Super-resolution Imaging Approach Research Articles

A Molecular Logic Gate Enables Unconventional Super-resolution Same-Day Imaging of Lysosome Membrane in Live Cells.

Lysosomes are acidic membrane-bound organelles that aid digestion, excretion, and cell renewal. The lysosomal membranes are essential for maintaining lysosomal functions and cellular homeostasis. In this work, we developed a molecular "NOR" logic gate, SIATFluor-580L, by introducing malachite green into the spirocyclic rhodamine. SIATFluor-580L requires restriction of molecular rotation of the malachite green motif (Input 1, tight membrane structure) and a large amount of H+ ions to convert the spirocyclic rhodamine into the zwitterionic form (Input 2, acidic environment) to produce a fluorescent product (Output), providing a fluorogenic probe to visualize the lysosomal membrane dynamics in living cells with subdiffraction resolution by using HyVolution (also known as Lightning), an unconventional and inexpensive super-resolution imaging approach based on a basic confocal optical system.

Reduced Non-Specific Binding of Super-Resolution DNA-PAINT Markers by Shielded DNA-PAINT Labeling Protocols.

The DNA-based single molecule super-resolution imaging approach, DNA-PAINT, can achieve nanometer resolution of single targets. However, the approach can suffer from significant non-specific background signals originating from non-specifically bound DNA-conjugated DNA-PAINT secondary antibodies as shown here. Using dye-modified oligonucleotides the location of DNA-PAINT secondary antibody probes can easily be observed with widefield imaging prior to beginning a super-resolution measurement. This reveals that a substantial proportion of DNA probes can accumulate, non-specifically, within the nucleus, as well as across the cytoplasm, of cells. Here, Shielded DNA-PAINT labeling is introduced, a method using partially or fully double-stranded docking strand sequences, prior to labeling, in buffers with increased ionic strength to greatly reduce non-specific interactions in the nucleus as well as the cytoplasm. This new labeling approach is evaluated against various conditions and it is shown that applying Shielded DNA-PAINT can reduce non-specific events approximately five-fold within the nucleus. This marked reduction in non-specific binding of probes during the labeling procedure is comparable to results obtained with unnatural left-handed DNA albeit at a fraction of the cost. Shielded DNA-PAINT is a straightforward adaption of current DNA-PAINT protocols and enables nanometer precision imaging of nuclear targets with low non-specific backgrounds.

Imaging interorganelle contacts at a glance.

Eukaryotic cells are compartmentalized into membrane-bound organelles that must coordinate their responses to stimuli. One way that organelles communicate is via membrane contact sites (MCSs), sites of close apposition between organelles used for the exchange of ions, lipids and information. In this Cell Science at a Glance article and the accompanying poster, we describe an explosion of new methods that have led to exciting progress in this area and discuss key examples of how these methods have advanced our understanding of MCSs. We discuss how diffraction-limited and super-resolution fluorescence imaging approaches have provided important insight into the biology of interorganelle communication. We also describe how the development of multiple proximity-based methods has enabled the detection of MCSs with high accuracy and precision. Finally, we assess how recent advances in electron microscopy (EM), considered the gold standard for detecting MCSs, have allowed the visualization of MCSs and associated proteins in 3D at ever greater resolution.

Super-Resolution Ultrasound Imaging Using the Erythrocytes-Part I: Density Images.

A new approach for vascular super-resolution (SR) imaging using the erythrocytes as targets (SUper-Resolution ultrasound imaging of Erythrocytes (SURE) imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index (MI) for ultrasound scanning for an increased penetration depth. A synthetic aperture (SA) ultrasound sequence was employed with 12 virtual sources (VSs) using a 10-MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was [Formula: see text]m) and the lateral resolution was [Formula: see text]m). Field IIpro simulations were conducted on 12.5- μ m radius vessel pairs with varying separations. A vessel pair with a separation of 70 μ m could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging and for 46.8 s for SR imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-computed tomography (CT) contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6- μ m voxel size for 11 h and for 20 h in a 5- μ m voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of 28 μ m, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 and 10 s. The vessel structure in the cortex was also similar to the SURE and SR images. Fourier ring correlation (FRC) indicated a resolution capability of 29 μ m. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.

