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Bland-Altman analyses revealed that Slice-O-Matic and NIH ImageJ results were comparable. Mean AVF values for investigators A and B ranged from 168 to 170 cm(2) using Slice-O-Matic and NIH ImageJ. Regions of interest included abdominal total area, total fat area, subcutaneous fat area, visceral fat area (AVF), and right and left thigh total area, fat area, and skeletal muscle area.įor all images, intra-investigator coefficients of variation ranged from 0.2% to 3.4% and from 0.4% to 5.6% and inter-investigator coefficients of variation ranged from 0.9% to 4.8% and 0.2% to 2.6% for Slice-O-Matic and NIH ImageJ, respectively, with intra- and inter-investigator coefficients of reliability of R(2) = 0.99. Adipose tissue and skeletal muscle cross-sectional areas (centimeters squared) were calculated using standard Hounsfield unit ranges (adipose tissue: -190 to -30 and skeletal muscle: -29 to 150). Two trained investigators analyzed each computed tomography image in duplicate. The method and program are validated using the analysis of the spatio-temporal interactions between a G-protein coupled receptor, the tachykinin NK2 receptor, and the beta-arrestin 2 as an example.To compare reliability and limits of agreement of soft tissue cross-sectional areas obtained using Slice-O-Matic and NIH ImageJ medical imaging software packages.Ībdominal and midthigh images were obtained using single-slice computed tomography. It is particularly adapted when transient expression of the fluorescent proteins is used thereby giving very variable expression levels or when the colocalization of the two partners is varying in proportion, in amount, and in size, as a function of time.
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This method called "FRET and Colocalization Analyzer" has been implemented in a Plug-in of the freely available ImageJ software. Finally, it proposes an alternative to normalization of the FRET intensities to compare FRET signal variations between samples. It displays FRET images as a function of the colocalization of the two fluorescent partners.
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It proposes imaging treatments and the display of control images to validate the BT calculation and the image corrections. Our method reduces the interference of the user to a minimum by analyzing the entire image, pixel by pixel. Authentic FRET signal measurements require the correction from the FRET channel of the undesired bleed-through signals (BT) resulting from both the leak-through of the donor emission and the direct acceptor emission. We present a method for visualization of FRET images acquired by confocal sensitized emission, involving excitation of the donor fluorophore and detection of the energy transfer as an emission from the acceptor fluorophore into the FRET channel. Fluorescence resonance energy transfer (FRET) between an adequate pair of fluorophores is an indication of closer proximity than colocalization and is used by biologists to study fluorescently modified protein interactions inside cells.