Ubiquitin-Specific Protease 29 Regulates Cdc25A-Mediated Tumorigenesis

Cell division cycle 25A (Cdc25A) is a dual-specificity phosphatase that is overexpressed in several cancer cells and promotes tumorigenesis. In normal cells, Cdc25A expression is regulated tightly, but the changes in expression patterns in cancer cells that lead to tumorigenesis are unknown. In this study, we showed that ubiquitin-specific protease 29 (USP29) stabilized Cdc25A protein expression in cancer cell lines by protecting it from ubiquitin-mediated proteasomal degradation. The presence of USP29 effectively blocked polyubiquitination of Cdc25A and extended its half-life. CRISPR-Cas9-mediated knockdown of USP29 in HeLa cells resulted in cell cycle arrest at the G0/G1 phase. We also showed that USP29 knockdown hampered Cdc25A-mediated cell proliferation, migration, and invasion of cancer cells in vitro. Moreover, NSG nude mice transplanted with USP29-depleted cells significantly reduced the size of the tumors, whereas the reconstitution of Cdc25A in USP29-depleted cells significantly increased the tumor size. Altogether, our results implied that USP29 promoted cell cycle progression and oncogenic transformation by regulating protein turnover of Cdc25A.     

Catalytic reduction of no over perovskite-type catalysts

In the present work, we have investigated the reduction of NO by propane over perovskite-type oxides prepared by malic acid method. The catalysts were modified to enhance the activity by substitution of metal into A or B site of perovskite oxides. In addition, the reaction conditions, such as temperature, O₂ concentration, and space velocity have been varied to understand their effects on the catalytic performance. In the LaCoO₃ type catalyst, the partial substitution of Ba and Sr into A site enhanced the catalytic activity in the reduction of NO. For the La_0.6Ba (Sr)_o.4 Co_1−x Fe_xO₃ (x=0-1.0) catalyst, the partial substitution of Fe into B site enhanced the conversion of NO, but excess amount of Fe decreased the conversion of NO. The surface area and catalytic activity of perovskite catalysts prepared by malic acid method showed higher values than those of solid reaction method. The conversion of NO increased with increasing O₂ concentration and contact time. The introduction of water into reactant feed decreased the catalytic activity but the deactivation was shown to be reversible over La_0.6Ba_0.4Co_1−x ,Fe_xO₃ catalyst.     

The kinetics of hydrogen transport through amorphous Pd82−yNiySi18 alloys (y=0-32) by analysis of anodic current transient

Hydrogen transport through amorphous Pd_82−yNi_ySi₁₈ alloys (y=0-32) was investigated in 0.1 M NaOH solution by analysis of the anodic current transient. It was found that the anodic current transient shows the non-Cottrell behaviour, but its shape and value remain nearly constant regardless of the hydrogen discharging potential. From the coincidence of the anodic current transient theoretically calculated with that experimentally measured, it is suggested that the change in surface concentration of hydrogen with time is uniquely given by the rate of hydrogen transfer from absorbed state at the electrode sub-surface to adsorbed state on the electrode surface. This means that neither the ‘constraint of constant concentration’ nor the ‘constraint by Butler-Volmer behaviour’ is effective at the electrode surface during hydrogen extraction. On the basis of the theoretical current-time relation under the ‘constraint by hydrogen transfer of absorbed state to adsorbed state’, the hydrogen diffusivity was determined to have an almost constant value of (1.3±0.4)×10⁻⁸ cm² s⁻¹, irrespective of the Ni content and in the absence of Ni. On the other hand, it is inferred that the rate constant of hydrogen transfer decreases markedly with increasing Ni content due to the Ni(OH)₂ layer formed on the electrode surface.     

