Dynamic holographic profiling of thick samples is limited due to the reduced field of view (FOV) of off-axis holography. We present an improved six-pack holography system for the simultaneous acquisition of six complex wavefronts in a single camera exposure from two fields of view (FOVs) and three wavelengths, for quantitative phase unwrapping of thick and extended transparent objects. By dynamically generating three synthetic wavelength quantitative phase maps for each of the two FOVs, with the longest wavelength being 6207 nm, hierarchical phase unwrapping can be used to reduce noise while maintaining the improvements in the 2 π phase ambiguity due to the longer synthetic wavelength. The system was tested on a 7 μm tall PDMS microchannel and is shown to produce quantitative phase maps with 96% accuracy, while the hierarchical unwrapping reduces noise by 93%. A monolayer of live onion epidermal tissue was also successfully scanned, demonstrating the potential of the system to dynamically decrease scanning time of optically thick and extended samples.
Crystalline riboflavin (vitamin B-2) performs an important biological role as an optically functional material in the tapetum lucidum of certain animals, notably lemurs and cats. The tapetum lucidum is a reflecting layer behind the retina, which serves to enhance photon capture and vision in low-light settings. Motivated by the aim of rationalizing its biological role, and given that the structure of biogenic solid-state riboflavin remains unknown, we have used a range of experimental and computational techniques to determine the solid-state structure of synthetic riboflavin. Our multitechnique approach included microcrystal XRD, powder XRD, three-dimensional electron diffraction (3D-ED), high-resolution solid-state C-13 NMR spectroscopy, and dispersion-augmented density functional theory (DFT-D) calculations. Although an independent report of the crystal structure of riboflavin was published recently, our structural investigations reported herein provide a different interpretation of the intermolecular hydrogen-bonding arrangement in this material, supported by all the experimental and computational approaches utilized in our study. We also discuss, more generally, potential pitfalls that may arise in applying DFT-D geometry optimization as a bridging step between structure solution and Rietveld refinement in the structure determination of hydrogen-bonded materials from powder XRD data. Finally, we report experimental and computational values for the refractive index of riboflavin, with implications for its optical function.
We developed a new method to enhance the resolution of blood platelet aggregates imaged via quantitative phase imaging (QPI) using a Pix2Pix generative adversarial network (GAN). First, 1 mu m polystyrene beads were imaged with low- and high-resolution QPI, to train the GAN model and validate its applicability. Testing on the polystyrene beads demonstrated a mean error of 4.14% in the generated high-resolution optical-path-delay values compared to the optically acquired ones. Next, blood platelets were collected with low- and high-resolution QPI, and a deep neural network was trained to predict the high-resolution platelet optical-path-delay profiles using the low-resolution profiles, achieving a mean error of 7.01% in the generated high-resolution optical-path-delay values compared to the optically acquired ones. These results highlight the potential of the method in enhancing QPI resolution of cell aggregates without the need for sophisticated optical equipment and optical system modifications for high-resolution microscopy, allowing for better understanding of platelet-related disorders and conditions such as thrombocytopenia and thrombocytosis. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
Carbon quantum dots (CQDs) are one of the most promising types of fluorescent nanomaterials due to their exceptional water solubility, excellent optical properties, biocompatibility, chemical inertness, excellent refractive index, and photostability. Nitrogen-containing CQDs, which include amino acid based CQDs, are especially attractive due to their high quantum yield, thermal stability, and potential biomedical applications. Recent studies have attempted to improve the preparation of amino acid based CQDs. However, the highest quantum yield obtained for these dots was only 44%. Furthermore, the refractive indices of amino acid derived CQDs were not determined. Here, we systematically explored the performance of CQDs prepared from all 20 coded amino acids using modified hydrothermal techniques allowing more passivation layers on the surface of the dots to optimize their performance. Intriguingly, we obtained the highest refractive indices ever reported for any CQDs. The values differed among the amino acids, with the highest refractive indices found for positively charged amino acids including arginine-CQDs (∼2.1), histidine-CQDs (∼2.0), and lysine-CQDs (∼1.8). Furthermore, the arginine-CQDs reported here showed a nearly 2-fold increase in the quantum yield (∼86%) and a longer decay time (∼8.0 ns) compared to previous reports. In addition, we also demonstrated that all amino acid based CQD materials displayed excitation-dependent emission profiles (from UV to visible) and were photostable, water-soluble, noncytotoxic, and excellent for high contrast live cell imaging or bioimaging. These results indicate that amino acid based CQD materials are high-refractive-index materials applicable for optoelectronic devices, bioimaging, biosensing, and studying cellular organelles in vivo. This extraordinary RI may be highly useful for exploring cellular elements with different densities.