Parallel compressive super-resolution imaging with wide field-of-view based on physics enhanced network

Parallel compressive super-resolution imaging has attracted increasing attention in recent years. However, the super-resolution quality depends on modulation masks and reconstruction algorithms. A deep-learning method provides an efficient solution, but in wide field-of-view (FOV) scenarios, the differences between optical transfer functions (OTFs) of each pixel increase the system complexity and limit its practical application. This study proposed a wide FOV parallel compressive super-resolution imaging approach based on a physics-enhanced network. First, the network and modulation masks of an arbitrary 128 × 128-pixel region were trained; then, the trained network was fine-tuned for the rest of the 128 × 128-pixel regions in the entire wide FOV, which effectively eliminated the OTF variability. Numerical simulations and practical experiments demonstrated that through the proposed approach, super-resolution images of 1020 × 1500 pixels can be reconstructed from 272 × 400-pixel low-resolution measurements using only three designed masks, with the resolution enhanced 3.75×3.75 times and the peak signal-to-noise ratio improved by 89.4% compared to the results of the previous compressed sensing algorithm. Besides, the training time was dramatically reduced by 95.5-fold compared with the traditional training strategy for each region alone. This approach decreases the imaging complexity of wide FOV and achieves the high-quality super-resolution reconstruction under few trained masks, thus we believe it can promote rapid imaging for super-resolution and a wide FOV ranging from infrared to terahertz.

Blinking Carbon Dots as a Super-resolution Imaging Probe.

Single-molecule localization microscopy (SMLM) emerges as a powerful approach for super-resolution imaging that provides unprecedented resolution at the nanometer length scale. However, the development of appropriate probes with specific photophysical traits and characteristics is crucial for this approach. This study demonstrates two different fluorescent carbon dots (CDs) derived from the same molecular precursor─one emitting in red and the other in green─as a SMLM-based super-resolution imaging probe for different applications with an average localization precision of 20 nm and a resolution of 60 nm. Both the CDs exhibit spontaneous blinking with high photon count and low duty cycle but with different blinking cycles. The red emissive CDs with a lower blinking cycle are ideal for quantitative analysis, whereas green emissive CDs with a higher blinking cycle are ideal for high-resolution imaging. We show that the difference in blinking features is linked to their chemical compositions, and the presence of much denser trap states in red emitting CDs is responsible for the reduction of its blinking cycle. This study shows that CDs can be designed as a potential probe for SMLM-based super-resolution imaging for diverse bioimaging applications.

ISAR Super-Resolution Imaging Approach Based on Low-Rank Sparse Joint Constraint Under Low SNR

ISAR Super-Resolution Imaging Approach Based on Low-Rank Sparse Joint Constraint Under Low SNR

TauSTED super-resolution imaging of labile iron in primary hippocampal neurons.

Iron dyshomeostasis is involved in many neurological disorders, particularly neurodegenerative diseases where iron accumulates in various brain regions. Identifying mechanisms of iron transport in the brain is crucial for understanding the role of iron in healthy and pathological states. In neurons, it has been suggested that iron can be transported by the axon to different brain regions in the form of labile iron; a pool of reactive and exchangeable intracellular iron. Here we report a novel approach to imaging labile ferrous iron, Fe(II), in live primary hippocampal neurons using confocal and TauSTED (stimulated emission depletion) microscopy. TauSTED is based on super-resolution STED nanoscopy, which combines high spatial resolution imaging (<40nm) with fluorescence lifetime information, thus reducing background noise and improving image quality. We applied TauSTED imaging utilizing biotracker FerroFarRed Fe(II) and found that labile iron was present as submicrometric puncta in dendrites and axons. Some of these iron-rich structures are mobile and move along neuritic pathways, arguing for a labile iron transport mechanism in neurons. This super-resolution imaging approach offers a new perspective for studying the dynamic mechanisms of axonal and dendritic transport of iron at high spatial resolution in living neurons. In addition, this methodology could be transposed to the imaging of other fluorescent metal sensors.

Role of α2δ-3 in regulating calcium channel localization at presynaptic active zones during homeostatic plasticity.

