Hi Erika,

I don't have any experience with the stomach mucosa but I have some experience with polarised cell types and morphological analysis. From looking at some google images on these cells I would suggest that you simply select a region of interest (ROI) that contains a number of cells in row (I don't know, maybe 15-20 cells/ region???). The ROI is important as it controls for the number of cells analysed, the constant distance analysed...etc., therefore the only variable is the intercellular space. Once you have selected that ROI then I would do a simple measurement of the intercellular spaces between each cell. I would do this in imageJ.

Since you are using TEM you should have the scales (pixels:microns) sorted, which will make things easier. Otherwise if the image opens up in pixels, you can just scale the image pixel depth into microns using the indented TEM scale bar (unless you want to measure in pixels). I personally would aim for 50-100 cells spread over at least three slices/ experimental repeats. This should give you a good N of intercellular spaces to then average and run stats against (control vs treatment group) and I would suggest an easy test such as a Student's T-test just to observe what happens.

If you wanted to get more fancy about it you could go a step further and measure cell perimeter, again using imageJ. Given the fact that you observe larger intercellular spaces you will need to assess if the treatment is reducing cell size or maybe spacing them further apart. Again I would have a similar set-up to the ROI mentioned above. To be honest there a number of things you could do with this as morphological classifications (qualitative into quantitative data) is still quite a recent thing within cell based research! Anyways all the best and it would be interesting to hear the result!

Best,

Chris

I use fluorescence deconvolution microscopy