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Item Oxidized Extracellular DNA as a Stress Signal in Human Cells(Hindawi Publishing Corporation, 2013-01) Ermakov, Aleksei V.; Konkova, Marina S.; Kostyuk, Svetlana V.; Izevskaya, Vera L.; Baranova, Ancha; Veiko, Natalya N.The term “cell-free DNA” (cfDNA) was recently coined for DNA fragments from plasma/serum, while DNA present in in vitro cell culture media is known as extracellular DNA (ecDNA). Under oxidative stress conditions, the levels of oxidative modification of cellular DNA and the rate of cell death increase. Dying cells release their damaged DNA, thus, contributing oxidized DNA fragments to the pool of cfDNA/ecDNA. Oxidized cell-free DNA could serve as a stress signal that promotes irradiation-induced bystander effect. Evidence points to TLR9 as a possible candidate for oxidized DNA sensor. An exposure to oxidized ecDNA stimulates a synthesis of reactive oxygen species (ROS) that evokes an adaptive response that includes transposition of the homologous loci within the nucleus, polymerization and the formation of the stress fibers of the actin, as well as activation of the ribosomal gene expression, and nuclear translocation of NF-E2 related factor-2 (NRF2) that, in turn, mediates induction of phase II detoxifying and antioxidant enzymes. In conclusion, the oxidized DNA is a stress signal released in response to oxidative stress in the cultured cells and, possibly, in the human body; in particular, it might contribute to systemic abscopal effects of localized irradiation treatments.Item Signaling Pathways Involved in Striatal Synaptic Plasticity are Sensitive to Temporal Pattern and Exhibit Spatial Specificity(Public Library of Science, 2013-03-14) Kim, BoHung; Hawes, Sarah L.; Gillani, Fawad; Wallace, Lane J.; Blackwell, Kim T.The basal ganglia is a brain region critically involved in reinforcement learning and motor control. Synaptic plasticity in the striatum of the basal ganglia is a cellular mechanism implicated in learning and neuronal information processing. Therefore, understanding how different spatio-temporal patterns of synaptic input select for different types of plasticity is key to understanding learning mechanisms. In striatal medium spiny projection neurons (MSPN), both long term potentiation (LTP) and long term depression (LTD) require an elevation in intracellular calcium concentration; however, it is unknown how the post-synaptic neuron discriminates between different patterns of calcium influx. Using computer modeling, we investigate the hypothesis that temporal pattern of stimulation can select for either endocannabinoid production (for LTD) or protein kinase C (PKC) activation (for LTP) in striatal MSPNs. We implement a stochastic model of the post-synaptic signaling pathways in a dendrite with one or more diffusionally coupled spines. The model is validated by comparison to experiments measuring endocannabinoid-dependent depolarization induced suppression of inhibition. Using the validated model, simulations demonstrate that theta burst stimulation, which produces LTP, increases the activation of PKC as compared to 20 Hz stimulation, which produces LTD. The model prediction that PKC activation is required for theta burst LTP is confirmed experimentally. Using the ratio of PKC to endocannabinoid production as an index of plasticity direction, model simulations demonstrate that LTP exhibits spine level spatial specificity, whereas LTD is more diffuse. These results suggest that spatio-temporal control of striatal information processing employs these Gq coupled pathways.Item Improving remote sensing flood assessment using volunteered geographical data(Copernicus Publications, 2013-03-19) Schnebele, E.; Cervone, G.A new methodology for the generation of flood hazard maps is presented fusing remote sensing and volunteered geographical data. Water pixels are identified utilizing a machine learning classification of two Landsat remote sensing scenes, acquired before and during the flooding event as well as a digital elevation model paired with river gage data. A statistical model computes the probability of flooded areas as a function of the number of adjacent pixels classified as water. Volunteered data obtained through Google news, videos and photos are added to modify the contour regions. It is shown that even a small amount of volunteered ground data can dramatically improve results.Item Understanding Electronic Medical Record Adoption in the United States: Communication and Sociocultural Perspectives(JMIR Publications, 2013-03-26) Nambisan, Priya; Kreps, Gary L.; Polit, StanBackground: This paper adopts a communication and sociocultural perspective to analyze the factors behind the lag in electronic medical record (EMR) adoption in the United States. Much of the extant research on this topic has emphasized economic factors, particularly, lack of economic incentives, as the primary cause of the delay in EMR adoption. This prompted the Health Information Technology on Economic and Clinical Health Act that allow financial incentives through the Centers of Medicare and Medicaid Services for many health care organizations planning to adopt EMR. However, financial incentives alone have not solved the problem; many new innovations do not diffuse even when offered for free. Thus, this paper underlines the need to consider communication and sociocultural factors to develop a better understanding of the impediments