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Grand Challenges is a family of initiatives fostering innovation to solve key global health and development problems. Each initiative is an experiment in the use of challenges to focus innovation on making an impact. Individual challenges address some of the same problems, but from differing perspectives.


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Challenges: Brain Function/Gestational Age
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A Machine Learning-Based Tool to Estimate Gestational Age

Ana Namburete, University of Oxford (Oxford, United Kingdom)
May 1, 2015

Ana Namburete of the University of Oxford in the United Kingdom will develop a computational tool called Autodate that identifies physical features of the fetal brain from a routine ultrasound image to automatically estimate gestational age at any stage of pregnancy. Determining accurate gestational age is important for healthy pregnancy. However, ultrasound, which is the most accurate technique, can only estimate gestational age when used during the early stages of pregnancy by a trained sonographer, who are often absent in low-income settings. To overcome these limitations, they will use existing ultrasound images of fetal brains to develop software that can automatically extract structural features. Machine learning will be used to identify links between these brain features and gestational age. The ability of Autodate to accurately estimate gestational age will be validated on newly acquired images from pregnant women in Kenya.

Dense Metabolomics Profiling Over the Course of Gestation

Mads Melbye, Statens Serum Institut (Copenhagen, Denmark)
May 1, 2015

Mads Melbye of Statens Serum Institut in Denmark will analyze the metabolic changes that occur in women over the full course of pregnancy to help identify signatures that could diagnose disease or predict gestational age. They will use liquid chromatography coupled to mass spectrometry to measure the plasma levels of a broad range of metabolites in 30 pregnant women every two weeks. They will also collect samples for future analyses to profile the types and levels of other molecules and microbes at different stages of pregnancy. They will analyze their data for associations between specific metabolites and gestational age, and validate these on an existing independent cohort of 100,000 mother-child pairs.

Estimation of Weight, Volume and Density of a Neonatal Brain

Nishant Kumar, Embryyo Technologies Private Ltd. (Pune, Maharashtra, India)
May 1, 2015

Nishant Kumar of Embryyo Technologies Private Limited will develop a head scanner that can determine the weight and volume of the brain of a newborn to help monitor health. Current methods rely on expensive or complex techniques that require trained staff. They will develop a portable imaging scanner and a mattress that can measure the weight of the head, and use them to render a 3D mesh volume template of the head. This template can then be used to compute brain volume and weight by subtracting known volumes of bone and dermal tissues. They will test their scanner on 100 neonates and determine its efficacy by comparing the results with standard methods.

GMApp - The Developing Brain and the Developing World at Hand

Peter Marschik, Medical University of Graz (Graz, Austria)
May 1, 2015

Peter Marschik from the Medical University of Graz in Austria will develop a mobile phone app to assess general movement in infants under 6 months of age for diagnosing neurological defects and predicting the development of abnormalities particularly in low-resource settings. General movement assessments (GMA) reflect the functioning of the developing brain and are normally made by video recording the whole body of an infant over 3-5 minutes followed by expert analysis. To expand access of this technique to developing countries, he will develop software for a smart phone to capture the general movements of an infant, and to relay the acquired data directly to a GM expert for immediate diagnosis and to plan any required treatment.

Latent Variable Approaches for Estimating Gestational Age

Paul Albert, Eunice Kennedy Shriver National Institute of Child Health and Human Development (Bethesda, Maryland, United States)
May 1, 2015

Paul Albert of Eunice Kennedy Shriver National Institute of Child Health and Human Development in the U.S. will use a modeling approach to help clinicians with different resources better estimate gestational age, which is critical for monitoring maternal and child health. Gestational age is currently estimated using ultrasound, which is often unavailable in low-resource settings, or the date of the last menstrual period and external measurements of the uterus, which can be imprecise. The timing of these measurements during pregnancy also influences the accuracy of the estimate. They will develop an empirical Bayesian estimation strategy that can translate different combinations of measurements taken at different time points into an accurate estimate of gestational age, even without ultrasound. They will test their model using available measurements from 3,000 women of mixed race from the U.S.

