STAT1, STAT2, STAT3, STAT4, STAT5a, STAT5b, STAT6) [76], and the dysregulated JAK/STAT signaling pathways contribute to a variety of human diseases, which makes this signaling a promising drug target [77].
In the early phase of aGVHD, tissue damage due to the preconditioning regimen and the disease results in the release of DAMPs, leading to the increased expression of MHC on APCs at the infusion of donor cells [78]. Donor T cells are activated via direct or indirect allorecognition, and the activated donor T cells produce IFNγ to initiate the JAK/STAT signaling pathways through IFNγ receptors [78]. The resultant increase in the expression of the chemokine receptor CXCR3 on T cells enhances their migration to aGVHD target organs, which promotes tissue damage [79].
While clinical manifestations of cGVHD are different from those of aGVHD, they have similarities in some aspects of the pathogenic processes [80]. The JAK/STAT signaling pathways in the context of cGVHD have been intensively investigated [81]. Tregs play a crucial role in the reduction of cGVHD, and JAK1/JAK2 signaling pathways are thought to negatively regulate the development and proliferation of Tregs, as indicated by the fact that JAK2 inhibition can promote Treg proliferation [82, 83]. Tissue fibrosis is highly problematic in cGVHD, and M2-like macrophages producing TGF-β are presumably a key player [84]. IL-10 skews macrophages towards an M2-like phenotype through the IL-10 receptor-JAK1/STAT3 pathway [85]. Given these reports, it would be intriguing to investigate an association between macrophages and the JAK/STAT signaling pathways in the development of cGVHD-induced fibrosis.
Many researchers have focused on the development of inhibitors targeting JAK/STAT signaling pathways for the treatment of aGVHD and cGVHD [81]. As demonstrated by several preclinical data, inhibition of the JAK/STAT pathways can mitigate GVHD without affecting the GVL effect [81] Most recently, the JAK1/JAK2 inhibitor ruxolitinib has been approved by FDA for aGVHD and cGVHD. In 2019, FDA approved ruxolitinib to treat steroid-refractory aGVHD patients 12 years or older [86]. The clinical trials show that the day-28 overall response rate (ORR) was 100% for Grade 2 aGVHD, 40.7% for Grade 3 aGVHD, and 44.4% for Grade 4 aGVHD [86]. In 2021, FDA approval was also granted to ruxolitinib for the therapy of steroid-resistant cGVHD patients 12 years or older [87]. The clinical trial data demonstrate that the ORR was 70%, and the median durations of response, which were calculated from first response to progression, death, or new systemic therapies for cGVHD, were 4.2 months [87]. A crystal structure of JAK2 in complex with ruxolitinib is provided in the PDB database (PDB: 6VGL) [88], and this structural information could be useful for the design of more potent and selective JAK1/JAK2 inhibitors. Another promising JAK1 inhibitor is itacitinib [89]. Data from a phase 1 clinical trial of itacitinib shows that 70.6% of steroid-refractory cGVHD patients were treated in a satisfactory manner [90]. Furthermore, two clinical trials of itacitinib for cGVHD have recently commenced (ClinicalTrials.gov identifier: NCT04200365, NCT03584516). It is of great medical significance that novel drugs targeting the JAK/STAT signaling will continue to be developed for the treatment of aGVHD and cGVHD.
The transcription factor nuclear factor kappa B (NF-κB) controls the expression of various genes important for the induction of inflammatory responses in innate and adaptive immune cells [91]. NF-κB is a family of heterodimers or homodimers generated from different combinations of the following 5 proteins: p65/RelA, RelB, c-Rel, p105/p50 (NF-κB1), and p100/p52 (NF-κB2) [92]. Among them, the p50/p65 complex is thought to be the most abundant form of NF-κB dimer [93]. When NF-κB is inactive, it is retained in the cytoplasm by the IκB family of inhibitors [94, 95]. In response to a wide range of stimuli such as the proinflammatory cytokines IL-1 and TNF-α, IκB kinase (IKK) is activated to phosphorylate the 2 serine residues of IκBα [96]. The phosphorylation causes the 26S proteasome to induce the ubiquitination and degradation of IKβ. Subsequently, NF-κB is translocated into the nucleus and triggers gene transcription, leading to the production of proteins necessary for immune responses [97]. Thus, NF-κB is regarded as a therapeutic target for the treatment of various inflammatory diseases.
