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  • 2016  (18)
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  • 2016  (18)
  • 1
    Language: English
    In: Virus Research, 15 June 2016, Vol.218, pp.1-1
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.virusres.2016.05.020 Byline: Lars Kaderali Author Affiliation: Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
    Keywords: Biology
    ISSN: 0168-1702
    E-ISSN: 1872-7492
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  • 2
    In: PLoS ONE, 2016, Vol.11(5)
    Description: This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious bias in predictive modeling. Since standard data mining methods often produce poor performance measures, we argue for development of specialized techniques of data-preprocessing and classification. In this paper, we propose a new method to simultaneously classify large datasets and reduce the effects of missing values. It is based on a multilevel framework of the cost-sensitive SVM and the expected maximization imputation method for missing values, which relies on iterated regression analyses. We compare classification results of multilevel SVM-based algorithms on public benchmark datasets with imbalanced classes and missing values as well as real data in health applications, and show that our multilevel SVM-based method produces fast, and more accurate and robust classification results.
    Keywords: Research Article ; Biology And Life Sciences ; Computer And Information Sciences ; Biology And Life Sciences ; Computer And Information Sciences ; Physical Sciences ; Research And Analysis Methods ; Social Sciences ; Computer And Information Sciences ; Research And Analysis Methods ; Physical Sciences ; Physical Sciences ; Research And Analysis Methods ; Biology And Life Sciences ; Computer And Information Sciences ; Physical Sciences
    E-ISSN: 1932-6203
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  • 3
    In: PLoS ONE, 2016, Vol.11(12)
    Description: The development of high-throughput sequencing technologies have allowed the possibility to investigate and characterise the entire microbiome of individuals, providing better insight to the complex interaction between different microorganisms. This will help to understand how the microbiome influence the susceptibility of secondary agents and development of disease. We have applied viral metagenomics to investigate the virome of lymph nodes from Swedish pigs suffering from the multifactorial disease postweaning multisystemic wasting syndrome (PMWS) as well as from healthy pigs. The aim is to increase knowledge of potential viruses, apart from porcine circovirus type 2 (PCV2), involved in PMWS development as well as to increase knowledge on the virome of healthy individuals. In healthy individuals, a diverse viral flora was seen with several different viruses present simultaneously. The majority of the identified viruses were small linear and circular DNA viruses, such as different circoviruses, anelloviruses and bocaviruses. In the pigs suffering from PMWS, PCV2 sequences were, as expected, detected to a high extent but other viruses were also identified in the background of PCV2. Apart from DNA viruses also RNA viruses were identified, among them were a porcine pestivirus showing high similarity to a recently (in 2015) discovered atypical porcine pestivirus in the US. Majority of the viruses identified in the background of PCV2 in PMWS pigs could also be identified in the healthy pigs. PCV2 sequences were also identified in the healthy pigs but to a much lower extent than in PMWS affected pigs. Although the method used here is not quantitative the very clear difference in amount of PCV2 sequences in PMWS affected pigs and healthy pigs most likely reflect the very strong replication of PCV2 known to be a hallmark of PMWS. Taken together, these findings illustrate that pigs appear to have a considerable viral flora consisting to a large extent of small single-stranded and circular DNA viruses. Future research on these types of viruses will help to better understand the role that these ubiquitous viruses may have on health and disease of pigs. We also demonstrate for the first time, in Europe, the presence of a novel porcine pestivirus.
