An effective treatment approach of liposomally encapsulated metformin in colon cancer.

Metformin is a drug that is widely used in the treatment of type-2 diabetes and its anticarcinogenic effect has been detected in many studies since the 2000s. Metformin has a short half-life and poor biocompatibility, which limits the activity of the drug. As a solution to this situation, our study aimed to increase the anticarcinogenic effects and reduce the side effects of metformin in colon cancer by liposomal encapsulation. For this purpose, in our study, liposome production was carried out using the thin film hydration method. The amount of metformin loaded in liposomes was determined by a standard absorbance curve at 237 nm. Size distributions and membrane zeta potentials of the liposomes were evaluated with Malvern Zetasizer ZS90. Transmission electron microscopy was performed by staining the liposomes negatively with uranyl acetate. Cultured HT-29 cells were treated with liposomal metformin or free metformin at concentrations of 0, 10, 20, and 40 mM for 24 and 48 h. At the end of the treatment period, cell viability was evaluated by CellTiter-Glo luminescent cell viability test. The anticarcinogenic effects of liposomal and free metformin on HT-29 cells were compared. As a result, liposome encapsulated metformin treatment for 24 h was more effective on HT-29 cells at 20- and 40-mM concentrations causing significantly greater decrease in the IC-50 dose compared to the free metformin. The result suggests that liposomal encapsulated metformin may offer a promising approach to increase the efficacy of the drug in the treatment of colon cancer.

Computer vision based analysis of potato chips--a tool for rapid detection of acrylamide level.

In this study, analysis of digital color images of fried potato chips were combined with parallel LC-MS based analysis of acrylamide in order to develop a rapid tool for the estimation of acrylamide during processing. Pixels of the fried potato image were classified into three sets based on their Euclidian distances to the representative mean values of typical bright yellow, yellowish brown, and dark brown regions using a semiautomatic segmentation algorithm. The featuring parameter extracted from the segmented image was NA2 value which was defined as the number of pixels in Set-2 divided by the total number of pixels of the entire fried potato image. Using training images of potato chips, it was shown that there was a strong linear correlation (r = 0.989) between acrylamide level and NA2 value. Images of a number of test samples were analyzed to predict their acrylamide level by means of this correlation data. The results confirmed that computer vision system described here provided explicit and meaningful description from the viewpoint of inspection and evaluation purpose for potato chips. Assuming a provisional threshold limit of 1000 ng/g for acrylamide, test samples could be successfully inspected with only one failure out of 60 potato chips.