Myelodysplastic syndromes (MDSs) are a group of potentially deadly diseases that affect the morphology and function of neutrophils. Rapid diagnosis of MDS is crucial for the initiation of treatment that can vastly improve disease outcome. In this work, we present a new approach for detecting morphological differences between neutrophils isolated from blood samples of high-risk MDS patients and blood bank donors (BBDs). Using fluorescent flow cytometry, neutrophils were stained with 2′,7′-dichlorofluorescin diacetate (DCF), which reacts with reactive oxygen species (ROS), and Hoechst, which binds to DNA. We observed that BBDs possessed two cell clusters (designated H and L), whereas MDS patients possessed a single cluster (L). Later, we used FACS to sort the H and the L cells and used interferometric phase microscopy (IPM) to image the cells without utilizing cell staining. IPM images showed that H cells are characterized by low optical path delay (OPD) in the nucleus relative to the cytoplasm, especially in cell vesicles containing ROS, whereas L cells are characterized by low OPD in the cytoplasm relative to the nucleus and no ROS-containing vesicles. Moreover, L cells present a higher average OPD and dry mass compared to H cells. When examining neutrophils from MDS patients and BBDs by IPM during flow, we identified ~20% of cells as H cells in BBDs in contrast to ~4% in MDS patients. These results indicate that IPM can be utilized for the diagnosis of complex hematological pathologies such as MDS.
We present a multidisciplinary approach for predicting how sperm cells with various morphologies swim in three-dimensions (3D), from milliseconds to much longer time scales at spatial resolutions of less than half a micron. We created the sperm 3D geometry and built a numerical mechanical model using the experimentally acquired dynamic 3D refractive-index profiles of sperm cells swimming in vitro as imaged by high-resolution optical diffraction tomography. By controlling parameters in the model, such as the size and shape of the sperm head and tail, we can then predict how different sperm cells, normal or abnormal, would swim in 3D, in the short or long term. We quantified various 3D structural factor effects on the sperm long-term motility. We found that some abnormal sperm cells swim faster than normal sperm cells, in contrast to the commonly used sperm selection assumption during in vitro fertilization (IVF), according to which sperm cells should mainly be chosen based on their progressive motion. We thus establish a new tool for sperm analysis and male-infertility diagnosis, as well as sperm selection criteria for fertility treatments.
Three-dimensional (3D) optical imaging of rapidly moving biological cells is difficult to achieve as such samples cannot be scanned over time. Here, we present a dynamic scan-free optical tomography approach for stain-free 3D imaging of biological cells using our new double six-pack tomography technique, whereby 12 off-axis holograms are captured in a single camera exposure without sacrificing resolution or field of view. The proposed system illuminates the sample from 12 angles simultaneously, and 3D refractive index (RI) tomograms are reconstructed from each recorded video frame of the dynamic sample. The technique is verified experimentally by recording flowing silica beads, 3 μm in diameter, with the resulting tomogram RI accuracy being 98.5%. A live swimming sperm cell is also imaged, and dynamic 3D imaging results for both beads and sperm cell are presented. The proposed technique represents a 12-fold increase in dynamic holographic data for tomography.