Pipe crack identification based on the energy method and committee of neural networks

A crack identification method using an equivalent bending stiffness for cracked beam and committee of neural networks is presented. The equivalent bending stiffness is constructed based on an energy method for a straight thin-walled pipe, which has a through-the-thickness crack, subjected to bending. Several numerical analysis for a steel cantilever pipe using the equivalent bending stiffness are carried out to extract the natural frequencies and mode shapes of the cracked beam. The extracted modal properties are used in constructing a training patterns of a neural network. The input to the neural network consists of the modal properties and the output is composed of the crack location and size. Multiple neural networks are constructed and each individual network is trained independently with the different initial synaptic weights. Then, the estimated crack locations and sizes from different neural networks are averaged. Crack detection is carried out for 16 damage cases using the proposed method, and the identified crack locations and sizes agree reasonably well with the exact values.     

Redox-induced performance degradation of anode-supported tubular solid oxide fuel cells

Redox behavior of a Ni-Y₂O₃-stabilized ZrO₂ (YSZ) composite anode support and the performance degradation of an anode-supported tubular solid oxide fuel cell (SOFC) were studied under complete oxidation and reduction conditions (degrees of oxidation and reduction = 100%). Materials characterization studies showed that the exposure time in oxidizing and reducing atmospheres played a critical role in the degradation of the porous structures and the physical properties of the anode support. In particular, the redox cycling with an 8 h exposure time resulted in the cracking of YSZ network, leading to significant decay of the mechanical strength. The polarization experiments on the redox-cycled anode-supported tubular cell showed serious performance degradation as a result of the decreases of open-circuit potential and power density. The ac-impedance measurements combined with microstructural observations indicated that the performance degradation resulted mainly from (i) the degradation of anode support, (ii) microcracks across the whole cell, and (iii) interface delamination.     

Conventional detection of 2,4-dinitrophenol using quartz crystal microbalance

We present conventional detection of 2,4-dinitrophenol (DNP) for using the competitive reaction between DNP and DNP-conjugated albumin onto DNP antibody immobilized quartz crystal microbalance (QCM). This QCM method allows detection of DNP concentration in the range of 0.01 to 100 ng/ml; linear correlation obtains DNP concentration from 1 to 100 ng/ml.     

Efficient indexing of interval time sequences

Time sequences, which are ordered sets of observations, have been studied in various database applications. In this paper, we introduce a new class of time sequences where each observation is represented by an interval rather than a number. Such sequences may arise in many situations. For instance, we may not be able to determine the exact value at a time point due to uncertainty or aggregation. Such observation may be represented better by a range of possible values. Similarity search with interval time sequences as both query and data sequences poses a new challenge for research. We first address the issue of (dis)similarity measures for interval time sequences. We choose an L₁ norm-based measure because it effectively quantifies the degree of overlapping and remoteness between two intervals, and is invariant irrespective of the position of an interval when it is enclosed within another interval. We next propose an efficient indexing technique for fast retrieval of similar interval time sequences from large databases. More specifically, we propose: (1) to extract a segment-based feature vector for each sequence, and (2) to map each feature vector to either a point or a hyper-rectangle in a multi-dimensional feature space. We then show how we can use existing multi-dimensional index structures such as the R-tree for efficient query processing. The proposed method guarantees no false dismissals. Experimental results show that, for synthetic and real stock data, it is superior to sequential scanning in performance and scales well with the data size.     

Method to Estimate Thermal Shrinkage Behavior of Glasses

We present a method to estimate the effect of heat treatment on the shrinkage behavior of glasses. As a pre-requisite, sensitivity of the glass density as a function of glass fictive temperature is measured using the sink–float method and the slope of the relationship is used to determine the linear thermal strain proportionality factor. Evolution of the fictive temperature for different temperature–time history is measured using the infrared spectroscopy method and the results are used to estimate the structural relaxation parameters in the temperature range of interest. The overall shrinkage behavior is predicted using the linear thermal strain factor and estimated change in fictive temperature due to the thermal treatment. The predicted shrinkage behavior is observed to be in good agreement with the independent dimensional change measurements performed on large glass sheets that have undergone similar thermal treatments.