13 resultados para HOST-MISTLETOE INTERACTION NETWORK
em Digital Commons at Florida International University
Resumo:
Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen. Several antibiotic resistant strains of P. aeruginosa are commonly found as secondary infection in immune-compromised patients leaving significant mortality and healthcare cost. Pseudomonas aeruginosa successfully avoids the process of phagocytosis, the first line of host defense, by secreting several toxic effectors. Effectors produced from P. aeruginosa Type III secretion system are critical molecules required to disrupt mammalian cell signaling and holds particular interest to the scientists studying host-pathogen interaction. Exoenzyme S (ExoS) is a bi-functional Type III effector that ADP-ribosylates several intracellular Ras (Rat sarcoma) and Rab (Response to abscisic acid) small GTPases in targeted host cells. The Rab5 protein acts as a rate limiting protein during phagocytosis by switching from a GDP- bound inactive form to a GTP-bound active form. Activation and inactivation of Rab5 protein is regulated by several Rab5-GAPs (GTPase Activating Proteins) and Rab5-GEFs (Rab5-Guanine nucleotide Exchange Factors). Some pathogenic bacteria have shown affinity for Rab proteins during infection and make their way inside the cell. This dissertation demonstrated that Rab5 plays a critical role during early steps of P. aeruginosa invasion in J774-Eclone macrophages. It was found that live, but not heat inactivated, P. aeruginosa inhibited phagocytosis that occurred in conjunction with down-regulation of Rab5 activity. Inactivation of Rab5 was dependent on ExoS ADP-ribosyltransferase activity, and more than one arginine sites in Rab5 are possible targets for ADP-ribosylation modification. However, the expression of Rin1, but not other Rab5GEFs (Rabex-5 and Rap6) reversed this down-regulation of Rab5 in vivo. Further studies revealed that the C-terminus of Rin1 carrying Rin1:Vps9 and Rin1:RA domains are required for optimal Rab5 activation in conjunction with active Ras. These observations demonstrate a novel mechanism of Rab5 targeting to phagosome via Rin1 during the phagocytosis of P. aeruginosa. The second part of this dissertation investigated antimicrobial activities of Dehydroleucodine (DhL), a secondary metabolite from Artemisia douglasiana, against P. aeruginosa growth and virulence. Populations of several P. aeruginosa strains were completely susceptible to DhL at a concentration between 0.48~0.96 mg/ml and treatment at a threshold concentration (0.12 mg/ml) inhibited growth and many virulent activities without damaging the integrity of the cell suggesting anti-Pseudomonas activity of DhL.
Resumo:
Background: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data. Results: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers. Conclusions: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.
Resumo:
Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.
Resumo:
Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.
Resumo:
Brazilian pepper (Schinus terebinthifolius) is an exotic shrub or small tree that has become well established as an invasive and highly competitive species through much of southern Florida. Love vine (Cassytha filiformis), a native parasitic plant, was noted parasitizing Brazilian pepper, apparently affecting its health. The objective of this study was to investigate the nature of this parasitic interaction in southern Florida. Brazilian pepper populations were studied to determine whether parasitism by love vine may affect growth and reproduction. Anatomical studies of love vine parasitizing Brazilian pepper determined physical aspects of the parasitic interaction at the cell and tissue level. Physiological aspects of this interaction were investigated to help describe love vine resource acquisition as a parasite on host Brazilian pepper plants, and as an autotrophic plant. An investigation of ecological aspects of this parasitic interaction was done to determine whether physical or biological aspects of habitats may contribute to love vine parasitism on Brazilian pepper. These studies indicated that: (1) parasitism by love vine significantly decreased growth and reproduction of Brazilian pepper plants; (2) anatomical and physiological investigations indicated that love vine was primarily a xylem parasite on Brazilian pepper, but that some assimilated carbon nutrients may also be acquired from the host; (3) love vine is autotrophic (i.e., hemiparasitic), but is totally dependent on its host for necessary resources; (4) the occurrence of love vine parasitism on Brazilian pepper is mediated by physical characters of the biological community. ^
