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- 저자 : Shailendra (검색결과 85 건)
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Shailendra Kapoor 대한흉부외과학회 2013 Journal of Chest Surgery (J Chest Surg) Vol.46 No.2
I read with great interest the recent article by Kim et al. [1]. Interestingly, alpha-lipoic acid has recently been shown to exert anti-neoplastic effects in a number of systemic tumors other than lung carcinomas. For instance, alpha-lipoic acid exerts anti-neoplastic effects in colon carcinomas. DHL-HisZnNa is a newer alpha-lipoic acid derivative that has shown similar anti-neoplastic effects in colon cancer cell lines [2]. Levels of retinoblastoma protein are attenuated by DHL-HisZnNa while a simultaneous accentuation of p21 levels is seen. Similarly, anti-proliferative effects have been seen in hepatocellular carcinomas following the administration of alpha-lipoic acid in conjunction with caffeic acid and a new synthesized lipoyl-caffeic conjugate. This combination results in enhanced interleukin 10 levels and attenuated tumor necrosis factor-a levels. Similarly, alpha-lipoic acid derivatives such as CPI-613 demonstrate anti-neoplastic effects in pancreatic malignancies by disrupting the mitochondrial metabolism in tumor cells resulting in accentuated apoptosis in these cells. For instance, Schwartz et al. [3] have recently reported the case of an 80-year-old female with pancreatic adenocarcinoma and hepatic metastases who responded favorably to a treatment regimen in which the efficacy of gemcitabine was enhanced by using a combination of hydroxycitrate in conjunction with alpha-lipoic acid. Hydroxycitrate and alpha-lipoic acid combinations also exert anti-proliferative effects in mouse bladder carcinoma-2 cell line bladder transitional cell carcinoma lines, which is equivalent to the anti-neoplastic effects exerted by conventional chemotherapeutic agents such as 5-fluorouracil [4]. Similarly, alpha-lipoic acid exerts anti-proliferative effects in breast carcinomas. These anti-neoplastic effects are mediated by its attenuating effect on matrix metalloproteinase (MMP)-2 and MMP-9 levels. It not only down-regulates the expression of these molecules but also decreases their activity. In particular, it decreases cellular migration and cellular motility, resulting in decreased metastases. Besides this, it also alters the Bax/Bcl-2 ratio [5]. A simultaneous increase in p27 (kip1) expression is seen, resulting in accentuated apoptosis in breast malignancies. Alpha-lipoic acid also demonstrates benefits in the management of dermatological malignancies. It exerts these effects by inhibiting proliferation and by accentuating apoptosis in these tumors. It also enhances the apoptosis of cells with aberrant nuclei, thus further attenuating tumor growth in these malignancies. These effects have been seen particularly in B16-F10 melanoma cell lines [5]. The above examples clearly illustrate the anti-neoplastic effects of alpha-lipoic acid and the need for further studies to assess its potential efficacy in the management of other systemic tumors.
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Smart Deployment of Sensor Nodes Using SA & GFA
Shailendra Singh,Deepa verma 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.2
In wireless sensor networks, network connectivity problems and sensor coverage are mainly affected by the restricted communication and sensing range of the nodes. To solve all these problems, many studies have been undertaken till now but most of these works is limited to be applied to the real environments because these do not consider various environmental factors that affect wireless sensor network deployment. In this paper, we propose a node deployment strategy that considers environmental factors and the number of nodes for surveillance .Deployment of the sensor nodes, and relay nodes considering all features of the surveillance and reconnaissance sensor networks as well as environmental factors. Smarty deploying the sensor nodes is very important if we are considering the performance of wireless sensor nodes (wsn). This paper focuses on real time deployment of sensor nodes using unmanned aerial vehicle (UAV). Smart deployment has importance in battlefield surveillance, disaster monitoring, environmental and habitat monitoring etc. It plays a very important role mainly in disasters affecting areas like flood affected or fire affected forests for sensing different conditions and physical data out there. The objective of this paper is to deploy sensor nodes smartly only in terrain of interest not in fire or water so that it can conserve environment and can reduce the loss of sensor nodes from being deploy in fire or water. Image segmentation of the images captured by camera situated on a board of UAV.. Comparison of these optimization tools SA and GFA are presented here for different images. Simulation results show that GFA performs better than SA when compared with no. of individuals and SA is faster than GFA.
