Abstract:
OBJECTIVE:The objective of this study was the identification of the stain HIF-alpha using the Image Cytometry, and to help to count the positive cells (with HIF-alpha) and the negative cells (without HIF-alpha) from the same sample. METHOD:17 images of renal tissues from male rats of Winstar lineage; overall, there were 12.587 objects (cells) in the images for analysis. The acquired images were then analyzed through the free softwares CellProfiler (version 2.1.1) and CellProfiler Analyst (version 2.0). In the software CellProfiler Anlyst, there was a separation with the classes of the object, using a classifier, and the classes were: 1) class with HIF-alpha and 2) class without HIF-alpha. RESULTS:With the data obtained through Score All, it was possible to calculate the percentage of cells that had HIF-alpha; out of 12.587 objects of the sample, 6.773 (54%) had HIF-alpha and 5.814 (46%) did not have HIF-alpha. Data of sensibility 0.90, specificity 0.84 and standard deviation 0.10 and 0.12. CONCLUSION:The research shows that the free software CellProfiler, through the light microscope, was able to identify the stains, perform the machine's learning, and subsequently count and separate cells from distinct classes (with and without the stain of HIF-alpha).
journal_name
J Immunol Methodsjournal_title
Journal of immunological methodsauthors
Buzin AR,Macedo ND,De Araujo IB,Nogueira BV,de Andrade TU,Endringer DC,Lenz Ddoi
10.1016/j.jim.2017.02.005subject
Has Abstractpub_date
2017-05-01 00:00:00pages
47-50eissn
0022-1759issn
1872-7905pii
S0022-1759(17)30069-8journal_volume
444pub_type
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