Optica

Light sheet fluorescence microscopy enables volumetric imaging with high imaging speed, optical sectioning capability, and reduced photobleaching and phototoxicity, and has become a workhorse in bioimaging. However, widely adopted Gaussian light sheets face an inherent trade-off between axial resolution and field-of-view due to diffraction. State-of-the-art nondiffracting light sheets--including Bessel beam, Airy beam, and lattice light sheet--alleviate this trade-off but suffer from optical aberrations that compromise performance with increasing imaging depth. While the integration of adaptive optics offers a promising solution, such integrated systems are typically complex, expensive, and slow due to the need for serial mapping and correction of spatially varying aberrations across the specimen. Here, we present polarization-engineered aberration-resilient light sheet (PEARLS), a new class of monochromatic nondiffracting light sheet with temporally invariant profile and robustness to optical aberrations. In comparison with existing light sheets, PEARLS showed significantly reduced photobleaching and enhanced aberration-resilience, permitting imaging of three-dimensional subcellular dynamics in optically complex environments. We applied PEARLS for noninvasive observations of biological dynamics in various living systems, revealing phenotypic diversity across spatial and temporal scales--from rapid membrane dynamics and organelle interactions in cultured cells to coordinated mitosis and cell migrations in developing embryos.

For decades, the photon counting histogram (PCH) was used as the sole method to quantify fluorophore numbers in a diffraction-limited focal volume. This technique combines spatial excitation profiles, and the distribution of photon counts to register the photon emission statistics of individual fluorophores. However, this approach has not yet been transferred to widefield fluorescent imaging due to the lack of fast and single photon sensitive camera sensors which can capture the photon emission statistics of a single fluorophore. Here, we explore avenues towards quantitative analysis of the active fluorophore number by leveraging recent advancements in single photon avalanche diode (SPAD) array technology. Binary exposures of a SPAD array can be synchronized with picosecond laser pulses to measure the PCH in a widefield setting. Then, by modeling the statistical relationship between the active fluorophore number and the PCH in a region of interest following a laser pulse, we can perform Bayesian inference of this number. The model is demonstrated experimentally by counting quantum dots and various numbers of fluorescent dye molecules bound to DNA origamis. We find that this method has several important applications in widefield microscopy, including enhanced localization microscopy and constrained fitting of multiple unresolvable fluorescent emitters.

Protein-protein interactions (PPIs) mediate diverse cellular processes, but PPIs are typically characterized using reconstituted in vitro biochemical and biophysical approaches. Current approaches for PPI detection in living cells are limited in the scope of interactions they can capture and often require prior knowledge of the interacting partners. To close this gap, we developed triplet tumbling microscopy (TTM), which reveals the interactions of a tagged protein of interest in cells in real time. TTM reports protein complex size from rotational diffusion ("tumbling") by leveraging infrared-triggerable emission from triplet states to track tumbling over nanoseconds to hundreds of microseconds. These long-lived triplets overcome the size limitations of existing rotational diffusion-based approaches, enabling TTM to measure species from small protein complexes to organelle-scale beads. In living cells, we apply TTM to detect PPIs, quantify fraction bound, and distinguish protein complexes by size. We measure diverse types of interactions, including rapamycin-induced dimerization, p53 homo-oligomerization, and binding of the E3-ligase E6AP to the human papilloma virus 16 E6 protein. The required hardware is compatible with most fluorescent microscopes, making TTM a versatile way to extract molecular insights from the complex context of living cells. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/723557v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1e70768org.highwire.dtl.DTLVardef@974813org.highwire.dtl.DTLVardef@1fd122borg.highwire.dtl.DTLVardef@1b3da96_HPS_FORMAT_FIGEXP M_FIG C_FIG

