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Find video protocols related to scientific articles indexed in Pubmed.
Oat1/3 Restoration Protects against Renal Damage after Ischemic AKI.
Am. J. Physiol. Renal Physiol.
PUBLISHED: 11-14-2014
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Expression of proximal tubular organic anion transporters Oat1 and Oat3 is reduced by prostaglandin E2 (PGE2) after renal ischemia and reperfusion (I/R) injury. We hypothesized that impaired expression of Oat1/3 is decisively involved in deterioration of renal function after I/R injury. Therefore, we administered probenecid, which blocks proximal tubular indomethacin uptake, to abolish indomethacin mediated restoration of Oat1/3 regulation and its effect on renal functional and morphological outcome. Ischemic AKI was induced in rats by bilateral clamping of renal arteries for 45 min with 24h follow up. Low-dose indomethacin (1mg/kg) was given i.p. at the end of ischemia. Probenecid (50mg/kg) was administered i.p. 20 min later. Indomethacin restored Oat1/3 expression, PAH net secretion and PGE2 clearance and improved kidney function as measured by GFR, renal perfusion as determined by corrected PAH clearance and morphology, whereas it reduced renal cortical apoptosis and nitric oxide production. Notably, indomethacin did not affect inflammation parameters in the kidneys (e.g. MCP-1, ED1+-cells). On the other hand, probenecid blocked indomethacin induced restoration of Oat1/3 and moreover abrogated all beneficial effects. Our study indicates that the beneficial effect of low-dose indomethacin in iAKI is not due to its anti-inflammatory potency, but to its restoration of Oat1/3 expression and/or general renal function. Inhibition of proximal tubular indomethacin uptake abrogates the beneficial effect of indomethacin by resetting the PGE2 mediated Oat1/3 impairment, thus re-establishing renal damage. This provides evidence for a mechanistic effect of Oat1/3 in a new model of the induction of renal damage following ischemic AKI.
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BioTextQuest+: a knowledge integration platform for literature mining and concept discovery.
Bioinformatics
PUBLISHED: 08-06-2014
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The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related biological databases. Herein, we describe BioTextQuest(+), a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest(+) enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest(+) addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest(+) through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing.
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PredictProtein--an open resource for online prediction of protein structural and functional features.
Nucleic Acids Res.
PUBLISHED: 05-05-2014
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PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein-protein binding sites (ISIS2), protein-polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.
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COMPARTMENTS: unification and visualization of protein subcellular localization evidence.
Database (Oxford)
PUBLISHED: 01-01-2014
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Information on protein subcellular localization is important to understand the cellular functions of proteins. Currently, such information is manually curated from the literature, obtained from high-throughput microscopy-based screens and predicted from primary sequence. To get a comprehensive view of the localization of a protein, it is thus necessary to consult multiple databases and prediction tools. To address this, we present the COMPARTMENTS resource, which integrates all sources listed above as well as the results of automatic text mining. The resource is automatically kept up to date with source databases, and all localization evidence is mapped onto common protein identifiers and Gene Ontology terms. We further assign confidence scores to the localization evidence to facilitate comparison of different types and sources of evidence. To further improve the comparability, we assign confidence scores based on the type and source of the localization evidence. Finally, we visualize the unified localization evidence for a protein on a schematic cell to provide a simple overview. Database URL: http://compartments.jensenlab.org.
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Signaling in Insulin-Secreting MIN6 Pseudoislets and Monolayer Cells.
J. Proteome Res.
PUBLISHED: 09-30-2013
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Cell-cell interactions are of fundamental importance for cellular function. In islets of Langerhans, which control blood glucose levels by secreting insulin in response to the blood glucose concentration, the secretory response of intact islets is higher than that of insulin-producing beta-cells not arranged in the islet architecture. The objective was to define mechanisms by which cellular performance is enhanced when cells are arranged in three-dimensional space. The task was addressed by making a comprehensive analysis based on protein expression patterns generated from insulin-secreting MIN6 cells grown as islet-like clusters, so-called pseudoislets, and in monolayers. After culture, glucose-stimulated insulin secretion (GSIS) was measured from monolayers and pseudoislets. GSIS rose 6-fold in pseudoislets but only 3-fold in monolayers when the glucose concentration was increased from 2 to 20 mmol/L. Proteins from pseudoislets and monolayers were extracted and analyzed by liquid-chromatography mass spectrometry, and differentially expressed proteins were mapped onto KEGG pathways. Protein profiling identified 1576 proteins, which were common to pseudoislets and monolayers. When mapped onto KEGG pathways, 11 highly enriched pathways were identified. On the basis of differences in expression of proteins belonging to the pathways in pseudoislets and monolayers, predictions of differential pathway activation were performed. Mechanisms enhancing insulin secretory capacity of the beta-cell, when situated in the islet, include pathways regulating glucose metabolism, cell interaction, and translational regulation.
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Toward silicon anodes for next-generation lithium ion batteries: a comparative performance study of various polymer binders and silicon nanopowders.
ACS Appl Mater Interfaces
PUBLISHED: 08-01-2013
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Silicon is widely regarded as one of the most promising anode materials for lithium ion and next-generation lithium batteries because of its high theoretical specific capacity. However, major issues arise from the large volume changes during alloying with lithium. In recent years, much effort has been spent on preparing nanostructured silicon and optimizing various aspects of material processing with the goal of preserving the electrode integrity upon lithiation/delithiation. The performance of silicon anodes is known to depend on a large number of parameters and, thus, the general definition of a "standard" is virtually impossible. In this work, we conduct a comparative performance study of silicon anode tapes prepared from commercially available materials while using both a well-defined electrode configuration and cycling method. Our results demonstrate that the polymer binder has a profound effect on the cell performance. Furthermore, we show that key parameters such as specific capacity, capacity retention, rate capability, and so forth can be strongly affected by the choice of silicon material, polymer binder and electrolyte system - even the formation of metastable crystalline Li15Si4 is found to depend on the electrode composition and low potential exposure time. Overall, the use of either poly(acrylic acid) with a viscosity-average molecular weight of 450.000 or poly(vinyl alcohol) Selvol 425 in combination with both silicon nanopowder containing a native oxide surface layer of ?1 nm in diameter and with a monofluoroethylene carbonate-based electrolyte led to improved cycling stability at high loadings.
