Sea ice plays a significant role in the global climate, but the details of summer melt processes remain poorly resolved. Sustained low-wind events over the Arctic Ocean have been observed to correspond to high salinity and temperature stratification in sea-ice leads, consequently increasing lateral melt rates during summer. Such an effect is currently unaccounted for in leading climate models, and appropriate parameterization could potentially reduce error in projections. We used a wind reanalysis dataset produced by the National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) to study wind patterns in the Arctic. We focused on daily variation in oceanic regions at latitudes above 65 degrees during Summer (May 1 - September 30) over 2010-2019. An index of low-wind events was extracted from the reanalysis data and these events were classified according to length of event and geographical extent. Our results suggest that low wind events are frequent throughout the summer, but are not equally distributed spatially across the basin. Low-wind events were compared to other climate data, including sea-ice extent, on a spatial and temporal basis. Our results were compared to climate model output and differences were examined. We propose a basic parameterization of the effect of low-wind events on sea ice melt, and suggest further collection of observational data to improve physical representation in climate models.

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by impairments in social interaction and repetitive behaviors. One of the most common mutations leading to ASD is 15q11-q13 duplication, a CNV mutation where extra copies of a chromosomal region are expressed. The major gene within this region is ube3a. My lab has generated a mice model with increased copies of this gene and demonstrated a novel deficit in phosphorylated-AKT, a key protein in the mTOR/AKT signaling pathway. Other mice models of autism have exhibited deficits in this pathway and have rescued behavioral deficits with a drug, rapamycin. Rapamycin is an inhibitor of a key protein of the mTOR/AKT pathway suggesting a similar behavioral rescue might be observed with ube3a transgenic autism model mice. Behavioral testing of 4 groups of 20 mice, wild type and ube3a transgenic mice treated with and without rapamycin, found that there were no baseline social deficits in ube3a transgenic mice not treated with rapamycin. This is not similar to previously published findings and could be due to a number of reasons. It can be difficult to get consistent results with mice behavioral testing. In order to assess if rapamycin had its intended effect in restoring deficit levels of phospho-AKT, protein levels will be assessed. Brain slices from the hippocampus of behaviorally tested mice will be analyzed by western blot, a method of identifying and measuring specific proteins. Successful rapamycin treatment would be observed as increased levels of phospho-AKT, similar to wild type mice. This would suggest that repeated mice behavioral testing is needed and therapeutic treatment of the mTOR/AKT signaling pathway could be a viable target for patients with 15q11-q13 duplication.

Human Immunodeficiency Virus (HIV) remains on the forefront of research due to the ongoing global epidemic. HIV is comprised of two genetically different types, HIV-1 and HIV-2. HIV-2 is inherently resistant to some classes of antiretroviral drugs, and many HIV-2 patients develop drug resistance to first-line and subsequent regimens. HIV-2 can further be divided into two distinct genetic groups: A and B. While both are endemic to West Africa, group A accounts for the majority of infections and remains the most studied of the two groups. In-depth knowledge of drug resistance in HIV-2 group B is lacking, as only a few patients with drug-resistant virus are described in the literature and there have been no systematic efforts to characterize the drug resistance patterns of HIV-2 group B isolates in cell culture. My project's goal is to build drug resistance mutations, documented in literature, for HIV-2 group A into a full-length HIV-2 group B infectious molecular clone. Those results are used to compare the relative drug resistance conferred by those mutations to the phenotypes observed for equivalent mutants of HIV-2 group A. More specifically, common drug resistance mutations are introduced into the pol gene of a group B clone, individual mutant clones are isolated, and these are used to transfect replication-competent cells for virus production and drug susceptibility testing. Inhibitors targeting the reverse transcriptase, protease and integrase targets of HIV-2 are evaluated. The resultant drug resistance profiles are then compared to those found in published datasets for HIV-2 group A to determine how HIV-2 group A and group B mutants differ in terms of the magnitude and/or scope of drug resistance. These data are essential for developing evidence-based treatment guidelines for HIV-2–infected patients that harbor drug-resistant group B strains.

Human immunodeficiency virus (HIV) infection is a significant global health issue, with approximately 75 million infections, and over 35 million deaths, since the beginning of the AIDS pandemic. The majority of these are attributable to HIV type 1 (HIV-1). A second form of HIV – HIV type 2 (HIV-2) – is endemic in West Africa and has spread to other areas with socioeconomic ties to the region. Historically, regimens for first-line treatment of HIV-2 have differed from those used in HIV-1-infected patients due to the intrinsic resistance of HIV-2 to nonnucleoside reverse transcriptase inhibitors. This distinction is coming to an end, as countries throughout West Africa are implementing a new WHO-recommended treatment regimen for first-line treatment of all HIV-infected patients, including those with HIV-2. The regimen, known as TLD, is comprised of the nucleoside reverse transcriptase inhibitors tenofovir and lamivudine and the integrase inhibitor, dolutegravir that has potent activity against both HIV-1 and HIV-2. Although treatment-emergent drug resistance has been well characterized for HIV-2 patients receiving tenofovir and lamivudine, there are few data regarding resistance mechanisms in patients receiving the third component of TLD, dolutegravir. The two objectives of my project are: (1) to construct a system for generating recombinant HIV-2 clones that encode and express integrase sequences from TLD-treated HIV-2 patients, and (2) to determine the in vitro susceptibility of viruses produced from the patient-derived clones to the integrase inhibitor dolutegravir. Specifically, I am engineering a plasmid vector into which patient-derived integrase sequences can be ligated for virus production and drug resistance testing in culture. The plasmid vector produced in this study will be used to characterize novel genetic pathways to dolutegravir resistance in HIV-2 and will help identify patients who are failing TLD treatment due to drug resistance. This information is crucial for improving treatment outcomes in HIV-2-infected individuals worldwide.

Clouds, in general, are difficult to account for in climate and numerical weather prediction models. They represent a complex mix of radiative forcings that currently aren’t fully understood or quantifiable. Especially difficult are “mixed-phase” clouds: clouds that exist below the freezing temperature of water but are composed of both ice crystals (water in the solid phase) and supercooled liquid droplets (water in the liquid phase). Hence the name “mixed-phase”. While common, the formation of ice in these clouds remains poorly understood – further observations are vital for obtaining insight into this process. Fortunately, we have new measurements that can provide much-needed insight into their behavior. So far, I have been using measurements from the Department of Energy’s Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) atmospheric observatory on Graciosa Island in the Azores archipelago which is in the northeastern Atlantic Ocean west of Portugal. The observatory is an ideal site for analyzing these clouds for several reasons, but chief among them is its Raman lidar. By measuring a phenomenon called Raman scattering and utilizing algorithms developed by a previous UW graduate student Tyler Thorsen, this instrument can detect different cloud types and aerosol sizes with high confidence up to twenty kilometers into the atmosphere. I’ve been exploring this data using the programming language Python, looking for patterns in these clouds utilizing the ground-based ENA data and verifying my findings with the lidar on the NASA satellite Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The poster will explore how the phase of clouds over the Azores varies with season and with temperature.