Cultured meat is a novel food technology that promises to produce meat in a more environmentally friendly and animal-friendly way. We conducted an internet survey in ten countries (Australia, China, England, France, Germany, Mexico, South Africa, Spain, Sweden and the US) with a total sample of 6128 participants. Results suggest that there are large cultural differences regarding the acceptance of cultured meat. French consumers were significantly less accepting of the idea than consumers in all other countries. Perceived naturalness of and disgust evoked by cultured meat were important factors in the acceptance of this novel food technology in all countries. Trust in the food industry, food neophobia and food disgust sensitivity indirectly and directly influenced the acceptance of cultured meat in almost all countries. In order to increase the acceptance of cultured meat, the similarity of cultured meat to traditional meat needs to be emphasized rather than the rather technical production process, which may evoke associations of unnaturalness and disgust.A systematic review with meta-analysis was performed to 1) estimate the prevalence of both mental and physical health problems in older offenders; 2) calculate relative risks for the health conditions in relation to non-offender older adults and; 3) explore the potential confounding role of several variables. We searched five databases up to August 2019. Studies involving offenders older than 50 years old were included. Fifty-five publications met criteria. The pooled prevalence for 18 mental and 28 physical health problems was calculated. In comparison with non-offender older adults, older offenders showed significantly higher risk for Hypertension (RR = 1.16, CI = 1.1, 1.2), Cardiovascular Diseases (RR = 1.24, CI = 1.09, 1.41), Respiratory diseases (RR = 1.75, CI = 1.29, 2.35), and Arthritis (RR = 1.19, CI = 1.12, 1.25). Heterogeneity was significant for all meta-analyses and partially explained by the confounding effect of country, the diagnosis assessment method, and the sample characteristics. Future research should include comparison groups of non-offender older adults and use longitudinal study designs to identify risk factors that can be targeted in preventive programmes.Various theories for the neural basis of consciousness have been proposed, suggesting a diversity of neural signs and mechanisms. We ask to what extent this diversity is real, or whether many theories share the same basic ideas with a potential for convergence towards a more unified theory of the neural basis of consciousness. For that purpose, we review and compare the various neural signs, measures, and mechanisms proposed in the different theories. We demonstrate that different theories focus on neural signs and measures of distinct aspects of neural activity including stimulus-related, prestimulus, and resting state activity as well as on distinct features of consciousness. Therefore, the various mechanisms proposed in the different theories may, in part, complement each other. 2-Aminoethanethiol chemical Together, we provide insight into the shared basis and convergences (and, in part, discrepancies) of the different theories of consciousness. We conclude that the different theories concern distinct aspects of both neural activity and consciousness which, as we suppose, may be integrated and nested within the brain's overall temporo-spatial dynamics.Interpersonal motor alignment is a ubiquitous behavior in daily social life. It is a building block for higher social cognition, including empathy and mentalizing and promotes positive social effects. It can be observed as mimicry, synchrony and automatic imitation, to name a few. These phenomena rely on motor resonance processes, i.e., a direct link between the perception of an action and its execution. While a considerable literature debates its underlying mechanisms and measurement methods, the question of how motor alignment comes about and changes in ontogeny all the way until adulthood, is rarely discussed specifically. In this review we will focus on the link between interpersonal motor alignment, positive social effects and social cognition in infants, children, and adolescents, demonstrating that this link is present early on in development. Yet, in reviewing the existing literature pertaining to social psychology and developmental social cognitive neuroscience, we identify a knowledge gap regarding the healthy developmental changes in interpersonal motor alignment especially in adolescence.Biomineralization research examines structure-function relations in all types of exo- and endo-skeletons and other hard tissues of living organisms, and it relies heavily on 3D imaging. Segmentation of 3D renderings of biomineralized structures has long been a bottleneck because of human limitations such as our available time, attention span, eye-hand coordination, cognitive biases, and attainable precision, amongst other limitations. Since recently, some of these routine limitations appear to be surmountable thanks to the development of deep-learning algorithms for biological imagery in general, and for 3D image segmentation in particular. Many components of deep learning often appear too abstract for a life scientist. Despite this, the basic principles underlying deep learning have many easy-to-grasp commonalities with human learning and universal logic. This primer presents these basic principles in what we feel is an intuitive manner, without relying on prerequisite knowledge of informatics and computer science, and with the aim of improving the reader's general literacy in artificial intelligence and deep learning. Here, biomineralization case studies are presented to illustrate the application of deep learning for solving segmentation and analysis problems of 3D images ridden by various artifacts, and/or which are plainly difficult to interpret. The presented portfolio of case studies includes three examples of imaging using micro-computed tomography (µCT), and three examples using focused-ion beam scanning electron microscopy (FIB-SEM), all on mineralized tissues. We believe this primer will expand the circle of users of deep learning amongst biomineralization researchers and other life scientists involved with 3D imaging, and will encourage incorporation of this powerful tool into their professional skillsets and to explore it further.