Computational Methods for the Analysis of Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visualization and genomic profile analysis, review currently available software packages, and raise considerations for future software development

Effects of calorie restriction and IGF-1 receptor blockade on the progression of 22Rv1 prostate cancer xenografts.

Calorie restriction (CR) inhibits prostate cancer progression, partially through modulation of the IGF axis. IGF-1 receptor (IGF-1R) blockade reduces prostate cancer xenograft growth. We hypothesized that combining calorie restriction with IGF-1R blockade would have an additive effect on prostate cancer growth. Severe combined immunodeficient mice were subcutaneously injected with 22Rv1 cells and randomized to: (1) Ad libitum feeding/intraperitoneal saline (Ad-lib); (2) Ad-lib/20 mg/kg twice weekly, intraperitoneal ganitumab [anti-IGF-1R antibody (Ad-lib/Ab)]; (3) 40% calorie restriction/intraperitoneal saline (CR); (4) CR/ intraperitoneal ganitumab, (CR/Ab). CR and ganitumab treatment were initiated one week after tumor injection. Euthanasia occurred 19 days post treatment. Results showed that CR alone decreased final tumor weight, plasma insulin and IGF-1 levels, and increased apoptosis. Ganitumab therapy alone reduced tumor growth but had no effect on final tumor weight. The combination therapy (CR/Ab) further decreased final tumor weight and proliferation, increased apoptosis in comparison to the Ad-lib group, and lowered plasma insulin levels relative to the Ad-lib and Ad-lib/Ab groups. Tumor AKT activation directly correlated with plasma IGF-1 levels. In conclusion, whereas ganitumab therapy modestly affected 22Rv1 tumor growth, combining IGF-1R blockade with calorie restriction resulted in a significant decrease in final tumor weight and improved metabolic profile

Towards energy transition: conjoint assessment of large-scale PV system performance and interconnection impacts in isolated microgrid

Environmental, energy security and electricity demand concerns stimulate solar-grid integration. However, intermittent, non-dispatchable PV characteristics may challenge passive grid operation. This paper contains the comprehensive planning and assessment of a 2 MWp CdTe-based PV system deployment proposed for hybrid operation in an isolated 11 kV 10-bus microgrid in Brunei. The presented approach combinedly assesses PV system performance and scenario-based interconnection impacts based on a detailed PV system model considering deployment conditions. Various interconnection points with multiple sets of feeder-specific measured load profiles are examined. Results show the PV system designed for maximum annual generation achieves performance ratio of 90.6%. While time-series power flow assessment reveals grid operation enhancement, there are concerns at times of generation-demand mismatch requiring proper genset sequencing and reactive power management. Meanwhile, faster relay operating time and reverse fault current are demonstrated in existing protection scheme. Dynamic grid stabilities are preserved in various generation intermittency and loss events, including the most challenging condition of further inertia and spinning reserve reduction reaching a frequency of 96.02%. Finally, optimal interconnection point fulfilling multi-objectives on losses, voltage profile and line reserve capacity is identified. The findings indicate a good prospect of the synergy for advancing energy transition. The analysis could facilitate RE planning and policymaking

Crystallization and preliminary x-ray diffraction analysis of the unliganded human growth hormone receptor

The crystal structure of the extracellular domain of growth hormone receptor complexed to its ligand, growth hormone, has been known since 1992. However, no information exists for the unliganded form of the receptor. The human growth hormone receptor's extracellular ligand-binding domain, encompassing amino-acid residues 1 - 238, has been expressed in Escherichia coli, purified by anion ion-exchange chromatography and crystallized in its unliganded state by the hanging-drop vapour-diffusion method in 100 mM HEPES pH 7.0 containing 27.5%(w/v) PEG 5000 monomethyl ether and 200 mM ammonium sulfate as the co-precipitants. The crystals belong to the othorhombic space group C222(1), have unit-cell parameters a = 99.7, b = 112.2, c = 93.2 Angstrom and diffract to 2.5 Angstrom resolution using synchrotron radiation. The crystal structure will shed light on the nature of any conformation changes that occur upon ligand binding and will provide information to develop potential low-molecular-weight agonists/antagonists to treat clinical diseases in which the growth hormone receptor is implicated

SIGMA: A System for Integrative Genomic Microarray Analysis of Cancer Genomes

BACKGROUND: The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. RESULTS: We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. CONCLUSION: In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA) of cancer genomes, can be accessed at

Development and assessment of scoring functions for protein identification using PMF data

PMF is one of the major methods for protein identification using the MS technology. It is faster and cheaper than MS/MS. Although PMF does not differentiate trypsin-digested peptides of identical mass, which makes it less informative than MS/MS, current computational methods for PMF have the potential to improve its detection accuracy by better use of the information content in PMF spectra. We developed a number of new probability-based scoring functions for PMF protein identification based on the MOWSE algorithm. We considered a detailed distribution of matching masses in a protein database and peak intensity, as well as the likelihood of peptide matches to be close to each other in a protein sequence. Our computational methods are assessed and compared with other methods using PMF data of 52 gel spots of known protein standards. The comparison shows that our new scoring schemes have higher or comparable accuracies for protein identification in comparison to the existing methods. Our software is freely available upon request. The scoring functions can be easily incorporated into other proteomics software packages

Influenza D Virus Infection in Feral Swine Populations, United States

Influenza D virus (IDV) has been identified in domestic cattle, swine, camelid, and small ruminant populations across North America, Europe, Asia, South America, and Africa. Our study investigated seroprevalence and transmissibility of IDV in feral swine. During 2012–2013, we evaluated feral swine populations in 4 US states; of 256 swine tested, 57 (19.1%) were IDV seropositive. Among 96 archived influenza A virus–seropositive feral swine samples collected from 16 US states during 2010–2013, 41 (42.7%) were IDV seropositive. Infection studies demonstrated that IDV-inoculated feral swine shed virus 3–5 days postinoculation and seroconverted at 21 days postinoculation; 50% of in-contact naive feral swine shed virus, seroconverted, or both. Immunohistochemical staining showed viral antigen within epithelial cells of the respiratory tract, including trachea, soft palate, and lungs. Our findings suggest that feral swine might serve an important role in the ecology of IDV

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics. Methodology/Principal Findings. We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005. Conclusions/Significance. Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling