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        <title>BioMed Central - Most accessed articles</title>
        <link>http://www.biomedcentral.com/</link>
        <description>The most accessed research articles published by BioMed Central</description>
        <dc:date>2009-06-22T00:00:00Z</dc:date>
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                                <rdf:li rdf:resource="http://www.biomedcentral.com/1471-2296/10/43" />
                                <rdf:li rdf:resource="http://www.cardiab.com/content/4/1/4" />
                                <rdf:li rdf:resource="http://arthritis-research.com/content/11/3/R91" />
                                <rdf:li rdf:resource="http://www.nonlinearbiomedphys.com/content/1/1/4" />
                                <rdf:li rdf:resource="http://genomebiology.com/2009/10/6/R64" />
                                <rdf:li rdf:resource="http://jbiol.com/content/8/5/45" />
                                <rdf:li rdf:resource="http://www.biomedcentral.com/1741-7015/7/30" />
                                <rdf:li rdf:resource="http://www.jnanobiotechnology.com/content/4/1/10" />
                                <rdf:li rdf:resource="http://genomebiology.com/2009/10/3/R32" />
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        <item rdf:about="http://www.biomedcentral.com/1471-2296/10/43">
        <title>How accurate is patients&apos; anatomical knowledge : a cross-sectional, questionnaire study of six patient groups and a general public sample.</title>
        <description>Background:
Older studies have shown that patients often do not understand the terms used by doctors and many do not even have a rudimentary understanding of anatomy. The present study was designed to investigate the levels of anatomical knowledge of different patient groups and the general public in order to see whether this has improved over time and whether patients with a specific organ pathology (e.g. liver disease) have a relatively better understanding of the location of that organ.
Methods:
Level of anatomical knowledge was assessed on a multiple-choice questionnaire, in a sample of 722 participants, comprising approximately 100 patients in each of 6 different diagnostic groups and 133 in the general population, using a between-groups, cross-sectional design. Comparisons of relative accuracy of anatomical knowledge between the present and earlier results, and across the clinical and general public groups were evaluated using Chi square tests. Associations with age and education were assessed with the Pearson correlation test and one-way analysis of variance, respectively.
Results:
Across groups knowledge of the location of body organs was poor and has not significantly improved since an earlier equivalent study over 30 years ago (&#967;2 = 0.04, df = 1, ns). Diagnostic groups did not differ in their overall scores but those with liver disease and diabetes were more accurate regarding the location of their respective affected organs (&#967;2 = 18.10, p &lt; 0.001, df = 1; &#967;2 = 10.75, p &lt; 0.01, df = 1). Age was significantly negatively correlated (r = -0.084, p = 0.025) and education was positively correlated with anatomical knowledge (F = 12.94, p = 0.000). Although there was no overall gender difference, women were significantly better at identifying organs on female body outlines.
Conclusion:
Many patients and general public do not know the location of key body organs, even those in which their medical problem is located, which could have important consequences for doctor-patient communication. These results indicate that healthcare professionals still need to take care in providing organ specific information to patients and should not assume that patients have this information, even for those organs in which their medical problem is located.</description>
        <link>http://www.biomedcentral.com/1471-2296/10/43</link>
                <dc:creator>John Weinman</dc:creator>
                <dc:creator>Gibran Yusuf</dc:creator>
                <dc:creator>Robert Berks</dc:creator>
                <dc:creator>Sam Rayner</dc:creator>
                <dc:creator>Keith Petrie</dc:creator>
                <dc:source>BMC Family Practice 2009, 10:43</dc:source>
        <dc:date>2009-06-12T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1471-2296-10-43</dc:identifier>
        <prism:publicationName>BMC Family Practice</prism:publicationName>
        <prism:issn>1471-2296</prism:issn>
        <prism:volume>10</prism:volume>
        <prism:startingPage>43</prism:startingPage>
        <prism:publicationDate>2009-06-12T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
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        <item rdf:about="http://www.cardiab.com/content/4/1/4">
        <title>Vascular ossification - calcification in metabolic syndrome, type 2 diabetes mellitus, chronic kidney disease, and calciphylaxis - calcific uremic arteriolopathy: the emerging role of sodium thiosulfate</title>
        <description>Background:
Vascular calcification is associated with metabolic syndrome, diabetes, hypertension, atherosclerosis, chronic kidney disease, and end stage renal disease. Each of the above contributes to an accelerated and premature demise primarily due to cardiovascular disease. The above conditions are associated with multiple metabolic toxicities resulting in an increase in reactive oxygen species to the arterial vessel wall, which results in a response to injury wound healing (remodeling). The endothelium seems to be at the very center of these disease processes, acting as the first line of defense against these multiple metabolic toxicities and the first to encounter their damaging effects to the arterial vessel wall.
Results:
The pathobiomolecular mechanisms of vascular calcification are presented in order to provide the clinician &#8211; researcher a database of knowledge to assist in the clinical management of these high-risk patients and examine newer therapies. Calciphylaxis is associated with medial arteriolar vascular calcification and results in ischemic subcutaneous necrosis with vulnerable skin ulcerations and high mortality. Recently, this clinical syndrome (once thought to be rare) is presenting with increasing frequency. Consequently, newer therapeutic modalities need to be explored. Intravenous sodium thiosulfate is currently used as an antidote for the treatment of cyanide poisioning and prevention of toxicities of cisplatin cancer therapies. It is used as a food and medicinal preservative and topically used as an antifungal medication.
Conclusion:
A discussion of sodium thiosulfate&apos;s dual role as a potent antioxidant and chelator of calcium is presented in order to better understand its role as an emerging novel therapy for the clinical syndrome of calciphylaxis and its complications.</description>
        <link>http://www.cardiab.com/content/4/1/4</link>
                <dc:creator>Melvin Hayden</dc:creator>
                <dc:creator>Suresh Tyagi</dc:creator>
                <dc:creator>Lisa Kolb</dc:creator>
                <dc:creator>James Sowers</dc:creator>
                <dc:creator>Ramesh Khanna</dc:creator>
                <dc:source>Cardiovascular Diabetology 2005, 4:4</dc:source>
        <dc:date>2005-03-18T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1475-2840-4-4</dc:identifier>
        <prism:publicationName>Cardiovascular Diabetology</prism:publicationName>
        <prism:issn>1475-2840</prism:issn>
        <prism:volume>4</prism:volume>
        <prism:startingPage>4</prism:startingPage>
        <prism:publicationDate>2005-03-18T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
    </item>
        <item rdf:about="http://arthritis-research.com/content/11/3/R91">
        <title>Negative association of the chemokine receptor CCR5 d32 polymorphism with systemic inflammatory response, extra-articular symptoms and joint erosion in rheumatoid arthritis</title>
        <description>IntroductionChemokines and their receptors control immune cell migration during infections as well as in autoimmune responses. A 32 bp deletion in the gene of the chemokine receptor CCR5 confers protection against HIV infection, but has also been reported to decrease susceptibility to rheumatoid arthritis (RA). The influence of this deletion variant on the clinical course of this autoimmune disease was investigated.
Methods:
Genotyping for CCR5d32 was performed by PCR and subsequent electrophoretic fragment length determination. For the clinical analysis, the following extra-articular manifestations of RA were documented by the rheumatologist following the patient: presence of rheumatoid nodules, major organ vasculitis, pulmonary fibrosis, serositis or a Raynaud&apos;s syndrome. All documented CRP levels were analyzed retrospectively, and the last available hand and feet radiographs were analyzed with regards to the presence or absence of erosive disease.
Results:
Analysis of the CCR5 polymorphism in 503 RA patients and in 459 age-matched healthy controls revealed a significantly decreased disease susceptibility for carriers of the CCR5d32 deletion (Odds ratio 0.67, P = 0.0437). Within the RA patient cohort, CCR5d32 was significantly less frequent in patients with extra-articular manifestations compared with those with limited, articular disease (13.2% versus 22.8%, P = 0.0374). In addition, the deletion was associated with significantly lower average CRP levels over time (median 8.85 vs. median 14.1, P = 0.0041) and had a protective effect against the development of erosive disease (OR = 0.40, P = 0.0047). Intriguingly, homozygosity for the RA associated DNASE2 -1066 G allele had an additive effect on the disease susceptibility conferred by the wt allele of CCR5 (OR = 2.24, P = 0.0051 for carrier of both RA associated alleles)
Conclusions:
The presence of CCR5d32 significantly influenced disease susceptibility to and clinical course of RA in a German study population. The protective effect of this deletion, which has been described to lead to a decreased receptor expression in heterozygous patients, underlines the importance of chemokines in the pathogenesis of RA.</description>
        <link>http://arthritis-research.com/content/11/3/R91</link>
                <dc:creator>Manuela Rossol</dc:creator>
                <dc:creator>Matthias Pierer</dc:creator>
                <dc:creator>Sybille Arnold</dc:creator>
                <dc:creator>Gernot KeySZer</dc:creator>
                <dc:creator>Harald Burkhardt</dc:creator>
                <dc:creator>Christoph Baerwald</dc:creator>
                <dc:creator>Ulf Wagner</dc:creator>
                <dc:source>Arthritis Research &amp; Therapy 2009, 11:R91</dc:source>
        <dc:date>2009-06-18T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/ar2733</dc:identifier>
        <prism:publicationName>Arthritis Research &amp; Therapy</prism:publicationName>
        <prism:issn>1478-6354</prism:issn>
        <prism:volume>11</prism:volume>
        <prism:startingPage>R91</prism:startingPage>
        <prism:publicationDate>2009-06-18T00:00:00Z</prism:publicationDate>
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                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
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        <item rdf:about="http://www.nonlinearbiomedphys.com/content/1/1/4">
        <title>Stochastic nonlinear dynamics pattern formation and growth models</title>
        <description>Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature.</description>
        <link>http://www.nonlinearbiomedphys.com/content/1/1/4</link>
                <dc:creator>Leonid Yaroslavsky</dc:creator>
                <dc:source>Nonlinear Biomedical Physics 2007, 1:4</dc:source>
        <dc:date>2007-07-05T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1753-4631-1-4</dc:identifier>
        <prism:publicationName>Nonlinear Biomedical Physics</prism:publicationName>
        <prism:issn>1753-4631</prism:issn>
        <prism:volume>1</prism:volume>
        <prism:startingPage>4</prism:startingPage>
        <prism:publicationDate>2007-07-05T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
    </item>
        <item rdf:about="http://genomebiology.com/2009/10/6/R64">
        <title>A novel and universal method for microRNA RT-qPCR data normalization</title>
        <description>Gene expression analysis of microRNA molecules is becoming increasingly important. In this study we assess the use of the mean expression value of all expressed microRNAs in a given sample as a normalization factor for microRNA real-time quantitative PCR data and compare its performance to the currently adopted approach. We demonstrate that the mean expression value outperforms the current normalization strategy in terms of better reduction of technical variation and more accurate appreciation of biological changes.</description>
        <link>http://genomebiology.com/2009/10/6/R64</link>
                <dc:creator>Pieter Mestdagh</dc:creator>
                <dc:creator>Pieter Van Vlierberghe</dc:creator>
                <dc:creator>An De Weer</dc:creator>
                <dc:creator>Daniel Muth</dc:creator>
                <dc:creator>Frank Westermann</dc:creator>
                <dc:creator>Frank Speleman</dc:creator>
                <dc:creator>Jo Vandesompele</dc:creator>
                <dc:source>Genome Biology 2009, 10:R64</dc:source>
        <dc:date>2009-06-16T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/gb-2009-10-6-r64</dc:identifier>
        <prism:publicationName>Genome Biology</prism:publicationName>
        <prism:issn>1465-6906</prism:issn>
        <prism:volume>10</prism:volume>
        <prism:startingPage>R64</prism:startingPage>
        <prism:publicationDate>2009-06-16T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
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        <item rdf:about="http://jbiol.com/content/8/5/45">
        <title>Influenza: one or two more questions</title>
        <description>No description available</description>
        <link>http://jbiol.com/content/8/5/45</link>
                <dc:source>Journal of Biology 2009, 8:45</dc:source>
        <dc:date>2009-06-12T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/jbiol158</dc:identifier>
        <prism:publicationName>Journal of Biology</prism:publicationName>
        <prism:issn>1475-4924</prism:issn>
        <prism:volume>8</prism:volume>
