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.

"One of our hosts in another country": Challenges of data geolocation in cloud storage

Physical location of data in cloud storage is an increasingly urgent problem. In a short time, it has evolved from the concern of a few regulated businesses to an important consideration for many cloud storage users. One of the characteristics of cloud storage is fluid transfer of data both within and among the data centres of a cloud provider. However, this has weakened the guarantees with respect to control over data replicas, protection of data in transit and physical location of data. This paper addresses the lack of reliable solutions for data placement control in cloud storage systems. We analyse the currently available solutions and identify their shortcomings. Furthermore, we describe a high-level architecture for a trusted, geolocation-based mechanism for data placement control in distributed cloud storage systems, which are the basis of an on-going work to define the detailed protocol and a prototype of such a solution. This mechanism aims to provide granular control over the capabilities of tenants to access data placed on geographically dispersed storage units comprising the cloud storage.