The receptor erbB2/neu is a member of the epidermal growth factor receptor (EGFR or erbB) family that also includes erbB3 and erbB4. Amplification of the erbB2/neu gene is found in many cancer types and its overexpression is correlated with a poor prognosis for breast and ovarian cancer patients. Investigation of the biology of erbB2 led to the identification of a family of ligands termed neuregulins which included the neu-differentiation factors, the heregulins, a ligand with acetylcholine-receptor-inducing activity and glial growth factor. Several lines of evidence suggest that heterodimerization of erbB2 with other erbB receptors is required for neuregulin signalling. Here we investigate the developmental role of erbB2 in mammalian development in mice carrying an erbB2 null allele. We find that mutant embryos die before E11, probably as a result of dysfunctions associated with a lack of cardiac trabeculae. Development of cranial neural-crest-derived sensory ganglia was markedly affected. DiI retrograde tracing revealed that the development of motor nerves was also compromised. Our results demonstrate the importance of erbB2 in neural and cardiac development.

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Abstract-Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

Model-driven engineering promotes models and model transformations as the primary assets in software development. The models@run-time approach provides an abstract representation of a system at run-time, whereby changes in the model and the system are constantly reflected on each other. In this paper, we report on more than three years of experience with realising models@run-time in scalable cloud scenarios using a technology stack consisting of the Eclipse Modelling Framework (EMF) and Connected Data Objects (CDO). We establish requirements for the three roles domain-specific language (DSL) designer, developer, and operator, and compare them against the capabilities of EM-F/CDO. It turns out that this technology stack is well-suited for DSL designers, but less recommendable for developers and even less suited for operators. For these roles, we experienced a steep learning curve and several lacking features that hinder the implementation of models@run-time in scalable cloud scenarios. Performance experiences show limitations for write heavy scenarios with an increasing amount of total elements. While we do not discourage the use of EMF/CDO for such scenarios, we recommend that its adoption for similar use cases is carefully evaluated until this technology stack has realised our wish list of advanced features.