262 research outputs found

    Clinical decision support tools: analysis of online drug information databases

    Get PDF
    BACKGROUND: Online drug information databases are used to assist in enhancing clinical decision support. However, the choice of which online database to consult, purchase or subscribe to is likely made based on subjective elements such as history of use, familiarity, or availability during professional training. The purpose of this study was to evaluate clinical decision support tools for drug information by systematically comparing the most commonly used online drug information databases. METHODS: Five commercially available and two freely available online drug information databases were evaluated according to scope (presence or absence of answer), completeness (the comprehensiveness of the answers), and ease of use. Additionally, a composite score integrating all three criteria was utilized. Fifteen weighted categories comprised of 158 questions were used to conduct the analysis. Descriptive statistics and Chi-square were used to summarize the evaluation components and make comparisons between databases. Scheffe's multiple comparison procedure was used to determine statistically different scope and completeness scores. The composite score was subjected to sensitivity analysis to investigate the effect of the choice of percentages for scope and completeness. RESULTS: The rankings for the databases from highest to lowest, based on composite scores were Clinical Pharmacology, Micromedex, Lexi-Comp Online, Facts & Comparisons 4.0, Epocrates Online Premium, RxList.com, and Epocrates Online Free. Differences in scope produced three statistical groupings with Group 1 (best) performers being: Clinical Pharmacology, Micromedex, Facts & Comparisons 4.0, Lexi-Comp Online, Group 2: Epocrates Premium and RxList.com and Group 3: Epocrates Free (p < 0.05). Completeness scores were similarly stratified. Collapsing the databases into two groups by access (subscription or free), showed the subscription databases performed better than the free databases in the measured criteria (p < 0.001). CONCLUSION: Online drug information databases, which belong to clinical decision support, vary in their ability to answer questions across a range of categories

    ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence

    Get PDF
    Background: The possibilities offered by next generation sequencing (NGS) platforms are revolutionizing biotechnological laboratories. Moreover, the combination of NGS sequencing and affordable high-throughput genotyping technologies is facilitating the rapid discovery and use of SNPs in non-model species. However, this abundance of sequences and polymorphisms creates new software needs. To fulfill these needs, we have developed a powerful, yet easy-to-use application. Results: The ngs_backbone software is a parallel pipeline capable of analyzing Sanger, 454, Illumina and SOLiD (Sequencing by Oligonucleotide Ligation and Detection) sequence reads. Its main supported analyses are: read cleaning, transcriptome assembly and annotation, read mapping and single nucleotide polymorphism (SNP) calling and selection. In order to build a truly useful tool, the software development was paired with a laboratory experiment. All public tomato Sanger EST reads plus 14.2 million Illumina reads were employed to test the tool and predict polymorphism in tomato. The cleaned reads were mapped to the SGN tomato transcriptome obtaining a coverage of 4.2 for Sanger and 8.5 for Illumina. 23,360 single nucleotide variations (SNVs) were predicted. A total of 76 SNVs were experimentally validated, and 85% were found to be real. Conclusions: ngs_backbone is a new software package capable of analyzing sequences produced by NGS technologies and predicting SNVs with great accuracy. In our tomato example, we created a highly polymorphic collection of SNVs that will be a useful resource for tomato researchers and breeders. The software developed along with its documentation is freely available under the AGPL license and can be downloaded from http://bioinf. comav.upv.es/ngs_backbone/ or http://github.com/JoseBlanca/franklin.Blanca Postigo, JM.; Pascual Bañuls, L.; Ziarsolo Areitioaurtena, P.; Nuez Viñals, F.; Cañizares Sales, J. (2011). Ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence. BMC Genomics. 12:1-8. doi:10.1186/1471-2164-12-285S1812Metzker ML: Sequencing technologies - the next generation. Nature Reviews Genetics. 2010, 11 (1): 31-46. 10.1038/nrg2626.454 sequencing. [ http://www.454.com/ ]Illumina Inc. [ http://www.illumina.com/ ]Flicek P, Birney E: Sense from sequence reads: methods for alignment and assembly (vol 6, pg S6, 2009). Nature Methods. 2010, 7 (6): 479-479.Chevreux B, Pfisterer T, Drescher B, Driesel AJ, Muller WEG, Wetter T, Suhai S: Using the miraEST assembler for reliable and automated mRNA transcript assembly and SNP detection in sequenced ESTs. Genome Research. 2004, 14 (6): 1147-1159. 10.1101/gr.1917404.Li H, Durbin R: Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009, 25 (14): 1754-1760. 10.1093/bioinformatics/btp324.Langmead B, Trapnell C, Pop M, Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biology. 2009, 10 (3):Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Genome Project Data P: The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009, 25 (16): 2078-2079. 10.1093/bioinformatics/btp352.1000 Genomes. A deep Catalog of Human Genetic Variation. [ http://1000genomes.org/wiki/doku.php?id=1000_genomes:analysis:vcf4.0 ]The seqanswers internet forum. [ http://seqanswers.com/ ]Blankenberg D, Taylor J, Schenck I, He JB, Zhang Y, Ghent M, Veeraraghavan N, Albert I, Miller W, Makova KD, Ross CH, Nekrutenko A: A framework for collaborative analysis of ENCODE data: Making large-scale analyses biologist-friendly. Genome Research. 2007, 17 (6): 960-964. 10.1101/gr.5578007.CloVR Automated Sequence Analysis from Your Desktop. [ http://clovr.org/ ]Papanicolaou A, Stierli R, Ffrench-Constant RH, Heckel DG: Next generation transcriptomes for next generation genomes using est2assembly. Bmc Bioinformatics. 2009, 10:Applied Biosystems by life technologies. [ http://www.appliedbiosystems.com/absite/us/en/home/applications-technologies/solid-next-generation-sequencing.html ]Wall PK, Leebens-Mack J, Chanderbali AS, Barakat A, Wolcott E, Liang HY, Landherr L, Tomsho LP, Hu Y, Carlson JE, Ma H, Schuster SC, Soltis DE, Soltis PS, Altman N, dePamphilis CW: Comparison of next generation sequencing technologies for transcriptome characterization. Bmc Genomics. 2009, 10:Murchison EP, Tovar C, Hsu A, Bender HS, Kheradpour P, Rebbeck CA, Obendorf D, Conlan C, Bahlo M, Blizzard CA, Pyecroft S, Kreiss A, Kellis M, Stark A, Harkins TT, Marshall Graves JA, Woods GM, Hanon GJ, Papenfuss AT: The Tasmanian Devil Transcriptome Reveals Schwann Cell Origins of a Clonally Transmissible Cancer. Science. 2010, 327 (5961): 84-87. 10.1126/science.1180616.Parchman TL, Geist KS, Grahnen JA, Benkman CW, Buerkle CA: Transcriptome sequencing in an ecologically important tree species: assembly, annotation, and marker discovery. Bmc Genomics. 2010, 11:Babik W, Stuglik M, Qi W, Kuenzli M, Kuduk K, Koteja P, Radwan J: Heart transcriptome of the bank vole (Myodes glareolus): towards understanding the evolutionary variation in metabolic rate. BMC Genomics. 2010, 11: 390-10.1186/1471-2164-11-390.Miller JC, Tanksley SD: RFLP analysis of phylogenetic-relationships and genetic-variation in the genus Lycopersicon. Theoretical and Applied Genetics. 1990, 80 (4): 437-448.Williams CE, Stclair DA: Phenetic relationships and levels of variability detected by restriction-fragment-length-polymorphism and random amplified polymorphic DNA analysis of cultivated and wild accessions of Lycopersicon-esculentum. Genome. 1993, 36 (3): 619-630. 10.1139/g93-083.Rick CM: Tomato, Lycopersicon esculentum (Solanaceae). Evolution of crop plants. Edited by: Simmonds NW. 1976, London: Longman Group, 268-273.Labate JA, Baldo AM: Tomato SNP discovery by EST mining and resequencing. Molecular Breeding. 2005, 16 (4): 343-349. 10.1007/s11032-005-1911-5.Yano K, Watanabe M, Yamamoto N, Maeda F, Tsugane T, Shibata D: Expressed sequence tags (EST) database of a miniature tomato cultivar, Micro-Tom. Plant and Cell Physiology. 2005, 46: S139-S139.Jimenez-Gomez JM, Maloof JN: Sequence diversity in three tomato species: SNPs, markers, and molecular evolution. Bmc Plant Biology. 2009, 9:Yang WC, Bai XD, Kabelka E, Eaton C, Kamoun S, van der Knaap E, Francis D: Discovery of single nucleotide polymorphisms in Lycopersicon esculentum by computer aided analysis of expressed sequence tags. Molecular Breeding. 2004, 14 (1): 21-34.Van Deynze A, Stoffel K, Buell CR, Kozik A, Liu J, van der Knaap E, Francis D: Diversity in conserved genes in tomato. Bmc Genomics. 2007, 8:Sim SC, Robbins MD, Chilcott C, Zhu T, Francis DM: Oligonucleotide array discovery of polymorphisms in cultivated tomato (Solanum lycopersicum L.) reveals patterns of SNP variation associated with breeding. Bmc Genomics. 2009, 10:Bioinformatics at COMAV. [ http://bioinf.comav.upv.es/ngs_backbone/index.html ]Broad institute. [ http://www.broadinstitute.org/igv ]Bioinformatics at COMAV. [ http://bioinf.comav.upv.es/ngs_backbone/install.html ]Github social coding. [ http://github.com/JoseBlanca/franklin ]Chou HH, Holmes MH: DNA sequence quality trimming and vector removal. Bioinformatics. 2001, 17 (12): 1093-1104. 10.1093/bioinformatics/17.12.1093.Picard. [ http://picard.sourceforge.net/index.shtml ]McKenna A, Hanna M, Banks E, Sivachenko A, Citulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA: The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research. 2010, 20: 1297-1303. 10.1101/gr.107524.110.Sol Genomics Network. [ ftp://ftp.solgenomics.net/ ]NCBI Genbank. [ http://www.ncbi.nlm.nih.gov/genbank/ ]Gundry CN, Vandersteen JG, Reed GH, Pryor RJ, Chen J, Wittwer CT: Amplicon melting analysis with labeled primers: A closed-tube method for differentiating homozygotes and heterozygotes. Clinical Chemistry. 2003, 49 (3): 396-406. 10.1373/49.3.396

