The dynamics of human body weight change

An imbalance between energy intake and energy expenditure will lead to a change in body weight (mass) and body composition (fat and lean masses). A quantitative understanding of the processes involved, which currently remains lacking, will be useful in determining the etiology and treatment of obesity and other conditions resulting from prolonged energy imbalance. Here, we show that the long-term dynamics of human weight change can be captured by a mathematical model of the macronutrient flux balances and all previous models are special cases of this model. We show that the generic dynamical behavior of body composition for a clamped diet can be divided into two classes. In the first class, the body composition and mass are determined uniquely. In the second class, the body composition can exist at an infinite number of possible states. Surprisingly, perturbations of dietary energy intake or energy expenditure can give identical responses in both model classes and existing data are insufficient to distinguish between these two possibilities. However, this distinction is important for the efficacy of clinical interventions that alter body composition and mass

Lineage Abundance Estimation for SARS-CoV-2 in Wastewater Using Transcriptome Quantification Techniques

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large‐scale studies. In response, we used cross‐sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to infer age‐related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta‐analysis and one‐way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Consortium to examine age‐related trajectories inferred from cross‐sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3–90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter‐individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age‐related morphometric patterns

Vaping and Instagram: A content analysis of e-Cigarette posts using the Content Appealing to Youth (CAY) Index

The promotion of flavors, perceptions of “coolness,” and general curiosity are characteristics of electronic nicotine delivery systems (ENDS) that have appealed to young adults. However, little is known about the characteristics of popular social media posts related to ENDS on the social media network, Instagram. Methods: Content analysis was performed using the Content Appealing to Youth (CAY) index. Over 700 posts were collected from August 2019 – December 2019 by searching the Instagram hashtags, #vape and #vapelife. Frequencies and percentages were calculated for each of the six major categories and 35 sub-categories. Results: Nearly all of the images were color photographs and 84% featured an ENDS device (mod) as the focal point. The style of the device was often matte (75%) in only one or two main colors (55%). Warnings about age restrictions and nicotine were included in 28% of images, but commonly used promotional tactics, such as humor, presence of vapor puffs, and flavors were rarely utilized. Conclusions: Instagram posts featuring ENDS are visually appealing and like cigarette packaging, may have the capacity to influence perceptions about the product. Since it is culturally normative for appealing images to be shared on Instagram, greater attention should be placed on media literacy skills to educate young adults about ENDS viewed on social media.Journal ArticlePublishe

Practicing Mindfulness through mHealth Applications: Emerging Adults’ Health-Enhancing and Inhibiting Experiences

Mindfulness-based interventions (MBIs) and practices (MBPs) can promote better health outcomes. Although MBIs and MBPs were developed to be delivered in-person, mobile health (mHealth) tools such as apps have made these more accessible. Mindfulness apps (MAs) are popular among emerging adults (EAs) who have the highest ownership of smartphones and who are also at risk for distress. While adverse effects have been observed with MBIs/MBPs, this has not been examined when mindfulness is practiced using apps. We interviewed EAs (n = 22) to capture their motivations for using these apps and identified health-inhibiting and enhancing experiences. Data were thematically analyzed using the constant comparative method. Motivations for app use included accessibility, convenience, and stress/health management. EAs described health-enhancing outcomes (reduced distress, improved physical symptoms, increased focus) and health-inhibiting outcomes (worsened distress, performance uncertainty, dependency development, worsened physical health). They provided suggestions for improving apps (e.g., feedback option). These findings illustrate benefits and risks that EAs may encounter when practicing mindfulness using apps, which can inform the best practices for app design