Light-Scan Skin Age

Zilma Reis, Universidade Federal de Minas Gerais (Belo Horizonte, Minas Gerais, Brazil)
May 1, 2015

Zilma Reis of Universidade Federal de Minas Gerais in Brazil will develop a portable device to measure epidermal properties of the skin and evaluate its ability to determine gestational age in newborns. The skin epidermis is known to change during fetal development. They will exploit a non-invasive optical technique called photoelectric plethysmography that characterizes a material by analyzing its effect on the properties of an LED light shone on it. They will measure the optical properties of a phantom material that resembles fetal skin at different body sites, and select an LED and sensor that can best measure the relevant properties. They will develop software to transform the light signal into transmittable data, and build a prototype platform to test on newborns over a two week period in order to calibrate the light changes with gestational age. Finally, a prototype device will be constructed by 3D printing for future testing.

Mapping the Effects of Malnutrition on Brain Development

Joseph Culver, Washington University in St. Louis (St. Louis, Missouri, United States)
May 1, 2015

Joseph Culver of Washington University in St Louis in the U.S. is developing a portable, optical neuroimaging technology (high-density diffuse optical tomography [HD-DOT]) to monitor the effects of malnutrition on brain development in young children in low-resource settings. During the first ten years of life, the brain develops many skills such as visual and language processing, and has unique nutritional requirements. If these are not met, there may be many short- and long-term consequences including neurodevelopmental delays and increased health risks later in life that could be prevented by dietary supplements. Magnetic resonance imaging is currently used to measure brain development, but it is rarely available in low-resource settings where malnutrition is common. In Phase I, they produced a portable, field-ready HD-DOT instrument that was adapted for preschool-age children and developed a neuroimaging protocol that uses movies to better engage them while mapping distinct cortical areas. This produced reliable, high-quality data when tested on 20 participants in Cali, Colombia. In Phase II, they will improve the sensitivity of their approach for quantifying brain development and adapt it for even younger children, from birth through four years of age, for use in rural and community clinics to ultimately enable prospective measurements of brain function from infancy through childhood in low-income regions.

Neuro-Humoral Biomarkers for Kangaroo Mother Care

Vinod Bhutani, Stanford University (Stanford, California, United States)
May 1, 2015

Vinod Bhutani of Stanford University in the U.S. will measure neurosteroid levels in infants from birth to 72 hours of age to determine whether they are affected by skin-to-skin contact (kangaroo mother care), thereby influencing neurodevelopment. Skin-to-skin contact between mother and child shortly after birth has been linked with improved infant growth, breastfeeding and attachment, and, for preterm infants, enhanced neurodevelopment. The biological basis for this in humans is unclear, however in horses, high levels of neuroactive steroids in newborn foals can induce abnormal behavior including a failure to breastfeed. They will track neurosteroid levels in 48 human infants, both full-term and late preterm, some of whom receive routine kangaroo mother care, to identify any associations between the two that could be used to identify potential neurodevelopmental defects that could be treated by kangaroo mother care.

Prenatal Marker of Early Brain Development

William Fifer, Columbia University in the City (New York, New York, United States)
May 1, 2015

William Fifer of Columbia University in the U.S. is developing a non-invasive method to measure heart rate and heart rate variability in the fetus during pregnancy as a window into brain function to help warn of emerging brain abnormalities. They aim to produce charts of brain development beginning during pregnancy and continuing into early childhood that can be used in limited-resource settings for monitoring child health. In Phase I, they analyzed heart rate data from fetuses obtained during different sleep states from 356 pregnant mothers in South Africa, and found that it correlated with their brain activity measured around four days after birth. In Phase II, they will extend the analysis to infants between 24 and 36 months to determine whether the heart rate patterns measured in utero and the brain activity measured soon after birth are also related to various aspects of neurodevelopment including growth, cognition, and language in toddlers. They will also study a new cohort of 50 pregnant mothers to optimize the heart rate and brain activity measurements to help identify the best markers of abnormal brain development that can be used in low-resource settings for timely interventions.

Skin to Skin: Sensing Age Through Light

Christopher Yip, University of Toronto (Toronto, Ontario, Canada)
May 1, 2015

Christopher Yip of the University of Toronto in Canada will test whether measuring skin thickness and cellular composition by non-invasive diffuse optical spectroscopy can be used to estimate the gestational age of newborns, which is important for maternal and child health. They will first determine how light absorption and scattering properties of skin tissue at differing depths correlate with skin structure and then apply their approach to neonates of defined ages. They will also develop relevant hardware and software strategies to translate the selected optical properties into gestational age, and plan to build a low-cost and portable spectroscopy device. In the future, this device could be configured to detect other disease-related biomarkers such as hydration levels.

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The Bill & Melinda Gates Foundation is part of the Grand Challenges partnership network. Visit www.grandchallenges.org to view the map of awarded grants across this network and grant opportunities from partners.