    Improving the practicality of using non-aversive handling methods to reduce background stress and anxiety in laboratory mice

    Get PDF
    Handling can stimulate stress and anxiety in laboratory animals that negatively impacts welfare and introduces a confounding factor in many areas of research. Picking up mice by the tail is a major source of handling stress that results in strong aversion to the handler, while mice familiarised with being picked up in a tunnel or cupped on the open hand show low stress and anxiety, and actively seek interaction with their handlers. Here we investigate the duration and frequency of handling required for effective familiarisation with these non-aversive handling methods, and test whether this is sufficient to prevent aversion and anxiety when animals then experience immobilisation and a mild procedure (subcutaneous injection). Very brief handling (2 s) was sufficient to familiarise mice with tunnel handling, even when experienced only during cage cleaning. Brief but more frequent handling was needed for familiarisation with cup handling, while pick up by tail induced strong aversion even when handling was brief and infrequent. Experience of repeated immobilisation and subcutaneous injection did not reverse the positive effects of tunnel handling. Our findings demonstrate that replacing tail with tunnel handling during routine cage cleaning and procedures provides a major refinement with little if any cost for familiarisation

    Hypermethylated 14-3-3-σ and ESR1 gene promoters in serum as candidate biomarkers for the diagnosis and treatment efficacy of breast cancer metastasis

