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Abstract Organoids, which are miniature in vitro versions of organs, possess significant potential for studying human diseases and elucidating their underlying mechanisms. Live imaging techniques play a crucial role in organoid research and contribute to elucidating the complex structure and dynamic biological phenomena of organoids. However, live, unlabeled high-resolution imaging of native organoids is challenging, primarily owing to the complexities of sample handling and optical scattering inherent in three-dimensional (3D) structures. Additionally, conventional imaging methods fail to capture the real-time dynamic processes of growing organoids. In this study, we introduce low-coherence holotomography as an advanced, label-free, quantitative imaging modality designed to overcome several technical obstacles for long-term live imaging of 3D organoids. We demonstrate the efficacy of low-coherence holotomography by capturing high-resolution morphological details and dynamic activities within mouse small intestinal organoids at subcellular resolution. Moreover, our approach facilitates the distinction between viable and nonviable organoids, significantly enhancing its utility in organoid-based research. This advancement underscores the critical role of live imaging in organoid studies, offering a more comprehensive understanding of these complex systems.

Abstract Rapid and accurate diagnosis of acute myeloid leukemia (AML) remains a significant challenge, particularly in the context of myelodysplastic syndrome (MDS) or MDS/myeloproliferative neoplasm with NPM1 mutations. This study introduces an innovative approach using holotomography (HT), a 3D label-free quantitative phase imaging technique, to detect NPM1 mutations. We analyzed a dataset of 2073 HT myeloblast images from 48 individuals, including both NPM1 wild-type and mutated samples, to distinguish subcellular morphological changes associated with NPM1 mutations. Employing a convolutional neural network, we analyzed 3D cell morphology, focusing on refractive index distributions. The machine learning model showed high accuracy, with an area under the receiver operating characteristic curve of 0.9375 and a validation accuracy of 76.0%. Our findings reveal distinct morphological differences between the NPM1 wild-type and mutation at the subcellular level. This study demonstrates the potential of HT combined with deep learning for early, efficient, and cost-effective diagnosis of AML, offering a promising alternative to traditional stepwise genetic testing methods and providing additional assistance in morphological myeloblast discrimination. This approach may revolutionize the diagnostic process in leukemia, facilitating early detection and potentially reducing the reliance on extensive genetic testing.

Abstract A critical requirement for studying cell mechanics is three-dimensional assessment of cellular shapes and forces with high spatiotemporal resolution. Traction force microscopy with fluorescence imaging enables the measurement of cellular forces, but it is limited by photobleaching and a slow acquisition speed. Here, we present refractive-index traction force microscopy (RI-TFM), which simultaneously quantifies the volumetric morphology and traction force of cells using a high-speed illumination scheme with 0.5-Hz temporal resolution. Without labelling, our method enables quantitative analyses of dry-mass distributions and shear (in-plane) and normal (out-of-plane) tractions of single cells on the extracellular matrix. When combined with a constrained total variation-based deconvolution algorithm, it provides 0.55-Pa shear and 1.59-Pa normal traction sensitivity for a 1-kPa hydrogel substrate. We demonstrate its utility by assessing the effects of compromised intracellular stress and capturing the rapid dynamics of cellular junction formation in the spatiotemporal changes in non-planar traction components.

Abstract An ideal holographic camera measures the amplitude and phase of the light field so that the focus can be numerically adjusted after the acquisition, and depth information about an imaged object can be deduced. The performance of holographic cameras based on reference-assisted holography is significantly limited owing to their vulnerability to vibration and complex optical configurations. Non-interferometric holographic cameras can resolve these issues. However, existing methods require constraints on an object or measurement of multiple-intensity images. In this paper, we present a holographic image sensor that reconstructs the complex amplitude of scattered light from a single-intensity image using reciprocal diffractive imaging. We experimentally demonstrate holographic imaging of three-dimensional diffusive objects and suggest its potential applications by imaging a variety of samples under both static and dynamic conditions.

Abstract We developed a machine learning algorithm (MLA) that can classify human thyroid cell clusters by exploiting both Papanicolaou staining and intrinsic refractive index (RI) as correlative imaging contrasts and evaluated the effects of this combination on diagnostic performance. Thyroid fine-needle aspiration biopsy (FNAB) specimens were analyzed using correlative optical diffraction tomography, which can simultaneously measure both, the color brightfield of Papanicolaou staining and three-dimensional RI distribution. The MLA was designed to classify benign and malignant cell clusters using color images, RI images, or both. We included 1535 thyroid cell clusters (benign: malignancy = 1128:407) from 124 patients. Accuracies of MLA classifiers using color images, RI images, and both were 98.0%, 98.0%, and 100%, respectively. As information for classification, the nucleus size was mainly used in the color image; however, detailed morphological information of the nucleus was also used in the RI image. We demonstrate that the present MLA and correlative FNAB imaging approach has the potential for diagnosing thyroid cancer, and complementary information from color and RI images can improve the performance of the MLA.

