Small Methods

Despite rapid advances in diagnostic and imaging technologies, a method for noninvasive monitoring of the immune system does not exist. The standard white blood cell count (WBCC), a key clinical measure for assessing patients health, requires drawing blood, which poses inherent risks for secondary infection and anemia in vulnerable patient populations. In addition, the specialized equipment, expertise, and infrastructure are not always available in resource-poor settings. Here we present a method for noninvasive and label-free WBCC by imaging human oral mucosa with a miniaturized oblique back-illumination microscope (mOBM). In a pilot study involving 34 healthy subjects, we validated our systems ability to detect and quantify circulating leukocytes and compared our image-based WBCC to standard laboratory measurements. The ability to perform noninvasive WBCC will enable real-time assessment of the immune status during infection and inflammation or in response to therapeutic intervention without repetitive blood sampling.

Understanding the spatial heterogeneity in blood vessel formation and development is crucial for various biomedical applications. Traditional methods for in-vitro microvessel segmentation rely on fluorescent labeling, which either interferes with the sample homeostasis, limits the study to a restricted set of precursor cells, or requires sample fixation, thus preventing live measurements. Moreover, these methods often focus on small, cropped images, neglecting global spatial heterogeneity of microvasculature, leading to biased data interpretation. To overcome these limitations, we present VascuMap, a deep-learning-based tool for label-free vessel segmentation and spatial analysis. VascuMap enables a comprehensive examination of entire vessel networks, capturing both morphological and topological features across the full vascular bed. Our method achieves high segmentation accuracy, comparable to the state-of-the-art fluorescence-based models. VascuMaps capabilities extend to characterizing vasculature generated from label-free patient-derived samples, a vital step towards personalized medicine. Its compatibility with widefield label-free microscopy also accelerates sample acquisition, making it ideal for high-throughput systems crucial for drug toxicity and safety screens.

Ultrasound-mediated blood-brain barrier (BBB) opening is promising for non-invasive, localized, and reversible drug delivery to the brain. However, the underlying mechanisms remain unclear, particularly at microscopic level in real time. Recently developed short-pulse ultrasound enhances safety by reducing side effects compared to conventional long-pulse ultrasound. Using vessel-mimicking microchannels cultured with brain endothelial monolayers, we directly observed bubble dynamics and cellular bioeffects under flow conditions. Intriguingly, cyclic jetting during stable cavitation occurs at long-pulse mode, accompanied by a few localized cell detachments and extensive sonoporation. In contrast, short-pulse ultrasound induced milder, uniform bubble dynamics, reversible sonoporation and calcium signaling, promoting safer BBB modulation. In vivo two-photon imaging and histology in mice confirmed these findings, showing that long-pulse ultrasound enabled higher drug delivery efficiency but caused localized endothelial damage, while short-pulse ultrasound facilitated uniform delivery and faster BBB recovery. The differential bubble dynamics and cellular responses correlated well between in vitro and in vivo models. This study establishes a cross-scale framework for real-time analysis of ultrasound-mediated BBB opening, revealing key biophysical factors governing safety and efficacy. The findings provide guidance for the optimization of ultrasound protocols for vascular drug delivery, with potential applications in treating brain tumors, neurodegenerative diseases, and other disorders.

Virtual staining is the current state-of-the-art computational technique to cleverly enhance intracellular specificity in unstained biological samples by using convolutional neural networks (CNNs) trained on co-registered pairs of unstained/stained images. While effective, this approach suffers from unpredictable biases inherent to fluorescence microscopy and encounters challenges when applied to flow cytometry data as it would require accurate co-registration on a huge number of images. Here, we present a novel method that exploits for the first time a Holotomography-driven learning to completely eliminate the need for co-registration. We demonstrate that training a CNN on a stain-free dataset of 3D refractive index tomograms of flowing cells elegantly unlocks stain-free intracellular specificity in quantitative phase imaging flow cytometry. This breakthrough, by circumventing the critical co-registration bottleneck, opens unprecedented perspectives for label-free, high-throughput imaging flow cytometry, offering a powerful new paradigm for advanced 2D and 3D single-cell analysis.