    Keywords: Research Article ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Research And Analysis Methods ; Research And Analysis Methods ; Biology And Life Sciences ; Research And Analysis Methods
    E-ISSN: 1932-6203
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  • 4
    In: PLoS ONE, 2016, Vol.11(4)
    Description: A key feature of precision medicine is that it takes individual variability at the genetic or molecular level into account in determining the best treatment for patients diagnosed with diseases detected by recently developed novel biotechnologies. The enrichment design is an efficient design that enrolls only the patients testing positive for specific molecular targets and randomly assigns them for the targeted treatment or the concurrent control. However there is no diagnostic device with perfect accuracy and precision for detecting molecular targets. In particular, the positive predictive value (PPV) can be quite low for rare diseases with low prevalence. Under the enrichment design, some patients testing positive for specific molecular targets may not have the molecular targets. The efficacy of the targeted therapy may be underestimated in the patients that actually do have the molecular targets. To address the loss of efficiency due to misclassification error, we apply the discrete mixture modeling for time-to-event data proposed by Eng and Hanlon [ 8 ] to develop an inferential procedure, based on the Cox proportional hazard model, for treatment effects of the targeted treatment effect for the true-positive patients with the molecular targets. Our proposed procedure incorporates both inaccuracy of diagnostic devices and uncertainty of estimated accuracy measures. We employed the expectation-maximization algorithm in conjunction with the bootstrap technique for estimation of the hazard ratio and its estimated variance. We report the results of simulation studies which empirically investigated the performance of the proposed method. Our proposed method is illustrated by a numerical example.
    Keywords: Research Article ; Research And Analysis Methods ; Physical Sciences ; Medicine And Health Sciences ; Physical Sciences ; Research And Analysis Methods ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Research And Analysis Methods ; Physical Sciences
    E-ISSN: 1932-6203
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  • 5
    In: PLoS ONE, 2016, Vol.11(5)
    Description: Objective The purpose of our study was to determine the association of type 1 diabetes mellitus (T1DM) and the risk of herpes zoster (HZ). Methods In this cohort study, we selected 4736 patients with T1DM registered in the Catastrophic Illness Patient Database who received insulin therapy before 2003 and 18944 participants without DM who were selected by frequency matched based on sex and age. Cox proportional hazard regression analysis was used to measure the hazard ratios (HRs) of HZ in the T1DM group compared with that in the non-T1DM group. Results Cox proportional hazard regression analysis showed that the adjusted HR of HZ was 2.38 times higher for patients in the T1DM group (95% CI = 1.77–3.19) than for those in the non-T1DM group. According to diabetes severity, mild and serious T1DM patients were associated with a higher risk of HZ (adjusted HR = 2.26, 95% CI = 1.67–3.05; and adjusted HR = 5.08, 95% CI = 2.66–9.71, respectively) than subjects without T1DM. Conclusion Patients with T1DM are at a higher risk of HZ than those without T1DM.
    Keywords: Research Article ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; People And Places
    E-ISSN: 1932-6203
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  • 6
    In: PLoS ONE, 2016, Vol.11(3)
    Description: Background Here, we aimed to gain a comprehensive picture of the HIV-1 diversity in the northeast and southeast part of Brazil. To this end, a high-throughput sequencing-by-synthesis protocol and instrument were used to characterize the near full length (NFLG) and partial HIV-1 proviral genome in 259 HIV-1 infected blood donors at four major blood centers in Brazil: Pro-Sangue foundation (São Paulo state (SP), n 51), Hemominas foundation (Minas Gerais state (MG), n 41), Hemope foundation (Recife state (PE), n 96) and Hemorio blood bank (Rio de Janeiro (RJ), n 70). Materials and Methods A total of 259 blood samples were obtained from 195 donors with long-standing infections and 64 donors with a lack of stage information. DNA was extracted from the peripheral blood mononuclear cells (PBMCs) to amplify the HIV-1 NFLGs from five overlapping fragments. The amplicons were molecularly bar-coded, pooled, and sequenced by Illumina paired-end protocol. Results Of the 259 samples studied, 208 (80%) NFLGs and 49 (18.8%) partial fragments were de novo assembled into contiguous sequences and successfully subtyped. Of these 257 samples, 183 (71.2%) were pure subtypes consisting of clade B (n = 167, 65%), C (n = 10, 3.9%), F1 (n = 4, 1.5%), and D (n = 2, 0.7%). Recombinant viruses were detected in 74 (28.8%) samples and consist of unique BF1 (n = 41, 15.9%), BC (n = 7, 2.7%), BCF1 (n = 4, 1.5%), CF1 and CDK (n = 1, 0.4%, each), CRF70_BF1 (n = 4, 1.5%), CRF71_BF1 (n = 12, 4.7%), and CRF72_BF1 (n = 4, 1.5%). Evidence of dual infection was detected in four patients coinfected with the same subtype (n = 3) and distinct subtype (n = 1). Conclusion Based on this work, subtype B appears to be the prevalent subtype followed by a high proportion of intersubtype recombinants that appeared to be arising continually in this country. Our study represents the largest analysis of the viral NFLG ever undertaken worldwide and provides insights into the understanding the genesis of the HIV-1 epidemic in this particular area of South America and informs vaccine design and clinical trials.