Abstract Biomolecular condensates play a key role in organizing cellular reactions by concentrating a specific set of biomolecules. However, whether condensate formation is accompanied by an increase in the total mass concentration within condensates or by the demixing of already highly crowded intracellular components remains elusive. Here, using refractive index imaging, we quantify the mass density of several condensates, including nucleoli, heterochromatin, nuclear speckles, and stress granules. Surprisingly, the latter two condensates exhibit low densities with a total mass concentration similar to the surrounding cyto- or nucleoplasm. Low-density condensates display higher permeability to cellular protein probes. We find that RNA tunes the biomolecular density of condensates. Moreover, intracellular structures such as mitochondria heavily influence the way phase separation proceeds, impacting the localization, morphology, and growth of condensates. These findings favor a model where segregative phase separation driven by non-associative or repulsive molecular interactions together with RNA-mediated selective association of specific components can give rise to low-density condensates in the crowded cellular environment.

High-resolution X-ray sample field image is directly retrieved in a single shot using the mathematical relations of spatially pseudorandom (i.e., speckle) fields.

High‐resolution structural imaging of brain tissue is important for neuroscience research. However, conventional approaches have several limitations, such as the need for exogenous staining, limited accessibility to volumetric information, and qualitative analysis. Herein, high‐resolution label‐free volumetric imaging and analysis of mouse brain tissue are presented using 3D quantitative phase imaging. Measurement of the refractive index distribution of tissue enables direct imaging of the cellular and subcellular structures. Quantification of subcellular organelles is performed in the anatomical regions of the somatosensory cortex, corpus callosum, caudoputamen, and thalamus regions.

Abstract Three-dimensional (3D) quantitative phase imaging (QPI) enables long-term label-free tomographic imaging and quantitative analysis of live individual bacteria. However, the Brownian motion or motility of bacteria in a liquid medium produces motion artifacts during 3D measurements and hinders precise cell imaging and analysis. Meanwhile, existing cell immobilization methods produce noisy backgrounds and even alter cellular physiology. Here, we introduce a protocol that utilizes hydrogels for high-quality 3D QPI of live bacteria maintaining bacterial physiology. We demonstrate long-term high-resolution quantitative imaging and analysis of individual bacteria, including measuring the biophysical parameters of bacteria and responses to antibiotic treatments.

Background and Aims: Time-lapse technology is an emerging assisted reproductive technology (ART) that enables simultaneous culture and monitoring of embryos in vitro during their development. It provides extra information on key events during embryo development, which can assist embryologists in selecting embryos alongside traditional morphology evaluations. Various imaging technologies have been utilised to visualise and evaluate embryos such as brightfield microscopy, darkfield microscopy, and Hoffman modulation contrast microscopy. Although these imaging technologies allow for non-invasive imaging of human embryos in a clinical setting, 3D imaging of a whole embryo with subcellular resolution remains a challenge. Method: We demonstrate 3D time-lapse label-free imaging of live mouse embryos using the 3D refractive index (RI) imaging technique. The proposed method is a quantitative phase imaging technique that measures multiple-intensity images of transmitted light through the embryos via axial scanning to reconstruct the 3D RI map of the embryos. Results: Using the proposed method, live mouse embryos were monitored at different developmental stages, ranging from 2-cell embryos to expanded blastocysts. The measured 3D RI maps of the developing embryos reveal 3D landscape of subcellular features inside the embryos (Fig. 1). In the quantitative assessment of embryonic development, various morphokinematic parameters were extracted from the measured 3D RI maps of the embryos. Conclusion: Based on the results, we envision that our method has broad applications where non-invasive and quantitative assessment of embryonic development is required.

An optical field is described by the amplitude and phase, and thus has a complex representation described in the complex plane. However, because the only thing we can measure is the amplitude of the complex field on the real axis when not introducing an additional imaging system, it is difficult to identify how the complex field behaves throughout the complex plane. In this study, we interpret quantitative phase imaging methods via the Hilbert transform in terms of analytic continuation, manifesting the behavior in the whole complex plane. Using Rouché's theorem, we prove the imaging conditions imposed by Kramers-Kronig holographic imaging. The deviation from Kramers-Kronig holography conditions is examined using computational images and experimental data. We believe that this study provides a clue for holographic imaging using the holomorphic characteristics of a complex optical field.

Label-free rapid deep-learning-based identification of bacterial species that classifies 3D refractive index tomograms into the species.