Scientific user facilities routinely generate large-scale microscopy datasets across diverse instruments and vendors, differing substantially in file formats, dimensionality, and resolution. Beyond these inconsistencies, datasets are frequently fragmented living across isolated instruments and constrained by security policies and uneven metadata practices. Consequently, tracking, standardizing, processing, and visualizing these datasets in a manner compatible with modern machine learning and autonomous experimentation workflows remains a major challenge. While existing initiatives address data archiving, standardization, or analysis individually, few provide integrated solutions that bridge instrument-level acquisition and scalable ML workflows within heterogeneous, security-constrained user facilities. Here, we establish a deployable, facility-scale infrastructure that bridges instrument-level data generation with cloud-based ML analytics while remaining compliant with institutional network constraints. Our framework integrates on-premises cloud computing, the in-house Pycroscopy ecosystem, and an open-source metadata management platform to transform heterogeneous microscopy datasets into standardized, ML-ready representations. We demonstrate this approach across distinct microscopy modalities through end-to-end workflows encompassing metadata capture, format harmonization, automated database ingestion, segmentation-based ML inference, and interactive visualization. By structurally separating acquisition from cloud-based analysis services, the framework enables scalable model deployment and iterative refinement without direct connectivity to instrument computers. Together, this work provides a reproducible blueprint for facility-scale data and AI infrastructure, enabling ML-ready analytics, metadata traceability, and future autonomous experimentation workflows in microscopy-driven research.

Understanding processes such as blood-brain barrier (BBB) disruption and tumor progression can greatly benefit from simultaneous molecular, functional, and hemodynamic imaging in deep tissue, yet few existing imaging modalities can provide all three in a single system. Here, we present an integrated imaging platform that combines 3D photoacoustic tomography with ultrasound localization microscopy (3D-PAULM) to enable intrinsically co-registered, multiparametric imaging. 3D-PAULM unifies multispectral photoacoustic molecular imaging, ultrasound B-mode imaging, microbubble-enhanced power Doppler, and ultrasound localization microscopy, and concurrently measures blood oxygenation, blood perfusion, microvascular flow dynamics, and molecular probes from near-infrared dyes and photoswitchable phytochromes. We apply 3D-PAULM to quantify BBB leakage in focal ischemia and systemic inflammation, and to perform high-sensitivity molecular imaging of solid tumors alongside functional mapping of tumor hypoxia and super-resolved vascular remodeling. Together, these results establish 3D-PAULM as a versatile platform for integrated functional and molecular imaging in deep tissue.

Mapping the three-dimensional directional organization of biological tissues is essential for understanding their structure and function. However, existing methods cannot resolve micrometer-scale orientation in volumetric samples. We introduce tensor light-sheet scattering microscopy (tLSSM), a label-free method that reconstructs 3D fiber orientations at micrometer resolution in optically cleared tissues, enabling whole-organ imaging. We discovered that even in transparent samples, organized structures such as neural fibers scatter light in directional patterns, consistent with models of light scattering by cylinders. We compared tLSSM against diffusion MRI in the mouse brain, demonstrating strong agreement and orders of magnitude superior spatial resolution. Furthermore, we showcase tLSSMs versatility across diverse contexts, including whole-brain label-free tracing, pathological demyelination lesions, heart tissue, peripheral nerves, and human white matter. By enabling whole-organ fiber orientation mapping compatible with standard light-sheet microscopes, tLSSM establishes a new standard for mesoscopic connectivity studies by mapping tissue architecture beyond the limits of traditional sectioning.

