Enhancing the fraction of grafted polystyrene on silica hybrid nanoparticles

Polymer-grafted inorganic nanoparticles are being developed for a diverse array of applications, ranging from drug delivery to multifunctional composites. In many instances, performance of these core-shell hybrids is limited by relatively broad distributions of size and composition, as well as the presence of impurities, such as unattached polymer chains. Herein, further synthetic improvements, and associated characterization techniques, to enhance the fraction of the grafted polystyrene shell on silica hybrid nanoparticles are discussed. We found that during surface-initiated atom transfer radical polymerization (SI-ATRP) from the silica nanoparticles, thermal self-initiation of styrene produces unattached polymer chains. Size exclusion chromatography afforded a facile approach to quantify the mass of the unattached polymer, and provide a substantial refinement to estimates of chain graft density beyond traditionally-used approaches, such as thermogravimetry. This fraction of unattached polymer is still present even after post-polymerization work-up via precipitation and re-dissolution. Removal necessitates additional procedures, such as high speed centrifugation. Selection of a lower polymerization temperature, in concert with a more reactive Cu complex, significantly reduces the amount of unattached polystyrene impurity. The improved polymerization conditions and post-polymerization purification provide more refined polystyrene-grafted silica nanoparticles to clarify structure-property relationships of these core-shell hybrids.     

Random and block copolymers based on 4-methyl-1-pentene and 1-pentene

The zirconium acetamidinate catalyst {Cp*Zr(Me)₂[N(Et)C(Me)N(tBu)]} (Cp* = ?⁵-C₅Me₅) was used to synthesize both random and block copolymers based on 4-methyl-1-pentene (4M1P) and 1-pentene. The polymers have been characterized by NMR spectroscopy, SEC, DSC, high temperature HPLC and CRYSTAF. Unexpectedly, the yields and molecular weights decreased with increasing amounts of 1-pentene. The reason for this behavior is that 1-pentene occasionally undergoes 2,1-misinsertions trapping the catalyst in a dormant state. These 2,1-misinsertions do not seem to occur with the bulky 4M1P (branched α-olefin). Adding a small amount of ethylene reactivates the catalyst. Unlike most semi-crystalline polymers, the density of the crystalline phase of isotactic P4M1P can be lower than of the amorphous phase, when crystallized under very high pressures. To characterize this peculiar behavior of 4M1P-based polymers, various samples have been subjected to Pressure-Volume-Temperature (PVT) measurements. While the P4M1P homopolymers and block copolymers show the expected decrease in specific volume upon crystallization, the 4M1P-rich random copolymers proved not to vary in specific volume under the same conditions.     

Personalization of cardiac motion and contractility from images using variational data assimilation

Personalization is a key aspect of biophysical models in order to impact clinical practice. In this paper, we propose a personalization method of electromechanical models of the heart from cine-MR images based on the adjoint method. After estimation of electrophysiological parameters, the cardiac motion is estimated based on a proactive electromechanical model. Then cardiac contractilities on two or three regions are estimated by minimizing the discrepancy between measured and simulation motion. Evaluation of the method on three patients with infarcted or dilated myocardium is provided.     

Entropy-based measures for quantifying sleep-stage transition dynamics: relationship to sleep fragmentation and daytime sleepiness

