Formation of dityrosine and other fluorescent amino acids by reaction of amino acids with lipid hydroperoxides

Formation of fluorescence by the reaction of various amino acids with lipid hydroperoxides,i.e., linoleic acid 13-monohydroperoxide, methyl linoleate 13-monohydroperoxide and phosphatidylcholine hydroperoxide, in the presence of methemoglobin was investigated. Two types of fluorescence were produced: fluorescent dityrosine (3,3′-dityrosine) from tyrosine, and unidentified fluorophores with α- and ε-amino groups of various amino acids. While the former was stable after treatment with borohydride, the latter fluorophores were readily destroyed. The rate of dityrosine formation was rapid, and the yield of dityrosine was dependent on the concentrations of tyrosine and the lipid hydroperoxides. Butylated hydroxytoluene and tocopherol inhibited the formation of dityrosine, but did not affect the formation of fluorophores on the amino groups. Dityrosine appears to be formed by radical reaction of the lipid hydroperoxides, while the other fluorophores seem to be created by nonradical mechanisms.     

Controlling the familywise error rate in functional neuroimaging: a comparative review

Functional neuroimaging data embodies a massive multiple testing problem, where 100,000 correlated test statistics must be assessed. The familywise error rate, the chance of any false positives is the standard measure of Type I errors in multiple testing. In this paper we review and evaluate three approaches to thresholding images of test statistics: Bonferroni, random field and the permutation test. Owing to recent developments, improved Bonferroni procedures, such as Hochberg's methods, are now applicable to dependent data. Continuous random field methods use the smoothness of the image to adapt to the severity of the multiple testing problem. Also, increased computing power has made both permutation and bootstrap methods applicable to functional neuroimaging. We evaluate these approaches on t images using simulations and a collection of real datasets. We find that Bonferroni-related tests offer little improvement over Bonferroni, while the permutation method offers substantial improvement over the random field method for low smoothness and low degrees of freedom. We also show the limitations of trying to find an equivalent number of independent tests for an image of correlated test statistics.     

Preparation of silk fibroin and polyallylamine composites

Composite films made of silk fibroin (SF) and polyallylamine (PAA) are prepared that contain various compositional ratios. These materials are analyzed to elucidate the resulting physical properties and to assess their potential toward advanced applications as industrial materials. The composite films are obtained from a SF and PAA binary system by dry casting from aqueous solution. These composite films exhibit excellent processability such as film forming capabilities, and the elongation at break is increased in the wet state. The differential scanning calorimetry (DSC) curves of the composites suggest that a mutual interaction takes place between the SF and PAA. This interaction is believed to occur because the endothermic peak, corresponding to the individual polymer, shifts with increasing SF content. The random coil conformation of the SF is present, regardless of the PAA blending, as confirmed by FTIR and DSC measurements. Additionally, living cells from Antheraea pernyi and Bombyx mori insect tissues are shown to grow effectively on the composite films. Maximum growth levels occur when the cultivation flask is coated with the material in SF/PAA ratios of 75:25 to 25:75. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 1963–1970, 2002; DOI 10.1002/app.10491     

A Network Architecture with High Availability for Real-time Premium Traffic over the Internet

Real-time traffic will be a predominant traffic type in the next generation networks, and networks with 100% reliability and availability will be required by real-time premium traffic. It is believed that QoS guarantees could be better provided by connection oriented networks such as Multi Protocol Label Switching (MPLS). These connection oriented networks are more vulnerable to network failure. Conventional path protection methods perform re-routing to cope with this. However, re-routing always causes packet losses and results in service outage. These losses are bursty in nature and highly degrade the QoS of the real-time premium traffic. Thus, 100% availability cannot be achieved by conventional methods. The novel path protection proposed in this paper recovers the bursty packet losses due to re-routing by using forward error correction (FEC) path. Therefore, it can provide network architecture with no service outage for such traffic. The numerical results show that the proposed method can achieve a very high availability for real-time premium traffic in future IP/MPLS networks.

A multi-spectral non-local method for retrieval of boundary layer cloud properties from optical remote sensing data

