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Human brain organoids produce anatomically relevant cellular structures and recapitulate key aspects of in vivo brain function, which holds great potential to model neurological diseases and screen therapeutics. However, the long growth time of 3D systems complicates the culturing of brain organoids and results in heterogeneity across samples hampering their applications. An integrated platform is developed to enable robust and long‐term culturing of 3D brain organoids. A mesofluidic bioreactor device is designed based on a reaction‐diffusion scaling theory, which achieves robust media exchange for sufficient nutrient delivery in long‐term culture. This device is integrated with longitudinal tracking and machine learning‐based classification tools to enable non‐invasive quality control of live organoids. This integrated platform allows for sample pre‐selection for downstream molecular analysis. Transcriptome analyses of organoids revealed that the mesofluidic bioreactor promoted organoid development while reducing cell death. This platform thus offers a generalizable tool to establish reproducible culture standards for 3D cellular systems for a variety of applications beyond brain organoids. [ABSTRACT FROM AUTHOR]

Only 30% of embryos from in vitro fertilized oocytes successfully implant and develop to term, leading to repeated transfer cycles. To reduce time-to-pregnancy and stress for patients, there is a need for a diagnostic tool to better select embryos and oocytes based on their physiology. The current standard employs brightfield imaging, which provides limited physiological information. Here, we introduce METAPHOR: Metabolic Evaluation through Phasor-based Hyperspectral Imaging and Organelle Recognition. This non-invasive, label-free imaging method combines two-photon illumination and AI to deliver the metabolic profile of embryos and oocytes based on intrinsic autofluorescence signals. We used it to classify i) mouse blastocysts cultured under standard conditions or with depletion of selected metabolites (glucose, pyruvate, lactate); and ii) oocytes from young and old mouse females, or in vitro-aged oocytes. The imaging process was safe for blastocysts and oocytes. The METAPHOR classification of control vs. metabolites-depleted embryos reached an area under the ROC curve (AUC) of 93.7%, compared to 51% achieved for human grading using brightfield imaging. The binary classification of young vs. old/in vitro-aged oocytes and their blastulation prediction using METAPHOR reached an AUC of 96.2% and 82.2%, respectively. Finally, organelle recognition and segmentation based on the flavin adenine dinucleotide signal revealed that quantification of mitochondria size and distribution can be used as a biomarker to classify oocytes and embryos. The performance and safety of the method highlight the accuracy of noninvasive metabolic imaging as a complementary approach to evaluate oocytes and embryos based on their physiology. [ABSTRACT FROM AUTHOR]

Although quantitative analysis of biological images demands precise extraction of specific organelles or cells, it remains challenging in broad-field grayscale images, where traditional thresholding methods have been hampered due to complex image features. Nevertheless, rapidly growing artificial intelligence technology is overcoming obstacles. We previously reported the fine-tuned apodized phase-contrast microscopy system to capture high-resolution, label-free images of organelle dynamics in unstained living cells (Shimasaki, K. et al. (2024). Cell Struct. Funct., 49: 21–29). We here showed machine learning-based segmentation models for subcellular targeted objects in phase-contrast images using fluorescent markers as origins of ground truth masks. This method enables accurate segmentation of organelles in high-resolution phase-contrast images, providing a practical framework for studying cellular dynamics in unstained living cells. Key words: label-free imaging, organelle dynamics, apodized phase contrast, deep learning-based segmentation

Cell biologists have long sought the ability to observe intracellular structures in living cells without labels. This study presents procedures to adjust a commercially available apodized phase-contrast (APC) microscopy system for better visualizing the dynamic behaviors of various subcellular organelles in living cells. By harnessing the versatility of this technique to capture sequential images, we could observe morphological changes in cellular geometry after virus infection in real time without probes or invasive staining. The tune-up APC microscopy system is a highly efficient platform for simultaneously observing the dynamic behaviors of diverse subcellular structures with exceptional resolution.

Lysosomes are the terminal end of catabolic pathways in the cell, as well as signaling centers performing important functions such as the recycling of macromolecules, organelles, and nutrient adaptation. The importance of lysosomes in human health is supported by the fact that the deficiency of most lysosomal genes causes monogenic diseases called as a group Lysosomal Storage Diseases (LSDs). A common phenotypic hallmark of LSDs is the expansion of the lysosomal compartment that can be detected by using conventional imaging methods based on immunofluorescence protocols or overexpression of tagged lysosomal proteins. These methods require the alteration of the cellular architecture (i.e., due to fixation methods), can alter the behavior of cells (i.e., by the overexpression of proteins), and require sample preparation and the accurate selection of compatible fluorescent markers in relation to the type of analysis, therefore limiting the possibility of characterizing cellular status with simplicity. Therefore, a quantitative and label‐free methodology, such as Quantitative Phase Imaging through Digital Holographic (QPI‐DH), for the microscopic imaging of lysosomes in health and disease conditions may represent an important advance to study and effectively diagnose the presence of lysosomal storage in human disease. Here we proof the effectiveness of the QPI‐DH method in accomplishing the detection of the lysosomal compartment using mouse embryonic fibroblasts (MEFs) derived from a Mucopolysaccharidosis type III‐A (MSP‐IIIA) mouse model, and comparing them with wild‐type (WT) MEFs. We found that it is possible to identify label‐free biomarkers able to supply a first pre‐screening of the two populations, thus showing that QPI‐DH can be a suitable candidate to surpass fluorescent drawbacks in the detection of lysosomes dysfunction. An appropriate numerical procedure was developed for detecting and evaluate such cellular substructures from in vitro cells cultures. Results reported in this study are encouraging about the further development of the proposed QPI‐DH approach for such type of investigations about LSDs. [ABSTRACT FROM AUTHOR]

Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy‐induced peripheral neuropathy (CIPN). These processes are influenced by a broad range of entwined events facilitated by chemical, electrical, and mechanical signals. The progress of each process is inherently linked to phenotypic changes in cells. Currently, the primary means of demonstrating morphological changes rely on measurements of neurite outgrowth and axon length. However, conventional techniques for monitoring these processes often require extensive preparation to enable manual or semi‐automated measurements. Here, a label‐free and non‐invasive approach is employed for monitoring neuronal differentiation and degeneration using quantitative phase imaging (QPI). Operating on unlabeled specimens and offering little to no phototoxicity and photobleaching, QPI delivers quantitative maps of optical path length delays that provide an objective measure of cellular morphology and dynamics. This approach enables the visualization and quantification of axon length and other physical properties of dorsal root ganglion (DRG) neuronal cells, allowing greater understanding of neuronal responses to stimuli simulating CIPN conditions. This research paves new avenues for the development of more effective strategies in the clinical management of neurotoxicity. [ABSTRACT FROM AUTHOR]

Label-free and multiphoton micro-endoscopy can transform clinical histopathology by providing an in situ tool for diagnostic imaging and surgical treatment in diseases such as cancer. Key to a multiphoton imaging-based micro-endoscopic device is the optical fiber, for distortion-free and efficient delivery of ultra-short laser pulses to the sample and effective signal collection. In this work, we study a new hollow-core (air-filled) double-clad anti-resonant fiber (DC-ARF) as a high-performance candidate for multiphoton micro-endoscopy. We compare the fiber characteristics of the DC-ARF with a single-clad anti-resonant fiber (SC-ARF) and a solid core fiber (SCF). In this work, while the DC-ARF and the SC-ARF enable low-loss (<0.2 dBm−1), close to dispersion-free excitation pulse delivery (<10% pulse width increase at 900 nm per 1 m fiber) without any induced non-linearities, the SCF resulted in spectral broadening and pulse-stretching (>2000% of pulse width increase at 900 nm per 1 m fiber). An ideal optical fiber endoscope needs to be several meters long and should enable both excitation and collection through the fiber. Therefore, we performed multiphoton imaging on endoscopy-compatible 1 m and 3 m lengths of fiber in the back-scattered geometry, wherein the signals were collected either directly (non-descanned detection) or through the fiber (descanned detection). Second harmonic images were collected from barium titanate crystals as well as from biological samples (mouse tail tendon). In non-descanned detection conditions, the ARFs outperformed the SCF by up to 10 times in terms of signal-to-noise ratio of images. Significantly, only the DC-ARF, due to its high numerical aperture (NA) of 0.45 and wide-collection bandwidth (>1 µm), could provide images in the de-scanned detection configuration desirable for endoscopy. Thus, our systematic characterization and comparison of different optical fibers under different image collection configurations, confirms and establishes the utility of DC-ARFs for high-performing label-free multiphoton imaging-based micro-endoscopy. [ABSTRACT FROM AUTHOR]

There is an increasing demand for label‐free imaging of subwavelength low‐index dielectric samples with high contrast and high sensitivity using a dark‐field optical microscope. However, subwavelength low‐index dielectric samples usually do not show strong Mie scattering resonance characteristics due to the weak light confining ability, which makes them difficult to clearly resolve under a traditional optical microscope. In this work, a fast, simple, and effective approach is proposed to enhance the optical response of subwavelength low‐index dielectric samples by using metallic substrate‐enhanced scattering nanoscopy. It is found that the high reflectance of a substrate can significantly enhance the electric dipole resonance of a SiO2 nanoparticle and the substrate‐nanoparticle interaction, which amplifies the scattering signal of the sample and improves the imaging contrast. Compared with the silica substrate, the Ag‐coated substrate can enhance the scattering intensity of a SiO2 nanoparticle up to 3.7 times under 540 nm wavelength illumination. Furthermore, label‐free stand‐alone 50‐nm‐radius SiO2 nanoparticles and ≈100‐nm‐thick bacterial capsules can be clearly observed when placed on Ag‐coated substrates under a conventional dark‐field optical microscope. The substrate‐enhanced subwavelength‐resolution scattering nanoscopy can enhance the scattering of low‐index subwavelength samples and benefit a significant application in biology, medical testing, and optical detection. [ABSTRACT FROM AUTHOR]

The Compact Morpho‐Molecular Microscopy (CM3) is proposed and demonstrated for multi‐functional imaging and characterization of living cells and material structures by simultaneously offering quantitative phase imaging (QPI), dispersion characterization, and fluorescence imaging. The compactness and stability of CM3 are realized by propagating lasers of different wavelengths in specially treated optical fibers and fiber‐based beam splitters and wavelength division multiplexers, as well as simplifying the detection scheme through Fourier‐space multiplexing and implementing a single camera for both QPI and fluorescence imaging. Quantitative phase maps of two wavelengths are retrieved from a multiplexed interferogram, and a synthesized wavelength phase map is derived to guide the height profiling of samples with extended depth. With the wavelength resolved phase maps, a physical model is derived to obtain sample dispersion parameters, which further enables us to quantify the hemoglobin concentration of red blood cells in real time. By inserting an appropriate emission color filter, fluorescence imaging is realized using the same camera, which significantly broadens the cell imaging applications of CM3. As a cost‐effective and multifaceted imaging method, CM3 may find many promising applications in live‐cell imaging and material characterization. [ABSTRACT FROM AUTHOR]

