Interaction between the 5-HT system and the basal ganglia: functional implication and therapeutic perspective in Parkinson's disease

The neurotransmitter serotonin (5-HT) has a multifaceted function in the modulation of information processing through the activation of multiple receptor families, including G-protein-coupled receptor subtypes (5-HT1, 5-HT2, 5-HT4-7) and ligand-gated ion channels (5-HT3). The largest population of serotonergic neurons is located in the midbrain, specifically in the raphe nuclei. Although the medial and dorsal raphe nucleus (DRN) share common projecting areas, in the basal ganglia (BG) nuclei serotonergic innervations come mainly from the DRN. The BG are a highly organized network of subcortical nuclei composed of the striatum (caudate and putamen), subthalamic nucleus (STN), internal and external globus pallidus (or entopeduncular nucleus in rodents, GPi/EP and GPe) and substantia nigra (pars compacta, SNc, and pars reticulata, SNr). The BG are part of the cortico-BG-thalamic circuits, which play a role in many functions like motor control, emotion, and cognition and are critically involved in diseases such as Parkinson's disease (PD). This review provides an overview of serotonergic modulation of the BG at the functional level and a discussion of how this interaction may be relevant to treating PD and the motor complications induced by chronic treatment with L-DOPA.

Development of nucleic acid vaccines: use of self-amplifying RNA in lipid nanoparticles

Self-amplifying RNA or RNA replicon is a form of nucleic acid-based vaccine derived from either positive-strand or negative-strand RNA viruses. The gene sequences encoding structural proteins in these RNA viruses are replaced by mRNA encoding antigens of interest as well as by RNA polymerase for replication and transcription. This kind of vaccine has been successfully assayed with many different antigens as vaccines candidates, and has been shown to be potent in several animal species, including mice, nonhuman primates, and humans. A key challenge to realizing the broad potential of self-amplifying vaccines is the need for safe and effective delivery methods. Ideally, an RNA nanocarrier should provide protection from blood nucleases and extended blood circulation, which ultimately would increase the possibility of reaching the target tissue. The delivery system must then be internalized by the target cell and, upon receptor-mediated endocytosis, must be able to escape from the endosomal compartment into the cell cytoplasm, where the RNA machinery is located, while avoiding degradation by lysosomal enzymes. Further, delivery systems for systemic administration ought to be well tolerated upon administration. They should be safe, enabling the multiadministration treatment modalities required for improved clinical outcomes and, from a developmental point of view, production of large batches with reproducible specifications is also desirable. In this review, the concept of self-amplifying RNA vaccines and the most promising lipid-based delivery systems are discussed.

The Cryo-EM Structure of a Complete 30S Translation Initiation Complex from Escherichia coli

11 p.

Prioritization of candidate cancer genes-an aid to oncogenomic studies

The development of techniques for oncogenomic analyses such as array comparative genomic hybridization, messenger RNA expression arrays and mutational screens have come to the fore in modern cancer research. Studies utilizing these techniques are able to highlight panels of genes that are altered in cancer. However, these candidate cancer genes must then be scrutinized to reveal whether they contribute to oncogenesis or are coincidental and non-causative. We present a computational method for the prioritization of candidate (i) proto-oncogenes and (ii) tumour suppressor genes from oncogenomic experiments. We constructed computational classifiers using different combinations of sequence and functional data including sequence conservation, protein domains and interactions, and regulatory data. We found that these classifiers are able to distinguish between known cancer genes and other human genes. Furthermore, the classifiers also discriminate candidate cancer genes from a recent mutational screen from other human genes. We provide a web-based facility through which cancer biologists may access our results and we propose computational cancer gene classification as a useful method of prioritizing candidate cancer genes identified in oncogenomic studies.