One major challenge associated with lung cancer organoids (LCOs) is their predominant derivation from surgical specimens of patients with early-stage lung cancer. However, patients with advanced lung cancer, who are in need of chemotherapy, often cannot undergo surgery. Therefore, there is an urgent need to successfully generate LCOs from biopsy specimens. Conventional lung biopsy techniques, such as transthoracic needle biopsy and forceps biopsy, only yield small amounts of lung tissue, resulting in a low success rate for culturing LCOs from biopsy samples. Furthermore, potential complications, like bleeding and pneumothorax, make it difficult to obtain sufficient tissue. Another critical issue is the overgrowth of normal lung cells in later passages of LCO culture, and the optimal culture conditions for LCOs are yet to be determined. To address these limitations, we attempted to create LCOs from cryobiopsy specimens obtained from patients with lung cancer (n = 113). Overall, the initial success rate of establishing LCOs from cryobiopsy samples was 40.7% (n = 46). Transbronchial cryobiopsy enables the retrieval of significantly larger amounts of lung tissue than bronchoscopic forceps biopsy. Additionally, cryobiopsy can be employed for peripheral lesions, and it is aided via radial endobronchial ultrasonography. This study significantly improved the success rate of LCO culture and demonstrated that the LCOs retained characteristics that resembled the primary tumors. Single-cell RNA sequencing confirmed high cancer cell purity in early passages of LCOs derived from patients with advanced lung cancer. Furthermore, the three-dimensional structure and intracellular components of LCOs were characterized using three-dimensional holotomography. Finally, drug screening was performed using a specialized micropillar culture system with cryobiopsy-derived LCOs. LCOs derived from cryobiopsy specimens offer a promising solution to the critical limitations of conventional LCOs. Cryobiopsy can be applied to patients with lung cancer at all stages, including those with peripheral lesions, and can provide sufficient cells for LCO generation. Therefore, we anticipate that cryobiopsy will serve as a breakthrough strategy for the clinical application of LCOs in all stages of lung cancer.

Abstract Background Surgical resection (SR) has been selectively applied in hepatocellular carcinoma (HCC) presenting with minor gross vascular invasion (mGVI) which is defined when tumor invasion is confined to second-order portal branches or segmental branches of hepatic vein. However, little data of long-term outcomes are available for supporting the role of SR as a potentially curable therapeutic option for HCC presenting with mGVI. This study is aimed to estimate a statistical cure fraction and the improvement of recurrence-free conditional survival (RFCS) over time among patients undergoing SR for HCC presenting with mGVI. Methods The literature search was conducted focusing on previous studies that investigated the long-term survival rates of patients after SR for HCC presenting with mGVI. The reference cohort was extracted from a study including patients undergoing SR for HCC without vascular invasion. A non-mixture cure model was adopted to estimate the statistical cure fraction. The 5-year RFCS probabilities were also calculated. Results Three retrospective studies were secondarily analyzed. The probability of being statistically cured after SR for HCC presenting with mGVI was 7.3% (95% confidence interval, 4.4%–11.2%) in the mGVI group, lower than that of the reference cohort (hazard ratio, 1.81; 95% confidence interval, 1.59–2.05). The estimated 5-year RFCS probabilities improved with each additional year of survival. Moreover, 1 year after SR, the 5-year RFCS probabilities of patients with HCC presenting with mGVI was essentially the same as that of the reference cohort. Conclusions This study shows that a cure can be expected in around seven percent of patients undergoing SR for HCC presenting with mGVI. Furthermore, recurrence-free survival expectancy improves dramatically over time among those patients who do not have recurrence. Overall, these findings suggest that SR should be considered as a potentially curable treatment for patients with HCC presenting with mGVI.

Abstract Absorption spectroscopy is widely used to detect samples with spectral specificity. Here, we propose and demonstrate a method for enhancing the sensitivity of absorption spectroscopy. Exploiting multiple light scattering generated by a boron nitride (h-BN) scattering cavity, the optical path lengths of light inside a diffusive reflective cavity are significantly increased, resulting in more than ten times enhancement of sensitivity in absorption spectroscopy. We demonstrate highly sensitive spectral measurements of low concentrations of malachite green and crystal violet aqueous solutions. Because this method only requires the addition of a scattering cavity to existing absorption spectroscopy, it is expected to enable immediate and widespread applications in various fields, from analytical chemistry to environmental sciences.

Optical techniques offer a wide variety of applications as light-matter interactions provide extremely sensitive mechanisms to probe or treat target media. Most of these implementations rely on the usage of ballistic or quasi-ballistic photons to achieve high spatial resolution. However, the inherent scattering nature of light in biological tissues or tissue-like scattering media constitutes a critical obstacle that has restricted the penetration depth of non-scattered photons and hence limited the implementation of most optical techniques for wider applications. In addition, the components of an optical system are usually designed and manufactured for a fixed function or performance. Recent advances in wavefront shaping have demonstrated that scattering- or component-induced phase distortions can be compensated by optimizing the wavefront of the input light pattern through iteration or by conjugating the transmission matrix of the scattering medium. This offers unprecedented opportunities in many applications to achieve controllable optical delivery or detection at depths or dynamically configurable functionalities by using scattering media to substitute conventional optical components. In this article, the recent progress of wavefront shaping in multidisciplinary fields is reviewed, from optical focusing and imaging with scattering media, functionalized devices, modulation of mode coupling, and nonlinearity in multimode fiber to multimode fiber-based applications. Apart from insights into the underlying principles and recent advances in wavefront shaping implementations, practical limitations and roadmap for future development are discussed in depth. Looking back and looking forward, it is believed that wavefront shaping holds a bright future that will open new avenues for noninvasive or minimally invasive optical interactions and arbitrary control inside deep tissues. The high degree of freedom with multiple scattering will also provide unprecedented opportunities to develop novel optical devices based on a single scattering medium (generic or customized) that can outperform traditional optical components.

