A study of glycaemic effects following acute anthocyanin-rich blueberry supplementation in healthy young adults

The postprandial response to ingested carbohydrate is recognised as a marker of metabolic health. Postprandial hyperglycaemia is observed in type 2 diabetes mellitus and is a significant risk factor for cardiovascular disease. Cognitive deficits are also associated with type 2 diabetes. Therefore interventions which moderate postprandial glucose profiles are desirable. Here we investigated the impact of anthocyanin-rich wild blueberries on postprandial glucose response. Seventeen healthy young adults consumed a range of doses of freeze-dried wild blueberry powder, in smoothie form, in both sugar-matched and no-added-sugar conditions. Plasma glucose was determined by a capillary sampling method at baseline and at regular intervals up to 2.5 hours postprandially. Blueberries were observed to significantly extend the postprandial glucose response beyond the period observed for a sugar-matched control, characteristic of a beneficial glycaemic response. Furthermore, blueberries were observed to reduce peak postprandial glucose levels, although statistical significance was not achieved. The findings suggest a tempering of the postprandial glucose response in the presence of anthocyanin-rich blueberry, and are discussed with reference to likely glucoregulatory mechanisms of action and their implications for cognitive and type 2 diabetes research

Multiple Subject Barycentric Discriminant Analysis (MUSUBADA): How to Assign Scans to Categories without Using Spatial Normalization

We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can analyze datasets with different voxel numbers per participant and, so does not require spatial normalization. MUSUBADA statistical inferences are implemented with cross-validation techniques (e.g., jackknife and bootstrap), its performance is evaluated with confusion matrices (for fixed and random models) and represented with prediction, tolerance, and confidence intervals. We present an example where we predict the image categories (houses, shoes, chairs, and human, monkey, dog, faces,) of images watched by participants whose brains were scanned. This example corresponds to a DA question in which the data table is made of subtables (one per subject) and with more variables than observations

Diabetes, Abdominal Adiposity, and Atherogenic Dyslipoproteinemia in Women Compared With Men

OBJECTIVE—To understand why atherogenic risk differs more between diabetic and nondiabetic women than between diabetic and nondiabetic men

Multiple Subject Barycentric Discriminant Analysis (MUSUBADA): How to Assign Scans to Categories without Using Spatial Normalization

We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can analyze datasets with different voxel numbers per participant and, so does not require spatial normalization. MUSUBADA statistical inferences are implemented with cross-validation techniques (e.g., jackknife and bootstrap), its performance is evaluated with confusion matrices (for fixed and random models) and represented with prediction, tolerance, and confidence intervals. We present an example where we predict the image categories (houses, shoes, chairs, and human, monkey, dog, faces,) of images watched by participants whose brains were scanned. This example corresponds to a DA question in which the data table is made of subtables (one per subject) and with more variables than observations

Diabetes, Abdominal Adiposity, and Atherogenic Dyslipoproteinemia in Women Compared With Men

OBJECTIVE—To understand why atherogenic risk differs more between diabetic and nondiabetic women than between diabetic and nondiabetic men

Impact of Baseline Heart Failure Burden on Post-Implantable Cardioverter-Defibrillator Mortality Among Medicare Beneficiaries

