Nature Photonics

Single-molecule localization microscopy (SMLM) enables nanoscale imaging but remains limited in three-dimensional (3D), high-speed, and high-density applications due to background fluorescence, photon inefficiency, and large point-spread function (PSF) footprints. Here, we present single-objective light-sheet microscopy with PSF-engineering enhanced biplane detection (SoLiD-3D), a versatile imaging platform that integrates dual-wavelength light-sheet illumination with dual-color, multi-configuration biplane imaging for parallel acquisition with PSF engineered detection for high-speed volumetric SMLM. Parallelized single-objective light-sheet excitation combined with PSF engineering overcomes key limitations of conventional wide-field and biplane approaches. Independent control of two excitation wavelengths for optical sectioning enables simultaneous dual-target imaging and single-target dual-color imaging with improved contrast and temporal resolution utilizing dynamically displaced light sheets for volumetric coverage. Using SoLiD-3D, we demonstrate high-speed single- and dual-target dual-color imaging that doubles localization density without sacrificing photon efficiency and continuous volumetric imaging via PSF-engineering enhanced biplane detection for whole-cell 3D imaging with improved axial localization performance over extended depth ranges. We further demonstrate improved speed by utilizing the Hummus PSF, a compact engineered PSF that enables high-precision 3D localization with a substantially reduced spatial footprint, for the first time for super-resolution imaging applications. Taken together, SoLiD-3D mitigates the trade-off between axial range and localization precision and offers improved speed compared to conventional 3D SMLM approaches.

High-quality cellular imaging, especially in live cells, remains constrained by the trade-off among signal-to-noise ratio, phototoxicity, and instrumentation complexity. Here, we report a scalable plasmonic metasurface that generates a spatially ordered array of fluorescence-enhancing near-field hotspots and enables self-supervised denoised, cellular imaging with improved feature readability on a conventional wide-field microscope. The registered hotspot lattice serves as a physics-derived functional prior that identifies where fluorescence amplification is physically grounded and steers neural-network training accordingly, reducing reliance on paired ground truth, large external pretrained models, or extensive supervised datasets. We demonstrate two labeling-density-dependent operating regimes: dense labeling for cytoskeleton structural imaging and sparse labeling for multiplexed sensing of plasma-membrane-associated dynamics across the hotspot array. Our work unites scalable nanophotonic hardware and self-supervised computational imaging into a practical platform for structural bioimaging and on-chip live-cell biosensing under simple wide-field imaging conditions.

The accurate quantification of biological nanoparticles, such as small extracellular vesicles (sEVs), is fundamentally hindered by a resolution-coincidence trade-off in digital assays. While physical confinement can isolate single particles, conventional optical readouts remain diffraction-limited, causing multi-particle occupancy to be miscounted as single events and thereby restricting the analytical dynamic range. Here, we report a nanoplasmonic platform that overcomes this limit by introducing a geometry-defined interface that uniquely unifies nanoscale compartmentalisation and near-field-assisted super-resolution imaging. Utilising a gold plasmonic nanohole array, the strict geometric periodicity of the lattice simultaneously serves as a template for single-vesicle confinement and a deterministic grid that generates an array of localised surface plasmon resonance near-field hotspots. This position-deterministic illumination pattern imposes known geometric priors on the excitation field, shifting high-spatial-frequency information into the detectable bandwidth to achieve sub-100 nm lateral resolution. This dual-purpose geometric determinism enables high-fidelity digital readout of individual vesicles with significantly fewer sub-images than stochastic, speckle-based metasurface structured illumination microscopy approaches. The assay achieves an analytical limit of detection of 143 sEVs/{micro}L, matching the performance of state-of-the-art single-EV counting technologies. It successfully differentiates distinct sEV subpopulations based on surface biomarker expression, establishing a clear pathway for future clinical liquid biopsy applications. By replacing stochastic loading and illumination with geometric design, this work establishes a robust framework for precise vesicle interrogation with broad implications for emerging translational applications and fundamental biology.

