103 research outputs found

    Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm

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    <p>Abstract</p> <p>Background</p> <p>Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space.</p> <p>Results</p> <p>We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (<it>Plasmodium chabaudi</it>), systemic acquired resistance in <it>Arabidopsis thaliana</it>, similarities and differences between inner and outer cotyledon in <it>Brassica napus </it>during seed development, and to <it>Brassica napus </it>whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples.</p> <p>Conclusions</p> <p>Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.</p

    Query Large Scale Microarray Compendium Datasets Using a Model-Based Bayesian Approach with Variable Selection

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    In microarray gene expression data analysis, it is often of interest to identify genes that share similar expression profiles with a particular gene such as a key regulatory protein. Multiple studies have been conducted using various correlation measures to identify co-expressed genes. While working well for small datasets, the heterogeneity introduced from increased sample size inevitably reduces the sensitivity and specificity of these approaches. This is because most co-expression relationships do not extend to all experimental conditions. With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge. We develop a model-based gene expression query algorithm built under the Bayesian model selection framework. It is capable of detecting co-expression profiles under a subset of samples/experimental conditions. In addition, it allows linearly transformed expression patterns to be recognized and is robust against sporadic outliers in the data. Both features are critically important for increasing the power of identifying co-expressed genes in large scale gene expression datasets. Our simulation studies suggest that this method outperforms existing correlation coefficients or mutual information-based query tools. When we apply this new method to the Escherichia coli microarray compendium data, it identifies a majority of known regulons as well as novel potential target genes of numerous key transcription factors

    A Platform for Processing Expression of Short Time Series (PESTS)

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    <p>Abstract</p> <p>Background</p> <p>Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamically expressed under given conditions, and to determine the interaction between these genes. Because of cost and resource issues, most time series datasets contain less than 9 points and there are few tools available geared towards the analysis of this type of data.</p> <p>Results</p> <p>To this end, we introduce a platform for Processing Expression of Short Time Series (PESTS). It was designed with a focus on usability and interpretability of analyses for the researcher. As such, it implements several standard techniques for comparability as well as visualization functions. However, it is designed specifically for the unique methods we have developed for significance analysis, multiple test correction and clustering of short time series data. The central tenet of these methods is the use of biologically relevant features for analysis. Features summarize short gene expression profiles, inherently incorporate dependence across time, and allow for both full description of the examined curve and missing data points.</p> <p>Conclusions</p> <p>PESTS is fully generalizable to other types of time series analyses. PESTS implements novel methods as well as several standard techniques for comparability and visualization functions. These features and functionality make PESTS a valuable resource for a researcher's toolkit. PESTS is available to download for free to academic and non-profit users at <url>http://www.mailman.columbia.edu/academic-departments/biostatistics/research-service/software-development</url>.</p

    Community-Based Outbreaks in Vulnerable Populations of Invasive Infections Caused by Streptococcus pneumoniae Serotypes 5 and 8 in Calgary, Canada

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    BACKGROUND: Outbreaks of invasive pneumococcal disease (IPD) typically occur within institutions. Beginning in 2005, we detected an increase in serotype (ST) 5 and ST8 IPD cases, predominantly in homeless persons living in an open community. METHODOLOGY/PRINCIPAL FINDINGS: CASPER (Calgary Area S. pneumoniae Epidemiology Research) surveillance study of all IPD (sterile site isolates) in our region (pop ~1,100,000). Interviews and chart reviews of all cases and all isolates phenotypically analyzed and selected isolated tested by multi-locus sequence typing (MLST). CONCLUSIONS/SIGNIFICANCE: During 2005-2007, 162 cases of ST5 IPD and 45 cases of ST8 IPD were identified. The isolates demonstrated phenotypic and genotypic clonality. The ST5 isolates were sequence type (ST) 289 and demonstrated intermediate susceptibility to TMP-SMX. The ST8 isolates were predominantly ST1268, with a susceptible antimicrobial susceptibility profile. Individuals with ST5 IPD were more likely to be middle aged (OR 2.6), homeless (OR 4.4), using illicit drugs(OR 4.8), and asthmatic(OR 2.6). Those with ST8 were more likely to be male (OR 4.4), homeless (OR 2.6), aboriginal (OR7.3), and a current smoker (OR 2.5). Overlapping outbreaks of ST5 and ST8 IPD occurred in an open community in Calgary, Canada and homelessness was a predominant risk factor. Homelessness represents a unique community in which pneumococcal outbreaks can occur

    A prospective study of symptoms, function, and medication use during acute illness in nursing home residents: design, rationale and cohort description