    Get PDF
    Background: Numerous hypermethylated genes have been reported in breast cancer, and the silencing of these genes plays an important role in carcinogenesis, tumor progression and diagnosis. These hypermethylated promoters are very rarely found in normal breast. It has been suggested that aberrant hypermethylation may be useful as a biomarker, with implications for breast cancer etiology, diagnosis, and management. The relationship between primary neoplasm and metastasis remains largely unknown. There has been no comprehensive comparative study on the clinical usefulness of tumor-associated methylated DNA biomarkers in primary breast carcinoma and metastatic breast carcinoma. The objective of the present study was to investigate the association between clinical extension of breast cancer and methylation status of Estrogen Receptor1 (ESR1) and Stratifin (14-3-3-σ) gene promoters in disease-free and metastatic breast cancer patients. Methods: We studied two cohorts of patients: 77 patients treated for breast cancer with no signs of disease, and 34 patients with metastatic breast cancer. DNA was obtained from serum samples, and promoter methylation status was determined by using DNA bisulfite modification and quantitative methylation-specific PCR. Results: Serum levels of methylated gene promoter 14-3-3-σ significantly differed between Control and Metastatic Breast Cancer groups (P < 0.001), and between Disease-Free and Metastatic Breast Cancer groups (P < 0.001). The ratio of the 14-3-3-σ level before the first chemotherapy cycle to the level just before administration of the second chemotherapy cycle was defined as the Biomarker Response Ratio [BRR]. We calculated BRR values for the "continuous decline" and "rise-and-fall" groups. Subsequent ROC analysis showed a sensitivity of 75% (95% CI: 47.6 - 86.7) and a specificity of 66.7% (95% CI: 41.0 - 86.7) to discriminate between the groups for a cut-off level of BRR = 2.39. The area under the ROC curve (Z = 0.804 ± 0.074) indicates that this test is a good approach to post-treatment prognosis. Conclusions: The relationship of 14-3-3-σ with breast cancer metastasis and progression found in this study suggests a possible application of 14-3-3-σ as a biomarker to screen for metastasis and to follow up patients treated for metastatic breast cancer, monitoring their disease status and treatment response.This study was supported by a grant from the Ministerio de Ciencia e Innovación: SAF 2004-00889; JL Linares is supported by the Junta de Andalucía (P06-CTS-1385)

    The membrane-spanning 4-domains, subfamily A (MS4A) gene cluster contains a common variant associated with Alzheimer's disease

    Get PDF
    Background\ud In order to identify novel loci associated with Alzheimer's disease (AD), we conducted a genome-wide association study (GWAS) in the Spanish population.\ud \ud Methods\ud We genotyped 1,128 individuals using the Affymetrix Nsp I 250K chip. A sample of 327 sporadic AD patients and 801 controls with unknown cognitive status from the Spanish general population were included in our initial study. To increase the power of the study, we combined our results with those of four other public GWAS datasets by applying identical quality control filters and the same imputation methods, which were then analyzed with a global meta-GWAS. A replication sample with 2,200 sporadic AD patients and 2,301 controls was genotyped to confirm our GWAS findings.\ud \ud Results\ud Meta-analysis of our data and independent replication datasets allowed us to confirm a novel genome-wide significant association of AD with the membrane-spanning 4-domains subfamily A (MS4A) gene cluster (rs1562990, P = 4.40E-11, odds ratio = 0.88, 95% confidence interval 0.85 to 0.91, n = 10,181 cases and 14,341 controls).\ud \ud Conclusions\ud Our results underscore the importance of international efforts combining GWAS datasets to isolate genetic loci for complex diseases

    Telomerase activity, estrogen receptors (α, β), Bcl-2 expression in human breast cancer and treatment response