Light scattering in scintillators is a pervasive problem and a key factor limiting X-ray imaging resolution. Here, we shift scintillator radioluminescence from the traditional visible range into the short-wave infrared (SWIR) or near-infrared II (NIR-II, 1000-3000 nm) window to mitigate light scattering and thereby enhance light penetration and X-ray imaging resolution. We present an NIR II MgGa2O4:Ni2+ scintillator with peak emission at 1340 nm, achieving a threefold improvement in X-ray imaging resolution compared with visible scintillators owing to reduced light scattering. This heavy-metal-free NIR-II scintillator exhibits intense radioluminescence comparable to that of conventional visible-emitting CsI:Tl, achieving a detection limit of 56 nanograys per second, ~100-fold lower than typical doses used in medical imaging. We show that this NIR-II scintillator enables high-resolution X-ray radiography of electronic circuit boards and biological tissues.

Temperature is a fundamental parameter governing all molecular processes, including those that define life. Fluorescence microscopy is a powerful tool to observe molecular processes in living systems in real time. Precise control and measurement of temperature during fluorescence microscopy is therefore essential. We present here a robust temperature measurement based on the excited-state lifetime of the widely available and relatively inexpensive fluorescent dye pentamethine cyanine (Cy5). The excited-state lifetime of Cy5 shows a monotonic decline in the measurement range of 0 {degrees}C - 80 {degrees}C. The measured dependency is linear until 39 {degrees}C and monoexponential above. The dependance of excited-state lifetime upon temperature is used to measure temperature up to a precision of 0.5 {degrees}C or less, a temporal resolution down to <1 millisecond and to resolve temperature gradients with spatial resolutions that are only diffraction-limited. The far-red excitation and emission of Cy5 leaves bandwidth to simultaneously measure at least 3 additional spectral channels in standard fluorescent microscopes simultaneously. We demonstrate determination of temperature during 4-color live-cell fluorescence microscopy for a temperature-controlled experiment. We also show its applicability in measuring temperature gradients and laser-induced sample heating such as during STED nanoscopy.

Multispectral imaging is a cornerstone of chemical imaging, with bioluminescence, fluorescence, and phosphorescence imaging underpin much of preclinical and analytical chemical measurements. However, conventional implementations are typically proprietary, costly, and resolve spectral content from the reflectance of a broadband source, without control over the excitation spectrum. This architecture cannot isolate excitation-dependent photophysical processes. Spectral discrimination through sequentially resolved narrowband excitation, detected on a single broadband-sensitive camera, instead enables excitation-dependent fluorescence, phosphorescence, and reflectance measurements not available to such broadband approaches. We describe AURORA-MSI, an open-source multispectral platform that inverts this arrangement with fourteen narrowband LEDs spanning 367-940 nm, a 120-element annular illumination ring with eight independently addressable azimuthal sectors, and a thermoelectrically cooled monochrome CMOS camera. Radiometric calibration, spatial uniformity mapping, and camera noise characterization establish the quantitative measurement foundation. In bioluminescence imaging, AURORA-MSI localized sources in a calibrated tissue-mimicking mouse phantom comparably to a commercial Revvity IVIS Spectrum, detected luciferase-expressing HSJD-GBM1-001 glioblastoma cells across a dilution series, with reduced replicate consistency at the lowest densities, and mapped substrate-free fungal-pathway emission in an intact bioluminescent Petunia hybrida, none requiring photon-counting instrumentation. Time-resolved phosphorescence decay imaging of six inorganic phosphors over 33 minutes found tri-exponential models adequate at early times, while distributed-lifetime models were preferred at extended timescales. Multispectral image-texture features extracted across all fourteen excitation bands discriminated ten pharmaceutical and household powders spanning distinct chemical compositions and, in two cases, distinct formulations of the same compound. Generality beyond these regimes was established through dual-excitation fluorescence fingerprinting of fifteen mineral specimens and wavelength-selective plant-tissue imaging exploiting UV and NIR penetration-depth differences. Excitation-side spectral encoding enables photophysical measurements that detection-side systems with uncontrolled broadband illumination cannot isolate, and the cooled-camera architecture supports weak-signal modalities without photon-counting instrumentation.

