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Weinreich Vasquez posted an update 6 months ago
The emergence of carbapenem-resistant (CR) Escherichia coli obliges an assessment of such strains’ molecular epidemiology. Accordingly, we characterized in detail a globally distributed collection of CR E. coli isolates, then explored for associations between geographical origin and bacterial traits, and between different bacterial traits. We used established PCR-based assays and broth microdilution MIC determinations to characterize 343 global CR (i.e., non-susceptible to ≥ 1 carbapenem) extraintestinal E. coli isolates (2002-2017) for diverse molecular traits-including phylogroups, sequence types (STs), beta-lactamase genes, and 51 virulence genes-and susceptibility to 12 relevant antimicrobial agents. The study population was tremendously diverse according to all assessed variables. Nonetheless, certain geographically aligned, unifying themes emerged. These included an association of an Asia/West Pacific origin with non-B2/D/F phylogroups and STs, lower molecularly inferred virulence, more extensive resistance, and specific resistance genes (notably, metallo-beta-lactamases). Likewise, U.S. isolates from the central region, vs. other regions, were more virulent-appearing and more often from phylogroup B2 and ST131, but less extensively resistant and more often carbapenemase-gene negative. The global CR E. coli population is highly diverse according to multiple characteristics and varies significantly by geographical region. This predictably will pose challenges for prevention and management, and obliges ongoing surveillance.Environmental and energy security has now become a serious global problem, requiring a lot of research to find and implement its cost-effective and environmentally friendly alternatives. Ro-3306 price The development and use of renewable energy sources is necessary and important in order to avoid the emergence of a global economic crisis. One of the solution to prevent a future crisis caused by energy shortages is to introduce biofuels into the fuel market. Despite the fact that various forms of renewable energy are currently used, the prospects for the production of biofuels from cyanobacteria are quite high due to their unique properties, such as a high lipid content and a suitable fatty acid (FA) composition for the production of biofuels, their suitability for growing open water and the ability to grow on wastewater. The purpose of this article is to provide a comprehensive overview of the potential of cyanobacteria in the conversion of wastewater into biofuels. The article covers comparative data on the accumulation of lipids and the content of fatty acids in various representatives of cyanobacteria and their possibilities in the remediation of wastewater. Various approaches to the extraction of lipids from phototrophic microorganisms that are currently available, their advantages and disadvantages, and the results of the monitoring of the main key points of the development of the technology for converting cyanobacterial biomass into biofuels, with an emphasis on the existing barriers, effects and solutions, are also considered. Further research in this field is required for the successful implementation of this technology on an industrial scale.
The Edmonton Symptom Assessment System-Revised Renal (ESAS-r Renal) is a disease-specific patient-reported outcome measure (PROM) that assesses symptoms common in chronic kidney disease (CKD). There is no preference-based scoring system for the ESAS-r Renal or a mapping algorithm to predict health utility values. We aimed to develop a mapping algorithm from the ESAS-r Renal to the Canadian EQ-5D-5L index scores.
We used data from a multi-centre cluster randomized-controlled trial of the routine measurement and reporting of PROMs in hemodialysis units in Northern Alberta, Canada. In two arms of the trial, both the ESAS-r Renal and the EQ-5D-5L were administered to CKD patients undergoing hemodialysis. We used data from one arm for model estimation, and data from the other for validation. We explored direct and indirect mapping models; model selection was based on statistical fit and predictive power.
Complete data were available for 506 patient records in the estimation sample and 242 in the validation sample. All models tended to perform better in patients with good health, and worse in those with poor health. Generalized estimating equations (GEE) and generalized linear model (GLM) on selected ESAS-r Renal items were selected as final models as they fitted the best in estimation and validation sample.
When only ESAS-r Renal data are available, one could use GEE and GLM to predict EQ-5D-5L index scores for use in economic evaluation. External validation on populations with different characteristics is warranted, especially where renal-specific symptoms are more prevalent.
When only ESAS-r Renal data are available, one could use GEE and GLM to predict EQ-5D-5L index scores for use in economic evaluation. External validation on populations with different characteristics is warranted, especially where renal-specific symptoms are more prevalent.Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum-mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, pKa) and SAMPL6.2 (octanol-water partition coefficients, log P) the methodology was applied to the recent SAMPL7 physical property challenge on aqueous pKa and octanol-water log P values. Not part of the challenge but provided by the organizers, we also computed distribution coefficients log D7.4 from predicted pKa and log P data. While macroscopic pKa predictions compared very favorably with experimental data (root mean square error, RMSE 0.72 pK units), the performance of the log P model (RMSE 1.84) fell behind expectations from the SAMPL6.2 challenge, leading to reasonable log D7.4 predictions (RMSE 1.69) from combining the independent calculations. In the post-submission phase, conformations generated by different methodology yielded results that did not significantly improve the original predictions. While overall satisfactory compared to previous log D challenges, the predicted data suggest that further effort is needed for optimizing the robustness of the partition coefficient model within EC-RISM calculations and for shaping the agreement between experimental conditions and the corresponding model description.
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