The DNA damage response (DDR) is a fundamental readout for evaluating efficacy of cancer therapeutics, many of which target DNA associated processes. Current techniques to evaluate DDR rely on immunostaining for phosphorylated histone H2AX (γH2AX), which is an indicator of DNA double-strand breaks. While γH2AX immunostaining can provide a snapshot of DDR in fixed cell and tissue samples, this method is technically cumbersome due to temporal monitoring of DDR requiring timepoint replicates, extensive assay development efforts for 3D cell culture samples such as organoids, and time-consuming protocols for γH2AX immunostaining and its evaluation. The goal of this current study is to reduce overall burden on assay duration and development in non-small cell lung cancer (NSCLC) organoids by leveraging label-free multiphoton imaging. In this study, simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy was used to provide rich intracellular information based on endogenous contrasts. SLAM microscopy enables imaging of live samples eliminating the need to generate sacrificial sample replicates and has improved image acquisition in 3D space over conventional confocal microscopy. Predictive modeling between label-free SLAM microscopy and γH2AX immunostained images confirmed strong correlation between SLAM image features and γH2AX signal. Across multiple DNA targeting chemotherapeutics and multiple patient-derived NSCLC organoid lines, the optical redox ratio and third harmonic generation channels were used to robustly predict DDR. Imaging via SLAM microscopy can be used to more rapidly predict DDR in live 3D NSCLC organoids with minimal sample handling and without labeling.

Abstract The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the functional dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over 5 days, we observed increased dynamics in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize microbial dynamics within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial dynamics and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture.

Breast cancer often necessitates surgical interventions such as breast-conserving surgery or mastectomy. In these surgeries, sentinel lymph node (SLN) samples are often excised for histopathological examination to ascertain the presence of cancer metastasis. Despite its importance, traditional hematoxylin and eosin (H&E) staining, considerably prolongs the operation because of its complex processing requirements. Ultraviolet photoacoustic microscopy (UV-PAM) has emerged as a solution for bypassing the necessity of tissue staining or sectioning. However, its clinical application has been hindered by imaging speed. To overcome this challenge, we have developed a fast-scanning, reflection-mode UV-PAM designed for histopathology without staining based on high-sensitivity, wide-vision optical ultrasound detection. A specimen area of around 12 mm2 can be scanned in 8 min with a lateral resolution of 1.5 μm. To enhance imaging speed, multi-focal PAM was implemented, resulting in a fourfold acceleration. This PAM technique has been utilized in SLN biopsy to differentiate cancerous tissue in breast cancer patients.

The increasing global demand for food, coupled with concerns about the environmental impact of synthetic fertilizers, underscores the urgency of developing sustainable agricultural practices. Nitrogen-fixing bacteria, known as diazotrophs, offer a potential solution by converting atmospheric nitrogen into bioavailable forms, reducing the reliance on synthetic fertilizers. However, a deeper understanding of their interactions with plants and other microbes is needed. In this study, we introduce a recently developed label-free 3D quantitative phase imaging technology called dynamic quantitative oblique back-illumination microscopy (DqOBM) to assess the functional dynamic activity of diazotrophs in vitro and in situ. Our experiments involved three different diazotrophs (Sinorhizobium meliloti, Azotobacter vinelandii, and Rahnella aquatilis) cultured on media with amendments of carbon and nitrogen sources. Over 5 days, we observed increased dynamics in nutrient-amended media. These results suggest that the observed bacterial dynamics correlate with their metabolic activity. Furthermore, we applied qOBM to visualize microbial dynamics within the root cap and elongation zone of Arabidopsis thaliana primary roots. This allowed us to identify distinct areas of microbial infiltration in plant roots without the need for fluorescent markers. Our findings demonstrate that DqOBM can effectively characterize microbial dynamics and provide insights into plant-microbe interactions in situ, offering a valuable tool for advancing our understanding of sustainable agriculture. [ABSTRACT FROM AUTHOR]

Significance: Label-free nonlinear optical microscopy has become a powerful tool for biomedical research. However, the possible photodamage risk hinders further clinical applications. Aim: To reduce these adverse effects, we constructed a new platform of simultaneous label-free autofluorescence multi-harmonic (SLAM) microscopy, featuring four-channel multimodal imaging, inline photodamage monitoring, and pulse repetition-rate tuning. Approach: Using a large-core birefringent photonic crystal fiber for spectral broadening and a prism compressor for pulse pre-chirping, this system allows users to independently adjust pulse width, repetition rate, and energy, which is useful for optimizing imaging conditions towards no/minimal photodamage. Results: It demonstrates label-free multichannel imaging at one excitation pulse per image pixel and thus paves the way for improving the imaging speed by a faster optical scanner with a low risk of nonlinear photodamage. Moreover, the system grants users the flexibility to autonomously fine-tune repetition rate, pulse width, and average power, free from interference, ensuring the discovery of optimal imaging conditions with high SNR and minimal phototoxicity across various applications. Conclusions: The combination of a stable laser source, independently tunable ultrashort pulse, photodamage monitoring features, and a compact design makes this new system a robust, powerful, and user-friendly imaging platform. [ABSTRACT FROM AUTHOR]

Medical applications of optical technology have increased tremendously in recent decades. Label-free techniques have the unique advantage of investigating biological samples in vivo without introducing exogenous agents. This is especially beneficial for a rapid clinical translation as it reduces the need for toxicity studies and regulatory approval for exogenous labels. Emerging applications have utilized label-free optical technology for screening, diagnosis, and surgical guidance. Advancements in detection technology and rapid improvements in artificial intelligence have expedited the clinical implementation of some optical technologies. Among numerous biomedical application areas, middle-ear disease is a unique space where label-free technology has great potential. The middle ear has a unique anatomical location that can be accessed through a dark channel, the external auditory canal; it can be sampled through a tympanic membrane of approximately 100 microns in thickness. The tympanic membrane is the only membrane in the body that is surrounded by air on both sides, under normal conditions. Despite these favorable characteristics, current examination modalities for middle-ear space utilize century-old technology such as white-light otoscopy. This paper reviews existing label-free imaging technologies and their current progress in visualizing middle-ear diseases. We discuss potential opportunities, barriers, and practical considerations when transitioning label-free technology to clinical applications. [ABSTRACT FROM AUTHOR]

