Ultrafast laser-scanning time-stretch imaging at visible wavelengths

Compressive time-stretch spectroscopy with pulse-by-pulse intensity modulation

The photonic time-stretch technique is a single-pulse broadband spectroscopy method enabled by dispersive Fourier transformation. This technique enables an extremely high spectrum acquisition rate, determined by the repetition rates of femtosecond mode-locked lasers, which are typically in the range of tens of MHz. However, achieving this high spectrum acquisition rate necessitates a compromise in either the spectral resolution or the spectral bandwidth to prevent overlaps between adjacent stretched pulses. In this study, we introduce a method that overcomes this limitation by incorporating compressive sensing with pulse-by-pulse amplitude modulation, enabling the decomposition of excessively stretched, overlapping pulses. Through numerical evaluations of optofluidic microparticle flow analysis and high-speed gas-phase molecular spectroscopy, we demonstrate the efficacy of our noise-resilient algorithm, showcasing a severalfold increase in the spectrum acquisition rate without compromising resolution and bandwidth.

Information-Distilled Generative Label-Free Morphological Profiling Encodes Cellular Heterogeneity

Image-based cytometry faces challenges due to technical variations arising from different experimental batches and conditions, such as differences in instrument configurations or image acquisition protocols, impeding genuine biological interpretation of cell morphology. Existing solutions, often necessitating extensive pre-existing data knowledge or control samples across batches, have proved limited, especially with complex cell image data. To overcome this, "Cyto-Morphology Adversarial Distillation" (CytoMAD), a self-supervised multi-task learning strategy that distills biologically relevant cellular morphological information from batch variations, is introduced to enable integrated analysis across multiple data batches without complex data assumptions or extensive manual annotation. Unique to CytoMAD is its "morphology distillation", symbiotically paired with deep-learning image-contrast translation-offering additional interpretable insights into label-free cell morphology. The versatile efficacy of CytoMAD is demonstrated in augmenting the power of biophysical imaging cytometry. It allows integrated label-free classification of human lung cancer cell types and accurately recapitulates their progressive drug responses, even when trained without the drug concentration information. CytoMAD  also allows joint analysis of tumor biophysical cellular heterogeneity, linked to epithelial-mesenchymal plasticity, that standard fluorescence markers overlook. CytoMAD can substantiate the wide adoption of biophysical cytometry for cost-effective diagnosis and screening.

High-speed optical imaging with sCMOS pixel reassignment

Fluorescence microscopy has undergone rapid advancements, offering unprecedented visualization of biological events and shedding light on the intricate mechanisms governing living organisms. However, the exploration of rapid biological dynamics still poses a significant challenge due to the limitations of current digital camera architectures and the inherent compromise between imaging speed and other capabilities. Here, we introduce sHAPR, a high-speed acquisition technique that leverages the operating principles of sCMOS cameras to capture fast cellular and subcellular processes. sHAPR harnesses custom fiber optics to convert microscopy images into one-dimensional recordings, enabling acquisition at the maximum camera readout rate, typically between 25 and 250 kHz. We have demonstrated the utility of sHAPR with a variety of phantom and dynamic systems, including high-throughput flow cytometry, cardiomyocyte contraction, and neuronal calcium waves, using a standard epi-fluorescence microscope. sHAPR is highly adaptable and can be integrated into existing microscopy systems without requiring extensive platform modifications. This method pushes the boundaries of current fluorescence imaging capabilities, opening up new avenues for investigating high-speed biological phenomena.

Scan-less 3D microscopy based on spatiotemporal encoding on a single-cavity dual-comb laser

Dual-comb microscopy enables high-speed and high-precision optical sampling by simultaneously extracting both amplitude and phase information from the interference signals with frequency division multiplexing. In this Letter, we introduce a spatiotemporal encoding approach for dual-comb microscopy that overcomes previous limitations such as mechanical scanning, low sampling efficiency, and system complexity. By employing free-space angular-chirp-enhanced delay (FACED) and a low-noise single-cavity dual-comb laser, we achieve scan-less 3D imaging with nanometer precision and a 3D distance-imaging rate of 330 Hz, restricted only by the repetition rate difference of the dual-comb laser. Specifically, the FACED unit linearly arranges the laser beam into an array. A grating subsequently disperses this array transversely into lines, facilitating ultrafast spectroscopic applications that are 1-2 orders of magnitude quicker than traditional dual-comb methods. This spatiotemporal encoding also eases the stringent conditions on various dual-comb laser parameters, such as repetition rates, coherence, and stability. Through carefully designed experiments, we demonstrate that our scan-less system can measure 3D profiles of microfabricated structures at a rate of 7 million pixels per second. Our method significantly enhances measurement speed while maintaining high precision, using a compact light source. This advancement has the potential for broad applications, including phase imaging, surface topography, distance ranging, and spectroscopy.

Graded arc beam in light needle microscopy for axially resolved, rapid volumetric imaging without nonlinear processes

High-speed three-dimensional (3D) imaging is essential for revealing the structure and functions of biological specimens. Confocal laser scanning microscopy has been widely employed for this purpose. However, it requires a time-consuming image-stacking procedure. As a solution, we previously developed light needle microscopy using a Bessel beam with a wavefront-engineered approach [Biomed. Opt. Express13, 1702 (2022)10.1364/BOE.449329]. However, this method applies only to multiphoton excitation microscopy because of the requirement to reduce the sidelobes of the Bessel beam. Here, we introduce a beam that produces a needle spot while eluding the intractable artifacts due to the sidelobes. This beam can be adopted even in one-photon excitation fluorescence 3D imaging. The proposed method can achieve real-time, rapid 3D observation of 200-nm particles in water at a rate of over 50 volumes per second. In addition, fine structures, such as the spines of neurons in fixed mouse brain tissue, can be visualized in 3D from a single raster scan of the needle spot. The proposed method can be applied to various modalities in biological imaging, enabling rapid 3D image acquisition.

