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to calculate the Nuclear/Cytoplasmic ratio, simply divide the staining mean intensity i,e MEAN of nuclear/ mean of cytoplasmic. The Mean value is in the results window.

Hello, it looks like the site is down. I can send you the plugin if you provide your email

welcome. the weka segmentation cannot itself be used for cell counts. once you save the image after segmentation, use this image to count cells using imagej separately

Hello, you are welcome. Here is an interesting forum that discuss about calculating intden forum.image.sc/t/mean-gray-intensity-integrated-density-and-raw-integrated-density/4983/2

Hello, have a look at this forum discussion forum.image.sc/t/mast-cells-quantification-toluidine-blue-stained-skin-epidermis-dermis/79478 if you need the weka segmentation according to this discussion here is the link to the video th-cam.com/video/tmPr5Iw_9XY/w-d-xo.html

y axis will be the fold change of the gene expression and x axis will be the names of the test or conditions

you are welcome. if your end result is to analyze cell count etc, then you could try weka segmentation. this could also be a little tricky as your images have almost similar background. however, if trained well, may be this could provide a way out. Let me know if this works for you. The link to the video is th-cam.com/video/tmPr5Iw_9XY/w-d-xo.html

Hello, you are welcome. Could you please send me a sample of your cropped image? i can get back to you after troubleshooting, it is a bit difficult to answer without seeing the image.

@@nrttaye4033 thank you so much for your response. I was able to solve it🙏🏻

After practice, i will measure the diameter of the fibers

You are welcome. need to set the values in pixels. For example if 6 cm corresponds to 100 pixels then you need to input 100. All the best.

Hello, thanks and you are welcome. You can definitely use this for vascular density analysis. For vessel/branch length and numbers please have a look at these videos th-cam.com/video/v5URAQI_lOE/w-d-xo.html th-cam.com/video/sQLYoJxgUCk/w-d-xo.html th-cam.com/video/fcqNutzR7F4/w-d-xo.html

okay i will try to do by this method. but my mexican hat filter is not generating images like yours before 5 months ago when i saw all your videos that time i have done the whole analysis like you showed. but today when i trying to do the analysis the threshold 255 not generating the EDT images. Can you please guide me...Thank You..! can you please perform the above steps and check whether its a software problem or its something else. please rply

Hello, I tried the mexican hat filter and i can confirm that it is working. Could you try changing the threshold value? depending on the image you may also need to select inverse case in the edt. let me know if that worked or i could troubleshoot it if you could send me a sample image.

Thank you for reply..😊 my problem was solved. But I have one request please make video on Angiotool software because no one actually made video and no one knows how to fo analysis using Angiotool. I will share you some images of CAM so it will be easy for you to make video. Please tell me how to share images of CAM?

That would be great. I will get back to know once I am ready with the Angiotool software.

You are welcome. Glad it was helpful

You are welcome. It would depend on the output result you are looking for such as branch numbers, curvature, thickness, length, tracing etc. I think all these parameters may not be analyzed with a single imagej plugin or way of analysis. Hence various methods or combinations may be used. Here are the links th-cam.com/video/3VZ_Qjvmh64/w-d-xo.html th-cam.com/video/sQLYoJxgUCk/w-d-xo.html th-cam.com/video/v5URAQI_lOE/w-d-xo.html all the best with your thesis

Hello, thanks for reaching out. If there is a scale image in one of your mice stomach images, that will be used as the measuring unit/length for all the subsequent images. To set the scale, first draw a line parallel to the scale. It does not matter how long it is drawn. In the above video the line is parallel to 1 cm in the scale. In the known distance input "1" since the line drawn equals 1 cm. in the unit of length input "cm" because this is a cm scale. alternatively you can also input it as 10 mm where known distance will be 10 and unit will be in mm. the distance in pixels will be set automatically. All the best with your experiment.

@@nrttaye4033 can we ask help via email? we are not really sure how to use image J software... especially the sample is the stomach of mice 🥺. We already have here the picture of stomach of mice as sample.

Could you send me a sample image that contains a scale/measurement unit . Happy to help.

@@nrttaye4033 ofcourse! Thank you so much

@@nrttaye4033 can I send it through email?