A new label‐free imaging flow cytometry method for noninvasive and automated biological cell classification is presented. Each cell is rolled during flow, and its off‐axis holograms from multiple viewpoints are acquired. Using the reconstructed quantitative phase profiles of the cell projections, highly discriminating features, enabling cell detection, classification, and differentiation, are extracted via a modified ResNet‐18 deep convolutional neural network architecture. The model is first validated by classifying metastatic breast carcinoma cells (MCF‐7) and normal human mammary epithelial cells (MCF‐10A). An increase in classification accuracy by 1% is achieved when processing five interferometric projections versus processing a single interferometric projection. This model is further tested on four types of white blood cells and exhibits an accuracy increase of 5% when processing 12 interferometric projections versus processing a single interferometric projection. This approach is shown to be superior to that of using conventional 2D‐rotation augmentation, and can be used to decrease substantially the number of cell examples needed for training the classification model without impairing the results. This novel concept has great potential to be incorporated into label‐free imaging flow cytometry and improve cell classification, and be used to detect various types of medical conditions and diseases. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is a major risk for the aging population. The pathological hallmarks of AD-an abnormal deposition of amyloid β-protein (Aβ) and phosphorylated tau (pTau)-have been demonstrated in the retinas of AD patients, including in prodromal patients with mild cognitive impairment (MCI). Aβ pathology, especially the accumulation of the amyloidogenic 42-residue long alloform (Aβ42), is considered an early and specific sign of AD, and together with tauopathy, confirms AD diagnosis. To visualize retinal Aβ and pTau, state-of-the-art methods use fluorescence. However, administering contrast agents complicates the imaging procedure. To address this problem from fundamentals, ex-vivo studies were performed to develop a label-free hyperspectral imaging method to detect the spectral signatures of Aβ42 and pS396-Tau, and predicted their abundance in retinal cross-sections. For the first time, we reported the spectral signature of pTau and demonstrated an accurate prediction of Aβ and pTau distribution powered by deep learning. We expect our finding will lay the groundwork for label-free detection of AD.

Adoptive T lymphocyte (T cell) transfer and tumour‐specific peptide vaccines are innovative cancer therapies. An accurate assessment of the specific reactivity of T cell receptors (TCRs) to tumour antigens is required because of the high heterogeneity of tumour cells and the immunosuppressive tumour microenvironment. In this study, we report a label‐free electrochemiluminescence (ECL) imaging approach for recognising and discriminating between TCRs and tumour‐specific antigens by imaging the immune synapses of T cells. Various T cell stimuli, including agonistic antibodies, auxiliary molecules, and tumour‐specific antigens, were modified on the electrode's surface to allow for their interaction with T cells bearing different TCRs. The formation of immune synapses activated by specific stimuli produced a negative (shadow) ECL image, from which T cell antigen recognition and discrimination were evaluated by analysing the spreading area and the recognition intensity of T cells. This approach provides an easy way to assess TCR‐antigen specificity and screen both of them for immunotherapies. [ABSTRACT FROM AUTHOR]

Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state‐of‐the‐art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label‐free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction‐limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super‐resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near‐field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere‐assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field. [ABSTRACT FROM AUTHOR]

We demonstrate label‐free imaging of genetically induced hepatocellular carcinoma (HCC) in a murine model provided by two‐ and three‐photon fluorescence microscopy of endogenous fluorophores excited at the central wavelengths of 790, 980 and 1250 nm and reinforced by second and third harmonic generation microscopy. We show, that autofluorescence imaging presents abundant information about cell arrangement and lipid accumulation in hepatocytes and hepatic stellate cells (HSCs), harmonics generation microscopy provides a versatile tool for fibrogenesis and steatosis study. Multimodal images may be performed by a single ultrafast laser source at 1250 nm falling in tissue transparency window. Various grades of HCC are examined revealing fibrosis, steatosis, liver cell dysplasia, activation of HSCs and hepatocyte necrosis, that shows a great ability of multimodal label‐free microscopy to intravital visualization of liver pathology development. [ABSTRACT FROM AUTHOR]

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy. [ABSTRACT FROM AUTHOR]

A new label‐free imaging flow cytometry method for noninvasive and automated biological cell classification is presented. Each cell is rolled during flow, and its off‐axis holograms from multiple viewpoints are acquired. Using the reconstructed quantitative phase profiles of the cell projections, highly discriminating features, enabling cell detection, classification, and differentiation, are extracted via a modified ResNet‐18 deep convolutional neural network architecture. The model is first validated by classifying metastatic breast carcinoma cells (MCF‐7) and normal human mammary epithelial cells (MCF‐10A). An increase in classification accuracy by 1% is achieved when processing five interferometric projections versus processing a single interferometric projection. This model is further tested on four types of white blood cells and exhibits an accuracy increase of 5% when processing 12 interferometric projections versus processing a single interferometric projection. This approach is shown to be superior to that of using conventional 2D‐rotation augmentation, and can be used to decrease substantially the number of cell examples needed for training the classification model without impairing the results. This novel concept has great potential to be incorporated into label‐free imaging flow cytometry and improve cell classification, and be used to detect various types of medical conditions and diseases.

