Don Sharkey of the University of Nottingham in the United Kingdom will develop a software-based analysis tool to automatically calculate gestational age from simple videos of newborn faces and feet. Knowing the gestational age, particularly for babies born preterm, is critical for ensuring their healthy development. However, current dating procedures are expensive and/or require trained personnel, and as such are often unavailable in low-middle income countries. They will create a face and foot video database of newborns with known gestational ages of between 23 and 42 weeks, and use automated methods to extract specific features and generate a gestational algorithm. This algorithm will then be validated in a separate group of newborns.

Vasily Yarnykh from the University of Washington in the U.S. will test whether measuring myelin content in the brain using a low-cost magnetic resonance imaging method can act as a reliable biomarker for brain maturation. They will build on a method involving the measurement of the macromolecular proton fraction by magnetic resonance. This method will be converted to a non-image-based and non-localized method that can be more easily and inexpensively used to measure myelin content in developing countries. The new method will be tested for accuracy compared to the standard method, and used on children of a range of ages to see if it can differentiate brain maturation level.

George Wehby and colleagues at the University of Iowa in the U.S. will evaluate newborn metabolic biomarkers for their ability to predict gestational age, and identify associations between them and long-term academic achievement. They will analyze existing newborn metabolic profiles and academic tests from almost one million children in Iowa born between 1980 and 2006 to identify the most predictive biomarkers. In the future they will expand their method to developing countries to help estimate gestational age and identify newborns at risk of neurodevelopmental defects. Being able to accurately determine gestational age is critical in preterm birth, which is the leading cause of child death worldwide. And knowing which regions have the highest incidence of preterm births would help better target prevention strategies. In Phase I, they identified candidate biomarkers that can be detected by tandem mass spectrometry using existing dried blood spot samples and based on around 150,000 children born between 1980 and 2006 in Iowa, they developed a predictive model for gestational age. With follow-on funding, through a grant awarded to Kelli Ryckman, their model will be tested using around 2,000 cord blood samples from newborns in Bangladesh, Pakistan and Tanzania, and refine it to improve accuracy by measuring additional biomarkers such as hemoglobin.

Alice Cepeda from the University of Southern California in the U.S. will project short 3-D messages given by crack users on selected walls and buildings to illustrate the dangers of crack use on HIV risk, and to promote healthy behavior and testing in local communities. Mexico has seen a recent increase in crack cocaine consumption, which is associated with an increased risk of HIV. They will focus on a vulnerable community in Mexico City, and select message content and ideal sites and times to project the messages. During the projections, they will provide trained individuals to offer additional health advice and on-site HIV testing. The effects will be evaluated on the behavior of 50 local crack users.