Teaching robots to efficiently search for a target object (such as medication) in cluttered environments (such as a house) with limited prior information is a challenging yet important task, with applications ranging from home assistance to search and rescue. An ideal search policy, i.e. strategy, maximizes the accumulation of the target object while travelling along an efficient search route. We formulate object-search as a combinatorial-optimization problem known as the Stochastic Orienteering Problem (SOP), which is a graph traversal problem where an agent must identify and traverse a subset of nodes (such as furniture items, in our case) in a graph data-structure, with each edge associated with some cost and each node associated with some expected reward. The agent must choose a path that maximizes expected reward and keeps total travel cost under some prespecified bound, where the bound is informed by an unavoidable real-world constraint such as battery-usage. In our formulation, we call each node a "container", a catch-all term for any distinct area that can hold an object (such as a cabinet), and the edge costs represent the distances between each container. In this work, we mathematically show how this SOP can describe object-search tasks at a high-level, and present a simulated agent trained in a basic grid-world environment. We leverage the powerful reward-maximization capabilities of deep reinforcement-learning (a subfield of machine learning) to achieve near-optimal performance for solving this object-search SOP. The broader implication of this work is that real-world robotic object-search tasks are well-described by SOPs, since the multi-objective nature of SOPs forces the agent to choose search policies that both have a high-likelihood of finding the object(s) and do not exceed a hard constraint, such as energy expenditure.

The Ubiquitin Proteasome System (UPS) is a molecular recycling machine, responsible for  proteolysis and protein activity regulation. The components of the UPS attach a small protein ubiquitin onto other proteins which directly affects their activity or serves as a signal calling for modification or lysis. Ubiquitin-conjugating enzymes (E2) and ubiquitin ligases (E3) are two classes of proteins that determine which proteins are tagged. Ube2W is an E2 with a unique function—it is the only E2 that places ubiquitin onto disordered N termini and amino acylated side chains. In this study we aim to elucidate the mechanism of reactivity and specificity of the enigmatic Ube2W. What structural and chemical features are responsible for its one-of-a-kind functionality? What does this imply about the role of this E2 on the cellular level? We designed a set of Ube2W mutants that had various putatively important features removed or changed to analogs from different E2s. We performed mutagenesis PCR followed by reactivity assays in the presence of known Ube2W substrates. We plan to collect NMR data for the Ube2W-substrate and Ube2W-ubiquitin interactions. We hope to determine which features are critical for this unique E2’s function by following the changes in reactivity when they are removed or altered. The interactions of substrates with these critical residues will help draft an outline for the precise mechanism. Improving our mechanistic understanding of Ube2W will pave the way for being able to control when and under what circumstances this unique biochemical reaction is used by the cell. This work aims to expand the current understanding of the UPS and aid in taming UPS-related diseases.

In low- and middle-income countries (LMICs), human exposure to animals can represent a significant source of enteropathogens. The presence of domestic and non-domestic animals either in the vicinity or in immediate households within LMICs have the potential to contaminate soil and high-touch surfaces leading to enteropathogen transmission and infection. Among LMICs, access to water, sanitation, and hygiene (WASH) is limited and is responsible for contributing to the global disease burden. Lack of WASH regulations and implementation can compound transmission and infection rates of enteropathogens from animal exposures. The objective of this study is to determine the sources and quantities of household animal fecal contamination, an important exposure pathway for enteropathogens, in Ecuadorian households. Quantitative PCR (qPCR) assays were used to identify host-associated fecal contamination by detecting gene fragments of gut microbes that are specific to the feces of a given human or animal host. These microbial source tracking (MST) marker assays were used on environmental samples collected in Ecuador households including floor, mother and child hand rinses, and domestic water to assess the abundance and sources of household fecal contamination. MST marker targets included human feces associated markers (HF183 & HumM2), dog feces makers (DG37), ruminant feces markers (Rum2Bac), pig feces markers (Pic2Bac), bird droppings markers (GFD), and general bacteroidales markers (GenBac). The anticipated results are that the qPCR data will continue to indicate high levels of general and human-associated animal fecal contamination in animal-owning Ecuadorian households as previously observed in Phase 2 of this study. Findings from this study will highlight the need for the development and implementation of relevant public health interventions aimed at reducing animal exposures and improving overall hygiene practices to decrease the global disease burden among LMICs.

In the ubiquitin-proteasome system, the E2 enzymes are involved in the second step of transferring the ubiquitin (Ub) to a substrate. Specifically, an E2 enzyme receives the ubiquitin from an E1-Ubiquitin(E1-Ub) conjugate and becomes an E2-Ub conjugate. Then, an E3 enzyme can deliver the ubiquitin from the E2-Ub conjugate to a substrate to form a substrate-Ub conjugate. Most of the E2s attach Ub to a substrate lysine residue, but Ubc6, an E2 from yeast, also seems to react with substrate hydroxyl groups on serine/threonine/tyrosine. This project is divided into two parts: first, validate the reactivity of Ubc6 in different amino acid (serine/threonine/lysine/cysteine/tyrosine) conditions. Second, apply a proper machine model to predict the reactivity of Ube2J2-Ub, a mammalian homolog of the Ubc6-Ub conjugate. The quantification analysis on the Ubc6 charge/discharge assays can reveal the rate of the reactivity of the Ubc6 in different amino acid conditions. After validation, three types of E2s with known reactivities: Ubc2D(1/2/3/4)-Ub, Ube2L3-Ub, and Ubc6-Ub, can be used as training sets for the machine learning model. Once the model predicts the reactivity of Ube2J2, the prediction can be validated by performing assays on Ube2J2. We expect that Ubc6 reacts fastest with Cysteine, followed by Threonine, Lysine, Tyrosine, and Serine. Since Ube2J2 is a human homolog of Ubc6, we predict that Ube2J2 has the same reactivity as Ubc6. The implication of this project is whether machine learning can assist with finding the reactivity of a protein enzyme.

The main objective of HIV treatment is reducing mortality and morbidity for people living with HIV and preventing new infections. Accessing and maintaining chronic HIV care is critical for patient wellness and preventing new infections. A normal and healthy quality of life with a reduced chance of transmission can be achieved by maintaining a clinically undetectable viral load, which is directly dependent on regular medical appointments with a primary care provider and adherence to antiretroviral therapy. For patients experiencing significant socioeconomic barriers, maintaining an undetectable viral load is difficult. To help overcome these barriers, our clinic provides patients with higher needs interventions to help them regularly attend medical appointments and obtain medications. This descriptive study examines the effectiveness of offering low threshold healthcare by examining viral loads, socioeconomic factors, and experiences of a group of 100 patients with varying levels of need who are receiving treatment at the MAX clinic in Tacoma, WA since August of 2021. We selected consenting participants who met eligibility by being currently enrolled with a detectable viral load within a year of the study start date. One group, designated as having lower levels of need, consists of those with a history of adhering to care and with no significant socioeconomic or circumstantial barriers for accessing treatment. The second group consists of those with higher needs who have a history of non-adherence to care due to socioeconomic factors, substance use, or circumstantial crisis. We are collecting quantitative and qualitative data from regular HIV test results and interviews conducted every six months. Interviews focus on participants’ experiences with HIV healthcare, situational developments, and patient-centered outcomes. Preliminary results of this study support a low-barrier care model contributes to undetectable viral loads by helping patients with higher needs regularly attend medical appointments and adhere to antiretroviral therapy.