45 research outputs found

    The Pathogenic Potential of Campylobacter concisus Strains Associated with Chronic Intestinal Diseases

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    Campylobacter concisus has garnered increasing attention due to its association with intestinal disease, thus, the pathogenic potential of strains isolated from different intestinal diseases was investigated. A method to isolate C. concisus was developed and the ability of eight strains from chronic and acute intestinal diseases to adhere to and invade intestinal epithelial cells was determined. Features associated with bacterial invasion were investigated using comparative genomic analyses and the effect of C. concisus on host protein expression was examined using proteomics. Our isolation method from intestinal biopsies resulted in the isolation of three C. concisus strains from children with Crohn's disease or chronic gastroenteritis. Four C. concisus strains from patients with chronic intestinal diseases can attach to and invade host cells using mechanisms such as chemoattraction to mucin, aggregation, flagellum-mediated attachment, “membrane ruffling”, cell penetration and damage. C. concisus strains isolated from patients with chronic intestinal diseases have significantly higher invasive potential than those from acute intestinal diseases. Investigation of the cause of this increased pathogenic potential revealed a plasmid to be responsible. 78 and 47 proteins were upregulated and downregulated in cells infected with C. concisus, respectively. Functional analysis of these proteins showed that C. concisus infection regulated processes related to interleukin-12 production, proteasome activation and NF-ÎșB activation. Infection with all eight C. concisus strains resulted in host cells producing high levels of interleukin-12, however, only strains capable of invading host cells resulted in interferon-Îł production as confirmed by ELISA. These findings considerably support the emergence of C. concisus as an intestinal pathogen, but more significantly, provide novel insights into the host immune response and an explanation for the heterogeneity observed in the outcome of C. concisus infection. Moreover, response to infection with invasive strains has substantial similarities to that observed in the inflamed mucosa of Crohn's disease patients

    Comparison of deterministic and statistical models for water quality compliance forecasting in the San Joaquin river basin, California

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    Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020
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