HDAC8-Selective Inhibition by PCI-34051 Enhances the Anticancer Effects of ACY-241 in Ovarian Cancer Cells

HDAC6 is overexpressed in ovarian cancer and is known to be correlated with tumorigenesis. Accordingly, ACY-241, a selective HDAC6 inhibitor, is currently under clinical trial and has been tested in combination with various drugs. HDAC8, another member of the HDAC family, has recently gained attention as a novel target for cancer therapy. Here, we evaluated the synergistic anticancer effects of PCI-34051 and ACY-241 in ovarian cancer. Among various ovarian cancer cells, PCI-34051 effectively suppresses cell proliferation in wild-type p53 ovarian cancer cells compared with mutant p53 ovarian cancer cells. In ovarian cancer cells harboring wild-type p53, PCI-34051 in combination with ACY-241 synergistically represses cell proliferation, enhances apoptosis, and suppresses cell migration. The expression of pro-apoptotic proteins is synergistically upregulated, whereas the expressions of anti-apoptotic proteins and metastasis-associated proteins are significantly downregulated in combination treatment. Furthermore, the level of acetyl-p53 at K381 is synergistically upregulated upon combination treatment. Overall, co-inhibition of HDAC6 and HDAC8 through selective inhibitors synergistically suppresses cancer cell proliferation and metastasis in p53 wild-type ovarian cancer cells. These results suggest a novel approach to treating ovarian cancer patients and the therapeutic potential in developing HDAC6/8 dual inhibitors.     

Robust moving object detection against fast illumination change

To solve the problem due to fast illumination change in a visual surveillance system, we propose a novel moving object detection algorithm for which we develop an illumination change model, a chromaticity difference model, and a brightness ratio model. When fast illumination change occurs, background pixels as well as moving object pixels are detected as foreground pixels. To separate detected foreground pixels into moving object pixels and false foreground pixels, we develop a chromaticity difference model and a brightness ratio model that estimates the intensity difference and intensity ratio of false foreground pixels, respectively. These models are based on the proposed illumination change model. Based on experimental results, the proposed method shows excellent performance under various illumination change conditions while operating in real-time.     

Retrieval of movie scenes by semantic matrix and automatic feature weight update

A new semantic-based video scene retrieval method is proposed in this paper. Twelve low-level features extracted from a video clip are represented in a genetic chromosome and target videos that user has in mind are retrieved by the interactive genetic algorithm through the feedback iteration. In this procedure, high-level semantic relevance between retrieved videos is accumulated with so-called semantic relevance matrix and semantic frequency matrix for each iteration, and they are combined with an automatic feature weight update scheme to retrieve more target videos at the next iteration. Experiments over 300 movie scene clips extracted from latest well-known movies, showed an user satisfaction of 0.71 at the fourth iteration for eight queries such as “gloominess”, “happiness”, “quietness”, “action”, “conversation”, “explosion”, “war”, and “car chase”.     

Modeling and performance analysis of a novel M-shaped piezoelectric energy harvester employing magnets

Journal of Mechanical Science and Technology - Piezoelectric energy harvesters convert the vibration energy of a mechanical system into the electrical energy. Among them, cantilever type is the...     

A diagnoser algorithm for anomaly detection in DEDS under partial and unreliable observations: characterization and inclusion in sensor configuration optimization

Complex engineering systems have to be carefully monitored to meet demanding performance requirements, including detecting anomalies in their operations. There are two major monitoring challenges for these systems. The first challenge is that information collected from the monitored system is often partial and/or unreliable, in the sense that some occurred events may not be reported and/or may be reported incorrectly (e.g., reported as another event). The second is that anomalies often consist of sequences of event patterns separated in space and time. This paper introduces and analyzes a diagnoser algorithm that meets these challenges for detecting and counting occurrences of anomalies in engineering systems. The proposed diagnoser algorithm assumes that models are available for characterizing plant operations (via stochastic automata) and sensors (via probabilistic mappings) used for reporting partial and unreliable information. Methods for analyzing the effects of model uncertainties on the diagnoser performance are also discussed. In order to select configurations that reduce sensor costs, while satisfying diagnoser performance requirements, a sensor configuration selection algorithm developed in previous work is then extended for the proposed diagnoser algorithm. The proposed algorithms and methods are then applied to a multi-unit-operation system, which is derived from an actual facility application. Results show that the proposed diagnoser algorithm is able to detect and count occurrences of anomalies accurately and that its performance is robust to model uncertainties. Furthermore, the sensor configuration selection algorithm is able to suggest optimal sensor configurations with significantly reduced costs, while still yielding acceptable performance for counting the occurrences of anomalies.     

