Cadmium sulfide and cadmium selenide/cadmium sulfide nanoparticles stabilized in water with poly(cysteine acrylamide)

Cysteine acrylamide (N-acryloyl L-cysteine) stabilizes CdS nanoparticles as the particles form in aqueous dispersions. Cysteine acrylamide also exchanges for citrate on the surfaces of CdSe and core/shell CdSe/CdS nanoparticles to provide greater stability. Heating of the nanoparticle dispersions polymerizes the cysteine acrylamide on the surface to form a more efficient polydentate stabilizer. The polymer-coated nanoparticle dispersions are colloidally stable even after removal of low molecular weight solutes by dialysis. Emission quantum yields of the polymer-coated CdSe and CdSe/CdS samples were 0.9% and 2.6%, respectively, after aging of the samples in light. CdSe/CdS coated with poly(cysteine acrylamide) is colloidally stable for at least two years in the dark at 5 degrees C.     

Heavy metal contamination in the Taimyr Peninsula,Siberian Arctic

The Taimyr Peninsula is directly north of the world's largest heavy metal smelting complex (Norilsk, Russia). Despite this proximity, there has been little research to examine the extent of contamination of the Taimyr Peninsula. We analyzed heavy metal concentrations in lichen (Cetraria cucullata), moss (Hylocomium splendens), soils, lake sediment, freshwater fish (Salvelinus alpinus, Lota lota and Coregonus spp.) and collared lemming (Dicrostonyx torquatus) from 13 sites between 30 and 300 km from Norilsk. Element concentrations were low in both C. cucullata and H. splendens, although concentrations of Al, Fe, Cu, Ni and Pb were significantly higher than those in Arctic Alaska, probably due to natural differences in the geochemical environments. Inorganic surface soils had significantly higher concentrations of Cd, Zn, Pb and Mg than inorganic soils at depth, although a lake sediment core from the eastern Taimyr Peninsula indicated no recent enrichment by atmospherically transported elements. Tissue concentrations of heavy metals in fish and lemming were not elevated relative to other Arctic sites. Our results show that the impact of the Norilsk smelting complex is primarily localized rather than regional, and does not extend northward beyond 100 km.     

Data mining in brain imaging

Data mining in brain imaging is proving to be an effective methodology for disease prognosis and prevention. This, together with the rapid accumulation of massive heterogeneous data sets, motivates the need for efficient methods that filter, clarify, assess, correlate and cluster brain-related information. Here, we present data mining methods that have been or could be employed in the analysis of brain images. These methods address two types of brain imaging data: structural and functional. We introduce statistical methods that aid the discovery of interesting associations and patterns between brain images and other clinical data. We consider several applications of these methods, such as the analysis of task-activation, lesion-deficit, and structure morphological variability; the development of probabilistic atlases; and tumour analysis. We include examples of applications to real brain data. Several data mining issues, such as that of method validation or verification, are also discussed.     

Parallelisation of the Lagrangian atmospheric dispersion model NAME

The NAME  Atmospheric Dispersion Model is a Lagrangian particle model used by the Met Office to predict the propagation and spread of pollutants in the atmosphere. The model is routinely used in emergency response applications, where it is important to obtain results as quickly as possible. This requirement for a short runtime and the increase in core number of commonly available CPUs, such as the Intel Xeon series, has motivated the parallelisation of NAME  in the OpenMP  shared memory framework. In this work we describe the implementation of this parallelisation strategy in NAME  and discuss the performance of the model for different setups. Due to the independence of the model particles, the parallelisation of the main compute intensive loops is relatively straightforward. The random number generator for modelling sub-grid scale turbulent motion needs to be adapted to ensure that different particles use independent sets of random numbers. We find that on Intel Xeon X5680 CPUs the model shows very good strong scaling up to 12 cores in a realistic emergency response application for predicting the dispersion of volcanic ash in the North Atlantic airspace. We implemented a mechanism for asynchronous reading of meteorological data from disk and demonstrate how this can reduce the runtime if disk access plays a significant role in a model run. To explore the performance on different chip architectures we also ported the part of the code which is used for calculating the gamma dose from a cloud of radioactive particles to a graphics processing unit (GPU) using CUDA-C. We were able to demonstrate a significant speedup of around one order of magnitude relative to the serial CPU version.     