        <prism:startingPage>45</prism:startingPage>
        <prism:publicationDate>2009-06-12T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
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        <item rdf:about="http://www.biomedcentral.com/1741-7015/7/30">
        <title>Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)</title>
        <description>Here we present a review of the literature of influenza modeling studies, and discuss how these models can provide insights into the future of the currently circulating novel strain of influenza A (H1N1), formerly known as swine flu. We discuss how the feasibility of controlling an epidemic critically depends on the value of the Basic Reproduction Number (R0). The R0 for novel influenza A (H1N1) has recently been estimated to be between 1.4 and 1.6. This value is below values of R0 estimated for the 1918-1919 pandemic strain (mean R0 ~ 2:  range 1.4 to 2.8) and is comparable to R0 values estimated for seasonal strains of influenza (mean R0 1.3: range 0.9 to 2.1). By reviewing results from previous modeling studies we conclude it is likely that a pandemic of H1N1 could be contained, but a cooperative global control strategy will be imperative. If this does not occur, resource-constrained and resource-poor countries will suffer from a significantly disproportionate burden of disease. We discuss the necessity for formulating new mathematical models that simultaneously track the transmission dynamics of multiple strains of influenza in bird, pig, and human populations. We show, by modeling cross-species transmission, how it may be possible to predict the emergence of pandemic strains of influenza. The biologically complex models that we are recommending be developed could be critical for identifying effective new interventions, and informing pandemic preparedness planning.</description>
        <link>http://www.biomedcentral.com/1741-7015/7/30</link>
                <dc:creator>Brian Coburn</dc:creator>
                <dc:creator>Bradley Wagner</dc:creator>
                <dc:creator>Sally Blower</dc:creator>
                <dc:source>BMC Medicine 2009, 7:30</dc:source>
        <dc:date>2009-06-22T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1741-7015-7-30</dc:identifier>
        <prism:publicationName>BMC Medicine</prism:publicationName>
        <prism:issn>1741-7015</prism:issn>
        <prism:volume>7</prism:volume>
        <prism:startingPage>30</prism:startingPage>
        <prism:publicationDate>2009-06-22T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>PDF</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
    </item>
        <item rdf:about="http://www.jnanobiotechnology.com/content/4/1/10">
        <title>Three-dimensional reconstruction of cell nuclei, internalized quantum dots and sites of lipid peroxidation</title>
        <description>Background:
The purpose of the study was to develop and illustrate three-dimensional (3-D) reconstruction of nuclei and intracellular lipid peroxidation in cells exposed to oxidative stress induced by quantum dots. Programmed cell death is characterized by multiple biochemical and morphological changes in different organelles, including nuclei, mitochondria and lysosomes. It is the dynamics of the spatio-temporal changes in the signalling and morphological adaptations which will ultimately determine the &apos;shape&apos; and fate of the cell.
Results:
We present new approaches to the 3-D reconstruction of organelle morphology and biochemical changes in confocal live-cell images. We demonstrate the 3-D shapes of nuclei, the 3-D intracellular distributions of QDs and the accompanying lipid-membrane peroxidation, and provide methods for quantification.
Conclusion:
This study provides an approach to 3-D organelle and nanoparticle visualization in the context of cell death; however, this approach is also applicable more generally to investigating changes in organelle morphology in response to therapeutic interventions, stressful stimuli and internalized nanoparticles. Moreover, the approach provides quantitative data for such changes, which will help us to better integrate compartmentalization of subcellular events and to link morphological and biochemical changes with physiological outcomes.</description>
        <link>http://www.jnanobiotechnology.com/content/4/1/10</link>
                <dc:creator>W. Robert J. Funnell</dc:creator>
                <dc:creator>Dusica Maysinger</dc:creator>
                <dc:source>Journal of Nanobiotechnology 2006, 4:10</dc:source>
        <dc:date>2006-10-20T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/1477-3155-4-10</dc:identifier>
        <prism:publicationName>Journal of Nanobiotechnology</prism:publicationName>
        <prism:issn>1477-3155</prism:issn>
        <prism:volume>4</prism:volume>
        <prism:startingPage>10</prism:startingPage>
        <prism:publicationDate>2006-10-20T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
    </item>
        <item rdf:about="http://genomebiology.com/2009/10/3/R32">
        <title>Evaluation of next generation sequencing platforms for population targeted sequencing studies</title>
        <description>Background:
Next generation sequencing (NGS) platforms are currently being utilized for targeted sequencing of candidate genes or genomic intervals to perform sequence-based association studies. To evaluate these platforms for this application, we analyzed human sequence generated by the Roche 454, Illumina GA, and the ABI SOLiD technologies for the same 260 kb in four individuals.
