All matter in the universe interacts through the force of gravity. Stars group together into galaxies, and galaxies clump together to form groups and clusters. These galaxy clusters are the largest structures in the universe, and even they can be pulled towards each other. When clusters are gravitationally attracted to each other, they can merge and interact in fascinating ways. This merging of galaxy clusters is the focus of my research.
I observe with both ground- and space-based telescopes, using visible light and X-rays, to illuminate different parts of galaxy clusters. When clusters merge, their interactions lend insight into how all structures in the universe form and evolve. For example, when gas from one cluster collides with gas from another cluster, it affects how stars form within the clusters. I measure how this star formation changes based on how crowded parts of a cluster are or how galaxies are moving within a cluster. Studying how stars form in clusters can help astronomers understand how mergers help shape the universe, how galaxies like our own formed and evolved, and where the universe is headed in the future.
Bacterial infections of the digestive tract such as travelers' diarrhea, cholera, and salmonella afflict hundreds of thousands of people each year. Learning more about how bacteria cause disease in humans is part of my project in the Kull lab. Findings from my project will allow for a better understanding of how different bacteria cause disease.
In order for a bacterium of the digestive tract to cause a person to become sick, it must enter the person's digestive tract, adhere to the their cells, and then secrete toxins. These processes are tightly controlled by a family of bacterial proteins called AraC proteins. If this control can be disrupted, the bacteria's ability to cause sickness will be halted. My goal is to better understand what signals AraC proteins use to control these processes, and determine if these signals can be manipulated to stop bacterial infections.
To do this, it is necessary to know the shapes of these proteins. Getting this information is very hard because the proteins are too small even to be seen with a powerful microscope. By shooting X-rays at a crystal made of protein, I can get information that can be used to determine the shape of the protein.
Armed with this information, I can better understand how the protein is working and the signals to which it responds. This may ultimately allow the design of novel treatments for bacterial sickness that will disrupt protein control over important bacterial processes.
The act of seeing is a deceptively simple process. You open your eyes and the entire world, crisp and clear (or blurry, if you need glasses), is right there in front of you. Thus, for the typical, neurologically healthy adult, it is ridiculously easy to scan the visual environment and name (almost) every object that one sees, to be able to approximate one's distance from those objects, and to have a pretty decent idea of their overall three-dimensional shape and their layout within the environment. However, these abilities, which depend on brain processes that take mere hundreds of milliseconds, are really nothing short of biological miracles. The fact that patterns of light hitting the retina (the dark back part of your eyeball that actually captures light from the environment) can create such an incredibly rich and detailed visual representation of the world inside your mind is astounding, and the brain processes that cause it are astoundingly complicated.
I am attempting to dispel some of this mystery by studying how it is that we acquire experience with groups of objects we have never seen before (for example, totally novel, three-dimensional creatures), how that knowledge fits into one's broader (visual and non-visual) knowledge base, and how the representation of this knowledge changes the brain. So, once one has had lots of training with these creatures are they represented more like animals or like asteroids? Does the way in which you learn about these objects affect the way in which they are represented? I attempt to answer these and related questions by using a combination of brain imaging (fMRI), which allows us to peer into the human brain to begin to locate where certain visual processes happen, and visual behavioral (psychophysical) experiments, which allow us to infer the relative timing of perceptual processes that occur between the retinal patterns of light and the visual experience of an object.
When we think of springtime, we think of flowers blooming, birds chirping, and ladybugs munching on aphids that in turn are munching on the roses growing in the garden.We think of springtime as a season ofre-birth, a season that consistently brings fresh growth and the return of life. This timing of natural events, such as date of flowers or insect emergence, is known as phenology, and is something that humans have been paying attention to for centuries. Plants and animals usually use an environmental cue, such as temperature or number of hours of daylight, to cue their phenology of a particular life history trait. In a predictable environment, using that environmental cue might be an excellent way of timing phenology, but changing the environment could affect phenology in undesirable ways. Climate change is altering the phenologies of many species around the world, but we know surprisingly little about what changes in phenology will meanfor the success of organisms. My research focuses on investigating the consequences of changes in phenology, especially the phenologies of plants and pollinators.
