Perspective: Dietary Biomarkers of Intake and Exposure - Exploration with Omics Approaches

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Individual differences in nurse and teacher training students' attitudes toward and use of information technology

Students in both nurse and teacher training are now expected to learn to make effective use of IT for their profession. However, they enter training with a variety of experience in IT which will affect how they respond to further IT skills training. In this survey, 154 nursing and 128 teacher training students reported on the uses they had made of computers and their attitudes towards them. Also, as a sense of being in control of the computer is important for becoming involved in its use, they completed a questionnaire to locate their locus of internal control. The teacher training students were more likely than the nursing students to have access to a home computer, to use computers more often and to have used a greater variety of software. However, this may be a gender effect as a greater proportion of the teacher trainees were male. For both teacher training and nursing students, having a more internal locus of control was correlated with more positive attitudes towards computers. This finding is important for those introducing students to the use of IT in their professions, so that appropriate software and teaching styles involving less open-ended tasks may be provided for the less internally controlled individuals. Interestingly, a much stronger relationship between being more internally controlled and being less scared of using a computer was found for teacher trainees than for nurse trainees. Thus for nurse trainees it is more likely that there are other individual factors predisposing them to fear using computers. © 2002 Published by Elsevier Science Ltd

Dietary and health biomarkers-time for an update

FoodBAll is a project funded by the BIO-NH call under the Joint Programming Initiative, "a Healthy Diet for a Healthy Life" (grant number 529051002). The project is funded nationally by the respective Research Councils; the work was funded in part by a grant from the Danish Innovation Foundation (#4203-00002B) and a Semper Ardens grant from the Carlsberg Foundation to LOD, a postdoc grant from the University of Rome La Sapienza ("Borsa di studio per la frequenza di corsi o attivita di perfezionamento all'estero" erogata ai sensi della legge 398/89) to GP, a grant from the China Scholarship Council (201506350127) to QG, a grant from the Agence Nationale de la Recherche (#ANR-14-HDHL-0002-02) to CM, and a grant from the Canadian Institutes of Health Research (CIHR) to DSW.In the dietary and health research area, biomarkers are extensively used for multiple purposes. These include biomarkers of dietary intake and nutrient status, biomarkers used to measure the biological effects of specific dietary components, and biomarkers to assess the effects of diet on health. The implementation of biomarkers in nutritional research will be important to improve measurements of dietary intake, exposure to specific dietary components, and of compliance to dietary interventions. Biomarkers could also help with improved characterization of nutritional status in study volunteers and to provide much mechanistic insight into the effects of food components and diets. Although hundreds of papers in nutrition are published annually, there is no current ontology for the area, no generally accepted classification terminology for biomarkers in nutrition and health, no systematic validation scheme for these biomarker classes, and no recent systematic review of all proposed biomarkers for food intake. While advanced databases exist for the human and food metabolomes, additional tools are needed to curate and evaluate current data on dietary and health biomarkers. The Food Biomarkers Alliance (FoodBAll) under the Joint Programming Initiative-A Healthy Diet for a Healthy Life (JPI-HDHL)-is aimed at meeting some of these challenges, identifying new dietary biomarkers, and producing new databases and review papers on biomarkers for nutritional research. This current paper outlines the needs and serves as an introduction to this thematic issue of Genes & Nutrition on dietary and health biomarker