The effect of brain size evolution on feeding propensity, digestive efficiency, and juvenile growth

One key hypothesis in the study of brain size evolution is the expensive tissue hypothesis; the idea that increased investment into the brain should be compensated by decreased investment into other costly organs, for instance the gut. Although the hypothesis is supported by both comparative and experimental evidence, little is known about the potential changes in energetic requirements or digestive traits following such evolutionary shifts in brain and gut size. Organisms may meet the greater metabolic requirements of larger brains despite smaller guts via increased food intake or better digestion. But increased investment in the brain may also hamper somatic growth. To test these hypotheses we here used guppy (Poecilia reticulata) brain size selection lines with a pronounced negative association between brain and gut size and investigated feeding propensity, digestive efficiency (DE), and juvenile growth rate. We did not find any difference in feeding propensity or DE between large- and small-brained individuals. Instead, we found that large-brained females had slower growth during the first 10 weeks after birth. Our study provides experimental support that investment into larger brains at the expense of gut tissue carries costs that are not necessarily compensated by a more efficient digestive system.

Sugar- and artificially sweetened beverages and intrahepatic fat: A randomized controlled trial.

OBJECTIVE To test the hypothesis that substituting artificially sweetened beverages (ASB) for sugar-sweetened beverages (SSB) decreases intrahepatocellular lipid concentrations (IHCL) in overweight subjects with high SSB consumption. METHODS About 31 healthy subjects with BMI greater than 25 kg/m(2) and a daily consumption of at least 660 ml SSB were randomized to a 12-week intervention in which they replaced SSBs with ASBs. Their IHCL (magnetic resonance spectroscopy), visceral adipose tissue volume (VAT; magnetic resonance imaging), food intake (2-day food records), and fasting blood concentrations of metabolic markers were measured after a 4-week run-in period and after a 12-week period with ASB or control (CTRL). RESULTS About 27 subjects completed the study. IHCL was reduced to 74% of the initial values with ASB (N = 14; P < 0.05) but did not change with CTRL. The decrease in IHCL attained with ASB was more important in subjects with IHCL greater than 60 mmol/l than in subjects with low IHCL. ALT decreased significantly with SSB only in subjects with IHCL greater than 60 mmol/l. There was otherwise no significant effect of ASB on body weight, VAT, or metabolic markers. CONCLUSIONS In subjects with overweight or obesity and a high SSB intake, replacing SSB with ASB decreased intrahepatic fat over a 12-week period.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.