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Troglitazone and tumor inhibition: an evolving concept in the management of systemic malignancies
Shailendra Kapoor 대한방사선종양학회 2012 Radiation Oncology Journal Vol.30 No.4
The recent article by An et al. [1] provided for highly stimulating reading. Interestingly, recent data suggests that troglitazone may attenuate tumor growth in a number of systemic malignancies besides accentuating the radio-sensitivity of cervical carcinomas. For instance, troglitazone attenuates tumor growth in gastric malignancies. It mediates this role by modulating the early growth response protein 1 (EGR-1) pathway. It accentuates nonsteroidal anti-inflammatory drug-activated gene 1 (NAG-1) expression within the cancerous cells [2]. As a result it augments intra-tumoral apoptosis within the gastric carcinomas. These effects are time dependent. Similar effects have been seen in colon carcinomas; it mediates this role by accentuating nuclear factor kappa B (NFκB) inactivation via attenuation of glycogen synthase kinase (GSK)-3β activity within the tumor cells. Intra-tumoral Bax levels are accentuated. As a result apoptosis is markedly augmented [3]. Cyclin B1 and cyclin D1 levels are attenuated. G0/G1 phase arrest is typically seen. Caspase-9 levels are typically accentuated. Troglitazone also decreases FLIP activity and thereby increase the sensitivity of the colon cancer cells to TRAIL induced apoptosis [4]. The anti-neoplastic activity of troglitazone is augmented by loss of X-linked inhibitor of apoptosis protein (XIAP) [5]. Similarly, troglitazone decreases tumor growth in breast cancers. It mediates this role by attenuating human telomerase reverse transcriptase (hTERT) expression within the mammary malignancies [6]. Telomerase activity is markedly reduced. Cdk2 and Cdk4 levels are markedly attenuated. As a result, increased G1 phase arrest is typically seen. In addition, it inhibits histone deacetylase resulting in attenuated phosphatidylinositol 3-kinase (PI3K) signaling [7]. p27 levels are accentuated [8]. These effects are dose dependent. Similar effects are seen in prostate malignancies. Troglitazone primarily exerts these anti-neoplastic effects by accentuating intra-tumoral inactivation of NFκB. It mediates this role by suppression of GSK-3β expression [9]. Troglitazone also mediates this role by augmenting Erk phosphorylation within the cancerous cells. It also modulates p21 and c-myc expression [10]. It down-regulates expression of c-myc. As a result there is increased G0/G1 phase arrest [11]. These effects have been seen both in vivo and in vitro. The above examples clearly illustrate the significant anti-neoplastic activity of troglitazone and the need for further studies in this regard.
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Size-effect of fracture parameters for crack propagation in concrete: a comparative study
Shailendra Kumar,S.V. Barai 사단법인 한국계산역학회 2012 Computers and Concrete, An International Journal Vol.9 No.1
The size-effect study of various fracture parameters obtained from two parameter fracture model, effective crack model, double-K fracture model and double-G fracture model is presented in the paper. Fictitious crack model (FCM) for three-point bend test geometry for cracked concrete beam of laboratory size range 100-400 mm is developed and the different fracture parameters from size effect model, effective crack model, double-K fracture model and double-G fracture model are evaluated using the input data obtained from FCM. In addition, the fracture parameters of two parameter fracture model are obtained using the mathematical coefficients available in literature. From the study it is concluded that the fracture parameters obtained from various nonlinear fracture models including the double-K and double-G fracture models are influenced by the specimen size. These fracture parameters maintain some definite interrelationship depending upon the specimen size and relative size of initial notch length.
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Cyber Attack Detection System based on Improved Support Vector Machine
Shailendra Singh,Sanjay Silakari 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.9
This paper presents a novel cyber attack classification approach using improved Support Vector Machine (iSVM) by modifying Gaussian kernel. The Support Vector Machine (SVM) is based on machine learning technique known to perform well at various pattern recognition tasks; such as image classification, text categorization and handwritten character recognition. The cyber attack detection is basically a pattern classification problem, in which classification of normal pattern is done from the abnormal pattern (attack). Although, traditional SVM is better classifier in terms of fast training, scalable and generalization capability. Performance of traditional SVM is enhanced in this work by modifying Gaussian kernel to enlarge the spatial resolution around the margin by a conformal mapping, so that the separability between attack classes is increased. It is based on the Riemannian geometrical structure induced by the kernel function. In the proposed method, class specific Cyber Attack Detection System which combines feature reduction technique and improved support vector machine classifier. This technique has two phases, in the first phase we reduced the redundant features of the original KDDCUP2009 dataset by Generalized Discriminant Analysis (GDA). In the second phase we used improved Support Vector Machine (iSVM) classifier to classify the reduced dataset obtained from first phase. Result shows that iSVM gives 100% detection accuracy for Normal and Denial of Service (DOS) classes and comparable to false alarm rate, training, and testing times.
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