Preface

Nanoporous materials are porous solids that possess pores in the range of 0.2 nm up to 50 nm, for example zeolites and zeolite-like materials, mesoporous oxides such as silica, metal organic frameworks, pillared clays, porous carbons, and related materials. These materials provide unique template platforms for the synthesis of other nanostructures with controlled geometric features. Nanoporous materials are outstanding due to their unique chemical and physical properties such as high specific surface areas, well-defined pore sizes, and functional sites, which make them suitable candidate for a plethora of applications, including catalysis, energy harvesting and storage, photonics and optoelectronics, nanomedicine, sensing etc.

This book is a collection of comprehensive chapters of lasting value to the field. The contributions cover all aspects of nanoporous materials, including their preparation, structure, post-synthetic modification, characterization, and potential applications. The book covers the new trends and challenges in the synthesis and surface engineering of a wide range of nanoporous materials. All the chapters are written by professionals that make this book an especially valuable and reliable source of information. To illustrate the scope of nanoporous materials, the chapters are presented with simple diagrams, charts, and graphs. We hope this book will benefit the scientists and engineers to enhance the understanding of nanoporous materials to a new level and its subsequent utilization to accelerate the advancement in technology. We are deeply thankful to the authors for their hard work and contributions. We wish to express our gratitude to the staff of IntechOpen publishers for their patience during the development of this project and for encouraging us during the various stages of preparation. Without all this support, it would not have been possible for us to publish this book.

#### **Mohsen Sheikholeslami Kandelousi**

Babol Noshirvani University of Technology, Islamic Republic of Iran

#### **Sadia Ameen**

Advanced Materials and Devices Laboratory, Department of Bio-Convergence Science, Jeongeup Campus, Jeonbuk National University, Republic of Korea

#### **M. Shaheer Akhtar**

New & Renewable Energy Material Development Center (NewREC), Jeonbuk National University, Republic of Korea


**4. Evaluation experiment**

In the survey report on study trend published in 2004, Tatsubori et al. used the publication databases of IBM to survey the research trend of software architecture after 1999. They manually extracted 51 major papers [8]. In this study, we examine how well the automated method can extract the major papers that were manually extracted by experts.

Academic Landscape Based on Network Analysis

as major papers.

**5. Conclusion**

**6. References**

et al. for quantitative evaluation of research trend.

Fig. 6. An image of extraction of papers by SciHi

task we will examine these papers to see what meaning they have.

Considering Analysis of Variation in the Years of Lucubration Publishing 377

30, 32~39, 41~43 and 49~51). Regarding five roles in Fig.5., we manually made minute adjustment for SciHi (see Fig.6.) because they were an original classification set by Tatsubori

As shown in Fig.6., visualization result by the page rank algorithm (hereafter, it is referred as this algorithm) with the variance value of a target paper taken into consideration as weight showed all the 23 papers were extracted as major papers. Especially, the papers (44~58 in Fig.6.) were extracted manually by Tatsubori et al. and all of them were extracted

Thus, this algorithm can automatically extract major papers that are the same papers manually extracted by experts. However, SciHi extracted major papers that were not extracted by Tatsubori et al. such as a large (green) node in the cluster of [R]. As a future

In this study on the network analysis of quoted academic papers, we tried automated extraction of major papers in each one of the fields identified by clustering. Specifically, we analyzed the variance of the release years of papers quoting the target paper; applied the result to the page rank algorithm to calculate the importance of the target paper. Then, we examined how well the automated method can extract the major papers that were extracted by experts by comparing the result with the report on research trend in the software architecture field that was published by Tatsubori et al. in 2004. As a result, this algorithm could extract all the target papers as major papers. In other words, this algorithm could automatically extract major papers with the same result as what experts manually obtained. Last of all, in our experiment for evaluation, SciHi also extracted major papers that experts

did not manually. As a future task we will examine what these papers mean.

[1] R・J・Wilson .(2001). *Introduction to Graph Theory*, Kindai Kagaku Sha Co.,Ltd.

*networks*, Physical Review E, Vol. 69.

[2] M. E. J. Newman and M. Girvan.(2004). *Finding and evaluating community structure in*

Tatsubori et al. used GoogleScholar to obtain the number of quotations for each year and extracted top 40 papers in a year. In addition to them, they extracted 11 more papers about software architecture by identifying international conferences that they thought particularly important, resulting in 51 major papers. Furthermore, they adopted a unique classification method in order to evaluate study trend quantitatively. Specifically, they classified 51 papers by defining each paper focused on which one of the following five roles that software architecture played in software development process. Fig.5. shows the classification result.

Fig. 5. An image of classification of papers by five roles of software architecture

Fig.6. shows the major papers extracted by SciHi in a similar manner to that of Tachibori et al. Fig.5. and Fig.6. both indicate the paper numbers.

The following describes the way of extraction by SciHi: We used SCOPUS as publication databases. Then, we selected "Software Architecture" for query and "1999 to 2004" for the period for extraction of papers. Among 51 papers, 28 papers were not included because they did not exist in SCOPUS (see the papers numbers in Fig.5. : 1, 5, 12~14, 16~19, 21, 24, 27, 29,

30, 32~39, 41~43 and 49~51). Regarding five roles in Fig.5., we manually made minute adjustment for SciHi (see Fig.6.) because they were an original classification set by Tatsubori et al. for quantitative evaluation of research trend.

As shown in Fig.6., visualization result by the page rank algorithm (hereafter, it is referred as this algorithm) with the variance value of a target paper taken into consideration as weight showed all the 23 papers were extracted as major papers. Especially, the papers (44~58 in Fig.6.) were extracted manually by Tatsubori et al. and all of them were extracted as major papers.

Thus, this algorithm can automatically extract major papers that are the same papers manually extracted by experts. However, SciHi extracted major papers that were not extracted by Tatsubori et al. such as a large (green) node in the cluster of [R]. As a future task we will examine these papers to see what meaning they have.

Fig. 6. An image of extraction of papers by SciHi


**5. Protein liaison in tethering to ER and mitochondria**

control and BK transfected hair cells. The 50 μg of proteins were mixed with sample buffer and loaded in IEF gel strips. IEF will be performed using 7 cm immobilized pH gradient (IPG) gel strip, pH 3–10 (Protean IEF Cell System, Bio-Rad). Proteins were resolved by IEF in the first dimension and SDS-PAGE (12% acrylamide) in the second dimension. Precision Plus (Bio-Rad) molecular weight marker was used to determine relative mobilities. Gels were stained with silver staining and images were captured using the Molecular Imager versa doc MP Imaging System (Bio-Rad). The resolution of the scanning gel was 53 μm, and images were processed with the standard version of PDQUEST software (Bio-Rad), which is used to identify spots by pi and molecular weight with the help of standards. The BKα transfected protein gel is compared with control gel and qualitative differences of appeared (up-regulated proteins) and disappeared (down-regulated proteins) protein spots were excised and subjected to reduction, alkylation, and trypsin digestion as described previously [19]. Peptides were extracted and concentrated under vacuum centrifugation. The peptides of each sample

The mitochondria consists of two membranes viz. an outer mitochondrial membrane (OMM) and inner mitochondrial membrane (IMM) which have several convoluted foldings called as cristae. The shape of mitochondria is very heterogeneous in living cells from sphere to interconnected tubules [20]. The formation of mitochondrial network is well documented by the continuous movements of mitochondria by motor proteins. During the mitochondrial movements rarely two mitochondria encounter each other to form fuse [20]. Sometimes the mitochondrial tubules can undergo fission to form two or more mitochondrial units. However, both mitochondrial processes are much complicated because of the coordination of fusion and fission of four lipid bilayers. The first mitochondrial fusion protein Fuzzy onions 1 protein (Fzolp) was identified in *Drosophila melanogaster* [21]. Later two Fzolp homologus mitofusin 1 (MFN1) and mitofusin 2 (MFN2) were identified from mammals [22]. The MFN1 and MFN2 have very high 81% homology and both are localized in the outer mitochondrial membrane [23]. These proteins are formed by the docking of two juxtaposed mitochondrial fusion through their transmembrane spanning region [24]. During the mitochondrial fission

both Fis1 and dynamin-related protein1 (Drp1) play a vital role in mammals [25].

The endoplasmic reticulum is an extensive network of cisternae and microtubules and stretches from the nuclear envelop to the plasma membrane of all eukaryotic cells occupying 10% of the total cell volume [26]. The ribosomes bind to the peripheral of ER and to the nuclear envelope comprising the rough ER and ribosome-free is called as smooth ER. The peripheral ER consists of sheath-like cisternae and the thickness of the sheets and diameter of the tubules ranges from 60–100 nm. ER and microtubule associated proteins play a predominant role in shaping of mammalian cells [27]. The cytoskeleton membrane proteins 63 kDa (CLIMP63), VAP-B/Nir3 couple and p22 are involved with dynamics of ER and microtubule [28]. CLIMP63 is an integral peripheral ER membrane proteins which is anchoring of ER to microtubules and maintains the spatial distribution of ER network. The p22 has myristoylated EF-hand protein binds microtubule in a Ca2+ dependent manner and providing a link between

were injected into LC–MS/MS then identification of each protein spots.

**4. Structural link between ER and mitochondria**

60 Current Understanding of Apoptosis - Programmed Cell Death

Close contact between the membrane of ER and outer mitochondrial membrane was first identified in late 1960 by several independent groups [32]. ER membranes co-purifying with mitochondrial fractions were observed under electron microscopy which, revealed that direct communication between cisternal space of ER and inner mitochondrial membrane (IMM) space [33]. The 20% of mitochondrial surface were direct contact with ER and each contact appears to vary between 10 to 25 nm in length [34]. The functional importance of these two organelles contact sites is further established by the quasi-synaptic mechanism of transmission of Ca2+ crucial function of during apoptosis.

