Immunological network signatures of cancer progression and survival

<p>Abstract</p> <p>Background</p> <p>The immune contribution to cancer progression is complex and difficult to characterize. For example in tumors, immune gene expression is detected from the combination of normal, tumor and immune cells in the tumor microenvironment. Profiling the immune component of tumors may facilitate the characterization of the poorly understood roles immunity plays in cancer progression. However, the current approaches to analyze the immune component of a tumor rely on incomplete identification of immune factors.</p> <p>Methods</p> <p>To facilitate a more comprehensive approach, we created a ranked immunological relevance score for all human genes, developed using a novel strategy that combines text mining and information theory. We used this score to assign an immunological grade to gene expression profiles, and thereby quantify the immunological component of tumors. This immunological relevance score was benchmarked against existing manually curated immune resources as well as high-throughput studies. To further characterize immunological relevance for genes, the relevance score was charted against both the human interactome and cancer information, forming an expanded interactome landscape of tumor immunity. We applied this approach to expression profiles in melanomas, thus identifying and grading their immunological components, followed by identification of their associated protein interactions.</p> <p>Results</p> <p>The power of this strategy was demonstrated by the observation of early activation of the adaptive immune response and the diversity of the immune component during melanoma progression. Furthermore, the genome-wide immunological relevance score classified melanoma patient groups, whose immunological grade correlated with clinical features, such as immune phenotypes and survival.</p> <p>Conclusions</p> <p>The assignment of a ranked immunological relevance score to all human genes extends the content of existing immune gene resources and enriches our understanding of immune involvement in complex biological networks. The application of this approach to tumor immunity represents an automated systems strategy that quantifies the immunological component in complex disease. In so doing, it stratifies patients according to their immune profiles, which may lead to effective computational prognostic and clinical guides.</p

Quantifying Cost-Effectiveness of Controlling Nosocomial Spread of Antibiotic-Resistant Bacteria: The Case of MRSA

BACKGROUND: The costs and benefits of controlling nosocomial spread of antibiotic-resistant bacteria are unknown. METHODS: We developed a mathematical algorithm to determine cost-effectiveness of infection control programs and explored the dynamical interactions between different epidemiological variables and cost-effectiveness. The algorithm includes occurrence of nosocomial infections, attributable mortality, costs and efficacy of infection control and how antibiotic-resistant bacteria affect total number of infections: do infections with antibiotic-resistant bacteria replace infections caused by susceptible bacteria (replacement scenario) or occur in addition to them (addition scenario). Methicillin-resistant Staphylococcus aureus (MRSA) bacteremia was used for illustration using observational data on S. aureus bacteremia (SAB) in our hospital (n = 189 between 2001-2004, all being methicillin-susceptible S. aureus [MSSA]). RESULTS: In the replacement scenario, the costs per life year gained range from 45,912 euros to 6590 euros for attributable mortality rates ranging from 10% to 50%. Using 20,000 euros per life year gained as a threshold, completely preventing MRSA would be cost-effective in the replacement scenario if attributable mortality of MRSA is > or = 21%. In the addition scenario, infection control would be cost saving along the entire range of estimates for attributable mortality. CONCLUSIONS: Cost-effectiveness of controlling antibiotic-resistant bacteria is highly sensitive to the interaction between infections caused by resistant and susceptible bacteria (addition or replacement) and attributable mortality. In our setting, controlling MRSA would be cost saving for the addition scenario but would not be cost-effective in the replacement scenario if attributable mortality would be < 21%