We present a new six-pack holography (6PH) system for simultaneous acquisition of six off-axis holograms in a single exposure from two fields of view and three wavelengths. The system is based on an external 6PH module, placed at the output of an inverted microscope, presenting a significantly more elegant solution compared to previous 6PH systems, which were based on cumbersome Mach–Zehnder interferometers built around the sample. This is also the first time in which six-pack holography is utilized for multi-wavelength imaging. We demonstrate using the new system to acquire volumetric data of flowing erythrocytes with twice the field of view of previous multi-wavelength holographic techniques. This volumetric data includes mean corpuscular volume, mean corpuscular hemoglobin (Hb) concentration, mean corpuscular Hb, and sphericity.
In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there is no method today to measure the DNA fragmentation of live and unstained cells during ICSI. We present a new method to predict the DNA fragmentation of sperm cells using multi-layer stain-free imaging data, including quantitative phase imaging, and lightweight deep learning architectures. The DNA fragmentation ground truth is achieved by staining the cells with acridine orange and imaging them via fluorescence microscopy. Our prediction model is based on the MobileNet convolutional neural network architecture combined with confidence measurement determined by distances between vectors in the latent space. Our results show that the mean absolute error for cells with high prediction confidence is 0.05 and the 90th percentile mean absolute error is 0.1, where the range of DNA fragmentation score is [0,1]. In the future, this model may be applied to improve cell selection by embryologists during ICSI.
A new technique for sperm analysis is presented, measuring DNA fragmentation, morphology with virtual staining, and motility, all three criteria on the same individual unstained live cell. The method relies on quantitative stain‐free interferometric imaging, providing unique topographic structural and content maps of the cell, becoming available for the first time for clinical use, together with deep‐learning frameworks and least‐squares linear approximation. In the common clinical practice, only motility evaluation can be carried out on live human cells, while full morphological evaluation and DNA fragmentation assays require different staining protocols, and therefore cannot be performed on the same cell, resulting in inconsistencies in fertility evaluation. A clinic‐ready interferometric module is used to acquire dynamic sperm cells without chemical staining, together with deep learning to evaluate all three scores per cell with accuracy of 93.1%, 88%, and 90% for morphology, motility, and DNA fragmentation, respectively. It is shown that the expected number of cells that pass all three criteria based on the current evaluations performed separately does not correspond with the number of cells that pass all criteria, demonstrating the importance of the suggested method. The proposed stain‐free evaluation method is expected to decrease uncertainty in infertility diagnosis, increasing treatment success rates.
Typically, tomographic reconstruction of dynamic 3D samples is limited by sample movement speed and illumination scanning speed. However, using the six-pack holography technique that we have developed, 6 off-axis holograms of different illumination angles can be acquired in a single camera exposure, without sacrificing individual image resolution or field of view, and without requiring sample sparsity. Using these 6 holograms we reconstruct the 3D refractive index tomogram of a dynamic sample from each video frame using the optical diffraction tomography algorithm. We demonstrate our technique experimentally on flowing microbeads and swimming microalgae.
We report a module employing shearing interferometry with constant off-axis angle (SICA) that works both for coherent light sources and low-coherence light sources, in which the shearing distance in uncoupled to the off-axis angle. In the module, two laterally sheared sample beams are generated by a grating, and the part of the sample area containing no sample details serves as the reference beam, as in any shearing interferometer. However, in our module, the shearing distance can be flexibly adjusted by controlling the axial location of the grating, while the off-axis interference angle remains constant.
We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the threedimensional movement and structure of individual human sperm cells swimming freely. We achieve both retrieval of the three-dimensional refractive-index profile of the sperm head, revealing its fine internal organelles and timevarying orientation, and the detailed four-dimensional localization of the thin, highly-dynamic flagellum of the sperm cell. Live human sperm cells were acquired during free swim using a high-speed off-axis holographic system that does not require any moving elements or cell staining. The reconstruction is based solely on the natural movement of the sperm cell and a novel set of algorithms, enabling the detailed four-dimensional recovery. Using this refractive-index imaging approach, we believe that we have detected an area in the cell that is attributed to the centriole. This method has great potential for both biological assays and clinical use of intact sperm cells.
