CHARACTERIZATION OF THE HABENULO-INTERPEDUNCULAR PATHWAY IN THE ZEBRAFISH BRAIN

In the brain of all vertebrates the bilaterally-paired habenular (Hb) nuclei of the dorsal diencephalon predominately innervate a shared midbrain target, the interpeduncular nucleus (IPN). The Hb-IPN pathway has been implicated in many behaviors including fear/anxiety, addiction, and sleep. To better understand the molecular, anatomical and connectivity features of this conserved and essential pathway, I characterized the Hb-IPN system of the zebrafish brain. I identified a previously unknown population of somatostatinergic neurons in the dorsal habenular nuclei (dHb) (homologous to the mammalian medial Hb). In zebrafish and other teleosts, the dHb show prominent left-right differences in size, organization and molecular characteristics. Accordingly, the somatostatinergic neuronal population is larger in the right dHb compared to the left. These findings and related work on other neurotransmitters and neuropeptides contribute to a more comprehensive map of neuronal organization in the zebrafish dHb. By generating a transgenic line that selectively labels somatostatinergic dHb neurons with a membrane-tagged fluorescent protein, I determined that they innervate a discrete region of the ventral IPN (vIPN), which is enriched in neurons expressing the algesic neuropeptide nociceptin. The results reveal a precise connection between subregions of the dHb and the IPN and lead to a model in which somatostatinergic dHb neurons inhibit neural activity in the vIPN and, thus, regulating serotonin in the raphe nucleus to modulate fear and pain processing. Further, I conducted transcriptional profiling of the IPN by taking advantage of a transgenic line, in which fluorescent labeling permits microdissection of IPN tissue. Transcriptional profiling identified over five hundred transcripts enriched in the IPN. I confirmed the expression of a subset of genes that encode neuropeptides, proteins involved in neurotransmitter synthesis or reception and proteins with localized functions in the dorsal, intermediate or ventral IPN. This information is valuable for understanding the organization of the IPN and the molecular and functional diversity of its neuronal populations. The above results, along with my work on validating new transgenic techniques for gene regulation in zebrafish, provide a better understanding of the Hb-IPN pathway as well as a valuable set of tools for future studies on its diverse functions

Managing Uncertainty and Ontologies in Databases

Nowadays a vast amount of data is generated in Extensible Markup Language (XML). However, it is necessary for applications in some domains to store and manipulate uncertain information, e.g. when the sensor inputs are noisy, or we want to store data that is uncertain. Another big change we can see in applications and web data is the increasing use of ontologies to describe the semantics of data, i.e., the semantic relationships between the terms in the databases. As such information is usually absent from traditional databases, there is tremendous opportunity to ask new kinds of queries that could not be handled in the past. This provides new challenges on how to manipulate and maintain such new kinds of database systems. In this dissertation, we will see how we can (i) incorporate and manipulate uncertainty in databases, and (ii) efficiently compute aggregates and maintain views on ontology databases. First, I explain applications that require manipulating uncertain information in XML databases and maintaining web ontology databases written in Resource Description Framework (RDF). I then introduce the probabilistic semistructured PXML data model with two formal semantics. I describe a set of algebraic operations and its efficient implementation. Aggregations of PXML instances are studied with two semantics proposed: possible-worlds semantics and expectation semantics. Efficient algorithms with pruning are given and evaluated to show their feasibility. I introduce PIXML, an interval probability version of PXML, and develop a formal semantics for it. A query language and its operational semantics are given and proved to be sound and complete. Based on XML, RDF is a language used to describe web ontologies. RDQL, an RDF query language, is extended to support view definition and aggregations. Two sets of algorithms are given to maintain non-aggregate and aggregate views. Experimental results show that they are efficient compared with standard relational view maintenance algorithms