The NF-κB signaling pathways have captured increasing attention from GVHD researchers. It has been reported that the activation of RelB in APCs contributes to the expansion of donor Th1 cells and subsequent alloreactivity, which leads to the development of aGVHD [98]. The NF-kB signaling pathways can be survival and proliferation signals and contribute to B-cell alloantibody deposition and germinal center formation, which play a critical role in the pathogenic process of cGVHD [99, 100].
Bortezomib is an FDA-approved drug for the treatment of multiple myeloma and is known to be an indirect inhibitor of NF-κB [101]. A murine study suggests that aGVHD can be prevented by treatment with bortezomib early after allogeneic HSCT [102, 103]. Bortezomib is undergoing clinical trials for aGVHD (BMT CTN 1203), and the phase1/2 study shows that bortezomib can be used in combination with tacrolimus and methotrexate in a tolerable immunosuppressive regimen after allogeneic HSCT [104]. Bortezomib can also be effective for the treatment of cGVHD. NF-κB inhibition with Bortezomib is suggested to cause apoptosis of germinal center B cells during reconstitution, leading to the decrease in donor-derived B cell numbers and BAFF expression [103]. With these promising data, clinical trials of bortezomib for the treatment of steroid-refractory cGVHD are in progress (NCT01158105). At present, there are no NF-κB inhibitors approved by FDA for aGVHD or cGVHD. Generally, direct inhibitors are superior to indirect ones in terms of selectivity. Thus, novel direct NF-κB inhibitors with high selectivity are greatly anticipated for the treatment of GVHD.
The Hedgehog signaling pathways are involved in the regulation of cell proliferation, survival, and differentiation [105], and its aberrant activation contributes to detrimental events such as the self-renewal and metastasis of cancer stem cells [106]. In the absence of Hedgehog ligand (Hh), the activation of Smoothened (SMO) is inhibited by Patched (PTCH) [107]. Subsequently, the activity of glioma-associated oncogene homolog (Gli) is suppressed by a protein complex mainly composed of a suppressor of fused (SUFU), which phosphorylates Gli and prevents it from entering the nucleus. In the presence of Hh, the binding of Hh to PTCH precludes the SMO inhibition mediated by PTCH [107]. Activated SMO prevents phosphorylation of Gli mediated by the SUFU complex, leading to the migration of Gli to the nucleus and the induction of downstream target gene expression [107].
Fibrosis is a highly problematic feature of cGVHD, and a profibrotic activity of Hedgehog signaling in patients and mouse models of cGVHD has been reported [108]. Overexpression of Hh, which is an inducer of the Hedgehog signaling pathways, is observed in human and murine sclerodermatous cGVHD [108]. The downstream processes of the Hedgehog signaling pathway cause overexpression of Gli-1 and Gli-2, particularly in fibroblasts [109]. The abnormal expression of Gli-1 and Gli-2 may result in the overproduction of collagen and the resultant pathologic fibrosis in cGVHD target organs [109]. Furthermore, the Hedgehog signaling is suggested to contribute to the increase of profibrotic M2-like macrophages in the cGVHD-affected skin [109].
There are several inhibitors of the Hedgehog pathways. Among others, sonidegib, vismodegib, and glasdegib are SMO inhibitors approved by FDA for the treatment of basal cell carcinoma [110]. These 3 SMO inhibitors are currently undergoing clinical trials for cGVHD therapy (NCT02086513, NCT02337517, NCT04111497). According to a report of the Phase-1 trial of sonidegib, where 17 steroid-refractory cGVHD patients participated, protein expression of hedgehog signaling pathway molecules was decreased by treatment with sonidegib as judged by immunohistochemical evaluation of the skin [111]. With respect to the creation of novel SMO inhibitors for the treatment of GVHD, Lacroix et al. found a potential SMO inhibitor by performing structure-based virtual screening of 3.2 million available, lead-like molecules against Smoothened and subsequent biological validations of the top-ranked compounds [112]. This information could benefit the design and synthesis of more potent and selective inhibitors of SMO.
