Integrated Calendar

Ancestral environmental exposures to endocrine disrupting chemicals (EDCs) can promote epigenetic transgenerational inheritance and influence all aspects of the life history of descendants. What happens in the life of descendant is also important, and it is well established that proximate life events such as chronic stress during adolescence modify elements of the adult phenotype, including physiological, neural, and behavioral traits. We use a systems biology approach to investigate in rats to explore this interaction of the ancestral modifications carried transgenerationally in the germ line and the proximate modifications involving chronic restraint stress during adolescence. We find that a single exposure to a common-use fungicide (vinclozolin) three generations removed alters the physiology, behavior, metabolic activity, and transcriptome in discrete brain nuclei in descendant males, causing them to respond differently to chronic restraint stress. This alteration of baseline brain maturation promotes a change in neural genomic activity that correlates with changes in physiology and behavior, revealing the interaction of genetics, environment, and epigenetic transgenerational inheritance in the shaping of the adult phenotype. Further, in many of these traits females differ fundamentally from males, indicating that such effects are not general but sex-specific in how descendants of these progenitor individuals perceive and respond to a common challenges (e.g., chronic restraint stress) experienced during their own life history.

The Dark Energy Survey has been designed to probe the origin of the accelerating universe and help uncover the nature of dark energy. Starting last September and continuing for five years, DES will survey 5000 square degrees of the southern sky, about 300 million galaxies, and will help constrain dark energy with 5 different probes. I will present two of the projects University College of London has been involved in, both of them using tools from machine learning and, more particularly, artificial neural networks. The first project aims to develop a new method for photometric redshift measurement. The second project aims to redefine DES science requirements in term of star-galaxy separation, and to build a new tool to classify stars and galaxies.