Abstract Optical diffraction tomography (ODT) enables imaging of unlabeled intracellular components by measuring the three-dimensional (3D) refractive index (RI). We aimed to detect intracellular monosodium urate (MSU) crystals in synovial leukocytes derived from gout patients using ODT. The 3D RI values of the synthetic MSU crystals, measured by ODT, ranged between 1.383 and 1.440. After adding synthetic MSU crystals to a macrophage, RI tomograms were reconstructed using ODT, and the reconstructed RI tomograms discerned intracellular and extracellular MSU crystals. We observed unlabeled synthetic MSU crystal entry into the cytoplasm of a macrophage through time-lapse imaging. Furthermore, using gout patient-derived synovial leukocytes, we successfully obtained RI tomogram images of intracellular MSU crystals. The 3D RI identification of MSU crystals was verified with birefringence through polarization-sensitive ODT measurements. Together, our results provide evidence that this novel ODT can identify birefringent MSU crystals in synovial leukocytes of patients with gout.

A general method for the in-situ isotropic microtomography of freestanding specimens, exploiting complex wavefront shaping and optical tweezers.

Abstract Drug resistance remains the major culprit of therapy failure in disseminated cancers. Simultaneous resistance to multiple, chemically different drugs feeds this failure resulting in cancer relapse. Here, we investigate co-resistance signatures shared between antimitotic drugs (AMDs) and inhibitors of receptor tyrosine kinases (RTKs) to probe mechanisms of secondary resistance. We map co-resistance ranks in multiple drug pairs and identified a more widespread occurrence of co-resistance to the EGFR-tyrosine kinase inhibitor (TKI) gefitinib in hundreds of cancer cell lines resistant to at least 11 AMDs. By surveying different parameters of genomic alterations, we find that the two RTKs EGFR and AXL displayed similar alteration and expression signatures. Using acquired paclitaxel and epothilone B resistance as first-line AMD failure models, we show that a stable collateral resistance to gefitinib can be relayed by entering a dynamic, drug-tolerant persister state where AXL acts as bypass signal. Delayed AXL degradation rendered this persistence to become stably resistant. We probed this degradation process using a new EGFR-TKI candidate YD and demonstrated that AXL bypass-driven collateral resistance can be suppressed pharmacologically. The findings emphasize that AXL bypass track is employed by chemoresistant cancer cells upon EGFR inhibition to enter a persister state and evolve resistance to EGFR-TKIs.

Abstract The rheological and physiological properties of red blood cells (RBCs) are affected by many factors in the vascular environment. Among them, membrane fluctuations (MFs), particularly dynamic fluctuations in RBC cell membrane thickness (RBC-MFs), are likely to be altered by the level of glycation of haemoglobin in patients with diabetes mellitus (DM). We investigated the associations of RBC-MFs with physiological variables associated with DM and cardiovascular diseases (CVDs). Forty-one healthy control subjects and 59 patients with DM were enrolled. Five-microliter samples of blood were collected and diluted 400 times. To measure the RBC-MFs, holotomography was used, which non-invasively and precisely analyses the optical characteristics of RBCs. Associations between the RBC-MFs and biochemical parameters related to glucose homeostasis and lipid profiles were investigated. Independent associations of the RBC-MFs with the presence of CVDs were also analysed. RBC-MFs were lower in patients with DM than in healthy participants (61.64 ± 7.49 nm vs 70.65 ± 6.65 nm, P = 1.4 × 10−8). RBC-MFs correlated modestly with glycated haemoglobin level (ρ = − 0.47) and weakly with age (ρ = − 0.36), duration of diabetes (ρ = − 0.36), fasting plasma glucose level (ρ = − 0.37), and the 10-year Framingham risk score (ρ = − 0.38) (all P

Non-resonant lasers have many advantages since the allow for a diverse set of architectures and gain media, but their application is limited due to their low directionality and efficiency. Here, the authors present a scattering cavity laser with a single hole to achieve efficient and directional emission.

