Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake.

Nutritional epidemiology aims to link dietary exposures to chronic disease, but the instruments for evaluating dietary intake are inaccurate. One way to identify unreliable data and the sources of errors is to compare estimated intakes with the total energy expenditure (TEE). In this study, we used the International Atomic Energy Agency Doubly Labeled Water Database to derive a predictive equation for TEE using 6,497 measures of TEE in individuals aged 4 to 96 years.

Quantum and statistical state-to-state studies of cold Ar + H collisions.

In this work we present new state-to-state integral scattering cross sections and initial-state selected rate coefficients for the Ar (S) + H (XΣ, = 0,) reactive system for collision energies up to 0.1 eV (with respect to the Ar (S) + H (XΣ, = 0, = 0) channel). To the best of our knowledge, these cross sections are the first fully state resolved ones that were obtained by performing time-independent quantum mechanical and quantum statistical calculations.

Higher adiposity predicts greater intra-individual inconsistencies in postprandial glycemic measurements-an analysis of three randomized controlled trials in Asian populations.

Background/objectives: Acute glycemic responses offer important insights into glucose homeostasis although the repeatability of these measurements particularly in Asian populations remains unclear. This research aimed to critically investigate the inconsistencies of the postprandial glycemic profile within individuals, and identify potential variables predicting greater inconsistencies.

Subjects/methods: This was a secondary analysis of three randomized controlled trials which fed subjects with glucose (and other carbohydrate-rich foods), and measured postprandial blood glucose at regular intervals.

Outbreak in an Intensive Care Unit: Source Analysis with Whole Genome Sequencing and Short Tandem Repeats.

Whole genome sequencing (WGS) is widely used for outbreak analysis of bacteriology and virology but is scarcely used in mycology. Here, we used WGS for genotyping isolates from a potential outbreak in an intensive care unit (ICU) during construction work. After detecting the outbreak, fungal cultures were performed on all surveillance and/or patient respiratory samples.