Optimization of QuEChERS Extraction for Determination of Carotenoids, Polyphenols, and Sterols in Orange Juice Using Design of Experiments and Response Surface Methodology.

Several compounds with different physical properties are present in foods, biological components, and environmental samples, and there are cases in which these must be analyzed simultaneously. However, it is difficult to extract compounds with different physical properties from the same sample using a single method. In the present study, we examined the optimal conditions for the QuEChERS extraction of several kinds of compounds from orange juice using design of experiments (DoE) and response surface methodology (RSM) to determine the optimal ratio of organic solvent to sodium chloride. We determined the optimal extraction conditions, which were within the design space, using 100% tetrahydrofuran (THF) as the extraction organic solvent and NaCl:MgSO4 = 75:25 as the salt. The developed LC/MS/MS method using QuEChERS extraction achieved specific detection and precise quantification. Finally, we measured the polyphenols, sterols, and carotenoids in citrus juice using the optimized QuEChERS extraction method before LC/MS/MS analysis. Most of the analytes were quantifiable in orange juice. The optimized method achieved ease of operation, the extraction of analytes from food samples in a short time (within 30 min), minimization of analytical residues, and reliability. The DoE and RSM approach may contribute to better optimization of the extraction conditions for the lowest number of experiments.

Intelligent image-activated cell sorting 2.0.

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

On-chip cell sorting by high-speed local-flow control using dual membrane pumps.

Although researchers have proposed various methods of on-chip cell sorting, high-throughput sorting of large cells remains hampered by the difficulty of controlling high-speed flow over a wide sorting area. To overcome this problem, we proposed high-speed local-flow control using dual membrane pumps driven by piezoelectric actuators placed on the outside of a microfluidic chip in this paper. We evaluated the controllability of shifting the flow profile by the local-flow. The results indicated that we could sort large cells up to approximately 150 µm in size with an equivalent throughput of 31 kHz. Because our method can control the flow profiles, it is applicable not only to large cells but also to small cells. The cell-sorting efficacy of the proposed method was experimentally evaluated on Euglena gracilis NIES-48 (E. gracilis) cells as large target cells and GCIY-EGFP (GCIY) cells derived from a gastric cancer cell line as small target cells. In E. gracilis cells sorting, the throughput is 23 kHz with a 92.8% success rate, 95.8% purity, and 90.8% cell viability. In GCIY sorting, the throughput is 11 kHz with a 97.8% success rate, 98.9% purity, and 90.7% cell viability. These results confirm that the proposed method sorts differently sized cells with high throughput and hence, overcomes the throughput-size trade-off that exists in conventional on-chip cell sorters.

Mechanical diagnosis of human erythrocytes by ultra-high speed manipulation unraveled critical time window for global cytoskeletal remodeling.

Large deformability of erythrocytes in microvasculature is a prerequisite to realize smooth circulation. We develop a novel tool for the three-step "Catch-Load-Launch" manipulation of a human erythrocyte based on an ultra-high speed position control by a microfluidic "robotic pump". Quantification of the erythrocyte shape recovery as a function of loading time uncovered the critical time window for the transition between fast and slow recoveries. The comparison with erythrocytes under depletion of adenosine triphosphate revealed that the cytoskeletal remodeling over a whole cell occurs in 3 orders of magnitude longer timescale than the local dissociation-reassociation of a single spectrin node. Finally, we modeled septic conditions by incubating erythrocytes with endotoxin, and found that the exposure to endotoxin results in a significant delay in the characteristic transition time for cytoskeletal remodeling. The high speed manipulation of erythrocytes with a robotic pump technique allows for high throughput mechanical diagnosis of blood-related diseases.