Biological Networks: Modeling and Structural Analysis

Biological networks are receiving increased attention due to their importance in understanding life at the cellular level. There exist many different kinds of biological networks, and different models have been proposed for them. In this dissertation we focus on suitable network models for representing experimental data on protein interaction networks and protein complex networks (protein complexes are groups of proteins that associate to accomplish some function in the cell), and to design algorithms for exploring such networks. Our goal is to enable biologists to identify the general principles that govern the organization of protein-protein interaction networks and protein complex networks. For protein complex networks, we propose a hypergraph model which more accurately represents the data than earlier models. We define the concept of k-cores in hypergraphs, which are highly connected subhypergraphs, and design an algorithm for computing k -cores in hypergraphs. A major challenge in computational systems biology is to understand the modular structure of biological networks. We construct computational models for predicting functional modules through the use of graph clustering techniques. The application of earlier graph clustering techniques to proteomic networks does not yield good results due to the high error rates present, and the small-world and power-law properties of these networks. We discuss the various requirements that clusterings of biological networks are required to satisfy, design an algorithm for computing a clustering, and show that our clustering approach is robust and scalable. Moreover, we design a new algorithm to compute overlapping clustering rather than exclusive clustering. Our approach identifies a set of clusters and a set of bridge proteins that form the overlap among the clusters. Finally we assess the quality of our proposed clusterings using different reference sets

The effect of foliar application of methanol on productivity and fruit quality of grapevine cv. Flame Seedless

Field experiments were conducted in 2002 and 2003 on 6-year-old grapevine cv. Flame Seedless. The content of chlorophyll a and b, carotenoids and total carbohydrates increased after methanol application. Foliar application of aqueous methanol was very effective increasing the number of leaves per shoot and leaf area. Furthermore, 30 % methanol increased significantly the number of stomata of developing leaves at the first application time (shoot length: 20-30 cm) while 10, 30, 40 and 50 % methanol solutions were more effective at the second application date (prebloom). Increasing the chlorophyll content, the leaf area and the number of stomata per unit leaf area by methanol application increased net productivity of vines. There was a highly significant positive correlation between total yield, chlorophyll and carbohydrates content. Generally, all methanol treatments significantly increased length and diameter of shoots and internode length at both application dates. Application of methanol increased total soluble solids (TSS), the TSS/acid ratio and total anthocyanins in berry skins but decreased total acidity. Most significant effects were obtained by spraying 30 % methanol at the two application dates.

Security Enhancement of IoT and Fog Computing Via Blockchain Applications

Blockchain technology is now becoming highly appealing to the next generation because it is better tailored to the information age. Blockchain technologies can also be used in the Internet of Things (IoT) and fog computing. The development of IoT and Fog Computing technologies in different fields has resulted in a major improvement in distributed networks. Blockchain technology is now becoming highly appealing to the next generation because it is better tailored to the information age. Blockchain technologies can also be used in IoT and fog computing.  The blockchain principle necessitates a transparent data storage mechanism for storing and exchanging data and transactions throughout the network. In this paper, first, we explained Blockchain, its architecture, and its security. Then we view Blockchain application in IoT security. Then we explained Fog computing, Generic Security Requirements for Fog Computing, and we also discuss Blockchain applications that enhance Fog Computing Security. Finally, we conduct a review of some recent literature on using Blockchain applications to improve the security of IoT and fog computing and a comparison of the methods proposed in the literature

The Shigella ProU system is required for osmotic tolerance and virulence : Shigella ProU in osmotic tolerance and virulence

To cope with hyperosmotic stress encountered in the environments and in the host, the pathogenic as well as non-pathogenic microbes use diverse transport systems to obtain osmoprotectants. To study the role of Shigella sonnei ProU system in response to hyperosmotic stress and virulence, we constructed deletion and complementation strains of proV and used an RNAi approach to silence the whole ProU operon. We compared the response between wild type and the mutants to the hyperosmotic pressure in vitro, and assessed virulence properties of the mutants using gentamicin protection assay as well as Galleria mellonella moth larvae model. In response to osmotic stress by either NaCl or KCl, S. sonnei highly up-regulates transcription of proVWX genes. Supplementation of betaine greatly elevates the growth of the wild type S. sonnei but not the proV mutants in M9 medium containing 0.2 M NaCl or 0.2 M KCl. The proV mutants are also defective in intracellular growth compared with the wild type. The moth larvae model of G. mellonella shows that either deletion of proV gene or knockdown of proVWX transcripts by RNAi significantly attenuates virulence. ProU system in S. sonnei is required to cope with osmotic stress for survival and multiplication in vitro and ex vivo, and for infection