Three-dimensional photoacoustic tomography (3D-PAT) enables noninvasive structural and functional imaging with optical absorption contrast and ultrasonic detection depth. However, its spatial resolution is limited by acoustic diffraction, and incomplete detection geometry can substantially degrade image fidelity and quantitative accuracy. Here, we present a ULM-guided model-based reconstruction framework, termed 3D-PAULMprior that incorporates sub-diffraction vascular priors from concurrent ultrasound localization microscopy (ULM) into 3D photoacoustic reconstruction. The method uses weighted regional Laplacian regularization to integrate high-resolution vascular information into the inverse problem, thereby enhancing vascular sharpness, suppressing limited-view artifacts, and improving blood oxygen saturation estimation. We validated 3D-PAULMprior using numerical simulations, tissue-mimicking phantoms, and in vivo mouse brain imaging. Compared with conventional reconstruction, 3D- PAULMprior improved spatial resolution by over 50%, increased contrast-to-noise ratio by 261.2%, and enhanced structural similarity index by 24.6%. In vivo, 3D-PAULMprior recovered vascular structures that were poorly resolved or missing in conventional reconstructions and produced more spatially confined sO2 maps. These results establish 3D-PAULMprior as a robust multimodal reconstruction strategy for high-resolution structural and functional photoacoustic imaging.

A quantitative description of the three-dimensional organization of the human cortical vasculature at micron scale is critical for understanding the influence of the vascular architecture on cerebral blood flow, neurovascular coupling, neurological disease, and human neuroimaging signals. However, high-resolution volumetric vascular data from human cortex are scarce, as the acquisition relies on postmortem microscopy, and tissue-clearing and whole-mount immunolabeling approaches developed for rodent tissues are less effective in heavily crosslinked, pigment rich fixed human cortex. Here we introduce h-iDISCO+, a workflow that enables whole-mount immunolabeling and high-resolution light-sheet imaging of arteries, capillaries, and veins in long-term formalin fixed human brain tissue. By integrating extended oxidative and photobleaching prior to tissue staining, we achieve uniform sample transparency and full-depth antibody penetration. Applying this workflow to tissue samples from human primary visual cortex, we quantified vessel geometrical properties and vascular density across cortical depth. This approach allows quantitative reconstruction of human cortical vascular networks at micron resolution, enabling volumetric datasets of the human cortical vasculature that were previously unavailable.

Cryo-electron tomography (cryo-ET) is a powerful approach for visualizing macromolecular structures directly within cells, but its broader application is limited by the difficulty of reliably targeting specific structures for imaging. In particular, capturing small or rare objects within FIB-milled lamellae remains a major bottleneck. Here, we establish fluorescence-guided cryo-FIB milling workflows that overcome key sources of targeting error and enable routine capture of structures across a wide size range. For larger objects (>500 nm), we develop a single step registration-based targeting strategy that combines FIB-milled fiducials with physically grounded depth correction to account for focal shifts arising from refractive index mismatch. For smaller targets (150-500 nm), we implement real-time fluorescence-guided milling on a commercially available FIB SEM instrument with an integrated cryo fluorescence microscope allowing dynamic monitoring and precise termination of milling at the onset of target ablation. Using this strategy, we achieve consistent recovery of lamellae containing the targeted structure, including small single-copy organelles such as centrioles and cilia. Together, these workflows expand the accessible target space for cryo-ET and provide practical solutions for studying cellular structures that have previously been difficult to capture.

Here, we develop CandiChrome, a multiplex labeling toolkit for Candida albicans, through combined in vitro and in vivo characterization of fluorescent proteins in a standard strain background. To this end, we screened 13 candidate fluorophores across the visible spectrum and assessed their practical performance based on brightness, stability, and usability. This analysis identified a seven-fluorophore set that achieved the most effective balance of signal strength, robustness, and compatibility. We used this optimized panel to build a modular multicolor platform that enables strain labeling, mixed-population imaging, and competition assays in C. albicans. This platform could resolve up to 21 distinct populations by flow cytometry and microscopy. Importantly, CandiChrome supported the resolution of differentially labeled populations both in vitro and in the murine host, supporting the simultaneous tracking of multiple strains in complex settings. Together, these results establish CandiChrome as a flexible platform for multiplex fungal imaging in a pathogenic species where multicolor tools remain underdeveloped.

