Faculty Opinions recommendation of Incoherent structured illumination improves optical sectioning and contrast in multiphoton super-resolution microscopy.

2016 ◽  
Author(s):  
Christopher Janetopoulos
Keyword(s):  
Super Resolution ◽  
Structured Illumination ◽  
Optical Sectioning ◽  
Super Resolution Microscopy

scholarly journals Incoherent structured illumination improves optical sectioning and contrast in multiphoton super-resolution microscopy

2015 ◽  
Vol 23 (4) ◽  
pp. 5327 ◽  
Author(s):  
Peter W. Winter ◽  
Panagiotis Chandris ◽  
Robert S Fischer ◽  
Yicong Wu ◽  
Clare M Waterman ◽  
...  
Keyword(s):  
Super Resolution ◽  
Structured Illumination ◽  
Optical Sectioning ◽  
Super Resolution Microscopy

scholarly journals Fluorogenic probe for fast 3D whole-cell DNA-PAINT

2020 ◽  
Author(s):  
Kenny KH Chung ◽  
Zhao Zhang ◽  
Phylicia Kidd ◽  
Yongdeng Zhang ◽  
Nathan D Williams ◽  
...  
Keyword(s):  
3D Imaging ◽  
Super Resolution ◽  
Fold Increase ◽  
High Fidelity ◽  
Optical Sectioning ◽  
High Background ◽  
Fluorogenic Probe ◽  
Microscopy Method ◽  
Super Resolution Microscopy ◽  
Imaging Speed

AbstractDNA-PAINT is an increasingly popular super-resolution microscopy method that can acquire high-fidelity images at nanometer resolution. It suffers, however, from high background and very slow imaging speed, both of which can be attributed to the presence of unbound fluorophores in solution. We present a fluorogenic DNA-PAINT probe that solves these problems and demonstrate 3D imaging without the need for optical sectioning and a 26-fold increase in imaging speed over regular DNA-PAINT.

scholarly journals Artifact-free whole-slide imaging with structured illumination microscopy and Bayesian image reconstruction

GigaScience ◽  
2020 ◽  
Vol 9 (4) ◽  
Author(s):  
Karl A Johnson ◽  
Guy M Hagen
Keyword(s):  
Super Resolution ◽  
Structured Illumination ◽  
Optical Sectioning ◽  
Structured Illumination Microscopy ◽  
High Quality ◽  
Related Data ◽  
Reconstruction Methods ◽  
Set Up ◽  
Bayesian Image Reconstruction ◽  
Hematoxylin Eosin

Abstract Background Structured illumination microscopy (SIM) is a method that can be used to image biological samples and can achieve both optical sectioning and super-resolution effects. Optimization of the imaging set-up and data-processing methods results in high-quality images without artifacts due to mosaicking or due to the use of SIM methods. Reconstruction methods based on Bayesian estimation can be used to produce images with a resolution beyond that dictated by the optical system. Findings Five complete datasets are presented including large panoramic SIM images of human tissues in pathophysiological conditions. Cancers of the prostate, skin, ovary, and breast, as well as tuberculosis of the lung, were imaged using SIM. The samples are available commercially and are standard histological preparations stained with hematoxylin-eosin. Conclusion The use of fluorescence microscopy is increasing in histopathology. There is a need for methods that reduce artifacts caused by the use of image-stitching methods or optical sectioning methods such as SIM. Stitched SIM images produce results that may be useful for intraoperative histology. Releasing high-quality, full-slide images and related data will aid researchers in furthering the field of fluorescent histopathology.

