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The liver is the central organ for detoxification of xenobiotics in the body. In pharmacokinetic modeling, hepatic metabolization capacity is typically quantified as hepatic clearance computed as degradation in well-stirred compartments. This is an accurate mechanistic description once a quasi-equilibrium between blood and surrounding tissue is established. However, this model structure cannot be used to simulate spatio-temporal distribution during the first instants after drug injection. In this paper, we introduce a new spatially resolved model to simulate first pass perfusion of compounds within the naive liver. The model is based on vascular structures obtained from computed tomography as well as physiologically based mass transfer descriptions obtained from pharmacokinetic modeling. The physiological architecture of hepatic tissue in our model is governed by both vascular geometry and the composition of the connecting hepatic tissue. In particular, we here consider locally distributed mass flow in liver tissue instead of considering well-stirred compartments. Experimentally, the model structure corresponds to an isolated perfused liver and provides an ideal platform to address first pass effects and questions of hepatic heterogeneity. The model was evaluated for three exemplary compounds covering key aspects of perfusion, distribution and metabolization within the liver. As pathophysiological states we considered the influence of steatosis and carbon tetrachloride-induced liver necrosis on total hepatic distribution and metabolic capacity. Notably, we found that our computational predictions are in qualitative agreement with previously published experimental data. The simulation results provide an unprecedented level of detail in compound concentration profiles during first pass perfusion, both spatio-temporally in liver tissue itself and temporally in the outflowing blood. We expect our model to be the foundation of further spatially resolved models of the liver in the future. [ABSTRACT FROM AUTHOR]

The evaluation of engineered nanomaterial safety has been hindered by conflicting reports demonstrating differential degrees of toxicity with the same nanoparticles. The unique properties of these materials increase the likelihood that they will interfere with analytical techniques, which may contribute to this phenomenon. We tested the potential for: 1) nanoparticle intrinsic fluorescence/absorbance, 2) interactions between nanoparticles and assay components, and 3) the effects of adding both nanoparticles and analytes to an assay, to interfere with the accurate assessment of toxicity. Silicon, cadmium selenide, titanium dioxide, and helical rosette nanotubes each affected at least one of the six assays tested, resulting in either substantial over- or under-estimations of toxicity. Simulation of realistic assay conditions revealed that interference could not be predicted solely by interactions between nanoparticles and assay components. Moreover, the nature and degree of interference cannot be predicted solely based on our current understanding of nanomaterial behaviour. A literature survey indicated that ca. 95% of papers from 2010 using biochemical techniques to assess nanotoxicity did not account for potential interference of nanoparticles, and this number had not substantially improved in 2012. We provide guidance on avoiding and/or controlling for such interference to improve the accuracy of nanotoxicity assessments. [ABSTRACT FROM AUTHOR]

Open vascular reconstructions frequently fail due to the development of recurrent disease or intimal hyperplasia (IH). This paper reports a novel drug delivery method using a rapamycin-loaded poly(lactide-co-glycolide) (PLGA) nanoparticles (NPs)/pluronic gel system that can be applied periadventitially around the carotid artery immediately following the open surgery. In vitro studies revealed that rapamycin dispersed in pluronic gel was rapidly released over 3 days whereas release of rapamycin from rapamycin-loaded PLGA NPs embedded in pluronic gel was more gradual over 4 weeks. In cultured rat vascular smooth muscle cells (SMCs), rapamycin-loaded NPs produced durable (14 days versus 3 days for free rapamycin) inhibition of phosphorylation of S6 kinase (S6K1), a downstream target in the mTOR pathway. In a rat balloon injury model, periadventitial delivery of rapamycin-loaded NPs produced inhibition of phospho-S6K1 14 days after balloon injury. Immunostaining revealed that rapamycin-loaded NPs reduced SMC proliferation at both 14 and 28 days whereas rapamycin alone suppressed proliferation at day 14 only. Moreover, rapamycin-loaded NPs sustainably suppressed IH for at least 28 days following treatment, whereas rapamycin alone produced suppression on day 14 with rebound of IH by day 28. Since rapamycin, PLGA, and pluronic gel have all been approved by the FDA for other human therapies, this drug delivery method could potentially be translated into human use quickly to prevent failure of open vascular reconstructions. [ABSTRACT FROM AUTHOR]