The number and biodiversity of the parasites from small mammals in the evacuation area of the Chernobyl Nuclear Power Station

The study of the micromammalian parasite complexes in the Belorussian part of the evacuation zone of the Chernobyl nuclear station revealed 13 species of Coccidia and 30 species of ectoparasitic Arthropoda. Total increase of abundance and biodiversity of both parasites and their hosts was observed. The part of ectoparasites being epidemically hazardous was significantly increased. An analysis of a long-term dynamics of parasite abundance reveals their adaptation to new conditions in the Belorussia.     

Photonic page buffer based on GaAs multiple-quantum-well modulators bonded directly over active silicon complementary-metal-oxide-semiconductor (CMOS) circuits

We present a 2-kbit, 50-Mpage/s, photonic first-in, first-out page buffer based on gallium arsenide/aluminium-gallium arsenide multiple-quantum-well diodes that are flip-chip bonded to submicrometer silicon complementary-metal-oxide-semiconductor circuits. This photonic chip provides nonvolatile storage (buffering), asynchronous-to-synchronous conversion, bandwidth smoothing, tolerance to jitter or skew, spatial format conversion, wavelength conversion, and independent flow control for the input and the output channels. It serves as an interface chip for parallel-accessed optical bit-plane data. It represents the first smart-pixel array that accomplishes the vertical integration of multiple-quantum-well modulators and detectors directly over active silicon VLSI circuits and provides over 340 transistors per optical input-output. Results from high-speed single-channel testing and real-time array operation of the photonic page buffer are reported.     

The sizes of peptides generated from protein by mammalian 26 and 20 S proteasomes. Implications for understanding the degradative mechanism and antigen presentation

Knowledge about the sizes of peptides generated by proteasomes during protein degradation is essential to fully understand their degradative mechanisms and the subsequent steps in protein turnover and generation of major histocompatibility complex class I antigenic peptides. We demonstrate here that 26 S and activated 20 S proteasomes from rabbit muscle degrade denatured, nonubiquitinated proteins in a highly processive fashion but generate different patterns of peptides (despite their containing identical proteolytic sites). With both enzymes, products range in length from 3 to 22 residues, and their abundance decreases with increasing length according to a log-normal distribution. Less than 15% of the products are the length of class I presented peptides (8 or 9 residues), and two-thirds are too short to function in antigen presentation. Surprisingly, these mammalian proteasomes, which contain two "chymotryptic," two "tryptic," and two "post-acidic" active sites, generate peptides with a similar size distribution as do archaeal 20 S proteasomes, which have 14 identical sites. Furthermore, inactivation of the "tryptic" sites altered the peptides produced without significantly affecting their size distribution. Therefore, this distribution is not determined by the number, specificity, or arrangement of the active sites (as proposed by the "molecular ruler" model); instead, we propose that proteolysis continues until products are small enough to diffuse out of the proteasomes.     

Hilar cholangiocarcinoma: thin-section spiral CT findings with cholangiographic correlation

Hilar cholangiocarcinoma, a highly lethal tumor, is difficult to diagnose with conventional computed tomography (CT) because of its small size. Spiral CT allows more effective evaluation of these small lesions and better demonstrates the status of the hepatic arterial or portal venous circulation. Among 27 patients with hilar cholangiocarcinoma (infiltrative in 21, exophytic in two, polypoid in one, diffuse in three), thin-section spiral CT allowed identification of each tumor as an area of focal wall thickening that obliterated the lumen. Seventeen of the infiltrative tumors (81%) showed high attenuation. Identification of the level of biliary obstruction was possible in 63% of the patients (17 of 27). The level of obstruction was underestimated in six patients and overestimated in four. Spiral CT is a valuable method for diagnosis of hilar cholangiocarcinoma; however, spiral CT is less accurate in evaluation of intraductal tumor extent because of the limited z-axis resolution.