Recent success in identifying gene regulatory elements in the context of recombinant adeno-associated virus vectors have enabled cell type-restricted gene expression. However, within the cerebral cortex these tools are presently limited to broad classes of neurons. To overcome this limitation, we developed a strategy that led to the identification of multiple novel enhancers to target functionally distinct neuronal subtypes. By investigating the regulatory landscape of the disease gene Scn1a, we identified enhancers that target the breadth of its expression, including two that are selective for parvalbumin and vasoactive intestinal peptide cortical interneurons. Demonstrating the functional utility of these elements, we found that the PV-specific enhancer allowed for the selective targeting and manipulation of these neurons across species, from mice to humans. Finally, we demonstrate that our selection method is generalizable to other genes and characterize four additional PV-specific enhancers with exquisite specificity for distinct regions of the brain. Altogether, these viral tools can be used for cell-type specific circuit manipulation and hold considerable promise for use in therapeutic interventions.Large-scale transcriptomic studies are rapidly revealing where and when genes associated with neuropsychiatric disease are expressed within specific cell types (1-4). Approaches for understanding and treating these disorders will require methods for targeting and manipulating specific neuronal subtypes. Thus, gaining access to these populations in non-human primates and humans has become paramount. AAVs are the method of choice for gene delivery in the nervous system but have a limited genomic payload and are not intrinsically selective for particular neuronal populations (5). We and others have identified short regulatory elements capable of restricting viral expression to broad neuronal classes. In addition, systematic enhancer discovery has been accelerated by the recent development of technologies allowing for transcriptomic and epigenetic studies at single-cell resolution (6-12). Despite these advances, the search space for enhancer selection remains enormous and to date success has been limited. To focus our enhancer selection, we chose to specifically examine the regulatory landscape of Scn1a, a gene expressed in distinct neuronal populations and whose disruption is associated with severe epilepsy (13).Combining single-cell ATAC-seq data with sequence conservation across species, we nominated ten candidate regulatory sequences in the vicinity of this gene. By thoroughly investigating each of these elements for their ability to direct viral expression, we identified three enhancers that collectively target the breadth of neuronal populations expressing Scn1a. Among these, one particular short regulatory sequence was capable of restricting viral expression to parvalbumin-expressing cortical interneurons (PV cINs). To fully assess the utility of this element beyond reporter expression, we validated it in a v...

Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual’s characteristics, known as personalized or “stratified medicine.” Developments, such as crowdsourcing, participatory surveillance, and individuals pledging to become “data donors” and the “quantified self” movement (where citizens share data through mobile device-connected technologies), have great potential to contribute to our knowledge of disease, improving diagnostics, and delivery of ­healthcare and treatment. There is not only a great potential but also major concerns over privacy, confidentiality, and control of data about individuals once it is shared. Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming increasingly scrutinized at national and international levels. This can be seen in the recent backlash over the proposed implementation of care.data, which enables individuals’ NHS data to be linked, retained, and shared for other uses, such as research and, more controversially, with businesses for commercial exploitation. By way of contrast, through increasing popularity of social media, GPS-enabled mobile apps and tracking/wearable devices, the IT industry and MedTech giants are pursuing new projects without clear public and policy discussion about ownership and responsibility for user-generated data. In the absence of transparent regulation, this paper addresses the opportunities of Big Data in healthcare together with issues of responsibility and accountability. It also aims to pave the way for public policy to support a balanced agenda that safeguards personal information while enabling the use of data to improve public health.

We produced case studies of fourteen families based on nine rounds of data collection during the period from June 2008 to October 2009. We focused on fourteen children who were three years old when our visits started and used an ecocultural approach to examine their experiences of learning and playing with technologies at home. The study describes i) which technologies children encounter at home, ii) how family practices influence children's encounters with technology, and iii) what children are learning through their interactions with technology. We present a framework of four areas of learning that could be supported by technology: acquiring operational skills, extending knowledge and understanding of the world, developing dispositions to learn, and understanding the role of technology in everyday life.

Responding to reports of missing persons represents one of the biggest demands on the resources of police organisations. In the UK, for example, it is estimated that over 300,000 missing persons incidents are recorded by the police each year which means that a person in the UK is recorded missing by the police approximately every two minutes. However, there is a complex web of behaviours that surround the phenomenon of missing persons which can make it difficult to establish whether someone's disappearance is 'intentional' or 'unintentional' or whether they might be at risk of harm from themselves or others. Drawing on a set of missing person case reconstructions and interviews with the officers involved with these cases, this paper provides insights into the different stages of the investigative process and some of the key influences which shape the trajectory of a missing person's investigation. In particular it highlights the complex interplay between actions which are 'ordered and conditioned' by a procedural discourse around how missing persons investigations should be conducted, and the narratives that officers construct about how they approach investigations which are often shaped by a mix of police craft , 'science' and 'reputational' issues.

This article describes a novel approach to experience sampling as a response to the challenges of researching the everyday lives of young children at home. Parents from 11 families used mobile phones to send the research team combined picture and text messages to provide 'experience snapshots' of their child's activities six times on each of three separate days. The article describes how the method aligns with an ecocultural approach, illustrates the variation in children's experiences and provides sufficient detail for researchers to adapt the method for the purposes of collecting data in other contexts. The article summarizes the benefits and shortcomings from the perspectives of families and researchers.