Publications by authors named "Rossella Ferrara"

Cardiomyopathies are a heterogeneous group of cardiac diseases for which diagnosis and treatment are not always simple. The diagnosis of cardiomyopathy, in particular the etiology, comes from an integration between symptoms and results collected by several instrumental exams. The brain storming for the diagnosis includes also the identification of the "red flags", i.

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Background: Metabolic and immuno-inflammatory risk factors contribute to cardiac allograft vasculopathy (CAV) pathogenesis. Although systemic inflammation, as detected by C-reactive protein (CRP), predicts CAV development, the relationship between CRP and markers of metabolic abnormalities remains unexplored.

Methods: CRP and the entire metabolic panel were evaluated in 98 consecutive heart transplant recipients at the time of annual coronary angiography, 5.

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Cardiac allograft vasculopathy is still the main cause of long-term graft loss after heart transplantation. Indeed, recent advances in immunosuppression management led to a significant improvement in short-term survival, while long-term death rate did not change significantly in the last 20 years. In this paper, we will review the latest advances in the understanding of this peculiar form of atherosclerosis, focusing on the mechanisms that can be potentially targeted by specific therapeutic interventions.

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Background: Recent successes in the treatment of in-stent restenosis (ISR) by drug-eluting stents belie the challenges still faced in certain lesions and patient groups. We analyzed human coronary atheroma in de novo and restenotic disease to identify targets of therapy that might avoid these limitations.

Methods And Results: We recruited 89 patients who underwent coronary atherectomy for de novo atherosclerosis (n=55) or in-stent restenosis (ISR) of a bare metal stent (n=34).

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Large-scale gene expression studies provide significant insight into genes differentially regulated in disease processes such as cancer. However, these investigations offer limited understanding of multisystem, multicellular diseases such as atherosclerosis. A systems biology approach that accounts for gene interactions, incorporates nontranscriptionally regulated genes, and integrates prior knowledge offers many advantages.

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The propensity for developing atherosclerosis is dependent on underlying genetic risk and varies as a function of age and exposure to environmental risk factors. Employing three mouse models with different disease susceptibility, two diets, and a longitudinal experimental design, it was possible to manipulate each of these factors to focus analysis on genes most likely to have a specific disease-related function. To identify differences in longitudinal gene expression patterns of atherosclerosis, we have developed and employed a statistical algorithm that relies on generalized regression and permutation analysis.

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