We introduce a new shearing interferometry module for digital holographic microscopy, in which the off-axis angle, which defines the interference fringe frequency, is not coupled to the shearing distance, as is the case in most shearing interferometers. Thus, it enables the selection of shearing distance based on the spatial density of the sample, without losing spatial frequency content due to overlapping of the complex wave fronts in the spatial frequency domain. Our module is based on a 4f imaging unit and a diffraction grating, in which the hologram is generated from two mutually coherent, partially overlapping sample beams, with adjustable shearing distance, as defined by the position of the grating, but with a constant off-axis angle, as defined by the grating period. The module is simple, easy to align, and presents a nearly common-path geometry. By placing this module as an add-on unit at the exit port of an inverted microscope, quantitative phase imaging can easily be performed. The system is characterized by a 2.5 nm temporal stability and a 3.4 nm spatial stability, without using anti-vibration techniques. We provide quantitative phase imaging experiments of silica beads with different shearing distances, red blood cell fluctuations, and cancer cells flowing in a micro-channel, which demonstrate the capability and versatility of our approach in different imaging scenarios.
Six-pack holography (6PH) is the first holographic imaging modality that is more spatial bandwidth efficient than on-axis holography. 6PH utilizes a low-coherence light source and a phase delay plate to enable the spatial multiplexing of six off-axis holograms without cross-talk between the six sample and six reference beams, and is thus capable of acquiring six off-axis holograms in a single camera exposure. We applied 6PH to synthetic aperture (SA) superresolution, and produced an SA capable of dynamically increasing the resolution by a factor of 1.62. 6PH presents a valuable general purpose technique for all holography applications and label-free imaging.
We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the threedimensional movement and structure of individual human sperm cells swimming freely. We achieve both retrieval of the three-dimensional refractive-index profile of the sperm head, revealing its fine internal organelles and timevarying orientation, and the detailed four-dimensional localization of the thin, highly-dynamic flagellum of the sperm cell. Live human sperm cells were acquired during free swim using a high-speed off-axis holographic system that does not require any moving elements or cell staining. The reconstruction is based solely on the natural movement of the sperm cell and a novel set of algorithms, enabling the detailed four-dimensional recovery. Using this refractive-index imaging approach, we believe that we have detected an area in the cell that is attributed to the centriole. This method has great potential for both biological assays and clinical use of intact sperm cells.
We present a new acquisition method that enables high-resolution, fine-detail full reconstruction of the three-dimensional movement and structure of individual human sperm cells swimming freely. We achieve both retrieval of the three-dimensional refractive-index profile of the sperm head, revealing its fine internal organelles and time-varying orientation, and the detailed four-dimensional localization of the thin, highly-dynamic flagellum of the sperm cell. Live human sperm cells were acquired during free swim using a high-speed off-axis holographic system that does not require any moving elements or cell staining. The reconstruction is based solely on the natural movement of the sperm cell and a novel set of algorithms, enabling the detailed four-dimensional recovery. Using this refractive-index imaging approach, we believe that we have detected an area in the cell that is attributed to the centriole. This method has great potential for both biological assays and clinical use of intact sperm cells.
We present a deep-learning approach for solving the problem of 2π phase ambiguities in two-dimensional quantitative phase maps of biological cells, using a multi-layer encoder-decoder residual convolutional neural network. We test the trained network, PhUn-Net, on various types of biological cells, captured with various interferometric setups, as well as on simulated phantoms. These tests demonstrate the robustness and generality of the network, even for cells of different morphologies or different illumination conditions than PhUn-Net has been trained on. In this paper, for the first time, we make the trained network publicly available in a global format, such that it can be easily deployed on every platform, to yield fast and robust phase unwrapping, not requiring prior knowledge or complex implementation. By this, we expect our phase unwrapping approach to be widely used, substituting conventional and more time-consuming phase unwrapping algorithms.