摘要 :
Multiple processes are increasingly recognized as being responsible for species' extinctions. We evaluated population extinctions between 1930 and 1998 for the endangered Quino checkerspot (Euphydryas editha quino) butterfly relat...
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Multiple processes are increasingly recognized as being responsible for species' extinctions. We evaluated population extinctions between 1930 and 1998 for the endangered Quino checkerspot (Euphydryas editha quino) butterfly relative to agricultural history, human population growth, climate variability, topographical diversity, and wildflower abundance. Overall agricultural land use was calculated for extinct and extant populations based upon cultivation and grazing intensities averaged across five time periods reflecting distinct agricultural practices from 1769 to present. Extinct populations were associated with a history of more intensive agriculture and greater human population growth at time of extinction. A long history of intensive livestock grazing was the strongest agricultural predictor of extinction. Based upon historic vegetation maps, extinct butterfly populations were typically isolated from other known populations by 1930, and in landscapes fragmented by cultivation and development. Precipitation and topographical variability were not important predictors of extinction. Wildflower host plants and nectar sources have declined across the butterfly's range because of invasive plants and habitat loss. The proportion of years considered average or abundant in wildflowers declined significantly during extinction periods. The Quino checkerspot has shifted in distribution from the coast into foothills and mountains. Newly discovered higher elevation populations experience more precipitation and are buffered from drought. Efforts to conserve Quino checkerspot are enhanced by understanding that the butterfly's decline and shifting distribution is a complex multi-scale process related to agricultural history, human population growth, climate variability, and wildflower decline.
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摘要 :
Clinical trials are a fundamental tool used to evaluate the efficacy and safety of new drugs and medical devices and other health system interventions. The traditional clinical trials system acts as a quality funnel for the develo...
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Clinical trials are a fundamental tool used to evaluate the efficacy and safety of new drugs and medical devices and other health system interventions. The traditional clinical trials system acts as a quality funnel for the development and implementation of new drugs, devices and health system interventions. The concept of a “digital clinical trial” involves leveraging digital technology to improve participant access, engagement, trial-related measurements, and/or interventions, enable concealed randomized intervention allocation, and has the potential to transform clinical trials and to lower their cost. In April 2019, the US National Institutes of Health (NIH) and the National Science Foundation (NSF) held a workshop bringing together experts in clinical trials, digital technology, and digital analytics to discuss strategies to implement the use of digital technologies in clinical trials while considering potential challenges. This position paper builds on this workshop to describe the current state of the art for digital clinical trials including (1) defining and outlining the composition and elements of digital trials; (2) describing recruitment and retention using digital technology; (3) outlining data collection elements including mobile health, wearable technologies, application programming interfaces (APIs), digital transmission of data, and consideration of regulatory oversight and guidance for data security, privacy, and remotely provided informed consent; (4) elucidating digital analytics and data science approaches leveraging artificial intelligence and machine learning algorithms; and (5) setting future priorities and strategies that should be addressed to successfully harness digital methods and the myriad benefits of such technologies for clinical research.
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