149 research outputs found

    Identifying Pathway Proteins in Networks using Convergence

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    One of the key goals of systems biology concerns the analysis of experimental biological data available to the scientific public. New technologies are rapidly developed to observe and report whole-scale biological phenomena; however, few methods exist with the ability to produce specific, testable hypotheses from this noisy ‘big’ data. In this work, we propose an approach that combines the power of data-driven network theory along with knowledge-based ontology to tackle this problem. Network models are especially powerful due to their ability to display elements of interest and their relationships as internetwork structures. Additionally, ontological data actually supplements the confidence of relationships within the model without clouding critical structure identification. As such, we postulate that given a (gene/protein) marker set of interest, we can systematically identify the core of their interactions (if they are indeed working together toward a biological function), via elimination of original markers and addition of additional necessary markers. This concept, which we refer to as “convergence,” harnesses the idea of “guilt-by-association” and recursion to identify whether a core of relationships exists between markers. In this study, we test graph theoretic concepts such as shortest-path, k-Nearest- Neighbor and clustering) to identify cores iteratively in data- and knowledge-based networks in the canonical yeast Pheromone Mating Response pathway. Additionally, we provide results for convergence application in virus infection, hearing loss, and Parkinson’s disease. Our results indicate that if a marker set has common discrete function, this approach is able to identify that function, its interacting markers, and any new elements necessary to complete the structural core of that function. The result below find that the shortest path function is the best approach of those used, finding small target sets that contain a majority or all of the markers in the gold standard pathway. The power of this approach lies in its ability to be used in investigative studies to inform decisions concerning target selection

    Efficacy, acceptability, and safety of muscle relaxants for adults with non-specific low back pain: Systematic review and meta-analysis

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    AbstractObjective To investigate the efficacy, acceptability, and safety of muscle relaxants for low back pain. Design Systematic review and meta-analysis of randomised controlled trials. Data sources Medline, Embase, CINAHL, CENTRAL, ClinicalTrials.gov, clinicialtrialsregister.eu, and WHO ICTRP from inception to 23 February 2021. Eligibility criteria for study selection Randomised controlled trials of muscle relaxants compared with placebo, usual care, waiting list, or no treatment in adults (≥18 years) reporting non-specific low back pain. Data extraction and synthesis Two reviewers independently identified studies, extracted data, and assessed the risk of bias and certainty of the evidence using the Cochrane risk-of-bias tool and Grading of Recommendations, Assessment, Development and Evaluations, respectively. Random effects meta-analytical models through restricted maximum likelihood estimation were used to estimate pooled effects and corresponding 95% confidence intervals. Outcomes included pain intensity (measured on a 0-100 point scale), disability (0-100 point scale), acceptability (discontinuation of the drug for any reason during treatment), and safety (adverse events, serious adverse events, and number of participants who withdrew from the trial because of an adverse event). Results 49 trials were included in the review, of which 31, sampling 6505 participants, were quantitatively analysed. For acute low back pain, very low certainty evidence showed that at two weeks or less non-benzodiazepine antispasmodics were associated with a reduction in pain intensity compared with control (mean difference -7.7, 95% confidence interval-12.1 to-3.3) but not a reduction in disability (-3.3, -7.3 to 0.7). Low and very low certainty evidence showed that non-benzodiazepine antispasmodics might increase the risk of an adverse event (relative risk 1.6, 1.2 to 2.0) and might have little to no effect on acceptability (0.8, 0.6 to 1.1) compared with control for acute low back pain, respectively. The number of trials investigating other muscle relaxants and different durations of low back pain were small and the certainty of evidence was reduced because most trials were at high risk of bias. Conclusions Considerable uncertainty exists about the clinical efficacy and safety of muscle relaxants. Very low and low certainty evidence shows that non-benzodiazepine antispasmodics might provide small but not clinically important reductions in pain intensity at or before two weeks and might increase the risk of an adverse event in acute low back pain, respectively. Large, high quality, placebo controlled trials are urgently needed to resolve uncertainty. Systematic review registration PROSPERO CRD42019126820 and Open Science Framework https://osf.io/mu2f5/

    Evolution of associative learning in chemical networks

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    Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

    Lignin biomarkers as tracers of mercury sources in lakes water column

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    This study presents the role of specific terrigenous organic compounds as important vectors of mercury (Hg) transported from watersheds to lakes of the Canadian boreal forest. In order to differentiate the autochthonous from the allochthonous organic matter (OM), lignin derived biomarker signatures [Lambda, S/V, C/V, P/(V ? S), 3,5-Bd/V and (Ad/Al)v] were used. Since lignin is exclusively produced by terrigenous plants, this approach can give a non equivocal picture of the watershed inputs to the lakes. Moreover, it allows a characterization of the source of OM and its state of degradation. The water column of six lakes from the Canadian Shield was sampled monthly between June and September 2005. Lake total dissolved Hg concentrations and Lambda were positively correlated, meaning that Hg and ligneous inputs are linked (dissolved OM r2 = 0.62, p\0.0001; particulate OM r2 = 0.76, p\0.0001). Ratios of P/(V ? S) and 3,5-Bd/V from both dissolved OM and particulate OM of the water column suggest an inverse relationship between the progressive state of pedogenesis and maturation of the OM in soil before entering the lake, and the Hg concentrations in the water column. No relation was found between Hg levels in the lakes and the watershed flora composition—angiosperm versus gymnosperm or woody versus non-woody compounds. This study has significant implications for watershed management of ecosystems since limiting fresh terrestrial OM inputs should reduce Hg inputs to the aquatic systems. This is particularly the case for largescale land-use impacts, such as deforestation, agriculture and urbanization, associated to large quantities of soil OM being transferred to aquatic systems

