Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Electronic Techtonics: Thinking at the Interface

This volume originated in HASTAC’s first international conference, “Electronic Techtonics: Thinking at the Interface,” held at Duke University during April 19-21, 2007. “Electronic Techtonics” was the site of truly unforgettable conversations and encounters that traversed domains, disciplines, and media – conversations that explored the fluidity of technology both as interface as well as at the interface. This hardcopy version of the conference proceedings is published in conjunction with its electronic counterpart (found at www.hastac.org). Both versions exist as records of the range and depth of conversations that took place at the conference. Some of the papers in this volume are almost exact records of talks given at the conference, while others are versions that were revised and reworked some time after the conference. These papers are drawn from a variety of fields and we have not made an effort to homogenize them in any way, but have instead retained the individual format and style of each author.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

Reducing Electronic Information Overload

College students receive a wealth of information through electronic communications that they are unable to process efficiently. This information overload negatively impacts their affect, which is officially defined in the field of psychology as the experience of feeling or emotion. To address this problem, we postulated that we could create an application that organizes and presents incoming content in a manner that optimizes users’ ability to process information. First, we conducted surveys that quantitatively measured each participant’s psychological affect while handling electronic communications, which was used to tailor the features of the application to what the user’s desire. After designing and implementing the application, we again measured the user's affect using this product. Our goal was to find that the program promoted a positive change in affect. Our application, Brevitus, was able to match Gmail on affect reduction profiles, while succeeding in implementing certain user interface specifications.

Development of a GEM Electronic Board (GEB) for triple-GEM detectors

Developed for use with triple GEM detectors, the GEM Electronic Board (GEB) forms a crucial part of the electronics readout system being developed as part of the CMS muon upgrade program. The objective of the GEB is threefold; to provide stable powering and ground for the VFAT3 front ends, to enable high-speed communication between 24 VFAT3 front ends and an optohybrid, and to shield the GEM detector from electromagnetic interference. The paper describes the concept and design of a large-size GEB in detail, highlighting the challenges in terms of design and feasibility of this deceptively difficult system component.

Immunological Signatures Identifying Different Stages of Latent Mycobacterium tuberculosis Infection and Discriminating Latent from Active Tuberculosis in Humans

Objectives: One third of the world population is considered latently infected with Mycobacterium tuberculosis(LTBI) and sterilizing this reservoir of bacteria that may reactivate is required for tuberculosis (TB) elimination. Thegroup of individuals with LTBI is heterogeneous with some of them being more at risk to develop TB disease thanothers. Improved diagnosis of subjects with LTBI is needed, allowing to differentiate subjects with LTBI from thosewith active TB, and to select among LTBI subjects those who are more at risk to develop active TB. We havecharacterized at the cellular level both the quantitative and qualitative T cell responses to different mycobacterialantigens in selected populations of infected subjects in order to identify new biomarkers that could help to identify M.tuberculosis-infected subjects and to stratify them in risk groups for reactivation of the infection.Methods: Lymphoblast frequencies and cytokine production (IFN-γ, TNF-α, IL-2) among CD4+ and CD8+ T cellswere analyzed by flow cytometry after in vitro stimulation with the latency antigen heparin-binding haemagglutinin(HBHA) or early-secreted antigen Target-6 (ESAT-6) of peripheral blood mononuclear cells from clinically wellcharacterized M. tuberculosis-infected humans (28 LTBI, 22 TB disease,12 controls). The LTBI group definedaccording to the Center for Disease Control guidelines was subdivided into QuantiFERON-TB Gold in-Tube (QFT)positive and negative subgroups.Results: Similar to TB patients, QFT+ LTBI subjects had higher proportions of HBHA-induced TNF-αsingle+ CD4+lymphocytes than QFT- LTBI subjects (p<0.05). Compared to LTBI subjects, TB patients had higher frequencies ofESAT-6-induced CD8+ lymphoblasts (p<0.001), higher proportions of ESAT-6-induced IFN-γ+TNF-α+ CD4+ Tlymphocytes (p<0.05), and lower proportions of HBHA-induced IFN-γ+TNF-α+IL-2+ (p<0.05) CD4+ T lymphocytes.Conclusions: These data provide new biomarkers to discriminate active TB from LTBI, and more interestingly,help to identify LTBI subjects with increased likelihood to develop TB disease.

Flo/Stress: an integrated software module to predict stress in electronic products

Software technology that predicts stress in electronic systems and packages, developed as part of TCS Programme, is described. The software is closely integrated within a thermal design tool providing the ability to simulate the coupled effects of airflow, temperature and stress on product performance. This integrated approach to analysis will help decrease the number of design cycles.

Optimization and finite element analysis for reliable electronic packaging

This paper demonstrates a modeling and design approach that couples computational mechanics techniques with numerical optimisation and statistical models for virtual prototyping and testing in different application areas concerning reliability of eletronic packages. The integrated software modules provide a design engineer in the electronic manufacturing sector with fast design and process solutions by optimizing key parameters and taking into account complexity of certain operational conditions. The integrated modeling framework is obtained by coupling the multi-phsyics finite element framework - PHYSICA - with the numerical optimisation tool - VisualDOC into a fully automated design tool for solutions of electronic packaging problems. Response Surface Modeling Methodolgy and Design of Experiments statistical tools plus numerical optimisaiton techniques are demonstrated as a part of the modeling framework. Two different problems are discussed and solved using the integrated numerical FEM-Optimisation tool. First, an example of thermal management of an electronic package on a board is illustrated. Location of the device is optimized to ensure reduced junction temperature and stress in the die subject to certain cooling air profile and other heat dissipating active components. In the second example thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and subsequently used to optimise the life-time of solder interconnects under thermal cycling.