Abstract In tomographic reconstruction, the image quality of the reconstructed images can be significantly degraded by defects in the measured two-dimensional (2D) raw image data. Despite the importance of screening defective 2D images for robust tomographic reconstruction, manual inspection and rule-based automation suffer from low-throughput and insufficient accuracy, respectively. Here, we present deep learning-enabled quality control for holographic data to produce robust and high-throughput optical diffraction tomography (ODT). The key idea is to distil the knowledge of an expert into a deep convolutional neural network. We built an extensive database of optical field images with clean/noisy annotations, and then trained a binary-classification network based upon the data. The trained network outperformed visual inspection by non-expert users and a widely used rule-based algorithm, with >90% test accuracy. Subsequently, we confirmed that the superior screening performance significantly improved the tomogram quality. To further confirm the trained model’s performance and generalisability, we evaluated it on unseen biological cell data obtained with a setup that was not used to generate the training dataset. Lastly, we interpreted the trained model using various visualisation techniques that provided the saliency map underlying each model inference. We envision the proposed network would a powerful lightweight module in the tomographic reconstruction pipeline.

3D holographic displays still face many challenges such as small viewing angle and image size. Here the authors present a scalable method for displaying large holographic images with a wide viewing angle using a wide-angle diffracting element in a flat panel; a non-periodic photon sieve.

We proposed a method of label-free segmentation of cell nuclei by exploiting a deep learning (DL) framework. Over the years, fluorescent proteins and staining agents have been widely used to identify cell nuclei. However, the use of exogenous agents inevitably prevents from long-term imaging of live cells and rapid analysis and even interferes with intrinsic physiological conditions. Without any agents, the proposed method was applied to label-free optical diffraction tomography (ODT) of human breast cancer cells. A novel architecture with optimized training strategies was validated through cross-modality and cross-laboratory experiments. The nucleus volumes from the DL-based label-free ODT segmentation accurately agreed with those from fluorescent-based. Furthermore, the 4D cell nucleus segmentation was successfully performed for the time-lapse ODT images. The proposed method would bring out broad and immediate biomedical applications with our framework publicly available.

Objective and Impact Statement. We propose a rapid and accurate blood cell identification method exploiting deep learning and label-free refractive index (RI) tomography. Our computational approach that fully utilizes tomographic information of bone marrow (BM) white blood cell (WBC) enables us to not only classify the blood cells with deep learning but also quantitatively study their morphological and biochemical properties for hematology research. Introduction. Conventional methods for examining blood cells, such as blood smear analysis by medical professionals and fluorescence-activated cell sorting, require significant time, costs, and domain knowledge that could affect test results. While label-free imaging techniques that use a specimen’s intrinsic contrast (e.g., multiphoton and Raman microscopy) have been used to characterize blood cells, their imaging procedures and instrumentations are relatively time-consuming and complex. Methods. The RI tomograms of the BM WBCs are acquired via Mach-Zehnder interferometer-based tomographic microscope and classified by a 3D convolutional neural network. We test our deep learning classifier for the four types of bone marrow WBC collected from healthy donors (n=10): monocyte, myelocyte, B lymphocyte, and T lymphocyte. The quantitative parameters of WBC are directly obtained from the tomograms. Results. Our results show >99% accuracy for the binary classification of myeloids and lymphoids and >96% accuracy for the four-type classification of B and T lymphocytes, monocyte, and myelocytes. The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique. Conclusion. We envision that the proposed cell classification framework can be easily integrated into existing blood cell investigation workflows, providing cost-effective and rapid diagnosis for hematologic malignancy.

Phosphate-buffered saline (PBS) and Alsever’s solution (AS) are frequently used as media in blood-related studies, while 0.9% normal saline (NS) is frequently used in transfusion medicine. Despite the frequent use, the effects of these solutions on the shape and volume of red blood cells (RBCs) have not been reported. We collected blood samples from five healthy adults and used three-dimensional refractive index tomography to investigate the changes in the morphology of RBCs caused by changes in osmolality and solutes at the single-cell level. After diluting 2 μL of RBCs 200-fold with each solution (PBS, AS, and 0.9% NS), 40 randomly selected RBCs were microscopically observed. RBC shape was measured considering sphericity, which is a dimensionless quantity ranging from 0 (flat) to 1 (spherical). RBCs in plasma or AS showed a biconcave shape with a small sphericity, whereas those in 0.9% NS or PBS showed a spherical shape with a large sphericity. Moreover, we confirmed that sodium chloride alone could not elicit the biconcave shape of RBCs, which could be maintained only in the presence of an osmotic pressure-maintaining substance, such as glucose or mannitol. Although 0.9% NS solution is one of the most commonly used fluids in hematology and transfusion medicine, RBCs in 0.9% NS or PBS are not biconcave. Therefore, as the debate on the use of NS continues, future clinical studies or applications should consider the effect of glucose or mannitol on the shape of RBCs.

The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniques, most of which rely on fluorescence microscopy, have been used to study the dynamics of IS. However, the inherent limitations associated with the fluorescence-based imaging, such as photo-bleaching and photo-toxicity, prevent the long-term assessment of dynamic changes of IS with high frequency. Here, we propose and experimentally validate a label-free, volumetric, and automated assessment method for IS dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed method enables an automatic and quantitative spatiotemporal analysis of IS kinetics of morphological and biochemical parameters associated with IS dynamics, providing a new option for immunological research.