Single-shot optical imaging with spectrum circuit bridging timescales in high-speed photography

Single-shot optical imaging based on ultrashort lasers has revealed nonrepetitive processes in subnanosecond timescales beyond the recording range of conventional high-speed cameras. However, nanosecond photography without sacrificing short exposure time and image quality is still missing because of the gap in recordable timescales between ultrafast optical imaging and high-speed electronic cameras. Here, we demonstrate nanosecond photography and ultrawide time-range high-speed photography using a spectrum circuit that produces interval-tunable pulse trains while keeping short pulse durations. We capture a shock wave propagating through a biological cell with a 1.5-ns frame interval and 44-ps exposure time while suppressing image blur. Furthermore, we observe femtosecond laser processing over multiple timescales (25-ps, 2.0-ns, and 1-ms frame intervals), showing that the plasma generated at the picosecond timescale affects subsequent shock wave formation at the nanosecond timescale. Our technique contributes to accumulating data of various fast processes for analysis and to analyzing multi-timescale phenomena as a series of physical processes.

Artificial intelligence-enabled quantitative phase imaging methods for life sciences

Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dimensional label-free phase imaging techniques that exploit refractive index as an intrinsic optical imaging contrast. In particular, we discuss artificial intelligence-based analysis methodologies for biomedical studies including image enhancement, segmentation of cellular or subcellular structures, classification of types of biological samples and image translation to furnish subcellular and histochemical information from label-free phase images. We also discuss the advantages and challenges of artificial intelligence-enabled quantitative phase imaging analyses, summarize recent notable applications in the life sciences, and cover the potential of this field for basic and industrial research in the life sciences.

Is AI essential? Examining the need for deep learning in image-activated sorting of Saccharomyces cerevisiae

Artificial intelligence (AI) has become a focal point across a multitude of societal sectors, with science not being an exception. Particularly in the life sciences, imaging flow cytometry has increasingly integrated AI for automated management and categorization of extensive cell image data. However, the necessity of AI over traditional classification methods when extending imaging flow cytometry to include cell sorting remains uncertain, primarily due to the time constraints between image acquisition and sorting actuation. AI-enabled image-activated cell sorting (IACS) methods remain substantially limited, even as recent advancements in IACS have found success while largely relying on traditional feature gating strategies. Here we assess the necessity of AI for image classification in IACS by contrasting the performance of feature gating, classical machine learning (ML), and deep learning (DL) with convolutional neural networks (CNNs) in the differentiation of Saccharomyces cerevisiae mutant images. We show that classical ML could only yield a 2.8-fold enhancement in target enrichment capability, albeit at the cost of a 13.7-fold increase in processing time. Conversely, a CNN could offer an 11.0-fold improvement in enrichment capability at an 11.5-fold increase in processing time. We further executed IACS on mixed mutant populations and quantified target strain enrichment via downstream DNA sequencing to substantiate the applicability of DL for the proposed study. Our findings validate the feasibility and value of employing DL in IACS for morphology-based genetic screening of S. cerevisiae, encouraging its incorporation in future advancements of similar technologies.

High ytterbium concentration Yb/Al/P/Ce co-doped silica fiber for 1-µm ultra-short cavity fiber laser application

We demonstrate a high ytterbium concentration Yb/Al/P/Ce co-doped silica fiber by conventional modified chemical vapor deposition (MCVD) technology and solution doping process. The fiber has a Yb concentration of about 2.5 wt%, and the corresponding core absorption coefficient is measured to be ∼1400 dB/m at 976 nm. The gain coefficient was measured to be approximately 1.0 dB/cm. It is found that the Yb/Al/P/Ce co-doped silica shows a lower photodarkening-induced equilibrium loss of 52 dB/m at 633 nm than the Yb/Al/P co-doped silica fiber of 117 dB/m. Using the heavily Yb3+-doped silica fiber, a compact and robust ultrashort cavity single-frequency fiber laser was achieved with a maximum output power of 75 mW and a linewidth of 14 kHz. Furthermore, a compact passively mode-locked fiber laser (MLFL) with a repetition rate of 1.23 GHz was also proposed using our developed Yb-doped fiber. The laser properties of the proposed lasers were systematically investigated, demonstrating the superior performance of this fiber in terms of photodarkening resistance and ultrashort-cavity laser application. Furthermore, utilizing an all-fiber structure based on silica-based fiber offers the significant advantage of high stability and reliability.

Dynamic Volumetric Imaging of Mouse Cerebral Blood Vessels In Vivo with an Ultralong Anti-Diffracting Beam

Volumetric imaging of a mouse brain in vivo with one-photon and two-photon ultralong anti-diffracting (UAD) beam illumination was performed. The three-dimensional (3D) structure of blood vessels in the mouse brain were mapped to a two-dimensional (2D) image. The speed of volumetric imaging was significantly improved due to the long focal length of the UAD beam. Comparing one-photon and two-photon UAD beam volumetric imaging, we found that the imaging depth of two-photon volumetric imaging (80 μm) is better than that of one-photon volumetric imaging (60 μm), and the signal-to-background ratio (SBR) of two-photon volumetric imaging is two times that of one-photon volumetric imaging. Therefore, we used two-photon UAD volumetric imaging to perform dynamic volumetric imaging of mouse brain blood vessels in vivo, and obtained the blood flow velocity.