Whole-brain imaging has revolutionized neuroscience research, providing comprehensive insights into neural networks across the entire brain. This powerful approach has greatly advanced our understanding of brain functions and the mechanisms underlying various diseases. One primary challenge in whole-brain imaging technology is to achieve high-resolution observation of neural networks at large scales. Although Golgi method allows labeling random neurons in their entirety in the brain, visualizing individual dendritic trees, and tracing long-distance axonal projections, the lengthy processing time pose a limit on its use, i.e., staining a mouse whole-brain sample of just 300 mm3 takes over two weeks. Here, we developed a rapid staining technique for whole-brain neurons using high-pressure assisted Golgi (HP Golgi). This method significantly reduced the staining time for mouse whole-brain neurons from 16 days to only 4 days. We demonstrated the broad applicability of the HP Golgi method across various model organisms, achieving whole-brain neuronal staining in zebrafish, mice, and rats. Further, we successfully performed rapid staining of hippocampal neurons in an intact pig brain, which is difficult to achieve with the classic Golgi-Cox method. We also demonstrated that the combination of the HP Golgi method with synchrotron-based X-ray microscopy for high-resolution imaging of whole-brain neurons in mice. This HP Golgi method enables fast and high-resolution neuronal imaging in large model organisms, showcasing its broad applicability for diverse applications.

Fluorescence nanoscopy has become increasingly powerful for biomedical research, but it has historically afforded a small field-of-view (FOV) around 50 {micro}m x 50 {micro}m at once and more recently up to ~200 {micro}m x 200 {micro}m. Efforts to further increase the FOV in fluorescence nanoscopy have thus far relied on the use of fabricated waveguide substrates, adding cost and sample constraints on the applications. Here we report PRism-Illumination and Microfluidics-Enhanced DNA-PAINT (PRIME-PAINT) for multiplexed fluorescence nanoscopy across millimeter-scale FOVs. Built upon the well-established prism-type total internal reflection microscopy, PRIME-PAINT achieves robust single-molecule localization with up to ~520 {micro}m x 520 {micro}m single FOVs and 25-40 nm lateral resolutions. Through stitching, nanoscopic imaging over mm2 sample areas can be completed in as little as 40 minutes per target. An on-stage microfluidics chamber facilitates probe exchange for multiplexing and enhances image quality particularly for formalin-fixed paraffin-embedded (FFPE) tissue sections. We demonstrate the utility of PRIME-PAINT by analyzing ~106 caveolae structures in ~1,000 cells and imaging entire pancreatic cancer lesions from patient tissue biopsies. By imaging from nanometers to millimeters with multiplexity and broad sample compatibility, PRIME-PAINT will be useful for building multiscale, Google-Earth-like views of biological systems.

Live-cell imaging of cell surface topography and intracellular architecture is essential for understanding cellular function. However, conventional approaches often involve trade-offs between resolution, invasiveness, and volumetric coverage. Here, we present an integrated Scanning Ion Conductance Microscope and single-objective Oblique Plane Microscope (SICM-OPM) system that enables simultaneous non-contact topographical imaging and volumetric fluorescence imaging within the same live cell. Beyond correlative live imaging, the platform supports nanomechanical mapping with tens-of-nanometres resolution, fluorescence-guided localised molecular delivery via the SICM, and benefits from reduced photobleaching due to light-sheet excitation. We demonstrate this platforms capabilities by visualising imipramine-induced T-tubule remodelling in live cardiomyocytes, revealing subsurface detubulation while surface morphology remains preserved. Additionally, we show precision delivery of fluorescent cargos--including dextrans and -synuclein--into diatom and mammalian cells, alongside localised stiffness mapping to evaluate mechanical responses. We believe this technique opens new avenues for correlative structural, functional, and biophysical studies in live cells, with broad relevance to cell biology, neurodegeneration, and mechanobiology.