The measurement of three-dimensional (3D) images and the analysis of subcellular organelles are crucial for the study of the pathophysiology of cells and tissues. Optical diffraction tomography (ODT) facilitates label-free and quantitative imaging of live cells by reconstructing 3D refractive index (RI) distributions. In many cases, however, the contrast in RI distributions is not strong enough to effectively distinguish subcellular organelles in live cells. To realize label-free and quantitative imaging of subcellular organelles in unlabeled live cells with enhanced contrasts, we present a computational approach using ODT. We demonstrate that the contrast of ODT can be enhanced via spatial high-pass filtering in a 3D spatial frequency domain, and that it yields theoretically equivalent results to physical dark-field illumination. Without changing the optical instruments used in ODT, subcellular organelles in live cells are clearly distinguished by applying a simple but effective computational approach that is validated by comparison with 3D epifluorescence images. We expect that the proposed method will satisfy the demand for label-free organelle observations and will be extended to fully utilize complex information in 3D RI distributions.

Human epidermal growth factor receptors (HERs) are the primary targets of many directed cancer therapies. However, the reason a specific dimer of HERs generates a stronger proliferative signal than other permutations remains unclear. Here, we used single-molecule immunoprecipitation to develop a biochemical assay for endogenously-formed, entire HER2-HER3 heterodimers. We observed unexpected, large conformational fluctuations in juxta-membrane and kinase domains of the HER2-HER3 heterodimer. Nevertheless, the individual HER2-HER3 heterodimers catalyze tyrosine phosphorylation at an unusually high rate, while simultaneously interacting with multiple copies of downstream signaling effectors. Our results suggest that the high catalytic rate and multi-tasking capability make a concerted contribution to the strong signaling potency of the HER2-HER3 heterodimers.

Abstract 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.

Anticancer treatment strategies using bacteria as a vector are currently expanding with the development of anticancer drugs. Here, we present a research strategy to develop anticancer drugs using bacteria that contain miRNAs. We also present a strategy for the development of novel bacterial anticancer drugs in combination with radiation. Salmonella strains expressing miRNA were produced by modifying the miRNA expression vector encoding INHA, a radiation-resistant gene developed previously. The anticancer effect of INHA was confirmed using skin cancer cell lines. We also tested a combination strategy comprising bacteria and radiation for its anticancer efficacy against radiation-resistant mouse melanoma to increase the efficacy of radiation therapy as a novel strategy. The recombinant strain was confirmed to promote effective cell death even when combined with radiation therapy, which exerts its cytotoxicity by enhancing reactive oxygen species production. Moreover, a combination of bacterial and radiation therapy enhanced radiotherapy efficacy. When combined with radiation therapy, bacterial therapy exhibited effective anti-cancer properties even when administered to animals harboring radiation-resistant tumors. This strategy may promote the secretion of cytokines in cells and more effectively reduce the number of bacteria remaining in the animal. Thus, this study may lead to the development of a strategy to improve the effectiveness of radiation therapy using Salmonella expressing cancer-specific miRNA for intractable cancers such as those resistant to radiation.

Abstract Intact optical information of an object delivered through an imaging system is deteriorated by imperfect optical elements and unwanted defects. Image deconvolution has been widely exploited as a recovery technique due to its practical feasibility, and operates by assuming linear shift-invariant property of the imaging system. However, shift invariance does not rigorously hold in all imaging situations and is not a necessary condition for solving an inverse problem of light propagation. Several improved deconvolution techniques exploiting spatially variant point spread functions have been proposed in previous studies. However, the full characterization of an optical imaging system for compensating aberrations has not been considered. Here, we present a generalized method to solve the linear inverse problem of coherent light propagations without any regularization method or constraint on shift invariance by fully measuring the transmission matrix of the imaging system. Our results show that severe aberrations produced by a tilted lens or an inserted disordered layer can be corrected properly only by the proposed generalized image deconvolution. This work generalizes the theory of image deconvolution, and enables distortion-free imaging under general imaging condition.

Abstract Identification of lymphocyte cell types are crucial for understanding their pathophysiological roles in human diseases. Current methods for discriminating lymphocyte cell types primarily rely on labelling techniques with magnetic beads or fluorescence agents, which take time and have costs for sample preparation and may also have a potential risk of altering cellular functions. Here, we present the identification of non-activated lymphocyte cell types at the single-cell level using refractive index (RI) tomography and machine learning. From the measurements of three-dimensional RI maps of individual lymphocytes, the morphological and biochemical properties of the cells are quantitatively retrieved. To construct cell type classification models, various statistical classification algorithms are compared, and the k-NN (k = 4) algorithm was selected. The algorithm combines multiple quantitative characteristics of the lymphocyte to construct the cell type classifiers. After optimizing the feature sets via cross-validation, the trained classifiers enable identification of three lymphocyte cell types (B, CD4+ T, and CD8+ T cells) with high sensitivity and specificity. The present method, which combines RI tomography and machine learning for the first time to our knowledge, could be a versatile tool for investigating the pathophysiological roles of lymphocytes in various diseases including cancers, autoimmune diseases, and virus infections.