For my dissertation research I am investigating the consequences of altered phenology by performing field experiments in the Rocky Mountains of Colorado, where springtime flowering has been found to be closely correlated with snowmelt date. I alter the phenologies of flowering plants by manipulating snowmelt timing. I remove snow from some areas, causing the flowers to bloom earlier in the spring, and I add snow to other areas, causing the flowers to bloom later. My goals are to understand how the changing phenology of flowering plants affects their reproduction and to investigate the mechanisms of any reproductive changes. Plants with manipulated phenology often have reduced reproductive success, and that part this reduction is due to alterations of plant-pollinator relationships. Since over 90% of flowering plants, including many food crops, depend on insects or other animals for pollination, it is important that we understand how changing phenology may affect plants, pollinators, and plant pollinator interactions. I am also trying to determine the likelihood of mismatches in timing of plant and pollinator emergence.
If cancer is like a weed, then cancer stem cells are like the taproots of the cancer. These cells represent a small fraction of the cells of a tumor, but they are responsible for many of the properties that make cancer dangerous. Each cancer stem cell has the ability to generate a new tumor, so they are responsible for recurrences (when tumors grow back after treatment) and for metastasis (when the tumor spreads to other organs in the body). In the case of breast cancer, metastasis is the most dangerous aspect of the disease. We are studying how the genes that cause cancer change the growth patterns of normal breast cells and make them act like cancer stem cells. To do this, we infect breast cells with viruses that carry genes known to drive cancer. Then we measure the way the breast cells grow under different conditions. The application of this work will be to figure out how to kill cancer stem cells. When we can kill cancer stem cells, we will be able to cure breast cancer.
Everyone longs for deep connection. Making and maintaining these connections, however, requires empathy—the ability to recognize and share the emotions of others. We know when we "click" with someone, but is this "clicking" something we can see?
It has been suggested that changes in pupil size can be used as a measure of empathy. Pupils get bigger or smaller in response to external factors such as the color and brightness of an object, but also to internal factors such as mental effort and emotional intensity. Thus, changes in pupil size may give you information about a person's internal state—for instance, how much they are paying attention to you.
My research focuses on emotional connection, and how the eyes can give us information about the quality of this connection. By tracking pupil fluctuations over time, it may be possible to discern how engaged an individual is on a second-to-second basis. Further, emotional resonance does not stop at interpersonal relationships. Art, music, and dance are all mediums that can induce powerful emotions. How might these non-person relationships be expressed in the behavior of the eyes? Do we respond to a favorite piece of music the same way we respond to a close friend? Understanding these questions may lend insight not only into how we forge social relationships with others, but also into helping those who cannot.
Breast cancer is the most diagnosed cancer among women in the modernized world. Though a controversial issue, a breast contrast-MRI screening scan is recommended each year to high-risk women because of MR's high sensitivity to breast tumors. However, breast contrast-MR yields a high number of false positives and leads to stressful biopsy procedures that are sometimes unnecessary. Therefore, there is a growing need for superior biomarkers derived from the cancer lesion during the MR scan, so that the high sensitivity can be matched by a high specificity. We use a Near-Infrared Spectroscopy (NIRS) to augment MR information by providing information about blood content, blood oxygen saturation, water, fat, and scatter components. This functional information has been shown to provide information about tumor malignancy. An instrument that combines MR with NIRS has been developed at Dartmouth to non-invasively image high-contrast intrinsic properties of malignant breast lesions. The best performance in detecting breast lesions is likely to be found by combining these two imaging modalities to couple the strengths of each into one patient exam, and we hypothesize that we will be able to distinguish malignant from benign lesions with statistical significance.
This project has focused on improving the design and performance of the MR-guided NIRS system. Optical fibers are coupled into an MRI breast biopsy system and focus on 3D imaging. Tumors will be characterized based on measurements from the entire breast volume, which is vital to provide accurate quantification. Tissue-simulating phantom work has been shown to recover total hemoglobin levels to within 10% of the correct value. This technology has been demonstrated extensively in healthy human populations. Preliminary results in cancer patients are promising and we expect to improve the specificity of clinical MR-imaging by adding functional information obtained from NIRS.
Last Updated: 7/25/12