Toward fabrication of devices based on graphene/oxide multilayers

Owing to its high electrical conductivity, low density, and flexibility, graphene has great potential for use as a building block in a wide range of applications from nanoelectronics to biosensing and high-frequency devices. For many device applications, it is required to deposit dielectric materials on graphene at high temperatures and in ambient oxygen. This has been proven to be highly challenging because these conditions cause significant degradation in graphene. In this work, we investigate the degradation of graphene at elevated temperatures in an oxygen atmosphere and possible protection mechanisms to enable the growth of oxide thin films on graphene at higher temperatures. We show that coating graphene with self-assembled monolayers of hexamethyldisilazane (HMDS) prior to a high-temperature deposition can significantly reduce the damage induced. Furthermore, a graphene sample treated with HMDS displayed a weaker doping effect due to weak interaction with oxygen species than bare graphene, and a much slower rate of electrical resistance degradation was exhibited during annealing. Thus, it is a promising approach that could enable the deposition of metal oxide materials on graphene at high temperatures without significant degradation in graphene quality, which is critical for a wide range of applications

Carnosol induces ROS-mediated beclin1-independent autophagy and apoptosis in triple negative breast cancer

Background: In this study we investigated the in vitro and in vivo anticancer effect of carnosol, a naturally occurring polyphenol, in triple negative breast cancer.Results: We found that carnosol significantly inhibited the viability and colony growth induced G2 arrest in the triple negative MDA-MB-231. Blockade of the cell cycle was associated with increased p21/WAF1 expression and downregulation of p27. Interestingly, carnosol was found to induce beclin1-independent autophagy and apoptosis in MDA-MB-231 cells. The coexistence of both events, autophagy and apoptosis, was confirmed by electron micrography. Induction of autophagy was found to be an early event, detected within 3 h post-treatment, which subsequently led to apoptosis. Carnosol treatment also caused a dose-dependent increase in the levels of phosphorylated extracellular signal-regulated kinase 1 and 2 (pERK1/2). Moreover, we show that carnosol induced DNA damage, reduced the mitochondrial potential and triggered the activation of the intrinsic and extrinsic apoptotic pathway. Furthermore, we found that carnosol induced a dose-dependent generation of reactive oxygen species (ROS) and inhibition of ROS by tiron, a ROS scavenger, blocked the induction of autophagy and apoptosis and attenuated DNA damage. To our knowledge, this is the first report to identify the induction of autophagy by carnosol.Conclusion: In conclusion our findings provide strong evidence that carnosol may be an alternative therapeutic candidate against the aggressive form of breast cancer and hence deserves more exploration.Scopu

Facile biosensors for rapid detection of COVID-19

Currently the world is being challenged by a public health emergency caused by the coronavirus pandemic (COVID-19). Extensive efforts in testing for coronavirus infection, combined with isolating infected cases and quarantining those in contact, have proven successful in bringing the epidemic under control. Rapid and facile screening of this disease is in high demand. This review summarises recent advances in strategies reported by international researchers and engineers concerning how to tackle COVID-19 via rapid testing, mainly through nucleic acid- and antibody- testing. The roles of biosensors as powerful analytical tools are emphasized for the detection of viral RNAs, surface antigens, whole viral particles, antibodies and other potential biomarkers in human specimen. We critically review in depth newly developed biosensing methods especially for in-field and point-of-care detection of SARS-CoV-2. Additionally, this review describes possible future strategies for virus rapid detection. It helps researchers working on novel sensor technologies to tailor their technologies in a way to address the challenge for effective detection of COVID-19

Frequency-Tunable and Pattern Diversity Antennas for Cognitive Radio Applications

Frequency-tunable microstrip antennas, for cognitive radio applications, are proposed herein. The approach is based on tuning the operating frequency of a bandpass filter that is incorporated into a wideband antenna. The integration of an open loop resonator- (OLR-) based adjustable bandpass filter into a wideband antenna to transform it into a tunable filter-antenna is presented. The same technique is employed to design a cognitive radio pattern diversity tunable filter-antenna. A good agreement between the simulated and measured results for the fabricated prototypes is obtained. The radiation characteristics of each designed tunable filter-antenna are included herein