DIRECT, a low-cost system for high-speed, low-noise imaging of fluorescent bio-samples

A targeted imaging system has been developed for applications requiring recording from stationary samples at high spatiotemporal resolutions. It works by illuminating regions of interest in rapid sequence, and recording the signal from the whole field of view onto a single photodetector. It can be implemented at low cost on an existing microscope without compromising existing functionality. The system is characterized in terms of speed, spatial resolution, and tissue penetration depth, before being used to record individual action potentials from ASAP-3 expressing neurons in an ex vivo mouse brain slice preparation.

Single-Shot Multi-Frame Imaging of Femtosecond Laser-Induced Plasma Propagation

Single-shot ultrafast multi-frame imaging technology plays a crucial role in the observation of laser-induced plasma. However, there are many challenges in the application of laser processing, such as technology fusion and imaging stability. To provide a stable and reliable observation method, we propose an ultrafast single-shot multi-frame imaging technology based on wavelength polarization multiplexing. Through the frequency doubling and birefringence effects of the BBO and the quartz crystal, the 800 nm femtosecond laser pulse was frequency doubled to 400 nm, and a sequence of probe sub-pulses with dual-wavelength and different polarization was generated. The coaxial propagation and framing imaging of multi-frequency pulses provided stable imaging quality and clarity, as well as high temporal/spatial resolution (200 fs and 228 lp/mm). In the experiments involving femtosecond laser-induced plasma propagation, the probe sub-pulses measured their time intervals by capturing the same results. Specifically, the measured time intervals were 200 fs between the same color pulses and 1 ps between the adjacent different. Finally, based on the obtained system time resolution, we observed and revealed the evolution mechanism of femtosecond laser-induced air plasma filaments, the multifilament propagation of femtosecond laser in fused silica, and the influence mechanism of air ionization on laser-induced shock waves.

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier-Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

On monocytes and lymphocytes biolens clustering by in flow holographic microscopy

Live cells act as biological lenses and can be employed as real-world optical components in bio-hybrid systems. Imaging at nanoscale, optical tweezers, lithography and also photonic waveguiding are some of the already proven functionalities, boosted by the advantage that cells are fully biocompatible for intra-body applications. So far, various cell types have been studied for this purpose, such as red blood cells, bacterial cells, stem cells and yeast cells. White Blood Cells (WBCs) play a very important role in the regulation of the human body activities and are usually monitored for assessing its health. WBCs can be considered bio-lenses but, to the best of our knowledge, characterization of their optical properties have not been investigated yet. Here, we report for the first time an accurate study of two model classes of WBCs (i.e., monocytes and lymphocytes) by means of a digital holographic microscope coupled with a microfluidic system, assuming WBCs bio-lens characteristics. Thus, quantitative phase maps for many WBCs have been retrieved in flow-cytometry (FC) by achieving a significant statistical analysis to prove the enhancement in differentiation among sphere-like bio-lenses according to their sizes (i.e., diameter d) exploiting intensity parameters of the modulated light in proximity of the cell optical axis. We show that the measure of the low intensity area (S: I z < I th z ) in a fixed plane, is a feasible parameter for cell clustering, while achieving robustness against experimental misalignments and allowing to adjust the measurement sensitivity in post-processing. 2D scatterplots of the identified parameters (d-S) show better differentiation respect to the 1D case. The results show that the optical focusing properties of WBCs allow the clustering of the two populations by means of a mere morphological analysis, thus leading to the new concept of cell-optical-fingerprint avoiding fluorescent dyes. This perspective can open new routes in biomedical sciences, such as the chance to find optical-biomarkers at single cell level for label-free diagnosis.

Studying the efficacy of antiplatelet drugs on atherosclerosis by optofluidic imaging on a chip

Vascular stenosis caused by atherosclerosis instigates activation and aggregation of platelets, eventually resulting in thrombus formation. Although antiplatelet drugs are commonly used to inhibit platelet activation and aggregation, they unfortunately cannot prevent recurrent thrombotic events in patients with atherosclerosis. This is partially due to the limited understanding of the efficacy of antiplatelet drugs in the complex hemodynamic environment of vascular stenosis. Conventional methods for evaluating the efficacy of antiplatelet drugs under stenosis either fail to simulate the hemodynamic environment of vascular stenosis characterized by high shear stress and recirculatory flow or lack spatial resolution in their analytical techniques to statistically identify and characterize platelet aggregates. Here we propose and experimentally demonstrate a method comprising an in vitro 3D stenosis microfluidic chip and an optical time-stretch quantitative phase imaging system for studying the efficacy of antiplatelet drugs under stenosis. Our method simulates the atherogenic flow environment of vascular stenosis while enabling high-resolution and statistical analysis of platelet aggregates. Using our method, we distinguished the efficacy of three antiplatelet drugs, acetylsalicylic acid (ASA), cangrelor, and eptifibatide, for inhibiting platelet aggregation induced by stenosis. Specifically, ASA failed to inhibit stenosis-induced platelet aggregation, while eptifibatide and cangrelor showed high and moderate efficacy, respectively. Furthermore, we demonstrated that the drugs tested also differed in their efficacy for inhibiting platelet aggregation synergistically induced by stenosis and agonists (e.g., adenosine diphosphate, and collagen). Taken together, our method is an effective tool for investigating the efficacy of antiplatelet drugs under vascular stenosis, which could assist the development of optimal pharmacologic strategies for patients with atherosclerosis.

Depth random-access two-photon Bessel light-sheet imaging in brain tissue

Two-photon light-sheet fluorescence microscopy enables high-resolution imaging of neural activity in brain tissue at a high frame rate. Traditionally, light-sheet microscopy builds up a 3D stack by multiple depth scans with uniform spatial intervals, which substantially limits the volumetric imaging speed. Here, we introduce the depth random-access light-sheet microscopy, allowing rapid switching scanning depth for light-sheet imaging. With a low-cost electrically tunable lens and minimum modification of an existing two-photon light-sheet imaging instrument, we demonstrated fast random depth hopping light-sheet imaging at 100 frames per second in the live brain slice. Through depth random-access, calcium activities for an astrocyte were recorded on four user-selected detection planes at a refreshing rate of 25 Hz.