Altair-dvOPM is an open-access direct-view oblique plane microscope designed for large-field, three-dimensional imaging of cleared and expanded tissue sections. By combining photographic-lens-based detection, externally launched oblique illumination and precision-registered modular baseplates, the system achieves micrometer-scale lateral resolution over a ~5.4 mm field of view without custom objectives or highly specialized alignment procedures. We demonstrate imaging across scales, from subcellular structures in expanded cells to centimeter-scale expanded tissue sections, and provide documentation, CAD files, Zemax models and open-source control software to support replication and extension.

Microbubble contrast-enhanced ultrasound (CEUS) relies on discriminating nonlinear bubble signals from linear tissue backscattering. While Singular Value Decomposition (SVD) filtering improves this discrimination, existing techniques often fail to retain the slowly-moving microbubble signals from static clutter. Here, we present a novel multi-stage singular value decomposition (MS-SVD) framework for ultrafast CEUS imaging. Our method employs plane-wave transmissions at multiple angles and acoustic pressure levels (implemented via duty-cycle modulation) and alternating transmit polarity. The beamformed data are then processed by three sequential SVD filters: (1) spatial-angular SVD to extract coherent signals across all transmit angles, (2) spatial-pressure SVD to separate linear fundamental and nonlinear harmonic components, and (3) spatiotemporal SVD to isolate moving microbubble echoes from tissue clutter. In in vitro flow phantoms and in vivo rat brain through a cranial window, MS-SVD dramatically improves microbubble detection compared to conventional SVD filtering, MS-SVD yields much stronger vascular contrast and suppresses tissue clutter to a greater extent. The resulting power-Doppler and super-resolution maps are notably cleaner and more complete: MS-SVD detects substantially more microbubble events in ULM, revealing finer vessel details and more accurate flow speeds. By capturing the full acoustic signature of microbubbles (both fundamental and harmonic), MS-SVD achieves higher contrast-to-noise and sensitivity in CEUS. These gains make it a powerful front-end for super-resolution ultrasound localization microscopy and other high-sensitivity microvascular imaging applications.

Apohas Liquid State Intelligence Platform (LSIP) records ellipsometric waveforms from injections depositing sub-microgram quantities of antibody drop-by-drop onto a liquid reservoir. We previously showed that a behavioural feature extracted from the waveforms, VIBE1, identified antibodies carrying multiple biophysical liabilities in an industrial dataset of 71 monoclonal antibodies, and enriched for clinical failure across a larger dataset of 235 therapeutic antibodies [1]. Here, we use an auxiliary coalescence-sensor channel to decode VIBE1 by separating the coalescence event from its propagation through the substrate. The pertitration drop-to-drop standard deviation of pinch-off time,{sigma}{tau} , explains most of VIBE1s variance across the dataset (R2 = 0.92, n = 1182). High-speed imaging at 10,000 frames per second reveals that all imaged drops initially thin at the same Newtonian capillary-inertial rate while the neck remains wide. In drops from certain antibodies, the thinning bridge then decelerates as internal strain builds in the narrowing neck. This elasto-capillary stiffening response has a timescale{lambda} that decreases as pinch-off time{tau} i increases across the imaged set.{sigma}{tau} is therefore a readout of the antibodys propensity to undergo a transient gel-like stiffening response during coalescence, and that variability is what VIBE1 captures. The signal is concentration dependent, and absent in bovine serum albumin (BSA) tested at up to an order of magnitude higher molarity than the antibodies, despite BSA being a strongly surface-active globular protein. The instrument is configured so that complex behaviours of this kind appear in its recorded waveforms; the gel-like coalescence response we identify here is one such phenomenon.

