Assessment of healthy brain maturation can be useful toward better understanding natural patterns of brain growth and toward the characterization of a variety of neurodevelopmental disorders as deviations from normal growth trajectories. Structural magnetic resonance imaging (MRI) provides excellent soft‐tissue contrast, which allows for the assessment of gray and white matter in the developing brain. We performed a large‐scale retrospective analysis of 993 pediatric structural brain MRI examinations of healthy subjects (n = 988, aged 0–32 years) imaged clinically at 3 T, and extracted a wide variety of measurements such as white matter volumes, cortical thickness, and gyral curvature localized to subregions of the brain. All extracted structural biomarkers were tested for their correlation with subject age at time of imaging, providing measurements that may assist in the assessment of neurological maturation. Additional analyses were also performed to assess gender‐based differences in the brain at a variety of developmental stages, and to assess hemispheric asymmetries. Results add to the literature by analyzing a realistic distribution of healthy participants imaged clinically, a useful cohort toward the investigation and creation of diagnostic tests for a variety of pathologies as aberrations from healthy growth trajectories. The next generation of diagnostic tests will be responsible for identifying pathological conditions from populations of healthy clinically imaged individuals. Hum Brain Mapp 38:5931–5942, 2017. © 2017 Wiley Periodicals, Inc.

Food-drug interactions (FDIs) arise when nutritional dietary consumption regulates biochemical mechanisms involved in drug metabolism. This study proposes FDMine, a novel systematic framework that models the FDI problem as a homogenous graph. Our dataset consists of 788 unique approved small molecule drugs with metabolism-related drug-drug interactions and 320 unique food items, composed of 563 unique compounds. The potential number of interactions is 87,192 and 92,143 for disjoint and joint versions of the graph. We defined several similarity subnetworks comprising food-drug similarity, drug-drug similarity, and food-food similarity networks. A unique part of the graph involves encoding the food composition as a set of nodes and calculating a content contribution score. To predict new FDIs, we considered several link prediction algorithms and various performance metrics, including the precision@top (top 1%, 2%, and 5%) of the newly predicted links. The shortest path-based method has achieved a precision of 84%, 60% and 40% for the top 1%, 2% and 5% of FDIs identified, respectively. We validated the top FDIs predicted using FDMine to demonstrate its applicability, and we relate therapeutic anti-inflammatory effects of food items informed by FDIs. FDMine is publicly available to support clinicians and researchers.

Early interventions for autism spectrum disorder (ASD) are increasingly available, while only 42–50% of ASD children are diagnosed before 3 years old (YO). To identify neuroimaging biomarkers for early ASD diagnosis, we evaluated surface- and voxel-based brain morphometry in participants under 3YO who were later diagnosed with ASD. Magnetic resonance imaging data were retrospectively obtained from patients later diagnosed with ASD at Boston Children’s Hospital. The ASD participants with comorbidities such as congenital disorder, epilepsy, and global developmental delay/intellectual disability were excluded from statistical analyses. Eighty-five structural brain magnetic resonance imaging images were collected from 81 participants under 3YO and compared with 45 images from 45 gender- and age-matched nonautistic controls (non-ASD). Using an Infant FreeSurfer pipeline, 236 regionally distributed measurements were extracted from each scan. By t-tests and linear mixed models, the smaller nucleus accumbens and larger bilateral lateral, third, and fourth ventricles were identified in the ASD group. Vertex-wise t-statistical maps showed decreased thickness in the caudal anterior cingulate cortex and increased thickness in the right medial orbitofrontal cortex in ASD. The smaller bilateral accumbens nuclei and larger cerebral ventricles were independent of age, gender, or gestational age at birth, suggesting that there are MRI-based biomarkers in prospective ASD patients before they receive the diagnosis and that the volume of the nucleus accumbens and cerebral ventricles can be key MRI-based early biomarkers to predict the emergence of ASD.

• Volumetric abnormalities detected in the perirhinal, entorhinal memory regions. • Volumetric abnormalities detected in key additional brain regions. • Extensive clinical validation of previous Down Syndrome findings included. • Perirhinal and entorhinal involvement in Alzheimer’s etiology hypothesized.