Ultrafast two-photon fluorescence imaging of cerebral blood circulation in the mouse brain in vivo

SignificanceCharacterizing blood flow by tracking individual red blood cells as they move through vessels is essential for understanding vascular function. With high spatial resolution, two-photon fluorescence microscopy is the method of choice for imaging blood flow at the cellular level. However, its application is limited to a low flow speed regimen in anesthetized animals by its slow focus scanning mechanism. Using an ultrafast scanning module, we demonstrated two-photon fluorescence imaging of blood flow at 1,000 two-dimensional frames and 1,000,000 one-dimensional line scans per second in the brains of awake mice. These ultrafast measurements enabled us to study hemodynamic and fluid mechanical regimens beyond the reach of conventional methods.

Acousto-optically driven lensless single-shot ultrafast optical imaging

Driven by many applications in a wide span of scientific fields, a myriad of advanced ultrafast imaging techniques have emerged in the last decade, featuring record-high imaging speeds above a trillion-frame-per-second with long sequence depths. Although bringing remarkable insights into various ultrafast phenomena, their application out of a laboratory environment is however limited in most cases, either by the cost, complexity of the operation or by heavy data processing. We then report a versatile single-shot imaging technique combining sequentially timed all-optical mapping photography (STAMP) with acousto-optics programmable dispersive filtering (AOPDF) and digital in-line holography (DIH). On the one hand, a high degree of simplicity is reached through the AOPDF, which enables full control over the acquisition parameters via an electrically driven phase and amplitude spectro-temporal tailoring of the imaging pulses. Here, contrary to most single-shot techniques, the frame rate, exposure time, and frame intensities can be independently adjusted in a wide range of pulse durations and chirp values without resorting to complex shaping stages, making the system remarkably agile and user-friendly. On the other hand, the use of DIH, which does not require any reference beam, allows to achieve an even higher technical simplicity by allowing its lensless operation but also for reconstructing the object on a wide depth of field, contrary to classical techniques that only provide images in a single plane. The imaging speed of the system as well as its flexibility are demonstrated by visualizing ultrashort events on both the picosecond and nanosecond timescales. The virtues and limitations as well as the potential improvements of this on-demand ultrafast imaging method are critically discussed.

Wavefront engineered light needle microscopy for axially resolved rapid volumetric imaging

Increasing the acquisition speed of three-dimensional volumetric images is important-particularly in biological imaging-to unveil the structural dynamics and functionalities of specimens in detail. In conventional laser scanning fluorescence microscopy, volumetric images are constructed from optical sectioning images sequentially acquired by changing the observation plane, limiting the acquisition speed. Here, we present a novel method to realize volumetric imaging from two-dimensional raster scanning of a light needle spot without sectioning, even in the traditional framework of laser scanning microscopy. Information from multiple axial planes is simultaneously captured using wavefront engineering for fluorescence signals, allowing us to readily survey the entire depth range while maintaining spatial resolution. This technique is applied to real-time and video-rate three-dimensional tracking of micrometer-sized particles, as well as the prompt visualization of thick fixed biological specimens, offering substantially faster volumetric imaging.

Light sheet based volume flow cytometry (VFC) for rapid volume reconstruction and parameter estimation on the go

Optical imaging is paramount for disease diagnosis and to access its progression over time. The proposed optical flow imaging (VFC/iLIFE) is a powerful technique that adds new capabilities (3D volume visualization, organelle-level resolution, and multi-organelle screening) to the existing system. Unlike state-of-the-art point-illumination-based biomedical imaging techniques, the sheet-based VFC technique is capable of single-shot sectional visualization, high throughput interrogation, real-time parameter estimation, and instant volume reconstruction with organelle-level resolution of live specimens. The specimen flow system was realized on a multichannel (Y-type) microfluidic chip that enables visualization of organelle distribution in several cells in-parallel at a relatively high flow-rate (2000 nl/min). The calibration of VFC system requires the study of point emitters (fluorescent beads) at physiologically relevant flow-rates (500-2000 nl/min) for determining flow-induced optical aberration in the system point spread function (PSF). Subsequently, the recorded raw images and volumes were computationally deconvolved with flow-variant PSF to reconstruct the cell volume. High throughput investigation of the mitochondrial network in HeLa cancer cell was carried out at sub-cellular resolution in real-time and critical parameters (mitochondria count and size distribution, morphology, entropy, and cell strain statistics) were determined on-the-go. These parameters determine the physiological state of cells, and the changes over-time, revealing the metastatic progression of diseases. Overall, the developed VFC system enables real-time monitoring of sub-cellular organelle organization at a high-throughput with high-content capacity.

Scan multiplier unit for ultrafast laser scanning beyond the inertia limit

A passive add-on greatly multiplies the sweep rate of any mechanical scanner while also enhancing throughput, enabling a single linear scanner to produce ultrafast 1D or 2D laser scans for general applications.

Deep Phenotypic Cell Classification using Capsule Neural Network

Recent developments in ultra-high-throughput microscopy have created a new generation of cell classification methodologies focused solely on image-based cell phenotypes. These image-based analyses enable morphological profiling and screening of thousands or even millions of single cells at a fraction of the cost. They have been shown to demonstrate the statistical significance required for understanding the role of cell heterogeneity in diverse biologists. However, these single-cell analysis techniques are slow and require expensive genetic/epigenetic analysis. This treatise proposes an innovative DL system based on the newly created capsule networks (CapsNet) architecture. The proposed deep CapsNet model employs "Capsules" for high-level feature abstraction relevant to the cell category. Experiments demonstrate that our proposed system can accurately classify different types of cells based on phenotypic label-free bright-field images with over 98.06% accuracy and that deep CapsNet models outperform CNN models in the prior art.