DNA-based technologies rely on short, transient hybridization events, but selecting sequences with desired kinetic properties remains largely empirical because hybridization kinetics are difficult to predict from sequence and slow to measure one sequence at a time. Here, we introduce SPARXS-Hyb, an implementation of SPARXS (Single-molecule Parallel Analysis for Rapid eXploration of Sequence space) for multiplexed sequence-resolved screening of DNA hybridization. Using a surface-immobilized docking-strand library and a quencher-labelled imager-strand library, we screened 128 different DNA sequences in a single kinetic measurement, exposing all sequences to identical experimental conditions. This multiplexed approach removes a major confounding factor of serial measurements, allowing sequence-dependent differences to be compared directly. The resulting dataset reveals sequence-dependent transient binding behaviours and enabled us to identify a sequence with which an order-of-magnitude higher sampling rate can be achieved in DNA-PAINT (DNA points accumulation for imaging in nanoscale topography), a super-resolution microscopy technique based on DNA hybridization. By enabling multiplexed screening across a sequence library, SPARXS-Hyb provides a route to kinetics-guided sequence selection for programmable transient interactions in DNA nanotechnology.

Quantitative fluorescence imaging techniques such as fluorescence lifetime imaging microscopy and hyperspectral imaging infer molecular contrast from photons distributed across spatial pixels and temporal or spectral channels. In the few-photon regime, however, conventional pixel-wise analysis discards the spatial relationships imposed across neighboring pixels by the microscope point-spread function (PSF). Here we show that this spatially distributed information can be recovered without prior knowledge of emitter positions, spatial support or component assignments. We introduce SPOOL (Spatially Pooled Optical Observation Likelihood), a training-free Poisson inverse framework that jointly recovers source-space amplitudes and quantitative contrast by combining the PSF with temporal-decay or spectral-response dictionaries. For an isolated source, the attainable precision gain is governed by a dimensionless optical quantity: the PSF width expressed in detector pixels. The predicted gain therefore scales with optical sampling rather than with the physical origin of the contrast. The model predicts that lifetime-precision gain scales approximately linearly with the number of pixels spanning the PSF full width at half maximum, a scaling reproduced by Monte Carlo simulations. At one detected photon per foreground pixel, the reconstruction reduces lifetime dispersion sixfold in fluorescent-bead experiments and decreases the lifetime root-mean-square error relative to a high-photon reference from 1.19 to 0.45 ns in dual-labeled cells. The same framework transfers unchanged to hyperspectral imaging, recovering spectral contrast from generic emission bands without prior fluorophore spectra.

Label-free scattering imaging is widely used in pathology because it enables sensitive tissue assessment without exogenous contrast agents. Yet its limited optical penetration has prevented scattering-based methods from being applied to whole-organ pathology mapping. Here we present clearing-assisted scattering tomography (CAST), a high-throughput, label-free whole-brain mesoscope enabled by selective lipid clearance for scattering enhancement (SELiC). SELiC modulates endogenous refractive-index heterogeneity in cleared tissue, providing whole-brain optical penetration while retaining strong scattering contrast from amyloid plaques and white-matter fibre bundles. CAST enables volumetric imaging of intact mouse brains and brain-wide mapping of amyloid plaque pathology across anatomical regions. This platform establishes a scalable route for label-free, system-level analysis of amyloid pathology and tissue architecture in Alzheimers disease (AD) models.

Cellular metabolic activities can be studied using label-free vibrational spectroscopic imaging to leverage the endogenous contrast of biomolecules. However, fast live-cell imaging over large fields-of-view remains challenging due to the need for raster scanning and despite advances in wide-field modalities, imaging rapid cellular activities across large cell populations remains challenging. Here, we introduce a mid-infrared optothermal microscopy method termed Instantaneous Phase-Shifting Optothermal Microscopy (IPSOM). IPSOM circumvents conventional mechanical phase-shifting methods, achieved single-frame imaging speed 588-fold increase compared to the sequential approach, under field-of-view of 300x350 {micro}m. For multi-wavelength hyperspectral imaging, IPSOM achieves an 8-fold speed improvement. IPSOM is used here to monitor lipid remodelling in adipocytes during lipolysis, demonstrating its potential for studying rapid cellular metabolism.

Deep learning has enabled single-molecule localization microscopy (SMLM) at high emitter densities, but only for single channel systems. Here we present DECODE-Plex, a deep-learning-based framework to localize dense single molecules with overlapping point spread functions simultaneously in multiple channels. We showcase DECODE-Plex on experimental ultra-high density dual-color and 3D live-cell data. Packaged for ease of use, it will enable many groups to improve imaging speed and quality of multi-channel SMLM.

