In the last few years, utilizing fiber reinforced additive manufacturing (FRAM)-based components in several industries has become quite popular. Compared to conventional AM technologies, FRAM offered complementary solutions to their needs. In general, fibers have been traditionally used in many manufacturing processes for various reasons. However, using conventional methods, there are obstacles in obtaining the desired complex geometries and low setup costs. AM offers possible avoidance of these limitations. Shape complexity, infill density, and manufacturing lead times are no longer barriers. Bridging AM with fiber reinforced materials offers a vast opportunity for lightweight and strong parts. Depending on the affinity, fibers with different structures can be mixed with different matrix materials and, thus, create stronger parts with improved mechanical properties. Process parameters like raster angle, infill speed, layer thickness, and nozzle temperature also strongly impact physical properties of FRAM products and are considered carefully. FRAM-based components are used in many industries such as aerospace, motorsports, and biomedicine, where the weight, strength, and complexity of parts are critical. Hence, numerous industrial companies and research facilities are investigating the implementation and adaptation of FRAM to their requirements. Studies are generally conducted on new materials, new FRAM technologies, the effect of fiber orientations and fraction on the performance of parts, improving the printing parameters, and other subjects. Furthermore, this study reports the current trends and challenges that FRAM is bringing to AM ecosystem.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Citrus bioflavonoids dipeptidyl peptidase-4 inhibition compared with gliptin antidiabetic medications

Highlights: • The citrus bioflavonoids may possess dipeptidyl peptidase-4 (DPP-4) inhibition activity similar to gliptins. • Various citrus bioflavonoids may have a variable DPP-4 inhibition activity. • The measurement of the DPP-4 inhibition activity can be done using DPP-4 inhibition kit. • Commercial citrus bioflavonoid supplements contain various citrus bioflavonoids with different DPP-4 inhibition activities. This study compared dipeptidyl peptidase-4 (DPP-4) inhibitory activity of citrus bioflavonoid nutraceuticals compared with three gliptins. Citrus bioflavonoid standards and three commercially available citrus bioflavonoid supplements (Thompson's Super Bioflavonoid Complex{sup ®}(SB), Ethical Nutrients Bioflavonoids Plus Vitamin C{sup ®}(EN), and Country Life Citrus Bioflavonoids and Rutin{sup ®}(CB)) were considered in this study. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis was undertaken to identify and quantitate the citrus bioflavonoids present in each supplement. The DPP-4 inhibitory activity was determined by fluorometric assay. All of the tested individual citrus flavonoids demonstrated DPP-4 inhibitory activity, with IC{sub 50} values ranging from 485 μM (rutin) to 5700 μM (hesperitin and eriodictyol). Similarly, the flavonoid supplements had IC{sub 50} values of 16.9 mg/mL (EN), 3.44 mg/mL (SB) and 2.72 mg/mL (CB). These values compare with gliptin IC{sub 50} values of 0.684 μM (sitagliptin), 0.707 μM (saxagliptin) and 2.286 μM (vildagliptin). The supplement flavonoid content varied from 11.98% (CB) to 5.26% (EN) and 14.51% (SB) of tablet mass, corresponding to daily flavonoid doses of around 300, 150 and 400 mg, respectively, with CB and SB containing rutin at levels of 7.0% and 7.5% of tablet mass, respectively. While our data demonstrated that citrus bioflavonoid based supplements do possess DPP-4 inhibitory activity, they are several orders of magnitude less potent than gliptins. Further studies using higher concentrations of citrus bioflavonoids, as well as investigations into antioxidant properties which may add additional benefit are warranted.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Facile target validation in an animal model with intracellularly expressed monobodies

Abstract not provided

Gupta, Ankit↗

DOE OSTI2016

Inhibition of RAS function through targeting an allosteric regulatory site

Abstract not provided

Spencer-Smith, Russell↗

DOE OSTI2015

ETO family protein Mtgr1 mediates Prdm14 functions in stem cell maintenance and primordial germ cell formation

Prdm14 is a sequence-specific transcriptional regulator of embryonic stem cell (ESC) pluripotency and primordial germ cell (PGC) formation. It exerts its function, at least in part, through repressing genes associated with epigenetic modification and cell differentiation. Here, we show that this repressive function is mediated through an ETO-family co-repressor Mtgr1, which tightly binds to the pre-SET/SET domains of Prdm14 and co-occupies its genomic targets in mouse ESCs. We generated two monobodies, synthetic binding proteins, targeting the Prdm14 SET domain and demonstrate their utility, respectively, in facilitating crystallization and structure determination of the Prdm14-Mtgr1 complex, or as genetically encoded inhibitor of the Prdm14-Mtgr1 interaction. Structure-guided point mutants and the monobody abrogated the Prdm14-Mtgr1 association and disrupted Prdm14's function in mESC gene expression and PGC formation in vitro. Altogether, our work uncovers the molecular mechanism underlying Prdm14-mediated repression and provides renewable reagents for studying and controlling Prdm14 functions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Adaptive hybrid simulations for multiscale stochastic reaction networks

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