Key signalling nodes in mammary gland development and cancer. Signalling downstream of PI3 kinase in mammary epithelium: a play in 3 Akts

The protein serine/threonine kinase Akt, also known as protein kinase B (PKB), is arguably the most important signalling nexus in the cell. Akt integrates a plethora of extracellular signals to generate diverse outcomes, including proliferation, motility, growth, glucose homeostasis, survival, and cell death. The phosphatidylinositol 3-kinase (PI3K)/Akt pathway is the second most frequently mutated pathway in cancer, after p53, and mutations in components of this pathway are found in around 70% of breast cancers. Thus, understanding how Akt relays input signals to downstream effectors is critically important for the design of therapeutic strategies to combat breast cancer. In this review, we will discuss the various signals upstream of Akt that impact on its activity, how Akt integrates these signals and modulates the activity of downstream targets to control mammary gland development, and how mutations in components of the pathway result in breast cancer

Role and task allocation framework for Multi-Robot Collaboration with latent knowledge estimation

In this work a novel framework for modeling role and task allocation in Cooperative Heterogeneous Multi-Robot Systems (CHMRSs) is presented. This framework encodes a CHMRS as a set of multidimensional relational structures (MDRSs). This set of structure defines collaborative tasks through both temporal and spatial relations between processes of heterogeneous robots. These relations are enriched with tensors which allow for geometrical reasoning about collaborative tasks. A learning schema is also proposed in order to derive the components of each MDRS. According to this schema, the components are learnt from data reporting the situated history of the processes executed by the team of robots. Data are organized as a multirobot collaboration treebank (MRCT) in order to support learning. Moreover, a generative approach, based on a probabilistic model, is combined together with nonnegative tensor decomposition (NTD) for both building the tensors and estimating latent knowledge. Preliminary evaluation of the performance of this framework is performed in simulation with three heterogeneous robots, namely, two Unmanned Ground Vehicles (UGVs) and one Unmanned Aerial Vehicle (UAV)

Mammary Involution and Breast Cancer Risk: Transgenic Models and Clinical Studies

Postlactational involution is the process following weaning during which the mammary gland undergoes massive cell death and tissue remodeling as it returns to the pre-pregnant state. Lobular involution is the process by which the breast epithelial tissue is gradually lost with aging of the mammary gland. While postlactational involution and lobular involution are distinct processes, recent studies have indicated that both are related to breast cancer development. Experiments using a variety of rodent models, as well as observations in human populations, suggest that deregulation of postlactational involution may act to facilitate tumor formation. By contrast, new human studies show that completion of lobular involution protects against subsequent breast cancer incidence