Generalized and scalable trajectory inference in single-cell omics data with VIA

Inferring cellular trajectories using a variety of omic data is a critical task in single-cell data science. However, accurate prediction of cell fates, and thereby biologically meaningful discovery, is challenged by the sheer size of single-cell data, the diversity of omic data types, and the complexity of their topologies. We present VIA, a scalable trajectory inference algorithm that overcomes these limitations by using lazy-teleporting random walks to accurately reconstruct complex cellular trajectories beyond tree-like pathways (e.g., cyclic or disconnected structures). We show that VIA robustly and efficiently unravels the fine-grained sub-trajectories in a 1.3-million-cell transcriptomic mouse atlas without losing the global connectivity at such a high cell count. We further apply VIA to discovering elusive lineages and less populous cell fates missed by other methods across a variety of data types, including single-cell proteomic, epigenomic, multi-omics datasets, and a new in-house single-cell morphological dataset.

High-speed, cortex-wide volumetric recording of neuroactivity at cellular resolution using light beads microscopy

Two-photon microscopy has enabled high-resolution imaging of neuroactivity at depth within scattering brain tissue. However, its various realizations have not overcome the tradeoffs between speed and spatiotemporal sampling that would be necessary to enable mesoscale volumetric recording of neuroactivity at cellular resolution and speed compatible with resolving calcium transients. Here, we introduce light beads microscopy (LBM), a scalable and spatiotemporally optimal acquisition approach limited only by fluorescence lifetime, where a set of axially separated and temporally distinct foci record the entire axial imaging range near-simultaneously, enabling volumetric recording at 1.41 × 10⁸ voxels per second. Using LBM, we demonstrate mesoscopic and volumetric imaging at multiple scales in the mouse cortex, including cellular-resolution recordings within ~3 × 5 × 0.5 mm volumes containing >200,000 neurons at ~5 Hz and recordings of populations of ~1 million neurons within ~5.4 × 6 × 0.5 mm volumes at ~2 Hz, as well as higher speed (9.6 Hz) subcellular-resolution volumetric recordings. LBM provides an opportunity for discovering the neurocomputations underlying cortex-wide encoding and processing of information in the mammalian brain.

High-speed laser-scanning biological microscopy using FACED

Laser scanning is used in advanced biological microscopy to deliver superior imaging contrast, resolution and sensitivity. However, it is challenging to scale up the scanning speed required for interrogating a large and heterogeneous population of biological specimens or capturing highly dynamic biological processes at high spatiotemporal resolution. Bypassing the speed limitation of traditional mechanical methods, free-space angular-chirp-enhanced delay (FACED) is an all-optical, passive and reconfigurable laser-scanning approach that has been successfully applied in different microscopy modalities at an ultrafast line-scan rate of 1-80 MHz. Optimal FACED imaging performance requires optimized experimental design and implementation to enable specific high-speed applications. In this protocol, we aim to disseminate information allowing FACED to be applied to a broader range of imaging modalities. We provide (i) a comprehensive guide and design specifications for the FACED hardware; (ii) step-by-step optical implementations of the FACED module including the key custom components; and (iii) the overall image acquisition and reconstruction pipeline. We illustrate two practical imaging configurations: multimodal FACED imaging flow cytometry (bright-field, fluorescence and second-harmonic generation) and kHz 2D two-photon fluorescence microscopy. Users with basic experience in optical microscope operation and software engineering should be able to complete the setup of the FACED imaging hardware and software in ~2-3 months.

Morphological Indicator for Directed Evolution of Euglena gracilis with a High Heavy Metal Removal Efficiency

In the past few decades, microalgae-based bioremediation methods for treating heavy metal (HM)-polluted wastewater have attracted much attention by virtue of their environment friendliness, cost efficiency, and sustainability. However, their HM removal efficiency is far from practical use. Directed evolution is expected to be effective for developing microalgae with a much higher HM removal efficiency, but there is no non-invasive or label-free indicator to identify them. Here, we present an intelligent cellular morphological indicator for identifying the HM removal efficiency of Euglena gracilis in a non-invasive and label-free manner. Specifically, we show a strong monotonic correlation (Spearman's ρ = -0.82, P = 2.1 × 10^-5) between a morphological meta-feature recognized via our machine learning algorithms and the Cu²⁺ removal efficiency of 19 E. gracilis clones. Our findings firmly suggest that the morphology of E. gracilis cells can serve as an effective HM removal efficiency indicator and hence have great potential, when combined with a high-throughput image-activated cell sorter, for directed-evolution-based development of E. gracilis with an extremely high HM removal efficiency for practical wastewater treatment worldwide.

Low-cost compressive sensing imaging based on spectrum-encoded time-stretch structure

A low-cost compressive sensing imaging (CSI) system based on spectrum-encoded time-stretch (SETS) structure involving cascaded Mach-Zehnder Interferometers (MZIs) for spectral domain random mixing (also known as the optical random pattern generator) is proposed and experimentally demonstrated. A proof-of-principle simulation and experiment is performed. A mode-locked laser with a repetition rate of 50MHz and low-cost cascaded MZIs as the key devices enable fast CSI system. Data compression ratio from 6% to 25% are obtained using proposed CSI based SETS system. The proposed design solves the big data issue in the traditional time-stretch system. It has great potential in fast dynamic phenomena with low-cost and easy-access components.