The homeostatic modulation of synaptic transmission is an evolutionarily conserved mechanism that is critical for stabilizing the nervous system. At the Drosophila neuromuscular junction (NMJ), presynaptic homeostatic potentiation (PHP) compensates for impairments in postsynaptic glutamate receptors due to pharmacological blockade or genetic deletion. During PHP, there is an increase in presynaptic neurotransmitter release, counteracting postsynaptic changes and restoring excitation to baseline levels. Previous studies have shown that α2δ-3, an auxiliary subunit of voltage-gated calcium channels (VGCCs), is essential for both the rapid induction and sustained expression of PHP at the Drosophila NMJ. However, the molecular mechanisms by which α2δ-3 regulates neurotransmitter release during PHP remain to be elucidated. In this study, we utilized electrophysiological, confocal imaging, and super-resolution imaging approaches to explore how α2δ-3 regulates synaptic transmission during PHP. Our findings suggest that α2δ-3 governs PHP by controlling the localization of the calcium channel pore-forming α1 subunit at presynaptic release sites, or active zones. Moreover, we examined the role of two structural domains within α2δ-3 in regulating neurotransmitter release and calcium channel localization. Our results highlight that these domains in α2δ-3 serve distinct functions in controlling synaptic transmission and presynaptic calcium channel abundance, at baseline in the absence of perturbations and during PHP. In summary, our research offers compelling evidence that α2δ-3 is an indispensable signaling component for controlling calcium channel trafficking and stabilization in homeostatic plasticity.

Super-resolution ultrasound imaging approaches to visualise changes in gut structure

Super-resolution ultrasound imaging approaches to visualise changes in gut structure

Study on the Propagation and Conversion of Evanescent Lamb Waves in Discontinuous Plate Structures

In conventional Lamb wave based non-destructive testing (NDT), subwavelength imaging cannot be performed for very small damages due to diffraction limits, which may pose safety hazards to engineering structures and large equipment, and even cause major safety accidents, leading to property damage and casualties. However, in evanescent Lamb waves, there is the necessary subwavelength information that can be converted into propagable Lamb waves, which contain subwavelength damage information that can be received to form super-resolution imaging. Therefore, this article investigates the propagation and transformation characteristics of evanescent Lamb waves in a discontinuous plate structure, providing a research approach for further super-resolution imaging, which has certain scientific research and practical application value.

Population Control of Upconversion Energy Transfer for Stimulation Emission Depletion Nanoscopy.

Upconverting stimulated emission depletion microscopy (U-STED) is emerging as an effective approach for super-resolution imaging due to its significantly low depletion power and its ability to surpass the limitations of the square-root law and achieve higher resolution. Though the compelling performance, a trade-off between the spatial resolution and imaging quality in U-STED has been recognized in restricting the usability due to the low excitation power drove high depletion efficiency. Moreover, it is a burden to search for the right power relying on trial and error as the underpinning mechanism is unknown. Here, a method is proposed that can easily predict the ideal excitation power for high depletion efficiency with the assistance of the non-saturate excitation based on the dynamic cross-relaxation (CR) energy transfer of upconversion nanoparticles. This allows the authors to employ the rate equation model to simulate the populations of each relevant energy state of lanthanides and predict the ideal excitation power for high depletion efficiency. The authors demonstrate that the resolution of STED with the assistance of nonsaturated confocal super-resolution results can easily achieve the highest resolution of sub-40nm, 1/24th of the excitation wavelengths. The finding on the CR effect provides opportunities for population control in realizing low-power high-resolution nanoscopy.

MGluR5 is transiently confined in perisynaptic nanodomains to shape synaptic function

The unique perisynaptic distribution of postsynaptic metabotropic glutamate receptors (mGluRs) at excitatory synapses is predicted to directly shape synaptic function, but mechanistic insight into how this distribution is regulated and impacts synaptic signaling is lacking. We used live-cell and super-resolution imaging approaches, and developed molecular tools to resolve and acutely manipulate the dynamic nanoscale distribution of mGluR5. Here we show that mGluR5 is dynamically organized in perisynaptic nanodomains that localize close to, but not in the synapse. The C-terminal domain of mGluR5 critically controlled perisynaptic confinement and prevented synaptic entry. We developed an inducible interaction system to overcome synaptic exclusion of mGluR5 and investigate the impact on synaptic function. We found that mGluR5 recruitment to the synapse acutely increased synaptic calcium responses. Altogether, we propose that transient confinement of mGluR5 in perisynaptic nanodomains allows flexible modulation of synaptic function.