While elucidation of mechanisms of cGVHD is still elusive, chronic inflammation is characteristic of cGVHD [113]. Senescent macrophages contribute to ocular cGVHD in mice, and gray eyebrows, skin wrinkles and conjunctival cancer are observed in human cGVHD [71, 114]. These findings suggest that ageing in donor- and recipient-derived cells is induced in cGVHD [71]. Evidence suggests that chronic inflammation and age-related diseases are associated with the elevation of endoplasmic reticulum (ER) stress [115, 116]. Mukai et al found that ER stress was increased in organs affected by cGVHD in mice [117]. Treatment of cGVHD-affected mice with the known ER stress reducer 4-phenylburyric acid (PBA) resulted in mitigation of systemic inflammation and fibrosis induced by cGVHD [117]. Of note, PBA is approved by FDA for the treatment of urea cycle disorders, and its safety was proven [118]. Investigation at the cellular level indicates that ER stress contributes to fibrosis as well as inflammation induced by cGVHD. Elevated ER stress caused (i) the dysregulation of lacrimal-gland-derived fibroblasts and (ii) abnormal production of MCP-1/CCL2, IL-6, and connective tissue growth factor (CTGF) [117]. Suppression of ER stress with PBA reduced their abnormal production of the inflammatory and fibrotic molecules [117]. In addition, ER stress induced by cGVHD skewed splenic macrophages towards an M2-like phenotype, and treatment of them with PBA promoted their differentiation into an M1-like phenotype [117]. Several reports also indicate that the augmentation of M2-like macrophages is implicated in the progression of cGVHD [84, 119, 120]. M2-like macrophages are thought to contribute to the pathogenesis of fibrosis-associated diseases [121], and it seems to be the case with cGVHD. As these analyses were performed in a bulk population, further investigation will be needed. Macrophages and fibroblasts are known to be heterogeneous populations [122, 123, 124, 125]. In particular, mounting evidence suggests that macrophage heterogeneity is multidimensional and more complex than M1/M2 classification [126]. Hence, single-cell analyses could greatly facilitate the understanding of a correlation between ER stress and macrophages/fibroblasts in the development of cGVHD and make ER stress a more compelling therapeutic target for cGVHD therapy.
While aGVHD and cGVHD show different clinical manifestations, one of their common features is abnormal immune cell infiltration, which results in organ damage and severe inflammation and fibrosis. Mukai et al devised a novel therapeutic strategy for both types of GVHD by targeting vascular adhesion protein-1 (VAP-1) [127], which is known to be overexpressed in inflamed organs [128]. VAP-1 is an endothelial surface glycoprotein assisting leucocyte migration from the bloodstream to tissues and possesses the following 2 functional domains: a distal adhesion domain and a catalytic amine oxidase domain [129]. For infiltration into tissues, the amino group in leukocytes undergoes a nucleophilic attack on the carbonyl group in VAP-1 [129]. The subsequent catalytic conversion of the primary amine to the corresponding aldehyde allows immune cells to squeeze into tissues through blood vessels [129, 130]. Pursuant to their study with the use of a mouse model where aGVHD shifts to cGVHD [127], (i) the protein expression of VAP-1 is increased in organs with GVHD, where the number of inflammatory cells is accordingly augmented, (ii) blockade of VAP-1 with a novel inhibitor reduced the number of tissue-infiltrating leukocytes and thereby mitigated GVHD manifestations such as inflammation and fibrosis and (iii) the VAP-1 inhibition caused few to no severe adverse effects. Collectively, inhibition of VAP-1 could be an effective all-in-one approach for the treatment of aGVHD and cGVHD.
The Notch signaling pathways are cell-to-cell communication induced by interactions between Notch receptors (NOTCH1, NOTCH2, NOTCH3, and NOTCH4) and NOTCH ligands (Jagged1 (JAG1), JAG2, Delta-like 1 (DLL1), DLL3 and DLL4) [131]. Due to these intercellular interactions, the NOTCH receptor is proteolytically activated by an ADAM family metalloprotease and subsequently by the γ-secretase complex [132]. The sequential cleavages lead to the release of the intracellular NOTCH domain (NICD), which is a transcriptionally active fragment [133]. NICD migrates to the nucleus and binds to the DNA binding CSL/RBP-Jk factor, forming a transcriptional activation complex with a mastermind-like (MAML) family coactivator [133]. This final complex triggers the transcription of target genes which are important for biological processes such as proliferation, differentiation, and survival [134].