Toward deep biophysical cytometry: prospects and challenges

The biophysical properties of cells reflect their identities, underpin their homeostatic state in health, and define the pathogenesis of disease. Recent leapfrogging advances in biophysical cytometry now give access to this information, which is obscured in molecular assays, with a discriminative power that was once inconceivable. However, biophysical cytometry should go 'deeper' in terms of exploiting the information-rich cellular biophysical content, generating a molecular knowledge base of cellular biophysical properties, and standardizing the protocols for wider dissemination. Overcoming these barriers, which requires concurrent innovations in microfluidics, optical imaging, and computer vision, could unleash the enormous potential of biophysical cytometry not only for gaining a new mechanistic understanding of biological systems but also for identifying new cost-effective biomarkers of disease.

High-throughput multiparametric imaging flow cytometry: toward diffraction-limited sub-cellular detection and monitoring of sub-cellular processes

We present a sheathless, microfluidic imaging flow cytometer that incorporates stroboscopic illumination for blur-free fluorescence detection at ultra-high analytical throughput. The imaging platform is capable of multiparametric fluorescence quantification and sub-cellular localization of these structures down to 500 nm with microscopy image quality. We demonstrate the efficacy of the approach through the analysis and localization of P-bodies and stress granules in yeast and human cells using fluorescence and bright-field detection at analytical throughputs in excess of 60,000 and 400,000 cells/s, respectively. Results highlight the utility of our imaging flow cytometer in directly investigating phase-separated compartments within cellular environments and screening rare events at the sub-cellular level for a range of diagnostic applications.

High-speed volumetric two-photon fluorescence imaging of neurovascular dynamics

Understanding the structure and function of vasculature in the brain requires us to monitor distributed hemodynamics at high spatial and temporal resolution in three-dimensional (3D) volumes in vivo. Currently, a volumetric vasculature imaging method with sub-capillary spatial resolution and blood flow-resolving speed is lacking. Here, using two-photon laser scanning microscopy (TPLSM) with an axially extended Bessel focus, we capture volumetric hemodynamics in the awake mouse brain at a spatiotemporal resolution sufficient for measuring capillary size and blood flow. With Bessel TPLSM, the fluorescence signal of a vessel becomes proportional to its size, which enables convenient intensity-based analysis of vessel dilation and constriction dynamics in large volumes. We observe entrainment of vasodilation and vasoconstriction with pupil diameter and measure 3D blood flow at 99 volumes/second. Demonstrating high-throughput monitoring of hemodynamics in the awake brain, we expect Bessel TPLSM to make broad impacts on neurovasculature research.

Single-shot stereo-polarimetric compressed ultrafast photography for light-speed observation of high-dimensional optical transients with picosecond resolution

Simultaneous and efficient ultrafast recording of multiple photon tags contributes to high-dimensional optical imaging and characterization in numerous fields. Existing high-dimensional optical imaging techniques that record space and polarization cannot detect the photon's time of arrival owing to the limited speeds of the state-of-the-art electronic sensors. Here, we overcome this long-standing limitation by implementing stereo-polarimetric compressed ultrafast photography (SP-CUP) to record light-speed high-dimensional events in a single exposure. Synergizing compressed sensing and streak imaging with stereoscopy and polarimetry, SP-CUP enables video-recording of five photon tags (x, y, z: space; t: time of arrival; and ψ: angle of linear polarization) at 100 billion frames per second with a picosecond temporal resolution. We applied SP-CUP to the spatiotemporal characterization of linear polarization dynamics in early-stage plasma emission from laser-induced breakdown. This system also allowed three-dimensional ultrafast imaging of the linear polarization properties of a single ultrashort laser pulse propagating in a scattering medium.

Analysis of signal detection configurations in optical time-stretch imaging

Optical time-stretch (OTS) imaging is effective for observing ultra-fast dynamic events in real time by virtue of its capability of acquiring images with high spatial resolution at high speed. In different implementations of OTS imaging, different configurations of its signal detection, i.e. fiber-coupled and free-space detection schemes, are employed. In this research, we quantitatively analyze and compare the two detection configurations of OTS imaging in terms of sensitivity and image quality with the USAF-1951 resolution chart and diamond films, respectively, providing a valuable guidance for the system design of OTS imaging in diverse fields.

Single-shot ultrafast burst imaging using an integral field spectroscope with a microlens array

To fully utilize the functions of a center-wavelength-sweeping pulse train generated by a free-space angular-chirp-enhanced delay optical layout for a probe laser pulse in sequentially timed all-optical mapping photography (STAMP), we introduced an integral field spectroscopy (IFS) method using a microlens array (MLA) to produce hyperspectral images, referring to the technique as lens array (LA)-STAMP. Compared with the previous STAMP utilizing spectral filtering where a bandpass filter generated hyperspectral images, LA-STAMP achieved much higher optical throughput. In a prototype setup, we used a 60×60 MLA and demonstrated single-shot burst imaging of a femtosecond laser-induced ablation process on a glass surface with 300 ps frame intervals in a 1.8 ns time window. Each frame image was constructed by assembling spectrally dispersed 36×36 monochromatic segments distributed by each lenslet on 5×5 pixels of a CCD camera. The spatial resolution was ∼4.4µm, which was determined by the MLA's pitch and the magnification of the microscope lens. We limited the number of frames to seven in this prototype setup, although it can be scaled to ∼24 with a spatial resolution of ∼1µm by designing IFS with a fine pitch MLA.

