scholarly journals ExEm-FRET two-hybrid assay: FRET two-hybrid assay based on linear unmixing of excitation-emission spectra

2019 ◽  
Vol 27 (13) ◽  
pp. 18282
Author(s):  
Chenshuang Zhang ◽  
Yangpei Liu ◽  
Wenfeng Qu ◽  
Wenhua Su ◽  
Mengyan Du ◽  
...  
2019 ◽  
Author(s):  
Tristan D. McRae ◽  
David Oleksyn ◽  
Jim Miller ◽  
Yu-Rong Gao

AbstractDue to the overlapping emission spectra of fluorophores, fluorescence microscopy images often have bleed-through problems, leading to a false positive detection. This problem is almost unavoidable when the samples are labeled with three or more fluorophores, and the situation is complicated even further when imaged under a multiphoton microscope. Several methods have been developed and commonly used by biologists for fluorescence microscopy spectral unmixing, such as linear unmixing, non-negative matrix factorization, deconvolution, and principal component analysis. However, they either require pre-knowledge of emission spectra or restrict the number of fluorophores to be the same as detection channels, which highly limits the real-world applications of those spectral unmixing methods. In this paper, we developed a robust and flexible spectral unmixing method: Learning Unsupervised Means of Spectra (LUMoS), which uses an unsupervised machine learning clustering method to learn individual fluorophores’ spectral signatures from mixed images, and blindly separate channels without restrictions on the number of fluorophores that can be imaged. This method highly expands the hardware capability of two-photon microscopy to simultaneously image more fluorophores than is possible with instrumentation alone. Experimental and simulated results demonstrated the robustness of LUMoS in multi-channel separations of two-photon microscopy images. We also extended the application of this method to background/autofluorescence removal and colocalization analysis. Lastly, we integrated this tool into ImageJ to offer an easy to use spectral unmixing tool for fluorescence imaging. LUMoS allows us to gain a higher spectral resolution and obtain a cleaner image without the need to upgrade the imaging hardware capabilities.


Author(s):  
Y. Y. Wang ◽  
H. Zhang ◽  
V. P. Dravid ◽  
H. Zhang ◽  
L. D. Marks ◽  
...  

Azuma et al. observed planar defects in a high pressure synthesized infinitelayer compound (i.e. ACuO2 (A=cation)), which exhibits superconductivity at ~110 K. It was proposed that the defects are cation deficient and that the superconductivity in this material is related to the planar defects. In this report, we present quantitative analysis of the planar defects utilizing nanometer probe xray microanalysis, high resolution electron microscopy, and image simulation to determine the chemical composition and atomic structure of the planar defects. We propose an atomic structure model for the planar defects.Infinite-layer samples with the nominal chemical formula, (Sr1-xCax)yCuO2 (x=0.3; y=0.9,1.0,1.1), were prepared using solid state synthesized low pressure forms of (Sr1-xCax)CuO2 with additions of CuO or (Sr1-xCax)2CuO3, followed by a high pressure treatment.Quantitative x-ray microanalysis, with a 1 nm probe, was performed using a cold field emission gun TEM (Hitachi HF-2000) equipped with an Oxford Pentafet thin-window x-ray detector. The probe was positioned on the planar defects, which has a 0.74 nm width, and x-ray emission spectra from the defects were compared with those obtained from vicinity regions.


1997 ◽  
Vol 7 (C2) ◽  
pp. C2-515-C2-516
Author(s):  
H. Agren ◽  
L. G.M. Pettersson ◽  
V. Carravetta ◽  
Y. Luo ◽  
L. Yang ◽  
...  

1980 ◽  
Vol 41 (12) ◽  
pp. 1431-1436 ◽  
Author(s):  
M. Larzillière ◽  
F. Launay ◽  
J.-Y. Roncin

1979 ◽  
Vol 40 (C2) ◽  
pp. C2-417-C2-419
Author(s):  
C. H.W. Jones ◽  
M. Dombsky
Keyword(s):  

1974 ◽  
Vol 35 (C6) ◽  
pp. C6-324-C6-324
Author(s):  
A. G. MADDOCK ◽  
A. F. WILLIAMS ◽  
J. FENGER ◽  
K. E. SIERKIERSKA
Keyword(s):  

1987 ◽  
Vol 48 (C9) ◽  
pp. C9-1059-C9-1062
Author(s):  
P. J. DURHAM ◽  
C. F. HAGUE ◽  
J.-M. MARIOT ◽  
W. M. TEMMERMAN

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