Interdisciplinary

Making Learning Visible in the Clinical Team-based Simulations

In the medical field, the concept of “breaking bad news” is incredibly important for future doctors and social workers to practice and receive meaningful feedback on. The moment a medical professional tells a family member bad news, that instance stays with the patient’s family for the rest of their life. Our team transcribed, analyzed, and interpreted over 150 medical simulation videos to analyze body language, tone of voice, and responses to see how they reacted to feedback from debriefers. Our goal is to optimize the feedback given in order to fully prepare future medical professionals for this critical task. This study was conducted on a sample of over 150 fifteen-minute long videos of medical and social work students debriefing with supervisors about their breaking bad news standardized patient simulation.

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Neutrophil depletion’s effect on lung cancer

jmanassa

Lung cancer remains the leading cause of cancer-related deaths worldwide, with non-small cell lung cancer (NSCLC) making up 85% of lung cancers. NSCLC is comprised of adenocarcinomas and lung squamous cell carcinoma and develops primarily in individuals over the age of 55 who regularly smoke. Current research on the tumor microenvironment revealed that neutrophils, a type of white blood cell responsible for fighting infections, actually aids tumor progression by allowing the creation of chemotaxis that promote tumor metastasis. Additionally, current immunotherapies are only 30% effective. This study looks specifically at how neutrophils affect the tumor microenvironment (TME). We hypothesized that if neutrophils depleted in mice with adenocarcinoma they would decrease in tumor burden, as the chemotaxis transport mechanism for cancer cells would be gone. We have established a murine model of lung cancer, wherein expression of oncogenic Kras and p53 can be controlled genetically, allowing activation of oncogenic Kras to initiate tumor growth, tumor eradication upon Kras depletion and re-activation as a means to model relapse, and p53 speeds up tumor progression. Control mice were used alongside our cancer inducible mice, to test the effects of neutrophil depletion. Half of the mice were given the antibody IgG that has no effect on neutrophil depletion while GR-1, a neutrophil depleted antibody was given to the other half. After 4-week treatment, we took lung tissue; paraffin embedded it and stained it with HE. Tumors were counted and the subsequent analysis revealed 1) Mice with both Kras and p53 on have more tumors than those with just Kras on 2) Neutrophil depletion resulted in lower tumor counts for mice. In summary, neutrophils play likely a tumor-promoting role in lung cancer. Depletion of neutrophils by antibodies resulted in a decrease in tumor burden suggesting new treatment option for lung cancer patients by modulating TME.

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Dark Matter searches with LZ

eflosky

In the universe, the orbital mechanics of stellar objects is explained by their gravity and hence their mass. For example, our understanding of gravity tells us that when an object orbits an amount of matter gets farther away from that mass, the object’s orbital velocity will decrease. Using optical observations of galaxies we observe that their matter is concentrated at their center. However, we measure the velocity of stars at the fringe of galaxies, their velocities are much faster than what we would expect. To explain this observation, many scientists believe that some sort of invisible matter exists that causes these observations. It is known as Dark Matter. The LUX Zeplin team is currently building a detector one mile underground to discover if this matter exists. Later in 2021, the LZ detector will finally go online and start to collect data. It is expected that if Dark Matter exists, it is a particle that would have a mass of 1 GeV or thousands of GeV heavier. The team hopes that the detector will be able to observe particle interactions, among them rare dark matter interactions, and be able to analyze them to search for these Dark Matter events. Then LZ physicists will analyze this data and will come to a conclusion on dark matter’s existence. If found, this new type of matter will help explain orbital velocity observations and may even deepen our understanding about the development of the universe.

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Characterizing Black Hole Binary Outbursts: X-ray Characterization of AT2019wey

astrorya

AT2019wey is a transient optical source discovered in late 2019 and identified as a bright X-ray by the eROSITA X-ray telescope in early 2020. The nature of the source is unknown, with the source location and outburst properties suggesting an origin in a Galactic low mass X-ray binary. Herein, we present an analysis of multiple observations of AT2019wey made by the Neil Gehrels Swift Observatory over the course of 6 months in 2020. X-ray spectra in the 1 – 10 keV energy band have been modeled with an absorbed power-law model to study the temporal evolution of the X-ray properties of the source. Over time, the power-law photon index is observed to increase as the source brightened, consistent with the emergence of a prominent accretion disk. We discuss the results of this analysis and place constraints on the nature of this system in the context of models for accreting black holes and neutron stars.