Resumo:
Security remains a top priority for organizations as their information systems continue to be plagued by security breaches. This dissertation developed a unique approach to assess the security risks associated with information systems based on dynamic neural network architecture. The risks that are considered encompass the production computing environment and the client machine environment. The risks are established as metrics that define how susceptible each of the computing environments is to security breaches. ^ The merit of the approach developed in this dissertation is based on the design and implementation of Artificial Neural Networks to assess the risks in the computing and client machine environments. The datasets that were utilized in the implementation and validation of the model were obtained from business organizations using a web survey tool hosted by Microsoft. This site was designed as a host site for anonymous surveys that were devised specifically as part of this dissertation. Microsoft customers can login to the website and submit their responses to the questionnaire. ^ This work asserted that security in information systems is not dependent exclusively on technology but rather on the triumvirate people, process and technology. The questionnaire and consequently the developed neural network architecture accounted for all three key factors that impact information systems security. ^ As part of the study, a methodology on how to develop, train and validate such a predictive model was devised and successfully deployed. This methodology prescribed how to determine the optimal topology, activation function, and associated parameters for this security based scenario. The assessment of the effects of security breaches to the information systems has traditionally been post-mortem whereas this dissertation provided a predictive solution where organizations can determine how susceptible their environments are to security breaches in a proactive way. ^
Resumo:
Antibiotic resistance, production of alginate and virulence factors, and altered host immune responses are the hallmarks of chronic Pseudomonas aeruginosa infection. Failure of antibiotic therapy has been attributed to the emergence of P. aeruginosa strains that produce β-lactamase constitutively. In Enterobacteriaceae, β-lactamase induction involves four genes with known functions: ampC, ampR, ampD, and ampG, encoding the enzyme, transcriptional regulator, amidase and permease, respectively. In addition to all these amp genes, P. aeruginosa possesses two ampG paralogs, designated ampG and ampP. In this study, P. aeruginosa ampC, ampR, ampG and ampP were analyzed. Inactivation of ampC in the prototypic PAO1 failed to abolish the β-lactamase activity leading to the discovery of P. aeruginosa oxacillinase PoxB. Cloning and expression of poxB in Escherichia coli confers β-lactam resistance. Both AmpC and PoxB contribute to P. aeruginosa resistance against a wide spectrum of β-lactam antibiotics. The expression of PoxB and AmpC is regulated by a LysR-type transcriptional regulator AmpR that up-regulates AmpC but down-regulates PoxB activities. Analyses of P. aeruginosa ampR mutant demonstrate that AmpR is a global regulator that modulates the expressions of Las and Rhl quorum sensing (QS) systems, and the production of pyocyanin, LasA protease and LasB elastase. Introduction of the ampR mutation into an alginate-producing strain reveals the presence of a complex co-regulatory network between antibiotic resistance, QS alginate and other virulence factor production. Using phoA and lacZ protein fusion analyses, AmpR, AmpG and AmpP were localized to the inner membrane with one, 16 and 10 transmembrane helices, respectively. AmpR has a cytoplasmic DNA-binding and a periplasmic substrate binding domains. AmpG and AmpP are essential for the maximal expression of β-lactamase. Analysis of the murein breakdown products suggests that AmpG exports UDP-N-acetylmuramyl-L-alanine-γ-D-glutamate-meso-diaminopimelic acid-D-alanine-D-alanine (UDP-MurNAc-pentapeptide), the corepressor of AmpR, whereas AmpP imports N-acetylglucosaminyl-beta-1,4-anhydro-N-acetylmuramic acid-Ala-γ-D-Glu-meso-diaminopimelic acid (GlcNAc-anhMurNAc-tripeptide) and GlcNAc-anhMurNAc-pentapeptide, the co-inducers of AmpR. This study reveals a complex interaction between the Amp proteins and murein breakdown products involved in P. aeruginosa β-lactamase induction. In summary, this dissertation takes us a little closer to understanding the P. aeruginosa complex co-regulatory mechanism in the development of β-lactam resistance and establishment of chronic infection. ^
