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Hilar Prox1 Cells Quantification

These are a series of scripts in JavaScript for Photoshop, Python scripts and macros in ImageJ to estimate the number of immuno-reactive Prox1 cells in the hilus of the dentate gyrus of the hippocampus in mice.

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Hilar Prox1 Cells Quantification

The scripts can be used individually . You can go ahead and copy each script or copy the ones you are interested in.

Immunohistochemistry

The first step is to perform Immunohistochemistry for Prox1 in free floating brain sections as explained in Myers et al 2013. Then sections need to be dehydrated an coverslipped in permount and photographed with a brightfield microscope and digital camera.Photographs need to be taken at a 20X magnification.

Fig.1 - Prox1 immunohistochemsitry from a mouse hippocampal section. GCL= granule cell layer; ML= molecular layer.

Folder Structure

For each animal you need to create a folder for each section and label each as "Section1","Section2", etc. Take the pictures of each section and save them on the corresponding folder.

Fig. 2 - Folders

Scripts

For each of the following steps there is a folder with macros and scripts.

Note: These steps need to be completed for each animal.

  1. Photomerge the images by using the JavaScript script from Step1 in Photoshop.After photomerging make sure the sections are in order and make sure to label each section with a number that corresponds to the position of each section.
    Fig. 3 - Sections
  2. After photomerging all the images. Draw the regions of interests(ROI)s as indicated in Step1.5.
    Fig. 4 - Example of the GCL region of interest.
    Fig. 5 - Example of the Hilus region of interest.
  3. Then proceed to create ROI binary images from the alpha channels using the JavaScript in Step2 called "Fill_All.jsx". In the scripts change the name of the ROIs that you wish to create binary images. To create an ROI that corresponds to two ROIs uncomment the line that extends the selection.
  4. After creating the binary images create the ROIs in ImageJ by running the ImageJ macro in Step3.
  5. Then create the thresholded images using an ImageJ macro in Step5.
  6. Then create txt files with the number of cells in each section by using the ImageJ macro in Step6.
  7. Organize the count txt data into a csv file using the Python script in Step8.
  8. Organize the area txt data into a csv file using the Python script in Step7.
  9. This step is optional. Orgnize and plot the data of all the animals by using the Python script in Step9.

Note: All the scripts are a work in progress and were written for my use. There might be more than one script in each folder. This may correspond to different ROIs or different groups of animals. Example, in these scripts I had the group "P16_P30_P60" and "Cre Bax", and for ROIs I had "H","Hilus", and "SGZ".