Benefits and risks of the hormetic effects of dietary isothiocyanates on cancer prevention

The isothiocyanate (ITC) sulforaphane (SFN) was shown at low levels (1-5 µM) to promote cell proliferation to 120-143% of the controls in a number of human cell lines, whilst at high levels (10-40 µM) it inhibited such cell proliferation. Similar dose responses were observed for cell migration, i.e. SFN at 2.5 µM increased cell migration in bladder cancer T24 cells to 128% whilst high levels inhibited cell migration. This hormetic action was also found in an angiogenesis assay where SFN at 2.5 µM promoted endothelial tube formation (118% of the control), whereas at 10-20 µM it caused significant inhibition. The precise mechanism by which SFN influences promotion of cell growth and migration is not known, but probably involves activation of autophagy since an autophagy inhibitor, 3-methyladenine, abolished the effect of SFN on cell migration. Moreover, low doses of SFN offered a protective effect against free-radical mediated cell death, an effect that was enhanced by co-treatment with selenium. These results suggest that SFN may either prevent or promote tumour cell growth depending on the dose and the nature of the target cells. In normal cells, the promotion of cell growth may be of benefit, but in transformed or cancer cells it may be an undesirable risk factor. In summary, ITCs have a biphasic effect on cell growth and migration. The benefits and risks of ITCs are not only determined by the doses, but are affected by interactions with Se and the measured endpoint

Infectious Disease Modeling of Social Contagion in Networks

Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.National Institutes of Health (U.S.) (grant R01GM078986)National Science Foundation (U.S.)Bill & Melinda Gates FoundationTempleton FoundationNational Institute on Aging (grant P01 AG031093)Framingham Heart Study (contract number N01-HC-25195

Robustness of circadian clocks to daylight fluctuations: hints from the picoeucaryote Ostreococcus tauri

The development of systemic approaches in biology has put emphasis on identifying genetic modules whose behavior can be modeled accurately so as to gain insight into their structure and function. However most gene circuits in a cell are under control of external signals and thus quantitative agreement between experimental data and a mathematical model is difficult. Circadian biology has been one notable exception: quantitative models of the internal clock that orchestrates biological processes over the 24-hour diurnal cycle have been constructed for a few organisms, from cyanobacteria to plants and mammals. In most cases, a complex architecture with interlocked feedback loops has been evidenced. Here we present first modeling results for the circadian clock of the green unicellular alga Ostreococcus tauri. Two plant-like clock genes have been shown to play a central role in Ostreococcus clock. We find that their expression time profiles can be accurately reproduced by a minimal model of a two-gene transcriptional feedback loop. Remarkably, best adjustment of data recorded under light/dark alternation is obtained when assuming that the oscillator is not coupled to the diurnal cycle. This suggests that coupling to light is confined to specific time intervals and has no dynamical effect when the oscillator is entrained by the diurnal cycle. This intringuing property may reflect a strategy to minimize the impact of fluctuations in daylight intensity on the core circadian oscillator, a type of perturbation that has been rarely considered when assessing the robustness of circadian clocks

Prospects for radical emissions reduction through behaviour and lifestyle change

Over the past two decades, scholars and practitioners across the social sciences, in policy and beyond have proposed, trialled and developed a wide range of theoretical and practical approaches designed to bring about changes in behaviours and lifestyles that contribute to climate change. With the exception of the establishment of a small number of iconic behaviours such as recycling, it has however proved extremely difficult to bring about meaningful transformations in personal greenhouse gas emissions at either the individual or societal level, with multiple reviews now pointing to the limited efficacy of current approaches. We argue that the majority of approaches designed to achieve mitigation have been constrained by the need to operate within prevailing social scientific, economic and political orthodoxies which have precluded the possibility of non-marginal change. In this paper we ask what a truly radical approach to reducing personal emissions would look like from social science perspectives which challenge the unstated assumptions severely limiting action to date, and which explore new alternatives for change. We emphasise the difficulties likely to impede the instituting of genuinely radical societal change regarding climate change mitigation, whilst proposing ways that the ground could be prepared for such a transformation to take place

