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. We developed an integrated platform to enable robust and long-term culturing of 3D brain organoids. We designed a mesofluidic bioreactor device based on a reaction-diffusion scaling theory, which achieves robust media exchange for sufficient nutrient delivery in long-term culture. We integrated this device 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 our mesofluidic bioreactor promoted organoid development while reducing cell death. Our platform thus offers a generalizable tool to establish reproducible culture standards for 3D cellular systems for a variety of applications beyond brain organoids.

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.

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.

UNASSIGNED: Heart disease is the leading cause of death in the United States, yet research is limited by the inability to culture primary cardiac cells. Cardiomyocytes (CMs) derived from human induced pluripotent stem cells (iPSCs) are a promising solution for drug screening and disease modeling.
UNASSIGNED: Induced pluripotent stem cell-derived CM (iPSC-CM) differentiation and maturation studies typically use heterogeneous substrates for growth and destructive verification methods. Reproducible, tunable substrates and touch-free monitoring are needed to identify ideal conditions to produce homogenous, functional CMs.
UNASSIGNED: We generated synthetic polyethylene glycol-based hydrogels for iPSC-CM differentiation and maturation. Peptide concentrations, combinations, and gel stiffness were tuned independently. Label-free optical redox imaging (ORI) was performed on a widefield microscope in a 96-well screen of gel formulations. We performed live-cell imaging throughout differentiation and early to late maturation to identify key metabolic shifts.
UNASSIGNED: Label-free ORI confirmed the expected metabolic shifts toward oxidative phosphorylation throughout the differentiation and maturation processes of iPSC-CMs on synthetic hydrogels. Furthermore, ORI distinguished high and low differentiation efficiency cell batches in the cardiac progenitor stage.
UNASSIGNED: We established a workflow for medium throughput screening of synthetic hydrogel conditions with the ability to perform repeated live-cell measurements and confirm expected metabolic shifts. These methods have implications for reproducible iPSC-CM generation in biomanufacturing.

UNASSIGNED: Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to 75   frames / s ). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining.
UNASSIGNED: We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images.
UNASSIGNED: Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, viz., M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability.
UNASSIGNED: We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves 912.3    lp / mm , and our analysis scheme accurately retrieves the phase with a high correlation coefficient ( ∼ 0.99 ), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be 0.55    μ m for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings.
UNASSIGNED: Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.

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.

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 which need to be overcome to break the classical diffraction limit of the LFSR 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 which 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.

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.

Polyene macrolides are antifungal substances, which interact with cells in a sterol-dependent manner. While being widely used, their mode of action is poorly understood. Here, we employ ultraviolet-sensitive (UV) microscopy to show that the antifungal polyene natamycin binds to the yeast plasma membrane (PM) and causes permeation of propidium iodide into cells. Right before membrane permeability became compromised, we observed clustering of natamycin in the PM that was independent of PM protein domains. Aggregation of natamycin was paralleled by cell deformation and membrane blebbing as revealed by soft X-ray microscopy. Substituting ergosterol for cholesterol decreased natamycin binding and caused a reduced clustering of natamycin in the PM. Blocking of ergosterol synthesis necessitates sterol import via the ABC transporters Aus1/Pdr11 to ensure natamycin binding. Quantitative imaging of dehydroergosterol (DHE) and cholestatrienol (CTL), two analogues of ergosterol and cholesterol, respectively, revealed a largely homogeneous lateral sterol distribution in the PM, ruling out that natamycin binds to pre-assembled sterol domains. Depletion of sphingolipids using myriocin increased natamycin binding to yeast cells, likely by increasing the ergosterol fraction in the outer PM leaflet. Importantly, binding and membrane aggregation of natamycin was paralleled by a decrease of the dipole potential in the PM, and this effect was enhanced in the presence of myriocin. We conclude that ergosterol promotes binding and aggregation of natamycin in the yeast PM, which can be synergistically enhanced by inhibitors of sphingolipid synthesis.

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.