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- All Subjects: Neuroscience
- Creators: Harrington Bioengineering Program
- Creators: College of Integrative Sciences and Arts
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.
Okur-Chung Neurodevelopmental syndrome (OCNDS) is a rare disorder characterized by hypotonia, developmental delay, dysmorphic features, and more. It is caused by pathogenic variants on CSNK2A1, the α subunit of protein kinase CK2. CK2 is considered a master regulator involved in many cell functions from cell differentiation and proliferation to apoptosis. Here, we create a potential zebrafish model of OCNDS with CK2 inhibition and characterize fibroblast cells with, K198R, D156E, and R47G variants of CSNK2A1. RNAseq results display a wide range of effects notably in the Myosin Protein superfamily, Insulin-like Growth Factor family, and in proteins related to mitochondrial function and cell metabolism. Factors in cell growth and metabolism across the nervous system and neuromuscular interactions appear to be most affected with similarities in markers to oncogenic states in some cases.
For my thesis, I conducted a study on a healthy pediatric cohort to investigate how DNA methylation of genes related to myelin may predict total white matter volume in a healthy pediatric cohort. The relatively new field of neuroimaging epigenetics investigates how methylation of genes in peripheral tissue samples is related to certain structural or functional features of the brain, as measured by neuroimaging data. Research has already demonstrated that methylation of genes in peripheral tissues is related to a variety of brain disorders. We hypothesized that methylation of myelin-related genes as measured in saliva samples would predict total white matter volume in a healthy pediatric cohort. After processing DNA methylation data from saliva samples from participants, multiple linear regressions were ran to determine if DNA methylation of myelin related genes was related to total white matter volume, as measured by data from structural MRIs. Results showed that these genes, which included MOG, MBP, and MYRF, significantly predicted total white matter volume. Two genes that were significant in our results have been previously shown to produce proteins that are essential to the structure of myelin.
With millions of people living with a disease as restraining as migraines, there are no ways to diagnose them before they occur. In this study, a migraine model using nitroglycerin is used in rats to study the awake brain activity during the migraine state. In an attempt to search for a biomarker for the migraine state, we found multiple deviations in EEG brain activity across different bands. Firstly, there was a clear decrease in power in the delta, beta, alpha, and theta bands. A slight increase in power in the gamma and high frequency bands was also found, which is consistent with other pain-related studies12. Additionally, we searched for a decreased pain threshold in this deviation, in which we concluded that more data analysis is needed to eliminate the multiple potential noise influxes throughout each dataset. However, with this study we did find a clear change in brain activity, but a more detailed analysis will narrow down what this change could mean and how it impacts the migraine state.