Resumo:
Understanding how decisions for international investments are made and how this affects the overall pattern of investments and firm’s performance is of particular importance both in strategy and international business research. This dissertation introduced first home-host country relatedness (HHCR) as the degree to which countries are efficiently combined within the investment portfolios of firms. It theorized and demonstrated that HHCR will vary with the motivation for investments along at least two key dimensions: the nature of foreign investments and the connectedness of potential host countries to the rest of the world. Drawing on cognitive psychology and decision-making research, it developed a theory of strategic decision making proposing that strategic solutions are chosen close to a convenient anchor. Building on research on memory imprinting, it also proposed that managers tend to rely on older knowledge representation. In the context of international investment decisions, managers use their home countries as an anchor and are more likely to choose as a site for foreign investments host countries that are ‘close’ to the home country. These decisions are also likely to rely more strongly on closeness to time invariant country factors of historic and geographic nature rather than time-variant institutions. Empirical tests using comprehensive investments data by all public multinational companies (MNC) worldwide, or over 15,000 MNCs with over half a million subsidiaries, support the claims. Finally, the dissertation introduced the concept of International Coherence (IC) defined as the degree to which an MNE’s network comprises countries that are related. It was hypothesized that maintaining a high level of coherence is important for firm performance and will enhance it. Also, the presence of international coherence mitigates some of the negative effects of unrelated product diversification. Empirical tests using data on foreign investments of over 20,000 public firms, while also developing a home-host country relatedness index for up to 24,300 home-host pairs, provided support for the theory advanced.
Resumo:
The presence of the conceptus in uterine cavity necessitates an elaborate network of interactions between the implanting embryo and a receptive endometrial tissue. We believe that embryo-derived signals play an important role in the remodeling and the extension of endometrial receptivity period. Our previous studies provided original evidence that human Chorionic Gonadotropin (hCG) modulates and potentiates endometrial epithelial as well as stromal cell responsiveness to interleukin 1 (IL1), one of the earliest embryonic signals, which may represent a novel pathway by which the embryo favors its own implantation and growth within the maternal endometrial host. The present study was designed to gain a broader understanding of hCG impact on the modulation of endometrial cell receptivity, and in particular, cell responsiveness to IL1 and the acquisition of growth-promoting phenotype capable of receiving, sustaining, and promoting early and crucial steps of embryonic development. Our results showed significant changes in the expression of genes involved in cell proliferation, immune modulation, tissue remodeling, apoptotic and angiogenic processes. This points to a relevant impact of these embryonic signals on the receptivity of the maternal endometrium, its adaptation to the implanting embryo and the creation of an environment that is favorable for the implantation and the growth of this latter within a new and likely hostile host tissue. Interestingly our data further identified a complex interaction between IL1 and hCG, which, despite a synergistic action on several significant endometrial target genes, may encompass a tight control of endogenous IL1 and extends to other IL1 family members.
Resumo:
In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.
