90 research outputs found

    Recurrent transcriptional responses in AML and MDS patients treated with decitabine

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    The molecular events responsible for decitabine responses in myelodysplastic syndrome and acute myeloid leukemia patients are poorly understood. Decitabine has a short serum half-life and limited stability in tissue culture. Therefore, theoretical pharmacologic differences may exist between patient molecular changes in vitro and the consequences of in vivo treatment. To systematically identify the global genomic and transcriptomic alterations induced by decitabine in vivo, we evaluated primary bone marrow samples that were collected during patient treatment and applied whole-genome bisulfite sequencing, RNA-sequencing, and single-cell RNA sequencing. Decitabine induced global, reversible hypomethylation after 10 days of therapy in all patients, which was associated with induction of interferon-induced pathways, the expression of endogenous retroviral elements, and inhibition of erythroid-related transcripts, recapitulating many effects seen previously in in vitro studies. However, at relapse after decitabine treatment, interferon-induced transcripts remained elevated relative to day 0, but erythroid-related transcripts now were more highly expressed than at day 0. Clinical responses were not correlated with epigenetic or transcriptional signatures, although sample size and interpatient variance restricted the statistical power required for capturing smaller effects. Collectively, these data define global hypomethylation by decitabine and find that erythroid-related pathways may be relevant because they are inhibited by therapy and reverse at relapse

    Translating clinicians' beliefs into implementation interventions (TRACII) : a protocol for an intervention modeling experiment to change clinicians' intentions to implement evidence-based practice

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    Background: Biomedical research constantly produces new findings, but these are not routinely incorporated into health care practice. Currently, a range of interventions to promote the uptake of emerging evidence are available. While their effectiveness has been tested in pragmatic trials, these do not form a basis from which to generalise to routine care settings. Implementation research is the scientific study of methods to promote the uptake of research findings, and hence to reduce inappropriate care. As clinical practice is a form of human behaviour, theories of human behaviour that have proved to be useful in other settings offer a basis for developing a scientific rationale for the choice of interventions. Aims: The aims of this protocol are 1) to develop interventions to change beliefs that have already been identified as antecedents to antibiotic prescribing for sore throats, and 2) to experimentally evaluate these interventions to identify those that have the largest impact on behavioural intention and behavioural simulation. Design: The clinical focus for this work will be the management of uncomplicated sore throat in general practice. Symptoms of upper respiratory tract infections are common presenting features in primary care. They are frequently treated with antibiotics, and research evidence is clear that antibiotic treatment offers little or no benefit to otherwise healthy adult patients. Reducing antibiotic prescribing in the community by the "prudent" use of antibiotics is seen as one way to slow the rise in antibiotic resistance, and appears safe, at least in children. However, our understanding of how to do this is limited. Participants will be general medical practitioners. Two theory-based interventions will be designed to address the discriminant beliefs in the prescribing of antibiotics for sore throat, using empirically derived resources. The interventions will be evaluated in a 2 × 2 factorial randomised controlled trial delivered in a postal questionnaire survey. Two outcome measures will be assessed: behavioural intention and behavioural simulation.This study is funded by the European Commission Research Directorate as part of a multi-partner program: Research Based Education and Quality Improvement (ReBEQI): A Framework and tools to develop effective quality improvement programs in European healthcare. (Proposal No: QLRT-2001-00657)

    Variation in the Neisseria lactamica porin, and its relationship to meningococcal PorB

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    One potential vaccine strategy in the fight against meningococcal disease involves the exploitation of outer-membrane components of Neisseria lactamica, a commensal bacterium closely related to the meningococcus, Neisseria meningitidis. Although N. lactamica shares many surface structures with the meningococcus, little is known about the antigenic diversity of this commensal bacterium or the antigenic relationships between N. lactamica and N. meningitidis. Here, the N. lactamica porin protein (Por) was examined and compared to the related PorB antigens of N. meningitidis, to investigate potential involvement in anti-meningococcal immunity. Relationships among porin sequences were determined using distance-based methods and FST, and maximum-likelihood analyses were used to compare the selection pressures acting on the encoded proteins. These analyses demonstrated that the N. lactamica porin was less diverse than meningococcal PorB and although it was subject to positive selection, this was not as strong as the positive selection pressures acting on the meningococcal porin. In addition, the N. lactamica porin gene sequences and the protein sequences of the loop regions predicted to be exposed to the human immune system were dissimilar to the corresponding sequences in the meningococcus. This suggests that N. lactamica Por, contrary to previous suggestions, may have limited involvement in the development of natural immunity to meningococcal disease and might not be effective as a meningococcal vaccine component

    Grassroots Agency: Participation and Conflict in Buenos Aires Shantytowns seen through the Pilot Plan for Villa 7 (1971–1975)

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    open access articleIn 1971, after more than a decade of national and municipal policies aimed at the top-down removal of shantytowns, the Buenos Aires City Council approved the Plan Piloto para la Relocalización de Villa 7 (Pilot Plan for the Relocation of Shantytown 7; 1971–1975, referred to as the Pilot Plan hereinafter). This particular plan, which resulted in the construction of the housing complex, Barrio Justo Suárez, endures in the collective memory of Argentines as a landmark project regarding grassroots participation in state housing initiatives addressed at shantytowns. Emerging from a context of a housing shortage for the growing urban poor and intense popular mobilizations during the transition to democracy, the authors of the Pilot Plan sought to empower shantytown residents in novel ways by: 1) maintaining the shantytown’s location as opposed to eradication schemes that relocated the residents elsewhere, 2) formally employing some of the residents for the stage of construction, as opposed to “self-help” housing projects in which the residents contributed with unpaid labor, and 3) including them in the urban and architectural design of the of the new housing. This paper will examine the context in which the Pilot Plan was conceived of as a way of re-assessing the roles of the state, the user, and housing-related professionals, often seen as antagonistic. The paper argues that residents’ fair participation and state intervention in housing schemes are not necessarily incompatible, and can function in specific social and political contexts through multiactor proposals backed by a political will that prioritizes grassroots agency

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Analyzing and Biasing Simulations with PLUMED

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    This chapter discusses how the PLUMED plugin for molecular dynamics can be used to analyze and bias molecular dynamics trajectories. The chapter begins by introducing the notion of a collective variable and by then explaining how the free energy can be computed as a function of one or more collective variables. A number of practical issues mostly around periodic boundary conditions that arise when these types of calculations are performed using PLUMED are then discussed. Later parts of the chapter discuss how PLUMED can be used to perform enhanced sampling simulations that introduce simulation biases or multiple replicas of the system and Monte Carlo exchanges between these replicas. This section is then followed by a discussion on how free-energy surfaces and associated error bars can be extracted from such simulations by using weighted histogram and block averaging techniques

    A framework for human microbiome research

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    A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies
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