Correction: Ingestion of taxifolin-rich foods affects brain activity, mental fatigue, and the whole blood transcriptome in healthy young adults: a randomized, double-blind, placebo-controlled, crossover study.

Correction for 'Ingestion of taxifolin-rich foods affects brain activity, mental fatigue, and the whole blood transcriptome in healthy young adults: a randomized, double-blind, placebo-controlled, crossover study' by Fumika Shinozaki , , 2023, https://doi.org/10.1039/d2fo03151e.

Ingestion of taxifolin-rich foods affects brain activity, mental fatigue, and the whole blood transcriptome in healthy young adults: a randomized, double-blind, placebo-controlled, crossover study.

The antioxidant properties of polyphenols, which are found in most plants, have been shown to be useful for maintaining health, including enhancing brain function and alleviating stress. We aimed to investigate the effect of a single intake of taxifolin-containing foods on cognitive task performance and whole blood gene expression in healthy young adults. This study was a randomized, placebo-controlled, double-blind, crossover trial in which healthy young adults were administered a single dose of either a placebo or food containing taxifolin.

Association between insulin resistance and plasma amino acid profile in non-diabetic Japanese subjects.

Aims/introduction: Elevation of the branched-chain amino acids (BCAAs), valine, leucine and isoleucine; and the aromatic amino acids, tyrosine and phenylalanine, has been observed in obesity-related insulin resistance. However, there have been few studies on Asians, who are generally less obese and less insulin-resistant than Caucasian or African-Americans. In the present study, we investigated the relationship between homeostasis model assessment of insulin resistance (HOMA-IR) and plasma amino acid concentration in non-diabetic Japanese participants.

The phenotype and genotype experiment object model (PaGE-OM): a robust data structure for information related to DNA variation.

Torrents of genotype-phenotype data are being generated, all of which must be captured, processed, integrated, and exploited. To do this optimally requires the use of standard and interoperable "object models," providing a description of how to partition the total spectrum of information being dealt with into elemental "objects" (such as "alleles," "genotypes," "phenotype values," "methods") with precisely stated logical interrelationships (such as "A objects are made up from one or more B objects"). We herein propose the Phenotype and Genotype Experiment Object Model (PaGE-OM; www.