    Influenza Virus Respiratory Infection and Transmission Following Ocular Inoculation in Ferrets

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    While influenza viruses are a common respiratory pathogen, sporadic reports of conjunctivitis following human infection demonstrates the ability of this virus to cause disease outside of the respiratory tract. The ocular surface represents both a potential site of virus replication and a portal of entry for establishment of a respiratory infection. However, the properties which govern ocular tropism of influenza viruses, the mechanisms of virus spread from ocular to respiratory tissue, and the potential differences in respiratory disease initiated from different exposure routes are poorly understood. Here, we established a ferret model of ocular inoculation to explore the development of virus pathogenicity and transmissibility following influenza virus exposure by the ocular route. We found that multiple subtypes of human and avian influenza viruses mounted a productive virus infection in the upper respiratory tract of ferrets following ocular inoculation, and were additionally detected in ocular tissue during the acute phase of infection. H5N1 viruses maintained their ability for systemic spread and lethal infection following inoculation by the ocular route. Replication-independent deposition of virus inoculum from ocular to respiratory tissue was limited to the nares and upper trachea, unlike traditional intranasal inoculation which results in virus deposition in both upper and lower respiratory tract tissues. Despite high titers of replicating transmissible seasonal viruses in the upper respiratory tract of ferrets inoculated by the ocular route, virus transmissibility to naïve contacts by respiratory droplets was reduced following ocular inoculation. These data improve our understanding of the mechanisms of virus spread following ocular exposure and highlight differences in the establishment of respiratory disease and virus transmissibility following use of different inoculation volumes and routes

    Impact of Chromatin Structures on DNA Processing for Genomic Analyses

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    Chromatin has an impact on recombination, repair, replication, and evolution of DNA. Here we report that chromatin structure also affects laboratory DNA manipulation in ways that distort the results of chromatin immunoprecipitation (ChIP) experiments. We initially discovered this effect at the Saccharomyces cerevisiae HMR locus, where we found that silenced chromatin was refractory to shearing, relative to euchromatin. Using input samples from ChIP-Seq studies, we detected a similar bias throughout the heterochromatic portions of the yeast genome. We also observed significant chromatin-related effects at telomeres, protein binding sites, and genes, reflected in the variation of input-Seq coverage. Experimental tests of candidate regions showed that chromatin influenced shearing at some loci, and that chromatin could also lead to enriched or depleted DNA levels in prepared samples, independently of shearing effects. Our results suggested that assays relying on immunoprecipitation of chromatin will be biased by intrinsic differences between regions packaged into different chromatin structures - biases which have been largely ignored to date. These results established the pervasiveness of this bias genome-wide, and suggested that this bias can be used to detect differences in chromatin structures across the genome

    Heterogeneous shedding of influenza by human subjects and its implications for epidemiology and control

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    International audienceHeterogeneity of infectiousness is an important feature of the spread of many infections, with implications for disease dynamics and control, but its relevance to human influenza virus is still unclear. For a transmission event to occur, an infected individual needs to release infectious particles via respiratory symptoms. Key factors to take into account are virus dynamics, particle release in relation to respiratory symptoms, the amount of virus shed and, importantly, how these vary between infected individuals. A quantitative understanding of the process of influenza transmission is relevant to designing effective mitigation measures. Here we develop an influenza infection dynamics model fitted to virological, systemic and respiratory symptoms to investigate how within-host dynamics relates to infectiousness. We show that influenza virus shedding is highly heterogeneous between subjects. From analysis of data on experimental infections, we find that a small proportion (<20%) of influenza infected individuals are responsible for the production of 95% of infectious particles. Our work supports targeting mitigation measures at most infectious subjects to efficiently reduce transmission. The effectiveness of public health interventions targeted at highly infectious individuals would depend on accurate identification of these subjects and on how quickly control measures can be applied

    Neighbor Overlap Is Enriched in the Yeast Interaction Network: Analysis and Implications

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    The yeast protein-protein interaction network has been shown to have distinct topological features such as a scale free degree distribution and a high level of clustering. Here we analyze an additional feature which is called Neighbor Overlap. This feature reflects the number of shared neighbors between a pair of proteins. We show that Neighbor Overlap is enriched in the yeast protein-protein interaction network compared with control networks carefully designed to match the characteristics of the yeast network in terms of degree distribution and clustering coefficient. Our analysis also reveals that pairs of proteins with high Neighbor Overlap have higher sequence similarity, more similar GO annotations and stronger genetic interactions than pairs with low ones. Finally, we demonstrate that pairs of proteins with redundant functions tend to have high Neighbor Overlap. We suggest that a combination of three mechanisms is the basis for this feature: The abundance of protein complexes, selection for backup of function, and the need to allow functional variation
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