142 research outputs found

    Considering the impact of situation-specific motivations and constraints in the design of naturally ventilated and hybrid buildings

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    A simple logical model of the interaction between a building and its occupants is presented based on the principle that if free to do so, people will adjust their posture, clothing or available building controls (windows, blinds, doors, fans, and thermostats) with the aim of achieving or restoring comfort and reducing discomfort. These adjustments are related to building design in two ways: first the freedom to adjust depends on the availability and ease-of-use of control options; second the use of controls affects building comfort and energy performance. Hence it is essential that these interactions are considered in the design process. The model captures occupant use of controls in response to thermal stimuli (too warm, too cold etc.) and non-thermal stimuli (e.g. desire for fresh air). The situation-specific motivations and constraints on control use are represented through trigger temperatures at which control actions occur, motivations are included as negative constraints and incorporated into a single constraint value describing the specifics of each situation. The values of constraints are quantified for a range of existing buildings in Europe and Pakistan. The integration of the model within a design flow is proposed and the impact of different levels of constraints demonstrated. It is proposed that to minimise energy use and maximise comfort in naturally ventilated and hybrid buildings the designer should take the following steps: 1. Provide unconstrained low energy adaptive control options where possible, 2. Avoid problems with indoor air quality which provide motivations for excessive ventilation rates, 3. Incorporate situation-specific adaptive behaviour of occupants in design simulations, 4. Analyse the robustness of designs against variations in patterns of use and climate, and 5. Incorporate appropriate comfort standards into the operational building controls (e.g. BEMS)

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

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    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

    A Single Molecule Scaffold for the Maize Genome

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    About 85% of the maize genome consists of highly repetitive sequences that are interspersed by low-copy, gene-coding sequences. The maize community has dealt with this genomic complexity by the construction of an integrated genetic and physical map (iMap), but this resource alone was not sufficient for ensuring the quality of the current sequence build. For this purpose, we constructed a genome-wide, high-resolution optical map of the maize inbred line B73 genome containing >91,000 restriction sites (averaging 1 site/∼23 kb) accrued from mapping genomic DNA molecules. Our optical map comprises 66 contigs, averaging 31.88 Mb in size and spanning 91.5% (2,103.93 Mb/∼2,300 Mb) of the maize genome. A new algorithm was created that considered both optical map and unfinished BAC sequence data for placing 60/66 (2,032.42 Mb) optical map contigs onto the maize iMap. The alignment of optical maps against numerous data sources yielded comprehensive results that proved revealing and productive. For example, gaps were uncovered and characterized within the iMap, the FPC (fingerprinted contigs) map, and the chromosome-wide pseudomolecules. Such alignments also suggested amended placements of FPC contigs on the maize genetic map and proactively guided the assembly of chromosome-wide pseudomolecules, especially within complex genomic regions. Lastly, we think that the full integration of B73 optical maps with the maize iMap would greatly facilitate maize sequence finishing efforts that would make it a valuable reference for comparative studies among cereals, or other maize inbred lines and cultivars

    Systems microscopy approaches to understand cancer cell migration and metastasis

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    Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration
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