Browsing by Author "Baramaki, Iman"

This study aimed to optimize the iDISCO+ tissue clearing method for studying neural networks and proteins expression in intact brain tissue and to establish an efficient analysis pipeline, particularly for analyzing c-Fos-stained brain samples. Additionally, our objective was to utilize iDISCO for investigating the effects of the rapid-acting antidepressant nitrous oxide (N2O), an N-Methyl-D-Aspartate Receptor (NMDAR) antagonist, using c-Fos expression as a biomarker of neural activity. We conducted two experiments: initially, a small-scale study inducing myoclonic seizures with 10% flurothyl (N=6). The cleared samples, immunolabeled with an anti-c-Fos antibody, were imaged using light-sheet microscopy. Despite a good signal-to-noise ratio, we observed limitations in antibody penetration as well as issues with autofluorescence loss and high signal artifacts within the brain ventricles. These findings indicated the need for protocol modifications and optimization. Next, a larger-scale experiment (N=12) with 50% N2O treatment was conducted to investigate its impact on brain activity. DELiVR, a deep learning-based analysis pipeline, was used for cell detection and atlas alignment. Preliminary analysis with DELiVR showed promising results, highlighting the need for further refinement in optimizing the algorithm tailored to the specific datasets. Additionally, an observation suggesting heightened activity in the hippocampal formation and retrosplenial area following 50% N2O administration was noted, consistent with previous literature. While the optimized iDISCO+ protocol successfully addressed earlier challenges, additional research is required to fine-tune the analysis pipeline for reliable quantitative conclusions.