Label-free and multiphoton micro-endoscopy can transform clinical histopathology by providing an in situ tool for diagnostic imaging and surgical treatment in diseases such as cancer. Key to a multiphoton imaging-based micro-endoscopic device is the optical fiber, for distortion-free and efficient delivery of ultra-short laser pulses to the sample and effective signal collection. In this work, we study a new hollow-core (air-filled) double-clad anti-resonant fiber (DC-ARF) as a high-performance candidate for multiphoton micro-endoscopy. We compare the fiber characteristics of the DC-ARF with a single-clad anti-resonant fiber (SC-ARF) and a solid core fiber (SCF). In this work, while the DC-ARF and the SC-ARF enable low-loss (−1), close to dispersion-free excitation pulse delivery (2000% of pulse width increase at 900 nm per 1 m fiber). An ideal optical fiber endoscope needs to be several meters long and should enable both excitation and collection through the fiber. Therefore, we performed multiphoton imaging on endoscopy-compatible 1 m and 3 m lengths of fiber in the back-scattered geometry, wherein the signals were collected either directly (non-descanned detection) or through the fiber (descanned detection). Second harmonic images were collected from barium titanate crystals as well as from biological samples (mouse tail tendon). In non-descanned detection conditions, the ARFs outperformed the SCF by up to 10 times in terms of signal-to-noise ratio of images. Significantly, only the DC-ARF, due to its high numerical aperture (NA) of 0.45 and wide-collection bandwidth (>1 µm), could provide images in the de-scanned detection configuration desirable for endoscopy. Thus, our systematic characterization and comparison of different optical fibers under different image collection configurations, confirms and establishes the utility of DC-ARFs for high-performing label-free multiphoton imaging-based micro-endoscopy.

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy.

Blood‐circulating exosomes as a disease biomarker have great potential in clinical applications as they contain molecular information about their parental cells. However, label‐free characterization of exosomes is challenging due to their small size. Without labeling, exosomes are virtually indistinguishable from other entities of similar size. Over recent years, several techniques have been developed to overcome the existing challenges. This article demonstrates a new label‐free approach based on dynamic PlAsmonic NanO‐apeRture lAbel‐free iMAging (D‐PANORAMA), a bright‐field technique implemented on arrayed gold nanodisks on invisible substrates (AGNIS). PANORAMA provides high surface sensitivity and has been shown to count single 25 nm polystyrene beads previously. Herein, it is shown that using the dynamic imaging mode, D‐PANORAMA can yield 3D, subdiffraction limited localization of individual 25 nm beads. Furthermore, D‐PANORAMA's capability to size, count, and localize the 3D, subdiffraction limited position of individual exosomes is demonstrated as they bind to the AGNIS surface. The importance of both the in‐plane and out‐of‐plane localization, which exploit the synergy of 2D imaging and the intensity contrast, is emphasized. [ABSTRACT FROM AUTHOR]

Toxoplasma gondii is a widespread single-celled intracellular eukaryotic apicomplexan protozoan parasite primarily associated with mammalian foetal impairment and miscarriage, including in humans. Is estimated that approximately one third of the human population worldwide is infected by this parasite. Here we used cutting-edge, label-free 3D quantitative optical diffraction holotomography to capture and evaluate the Toxoplasma lytic cycle (invasion, proliferation and egress) in real-time based on the refractive index distribution. In addition, we used this technology to analyse an engineered CRISPR-Cas9 Toxoplasma mutant to reveal differences in cellular physical properties when compared to the parental line. Collectively, these data support the use of holotomography as a powerful tool for the study of protozoan parasites and their interactions with their host cells. [ABSTRACT FROM AUTHOR]

Medical applications of optical technology have increased tremendously in recent decades. Label-free techniques have the unique advantage of investigating biological samples in vivo without introducing exogenous agents. This is especially beneficial for a rapid clinical translation as it reduces the need for toxicity studies and regulatory approval for exogenous labels. Emerging applications have utilized label-free optical technology for screening, diagnosis, and surgical guidance. Advancements in detection technology and rapid improvements in artificial intelligence have expedited the clinical implementation of some optical technologies. Among numerous biomedical application areas, middle-ear disease is a unique space where label-free technology has great potential. The middle ear has a unique anatomical location that can be accessed through a dark channel, the external auditory canal; it can be sampled through a tympanic membrane of approximately 100 microns in thickness. The tympanic membrane is the only membrane in the body that is surrounded by air on both sides, under normal conditions. Despite these favorable characteristics, current examination modalities for middle-ear space utilize century-old technology such as white-light otoscopy. This paper reviews existing label-free imaging technologies and their current progress in visualizing middle-ear diseases. We discuss potential opportunities, barriers, and practical considerations when transitioning label-free technology to clinical applications.

Blood‐circulating exosomes as a disease biomarker have great potential in clinical applications as they contain molecular information about their parental cells. However, label‐free characterization of exosomes is challenging due to their small size. Without labeling, exosomes are virtually indistinguishable from other entities of similar size. Over recent years, several techniques have been developed to overcome the existing challenges. This article demonstrates a new label‐free approach based on dynamic PlAsmonic NanO‐apeRture lAbel‐free iMAging (D‐PANORAMA), a bright‐field technique implemented on arrayed gold nanodisks on invisible substrates (AGNIS). PANORAMA provides high surface sensitivity and has been shown to count single 25 nm polystyrene beads previously. Herein, it is shown that using the dynamic imaging mode, D‐PANORAMA can yield 3D, subdiffraction limited localization of individual 25 nm beads. Furthermore, D‐PANORAMA's capability to size, count, and localize the 3D, subdiffraction limited position of individual exosomes is demonstrated as they bind to the AGNIS surface. The importance of both the in‐plane and out‐of‐plane localization, which exploit the synergy of 2D imaging and the intensity contrast, is emphasized.

Toxoplasma gondii is a widespread single-celled intracellular eukaryotic apicomplexan protozoan parasite primarily associated with mammalian foetal impairment and miscarriage, including in humans. Is estimated that approximately one third of the human population worldwide is infected by this parasite. Here we used cutting-edge, label-free 3D quantitative optical diffraction holotomography to capture and evaluate the Toxoplasma lytic cycle (invasion, proliferation and egress) in real-time based on the refractive index distribution. In addition, we used this technology to analyse an engineered CRISPR-Cas9 Toxoplasma mutant to reveal differences in cellular physical properties when compared to the parental line. Collectively, these data support the use of holotomography as a powerful tool for the study of protozoan parasites and their interactions with their host cells.