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iAnn: an event sharing platform for the life sciences.
Bioinformatics
PUBLISHED: 06-05-2013
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We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available.
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Transformation of the matrix structure of shrimp shells during bacterial deproteination and demineralization.
Microb. Cell Fact.
PUBLISHED: 05-22-2013
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After cellulose and starch, chitin is the third-most abundant biopolymer on earth. Chitin or its deacetylated derivative chitosan is a valuable product with a number of applications. It is one of the main components of shrimp shells, a waste product of the fish industry. To obtain chitin from Penaeus monodon, wet and dried shrimp shells were deproteinated with two specifically enriched proteolytic cultures M1 and M2 and decalcified by in-situ lactic acid forming microorganisms. The viscosity of biologically processed chitin was compared with chemically processed chitin. The former was further investigated for purity, structure and elemental composition by several microscopic techniques and (13)C solid state NMR spectroscopy.
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Application of low-energy scanning transmission electron microscopy for the study of Pt-nanoparticle uptake in human colon carcinoma cells.
Nanotoxicology
PUBLISHED: 05-09-2013
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Abstract High-angle annular dark-field scanning transmission electron microscopy (HAADF STEM) in a scanning electron microscope facilitates the acquisition of images with high chemical sensitivity and high resolution. HAADF STEM at low electron energies is particularly suited to image nanoparticles (NPs) in thin cell sections which are not subjected to poststaining procedures as demonstrated by comparison with bright-field TEM. High membrane contrast is achieved and distinction of NPs with different chemical composition is possible at first sight. Low-energy HAADF STEM was applied to systematically study the uptake of Pt-NPs with a broad size distribution in HT29 colon carcinoma cells as a function of incubation time and incubation temperature. The cellular dose was quantified, that is, the amount and number density of NPs taken up by the cells, as well as the particle-size distribution. The results show a strong dependence of the amount of incubated NPs on the exposure time which can be understood by considering size-dependent diffusion and gravitational settling of the NPs in the cell culture medium.
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Increased symmetrical dimethylarginine in ischemic acute kidney injury as a causative factor of renal L-arginine deficiency.
Transl Res
PUBLISHED: 04-25-2013
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Availability of L-arginine, the exclusive substrate for nitric oxide synthases, plays an important role in kidney ischemia/reperfusion injury. The endogenous L-arginine derivatives asymmetrical dimethylarginine (ADMA) and symmetrical dimethylarginine (SDMA) block cellular L-arginine uptake competitively, thereby inhibiting the production of nitric oxide. ADMA also blocks nitric oxide synthase activity directly. Here, we investigate the pathomechanistic impact of ADMA and SDMA on ischemic acute kidney injury. Rats were subject to bilateral renal ischemia (60 minutes)/reperfusion (24 hours) injury. Impairment of renal function was determined with inulin clearance (glomerular filtration rate) and para-aminohippurate (PAH) clearance (renal plasma flow). L-arginine, ADMA, and SDMA levels were measured by liquid chromatography-tandem mass spectrometry. L-arginine was extracted from renal tissue and analyzed by enzyme-linked immunosorbent assay, and protein and messenger RNA expressions were determined by Western blot and real-time reverse transcription polymerase chain reaction. Renal function deteriorated severely after ischemia/reperfusion injury, as demonstrated by inulin and PAH clearance. Serum ADMA and SDMA increased, but tissue expression of specific ADMA or SDMA synthesizing and metabolizing enzymes (protein arginine methyltransferases and dimethyl arginine dimethylaminohydrolases) did not alter. Serum L-arginine increased as well, whereas intracellular L-arginine concentration diminished. Renal messenger RNA expression of cationic amino acid transporters, which mediate L-arginine uptake, remained unchanged. In serum, the ratio of L-arginine to ADMA did not alter after ischemia/reperfusion injury, whereas the ratios of L-arginine to SDMA and ADMA to SDMA decreased. A marked increase in serum SDMA, especially when accompanied by a diminished L-arginine-to-SDMA ratio, might reflect competitive inhibition of cellular L-arginine uptake by SDMA. As a consequence, a pathologic renal L-arginine deficiency in ischemic acute kidney injury results.
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Integrating Pathways of Parkinsons Disease in a Molecular Interaction Map.
Mol. Neurobiol.
PUBLISHED: 04-15-2013
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Parkinsons disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map .
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Visualizing time-related data in biology, a review.
Brief. Bioinformatics
PUBLISHED: 04-12-2013
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Time is of the essence in biology as in so much else. For example, monitoring disease progression or the timing of developmental defects is important for the processes of drug discovery and therapy trials. Furthermore, an understanding of the basic dynamics of biological phenomena that are often strictly time regulated (e.g. circadian rhythms) is needed to make accurate inferences about the evolution of biological processes. Recent advances in technologies have enabled us to measure timing effects more accurately and in more detail. This has driven related advances in visualization and analysis tools that try to effectively exploit this data. Beyond timeline plots, notable attempts at more involved temporal interpretation have been made in recent years, but awareness of the available resources is still limited within the scientific community. Here, we review some advances in biological visualization of time-driven processes and consider how they aid data analysis and interpretation.
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Genome-wide identification and functional analyses of microRNA signatures associated with cancer pain.