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    <p>Abstract</p> <p>Background</p> <p>Nursing home residents are at high risk for developing acute illnesses. Compared with community dwelling adults, nursing home residents are often more frail, prone to multiple medical problems and symptoms, and are at higher risk for adverse outcomes from acute illnesses. In addition, because of polypharmacy and the high burden of chronic disease, nursing home residents are particularly vulnerable to disruptions in transitions of care such as medication interruptions in the setting of acute illness. In order to better estimate the effect of acute illness on nursing home residents, we have initiated a prospective cohort which will allow us to observe patterns of acute illnesses and the consequence of acute illnesses, including symptoms and function, among nursing home residents. We also aim to examine the patterns of medication interruption, and identify patient, provider and environmental factors that influence continuity of medication prescribing at different points of care transition.</p> <p>Methods</p> <p>This is a prospective cohort of nursing home residents residing in two nursing homes in a metropolitan area. Baseline characteristics including age, gender, race, and comorbid conditions are recorded. Participants are followed longitudinally for a planned period of 3 years. We record acute illness incidence and characteristics, and measure symptoms including depression, pain, withdrawal symptoms, and function using standardized scales.</p> <p>Results</p> <p>76 nursing home residents have been followed for a median of 666 days to date. At baseline, mean age of residents was 74.4 (± 11.9); 32% were female; 59% were white. The most common chronic conditions were dementia (41%), depression (38%), congestive heart failure (25%) and chronic obstructive lung disease (27%). Mean pain score was 4.7 (± 3.6) on a scale of 0 to 10; Geriatric Depression Scale (GDS-15) score was 5.2 (± 4.4). During follow up, 138 acute illness episodes were identified, for an incidence of 1.5 (SD 2.0) episodes per resident per year; 74% were managed in the nursing home and 26% managed in the acute care setting.</p> <p>Conclusion</p> <p>In this report, we describe the conceptual model and methods of designing a longitudinal cohort to measure acute illness patterns and symptoms among nursing home residents, and describe the characteristics of our cohort at baseline. In our planned analysis, we will further estimate the effect of the use and interruption of medications on withdrawal and relapse symptoms and illness outcomes.</p

    AmrZ is a major determinant of c-di-GMP levels in Pseudomonas fluorescens F113

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    The transcriptional regulator AmrZ is a global regulatory protein conserved within the pseudomonads. AmrZ can act both as a positive and a negative regulator of gene expression, controlling many genes implicated in environmental adaption. Regulated traits include motility, iron homeostasis, exopolysaccharides production and the ability to form biofilms. In Pseudomonas fluorescens F113, an amrZ mutant presents a pleiotropic phenotype, showing increased swimming motility, decreased biofilm formation and very limited ability for competitive colonization of rhizosphere, its natural habitat. It also shows different colony morphology and binding of the dye Congo Red. The amrZ mutant presents severely reduced levels of the messenger molecule cyclic-di-GMP (c-di-GMP), which is consistent with the motility and biofilm formation phenotypes. Most of the genes encoding proteins with diguanylate cyclase (DGCs) or phosphodiesterase (PDEs) domains, implicated in c-di-GMP turnover in this bacterium, appear to be regulated by AmrZ. Phenotypic analysis of eight mutants in genes shown to be directly regulated by AmrZ and encoding c-di-GMP related enzymes, showed that seven of them were altered in motility and/or biofilm formation. The results presented here show that in P. fluorescens, AmrZ determines c-di-GMP levels through the regulation of a complex network of genes encoding DGCs and PDEs

    Preventable hospitalization and access to primary health care in an area of Southern Italy