    Keywords: Research Article ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Research And Analysis Methods ; Biology And Life Sciences ; Research And Analysis Methods ; People And Places ; Medicine And Health Sciences ; Biology And Life Sciences ; Research And Analysis Methods ; Biology And Life Sciences ; Research And Analysis Methods ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Medicine And Health Sciences ; Biology And Life Sciences
    E-ISSN: 1932-6203
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  • 7
    Language: English
    In: Cellular Signalling, August 2016, Vol.28(8), pp.861-870
    Description: The epithelial-mesenchymal transition (EMT) is the crucial step that cancer cells must pass before they can undergo metastasis. The transition requires the activity of complex functional networks that downregulate properties of the epithelial phenotype and upregulate characteristics of the mesenchymal phenotype. The networks frequently include reciprocal repressions between transcription factors (TFs) driving the EMT and microRNAs (miRs) inducing the reverse process, termed mesenchymal-epithelial transition (MET). In this work we develop four kinetic models that are based on experimental data and hypotheses describing how autocrine transforming growth factor-β (TGF-β) signal transduction induces and maintains an EMT by upregulating the TFs ZEB1 and ZEB2 which repress the expression of the miR-200b/c family members. After successful model calibration we validate our models by predicting requirements for the maintenance of the mesenchymal steady state which agree with experimental data. Finally, we apply our validated kinetic models for the design of experiments in cancer therapy. We demonstrate how steady state properties of the kinetic models, combined with data from tumor-derived cell lines of individual patients, can predict the minimal amount of an inhibitor to induce a MET.
    Keywords: Epithelial-Mesenchymal Transition ; Interaction Between Zeb and Microrna-200 ; Kinetic Model ; Metastasis Inhibition ; Design of Experiments ; Biology
    ISSN: 0898-6568
    E-ISSN: 1873-3913
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  • 8
    Language: English
    In: Virus Research, 15 June 2016, Vol.218, pp.96-101
    Description: Hepatitis C virus (HCV) infections are a global health problem, and extensive research over the last decades has been targeted at understanding its molecular biology and developing effective antiviral treatments. Recently, a number of potent direct acting antiviral drugs have been developed targeting specific processes in the viral life cycle. Here, we developed a mathematical multi-scale model of the within-host dynamics of HCV infection by integrating a standard model for viral infection with a detailed model of the viral replication cycle inside infected cells. We use this model to study patient time courses of viral load under treatment with daclatasvir, an inhibitor of the viral non-structural protein NS5A. Model analysis predicts that treatment efficacy can be increased by combining daclatasvir with dedicated viral polymerase inhibitors, corresponding to promising current strategies in drug development. Hence, our model presents a predictive tool for simulations, which can be used to study and optimize direct acting antiviral drug treatment.
