Lumazine Synthase Protein Nanoparticle-Gd(III)-DOTA Conjugate as a T1 contrast agent for high-field MRI

With the applications of magnetic resonance imaging (MRI) at higher magnetic fields increasing, there is demand for MRI contrast agents with improved relaxivity at higher magnetic fields. Macromolecule-based contrast agents, such as protein-based ones, are known to yield significantly higher r(1) relaxivity at low fields, but tend to lose this merit when used as T-1 contrast agents (r(1)/r(2) = 0.5 similar to 1), with their r(1) decreasing and r(2) increasing as magnetic field strength increases. Here, we developed and characterized an in vivo applicable magnetic resonance (MR) positive contrast agent by conjugating Gd(III)-chelating agent complexes to lumazine synthase isolated from Aquifex aeolicus (AaLS). The r(1) relaxivity of Gd(III)-DOTA-AaLS-R108C was 16.49 mM(-1)s(-1) and its r(1)/r(2) ratio was 0.52 at the magnetic field strength of 7 T. The results of 3D MR angiography demonstrated the feasibility of vasculature imaging within 2 h of intravenous injection of the agent and a significant reduction in T-1 values were observed in the tumor region 7 h post-injection in the SCC-7 flank tumor model. Our findings suggest that Gd(III)-DOTA-AaLS-R108C could serve as a potential theranostic nanoplatform at high magnetic field strength.open0

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process

Aqueous Eu^II-Containing Complex with Bright Yellow Luminescence

Eu^II-containing materials have unique luminescence, redox, and magnetic properties that have potential applications in optoelectronics, sensors, and imaging. Here, we report the synthesis and characterization of Eu^II-containing aza-222 cryptate that displays yellow luminescence and a quantum yield of 26% in aqueous media. The crystal structure reveals a staggered hula-hoop geometry. Both solid-state and solution-phase data are presented that indicate that the high quantum yield is a result of the absence of OH oscillators in the inner sphere of the complex. We expect that Eu^II-containing aza-222 cryptate is a step toward Eu^II-containing luminescent materials that can be used in a variety of applications including biological imaging