You are welcome. The whole point of defining threshold is to select the specific area of interest for analyzing. The image may contain debris or noise that needs to be excluded during thresholding. Performing a correct thresholding is necessary to maintain accuracy of quantification. There is a debate amongst the scientific community, whether to keep the thresholding value same or different across all the images during analysis for comparison. Here are links to some discussion that you may find it interesting forum.image.sc/t/how-to-set-threshold-for-image-j-and-then-do-image-calculations/3696 forum.image.sc/t/thresholding-methods-how-to-choose-wisely/25472

Hello, I am not aware of another source.

Hello, you are welcome. Try doing color threshold. Here are links to some related videos th-cam.com/video/Z9-Bb68t6ns/w-d-xo.html th-cam.com/video/8LOYwwv2syU/w-d-xo.html Similar background color issue is a bit tricky (th-cam.com/video/xeAuh_E8z8k/w-d-xo.html) specially if need to count many cells. I had similar instance, and i had to manually count th-cam.com/video/BhFNiPsVRoM/w-d-xo.html

hello, thanks for reaching out. Please check these videos th-cam.com/video/b3Z2t62i9Ds/w-d-xo.html and th-cam.com/video/CP2A-Jt279c/w-d-xo.html

@@nrttaye4033 Hello, thank you very much for the second video, I hadn't seen it yet. It will help me a lot :) Do you also have a video in which you exclude foreign bodies that are along with the filaments? I need to exclude them so that imagej only considers the filamentous ones.

If the filament color is different from the forein bodies, then yes it is possible to first segment the filaments out and then perform the analysis. Here is the link to the video th-cam.com/video/tmPr5Iw_9XY/w-d-xo.html

@@nrttaye4033 wow, you can't even imagine how much you're helping me <3 all the best

Thanks and welcome. I am here to help. All the best with your analysis.

Hello, thanks for reaching out. Here is the video to calculate CTCF th-cam.com/video/WDGmrj4_T1o/w-d-xo.html

You're welcome! Glad you found it useful. Stay tuned for more interesting videos like this.

You're welcome! Glad you found it useful. Stay tuned for more interesting videos like this.

Thank you

Hello, there is an imageJ plugin called MicrobeJ. This plugin may answer your question. Here is the link to the plugin www.microbej.com/download-2/

Hello, thanks for reaching out. sure, here is the link to the video th-cam.com/video/Z9-Bb68t6ns/w-d-xo.html all the best with your experiment.

Hello, you are welcome and thanks for reaching out. I appreciate you watching the video. You asked a great question, so don't stress about your English. It is possible to measure the 'tube length' in the HUVEC tube formation assay by looking for the parameter "show branches, show master segments and show suppressed elements" in the angiogenesis analyzer settings. Yes, you might be interested in looking at the "total branch length" in the results table. Please don't hesitate to ask further questions if you need more information or clarity. I hope your experiments turn out well.

Thank you for kind reply😀 I have one more question then, what does 'total segment length' patameter means?

Hello, thanks for reaching out. The identification of DNA sequences that are biologically relevant TFBS is challenging. The promoter region, located a few hundred base pairs upstream of the TSS, is a hotspot for TFBS. It frequently houses critical regulatory elements such as the TATA box, CAAT box, and GC-rich regions. TFBS can also be located further from the TSS, in enhancers, silencers, and other regulatory areas. The chromatin structure and 3D arrangement of DNA can also influence TF binding. Some TFs bind to locations far from the TSS but brought into close proximity by chromatin looping. Thus, to answer to your question, you can definitely change according to the biological questions being asked.

@@nrttaye4033 Thankyou so much for the reply. I understood what you explained.

Hello, thanks for reaching out. I will reply to your comment with the protocol on Monday. Thanks for watching the video.

Hello, here is the protocol. The seeding density varies with the cell types, (MDA-MB 231 cells) is 5 X 10^5 cells in a 6 well plate. Mitomycin treatment was performed next day and a sterile 10 or 20 ul pipette tip was used to generate the scratch. Washed off the floating cells with complete medium once and scratch images were taken at 10X after 0 and 12 hours.

Hello, vascular density here is calculated as vascular density = vessel area/total area X 100%. The unit of vessel area is pixels. Scale bar option can be used to set your own unit of measurement.

Hello, you can get a number for the speckle area. in the "set measurements" option select "area". now using the free hand selection tool draw the outline of a speckle. now click on analyze and measure. The area in pixels you get is the number that needs to be excluded. On a safer side you may want to put a slightly higher number during analyze particle than the measured speckle area. let me know if that worked

@@nrttaye4033 yes it worked thank you! only problem im now facing is when i press clear outside, the background does not dissapear but the inside of my cells become blue instead?