EMBO Mol Med
PUBLISHED: 03-23-2013
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Cancer pain remains a major challenge and there is an urgent demand for the development of specific mechanism-based therapies. Various diseases are associated with unique signatures of expression of microRNAs (miRNAs), which reveal deep insights into disease pathology. Using a comprehensive approach combining genome-wide miRNA screening, molecular and in silico analyses with behavioural approaches in a clinically relevant model of metastatic bone-cancer pain in mice, we now show that tumour-induced conditions are associated with a marked dysregulation of 57 miRNAs in sensory neurons corresponding to tumour-affected areas. By establishing protocols for interference with disease-induced miRNA dysregulation in peripheral sensory neurons in vivo, we functionally validate six dysregulated miRNAs as significant modulators of tumour-associated hypersensitivity. In silico analyses revealed that their predicted targets include key pain-related genes and we identified Clcn3, a gene encoding a chloride channel, as a key miRNA target in sensory neurons, which is functionally important in tumour-induced nociceptive hypersensitivity in vivo. Our results provide new insights into endogenous gene regulatory mechanisms in cancer pain and open up attractive and viable therapeutic options.
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Unraveling genomic variation from next generation sequencing data.
BioData Min
PUBLISHED: 03-22-2013
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Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have been generated in various biological areas. Few of these areas, which get shaped by the new technological advances, involve evolution of species, microbial mapping, population genetics, genome-wide association studies (GWAs), comparative genomics, variant analysis, gene expression, gene regulation, epigenetics and personalized medicine. While NGS techniques stand as key players in modern biological research, the analysis and the interpretation of the vast amount of data that gets produced is a not an easy or a trivial task and still remains a great challenge in the field of bioinformatics. Therefore, efficient tools to cope with information overload, tackle the high complexity and provide meaningful visualizations to make the knowledge extraction easier are essential. In this article, we briefly refer to the sequencing methodologies and the available equipment to serve these analyses and we describe the data formats of the files which get produced by them. We conclude with a thorough review of tools developed to efficiently store, analyze and visualize such data with emphasis in structural variation analysis and comparative genomics. We finally comment on their functionality, strengths and weaknesses and we discuss how future applications could further develop in this field.
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Transcriptional mechanisms underlying sensitization of peripheral sensory neurons by granulocyte-/granulocyte-macrophage colony stimulating factors.
Mol Pain
PUBLISHED: 03-21-2013
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Cancer-associated pain is a major cause of poor quality of life in cancer patients and is frequently resistant to conventional therapy. Recent studies indicate that some hematopoietic growth factors, namely granulocyte macrophage colony stimulating factor (GMCSF) and granulocyte colony stimulating factor (GCSF), are abundantly released in the tumor microenvironment and play a key role in regulating tumor-nerve interactions and tumor-associated pain by activating receptors on dorsal root ganglion (DRG) neurons. Moreover, these hematopoietic factors have been highly implicated in postsurgical pain, inflammatory pain and osteoarthritic pain. However, the molecular mechanisms via which G-/GMCSF bring about nociceptive sensitization and elicit pain are not known.
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Mild therapeutic hypothermia after out-of-hospital cardiac arrest complicating ST-elevation myocardial infarction: long-term results in clinical practice.
Clin Cardiol
PUBLISHED: 02-06-2013
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Recently, mild therapeutic hypothermia (MTH) has been integrated into the European resuscitation guidelines to improve outcomes after out-of-hospital cardiac arrest (OHCA). Data on long-term results are limited, especially in patients with acute ST-elevation myocardial infarction (STEMI).
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Resemblance of electrospun collagen nanofibers to their native structure.
Langmuir
PUBLISHED: 01-22-2013
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Electrospinning is a promising method to mimic the native structure of the extracellular matrix. Collagen is the material of choice, since it is a natural fibrous structural protein. It is an open question how much the spinning process preserves or alters the native structure of collagen. There are conflicting results in the literature, mainly due to the different solvent systems in use and due to the fact that gelatin is employed as a reference state for the completely unfolded state of collagen in calculations. Here we used circular dichroism (CD) and Fourier-transform infrared spectroscopy (FTIR) to investigate the structure of regenerated collagen samples and scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to illuminate the electrospun nanofibers. Collagen is mostly composed of folded and unfolded structures with different ratios, depending on the applied temperature. Therefore, CD spectra were acquired as a temperature series during thermal denaturation of native calf skin collagen type I and used as a reference basis to extract the degree of collagen folding in the regenerated electrospun samples. We discussed three different approaches to determine the folded fraction of collagen, based on CD spectra of collagen from 185 to 260 nm, since it would not be sufficient to obtain simply the fraction of folded structure ? from the ellipticity at a single wavelength of 221.5 nm. We demonstrated that collagen almost completely unfolded in fluorinated solvents and partially preserved its folded structure ? in HAc/EtOH. However, during the spinning process it refolded and the PP-II fraction increased. Nevertheless, it did not exceed 42% as deduced from the different secondary structure evaluation methods, discussed here. PP-II fractions in electrospun collagen nanofibers were almost same, being independent from the initial solvent systems which were used to solubilize the collagen for electrospinning process.
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Nuclear calcium signaling in spinal neurons drives a genomic program required for persistent inflammatory pain.
Neuron
PUBLISHED: 01-15-2013
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Persistent pain induced by noxious stimuli is characterized by the transition from normosensitivity to hypersensitivity. Underlying mechanisms are not well understood, although gene expression is considered important. Here, we show that persistent nociceptive-like activity triggers calcium transients in neuronal nuclei within the superficial spinal dorsal horn, and that nuclear calcium is necessary for the development of long-term inflammatory hypersensitivity. Using a nucleus-specific calcium signal perturbation strategy in vivo complemented by gene profiling, bioinformatics, and functional analyses, we discovered a pain-associated, nuclear calcium-regulated gene program in spinal excitatory neurons. This includes C1q, a modulator of synaptic spine morphogenesis, which we found to contribute to activity-dependent spine remodelling on spinal neurons in a manner functionally associated with inflammatory hypersensitivity. Thus, nuclear calcium integrates synapse-to-nucleus communication following noxious stimulation and controls a spinal genomic response that mediates the transition between acute and long-term nociceptive sensitization by modulating functional and structural plasticity.