We present two novel entropy-based measures that quantify sleep-stage transition dynamics (sleep structure) from polysomnogram derived hypnograms: Walsh spectral entropy (WSE) and Haar spectral entropy (HSE). These measures quantify patterns of temporal regularity of a categorical time series without requiring numerical encoding (scaling) of the (categorical) sleep stages. Additionally, we show that conditional entropy (CE) is well suited for quantifying predictability of the hypnogram. The relationship of those measures with traditional sleep fragmentation indices (arousal index, total sleep time, and sleep efficiency) is explored for a 394 participant sample of the Cleveland Family Study, an epidemiologic study in which standardized single-night polysomnogram data were collected. The new entropy-based sleep structure measures (WSE, HSE, and CE) are positively correlated (moderate to weak) with the traditional sleep fragmentation indices. Because the sleep structure measures developed in this paper provide direct information related to temporal patterns of sleep that is not contained in traditional sleep fragmentation measures, the correlation between these new alternative sleep structure measures and the traditional sleep fragmentation measures is less important. Our goal is not to develop alternative measures that correlate highly with traditional measures of sleep fragmentation, but rather to provide methods to quantify sleep structure by examining other (e.g., dynamic sleep-stage transition) properties of the hypnogram. Additionally, the relationship of the new entropy-based and traditional measures with daytime sleepiness as quantified by the Epworth sleepiness scale (ESS) is investigated. Multiple linear regression analysis shows that WSE has a stronger relationship with ESS than the traditional measures, even after both are adjusted for common confounders (age, race, gender, and body mass index). This further suggests that the entropy-based measures, especially WSE, are capturing additional temporal patterns of sleep not captured in the traditional sleep fragmentation measures, and have a relationship with daytime sleepiness.     

Multiscale evolving complex network model of functional connectivity in neuronal cultures

Cultures of cortical neurons grown on multielectrode arrays exhibit spontaneous, robust, and recurrent patterns of highly synchronous activity called bursts. These bursts play a crucial role in the development and topological self-organization of neuronal networks. Thus, understanding the evolution of synchrony within these bursts could give insight into network growth and the functional processes involved in learning and memory. Functional connectivity networks can be constructed by observing patterns of synchrony that evolve during bursts. To capture this evolution, a modeling approach is adopted using a framework of emergent evolving complex networks and, through taking advantage of the multiple time scales of the system, aims to show the importance of sequential and ordered synchronization in network function.     

Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

Fast and accurate tissue elasticity imaging is essential in studying dynamic tissue mechanical properties. Various ultrasound shear elasticity imaging techniques have been developed in the last two decades. However, to reconstruct a full field-of-view 2-D shear elasticity map, multiple data acquisitions are typically required. In this paper, a novel shear elasticity imaging technique, comb-push ultrasound shear elastography (CUSE), is introduced in which only one rapid data acquisition (less than 35 ms) is needed to reconstruct a full field-of-view 2-D shear wave speed map (40 × 38 mm). Multiple unfocused ultrasound beams arranged in a comb pattern (comb-push) are used to generate shear waves. A directional filter is then applied upon the shear wave field to extract the left-to-right (LR) and right-to-left (RL) propagating shear waves. Local shear wave speed is recovered using a time-of-flight method based on both LR and RL waves. Finally, a 2-D shear wave speed map is reconstructed by combining the LR and RL speed maps. Smooth and accurate shear wave speed maps are reconstructed using the proposed CUSE method in two calibrated homogeneous phantoms with different moduli. Inclusion phantom experiments demonstrate that CUSE is capable of providing good contrast (contrast-to-noise ratio ≥ 25 dB) between the inclusion and background without artifacts and is insensitive to inclusion positions. Safety measurements demonstrate that all regulated parameters of the ultrasound output level used in CUSE sequence are well below the FDA limits for diagnostic ultrasound.     

Single frequency inverse obstacle scattering: a sparsity constrained linear sampling method approach

The linear sampling method (LSM) offers a qualitative image reconstruction approach, which is known as a viable alternative for obstacle support identification to the well-studied filtered backprojection (FBP), which depends on a linearized forward scattering model. Of practical interest is the imaging of obstacles from sparse aperture far-field data under a fixed single frequency mode of operation. Under this scenario, the Tikhonov regularization typically applied to LSM produces poor images that fail to capture the obstacle boundary. In this paper, we employ an alternative regularization strategy based on constraining the sparsity of the solution's spatial gradient. Two regularization approaches based on the spatial gradient are developed. A numerical comparison to the FBP demonstrates that the new method's ability to account for aspect-dependent scattering permits more accurate reconstruction of concave obstacles, whereas a comparison to Tikhonov-regularized LSM demonstrates that the proposed approach significantly improves obstacle recovery with sparse-aperture data.