Using Dashboard Networks to Visualize Multiple Patient Histories: A Design Study on Post-operative Prostate Cancer

In this design study, we present a visualization technique that segments patients' histories instead of treating them as raw event sequences, aggregates the segments using criteria such as the whole history or treatment combinations, and then visualizes the aggregated segments as static dashboards that are arranged in a dashboard network to show longitudinal changes. The static dashboards were developed in nine iterations, to show 15 important attributes from the patients' histories. The final design was evaluated with five non-experts, five visualization experts and four medical experts, who successfully used it to gain an overview of a 2,000 patient dataset, and to make observations about longitudinal changes and differences between two cohorts. The research represents a step-change in the detail of large-scale data that may be successfully visualized using dashboards, and provides guidance about how the approach may be generalized

Methods and a research agenda for the evaluation of event sequence visualization techniques

The present paper asks how can visualization help data scientists make sense of event sequences, and makes three main contributions. The first is a research agenda, which we divide into methods for presentation, interaction & computation, and scale-up. Second, we introduce the concept of Event Maps to help with scale-up, and illustrate coarse-, medium- and fine-grained Event Maps with electronic health record (EHR) data for prostate cancer. Third, in an experiment we investigated participants’ ability to judge the similarity of event sequences. Contrary to previous research into categorical data, color and shape were better than position for encoding event type. However, even with simple sequences (5 events of 3 types in the target sequence), participants only got 88% correct despite averaging 7.4 seconds to respond. This indicates that simple visualization techniques are not effective

The Effect of Alignment on Peoples Ability to Judge Event Sequence Similarity

Event sequences are central to the analysis of data in domains that range from biology and health, to logfile analysis and people's everyday behavior. Many visualization tools have been created for such data, but people are error-prone when asked to judge the similarity of event sequences with basic presentation methods. This paper describes an experiment that investigates whether local and global alignment techniques improve people's performance when judging sequence similarity. Participants were divided into three groups (basic vs. local vs. global alignment), and each participant judged the similarity of 180 sets of pseudo-randomly generated sequences. Each set comprised a target, a correct choice and a wrong choice. After training, the global alignment group was more accurate than the local alignment group (98% vs. 93% correct), with the basic group getting 95% correct. Participants' response times were primarily affected by the number of event types, the similarity of sequences (measured by the Levenshtein distance) and the edit types (nine combinations of deletion, insertion and substitution). In summary, global alignment is superior and people's performance could be further improved by choosing alignment parameters that explicitly penalize sequence mismatches

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac

Regulation of normal B-cell differentiation and malignant B-cell survival by OCT2.

The requirement for the B-cell transcription factor OCT2 (octamer-binding protein 2, encoded by Pou2f2) in germinal center B cells has proved controversial. Here, we report that germinal center B cells are formed normally after depletion of OCT2 in a conditional knockout mouse, but their proliferation is reduced and in vivo differentiation to antibody-secreting plasma cells is blocked. This finding led us to examine the role of OCT2 in germinal center-derived lymphomas. shRNA knockdown showed that almost all diffuse large B-cell lymphoma (DLBCL) cell lines are addicted to the expression of OCT2 and its coactivator OCA-B. Genome-wide chromatin immunoprecipitation (ChIP) analysis and gene-expression profiling revealed the broad transcriptional program regulated by OCT2 that includes the expression of STAT3, IL-10, ELL2, XBP1, MYC, TERT, and ADA. Importantly, genetic alteration of OCT2 is not a requirement for cellular addiction in DLBCL. However, we detected amplifications of the POU2F2 locus in DLBCL tumor biopsies and a recurrent mutation of threonine 223 in the DNA-binding domain of OCT2. This neomorphic mutation subtly alters the DNA-binding preference of OCT2, leading to the transactivation of noncanonical target genes including HIF1a and FCRL3 Finally, by introducing mutations designed to disrupt the OCT2-OCA-B interface, we reveal a requirement for this protein-protein interface that ultimately might be exploited therapeutically. Our findings, combined with the predominantly B-cell-restricted expression of OCT2 and the absence of a systemic phenotype in our knockout mice, suggest that an OCT2-targeted therapeutic strategy would be efficacious in both major subtypes of DLBCL while avoiding systemic toxicity.This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. DJH was supported by a Kay Kendall Leukaemia Fund Intermediate Fellowship from the UK.This is the author accepted manuscript. The final version is available from the National Academy of Sciences via http://dx.doi.org/10.1073/pnas.160055711

Non-participation in population-based disease prevention programs in general practice

