Biomarkers of food intake and nutrient status are associated with glucose tolerance status and development of type 2 diabetes in older Swedish women

Background: Diet is frequently associated with both the development and prevention of type 2 diabetes (T2D), but there is a lack of objective tools for assessing the relation between diet and T2D. Biomarkers of dietary intake are unconfounded by recall and reporting bias, and using multiple dietary biomarkers could help strengthen the link between a healthy diet and the prevention of T2D.Objective: The objective of this study was to explore how diet is related to glucose tolerance status (GTS) and to future development of T2D irrespective of common T2D and cardiovascular disease risk factors by using multiple dietary biomarkers.Design: Dietary biomarkers were measured in plasma from 64-y-old Swedish women with different GTS [normal glucose tolerance (NGT; n = 190), impaired glucose tolerance (IGT; n = 209), and diabetes (n = 230)]. The same subjects were followed up after 5 y to determine changes in glucose tolerance (n = 167 for NGT, n = 174 for IGT, and n = 159 for diabetes). ANCOVA and logistic regression were used to explore baseline data for associations between dietary biomarkers, GTS, and new T2D cases at follow-up (n = 69).Results: Of the 10 dietary biomarkers analyzed, β-alanine (beef) (P-ra

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered

Dynamics of the normal gut microbiota: A longitudinal one-year population study in Sweden

Temporal dynamics of the gut microbiota potentially limit the identification of microbial features associated with health status. Here, we used whole-genome metagenomic and 16S rRNA gene sequencing to characterize the intra- and inter-individual variations of gut microbiota composition and functional potential of a disease-free Swedish population (n = 75) over one year. We found that 23% of the total compositional variance was explained by intra-individual variation. The degree of intra-individual compositional variability was negatively associated with the abundance of Faecalibacterium prausnitzii (a butyrate producer) and two Bifidobacterium species. By contrast, the abundance of facultative anaerobes and aerotolerant bacteria such as Escherichia coli and Lactobacillus acidophilus varied extensively, independent of compositional stability. The contribution of intra-individual variance to the total variance was greater for functional pathways than for microbial species. Thus, reliable quantification of microbial features requires repeated samples to address the issue of intra-individual variations of the gut microbiota

Topographic modelling of haptic properties of tissue products

The way a product or material feels when touched, haptics, has been shown to be a property that plays an important role when consumers determine the quality of products For tissue products in constant touch with the skin, softness becomes a primary quality parameter. In the present work, the relationship between topography and the feeling of the surface has been investigated for commercial tissues with varying degree of texture from the low textured crepe tissue to the highly textured embossed- and air-dried tissue products. A trained sensory panel at was used to grade perceived haptic \uabroughness\ubb. The technique used to characterize the topography was Digital light projection (DLP) technique, By the use of multivariate statistics, strong correlations between perceived roughness and topography were found with predictability of above 90 percent even though highly textured products were included. Characterization was made using areal ISO 25178-2 topography parameters in combination with non-contacting topography measurement. The best prediction ability was obtained when combining haptic properties with the topography parameters auto-correlation length (Sal), peak material volume (Vmp), core roughness depth (Sk) and the maximum height of the surface (Sz). \ua9 Published under licence by IOP Publishing Ltd

Percentage White: A New Feature for Ultrasound Classification of Plaque Echogenicity in Carotid Artery Atherosclerosis.

Atherosclerotic stenotic and nonstenotic plaques of the carotid artery with low echogenicity have been shown to be associated with cardiovascular disease. The aim was to develop a new method for semiautomated ultrasound image analysis to classify nonstenotic carotid plaques, evaluate cases with multiple plaques and examine the association between a new image analysis feature of echogenicity and predictors of cardiovascular disease. The new image analysis feature, percentage white (PW), represents the fraction of bright structures inside a plaque and is integrated in an objective semiautomated method to evaluate echogenicity (SAMEE) in carotid plaques. PW was constructed to take into account overall echogenicity of the image as well as noise surrounding the plaque. Consecutive ultrasound examinations of carotid plaques from a population-based screening of 64-year-old women with varying risk for cardiovascular disease were selected for the present project; 92 far-wall and 47 near-wall plaques were used as a training dataset to develop the SAMEE algorithm with visual classification according to Gray-Weale as reference; 273 plaques were used to validate the method. All plaques were included in an analysis relating predictors of cardiovascular to average PW in all plaques, PW in the biggest plaque and to the plaque with lowest PW in each subject, respectively. In the training dataset the intermethodological variability between SAMEE and visual classification showed a kappa of 0.78 and a sensitivity and specificity of 96% and 81%, respectively. In the validation set, SAMEE and visual classification showed a kappa of 0.77, a sensitivity of 96% and a specificity of 80%. The reproducibility of PW was high, evidenced by r = 0.96 and CV = 9.85% at repeated examinations. Average PW values were associated with several predictors of cardiovascular risk: lipoprotein (a), HbA1c, blood glucose, apolipoproteinB/apolipoproteinA-I; and associated negatively with the levels of adiponectin and apolipoprotein A-I. In conclusion, PW integrated within a SAMEE is a new feature for assessment of echogenicity in carotid plaques and shows excellent reproducibility and agreement with visual assessment

Percentage White: A New Feature for Ultrasound Classification of Plaque Echogenicity in Carotid Artery Atherosclerosis.

Atherosclerotic stenotic and nonstenotic plaques of the carotid artery with low echogenicity have been shown to be associated with cardiovascular disease. The aim was to develop a new method for semiautomated ultrasound image analysis to classify nonstenotic carotid plaques, evaluate cases with multiple plaques and examine the association between a new image analysis feature of echogenicity and predictors of cardiovascular disease. The new image analysis feature, percentage white (PW), represents the fraction of bright structures inside a plaque and is integrated in an objective semiautomated method to evaluate echogenicity (SAMEE) in carotid plaques. PW was constructed to take into account overall echogenicity of the image as well as noise surrounding the plaque. Consecutive ultrasound examinations of carotid plaques from a population-based screening of 64-year-old women with varying risk for cardiovascular disease were selected for the present project; 92 far-wall and 47 near-wall plaques were used as a training dataset to develop the SAMEE algorithm with visual classification according to Gray-Weale as reference; 273 plaques were used to validate the method. All plaques were included in an analysis relating predictors of cardiovascular to average PW in all plaques, PW in the biggest plaque and to the plaque with lowest PW in each subject, respectively. In the training dataset the intermethodological variability between SAMEE and visual classification showed a kappa of 0.78 and a sensitivity and specificity of 96% and 81%, respectively. In the validation set, SAMEE and visual classification showed a kappa of 0.77, a sensitivity of 96% and a specificity of 80%. The reproducibility of PW was high, evidenced by r = 0.96 and CV = 9.85% at repeated examinations. Average PW values were associated with several predictors of cardiovascular risk: lipoprotein (a), HbA1c, blood glucose, apolipoproteinB/apolipoproteinA-I; and associated negatively with the levels of adiponectin and apolipoprotein A-I. In conclusion, PW integrated within a SAMEE is a new feature for assessment of echogenicity in carotid plaques and shows excellent reproducibility and agreement with visual assessment

Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers

Biomarkers of food intake and nutrient status are associated with glucose tolerance status and development of Type 2 diabetes

BACKGROUND Diet is frequently associated with both the development and prevention of type 2 diabetes (T2D) but there are a lack of objective tools for assessing the causal relationships between diet and T2D. Biomarkers of dietary intake could help strengthen the link between a healthy diet and prevention of diabetes.OBJECTIVE The objective of this study was to explore how diet is related to glucose tolerance status (GTS) and future development of T2D irrespective of metabolic syndrome (MetS) risk factors, using dietary biomarkers as an objective measure of dietary intake unconfounded by recall and reporting bias.RESEARCH DESIGN AND METHODS Dietary biomarkers were measured in plasma from 64-year old women with different glucose tolerance classifications (normal glucose tolerance; NGT (n=190), impaired glucose tolerance; IGT (n=209), and diabetes (n=230)), randomly selected from the population register in Gothenburg, Sweden. The same subjects were followed up after 5 years to determine changes in glucose tolerance (NGT (n=167), IGT (n=174) and diabetes (n=159)). Analysis of covariance (ANCOVA) adjusted for significant measures of MetS was used to explore baseline data for associations between dietary biomarkers, GTS and new T2D cases at follow up (n=69).RESULTS After adjustment for MetS risk factors, alpha-tocopherol, alkylresorcinols C17 and C19 (markers of whole grain wheat and rye), b-alanine (meat), eicosapentaenoic acid (fish) and linoleic acid were associated with GTS and 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) (fish) and alpha-tocopherol with future development of T2D.CONCLUSIONS Several dietary biomarkers were strongly associated with GTS irrespective of MetS factors, underlining the role of diet in development and prevention of T2D. The use of multiple dietary biomarkers can provide a link with diet that is unencumbered by recall bias normally associated with dietary studies and allows examination of the role of diet even when dietary information is not available