171 research outputs found

    Glomerular cells in culture

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    Major components of atmospheric organic aerosol in southern California as determined by hourly measurements of source marker compounds

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    We report the first hourly in-situ measurements of speciated organic aerosol (OA) composition in an urban environment. Field measurements were made in southern California at the University of California–Riverside during the 2005 Study of Organic Aerosol at Riverside (SOAR), which included two separate measurement periods: a summer study (15 July–15 August) and a fall study (31 October–28 November). Hourly measurements of over 300 semivolatile and nonvolatile organic compounds were made using the thermal desorption aerosol gas chromatograph (TAG). Positive matrix factorization (PMF) was performed on a subset of these compounds to identify major components contributing to submicron (i.e., PM<sub>1</sub>) OA at the site, as measured by an aerosol mass spectrometer (AMS). PMF analysis was performed on an 11-day focus period in each season, representing average seasonal conditions during the summer and a period of urban influence during the fall. As a result of this analysis, we identify multiple types of primary and secondary OA (POA and SOA). Secondary sources contribute substantially to fine OA mass at Riverside, which commonly receives regional air masses that pass through metropolitan Los Angeles during the summer. Four individual summertime SOA components are defined, and when combined, they are estimated to contribute an average 88% of the total fine OA mass during summer afternoons according to PMF results. These sources appear to be mostly from the oxidation of anthropogenic precursor gases, with one SOA component having contributions from oxygenated biogenics. During the fall, three out of four aerosol components that contain SOA are inseparable from covarying primary emissions, and therefore we cannot estimate the fraction of total OA that is secondary in nature during the fall study. Identified primary OA components are attributed to vehicle emissions, food cooking, primary biogenics, and biomass burning aerosol. While a distinction between local and regional vehicle emissions is made, a combination of these two factors accounted for approximately 11% of observed submicron OA during both sampling periods. Food cooking operations contributed ~10% of submicron OA mass during the summer, but was not separable from SOA during the fall due to high covariance of sources. Biomass burning aerosol contributed a larger fraction of fine OA mass during the fall (~11%) than compared to summer (~7%). Primary biogenic aerosol was also identified during the summer, contributing ~1% of the OA, but not during the fall. While the contribution of both local and regional primary vehicle OA accounts for only ~11% of total OA during both seasons, gas-phase vehicle emissions likely create a substantial fraction of the observed SOA as a result of atmospheric processing

    Methods for visual mining of genomic and proteomic data atlases

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    <p>Abstract</p> <p>Background</p> <p>As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data. The challenge addressing bioinformatics researches is how to apply this knowledge to data sets that are continually growing in a field that is rapidly changing.</p> <p>Results</p> <p>This paper discusses an approach to the development of visual mining tools capable of supporting the mining of massive data collections used in systems biology research, and also discusses lessons that have been learned providing tools for both local researchers and the wider community. Example tools were developed which are designed to enable the exploration and analyses of both proteomics and genomics based atlases. These atlases represent large repositories of raw and processed experiment data generated to support the identification of biomarkers through mass spectrometry (the PeptideAtlas) and the genomic characterization of cancer (The Cancer Genome Atlas). Specifically the tools are designed to allow for: the visual mining of thousands of mass spectrometry experiments, to assist in designing informed targeted protein assays; and the interactive analysis of hundreds of genomes, to explore the variations across different cancer genomes and cancer types.</p> <p>Conclusions</p> <p>The mining of massive repositories of biological data requires the development of new tools and techniques. Visual exploration of the large-scale atlas data sets allows researchers to mine data to find new meaning and make sense at scales from single samples to entire populations. Providing linked task specific views that allow a user to start from points of interest (from diseases to single genes) enables targeted exploration of thousands of spectra and genomes. As the composition of the atlases changes, and our understanding of the biology increase, new tasks will continually arise. It is therefore important to provide the means to make the data available in a suitable manner in as short a time as possible. We have done this through the use of common visualization workflows, into which we rapidly deploy visual tools. These visualizations follow common metaphors where possible to assist users in understanding the displayed data. Rapid development of tools and task specific views allows researchers to mine large-scale data almost as quickly as it is produced. Ultimately these visual tools enable new inferences, new analyses and further refinement of the large scale data being provided in atlases such as PeptideAtlas and The Cancer Genome Atlas.</p