The analysis of nanoscopic species, such as proteins and colloidal assemblies, at the single-molecule level has become vital in many areas of fundamental and applied research. Approaches to increase the detection timescales for single molecules in solution without immobilising them onto a substrate surface and applying external fields are much sought after. Here we present an easy-to-implement and versatile nanofluidics-based approach that enables increased observational-timescale analysis of single biomacromolecules and nanoscale colloids in solution. We use two-photon-based hybrid lithography in conjunction with soft lithography to fabricate nanofluidic devices with nano-trapping geometries down to 100 nm in height. We provide a rigorous description and characterisation of the fabrication route that enables the writing of nanoscopic 3D structures directly in photoresist and allows for the integration of nano-trapping and nano-channel geometries within micro-channel devices. Using confocal fluorescence burst detection, we validated the functionality of particle confinement in our nano-trap geometries through measurement of particle residence times. All species under study, including nanoscale colloids, -synuclein oligomers, and double-stranded DNA, showed a three to five-fold increase in average residence time in the detection volume of nano-traps, due to the additional local steric confinement, in comparison to free space diffusion in a nearby micro-channel. Our approach thus opens-up the possibility for single-molecule studies at prolonged observational timescales to analyse and detect nanoparticles and protein assemblies in solution without the need for surface immobilisation.

Both the ultrastructures and dynamics of living erythrocyte membranes provide critical criteria for clinical diagnostics. However, it is challenging to simultaneously visualize these features at the single-molecule level due to the rigid photophysical requirements of different single-molecule imaging techniques. Herein, we rationally developed a far-red boron dipyrromethene membrane (BDP-Mem) probe that not only retained consistent and intensive single-molecule emission but also possessed the capability to photoswitch on cellular membranes. We also constructed a microfluidic platform for the noninvasive trapping and long-term imaging of nonadherent erythrocytes. By combining these advantageous technologies, super-resolution reconstruction and single-molecule tracking of living human RBC membranes were achieved at the molecular scale in a high-throughput fashion. Our integrated paradigm defines a quantitative approach for analyzing living RBC membranes under physiological and pathological conditions, improving imaging precisions and revealing new perspectives for future disease diagnostic approaches.

Neuron typing in intact brain sections demands 3D imaging reconciling thickness compatibility with large-area coverage--a persistent challenge for RNA imaging methods limited by either restricted fields-of-view (<1 mm2) or thin-section constraints (<20 m). Here we introduce oblique thick light-sheet microscopy integrated with spatiotemporal 3D localization, enabling multiplexed RNA imaging across 50 m-thick tissue sections and centimeter-scale regions. The 45{degrees} illumination geometry achieves optical-interference-free imaging in >100 m-thick tissues during single-plane scans, while a spatiotemporal localization algorithm recovers submicron resolution by pinpointing fluorescence in situ hybridization (FISH) spots within volumetric excitation. This strategy reveals layer-spanning neuronal distributions and region-specific expression gradients unattainable with conventional RNA imaging approaches. By resolving the historical trade-off between imaging depth and spatial coverage, our platform advances whole-brain transcriptomics, enabling 3D neuron typing capability critical for deciphering brain-wide cellular architectures.