of EMR adoption. Objective: The objective of this paper was to develop a holistic understanding of EMR adoption by identifying and analyzing the impact of communication and sociocultural factors that operate at 3 levels: macro (environmental), meso (organizational), and micro (individual). Methods: We use the systems approach to focus on the 3 levels (macro, meso, and micro) and developed propositions at each level drawing on the communication and sociocultural perspectives. Results: Our analysis resulted in 10 propositions that connect communication and sociocultural aspects with EMR adoption. Conclusions: This paper brings perspectives from the social sciences that have largely been missing in the extant literature of health information technology (HIT) adoption. In doing so, it implies how communication and sociocultural factors may complement (and in some instances, reinforce) the impact of economic factors on HIT adoption.Item CoreGenes3.5: a webserver for the determination of core genes from sets of viral and small bacterial genomes(BioMed Central, 2013-04-08) Turner, Dann; Reynolds, Darren; Seto, Donald; Mahadevan, PadmanabhanBackground: CoreGenes3.5 is a webserver that determines sets of core genes from viral and small bacterial genomes as an automated batch process. Previous versions of CoreGenes have been used to classify bacteriophage genomes and mine data from pathogen genomes. Findings: CoreGenes3.5 accepts as input GenBank accession numbers of genomes and performs iterative BLASTP analyses to output a set of core genes. After completion of the program run, the results can be either displayed in a new window for one pair of reference and query genomes or emailed to the user for multiple pairs of small genomes in tabular format. Conclusions: With the number of genomes sequenced increasing daily and interest in determining phylogenetic relationships, CoreGenes3.5 provides a user-friendly web interface for wet-bench biologists to process multiple small genomes for core gene determinations. CoreGenes3.5 is available at http://binf.gmu.edu:8080/CoreGenes3.5.Item The socio-cultural importance of Mauritia flexuosa palm swamps (aguajales) and implications for multi-use management in two Maijuna communities of the Peruvian Amazon(BioMed Central, 2013-04-22) Gilmore, Michael P.; Endress, Bryan A.; Horn, Christa M.Background Fruit from the palm Mauritia flexuosa (aguaje) is harvested throughout the Peruvian Amazon for subsistence and commercial purposes. Recent estimates suggest that residents of Iquitos, the largest city in the region, consume approximately 148.8 metric tons of aguaje fruit per month, the vast majority of which is harvested by felling and killing adult female trees. In this study, we sought to better understand and document the importance of M. flexuosa palm swamps (aguajales) in two Maijuna indigenous communities to inform the sustainable management of this habitat and species. Methods Semi-structured interviews, focus groups, and household surveys were carried out to assess the significance of aguajales and their associated plant and animal resources as well as to determine how the relationship that the Maijuna have with aguajales has changed over time. Results Aguajales and their associated resources are culturally significant and useful to the Maijuna in a wide variety of ways. In addition to M. flexuosa, the Maijuna use over 60 different species of plants from aguajales. When M. flexuosa is in fruit, aguajales are important hunting areas with a total of 20 different animal species hunted. The Maijuna also have traditional beliefs about aguajales, believing that malevolent supernatural beings reside in them. Notably, the relationship that the Maijuna have with aguajales has changed considerably over the years as aguaje fruit went from a subsistence item collected opportunistically from the ground to a market good destructively harvested beginning in the early 1990s. The Maijuna are concerned not only about how this has affected the future commercial harvest of aguaje but also about its effects on game animals given the importance of hunting to Maijuna cultural identity, subsistence, and income generation. Conclusions In order to meet the multiple socio-cultural and economic needs of the Maijuna, sustainable management efforts must be expanded to not only focus on the commercial harvest of aguaje but also other facets of their relationship with this habitat. Our study suggests that the research and development of multi-use forest management plans must not be restricted to commercial forest products and ecosystem services given that many communities rely on tropical forests for a wide range of non-market cultural, economic, and subsistence goods and services.Item Augmenting Weak Semantic Cognitive Maps with an “Abstractness” Dimension(Hindawi Publishing, 2013-04-29) Samsonovich, AlexeiThe emergent consensus on dimensional models of sentiment, appraisal, emotions, and values is on the semantics of the principal dimensions, typically interpreted as valence, arousal, and dominance. The notion of weak semantic maps was introduced recently as distribution of representations in abstract spaces that are not derived from human judgments, psychometrics, or any other a priori information about their semantics. Instead, they are defined entirely by binary semantic relations among representations, such as synonymy and antonymy. An interesting question concerns the ability