BackgroundIsoproterenol-induced cardiac hypertrophy in mice has been used in a number of studies to model human cardiac disease. In this study, we compared the transcriptional response of the heart in this model to other animal models of heart failure, as well as to the transcriptional response of human hearts suffering heart failure.ResultsWe performed microarray analyses on RNA from mice with isoproterenol-induced cardiac hypertrophy and mice with exercise-induced physiological hypertrophy and identified 865 and 2,534 genes that were significantly altered in pathological and physiological cardiac hypertrophy models, respectively. We compared our results to 18 different microarray data sets (318 individual arrays) representing various other animal models and four human cardiac diseases and identified a canonical set of 64 genes that are generally altered in failing hearts. We also produced a pairwise similarity matrix to illustrate relatedness of animal models with human heart disease and identified ischemia as the human condition that most resembles isoproterenol treatment.ConclusionThe overall patterns of gene expression are consistent with observed structural and molecular differences between normal and maladaptive cardiac hypertrophy and support a role for the immune system (or immune cell infiltration) in the pathology of stress-induced hypertrophy. Cross-study comparisons such as the results presented here provide targets for further research of cardiac disease that might generally apply to maladaptive cardiac stresses and are also a means of identifying which animal models best recapitulate human disease at the transcriptional level.
eTBLAST, an automated citation matching tool, and Déjà vu, the duplicate citation database, are freely available at http://invention.swmed.edu/ and http://spore.swmed.edu/dejavu
Authors, editors and reviewers alike use the biomedical literature to identify appropriate journals in which to publish, potential reviewers for papers or grants, and collaborators (or competitors) with similar interests. Traditionally, this process has either relied upon personal expertise and knowledge or upon a somewhat unsystematic and laborious process of manually searching through the literature for trends. To help with these tasks, we report three utilities that parse and summarize the results of an abstract similarity search to find appropriate journals for publication, authors with expertise in a given field, and documents similar to a submitted query. The utilities are based upon a program, eTBLAST, designed to identify similar documents within literature databases such as (but not limited to) MEDLINE. These services are freely accessible through the Internet at http://invention.swmed.edu/etblast/etblast.shtml, where users can upload a file or paste text such as an abstract into the browser interface.
In the scientific research community, plagiarism and covert multiple publications of the same data are considered unacceptable because they undermine the public confidence in the scientific integrity. Yet, little has been done to help authors and editors to identify highly similar citations, which sometimes may represent cases of unethical duplication. For this reason, we have made available Déjà vu, a publicly available database of highly similar Medline citations identified by the text similarity search engine eTBLAST. Following manual verification, highly similar citation pairs are classified into various categories ranging from duplicates with different authors to sanctioned duplicates. Déjà vu records also contain user-provided commentary and supporting information to substantiate each document's categorization. Déjà vu and eTBLAST are available to authors, editors, reviewers, ethicists and sociologists to study, intercept, annotate and deter questionable publication practices. These tools are part of a sustained effort to enhance the quality of Medline as ‘the’ biomedical corpus. The Déjà vu database is freely accessible at http://spore.swmed.edu/dejavu. The tool eTBLAST is also freely available at http://etblast.org.
The United States Food and Drug Administration-approved antibiotic doxycycline (DOX) inhibits matrix metalloproteases, which contribute to the development of cardiac hypertrophy (CH). We hypothesized that DOX might serve as a treatment for CH. The efficacy of DOX was tested in two mouse models of CH: induced by the -adrenergic agonist isoproterenol (ISO) and induced by transverse aortic banding. DOX significantly attenuated CH in these models, causing a profound reduction of the hypertrophic phenotype and a lower heart/body weight ratio (p Ͻ 0.05, n Ն 6). As expected, ISO increased matrix metalloprotease (MMP) 2 and 9 activities, and administration of DOX reversed this effect. Transcriptional profiles of normal, ISO-, and ISO ϩ DOX-treated mice were examined using microarrays, and the results were confirmed by real-time reverse transcriptase-polymerase chain reaction. Genes (206) were differentially expressed between normal and ISO mice that were reversibly altered between ISO-and ISO ϩ DOX-treated mice, indicating their potential role in CH development and DOX-induced improvement. These genes included those involved in the regulation of cell proliferation and fate, stress, and immune responses, cytoskeleton and extracellular matrix organization, and cardiac-specific signal transduction. The overall gene expression profile suggested that MMP2/9 inactivation was not the only mechanism whereby DOX exerts its beneficial effects. Western blot analysis identified potential signaling events associated with CH, including up-regulation of endothelial differentiation sphingolipid G-protein-coupled receptor 1 receptor and activation of extracellular signal-regulated kinase, p38, and the transcription factor activating transcription factor-2, which were reduced after administration of DOX. These results suggest that DOX might be evaluated as a potential CH therapeutic and also provide potential signaling mechanisms to investigate in the context of CH phenotype development and regression.
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