Effects of Fe3O4 Magnetic Nanoparticles on A549 Cells

Fe₃O₄ magnetic nanoparticles (MgNPs-Fe₃O₄) are widely used in medical applications, including magnetic resonance imaging, drug delivery, and in hyperthermia. However, the same properties that aid their utility in the clinic may potentially induce toxicity. Therefore, the purpose of this study was to investigate the cytotoxicity and genotoxicity of MgNPs-Fe₃O₄ in A549 human lung epithelial cells. MgNPs-Fe₃O₄ caused cell membrane damage, as assessed by the release of lactate dehydrogenase (LDH), only at a high concentration (100 μg/mL); a lower concentration (10 μg/mL) increased the production of reactive oxygen species, increased oxidative damage to DNA, and decreased the level of reduced glutathione. MgNPs-Fe₃O₄ caused a dose-dependent increase in the CD44⁺ fraction of A549 cells. MgNPs-Fe₃O₄ induced the expression of heme oxygenase-1 at a concentration of 1 μg/mL, and in a dose-dependent manner. Despite these effects, MgNPs-Fe₃O₄ had minimal effect on cell viability and elicited only a small increase in the number of cells undergoing apoptosis. Together, these data suggest that MgNPs-Fe₃O₄ exert little or no cytotoxicity until a high exposure level (100 μg/mL) is reached. This dissociation between elevated indices of cell damage and a small effect on cell viability warrants further study.     

A novel field‐sequential blue‐phase‐mode AMLCD

Abstract— Through the realization of a blue‐phase‐mode (hereinafter, the operational mode of liquid crystal having a blue phase is referred to as a blue‐phase mode), a display using an improved field‐sequential method was confirmed to be capable of display at a frame rate of 180 fps (field frequency of 540 Hz) or higher. Under this condition, an image without annoyance caused by color breakup was obtained. Moreover, a novel field‐sequential AMLCD integrated with a scan driver by combining the liquid‐crystal‐display (LCD) technology using blue phase and oxide‐semiconductor technology has been developed.     

A dual-axis MEMS capacitive inertial sensor with high-density proof mass

This paper reports a novel dual-axis microelectromechanical systems (MEMS) capacitive inertial sensor that utilizes multi-layered electroplated gold. All the MEMS structures are made by gold electroplating that is used as a post complementary metal-oxide semiconductor (CMOS) process. Due to the high density of gold, the Brownian noise on the proof mass becomes lower than those made of other materials such as silicon in the same size. The single gold proof mass works as a dual-axis sensing electrode by utilizing both out-of-plane (Z axis) and in-plane (X axis) motions; the proof mass has been designed to be 660 μm × 660 μm in area with the thickness of 12 μm, and the actual Brownian noise in the proof mass has been measured to be 1.2 \({\upmu}{\text{G/}}\sqrt {\text{Hz}}\) (in Z axis) and 0.29 \({\upmu}{\text{G/}}\sqrt {\text{Hz}}\) (in X axis) at room temperature, where 1 G = 9.8 m/s². The miniaturized dual-axis MEMS accelerometer can be implemented in integrated CMOS-MEMS accelerometers to detect a broad range of acceleration with sub-1G resolution on a single sensor chip.     

Two design methods of hyperparameters in variational Bayes learning for Bernoulli mixtures

Variational Bayes learning or mean field approximation is widely used in statistical models which are made of mixtures of exponential distributions, for example, normal mixtures, binomial mixtures, and hidden Markov models. To derive variational Bayes learning algorithm, we need to determine the hyperparameters in the a priori distribution; however, the design method of hyperparameters has not yet been established. In the present paper, we propose two different design methods of hyperparameters which are applied to the different purposes. In the former method, the hyperparameter is determined for minimization of the generalization error. In the latter method, it is chosen so that candidates of hidden structure in training data are extracted. It is experimentally shown that the optimal hyperparameters for two purposes are different from each other.     

PACKTER: implementation of internet traffic visualizer and extension for network forensics

Traffic visualization tools help network operators to maintain awareness of the status of a network, including anomalous activities. Unfortunately, the network operator may look away from the visualizer when beginning network forensics, such as launching a terminal application, logging into a server, and analyzing log files. Thus, the eyesight of the network operator will move from the visual screen even if valuable information is displayed. Our motivation is to develop the ability to use visualization tools as a network operation console. Whereas previous tools focused on outputting packet information, we herein extend the visualizer to accept inputting for operators to start their operations. Since little such software exists for our intent, we develop PACKTER, which is able to visualize traffic based on per-packet information in real time. We also extend PACKTER to have a function of negotiating to a network forensic system, which allows the operator to select an individual packet using a mouse, to start network forensics using a keyboard, and to receive results without looking away from the PACKTER viewer.     

Finding peculiar compositions of two frequent strings with background texts

We consider mining unusual patterns from a set  \(T\) of target texts. A typical method outputs unusual patterns if their observed frequencies are far from their expectation estimated under an assumed probabilistic model. However, it is difficult for the method to deal with the zero frequency and thus it suffers from data sparseness. We employ another set  \(B\) of background texts to define a composition  \(xy\) to be peculiar if both \(x\) and  \(y\) are more frequent in  \(B\) than in  \(T\) and conversely \(xy\) is more frequent in  \(T\) . \(xy\) is unusual because \(x\) and  \(y\) are infrequent in  \(T\) while \(xy\) is unexpectedly frequent compared to  \(xy\) in  \(B\) . To find frequent subpatterns and infrequent patterns simultaneously, we develop a fast algorithm using the suffix tree and show that it scales almost linearly under practical settings of parameters. Experiments using DNA sequences show that found peculiar compositions basically appear in rRNA while patterns found by an existing method seem not to relate to specific biological functions. We also show that discovered patterns have similar lengths at which the distribution of frequencies of fixed length substrings begins to skew. This fact explains why our method can find long peculiar compositions.     

Development of oriented morphology and tensile properties upon superdawing of solution-spun fibers of ultra-high molecular weight poly(acrylonitrile)

The uniaxial drawing of UHMW-PAN fibers spun from a dilute solution into methanol coagulation baths at different temperatures and the resultant structure and tensile properties of the drawn products were studied. Although the initial morphology of the fibers and the deformation mode in a lower draw ratio (DR_t) range were significantly dependent on the temperatures of the coagulation bath, the tensile properties at a given DR_t, as well as the maximum achieved ones, were comparable. Both the tensile modulus and strength increased steadily with the DR_t and reached 35 and 1.8 GPa, respectively, at the highest DR_t of ∼80. These tensile properties are among the highest ever reported for PAN fibers. The achievement of such high tensile properties for extremely drawn fibers is ascribed to the conformational changes of crystalline chains from the 3/1 helix to the planar-zigzag with increasing DR_t, the improvement in the uniformity of the fiber diameter along the fiber axis, and the decrease in fiber diameter. Indeed, the tensile strength of fibers prepared from a dilute solution and having comparable moduli increased with a decrease in the fiber diameters. The reciprocal of the strength was proportional to the square root of the diameter as suggested by the Griffith theory. Extrapolation to a zero diameter yielded an ultimate tensile strength of 2.4±0.1 GPa for a fiber having a maximum achieved tensile modulus of 35±1 GPa.