RAPID REPORTS Population and social conditions. Pupils and students in the Community in 1990/91. 1993.9

<div><p>It is known that the macronutrient content of a meal has different impacts on the postprandial satiety and appetite hormonal responses. Whether obesity interacts with such nutrient-dependent responses is not well characterized. We examined the postprandial appetite and satiety hormonal responses after a high-protein (HP), high-carbohydrate (HC), or high-fat (HF) mixed meal. This was a randomized cross-over study of 9 lean insulin-sensitive (mean±SEM HOMA-IR 0.83±0.10) and 9 obese insulin-resistant (HOMA-IR 4.34±0.41) young (age 21–40 years), normoglycaemic Chinese men. We measured fasting and postprandial plasma concentration of glucose, insulin, active glucagon-like peptide-1 (GLP-1), total peptide-YY (PYY), and acyl-ghrelin in response to HP, HF, or HC meals. Overall postprandial plasma insulin response was more robust in the lean compared to obese subjects. The postprandial GLP-1 response after HF or HP meal was higher than HC meal in both lean and obese subjects. In obese subjects, HF meal induced higher response in postprandial PYY compared to HC meal. HP and HF meals also suppressed ghrelin greater compared to HC meal in the obese than lean subjects. In conclusion, a high-protein or high-fat meal induces a more favorable postprandial satiety and appetite hormonal response than a high-carbohydrate meal in obese insulin-resistant subjects.</p></div

Review: Amino acid concentration of high protein food products and an overview of the current methods used to determine protein quality

<p>Quality of the dietary protein in foods rather than amount of dietary protein may be of greater importance from a human health and wellness standpoint. Various systems are in place to determine the value of dietary protein. Protein digestibility-corrected amino acid score (PDCAAS) and digestible indispensable amino acid score (DIAAS) are the two major protein standards used to determine the completeness of proteins by their unique concentration and digestibility of indispensable amino acids. The purpose of this review was to provide a comprehensive comparison of the amino acid concentration of high protein foods and provide the current status of the use and practicality of the PDCAAS and DIAAS system. This review builds upon previous research analyzing the total nutrient density of protein-rich foods and expands scientific research investigating the quality of proteins. In summary, the average sum of indispensable amino acids for meat and fish products is much more consistent than that of non-meat and plant-based food products. However, some non-meat products have relatively similar amounts of indispensable amino acids on a similar serving size basis. The overwhelming aspect of determining protein quality is that greater research is needed to determine protein digestibility of food products.</p

Data_Sheet_1_Radiomics analysis of pancreas based on dual-energy computed tomography for the detection of type 2 diabetes mellitus.PDF

ObjectiveTo utilize radiomics analysis on dual-energy CT images of the pancreas to establish a quantitative imaging biomarker for type 2 diabetes mellitus.Materials and methodsIn this retrospective study, 78 participants (45 with type 2 diabetes mellitus, 33 without) underwent a dual energy CT exam. Pancreas regions were segmented automatically using a deep learning algorithm. From these regions, radiomics features were extracted. Additionally, 24 clinical features were collected for each patient. Both radiomics and clinical features were then selected using the least absolute shrinkage and selection operator (LASSO) technique and then build classifies with random forest (RF), support vector machines (SVM) and Logistic. Three models were built: one using radiomics features, one using clinical features, and a combined model.ResultsSeven radiomic features were selected from the segmented pancreas regions, while eight clinical features were chosen from a pool of 24 using the LASSO method. These features were used to build a combined model, and its performance was evaluated using five-fold cross-validation. The best classifier type is Logistic and the reported area under the curve (AUC) values on the test dataset were 0.887 (0.73–1), 0.881 (0.715–1), and 0.922 (0.804–1) for the respective models.ConclusionRadiomics analysis of the pancreas on dual-energy CT images offers potential as a quantitative imaging biomarker in the detection of type 2 diabetes mellitus.</p

Photoaccelerated Water Dissociation Across One-Atom-Thick Electrodes

Recent experiments demonstrated that interfacial water dissociation (H2O ⇆ H+ + OH–) could be accelerated exponentially by an electric field applied to graphene electrodes, a phenomenon related to the Wien effect. Here we report an order-of-magnitude acceleration of the interfacial water dissociation reaction under visible-light illumination. This process is accompanied by spatial separation of protons and hydroxide ions across one-atom-thick graphene and enhanced by strong interfacial electric fields. The found photoeffect is attributed to the combination of graphene’s perfect selectivity with respect to protons, which prevents proton–hydroxide recombination, and to proton transport acceleration by the Wien effect, which occurs in synchrony with the water dissociation reaction. Our findings provide fundamental insights into ion dynamics near atomically thin proton-selective interfaces and suggest that strong interfacial fields can enhance and tune very fast ionic processes, which is of relevance for applications in photocatalysis and designing reconfigurable materials

Percentage change in plasma ghrelin, PYY, and GLP-1 over 6-hour after high-protein (HP), high-fat (HF), or high-carbohydrate (HC) meal using linear mixed models.

<p>Percentage change in plasma ghrelin, PYY, and GLP-1 over 6-hour after high-protein (HP), high-fat (HF), or high-carbohydrate (HC) meal using linear mixed models.</p

Incremental area-under-the-curve (iAUC) over 6 hours for plasma glucose, insulin, PYY, GLP-1, and ghrelin after ingestion of high-protein (HP), high-fat (HF) and high-carbohydrate (HC) meal.

<p>Incremental area-under-the-curve (iAUC) over 6 hours for plasma glucose, insulin, PYY, GLP-1, and ghrelin after ingestion of high-protein (HP), high-fat (HF) and high-carbohydrate (HC) meal.</p

Baseline anthropometry and fasting plasma biochemistry of study subjects.

<p>Baseline anthropometry and fasting plasma biochemistry of study subjects.</p