Comparison of Gene Expression Profiles in Chromate Transformed BEAS-2B Cells

Hexavalent chromium [Cr(VI)] is a potent human carcinogen. Occupational exposure has been associated with increased risk of respiratory cancer. Multiple mechanisms have been shown to contribute to Cr(VI) induced carcinogenesis, including DNA damage, genomic instability, and epigenetic modulation, however, the molecular mechanism and downstream genes mediating chromium's carcinogenicity remain to be elucidated.We established chromate transformed cell lines by chronic exposure of normal human bronchial epithelial BEAS-2B cells to low doses of Cr(VI) followed by anchorage-independent growth. These transformed cell lines not only exhibited consistent morphological changes but also acquired altered and distinct gene expression patterns compared with normal BEAS-2B cells and control cell lines (untreated) that arose spontaneously in soft agar. Interestingly, the gene expression profiles of six Cr(VI) transformed cell lines were remarkably similar to each other yet differed significantly from that of either control cell lines or normal BEAS-2B cells. A total of 409 differentially expressed genes were identified in Cr(VI) transformed cells compared to control cells. Genes related to cell-to-cell junction were upregulated in all Cr(VI) transformed cells, while genes associated with the interaction between cells and their extracellular matrices were down-regulated. Additionally, expression of genes involved in cell proliferation and apoptosis were also changed.This study is the first to report gene expression profiling of Cr(VI) transformed cells. The gene expression changes across individual chromate exposed clones were remarkably similar to each other but differed significantly from the gene expression found in anchorage-independent clones that arose spontaneously. Our analysis identified many novel gene expression changes that may contribute to chromate induced cell transformation, and collectively this type of information will provide a better understanding of the mechanism underlying chromate carcinogenicity

Performance measures of the specialty referral process: a systematic review of the literature

<p>Abstract</p> <p>Background</p> <p>Performance of specialty referrals is coming under scrutiny, but a lack of identifiable measures impedes measurement efforts. The objective of this study was to systematically review the literature to identify published measures that assess specialty referrals.</p> <p>Methods</p> <p>We performed a systematic review of the literature for measures of specialty referral. Searches were made of MEDLINE and HealthSTAR databases, references of eligible papers, and citations provided by content experts. Measures were eligible if they were published from January 1973 to June 2009, reported on validity and/or reliability of the measure, and were applicable to Organization for Economic Cooperation and Development healthcare systems. We classified measures according to a conceptual framework, which underwent content validation with an expert panel.</p> <p>Results</p> <p>We identified 2,964 potentially eligible papers. After abstract and full-text review, we selected 214 papers containing 244 measures. Most measures were applied in adults (57%), assessed structural elements of the referral process (60%), and collected data via survey (62%). Measures were classified into non-mutually exclusive domains: need for specialty care (N = 14), referral initiation (N = 73), entry into specialty care (N = 53), coordination (N = 60), referral type (N = 3), clinical tasks (N = 19), resource use (N = 13), quality (N = 57), and outcomes (N = 9).</p> <p>Conclusions</p> <p>Published measures are available to assess the specialty referral process, although some domains are limited. Because many of these measures have been not been extensively validated in general populations, assess limited aspects of the referral process, and require new data collection, their applicability and preference in assessment of the specialty referral process is needed.</p

Functional Connectivity fMRI of the Rodent Brain: Comparison of Functional Connectivity Networks in Rat and Mouse

At present, resting state functional MRI (rsfMRI) is increasingly used in human neuropathological research. The present study aims at implementing rsfMRI in mice, a species that holds the widest variety of neurological disease models. Moreover, by acquiring rsfMRI data with a comparable protocol for anesthesia, scanning and analysis, in both rats and mice we were able to compare findings obtained in both species. The outcome of rsfMRI is different for rats and mice and depends strongly on the applied number of components in the Independent Component Analysis (ICA). The most important difference was the appearance of unilateral cortical components for the mouse resting state data compared to bilateral rat cortical networks. Furthermore, a higher number of components was needed for the ICA analysis to separate different cortical regions in mice as compared to rats

Organizational interventions employing principles of complexity science have improved outcomes for patients with Type II diabetes

