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- All Subjects: Imaging
- Creators: Stabenfeldt, Sarah
- Creators: Frakes, David
- Status: Published
Methods: A virtual, 3D library of clinically-defined normal hearts was compiled from reconstructed CT and MR scans. Non-invasive imaging parameters and patient characteristics were collected and subjected to backward elimination linear regression to define a model relating patient parameters to the total cardiac volume. This regression model was then used to retrospectively accept or reject an ‘ideal’ donor graft from the library for 3 patients that had undergone heart transplantation. Oversized and undersized grafts were also transplanted to qualitatively analyze virtual transplantation specificity.
Results: The backward elimination approach of the data for the 20 patients rejected the factors of BMI, BSA, sex and both end-systolic and end-diastolic left ventricular measurements from echocardiography. Height and weight were included in the linear regression model yielding an adjusted R-squared of 82.5%. Height and weight showed statistical significance with p-values of 0.005 and 0.02 respectively. The final equation for the linear regression model was TCV = -169.320+ 2.874h + 3.578w ± 73 (h=height, w=weight, TCV= total cardiac volume).
Discussion: With the current regression model, height and weight significantly correlate to total cardiac volume. This regression model and virtual normal heart library provide for the possibility of virtual transplant and size-matching for transplantation. The study and regression model is, however, limited due to a small sample size. Additionally, the lack of volumetric resolution from the MR datasets is a potentially limiting factor. Despite these limitations the virtual library has the potential to be a critical tool for clinical care that will continue to grow as normal hearts are added to the virtual library.
Time-Lapse Visualization of Microglia Cell Processes using Fluorescent Miniature (Miniscope) Imaging
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.