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PhenoTimer: software for the visual mapping of time-resolved phenotypic landscapes.
PLoS ONE
PUBLISHED: 01-01-2013
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Timing common and specific modulators of disease progression is crucial for treatment, but the understanding of the underlying complex system of interactions is limited. While attempts at elucidating this experimentally have produced enormous amounts of phenotypic data, tools that are able to visualize and analyze them are scarce and the insight obtained from the data is often unsatisfactory. Linking and visualizing processes from genes to phenotypes and back, in a temporal context, remains a challenge in systems biology. We introduce PhenoTimer, a 2D/3D visualization tool for the mapping of time-resolved phenotypic links in a genetic context. It uses a novel visualization approach for relations between morphological defects, pathways or diseases, to enable fast pattern discovery and hypothesis generation. We illustrate its capabilities of tracing dynamic motifs on cell cycle datasets that explore the phenotypic order of events upon perturbations of the system, transcriptional activity programs and their connection to disease. By using this tool we are able to fine-grain regulatory programs for individual time points of the cell cycle and better understand which patterns arise when these programs fail. We also illustrate a way to identify common mechanisms of misregulation in diseases and drug abuse.
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Quantitative high-resolution transmission electron microscopy of single atoms.
Microsc. Microanal.
PUBLISHED: 12-12-2011
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Single atoms can be considered as the most basic objects for electron microscopy to test the microscope performance and basic concepts for modeling image contrast. In this work high-resolution transmission electron microscopy was applied to image single platinum, molybdenum, and titanium atoms in an aberration-corrected transmission electron microscope. The atoms are deposited on a self-assembled monolayer substrate that induces only negligible contrast. Single-atom contrast simulations were performed on the basis of Weickenmeier-Kohl and Doyle-Turner form factors. Experimental and simulated image intensities are in quantitative agreement on an absolute intensity scale, which is provided by the vacuum image intensity. This demonstrates that direct testing of basic properties such as form factors becomes feasible.
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PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data.
Bioinformatics
PUBLISHED: 11-28-2011
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Finding significant differences between the expression levels of genes or proteins across diverse biological conditions is one of the primary goals in the analysis of functional genomics data. However, existing methods for identifying differentially expressed genes or sets of genes by comparing measures of the average expression across predefined sample groups do not detect differential variance in the expression levels across genes in cellular pathways. Since corresponding pathway deregulations occur frequently in microarray gene or protein expression data, we present a new dedicated web application, PathVar, to analyze these data sources. The software ranks pathway-representing gene/protein sets in terms of the differences of the variance in the within-pathway expression levels across different biological conditions. Apart from identifying new pathway deregulation patterns, the tool exploits these patterns by combining different machine learning methods to find clusters of similar samples and build sample classification models.
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Which clustering algorithm is better for predicting protein complexes?
BMC Res Notes
PUBLISHED: 07-21-2011
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Protein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks.
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Out-of-hospital cardiac arrest and percutaneous coronary intervention for ST-elevation myocardial infarction: long-term survival and neurological outcome.
Int. J. Cardiol.
PUBLISHED: 06-16-2011
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Predictors of long-term outcome after ST-elevation myocardial infarction (STEMI) complicated by out-of-hospital cardiac arrest (OHCA) are incompletely understood, including the influence of successful coronary reperfusion.
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Medusa: A tool for exploring and clustering biological networks.
BMC Res Notes
PUBLISHED: 05-31-2011
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Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis.
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Using graph theory to analyze biological networks.
BioData Min
PUBLISHED: 04-28-2011
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Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system.
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Facile preparation of water-soluble fluorescent gold nanoclusters for cellular imaging applications.
Nanoscale
PUBLISHED: 02-10-2011
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We report a facile strategy to synthesize water-soluble, fluorescent gold nanoclusters (AuNCs) in one step by using a mild reductant, tetrakis(hydroxymethyl)phosphonium chloride (THPC). A zwitterionic functional ligand, D-penicillamine (DPA), as a capping agent endowed the AuNCs with excellent stability in aqueous solvent over the physiologically relevant pH range. The DPA-capped AuNCs displayed excitation and emission bands at 400 and 610 nm, respectively; the fluorescence quantum yield was 1.3%. The effect of borohydride reduction on the optical spectra and X-ray photoelectron spectroscopy (XPS) results indicated that the AuNC luminescence is closely related to the presence of Au(I) on their surfaces. In a first optical imaging application, we studied internalization of the AuNCs by live HeLa cells using confocal microscopy with two-photon excitation. A cell viability assay revealed good biocompatibility of these AuNCs. Our studies demonstrate a great potential of DPA-stabilized AuNCs as fluorescent nanoprobes in bioimaging and related applications.
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Ultraviolet photoluminescence of ZnO quantum dots sputtered at room-temperature.
Opt Express
PUBLISHED: 01-26-2011
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We observe ultraviolet photoluminescence from sputtered ZnO quantum dots which are fabricated with no annealing steps. The nanocrystals are embedded in amorphous SiO2 and exhibit a narrow size distribution of 3.5 ± 0.6 nm. Photoluminescence and transmittance measurements show a shift of ultraviolet emission and absorption of the dots compared to bulk ZnO material. This work paves the way for cheap nanooptical devices in the ultraviolet which are fabricated in a single sputtering run.
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Platinum nanoparticles and their cellular uptake and DNA platination at non-cytotoxic concentrations.
Arch. Toxicol.
