Lactate saturation limits bicarbonate detection in hyperpolarized 13 C-pyruvate MRI of the brain

PURPOSE: To investigate the potential effects of [1‐(13)C]lactate RF saturation pulses on [(13)C]bicarbonate detection in hyperpolarized [1‐(13)C]pyruvate MRI of the brain. METHODS: Thirteen healthy rats underwent MRI with hyperpolarized [1‐(13)C]pyruvate of either the brain (n = 8) or the kidneys, heart, and liver (n = 5). Dynamic, metabolite‐selective imaging was used in a cross‐over experiment in which [1‐(13)C]lactate was excited with either 0° or 90° flip angles. The [(13)C]bicarbonate SNR and apparent [1‐(13)C]pyruvate‐to‐[(13)C]bicarbonate conversion (k (PB)) were determined. Furthermore, simulations were performed to identify the SNR optimal flip‐angle scheme for detection of [1‐(13)C]lactate and [(13)C]bicarbonate. RESULTS: In the brain, the [(13)C]bicarbonate SNR was 64% higher when [1‐(13)C]lactate was not excited (5.8 ± 1.5 vs 3.6 ± 1.3; 1.2 to 3.3–point increase; p = 0.0027). The apparent k (PB) decreased 25% with [1‐(13)C]lactate saturation (0.0047 ± 0.0008 s(−1) vs 0.0034 ± 0.0006 s(−1); 95% confidence interval, 0.0006–0.0019 s(−1) increase; p = 0.0049). These effects were not present in the kidneys, heart, or liver. Simulations suggest that the optimal [(13)C]bicarbonate SNR with a TR of 1 s in the brain is obtained with [(13)C]bicarbonate, [1‐(13)C]lactate, and [1‐(13)C]pyruvate flip angles of 60°, 15°, and 10°, respectively. CONCLUSIONS: Radiofrequency saturation pulses on [1‐(13)C]lactate limit [(13)C]bicarbonate detection in the brain specifically, which could be due to shuttling of lactate from astrocytes to neurons. Our results have important implications for experimental design in studies in which [(13)C]bicarbonate detection is warranted

Parental socioeconomic position and development of overweight in adolescence: longitudinal study of Danish adolescents

<p>Abstract</p> <p>Background</p> <p>An inverse social gradient in overweight among adolescents has been shown in developed countries, but few studies have examined whether weight gain and the development of overweight differs among adolescents from different socioeconomic groups in a longitudinal study. The objective was to identify the possible association between parental socioeconomic position, weight change and the risk of developing overweight among adolescents between the ages 15 to 21.</p> <p>Methods</p> <p>Prospective cohort study conducted in Denmark with baseline examination in 1996 and follow-up questionnaire in 2003 with a mean follow-up time of 6.4 years. A sample of 1,656 adolescents participated in both baseline (mean age 14.8) and follow-up (mean age 21.3). Of these, 1,402 had a body mass index (BMI = weight/height²kg/m²) corresponding to a value below 25 at baseline when adjusted for age and gender according to guidelines from International Obesity Taskforce, and were at risk of developing overweight during the study period. The exposure was parental occupational status. The main outcome measures were change in BMI and development of overweight (from BMI < 25 to BMI > = 25).</p> <p>Results</p> <p>Average BMI increased from 21.3 to 22.7 for girls and from 20.6 to 23.6 in boys during follow-up. An inverse social gradient in overweight was seen for girls at baseline and follow-up and for boys at follow-up. In the full population there was a tendency to an inverse social gradient in the overall increase in BMI for girls, but not for boys. A total of 13.4% developed overweight during the follow-up period. Girls of lower parental socioeconomic position had a higher risk of developing overweight (OR's between 4.72; CI 1.31 to 17.04 and 2.03; CI 1.10-3.74) when compared to girls of high parental socioeconomic position. A tendency for an inverse social gradient in the development of overweight for boys was seen, but it did not meet the significance criteria</p> <p>Conclusions</p> <p>The levels of overweight and obesity among adolescents are high and continue to rise. Results from this study suggest that the inverse social gradient in overweight becomes steeper for girls and emerges for boys in late adolescence (age span 15 to 21 years). Late adolescence seems to be an important window of opportunity in reducing the social inequality in overweight among Danish adolescents.</p

Platform trials

Platform trials focus on the perpetual testing of many interventions in a disease or a setting. These trials have lasting organizational, administrative, data, analytic, and operational frameworks making them highly efficient. The use of adaptation often increases the probabilities of allocating participants to better interventions and obtaining conclusive results. The COVID-19 pandemic showed the potential of platform trials as a fast and valid way to improved treatments. This review gives an overview of key concepts and elements using the Intensive Care Platform Trial (INCEPT) as an example.</p

No interactions between previously associated 2-hour glucose gene variants and physical activity or BMI on 2-hour glucose levels.

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 × 10(-6)). All SNPs were associated with 2-h glucose (β = 0.06-0.12 mmol/allele, P ≤ 1.53 × 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks