Isolation, structure elucidation, and synthesis of antiplasmodial quinolones from Crinum firmifolium
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The long-lived positron emitter 89 Zr is a highly promising nuclide employed in diagnostic Positron Emission Tomography (PET) imaging. Methods of radiochemical processing to obtain 89 Zr for clinical use are traditionally performed with a single hydroxamate resin column. In this work, we present a tandem column purification method for the preparation of high-purity 89 Zr from cyclotron bombarded Y metal foils. The primary column is a macroporous, strongly basic anion exchange resin on styrene divinylbenzene co-polymer. The secondary microcolumn, with an internal volume of 33 µL, is packed with an extraction chromatography resin (ExCR) loaded with HDEHP. A condition of “inverted selectivity” is presented, wherein the 89 Zr elution from the primary column is synonymous with the load condition on the secondary column. The ability to transfer 89 Zr from one column to the next allows two sequential column clean-up methods to be performed prior to the final elution of the 89 Zr product. This approach assures delivery of very high purity 89 Zr . The tandem column purification process has been implemented into a prototype automated fluidic system. Optimization of the method is presented, followed by evaluation of the process using seven cyclotron bombarded Y metal foil targets. Once optimized, we found that 93.7±2.3% of the 89 Zr present in the foils was recovered in the secondary column elution fraction (0.8 M oxalic acid). Radiochromatograms of the product elution peaks enabled determination of full width at half-maximum (FWHM) and 89 Zr collection yields as a function of volume. Because of the small size of the secondary microcolumn, a 89 Zr product volume of ~0.28 mL is reported, which provides a substantially increased nuclide concentration over traditional methods. Finally, we evaluated the transchelation of the resulting 89 Zr oxalate product to deferoxamine mesylate (DFOM) salt. We observed effective specific activities (ESA) and bindable metals concentrations ([M B ]) that exceed those reported by the traditional single hydroxamate column method.
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We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.
Phosphatase-mediated hydrolysis of organic phosphate may be a viable means of stabilizing heavy metals via precipitation as a metal phosphate in bioremediation applications. We investigated the effect of triethyl phosphate (TEP) on soil microbial-phosphatase activity in a heavy-metal contaminated soil. Gaseous TEP has been used at subsurface sites for bioremediation of organic contaminants but not applied in heavy-metal contaminated areas. Little is known about how TEP affects microbial activity in soils and it is postulated that TEP can serve as a phosphate source in nutrient-poor groundwater and soil/sediments. Over a 3-week period, TEP amendment to microcosms containing heavy-metal contaminated soil resulted in increased activity of soil acid-phosphatase and repression of alkaline phosphatase, indicating a stimulatory effect on the microbial population. A soil-free enrichment of microorganisms adapted to heavy-metal and acidic conditions was derived from the TEP-amended soil microcosms using TEP as the sole phosphate source and the selected microbial consortium maintained a high acid-phosphatase activity with repression of alkaline phosphatase. Addition of 5 mM zinc to soil-free microcosms had little effect on acid phosphatase but inhibited alkaline phosphatase. One bacterial member from the consortium, identified as Burkholderia cepacia sp., expressed an acid-phosphatase activity uninhibited by high concentrations of zinc and produced a soluble, indigo pigment under phosphate limitation. The pigment was produced in a phosphate-free medium and was not produced in the presence of TEP or phosphate ion, indicative of purple acid-phosphatase types that are pressed by bioavailable phosphate. Finally, these results demonstrate that TEP amendment was bioavailable and increased overall phosphatase activity in both soil and soil-free microcosms supporting the possibility of positive outcomes in bioremediation applications.
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Highlights: • ROS levels in frog skin biopsy were determined by spin-trapping ESR spectroscopy. • Skin of frogs collected in polluted areas contains higher ROS concentration. • ROS levels determined in skin biopsy follow the same trend of those from liver samples. • Immunohistochemical analyses and enzymatic activity tests validate the method. • ROS concentration determined by ESR in biosentinel biopsy is an effective biomarker. Reactive oxygen species (ROS) in biological tissues of elected biosentinels represent an optimal biomarker for eco-monitoring of polluted areas. Electron spin resonance (ESR) is the most definitive method for detecting, quantifying and possibly identifying radicals in complex systems.
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Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.
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