PUBLISHED: 01-13-2011
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Three differently sized, highly dispersed platinum nanoparticle (Pt-NP) preparations were generated by supercritical fluid reactive deposition (SFRD) and deposited on a ?-cyclodextrin matrix. The average particle size and size distribution were steered by the precursor reduction conditions, resulting in particle preparations of <20, <100 and >100 nm as characterised by TEM and SEM. As reported previously, these Pt-NPs were found to cause DNA strand breaks in human colon carcinoma cells (HT29) in a concentration- and time-dependent manner and a distinct size dependency. Here, we addressed the question whether Pt-NPs might affect directly DNA integrity in these cells and thus behave analogous to platinum-based chemotherapeutics such as cisplatin. Therefore, DNA-associated Pt as well as the translocation of Pt-NPs through a Caco-2 monolayer was quantified by ICP-MS. STEM imaging demonstrated that Pt-NPs were taken up into HT29 cells in their particulate and aggregated form, but appear not to translocate into the nucleus or interact with mitochondria. The platinum content of the DNA of HT29 cells was found to increase in a time- and concentration-dependent manner with a maximal effect at 1,000 ng/cm(2). ICP-MS analysis of the cell culture medium indicated the formation of soluble Pt species, although to a limited extent. The observations suggest that DNA strand breaks mediated by metallic Pt-NPs are caused by Pt ions forming during the incubation of cells with these nanoparticles.
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A series of PDB related databases for everyday needs.
Nucleic Acids Res.
PUBLISHED: 11-11-2010
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The Protein Data Bank (PDB) is the world-wide repository of macromolecular structure information. We present a series of databases that run parallel to the PDB. Each database holds one entry, if possible, for each PDB entry. DSSP holds the secondary structure of the proteins. PDBREPORT holds reports on the structure quality and lists errors. HSSP holds a multiple sequence alignment for all proteins. The PDBFINDER holds easy to parse summaries of the PDB file content, augmented with essentials from the other systems. PDB_REDO holds re-refined, and often improved, copies of all structures solved by X-ray. WHY_NOT summarizes why certain files could not be produced. All these systems are updated weekly. The data sets can be used for the analysis of properties of protein structures in areas ranging from structural genomics, to cancer biology and protein design.
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GPCRs, G-proteins, effectors and their interactions: human-gpDB, a database employing visualization tools and data integration techniques.
Database (Oxford)
PUBLISHED: 08-07-2010
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G-protein coupled receptors (GPCRs) are a major family of membrane receptors in eukaryotic cells. They play a crucial role in the communication of a cell with the environment. Ligands bind to GPCRs on the outside of the cell, activating them by causing a conformational change, and allowing them to bind to G-proteins. Through their interaction with G-proteins, several effector molecules are activated leading to many kinds of cellular and physiological responses. The great importance of GPCRs and their corresponding signal transduction pathways is indicated by the fact that they take part in many diverse disease processes and that a large part of efforts towards drug development today is focused on them. We present Human-gpDB, a database which currently holds information about 713 human GPCRs, 36 human G-proteins and 99 human effectors. The collection of information about the interactions between these molecules was done manually and the current version of Human-gpDB holds information for about 1663 connections between GPCRs and G-proteins and 1618 connections between G-proteins and effectors. Major advantages of Human-gpDB are the integration of several external data sources and the support of advanced visualization techniques. Human-gpDB is a simple, yet a powerful tool for researchers in the life sciences field as it integrates an up-to-date, carefully curated collection of human GPCRs, G-proteins, effectors and their interactions. The database may be a reference guide for medical and pharmaceutical research, especially in the areas of understanding human diseases and chemical and drug discovery. Database URLs: http://schneider.embl.de/human_gpdb; http://bioinformatics.biol.uoa.gr/human_gpdb/
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Visualization of omics data for systems biology.
Nat. Methods
PUBLISHED: 03-03-2010
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High-throughput studies of biological systems are rapidly accumulating a wealth of omics-scale data. Visualization is a key aspect of both the analysis and understanding of these data, and users now have many visualization methods and tools to choose from. The challenge is to create clear, meaningful and integrated visualizations that give biological insight, without being overwhelmed by the intrinsic complexity of the data. In this review, we discuss how visualization tools are being used to help interpret protein interaction, gene expression and metabolic profile data, and we highlight emerging new directions.
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A reference guide for tree analysis and visualization.
BioData Min
PUBLISHED: 02-22-2010
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The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are becoming vast. Sequencing technologies become cheaper and easier to use and, thus, large-scale evolutionary studies towards the origins of life for all species and their evolution becomes more and more challenging. Databases holding information about how data are related and how they are hierarchically organized expand rapidly. Clustering analysis is becoming more and more difficult to be applied on very large amounts of data since the results of these algorithms cannot be efficiently visualized. Most of the available visualization tools that are able to represent such hierarchies, project data in 2D and are lacking often the necessary user friendliness and interactivity. For example, the current phylogenetic tree visualization tools are not able to display easy to understand large scale trees with more than a few thousand nodes. In this study, we review tools that are currently available for the visualization of biological trees and analysis, mainly developed during the last decade. We describe the uniform and standard computer readable formats to represent tree hierarchies and we comment on the functionality and the limitations of these tools. We also discuss on how these tools can be developed further and should become integrated with various data sources. Here we focus on freely available software that offers to the users various tree-representation methodologies for biological data analysis.
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Defective lamin A-Rb signaling in Hutchinson-Gilford Progeria Syndrome and reversal by farnesyltransferase inhibition.
PLoS ONE
PUBLISHED: 02-12-2010
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Hutchinson-Gilford Progeria Syndrome (HGPS) is a rare premature aging disorder caused by a de novo heterozygous point mutation G608G (GGC>GGT) within exon 11 of LMNA gene encoding A-type nuclear lamins. This mutation elicits an internal deletion of 50 amino acids in the carboxyl-terminus of prelamin A. The truncated protein, progerin, retains a farnesylated cysteine at its carboxyl terminus, a modification involved in HGPS pathogenesis. Inhibition of protein farnesylation has been shown to improve abnormal nuclear morphology and phenotype in cellular and animal models of HGPS. We analyzed global gene expression changes in fibroblasts from human subjects with HGPS and found that a lamin A-Rb signaling network is a major defective regulatory axis. Treatment of fibroblasts with a protein farnesyltransferase inhibitor reversed the gene expression defects. Our study identifies Rb as a key factor in HGPS pathogenesis and suggests that its modulation could ameliorate premature aging and possibly complications of physiological aging.