You are Welcome! Glad you found it useful.

Thank you. you can get a number for the speckle area. in the "set measurements" option select "area". now using the free hand selection tool draw the outline of a speckle. now click on analyze and measure. The area in pixels you get is the number that needs to be excluded. On a safer side you may want to put a slightly higher number during analyze particle than the measured speckle area.

Hello, I am not quite sure about it. It happens when the threholding (red) is mismatched with the foreground/background color. for instance, after binary the thresholded part may need to be black foreground with a white background. If you can send me a sample image I can get back to you after troubleshooting.

hello, could you please re-install the plugin again and then re-start imagej. alternately, for windows/mac users copy the plugin and paste it in the "plugins folder" and re-start imagej or drag the plugin into imagej toolbar and then install. let me know if that worked.

@nrttaye4033 thank you so much. I copied the file in plugin folder and it worked. Thanks a lot ^^

you are welcome. glad it worked

the output image with outline needs to be flattened before saving. In the ROI manager click on Flatten. To save the image Go to file and save as tiff format. Let me know if it worked. alternately, the overlay image can also be saved by clicking on image, overlay and flattened and then save as tiff.

@@nrttaye4033 oh wow it worked!! Thanks a ton. I had been struggling with it since last night. Have a great day!

glad it worked. you are welcome

Hello, I do not have a specific answer to your question. I believe there are enymatic activities taking place during browning of the fruit that may involve further changes in the cells/tissues structures. Cell segmentation can be applied to analyse the particle differences comparing the control vs browning apples. if the ROI of the browning areas are diffcult to select for analysis, try weka segmentation to seperate it first (th-cam.com/video/tmPr5Iw_9XY/w-d-xo.html) and then proceed for morphological analysis.

Hello, thanks for reaching out. Please have a look at this video if that would solve your query th-cam.com/video/cc-bryk_ihw/w-d-xo.html

hello, you are welcome and thanks for reaching out. λ is the wavelength of emitted light. For your second question, i may be able to answer you only after looking a sample image.

hello, click on this website sites.imagej.net/Daerr/plugins/ and download the "Goutte_pendante.jar-20130515204329". now rename the file as "pendante.jar" and install the plugin. in fiji you can find this in plugins, drop_analysis and pendent drop. let me know if that worked.

@@nrttaye4033 OMG its work, thank you so much. I'm very grateful to you <3 <3

glad it worked. you are welcome.

Hello, an image file of 10 Mb or more size takes a very long time to process or it shows an error. please try reducing the file size under Image, adjust and size and then run the process again. alternatively, try changing the brightness or contrast of the tube formation so that it is very distinct from the background color and run again.

Thank you for watching my videos. Gald you found it useful

I agree. That would have made the work significantly easier.

Welcome. Glad you found it useful.

Hello, thanks for reaching out. Please visit this video tutorial th-cam.com/video/Z9-Bb68t6ns/w-d-xo.html

Hello, thanks for reaching out. I do have plans to make a video on mitochondrial network analysis. Please stay tuned.

@@nrttaye4033 I'm very happy about that. I'm really looking forward to that video

Hi, you are welcome. Background removal has to be uniform throughout and not only of a single band. To get an accurate quantification, selecting and removing the background especially at the selection area around the band is critical. in this video, the selected area (near the first band) for background removal would remove all the mean pixel intensities (background) uniformly from the entire blot.

Hello here is the code. It however crops one image at a time while keeping the original image, duplicates, gray, binary and skeletonize. please define the path to save your image run("Duplicate...", " "); numSelections = 2; for (i = 1; i <= numSelections; i++) { run("Specify...", "x=0 y=0 width=0 height=0 oval=false"); run("Crop"); run("8-bit"); setOption("BlackBackground", true); run("Convert to Mask"); run("Skeletonize"); saveAs("Tiff", "//path/path/path/cropped_image_" + i + ".tif"); run("Restore Selection"); close(); }

Hello, are you using mac or windows OS? In addition, have you tried using the lastest version of the ImageJ and then install the plugins? Let me know if that worked.

Hello, thanks for reaching out. ImageJ splits an RGB image into red, green, and blue color channels. In this image, the immunostaining colors are red (cytoplasmic) and blue (dapi), and only the red immunostaining will be quantified. This image shows no green immunostaining and therefore no quantification needed for this channel. As a result, the green channel image is not considered.