Prevalence and inter-relationship of different Doppler measures of dyssynchrony in patients with heart failure and prolonged QRS: a report from CARE-HF

Background: Cardiac resynchronisation therapy (CRT) improves mortality and morbidity in heart failure patients with wide QRS. Observational studies suggest that patients having more left ventricular dyssynchrony pre-implantation obtain greater benefit on ventricular function and symptoms with CRT.Aim: To provide an analysis of the prevalence and type of dyssynchrony in patients included in the CARE-HF trial.Methods: 100 patients 67 (58 to 71) years were examined with echocardiography including tissue doppler imaging before receiving a CRT-pacemaker. Atrio-ventricular dyssynchrony (LVFT/RR) was defined as left ventricular filling time <40% of the RR-interval. Inter-ventricular mechanical delay (IVMD) was measured as the difference in onset of Doppler-flow in the pulmonary and aortic outflow tracts >40 ms. Intraventricular (regional) dyssynchrony in a 16-segment model was expressed either as a delayed longitudinal contraction (DLC) during the postsystolic phase or by tissue synchronisation imaging (TSI) with a predefined time-difference in systolic maximal velocities >85 ms.Results: LVFT/RR was present in 34% and IVMD in 60% of patients while intra-ventricular dyssynchrony was present in 85% (DLC) and 86% (TSI) with a high agreement between the measures (Kappascore 0.86-1.00), indicating the methods being interchangeable. Patients with cardiomyopathy (53%) were more likely to have LVFT/RR <40% (45% vs. 21% (p= 0.02)) and more segments affected by intra-ventricular dyssynchrony 4(3, 5) vs. 3(1, 4), p = 0.002, compared to patients with ischemic heart disease.Conclusion: The prevalence of intra-ventricular dyssynchrony is high in patients with heart failure, wide QRS and depressed systolic function. Most important, TSI appears to be a fast and reliable method to identify patients with intra-ventricular dyssynchrony likely to benefit from CRT

Transcriptional Control in the Segmentation Gene Network of Drosophila

The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks

Two different point mutations in ABL gene ATP-binding domain conferring Primary Imatinib resistance in a Chronic Myeloid Leukemia (CML) patient: A case report

Imatinib (Gleevec) is the effective therapy for BCR-ABL positive CML patients. Point mutations have been detected in ATP-binding domain of ABL gene which disturbs the binding of Gleevec to this target leading to resistance. Detection of mutations is helpful in clinical management of imatinib resistance. We established a very sensitive (ASO) PCR to detect mutations in an imatinib-resistant CML patient. Mutations C944T and T1052C were detected which cause complete partial imatinib resistance, respectively. This is the first report of multiple point mutations conferring primary imatinib resistance in same patient at the same time. Understanding the biological reasons of primary imatinib resistance is one of the emerging issues of pharmacogenomics and will be helpful in understanding primary resistance of molecularly-targeted cancer therapies. It will also be of great utilization in clinical management of imatinib resistance. Moreover, this ASO-PCR assay is very effective in detecting mutations related to imatinib resistance

Beta1-Adrenoceptor Polymorphism Predicts Flecainide Action in Patients with Atrial Fibrillation

BACKGROUND: Antiarrhythmic action of flecainide is based on sodium channel blockade. Beta(1)-adrenoceptor (beta(1)AR) activation induces sodium channel inhibition, too. The aim of the present study was to evaluate the impact of different beta(1)AR genotypes on antiarrhythmic action of flecainide in patients with structural heart disease and atrial fibrillation. METHODOLOGY/PRINCIPAL FINDINGS: In 145 subjects, 87 with atrial fibrillation, genotyping was performed to identify the individual beta(1)AR Arg389Gly and Ser49Gly polymorphism. Resting heart rate during atrial fibrillation and success of flecainide-induced cardioversion were correlated with beta(1)AR genotype. The overall cardioversion rate with flecainide was 39%. The Arg389Arg genotype was associated with the highest cardioversion rate (55.5%; OR 3.30; 95% CI; 1.34-8.13; p = 0.003) compared to patients with Arg389Gly (29.5%; OR 0.44; 95% CI; 0.18-1.06; p = 0.066) and Gly389Gly (14%; OR 0.24; 95% CI 0.03-2.07; p = 0.17) variants. The single Ser49Gly polymorphism did not influence the conversion rate. In combination, patients with Arg389Gly-Ser49Gly genotype displayed the lowest conversion rate with 20.8% (OR 0.31; 95% CI; 0.10-0.93; p = 0.03). In patients with Arg389Arg variants the heart rate during atrial fibrillation was significantly higher (110+/-2.7 bpm; p = 0.03 vs. other variants) compared to Arg389Gly (104.8+/-2.4 bpm) and Gly389Gly (96.9+/-5.8 bpm) carriers. The Arg389Gly-Ser49Gly genotype was more common in patients with atrial fibrillation compared to patients without atrial fibrillation (27.6% vs. 5.2%; HR 6.98; 95% CI; 1.99-24.46; p<0.001). CONCLUSIONS: The beta(1)AR Arg389Arg genotype is associated with increased flecainide potency and higher heart rate during atrial fibrillation. The Arg389Gly-Ser49Gly genotype might be of predictive value for atrial fibrillation