of the antonymy-based semantic maps to capture all “universal” semantic dimensions. The present work shows that those narrow weak semantic maps are not complete in this sense and can be augmented with other semantic relations. Specifically, including hyponym-hypernym relations yields a new semantic dimension of the map labeled here “abstractness” (or ontological generality) that is not reducible to any dimensions represented by antonym pairs or to traditional affective space dimensions. It is expected that including other semantic relations (e.g., meronymy/holonymy) will also result in the addition of new semantic dimensions to the map. These findings have broad implications for automated quantitative evaluation of the meaning of text and may shed light on the nature of human subjective experience.Item Employment Growth through Labor Flow Networks(Public Library of Science, 2013-05-02) Guerrero, Omar A.; Axtell, Robert L.It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.Item Mining social media and web searches for disease detection(PAGEPress, 2013-05-31) Yang, Y. Tony; Horneffer, Michael; DiLisio, NicoleWeb-based social media is increasingly being used across different settings in the health care industry. The increased frequency in the use of the Internet via computer or mobile devices provides an opportunity for social media to be the medium through which people can be provided with valuable health information quickly and directly. While traditional methods of detection relied predominately on hierarchical or bureaucratic lines of communication, these often failed to yield timely and accurate epidemiological intelligence. New web-based platforms promise increased opportunities for a more timely and accurate spreading of information and analysis. This article aims to provide an overview and discussion of the availability of timely and accurate information. It is especially useful for the rapid identification of an outbreak of an infectious disease that is necessary to promptly and effectively develop public health responses. These web-based platforms include search queries, data mining of web and social media, process and analysis of blogs containing epidemic key words, text mining, and geographical information system data analyses. These new sources of analysis and information are intended to complement traditional sources of epidemic intelligence. Despite the attractiveness of these new approaches, further study is needed to determine the accuracy of blogger statements, as increases in public participation may not necessarily mean the information provided is more accurate.Item An Evaluation Synthesis of US AIDS Drug Assistance Program Policy(Scientific Research, 2013-06) Horneffer, Michael A.; Yang, Y. TonyUS Congress passed the CARE Act in 1990 in response to a dramatically growing need for resources to combat the AIDS epidemic. One of the programs contained in the Act was the AIDS Drug Assistance Program (ADAP), a federally-funded but state-maintained and managed program primarily concerned with providing medication for low-income HIV/AIDS patients. While ADAP programs across the country reached one-third of all patients in 2007, these programs are now in budgetary danger due to the economic recession, state budgetary constraints, the rising cost of healthcare generally, and longer life expectancies associated with current highly active antiretroviral therapy (HAART). This paper first evaluates the current state of ADAP, its strengths and weaknesses, and examines its sustainability in the short term if short-term measures are taken. Concluding that such measures would not lead to long-term sustainability, this paper then argues for a long-term solution to ADAP’s current problems, namely a national, centralized ADAP standard for budgetary and administrative matters. Such a program would increase the long-term sustainability and effectiveness of current ADAP programs by employing more efficient, standard policies and allowing larger, wholesale purchases of costly HAART medications. Moreover, a national policy would address the disparity that currently exists in ADAP programs today with regard to both minorities and those on the waiting lists for treatment. The institution of a national ADAP program would certainly face many political hurdles. Consequently, this paper also looks to a recent political dispute, the enactment of the Affordable Care Act (ACA), for guidance. Using the passage of the ACA as an example could light the path for passage of a national ADAP standard. Ultimately, this would lead to a more effective and sustainable program for HIV/AIDS patients in the United States.Item Not so cool? Menthol’s discovered actions on the nicotinic receptor and its implications for nicotine addiction(Frontiers, 2013-07-23) Kabbani, NadineNicotine cigarette smoke is a large public health burden worldwide, contributing to various types of disease. Anti-tobacco media campaigns and control programs have significantly reduced smoking in the United States, yet trends for menthol cigarette smoking have not been as promising. Menthol cigarette smoking is particularly prevalent among young adults and African Americans, with implications for long-term impacts on health care. Continuing high rates of menthol cigarette addiction call into question the role of menthol in nicotine addiction. To date, a biological basis for the high rate of addiction and relapse among menthol cigarette