RESUMO
Mobile health tools are often said to empower users by providing them with the information they need to exercise control over their health. We aim to bring clarity to this claim, and in doing so explore the relationship between empowerment and autonomy. We have identified three distinct models embedded in the empowerment rhetoric: empowerment as information, empowerment as control, and empowerment as values. Each distinct model of empowerment gives rise to an associated problem. These problems, the Problem of Interpretation, the Value Alignment Problem, and the Priority Problem, show that mobile health tools in their current form are either insufficient for empowerment or are self-defeating. These digital health technologies encourage users to adopt an individualized conception of autonomy, one that may weaken the doctor-patient relationship and undermine practices in shared decision making, and ultimately may not deliver on improving the health outcomes for those that need it the most.
RESUMO
mRNA synthesis, processing, and destruction involve a complex series of molecular steps that are incompletely understood. Because the RNA intermediates in each of these steps have finite lifetimes, extensive mechanistic and dynamical information is encoded in total cellular RNA. Here we report the development of SnapShot-Seq, a set of computational methods that allow the determination of in vivo rates of pre-mRNA synthesis, splicing, intron degradation, and mRNA decay from a single RNA-Seq snapshot of total cellular RNA. SnapShot-Seq can detect in vivo changes in the rates of specific steps of splicing, and it provides genome-wide estimates of pre-mRNA synthesis rates comparable to those obtained via labeling of newly synthesized RNA. We used SnapShot-Seq to investigate the origins of the intrinsic bimodality of metazoan gene expression levels, and our results suggest that this bimodality is partly due to spillover of transcriptional activation from highly expressed genes to their poorly expressed neighbors. SnapShot-Seq dramatically expands the information obtainable from a standard RNA-Seq experiment.