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The recent advances in super-resolution fluorescence microscopy, including single-molecule localization microscopy (SMLM), has enabled the study of previously inaccessible details, such as the organization of proteins within cellular compartments and even nanostructures in nonbiological nanomaterials, such as the polymers and semiconductors. With such developments, the need for the development of various computational nanostructure analysis methods for SMLM images is also increasing; however, this has been limited to protein cluster analysis. In this study, we developed an edge structure analysis method for pointillistic SMLM images based on the line edge roughness and power spectral density analyses. By investigating the effect of point properties in SMLM images, such as the size, density, and localization precision on the roughness measurement, we successfully demonstrated this analysis method for experimental SMLM images of actual samples, including the semiconductor line patterns, cytoskeletal elements, and cell membranes. This systematic investigation of the effect of each localization rendering parameter on edge roughness measurement provides a range for the optimal rendering parameters that preserve the relevant nanoscale structure of interest. These new methods are expected to expand our understanding of the targets by providing valuable insights into edge nanoscale structures that have not been previously obtained quantitatively.

We present an innovative ellipsometry technique called self-interferometric pupil ellipsometry (SIPE), which integrates self-interference and pupil microscopy techniques to provide the high metrology sensitivity required for metrology applications of advanced semiconductor devices. Due to its unique configuration, rich angle-resolved ellipsometric information from a single-shot hologram can be extracted, where the full spectral information corresponding to incident angles from 0° to 70° with azimuthal angles from 0° to 360° is obtained, simultaneously. The performance and capability of the SIPE system were fully validated for various samples including thin-film layers, complicated 3D structures, and on-cell overlay samples on the actual semiconductor wafers. The results show that the proposed SIPE system can achieve metrology sensitivity up to 0.123 nm. In addition, it provides small spot metrology capability by minimizing the illumination spot diameter up to 1 µm, while the typical spot diameter of the industry standard ellipsometry is around 30 µm. As a result of collecting a huge amount of angular spectral data, undesirable multiple parameter correlation can be significantly reduced, making SIPE ideally suited for solving several critical metrology challenges we are currently facing.

Measuring alterations in bacteria upon antibiotic application is important for basic studies in microbiology, drug discovery, clinical diagnosis, and disease treatment. However, imaging and 3D time-lapse response analysis of individual bacteria upon antibiotic application remain largely unexplored mainly due to limitations in imaging techniques. Here, we present a method to systematically investigate the alterations in individual bacteria in 3D and quantitatively analyze the effects of antibiotics. Using optical diffraction tomography, in-situ responses of Escherichia coli and Bacillus subtilis to various concentrations of ampicillin were investigated in a label-free and quantitative manner. The presented method reconstructs the dynamic changes in the 3D refractive-index distributions of living bacteria in response to antibiotics at sub-micrometer spatial resolution., Competing Interests: Prof. Park and Mr. Moosung Lee have financial interests in Tomocube Inc., a company that commercializes optical diffraction tomography and quantitative phase imaging instruments and is one of the sponsors of the work., (© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement.)

Quantitative phase imaging (QPI) has emerged as one of the powerful imaging tools for the study of live cells in a non-invasive manner. In particular, multimodal approaches combining QPI and fluorescence microscopic techniques have been recently developed for superior spatiotemporal resolution as well as high molecular specificity. In this review, we briefly summarize recent advances in three-dimensional QPI combined with fluorescence techniques for the correlative study of cell pathophysiology. Through this review, biologists and clinicians can be provided with insights on this rapidly growing field of research and may find broader applications to investigate unrevealed nature in cell physiology and related diseases.

Microalgae are promising candidates for biofuel production due to their high lipid content. To facilitate utilization of the microalgae for biofuel, rapid quantification of the lipid contents in microalgae is necessary. However, conventional methods based on the chemical extraction of lipids require a time-consuming destructive extraction process. Here, we demonstrate label-free, non-invasive, rapid quantification of the lipid contents in individual micro-algal cells measuring the three-dimensional refractive index tomograms. We measure three-dimensional refractive index distributions within Nannochloropsis oculata cells and find that lipid droplets are identifiable in tomograms by their high refractive index. In addition, we alter N. oculata under nitrogen deficiency by measuring the volume, lipid weight, and dry cell weight of individual cells. Characterization of individual cells allows correlative analysis between the lipid content and size of individual cells.

We present a method to measure the vector-field light scattering of individual microscopic objects. The polarization-dependent optical field images are measured with quantitative phase imaging at the sample plane, and then numerically propagated to the far-field plane. This approach allows the two-dimensional polarization-dependent angle-resolved light scattered patterns from individual object to be obtained with high precision and sensitivity. Using this method, we present the measurements of the polarization-dependent light scattering of a liquid crystal droplet and individual silver nanowires over scattering angles of 50°. In addition, the spectroscopic extension of the polarization-dependent angle-resolved light scattering is demonstrated using wavelength-scanning illumination.

A novel optical holographic technique is presented to simultaneously measure both the real and imaginary components of the complex refractive index (CRI) of a protein solution over a wide visible wavelength range. Quantitative phase imaging was employed to precisely measure the optical field transmitted from a protein solution, from which the CRIs of the protein solution were retrieved using the Fourier light scattering technique. Using this method, we characterized the CRIs of the two dominant structural states of a photoactive yellow protein solution over a broad wavelength range (461-582 nm). The significant CRI deviation between the two structural states was quantified and analysed. The results of both states show the similar overall shape of the expected rRI obtained from the Kramers-Kronig relations.

Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells. After training, the network outperforms previous techniques in all accuracy measures, achieving single-spore sensitivity and subgenus specificity. The unique "representation learning" capability of deep learning enables direct training from raw images instead of manually extracted features. The method automatically recognizes key biological traits encoded in the images and exploits them as fingerprints. This remarkable learning ability makes the proposed method readily applicable to classifying various single cells in addition to B. anthracis , as demonstrated for the diagnosis of Listeria monocytogenes , without any modification. We believe that our strategy will make holographic microscopy more accessible to medical doctors and biomedical scientists for easy, rapid, and accurate point-of-care diagnosis of pathogens.

Here, we present a novel microscopic technique for measuring wavelength-dependent three-dimensional (3-D) distributions of the refractive indices (RIs) of microscopic samples in the visible wavelengths. Employing 3-D quantitative phase microscopy techniques with a wavelength-swept source, 3-D RI tomograms were obtained in the range of 450 - 700 nm with a spectral resolution of a few nanometers. The capability of the technique was demonstrated by measuring the hyperspectral 3-D RI tomograms of polystyrene beads, human red blood cells, and hepatocytes. The results demonstrate the potential for label-free molecular specific 3-D tomography of biological samples.

Rapid identification of bacterial species is crucial in medicine and food hygiene. In order to achieve rapid and label-free identification of bacterial species at the single bacterium level, we propose and experimentally demonstrate an optical method based on Fourier transform light scattering (FTLS) measurements and statistical classification. For individual rod-shaped bacteria belonging to four bacterial species (Listeria monocytogenes, Escherichia coli, Lactobacillus casei, and Bacillus subtilis), two-dimensional angle-resolved light scattering maps are precisely measured using FTLS technique. The scattering maps are then systematically analyzed, employing statistical classification in order to extract the unique fingerprint patterns for each species, so that a new unidentified bacterium can be identified by a single light scattering measurement. The single-bacterial and label-free nature of our method suggests wide applicability for rapid point-of-care bacterial diagnosis.

Spectral changes in individual micrometer-sized scatters are experimentally measured. Using an interferometric microscope equipped with a wavelength-swept illumination, the optical fields diffracted from the individual scatters are measured precisely, from which 2D light scattering spectra were retrieved as functions of the wavelength and scattering angle. In the measured scattering spectra of individual scatters, spectral shifts were clearly observed, which is also directly explained using the Mie scattering theory.

The identification and quantification of specific molecules are crucial for studying the pathophysiology of cells, tissues, and organs as well as diagnosis and treatment of diseases. Recent advances in holographic microspectroscopy, based on quantitative phase imaging or optical coherence tomography techniques, show promise for label-free noninvasive optical detection and quantification of specific molecules in living cells and tissues (e.g., hemoglobin protein). To provide important insight into the potential employment of holographic spectroscopy techniques in biological research and for related practical applications, we review the principles of holographic microspectroscopy techniques and highlight recent studies.

Two-dimensional angle-resolved light scattering maps of individual rod-shaped bacteria are measured at the single-cell level. Using quantitative phase imaging and Fourier transform light scattering techniques, the light scattering patterns of individual bacteria in four rod-shaped species (Bacillus subtilis, Lactobacillus casei, Synechococcus elongatus, and Escherichia coli) are measured with unprecedented sensitivity in a broad angular range from -70° to 70°. The measured light scattering patterns are analyzed along the two principal axes of rod-shaped bacteria in order to systematically investigate the species-specific characteristics of anisotropic light scattering. In addition, the cellular dry mass of individual bacteria is calculated and used to demonstrate that the cell-to-cell variations in light scattering within bacterial species is related to the cellular dry mass and growth.

Intraluminal crawling is considered to be important for extravasation of leukocytes in blood vessels, but biochemical/biophysical cues guiding the crawling of leukocytes have not been clearly understood. Here we provide evidence that T cells sense the topography of luminal surfaces and the nuclei of endothelial cells (ECs) using lamellipodia and filopodia, respectively, to optimize path finding during intraluminal crawling. Well-aligned EC layers or replicas of EC layers, which exhibit topography similar to that of EC layers, were fabricated, and flow was applied either parallel or perpendicular to the orientation of EC alignment. T cells crawled along the valleys of the topographical landscapes of the EC layers, while avoiding nuclei of ECs regardless of flow direction. Pharmacological inhibitor treatments revealed that sensing of topography and nuclei of EC layers was mediated by lamellipodia and filopodia, respectively. Lamellipodia or filopodia-inhibited T cells crawled significantly longer distances for extravasation than did normal T cells, indicating that sensing biophysical cues are critical for optimizing routes for extravasation.

The spectro-angular light scattering measurements of individual microscopic objects are presented. Using spectroscopic quantitative phase microscopy and Fourier transform light scattering, the 2D angle-resolved light scattering intensity and phase patterns are measured in a spectral range of 450-750 nm and an angular range of -70-70°. The spectro-angular light scattering measurements of individual polystyrene beads are demonstrated with high sensitivity and precision.

A cellular-level study of the pathophysiology is crucial for understanding the mechanisms behind human diseases. Recent advances in quantitative phase imaging (QPI) techniques show promises for the cellular-level understanding of the pathophysiology of diseases. To provide important insight on how the QPI techniques potentially improve the study of cell pathophysiology, here we present the principles of QPI and highlight some of the recent applications of QPI ranging from cell homeostasis to infectious diseases and cancer.