Controlling the three-dimensional behaviour of arbitrarily shaped and oriented particles with optical tweezers is a challenging task. Here, Kim and Park use tomographic active trapping to manipulate non-spherical particles and particle ensembles as well as biological cells.

Abstract In this paper, we present the optical characterisations of diabetic red blood cells (RBCs) in a non-invasive manner employing three-dimensional (3-D) quantitative phase imaging. By measuring 3-D refractive index tomograms and 2-D time-series phase images, the morphological (volume, surface area and sphericity), biochemical (haemoglobin concentration and content) and mechanical (membrane fluctuation) parameters were quantitatively retrieved at the individual cell level. With simultaneous measurements of individual cell properties, systematic correlative analyses on retrieved RBC parameters were also performed. Our measurements show there exist no statistically significant alterations in morphological and biochemical parameters of diabetic RBCs, compared to those of healthy (non-diabetic) RBCs. In contrast, membrane deformability of diabetic RBCs is significantly lower than that of healthy, non-diabetic RBCs. Interestingly, non-diabetic RBCs exhibit strong correlations between the elevated glycated haemoglobin in RBC cytoplasm and decreased cell deformability, whereas diabetic RBCs do not show correlations. Our observations strongly support the idea that slow and irreversible glycation of haemoglobin and membrane proteins of RBCs by hyperglycaemia significantly compromises RBC deformability in diabetic patients.

BackgroundAlthough gross vascular invasion (VI) has prognostic significance in patients with hepatocellular carcinoma (HCC) who have undergone hepatic resection, few studies have investigated the relationship between gross VI and aberrant expression of microribonucleic acids (miRNAs and miRs). Thus, the objective of this study was to identify miRNAs selectively expressed in HCC with gross VI and investigate their prognostic significance.Materials and methodsEligible two datasets (accession number: GSE20594 and GSE67140) were collected from the National Center for Biotechnology Information's (NCBI) Gene Expression Omnibus (GEO) database to compare miRNAs expression between HCC with and without gross VI. Differentially expressed miRNAs were externally validated using expression data from The Cancer Genome Atlas (TCGA) database. Prognostic significance and predicted functions of selected miRNAs for HCC were also investigated.ResultsThirty-five miRNAs were differentially expressed between HCC with and without gross VI in both datasets. Among them, three miRNAs were validated using TCGA database. miR-99a, miR-100, and miR-148a were downregulated to a greater extent in patients with HCC and gross VI than in those with HCC but no gross VI. Receiver operating characteristic (ROC) curve analysis showed discriminatory power of these miRNAs in predicting gross VI. Multivariate survival analysis revealed that types of surgery, advanced tumor node metastasis (TNM) stage, and low expression of miR-100-5p were independently associated with tumor recurrence. It also revealed that types of surgery, advanced TNM stage, low expression of miR-100-5p and miR-148a-3p were independent risk factors for overall survival (OS) after hepatic resection for HCC. A text mining analysis revealed that these miRNAs were linked to multifaceted hallmarks of cancer, including "invasion and metastasis."ConclusionsLow expressions of miR-100-5p and miR-148a-3p were associated with gross VI and poor survival of patients after hepatic resection for HCC.

Changes in microcirculation are believed to perform an important role after cardiac arrest. In particular, rheological changes in red blood cells (RBCs) have been observed during and after ischemic-reperfusion injury. Employing three-dimensional laser interferometric microscopy, we investigated three-dimensional shapes and deformability of RBCs during and after asphyxial cardiac arrest in rats at the individual cell level. Rat cardiac arrest was induced by asphyxia. Five rats were maintained for 7 min of no-flow time, and then, cardiopulmonary resuscitation (CPR) was started. Blood samples were obtained before cardiac arrest, during CPR, and 60 min after return of spontaneous circulation (ROSC). Quantitative phase imaging (QPI) techniques based on laser interferometry were used to measure the three-dimensional refractive index (RI) tomograms of the RBC, from which structural and biochemical properties were retrieved. Dynamic membrane fluctuations in the cell membrane were also quantitatively and sensitively measured in order to investigate cell deformability. Mean corpuscular hemoglobin, mean cell volume, mean corpuscular hemoglobin concentration, and red blood cell distribution width remained unchanged during CPR and after ROSC compared with those before cardiac arrest. QPI results revealed that RBC membrane fluctuations, sphericity, and surface area did not change significantly during CPR or after ROSC compared with initial values. In conclusion, no three-dimensional shapes and cell deformability changes in RBCs were detected.