smokers has not been defined. Studies have demonstrated a role for menthol in the metabolism of nicotine in the body. More recent findings now reveal an interaction between menthol and the nicotinic acetylcholine (nACh) receptor in cells. This receptor is central to the actions of nicotine in the brain, and plays an important role in nicotine addiction. The newly discovered effect of menthol on nACh receptors may begin to explain the unique addictive properties of menthol cigarettes.Item Functional Genomic Analyses of Two Morphologically Distinct Classes of Drosophila Sensory Neurons: Post-Mitotic Roles of Transcription Factors in Dendritic Patterning(Public Library of Science, 2013-08-15) Iyer, Eswar Prasad R.; Iyer, Srividya Chandramouli; Sullivan, Luis; Wang, Dennis; Meduri, Ramakrishna; Graybeal, Lacey L.; Cox, Daniel N.Background Neurons are one of the most structurally and functionally diverse cell types found in nature, owing in large part to their unique class specific dendritic architectures. Dendrites, being highly specialized in receiving and processing neuronal signals, play a key role in the formation of functional neural circuits. Hence, in order to understand the emergence and assembly of a complex nervous system, it is critical to understand the molecular mechanisms that direct class specific dendritogenesis. Methodology/Principal Findings We have used the Drosophila dendritic arborization (da) neurons to gain systems-level insight into dendritogenesis by a comparative study of the morphologically distinct Class-I (C-I) and Class-IV (C-IV) da neurons. We have used a combination of cell-type specific transcriptional expression profiling coupled to a targeted and systematic in vivo RNAi functional validation screen. Our comparative transcriptomic analyses have revealed a large number of differentially enriched/depleted gene-sets between C-I and C-IV neurons, including a broad range of molecular factors and biological processes such as proteolytic and metabolic pathways. Further, using this data, we have identified and validated the role of 37 transcription factors in regulating class specific dendrite development using in vivo class-specific RNAi knockdowns followed by rigorous and quantitative neurometric analysis. Conclusions/Significance This study reports the first global gene-expression profiles from purified Drosophila C-I and C-IV da neurons. We also report the first large-scale semi-automated reconstruction of over 4,900 da neurons, which were used to quantitatively validate the RNAi screen phenotypes. Overall, these analyses shed global and unbiased novel insights into the molecular differences that underlie the morphological diversity of distinct neuronal cell-types. Furthermore, our class-specific gene expression datasets should prove a valuable community resource in guiding further investigations designed to explore the molecular mechanisms underlying class specific neuronal patterning.Item A Novel Application of Musculoskeletal Ultrasound Imaging(Journal of Visualized Experiments, 2013-09) Eranki, Avinash; Cortes, Nelson; Ferenček3, Zrinka Gregurić; Siddhartha, SikdarUltrasound is an attractive modality for imaging muscle and tendon motion during dynamic tasks and can provide a complementary methodological approach for biomechanical studies in a clinical or laboratory setting. Towards this goal, methods for quantification of muscle kinematics from ultrasound imagery are being developed based on image processing. The temporal resolution of these methods is typically not sufficient for highly dynamic tasks, such as drop-landing. We propose a new approach that utilizes a Doppler method for quantifying muscle kinematics. We have developed a novel vector tissue Doppler imaging (vTDI) technique that can be used to measure musculoskeletal contraction velocity, strain and strain rate with sub-millisecond temporal resolution during dynamic activities using ultrasound. The goal of this preliminary study was to investigate the repeatability and potential applicability of the vTDI technique in measuring musculoskeletal velocities during a drop-landing task, in healthy subjects. The vTDI measurements can be performed concurrently with other biomechanical techniques, such as 3D motion capture for joint kinematics and kinetics, electromyography for timing of muscle activation and force plates for ground reaction force. Integration of these complementary techniques could lead to a better understanding of dynamic muscle function and dysfunction underlying the pathogenesis and pathophysiology of musculoskeletal disorders.Item Controlling Seizure-Like Events by Perturbing Ion Concentration Dynamics with Periodic Stimulation(Public Library of Science, 2013-09-16) Owen, Jeremy A.; Barreto, Ernest; Cressman, John R.We investigate the effects of adding periodic stimulation to a generic, conductance-based neuron model that includes ion concentration dynamics of sodium and potassium. Under conditions of high extracellular potassium, the model exhibits repeating, spontaneous, seizure-like bursting events associated with slow modulation of the ion concentrations local to the neuron. We show that for a range of parameter values, depolarizing and hyperpolarizing periodic stimulation pulses (including frequencies lower than 4 Hz) can stop the spontaneous bursting by interacting with the ion concentration dynamics. Stimulation can also control the magnitude of evoked responses to modeled