Discrimination of the harvesting season of green tea by alcohol/salt-based aqueous two-phase systems combined with chemometric analysis.

The flavor and aroma quality of green tea are closely related to the harvest season. The aim of this study was to identify the harvesting season of green tea by alcohol/salt-based aqueous two-phase system (ATPS) combined with chemometric analysis. In this paper, the single factor experiments (SFM) and response surface methodology (RSM) optimization were designed to investigate and select the optimal ATPS. A total of 180 green tea samples were studied in this work, including 86 spring tea and 94 autumn tea. After the active components in green tea samples were extracted by the optimal ethanol/(NH4)2SO4 ATPS, the qualitative and quantitative analysis was realized based on HPLC-DAD combined with alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) algorithm, with satisfactory spiked recoveries (86.00 %-112.45 %). The quantitative results obtained from ATLD-MCR model were subjected to chemometric pattern recognition analysis. The constructed partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models showed better results than the principal component analysis (PCA) model, and the R2Xcum values (>0.835) and R2Ycum (>0.937) were close to 1, the Q2cum values were greater than 0.75 (>0.933), and the differences between R2Ycum and Q2cum were not larger than 0.2, indicating excellent cross-validation prediction performance of the models. Furthermore, the classification results based on the hierarchical clustering analysis (HCA) were consistent with the PCA, PLS-DA and OPLS-DA results, establishing a good correlation between tea active components and the harvesting seasons of green tea. Overall, the combination of ATPS and chemometric methods is accurate, sensitive, fast and reliable for the qualitative and quantitative determination of tea active components, providing guidance for the quality control of green tea.

On-chip rapid drug screening of leukemia cells by acoustic streaming.

Rapid and personalized single-cell drug screening testing plays an essential role in acute myeloid leukemia drug combination chemotherapy. Conventional chemotherapeutic drug screening is a time-consuming process because of the natural resistance of cell membranes to drugs, and there are still great challenges related to using technologies that change membrane permeability such as sonoporation in high-throughput and precise single-cell drug screening with minimal damage. In this study, we proposed an acoustic streaming-based non-invasive single-cell drug screening acceleration method, using high-frequency acoustic waves (>10 MHz) in a concentration gradient microfluidic device. High-frequency acoustics leads to increased difficulties in inducing cavitation and generates acoustic streaming around each single cell. Therefore, single-cell membrane permeability is non-invasively increased by the acoustic pressure and acoustic streaming-induced shear force, which significantly improves the drug uptake process. In the experiment, single human myeloid leukemia mononuclear (THP-1) cells were trapped by triangle cell traps in concentration gradient chips with different cytarabine (Ara-C) drug concentrations. Due to this dual acoustic effect, the drugs affect cell viability in less than 30 min, which is faster than traditional methods (usually more than 24 h). This dual acoustic effect-based drug delivery strategy has the potential to save time and reduce the cost of drug screening, when combined with microfluidic technology for multi-concentration drug screening. This strategy offers enormous potential for use in multiple drug screening or efficient drug combination screening in individualized/personalized treatments, which can greatly improve efficiency and reduce costs.

Comparison of three second-order multivariate calibration methods for the rapid identification and quantitative analysis of tea polyphenols in Chinese teas using high-performance liquid chromatography.

Retention time shifts in second-order calibration-assisted chromatographic analysis seriously impact the modeling and quantitative accuracies in complex systems. In this work, three second-order methods, i.e. alternating trilinear decomposition (ATLD) algorithm, multivariate curve resolution-alternating least squares (MCR-ALS), alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR), were compared their performance to process liquid chromatographic data in the presence of retention time shifts and overlapped peaks. Firstly, the validation samples contain five tea polyphenols at three concentrate levels within the calibration ranges, helped to understand, visualize and interpret these features of three second-order multivariate methods. Secondly, experimental data were studied concerning the determination of polyphenols in Chinese tea samples by HPLC-DAD. The results showed that all three second-order multivariate methods realized satisfactory quantification for five targeted analytes in Pu-Er ripe tea samples and Green tea samples even with the interference of slight retention time shifts, average recoveries were 91.23% -113.16% for ATLD, 89.96%-115.96% for ATLD-MCR, 90.64%-117.60% for MCR-ALS, respectively. However, ATLD was disappointing in the case of larger time shifts (approx. 4.00 s and 6.40 s) occurring for the quantitative analysis of Black tea and Clinacanthus nutans tea, the average recoveries were just 67.33-84.05%. Relatively, MCR-ALS and ATLD-MCR were more significantly excellent, satisfactory results still can be obtained, the average recoveries for MCR-ALS and ATLD-MCR were in the range of 86.04-117.60% and 89.96-115.96%, respectively.