Search

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this paper was produced within the framework of the ESC Prevention of Cardiovascular Disease Programme which is led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP). The ESC Prevention of Cardiovascular Disease Programme is supported by unrestricted educational grants. The authors received no financial support for the research, authorship, and/or publication of this article. Rossello, X (corresponding author), Ctr Nacl Invest Cardiovasc CNIC Carlos III, Melchor Fernandez Almagro 3, Madrid 28029, Spain. fjrossello@cnic.es

LaPSvS1, a highly sulfated branched (1-->3)-beta-galactan was prepared from the arabino-galactan from Larix decidua Miller by partial hydrolysis and subsequent sulfation with SO(3)-pyridine in DMF. The molecular weight was analyzed by GPC and the sulfate content was determined by ion chromatography. LaPSvS1 exhibited good antiangiogenic and antiinflammatory effects in two different modifications of the known CAM-assay. In vitro results obtained in the FGF-2-trypsin-assay and in fluorospectrometric experiments revealed that LaPSvS1 interacts with the fibroblast growth factor 2 system. This interaction is correlated with the in vivo effect of LaPSvS1 on FGF-2 induced angiogenesis.

The migration of 51Cr-labeled autologous lymphocytes from intestinal or prescapular lymph was compared in fetal lambs and adult sheep. A subpopulation of lymphocytes present in intestinal lymph of adults which migrated to the small intestine was not found in fetal intestinal lymph. There were marked differences in the migration of fetal and adult lymphocytes to the lungs and liver. In spite of the absence of circulating antibodies or immunoglobulins and of extrinsic antigen in the immunologically virgin sheep fetus, the circulation of lymphocytes through the spleen and lymph nodes of fetal lambs was more intense than in the adult.

International audience; Introduction Infective endocarditis is one of the most difficult-to-treat infectious diseases. Areas covered We restricted this review to the anti-infective treatment of the main bacteria responsible for infective endocarditis, i.e. staphylococci, streptococci, enterococci, and Gram-negative bacilli, including HACEK. Specific topics of major interest in treatment strategy are covered as well, including empirical treatment, oral switch, and treatment duration. We searched in the MEDLINE database to identify relevant studies, trials, reviews, or meta-analyses until May 2020. Expert opinion The use of aminoglycosides for the treatment of endocarditis has been dramatically reduced over the last 20 years. It should be administered once daily, and no longer than 2 weeks. For staphylococcal endocarditis, recent data reinforced the role of anti-staphylococcal penicillins, for methicillin-susceptible isolates (alternative, cefazolin), and vancomycin for methicillin-resistant isolates (alternative, daptomycin). For staphylococcal prosthetic-valve endocarditis, these treatments will be reinforced by the addition of gentamicin during the first 2 weeks, and rifampin throughout the whole treatment duration, i.e. 6 weeks. The optimal duration of antibacterial treatment is 4 weeks for most native valve endocarditis, and 6 weeks for prosthetic-valve endocarditis. The oral switch is safe in patients stabilized after the initial intravenous course.

Cellular therapies have been increasingly applied to diverse human diseases. Intracoronary infusion of bone marrow-derived mononuclear cells (BMMNC) has demonstrated to improve ventricular function after acute myocardial infarction. However, less information is available about the role of BMMNC therapy for the treatment of dilated myocardiopathies (DCs) of non-ischemic origin. This article presents the methodological description of a study aimed at investigating the efficacy of intracoronary injection of autologous BMMNCs in the improvement of the ventricular function of patients with DC. This randomised, placebo-controlled, double-blinded phase IIb clinical trial compares the improvement on ventricular function (measured by the changes on the ejection fraction) of patients receiving the conventional treatment for DC in combination with a single dose of an intracoronary infusion of BMMNCs, with the functional recovery of patients receiving placebo plus conventional treatment. Patients assigned to both treatment groups are monitored for 24 months. This clinical trial is powered enough to detect a change in Left Ventricular Ejection Fraction (LVEF) equal to or greater than 9%, although an interim analysis is planned to re-calculate sample size. The study protocol was approved by the Andalusian Coordinating Ethics Committee for Biomedical Research (Comite Coordinador de Etica en Investigacion Biomedica de Andalucia), the Spanish Medicines and Medical Devices Agency (Agencia Espanola de Medicamentos y Productos Sanitarios), and is registered at the EU Clinical Trials Register (EudraCT: 2013–002015-98). The publication of the trial results in scientific journals will be performed in accordance with the applicable regulations and guidelines to clinical trials. ClinicalTrials.gov Identifier NCT02033278 (First Posted January 10, 2014): https://clinicaltrials.gov/ct2/show/NCT02033278 ; EudraCT number: 2013–002015-98, EU CT Register: https://www.clinicaltrialsregister.eu/ctr-search/search?query=2013-002015-98 . Trial results will also be published according to the CONSORT statement at conferences and reported peer-reviewed journals.

Background Reverse engineering in systems biology entails inference of gene regulatory networks from observational data. This data typically include gene expression measurements of wild type and mutant cells in response to a given stimulus. It has been shown that when more than one type of experiment is used in the network inference process the accuracy is higher. Therefore the development of generally applicable and effective methodologies that embed multiple sources of information in a single computational framework is a worthwhile objective. Results This paper presents a new method for network inference, which uses multi-objective optimisation (MOO) to integrate multiple inference methods and experiments. We illustrate the potential of the methodology by combining ODE and correlation-based network inference procedures as well as time course and gene inactivation experiments. Here we show that our methodology is effective for a wide spectrum of data sets and method integration strategies. Conclusions The approach we present in this paper is flexible and can be used in any scenario that benefits from integration of multiple sources of information and modelling procedures in the inference process. Moreover, the application of this method to two case studies representative of bacteria and vertebrate systems has shown potential in identifying key regulators of important biological processes.