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LAITOR--Literature Assistant for Identification of Terms co-Occurrences and Relationships.
BMC Bioinformatics
PUBLISHED: 02-01-2010
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Biological knowledge is represented in scientific literature that often describes the function of genes/proteins (bioentities) in terms of their interactions (biointeractions). Such bioentities are often related to biological concepts of interest that are specific of a determined research field. Therefore, the study of the current literature about a selected topic deposited in public databases, facilitates the generation of novel hypotheses associating a set of bioentities to a common context.
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Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.
Nature
PUBLISHED: 01-22-2010
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Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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EELS of niobium and stoichiometric niobium-oxide phases--Part I: plasmon and near-edges fine structure.
Microsc. Microanal.
PUBLISHED: 10-27-2009
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A comprehensive electron energy-loss spectroscopy study of niobium (Nb) and stable Nb-oxide phases (NbO, NbO2, Nb2O5) was carried out. In this work (Part I), the plasmons and energy-loss near-edge structures (ELNES) of all relevant Nb edges (Nb-N2,3, Nb-M4,5, Nb-M2,3, Nb-M1, and Nb-L2,3) up to energy losses of about 2600 eV and the O-K edge are analyzed with respect to achieving characteristic fingerprints of Nb in different formal oxidation states (0 for metallic Nb, +2 for NbO, +4 for NbO2, and +5 for Nb2O5). Chemical shifts of the Nb-N2,3, Nb-M4,5, Nb-M2,3, and Nb-L2,3 edges are extracted from the spectra that amount to about 4 eV as the oxidation state increases from 0 for Nb to +5 for Nb2O5. Four different microscopes, including a 200 keV ZEISS Libra with monochromator, were used. The corresponding wide range of experimental parameters with respect to the primary electron energy, convergence, and collection semi-angles as well as energy resolution allows an assessment of the influence of the experimental setup on the ELNES of the different edges. Finally, the intensity of the Nb-L2,3 white-line edges is correlated with niobium 4d-state occupancy in the different reference materials.
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EELS of niobium and stoichiometric niobium-oxide phases--Part II: quantification.
Microsc. Microanal.
PUBLISHED: 10-26-2009
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A comprehensive electron energy-loss spectroscopy (EELS) study of niobium (Nb) and stable Nb-oxide phases (NbO, NbO2, Nb2O5) was carried out. Part II of this work is devoted to quantitative EELS by means of experimental k-factors derived from the intensity ratio of the O-K edge and the Nb-M4,5 or Nb-M2,3 edges for all three stable Nb-oxides. The precision and accuracy of the quantification are investigated with respect to the influence of intensity-measurement energy windows, background subtraction, and sample thickness. Integration-window widths allowing optimum accuracy are determined. Owing to background-subtraction errors, the Nb-M4,5 edges rather than Nb-M2,3 are preferred for quantification. Different approaches are applied to improve the precision with regard to thickness-related errors. Thus, a precision up to +/-1.5% is achieved by averaging spectra from all three reference oxides to determine a k-factor using Nb-M4,5. Using the experimental k-factor, the determination of atomic concentration ratios CNb/CO in the range of 0.4 (Nb2O5) to 1 (NbO) was found to be possible with an accuracy of 0.6% (relative deviation between measured and nominal composition), whereas ratios of calculated partial ionization cross sections lead to less accurate results.
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Martini: using literature keywords to compare gene sets.
Nucleic Acids Res.
PUBLISHED: 10-25-2009
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Life scientists are often interested to compare two gene sets to gain insight into differences between two distinct, but related, phenotypes or conditions. Several tools have been developed for comparing gene sets, most of which find Gene Ontology (GO) terms that are significantly over-represented in one gene set. However, such tools often return GO terms that are too generic or too few to be informative. Here, we present Martini, an easy-to-use tool for comparing gene sets. Martini is based, not on GO, but on keywords extracted from Medline abstracts; Martini also supports a much wider range of species than comparable tools. To evaluate Martini we created a benchmark based on the human cell cycle, and we tested several comparable tools (CoPub, FatiGO, Marmite and ProfCom). Martini had the best benchmark performance, delivering a more detailed and accurate description of function. Martini also gave best or equal performance with three other datasets (related to Arabidopsis, melanoma and ovarian cancer), suggesting that Martini represents an advance in the automated comparison of gene sets. In agreement with previous studies, our results further suggest that literature-derived keywords are a richer source of gene-function information than GO annotations. Martini is freely available at http://martini.embl.de.
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Implementation of an in vitro model system for investigation of reperfusion damage after renal ischemia.
Cell. Physiol. Biochem.
PUBLISHED: 08-06-2009
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Ischemic acute kidney injury (iAKI) is a common event in organ transplantation and may occur during severe surgery. To gain mechanistic insights into ischemia-induced alterations at the level of proximal tubule cells we set up an in vitro model of ischemia and reperfusion using the rat proximal tubule cell line NRK-52E. In this particular model we simultaneously applied acidosis, hypoxia and aglycemia together for 2h, using low volume buffer systems and a hypoxia chamber. Thereafter reperfusion was mimicked by subsequently culturing the cells for up to 48h under standard conditions. In order to validate the system we investigated whether effects that take place in existing in vivo models of ischemia and reperfusion can be observed. Namely, induction of necrosis, apoptosis and of ischemia reperfusion induced protein (IRIP), dedifferentiation (alphaSMA), inflammation (MCP-1), inducible NO-synthase (iNOS), release of PGE(2) and basolateral uptake of organic anions. In fact, all parameters developed as described for the in vivo situation during reperfusion after ischemia. Taken altogether we have established an in vitro model of proximal tubule cell reperfusion damage after ischemia, showing typical changes described in vivo. Additionally, our model system is suitable for isolated application of the typical insults associated with ischemia (e.g. acidosis alone, hypoxia alone, aglycemia alone), in order to obtain more insight into the mechanistic events that lead to reperfusion damage in the kidney on the cellular level.
