Reduced Claudin-12 Expression Predicts Poor Prognosis in Cervical Cancer

Background: Within the claudin (CLDN) family, CLDN12 mRNA expression is altered in various types of cancer, but its clinicopathological relevance has yet to be established due to the absence of specific antibodies (Abs) with broad applications. Methods: We generated a monoclonal Ab (mAb) against human/mouse CLDN12 and verified its specificity. By performing immunohistochemical staining and semiquantification, we evaluated the relationship between CLDN12 expression and clinicopathological parameters in tissues from 138 cases of cervical cancer. Results: Western blot and immunohistochemical analyses revealed that the established mAb selectively recognized the CLDN12 protein. Twenty six of the 138 cases (18.8%) showed low CLDN12 expression, and the disease-specific survival (DSS) and recurrence-free survival rates were significantly decreased compared with those in the high CLDN12 expression group. We also demonstrated, via univariable and multivariable analyses, that the low CLDN12 expression represents a significant prognostic factor for the DSS of cervical cancer patients (HR 3.412, p = 0.002 and HR 2.615, p = 0.029, respectively). Conclusions: It can be concluded that a reduced CLDN12 expression predicts a poor outcome for cervical cancer. The novel anti-CLDN12 mAb could be a valuable tool to evaluate the biological relevance of the CLDN12 expression in diverse cancer types and other diseases.     

Polarity control of GaN epilayers grown on ZnO templates

We report the successful growth of Ga-polar GaN epilayers on O-polar ZnO templates pre-deposited on c-sapphire. Prior to GaN growth, NH₃ is exposed onto the ZnO template. The polarity of the GaN layers is confirmed by etching of the surface and by conversion beam electron diffraction (CBED), while the O-polar ZnO is confirmed by CBED. It is suggested that the NH₃ pre-exposure helps form a Zn₃N₂ layer, which possesses inversion symmetry and inverts the crystal from anion polar to cation polar.     

Molecular aggregation of PEEK with PES blends and the block copolymers composed of PEEK and PES components

Polymer blends of PEEK with PES were prepared by the solution blending method. Copolymers composed of PEEK and PES components were synthesized from these oligomers. The formation conditions exerted an influence over the molecular aggregation and the crystallization behaviors of the blend films and block copolymers which were examined by X-ray diffractometry and DSC analysis. As a result, phase-separation in the blend films was found when the formation temperature was high. The blend films formed at 340°C, quenched and annealed at 180°C, exhibited the same crystallization behavior as those of PEEK. In the case of the blend films formed at 300°C, the annealing of the films at 250°C was required to crystallize the blend films. The T_g of a copolymer with a PEEK component content of more than 50% tends to shift toward a higher temperature than the T_g of PEEK itself, and the T_m of the copolymer toward a lower temperature than that of PEEK ist.     

Prediction model of compressive strength development of fly-ash concrete

Based on experimental results concerning the compressive strength development of concrete containing fly ash, the authors derived an estimation equation for compressive strength development. The equation can express coefficient , which indicates the activity of fly ash as a binder, in the form of a function of age, fly-ash content, and Blaine specific surface area of fly ash.

This equation is capable of explaining the increases in the early strength due to fly ash in place of part of fine aggregate, the decreases in the early strength due to fly ash in place of part of cement, the increases in the long-term strength due to pozzolanic reaction, the relationship between the fly-ash replacement ratio and the ratio of strength increase/decrease, and the effect of fly ash's Blaine specific surface area on the strength.     

Threshold for Millimeter-Wave (60 GHz)-Induced Ocular Injury

Journal of Infrared, Millimeter, and Terahertz Waves - Millimeter waves (MMW) absorbed by skin or cornea may induce damage by heat. We have developed a 60 GHz MMW exposure-induced eye...     

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.     

Robust loss functions for boosting

Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.     

Imitating others by composition of primitive actions: A neuro-dynamic model

This paper introduces a novel neuro-dynamical model that accounts for possible mechanisms of action imitation and learning. It is considered that imitation learning requires at least two classes of generalization. One is generalization over sensory–motor trajectory variances, and the other class is on cognitive level which concerns on more qualitative understanding of compositional actions by own and others which do not necessarily depend on exact trajectories. This paper describes a possible model dealing with these classes of generalization by focusing on the problem of action compositionality. The model was evaluated in the experiments using a small humanoid robot. The robot was trained with a set of different actions concerning object manipulations which can be decomposed into sequences of action primitives. Then the robot was asked to imitate a novel compositional action demonstrated by a human subject which are composed from prior-learned action primitives. The results showed that the novel action can be successfully imitated by decomposing and composing it with the primitives by means of organizing unified intentional representation hosted by mirror neurons even though the trajectory-level appearance is different between the ones of observed and those of self-generated.     

Precise Speed Estimation From a Low-Resolution Encoder by Dual-Sampling-Rate Observer

This paper describes an effective way to estimate state variables, such as motor speed and disturbance from a low-resolution encoder at low speed by using the dual-sampling-rate observer. The dual-sampling-rate observer estimates the state variables at every DSP control period and correct the estimation error at the instant that the measurement signal is detected. A novel pole assignment method, which considers the relation of the estimation and error correction periods, is proposed to maintain the stability for long error correcting period. Moreover, the dual-sampling-rate observer can be applied for higher order systems since it is generalized in state space. The effectiveness of the observer is verified through various simulations and experiments     

Evaluation of R-curve behavior of ceramic-metal functionally graded materials by stable crack growth

This paper deals with the fracture toughness and R-curve behavior of ceramic-metal functionally graded materials (FGMs). A possibility of stable crack growth in a three-point-bending specimen is examined based on the driving force and resistance for crack growth in FGMs, and the distribution of fracture toughness or R-curve behavior is evaluated on FGMs fabricated by powder metallurgy using partially stabilized zirconia (PSZ) and stainless steel (SUS 304). The materials have a functionally graded surface layer (FGM layer) with a thickness of 1 mm or 2 mm on a SUS 304 substrate. Three-point-bending tests are carried out on a rectangular specimen with a very short crack in the ceramics surface. On the three-point-bending test, a crack is initiated from a short pre-crack in unstable manner, and then it propagates in stable manner through the FGM layer with an increase in the applied load. From the relationship between applied load and crack length during the stable crack growth in the FGM layer, the fracture toughness is evaluated. The fracture toughness increases with an increase in a volume fraction of SUS 304 phase.