Holographic techniques store and retrieve complete optical information, but the requirement of a reference beam can make the process complicated and sensitive to noise. Here, the authors develop a reference-free method that harnesses self-interference in a diffusive scattering medium.

The development of optical and computational techniques has enabled imaging without the need for traditional optical imaging systems. Modern lensless imaging techniques overcome several restrictions imposed by lenses, while preserving or even surpassing the capability of lens-based imaging. However, existing lensless methods often rely on a priori information about objects or imaging conditions. Thus, they are not ideal for general imaging purposes. The recent development of the speckle-correlation scattering matrix (SSM) techniques facilitates new opportunities for lensless imaging and sensing. In this review, we present the fundamentals of SSM methods and highlight recent implementations for holographic imaging, microscopy, optical mode demultiplexing, and quantification of the degree of the coherence of light. We conclude with a discussion of the potential of SSM and future research directions.

Multiple light scattering has been regarded as a barrier in imaging through complex media such as biological tissues. Owing to recent advances in wavefront shaping techniques, optical imaging through intact biological tissues without invasive procedures can now be used for direct experimental studies, presenting promising application opportunities in in vivo imaging and diagnosis. Although most of the recent proof of principle breakthroughs have been achieved in the laboratory setting with specialties in physics and engineering, we anticipate that these technologies can be translated to biological laboratories and clinical settings, which will revolutionize how we diagnose and treat a disease. To provide insight into the physical principle that enables the control of multiple light scattering in biological tissues and how recently developed techniques can improve bioimaging through thick tissues, we summarize recent progress on wavefront shaping techniques for controlling multiple light scattering in biological tissues.

The cell nucleus is a three-dimensional, dynamic organelle organized into subnuclear compartments such as chromatin and nucleoli. The structure and function of these compartments are maintained by diffusion and interactions between related factors as well as by dynamic and structural changes. Recent studies using fluorescent microscopic techniques suggest that protein factors can access and are freely mobile in heterochromatin and in mitotic chromosomes, despite their densely packed structure. However, the physicochemical properties of the chromosome during cell division are not fully understood. In the present study, characteristic properties such as the refractive index (RI), volume of the mitotic chromosomes, and diffusion coefficient (D) of fluorescent probes inside the chromosome were quantified using an approach combining label-free optical diffraction tomography with complementary confocal laser-scanning microscopy and fluorescence correlation spectroscopy. Variations in these parameters correlated with osmotic conditions, suggesting that changes in RI are consistent with those of the diffusion coefficient for mitotic chromosomes and cytosol. Serial RI tomography images of chromosomes in live cells during mitosis were compared with three-dimensional confocal micrographs to demonstrate that compaction and decompaction of chromosomes induced by osmotic change were characterized by linked changes in chromosome RI, volume, and the mobilities of fluorescent proteins.

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.

Three-dimensional imaging of biological cells is crucial for the investigation of cell biology, providing valuable information to reveal the mechanisms behind pathophysiology of cells and tissues. Recent advances in optical diffraction tomography (ODT) have demonstrated the potential for the study of various cells with its unique advantages of quantitative and label-free imaging capability. To provide insight on this rapidly growing field of research and to discuss its applications in biology and medicine, we present the summary of the ODT principle and highlight recent studies utilizing ODT with the emphasis on the applications to the pathophysiology of cells.

Upon infection and development within human erythrocytes, P. falciparum induces alterations to the infected RBC morphology and bio-mechanical properties to eventually rupture the host cells through parasitic and host derived proteases of cysteine and serine families. We used previously reported broad-spectrum inhibitors (E64d, EGTA-AM and chymostatin) to inhibit these proteases and impede rupture to analyze mechanical signatures associated with parasite escape. Treatment of late-stage iRBCs with E64d and EGTA-AM prevented rupture, resulted in no major RBC cytoskeletal reconfiguration but altered schizont morphology followed by dramatic re-distribution of three-dimensional refractive index (3D-RI) within the iRBC. These phenotypes demonstrated several-fold increased iRBC membrane flickering. In contrast, chymostatin treatment showed no 3D-RI changes and caused elevated fluctuations solely within the parasitophorous vacuole. We show that E64d and EGTA-AM supported PV breakdown and the resulting elevated fluctuations followed non-Gaussian pattern that resulted from direct merozoite impingement against the iRBC membrane. Optical trapping experiments highlighted reduced deformability of the iRBC membranes upon rupture-arrest, more specifically in the treatments that facilitated PV breakdown. Taken together, our experiments provide novel mechanistic interpretations on the role of parasitophorous vacuole in maintaining the spherical schizont morphology, the impact of PV breakdown on iRBC membrane fluctuations leading to eventual parasite escape and the evolution of membrane stiffness properties of host cells in which merozoites were irreversibly trapped, recourse to protease inhibitors. These findings provide a comprehensive, previously unavailable, body of information on the combined effects of biochemical and biophysical factors on parasite egress from iRBCs.