A xanthine oxidase inhibitor 1'-acetoxychavicol acetate inhibits azoxymethane-induced colonic aberrant crypt foci in rats

The modifying effect of dietary administration of a xanthine oxidase inhibitor 1'-acetoxychavicol acetate (ACA) present in an edible plant Languas galanga in Thailand on the development of azoxymethane (AOM)-induced colonic aberrant crypt foci (ACF) was investigated in rats. Male F344 rats were given s.c. injections of AOM (15 mg/kg body wt) once a week for 3 weeks to induce colonic ACF. They were fed the diets containing 100 or 200 ppm ACA for 5 weeks, starting 1 week before the first dosing of AOM. At the termination of the study (week 5), AOM induced 118 +/- 28 ACF/colon. Dietary administration of ACA caused significant reduction in the frequency of ACF (41% inhibition by 100 ppm ACA feeding and 37% inhibition by 200 ppm ACA feeding, P<0.01). Such inhibition might be associated with suppression of the proliferation biomarkers' expression such as ornithine decarboxylase activity in the colonic mucosa, number of silver-stained nucleolar organizer regions' protein in the colonic mucosal cell nuclei and blood polyamine content. These results indicate that ACA could inhibit the development of AOM-induced ACF through its suppression of cell proliferation in the colonic mucosa and ACA might be a possible chemopreventive agent against colon tumourigenesis.     

Photoluminescence and scintillation properties of Al(PO3)3–CsPO3–CsBr–CeBr3 glass scintillators

Scintillators, which are widely used as radiation detectors, are phosphors that release absorbed ionizing radiation energy as ultraviolet or visible light. Inorganic glass scintillators have several advantages over inorganic crystal scintillators, such as ease of fabrication and low costs. However, unlike inorganic crystals, which can emit up to tens of thousands of photons/MeV, inorganic glasses exhibit less than several hundred photons/MeV in most cases. Here, we studied an inorganic glass scintillator that exhibits a light yield of 2700 photons/MeV, which exceeds those of previous inorganic glass scintillators with high light yields of approximately 2000 photons/MeV. The density of this material is 3.28 g/cm³, which is relatively high among glass scintillators. Moreover, a fast scintillation decay with a decay time constant of 30.0 ns was obtained and is attributed to the 5d–4f transition of Ce³⁺. Thus, this glass is suitable for gamma- and X-ray detection, thereby expanding the practical applicability of inorganic glass scintillators.

     

Development of radiochromic dosimeters based on polymer films with fluoran and divinyl phthalide dyes

Journal of Materials Science: Materials in Electronics - We fabricated polyvinyl chloride (PVC) and poly(methyl methacrylate) (PMMA) films containing NIR Black78, Black100 and Black400 for use as...     

Use of support vector regression and numerically predicted cloudiness to forecast power output of a photovoltaic power plant in Kitakyushu,Japan

The development of a methodology to forecast accurately the power produced by photovoltaic systems can be an important tool for the dissemination and integration of such systems on the public electricity grids. Thus, the objective of this study was to forecast the power production of a 1‐MW photovoltaic power plant in Kitakyushu, Japan, using a new methodology based on support vector machines and on the use of several numerically predicted weather variables, including cloudiness. Hourly forecasts of the power produced for 1 year were carried out. Moreover, the effect of the use of numerically predicted cloudiness on the quality of the forecasts was also investigated. The forecasts of power production obtained with the proposed methodology had a root mean square error of 0.0948 MW h and a mean absolute error of 0.058 MW h. It was also found that the forecast and measured values of power production had a good level of correlation varying from 0.8 to 0.88 according to the season of the year. Finally, the use of numerically predicted cloudiness had an important role in the accuracy of the forecasts, and when cloudiness was not used, the root mean square error of the forecasts increased more than 32%, and the mean absolute error increased more than 42%. Copyright © 2011 John Wiley & Sons, Ltd.     

Avalanche breakdown voltage of GaAs hyperabrupt junctions

The avalanche breakdown voltage of a GaAs hyperabrupt junction diode is calculated by using unequal ionization rates for electrons and holes, and shown graphically as a function of the parameters which characterize the impurity profile of the diode. The breakdown voltage decreases abruptly at the critical point of the characteristic length L_c which varies in accordance with the impurity concentration N₀ at X = 0. For example, the critical length L_c is 7.7 × 10⁻⁶ cm and 3.3 × 10⁻⁵ cm for N₀ = 1 × 10¹⁸ cm⁻³ and 1 × 10¹⁷ cm⁻³, respectively. The breakdown voltage of a diode with extremely short or long characteristic length can be estimated from the results for corresponding abrupt junctions. The experimental results agree well with the calculated ones.     

