Effective SGLT2 Inhibitor for Patient with Type 2 Diabetes Mellitus (T2DM) and Depression

The case was a 55-year-old female patient with depression for 5 years and type 2 diabetes mellitus (T2DM) for 3 years. She has received anti-depressant and anti-hyperglycemic agents (OHAs). Approximately 1 year ago, her diabetic control became exacerbated without specific triggers. She was started to given Ipragliflozin L-Proline as Sodium-Glucose Cotransporter-2 (SGLT2) Inhibitor. After that, her glucose variability and depression had been improved. According to the previous reports, SGLT-2 inhibitors seem to have anti-depression efficacy for diabetes. The case has been followed up in detail, and this report is expected to be a useful reference for diabetes care

RiceXPro: a platform for monitoring gene expression in japonica rice grown under natural field conditions

Elucidating the function of all predicted genes in rice remains as the ultimate goal in cereal genomics in order to ensure the development of improved varieties that will sustain an expanding world population. We constructed a gene expression database (RiceXPro, URL: http://ricexpro.dna.affrc.go.jp/) to provide an overview of the transcriptional changes throughout the growth of the rice plant in the field. RiceXPro contains two data sets corresponding to spatiotemporal gene expression profiles of various organs and tissues, and continuous gene expression profiles of leaf from transplanting to harvesting. A user-friendly web interface enables the extraction of specific gene expression profiles by keyword and chromosome search, and basic data analysis, thereby providing useful information as to the organ/tissue and developmental stage specificity of expression of a particular gene. Analysis tools such as t-test, calculation of fold change and degree of correlation facilitate the comparison of expression profiles between two random samples and the prediction of function of uncharacterized genes. As a repository of expression data encompassing growth in the field, this database can provide baseline information of genes that underlie various agronomically important traits in rice