Although many lab-on-chip applications require inch-sized devices with microscale feature resolution, achieving this via current 3D printing methods remains challenging due to inherent tradeoffs between print resolution, design complexity, and build sizes. Inspired by microscopes that can switch objectives to achieve multiscale imaging, we report a new optical printer coined as Multipath Projection Stereolithography (MPS) specifically designed for printing microfluidic devices. MPS is designed to switch between high-resolution (1xmode, [~]10{micro}m) and low-resolution (3x mode, [~]30{micro}m) optical paths to generate centimeter sized constructs (3cm x 6cm) with a feature resolution of [~]10{micro}m. Illumination and projection systems were designed, resin formulations were optimized, and slicing software was integrated with hardware with the goal of ease of use. Using a test-case of micromixers, we show user-defined CAD models can be directly input to an automated slicing software to define printing of low-resolution features via the 3x mode with embedded microscale fins via 1x mode. A new computational model, validated using experimental results, was used to simulate various fin designs and experiments were conducted to verify simulated mixing efficiencies. New 3D out-of-plane micromixer designs were simulated and tested. To show broad applications of MPS, multi-chambered chips and microfluidic devices with microtraps were also printed. Overall, MPS can be a new fabrication tool to rapidly print a range of lab-on-chip applications.

Imaging flow cytometry enables the detailed analysis of cell morphology and internal structures through high-throughput cell imaging, and quantitative phase imaging (QPI)-based microfluidic approaches have extended this by providing label-free measures such as dry mass and refractive index (RI). Building on these developments, we present quantitative phase deformability cytometry (QP-DC), which integrates QPI with deformability cytometry to simultaneously measure morphology, mechanics, and intrinsic biophysical parameters such as mass density and dry mass. Numerical refocusing ensures in-focus images independent of axial position, improving precision in contour detection and feature extraction. Using microspheres and whole blood, we validated QP-DC and then applied it to neutrophils under lipopolysaccharide (LPS) stimulation and from patients with systemic lupus erythematosus (SLE). QP-DC revealed LPS-induced reductions in neutrophil mass density and identified heterogeneous subpopulations in SLE. These results demonstrate the capability of QP-DC for precise biophysical and mechanical characterization, offering significant potential for research and clinical diagnostics.

Holo-Tomographic Flow Cytometry (HTFC) holds the potential to transform cellular research and clinical screening through 3D label-free quantitative phase imaging (QPI) of flowing single cells. However, it has been limited by insufficient intracellular specificity in 3D refractive index (RI) distributions, since suspended cells act as highly aberrating spherical biolenses obscuring internal structures. Here, we show the Biolens Phase Compensation (BPC), a method that corrects phase aberrations in 2D QPI projections to transform the 3D RI tomogram. Working within this new 3D pseudo-RI space demonstrates for the first time the extraction of nucleoli in HTFC. Extensive validation against 2D fluorescence flow cytometry and 3D confocal microscopy demonstrates that BPC achieves reliable intranuclear specificity. Using statistically significant single-cell analysis, we provide multiplexed quantitative 3D measurements of nested intracellular compartments (cytoplasm, nucleoplasm, nucleoli). This approach extends label-free HTFC toward capabilities of gold-standard Fluorescence Microscopy, overcoming its well-known drawbacks in intracellular and intranuclear staining.

Altered vascular integrity is a hallmark for many diseases. Monitoring vascular permeability, including its extent and underlying transport pathways, is thus important for advancing our understanding of disease mechanisms towards innovative diagnosis and treatment. Here we show real-time fluorescence imaging using lanthanide-based upconversion nanoparticles as contrast agents to visualise subtle changes to vascular permeability in vivo. Based on simultaneous confocal imaging of the vasculature alongside single particle tracking in the wide-field at video rate, we performed high-throughput surveillance across live zebrafish larvae to pinpoint locations of potential nanoparticle extravasation, achieving superior sensitivity and specificity over conventional fluorescent dyes. Further analyses of the sub-second dynamics of individual nanoparticle extravasation events unveiled distinct characteristics to distinguish between transcellular and paracellular transport. We applied the technique to evaluate the blood-brain barrier (BBB) in zebrafish larvae at different developmental stages, and potential BBB perturbation strategy via nanoparticle functionalisation with polysorbates. Significantly increased BBB penetration by 36.5 folds was shown for the functionalised particles compared to phospholipid-coated particles, attributed to enhanced transcellular crossing. The technique is readily applicable to monitoring vascular integrity and investigating endothelial transport for improved understanding of vascular biology, facilitating advanced research in disease diagnostics and drug delivery towards translation.

