3/15/2024 0 Comments Count cell manually imagej fijicFos, a commonly studied IEG, is a proto-oncogene and member of the Fos family of transcription factors. Immediate early genes (IEGs) are rapidly transcribed and translated upon stimulus exposure, making them useful for post-behavioral, correlated readouts of cellular activity 1. The current study demonstrates that SCC is a novel, automated tool to quantify cells in brain tissue and complements current, open-sourced methods designed to detect cells in vitro. Additionally, SCC utilized a new approach to count overlapping cells with a pretrained convolutional neural network classifier. We found SCC to be highly accurate and efficient in quantifying cells with circular morphologies that expressed cFos. ![]() In Experiment 3, SCC analysis was conducted on images it was not trained on, to assess its general utility. In Experiment 2, performance analytics of OCFU, IMJM and SCC were compared. The absolute error in counts (manual versus automated method) was calculated and error types were categorized as false positives or negatives. In Experiment 1, manually-obtained cell counts were compared to those detected via OCFU, IMJM and SCC. Therefore, we created SimpylCellCounter (SCC), an automated method to quantify cells that express cFos protein, an index of neuronal activity, in brain tissue and benchmarked it against two widely-used methods: OpenColonyFormingUnit (OCFU) and ImageJ Edge Detection Macro (IMJM). Manual quantification of activated cells can provide valuable information about stimuli-induced changes within brain regions however, this analysis remains time intensive.
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