Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) is a spectrum of highly heritable neurodevelopmental disorders in which known mutations contribute to disease risk in 20% of cases. Here, we report the results of the largest blood transcriptome study to date that aims to identify differences in 170 ASD cases and 115 age/sex-matched controls and to evaluate the utility of gene expression profiling as a tool to aid in the diagnosis of ASD. The differentially expressed genes were enriched for the neurotrophin signaling, long-term potentiation/depression, and notch signaling pathways. We developed a 55-gene prediction model, using a cross-validation strategy, on a sample cohort of 66 male ASD cases and 33 age-matched male controls (P1). Subsequently, 104 ASD cases and 82 controls were recruited and used as a validation set (P2). This 55-gene expression signature achieved 68% classification accuracy with the validation cohort (area under the receiver operating characteristic curve (AUC): 0.70 [95% confidence interval [CI]: 0.62–0.77]). Not surprisingly, our prediction model that was built and trained with male samples performed well for males (AUC 0.73, 95% CI 0.65–0.82), but not for female samples (AUC 0.51, 95% CI 0.36–0.67). The 55-gene signature also performed robustly when the prediction model was trained with P2 male samples to classify P1 samples (AUC 0.69, 95% CI 0.58–0.80). Our result suggests that the use of blood expression profiling for ASD detection may be feasible. Further study is required to determine the age at which such a test should be deployed, and what genetic characteristics of ASD can be identified

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Legal Education of Minority Students: Review and Overview

Moderator: Walter J. LeonardPanelists: Dr. William Boyd, Frederick M. Hart, Dr. Stephen P. Klein, Michael D. Rappapor

Legal Education of Minority Students: Review and Overview

Moderator: Walter J. LeonardPanelists: Dr. William Boyd, Frederick M. Hart, Dr. Stephen P. Klein, Michael D. Rappapor

Assessing participation in a community-based health planning and services programme in Ghana

Background Community participation is increasingly seen as a pre-requisite for successful health service uptake. It is notoriously difficult to assess participation and little has been done to advance tools for the assessment of community participation. In this paper we illustrate an approach that combines a 'social psychology of participation' (theory) with 'spider-grams' (method) to assess participation and apply it to a Community-based Health Planning and Services (CHPS) programme in rural Ghana. Methods We draw on data from 17 individual in-depth interviews, two focus group discussions and a community conversation with a mix of service users, providers and community health committee members. It was during the community conversation that stakeholders collectively evaluated community participation in the CHPS programme and drew up a spider-gram. Results Thematic analysis of our data shows that participation was sustained through the recognition and use of community resources, CHPS integration with pre-existing community structures, and alignment of CHPS services with community interests. However, male dominance and didactic community leadership and management styles undermined real opportunities for broad-based community empowerment, particularly of women, young people and marginalised men. Conclusion We conclude that combining the 'spider-gram' tool and the 'social psychology of participation' framework provide health professionals with a useful starting point for assessing community participation and developing recommendations for more participatory and empowering health care programmes

Enabling physical analytics in retail stores using smart glasses

We consider the problem of tracking physical browsing by users in indoor spaces such as retail stores. Analogous to online browsing, where users choose to go to certain webpages, dwell on a subset of pages of interest to them, and click on links of interest while ignoring others, we can draw parallels in the physical setting, where a user might walk purposefully to a section of interest, dwell there for a while, gaze at specific items, and reach out for the ones that they wish to examine more closely. As our first contribution, we design techniques to track each of these elements of physical browsing using a combination of a first-person vision enabled by smart glasses, and inertial sensing using both the glasses and a smartphone. We address key challenges, in-cluding energy efficiency by using the less expensive inertial sen-sors to trigger the more expensive vision processing. Second, during gazing, we present a method for identifying the item(s) within view that the user is likely to focus on based on mea-suring the orientation of the user’s head. Finally, unlike in the online context, where every webpage is just a click away, proximity is important in the physical browsing setting. To enable the tracking of nearby items, even if outside the field of view, we use data gathered from smart-glasses-enabled users to infer the product layout using a novel technique called Au-toLayout. Further, we show how such inferences made from a small population of smart-glasses-enabled users could aid in tracking the physical browsing by the many smartphone-only users