2,930 research outputs found
Implementation of a line attractor-based model of the gaze holding integrator using nonlinear spiking neuron models
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 30-31).by Ben Y. Reis.M.Eng
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Concordance and predictive value of two adverse drug event data sets
Background: Accurate prediction of adverse drug events (ADEs) is an important means of controlling and reducing drug-related morbidity and mortality. Since no single âgold standardâ ADE data set exists, a range of different drug safety data sets are currently used for developing ADE prediction models. There is a critical need to assess the degree of concordance between these various ADE data sets and to validate ADE prediction models against multiple reference standards. Methods: We systematically evaluated the concordance of two widely used ADE data sets â Lexi-comp from 2010 and SIDER from 2012. The strength of the association between ADE (drug) counts in Lexi-comp and SIDER was assessed using Spearman rank correlation, while the differences between the two data sets were characterized in terms of drug categories, ADE categories and ADE frequencies. We also performed a comparative validation of the Predictive Pharmacosafety Networks (PPN) model using both ADE data sets. The predictive power of PPN using each of the two validation sets was assessed using the area under Receiver Operating Characteristic curve (AUROC). Results: The correlations between the counts of ADEs and drugs in the two data sets were 0.84 (95% CI: 0.82-0.86) and 0.92 (95% CI: 0.91-0.93), respectively. Relative to an earlier snapshot of Lexi-comp from 2005, Lexi-comp 2010 and SIDER 2012 introduced a mean of 1,973 and 4,810 new drug-ADE associations per year, respectively. The difference between these two data sets was most pronounced for Nervous System and Anti-infective drugs, Gastrointestinal and Nervous System ADEs, and postmarketing ADEs. A minor difference of 1.1% was found in the AUROC of PPN when SIDER 2012 was used for validation instead of Lexi-comp 2010. Conclusions: In conclusion, the ADE and drug counts in Lexi-comp and SIDER data sets were highly correlated and the choice of validation set did not greatly affect the overall prediction performance of PPN. Our results also suggest that it is important to be aware of the differences that exist among ADE data sets, especially in modeling applications focused on specific drug and ADE categories
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Pharmacointeraction Network Models Predict Unknown Drug-Drug Interactions
Drug-drug interactions (DDIs) can lead to serious and potentially lethal adverse events. In recent years, several drugs have been withdrawn from the market due to interaction-related adverse events (AEs). Current methods for detecting DDIs rely on the accumulation of sufficient clinical evidence in the post-market stage â a lengthy process that often takes years, during which time numerous patients may suffer from the adverse effects of the DDI. Detection methods are further hindered by the extremely large combinatoric space of possible drug-drug-AE combinations. There is therefore a practical need for predictive tools that can identify potential DDIs years in advance, enabling drug safety professionals to better prioritize their limited investigative resources and take appropriate regulatory action. To meet this need, we describe Predictive Pharmacointeraction Networks (PPINs) â a novel approach that predicts unknown DDIs by exploiting the network structure of all known DDIs, together with other intrinsic and taxonomic properties of drugs and AEs. We constructed an 856-drug DDI network from a 2009 snapshot of a widely-used drug safety database, and used it to develop PPIN models for predicting future DDIs. We compared the DDIs predicted based solely on these 2009 data, with newly reported DDIs that appeared in a 2012 snapshot of the same database. Using a standard multivariate approach to combine predictors, the PPIN model achieved an AUROC (area under the receiver operating characteristic curve) of 0.81 with a sensitivity of 48% given a specificity of 90%. An analysis of DDIs by severity level revealed that the model was most effective for predicting âcontraindicatedâ DDIs (AUROC = 0.92) and less effective for âminorâ DDIs (AUROC = 0.63). These results indicate that network based methods can be useful for predicting unknown drug-drug interactions
An Epidemiological Network Model for Disease Outbreak Detection
Most surveillance systems are not robust to shifts in health care utilization. Ben Reis and colleagues developed network models that detected localized outbreaks better and were more robust to unpredictable shifts
Cosmological Inhomogeneities with Bose-Einstein Condensate Dark Matter
We consider the growth of cosmological perturbations to the energy density of
dark matter during matter domination when dark matter is a scalar field that
has undergone Bose-Einstein condensation. We study these inhomogeneities within
the framework of both Newtonian gravity, where the calculation and results are
more transparent, and General Relativity. The direction we take is to derive
analytical expressions, which can be obtained in the small pressure limit.