A multi-spectral non-local (MSN) method is developed for advanced retrieval of boundary layer cloud properties from remote sensing data, as an alternative to the independent pixel approximation (IPA) method. The non-local method uses data at both the target pixel and neighboring pixels to retrieve cloud properties such as pixel-averaged cloud optical thickness and effective droplet radius. Radiance data to be observed from space were simulated by a three-dimensional (3D) radiation model and a stochastic boundary layer cloud model with two-dimensional (horizontal and vertical) variability in cloud liquid water and effective radius. An adiabatic assumption is used for each cloud column to model the geometrical thickness and vertical profiles of cloud liquid water content and effective droplet radius, neglecting drizzle and cloud brokenness for simplicity. The dependence of radiative smoothing and roughening on horizontal scale, optical thickness and single scattering albedo are investigated. Then, retrieval methods using 250-m horizontal resolution data onboard new generation satellites are discussed. The regression model for the MSN method was trained based on datasets from numerical simulations. The training was performed with respect to various domain averages of optical thickness and effective radius, because smoothing and roughening effects are strongly dependent on the two variables. Retrieval accuracy is discussed here with datasets independent of those used in the training, towards assessing the generality of the technique. It is demonstrated that retrieval accuracy of cloud optical thickness, which is often retrieved from single-spectral visible-wavelength data, is improved the most using neighboring pixel data and secondly using multi-spectral data, and ideally with both. When the IPA retrieval method is applied to optical thickness and effective radius, the root-mean-square relative errors can be 15-90%, depending on solar and view directions. In contrast, the MSN method has errors of 4-10%, which is smaller than IPA by a factor of 2-10. It is also suggested that the accuracy of the MSN method is insensitive to some assumptions in the inhomogeneous cloud input data used to train the regression model.     

Land cover in East Asia classified using Terra MODIS and DMSP OLS products

Land cover is classified over East Asia using 250‐m Moderate Resolution Imaging Spectroradiometer (MODIS) land surface reflectance, MODIS snow cover and Operational Linescan System (OLS) human settlement data. The classification method includes a decision tree classification scheme that considers 11 kinds of land surface features derived from the OLS product and the time series of two MODIS products in 2000. The decision tree was defined manually based on the experiment because of insufficient training data, ease of tuning by visual interpretation, and extensibility to further research. The resulting classification is compared to three kinds of reference data, i.e. MODIS land cover product, Chinese digital land cover map, and Chinese census. The land cover classification can be input into a hydrological model applied to the Yellow River in China.     

Antiatherogenic effects of the antioxidant BO-653 in three different animal models

Antioxidants have been proposed to have antiatherogenic potential by their inhibition of low density lipoprotein (LDL) oxidation. Here, we report an antioxidant, BO-653 (2,3-dihydro-5-hydroxy-2, 2-dipentyl-4,6-di-tert-butylbenzofuran), designed to exhibit antioxidative potency comparable to that of alpha-tocopherol, but yet possess a high degree of lipophilicity comparable to that of probucol. BO-653 exhibits a high affinity for LDL and is well distributed in aortic vessels in vivo. In atherosclerosis models of rabbits and mice, BO-653 has been shown to be able to suppress the formation of atherosclerotic lesions without untoward side effects. Specifically, there was no reduction of high density lipoprotein levels. This antioxidant provides additional evidence in support of the oxidized-LDL hypothesis, and itself is a promising candidate antioxidant for clinical use.     

Scalable architecture for word HMM-based speech recognition and VLSI implementation in complete system

This paper describes a scalable architecture for real-time speech recognizers based on word hidden Markov models (HMMs) that provide high recognition accuracy for word recognition tasks. However, the size of their recognition vocabulary is small because its extremely high computational costs cause long processing times. To achieve high-speed operations, we developed a VLSI system that has a scalable architecture. The architecture effectively uses parallel computations on the word HMM structure. It can reduce processing time and/or extend the word vocabulary. To explore the practicality of our architecture, we designed and evaluated a complete system recognizer, including speech analysis and noise robustness parts, on a 0.18-/spl mu/m CMOS standard cell library and field-programmable gate array. In the CMOS standard-cell implementation, the total processing time is 56.9 /spl mu/s/word at an operating frequency of 80 MHz in a single system. The recognizer gives a real-time response using an 800-word vocabulary.     

Method for simultaneous imaging of endogenous low molecular weight metabolites in mouse brain using TiO2 nanoparticles in nanoparticle-assisted laser desorption/ionization-imaging mass spectrometry

We report the detection of a group of endogenous low molecular weight metabolites (LMWM) in mouse brain (80-500 Da) using TiO(2) nanoparticles (NPs) in nanoparticle-assisted laser desorption/ionization-imaging mass spectrometry (Nano-PALDI-IMS) without any washing and separation step prior to MS analysis. The identification of metabolites using TiO(2) NPs was compared with a conventional organic matrix 2,5-dihydroxybenzoic acid (DHB) where signals of 179 molecules were specific to TiO(2) NPs, 4 were specific to DHB, and 21 were common to both TiO(2) NPs and DHB. The use of TiO(2) NPs enabled the detection of a higher number of LMWM as compared to DHB and gold NPs as a matrix. This approach is a simple, inexpensive, washing, and separation free for imaging and identification of LMWM in mouse brain. We believe that the biochemical information from distinct regions of the brain using a Nano-PALDI-IMS will be helpful in elucidating the imbalances linked with diseases in biomedical samples.