1,2-␣-L-Fucosidase (AfcA), which hydrolyzes the glycosidic linkage of Fuc␣1-2Gal via an inverting mechanism, was recently isolated from Bifidobacterium bifidum and classified as the first member of the novel glycoside hydrolase family 95. To better understand the molecular mechanism of this enzyme, we determined the x-ray crystal structures of the AfcA catalytic (Fuc) domain in unliganded and complexed forms with deoxyfuconojirimycin (inhibitor), 2-fucosyllactose (substrate), and L-fucose and lactose (products) at 1.12-2.10 Å resolution. The AfcA Fuc domain is composed of four regions, an N-terminal ␤ region, a helical linker, an (␣/␣) 6 helical barrel domain, and a C-terminal ␤ region, and this arrangement is similar to bacterial phosphorylases. In the complex structures, the ligands were buried in the central cavity of the helical barrel domain. Structural analyses in combination with mutational experiments revealed that the highly conserved Glu 566 probably acts as a general acid catalyst. However, no carboxylic acid residue is found at the appropriate position for a general base catalyst. Instead, a water molecule stabilized by Asn 423 in the substrate-bound complex is suitably located to perform a nucleophilic attack on the C1 atom of L-fucose moiety in 2-fucosyllactose, and its location is nearly identical near the O1 atom of ␤-L-fucose in the products-bound complex. Based on these data, we propose and discuss a novel catalytic reaction mechanism of AfcA.

Background: Analyzing real-world data, including health insurance claims, may help provide insights into preventing and treating various diseases. We developed a database covering Shizuoka Prefecture (Shizuoka Kokuho Database [SKDB]) in Japan, which included individual-level linked data on health-and care-insurance claims and health checkup results. Methods: Anonymized claims data on health insurance (National Health Insurance [age <75 years] and Latter-Stage Elderly Medical Care System [age ≥75 years]), care insurance, subscriber lists, annual health checkups, and all dates of death were collected from 35 municipalities in Shizuoka Prefecture. To efficiently link claims and health checkups, unique individual IDs were assigned using a novel procedure. Results: From April 2012 to September 2018, the SKDB included 2,230,848 individuals (men, 1,019,687; 45.7%). The median age (min-max) of men and women was 60 (0-106) and 62 (0-111) years, respectively. During the study period, the median subscription time was 4.4 years; 40.8% of individuals continuously subscribed for the 6.5 years; 213,566 individuals died. Health checkup data were available for 654,035 individuals, amounting to 2,469,648 records. Care-service recipient data were available for 283,537 individuals; they used care insurance to pay for care costs. Conclusions: SKDB, a population-based longitudinal cohort, provides a comprehensive dataset covering health checkups, disorders, medication, and care service. This database may provide a robust platform to identify epidemiological problems and generate hypotheses for preventing and treating disorders in the elderly.

The association of incident CKD with hyperuricaemia was stronger than with other chronic kidney disease-risk factors, this association becoming more significant in the advanced stage of chronic kidney disease. Although this result does not indicate the cause and result relationship, the data suggest that hyperuricaemia might not be appropriately treated in this population.

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Background Japan is one of the Organization for Economic Co-operation and Development (OECD) countries where population aging and increasing health care expenditures (HCE) are urgent issues. Recent studies have identified factors other than age, such as proximity to death and morbidity, as contributing factors to the increase in medical costs. It is important to assess HCE by disease and analyze their factors to estimate and improve future HCE. Methods We extracted individual records spanning approximately 2 years prior to the death of persons aged 65 to 95 years from the National Health Insurance data in Japan, and used a Bayesian approach to decompose monthly HCE into five disease groups (circulatory, chronic kidney disease, neoplasms, respiratory, and others). The relationship between the proximity to death and the average HCE in each disease group was stratified by sex and age and analyzed using a descriptive statistical method similar to the two-part model. Results The average HCE increased rapidly as death approached in most disease groups, but the increase-pattern differed greatly among disease groups, sex, and age groups. The effect of proximity to death on average HCE was small for chronic diseases, but large for lethal diseases. When stratified by age and sex, younger and male decedents tended to have higher average HCE, but the extent of this varied by disease group. The two-year cumulative average HCE for neoplasms in the 65–75 years age group was about six times larger than those in the 85–95 years age group. Conclusions In Japan, it was suggested that disease, proximity to death, age, and sex may contribute to HCE. However, these factors interact in a complex manner, and it is important to analyze HCE by disease. In addition, preventing or delaying the severity of diseases with high medical burdens in younger people may be effective in reducing future terminal care costs. These findings have important implications for future projections and improvements of HCE.