Evaluating the informatics for integrating biology and the bedside system for clinical research

<p>Abstract</p> <p>Background</p> <p>Selecting patient cohorts is a critical, iterative, and often time-consuming aspect of studies involving human subjects; informatics tools for helping streamline the process have been identified as important infrastructure components for enabling clinical and translational research. We describe the evaluation of a free and open source cohort selection tool from the Informatics for Integrating Biology and the Bedside (i2b2) group: the i2b2 hive.</p> <p>Methods</p> <p>Our evaluation included the usability and functionality of the i2b2 hive using several real world examples of research data requests received electronically at the University of Utah Health Sciences Center between 2006 - 2008. The hive server component and the visual query tool application were evaluated for their suitability as a cohort selection tool on the basis of the types of data elements requested, as well as the effort required to fulfill each research data request using the i2b2 hive alone.</p> <p>Results</p> <p>We found the i2b2 hive to be suitable for obtaining estimates of cohort sizes and generating research cohorts based on simple inclusion/exclusion criteria, which consisted of about 44% of the clinical research data requests sampled at our institution. Data requests that relied on post-coordinated clinical concepts, aggregate values of clinical findings, or temporal conditions in their inclusion/exclusion criteria could not be fulfilled using the i2b2 hive alone, and required one or more intermediate data steps in the form of pre- or post-processing, modifications to the hive metadata, etc.</p> <p>Conclusion</p> <p>The i2b2 hive was found to be a useful cohort-selection tool for fulfilling common types of requests for research data, and especially in the estimation of initial cohort sizes. For another institution that might want to use the i2b2 hive for clinical research, we recommend that the institution would need to have structured, coded clinical data and metadata available that can be transformed to fit the logical data models of the i2b2 hive, strategies for extracting relevant clinical data from source systems, and the ability to perform substantial pre- and post-processing of these data.</p

The Role of Quantitative Pharmacology in an Academic Translational Research Environment

Translational research is generally described as the application of basic science discoveries to the treatment or prevention of disease or injury. Its value is usually determined based on the likelihood that exploratory or developmental research can yield effective therapies. While the pharmaceutical industry has evolved into a highly specialized sector engaged in translational research, the academic medical research community has similarly embraced this paradigm largely through the motivation of the National Institute of Health (NIH) via its Roadmap initiative. The Clinical and Translational Science Award (CTSA) has created opportunities for institutions which can provide the multidisciplinary environment required to engage such research. A key component of the CTSA and an element of both the NIH Roadmap and the FDA Critical Path is the bridging of bench and bedside science via quantitative pharmacologic relationships. The infrastructure of the University of Pennsylvania/Children’s Hospital of Philadelphia CTSA is highlighted relative to both research and educational objectives reliant upon quantitative pharmacology. A case study, NIH-sponsored research program exploring NK1r antagonism for the treatment NeuroAIDS is used to illustrate the application of quantitative pharmacology in a translational research paradigm

Cardiovascular magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine stress

Contains fulltext : 96698.pdf (publisher's version ) (Open Access)BACKGROUND: Dobutamine stress cardiovascular magnetic resonance (DS-CMR) is an established tool to assess hibernating myocardium and ischemia. Analysis is typically based on visual assessment with considerable operator dependency. CMR myocardial feature tracking (CMR-FT) is a recently introduced technique for tissue voxel motion tracking on standard steady-state free precession (SSFP) images to derive circumferential and radial myocardial mechanics.We sought to determine the feasibility and reproducibility of CMR-FT for quantitative wall motion assessment during intermediate dose DS-CMR. METHODS: 10 healthy subjects were studied at 1.5 Tesla. Myocardial strain parameters were derived from SSFP cine images using dedicated CMR-FT software (Diogenes MRI prototype; Tomtec; Germany). Right ventricular (RV) and left ventricular (LV) longitudinal strain (EllRV and EllLV) and LV long-axis radial strain (ErrLAX) were derived from a 4-chamber view at rest. LV short-axis circumferential strain (EccSAX) and ErrSAX; LV ejection fraction (EF) and volumes were analyzed at rest and during dobutamine stress (10 and 20 mug . kg(1). min(1)). RESULTS: In all volunteers strain parameters could be derived from the SSFP images at rest and stress. EccSAX values showed significantly increased contraction with DSMR (rest: -24.1 +/- 6.7; 10 mug: -32.7 +/- 11.4; 20 mug: -39.2 +/- 15.2; p < 0.05). ErrSAX increased significantly with dobutamine (rest: 19.6 +/- 14.6; 10 mug: 31.8 +/- 20.9; 20 mug: 42.4 +/- 25.5; p < 0.05). In parallel with these changes; EF increased significantly with dobutamine (rest: 56.9 +/- 4.4%; 10 mug: 70.7 +/- 8.1; 20 mug: 76.8 +/- 4.6; p < 0.05). Observer variability was best for LV circumferential strain (EccSAX ) and worst for RV longitudinal strain (EllRV) as determined by 95% confidence intervals of the difference. CONCLUSIONS: CMR-FT reliably detects quantitative wall motion and strain derived from SSFP cine imaging that corresponds to inotropic stimulation. The current implementation may need improvement to reduce observer-induced variance. Within a given CMR lab; this novel technique holds promise of easy and fast quantification of wall mechanics and strain