AI on a chip

Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and cloud storage, the field of AI has shifted from mostly theoretical studies in the discipline of computer science to diverse real-life applications such as drug design, material discovery, speech recognition, self-driving cars, advertising, finance, medical imaging, and astronomical observation, where AI-produced outcomes have been proven to be comparable or even superior to the performance of human experts. In these applications, what is essentially important for the development of AI is the data needed for machine learning. Despite its prominent importance, the very first process of the AI development, namely data collection and data preparation, is typically the most laborious task and is often a limiting factor of constructing functional AI algorithms. Lab-on-a-chip technology, in particular microfluidics, is a powerful platform for both the construction and implementation of AI in a large-scale, cost-effective, high-throughput, automated, and multiplexed manner, thereby overcoming the above bottleneck. On this platform, high-throughput imaging is a critical tool as it can generate high-content information (e.g., size, shape, structure, composition, interaction) of objects on a large scale. High-throughput imaging can also be paired with sorting and DNA/RNA sequencing to conduct a massive survey of phenotype-genotype relations whose data is too complex to analyze with traditional computational tools, but is analyzable with the power of AI. In addition to its function as a data provider, lab-on-a-chip technology can also be employed to implement the developed AI for accurate identification, characterization, classification, and prediction of objects in mixed, heterogeneous, or unknown samples. In this review article, motivated by the excellent synergy between AI and lab-on-a-chip technology, we outline fundamental elements, recent advances, future challenges, and emerging opportunities of AI with lab-on-a-chip technology or "AI on a chip" for short.

Extension of time window into nanoseconds in single-shot ultrafast burst imaging by spectrally sweeping pulses

We achieved single-shot 2D-burst imaging with a ∼22ps temporal resolution in a nanosecond time window using sequentially timed all-optical mapping photography with a spectral filtering (SF-STAMP) scheme, where a single snapshot of spectral images measured with a linear frequency chirped laser pulse forms time-resolved snapshots. We combined a pulse-stretching scheme of a free-space angular-chirp-enhanced delay (FACED) composed of a pair of tilted mirrors and a 4f-system. With a 4f-FACED system, we generated collinearly propagating burst laser pulses with a different center wavelength and a tunable time interval and demonstrated single-shot burst imaging with a 303 ps interval in a 1.5 ns time window by an SF-STAMP with spectrally sweeping probe pulses.

Fast intelligent cell phenotyping for high-throughput optofluidic time-stretch microscopy based on the XGBoost algorithm

SIGNIFICANCE

The use of optofluidic time-stretch flow cytometry enables extreme-throughput cell imaging but suffers from the difficulties of capturing and processing a large amount of data. As significant amounts of continuous image data are generated, the images require identification with high speed.

AIM

We present an intelligent cell phenotyping framework for high-throughput optofluidic time-stretch microscopy based on the XGBoost algorithm, which is able to classify obtained cell images rapidly and accurately. The applied image recognition consists of density-based spatial clustering of applications with noise outlier detection, histograms of oriented gradients combining gray histogram fused feature, and XGBoost classification.

APPROACH

We tested the ability of this framework against other previously proposed or commonly used algorithms to phenotype two groups of cell images. We quantified their performances with measures of classification ability and computational complexity based on AUC and test runtime. The tested cell image datasets were acquired from high-throughput imaging of over 20,000 drug-treated and untreated cells with an optofluidic time-stretch microscope.

RESULTS

The framework we built beats other methods with an accuracy of over 97% and a classification frequency of 3000  cells  /  s. In addition, we determined the optimal structure of training sets according to model performances under different training set components.

CONCLUSIONS

The proposed XGBoost-based framework acts as a promising solution to processing large flow image data. This work provides a foundation for future cell sorting and clinical practice of high-throughput imaging cytometers.

The palette of techniques for cell cycle analysis

The cell division cycle is the generational period of cellular growth and propagation. Cell cycle progression needs to be highly regulated to preserve genomic fidelity while increasing cell number. In multicellular organisms, the cell cycle must also coordinate with cell fate specification during development and tissue homeostasis. Altered cell cycle dynamics play a central role also in a number of pathophysiological processes. Thus, extensive effort has been made to define the biochemical machineries that execute the cell cycle and their regulation, as well as implementing more sensitive and accurate cell cycle measurements. Here, we review the available techniques for cell cycle analysis, revisiting the assumptions behind conventional population-based measurements and discussing new tools to better address cell cycle heterogeneity in the single-cell era. We weigh the strengths, weaknesses, and trade-offs of methods designed to measure temporal aspects of the cell cycle. Finally, we discuss emerging techniques for capturing cell cycle speed at single-cell resolution in live animals.

Spatio-temporal-spectral imaging of non-repeatable dissipative soliton dynamics

Dissipative solitons (DSs) are multi-dimensionally localized waves that arise from complex dynamical balances in far-from-equilibrium nonlinear systems and widely exist in physics, chemistry and biology. Real-time observations of DS dynamics across many dimensions thus have a broad impact on unveiling various nonlinear complexities in different fields. However, these observations are challenging as DS transitions are stochastic, non-repeatable and often strongly coupled across spatio-temporal-spectral (STS) domains. Here we report multi-dimensional (space xy + discrete time t + wavelength λ) DS dynamics imaged by STS compressed ultrafast photography, enabling imaging at up to trillions of frames per second. Various transient and random phenomena of multimode DSs are revealed, highlighting the importance of real-time multi-dimensional observation without the need for event repetition in decomposing the complexities of DSs.

Due to three-dimensional, stochastic and non-repeatable transitions of dissipative solitons, it is challenging to monitor their full dynamics. Here, the authors resolve the dynamics by wavelength and along two spatial dimensions with up to trillions of frames per second using compressed ultrafast photography.

