Synchronized turbo apoptosis induced by cold-shock

In our research on the role of apoptosis in the pathogenesis of the autoimmune disease systemic lupus erythematosus (SLE), we aim to evaluate the effects of early and late apoptotic cells and blebs on antigen presenting cells. This requires the in vitro generation of sufficiently large and homogeneous populations of early and late apoptotic cells. Here, we present a quick method encountered by serendipity that results in highly reproducible synchronized homogeneous apoptotic cell populations. In brief, granulocytic 32Dcl3 cells are incubated on ice for 2 h and subsequently rewarmed at 37°C. After 30–90 min at 37°C more than 80–90% of the cells become early apoptotic (Annexin V positive/propidium iodide negative). After 24 h of rewarming at 37°C 98% of the cells were late apoptotic (secondary necrotic; Annexin V positive/propidium iodide positive). Cells already formed apoptotic blebs at their cell surface after approximately 20 min at 37°C. Inter-nucleosomal chromatin cleavage and caspase activation were other characteristics of this cold-shock-induced process of apoptosis. Consequently, apoptosis could be inhibited by a caspase inhibitor. Finally, SLE-derived anti-chromatin autoantibodies showed a high affinity for apoptotic blebs generated by cold-shock. Overall, cold-shock induced apoptosis is achieved without the addition of toxic compounds or antibodies, and quickly leads to synchronized homogeneous apoptotic cell populations, which can be applied for various research questions addressing apoptosis

Putting ourselves in another’s skin: using the plasticity of self-perception to enhance empathy and decrease prejudice

The self is one the most important concepts in social cognition and plays a crucial role in determining questions such as which social groups we view ourselves as belonging to and how we relate to others. In the past decade, the self has also become an important topic within cognitive neuroscience with an explosion in the number of studies seeking to understand how different aspects of the self are represented within the brain. In this paper, we first outline the recent research on the neurocognitive basis of the self and highlight a key distinction between two forms of self-representation. The first is the “bodily” self, which is thought to be the basis of subjective experience and is grounded in the processing of sensorimotor signals. The second is the “conceptual” self, which develops through our interactions of other and is formed of a rich network of associative and semantic information. We then investigate how both the bodily and conceptual self are related to social cognition with an emphasis on how self-representations are involved in the processing and creation of prejudice. We then highlight new research demonstrating that the bodily and conceptual self are both malleable and that this malleability can be harnessed in order to achieve a reduction in social prejudice. In particular, we will outline strong evidence that modulating people’s perceptions of the bodily self can lead to changes in attitudes at the conceptual level. We will highlight a series of studies demonstrating that social attitudes towards various social out-groups (e.g. racial groups) can lead to a reduction in prejudice towards that group. Finally, we seek to place these findings in a broader social context by considering how innovations in virtual reality technology can allow experiences of taking on another’s identity are likely to become both more commonplace and more convincing in the future and the various opportunities and risks associated with using such technology to reduce prejudice

Examining human individual differences in cyber security and possible implications for human-machine interface design

With society now heavily invested in cyber-technology and most cyber-attacks due to human error, it has never been more vital to focus research on human-centric interventions. Whilst some studies have previously investigated the importance of end-user individual differences (gender, age, education, risk-taking preferences, decision-making style, personality and impulsivity) the current study extended the research to also include acceptance of the internet and the constructs used to explain behavior within the Theory of Planned Behavior (TPB) and Protection Motivation Theory (PMT). Seventy-one participants completed a battery of questionnaires on personality, risk-taking preferences, decision-making style, personality, impulsivity, acceptance of the internet, the combined PMT and TPB questionnaire, as well as an online cyber-security behaviors questionnaire. Gender, age and education did not relate to any cyber-security behaviors, however a number of individual differences were associated. These behaviors include financial risk-taking, avoidant decision-making plus ease of use, facilitating conditions, and trust in the internet. It was also found that safer cyber-security behaviors are seen in those who appraise threat as high, perceive themselves to have the required skills to protect themselves, see value in this protection and understand their place in the cyber-security chain. These findings emphasize the importance of understanding how individual differences relate to cyber-security behaviors in order to create more tailored human-centric interventions such as computer-based decision support systems and other human-machine interface solutions

The Reproductive Ecology of Industrial Societies, Part I : Why Measuring Fertility Matters.

Is fertility relevant to evolutionary analyses conducted in modern industrial societies? This question has been the subject of a highly contentious debate, beginning in the late 1980s and continuing to this day. Researchers in both evolutionary and social sciences have argued that the measurement of fitness-related traits (e.g., fertility) offers little insight into evolutionary processes, on the grounds that modern industrial environments differ so greatly from those of our ancestral past that our behavior can no longer be expected to be adaptive. In contrast, we argue that fertility measurements in industrial society are essential for a complete evolutionary analysis: in particular, such data can provide evidence for any putative adaptive mismatch between ancestral environments and those of the present day, and they can provide insight into the selection pressures currently operating on contemporary populations. Having made this positive case, we then go on to discuss some challenges of fertility-related analyses among industrialized populations, particularly those that involve large-scale databases. These include "researcher degrees of freedom" (i.e., the choices made about which variables to analyze and how) and the different biases that may exist in such data. Despite these concerns, large datasets from multiple populations represent an excellent opportunity to test evolutionary hypotheses in great detail, enriching the evolutionary understanding of human behavior

Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena

Due to the ubiquitous presence of treatment heterogeneity, measurement error, and contextual confounders, numerous social phenomena are hard to study. Precise control of treatment variables and possible confounders is often key to the success of studies in the social sciences, yet often proves out of the realm of control of the experimenter. To amend this situation we propose a novel approach coined lock-in feedback which is based on a method that is routinely used in high-precision physics experiments to extract small signals out of a noisy environment. Here, we adapt the method to noisy social signals in multiple dimensions and evaluate it by studying an inherently noisy topic: the perception of (subjective) beauty. We show that the lock-in feedback approach allows one to select optimal treatment levels despite the presence of considerable noise. Furthermore, through the introduction of an external contextual shock we demonstrate that we can find relationships between noisy variables that were hitherto unknown. We therefore argue that lock-in methods may provide a valuable addition to the social scientist's experimental toolbox and we explicitly discuss a number of future applications