Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R2) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R2 (0.875) and RMSE (2.41%).

Effect of extraction methods on the chemical components and taste quality of green tea extract.

The physicochemical properties of tea extracts are significantly affected by the extraction method. The aim of this study was to compare the effects of static and dynamic extractions on the concentrations of chemical components and taste quality of green tea extracts. Our results show that extraction of chemical components using static extraction follows a pseudo-second-order reaction, while that of dynamic extraction follows a first-order reaction. The concentrations of the solids, polyphenols, and free amino acids in green tea extract prepared by dynamic extraction were much higher, although the overall yields were not significantly different between the two extraction methods. Green tea extracts obtained via dynamic extraction were of lower bitterness and astringency, as well and higher intensities of umami and overall acceptability. These results suggest that dynamic extraction is more suitable for the processing of green tea concentrate because of the higher concentration of green tea extract.

Glioma-Associated Oncogene Homolog1 (Gli1)-Aquaporin1 pathway promotes glioma cell metastasis.

Glioma-Associated Oncogene Homolog1 (Gli1) is known to be activated in malignant glioma; however, its downstream pathway has not been fully explained. The aim of this study was to explore the role of Gli1-Aquaporin1 (AQP1) signal pathway in glioma cell survival. Our data suggests that both Gli1 and AQP1 are upregulated in glioma tissues, as in comparison to in normal tissues. These up-regulation phenomena were also observed in glioma U251 and U87 cells. It was demonstrated that Gli1 positively regulated the AQP1 expression. By luciferase reporter gene and ChIP assay, we observed that this modulation process was realized by combination of Gli1 with AQP1 promotor. In addition, knock down of Gli1 by siRNA interference reduced the viability of glioma cells as well as suppressed cell metastasis. Also, the inhibitory effects of cell survival by silenced Gli1 were abrogated by AQP1 overexpression. In summary, glioma cell survival is a regulatory process and can be mediated by Gli1-AQP1 pathway. [BMB Reports 2016; 49(7): 394-399].

Identifying key non-volatile compounds in ready-to-drink green tea and their impact on taste profile.

Thirty-nine non-volatile compounds in seven ready-to-drink (RTD) green tea samples were analysed and quantified using liquid chromatography. Taste reconstruction experiments using thirteen selected compounds were conducted to identify the key non-volatile tastants. Taste profiles of the reconstructed samples did not differ significantly from the RTD tea samples. To investigate the taste contribution and significance of individual compounds, omission experiments were carried out by removing individual or a group of compounds. Sensory evaluation revealed that the astringent- and bitter-tasting (-)-epigallocatechin gallate, bitter-tasting caffeine, and the umami-tasting l-glutamic acid were the main contributors to the taste of RTD green tea. Subsequently, the taste profile of the reduced recombinant, comprising of a combination of these three compounds and l-theanine, was found to not differ significantly from the sample recombinant and RTD tea sample. Lastly, regression models were developed to objectively predict and assess the intensities of bitterness and astringency in RTD green teas.