A Composite Formation Route to Well‐Crystalline Manganese Oxide Nanocrystals: High Catalytic Activity of Manganate–Alumina Nanocomposites

Manganese oxide nanocrystals are combined with aluminum oxide nanocrystals to improve their crystallinity via calcination without a significant increase of crystal size. A nanocomposite, consisting of two metal oxides, can be synthesized by the reaction between permanganate anions and aluminum oxyhydroxide keggin cations. The as‐prepared manganese oxide–aluminum oxide nanocomposite is X‐ray amorphous whereas heat‐treatment gives rise to the crystallization of an α‐MnO₂ phase at 600 °C and Mn₃O₄/Mn₂O₃ and γ‐Al₂O₃ phases at 800 °C. Electron microscopy and N₂ adsorption‐desorption‐isotherm analysis clearly demonstrate that the as‐prepared nanocomposite is composed of a porous assembly of monodisperse primary particles with a size of ～20 nm and a surface area of >410 m² g^?1. Of particular interest is that the small particle size of the as‐prepared nanocomposite is well‐maintained up to 600 °C, a result of the prevention of the growth of manganate grains through nanoscale mixing with alumina grains. The calcined nanocomposite shows very‐high catalytic activity for the oxidation of cyclohexene with an extremely high conversion efficiency of >95% within 15 min. The present results show that the improvement of the crystallinity without significant crystal growth is very crucial for optimizing the catalytic activity of manganese oxide nanocrystals.     

Comments on “Analytic Equation of State for Solid–Liquid–Vapor Phases” (Int. J. Thermophys. 24, 589 (2003))

Among the thermodynamic models applicable to solid–liquid–vapor phases, Yokozeki’s model is considered as the first repulsion-based analytic equation of state (EOS) in which a discontinuity is introduced in the isotherm. However, it was found that the model violates some physical constraints due to the empirically introduced discontinuity. This work focuses on the evaluation of the empirical basis of the model through scaled-particle theory (SPT) and a modification of the model to satisfy the physical constraint.     

Study of impact energy propagation phenomenon and modal characteristics of an armored vehicle undergoing high velocity impact

A new manufacturing technology is being employed to build a new type of armored vehicle. While thick panels are welded together in the old manufacturing technology, relatively thin panels are welded to a frame structure in the new manufacturing technology. The structural integrity of the new type of armor vehicles can be maintained mainly by the frame structures while the panel thickness is reduced significantly to reduce the total vehicle weight. Since the dynamic characteristics of a frame-panel hybrid structure are different from those of the old type of structure which consists of only thick panels, they should be identified to achieve a good performance of the vehicle. For this purpose, a proper FE model of the hybrid type of structure needs to be developed. In the present study, FE models are proposed to represent the frame-panel hybrid type structure efficiently. The impact energy propagation, the transient response and the modal characteristics are investigated with the FE models. This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008. Hong-Hee Yoo received a B.S. and M.S. degree in Mechanical Engineering from Seoul National University in 1980 and 1982. He then went on to receive his Ph.D. degree from Michigan State University in 1989. Dr. Yoo is currently a Professor at the School of Mechanical Engineering at Hanyang University in Seoul, Korea. His research interests are in the area of Flexible body dynamics, vibration.     

Strengthening effects of sprayed fiber reinforced polymers on concrete

The objectives of this study were twofold. The first was to investigate the compressive and flexural behaviors of small‐sized concrete specimens strengthened with sprayed fiber reinforced polymer (SFRP), considering various fiber lengths, fiber volumes, and concrete strengths. The second was to evaluate the strengthening effects of SFRP on the flexural behaviors of large‐sized reinforced concrete beams. U‐shaped strips and shear keys were applied to the test specimens to improve the interfacial bond resistance between the concrete surface and SFRP. POLYM. COMPOS., 36:722–730, 2015. © 2014 Society of Plastics Engineers     

Production and Characterization of Branched Oligosaccharides from Liquefied Starch by the Action of B. Licheniformis Amylase

A branched oligosaccharides (BOS) mixture was produced from liquefied starch solution using a maltogenic amylase of Bacillus licheniformis (BLMA). The BOS mixture was produced by both α-1,4-bond hydrolyzing and α-1,6-transglycosylation activities of BLMA, and it contained 58.3% of various branched oligosaccharides. Small branched oligosaccharides such as isomaltose, isopanose, and panose were identified in the mixture by various analyses including high performance ion-chromatography (HPIC). Major branched DP4 and DP5 molecules in the mixture were determined as 6²-O-α-maltosylmaltose, 6³-O-α-maltosyl-maltotriose and 6²-O-α-maltotriosyl-maltose, respectively. Time course study of BOS production suggested that the hydrolysis and transglycosylation reactions catalyzed by BLMA were coupled. BLMA was likely to transfer a sugar moiety hydrolyzed from a non-reducing end of maltooligosaccharide, mainly maltose, to another moiety of sugar via the formation of α-1,6-linkage. Immobilization of BLMA was attempted as an effort to achieve a continuous process for BOS production. the immobilized enzyme showed improved thermal stability and slight loss of enzyme activity was observed during repeated usage.