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    <p>Abstract</p> <p>Background</p> <p>Ambulatory care-sensitive conditions (ACSC), such as hypertension, diabetes, chronic heart failure, chronic obstructive pulmonary disease and asthma, are conditions that can be managed with timely and effective outpatient care reducing the need of hospitalization. Avoidable hospitalizations for ACSC have been used to assess access, quality and performance of the primary care delivery system. The aims of this study were to quantify the proportion of avoidable hospital admissions for ACSCs, to identify the related patient's socio-demographic profile and health conditions, to assess the relationship between the primary care access characteristics and preventable hospitalizations, and the usefulness of avoidable hospitalizations for ACSCs to monitor the effectiveness of primary health care.</p> <p>Methods</p> <p>A random sample of 520 medical records of patients admitted to medical wards (Cardiology, Internal Medicine, Pneumology, Geriatrics) of a non-teaching acute care 717-bed hospital located in Catanzaro (Italy) were reviewed.</p> <p>Results</p> <p>A total of 31.5% of the hospitalizations in the sample were judged to be preventable. Of these, 40% were for congestive heart failure, 23.2% for chronic obstructive pulmonary disease, 13.5% for angina without procedure, 8.4% for hypertension, and 7.1% for bacterial pneumonia. Preventable hospitalizations were significantly associated to age and sex since they were higher in older patients and in males. The proportion of patients who had a preventable hospitalization significantly increased with regard to the number of hospital admissions in the previous year and to the number of patients for each primary care physician (PCP), with lower number of PCP accesses and PCP medical visits in the previous year, with less satisfaction about PCP health services, and, finally, with worse self-reported health status and shorter length of hospital stay.</p> <p>Conclusion</p> <p>The findings from this study add to the evidence and the urgency of developing and implementing effective interventions to improve delivery of health care at the community level and provided support to the usefulness of avoidable hospitalizations for ACSCs to monitor this process.</p

    A higher activation threshold of memory CD8+ T cells has a fitness cost that is modified by TCR affinity during Tuberculosis

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    All relevant data are within the paper and its Supporting Information files except for the primary TCR sequences. The data files for the primary TCR sequences are publicly deposited in the University of Massachusetts Medical School’s institutional repository, eScholarship@UMMS. The permanent link to the data is http://dx.doi.org/10.13028/M2CC70T cell vaccines against Mycobacterium tuberculosis (Mtb) and other pathogens are based on the principle that memory T cells rapidly generate effector responses upon challenge, leading to pathogen clearance. Despite eliciting a robust memory CD8+ T cell response to the immunodominant Mtb antigen TB10.4 (EsxH), we find the increased frequency of TB10.4-specific CD8+ T cells conferred by vaccination to be short-lived after Mtb challenge. To compare memory and naïve CD8+ T cell function during their response to Mtb, we track their expansions using TB10.4-specific retrogenic CD8+ T cells. We find that the primary (naïve) response outnumbers the secondary (memory) response during Mtb challenge, an effect moderated by increased TCR affinity. To determine whether the expansion of polyclonal memory T cells is restrained following Mtb challenge, we used TCRβ deep sequencing to track TB10.4-specific CD8+ T cells after vaccination and subsequent challenge in intact mice. Successful memory T cells, defined by their clonal expansion after Mtb challenge, express similar CDR3β sequences suggesting TCR selection by antigen. Thus, both TCR-dependent and -independent factors affect the fitness of memory CD8+ responses. The impaired expansion of the majority of memory T cell clonotypes may explain why some TB vaccines have not provided better protection.This work was supported by NIH R01 AI106725 as well as fellowship funding to SC from NIH AI T32 007061 and the UMass GSBS Millennium Program. The Small Animal Biocontainment Suite was supported in part by Center for AIDS Research Grant P30 AI 060354. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

    Evidence-based guidelines for use of probiotics in preterm neonates

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    <p>Abstract</p> <p>Background</p> <p>Current evidence indicates that probiotic supplementation significantly reduces all-cause mortality and definite necrotising enterocolitis without significant adverse effects in preterm neonates. As the debate about the pros and cons of routine probiotic supplementation continues, many institutions are satisfied with the current evidence and wish to use probiotics routinely. Because of the lack of detail on many practical aspects of probiotic supplementation, clinician-friendly guidelines are urgently needed to optimise use of probiotics in preterm neonates.</p> <p>Aim</p> <p>To develop evidence-based guidelines for probiotic supplementation in preterm neonates.</p> <p>Methods</p> <p>To develop core guidelines on use of probiotics, including strain selection, dose and duration of supplementation, we primarily used the data from our recent updated systematic review of randomised controlled trials. For equally important issues including strain identification, monitoring for adverse effects, product format, storage and transport, and regulatory hurdles, a comprehensive literature search, covering the period 1966-2010 without restriction on the study design, was conducted, using the databases PubMed and EMBASE, and the proceedings of scientific conferences; these data were used in our updated systematic review.</p> <p>Results</p> <p>In this review, we present guidelines, including level of evidence, for the practical aspects (for example, strain selection, dose, duration, clinical and laboratory surveillance) of probiotic supplementation, and for dealing with non-clinical but important issues (for example, regulatory requirements, product format). Evidence was inadequate in some areas, and these should be a target for further research.</p> <p>Conclusion</p> <p>We hope that these evidence-based guidelines will help to optimise the use of probiotics in preterm neonates. Continued research is essential to provide answers to the current gaps in knowledge about probiotics.</p
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