The World Health Organization estimates that one of the main consequences of global warming will be an increased burden of mosquito-borne diseases. The spatial complexity of mosquito-borne diseases is currently thwarting control efforts. The challenge is to understand how individuals, their movements and interactions, and the environment, each contribute to determining the local spread of disease. The collective behavior and interaction networks of ant colonies are analogous in some ways to those of human populations.
What makes individuals different? How and when do differences appear during early embryogenesis? Can we identify the sources of these differences, from random processes to precise mechanisms? These classical questions can be re-explored based on the quantitative reconstruction of multi scale dynamics from in vivo and in toto 4D images of developing model organisms (e.g. sea urchin, zebrafish…).
Is the spacetime we are living in the boundary of some higher-dimensional geometric structure? This question, broadly known as the holographic principle, has its quantum counterpart: what physical content is encoded in the asymptotic structures of a spacetime? Two different models are provided by asymptotically de Sitter and anti-de Sitter spacetimes, and one can ask how a quantum theory can be described in terms of data on the horizon.
Bacteria are extraordinarily important to many aspects of our existence, and are both extremely useful, and extremely dangerous, to humans. Many bacteria, both beneficial and harmful, have two cellular membranes: an inner membrane which contains most vital cellular processes, and an outer membrane that serves as a protective barrier from the outside world.
Despite big advances in disease management, hepatocellular carcinoma (a primary liver cancer) remains the second most common cause of cancer death worldwide. Indeed, 50% of hepatocellular carcinoma patients suffer from intermediate and advanced disease due to resistance to current anti-cancer drugs, lack of tools to detect very early disease, and underlying liver disease that limits the use of drugs. Anticancer treatment is highly dependent on the delivery of the drug to the tumor.
The striatum is a brain structure that is highly involved in motor action and reward-based behaviors, and its dysfunction is associated with many important neurological and psychiatric disorders such as Parkinson’s and Huntington’s disease. At the gross-anatomical level, the striatum is known to have several distinct sub-regions, each of which may play a different role in striatum-dependent behaviors. However, at the cellular level these sub-regions are similarly made up of striatal spiny projecting neurons, and are apparently indistinguishable.
Advancement in the field of cancer treatment is critically tied to the human immune system. For example, a healthy individual’s immune system can eliminate cells that become malignant. However, when the immune system is overwhelmed by increased disease or immunosuppression, cells can transform and escape immune action. Cells that escape the immune system rapidly proliferate, leading to the disease state known as cancer. Understanding how these malignant cells evade the immune system is key in re-activating the immune system to clear the cancer.
California’s geology, mining history and atmospheric deposition have led to an accumulation of the toxicant mercury in the Bay Area, with troubling implications for human and environmental health. Although mercury is well studied in aquatic ecosystems, little work has focused on the terrestrial pathway. The challenge is to determine how and where mercury is made bioavailable from soil to other organisms. We know that decomposition, as performed by earthworms, should make mercury more bioavailable to other organisms.
I developed a model to understand protein-RNA subject interactions. The lab I worked in had already developed ways to predict protein-protein and protein-DNA interactions, so I was building on a lot of already accomplished work. I read papers, gathered a dataset, curated the dataset, studied the 3D structures of proteins, and ran a series of tests and statistical analysis to build a protein-RNA interaction prediction model. In the end, I finished the summer with promising results and helped put together a plan for the next steps of the analysis.
I worked in a research lab under France’s National Institute of Health and Medical Research (INSERM) in Paris. I was assigned a Ph.D. advisor, who helped me realize my own research project. The lab specializes in studying DNA damage in yeast cells, and they currently use an enzyme that can make precise DNA breaks. However, currently, there is no way to stop the enzyme from persistently damaging the DNA after the cell repairs it. My project was to create a system that under certain conditions can degrade the enzyme.