physiological inputs. We develop an understanding of the nonlinear dynamics of this system by a timescale separation procedure that identifies effective nullclines in the ion concentration parameter space. Our results suggest that the manipulation of ion concentration dynamics via external or endogenous stimulation may play an important role in neuronal excitability, seizure dynamics, and control.Item Environmental influences on neural systems of relational complexity(Frontiers, 2013-09-26) Kalbfleisch, M. Layne; deBettencourt, Megan T.; Kopperman, Rebecca; Banasiak, Meredith; Roberts, Joshua M.; Halavi, MaryamConstructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC), defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2). The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of RC during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast (BWVC) add demand at a basic sensory level, but contributions from color and from BWVC are dissociable in cortex such that color engages a “reasoning heuristic” and BWVC engages a “sensory heuristic.” Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem solving.Item Sequence and structure based models of HIV-1 protease and reverse transcriptase drug resistance(BioMed Central, 2013-10-01) Masso, Majid; Vaisman, Iosif I.Background Successful management of chronic human immunodeficiency virus type 1 (HIV-1) infection with a cocktail of antiretroviral medications can be negatively affected by the presence of drug resistant mutations in the viral targets. These targets include the HIV-1 protease (PR) and reverse transcriptase (RT) proteins, for which a number of inhibitors are available on the market and routinely prescribed. Protein mutational patterns are associated with varying degrees of resistance to their respective inhibitors, with extremes that can range from continued susceptibility to cross-resistance across all drugs. Results Here we implement statistical learning algorithms to develop structure- and sequence-based models for systematically predicting the effects of mutations in the PR and RT proteins on resistance to each of eight and eleven inhibitors, respectively. Employing a four-body statistical potential, mutant proteins are represented as feature vectors whose components quantify relative environmental perturbations at amino acid residue positions in the respective target structures upon mutation. Two approaches are implemented in developing sequence-based models, based on use of either relative frequencies or counts of n-grams, to generate vectors for representing mutant proteins. To the best of our knowledge, this is the first reported study on structure- and sequence-based predictive models of HIV-1 PR and RT drug resistance developed by implementing a four-body statistical potential and n-grams, respectively, to generate mutant attribute vectors. Performance of the learning methods is evaluated on the basis of tenfold cross-validation, using previously assayed and publicly available in vitro data relating mutational patterns in the targets to quantified inhibitor susceptibility changes. Conclusion Overall performance results are competitive with those of a previously published study utilizing a sequence-based strategy, while our structure- and sequence-based models provide orthogonal and complementary prediction methodologies, respectively. In a novel application, we describe a technique for identifying every possible pair of RT inhibitors as either potentially effective together as part of a cocktail, or a combination that is to be avoided.Item Dynamical structure underlying inverse stochastic resonance and its implications(American Physical Society, 2013-10-31) Uzuntarla, Muhammet; Cressman, John R.; Ozer, Mahmut; Barreto, ErnestWe investigate inverse stochastic resonance (ISR), a recently reported phenomenon in which the spiking activity of a Hodgkin-Huxley model neuron subject to external noise exhibits a pronounced minimum as the noise intensity increases.We clarify the mechanism that underlies ISR and show that its most surprising features are a consequence of the dynamical structure of the model. Furthermore, we show that the ISR effect depends strongly on the procedures used to measure it. Our results are important for the experimentalist who seeks to observe the ISR phenomenon.Item Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimer’s disease(BioMed Central, 2013-11-07) Mayburd, Anatoly; Baranova, AnchaBackground High-throughput profiling of human tissues typically yield as results the gene lists comprised of a mix of relevant molecular entities with multiple false positives that obstruct the translation of such results into mechanistic hypotheses. From general probabilistic considerations, gene lists distilled for the mechanistically relevant components can be far more useful for subsequent experimental design or data interpretation. Results The input candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subsets of the same experiments and across different experiments and platforms. The cut-offs were established empirically through ontological and semantic enrichment; resultant shortened gene list was re-expanded by Ingenuity Pathway Assistant tool. The resulting sub-networks provided the basis for generating mechanistic hypotheses that were partially validated by literature search. This approach differs from previous consistency-based studies in that the cut-off on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The gene list distilled by this analytic technique and its network representation were termed Compact Disease Model (CDM). Here we present the CDM signature for the study of early-stage Alzheimer’s disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimer’s. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimer’s disease’ CDM. Conclusions A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses.Item Four-body atomic potential for modeling protein-ligand binding affinity: application to enzyme-inhibitor binding energy prediction(BioMed Central, 2013-11-08) Masso, MajidBackground : Models that are capable of reliably predicting binding affinities for protein-ligand complexes play an important role the field of structure-guided drug design. Methods : Here, we begin by applying the computational geometry technique of Delaunay tessellation to each set of atomic coordinates for over 1400 diverse macromolecular structures, for the purpose of deriving a four-body statistical potential that serves as a topological scoring function. Next, we identify a second, independent set of three hundred protein-ligand complexes, having both high-resolution structures and known dissociation constants. Two-thirds of these complexes are randomly selected to train a predictive model of binding affinity as follows: two tessellations are generated in each case, one for the entire complex and another strictly for the isolated protein without its bound ligand, and a topological score is computed for each tessellation with the four-body potential. Predicted protein-ligand binding affinity is then based on an empirically derived linear function of the difference between both topological scores, one that appropriately scales the value of this difference. Results : A comparison between experimental and calculated binding affinity values over the two hundred complexes reveals a Pearson's correlation coefficient of r = 0.79 with a standard error of SE = 1.98 kcal/mol. To validate the method, we similarly generated two tessellations for each of the remaining protein-ligand complexes, computed their topological scores and the difference between the two scores for each complex, and applied the previously derived linear transformation of this topological score difference to predict binding affinities. For these one hundred complexes, we again observe a correlation of r = 0.79 (SE = 1.93 kcal/mol) between known and calculated binding affinities. Applying our model to an independent test set of high-resolution structures for three hundred diverse enzyme-inhibitor complexes, each with an experimentally known inhibition constant, also yields a correlation of r = 0.79 (SE = 2.39 kcal/mol) between experimental and calculated binding energies. Conclusions : Lastly, we generate predictions with our model on a diverse test set of one hundred protein-ligand complexes previously used to benchmark 15 related methods, and our correlation of r = 0.66 between the calculated and experimental binding energies for this dataset exceeds those of the other approaches. Compared with these related prediction methods, our approach stands out based on salient features that include the reliability of our model, combined with the rapidity of the generated predictions, which are less than one second for an average sized complex.Item The Approach to Sample Acquisition and Its Impact on the Derived Human Fecal Microbiome and VOC Metabolome(Public Library of Science, 2013-11-18) Couch, Robin D.; Navarro, Karl; Sikaroodi, Masoumeh; Gillevet, Pat; Forsyth, Christopher B.; Mutlu, Ece; Engen, Phillip A.; Keshavarzian, AliRecent studies have illustrated the importance of the microbiota in maintaining a healthy state, as well as promoting disease states. The intestinal microbiota exerts its effects primarily through its metabolites, and metabolomics investigations have begun to evaluate the diagnostic and health implications of volatile organic compounds (VOCs) isolated from human feces, enabled by specialized sampling methods such as headspace solid-phase microextraction (hSPME). The approach to stool sample collection is an important consideration that could potentially introduce bias and affect the outcome of a fecal metagenomic and metabolomic investigation. To address this concern, a comparison of endoscopically collected (in vivo) and home collected (ex vivo) fecal samples was performed, revealing slight variability in the derived microbiomes. In contrast, the VOC metabolomes differ widely between the home collected and endoscopy collected samples. Additionally, as the VOC extraction profile is hyperbolic, with short extraction durations more vulnerable to variation than extractions continued to equilibrium, a second goal of our investigation was to ascertain if hSPME-based fecal metabolomics studies might be biased by the extraction duration employed. As anticipated, prolonged extraction (18 hours) results in the identification of considerably more metabolites than short (20 minute) extractions. A comparison of the metabolomes reveals several analytes deemed unique to a cohort with the 20 minute extraction, but found common to both cohorts when the VOC extraction was performed for 18 hours. Moreover, numerous analytes perceived to have significant fold change with a 20 minute extraction were found insignificant in fold change with the prolonged extraction, underscoring the potential for bias associated with a 20 minute hSPME.