Rapid progress in biotechnology has introduced a host of pressing ethical and policy issues pertaining to stem cell research. In this review, we provide an overview of the most significant issues with which the stem cell research community should be familiar. We draw on a sample of the bioethics and scientific literatures to address issues that are specific to stem cell research and therapy, as well as issues that are important for stem cell research and therapy but also for translational research in related fields, and issues that apply to all clinical research and therapy. Although debate about the moral status of the embryo in human embryonic stem cell research continues to have relevance, the discovery of other highly multipotent stem cell types and alternative methods of isolating and creating highly multipotent stem cells has raised new questions and concerns. Induced pluripotent stem cells hold great promise, but care is needed to ensure their safety in translational clinical trials, despite the temptation to move quickly from bench to bedside. A variety of highly multipotent stem cells - such as mesenchymal stem/stromal cells and stem cells derived from amniotic fluid, umbilical cord blood, adipose tissue, or urine - present the opportunity for widespread biobanking and increased access. With these increased opportunities, however, come pressing policy issues of consent, control, and justice. The imperatives to minimize risks of harm, obtain informed consent, reduce the likelihood of the therapeutic misconception, and facilitate sound translation from bench to bedside are not unique to stem cell research; their application to stem cell research and therapy nonetheless merits particular attention. Because stem cell research is both scientifically promising and ethically challenging, both the application of existing ethical frameworks and careful consideration of new ethical implications are necessary as this broad and diverse field moves forward.

Life expectancy and other outcomes for patients with serious mental illness (SMI) are unacceptably poor, largely due to a high prevalence of poorly controlled chronic diseases, high rates of tobacco use, and low rates of preventive care services. Since many of these illnesses are effectively treated in primary care settings, integrating primary care with behavioral health care is necessary to narrow health disparities for patients with SMI.

<div class="section abstract"><div class="htmlview paragraph">The development of perception functions for tomorrow’s automated vehicles is driven by enormous amounts of data: often exceeding a gigabyte per second and reaching into the terabytes per hour. Data is typically gathered by a fleet of dozens of mule vehicles which multiply the data generated into the hundreds of petabytes per year. Traditional methods for fueling data-driven development would record every bit of every second of a data logging drive on solid-state drives located on a PC in the vehicle. Recorded data must then be exported from these drives using an upload station which pushes to the data lake after arriving back at the garage.</div><div class="htmlview paragraph">This paper considers different techniques for curating logged data. These curation methods are performed to maximize the usefulness of the data throughout its lifecycle and minimize the amount of data necessary for perception development and validation The reduction of logged data has the effect of not only curtailing storage costs, but also minimizing latency for data availability and maximizing possible campaign drive time. Advanced techniques considered include: (a) the real-time evaluation of sensor and bus signals, (b) the application of artificial intelligence (e.g. for similarity-based image discovery and dynamic scene content detection), and (c) using function prototyping to inform the data curation process. In addition, various possible integration points for the curation techniques are considered in the data ingestion pipeline - from the cloud in the datacenter to the in-vehicle logging system on the edge. The trade-offs for each proposed techniques are considered across the various components of the data ingestion pipeline to explore the feasibility of - and to arrive at some conclusions for - designing more intelligent data collection campaigns.</div></div>

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