Intelligent Image-Activated Cell Sorting.

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.

High-speed single-pixel imaging by frequency-time-division multiplexing.

We propose and experimentally demonstrate high-speed single-pixel imaging by integrating frequency-division multiplexing and time-division multiplexing (techniques used widely in telecommunications) and applying the combined technique, namely, frequency-time-division multiplexing (FTDM), to optical imaging. Specifically, FTDM single-pixel imaging uses an array of broadband, spatially distributed, dual-frequency combs (i.e., spatial dual combs) for multidimensional illumination and detects an image-encoded time-domain signal with a single-pixel photodetector in a FTDM manner. As a proof-of-principle demonstration, we use the method to show ultrafast two-color (bright-field and fluorescence) single-pixel microscopy of breast cancer cells at a high frame rate of 32,000 fps and ultrafast image velocimetry of fluorescent particles flowing at a high speed of ${ \gt }{2}\;{\rm m/s}$>2m/s.

Simple, stable, compact implementation of frequency-division-multiplexed microscopy by inline interferometry.

Frequency-division-multiplexed (FDM) imaging is a powerful method for high-speed imaging that surpasses the speed limit of conventional imaging constrained by the frame rate of image sensors. However, its complexity, instability, and bulkiness deriving from the implementation with a Mach-Zehnder interferometer hamper its practical applications. Here we demonstrate a simple, stable, and compact implementation of FDM imaging by inline interferometry that makes the method readily available to practical situations. As a proof-of-concept demonstration, we demonstrate 2D bright-field and fluorescence image acquisition of fluorescent beads, microalgal cells, and breast cancer cells within 65.5 µs, corresponding to 15,300 frames per second.

Compact and fully collinear light source for broadband multiplex CARS microscopy covering the fingerprint region.

Compact and fully collinear light source for multiplex coherent anti-Stokes Raman scattering (CARS) microscopy was proposed and demonstrated. It consists of only a microchip laser, a short photonic crystal fiber, and a longpass filter. It offers performance of sensitivity, bandwidth, and spectral resolution suitable for biomedical applications, especially covering the entire fingerprint region (500-1800 cm(-1)). It can be readily implemented by a commercially available microchip laser and a photonic crystal fiber. It has great potential to expand the utility of CARS microscopy to a wide variety of fields such as endoscopy.

Compact light source for ultrabroadband coherent anti-Stoke Raman scattering (CARS) microscopy.

A compact light source module for ultrabroadband coherent anti-Stoke Raman scattering (CARS) microscopy was developed. It mainly consists of a nanosecond microchip laser, a photonic crystal fiber for Stokes light generation, and a single mode polarization maintaining fiber for pump light propagation. It is alignment-free and relatively low-cost compared with previous light sources of CARS microscopy. By using an assembled module, we successfully observed an ultrabroadband CARS spectrum and a CARS image of a murine adipocyte. The module is expected to greatly spread the CARS microscopy to various fields by its extreme easiness to handle.

Quantitative index of arbitrary molar concentration for coherent anti-Stoke Raman scattering (CARS) spectroscopy and microscopy.

We propose a simple quantitative index for coherent anti-Stoke Raman scattering (CARS) spectroscopy and microscopy. Unlike previous similar indices, it can be applied to samples with arbitrary molar concentration, and it is robust against environmental change. Concentrations of aqueous hydrogen peroxide solution and lipid concentration distribution in a live murine adipocyte were successfully quantified by the new index. The index can be obtained in a broad range of CARS setups and it is readily applicable to quantitative CARS microscopy for deep inspection of samples such as biological specimens.

Large-volume focus control at 10 MHz refresh rate via fast line-scanning amplitude-encoded scattering-assisted holography.

The capability of focus control has been central to optical technologies that require both high temporal and spatial resolutions. However, existing varifocal lens schemes are commonly limited to the response time on the microsecond timescale and share the fundamental trade-off between the response time and the tuning power. Here, we propose an ultrafast holographic focusing method enabled by translating the speed of a fast 1D beam scanner into the speed of the complex wavefront modulation of a relatively slow 2D spatial light modulator. Using a pair of a digital micromirror device and a resonant scanner, we demonstrate an unprecedented refresh rate of focus control of 31 MHz, which is more than 1,000 times faster than the switching rate of a digital micromirror device. We also show that multiple micrometer-sized focal spots can be independently addressed in a range of over 1 MHz within a large volume of 5 mm × 5 mm × 5.5 mm, validating the superior spatiotemporal characteristics of the proposed technique - high temporal and spatial precision, high tuning power, and random accessibility in a three-dimensional space. The demonstrated scheme offers a new route towards three-dimensional light manipulation in the 100 MHz regime.