Hematology analysis, a common clinical test for screening various diseases, has conventionally required a chemical staining process that is time-consuming and labor-intensive. To reduce the costs of chemical staining, label-free imaging can be utilized in hematology analysis. In this work, we exploit optical diffraction tomography and the fully convolutional one-stage object detector or FCOS, a deep learning architecture for object detection, to develop a label-free hematology analysis framework. Detected cells are classified into four groups: red blood cell, abnormal red blood cell, platelet, and white blood cell. In the results, the trained object detection model showed superior detection performance for blood cells in refractive index tomograms (0.977 mAP) and also showed high accuracy in the four-class classification of blood cells (0.9708 weighted F1 score, 0.9712 total accuracy). For further verification, mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) were compared with values obtained from reference hematology equipment, with our results showing reasonable correlation in both MCV (0.905) and MCH (0.889). This study provides a successful demonstration of the proposed framework in detecting and classifying blood cells using optical diffraction tomography for label-free hematology analysis.

Osteomyelitis is an infection of the bone that is often difficult to treat and causes a significant healthcare burden. Staphylococcus aureus is the most common pathogen causing osteomyelitis. Osteomyelitis mouse models have been established to gain further insights into the pathogenesis and host response. Here, we use an established S. aureus hematogenous osteomyelitis mouse model to investigate morphological tissue changes and bacterial localization in chronic osteomyelitis with a focus on the pelvis. X-ray imaging was performed to follow the disease progression. Six weeks post infection, when osteomyelitis had manifested itself with a macroscopically visible bone deformation in the pelvis, we used two orthogonal methods, namely fluorescence imaging and label-free Raman spectroscopy, to characterise tissue changes on a microscopic scale and to localise bacteria in different tissue regions. Hematoxylin and eosin as well as Gram staining were performed as a reference method. We could detect all signs of a chronically florid tissue infection with osseous and soft tissue changes as well as with different inflammatory infiltrate patterns. Large lesions dominated in the investigated tissue samples. Bacteria were found to form abscesses and were distributed in high numbers in the lesion, where they could occasionally also be detected intracellularly. In addition, bacteria were found in lower numbers in surrounding muscle tissue and even in lower numbers in trabecular bone tissue. The Raman spectroscopic imaging revealed a metabolic state of the bacteria with reduced activity in agreement with small cell variants found in other studies. In conclusion, we present novel optical methods to characterise bone infections, including inflammatory host tissue reactions and bacterial adaptation. [ABSTRACT FROM AUTHOR]

Time-lapse light microscopy combined with in vitro neuronal cultures has provided a significant contribution to the field of Developmental Neuroscience. The establishment of the neuronal polarity, i.e., formation of axons and dendrites, key structures responsible for inter-neuronal signaling, was described in 1988 by Dotti, Sullivan and Banker in a milestone paper that continues to be cited 30 years later. In the following decades, numerous fluorescently labeled tags and dyes were developed for live cell imaging, providing tremendous advancements in terms of resolution, acquisition speed and the ability to track specific cell structures. However, long-term recordings with fluorescence-based approaches remain challenging because of light-induced phototoxicity and/or interference of tags with cell physiology (e.g., perturbed cytoskeletal dynamics) resulting in compromised cell viability leading to cell death. Therefore, a label-free approach remains the most desirable method in long-term imaging of living neurons. In this paper we will focus on label-free high-resolution methods that can be successfully used over a prolonged period. We propose novel tools such as scanning ion conductance microscopy (SICM) or digital holography microscopy (DHM) that could provide new insights into live cell dynamics during neuronal development and regeneration after injury. [ABSTRACT FROM AUTHOR]

Simple Summary: Efforts to identify lesions of head and neck cancers with high malignant potential are important to improve patient outcomes, as 5-year survival rates remain low due to late detection. Optical imaging approaches that provide direct cellular and structural atypia could be helpful in detection and pathology guidance. This study evaluates the method of multiphoton autofluorescence microscopy (MPAM) for its ability to reveal atypia associated with neoplasia in resected tumor samples without the need for exogenous dyes or tissue sectioning, showing a correlation with the corresponding histology. Depth-resolved label-free optical imaging by the method of multiphoton autofluorescence microscopy (MPAM) may offer new ways to examine cellular and extracellular atypia associated with epithelial squamous cell carcinoma (SCC). MPAM was evaluated for its ability to identify cellular and microstructural atypia in head and neck tissues from resected discarded tumor tissue. Three-dimensional image volumes were obtained from tissues from the floor of the mouth, tongue, and larynx, and were then processed for histology. MPAM micrographs were evaluated for qualitative metrics of cell atypia and quantitative measures associated with nuclear pleomorphism. Statistical analyses correlated MPAM endpoints with histological grade from each imaged site. Cellular overcrowding, discohesion, anisonucleosis, and multinucleated cells, as observed through MPAM, were found to be statistically associated with dysplasia and SCC grading, but not in histologically benign regions. A quantitative measure of the coefficient of variance in nuclear size in SCC and dysplasia was statistically elevated above histologically benign regions. MPAM also allowed for the identification of cellular heterogeneity across transitional areas and other features, such as inflammatory infiltrates. In the future, MPAM could be evaluated for the non-invasive detection of neoplasia, possibly as an adjunct to traditional conventional examination and biopsy. [ABSTRACT FROM AUTHOR]

