199 research outputs found

    Prevalence of myocardial hypertrophy in a population of asymptomatic Swedish Maine coon cats

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    <p>Abstract</p> <p>Background</p> <p>Maine coon cats have a familial disposition for developing hypertrophic cardiomyopathy (HCM) with evidence of an autosomal dominant mode of inheritance <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. The current mode to diagnose HCM is by use of echocardiography. However, definite reference criteria have not been established. The objective of the study was to determine the prevalence of echocardigraphic changes consistent with hypertrophic cardiomyopathy in Swedish Maine coon cats, and to compare echocardiographic measurements with previously published reference values.</p> <p>Methods</p> <p>All cats over the age of 8 months owned by breeders living in Stockholm, listed on the website of the Maine Coon breeders in Sweden by February 2001, were invited to participate in the study. Physical examination and M-mode and 2D echocardiographic examinations were performed in all cats.</p> <p>Results</p> <p>Examinations of 42 asymptomatic Maine coon cats (10 males and 32 females) were performed. The age of the cats ranged from 0,7 to 9,3 years with a mean of 4,8 ± 2,3 years. Four cats (9,5%) had a diastolic interventricular septal (IVSd) or left ventricular free wall (LVPWd) thickness exceeding 6,0 mm. In 3 of these cats the hypertrophy was segmental. Two cats (4,8%) had systolic anterior motion (SAM) of the mitral valve without concomitant hypertrophy. Five cats (11,9%) had IVSd or LVPWd exceeding 5,0 mm but less than 6,0 mm.</p> <p>Conclusion</p> <p>Depending on the reference values used, the prevalence of HCM in this study varied from 9,5% to 26,2%. Our study suggests that the left ventricular wall thickness of a normal cat is 5,0 mm or less, rather than 6,0 mm, previously used by most cardiologists. Appropriate echocardiographic reference values for Maine coon cats, and diagnostic criteria for HCM need to be further investigated.</p

    Algorithms for automated DNA assembly

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    Generating a defined set of genetic constructs within a large combinatorial space provides a powerful method for engineering novel biological functions. However, the process of assembling more than a few specific DNA sequences can be costly, time consuming and error prone. Even if a correct theoretical construction scheme is developed manually, it is likely to be suboptimal by any number of cost metrics. Modular, robust and formal approaches are needed for exploring these vast design spaces. By automating the design of DNA fabrication schemes using computational algorithms, we can eliminate human error while reducing redundant operations, thus minimizing the time and cost required for conducting biological engineering experiments. Here, we provide algorithms that optimize the simultaneous assembly of a collection of related DNA sequences. We compare our algorithms to an exhaustive search on a small synthetic dataset and our results show that our algorithms can quickly find an optimal solution. Comparison with random search approaches on two real-world datasets show that our algorithms can also quickly find lower-cost solutions for large datasets

    Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

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    <div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div

    Genomic expression profiling of human inflammatory cardiomyopathy (DCMi) suggests novel therapeutic targets

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    The clinical phenotype of human dilated cardiomyopathy (DCM) encompasses a broad spectrum of etiologically distinct disorders. As targeting of etiology-related pathogenic pathways may be more efficient than current standard heart failure treatment, we obtained the genomic expression profile of a DCM subtype characterized by cardiac inflammation to identify possible new therapeutic targets in humans. In this inflammatory cardiomyopathy (DCMi), a distinctive cardiac expression pattern not described in any previous study of cardiac disorders was observed. Two significantly altered gene networks of particular interest and possible interdependence centered around the cysteine-rich angiogenic inducer 61 (CYR61) and adiponectin (APN) gene. CYR61 overexpression, as in human DCMi hearts in situ, was similarly induced by inflammatory cytokines in vascular endothelial cells in vitro. APN was strongly downregulated in DCMi hearts and completely abolished cytokine-dependent CYR61 induction in vitro. Dysbalance between the CYR61 and APN networks may play a pathogenic role in DCMi and contain novel therapeutic targets. Multiple immune cell-associated genes were also deregulated (e.g., chemokine ligand 14, interleukin-17D, nuclear factors of activated T cells). In contrast to previous investigations in patients with advanced or end-stage DCM where etiology-related pathomechanisms are overwhelmed by unspecific processes, the deregulations detected in this study occurred at a far less severe and most probably fully reversible disease stage. ELECTRONIC SUPPLEMENTARY MATERIAL: Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s00109-006-0122-9 and is accessible for authorized users

    Do changes in traditional coronary heart disease risk factors over time explain the association between socio-economic status and coronary heart disease?