Axial Super-Resolution Ultrasound Imaging With Quasi-Monopolar Pulses From a Dual-Frequency Transducer

In biomedical ultrasound imaging, the axial resolution is determined by the pulse length, which reaches the bottleneck for the existing piezoelectric materials. The resonance of piezoelectric materials in conventional ultrasound transducers causes relatively long pulses with multiple wavelengths, which cannot be effectively shortened for decades. The waveform with practically the shortest pulse length is a monopolar half-cycle sinusoidal wave, which is beyond the capability of traditional piezoelectric transducers. Here, we propose a method for generating quasi-monopolar ultrasound pulses by the superposition of two ultrasound signals from a stack-layer dual-frequency ultrasound transducer. In this article, we designed and fabricated a 1+ 3 MHz stack-layer dual-frequency ultrasound transducer, and validated the generation of the quasi-monopolar pulse by specific excitation of each piezoelectric layer. Imaging with the quasi-monopolar pulses on copper wire phantoms demonstrated a pulse length of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.17\lambda $ </tex-math></inline-formula> (85.5 ns referring to 2 MHz), which generates images with superb axial resolution and clearly differentiates the phantom wires separated with 1 mm. This design provides a practical approach for general-purpose super-resolution ultrasound imaging without a contrast agent.

Ultrathin Layered Hyperbolic Metamaterial-Assisted Illumination Nanoscopy.

Metamaterial-assisted illumination nanoscopy (MAIN) has been proven to be a promising approach for super-resolution microscopy with up to a 7-fold improvement in imaging resolution. Further resolution enhancement is possible in principle, however, has not yet been demonstrated due to the lack of high-quality ultrathin layered hyperbolic metamaterials (HMMs) used in the MAIN. Here, we fabricate a low-loss composite HMM consisting of high-quality bilayers of Al-doped Ag and MgO with a nominal thickness of 2.5 nm, and then use it to demonstrate an ultrathin layered hyperbolic metamaterial-assisted illumination nanoscopy (ULH-MAIN) with a 14-fold imaging resolution improvement. This improvement of resolution is achieved in fluorescent beads super-resolution experiments and verified with scanning electron microscopy. The ULH-MAIN presents a simple super-resolution imaging approach that offers distinct benefits such as low illumination power, low cost, and a broad spectrum of selectable probes, making it ideal for dynamic imaging of life science samples.

Deep learning acceleration of multiscale superresolution localization photoacoustic imaging

A superresolution imaging approach that localizes very small targets, such as red blood cells or droplets of injected photoacoustic dye, has significantly improved spatial resolution in various biological and medical imaging modalities. However, this superior spatial resolution is achieved by sacrificing temporal resolution because many raw image frames, each containing the localization target, must be superimposed to form a sufficiently sampled high-density superresolution image. Here, we demonstrate a computational strategy based on deep neural networks (DNNs) to reconstruct high-density superresolution images from far fewer raw image frames. The localization strategy can be applied for both 3D label-free localization optical-resolution photoacoustic microscopy (OR-PAM) and 2D labeled localization photoacoustic computed tomography (PACT). For the former, the required number of raw volumetric frames is reduced from tens to fewer than ten. For the latter, the required number of raw 2D frames is reduced by 12 fold. Therefore, our proposed method has simultaneously improved temporal (via the DNN) and spatial (via the localization method) resolutions in both label-free microscopy and labeled tomography. Deep-learning powered localization PA imaging can potentially provide a practical tool in preclinical and clinical studies requiring fast temporal and fine spatial resolutions.

DNA-PAINT Imaging Accelerated by Machine Learning.