Human stefin B, a member of the cystatin family of cysteine protease inhibitors, tends to form amyloid fibrils under relatively mild conditions, which is why it is used as a model protein to study amyloid fibrillation. Here, we show for the first time that bundles of amyloid fibrils, i.e., helically twisted ribbons, formed by human stefin B exhibit birefringence. This physical property is commonly observed in amyloid fibrils when stained with Congo red. However, we show that the fibrils arrange in regular anisotropic arrays and no staining is required. They share this property with anisotropic protein crystals, structured protein arrays such as tubulin and myosin, and other anisotropic elongated materials, such as textile fibres and liquid crystals. In certain macroscopic arrangements of amyloid fibrils, not only birefringence is observed, but also enhanced emission of intrinsic fluorescence, implying a possibility to detect amyloid fibrils with no labels by using optical microscopy. In our case, no enhancement of intrinsic tyrosine fluorescence was observed at 303 nm; instead, an additional fluorescence emission peak appeared at 425 to 430 nm. We believe that both phenomena, birefringence and fluorescence emission in the deep blue, should be further explored with this and other amyloidogenic proteins. This may allow the development of label-free detection methods for amyloid fibrils of different origins. [ABSTRACT FROM AUTHOR]

Lensless holographic microscopy (LHM) comes out as a promising label-free technique since it supplies high-quality imaging and adaptive magnification in a lens-free, compact and cost-effective way. Compact sizes and reduced prices of LHMs make them a perfect instrument for point-of-care diagnosis and increase their usability in limited-resource laboratories, remote areas, and poor countries. LHM can provide excellent intensity and phase imaging when the twin image is removed. In that sense, multi-illumination single-holographic-exposure lensless Fresnel (MISHELF) microscopy appears as a single-shot and phase-retrieved imaging technique employing multiple illumination/detection channels and a fast-iterative phase-retrieval algorithm. In this contribution, we review MISHELF microscopy through the description of the principles, the analysis of the performance, the presentation of the microscope prototypes and the inclusion of the main biomedical applications reported so far. [ABSTRACT FROM AUTHOR]

The study of highly heterogeneous tumor cells, especially acute myeloid leukemia (AML) cells, usually relies on invasive analytical methods such as morphology, immunology, cytogenetics, and molecular biology classification, which are complex and time-consuming to perform. Mortality is high if patients are not diagnosed in a timely manner, so rapid label-free analysis of gene expression and metabolites within single-cell substructures is extremely important for clinical diagnosis and treatment. As a label-free and non-destructive vibrational detection technique, spontaneous Raman scattering provides molecular information across the full spectrum of the cell but lacks rapid imaging localization capabilities. In contrast, stimulated Raman scattering (SRS) provides a high-speed, high-resolution imaging view that can offer real-time subcellular localization assistance for spontaneous Raman spectroscopic detection. In this paper, we combined multi-color SRS microscopy with spontaneous Raman to develop a co-localized Raman imaging and spectral detection system (CRIS) for high-speed chemical imaging and quantitative spectral analysis of subcellular structures. Combined with multivariate statistical analysis methods, CRIS efficiently differentiated AML from normal leukocytes with an accuracy of 98.1 % and revealed the differences in the composition of nuclei and cytoplasm of AML relative to normal leukocytes. Compared to conventional Raman spectroscopy blind sampling without imaging localization, CRIS increased the efficiency of single-cell detection by at least three times. In addition, using the same approach for further identification of AML subtypes M2 and M3, we demonstrated that intracytoplasmic differential expression of proteins is a marker for their rapid and accurate classifying. CRIS analysis methods are expected to pave the way for clinical translation of rapid tumor cell identification. [Display omitted] • A multi-dimensional analysis method of Raman imaging and spectral analysis for efficient identification of tumor cells. • Compared with conventional Raman detection, this method improves the identification efficiency and accuracy of cancer cells. • This method can quickly obtain Raman spectral information of components within subcellular structures without labeling. • This method shows high accuracy in AML identification and subtype classification. [ABSTRACT FROM AUTHOR]

Although the effects on neural activation and glucose consumption caused by opiates such as morphine are known, the metabolic machinery underlying opioid use and misuse is not fully explored. Multiphoton microscopy (MPM) techniques have been developed for optical imaging at high spatial resolution. Despite the increased use of MPM for neural imaging, the use of intrinsic optical contrast has seen minimal use in neuroscience. We present a label-free, multimodal microscopy technique for metabolic profiling of murine brain tissue following incubation with morphine sulfate (MSO 4). We evaluate two- and three-photon excited autofluorescence, and second and third harmonic generation to determine meaningful intrinsic contrast mechanisms in brain tissue using simultaneous label-free, autofluorescence multi-harmonic (SLAM) microscopy. Regional differences quantified in the cortex, caudate, and thalamus of the brain demonstrate region-specific changes to metabolic profiles measured from FAD intensity, along with brain-wide quantification. While the overall intensity of FAD signal significantly decreased after morphine incubation, this metabolic molecule accumulated near the nucleus accumbens. Histopathology requires tissue fixation and staining to determine cell type and morphology, lacking information about cellular metabolism. Tools such as fMRI or PET imaging have been widely used, but lack cellular resolution. SLAM microscopy obviates the need for tissue preparation, permitting immediate use and imaging of tissue with subcellular resolution in its native environment. This study demonstrates the utility of SLAM microscopy for label-free investigations of neural metabolism, especially the intensity changes in FAD autofluorescence and structural morphology from third-harmonic generation. • Neural metabolism via NAD(P)H and FAD was measured with a label-free microscope. • A consistent brain-wide decrease in FAD signal followed morphine incubation. • We observed a notable increase in FAD signal near the nucleus accumbens. • Label-free multiphoton microscopy shares unique insights to neural metabolism. [ABSTRACT FROM AUTHOR]

