Crystal structures of rare disaccharides, α-D-glucopyranosyl ß-D-psicofuranoside, and α-D-galactopyranosyl ß-D-psicofuranoside.

The crystal structures of α-D-glucopyranosyl ß-D-psicofuranoside and α-D-galactopyranosyl ß-D-psicofuranoside were determined by a single-crystal X-ray diffraction analysis, refined to R(1)=0.0307 and 0.0438, respectively. Both disaccharides have a similar molecular structure, in which psicofuranose rings adopt an intermediate form between (4)E and (4)T(3). Unique molecular packing of the disaccharides was found in crystals, with the molecules forming a layered structure stacked along the y-axis.

Evaluation of error levels in hemoglobin A1c and glycated albumin in type 2 diabetic patients due to inter-individual variability.

AIM: To evaluate error levels in hemoglobin A1c (A1C) and glycated albumin (GA) in type 2 diabetic patients due to inter-individual variability. METHODS: Type 2 diabetic patients with stable glycemic control and without complications affecting either A1C or GA were enrolled (n=154; age 68.4+/-9.9 years). Blood examination was performed 1-4h after breakfast or lunch every 2-3 months on > or =3 occasions. A1C data were changed to IFCC values for analysis. RESULTS: A1C and GA correlated significantly with postprandial plasma glucose. The correlation coefficient between A1C and GA was 0.728 (p<0.001) when calculated using raw data and 0.747 (p<0.001) when calculated using averaged data for each patient. The ratio R of GA to A1C was 3.88+/-0.50 for raw data and 3.88+/-0.47 for averaged data, indicating coefficients of variation of R (CV(R)) of 12.9% and 12.1%, respectively. Multiple regression analysis reduced CV(R) to 11.2%. After dividing CV(R)(2) into CV(A1C)(2) and CV(GA)(2), CV(A1C) and CV(GA) were calculated as 9.1% for raw data and 8.6% for averaged data, and were reduced to 7.9% after multiple regression analysis. CONCLUSIONS: Error levels in A1C and GA reach 7.9-9.1%, suggesting the existence of maximal 18% errors in A1C and GA levels.

Analysis of the method for conversion between levels of HbA1c and glycated albumin by linear regression analysis using a measurement error model.

AIM: To establish a method for conversion between HbA(1c) and glycated albumin (GA) using a measurement error model (MEM). METHODS: Type 2 diabetic patients, without complications that might affect either HbA(1c) or GA, were enrolled in the study (n=154, age 68.4+/-9.9). HbA(1c), GA and postprandial plasma glucose (PPG) levels were measured simultaneously on >or=3 occasions. RESULTS: PPG showed a significant correlation with HbA(1c) and GA (p<0.001 for both). Correlation between HbA(1c) and GA was very high (r=0.747, p<0.001). When the independent variable was assumed to be GA, common regression analysis yielded a regression line HbA(1c)=2.59+0.204GA. When the independent variable was changed to HbA(1c), the regression line became GA=2.26+2.74HbA(1c). The y-intercept of the first line was significantly positive, whereas that of the second was not. The regression line using MEM was HbA(1c)=1.73+0.245GA. The y-intercept was 1.73+/-0.38 (p<0.001) and the slope was 0.245+/-0.018 (p<0.001), showing that 1% increase in HbA(1c) level corresponds to 4% increase in GA level. CONCLUSIONS: The relationship between HbA(1c) and GA was examined by regression analysis using MEM. HbA(1c) levels in Japan appear to have a positive shift of approximately 1.7%. Incremental ratio 4 of GA vs. HbA(1c) showed good consistency with values derived from in vitro data.