An MRspec database query and visualization engine with applications as a clinical diagnostic and research tool.

PURPOSE: Proton magnetic resonance spectroscopy (MRspec), one of the very few techniques for in vivo assessment of neuro-metabolic profiles, is often complicated by lack of standard population norms and paucity of computational tools. METHODS: 7035 scans and clinical information from 4430 pediatric patients were collected from 2008 to 2014. Scans were conducted using a 1.5T (n=3664) or 3T scanner (n=3371), and with either a long (144ms, n=5559) or short echo time (35ms, n=1476). 3055 of these scans were localized in the basal ganglia (BG), 1211 in parieto-occipital white matter (WM). 34 metabolites were quantified using LCModel. A web application using MySQL, Python and Flask was developed to facilitate the exploration of the data set. RESULTS: Already piloting the application revealed numerous insights. (1), N-acetylaspartate (NAA) increased throughout all ages. During early infancy, total choline was highly varied and myo-inositol demonstrated a downward trend. (2), Total creatine (tCr) and creatine increased throughout childhood and adolescence, though phosphocreatine (PCr) remained constant beyond 200days. (3), tCr was higher in BG than WM. (4), No obvious gender-related differences were observed. (5), Field strength affects quantification using LCModel for some metabolites, most prominently for tCr and total NAA. (6), Outlier analysis identified patients treated with vigabatrin through elevated γ-aminobutyrate, and patients with Klippel-Feil syndrome, Leigh disease and L2-hydroxyglutaric aciduria through low choline in BG. CONCLUSIONS: We have established the largest MRSpec database and developed a robust and flexible computational tool for facilitating the exploration of vast metabolite datasets that proved its value for discovering neurochemical trends for clinical diagnosis, treatment monitoring, and research. Open access will lead to its widespread use, improving the diagnostic yield and contributing to better understanding of metabolic processes and conditions in the brain.

Advances in zebrafish high content and high throughput technologies.

The zebrafish has emerged as an excellent transitional screening model system between cell-based assays, which are rapid and inexpensive but have limited physiological relevance, and higher vertebrate models, which have better physiological relevance, but are more time-consuming and expensive to deploy. As vertebrates, zebrafish maintain significant evolutionary proximity to humans and have been validated as robust models for drug research, studies of mechanism and behavioral genetics. Unlike higher vertebrate models, zebrafish are well-suited to high-throughput applications owing to their high fecundity, rapid extrauterine development and transparency during organogenesis enabling in vivo labeling and imaging. Recent advances have been made in automating high content and high-throughput zebrafish screens, with the goal of developing fully automated drug screening platforms. The application and continued development of these technologies holds potential clinical significance in drug discovery and elucidating disease mechanisms.