    Get PDF
    BACKGROUND: The mechanism for maintaining telomere integrity is controlled by telomerase, a ribonucleoprotein enzyme that specifically restores telomere sequences, lost during replication by means of an intrinsic RNA component as a template for polymerization. Among the telomerase subunits, hTERT (human telomerase reverse transcriptase) is expressed concomitantly with the activation of telomerase. The role of estrogens and their receptors in the transcriptional regulation of hTERT has been demonstrated. The current study determines the possible association between telomerase activity, the expression of both molecular forms of estrogen receptor (ERα and ERβ) and the protein bcl-2, and their relative associations with clinical parameters. METHODS: Tissue samples from 44 patients with breast cancer were used to assess telomerase activity using the TRAP method and the expression of ERα, ERβ and bcl-2 by means of immunocytochemical techniques. RESULTS: Telomerase activity was detected in 59% of the 44 breast tumors examined. Telomerase activity ranged from 0 to 49.93 units of total product generated (TPG). A correlation was found between telomerase activity and differentiation grade (p = 0.03). The only significant independent marker of response to treatment was clinical stage. We found differences between the frequency of expression of ERα (88%) and ERβ (36%) (p = 0.007); bcl-2 was expressed in 79.5% of invasive breast carcinomas. We also found a significant correlation between low levels of telomerase activity and a lack of ERβ expression (p = 0.03). CONCLUSION: Lower telomerase activity was found among tumors that did not express estrogen receptor beta. This is the first published study demonstrating that the absence of expression of ERβ is associated with low levels of telomerase activity

    Temporal Dynamics of European Bat Lyssavirus Type 1 and Survival of Myotis myotis Bats in Natural Colonies

    Get PDF
    Many emerging RNA viruses of public health concern have recently been detected in bats. However, the dynamics of these viruses in natural bat colonies is presently unknown. Consequently, prediction of the spread of these viruses and the establishment of appropriate control measures are hindered by a lack of information. To this aim, we collected epidemiological, virological and ecological data during a twelve-year longitudinal study in two colonies of insectivorous bats (Myotis myotis) located in Spain and infected by the most common bat lyssavirus found in Europe, the European bat lyssavirus subtype 1 (EBLV-1). This active survey demonstrates that cyclic lyssavirus infections occurred with periodic oscillations in the number of susceptible, immune and infected bats. Persistence of immunity for more than one year was detected in some individuals. These data were further used to feed models to analyze the temporal dynamics of EBLV-1 and the survival rate of bats. According to these models, the infection is characterized by a predicted low basic reproductive rate (R0 = 1.706) and a short infectious period (D = 5.1 days). In contrast to observations in most non-flying animals infected with rabies, the survival model shows no variation in mortality after EBLV-1 infection of M. myotis. These findings have considerable public health implications in terms of management of colonies where lyssavirus-positive bats have been recorded and confirm the potential risk of rabies transmission to humans. A greater understanding of the dynamics of lyssavirus in bat colonies also provides a model to study how bats contribute to the maintenance and transmission of other viruses of public health concern

    A significant proportion of classic Hodgkin lymphoma recurrences represents clonally unrelated second primary lymphoma

    Get PDF
    Despite high cure rates in classic Hodgkin lymphoma (cHL), relapses are observed. Whether relapsed cHL represents second primary lymphoma or an underlying T-cell lymphoma (TCL) mimicking cHL is under-investigated. To analyze the nature of cHL recurrences, in-depth clonality testing of immunoglobulin (IG) and T-cell receptor (TR) rearrangements was performed in paired cHL diagnosis and recurrences of 60 patients, supported by targeted mutation analysis of lymphoma-associated genes. Clonal IG rearrangements were detected by next-generation sequencing (NGS) in 69/120 (58%) diagnosis and recurrence samples. The clonal relationship could be established in 34 cases, identifying clonally related relapsed cHL in 24/34 patients (71%). Clonally unrelated cHL was observed in 10/34 patients (29%) as determined by IG-NGS clonality assessment, and confirmed by the identification of predominantly mutually exclusive gene mutations in the paired cHL samples. In recurrences of &gt;2 years, ~60% of cHL patients for which the clonal relationship could be established showed a second primary cHL. Clonal TR gene rearrangements were identified in 14/125 samples (11%), and TCL-associated gene mutations were detected in 7/14 samples. Retrospective pathology review with integration of the molecular findings were consistent with an underlying TCL in 5 patients aged &gt;50 years. This study shows that cHL recurrences, especially after 2 years, sometimes represent a new primary cHL or TCL mimicking cHL, as uncovered by NGS-based IG/TR clonality testing and gene mutation analysis. Given the significant therapeutic consequences, molecular testing of a presumed relapse in cHL is crucial for subsequent appropriate treatment strategies adapted to the specific lymphoma presentation.</p
    corecore