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Short-term prognosis of contemporary interventional therapy of ST-elevation myocardial infarction: does gender matter?
Clin Res Cardiol
PUBLISHED: 07-30-2009
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A higher mortality risk for women with acute ST-elevation myocardial infarction (STEMI) has been a common finding in the past, even after acute percutaneous coronary intervention (PCI). We set out to analyze whether there are gender differences in real-world contemporary treatment and outcomes of STEMI.
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Monomeric C-reactive protein decreases acetylated LDL uptake in human endothelial cells.
Clin. Chem.
PUBLISHED: 07-17-2009
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C-reactive protein (CRP) is a risk marker for cardiovascular disease and has been implicated in atherogenesis. In atherosclerotic plaques, it colocalizes with oxidized LDL (oxLDL) and promotes oxLDL uptake by macrophages, suggesting an important cross-talk between CRP and lipid processing. A growing body of evidence indicates the existence of distinct configurations of human CRP, native pentameric (nCRP) and structurally modified monomeric (mCRP), that elicit opposing bioactivities in vitro and in vivo. Here, we tested the impact of mCRP and nCRP on the uptake of acetylated LDL (acLDL), which is internalized by receptors similar to those of oxLDL in human endothelial cells.
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GIBA: a clustering tool for detecting protein complexes.
BMC Bioinformatics
PUBLISHED: 06-16-2009
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During the last years, high throughput experimental methods have been developed which generate large datasets of protein - protein interactions (PPIs). However, due to the experimental methodologies these datasets contain errors mainly in terms of false positive data sets and reducing therefore the quality of any derived information. Typically these datasets can be modeled as graphs, where vertices represent proteins and edges the pairwise PPIs, making it easy to apply automated clustering methods to detect protein complexes or other biological significant functional groupings.
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jClust: a clustering and visualization toolbox.
Bioinformatics
PUBLISHED: 05-19-2009
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jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are k-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input file format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction.
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New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the Deep Web.
Curr Opin Drug Discov Devel
PUBLISHED: 04-28-2009
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The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the Deep Web (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.
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Cellular uptake of platinum nanoparticles in human colon carcinoma cells and their impact on cellular redox systems and DNA integrity.
Chem. Res. Toxicol.
PUBLISHED: 03-18-2009
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Supercritical fluid reactive deposition was used for the deposition of highly dispersed platinum nanoparticles with controllable metal content and particle size distribution on beta-cyclodextrin. The average particle size and size distribution were steered by the precursor reduction conditions, resulting in particle preparations <20, <100, and >100 nm as characterized by transmission electron microscopy and scanning electron microscopy (SEM). These particle preparations of different size distributions were used to address the question as to whether metallic platinum particles are able to invade cells of the gastrointestinal tract as exemplified for the human colon carcinoma cell line HT29 and thus affect the cellular redox status and DNA integrity. Combined focused ion beam and SEM demonstrated that platinum nanoparticles were taken up into HT29 cells in their particulate form. The chemical composition of the particles within the cells was confirmed by energy-dispersive X-ray spectroscopy. The potential influence of platinum nanoparticles on cellular redoxsystems was determined in the DCF assay, on the translocation of Nrf-2 and by monitoring the intracellular glutathione (GSH) levels. The impact on DNA integrity was investigated by single cell gel electrophoresis (comet assay) including the formation of sites sensitive to formamidopyrimidine-DNA-glycosylase. Platinum nanoparticles were found to decrease the cellular GSH level and to impair DNA integrity with a maximal effect at 1 ng/cm(2). These effects were correlated with the particle size in an inverse manner and were enhanced with increasing incubation time but appeared not to be based on the formation of reactive oxygen species.
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OnTheFly: a tool for automated document-based text annotation, data linking and network generation.
Bioinformatics
PUBLISHED: 02-17-2009
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OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database.
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Naïve adult stem cells from patients with Hutchinson-Gilford progeria syndrome express low levels of progerin in vivo.
Biol Open
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Hutchinson-Gilford progeria syndrome (HGPS, OMIM 176670) is a rare disorder characterized by segmental accelerated aging and early death from coronary artery disease or stroke. Nearly 90% of HGPS sufferers carry a G608G mutation within exon 11 of LMNA, producing a truncated form of prelamin A, referred to as "progerin". Here, we report the isolation of naïve multipotent skin-derived precursor (SKP) cells from dermal fibroblast cultures from HGPS donors. These cells form spheres and express the neural crest marker, nestin, in addition to the multipotent markers, OCT4, Sox2, Nanog and TG30; these cells can self-renew and differentiate into smooth muscle cells (SMCs) and fibroblasts. The SMCs derived from the HGPS-SKPs accumulate nuclear progerin with increasing passages. A subset of the HGPS-naïve SKPs express progerin in vitro and in situ in HGPS skin sections. This is the first in vivo evidence that progerin is produced in adult stem cells, and implies that this protein could induce stem cells exhaustion as a mechanism contributing to aging. Our study provides a basis on which to explore therapeutic applications for HGPS stem cells and opens avenues for investigating the pathogenesis of other genetic diseases.
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ReLiance: a machine learning and literature-based prioritization of receptor--ligand pairings.