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    <p>Abstract</p> <p>Background</p> <p>Socioeconomic status (SES) predicts coronary heart disease independently of the traditional risk factors included in the Framingham risk score. However, it is unknown whether <it>changes </it>in Framingham risk score variables over time explain the association between SES and coronary heart disease. We examined this question given its relevance to risk assessment in clinical decision making.</p> <p>Methods</p> <p>The Atherosclerosis Risk in Communities study data (initiated in 1987 with 10-years follow-up of 15,495 adults aged 45-64 years in four Southern and Mid-Western communities) were used. SES was assessed at baseline, dichotomized as low SES (defined as low education and/or low income) or not. The time dependent variables - smoking, total and high density lipoprotein cholesterol, systolic blood pressure and use of blood pressure lowering medication - were assessed every three years. Ten-year incidence of coronary heart disease was based on EKG and cardiac enzyme criteria, or adjudicated death certificate data. Cox survival analyses examined the contribution of SES to heart disease risk independent of baseline Framingham risk score, without and with further adjustment for the time dependent variables.</p> <p>Results</p> <p>Adjusting for baseline Framingham risk score, low SES was associated with an increased coronary heart disease risk (hazard ratio [HR] = 1.53; 95% Confidence Interval [CI], 1.27 to1.85). After further adjustment for the time dependent variables, the SES effect remained significant (HR = 1.44; 95% CI, 1.19 to1.74).</p> <p>Conclusion</p> <p>Using Framingham Risk Score alone under estimated the coronary heart disease risk in low SES persons. This bias was not eliminated by subsequent changes in Framingham risk score variables.</p

    Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease

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    <p>Abstract</p> <p>Background</p> <p>Cardiomyopathies, degenerative diseases of cardiac muscle, are among the leading causes of death in the developed world. Microarray studies of cardiomyopathies have identified up to several hundred genes that significantly alter their expression patterns as the disease progresses. However, the regulatory mechanisms driving these changes, in particular the networks of transcription factors involved, remain poorly understood. Our goals are (A) to identify modules of co-regulated genes that undergo similar changes in expression in various types of cardiomyopathies, and (B) to reveal the specific pattern of transcription factor binding sites, <it>cis</it>-elements, in the proximal promoter region of genes comprising such modules.</p> <p>Methods</p> <p>We analyzed 149 microarray samples from human hypertrophic and dilated cardiomyopathies of various etiologies. Hierarchical clustering and Gene Ontology annotations were applied to identify modules enriched in genes with highly correlated expression and a similar physiological function. To discover motifs that may underly changes in expression, we used the promoter regions for genes in three of the most interesting modules as input to motif discovery algorithms. The resulting motifs were used to construct a probabilistic model predictive of changes in expression across different cardiomyopathies.</p> <p>Results</p> <p>We found that three modules with the highest degree of functional enrichment contain genes involved in myocardial contraction (n = 9), energy generation (n = 20), or protein translation (n = 20). Using motif discovery tools revealed that genes in the contractile module were found to contain a TATA-box followed by a CACC-box, and are depleted in other GC-rich motifs; whereas genes in the translation module contain a pyrimidine-rich initiator, Elk-1, SP-1, and a novel motif with a GCGC core. Using a naïve Bayes classifier revealed that patterns of motifs are statistically predictive of expression patterns, with odds ratios of 2.7 (contractile), 1.9 (energy generation), and 5.5 (protein translation).</p> <p>Conclusion</p> <p>We identified patterns comprised of putative <it>cis</it>-regulatory motifs enriched in the upstream promoter sequence of genes that undergo similar changes in expression secondary to cardiomyopathies of various etiologies. Our analysis is a first step towards understanding transcription factor networks that are active in regulating gene expression during degenerative heart disease.</p

    Crystal Structure of Escherichia coli CusC, the Outer Membrane Component of a Heavy Metal Efflux Pump

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    Background: While copper has essential functions as an enzymatic co-factor, excess copper ions are toxic for cells, necessitating mechanisms for regulating its levels. The cusCBFA operon of E. coli encodes a four-component efflux pump dedicated to the extrusion of Cu(I) and Ag(I) ions. Methodology/Principal Findings: We have solved the X-ray crystal structure of CusC, the outer membrane component of the Cus heavy metal efflux pump, to 2.3 A ˚ resolution. The structure has the largest extracellular opening of any outer membrane factor (OMF) protein and suggests, for the first time, the presence of a tri-acylated N-terminal lipid anchor. Conclusions/Significance: The CusC protein does not have any obvious features that would make it specific for metal ions, suggesting that the narrow substrate specificity of the pump is provided by other components of the pump, most likely by the inner membrane component CusA

    Genomic mining of prokaryotic repressors for orthogonal logic gates

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    Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10[superscript 54] circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.United States. Air Force Office of Scientific Research (Award FA9550-11-C-0028)American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowship (32 CFR 168a)United States. Defense Advanced Research Projects Agency. Chronical of Lineage Indicative of Origins (N66001-12-C-4016)United States. Office of Naval Research (N00014-13-1-0074)National Institutes of Health (U.S.) (GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (SA5284-11210
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