Epithelial mesenchymal transition traits in human breast cancer cell lines parallel the CD44HI/CD24lO/-stem cell phenotype in human breast cancer

We review here the recently emerging relationship between epithelial-mesenchymal transition (EMT) and breast cancer stem cells (BCSC), and provide analyses of published data on human breast cancer cell lines, supporting their utility as a model for the EMT/BCSC state. Genome-wide transcriptional profiling of these cell lines has confirmed the existence of a subgroup with mesenchymal tendencies and enhanced invasive properties ('Basal B'/Mesenchymal), distinct from subgroups with either predominantly luminal ('Luminal') or mixed basal/luminal ('Basal A') features (Neve et al. Cancer Cell, 2006). A literature-derived EMT gene signature has shown specific enrichment within the Basal B subgroup of cell lines, consistent with their over-expression of various EMT transcriptional drivers. Basal B cell lines are found to resemble BCSC, being CD44highCD24low. Moreover, gene products that distinguish Basal B from Basal A and Luminal cell lines (Basal B Discriminators) showed close concordance with those that define BCSC isolated from clinical material, as reported by Shipitsin et al. (Cancer Cell, 2007). CD24 mRNA levels varied across Basal B cell lines, correlating with other Basal B Discriminators. Many gene products correlating with CD24 status in Basal B cell lines were also differentially expressed in isolated BCSC. These findings confirm and extend the importance of the cellular product of the EMT with Basal B cell lines, and illustrate the value of analysing these cell lines for new leads that may improve breast cancer outcomes. Gene products specific to Basal B cell lines may serve as tools for the detection, quantification, and analysis of BCSC/EMT attributes.

Parallel authentication and public-key encryption

A parallel authentication and public-key encryption is introduced and exemplified on joint encryption and signing which compares favorably with sequential Encrypt-then-Sign (ɛtS) or Sign-then-Encrypt (Stɛ) schemes as far as both efficiency and security are concerned. A security model for signcryption, and thus joint encryption and signing, has been recently defined which considers possible attacks and security goals. Such a scheme is considered secure if the encryption part guarantees indistinguishability and the signature part prevents existential forgeries, for outsider but also insider adversaries. We propose two schemes of parallel signcryption, which are efficient alternative to Commit-then-Sign-and- Encrypt (Ct&G3&S). They are both provably secure in the random oracle model. The first one, called generic parallel encrypt and sign, is secure if the encryption scheme is semantically secure against chosen-ciphertext attacks and the signature scheme prevents existential forgeries against random-message attacks. The second scheme, called optimal parallel encrypt. and sign, applies random oracles similar to the OAEP technique in order to achieve security using encryption and signature components with very weak security requirements — encryption is expected to be one-way under chosen-plaintext attacks while signature needs to be secure against universal forgeries under random-plaintext attack, that is actually the case for both the plain-RSA encryption and signature under the usual RSA assumption. Both proposals are generic in the sense that any suitable encryption and signature schemes (i.e. which simply achieve required security) can be used. Furthermore they allow both parallel encryption and signing, as well as parallel decryption and verification. Properties of parallel encrypt and sign schemes are considered and a new security standard for parallel signcryption is proposed.

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Part 3. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 3.) Practical application to the design and optimisation of UAV systems

These lecture notes highlight some of the recent applications of multi-objective and multidisciplinary design optimisation in aeronautical design using the framework and methodology described in References 8, 23, 24 and in Part 1 and 2 of the notes. A summary of the methodology is described and the treatment of uncertainties in flight conditions parameters by the HAPEAs software and game strategies is introduced. Several test cases dealing with detailed design and computed with the software are presented and results discussed in section 4 of these notes.

Building energy simulation and parallel computing : opportunities and challenges

Increased focus on energy cost savings and carbon footprint reduction efforts improved the visibility of building energy simulation, which became a mandatory requirement of several building rating systems. Despite developments in building energy simulation algorithms and user interfaces, there are some major challenges associated with building energy simulation; an important one is the computational demands and processing time. In this paper, we analyze the opportunities and challenges associated with this topic while executing a set of 275 parametric energy models simultaneously in EnergyPlus using a High Performance Computing (HPC) cluster. Successful parallel computing implementation of building energy simulations will not only improve the time necessary to get the results and enable scenario development for different design considerations, but also might enable Dynamic-Building Information Modeling (BIM) integration and near real-time decision-making. This paper concludes with the discussions on future directions and opportunities associated with building energy modeling simulations.

Large Scale Simulations of Hippocampal-Neocortical Interactions in a Parallel Version of Genesis

A hippocampal-CA3 memory model was constructed with PGENESIS, a recently developed version of GENESIS that allows for distributed processing of a neural network simulation. A number of neural models of the human memory system have identified the CA3 region of the hippocampus as storing the declarative memory trace. However, computational models designed to assess the viability of the putative mechanisms of storage and retrieval have generally been too abstract to allow comparison with empirical data. Recent experimental evidence has shown that selective knock-out of NMDA receptors in the CA1 of mice leads to reduced stability of firing specificity in place cells. Here a similar reduction of stability of input specificity is demonstrated in a biologically plausible neural network model of the CA3 region, under conditions of Hebbian synaptic plasticity versus an absence of plasticity. The CA3 region is also commonly associated with seizure activity. Further simulations of the same model tested the response to continuously repeating versus randomized nonrepeating input patterns. Each paradigm delivered input of equal intensity and duration. Non-repeating input patterns elicited a greater pyramidal cell spike count. This suggests that repetitive versus non-repeating neocortical inpus has a quantitatively different effect on the hippocampus. This may be relevant to the production of independent epileptogenic zones and the process of encoding new memories.

In silico biology : making the most of parallel computing

Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed.

A parallel approach to social network generation and agent-based epidemic simulation

Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.