Applications of Thermochemical Modeling in Molten Salt Reactors.

The extensively evaluated and consistent thermodynamic database, the Molten Salt Thermal Properties Database-Thermochemical (MSTDB-TC), was used along with additional thermodynamic values from other sources as examples of ways to examine molten salt reactor (MSR) fuel behavior. Relative stability with respect to halide potential and temperature for likely fuel and fission product components were mapped in Ellingham diagrams for the chloride and fluoride systems. The Ellingham diagrams provide a rich, visual means for identifying halide-forming components in proposed fuel/solvent salt systems. Thermochemical models and values from MSTDB-TC and ancillary sources were used in global equilibrium calculations to provide compositions for a close analysis of the behavior of a possible Molten Chloride Salt Fast Reactor and a Molten Salt Reactor Experiment-type system at high burnup (100 GWd/t). The results illustrated the oxidative nature of burnup in MSRs and provided information about redox behavior and possible control.

Ultra-high throughput mapping of genetic design space.

Massively parallel genetic screens have been used to map sequence-to-function relationships for a variety of genetic elements. However, because these approaches only interrogate short sequences, it remains challenging to perform high throughput (HT) assays on constructs containing combinations of sequence elements arranged across multi-kb length scales. Overcoming this barrier could accelerate synthetic biology; by screening diverse gene circuit designs, "composition-to-function" mappings could be created that reveal genetic part composability rules and enable rapid identification of behavior-optimized variants. Here, we introduce CLASSIC, a generalizable genetic screening platform that combines long- and short-read next-generation sequencing (NGS) modalities to quantitatively assess pooled libraries of DNA constructs of arbitrary length. We show that CLASSIC can measure expression profiles of >10 5 drug-inducible gene circuit designs (ranging from 6-9 kb) in a single experiment in human cells. Using statistical inference and machine learning (ML) approaches, we demonstrate that data obtained with CLASSIC enables predictive modeling of an entire circuit design landscape, offering critical insight into underlying design principles. Our work shows that by expanding the throughput and understanding gained with each design-build-test-learn (DBTL) cycle, CLASSIC dramatically augments the pace and scale of synthetic biology and establishes an experimental basis for data-driven design of complex genetic systems.

Modified electrospun chitosan membranes for controlled release of simvastatin.

Chitosan nanofibrous membranes have immense potential in tissue engineering and drug delivery applications because of their increased surface area, high degree of biocompatibility, and their ability to mimic the extracellular matrix. However, their use is often limited due to their extreme hydrophilic nature causing them to lose their nanofibrous structure in vivo. In the present study, chitosan membranes were modified either by acylation reactions using fatty acids of different chain lengths or tert-butyloxycarbonyl (tBOC) protecting groups to increase the hydrophobicity of the membranes and protect the nanofibrous structure. The modified membranes were characterized using scanning electron microscopy, attenuated total reflectance Fourier transform infrared spectroscopy, water contact angle and elemental analysis to confirm the addition of the modification groups. These membranes were then evaluated to control the release of a hydrophobic osteogenic drug-simvastatin (SMV). The interaction between SMV and the polymer was determined using molecular modeling. Pure SMV and SMV loaded membranes were examined for their in vitro cytotoxicity and osteogenic potential using preosteoblast mouse bone marrow stromal cells. From results, it was evident that as the fatty acid chain length increased from two to six methylene groups, the hydrophobicity of the membranes increased (59.2 ± 8.2° to 94.3 ± 8.5° water contact angle). The amount of drug released from the membranes could be controlled by changing the amount of initial drug loaded and/or the type of modifications. After 4 weeks, for a 500 µg loading, the short chain fatty acid modified membranes released 17.8 ± 3.2% of the drug whereas a long chain fatty acid released only 4.8 ± 0.8%. Similarly, for a 50 µg loading, short chain modified membranes released more (73.3 ± 33.3%) of the loaded drug as compared to the long chain membranes (43.0 ± 3.5%). The long chain fatty acid membranes released SMV for extended time periods of up to 90 days. This data was further supported by molecular modeling, which revealed that SMV was more compatible with more hydrophobic membranes. Cell studies showed that pure SMV from 75 to 600 ng/ml range possessed osteogenic potential in a dose dependent manner and the amount of SMV released from the most hydrophobic FA treated membranes was not cytotoxic and supported osteogenic differentiation. Therefore, this study demonstrates our ability to control the release of a hydrophobic drug from modified chitosan membranes as per the clinical need.

Proline derived guanidine catalysts forge extensive H-bonded architectures: a solution and solid state study.

The preparation of a range of amino acid derived guanidine organocatalysts is reported together with their application to the Michael addition of 2-hydroxy-1,4-napthoquinone to ß-nitrostyrene, achieving a maximum ee of 56%. Some insight into the mechanism was sought by using X-ray crystallography and a detailed study of the intra- and intermolecular hydrogen bonding is reported.