Multi-modal, multiscale imaging is crucial for quantitative high-content spatial profiling. We present an integrated image processing pipeline for comprehensive tissue analysis that combines quantitative phase microscopy for tissue architecture mapping, hyper-plex fluorescence imaging for immune microenvironment profiling, and whole-slide histopathology. This approach enables detailed morphological mapping of tissue architecture and cell morphology, while simultaneously linking them to the functional states of individual cells across the entire slide. By analyzing tissue biopsies from patients with ulcerative colitis, we demonstrate the potential of this pipeline for quantitative spatial analysis of molecular markers related to mucosal healing. Open-source and compatible with conventional microscopy systems, this pipeline provides a powerful tool for research and clinical applications through its comprehensive integration of quantitative, high-content, and histological imaging modalities.

The homing of hematopoietic stem/progenitor cells (HSPCs) and leukemic cells is a multistep process governed by complex spatiotemporal interactions between adhesion molecules under shear stress. While the molecular and biological mechanisms of this process have been extensively studied, the precise spatial and temporal organization of adhesion molecules that influences homing efficiency remains relatively poorly understood. In particular, the roles of the cell surface topography and its morphological changes during homing in shaping the spatial organization of adhesion molecules remain elusive. This is partly due to the lack of imaging techniques that simultaneously capture both nanoscopic cell surface morphology and the spatial distribution of the adhesion molecules. Here, we develop a microfluidics-based super-resolution (SR) imaging platform that enables the three-dimensional (3D) mapping of the cell surface morphology and the spatial distribution of the adhesion molecules during HSPC and leukemic cell rolling by integrating total internal reflection fluorescence microscopy (TIRFM) with single-molecule localization microscopy (SMLM). We reconstruct the cell surface morphology, which is critical to the homing, using TIRFM, and precisely overlay the spatial distribution of adhesion molecules, including CD44, PSGL-1, and actin cytoskeleton, determined by 3D-SMLM, on the topographic map. We show distinct nanoscopic localizations of adhesion molecules on the microvilli of HSPCs/leukemic cells and their reorganization under shear stress during cell rolling, at a spatial resolution of approximately 30 nm. The approach offers a powerful means to elucidate the complicated interplay between cell surface morphology and ligand-receptor interactions. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/672391v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@19e513eorg.highwire.dtl.DTLVardef@e7dd0corg.highwire.dtl.DTLVardef@617295org.highwire.dtl.DTLVardef@1a9ae0a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Hematologists evaluate alterations in blood cell enumeration and morphology to confirm the peripheral blood smear findings through manual microscopic examination. However, routine peripheral blood smear analysis is both time-consuming and labor-intensive. Here, we propose a smartphone-based autofluorescence microscopy (Smart-AM) system for imaging label-free blood smears at sub-cellular resolution and performing hematological analysis. Smart-AM enables rapid, high-quality, and label-free visualization of morphological features of different blood cells (leukocytes, erythrocytes, and thrombocytes) and abnormal variations in blood cells. Moreover, assisted with deep learning algorithms, this technique can automatically detect and classify different leukocytes with high accuracy, and transform the autofluorescence images into virtual Giemsa-stained images maintaining significant cellular features. The proposed technique is portable, cost-effective, and user-friendly, making it significant for broad point-of-care applications.

Quantitative analysis on a large number of organoids can provide meaningful information from the morphological variability observed in 3D organotypic cultures, called organoids. Yet, gathering statistics of growing organoids is currently limited by existing imaging methods and subsequent image analysis workflows that are either restricted to 2D, limited in resolution, or with a low throughput. Here, we present an automated high content imaging platform synergizing high density organoid cultures with 3D live light-sheet imaging. The platform is an add-on to a standard inverted microscope. We demonstrate our capacity to collect libraries of 3D images at a rate of 300 organoids per hour, enabling training of artificial intelligence-based algorithms to quantify the organoid morphogenetic organization at multiple scales with subcellular resolution. We validate our approach on different organotypic cell cultures (stem, primary, and cancer), and quantify the development of hundreds of neuroectoderm organoids (from human Embryonic Stem Cells) at cellular, multicellular and whole organoid scales.