ObjectivesThis study sought to assess the impact of baseline heart failure (HF) burden on survival with primary implantable cardioverter-defibrillator (ICD) among Medicare recipients.BackgroundSurvival after primary ICD implantation may differ between trial and Medicare populations.MethodsLinking data from the CMS (Centers for Medicare and Medicaid Services) ICD registry and the Medicare files (2005 to 2009), we identified primary ICD recipients age ≥66 years with ejection fraction ≤35%. Number of previous HF hospitalizations (prev-HF-hosp) and length of hospitalization prior to implantation were used to define HF burden. Crude all-cause mortality was estimated. Adjusted hazard ratios (HR) were derived from Cox models.ResultsOf 66,974 ICD recipients (73% men, 88% white, mean age 75 years), 11,876 died (average follow-up = 1.4 years), with 3-year mortality of 31%. Among patients with no prev-HF-hosp, 3-year mortality was 27% compared with 63% in those with ≥3 prev-HF-hosp (adjusted HR: 1.8). Among patients with same-day implantation, 3-year mortality was 25% compared with 53% in those with >1-week hospitalization days prior to implantation (adjusted HR: 1.9). Mortality at 3-year follow-up among the 31,685 ICD recipients with no prev-HF-hosp and same-day implantation (low HF burden) was similar to that in trials (22%).ConclusionsNearly one-third of Medicare ICD recipients died within 3 years, reflecting a population with more advanced age and disease than seen in trial populations for primary prevention ICD. Nearly one-half of Medicare recipients had a low HF burden and had a survival similar to trial ICD recipients. Future research is warranted to understand the effectiveness of primary ICD implantation among Medicare beneficiaries with heavy HF burdens

Dietary flavonoids and human cognition: a meta‐analysis

Abstract: Improving cognition is important in all age groups, from performance in school examinations to prevention of cognitive decline in later life. Dietary polyphenols, in particular flavonoids, have been examined for their benefits to cognitive outcomes. This meta‐analysis evaluates the effects of dietary flavonoids on cognition across the lifespan. In January 2020 databases were searched for randomized controlled trials investigating flavonoid effects on human cognition. Eighty studies, comprising 5519 participants, were included in the final meta‐analysis. The global analysis indicates dietary flavonoids induced significant benefit to cognitive performance (g = 0.148, p < 0.001), with subgroup analyses revealing that cocoa (g = 0.224, p = 0.036), ginkgo (g = 0.187, p ≤ 0.001), and berries (g = 0.149, p = 0.009) yielded the most notable improvements. Significant benefits were observed from chronic studies, in middle‐aged and older adults, and with low and medium doses. The domains of long‐term memory, processing speed, and mood showed sensitivity to flavonoid intervention. This meta‐analysis provides evidence for the positive effects of flavonoids on cognition and highlights several moderating factors. Flavonoid‐based dietary interventions therefore potentially offer a highly accessible, safe, and cost‐effective treatment to help tackle the burden of cognitive decline

Genome-Wide Association Study Identifies Loci for Liver Enzyme Concentrations in Mexican Americans: The GUARDIAN Consortium.

ObjectivePopulations of Mexican American ancestry are at an increased risk for nonalcoholic fatty liver disease. The objective of this study was to determine whether loci in known and novel genes were associated with variation in aspartate aminotransferase (AST) (n = 3,644), alanine aminotransferase (ALT) (n = 3,595), and gamma-glutamyl transferase (GGT) (n = 1,577) levels by conducting the first genome-wide association study (GWAS) of liver enzymes, which commonly measure liver function, in individuals of Mexican American ancestry.MethodsLevels of AST, ALT, and GGT were determined by enzymatic colorimetric assays. A multi-cohort GWAS of individuals of Mexican American ancestry was performed. Single-nucleotide polymorphisms (SNP) were tested for association with liver outcomes by multivariable linear regression using an additive genetic model. Association analyses were conducted separately in each cohort, followed by a nonparametric meta-analysis.ResultsIn the PNPLA3 gene, rs4823173 (P = 3.44 × 10-10 ), rs2896019 (P = 7.29 × 10-9 ), and rs2281135 (P = 8.73 × 10-9 ) were significantly associated with AST levels. Although not genome-wide significant, these same SNPs were the top hits for ALT (P = 7.12 × 10-8 , P = 1.98 × 10-7 , and P = 1.81 × 10-7 , respectively). The strong correlation (r2  = 1.0) for these SNPs indicated a single hit in the PNPLA3 gene. No genome-wide significant associations were found for GGT.ConclusionsPNPLA3, a locus previously identified with ALT, AST, and nonalcoholic fatty liver disease in European and Japanese GWAS, is also associated with liver enzymes in populations of Mexican American ancestry