Analytical‐Based Methodologies for Examining the In Vitro Absorption,Distribution, Metabolism,and Elimination (ADME) of Silver Nanoparticles

The clinical applications of silver nanoparticles (AgNPs) remain limited due to the lack of well‐established methodologies for studying their nanokinetics. Hereby, the primary goal is to adapt a suite of analytical‐based methodologies for examining the in vitro absorption, distribution, metabolism, and elimination of AgNPs. Vero 76 and HEK 293 cells are exposed to ≈10‐nm spherical AgNPs⁺ and AgNPs^? at relevant concentrations (0–300 µg mL^?1) and times (4–48 h). Absorption: Inductively coupled plasma optical emission spectroscopy (ICP‐OES) demonstrates that the two AgNP formulations are not bioequivalent. For example, different bioavailabilities (C _maximum < 20.7 ± 4% and 6.82 ± 0.4%), absorption times (T _maximum > 48 and ≈24 h), and absorption rate laws (first‐ and zeroth‐order at 300 µg mL^?1) are determined in Vero 76 for AgNPs⁺ and AgNPs^?, respectively. Distribution: Raman and CytoViva hyperspectral imaging show different cellular localizations for AgNPs⁺ and AgNPs^?. Metabolism: Cloud point extraction (CPE)‐tangential flow filtration (TFF) reveal that ≤ 11% ± 4% of the administered, sublethal AgNPs release Ag⁺ and contribute to the observed cytotoxicity. Elimination: ICP‐OES‐CPE suggests that AgNPs are cleared via exocytosis.     

Synthesis of Robustly Stabilizing General Order Compensators for Interval Plants Using Interval Analysis

Interval analysis is applied to synthesize a general order compensator that robustly stabilizes an interval plant. The application procedure gives a systematic way to reduce the design conservatism at each stage of the design process. An illustrative example is provided to demonstrate the procedure.     

Reliable Computation of Frequency Response Plots for Nonrational Transfer Functions to Prescribed Accuracy

We propose algorithms to compute the well known Bode, Nyquist, and Nichols frequency response plots for nonrational transfer functions. The proposed algorithms are very widely applicable—the magnitude and phase functions need to be only bounded and continuous in frequency. The proposed algorithms guarantee that the magnitude and phase plots are reliably computed to a prescribed accuracy, in a finite number of iterations. Through several practical nonrational examples, we demonstrate the superior performance of the proposed algorithm over the widely used routines in MATLAB's control system toolbox and over the conventional gridding method.     

A Parallelized Version of the Covering Algorithm for Solving Parameter-Dependent Systems of Nonlinear Equations

The so-called covering algorithm for enclosing the solution set of parameter—dependent systems of nonlinear equations has been recently proposed by Neumaier (The Enclosure of Solutions of Parameter Dependent Systems of Equations, in: Moore, R. E. (ed.), Reliability in Computing: The Role of Interval Methods in Scientific Computations, Academic Press, 1988). However, in the covering algorithm, only one box is processed in each iteration. This paper presents a parallelized version of the covering algorithm, in which all boxes present are processed simultaneously in each iteration. It is shown through several examples that this strategy results in speed-up of the algorithm by several orders of magnitude, particularly so in demanding problems. The proposed parallelized version can be run even on ordinary computers, i.e., it does not require a parallel computer.     

A low complexity model for predicting slice loss distortion for prioritizing H.264/AVC video

The cumulative mean squared error (CMSE) is a widely used measure of distortion introduced by a slice loss. We propose a low-complexity and low-delay generalized linear model for predicting CMSE contributed by the loss of individual H.264/AVC encoded video slices. We train the model over a video database by using a combination of video factors that are extracted during the encoding of the current frame, without using any data from future frames in the group of pictures (GOP). We then analyze the accuracy of the CMSE prediction model using cross-validation and correlation coefficients. We prioritize the slices within a GOP based on their predicted CMSE values. The performance of our model is evaluated by applying unequal error protection, using rate compatible punctured convolutional codes, to the prioritized slices over noisy channels. We also demonstrate an application of our slice prioritization by implementing a slice discard scheme, where the slices are dropped from the router when the network experiences congestion. The simulation results show that (i) the slice CMSE prediction model performs well for varying GOP structures, GOP lengths, and encoding bit rates, and (ii) the peak signal-to-noise ratio and video quality metric performance of an unequal error protection algorithm using slices prioritized by the predicted CMSE is similar to that of the measured CMSE values for different videos and channel signal-to-noise. We also extend the GOP-level slice prioritization to frame-level slice prioritization and show its performance over noisy channels.     