A correlation between the Notch signaling pathways and alloimmune responses has gained interest from GVHD researchers. Studies using animal models of aGVHD suggest that; (i) the Notch signaling promotes activation, differentiation, and alloreactivity of T cells [135] and (ii) dendritic cells with high DLL4 expression show an increase in the production of IFN-γ and IL-17 [136]. The Notch signaling is also implicated in the pathogenic process of cGVHD. A murine study shows that NOTCH1 and NOTCH2 as well as DLL1 and DLL4 serve significant functions in regulating proinflammatory cytokine production by T cells [137]. Investigation using
GVHD treatments by targeting the Notch signaling pathway have been reported. A series of experiments using a mouse model of aGVHD reveals; (i) inhibitors of γ-secretase block proteolytic activation of all the NOTCH receptors, but has severe toxicity in the gut epithelium, (ii) NOTCH1 inhibition using an antibody mitigates GVHD but causes serious toxicity and (iii) treatment with a combination of anti-DLL1 and anti-DLL4 reduces aGVHD without debilitating adverse effects while maintaining a GVL effect of donor T cells [139]. An anti-DLL1 antibody is also effective for the treatment of murine cGVHD in combination with an anti-DLL4 antibody [137]. Treatment with all-trans-retinoic acid (ATRA) prevents NOTCH2-induced BCR hyperresponsiveness, which plays a detrimental role in cGVHD pathogenesis [137]. It appears that NOTCH2 and DLL1/4 are promising drug targets for the treatment of the 2 types of GVHD. Therefore, it is highly anticipated that novel, selective inhibitors of NOTCH2 and DLL1/4 will be developed for use in human GVHD.
Rho-associated coiled-coil-containing protein kinases (ROCKs) are serine-threonine-specific protein kinases, and mammals have ROCK1 and ROCK2 [140]. ROCKs are downstream effector proteins of GTPase Rho, and abnormal activation of the Rho/ROCK pathways contributes to the development of various diseases [140]. In particular, ROCK2 is known to regulate (i) the balance of Th17 cells and Tregs and (ii) profibrotic pathways [141]. ROCK2 activation increases Th17 cell-specific transcription factors by promoting STAT3 phosphorylation [142]. In addition, when ROCK2 is activated by profibrotic mediators such as tumor growth factor-β (TGF-β), it causes myocardin-related transcription factors to activate profibrotic genes in fibroblasts [143, 144]. This profibrotic gene activation induces fibroblast-to-myofibroblast differentiation and the resultant increase in collagen production [143, 144].
A study using a cGVHD mouse model shows that treatment with belumosudil, which is a selective ROCK2 inhibitor, can substantially reduce cGVHD-induced fibrosis in the lung [145]. In 2021, belumosudil was approved by FDA for the treatment of cGVHD, and the clinical trial data show that the overall response rate was 75% (6% complete response and 69% partial response) [146].
ROCK1 is also thought to be involved in the development of fibrosis, and pan-ROCK inhibitors targeting ROCK1/2 are thereby expected to show better treatment outcomes for cGVHD [147]. Several pan-ROCK inhibitors have been granted approval for human use [148, 149, 150, 151] In particular, netarsudil has been approved by FDA for the treatment of glaucoma [151]. However, due to a lack of overall kinome selectivity of the reported dual ROCK1/2 inhibitors, there is still scope for improvement in pan-ROCK inhibitors [152]. Hu et al. has recently reported the synthesis and
While recent decades have seen significant technological and medical advances, aGVHD and cGVHD are still a major hurdle to successful allogeneic HSCT in clinical settings. Systemic corticosteroid therapy, with or without immunosuppressive agents, is the first-line treatment for GVHD, although it can cause severe adverse effects and approximately 50% of GVHD patients develop steroid-resistant GVHD. Thus, sophisticated treatments of steroid-refractory aGVHD and cGVHD are highly anticipated by medical settings. A great deal of effort has been invested in the elucidation of mechanisms of GVHD and development of safe and efficacious drugs for GVHD. Recently, several drugs have been approved by FDA for the treatment of steroid-refractory aGVHD and cGVHD. Despite this progress, there is still a need to create novel drugs with better efficacy for GVHD therapy. This chapter focused on druggable targets for the treatment of GVHD with an aim to stimulate various GVHD researchers (from medicinal chemists to biologists) to create novel drugs which can enter the clinic. While several signaling pathways have been intensively studied in the context of GVHD, there are underexplored signaling pathways. In particular, the purinergic signaling pathway is one of the understudied signaling pathways in GVHD. The P2X7, A2A, and P2Y14 receptors seem to be compelling drug targets for the treatment of GVHD, and clinical settings could benefit from safe and efficacious (i) inhibitors of the P2X7 receptor and (ii) activators of the A2A and/or P2Y14 receptors. However, the development of new drugs is a costly and time-consuming process. To overcome this setback, the use of AL/ML has captured great interest from many researchers and has been expected to substantially reduce the cost and time of drug development. A combination of AL/ML and molecular design could greatly facilitate the development of novel, effective, safe, and affordable drugs for the treatment of GVHD.
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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. 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He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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