Access to quantitative, robust, and affordable diagnostic tools is essential to address the global burden of infectious diseases. While manual microscopy remains a cornerstone of diagnostic workflows due to its broad adaptability, it is labor-intensive and prone to human error. Recent advances in artificial intelligence (AI) and robotics offer opportunities to automate and enhance microscopy, enabling high-throughput, multi-disease diagnostics with minimal reliance on complex supply chains. However, current automated microscopy platforms are often costly and inflexible -- barriers that are especially limiting in low-resource settings. Here we present Octopi 2.0, an open, highly configurable, general-purpose automated microscopy platform for a broad range of diagnostic applications, including sickle cell anemia and antibiotic resistance that we have reported recently. Applying Octopi to imaging malaria parasites with 4,6-diamidino-2-phenylindole (DAPI) staining, we discovered a spectral shift in fluorescence emission that allows rapid screening of blood smears at low magnification with throughput on the order of 1 million blood cells per minute. We further developed image processing and deep learning-based segmentation and classification pipelines to enable real-time processing for malaria diagnosis. For real-world performance validation, we collected a data set of 213 clinical samples from Uganda and the United States with a total of 905 million red blood cells and around 1.4 million malaria parasites. Using a ResNet-18 model and only one round of retraining, the model is able to achieve on average less than 5 false positive parasites/{micro}L and a per-parasite level false negative rate of less than 8% in our test dataset. This per-cell performance implies a limit of detection (LoD) around 12 parasites/{micro}L, and we measured patient-level performance of >97% specificity and sensitivity in our independent test data set of clinical samples from 73 patients/donors. As more data is collected in larger validation studies, we expect the robustness and performance of the model to continue to improve according to what we observe in our proof-of-concept experiments carried out in this study. With significant cost reduction in hardware compared to current automated microscopes and an open and versatile approach for tackling multiple diseases with standard glass slide-based sample preparation, we envision Octopi 2.0 to help enable the "app store" for equitable data-driven, AI-powered diagnostics of many diseases and conditions.

Peritoneal metastasis (PM) is the most common form of distant metastasis and one of the leading causes of death in gastric cancer (GC). For locally advanced GC, clinical guidelines recommend peritoneal lavage cytology for intraoperative PM detection. Unfortunately, current peritoneal lavage cytology is limited by low sensitivity (<60%). Here we established the stimulated Raman cytology (SRC), a chemical microscopy-based intelligent cytology. By taking advantages of stimulated Raman scattering in label-free, high-speed, and high-resolution chemical imaging, we firstly imaged 53951 exfoliated cells in ascites obtained from 80 GC patients (27 PM positive, 53 PM negative), at the Raman bands corresponding to DNA, protein, and lipid, respectively. Then, we revealed 12 single cell features of morphology and composition that were significantly different between PM positive and negative specimens, including cellular area, lipid protein ratio, etc. Importantly, we developed a single cell phenotyping algorithm to further transform the above raw features to feature matrix. Such matrix was crucial to identify the significant marker cell cluster, the divergence of which was finally used to differentiate the PM positive and negative. Compared with histopathology, the gold standard of PM detection, our SRC method assisted by machine learning classifiers could reach 81.5% sensitivity, 84.9% specificity, and the area under receiver operating characteristic curve of 0.85, within 20 minutes for each patient. Such remarkable improvement in detection accuracy is largely owing to incorporation of the single-cell composition features in SRC. Together, our SRC method shows great potential for accurate and rapid detection of PM from GC.