In this paper, intercalation of nanoclay in the miscible polymer blend of poly(vinylidene fluoride) (PVDF) and acrylic rubber(ACM) was studied. X-ray diffraction was used to investigate the formation of nanoscale polymer blend/clay hybrid. Infrared spectroscopy and X-ray analysis revealed the coexistence of β and γ crystalline forms in PVDF/Clay nanocomposite while α crystalline form was found to be dominant in PVDF/ACM/Clay miscible hybrids. Flory-Huggins interaction parameter (B) was used to further explain the miscibility phenomenon observed. The B parameter was determined by combining the melting point depression and the binary interaction model. The estimated B values for the ternary PVDF/ACM/Clay and PVDF/ACM pairs were all negative, showing both proper intercalation of the polymer melt into the nanoclay galleries and the good miscibility of PVDF and ACM blend. The B value for the PVDF/ACM blend was almost the same as that measured for the PVDF/ACM/Clay hybrid, suggesting that PVDF chains in nanocomposite hybrids interact with ACM chains and that nanoclay in hybrid systems is wrapped by ACM molecules. [ABSTRACT FROM AUTHOR]

Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. [ABSTRACT FROM AUTHOR]

In this paper, we describe the effects of the combination of topographical, mechanical, chemical and intracellular electrical stimuli on a co-culture of fibroblasts and skeletal muscle cells. The co-culture was anisotropically grown onto an engineered micro-grooved (10 µm-wide grooves) polyacrylamide substrate, showing a precisely tuned Young’s modulus (∼ 14 kPa) and a small thickness (∼ 12 µm). We enhanced the co-culture properties through intracellular stimulation produced by piezoelectric nanostructures (i.e., boron nitride nanotubes) activated by ultrasounds, thus exploiting the ability of boron nitride nanotubes to convert outer mechanical waves (such as ultrasounds) in intracellular electrical stimuli, by exploiting the direct piezoelectric effect. We demonstrated that nanotubes were internalized by muscle cells and localized in both early and late endosomes, while they were not internalized by the underneath fibroblast layer. Muscle cell differentiation benefited from the synergic combination of topographical, mechanical, chemical and nanoparticle-based stimuli, showing good myotube development and alignment towards a preferential direction, as well as high expression of genes encoding key proteins for muscle contraction (i.e., actin and myosin). We also clarified the possible role of fibroblasts in this process, highlighting their response to the above mentioned physical stimuli in terms of gene expression and cytokine production. Finally, calcium imaging-based experiments demonstrated a higher functionality of the stimulated co-cultures. [ABSTRACT FROM AUTHOR]

Biogenetic silica displays intricate patterns assembling from nano- to microsize level and interesting non-spherical structures differentiating in specific directions. Several model systems have been proposed to explain the formation of biosilica nanostructures. Of them, phase separation based on the physicochemical properties of organic amines was considered to be responsible for the pattern formation of biosilica. In this paper, using tetraethyl orthosilicate (TEOS, Si(OCH2CH3)4) as silica precursor, phospholipid (PL) and dodecylamine (DA) were introduced to initiate phase separation of organic components and influence silica precipitation. Morphology, structure and composition of the mineralized products were characterized using a range of techniques including field emission scanning electron microscopy (FESEM), transmission electron microscope (TEM), X-ray diffraction (XRD), thermogravimetric and differential thermal analysis (TG-DTA), infrared spectra (IR), and nitrogen physisorption. The results demonstrate that the phase separation process of the organic components leads to the formation of asymmetrically non-spherical silica structures, and the aspect ratios of the asymmetrical structures can be well controlled by varying the concentration of PL and DA. On the basis of the time-dependent experiments, a tentative mechanism is also proposed to illustrate the asymmetrical morphogenesis. Therefore, our results imply that in addition to explaining the hierarchical porous nanopatterning of biosilica, the phase separation process may also be responsible for the growth differentiation of siliceous structures in specific directions. Because organic amine (e.g., long-chair polyamines), phospholipids (e.g., silicalemma) and the phase separation process are associated with the biosilicification of diatoms, our results may provide a new insight into the mechanism of biosilicification. [ABSTRACT FROM AUTHOR]