Malondialdehyde (MDA) is one of the most frequently used indicators of lipid peroxidation. To generate reliable reference intervals for plasma malondialdehyde (P-MDA), a reference sample group was established in Funen, Denmark. The group consisted of 213 individuals (107 men, 106 women), ages 20–79 years. P-MDA was measured in EDTA-treated plasma after derivatization by thiobarbituric acid (TBA) and separation on HPLC. UV detection was performed at 532 nm. A reference interval was calculated as recommended by IFCC with REFVAL 3.42. The estimated reference limits (0.025 and 0.975 fractals) for the group were 0.36 and 1.24 μmol/L. The data were analyzed for gender- and age-related differences. Analysis of variance showed no interaction between gender and age, but separate analyses showed an independent effect of gender (P = 0.03), but not of age (P = 0.11). Daily smokers had a slightly higher average concentration of P-MDA than nonsmokers (P = 0.05), and P-MDA correlated with daily exposure to cigarette smoke (r = 0.162; P = 0.03). A positive correlation was also demonstrated between P-MDA and weekly alcohol consumption (r = 0.153; P = 0.03). Within-subject and day-to-day variations of P-MDA indicated that the potential of P-MDA as a biomarker for individuals is questionable. However, on a group basis, the present data support that P-MDA may be a potential biomarker for oxidative stress.
No abstract
The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral marketing. A quantitative study of emailing of articles from the NY Times (Berger and Milkman, 2010) finds a strong link between positive affect and virality, and, based on psychological theories it is concluded that this relation is universally valid. The conclusion appears to be in contrast with classic theory of diffusion in news media (Galtung and Ruge, 1965) emphasizing negative affect as promoting propagation. In this paper we explore the apparent paradox in a quantitative analysis of information diffusion on Twitter. Twitter is interesting in this context as it has been shown to present both the characteristics social and news media (Kwak et al., 2010). The basic measure of virality in Twitter is the probability of retweet. Twitter is different from email in that retweeting does not depend on pre-existing social relations, but often occur among strangers, thus in this respect Twitter may be more similar to traditional news media. We therefore hypothesize that negative news content is more likely to be retweeted, while for non-news tweets positive sentiments support virality. To test the hypothesis we analyze three corpora: A complete sample of tweets about the COP15 climate summit, a random sample of tweets, and a general text corpus including news. The latter allows us to train a classifier that can distinguish tweets that carry news and non-news information. We present evidence that negative sentiment enhances virality in the news segment, but not in the non-news segment. We conclude that the relation between affect and virality is more complex than expected based on the findings of Berger and Milkman (2010), in short 'if you want to be cited: Sweet talk your friends or serve bad news to the public'.
How can corporations develop legitimacy when coping with stakeholders who have multiple, often conflicting sustainable development (SD) agendas? We address this question by conducting an in-depth longitudinal case study of a corporation's stakeholder engagement in social media and propose the concept of a networked legitimacy strategy. With this strategy, legitimacy is gained through participation in non-hierarchical open platforms and the co-construction of agendas. We explore the organizational transition needed to yield this new legitimacy approach. We argue that, in this context, legitimacy gains may increase when firms are able to reduce the control over the engagements and relate non-hierarchically with their publics. We contribute to the extant literature on political corporate social responsibility and legitimacy by providing an understanding of a new context for engagement that reconfigures cultural, network, and power relations between the firm and their stakeholders in ways that challenge previous forms of legitimation.
Abstract-Modeling the haemodynamic response in functional magnetic resonance (fMRI) experiments is an important aspect of the analysis of functional neuroimages. This has been done in the past using parametric response function, from a limited family. In this contribution, we adopt a semi-parametric approach based on finite impulse response (FIR) filters. In order to cope with the increase in the number of degrees of freedom, we introduce a Gaussian process prior on the filter parameters. We show how to carry on the analysis by incorporating prior knowledge on the filters, optimizing hyper-parameters using the evidence framework, or sampling using a Markov Chain Monte Carlo (MCMC) approach. We present a comparison of our model with standard haemodynamic response kernels on simulated data, and perform a full analysis of data acquired during an experiment involving visual stimulation.
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