High-throughput fluorescence lifetime imaging flow cytometry.

Flow cytometry is a vital tool in biomedical research and laboratory medicine. However, its accuracy is often compromised by undesired fluctuations in fluorescence intensity. While fluorescence lifetime imaging microscopy (FLIM) bypasses this challenge as fluorescence lifetime remains unaffected by such fluctuations, the full integration of FLIM into flow cytometry has yet to be demonstrated due to speed limitations. Here we overcome the speed limitations in FLIM, thereby enabling high-throughput FLIM flow cytometry at a high rate of over 10,000 cells per second. This is made possible by using dual intensity-modulated continuous-wave beam arrays with complementary modulation frequency pairs for fluorophore excitation and acquiring fluorescence lifetime images of rapidly flowing cells. Moreover, our FLIM system distinguishes subpopulations in male rat glioma and captures dynamic changes in the cell nucleus induced by an anti-cancer drug. FLIM flow cytometry significantly enhances cellular analysis capabilities, providing detailed insights into cellular functions, interactions, and environments.

Virtual-freezing fluorescence imaging flow cytometry with 5-aminolevulinic acid stimulation and antibody labeling for detecting all forms of circulating tumor cells.

Circulating tumor cells (CTCs) are precursors to cancer metastasis. In blood circulation, they take various forms such as single CTCs, CTC clusters, and CTC-leukocyte clusters, all of which have unique characteristics in terms of physiological function and have been a subject of extensive research in the last several years. Unfortunately, conventional methods are limited in accurately analysing the highly heterogeneous nature of CTCs. Here we present an effective strategy for simultaneously analysing all forms of CTCs in blood by virtual-freezing fluorescence imaging (VIFFI) flow cytometry with 5-aminolevulinic acid (5-ALA) stimulation and antibody labeling. VIFFI is an optomechanical imaging method that virtually freezes the motion of fast-flowing cells on an image sensor to enable high-throughput yet sensitive imaging of every single event. 5-ALA stimulates cancer cells to induce the accumulation of protoporphyrin (PpIX), a red fluorescent substance, making it possible to detect all cancer cells even if they show no expression of the epithelial cell adhesion molecule, a typical CTC biomarker. Although PpIX signals are generally weak, VIFFI flow cytometry can detect them by virtue of its high sensitivity. As a proof-of-principle demonstration of the strategy, we applied cancer cells spiked in blood to the strategy to demonstrate image-based detection and accurate classification of single cancer cells, clusters of cancer cells, and clusters of a cancer cell(s) and a leukocyte(s). To show the clinical utility of our method, we used it to evaluate blood samples of four breast cancer patients and four healthy donors and identified EpCAM-positive PpIX-positive cells in one of the patient samples. Our work paves the way toward the determination of cancer prognosis, the guidance and monitoring of treatment, and the design of antitumor strategies for cancer patients.

Deep imaging flow cytometry.

Imaging flow cytometry (IFC) has become a powerful tool for diverse biomedical applications by virtue of its ability to image single cells in a high-throughput manner. However, there remains a challenge posed by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present deep-learning-enhanced imaging flow cytometry (dIFC) that circumvents this trade-off by implementing an image restoration algorithm on a virtual-freezing fluorescence imaging (VIFFI) flow cytometry platform, enabling higher throughput without sacrificing sensitivity and spatial resolution. A key component of dIFC is a high-resolution (HR) image generator that synthesizes "virtual" HR images from the corresponding low-resolution (LR) images acquired with a low-magnification lens (10×/0.4-NA). For IFC, a low-magnification lens is favorable because of reduced image blur of cells flowing at a higher speed, which allows higher throughput. We trained and developed the HR image generator with an architecture containing two generative adversarial networks (GANs). Furthermore, we developed dIFC as a method by combining the trained generator and IFC. We characterized dIFC using Chlamydomonas reinhardtii cell images, fluorescence in situ hybridization (FISH) images of Jurkat cells, and Saccharomyces cerevisiae (budding yeast) cell images, showing high similarities of dIFC images to images obtained with a high-magnification lens (40×/0.95-NA), at a high flow speed of 2 m s-1. We lastly employed dIFC to show enhancements in the accuracy of FISH-spot counting and neck-width measurement of budding yeast cells. These results pave the way for statistical analysis of cells with high-dimensional spatial information.