952 resultados para Gilbreth, Frank B. (Frank Bunker), 1868-1924.


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Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.<br/>Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).<br/>Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.

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Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.<br/><br/>Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.

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Objective: To investigate the effect of alcohol intake patterns on ischaemic heart disease in two countries with contrasting lifestyles, Northern Ireland and France. <br/>Design: Cohort data from the Prospective Epidemiological Study of Myocardial Infarction (PRIME) were analysed. Weekly alcohol consumption, incidence of binge drinking (alcohol >50 g on at least one day a week), incidence of regular drinking (at least one day a week, and alcohol <50 g if on only one occasion), volume of alcohol intake, frequency of consumption, and types of beverage consumed were assessed once at inclusion. All coronary events that occurred during the 10 year follow-up were prospectively registered. The relation between baseline characteristics and incidence of hard coronary events and angina events was assessed by Cox's proportional hazards regression analysis. <br/>Setting: One centre in Northern Ireland (Belfast) and three centres in France (Lille, Strasbourg, and Toulouse). <br/>Participants: 9778 men aged 50-59 free of ischaemic heart disease at baseline, who were recruited between 1991 and 1994. <br/>Main outcome measures: Incident myocardial infarction and coronary death ("hard" coronary events), and incident angina pectoris. <br/>Results: A total of 2405 men from Belfast and 7373 men from the French centres were included in the analyses, 1456 (60.5%) and 6679 (90.6%) of whom reported drinking alcohol at least once a week, respectively. Among drinkers, 12% (173/1456) of men in Belfast drank alcohol every day compared with 75% (5008/6679) of men in France. Mean alcohol consumption was 22.1 g/day in Belfast and 32.8 g/day in France. Binge drinkers comprised 9.4% (227/2405) and 0.5% (33/7373) of the Belfast and France samples, respectively. A total of 683 (7.0%) of the 9778 participants experienced ischaemic heart disease events during the 10 year follow-up: 322 (3.3%) hard coronary events and 361 (3.7%) angina events. Annual incidence of hard coronary events per 1000 person years was 5.63 (95% confidence interval 4.69 to 6.69) in Belfast and 2.78 (95% CI 2.41 to 3.20) in France. After multivariate adjustment for classic cardiovascular risk factors and centre, the hazard ratio for hard coronary events compared with regular drinkers was 1.97 (95% CI 1.21 to 3.22) for binge drinkers, 2.03 (95% CI 1.41 to 2.94) for never drinkers, and 1.57 (95% CI 1.11 to 2.21) for former drinkers for the entire cohort. The hazard ratio for hard coronary events in Belfast compared with in France was 1.76 (95% CI 1.37 to 2.67) before adjustment, and 1.09 (95% CI 0.79 to 1.50) after adjustment for alcohol patterns and wine drinking. Only wine drinking was associated with a lower risk of hard coronary events, irrespective of the country. <br/>Conclusions: Regular and moderate alcohol intake throughout the week, the typical pattern in middle aged men in France, is associated with a low risk of ischaemic heart disease, whereas the binge drinking pattern more prevalent in Belfast confers a higher risk.

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Since the early 1970s, the American electronic media artist Paul DeMarinis (b. 1948, Cleveland, Ohio, USA) has created works that re-imagine modes of communication and reinvent the technologies that enable communication. His works (see Table 1) have taken shape as recordings, performances, electronic inventions, and site-specific and interactive installations; many are considered landmarks in the histories of electronic music and media art. Paul DeMarinis pioneered live performance with computers, collaborated on landmark works with artists like David Tudor and Robert Ashley, undertook several tours with the Merce Cunningham Dance Company, and brought to life obscure technologies such as the flame loudspeaker (featured in his 2004 sculpture Firebirds). His interactive installation The Music Room (1982), commissioned by Frank Oppenheimer for the Exploratorium in San Francisco, was the first automatic music work to reach a significant audience. His album Music As A Second Language (1991) marks one of the most extensive explorations of the synthesized voice and speech melodies to date. Installations like The Edison Effect (1989-1993), in which lasers scan ancient recordings to produce music, and The Messenger (1998/2005), in which electronic mail messages are displayed on alphabetic telegraph receivers, illustrate a creative process that Douglas Kahn (1994) has called "reinventing invention." [etc]

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We present a simple quantum mechanical model to describe Coulomb explosion of H-2(+) and D-2(+) by short, intense infrared laser pulses. The model is based on the length gauge version of the molecular strong-field approximation and is valid when the process of dissociation prior to ionization is negligible. The results are compared with recent experimental data for the proton kinetic energy spectrum [Th. Ergler , Phys. Rev. Lett. 95, 093001 (2005); D. S. Murphy , J. Phys. B 40, S359 (2007)]. Using a Franck-Condon distribution over initial vibrational states, the theory reproduces the overall shape of the spectrum with only a small overestimation of slow protons. The agreement between theory and experiment can be made perfect by using a non-Frank-Condon initial distribution characteristic for H-2(+) (D-2(+)) targets produced by strong-field ionization of H-2 (D-2). For comparison, we also present results obtained by two different tunneling models for this process.

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We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P = 1 × 10(-5). We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10(-17); including ADGC data, meta P = 5.0 × 10(-21)) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10(-14); including ADGC data, meta P = 1.2 × 10(-16)) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10(-4); including ADGC data, meta P = 8.6 × 10(-9)), CD33 (GERAD+, P = 2.2 × 10(-4); including ADGC data, meta P = 1.6 × 10(-9)) and EPHA1 (GERAD+, P = 3.4 × 10(-4); including ADGC data, meta P = 6.0 × 10(-10)).

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We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as "stochastic extension of the Sznajd model for an open community, because it allows for "special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B.