This article reports briefly on the first UK prevalence study (undertaken in 2006-7) of the abuse and neglect of older people living in the community. Older people living in the community who reported mistreatment and neglect (2.6 per cent) equate to about 227,000 of the population aged 66 years and over. If figures are broadened to include neighbours and acquaintances, prevalence increases from 2.6 per cent to 4.0 per cent. This article identifies risk factors of loneliness, depression and poor quality of life. It suggests that nurses have a key role in day-to-day clinical practice in enabling older people to report abuse and neglect.
Acute myeloid leukemia (AML) is a phenotypically and genetically heterogeneous hematologic malignancy. Extensive sequencing efforts have mapped the genomic landscape of adult and pediatric AML revealing a number of biologically and prognostically relevant driver lesions. Beyond identifying recurrent genetic aberrations, it is of critical importance to fully delineate the complex mechanisms by which they contribute to the initiation and evolution of disease to ultimately facilitate the development of targeted therapies. Towards these aims, murine models of AML are indispensable research tools. The rapid evolution of genetic engineering techniques over the past 20 years has greatly advanced the use of murine models to mirror specific genetic subtypes of human AML, define cell-intrinsic and extrinsic disease mechanisms, study the interaction between co-occurring genetic lesions, and test novel therapeutic approaches. This review summarizes the mouse model systems that have been developed to recapitulate the most common genomic subtypes of AML. We will discuss the strengths and weaknesses of varying modeling strategies, highlight major discoveries emanating from these model systems, and outline future opportunities to leverage emerging technologies for mechanistic and preclinical investigations.
The IceCube Neutrino Observatory at the South Pole has tremendous emotional appeal-the extreme Antarctic environment coupled with the aura of a pioneering experiment that explores the universe in a new way. However, as with most cutting-edge experiments, it is still challenging to translate the exotic, demanding science into accessible language. We present three examples of recent successful education, outreach, and communication activities that demonstrate how we leverage efforts and sustain connections to produce engaging results. First we describe our participation in the PolarTREC program, which pairs researchers with educators to provide deployments in the Antarctic, and how we have sustained relationships with these educators to produce highquality experiences to reach target audiences even during a pandemic. We then focus on three activities from the past year: a summer enrichment program for high school students that was also modified for a 10-week IceCube after school program, a virtual visit to the South Pole for the ScienceWriters 2020 conference, and a series of short videos in English and Spanish suitable for all ages that explain traveling, living, and working at the South Pole.
This year sees the ALCF looking forward. As we prepare to enter the exascale era, the future of leadership computing lies in simulation, data, and learning. To best support this paradigm, we are striving to direct our efforts to develop the facility so that its growth synergizes with our users' research.In 2018, we expanded the Aurora Early Science Program (ESP), adding data analysis and machine learning projects to the simulation-based projects already underway.Collectively, these projects cover various combinations of techniques and approaches across a wide range of disciplines and goals. Common to all of them, though, is a substantial data challenge: at this point in computational science, data problems are no longer unique to projects that explicitly identify as such.The ALCF Data Science Program (ADSP) is yet another way we support projects that rely on advanced computational methods to enable data-driven discoveries. In addition, this year marked the first time that the INCITE program has explicitly sought data-and learning-based projects as part of its annual call for proposals.Partnering with the research teams supported by these programs allows us to take a collaborative approach to exploring not simply how to elevate the roles of data in computational science, but how to strike the appropriate balance between them and construct an architecture readily adaptable to each project's needs. A L c fWith a peak performance of more than 11 petaflops, the ALCF's Theta system is among the fastest supercomputers in the world for open scientific research.
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