Honey bees (Apis mellifera) offer an alternative model for investigating magnetoreception, exhibiting reliable navigation and behavioral responses to magnetic fields. Thanks to their compact brains, well-matched to the penetration depth of modern optical imaging techniques, they may offer insights into the neural and biochemical mechanisms underlying this sense, something that standard models, like migrating birds, have not so far provided. But also in honeybees, this progress requires tools capable of resolving weak, magnetically induced neural activity with high spatio-temporal precision. The approach, presented here, bridges quantum biology and neuroscience, allowing for testing the radical pair mechanism (RPM) as a potential basis for magnetic sensing. As the RPM predicts that magnetoreception is coupled to the visual system, we developed an in vivo two-photon calcium imaging approach to measure neural activity in the anterior optic tubercle, a higher-order visual center involved in chromatic processing and potentially navigation. Bees were prepared using a minimally invasive technique, in which this neuropil was retrogradely labelled with a fluorescent calcium indicator, enabling stable recording conditions over several hours. Controlled blue-light stimuli were provided by the scattered output of a fiber laser, and weak magnetic-field stimuli were applied by a shielded, three-axis Helmholtz coil system that allowed precise modulation of field strength and polarity while minimizing electromagnetic interference. Visual stimulation evoked consistent and reproducible calcium responses, validating the preparation and imaging stability. Magnetic stimulation produced small fluorescence decreases, suggesting field-dependent modulation of neural activity. The developed imaging framework shows the feasibility of detecting magnetic modulation in vision- and navigation-related brain regions, suggesting neural amplification of weak magnetic cues and providing a platform for controlled tests of RPM-specific predictions, including light dependence, polarity independence, and radiofrequency perturbation.

The spatial resolution of optical imaging systems is fundamentally restricted by the diffraction limit. However, in widefield live-cell microscopy, the achievable resolution is further constrained by the specimen motion, which indicates the existence of a fundamental spatio-temporal resolution trade-off between signal accumulation during the full frame integration and the resulting motion blur. To improve the fidelity with which moving objects can be imaged, a quantitative understanding of this spatio-temporal trade-off is necessary. Here, we present a systematic analysis of motion-induced resolution dynamics measured with spectral signal-to-noise ratio (SSNR). We developed a simulation framework which models the image formation of objects undergoing arbitrary motion, to evaluate the degradation of the spatial resolution under translational and rotational dynamics. Our results demonstrate that for translating objects, the spatial resolution is anisotropically reduced as a function of the orientation of the object relative to the motion vector, leading to the spectral signal-to-noise ratio degrading by up to 50% and the resolution by up to 40% for a 90{degrees} change in the motion direction. Furthermore, we show that for rotational motion, conventional radially averaged metrics such as the Fourier Ring Correlation are not able to quantify the effects of angular blur. On the other hand, the SSNR is able to accurately quantify this degradation. These findings underscore the necessity of an object-oriented imaging approach, in which acquisition parameters such as exposure time are tuned to specific biological spatio-temporal characteristics to optimize the trade-off between motion blur and spatial fidelity.

Proteins are major drivers of biological functions. Single-cell, organ-scale multiplexed protein imaging can reveal high-dimensional molecular and structural features of individual cells and their interactions, enabling an in-depth understanding of complex biological systems. However, such imaging has remained an elusive goal due to hurdles in multiplexed immunolabeling (mIF) of intact organs and integrative image analysis. Here, we present 3D CYCLIC, an organ-scale multiplexed immunolabeling technique, and TACTIC, a single-cell-level, organ-scale image co-registration algorithm. 3D CYCLIC combines ultrafast, versatile 3D immunolabeling with a cleavable crosslinker that preserves signals by protecting bound antibodies during optical clearing while enabling their detachment for subsequent rounds of immunolabeling. TACTIC uses deep warping networks coupled with a propagation-based cell-pair search to co-register individual cells across whole-brain images acquired from the same tissue across multiple rounds of 3D CYCLIC labeling. 3D CYCLIC enabled 6-plex protein profiling of a mouse brain hemisphere, with images that can be combined with TACTIC for integrative analysis. 3D CYCLIC and TACTIC will facilitate a holistic, unbiased understanding of diverse complex multicellular organ systems.

