The Nitrogen-Vacancy (NV) Color Center in Diamond is an optically active defect that has been demonstrated to be an effective nanoscale sensor of external electric and magnetic fields. Crucially, unlike other such sensors (such as SQUIDs or Mossbauer spectrometers), the NV center is capable of in situ, or local, imaging of these external fields. Moreover, for NVs in a diamond anvil cell (DAC) setup, one can perform in situ measurements of electric and magnetic fields in materials at very high pressures. This opens up the possibility of using the NV center to study the behavior of electric fields associated with the transition between a paraelectric and a ferroelectric. In my project, I plan to theoretically investigate the feasibility of studying the ferroelectric transition via the NV center. This will be done by theoretically computing dipole correlations in paradigmatic models of the ferroelectric transition and then characterizing the NVs response to […]
Numerical linear algebra underlies much of the modern world. It is essential to a wide variety situations, and as such, it is of great interest to analyze and optimize the underlying algorithms. In recent years, there has been an increased interest in optimizing algorithms to reduce communication, which is frequently many orders of magnitude slower than performing calculations. The Hlder-Brascamp-Lieb inequality and the Red-Blue Pebbling Game are two powerful approaches to theoretical analysis of communication, and both are used to derive communication optimal lower bounds. Once these bounds have been derived, the next challenge is to implement an algorithm that attains these minimums, and thus, is communication minimizing. Many currently implemented algorithms do not meet these bounds, and this is a matter of great importance, with large potential time and energy savings. In this way, our project has two broad goals. Our first is to implement a communication optimal algorithm […]
Multiple Sclerosis (MS) is a chronic and currently incurable neurodegenerative disease of the central nervous system. While whole brain atrophy for multiple sclerosis cohorts are on average more pronounced than the healthy population, thenatural change due to aging and inherent morphological variability of the human brain has remained a persistent barrier in interpreting whether significant percent variable change in an individual patient is diagnostically relevant. Using FSLs SIENAX/SIENA toolkit and UCLs SPM toolkit on over 10,000 patients and over 50,000 anatomical magnetic resonance imaging scans, we hope to break this barrier by sensitively mapping the natural variability in brain morphological over the human lifespan and the cross-section variability to recognize a patients unique morphological context. Via state of the art cluster techniques, we aim to construct a sensitive diagnostic test that can delineate between healthy aging and pathological processes.
With a rapidly increasing amount of tropical forest threatened by logging and land conversion, there is growing concern about retaining species diversity, and in turn, ecosystem sustainability. My research uses methods from the Operations Research field to incorporate ecological considerations for strategic planning in multi-use tropical forest landscapes. While past research has primarily focused on identifying sites for placing permanent reserves, my research develops optimization tools to create algorithms that apply principles of ecological sensitivity to both reserve patterns and harvest scheduling at once.I am utilizing recent advances in numerical optimization of integer programming problems to include spatial and temporal factors that until recently were difficult to solve with such precision. Varying harvesting patterns in response to species-specific spatial and temporal patterns in addition to reserve planning represents a promising new method inform future sustainability standards for forest management, thereby helping to conserve species diversity and maintain ecosystem function.
Species Distribution Models (SDMs) provide one of the only methods for projecting the future distribution of species and are increasingly used to prioritize conservation efforts. SDMs correlate species’ occurrence points with climatic variables (e.g., temperature and precipitation) to produce a distributional map of the climatic limits of a species. Genetic studies of geographic variation within species, or phylogeography, often uncover cryptic lineages that have remained evolutionarily isolated for thousands to millions of years. My research assesses how identifying cryptic diversity within species affects the predictions of SDMs. Faced with climate change, accurately identifying critical regions for management remains a key issue in effectively conserving Earth’s biodiversity. See Mark’s interview on the Understanding Evolution web site, a project of the University of California Museum of Paleontology.