Thermodynamics-Based Models of Transcriptional Regulation by Enhancers: The Roles of Synergistic Activation, Cooperative Binding and Short-Range Repression

Quantitative models of cis-regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled, or heuristic approximations of the underlying regulatory mechanisms. We have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence, as a function of transcription factor concentrations and their DNA-binding specificities. It uses statistical thermodynamics theory to model not only protein-DNA interaction, but also the effect of DNA-bound activators and repressors on gene expression. In addition, the model incorporates mechanistic features such as synergistic effect of multiple activators, short range repression, and cooperativity in transcription factor-DNA binding, allowing us to systematically evaluate the significance of these features in the context of available expression data. Using this model on segmentation-related enhancers in Drosophila, we find that transcriptional synergy due to simultaneous action of multiple activators helps explain the data beyond what can be explained by cooperative DNA-binding alone. We find clear support for the phenomenon of short-range repression, where repressors do not directly interact with the basal transcriptional machinery. We also find that the binding sites contributing to an enhancer's function may not be conserved during evolution, and a noticeable fraction of these undergo lineage-specific changes. Our implementation of the model, called GEMSTAT, is the first publicly available program for simultaneously modeling the regulatory activities of a given set of sequences

Lysophosphatidic Acid Acyltransferase β (LPAATβ) Promotes the Tumor Growth of Human Osteosarcoma

Osteosarcoma is the most common primary malignancy of bone with poorly characterized molecular pathways important in its pathogenesis. Increasing evidence indicates that elevated lipid biosynthesis is a characteristic feature of cancer. We sought to investigate the role of lysophosphatidic acid acyltransferase β (LPAATβ, aka, AGPAT2) in regulating the proliferation and growth of human osteosarcoma cells. LPAATβ can generate phosphatidic acid, which plays a key role in lipid biosynthesis as well as in cell proliferation and survival. Although elevated expression of LPAATβ has been reported in several types of human tumors, the role of LPAATβ in osteosarcoma progression has yet to be elucidated.Endogenous expression of LPAATβ in osteosarcoma cell lines is analyzed by using semi-quantitative PCR and immunohistochemical staining. Adenovirus-mediated overexpression of LPAATβ and silencing LPAATβ expression is employed to determine the effect of LPAATβ on osteosarcoma cell proliferation and migration in vitro and osteosarcoma tumor growth in vivo. We have found that expression of LPAATβ is readily detected in 8 of the 10 analyzed human osteosarcoma lines. Exogenous expression of LPAATβ promotes osteosarcoma cell proliferation and migration, while silencing LPAATβ expression inhibits these cellular characteristics. We further demonstrate that exogenous expression of LPAATβ effectively promotes tumor growth, while knockdown of LPAATβ expression inhibits tumor growth in an orthotopic xenograft model of human osteosarcoma.Our results strongly suggest that LPAATβ expression may be associated with the aggressive phenotypes of human osteosarcoma and that LPAATβ may play an important role in regulating osteosarcoma cell proliferation and tumor growth. Thus, targeting LPAATβ may be exploited as a novel therapeutic strategy for the clinical management of osteosarcoma. This is especially attractive given the availability of selective pharmacological inhibitors

Die primare Versorgung der Kriegsschusaverletzungen der grossen Gefaese.

Diss. München.OPLADEN-RUG0