scholarly journals Nonlinear structured illumination microscopy by surface plasmon enhanced stimulated emission depletion

2011 ◽  
Vol 19 (24) ◽  
pp. 24783 ◽  
Author(s):  
Han Zhang ◽  
Ming Zhao ◽  
Leilei Peng
Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1760
Author(s):  
Joshua J. A. Poole ◽  
Leila B. Mostaço-Guidolin

Biological tissues are not uniquely composed of cells. A substantial part of their volume is extracellular space, which is primarily filled by an intricate network of macromolecules constituting the extracellular matrix (ECM). The ECM serves as the scaffolding for tissues and organs throughout the body, playing an essential role in their structural and functional integrity. Understanding the intimate interaction between the cells and their structural microenvironment is central to our understanding of the factors driving the formation of normal versus remodelled tissue, including the processes involved in chronic fibrotic diseases. The visualization of the ECM is a key factor to track such changes successfully. This review is focused on presenting several optical imaging microscopy modalities used to characterize different ECM components. In this review, we describe and provide examples of applications of a vast gamut of microscopy techniques, such as widefield fluorescence, total internal reflection fluorescence, laser scanning confocal microscopy, multipoint/slit confocal microscopy, two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG, THG), coherent anti-Stokes Raman scattering (CARS), fluorescence lifetime imaging microscopy (FLIM), structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED), ground-state depletion microscopy (GSD), and photoactivated localization microscopy (PALM/fPALM), as well as their main advantages, limitations.


2020 ◽  
Author(s):  
Jiji Chen ◽  
Hideki Sasaki ◽  
Hoyin Lai ◽  
Yijun Su ◽  
Jiamin Liu ◽  
...  

Abstract We demonstrate residual channel attention networks (RCAN) for restoring and enhancing volumetric time-lapse (4D) fluorescence microscopy data. First, we modify RCAN to handle image volumes, showing that our network enables denoising competitive with three other state-of-the-art neural networks. We use RCAN to restore noisy 4D super-resolution data, enabling image capture over tens of thousands of images (thousands of volumes) without apparent photobleaching. Second, using simulations we show that RCAN enables class-leading resolution enhancement, superior to other networks. Third, we exploit RCAN for denoising and resolution improvement in confocal microscopy, enabling ~2.5-fold lateral resolution enhancement using stimulated emission depletion (STED) microscopy ground truth. Fourth, we develop methods to improve spatial resolution in structured illumination microscopy using expansion microscopy ground truth, achieving improvements of ~1.4-fold laterally and ~3.4-fold axially. Finally, we characterize the limits of denoising and resolution enhancement, suggesting practical benchmarks for evaluating and further enhancing network performance.


2021 ◽  
Author(s):  
Agnieszka Pancholi ◽  
Tim Klingberg ◽  
Weichun Zhang ◽  
Roshan Prizak ◽  
Irina Mamontova ◽  
...  

AbstractIt is essential for cells to control which genes are transcribed into RNA. In eukaryotes, two major control points are recruitment of RNA polymerase II (Pol II) into a paused state and subsequent pause release to begin transcript elongation. Pol II associates with macromolecular clusters during recruitment, but it remains unclear how Pol II recruitment and pause release might affect these clusters. Here, we show that clusters exhibit morphologies that are in line with wetting of chromatin by a liquid phase enriched in recruited Pol II. Applying instantaneous structured illumination microscopy and stimulated emission double depletion microscopy to pluripotent zebrafish embryos, we find recruited Pol II associated with large clusters, and elongating Pol II with dispersed clusters. A lattice kinetic Monte Carlo model representing recruited Pol II as a liquid phase reproduced the observed cluster morphologies. In this model, chromatin is a copolymer chain containing regions that attract or repel recruited Pol II, supporting droplet formation by wetting or droplet dispersal, respectively.


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