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335 protocols using imagej

1

Western Blot Analysis of PEDF in Rat DRG

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Total protein, Western blot, and subsequent densitometry were performed as described by us previously [5 (link)]. Briefly, total protein was extracted from L4/L5 DRG from three rats (randomised and masked; repeated on 3 independent occasions, total n = 9 rats/group) after DC injury and pooled together to ensure enough protein. Forty micrograms of total protein was resolved on 12% SDS polyacrylamide gels and blotted onto polyvinylidene fluoride (PVDF) membranes (Millipore, Watford, UK) and probed with relevant primary antibodies: goat anti-PEDF (1:500 dilution, R&D Systems) and β-actin (1:1000 dilution, Sigma; protein loading control). Membranes were then incubated with relevant HRP-labelled anti-goat and anti-mouse IgG secondary antibodies and bands were detected using the enhanced chemiluminescence kit (GE Healthcare, Buckinghamshire, UK).
For densitometry, Western blots were scanned into Adobe Photoshop (Adobe Systems Inc., San Jose, CA, USA), and the integrated density of bands was analysed using the built-in-macros for gel analysis in ImageJ (NIH, USA, ImageJ.nih.gov/ij">http://ImageJ.nih.gov/ij) by an investigator masked to the treatment conditions [5 (link), 11 (link), 19 (link)]. Means ± SEM were plotted in Microsoft Excel (Microsoft Corporation, CA, USA).
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2

Objective Evaluation of Dental Adhesion

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Dentist C captured intraoral photographs weekly, and followed up with them for 4 weeks. The photographer was blinded to the process. All teeth were followed up, and there were no dropouts. All intraoral images were captured using a digital camera according to the commonly adopted method [53 (link)]. We objectively evaluated the adhesion ability by previously described methods [45 (link)]. Each photograph was normalized for the color tone, white balance, contrast, size, and angle. Moreover, each red-colored region was extracted using Photoshop CS6 (Adobe, San Jose, CA, USA) by dentist D. The extracted areas were measured in triplicate by ImageJ (ImageJ.nih.gov/ij/">http://ImageJ.nih.gov/ij/, accessed on 11 November 2015) (Figure 1). The measured values were allocated by dentist A to the HC and BC groups.
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3

Quantitative Fluorescence and Blotting Analysis

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Each experiment was performed at least three biological replicates in all graphs. For fluorescence images, the intensity was quantified double‐blindly and measured using Adobe Photoshop CS6 and ImageJ. The band intensity of Western blotting or co‐IP was quantified with ImageJ. All data were expressed as mean ± SEM and were compared using ANOVA followed by a Tukey test (for experimental groups ≥ 3) or an unpaired Student's t test (for experimental groups = 2). Survival data were analyzed by log‐rank tests (Gronke et al., 2010). All statistical analysis was carried out using GraphPad Prism 5 software. A p < .05 was considered statistically significant: * indicates p < .05; ** indicates p < .01; *** indicates p < .001. All images were processed in Adobe Photoshop and assembled with Adobe Illustrator.
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4

Quantifying Protein Localization by ImageJ

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Image processing was done by Adobe Photoshop and ImageJ. For fluorescence intensity quantification in ImageJ, the GFP-Del foci were defined after background subtraction, thresholding. Using these foci as reference, the fluorescence intensity was quantified in other channels.
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5

Quantifying Collagenous Matrix Formation

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Samples were subjected to decalcification in trichloroacetic acid (TCA) for 7 days. Decalcified samples were then embedded in paraffin blocks and serially sectioned (6 μm/slice). Each slice was then stained with hematoxylin and eosin (HE) and Masson's trichrome (MT) in accordance with traditional histological techniques. Stained slices were imaged with an optical microscope (BX 41, Olympus Optical Company, Tokyo, Japan) coupled with a digital camera (Canon T3i, Oita Japan). Images were analyzed using Photoshop CS4 (Adobe Systems Inc., California, U.S.A.) and ImageJ (Freeware, available at ImageJ.nih.gov/ij/">http://ImageJ.nih.gov/ij/). The objective measurement (pixels2) of the formation of collagenous matrix on MT-stained samples was performed at the central region of each sample (200× magnification), also using ImageJ.
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6