<p>Abstract</p> <p>Background</p> <p>Despite the development of several models of care delivery for patients with chronic illness, consistent improvements in outcomes have not been achieved. These inconsistent results may be less related to the content of the models themselves, but to their underlying conceptualization of clinical settings as linear, predictable systems. The science of complex adaptive systems (CAS), suggests that clinical settings are non-linear, and increasingly has been used as a framework for describing and understanding clinical systems. The purpose of this study is to broaden the conceptualization by examining the relationship between interventions that leverage CAS characteristics in intervention design and implementation, and effectiveness of reported outcomes for patients with Type II diabetes.</p> <p>Methods</p> <p>We conducted a systematic review of the literature on organizational interventions to improve care of Type II diabetes. For each study we recorded measured process and clinical outcomes of diabetic patients. Two independent reviewers gave each study a score that reflected whether organizational interventions reflected one or more characteristics of a complex adaptive system. The effectiveness of the intervention was assessed by standardizing the scoring of the results of each study as 0 (no effect), 0.5 (mixed effect), or 1.0 (effective).</p> <p>Results</p> <p>Out of 157 potentially eligible studies, 32 met our eligibility criteria. Most studies were felt to utilize at least one CAS characteristic in their intervention designs, and ninety-one percent were scored as either "mixed effect" or "effective." The number of CAS characteristics present in each intervention was associated with effectiveness (p = 0.002). Two individual CAS characteristics were associated with effectiveness: interconnections between participants and co-evolution.</p> <p>Conclusion</p> <p>The significant association between CAS characteristics and effectiveness of reported outcomes for patients with Type II diabetes suggests that complexity science may provide an effective framework for designing and implementing interventions that lead to improved patient outcomes.</p

Network Structure Implied by Initial Axon Outgrowth in Rodent Cortex: Empirical Measurement and Models

The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains

Revisiting interaction in knowledge translation

Abstract Background Although the study of research utilization is not new, there has been increased emphasis on the topic over the recent past. Science push models that are researcher driven and controlled and demand pull models emphasizing users/decision-maker interests have largely been abandoned in favour of more interactive models that emphasize linkages between researchers and decisionmakers. However, despite these and other theoretical and empirical advances in the area of research utilization, there remains a fundamental gap between the generation of research findings and the application of those findings in practice. Methods Using a case approach, the current study looks at the impact of one particular interaction approach to research translation used by a Canadian funding agency. Results Results suggest there may be certain conditions under which different levels of decisionmaker involvement in research will be more or less effective. Four attributes are illuminated by the current case study: stakeholder diversity, addressability/actionability of results, finality of study design and methodology, and politicization of results. Future research could test whether these or other variables can be used to specify some of the conditions under which different approaches to interaction in knowledge translation are likely to facilitate research utilization. Conclusion This work suggests that the efficacy of interaction approaches to research translation may be more limited than current theory proposes and underscores the need for more completely specified models of research utilization that can help address the slow pace of change in this area.</p

Hearing aid effectiveness after aural rehabilitation - individual versus group (HEARING) trial: RCT design and baseline characteristics

<p>Abstract</p> <p>Background</p> <p>Hearing impairment is the most common body system disability in veterans. In 2008, nearly 520,000 veterans had a disability for hearing loss through the Department of Veterans Affairs (VA). Changes in eligibility for hearing aid services, along with the aging population, contributed to a greater than 300% increase in the number of hearing aids dispensed from 1996 to 2006. In 2006, the VA committed to having no wait times for patient visits while providing quality clinically-appropriate care. One approach to achieving this goal is the use of group visits as an alternative to individual visits. We sought to determine: 1) if group hearing aid fitting and follow-up visits were at least as effective as individual visits, and 2) whether group visits lead to cost savings through the six month period after the hearing aid fitting. We describe the rationale, design, and characteristics of the baseline cohort of the first randomized clinical trial to study the impact of group versus individual hearing aid fitting and follow-up visits.</p> <p>Methods</p> <p>Participants were recruited from the VA Puget Sound Health Care System Audiology Clinic. Eligible patients had no previous hearing aid use and monaural or binaural air-conduction hearing aids were ordered at the evaluation visit. Participants were randomized to receive the hearing aid fitting and the hearing aid follow-up in an individual or group visit. The primary outcomes were hearing-related function, measured with the first module of the Effectiveness of Aural Rehabilitation (Inner EAR), and hearing aid adherence. We tracked the total cost of planned and unplanned audiology visits over the 6-month interval after the hearing aid fitting.</p> <p>Discussion</p> <p>A cohort of 659 participants was randomized to receive group or individual hearing aid fitting and follow-up visits. Baseline demographic and self-reported health status and hearing-related measures were evenly distributed across the treatment arms.</p> <p>Outcomes after the 6-month follow-up period are needed to determine if group visits were as least as good as those for individual visits and will be reported in subsequent publication.</p> <p>Trial Registration</p> <p>NCT00260663</p