Uveal melanoma (UM) is the most frequent primary intraocular malignancy in adults, characterized by melanin depositions in melanocytes located in the uveal tract in the eyes. Differentiation of melanin species (eumelanin and pheomelanin) is crucial in the diagnosis and management of UM, yet it remains inaccessible for conventional histology. Here, we report that femtosecond time-resolved pump-probe microscopy could provide label-free and chemical-specific detection of melanin species in human UM based on their distinct transient relaxation dynamics at the subpicosecond timescale. The method is capable of delineating the interface between melanoma and paracancerous regions on various tissue conditions, including frozen sections, paraffin sections, and fresh tissues. Moreover, transcriptome sequencing was conducted to confirm the active eumelanin synthesis in UM. Our results may hold potential for sensitive detection of tumor boundaries and biomedical research on melanin metabolism in UM. [ABSTRACT FROM AUTHOR]

Quantitative phase microscopy (QPM) has been emerged as an indispensable diagnostic and characterization tool in biomedical imaging with its characteristic nature of label‐free, noninvasive, and real time imaging modality. The integration of holography to the conventional microscopy opens new advancements in QPM featuring high‐resolution and quantitative three‐dimensional image reconstruction. However, the holography schemes suffer in space‐bandwidth and time‐bandwidth issues in the off‐axis and phase‐shifting configuration, respectively. Here, we introduce an on‐axis phase‐shifting holography based QPM system with single‐shot imaging capability. The technique utilizes the Fizeau interferometry scheme in combination with polarization phase‐shifting and space‐division multiplexing to achieve the single‐shot recording of the multiple phase‐shifted holograms. Moreover, the high‐speed imaging capability with instantaneous recording of spatially phase shifted holograms offers the flexible utilization of the approach in dynamic quantitative phase imaging with robust phase stability. We experimentally demonstrated the validity of the approach by quantitative phase imaging and depth‐resolved imaging of paramecium cells. Furthermore, the technique is applied to the phase imaging and quantitative parameter estimation of red blood cells. This integration of a Fizeau‐based phase‐shifting scheme to the optical microscopy enables a simple and robust tool for the investigations of engineered and biological specimen with real‐time quantitative analysis. [ABSTRACT FROM AUTHOR]

The DNA damage response (DDR) is a fundamental readout for evaluating efficacy of cancer therapeutics, many of which target DNA associated processes. Current techniques to evaluate DDR rely on immunostaining for phosphorylated histone H2AX (γH2AX), which is an indicator of DNA double-strand breaks. While γH2AX immunostaining can provide a snapshot of DDR in fixed cell and tissue samples, this method is technically cumbersome due to temporal monitoring of DDR requiring timepoint replicates, extensive assay development efforts for 3D cell culture samples such as organoids, and time-consuming protocols for γH2AX immunostaining and its evaluation. The goal of this current study is to reduce overall burden on assay duration and development in non-small cell lung cancer (NSCLC) organoids by leveraging label-free multiphoton imaging. In this study, simultaneous label-free autofluorescence multiharmonic (SLAM) microscopy was used to provide rich intracellular information based on endogenous contrasts. SLAM microscopy enables imaging of live samples eliminating the need to generate sacrificial sample replicates and has improved image acquisition in 3D space over conventional confocal microscopy. Predictive modeling between label-free SLAM microscopy and γH2AX immunostained images confirmed strong correlation between SLAM image features and γH2AX signal. Across multiple DNA targeting chemotherapeutics and multiple patient-derived NSCLC organoid lines, the optical redox ratio and third harmonic generation channels were used to robustly predict DDR. Imaging via SLAM microscopy can be used to more rapidly predict DDR in live 3D NSCLC organoids with minimal sample handling and without labeling., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Stephen Boppart is co-founder of and holds equity interest in LiveBx, LLC, which specializes in consulting and building novel multimodal multiphoton imaging systems., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Although quantitative analysis of biological images demands precise extraction of specific organelles or cells, it remains challenging in broad-field grayscale images, where traditional thresholding methods have been hampered due to complex image features. Nevertheless, rapidly growing artificial intelligence technology is overcoming obstacles. We previously reported the fine-tuned apodized phase-contrast microscopy system to capture high-resolution, label-free images of organelle dynamics in unstained living cells (Shimasaki, K. et al. (2024). Cell Struct. Funct., 49: 21-29). We here showed machine learning-based segmentation models for subcellular targeted objects in phase-contrast images using fluorescent markers as origins of ground truth masks. This method enables accurate segmentation of organelles in high-resolution phase-contrast images, providing a practical framework for studying cellular dynamics in unstained living cells.Key words: label-free imaging, organelle dynamics, apodized phase contrast, deep learning-based segmentation.

Significance: Measuring changes in cellular structure and organelles is crucial for understanding disease progression and cellular responses to treatments. A label-free imaging method can aid in advancing biomedical research and therapeutic strategies., Aim: This study introduces a computational darkfield imaging approach named quadrant darkfield (QDF) to separate smaller cellular features from large structures, enabling label-free imaging of cell organelles and structures in living cells., Approach: Using a programmable LED array as illumination source, we vary the direction of illumination to encode additional information about the feature size within cells. This is possible due to the varying level of directional scattering produced by features based on their sizes relative to the wavelength of light used., Results: QDF successfully resolved small cellular features without interference from larger structures. QDF signal is more consistent during cell shape changes than traditional darkfield. QDF signals correlate with flow cytometry side scatter measurements, effectively differentiating cells by organelle content., Conclusions: QDF imaging enhances the study of subcellular structures in living cells, offering improved quantification of organelle content compared to darkfield without labels. This method can be simultaneously performed with other techniques such as quantitative phase imaging to generate a multidimensional picture of living cells in real-time., Competing Interests: Disclosures The authors declare no conflict of interest regarding this work.