Bioinformatics
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The prediction of receptor-ligand pairings is an important area of research as intercellular communications are mediated by the successful interaction of these key proteins. As the exhaustive assaying of receptor-ligand pairs is impractical, a computational approach to predict pairings is necessary. We propose a workflow to carry out this interaction prediction task, using a text mining approach in conjunction with a state of the art prediction method, as well as a widely accessible and comprehensive dataset. Among several modern classifiers, random forests have been found to be the best at this prediction task. The training of this classifier was carried out using an experimentally validated dataset of Database of Ligand-Receptor Partners (DLRP) receptor-ligand pairs. New examples, co-cited with the training receptors and ligands, are then classified using the trained classifier. After applying our method, we find that we are able to successfully predict receptor-ligand pairs within the GPCR family with a balanced accuracy of 0.96. Upon further inspection, we find several supported interactions that were not present in the Database of Interacting Proteins (DIPdatabase). We have measured the balanced accuracy of our method resulting in high quality predictions stored in the available database ReLiance.
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EnrichNet: network-based gene set enrichment analysis.
Bioinformatics
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Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets; (ii) it disregards genes with missing annotations; (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized.
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Paving the future: finding suitable ISMB venues.
Bioinformatics
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The International Society for Computational Biology, ISCB, organizes the largest event in the field of computational biology and bioinformatics, namely the annual international conference on Intelligent Systems for Molecular Biology, the ISMB. This year at ISMB 2012 in Long Beach, ISCB celebrated the 20th anniversary of its flagship meeting. ISCB is a young, lean and efficient society that aspires to make a significant impact with only limited resources. Many constraints make the choice of venues for ISMB a tough challenge. Here, we describe those challenges and invite the contribution of ideas for solutions.
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Human gene correlation analysis (HGCA): a tool for the identification of transcriptionally co-expressed genes.
BMC Res Notes
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Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell.
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How not to be a bioinformatician.
Source Code Biol Med
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Although published material exists about the skills required for a successful bioinformatics career, strangely enough no work to date has addressed the matter of how to excel at not being a bioinformatician. A set of basic guidelines and a code of conduct is hereby presented to re-address that imbalance for fellow-practitioners whose aim is to not to succeed in their chosen bioinformatics field. By scrupulously following these guidelines one can be sure to regress at a highly satisfactory rate.
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Rosiglitazone affects nitric oxide synthases and improves renal outcome in a rat model of severe ischemia/reperfusion injury.
PPAR Res
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Background. Nitric oxide (NO)-signal transduction plays an important role in renal ischemia/reperfusion (I/R) injury. NO produced by endothelial NO-synthase (eNOS) has protective functions whereas NO from inducible NO-synthase (iNOS) induces impairment. Rosiglitazone (RGZ), a peroxisome proliferator-activated receptor (PPAR)-? agonist exerted beneficial effects after renal I/R injury, so we investigated whether this might be causally linked with NOS imbalance. Methods. RGZ (5?mg/kg) was administered i.p. to SD-rats (f) subjected to bilateral renal ischemia (60?min). Following 24?h of reperfusion, inulin- and PAH-clearance as well as PAH-net secretion were determined. Morphological alterations were graded by histopathological scoring. Plasma NO(x)-production was measured. eNOS and iNOS expression was analyzed by qPCR. Cleaved caspase 3 (CC3) was determined as an apoptosis indicator and ED1 as a marker of macrophage infiltration in renal tissue. Results. RGZ improves renal function after renal I/R injury (PAH-/inulin-clearance, PAH-net secretion) and reduces histomorphological injury. Additionally, RGZ reduces NO(x) plasma levels, ED-1 positive cell infiltration and CC3 expression. iNOS-mRNA is reduced whereas eNOS-mRNA is increased by RGZ. Conclusion. RGZ has protective properties after severe renal I/R injury. Alterations of the NO pathway regarding eNOS and iNOS could be an explanation of the underlying mechanism of RGZ protection in renal I/R injury.
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Arena3D: visualizing time-driven phenotypic differences in biological systems.
BMC Bioinformatics
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Elucidating the genotype-phenotype connection is one of the big challenges of modern molecular biology. To fully understand this connection, it is necessary to consider the underlying networks and the time factor. In this context of data deluge and heterogeneous information, visualization plays an essential role in interpreting complex and dynamic topologies. Thus, software that is able to bring the network, phenotypic and temporal information together is needed. Arena3D has been previously introduced as a tool that facilitates link discovery between processes. It uses a layered display to separate different levels of information while emphasizing the connections between them. We present novel developments of the tool for the visualization and analysis of dynamic genotype-phenotype landscapes.
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Bioinformatics as a driver, not a passenger, of translational biomedical research: Perspectives from the 6th Benelux bioinformatics conference.
J Clin Bioinforma
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The 6th Benelux Bioinformatics Conference (BBC11) held in Luxembourg on 12 and 13 December 2011 attracted around 200 participants, including internationally-renowned guest speakers and more than 100 peer-reviewed submissions from 3 continents. Researchers from the public and private sectors convened at BBC11 to discuss advances and challenges in a wide spectrum of application areas. A key theme of the conference was the contribution of bioinformatics to enable and accelerate translational and clinical research. The BBC11 stressed the need for stronger collaborating efforts across disciplines and institutions. The demonstration of the clinical relevance of systems approaches and of next-generation sequencing-based measurement technologies are among the existing opportunities for increasing impact in translational research. Translational bioinformatics will benefit from research models that strike a balance between the importance of protecting intellectual property and the need to openly access scientific and technological advances. The full conference proceedings are freely available at http://www.bbc11.lu.
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Caipirini: using gene sets to rank literature.
BioData Min
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Keeping up-to-date with bioscience literature is becoming increasingly challenging. Several recent methods help meet this challenge by allowing literature search to be launched based on lists of abstracts that the user judges to be interesting. Some methods go further by allowing the user to provide a second input set of uninteresting abstracts; these two input sets are then used to search and rank literature by relevance. In this work we present the service Caipirini (http://caipirini.org) that also allows two input sets, but takes the novel approach of allowing ranking of literature based on one or more sets of genes.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.