The goal of Cosmic Microwave Background (CMB) instrumentation in the POLARBEAR polarization experiments is to improve the sensitivity of our instruments so we can more accurately measure CMB radiation with less noise. My project involves developing and assembling the window anti-reflection setup so that the window can maximally collect light. Achieving this is crucial as this is where we first manipulate light to later be analyzed. This will involve testing materials for their dielectric properties, reducing thermal emission, and designing apparatus to fabricate the window setup. The final product of my project will be the completed window, which will be deployed to the telescope in Chile.
Previous RNA-Seq analysis on mouse embryos revealed non-canonical mRNA splicing involving retrotransposon (RT) elements during pre-implantation development. The retrotransposon-element derived, non-canonical isoforms appear to be the dominant isoform in over 200 genes during critical stages of development. Specific retrotransposon-element knockout mice had been made to investigate possible developmental roles of the non-canonical gene regulation and protein expression. Preliminarily, heterozygous crosses between mice lacking a single retrotransposon fragment shows a statistically significant shift away from the expected mendelian ratio. In this project, through biochemical, histological and biostatics analysis, I aim to explore the phenotype associated with CRISPR-Cas9 deletion of the RT derived isoform of the nearby gene to explain the decrease in viability. This is one small step in the direction of understanding the role of retrotransposon, traditionally considered as “Junk DNA”, in embryo pre-implantation development.
This summer, I will continue to work at the Grinberg Lab (I started there in Fall 2017) on the AVID project where the ultimate goal is to alter the PET scan to be able to identify Alzheimer’s disease earlier in patients. My team works to scan high-quality images of slices of the brain. We then stitch these images together and use machine learning to identify concentrations of tau, a protein linked to Alzheimer’s, in the human brain. One of our final products will be a heat map of the analyzed brains in order to display the concentration of tau.
I will be going to Niger to analyse ethnographic research for the Center for Girls’ Education which is part of the OASIS initiative. The Center is expanding to Niger, and this research will allow it to take into account then specific dynamics and characteristic of rural Hausa communities in Niger in order to implement a more tailored program geared towards women’s empowerment in that region.
Wetlands in the San Francisco Bay-Delta have been threatened by encroaching development, climate change and other environmental factors. Local organization and agencies have provided significant efforts to protect and restore the large amount of wetland ecosystems lost over a century of development. For several years, Dronova Lab has been collecting and analyzing vegetation data in the San Francisco Bay-Delta in order to provide quantitative support for restoration effort in the San Francisco Bay-Delta by identifying factors that can promote restoration success at the site and landscape scale. This critical knowledge could then be used by local organizations and agencies to improve the planning and design of future projects. Through a combination of field assessment and analysis of satellite imagery, we can better understand the factors that contribute to a restoration projects success, or what might trigger a projects failure. This summer I will be continuing this research, with a focus […]
The underlying biophysical properties of cortical neurons such as different ion channels distribution determine their behavior. Currently, neuroscientists do not have a method to accurately determine the distribution of different ion channels in different parts of a neuron. This creates a big gap in understanding neuronal mechanisms in health and diseases. In this project we are developing a framework for predicting a neuron’s ion channels distribution by fitting models to empirical voltage recordings of cortical neurons. However, the immense computational complexity in addition to the nonconvex nature of this fitting problem makes it very difficult to generate highly accurate models. Using our framework, we were able to constrain simple models very accurately and we are now testing on more complex models. We are mainly focused in studying how mutations found in autism spectrum disorders affect the neuronal functions of individual neurons in the cortex of mice.