Visualizing Neuronal Morphology in Drosophila

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Images were adjusted for brightness and contrast without obscuring data. Images were processed in ImageJ (ImageJ.nih.gov/ij/">https://ImageJ.nih.gov/ij/) and Photoshop (Adobe Systems Inc.). Where noted, neurons were rendered and segmented from confocal stacks with VVDviewer software (https://github.com/takashi310/VVD_Viewer) 77 (link),78 (link) to visualize them in isolation. For this rendering and for computational alignment of brain images used where noted, brain images were registered using the Computational Morphometry Toolkit 79 to a standard brain template (“JFRC2014”) that was mounted and imaged with the same conditions. Segmented image stacks are available at https://splitgal4.janelia.org.
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7

Confocal Imaging of In Vivo Neuronal Morphology

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Confocal imaging of in vivo neuronal morphology was performed as previously described (Das et al., 2017 (link); Turner et al., 2016 (link)). Briefly, third instar larvae were mounted on slides with 1:5 (v/v) diethyl ether:halocarbon oil and imaged on a Zeiss LSM780 confocal system. Z-stacks of class IV md neurons were obtained and neuromorphometric analyses of two-dimensional maximum projections of the z-stacks were performed using Adobe Photoshop and ImageJ (Analyze Skeleton plug in: ImageJ.net/AnalyzeSkeleton">http://ImageJ.net/AnalyzeSkeleton) as previously described, with modification (Iyer et al., 2013 (link)). Statistical significance was tested using one-way ANOVA with Bonferroni multiple comparison post hoc test in GraphPad Prism.
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8

Computational Alignment of Fly Brains

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Images were adjusted for gain and contrast without obscuring data. Images were processed in ImageJ (ImageJ.nih.gov/ij/">https://ImageJ.nih.gov/ij/), Icy (http://icy.bioimageanalysis.org/) and Photoshop (Adobe Systems Inc). Where noted, motor neurons and muscles were rendered and segmented from confocal stacks with VVDviewer software (https://github.com/takashi310/VVD_Viewer), to visualize them in isolation. For this rendering and for computational alignment of brain images used where noted, brain images were registered using the Computational Morphometry Toolkit (http://nitrc.org/projects/cmtk) (Jefferis et al., 2007 (link)), to a standard brain template (‘JFRC2014’) mounted and imaged with the same conditions, which had been corrected by a z scaling factor of 1.568 to match the true proportions of a fly brain (obtained from frontal vs. horizontal stacks of the brain [Ito et al., 2014 (link)]).
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9

Quantitative Analysis of Fluorescent Microscopy Data

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Fluorescent images were analysed using Leica LAS AF, ImageJ (2.1.0) and Adobe Photoshop (CS6). Stitched images were processed from individual tiles by Adobe Photoshop. Ki67+ and BrdU acinar cell nuclei were manually counted. Immunohistochemistry images were analysed with Leica LAS 4.2, ImageJ and Adobe Photoshop. Statistical significance was determined by one-tailed unpaired two-sample t-test. Plots were generated by the ggplot2 package (3.2.1) in R Studio (1.2.5019) and Graphpad Prism (8.7).
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10

Densitometry Analysis of Immunoblot Data

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Densitometry analysis of x-ray films from immunoblotting studies was performed using Adobe Photoshop and ImageJ. Images were converted to grayscale in Photoshop, and the intensity of bands was measured in ImageJ. For each blot, measurements were taken using a constant size selection for regions of interest. Background measurements were also collected from the blank regions located just above these bands. Pixel density was inverted by subtracting the measured intensities of both the band and background regions from 255. Net values were determined by subtracting the inverted densities of the background regions from the inverted densities of their corresponding bands of interest. The net value for each band of interest (e.g., KEAP1) was then normalized to the net value of the loading control for that lane (e.g., β-Actin). Finally, these normalized net values were themselves normalized to the 42.2 °C band in the CETSA experiment and plotted as a function of temperature.
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