Filter with variable transmission characteristics for determination of three-dimensional roughness

In this study, we propose a low-pass filter whose transmission characteristics are determined to be more than 99.99% identical to the designed transmission characteristics at wavelengths greater than the cut-off wavelength. This low-pass filter is realized using a frequency-domain method which uses down-sampling, a frequency filter, and a cubic B-spline. When the frequency characteristics of a Gaussian filter (GF) were used as the designed transmission characteristics, this low-pass filter perfectly replaced the GF. In addition, no end effects and directional characteristics developed, and high-speed computation was possible. Furthermore, we can easily realize a low-pass filter having transmission characteristics that rise sharply at a right angle like a step edge.     

Chemoprevention of azoxymethane-induced rat colon carcinogenesis by a xanthine oxidase inhibitor, 1'-acetoxychavicol acetate

In our studies to find natural compounds with chemopreventive efficacy in foods, using azoxymethane (AOM)-induced colonic aberrant crypt foci and colonic mucosal cell proliferation as biomarkers, a xanthine oxidase inhibitor, 1'-acetoxychavicol acetate (ACA), present in the edible plant Languas galanga from Thailand was found to be effective. This study was conducted to test the ability of ACA to inhibit AOM-induced colon tumorigenesis when it was fed to rats during the initiation or post-initiation phase. Male F344 rats were given three weekly s.c. injections of AOM (15 mg/kg body weight) to induce colonic neoplasms. They were fed diet containing 100 or 500 ppm ACA for 4 weeks, starting one week before the first dosing of AOM (the initiation feeding). The other groups were fed the ACA diet for 34 weeks, starting one week after the last AOM injection (the post-initiation feeding). At the termination of the study (week 38), AOM had induced 71% incidence of colonic adenocarcinoma (12/17 rats). The initiation feeding with ACA caused significant reduction in the incidence of colon carcinoma (54% inhibition by 100 ppm ACA feeding and 77% inhibition by 500 ppm ACA feeding, P = 0.03 and P = 0.001, respectively). The post-initiation feeding with ACA also suppressed the incidence of colonic carcinoma (45% inhibition by 100 ppm ACA feeding and 93% inhibition by 500 ppm ACA feeding, P = 0.06 and P = 0.00003, respectively). Such inhibition was dose-dependent and was associated with suppression of proliferation biomarkers, such as ornithine decarboxylase activity in the colonic mucosa, and blood and colonic mucosal polyamine contents. ACA also elevated the activities of phase II enzymes, glutathione S-transferase (GST) and quinone reductase (QR), in the liver and colon. These results indicate that ACA could inhibit the development of AOM-induced colon tumorigenesis through its suppression of cell proliferation in the colonic mucosa and its induction of GST and QR. The results confirm our previous finding that ACA feeding effectively suppressed the development of colonic aberrant crypt foci. These findings suggest possible chemopreventive ability of ACA against colon tumorigenesis.     

Application of accelerators for the research and development of scintillators

We introduce experimental systems which use accelerators to evaluate scintillation properties such as scintillation intensity, wavelength, and lifetime. A single crystal of good optical quality is often unavailable during early stages in the research and development (R&D) of new scintillator materials. Because of their beams' high excitation power and/or low penetration depth, accelerators facilitate estimation of the properties of early samples which may only be available as powders, thin films, and very small crystals. We constructed a scintillation spectrum measurement system that uses a Van de Graaff accelerator and an optical multichannel analyzer to estimate the relative scintillation intensity. In addition, we constructed a scintillation time profile measurement system that uses an electron linear accelerator and a femtosecond streak camera or a microchannel plate photomultiplier tube followed by a digital oscilloscope to determine the scintillation lifetimes. The time resolution is approximately 10 ps. The scintillation spectra or time profiles can be obtained in a significantly shorter acquisition time in comparison with that required by conventional measuring systems. The advantages of the systems described in this study can significantly promote the R&D of novel scintillator materials.     

Neural discriminant analysis

The role of bootstrap is highlighted for nonlinear discriminant analysis using a feedforward neural network model. Statistical techniques are formulated in terms of the principle of the likelihood of a neural-network model when the data consist of ungrouped binary responses and a set of predictor variables. We illustrate that the information criterion based on the bootstrap method is shown to be favorable when selecting the optimum number of hidden units for a neural-network model. In order to summarize the measure of goodness-of-fit, the deviance on fitting a neural-network model to binary response data can be bootstrapped. We also provide the bootstrap estimates of the biases of excess error in a prediction rule constructed by fitting to the training sample in the neural network model. We also propose bootstrap methods for the analysis of residuals in order to identify outliers and examine distributional assumptions in neural-network model fitting. These methods are illustrated through the analyzes of medical diagnostic data.