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1. PSSR2: a user-friendly Python package for democratizing deep learning-based point-scanning super-resolution microscopy

   https://doi.org/10.1186/s44330-024-00020-5  

   Stites, Hayden C; Manor, Uri (December 2025, BMC Methods)

   Abstract BackgroundTo address the limitations of large-scale high quality microscopy image acquisition, PSSR (Point-Scanning Super-Resolution) was introduced to enhance easily acquired low quality microscopy data to a higher quality using deep learning-based methods. However, while PSSR was released as open-source, it was difficult for users to implement into their workflows due to an outdated codebase, limiting its usage by prospective users. Additionally, while the data enhancements provided by PSSR were significant, there was still potential for further improvement. MethodsTo overcome this, we introduce PSSR2, a redesigned implementation of PSSR workflows and methods built to put state-of-the-art technology into the hands of the general microscopy and biology research community. PSSR2 enables user-friendly implementation of super-resolution workflows for simultaneous super-resolution and denoising of undersampled microscopy data, especially through its integrated Command Line Interface and Napari plugin. PSSR2 improves and expands upon previously established PSSR algorithms, mainly through improvements in the semi-synthetic data generation (“crappification”) and training processes. ResultsIn benchmarking PSSR2 on a test dataset of paired high and low resolution electron microscopy images, PSSR2 super-resolves high-resolution images from low-resolution images to a significantly higher accuracy than PSSR. The super-resolved images are also more visually representative of real-world high-resolution images. DiscussionThe improvements in PSSR2, in providing higher quality images, should improve the performance of downstream analyses. We note that for accurate super-resolution, PSSR2 models should only be applied to super-resolve data sufficiently similar to training data and should be validated against real-world ground truth data. 

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2. MAxSIM: multi-angle-crossing structured illumination microscopy with height-controlled mirror for 3D topological mapping of live cells

   https://doi.org/10.1038/s42003-023-05380-2  

   Gardeazabal Rodriguez, Pedro Felipe; Lilach, Yigal; Ambegaonkar, Abhijit; Vitali, Teresa; Jafri, Haani; Sohn, Hae Won; Dalva, Matthew; Pierce, Susan; Chung, Inhee (December 2023, Communications Biology)

   Abstract Mapping 3D plasma membrane topology in live cells can bring unprecedented insights into cell biology. Widefield-based super-resolution methods such as 3D-structured illumination microscopy (3D-SIM) can achieve twice the axial ( ~ 300 nm) and lateral ( ~ 100 nm) resolution of widefield microscopy in real time in live cells. However, twice-resolution enhancement cannot sufficiently visualize nanoscale fine structures of the plasma membrane. Axial interferometry methods including fluorescence light interference contrast microscopy and its derivatives (e.g., scanning angle interference microscopy) can determine nanoscale axial locations of proteins on and near the plasma membrane. Thus, by combining super-resolution lateral imaging of 2D-SIM with axial interferometry, we developed multi-angle-crossing structured illumination microscopy (MAxSIM) to generate multiple incident angles by fast, optoelectronic creation of diffraction patterns. Axial localization accuracy can be enhanced by placing cells on a bottom glass substrate, locating a custom height-controlled mirror (HCM) at a fixed axial position above the glass substrate, and optimizing the height reconstruction algorithm for noisy experimental data. The HCM also enables imaging of both the apical and basal surfaces of a cell. MAxSIM with HCM offers high-fidelity nanoscale 3D topological mapping of cell plasma membranes with near-real-time ( ~ 0.5 Hz) imaging of live cells and 3D single-molecule tracking. 

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3. Synthesis and Characterization of Dye-Doped Au@SiO ₂ Core-Shell Nanoparticles for Super-Resolution Fluorescence Microscopy

   https://doi.org/10.1177/00037028221121357  

   Thompson, Shelby; Jorns, Mychele; Pappas, Dimitri (November 2022, Applied Spectroscopy)

   Dye-doped nanoparticles have been investigated as bright, fluorescent probes for localization-based super-resolution microscopy. Nanoparticle size is important in super-resolution microscopy to get an accurate size of the object of interest from image analysis. Due to their self-blinking behavior and metal-enhanced fluorescence (MEF), Ag@SiO₂and Au@Ag@SiO₂nanoparticles have shown promise as probes for localization-based super-resolution microscopy. Here, several noble metal-based dye-doped core-shell nanoparticles have been investigated as self-blinking nanomaterial probes. It was observed that both the gold- and silver-plated nanoparticle cores exhibit weak luminescence under certain conditions due to the surface plasmon resonance bands produced by each metal, and the gold cores exhibit blinking behavior which enhances the blinking and fluorescence of the dye-doped nanoparticle. However, the silver-plated nanoparticle cores, while weakly luminescent, did not exhibit any blinking; the dye-doped nanoparticle exhibited the same behavior as the core fluorescent, but did not blink. Because of the blinking behavior, stochastic optical reconstruction microscopy (STORM) super-resolution analysis was able to be performed with performed on the gold core nanoparticles. A preliminary study on the use of these nanoparticles for localization-based super-resolution showed that these nanoparticles are suitable for use in STORM super resolution. Resolution enhancement was two times better than the diffraction limited images, with core sizes reduced to 15 nm using the hybrid Au–Ag cores. 

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4. 4Pi stimulated Raman scattering for label-free super-resolution chemical imaging

   https://doi.org/10.1126/sciadv.aec0523  

   Kim, Jonathan I; Ellsworth, Zachary; Dunnington, Erin L; Wong, Brian S; Mehta, Nidhi R; Zensho, Chisa; Fu, Dan (January 2026, Science Advances)

   Super-resolution fluorescence microscopy has transformed biological imaging beyond the diffraction limit. However, many biomolecules, nanostructures, drug molecules, and metabolites cannot be easily tagged, requiring a label-free imaging approach. Stimulated Raman scattering (SRS) microscopy is a powerful platform for super-resolution label-free imaging, yet current super-resolution SRS approaches rely on photoswitching, saturation, or sample expansion, which are limited by labeling, photodamage, or signal dilution, respectively. Here, we combine SRS with 4Pi interferometry to enhance axial resolution nearly sevenfold. We report on improvements in imaging sensitivity and axial resolution using 80-nanometer polystyrene beads. Harnessing the improved axial resolution, we demonstrate super-resolution 4Pi-SRS imaging in resolving small lipid droplet structures in mammalian cells and lipid membranes inEscherichia colicells. Because 4Pi-SRS uses interferometry to improve axial resolution, it is orthogonal to all previous super-resolution SRS techniques; thus, it is straightforward to integrate it with existing methods to achieve much higher resolution chemical imaging than previously possible. 

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5. Roadmap on Label‐Free Super‐Resolution Imaging

   https://doi.org/10.1002/lpor.202200029  

   Astratov, Vasily N; Sahel, Yair Ben; Eldar, Yonina C; Huang, Luzhe; Ozcan, Aydogan; Zheludev, Nikolay; Zhao, Junxiang; Burns, Zachary; Liu, Zhaowei; Narimanov, Evgenii; et al (December 2023, Laser & Photonics Reviews)

   Abstract Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super‐resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state‐of‐the‐art in this field, and to discuss the resolution boundaries and hurdles that need to be overcome to break the classical diffraction limit of the label‐free imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction‐limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super‐resolution capability that are based on understanding resolution as an information science problem, on using novel structured illumination, near‐field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere‐assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field. 

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