Biomarker of food intake for assessing the consumption of dairy and egg products

Foods of animal origin constitute one of the predominant food groups consumed in Western diets. They play an essential role in human nutrition as they represent an excellent source of high quality proteins, vitamins, minerals and fats. Foods of animal origin are highly diverse (e.g. meat, fish, dairy products and eggs) and their associations with a range of nutritional and health outcomes are therefore heterogeneous. Such associations are also often weak or debated due to the difficulty in establishing correct assessments of dietary intake. Therefore, in order to better characterize associations between the consumption of specific foods of animal origin and health outcomes, it is important to identify reliable biomarkers of food intake (BFIs). BFIs provide a more accurate measure of intake and are independent of the memory and sincerity of the subjects as well as of their knowledge about the consumed foods. To date, only a very limited number of compounds have been proposed as biomarkers of the intake of foods of animal origin and further studies are necessary to validate them and to discover new candidate BFIs. We have, therefore, conducted a systematic search of the scientific literature to evaluate the current status of potential BFIs for each category of foods of animal origin commonly consumed in Europe. This review reports on candidate biomarkers for dairy products and eggs intake, while biomarkers for fish and meat intake will be published separately. Remarkably, validated BFIs for dairy products and eggs are not available. A series of challenges hinders their identification and validation, in particular the heterogeneous composition of each food within a product category and the lack of specificity of the markers identified so far. Untargeted metabolomic strategies may allow the identification of novel food biomarkers, that, when taken separately or in combination, could be used to assess the intake of dairy products and eggs

Racial disparities in diagnostic evaluation and revascularization in patients with acute myocardial infarction-a fifteen-year longitudinal study

We aimed to evaluate longitudinal trends of racial and ethnic disparities in the utilization of diagnostic angiograms, percutaneous coronary intervention (PCI), and coronary artery bypass graft surgery (CABG) for non-ST elevation myocardial infarction (NSTEMI) and ST-elevation myocardial infarction (STEMI). We retrospectively analyzed the National Inpatient Sample (2005-2019). The fifteen-year period was divided into five, three-year periods. Our study included 9 million adult patients (NSTEMI, 72%; STEMI, 28%). No improvement in utilization of these procedures was seen in period 5 (2017-2019) vs. period 1 (2005-2007) for both NSTEMI and STEMI in non-White patients vs. White patients (P\u3e.05 for all comparisons), excepting in CABG for STEMI in Black patients vs. White patients (difference in CABG rate: period 1, 2.6%; period 5, 1.4%; P=.03). Reducing disparities in PCI for NSTEMI and both PCI and CABG for STEMI in Black patients vs. White patients was associated with improved outcomes

A Memory-Bounded Best-First Beam Search and Its Application to Scheduling Halide Programs

Beam search is a popular algorithm for solving real-world problems --- especially where search space is an enormously large tree but real-time solutions are most preferred. We present a memory-bounded best-first beam search (MB2FBS), which can be viewed as an improved and generalized version of standard beam search in trees. The algorithm takes three parameters --- in contrast to the singular parameter beam size in standard beam search. We discuss how to recover standard beam search and how to realize other search behavior by setting these three parameters correspondingly. In particular, we show that the principal version of MB2FBS can be thought as an algorithm whose search expense is similar or upper bounded by beam search of certain beam size; however it often finds better solutions as it decides the number of nodes to be searched each depth dynamically with respect cost landscape. We apply our algorithm for tensor program auto-scheduling in Halide, an important industrial problem that uses tree search for optimizing tensor program executions. We show that the principal variants of MB2FBS deliver better empirical results than the highly optimized beam search counterpart. Most importantly, it finds superior schedules while no more computation cost is used for search, which is highly desirable for real-time program compilation and optimization

Livestock metabolomics and the livestock metabolome: A systematic review

<div><p>Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at <a href="http://www.lmdb.ca" target="_blank">http://www.lmdb.ca</a>). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.</p></div

Sample types.

<p>Sample types.</p

Sample types.

<p>Different varieties of samples and animal products have been analyzed in livestock metabolomics studies.</p

PRISMA diagram.

<p>The preferred reporting items for systematic reviews and meta-analysis (PRISMA) flow diagram identifies the total number of articles initially surveyed, the number of articles included and excluded for this systematic review. From: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PloS Med 6(7): e1000097. doi:<a href="https://doi.org/10.1371/journal.pmed1000097" target="_blank">10.1371/journal.pmed1000097</a>. <b>For more information, visit</b> <a href="http://www.prisma-statement.org" target="_blank">www.prisma-statement.org</a>.</p

Literature mining.

<p>Total number of livestock metabolomics articles considering only articles that reported ≥8 metabolites resulted in selection of 149 manuscripts for this review.</p