Resumo:
The primary goal of this dissertation is the study of patterns of viral evolution inferred from serially-sampled sequence data, i.e., sequence data obtained from strains isolated at consecutive time points from a single patient or host. RNA viral populations have an extremely high genetic variability, largely due to their astronomical population sizes within host systems, high replication rate, and short generation time. It is this aspect of their evolution that demands special attention and a different approach when studying the evolutionary relationships of serially-sampled sequence data. New methods that analyze serially-sampled data were developed shortly after a groundbreaking HIV-1 study of several patients from which viruses were isolated at recurring intervals over a period of 10 or more years. These methods assume a tree-like evolutionary model, while many RNA viruses have the capacity to exchange genetic material with one another using a process called recombination. ^ A genealogy involving recombination is best described by a network structure. A more general approach was implemented in a new computational tool, Sliding MinPD, one that is mindful of the sampling times of the input sequences and that reconstructs the viral evolutionary relationships in the form of a network structure with implicit representations of recombination events. The underlying network organization reveals unique patterns of viral evolution and could help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies. In order to comprehensively test the developed methods and to carry out comparison studies with other methods, synthetic data sets are critical. Therefore, appropriate sequence generators were also developed to simulate the evolution of serially-sampled recombinant viruses, new and more through evaluation criteria for recombination detection methods were established, and three major comparison studies were performed. The newly developed tools were also applied to "real" HIV-1 sequence data and it was shown that the results represented within an evolutionary network structure can be interpreted in biologically meaningful ways. ^
Resumo:
Brazilian pepper (Schinus terebinthifolius) is an exotic shrub or small tree that has become well established as an invasive and highly competitive species through much of southern Florida. Love vine (Cassytha filiformis), a native parasitic plant, was noted parasitizing Brazilian pepper, apparently affecting its health. The objective of this study was to investigate the nature of this parasitic interaction in southern Florida. Brazilian pepper populations were studied to determine whether parasitism by love vine may affect growth and reproduction. Anatomical studies of love vine parasitizing Brazilian pepper determined physical aspects of the parasitic interaction at the cell and tissue level. Physiological aspects of this interaction were investigated to help describe love vine resource acquisition as a parasite on host Brazilian pepper plants, and as an autotrophic plant. An investigation of ecological aspects of this parasitic interaction was done to determine whether physical or biological aspects of habitats may contribute to love vine parasitism on Brazilian pepper. These studies indicated that: 1) parasitism by love vine significantly decreased growth and reproduction of Brazilian pepper plants; 2) anatomical and physiological investigations indicated that love vine was primarily a xylem parasite on Brazilian pepper, but that some assimilated carbon nutrients may also be acquired from the host; 3) love vine is autotrophic (i. e., hemiparasitic), but is totally dependent on its host for necessary resources; 4) the occurrence of love vine parasitism on Brazilian pepper is mediated by physical characters of the biological community.
Resumo:
Vehicle fuel consumption and emission are two important effectiveness measurements of sustainable transportation development. Pavement plays an essential role in goals of fuel economy improvement and greenhouse gas (GHG) emission reduction. The main objective of this dissertation study is to experimentally investigate the effect of pavement-vehicle interaction (PVI) on vehicle fuel consumption under highway driving conditions. The goal is to provide a better understanding on the role of pavement in the green transportation initiates. Four study phases are carried out. The first phase involves a preliminary field investigation to detect the fuel consumption differences between paired flexible-rigid pavement sections with repeat measurements. The second phase continues the field investigation by a more detailed and comprehensive experimental design and independently investigates the effect of pavement type on vehicle fuel consumption. The third study phase calibrates the HDM-IV fuel consumption model with data collected in the second field phase. The purpose is to understand how pavement deflection affects vehicle fuel consumption from a mechanistic approach. The last phase applies the calibrated HDM-IV model to Florida’s interstate network and estimates the total annual fuel consumption and CO2 emissions on different scenarios. The potential annual fuel savings and emission reductions are derived based on the estimation results. Statistical results from the two field studies both show fuel savings on rigid pavement compared to flexible pavement with the test conditions specified. The savings derived from the first phase are 2.50% for the passenger car at 112km/h, and 4.04% for 18-wheel tractor-trailer at 93km/h. The savings resulted from the second phase are 2.25% and 2.22% for passenger car at 93km/h and 112km/h, and 3.57% and 3.15% for the 6-wheel medium-duty truck at 89km/h and 105km/h. All savings are statistically significant at 95% Confidence Level (C.L.). From the calibrated HDM-IV model, one unit of pavement deflection (1mm) on flexible pavement can cause an excess fuel consumption by 0.234-0.311 L/100km for the passenger car and by 1.123-1.277 L/100km for the truck. The effect is more evident at lower highway speed than at higher highway speed. From the network level estimation, approximately 40 million gallons of fuel (combined gasoline and diesel) and 0.39 million tons of CO2 emission can be saved/reduced annually if all Florida’s interstate flexible pavement are converted to rigid pavement with the same roughness levels. Moreover, each 1-mile of flexible-rigid conversion can result in a reduction of 29 thousand gallons of fuel and 258 tons of CO2 emission yearly.