Turbulence modelling and its effects on electronic systems

This paper presents simulated computational fluid dynamics (CFD) results for comparison against experimental data. The performance of four turbulence models has been assessed for electronic application areas considering both fluid flow and heat transfer phenomenon. CFD is vast becoming a powerful and almost essential tool for design, development and optimization in engineering problems. However turbulence models remain to be the key problem issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the performance of the turbulence model employed together with the wall functions implemented. To be able to resolve the abrupt changes in the turbulent energy and other parameters near the wall a particularly fine mesh is necessary which unfortunately increases the computer storage capacity requirements. The objective of turbulence modelling is to enhance computational procdures of sufficient acccuracy and generality for engineers to anticipate the Reynolds stresses and the scalar transport terms.

Turbulence modelling for thermal management of electronic systems

The electronics industry is developing rapidly together with the increasingly complex problem of microelectronic equipment cooling. It has now become necessary for thermal design engineers to consider the problem of equipment cooling at some level. The use of Computational Fluid Dynamics (CFD) for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimisation of engineering applications. However turbulence models remain a key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. This paper will discuss results from an investigation into the accuract of currently used turbulence models. Also a newly formulated transitional hybrid turbulence model will be introduced with comparisonsaagainst experimental data.

Collaborating components in mesh-based electronic packaging

From the model geometry creation to the model analysis, the stages in between such as mesh generation are the most manpower intensive phase in a mesh-based computational mechanics simulation process. On the other hand the model analysis is the most computing intensive phase. Advanced computational hardware and software have significantly reduced the computing time - and more importantly the trend is downward. With the kind of models envisaged coming, which are larger, more complex in geometry and modelling, and multiphysics, there is no clear trend that the manpower intensive phase is to decrease significantly in time - in the present way of operation it is more likely to increase with model complexity. In this paper we address this dilemma in collaborating components for models in electronic packaging application.

Computational modeling techniques for reliability of electronic components on printed circuit boards

This paper describes modeling technology and its use in providing data governing the assembly and subsequent reliability of electronic chip components on printed circuit boards (PCBs). Products, such as mobile phones, camcorders, intelligent displays, etc., are changing at a tremendous rate where newer technologies are being applied to satisfy the demands for smaller products with increased functionality. At ever decreasing dimensions, and increasing number of input/output connections, the design of these components, in terms of dimensions and materials used, is playing a key role in determining the reliability of the final assembly. Multiphysics modeling techniques are being adopted to predict a range of interacting physics-based phenomena associated with the manufacturing process. For example, heat transfer, solidification, marangoni fluid flow, void movement, and thermal-stress. The modeling techniques used are based on finite volume methods that are conservative and take advantage of being able to represent the physical domain using an unstructured mesh. These techniques are also used to provide data on thermal induced fatigue which is then mapped into product lifetime predictions.

Low Reynolds number turbulence models for accurate thermal simulations of electronic components

The electronics industry and the problems associated with the cooling of microelectronic equipment are developing rapidly. Thermal engineers now find it necessary to consider the complex area of equipment cooling at some level. This continually growing industry also faces heightened pressure from consumers to provide electronic product miniaturization, which in itself increases the demand for accurate thermal management predictions to assure product reliability. Computational fluid dynamics (CFD) is considered a powerful and almost essential tool for the design, development and optimization of engineering applications. CFD is now widely used within the electronics packaging design community to thermally characterize the performance of both the electronic component and system environment. This paper discusses CFD results for a large variety of investigated turbulence models. Comparison against experimental data illustrates the predictive accuracy of currently used models and highlights the growing demand for greater mathematical modelling accuracy with regards to thermal characterization. Also a newly formulated low Reynolds number (i.e. transitional) turbulence model is proposed with emphasis on hybrid techniques.

Turbulence modelling and its impact on CFD predictions for cooling of electronic components

This paper will discuss Computational Fluid Dynamics (CFD) results from an investigation into the accuracy of several turbulence models to predict air cooling for electronic packages and systems. Also new transitional turbulence models will be proposed with emphasis on hybrid techniques that use the k-ε model at an appropriate distance away from the wall and suitable models, with wall functions, near wall regions. A major proportion of heat emitted from electronic packages can be extracted by air cooling. This flow of air throughout an electronic system and the heat extracted is highly dependent on the nature of turbulence present in the flow. The use of CFD for such investigations is fast becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However turbulence models remain a key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt fluctuations experienced by the turbulent energy and other parameters located at near wall regions and shear layers a particularly fine computational mesh is necessary which inevitably increases the computer storage and run-time requirements. The PHYSICA Finite Volume code was used for this investigation. With the exception of the k-ε and k-ω models which are available as standard within PHYSICA, all other turbulence models mentioned were implemented via the source code by the authors. The LVEL, LVEL CAP, Wolfshtein, k-ε, k-ω, SST and kε/kl models are described and compared with experimental data.