Coherent super-resolution microscopy via laterally structured illumination

Micron ◽  
2007 ◽  
Vol 38 (2) ◽  
pp. 150-157 ◽  
Author(s):  
Brad Littleton ◽  
Kim Lai ◽  
Dennis Longstaff ◽  
Vassilios Sarafis ◽  
Paul Munroe ◽  
...  
Keyword(s):  
Super Resolution ◽  
Structured Illumination ◽  
Super Resolution Microscopy

scholarly journals Regulated protein stabilization underpins the functional interplay among basal body components in Trypanosoma brucei

2019 ◽  
Vol 295 (3) ◽  
pp. 729-742
Author(s):  
Kieu T. M. Pham ◽  
Ziyin Li
Keyword(s):  
Trypanosoma Brucei ◽  
Basal Body ◽  
Super Resolution ◽  
Specific Protein ◽  
Protein Stabilization ◽  
Structured Illumination ◽  
Human Parasite ◽  
Evolutionarily Conserved ◽  
Body Components ◽  
Super Resolution Microscopy

The basal body in the human parasite Trypanosoma brucei is structurally equivalent to the centriole in animals and functions in the nucleation of axonemal microtubules in the flagellum. T. brucei lacks many evolutionarily conserved centriolar protein homologs and constructs the basal body through unknown mechanisms. Two evolutionarily conserved centriole/basal body cartwheel proteins, TbSAS-6 and TbBLD10, and a trypanosome-specific protein, BBP65, play essential roles in basal body biogenesis in T. brucei, but how they cooperate in the regulation of basal body assembly remains elusive. Here using RNAi, endogenous epitope tagging, immunofluorescence microscopy, and 3D-structured illumination super-resolution microscopy, we identified a new trypanosome-specific protein named BBP164 and found that it has an essential role in basal body biogenesis in T. brucei. Further investigation of the functional interplay among BBP164 and the other three regulators of basal body assembly revealed that BBP164 and BBP65 are interdependent for maintaining their stability and depend on TbSAS-6 and TbBLD10 for their stabilization in the basal body. Additionally, TbSAS-6 and TbBLD10 are independent from each other and from BBP164 and BBP65 for maintaining their stability in the basal body. These findings demonstrate that basal body cartwheel proteins are required for stabilizing other basal body components and uncover that regulation of protein stability is an unusual control mechanism for assembly of the basal body in T. brucei.

scholarly journals Advances in High-Speed Structured Illumination Microscopy

2021 ◽  
Vol 9 ◽  
Author(s):  
Tianyu Zhao ◽  
Zhaojun Wang ◽  
Tongsheng Chen ◽  
Ming Lei ◽  
Baoli Yao ◽  
...  
Keyword(s):  
Live Cell Imaging ◽  
High Speed ◽  
Cell Imaging ◽  
Super Resolution ◽  
Live Cell ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Light Power ◽  
Recent Developments ◽  
Super Resolution Microscopy

Super-resolution microscopy surpasses the diffraction limit to enable the observation of the fine details in sub-cellular structures and their dynamics in diverse biological processes within living cells. Structured illumination microscopy (SIM) uses a relatively low illumination light power compared with other super-resolution microscopies and has great potential to meet the demands of live-cell imaging. However, the imaging acquisition and reconstruction speeds limit its further applications. In this article, recent developments all targeted at improving the overall speed of SIM are reviewed. These comprise both hardware and software improvements, which include a reduction in the number of raw images, GPU acceleration, deep learning and the spatial domain reconstruction. We also discuss the application of these developments in live-cell imaging.

scholarly journals Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction

2018 ◽  
Author(s):  
Jakub Pospíšil ◽  
Tomáš Lukeš ◽  
Justin Bendesky ◽  
Karel Fliegel ◽  
Kathrin Spendier ◽  
...  
Keyword(s):  
High Resolution ◽  
Open Source ◽  
Fluorescent Protein ◽  
Super Resolution ◽  
Live Cells ◽  
Structured Illumination ◽  
Optical Sectioning ◽  
Structured Illumination Microscopy ◽  
Raw Data ◽  
Bayesian Image Reconstruction

AbstractBackgroundStructured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution).FindingsFive complete and freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods, and with newer Bayesian restoration approaches which we are developing.ConclusionVarious methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments is not typically published. Publicly available, high quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data was processed with SIMToolbox, an open source and freely available software solution for SIM.

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