Visual neuroscience requires precise spatiotemporal projection of optical stimulation onto the retina, especially in experimental mouse models. However, in vivo patterned stimulation in mice is profoundly hindered by the extreme optical power and severe anatomical aberrations of the eye. Consequently, visual stimulation relies mainly on unverifiable, open-loop approximations that often lack spatial precision. Here, we introduce a closed-loop, spatially modulated stimulation platform that overcomes these barriers. By integrating a digital micromirror device (DMD) with electronically tunable lenses (ETLs) and a real-time, fundus camera-guided focus optimization module, we directly verify the location of patterned stimuli on the retina while dynamically correcting for chromatic and geometric defocus. This platform delivers quantitatively verified static and dynamic patterned stimuli to the living retina with lateral resolutions as fine as 6.7 {micro}m. Guided by ray-tracing optical analysis, our work establishes a technological foundation that enables highly reproducible, cellular-scale interrogations of the visual pathway.

Molecular information is vital for imaging technology. Optical imaging acquires molecular specificity almost exclusively via labeling strategy, which is fundamentally constrained by limited multiplexing capacity, high running costs, and experimental complexity. Conversely, label-free optical imaging offers substantial technical simplicity but is believed to have little true molecular specificity. Contrary to common belief, here we introduce super-multiplex optical imaging without labeling. By systematically studying paired vibrational spectroscopic imaging and mass spectrometry imaging, we discovered a surprisingly strong (more than 0.9) correlation between their latent space representations, supported by both experiments and theory. This insight prompts us to build supervised learning models to successfully predict spatial distribution of 100 molecular species directly from label-free vibrational images across diverse tissue systems. We developed this technology, named Prediction through Learning with AdvaNced Chemical Kaleidoscope (PLANCK), and demonstrated it with both infrared-based vibrational imaging of organ-scale tissues and Raman-based vibrational imaging of live tissues. Powered by AI, PLANCK decodes the exquisitely rich but otherwise hidden vibrational information into a surprisingly large number of ([&ge;]100) specific molecular species, providing a cost-effective and scalable solution for basic research and translation, including applications in live imaging.

Solid-state nanopores offer label-free, real-time single-molecule sensing. However, resolving fast biomolecular transport requires high-bandwidth data acquisition while the intrinsic high-frequency noise limits recovery of informative events. Here we present a hardware-software co-designed nanopore sensing platform that combines wafer-scale low-noise device engineering with deep learning-based signal reconstruction. A low-dielectric SU8 coating on silicon nitride nanopores reduces device capacitance to the pF range and suppresses high-frequency noise by up to 5-fold while maintaining facile, controllable and reproducible fabrication. This extends usable acquisition to 40 MHz and enables capture of fast molecular features. Coupled with a reconstruction model trained on synthetic translocation events embedded in experimentally measured noise, the platform recovers transient sublevels while preserving blockage edges and temporal fidelity. Using engineered DNA molecules carrying dumbbell-like barcodes, we resolve nanometer-scale structural spacings on sub-microsecond timescales, and experimentally quantify translocation dynamics within the sub-10 nanometer regime. Dual-channel measurement on a single nanopore device further demonstrates transferability of the platform by showing robust cross-channel signal reconstruction across distinct baseline noise levels. Our approach provides a general route for reliable recovery of fast event features and may enable more information-rich single-molecule sensing across diverse biomolecular targets.

Spectroscopic single-molecule localization microscopy (sSMLM) enables multiplexed super-resolution imaging by simultaneously acquiring the spatial position and spectral information of individual fluorophores. Dual-wedge prism (DWP)-based implementations provide a compact, alignment-stable approach to spectral dispersion, but trade-offs between localization precision, spectral precision, and experimental complexity remain. We systematically compare five DWP-based sSMLM configurations, including two-dimensional (2D) and three-dimensional (3D) implementations using single DWP (DWP-sSMLM) and symmetrically-dispersed DWP (SDDWP-sSMLM). We evaluate lateral precision, spectral precision, and ease of use. SDDWP configurations acquire spectral images in both channels and utilize both for spatial localization, yielding the highest lateral and spectral precision. However, for applications that do not require axial information, 2D-DWP provides a simple, plug-and-play solution with robust performance. This work offers a guideline for selecting DWP configurations based on experimental needs.

