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- All Subjects: Bioengineering
- All Subjects: TBI
- Creators: Stabenfeldt, Sarah
- Status: Published
In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
Traumatic brain injury (TBI) is defined as an injury to the head that disrupts normal brain function. TBI has been described as a disease process that can lead to an increased risk for developing chronic neurodegenerative diseases, like frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). A pathological hallmark of FTLD and a hallmark of ALS is the nuclear mislocalization of TAR DNA Binding Protein 43 (TDP-43). This project aims to explore neurodegenerative effects of TBI on cortical lesion area using immunohistochemical markers of TDP-43 proteinopathies. We analyzed the total percent of NEUN positive cells displaying TDP-43 nuclear mislocalization. We found that the percent of NEUN positive cells displaying TDP-43 nuclear mislocalization was significantly higher in cortical tissue following TBI when compared to the age-matched control brains. The cortical lesion area was analyzed for each injured brain sample, with respect to days post-injury (DPI), and it was found that there were no statistically significant differences between cortical lesion areas across time points. The percent of NEUN positive cells displaying TDP-43 nuclear mislocalization was analyzed for each cortical tissue sample, with respect to cortical lesion area, and it was found that there were no statistically significant differences between the percent of NEUN positive cells displaying TDP-43 nuclear mislocalization, with respect to cortical lesion area. In conclusion, we found no correlation between the percent of cortical NEUN positive cells displaying TDP-43 nuclear mislocalization with respect to the size of the cortical lesion area.
Annually approximately 1.5 million Americans suffer from a traumatic brain injury (TBI) increasing the risk of developing a further neurological complication later in life [1-3]. The molecular drivers of the subsequent ensuing pathologies after the initial injury event are vast and include signaling processes that may contribute to neurodegenerative diseases such as Alzheimer’s Disease (AD). One such molecular signaling pathway that may link TBI to AD is necroptosis. Necroptosis is an atypical mode of cell death compared with traditional apoptosis, both of which have been demonstrated to be present post-TBI [4-6]. Necroptosis is initiated by tissue necrosis factor (TNF) signaling through the RIPK1/RIPK3/MLKL pathway, leading to cell failure and subsequent death. Prior studies in rodent TBI models report necroptotic activity acutely after injury, within 48 hours. Here, the study objective was to recapitulate prior data and characterize MLKL and RIPK1 cortical expression post-TBI with our lab’s controlled cortical impact mouse model. Using standard immunohistochemistry approaches, it was determined that the tissue sections acquired by prior lab members were of poor quality to conduct robust MLKL and RIPK1 immunostaining assessment. Therefore, the thesis focused on presenting the staining method completed. The discussion also expanded on expected results from these studies regarding the spatial distribution necroptotic signaling in this TBI model.