The nature of ER–mitochondrial tethering has remained largely elusive. Szabadkai et al. [35] reported that IP3R is localized on membrane of ER and VDAC is localized on the OMM and both are physically attached through 75 kDa glucose-regulated proteins (GRP 75) (**Figure 2**). IP3R play a major role on the mobilization of calcium from ER to mitochondria as a function of apoptosis [36]. During steady-state transfer of Ca2+ molecules from ER to mitochondria, the mitochondrial anti-apoptotic proteins Bcl2 is drastically reduced [37]. The phosphofurin acidic cluster sorting protein-2 (PACS)-2 is also involved in the regulation of apoptosis

**Figure 2.** Tethers between ER and mitochondria.

through induces Bid translocation to mitochondria [38]. The first direct ER-mitochondrial tethering proteins are Mfn1 and Mfn2 [39]. They are localized on both organelles membrane and close contact point between the organelles. In addition, they are involved in maintaining the shape of both organelles. Moreover the regular juxtaposition of ER and mitochondria is the cytoskeletal network [40]. Both the organelles were bound with microtubules (MTs) and actin cytoskeleton that provide a scaffold that stabilizes the contact points between the compartments [41]. Recently identified mitostatin protein is binds with keratin and intermediate filaments that inhibits the juxtaposition of ER and mitochondria.

the mitochondrial associated-ER membrane (MAMs) to regulate calcium signaling of CICR and cell death. However, we are only beginning to understand the spatial organization and interorganellar signaling in between ER and mitochondria and their functional regulations. Mitochondria-associated ER membranes (MAMs) control Ca2+ influx between ER and mitochondrial subunit. We found that BKα subunits [2] localized in the inner mitochondrial membrane directly interact with other BKAPs like IP3R, calreticulin at the ER face of the MAMs. The molecular chaperone, glucose-regulated-protein 78 (grp78), is linked with inositol 1,4,5 triphosphate receptor-1 (InsP3R-1) and voltage-dependent anion channel (VDAC-1) of the outer mitochondrial membrane (**Figure 2**) [42]. Both Ca2+ overload and depletion of the ER Ca2+ pool can result in changes of two signaling pathways of unfolding protein response (UPR) and ER overload response (EOR) [43]. Latter induces mitochondrial membrane permeabilization (MMP), opening of the permeability transition pore (PTP), and release of cytochrome c and subsequent engagement of the mitochondrial apoptotic pathway [44]. The Ca2+-sensitive dehydrogenases of the Krebs cycle [45] are stimulated as increased mitochondrial Ca2+ boosts ATP production. Increasing ATP production leads to more leakage of free electrons, causing the formation of superoxides. The resulting oxygen ions, free radicals, and peroxides are collectively called reactive oxygen species (ROS), which are effective to damage DNA and apoptosis. ER membrane BK channels play a predominant role in ER retention, retrieval and normal trafficking [46]. InsP3R and BK channels are localized in the same hotspot region of glioma cells of lipid raft however; they are not directly interacting with each other [47]. The InsP3R are tightly linked with BK channel through continuous releasing of Ca2+ molecules in organelles and they are bind with EF-hand motif of Ca2+ bowl and activate BK channel to release the K+

The Role of Calcium-activated Potassium Channel in Mitochondria-Associated ER Membrane…

http://dx.doi.org/10.5772/intechopen.77329

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The cellular Ca2+ ion are transported through the plasma membrane by receptor and voltagesensitive channels. Once inside the cell, Ca2+ can either interact with Ca2+ binding proteins or sequestered into the ER or mitochondria. Both Ca2+ overload and depletion of the ER Ca2+ pool can result in changes of protein folding and an increase of ER stress by either unfolding protein response (UPR) or ER overload response (EOR) [42]. From these two responses, both incorrectly folded and accumulated proteins are eliminated through apoptosis [48]. Ca2+ depleted from the ER is then taken up by the mitochondria, leading to Ca2+ overload in this organelle. The latter induces mitochondrial membrane permeabilization (MMP), opening of the permeability transition pore (PTP), and release of cytochrome c and subsequent engagement of the mitochondrial apoptotic pathway [44]. The increasing mitochondrial Ca2+ boots ATP production leading to more leakage of free electrons, which results in the formation of superoxides. These oxygen ions, free radicals, and peroxides, collectively called ROS, damage DNA and leads to apoptosis. Reactive oxygen species (ROS) play a key role in mechanism for induction of cochlear damage under various patho-physiological conditions [2]. Caspase-12 is localized in ER and activated

by ER stress, including the accumulation of excess proteins that leads to cell death.

BK channel is involved in the regulation of pro-apoptosis in mouse cochlear hair cells. A group of proteins is involved in the regulation of mitochondria-associated ER membrane

ion (K+

efflux).

**7. Conclusions**