A reliable and accurate calculation of excitation capacitance value for an induction generator based on interval computation technique

A squirrel cage induction generator (SCIG) offers many advantages for wind energy conversion systems but suffers from poor voltage regulation under varying operating conditions. The value of excitation capacitance (C exct ) is very crucial for the selfexcitation and voltage build-up as well as voltage regulation in SCIG. Precise calculation of the value of C exct is, therefore, of considerable practical importance. Most of the existing calculation methods make use of the steady-state model of the SCIG in co...     

A novel approach for the biosynthesis of silver oxide nanoparticles using aqueous leaf extract of Callistemon lanceolatus (Myrtaceae) and their therapeutic potential

This study describes a novel biological route for the biosynthesis of silver oxide nanoparticles utilising the aqueous extract of Callistemon lanceolatus D.C. leaves. Formation of silver oxide nanoparticles was confirmed by UV–visible spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscope–energy dispersive X-ray spectroscopy and X-ray diffraction spectroscopy analysis. The biologically synthesised silver oxide nanoparticles were found to be 3–30 nm in size with spherical and hexagonal shape by high-resolution transmission electron microscope analysis. Furthermore, the biogenic silver oxide nanoparticles demonstrated significant (p?in vitro antioxidant methods. These particles also exhibited significant (p?相似文献   

Surface characterization of novel alumina-based composites for energy efficient sliding systems

Friction, wear, and lubrication have direct influence on performance, reliability, and service life of devices that contain moving components. These are universal in applications of energy conversion, power generation, energy harvesting in the broader fields such as agriculture, transportation, drug delivery, and bioengineering. The useful life of these systems and their energy efficiency can be improved by improving the surface properties (performances) of sliding systems. Further, the applications of sliding systems are limited in extreme environments such as high temperature and space application etc. due to their limited surface properties. Therefore, development of a new class of materials with superior surface properties will improve the energy efficiency, sustainability, and applicability. This paper focuses on development of self-lubricating materials with superior surface properties for reduced friction and wear applications.     

A New Subdivision Strategy for Range Computations

We present a new subdivision strategy in interval analysis for computing the ranges of functions. We show through several real-world examples that the proposed subdivision strategy is more efficient than the widely used uniform and adaptive subdivision strategies of Moore (Methods and Applications of Interval Analysis, SIAM, Philadelphia, 1979).     

Macrophage-targeted single walled carbon nanotubes stimulate phagocytosis via pH-dependent drug release

Atherosclerotic cardiovascular disease is the leading cause of mortality in the world.A driving feature of atherosclerotic plaque formation is dysfunctional efferocytosis.Because the“don’t eat me”molecule CD47 is upregulated in atherosclerotic plaque cores,CD47-blocking strategies can stimulate the efferocytic clearance of apoptotic cells and thereby help prevent the progression of plaque buildup.However,these therapies are generally costly and,in clinical and murine trials,they have resulted in side effects including anemia and reticulocytosis.Here,we developed and characterized an intracellular phagocytosis-stimulating treatment in the CD47-SIRPαpathway.We loaded a novel monocyte/macrophage-selective nanoparticle carrier system with a small molecule enzymatic inhibitor that is released in a pH-dependent manner to stimulate macrophage efferocytosis of apoptotic cell debris via the CD47-SIRPαsignaling pathway.We demonstrated that single-walled carbon nanotubes(SWNTs)can selectively deliver tyrosine phosphatase inhibitor 1(TPI)intracellularly to macrophages,which potently stimulates efferocytosis,and chemically characterized the nanocarrier.Thus,SWNT-delivered TPI can stimulate macrophage efferocytosis,with the potential to reduce or prevent atherosclerotic disease.