    Keywords: Hepatitis C Virus ; Viral Kinetics ; Pharmacodynamics ; Direct Acting Antiviral Treatment ; Ordinary Differential Equations Model ; Biology
    ISSN: 0168-1702
    E-ISSN: 1872-7492
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  • 9
    In: PLoS ONE, 2016, Vol.11(6)
    Description: Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year follow up. Replicates of selected samples were measured at both time points to identify technical variability. Deming regression, Passing-Bablok regression, linear mixed models, non-linear models as well as ReplicateRUV and ComBat were applied to eliminate batch effects between replicates. In a second step, quantile normalization prior to batch effect correction was performed for each method. Technical variation between batches was evaluated by principal component analysis. Associations between body mass index and transcriptomes were calculated before and after batch removal. Results from association analyses were compared to evaluate maintenance of biological variability. Quantile normalization, separately performed in each batch, combined with ComBat successfully reduced batch effects and maintained biological variability. ReplicateRUV performed perfectly in the replicate data subset of the study, but failed when applied to all samples. All other methods did not substantially reduce batch effects in the replicate data subset. Quantile normalization plus ComBat appears to be a valuable approach for batch correction in longitudinal gene expression data.
    Keywords: Research Article ; Biology And Life Sciences ; Biology And Life Sciences ; Research And Analysis Methods ; Biology And Life Sciences ; Research And Analysis Methods ; Research And Analysis Methods ; Research And Analysis Methods ; Research And Analysis Methods ; Physical Sciences ; Biology And Life Sciences ; Biology And Life Sciences ; Physical Sciences
    E-ISSN: 1932-6203
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  • 10
    In: Schneider, Constanze and Oellerich, Thomas and Baldauf, Hanna-Mari and Schwarz, Sarah-Marie and Thomas, Dominique and Flick, Robert and Bohnenberger, Hanibal and Kaderali, Lars and Stegmann, Lena and Cremer, Anjali and Martin, Margarethe and Lohmeyer, Julian and Michaelis, Martin and Hornung, Veit and Schliemann, Christoph and Berdel, Wolfgang E and Hartmann, Wolfgang and Wardelmann, Eva and Comoglio, Federico and Hansmann, Martin-Leo and Yakunin, Alexander F and Geisslinger, Gerd and Ströbel, Philipp and Ferreirós, Nerea and Serve, Hubert and Keppler, Oliver T and Cinatl, Jindrich (2016) SAMHD1 is a biomarker for cytarabine response and a therapeutic target in acute myeloid leukemia. Nature medicine, 23 (2). pp. 250-255.
    Description: The nucleoside analog cytarabine (Ara-C) is an essential component of primary and salvage chemotherapy regimens for acute myeloid leukemia (AML). After cellular uptake, Ara-C is converted into its therapeutically active triphosphate metabolite, Ara-CTP, which exerts antileukemic effects, primarily by inhibiting DNA synthesis in proliferating cells. Currently, a substantial fraction of patients with AML fail to respond effectively to Ara-C therapy, and reliable biomarkers for predicting the therapeutic response to Ara-C are lacking. SAMHD1 is a deoxynucleoside triphosphate (dNTP) triphosphohydrolase that cleaves physiological dNTPs into deoxyribonucleosides and inorganic triphosphate. Although it has been postulated that SAMHD1 sensitizes cancer cells to nucleoside-analog derivatives through the depletion of competing dNTPs, we show here that SAMHD1 reduces Ara-C cytotoxicity in AML cells. Mechanistically, dGTP-activated SAMHD1 hydrolyzes Ara-CTP, which results in a drastic reduction of Ara-CTP in leukemic cells. Loss of SAMHD1 activity-through genetic depletion, mutational inactivation of its triphosphohydrolase activity or proteasomal degradation using specialized, virus-like particles-potentiates the cytotoxicity of Ara-C in AML cells. In mouse models of retroviral AML transplantation, as well as in retrospective analyses of adult patients with AML, the response to Ara-C-containing therapy was inversely correlated with SAMHD1 expression. These results identify SAMHD1 as a potential biomarker for the stratification of patients with AML who might best respond to Ara-C-based therapy and as a target for treating Ara-C-refractory AML.
    Keywords: RM Therapeutics. Pharmacology
    ISSN: 1078-8956
    Source: University of Kent
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