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Transient and Variable Sources in the Gaia and Chandra Catalogs

mwanink

Large scale datasets are now being created across multiple wavelength regimes, and are crucial tools in our effort to probe many questions in Astronomy. Herein, we present an effort to identify candidate black hole and neutron star binaries via a cross comparison of the variable stars identified in the GAIA DR2 data release comprising >600 thousand sources and the population of >300 thousand X-ray sources identified by the Chandra X-ray telescope. Data from the GAIA catalog has been filtered to create a table for comparison with the point sources in the Chandra Source Catalog. We will present the results of this comparison and discuss the possibilities of comparing the different data sets. While this project focused on isolating a subset of stars from the GAIA data, the process of doing so and the comparisons made are just the first steps of what can be done with these data sets and what can be done on a much larger scale.

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Rb Magnetometer Evaluation for nEDM Experiment

dannycol

The neutron electric dipole moment (nEDM) experiment at Los Alamos National Laboratory will require the magnetometers to monitor the temporal change of the magnetic field and gradient of the magnetic field in the apparatus with precision of 50 femtoTesla (fT) and 100 fT/15cm, respectively. We evaluate commercial rubidium based magnetometers as candidates for use in the experiment by investigating their clock frequency bias, internal noise, and gradient drift sensitivity. We make these measurements in our lab with an apparatus consisting of three magnetometers linearly spaced, and parallel to the axis of a solenoid surrounding them. The solenoid produces a uniform magnetic field and is surrounded by a two or three layer magnetic shield. Measurements from all three magnetometers are used to gather the individual magnetometer readings, difference of pairs, average of three, first order gradients, and second order gradients. These metrics are evaluated with Allan Deviation studies to quantify their stability. QuSpin’s Total-Field Magnetometer (QTFM) shows promising results because its clock frequency bias is negligible, and it has a field sensitivity below 40 fT when averaged over 10 seconds. Additionally, we plan to evaluate custom magnetometers from Twinleaf, LLC.

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Modeling Cas9 efficiency in cutting Long Interspersed Nuclear Elements 1 through Biopython

atbooker

Transposable elements (TEs), DNA sequences that can change their position within the genome, can result in mutations associated with somatic and heritable diseases. TEs are repetitive in the genome and are therefore hard to map. In this study, we determined definitive mapping of one set of TEs, called Long Interspersed Nuclear Elements 1 (L1), through the utilization of recent technology, specifically CRISPR-Cas9 and nanopore sequencing. However, the cutting precision of Cas9 must be deduced for efficient mapping of these elements. This study aims to better understand the cutting preferences of Cas9 in the context of the L1 sequence by exploring how Python can map transposable elements in the genome. The biological analysis and mapping of these reads through the use of Biopython will result in a better understanding of the cutting preferences of Cas9 and its efficiency. Through an RNA guide, Cas9 targets and cuts at a specific region of DNA, where nanopore sequencing will then read the L1 retrotransposons. This data will be processed through the use of Biopython’s modules. A “for” loop was used to: extract individual reads contained within the input data files; perform a local alignment of each read to L1; and obtain the positions of the alignments with respect to L1. We also accounted for reads that align to the reverse complement of the L1 sequence by comparing the two scores obtained from the local alignments. Our data demonstrates that the median starting alignment position is consistent between alignments of the reads to L1 and its reverse complement. Thus, we conclude that Cas9 cutting occurs approximately 5900 bp downstream in L1. However, further analysis of the location of PAM sites and the RNA guide is necessary to confirm Cas9’s efficiency and function.

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Modeling Cas9 efficiency in cutting Long Interspersed Nuclear Elements 1 through Biopython

prparana

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Brain Networks for Fear Learning in Infant Rats

eshakaul

In this lab, we are conducting experiments to seek a better understanding about the correlation between behavior and the brain structure. More specifically, we are using fear conditioning and analyzing certain areas of the brain to see this correlation. This study is able to give insight by using infant rats and looking into how the brain network works when they are encountered by a “threatening stimuli.” Through the process of immunohistochemistry, we are able to examine slices of the brain and use specific proteins to highlight neurons that are associated with the behavior that occurs during the fear learning process. The desired section of the brain that is known to be associated with learning is called the amygdala, which is heavily analyzed in our study. This is important for us to understand how fear impacts our brain networks and can possibly reveal limitations that can be further explored (White).

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