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In vitro model systems used in drug discovery typically do not address the complex architecture of human disease tissues. Only few approaches aim to faithfully recapitulate the complexity, heterogeneity and cellular dynamics e.g. in epithelial tissues and carcinomas. The most important aspects relate to the (tumor-) microenvironment, including cell-cell and cell-matrix interactions, inflammation and the role of stromal components. All of these elements can have a significant, but often underestimated impact on differentiation, normal and abnormal tissue functions, or drug response versus drug resistance.

The basis for performing informative high content screening campaigns with such complex tissue models in vitro is access to fast, automated image analysis. We have developed a software platform (AMIDA, Automated Morphometric Image Data Analysis) that captures a large number of morphometric features in an unsupervised fashion. This approach enables us to capture much of the inherent complexity and dynamics of microtissues, yet still allows high experimental throughput. This screening platform is ideally suited for investigating a broad spectrum of defined, biological questions in drug discovery as well as personalised medicine.

Technology and screening platform are applicable for multiple types of research, such as quantitatively measuring the response of primary cancer cells or cell lines to drugs, siRNAs or other perturbations. Image analysis algorithms can also be adapted towards specific applications in neurodegenerative diseases, stem cell research, and to quantitate the interaction of epithelial cells with immune, adipocytes or mesenchymal stem cells.

Understanding the Self has fascinated artists, writers, philosophers and psychologist for generation. In the past two decades cognitive and neurocognitive tools have been applied to the study of the Self. The talk will present research on the Self and the Friend. Not surprisingly, it is consistently found that our brain prioritize the Self. For example, deciding whether a face looks to the left or right is faster on one’s own face than on a face of a friend. This prioritization transcend time, showing similar prioritization to one’s face in the past as in the present. Lesions to the fusiform gyrus hinders Self facilitation, while lesions to lateral frontal cortices amplifies it. Associating a simple geometric shape to oneself is done much more efficiently than to a stranger an effect that is mediated via the left STS, medial and lateral frontal cortices. Participants are also better at judging a perspective of an avatar if it is tagged as them than as a stranger. But in all these studies the Friend is also prioritized relative to a stranger. Why is the friend prioritized, is it because it is relevant, or because it is liked? In a simple shape-identity matching task, we manipulated orthogonally the valence and relevance of familiar identities. We found that prioritization is given based on relevance and valence in Western culture, but primarily based on valance in Asian cultures. Using spatial maps to represent the social space, we observed consistent representation of social relations as physical distances. Physical distance between identities was affected by the valence and relevance factors, though this was modulated by the participants’ culture. Finally, presenting participants with incongruent spatial maps of their social relations, resulted in increase and decrease responses in a large network of regions including the Amygdala and superior temporal structure known to play a rule in social cognition. Taken together this body of work highlight neurocognitive mechanism by which our brain prioritize information based on social rules.