We introduce a workflow to identify oligomeric structures that are recorded with single-molecule localization microscopy (SMLM) under cryogenic conditions. Typically, these oligomers are assumed to consist of protomers arranged as equilateral two-dimensional polygons and every protomer is labeled with a dye molecule for visualization. Unlike previous work, we consider scenarios in which the sample plane has an unknown orientation relative to the focal plane. Our contribution is a high-precision plane-fitting algorithm to determine the sample plane, combined with geometrical transformations and two circle-fitting algorithms to identify the oligomeric structures. Our simulations on synthetic data demonstrate that the proposed workflow achieves high accuracy in estimating both the unknown tilted plane and the oligomer size.

The biomechanical properties of the retina govern its function, structural integrity, and susceptibility to disease, yet remain difficult to measure in vivo due to the lack of safe, spatially localized mechanical actuation. Here, we introduce a framework for probing retinal biomechanics in the living human eye by leveraging intrinsic optical actuation driven by phototransduction. Using phase-resolved optical coherence tomography with a local phase-referencing approach, we resolved signed, nanometer-scale displacements of the major outer retinal interfaces evoked by light. The resulting deformation field, originating in the photoreceptor outer segment, was distributed across retinal compartments in an eccentricity-dependent manner, with efficient axial transfer in the fovea and attenuated propagation in the parafovea. A hybrid analytical and finite-element framework was developed that retrieved the biomechanical properties of the retinal compartments based on their coordinated deformation and the anatomical variation in retinal structure versus eccentricity. In retinitis pigmentosa, the paradigm enabled the detection of light-evoked deformation in the transition zone despite the loss of native lamination, enabling a functional readout of the vulnerable photoreceptors at the leading edge of degeneration. Together, these results establish intrinsic optical stimulation as a basis for in vivo retinal elastography and enable the non-invasive, quantitative imaging of retinal biomechanics and function in the living human retina.

Refined single-molecule localization microscopy methods demonstrated superior localization precisions on isolated sample but remain limited by labeling density and imaging speed in cells. Here we combine expansion microscopy (ExM) with two-dye-imager (TDI)-DNA-PAINT to resolve fine molecular details of protein assemblies in [~]8-fold expanded cells with nanometer resolution. Using lattice light-sheet (LLS) microscopy, Ex-TDI-DNA-PAINT provides a robust platform for three-dimensional (3D) volumetric nanoscopy of the molecular organization of cells.

Tracking immune cells deep within living tissue remains a fundamental challenge due to the diffraction-limited resolution of ultrasound imaging and the inability to resolve dense cellular populations. Here, we introduce an intracellular super-resolution ultrasound imaging framework based on stochastic phase-changing nanodroplets (NDs) and ultrasound localization microscopy (ULM). We engineer [~]170 nm perfluorocarbon NDs that undergo reversible, stochastic liquid-gas transitions under acoustic excitation, generating temporally sparse "blinking" signals. Leveraging the intrinsic endocytic activity of macrophages, these NDs are internalized, enabling intracellular contrast generation independent of vascular flow. We validate this approach across imaging scales, from controlled phantoms and in vitro systems to in vivo tumor models, demonstrating robust intracellular blinking, high cell viability, and consistent super-resolution reconstruction in dense cellular environments. The stochastic blinking of internalized NDs provides the temporal separation required to localize individual sources, overcoming a central limitation of conventional ULM. Following systemic administration, ND-labeled macrophages are tracked in vivo after homing to the liver, where super-resolution ULM resolves cellular distributions with a spatial resolution of 26.3 {+/-} 3.2 {micro}m, corresponding to a 6.1-fold improvement over diffraction-limited imaging. This work establishes a previously unexplored paradigm for ultrasound-based intracellular super-resolution imaging, enabling non-invasive visualization of immune cell organization in deep tissue. By introducing spatiotemporally programmable intracellular contrast, this approach expands ultrasound beyond vascular imaging toward functional cellular imaging, with broad implications for immunology, diagnostics, and cell-based therapies.