Cruel to be kind but not cruel for cash : harm aversion in the dictator game

People regularly take prosocial actions, making individual sacrifices for the greater good. Similarly, people generally avoid causing harm to others. These twin desires to do good and avoid harm often align, but sometimes they can diverge, creating situations of moral conflict. Here, we examined this moral conflict using a modified dictator game. Participants chose how much money to allocate away from a recipient who was designated as an orphan, creating a sense of harm. This money was then reallocated to either the participant or a charity. People were strongly prosocial: they allocated more money away from the orphan for charity than for themselves. Furthermore, people left more money with the orphan when the harm was framed as a means (taking) than as a side effect (splitting). As is predicted by dual-process theories of moral decision making, response times were longer with the take action and were positively correlated with the amount taken from the orphan. We concluded that just as people take positive actions for the greater good, they are similarly more willing to cause harm when it benefits others rather than themselves

Quantitative cross-species extrapolation between humans and fish: The case of the anti-depressant fluoxetine

This article has been made available through the Brunel Open Access Publishing Fund.Fish are an important model for the pharmacological and toxicological characterization of human pharmaceuticals in drug discovery, drug safety assessment and environmental toxicology. However, do fish respond to pharmaceuticals as humans do? To address this question, we provide a novel quantitative cross-species extrapolation approach (qCSE) based on the hypothesis that similar plasma concentrations of pharmaceuticals cause comparable target-mediated effects in both humans and fish at similar level of biological organization (Read-Across Hypothesis). To validate this hypothesis, the behavioural effects of the anti-depressant drug fluoxetine on the fish model fathead minnow (Pimephales promelas) were used as test case. Fish were exposed for 28 days to a range of measured water concentrations of fluoxetine (0.1, 1.0, 8.0, 16, 32, 64 μg/L) to produce plasma concentrations below, equal and above the range of Human Therapeutic Plasma Concentrations (HTPCs). Fluoxetine and its metabolite, norfluoxetine, were quantified in the plasma of individual fish and linked to behavioural anxiety-related endpoints. The minimum drug plasma concentrations that elicited anxiolytic responses in fish were above the upper value of the HTPC range, whereas no effects were observed at plasma concentrations below the HTPCs. In vivo metabolism of fluoxetine in humans and fish was similar, and displayed bi-phasic concentration-dependent kinetics driven by the auto-inhibitory dynamics and saturation of the enzymes that convert fluoxetine into norfluoxetine. The sensitivity of fish to fluoxetine was not so dissimilar from that of patients affected by general anxiety disorders. These results represent the first direct evidence of measured internal dose response effect of a pharmaceutical in fish, hence validating the Read-Across hypothesis applied to fluoxetine. Overall, this study demonstrates that the qCSE approach, anchored to internal drug concentrations, is a powerful tool to guide the assessment of the sensitivity of fish to pharmaceuticals, and strengthens the translational power of the cross-species extrapolation

Are all ‘research fields’ equal? Rethinking practice for the use of data from crowd-sourcing market places

New technologies like large-scale social media sides (e.g., Facebook and Twitter) and crowdsourcing services (e.g., Amazon Mechanical Turk, Crowdflower, Clickworker) impact social science research and provide many new and interesting avenues for research. The use of these new technologies for research has not been without challenges and a recently published psychological study on Facebook led to a widespread discussion on the ethics of conducting large-scale experiments online. Surprisingly little has been said about the ethics of conducting research using commercial crowdsourcing market places. In this paper, I want to focus on the question of which ethical questions are raised by data collection with crowdsourcing tools. I briefly draw on implications of internet research more generally and then focus on the specific challenges that research with crowdsourcing tools faces. I identify fair-pay and related issues of respect for autonomy as well as problems with power dynamics between researcher and participant, which has implications for ‘withdrawal-withoutprejudice’, as the major ethical challenges with crowdsourced data. Further, I will to draw attention on how we can develop a ‘best practice’ for researchers using crowdsourcing tools

Conducting interactive experiments online

Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a potentially valuable complement to laboratory studies

Biclustering models for two-mode ordinal data

The work in this paper introduces finite mixture models that can be used to simul- taneously cluster the rows and columns of two-mode ordinal categorical response data, such as those resulting from Likert scale responses. We use the popular proportional odds parameterisation and propose models which provide insights into major patterns in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation of rows and columns to corresponding clusters is obtained. The clustering ability of the models is evaluated in a simulation study and demonstrated using two real data sets