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Sphingosine 1-phosphate (S1P) signaling influences numerous cell biological mechanisms such as differentiation, proliferation, survival, migration, and angiogenesis. Intriguingly, our current knowledge is based solely on the role of S1P with an 18-carbon long-chain base length, S1P d18:1. Depending on the composition of the first and rate-limiting enzyme of the sphingolipid de novo metabolism, the serine palmitoyltransferase, other chain lengths have been described in vivo. While cells are also able to produce S1P d20:1, its abundance and function remains elusive so far. Our experiments are highlighting the role of S1P d20:1 in the mouse central nervous system (CNS) and human glioblastoma. We show here that S1P d20:1 and its precursors are detectable in both healthy mouse CNS-tissue and human glioblastoma. On the functional level, we focused our work on one particular, well-characterized pathway, the induction of cyclooxygenase (COX)-2 expression via the S1P receptor 2 (S1P2). Intriguingly, S1P d20:1 only fairly induces COX-2 expression and can block the S1P d18:1-induced COX-2 expression mediated via S1P2 activation in the human glioblastoma cell line LN229. This data indicates that S1P d20:1 might act as an endogenous modulator of S1P signaling via a partial agonism at the S1P2 receptor. While our findings might stimulate further research on the relevance of long-chain base lengths in sphingolipid signaling, the metabolism of S1P d20:1 has to be considered as an integral part of S1P signaling pathways in vivo.
The dissertation deals with the general problem of how the brain can establish correspondences between neural patterns stored in different cortical areas. Although an important capability in many cognitive areas like language understanding, abstract reasoning, or motor control, this thesis concentrates on invariant object recognition as application of correspondence finding. One part of the work presents a correspondence-based, neurally plausible system for face recognition. Other parts address the question of visual information routing over several stages by proposing optimal architectures for such routing ('switchyards') and deriving ontogenetic mechanisms for the growth of switchyards. Finally, the idea of multi-stage routing is united with the object recognition system introduced before, making suggestions of how the so far distinct feature-based and correspondence-based approaches to object recognition could be reconciled.