The immune system monitors the inner workings of all cells of the body in its search for abnormal cells, whether they be infected or otherwise transformed. Every cell displays its intracellular peptides on its surface, and specialized cells of the immune system called T cells examine these peptides. The repertoire of peptides presented on the surface is a representation of the state of the cell; an abnormal peptide repertoire indicates an abnormal cell. An important part of the processing pathway that peptides undergo before being presented is ERAAP, an enzyme that trims peptides. The immune system can detect inhibition of ERAAP, and my project explores the mechanism of this immune response. I will study this with regards to one specific gene that is in the altered peptide repertoire of ERAAP-inhibited cells. By understanding this gene and its presentation on the surface, I hope to elucidate the mechanism of immune response.
Understanding the genetic mechanisms that underlie morphological evolution is a long-standing goal in biology. The threespine stickleback (Gasterosteus aculeatus) is an emerging model organism with features ideal for studying the molecular basis of morphological evolution. Several stickleback populations display evolved differences in tooth number, likely adaptive to match different diets. These differences in tooth number are largely controlled by a Quantitative Trait Locus (QTL), a genomic region controlling a quantitative trait. This QTL is located on chromosome 21 and contains an excellent candidate gene: Bone Morphogenetic Protein 6 (Bmp6). I will use two approaches to test the hypothesis that Bmp6 underlies the chromosome 21 tooth QTL. First, I will use a reverse genetics approach with TALENs (TAL Effector Nucleases) to generate loss-of-function Bmp6 alleles to assess the role of Bmp6 in tooth patterning. Second, I will use a forward genetic approach of recombinant mapping to further fine-map the tooth QTL.
Cancer is a potent disease that occurs when cells acquire certain mutations that cause uncontrollable cell growth. MicroRNAs (miRNAs) are small non-coding RNAs that have been associated in cancer development. In our research, we specifically study the tumor suppressive effects of miRNAs on B cell lymphoma, a type of blood cancer in the lymph nodes. We have determined that the deletion of mir-34a or mir-34bc (tumor suppressive miRNAs) accelerate lyphomagenesis. More recently, it has been shown that there is a homologous cluster of miRNAs, the mir-449 family, suggesting similar functions. While the ultimate goal is to understand how these miRNA clusters interact and collectively act in a tumor suppressive role, I aim to understand the effects of losing the mir-449 cluster alone on lymphomagensis. I propose to determine the extent of acceleration of lymphomagenesis due to the loss of mir-449, and whether this acceleration is through proliferation or cell death.
Nor-1 is a protein that can promote death of CD4+ CD8+ double positive thymocytes, cells in the process of maturing into T cells. In the thymus, these double positive thymocytes undergo a process called negative selection, in which any thymocytes that recognize self-molecules that our own body produces are killed. This makes sure that our body mounts an immune response when it encounters a foreign pathogen. Failure during this negative process results in autoimmune diseases such as systemic lupus erythematosus (the go-to disease whenever someone is sick in the episodes of House), Graves’ disease and rheumatoid arthritis. Presently, the exact molecular mechanism of negative selection is poorly understood. Nor-1 can induce apoptosis (cell death) by assisting in translations of new proteins, but it can also promote cell death by moving into the mitochondria and turning on Bcl-2 into a pro-apoptotic molecule by exposing its killer BH3 domain1. The mechanism for […]
Type Ia supernovae are the thermonuclear explosions of critical mass white dwarves which have reached the Chandrasekar mass through accretion of mass from their binary companion. The near constancy of their maximum intrinsic brightness is the key to the use of these events in cosmological studies. Unfortunately, systematic errors associated with the diversity of type Ia supernovae continue to limit their usefulness as standard candles. I will use a very large spectroscopic and photometric data set gathered by the Palomar Transient Factory (PTF) in order to identify correlations between the stretch parameter of type Ia light curves and a variety of parameters derived from type Ia blackbody spectra. Combining the correlations between photometric and spectroscopic parameters I hope to obtain a new correction to type Ia maximum intrinsic luminosity. Furthermore, I would like to apply this new correction to obtain a new value for Hubbles constant using the PTF data.