>100 W GHz femtosecond burst mode all-fiber laser system at 1.0 µm

In this work, we report a >100 W femtosecond (fs) burst mode all-fiber laser system at 1.0 µm that operates at an intra-burst repetition rate of up to 1.2 GHz. This fiber laser system provides the highest output power that has been reported so far for GHz fs fiber lasers, to the best of our knowledge. In addition to the superior output power, this fiber laser system also shows a promising overall figure of merit, specifically in terms of pulse width (473 fs), long-term reliability (<0.67% power fluctuation) and system compactness (all-fiber configuration). We anticipate that this all-fiber laser system can be a promising ultrafast laser source for these applications requiring fs pulses with both high average power and high repetition rate, such as micromachining, bioimaging and frequency metrology.

Parallel array with axially coded light-sheet microscope

A parallel array of frequency modulated light sheets results in a scanning-less light sheet microscope capable of fast volumetric imaging.

Temporally interleaved optical time-stretch imaging

Optical time-stretch imaging has shown potential in diverse fields for its capability of acquiring images at high speed and high resolution. However, its wide application is hindered by the stringent requirement on the instrumentation hardware caused by the high-speed serial data stream. Here we demonstrate temporally interleaved optical time-stretch imaging that lowers the requirement without sacrificing the frame rate or spatial resolution by interleaving the high-speed data stream into multiple channels in the time domain. Its performance is validated with both a United States Air Force (USAF)-1951 resolution chart and a single-crystal diamond film. We achieve a 101 Mfps 1D scanning rate and 3 µm spatial resolution with only a 2.5 GS/s sampling rate by using a two-channel-interleaved system.

Kilohertz two-photon fluorescence microscopy imaging of neural activity in vivo

Understanding information processing in the brain requires us to monitor neural activity at high spatiotemporal resolution. Using an ultrafast two-photon fluorescence microscope (2PFM) empowered by all-optical laser scanning, we imaged neural activity in vivo at up to 3,000 frames per second and submicron spatial resolution. This ultrafast imaging method enabled monitoring of both supra- and sub-threshold electrical activity down to 345 μm below the brain surface in head-fixed awake mice.

Single-shot imaging of microscopic dynamic scenes at 5 THz frame rates by time and spatial frequency multiplexing

Femtosecond-scale ultrafast imaging is an essential tool for visualizing ultrafast dynamics in many scientific fields. We present a single-shot ultrafast microscopy that can capture more than a dozen frames at a time with the frame rate of 5 THz. We combine a spatial light modulator and a custom-made echelon for efficiently generating a large number of reference pulses with designed time delays and propagation angles. The single-shot recording of the interference image between these reference pulses with a sample pulse allows us to retrieve the stroboscopic images of the dynamic scene at the timing of the reference pulses. We demonstrated the recording of 14 temporal snapshots at a time, which is the largest to date, with the optimal temporal resolution set by the laser output pulse. This will have profound impacts on uncovering the interesting spatio-temporal dynamics yet to be explored.

Parallelized volumetric fluorescence microscopy with a reconfigurable coded incoherent light-sheet array

Parallelized fluorescence imaging has been a long-standing pursuit that can address the unmet need for a comprehensive three-dimensional (3D) visualization of dynamical biological processes with minimal photodamage. However, the available approaches are limited to incomplete parallelization in only two dimensions or sparse sampling in three dimensions. We hereby develop a novel fluorescence imaging approach, called coded light-sheet array microscopy (CLAM), which allows complete parallelized 3D imaging without mechanical scanning. Harnessing the concept of an "infinity mirror", CLAM generates a light-sheet array with controllable sheet density and degree of coherence. Thus, CLAM circumvents the common complications of multiple coherent light-sheet generation in terms of dedicated wavefront engineering and mechanical dithering/scanning. Moreover, the encoding of multiplexed optical sections in CLAM allows the synchronous capture of all sectioned images within the imaged volume. We demonstrate the utility of CLAM in different imaging scenarios, including a light-scattering medium, an optically cleared tissue, and microparticles in fluidic flow. CLAM can maximize the signal-to-noise ratio and the spatial duty cycle, and also provides a further reduction in photobleaching compared to the major scanning-based 3D imaging systems. The flexible implementation of CLAM regarding both hardware and software ensures compatibility with any light-sheet imaging modality and could thus be instrumental in a multitude of areas in biological research.

Photonic Time-Stretch Technology with Prismatic Pulse Dispersion towards Fast Real-Time Measurements

Photonic time-stretch (PTS) technology enables revolutionary technical breakthroughs in ultrafast electronic and optical systems. By means of employing large chromatic dispersion to map the spectrum of an ultrashort optical pulse into a stretched time-domain waveform (namely, using the dispersive Fourier transformation), PTS overcomes the fundamental speed limitations of conventional techniques. The chromatic dispersion utilized in PTS can be implemented using multiple optical prism arrays, which have the particular advantages of low loss in the extended spectrum outside of the specific telecommunication band, flexibility, and cost-effectiveness. In this article, we propose and demonstrate the PTS technology established for a pair of prisms, which works as a data acquisition approach in ultrafast digitizing, imaging, and measurement regimes.

Real-time spectral analysis of ultrafast pulses using a free-space angular chirp-enhanced delay

Frequency-to-time mapping is a powerful technique for observing ultrafast phenomena and nonrepetitive events in optics. However, many optical sources operate in wavelength regions, or at power levels, that are not compatible with standard frequency-to-time mapping implementations. The recently developed free-space angular chirp-enhanced delay (FACED) removes many of these limitations and offers a linear frequency-to-time mapping in any wavelength region where high-reflectivity mirrors and diffractive optics are available. In this work, we present a detailed formulation of the optical transfer function of a FACED device. Experimentally, we verify the properties of this transfer function and then present simple guidelines to guarantee the correct operation of a FACED frequency-to-time measurement. We also experimentally demonstrate the real-time spectral analysis of femtosecond and picosecond pulses using this system.

A practical guide to intelligent image-activated cell sorting

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software-hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.