University of Nottingham

Nottingham Research Data Management Repository (University of Nottingham)
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    2142 research outputs found

    Data for Encapsulation of copper phenanthroline within horse spleen apoferritin: characterisation, cytotoxic activity and ability to retain temozolomide

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    In this work, we investigate the encapsulation of a Cu(II)-phenanthroline complex (Cu(phen)(NO3)2) within HSAFt, as a potential vector for the delivery of anticancer agents. We immobilise Cu(II) within the protein as a metal complex with 1,10-phenanthroline, to form HSAFt-Cu(phen) dense particles that can be stored for months at low temperature (-20 °C). We subsequently characterise HSAFt-Cu(phen) by drug release studies and cytotoxicity assays against colorectal cancer cells and glioblastoma multiforme cells. We also investigate whether the presence of Cu(phen) inside HSAFt can offer additional benefits for the encapsulation and antitumour activity of anticancer drugs such as temozolomide (TMZ)

    A participatory system dynamics model to investigate sustainable urban water management in Ebbsfleet Garden City

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    Growing urban populations, changes in rainfall patterns and ageing infrastructure represent significant challenges for urban water management (UWM). There is a critical need for research into how cities should adapt to become resilient to these impacts under uncertain futures. UWM challenges in the Ebbsfleet Garden City (UK) were investigated via a participatory process and potential sustainable solutions were explored using a System Dynamics Model (SDM). Collaborative development of the SDM by the Ebbsfleet Learning and Action Alliance developed stakeholders’ understanding of future UWM options and enabled a structured exploration of interdependencies within the current UWM system. Discussion by stakeholders resulted in a focus on potable water use and the development of the SDM to investigate how residential potable water consumption in the Ebbsfleet Garden City might be reduced through a range of interventions, e.g., socio-environmental and economic policy incentives. The SDM approach supports decision-making at a strategic, system-wide level, and facilitates exploration of the long-term consequences of alternative strategies, particularly those that are difficult to include in quantitative models. While an SDM can be developed by experts alone, building it collaboratively allows the process to benefit from local knowledge, resulting in a collective learning process and increased potential for adoption

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