Targeted Nitric Oxide Delivery by Supramolecular Nanofibers for the Prevention of Restenosis After Arterial Injury
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MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.
This report describes the results for a coupled target-beam-moderator optimization analysis for the Second Target Station (STS) at ORNL's Spallation Neutron Source. This study is a continuation of the optimization analysis for the moderators in the preliminary design of STS performed in 2022. In the 2022 analysis the dimensions of the moderators are parameterized, while the target and the proton beam profile are kept constant. In this analysis the target height and the proton beam profile are added as parameters. This allows to study the coupled effects of changing target, moderator and beam dimensions. Similar to the 2022 analysis, this work is performed with an automated optimization workflow that uses the optimization toolbox DAKOTA, parameterized geometries in CREO and SpaceClaim, the unstructured mesh generation in Attila4MC, and the particle transport code MCNP6.2©. This workflow enables an efficient optimization using high-fidelity geometries. The main conclusions of this analysis are the following: • Coupled beam-target-moderator optimization provides a few additional percent performance gain over stand-alone moderator optimization. • The moderator performance is not very sensitive to the target height (between ≈60 and ≈80 mm) as long as the beam profile is chosen adequately. • The moderator performance is sensitive to the choice of beam spatial standard deviations, even when the footprint is kept constant. • The optimal moderator radius is the same for a beam footprint of 30 cm 2 , 62.5 cm 2 , and 90 cm 2 . Also the slope of the super-gaussian beam profile does not significantly impact the optimal moderator radius. • The optimal parameters and sensitivities are very similar to the 2022 optimization analysis. These results only indicate a a difference in the optimal radius of the cylindrical moderator, however, this has been corrected in the final design moderator optimization. The main purpose of this report is to document the simulations, results and lessons learned. The most impactful results are summarized in. We also note that the target geometry used in this work is not the final design.
Here, we describe the algorithm used to select the luminous red galaxy (LRG) sample for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV) using photometric data from both the SDSS and the Wide-field Infrared Survey Explorer. LRG targets are required to meet a set of color selection criteria and have z-band and i-band MODEL magnitudes z < 19.95 and 19.9 < i < 21.8, respectively. Our algorithm selects roughly 50 LRG targets per square degree, the great majority of which lie in the redshift range 0.6 < z < 1.0 (median redshift 0.71). We also demonstrate that our methods are highly effective at eliminating stellar contamination and lower-redshift galaxies. We perform a number of tests using spectroscopic data from SDSS-III/BOSS ancillary programs to determine the redshift reliability of our target selection and its ability to meet the science requirements of eBOSS. The SDSS spectra are of high enough signal-to-noise ratio that at least ~89% of the target sample yields secure redshift measurements. Finally, we present tests of the uniformity and homogeneity of the sample, demonstrating that it should be clean enough for studies of the large-scale structure of the universe at higher redshifts than SDSS-III/BOSS LRGs reached.
CRISPR-Cas systems have become ubiquitous for genome editing in eukaryotic as well as bacterial systems. Cas9 forms a complex with a guide RNA (gRNA) and searches DNA for a matching sequence (target site) next to a protospacer adjacent motif (PAM). Once found, Cas9 cuts the DNA. Cas9 is revolutionary for the ability to change the RNA sequence and target a new site easily. However, while algorithms have been developed to predict gRNA-specific Cas9 activity, a fundamental biological understanding of gRNA-specific activity is lacking. Here, the number of PAM sites in the genome is effectively a large pool of inhibitory substrates, competing with the target site for the Cas9/gRNA complex. We demonstrate that increasing the number of non-target sites for a given gRNA reduces on-target activity in a dose-dependent manner. Furthermore, we show that the use of Cas9 mutants with increased PAM specificity toward a smaller subset of PAMs (or smaller pool of competitive substrates) improves cutting rates, while increased PAM promiscuity decreases cutting rates. Decreasing the potential search space by increasing PAM specificity provides a path toward improving on-target activity for slower high-fidelity Cas9 variants. Engineering improved PAM specificity to reduce the competitive search space offers an alternative strategy to engineer Cas9 variants with increased specificity and maintained on-target activity.
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Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.
