SUMMARYDeregulated Ras signalling is implicated in most human neoplasia, exemplified by melanoma. Whereas Raf activation occurs almost ubiquitously in benign and malignant melanocytic neoplasms, implying an involvement in tumour initiation, phosphoinositide 3-kinase (PI3K) activation occurs predominantly in malignant neoplasms, implying an involvement in malignant progression. Here, we dissect the contributions of these two pathways to tumourigenesis in vivo, by modulating their activities in zebrafish melanocytes. Misexpression of oncogenic Ras (V12RAS) in founder fish induced frequent melanoma, beginning at larval stages, with concomitant activation of Raf-Mek-Erk and PI3K-Akt signalling. Misexpression of effector-domain mutants of V12RAS, or of various downstream effectors, confirmed a selective role for the Raf-Mek-Erk pathway in initiating neoplasia, but highlighted the requirement for additional Ras effector pathways for malignancy. The phenotype of animals with germ-line transmission of V12RAS resembled familial atypical mole and melanoma (FAMM) syndrome: melanocytes displayed hyperplasia, dysplasia, altered terminal differentiation and spontaneously progressed to invasive melanoma. Co-expressing a dominant-interfering form of PI3K abolished V12RAS-induced malignancy, demonstrating a direct role for PI3K signalling in the malignant progression of melanoma in vivo, and highlighting PI3K as a promising target for melanoma therapy.
The distributiveness and heterogeneity of today's systems of systems, such as the Internet of Things (IoT), on-line banking systems, and contemporary emergency information systems, require the integration of access and usage control mechanisms, for managing the right of access both to the corresponding services, and the plethora of information that is generated in a daily basis. Usage Control (UCON) is such a mechanism, allowing the fine-grained policy based management of system resources, based on dynamic monitoring and evaluation of object, subject, and environmental attributes. Yet, as we presented in an earlier article, a number of improvements can be introduced to the standard model regarding its resilience on active attacks, the simplification of the policy writing, but also in terms of run-time efficiency and scalability. In this article, we present an enhanced usage control architecture, that was developed for tackling the aforementioned issues. In order to achieve that, a dynamic role allocation system will be added to the existing architecture, alongside with a service grouping functionality which will be based on attribute aggregation. This is structured in accordance to a risk-based framework, which has been developed in order to aggregate the risk values that the individual attributes encapsulate into a unified risk value. These architectural enhancements are utilized in order to improve the resilience, scalability, and run-time efficiency of the existing model.
The enforcement of fine-grained access control policies in constrained dynamic networks can become a challenging task. The inherit constraints present in those networks, which result from the limitations of the edge devices in terms of power, computational capacity and storage, require an effective and efficient access control mechanism to be in place to provide suitable monitoring and control of actions and regulate the access over the resources. In this article, we present RESPOnSE, a framework for the specification and enforcement of security policies within such environments, where the computational burden is transferred to high-tier nodes, while low-tier nodes apply risk-aware policy enforcement. RESPOnSE builds on a combination of two widely used access control models, Attribute-Based Access Control and Role-Based Access Control, exploiting the benefits each one provides. Moreover, the proposed mechanism is founded on a compensatory multicriteria decision-making algorithm, based on the calculation of the Euclidean distance between the run-time values of the attributes present in the security policy and their ideal values, as those are specified within the established policy rules.
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