Results:
Local sequence characteristics contribute to systematic variability in sequence coverage (&gt;100-fold difference in per-base coverage), resulting in patterns for each NGS technology that are highly correlated between samples. A comparison of the base calls to 88 kb of overlapping ABI 3730xL Sanger sequence generated for the same samples showed that the NGS platforms all have high sensitivity, identifying &gt;95% of variant sites. At high coverage, depth base calling errors are systematic, resulting from local sequence contexts; as the coverage is lowered additional &apos;random sampling&apos; errors in base calling occur.
Conclusions:
Our study provides important insights into systematic biases and data variability that need to be considered when utilizing NGS platforms for population targeted sequencing studies.</description>
        <link>http://genomebiology.com/2009/10/3/R32</link>
                <dc:creator>Olivier Harismendy</dc:creator>
                <dc:creator>Pauline Ng</dc:creator>
                <dc:creator>Robert Strausberg</dc:creator>
                <dc:creator>Xiaoyun Wang</dc:creator>
                <dc:creator>Timothy Stockwell</dc:creator>
                <dc:creator>Karen Beeson</dc:creator>
                <dc:creator>Nicholas Schork</dc:creator>
                <dc:creator>Sarah Murray</dc:creator>
                <dc:creator>Eric Topol</dc:creator>
                <dc:creator>Samuel Levy</dc:creator>
                <dc:creator>Kelly Frazer</dc:creator>
                <dc:source>Genome Biology 2009, 10:R32</dc:source>
        <dc:date>2009-03-27T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/gb-2009-10-3-r32</dc:identifier>
        <prism:publicationName>Genome Biology</prism:publicationName>
        <prism:issn>1465-6906</prism:issn>
        <prism:volume>10</prism:volume>
        <prism:startingPage>R32</prism:startingPage>
        <prism:publicationDate>2009-03-27T00:00:00Z</prism:publicationDate>
                <prism:versionidentifier>XML</prism:versionidentifier>
                <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
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        <item rdf:about="http://genomebiology.com/2009/10/6/R60">
        <title>Closing gaps in the human genome using sequencing by synthesis</title>
        <description>The most recent release of the finished human genome contains 260 euchromatic gaps (excluding chromosome Y). Recent work has helped explain a large number of these unresolved regions as &apos;structural&apos; in nature. Another class of gaps is likely to be refractory to clone-based approaches, and cannot be approached in ways previously described. We present an approach for closing these gaps using 454 sequencing. As a proof of principle, we closed all three remaining non-structural gaps in chromosome 15.</description>
        <link>http://genomebiology.com/2009/10/6/R60</link>
                <dc:creator>Manuel Garber</dc:creator>
                <dc:creator>Michael Zody</dc:creator>
                <dc:creator>Harindra Arachchi</dc:creator>
                <dc:creator>Aaron Berlin</dc:creator>
                <dc:creator>Sante Gnerre</dc:creator>
                <dc:creator>Lisa Green</dc:creator>
                <dc:creator>Niall Lennon</dc:creator>
                <dc:creator>Chad Nusbaum</dc:creator>
                <dc:source>Genome Biology 2009, 10:R60</dc:source>
        <dc:date>2009-06-02T00:00:00Z</dc:date>
        <dc:identifier>doi:10.1186/gb-2009-10-6-r60</dc:identifier>
        <prism:publicationName>Genome Biology</prism:publicationName>
        <prism:issn>1465-6906</prism:issn>
        <prism:volume>10</prism:volume>
        <prism:startingPage>R60</prism:startingPage>
        <prism:publicationDate>2009-06-02T00:00:00Z</prism:publicationDate>
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