Purpose: Alpha-emitting radionuclides exhibit a potential advantage for cancer treatments because they release large amounts of ionizing energy over a few cell diameters (50–80 μm), causing localized, irreparable double-strand DNA breaks that lead to cell death. Radioimmunotherapy (RIT) approaches using monoclonal antibodies labeled with α emitters may thus inactivate targeted cells with minimal radiation damage to surrounding tissues. Tools are needed to visualize and quantify the radioactivity distribution and absorbed doses to targeted and nontargeted cells for accurate dosimetry of all treatment regimens utilizing α particles, including RIT and others (e.g., Ra-223), especially for organs and tumors with heterogeneous radionuclide distributions. The aim of this study was to evaluate and characterize a novel single-particle digital autoradiography imager, the ionizing-radiation quantum imaging detector (iQID) camera, for use in α-RIT experiments. Methods: The iQID camera is a scintillator-based radiation detection system that images and identifies charged-particle and gamma-ray/x-ray emissions spatially and temporally on an event-by-event basis. It employs CCD-CMOS cameras and high-performance computing hardware for real-time imaging and activity quantification of tissue sections, approaching cellular resolutions. In this work, the authors evaluated its characteristics for α-particle imaging, including measurements of intrinsic detector spatial resolutions and background count rates at various detector configurations and quantification of activity distributions. The technique was assessed for quantitative imaging of astatine-211 ({sup 211}At) activity distributions in cryosections of murine and canine tissue samples. Results: The highest spatial resolution was measured at ∼20 μm full width at half maximum and the α-particle background was measured at a rate as low as (2.6 ± 0.5) × 10{sup −4} cpm/cm{sup 2} (40 mm diameter detector area). Simultaneous imaging of multiple tissue sections was performed using a large-area iQID configuration (ø 11.5 cm). Estimation of the {sup 211}At activity distribution was demonstrated at mBq/μg-levels. Conclusions: Single-particle digital autoradiography of α emitters has advantages over traditional film-based autoradiographic techniques that use phosphor screens, in terms of spatial resolution, sensitivity, and activity quantification capability. The system features and characterization results presented in this study show that the iQID is a promising technology for microdosimetry, because it provides necessary information for interpreting alpha-RIT outcomes and for predicting the therapeutic efficacy of cell-targeted approaches using α emitters.
This report details the specifics of applying the Position-Averaged Method to the target wedges and staves. The methodology used to calculate the decay gamma sources for a single target wedge to the calculation of the Second Target Station (STS) target assembly activation and the resulting decay gamma source terms are detailed in this report. The methodology has been applied to the entire STS target assembly including all of the target wedges, staves, shaft, and drive. The target staves and shaft have been vertically segmented to ensure the decay gamma source gradient is sufficiently captured. MCNP ® Code Version 6.2.0 with the RNUCS patch coupled with CINDER2008 from the AARE V1.0 package are the main tools used to calculate the decay gamma source terms.
We report on the successful operation of a newly developed cryogenic jet target at high intensity laser-irradiation. Using the frequency-doubled Titan short pulse laser system at Jupiter Laser Facility, Lawrence Livermore National Laboratory, we demonstrate the generation of a pure proton beam a with maximum energy of 2 MeV. Furthermore, we record a quasi-monoenergetic peak at 1.1 MeV in the proton spectrum emitted in the laser forward direction suggesting an alternative acceleration mechanism. Using a solid-density mixed hydrogen-deuterium target, we are also able to produce pure proton-deuteron ion beams. With its high purity, limited size, near-critical density, and high-repetition rate capability, this target is promising for future applications.
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Highlights: • Advances in mass spectrometry have expanded our knowledge of lipids. • Targeted and non-targeted lipidomics are powerful strategies with distinct features. • We briefly review the applications of these lipidomics strategies in lipid research. • Current limitations and challenges in lipidomics are also discussed. Recent advances in mass spectrometry have expanded our knowledge of lipids and lipid metabolic pathways involved in many (patho)physiological events. Targeted and non-targeted lipidomics are powerful analytical strategies with distinct features, and a combination of these two approaches is often employed to maximize the coverage of lipid species detected and quantified in complex biological matrices. This review briefly summarizes the applications of targeted and non-targeted lipidomics, mainly focusing on electrospray ionization–liquid chromatography–tandem mass spectrometry (ESI–LC–MS/MS), along with recent technical advances in the field. Current limitations and challenges in lipidomics and possible solutions are also discussed.
To support the design of the Second Target Station, that aims to provide the world’s highest peak brightness of cold neutrons, studies that optimize the dimensions of the target and moderators are invaluable. In this work, we investigate the influence of the target dimensions and beam profile on the performance and optimal size of the moderators. We perform optimization runs with detailed MCNP6.2 simulations using high-fidelity unstructured mesh geometries generated from parametrized CAD models. We demonstrate that small changes in target height do not influence the moderator performance if the beam dimensions are chosen adequately. We quantify the effect of beam footprint and target width on the moderator performance and show that the optimal moderator dimensions are insensitive to limited changes in target and beam profile.