A thin-layer chromatography-bioautographic method for detecting dipeptidyl peptidase IV inhibitors in plants

A thin-layer chromatography (TLC)-bioautographic method was developed with the aim to detect dipeptidyl peptidase IV (DPP IV) inhibitors from plant extracts. The basic principle of the method is that the enzyme (DPP IV) hydrolyzes substrate (Gly-Pro-p-nitroaniline) into p-nitroaniline (pNA), which diazotizes with sodium nitrite, and then reacts with N-(1-naphthyl) ethylenediamine dihydrochloride in turn to form a rose-red azo dye which provides a rose-red background on the TLC plates. The DPP IV inhibitors showed white spots on the background as they blocked enzymolysis of the substrate to produce pNA. The method was validated with respect to selectivity, sensitivity, linearity, precision, recovery, and stability after optimizing key parameters including plate type, time and temperature of incubation, concentration of substrate, enzyme and derivatization reagents, and absorption wavelength. The results showed good lineary within amounts over 0.01–0.1 μg range for the positive control, diprotin A, with the coefficient of determination (r2) = 0.9668. The limits of detection (LOD) and quantification (LOQ) were 5 and 10 ng, respectively. The recoveries ranged from 98.9% to 107.5%. The averages of the intra- and inter-plate reproducibility were in the range of 4.1–9.7% and 7.6–14.7%, respectively. Among the nine methanolic extracts of medicinal herbs screened for DPP IV inhibitors by the newly developed method, Peganum nigellastrum Bunge was found to have one white active spot, which was then isolated and identified as harmine. By spectrophotometric method, harmine hydrochloride was found to have DPP-IV inhibitory activity of 32.4% at 10 mM comparing to that of 54.8% at 50 μM for diprotin A.

Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such asMRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat–muscle quantitation system (AMRATM Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRATM Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRATM Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRATM Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variationwas 1.4%for IAAT and 1.2%for ASAT, the intra-observer correlationwas 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRATM Profiler, opening up the possibility of large-scale human phenotypic studies.