    Expression and localisation of Akt-1, Akt-2 and Akt-3 correlate with clinical outcome of prostate cancer patients

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    We investigated the correlation between the expression and localisation of Akt-1, Akt-2, Akt-3, phospho-Akt proteins and the clinicopathological parameters in 63 prostate cancer specimens. More than 60% of cancerous tissues overexpressed Akt-1, Akt-2 or Akt-3. Cytoplasmic Akt-1 expression was correlated with a higher risk of postoperative prostate-specific antigen (PSA) recurrence and shorter PSA recurrence interval. Cytoplasmic Akt-2 did not show any significant correlation with clinicopathological parameters predicting outcomes. Cytoplasmic Akt-3 was associated with hormone-refractory disease progression and extracapsular invasion. Nuclear Akt-1 and Akt-2 expression were correlated with favourable outcome parameters such as absence of lymph node and perineural invasion. Kaplan–Meier analysis and Cox regression model also showed that Akt-1 and Akt-2, but not Akt-3 or phospho-Akt was associated with a significantly higher risk of PSA recurrence. In contrast, nuclear Akt-1 was significantly associated with a lower risk of PSA recurrence. Multivariate analysis revealed that clinical stage, Gleason score and the combined cytoplasmic nuclear Akt-1 marker in cancerous tissues were significant independent prognostic factors of PSA recurrence. This is the first report demonstrating in patients with prostate cancer and the particular role of Akt-1 isoform expression as a prognostic marker depending of its localisation

    Caffeic Acid Phenethyl Ester Causes p21Cip1 Induction, Akt Signaling Reduction, and Growth Inhibition in PC-3 Human Prostate Cancer Cells

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    Caffeic acid phenethyl ester (CAPE) treatment suppressed proliferation, colony formation, and cell cycle progression in PC-3 human prostate cancer cells. CAPE decreased protein expression of cyclin D1, cyclin E, SKP2, c-Myc, Akt1, Akt2, Akt3, total Akt, mTOR, Bcl-2, Rb, as well as phosphorylation of Rb, ERK1/2, Akt, mTOR, GSK3α, GSK3β, PDK1; but increased protein expression of KLF6 and p21Cip1. Microarray analysis indicated that pathways involved in cellular movement, cell death, proliferation, and cell cycle were affected by CAPE. Co-treatment of CAPE with chemotherapeutic drugs vinblastine, paclitaxol, and estramustine indicated synergistic suppression effect. CAPE administration may serve as a potential adjuvant therapy for prostate cancer

    Human malarial disease: a consequence of inflammatory cytokine release

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    Malaria causes an acute systemic human disease that bears many similarities, both clinically and mechanistically, to those caused by bacteria, rickettsia, and viruses. Over the past few decades, a literature has emerged that argues for most of the pathology seen in all of these infectious diseases being explained by activation of the inflammatory system, with the balance between the pro and anti-inflammatory cytokines being tipped towards the onset of systemic inflammation. Although not often expressed in energy terms, there is, when reduced to biochemical essentials, wide agreement that infection with falciparum malaria is often fatal because mitochondria are unable to generate enough ATP to maintain normal cellular function. Most, however, would contend that this largely occurs because sequestered parasitized red cells prevent sufficient oxygen getting to where it is needed. This review considers the evidence that an equally or more important way ATP deficency arises in malaria, as well as these other infectious diseases, is an inability of mitochondria, through the effects of inflammatory cytokines on their function, to utilise available oxygen. This activity of these cytokines, plus their capacity to control the pathways through which oxygen supply to mitochondria are restricted (particularly through directing sequestration and driving anaemia), combine to make falciparum malaria primarily an inflammatory cytokine-driven disease

    The Molecular Identification of Organic Compounds in the Atmosphere: State of the Art and Challenges

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