22 research outputs found

    Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

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    Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

    Surveillance of Carbapenem-Resistant Klebsiella pneumoniae: Tracking Molecular Epidemiology and Outcomes through a Regional Network

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    ABSTRACT Carbapenem resistance in Gram-negative bacteria is on the rise in the United States. A regional network was established to study microbiological and genetic determinants of clinical outcomes in hospitalized patients with carbapenem-resistant (CR) Klebsiella pneumoniae in a prospective, multicenter, observational study. To this end, predefined clinical characteristics and outcomes were recorded and K. pneumoniae isolates were analyzed for strain typing and resistance mechanism determination. In a 14-month period, 251 patients were included. While most of the patients were admitted from long-term care settings, 28% of them were admitted from home. Hospitalizations were prolonged and complicated. Nonsusceptibility to colistin and tigecycline occurred in isolates from 7 and 45% of the patients, respectively. Most of the CR K. pneumoniae isolates belonged to repetitive extragenic palindromic PCR (rep-PCR) types A and B (both sequence type 258) and carried either bla KPC-2 (48%) or bla KPC-3 (51%). One isolate tested positive for bla NDM-1 , a sentinel discovery in this region. Important differences between strain types were noted; rep-PCR type B strains were associated with bla KPC-3 (odds ratio [OR], 294; 95% confidence interval [CI], 58 to 2,552; P < 0.001), gentamicin nonsusceptibility (OR, 24; 95% CI, 8.39 to 79.38; P < 0.001), amikacin susceptibility (OR, 11.0; 95% CI, 3.21 to 42.42; P < 0.001), tigecycline nonsusceptibility (OR, 5.34; 95% CI, 1.30 to 36.41; P = 0.018), a shorter length of stay (OR, 0.98; 95% CI, 0.95 to 1.00; P = 0.043), and admission from a skilled-nursing facility (OR, 3.09; 95% CI, 1.26 to 8.08; P = 0.013). Our analysis shows that (i) CR K. pneumoniae is seen primarily in the elderly long-term care population and that (ii) regional monitoring of CR K. pneumoniae reveals insights into molecular characteristics. This work highlights the crucial role of ongoing surveillance of carbapenem resistance determinants

    Water Flow and Biofilm Cover Influence Environmental DNA Detection in Recirculating Streams

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    The increasing use of environmental DNA (eDNA) for determination of species presence in aquatic ecosystems is an invaluable technique for both ecology as a field and for the management of aquatic ecosystems. We examined the degradation dynamics of fish eDNA using an experimental array of recirculating streams, also using a “nested” primer assay to estimate degradation among eDNA fragment sizes. We introduced eDNA into streams with a range of water velocities (0.1–0.8 m s–1) and substrate biofilm coverage (0–100%) and monitored eDNA concentrations over time (∌10 d) to assess how biophysical conditions influence eDNA persistence. We found that the presence of biofilm significantly increased initial decay rates relative to previous studies conducted in nonflowing microcosms, suggesting important differences in detection and persistence in lentic vs lotic systems. Lastly, by using a nested primer assay that targeted different size eDNA fragments, we found that fragment size altered both the estimated rate constant coefficients, as well as eDNA detectability over time. Larger fragments (\u3e600 bp) were quickly degraded, while shorter fragments (\u3c100 \u3ebp) remained detectable for the entirety of the experiment. When using eDNA as a stream monitoring tool, understanding environmental factors controlling eDNA degradation will be critical for optimizing eDNA sampling strategies

    Water Flow and Biofilm Cover Influence Environmental DNA Detection in Recirculating Streams

    Get PDF
    The increasing use of environmental DNA (eDNA) for determination of species presence in aquatic ecosystems is an invaluable technique for both ecology as a field and for the management of aquatic ecosystems. We examined the degradation dynamics of fish eDNA using an experimental array of recirculating streams, also using a “nested” primer assay to estimate degradation among eDNA fragment sizes. We introduced eDNA into streams with a range of water velocities (0.1–0.8 m s<sup>–1</sup>) and substrate biofilm coverage (0–100%) and monitored eDNA concentrations over time (∌10 d) to assess how biophysical conditions influence eDNA persistence. We found that the presence of biofilm significantly increased initial decay rates relative to previous studies conducted in nonflowing microcosms, suggesting important differences in detection and persistence in lentic vs lotic systems. Lastly, by using a nested primer assay that targeted different size eDNA fragments, we found that fragment size altered both the estimated rate constant coefficients, as well as eDNA detectability over time. Larger fragments (>600 bp) were quickly degraded, while shorter fragments (<100 bp) remained detectable for the entirety of the experiment. When using eDNA as a stream monitoring tool, understanding environmental factors controlling eDNA degradation will be critical for optimizing eDNA sampling strategies
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