<p>Abstract</p> <p>Background</p> <p>The number of people with a chronic disease will strongly increase in the next decades. Therefore, prevention of disease becomes increasingly important. The aim of this systematic review was to identify factors that negatively influence participation in population-based disease prevention programs in General Practice and to establish whether the program type is related to non-participation levels.</p> <p>Methods</p> <p>We conducted a systematic review in Pubmed, EMBASE, CINAHL and PsycINFO, covering 2000 through July 6th 2012, to identify publications including information about characteristics of non-participants or reasons for non-participation in population-based disease prevention programs in General Practice.</p> <p>Results</p> <p>A total of 24 original studies met our criteria, seven of which focused on vaccination, eleven on screening aimed at early detection of disease, and six on screening aimed at identifying high risk of a disease, targeting a variety of diseases and conditions. Lack of personal relevance of the program, younger age, higher social deprivation and former non-participation were related to actual non-participation. No differences were found in non-participation levels or factors related to non-participation between the three program types. The large variation in non-participation levels within the program types may be partly due to differences in recruitment strategies, with more active, personalized strategies resulting in higher participation levels compared to an invitation letter.</p> <p>Conclusions</p> <p>There is still much to be gained by tailoring strategies to improve participation in those who are less likely to do so, namely younger individuals, those living in a deprived area and former non-participants. Participation may increase by applying more active recruitment strategies.</p

Transcriptional profiling of Epstein–Barr virus (EBV) genes and host cellular genes in nasal NK/T-cell lymphoma and chronic active EBV infection

Nasal NK/T-cell lymphoma is an aggressive subtype of non-Hodgkin lymphoma (NHL) that is closely associated with Epstein–Barr virus (EBV). The clonal expansion of EBV-infected NK or T cells is also seen in patients with chronic active EBV (CAEBV) infection, suggesting that two diseases might share a partially similar mechanism by which EBV affects host cellular gene expression. To understand the pathogenesis of EBV-associated NK/T-cell lymphoproliferative disorders (LPD) and design new therapies, we employed a novel EBV DNA microarray to compare patterns of EBV expression in six cell lines established from EBV-associated NK/T-cell LPD. We found that expression of BZLF1, which encodes the immediate-early gene product Zta, was expressed in SNK/T cells and the expression levels were preferentially high in cell lines from CAEBV infection. We also analyzsd the gene expression patterns of host cellular genes using a human oligonucleotide DNA microarray. We identified a subset of pathogenically and clinically relevant host cellular genes, including TNFRSF10D, CDK2, HSPCA, IL12A as a common molecular biological properties of EBV-associated NK/T-cell LPD and a subset of genes, such as PDCD4 as a putative contributor for disease progression. This study describes a novel approach from the aspects of viral and host gene expression, which could identify novel therapeutic targets in EBV-associated NK/T-cell LPD

Genomic deletion and promoter methylation status of Hypermethylated in Cancer 1 (HIC1) in mantle cell lymphoma

Mantle cell lymphomas (MCL), characterized by the t(11;14)(q13;q32), frequently carry secondary genetic alterations such as deletions in chromosome 17p involving the TP53 locus. Given that the association between TP53-deletions and concurrent mutations of the remaining allele is weak and based on our recent report that the Hypermethylated in Cancer 1 (HIC1) gene, that is located telomeric to the TP53 gene, may be targeted by deletions in 17p in diffuse large B-cell lymphoma (DLBCL), we investigated whether HIC1 inactivations might also occur in MCL. Monoallelic deletions of the TP53 locus were detected in 18 out of 59 MCL (31%), while overexpression of p53 protein occurred in only 8 out of 18 of these MCL (44%). In TP53-deleted MCL, the HIC1 gene locus was co-deleted in 11 out of 18 cases (61%). However, neither TP53 nor HIC1 deletions did affect survival of MCL patients. In most analyzed cases, no hypermethylation of the HIC1 exon 1A promoter was observed (17 out of 20, 85%). However, in MCL cell lines without HIC1-hypermethylation, the mRNA expression levels of HIC1 were nevertheless significantly reduced, when compared to reactive lymph node specimens, pointing to the occurrence of mechanisms other than epigenetic or genetic events for the inactivation of HIC1 in this entity

Towards a global participatory platform Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed

Towards a living earth simulator

The Living Earth Simulator (LES) is one of the core components of the FuturICT architecture. It will work as a federation of methods, tools, techniques and facilities supporting all of the FuturICT simulation-related activities to allow and encourage interactive exploration and understanding of societal issues. Society-relevant problems will be targeted by leaning on approaches based on complex systems theories and data science in tight interaction with the other components of FuturICT. The LES will evaluate and provide answers to realworld questions by taking into account multiple scenarios. It will build on present approaches such as agent-based simulation and modeling, multiscale modelling, statistical inference, and data mining, moving beyond disciplinary borders to achieve a new perspective on complex social systems. © The Author(s) 2012