In vivo infrared thermography is limited by the inherently poor spatial resolution at long wavelengths, low contrast, and the lack of biocompatible contrast agents. Here, we present 3-5 m mid-wave infrared (MWIR) thermography enhanced by an artificial intelligence (AI) network and cold phosphate-buffered saline (PBS) as a thermal contrast agent for noninvasive in vivo imaging with high contrast and resolution. MWIR imaging enabled high thermal sensitivity with microscale spatial resolution, strong relative thermal contrast, and facilitated visualization of the subcutaneous vasculature in the human arm, hand, ankle, the femoral artery and vein in rats, and the femoral vessels in mice, with image contrast further enhanced by AI networks. In a 4T1 tumor-bearing mouse model, AI-enhanced MWIR resolved early-stage tumors of ~2.3 mm and metastases as small as ~1.7 mm. Using cold PBS as a MWIR thermal contrast agent, we achieved precise tumor boundary visualization and real-time imaging-guided tumor resection. AI-enhanced MWIR offers a promising solution for early diagnosis and improved surgical precision.

Point-spread-function engineering by depth-encoding phase masks enables volumetric super-resolution imaging by 3D single-molecule localization microscopy (SMLM) but usually requires cumbersome relay optics. We demonstrate simple 3D SMLM implementation by phase mask insertion directly into the infinity space of a commercial microscope, along with appropriate computational compensation for field-dependence. The entire inserted component, including the phase mask, is 3D printing-based.

Direct modulation of neural activity with high spatiotemporal precision is a cornerstone in experimental neuroscience. Here, we present a blood-mediated optoacoustic stimulation (BOAS) approach that utilizes blood as an endogenous transducer for brain stimulation. By delivering 532-nm nanosecond pulsed laser to the cortex, we demonstrate that the absorption of hemoglobin generates sufficient acoustic pressure to trigger neuronal activity. By integrating BOAS with calcium imaging in GCaMP6f-expressing mice, localized neuronal responses were observed. Quantitative analysis reveals that BOAS produces responses comparable to natural visual stimulation and is significantly more efficient than the photothermal stimulation. Furthermore, we show that the response is dose-dependent. At high energy doses, BOAS induces cortical spreading depression. Histological evaluation confirmed that the brain maintains tissue integrity even under these stimulation parameters. Together, this work establishes a versatile method for precise brain stimulation as an alternative method for stimulating neuron at cortex.

Minimally invasive surgery is a powerful technique that enables operations deep within the body while minimizing patient trauma and recovery time. Optical endoscopes are key to providing intraoperative vision but still face challenges due to the loss of essential senses, including depth perception and tactile feedback for tissue evaluation. Thus, it is critical to develop endoscopic imaging technologies that can augment operators with critical information. In this work, we explore a prototype multimodal 3D imaging endoscope that integrates volumetric light-field imaging with laser-speckle contrast imaging to simultaneously capture 3D structure and blood-flow information in a clinically relevant form factor.

Weak, reversible interactions underpin biomolecular recognition, and single-molecule fluorescence (smF) imaging techniques can provide unprecedented insight into those biological processes. Unfortunately, such studies often require micromolar concentrations of fluorophore-labeled biomolecules, which is beyond the accessible range of conventional smF microscopies. Here, we describe a surface-functionalization method based on cloud-point polyethylene glycol (PEG) grafting that enables widefield smF microscopy measurements at micromolar concentrations without the use of nanophotonic devices. Using conventional total internal reflection fluorescence (TIRF) microscopy, we detected single-molecule fluorescence resonance energy transfer (smFRET) from surface-tethered, donor-labeled target molecules with up to 8 micromolar concentrations of freely diffusing, acceptor-labeled analyte molecules in the background--two orders of magnitude higher than typical studies in the literature. Weak, DNA-hybridization and protein-RNA binding equilibria were measured across micromolar range titrations. Together with advances in high-background data analysis, the robust method presented here enables kinetic and thermodynamic analyses of weak biomolecular interactions, especially those limited by nonspecific adsorption and high fluorescence backgrounds, using only standard smF instrumentation.