# Advancing Biological Research: New Automated Analysis of Immunofluorescence Signals
## 3 Results
### Validation Systems
#### 3.3.2 Nrf2 Quantification in SH-SYSY Neuronal Cells Subjected to Oxidative Stress  
In order to evaluate the versatile functioning of Q-IF workflow in different biological scenarios, we also test its performance in a neuronal-derived cell line, having different morphology and phenotypic features compared to skin fibroblasts. Differentiated SH-SYSY cells are treated with hydrogen peroxide for 24 h to induce rapid ROS accumulation and subsequent oxidative stress. Next, the IF for Nrf2 is performed. Nrf2 is highly unstable during normal conditions, as it undergoes continuous proteasomal degradation. Conversely, under oxidative conditions, Nrf2 stability is enhanced and protein levels increase, particularly at the nuclear level, where it binds to antioxidant response elements (ARE). This enhancer sequence is found in the promoter region of several genes encoding detoxification enzymes, ensuring an efficient antioxidant response [19; 20]. Ten images are acquired and subjected to fluorescence intensity quantification. Figure 7 shows that also in this context, the tool effectively generates consistent and reliable results. Indeed, the manual analysis of the images (Figure 7A) and the automatic analysis (Figure 7B) provide similar results as reported in the graphs. Figure 6: Representative images (**A**) of 8-OHdG (red) performed on control and H\({}_{2}\)O\({}_{2}\)-treated fibroblasts. Quantification of fluorescence intensity by manual image analysis (**B**) and by Q-IF tool (**C**). n = 8. The black dots distributed around the SD represent individual values, each derived from the average fluorescence of the cells analysed in a single image (each image is from a different experiment). Statistical analysis is performed using the unpaired Student’s \(t\)-test. ***\(p\) < 0.001. In detail, Q-IF reports a three-fold increase in Nrf2 fluorescence intensity between control- and H\({}_{2}\)O\({}_{2}\)-treated cells, a value perfectly comparable to that obtained by automatic analysis performed by the operator. The reliability of the automatic method is validated not only by calculating statistical position indexes such as the mean of the fluorescence intensity of the two experimental groups but also by applying the Student's \(t\)-test, which reports, for both analyses, a value of \(p\) < 0.001. Furthermore, also the statistical dispersion index SD, which expresses the dispersion of the data around the mean, has an approximately identical value between the two methods of analysis, suggesting low signal variability in the 10 analysed photos, regardless of the method used. To test the sensitivity of the software to correctly measure differences in fluorescence intensity, we then perform an additional experiment using the neuronal cell line SH-SYSY. The experiment is set up as previously described and oxidative stress is induced by the administration of hydrogen peroxide. To obtain experimental groups with different fluorescence intensities and to test the detection range of Q-IF, fixed cells are incubated with increasing dilutions of anti-Nrf2 antibody (1:500, 1:250, 1:50). As expected, confocal microscopy observation confirms an increasing fluorescence intensity in the three different groups, proportional to the antibody concentration (Figure 8A). In detail, both manual analysis and automated Q-IF quantification record a 2-fold increase in fluorescence between the 1:500 and 1:50 groups (Figure 8B,C). Concerning the comparison between the 1:500 and 1:50 groups, the manual analysis reports a 4-fold increase, compared to 3.5 for Q-IF. Despite the larger SD, especially in the group incubated with the antibody at the 1:500 dilution, Q-IF analysis efficiently discriminates among the different fluorescence signal  
Figure 7: Representative immunofluorescence (**A**) of Nrf2 (red) performed on control and H\({}_{2}\)O\({}_{2}\)-treated SH-SYSY. Mean fluorescence intensity quantification protein by manual image analysis (**B**) and Q-IF tool (**C**). n = 10 different experiments. Data represent mean \(\pm\) SD.