DNA point accumulation in nanoscale topography (DNA-PAINT) is an easy-to-implement approach for localization-based super-resolution imaging. Conventional DNA-PAINT imaging typically requires tens of thousands of frames of raw data to reconstruct one super-resolution image, which prevents its potential application for live imaging. Here, we introduce a new DNA-PAINT labeling method that allows for imaging of microtubules with both DNA-PAINT and widefield illumination. We develop a U-Net-based neural network, namely, U-PAINT to accelerate DNA-PAINT imaging from a widefield fluorescent image and a sparse single-molecule localization image. Compared with the conventional method, U-PAINT only requires one-tenth of the original raw data, which permits fast imaging and reconstruction of super-resolution microtubules and can be adopted to analyze other SMLM datasets. We anticipate that this machine learning method enables faster and even live-cell DNA-PAINT imaging in the future.

Fourier ptychography multi-parameunter neural network with composite physical priori optimization.

Fourier ptychography microscopy(FPM) is a recently developed computational imaging approach for microscopic super-resolution imaging. By turning on each light-emitting-diode (LED) located on different position on the LED array sequentially and acquiring the corresponding images that contain different spatial frequency components, high spatial resolution and quantitative phase imaging can be achieved in the case of large field-of-view. Nevertheless, FPM has high requirements for the system construction and data acquisition processes, such as precise LEDs position, accurate focusing and appropriate exposure time, which brings many limitations to its practical applications. In this paper, inspired by artificial neural network, we propose a Fourier ptychography multi-parameter neural network (FPMN) with composite physical prior optimization. A hybrid parameter determination strategy combining physical imaging model and data-driven network training is proposed to recover the multi layers of the network corresponding to different physical parameters, including sample complex function, system pupil function, defocus distance, LED array position deviation and illumination intensity fluctuation, etc. Among these parameters, LED array position deviation is recovered based on the features of brightfield to darkfield transition low-resolution images while the others are recovered in the process of training of the neural network. The feasibility and effectiveness of FPMN are verified through simulations and actual experiments. Therefore FPMN can evidently reduce the requirement for practical applications of FPM.

Super-resolution imaging using conventional and non-conventional beamforming

Super-resolution ultrasound surpasses diffraction limits by localizing spatio-temporally separable contrast agents and generates images that significantly exceed the resolution of conventional B-mode imaging methods. However, the ability to detect contrast agents and to separate their signal from the underlying tissue and from sources of image degradation such as phase aberration or reverberation clutter remains a process that is governed by fundamental wave propagation and beamforming. Here, super-resolution imaging and improvements in contrast detection, imaging depth, resolution, and registration accuracy are demonstrated using conventional and non-conventional beamforming methods in 2D and 3D. Three different imaging schemes: (a) single plane-wave, (b) three steered plane-wave compounding, and (c) 256 focused transmits are compared in vivo to quantify the improvements in contrast detection. Wide-beam 3D transcranial super-resolution and power Doppler images through a human and macaque skull are demonstrated using a 1.5 MHz sparse matrix array. These partially and fully focused methods are also demonstrated transcranially in rodents using 2D imaging at 15 MHz and volumetric imaging at 8 MHz. Finally super-harmonic super-resolution imaging approaches are demonstrated for stationary and moving bubbles in murine tumors. These imaging methods extend the capabilities of super-resolution imaging and may improve the clinical translatability of the technique.

Balanced Tikhonov and Total Variation Deconvolution Approach for Radar Forward-Looking Super-Resolution Imaging

In radar forward-looking super-resolution imaging, improving the azimuth resolution while acquiring the contour information of the target has significant research value. In this letter, an approach based on the balanced Tikhonov and total variation (TV) deconvolution is proposed for radar forward-looking super-resolution imaging. We combine the Tikhonov regularization and TV regularization to construct the objective function and resolve the respective cost function using the alternating direction method of multipliers (ADMM). In each iteration, the gradient function of the target scattering coefficient is used as the adaptive weighted parameter to control automatically the weighting between the penalty terms from TV and the Tikhonov regularization. For the target with a sharper outline, the proportion of TV regularization penalty terms is increased; for the target with a smoother outline, the proportion of penalty term from the Tikhonov regularization is enhanced. The simulation and experimental results are considered to show the effectiveness of the proposed method. Compared with traditional super-resolution imaging methods, the proposed approach has superior outline retention capacity.