Synaptophysin interacts with synaptobrevin in membranes of adult small synaptic vesicles. The synaptophysin/synaptobrevin complex promotes synaptobrevin to built up functional SNARE complexes thereby modulating synaptic efficiency. Synaptophysin in addition is a cholesterol-binding protein.Depleting the membranous cholesterol content by filipin or b-methylcyclodextrin (b-MCD) decreased the solubility of synaptophysin in Triton X-100 with less effects on synaptobrevin. In small synaptic vesicles from rat brain the synaptophysin/ synaptobrevin complex was diminished upon b-MCD treatment as revealed by chemical cross-linking. Mice with a genetic mutation in the Niemann-Pick C1 gene developing a defect in cholesterol sorting showed significantly reduced amounts of the synaptophysin/synaptobrevin complex compared to their homo-or heterozygous littermates. Finally when using primary cultures of mouse hippocampus the synaptophysin/synaptobrevin complex was down-regulated after depleting the endogenous cholesterol content by the HMG-CoA-reductase inhibitor lovastatin. Alternatively, treatment with cholesterol up-regulated the synaptophysin/synaptobrevin interaction in these cultures. These data indicate that the synaptophysin/synaptobrevin interaction critically depends on a high cholesterol content in the membrane of synaptic vesicles. Variations in the availability of cholesterol may promote or impair synaptic efficiency by interfering with this complex.
HighlightsMost EU Member States developed HEPA policies on “Sport”, “Health”, and “Education” sectors (27, 23 and 27, respectively).Seventeen countries developed policies on “Environment, Urban Planning, and Public Safety” and 16 on “Working Environment”.Less than 50% of the countries (N = 13) developed policies on the “Senior Citizens” sector.Few countries have implemented policies covering all areas of the monitoring framework.
Systems Biology is an approach to biology and medicine that has the potential to lead to a better understanding of how biological properties emerge from the interaction of genes, proteins, molecules, cells and organisms. The approach aims at elucidating how these interactions govern biological function by employing experimental data, mathematical models and computational simulations. As Systems Biology is inherently multidisciplinary, education within this field meets numerous hurdles including departmental barriers, availability of all required expertise locally, appropriate teaching material and example curricula. As university education at the Bachelor’s level is traditionally built upon disciplinary degrees, we believe that the most effective way to implement education in Systems Biology would be at the Master’s level, as it offers a more flexible framework. Our team of experts and active performers of Systems Biology education suggest here (i) a definition of the skills that students should acquire within a Master’s programme in Systems Biology, (ii) a possible basic educational curriculum with flexibility to adjust to different application areas and local research strengths, (iii) a description of possible career paths for students who undergo such an education, (iv) conditions that should improve the recruitment of students to such programmes and (v) mechanisms for collaboration and excellence spreading among education professionals. With the growing interest of industry in applying Systems Biology approaches in their fields, a concerted action between academia and industry is needed to build this expertise. Here we present a reflection of the European situation and expertise, where most of the challenges we discuss are universal, anticipating that our suggestions will be useful internationally. We believe that one of the overriding goals of any Systems Biology education should be a student’s ability to phrase and communicate research questions in such a manner that they can be solved by the integration of experiments and modelling, as well as to communicate and collaborate productively across different experimental and theoretical disciplines in research and development.
Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.
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