CRIPTO and its signaling partner GRP78 drive the metastatic phenotype in human osteotropic prostate cancer

CRIPTO (CR-1, TDGF1) is a cell surface/secreted oncoprotein actively involved in development and cancer. Here, we report that high expression of CRIPTO correlates with poor survival in stratified risk groups of prostate cancer (PCa) patients. CRIPTO and its signaling partner glucose-regulated protein 78 (GRP78) are highly expressed in PCa metastases and display higher levels in the metastatic ALDHhigh sub-population of PC-3M-Pro4Luc2 PCa cells compared with non-metastatic ALDHlow. Coculture of the osteotropic PC-3M-Pro4Luc2 PCa cells with differentiated primary human osteoblasts induced CRIPTO and GRP78 expression in cancer cells and increases the size of the ALDHhigh sub-population. Additionally, CRIPTO or GRP78 knockdown decreases proliferation, migration, clonogenicity and the size of the metastasis-initiating ALDHhigh sub-population. CRIPTO knockdown reduces the invasion of PC-3M-Pro4Luc2 cells in zebrafish and inhibits bone metastasis in a preclinical mouse model. These results highlight a functional role for CRIPTO and GRP78 in PCa metastasis and suggest that targeting CRIPTO/GRP78 signaling may have significant therapeutic potential.Oncogene advance online publication, 10 April 2017; doi:10.1038/onc.2017.87

In situ approaches to studying occupants

This chapter provides an overview of in situ methods to study occupant behavior and presence. The aim of the chapter is to provide new and established researchers with a systematic approach to in situ occupant monitoring studies, while also providing illustrative examples to demonstrate the complexities and solutions for navigating this method. The chapter begins with a recommended systematic procedure for designing, conducting, and publishing in situ occupant studies. Following that, in situ-specific sensor technologies and sensing strategies are discussed in detail, with numerous real examples. This chapter devotes considerable discussion on nuances and practical issues that are frequently encountered during in situ studies, including: sensor placement, validation, access to studied spaces, monitoring spaces with multiple occupants, biases such as the Hawthorne effect, participant recruitment, and ethical c

A library of building occupant behaviour models represented in a standardised schema

Over the past four decades, a substantial body of literature has explored the impacts of occupant behaviour (OB) on building technologies, operation, and energy consumption. A large number of data-driven behavioural models have been developed based on field data. These models lack standardisation and consistency, leading to difficulties in applications and comparison. To address this problem, an ontology was developed using the drivers-needs-actions-systems (DNAS) framework. Recent work has been carried out to implement the theoretical DNAS framework into an eXtensible Markup Language (XML) schema, titled ‘occupant behaviour XML’ (obXML) which is a practical implementation of OB models that can be integrated into building performance simulation (BPS) programs. This paper presents a newly developed library of OB models represented in the standardised obXML schema format. This library provides ready-to-use examples for BPS users to employ more accurate occupant representation in their energy models. The library, which contains an initial effort of 52 OB models, was made publicly available for the BPS community. As part of the library development process, limitations of the obXML schema were identified and addressed, and future improvements were proposed. Authors hope that by compiling this library building, energy modellers from all over the world can enhance their BPS models by integrating more accurate and robust OB patterns

Occupancy and occupants’ actions

Occupants’ presence and actions within the built environment are crucial aspects related to understanding variations in energy use. Within this chapter, first, a nomenclature for the field of research dealing with occupants in buildings is defined. This nomenclature distinguishes between occupants’ presence and behavior, states and actions, adaptive triggers, non-adaptive triggers, and contextual factors. Second, an extensive list of occupant behaviors is provided and categorizations of occupants’ actions are introduced. The list includes most of the possible phenomena that researchers may wish to study, measure, and ultimately model. The categories are physiological, individual, environmental, and spatial adjustments. Third, a list of adaptive and non-adaptive triggers together with contextual factors that could influence occupant behavior is presented. Individual elements are further grouped into physical environmental, physiological, psychological, and social aspects. Finally, a comprehe

A methodology for modelling energy-related human behaviour: Application to window opening behaviour in residential buildings

An energy simulation of a building is a mathematical representation of its physical behaviour considering all the thermal, lighting, acoustics aspects. However, a simulation cannot precisely replicate a real construction because all the simulations are based on a number of key assumptions that affect the results accuracy. Above all, the real energy performance can be affected by the actual behaviour of the building occupants. Thus, there are great benefits to be derived from improving models that simulate the behaviour of human beings within the context of engineered complex systems. The occupant behaviour related to the building control potentialities is a very complex process that has been studied only in the last years with some focuses related to natural ventilation (window opening behaviour), space heating energy demand (in particular the adjustments in the temperature set-point) and natural light (focusing on window blinds adjustments). In this paper, a methodology is presented to model the user behaviour in the context of real energy use and applied to a case study. The methodology, based on a medium/long-term monitoring, is aimed at shifting towards a probabilistic approach for modelling the human behaviour related to the control of indoor environment. The procedure is applied at models of occupants' interactions with windows (opening and closing behaviour). Models of occupants' window opening behaviour were inferred based on measurements and implemented in a simulation program. Simulation results were given as probability distributions of energy consumption and indoor environmental quality depending on user behaviou