Throughout we compare our results to those of the standard cosmology, where
dark matter is assumed pressureless, using our analytical expressions to
showcase precise differences. We find, compared to the standard cosmology, that
Bose-Einstein condensate dark matter leads to a scale factor, gravitational
potential and density contrast that increase at faster rates.Comment: 17 pages, 2 figures; typos corrected, references adde
Dynamics of continuous-time quantum walks in restricted geometries
We study quantum transport on finite discrete structures and we model the
process by means of continuous-time quantum walks. A direct and effective
comparison between quantum and classical walks can be attained based on the
average displacement of the walker as a function of time. Indeed, a fast growth
of the average displacement can be advantageously exploited to build up
efficient search algorithms. By means of analytical and numerical
investigations, we show that the finiteness and the inhomogeneity of the
substrate jointly weaken the quantum walk performance. We further highlight the
interplay between the quantum-walk dynamics and the underlying topology by
studying the temporal evolution of the transfer probability distribution and
the lower bound of long time averages.Comment: 25 pages, 13 figure
Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project
John Brownstein and colleagues discuss HealthMap, an automated real-time system that monitors and disseminates online information about emerging infectious diseases
Measuring the impact of health policies using Internet search patterns: the case of abortion
<p>Abstract</p> <p>Background</p> <p>Internet search patterns have emerged as a novel data source for monitoring infectious disease trends. We propose that these data can also be used more broadly to study the impact of health policies across different regions in a more efficient and timely manner.</p> <p>Methods</p> <p>As a test use case, we studied the relationships between abortion-related search volume, local abortion rates, and local abortion policies available for study.</p> <p>Results</p> <p>Our initial integrative analysis found that, both in the US and internationally, the volume of Internet searches for abortion is inversely proportional to local abortion rates and directly proportional to local restrictions on abortion.</p> <p>Conclusion</p> <p>These findings are consistent with published evidence that local restrictions on abortion lead individuals to seek abortion services outside of their area. Further validation of these methods has the potential to produce a timely, complementary data source for studying the effects of health policies.</p
Suppression of LPS-induced inflammatory responses in macrophages infected with Leishmania
<p>Abstract</p> <p>Background</p> <p>Chronic inflammation activated by macrophage innate pathogen recognition receptors such as TLR4 can lead to a range of inflammatory diseases, including atherosclerosis, Crohn's disease, arthritis and cancer. Unlike many microbes, the kinetoplastid protozoan pathogen <it>Leishmania </it>has been shown to avoid and even actively suppress host inflammatory cytokine responses, such as LPS-induced IL-12 production. The nature and scope of <it>Leishmania</it>-mediated inflammatory cytokine suppression, however, is not well characterized. Advancing our knowledge of such microbe-mediated cytokine suppression may provide new avenues for therapeutic intervention in inflammatory disease.</p> <p>Methods</p> <p>We explored the kinetics of a range of cytokine and chemokine responses in primary murine macrophages stimulated with LPS in the presence versus absence of two clinically distinct species of <it>Leishmania </it>using sensitive multiplex cytokine analyses. To confirm that these effects were parasite-specific, we compared the effects of <it>Leishmania </it>uptake on LPS-induced cytokine expression with uptake of inert latex beads.</p> <p>Results</p> <p>Whilst <it>Leishmania </it>uptake alone did not induce significant levels of any cytokine analysed in this study, <it>Leishmania </it>uptake in the presence of LPS caused parasite-specific suppression of certain LPS-induced pro-inflammatory cytokines, including IL-12, IL-17 and IL-6. Interestingly, <it>L. amazonensis </it>was generally more suppressive than <it>L. major</it>. We also found that other LPS-induced proinflammatory cytokines, such as IL-1Îą, TNF-Îą and the chemokines MIP-1Îą and MCP-1 and also the anti-inflammatory cytokine IL-10, were augmented during <it>Leishmania </it>uptake, in a parasite-specific manner.</p> <p>Conclusions</p> <p>During uptake by macrophages, <it>Leishmania </it>evades the activation of a broad range of cytokines and chemokines. Further, in the presence of a strong inflammatory stimulus, <it>Leishmania </it>suppresses certain proinflammatory cytokine responses in a parasite-specific manner, however it augments the production of other proinflammatory cytokines. Our findings highlight the complexity of inflammatory cytokine signalling regulation in the context of the macrophage and <it>Leishmania </it>interaction and confirm the utility of the <it>Leishmania</it>/macrophage infection model as an experimental system for further studies of inflammatory regulation. Such studies may advance the development of therapies against inflammatory disease.</p
Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.
BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell
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