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- All Subjects: Neuroscience
- Creators: Harrington Bioengineering Program
- Creators: Gallitano, Amelia
Environmental and genetic factors influence schizophrenia risk. Individuals who have direct family members with schizophrenia have a much higher incidence. Also, acute stress or life crisis may precede the onset of the disease. This study aims to understand the effects of environment on genes related to schizophrenia risk. It investigates the impact of sleep deprivation as an acute environmental stressor on the expression of Htr2a in mice, a gene that codes for the serotonin 2A receptor (5-HT2AR). HTR2A is associated with schizophrenia risk through genetic association studies and expression is decreased in post-mortem studies of patients with the disease. Furthermore, sleep deprivation as a stressor in human trials has been shown to increase the binding capacity of 5-HT2AR. We hypothesize that sleep deprivation will increase the number of cells expressing Htr2a in the mouse anterior prefrontal cortex when compared to controls. Sleep deprived that mice express EGFP under control of the Htr2a promoter displayed anteroposterior gradients of expression across sagittal sections, with concentrations seen most densely within the prefrontal cortex as well as the anterior pretectal nucleus, thalamic nucleus, as well as the cingulate gyrus. Htr2a-EGFP expression was most densely visualized in cortical layer V and VI pyramidal neurons within the lateral prefrontal cortex of coronal sections. Furthermore, the medial prefrontal cortex contained significantly cells expressing Htr2a¬-EGFP than the lateral prefrontal cortex. Ultimately, the hypothesis was not supported and sleep deprivation did not result in more ¬Htr2a-EGFP expressing cells compared to basal levels. However, expressing cells appeared visibly brighter in sleep-deprived animals when compared to controls, indicating that the amount of intracellular Htr2a-GFP expression may be higher. This study provides strong visual representations of expression gradients following sleep deprivation as an acute stressor and paves the way for future studies regarding 5H-T2AR’s role in schizophrenia.
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
Advancing the understanding and treatment of many neurological disorders can be achieved by improving methods of neuronal detection at increased depth in the mammalian brain. Different cell subtypes cannot be detected using non-invasive techniques beyond 1 mm from cortical surface, in the context of targeting particular cell types in vivo (Wang, 2012). These limitations in the depth of imaging and targeting are due to optical scattering (Ntziachristos, 2010). In order to overcome these restrictions, longer wavelength fluorescent proteins have been utilized by researchers to see tagged cells at depth. Optical techniques such as two-photon and confocal microscopy have been used in combination with fluorescent proteins to expand depth, but are still limited by the penetration depth of light due to optical scattering (Lee, 2015). This research aims to build on other detection methods, such as the photoacoustic effect and automated fluorescence-guided electrophysiology, to overcome this limitation.