A stimulus to define informatics and health information technology

<p>Abstract</p> <p>Background</p> <p>Despite the growing interest by leaders, policy makers, and others, the terminology of health information technology as well as biomedical and health informatics is poorly understood and not even agreed upon by academics and professionals in the field.</p> <p>Discussion</p> <p>The paper, presented as a Debate to encourage further discussion and disagreement, provides definitions of the major terminology used in biomedical and health informatics and health information technology. For informatics, it focuses on the words that modify the term as well as individuals who practice the discipline. Other categories of related terms are covered as well, from the associated disciplines of computer science, information technolog and health information management to the major application categories of applications used. The discussion closes with a classification of individuals who work in the largest segment of the field, namely clinical informatics.</p> <p>Summary</p> <p>The goal of presenting in Debate format is to provide a starting point for discussion to reach a documented consensus on the definition and use of these terms.</p

Word add-in for ontology recognition: semantic enrichment of scientific literature

<p>Abstract</p> <p>Background</p> <p>In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles.</p> <p>Results</p> <p>The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at <url>http://www.codeplex.com/UCSDBioLit</url>.</p> <p>Conclusions</p> <p>The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata.</p

CD4-Independent Human Immunodeficiency Virus Infection Involves Participation of Endocytosis and Cathepsin B

During a comparison of the infectivity of mNDK, a CD4-independent human immunodeficiency virus type 1 (HIV-1) strain, to various cell lines, we found that HeLa cells were much less susceptible than 293T and TE671 cells. Hybridoma cells between HeLa and 293T cells were as susceptible as 293T cells, suggesting that cellular factors enhance the mNDK infection in 293T cells. By screening a cDNA expression library in HeLa cells, cystatin C was isolated as an enhancer of the mNDK infection. Because cathepsin B protease, a natural ligand of cystatin C, was upregulated in HeLa cells, we speculated that the high levels of cathepsin B activities were inhibitory to the CD4-independent infection and that cystatin C enhanced the infection by impairing the excessive cathepsin B activity. Consistent with this idea, pretreatment of HeLa cells with 125 µM of CA-074Me, a cathepsin B inhibitor, resulted in an 8-fold enhancement of the mNDK infectivity. Because cathepsin B is activated by low pH in acidic endosomes, we further examined the potential roles of endosomes in the CD4-independent infection. Suppression of endosome acidification or endocytosis by inhibitors or by an Eps15 dominant negative mutant reduced the infectivity of mNDK in which CD4-dependent infections were not significantly impaired. Taken together, these results suggest that endocytosis, endosomal acidification, and cathepsin B activity are involved in the CD4-independent entry of HIV-1

Factors influencing the participation of gastroenterologists and hepatologists in clinical research

<p>Abstract</p> <p>Background</p> <p>Although clinical research is integral to the advancement of medical knowledge, physicians face a variety of obstacles to their participation as investigators in clinical trials. We examined factors that influence the participation of gastroenterologists and hepatologists in clinical research.</p> <p>Methods</p> <p>We surveyed 1050 members of the American Association for the Study of Liver Diseases regarding their participation in clinical research. We compared the survey responses by specialty and level of clinical trial experience.</p> <p>Results</p> <p>A majority of the respondents (71.6%) reported involvement in research activities. Factors most influential in clinical trial participation included funding and compensation (88.3%) and intellectual pursuit (87.8%). Barriers to participation were similar between gastroenterologists (n = 160) and hepatologists (n = 189) and between highly experienced (n = 62) and less experienced (n = 159) clinical researchers. These barriers included uncompensated research costs and lack of specialized support. Industry marketing was a greater influence among respondents with less trial experience, compared to those with extensive experience (15.7% vs 1.6%; <it>P </it>< .01). Hepatologists and respondents with extensive clinical trial experience tended to be more interested in phase 1 and 2 studies, whereas gastroenterologists and less experienced investigators were more interested in phase 4 studies.</p> <p>Conclusion</p> <p>This study suggests that the greatest barrier to participation in clinical research is lack of adequate resources. Respondents also favored industry-sponsored research with less complex trial protocols and studies of relatively short duration.</p

Assembling a global database of malaria parasite prevalence for the Malaria Atlas Project

BACKGROUND: Open access to databases of information generated by the research community can synergize individual efforts and are epitomized by the genome mapping projects. Open source models for outputs of scientific research funded by tax-payers and charities are becoming the norm. This has yet to be extended to malaria epidemiology and control. METHODS: The exhaustive searches and assembly process for a global database of malaria parasite prevalence as part of the Malaria Atlas Project (MAP) are described. The different data sources visited and how productive these were in terms of availability of parasite rate (PR) data are presented, followed by a description of the methods used to assemble a relational database and an associated geographic information system. The challenges facing spatial data assembly from varied sources are described in an effort to help inform similar future applications. RESULTS: At the time of writing, the MAP database held 3,351 spatially independent PR estimates from community surveys conducted since 1985. These include 3,036 Plasmodium falciparum and 1,347 Plasmodium vivax estimates in 74 countries derived from 671 primary sources. More than half of these data represent malaria prevalence after the year 2000. CONCLUSION: This database will help refine maps of the global spatial limits of malaria and be the foundation for the development of global malaria endemicity models as part of MAP. A widespread application of these maps is envisaged. The data compiled and the products generated by MAP are planned to be released in June 2009 to facilitate a more informed approach to global malaria control