Diaries can serve as a rich resource to understand the context of a time and place. The diaries of Joseph Mathia Svoboda capture over 40 years of trade on the Tigris, detailing his day to day journeys as a steamboat purser during the late 19th and early 20th centuries, specifically between the cities of Basra and Baghdad. These diaries offer a unique perspective into daily life, community structure, and social relations in the area, which are instrumental to understanding the intricate geopolitical relationship between the British and the Ottoman empires. However, with over 600 pages of transcribed material and many more diaries still in the process of being transcribed, it is difficult to track patterns and changes in Joseph Svoboda’s social relationships and daily life by way of reading and inference alone. This paper describes a project to automatically identify mentions of persons, explore social relationships in the Svoboda diaries, and analyze social networks over time through qualitative and quantitative metrics, to facilitate discussion of Ottoman Iraq society. To automatically extract people from the diaries, we use natural language processing (NLP) methods, and to explore social relationships, we employ network visualization techniques to render networks of persons mentioned in the diaries. Furthermore, by utilizing information gathered through close readings of the diaries and manual extraction, we render networks highlighting kinship and spatiality and then analyze these networks by identifying changes in prominent persons and changes in computed network metrics over time. This project combines the methods of natural language processing and social network analysis to show how the spatial and kinship relations of Joseph Mathia Svoboda change over time. Our research demonstrates how findings based on this methodology can facilitate the study of social and economic life in Ottoman Iraq.

Endothelial cells (ECs) acquire their identities through interactions with surrounding matrices and parenchyma cells, which in turn guide organ development. Understanding the EC specificity is important for improved engineering outcomes of tissue regeneration and disease modeling. In particular, engineered cardiac patches are being explored as a method to supplement tissue function after a myocardial infarction. Successful vascularization has been a key criteria for host integration and tissue survival, however, heart specific vasculature has not yet been achieved. The Zheng Lab has engineered microvessel networks and seeded them with human embryonic stem cell-derived ECs, finding that the vessels effectively integrated into host tissues and were highly angiogenic. However, limited functional benefit has been shown in these vascularized patches. We hypothesize that this is due to a lack of organ specificity in the microvascular construct because heart microvascular ECs exhibit unique potential and metabolic function. Here I aim to construct a cardiac-specific microenvironment by engineering a hydrogel composed of decellularized myocardial extracellular matrix and Type I collagen to induce cardiac organ specificity in ECs. Gene expression analysis via reverse transcription quantitative PCR and protein expression analysis via immunofluorescence staining were used to quantify organ-specificity. A three-dimensional gel containing cardiomyocytes and ECs with a sharp boundary between the organ-specific hydrogel and Type 1 collagen was used to characterize the biochemical effects of the decellularized matrix. The organ-specific hydrogel was then used as a structural component of a grid microvascular network and seeded with beads to demonstrate that the gel maintains structural integrity under flow. This hydrogel has the potential to be adapted into numerous engineered tissue types by altering the decellularized matrix component, allowing for more physiologically significant studies on the effects of drugs and disease.

Seattle, Washington was one of the first major U.S. cities to be impacted by the COVID-19 pandemic. In March 2020, the city implemented a stay-at-home order, shutting down businesses and restricting gatherings. In response, the COVID-19 Seattle Streetview Campaign project was launched in May 2020 to collect longitudinal photographic data to track the impacts of the pandemic on the city, as well as its recovery. Using technology similar to Google Streetview, the campaign collects data every 2-3 weeks along a consistent route in the city of Seattle. Our research objective is to utilize images collected from the Streetview Campaign project to understand COVID-19’s impact on Seattle’s hospitals and parks following non-pharmaceutical interventions (NPIs) such as stay-at-home orders. We described and compared changes in the content of images collected in the Streetview Campaign at hospitals and parks in Seattle from May to December 2020. Our data analysis first identified parks and hospitals that were fully visible along the route. Then, we selected a purposive sample of five fully visible hospitals and five fully visible parks, with a goal of diverse socioeconomic representation. In pairs, we each independently reviewed the images at a mutually-agreed upon location and wrote open-ended descriptions about the content of the images (e.g., number of people and cars; presence of other objects like construction equipment and bikes). We met weekly to compare results, identify discrepancies, and formulate a mutually-agreed upon description of the images. We then explored changes in the content of the images over time. Our findings include information about changes observed in images at hospitals and parks throughout the COVID-19 pandemic. They also provide insights about unique contributions of Streetview data can make in understanding the impacts of the pandemic and associated NPIs, as well as inform future analyses using machine learning and corresponding qualitative inquiry.

Hydrogels, water-swollen materials made of polymer networks, replicate the chemical and structural signals that influence cells growing in vivo, allowing researchers to control stimuli and study cell behavior outside of the body. In vivo, cells grow in curved environments, which provide additional cues that influence cell differentiation and behavior. The goal of this project is to develop a hydrogel where curvature can be activated by allowing contractile cells to compact the hydrogel in a spatially controlled manner. To achieve this, we synthesized a cyclic crosslinker peptide that acts as a two-input Boolean AND gate, with one arm of the cycle degradable by cell-secreted enzymes and the other arm degradable by user-administered transpeptidase. This crosslinker forms gels that dissolve in response to both stimuli, but not in response to either individually. In a cell-adhesive hydrogel polymerized by this crosslinker, we predict that curvature can be activated in hydrogels upon user addition of exogenous transpeptidase, due to an increase in cell spreading and macroscopic contraction. Once the hydrogel system behaves as designed, we intend to investigate the response of cardiac cell types to tissue curvature in a controlled environment, in order to unveil the mechanisms by which the geometric cue impacts disease and development. This understanding can help researchers identify possible drugs that target signals from tissue curvature, and in regenerative medicine, it can help inform how tissue is grown in vitro to better match native tissue.

Hydrogels are a versatile biomaterial commonly used for tissue engineering and drug delivery. In particular, photodegradable hydrogels have facilitated research breakthroughs in multiple fields, including organ development, disease progression, and blood vessel formation. While these reports have contributed greatly to the literature using in vitro experiments, current photodegradable designs are unable to function inside the human body due to their insensitivity to low energy light. Nearly all photodegradable hydrogels incorporate ortho-nitrobenzyl moieties as photosensitizers, which responds to UV light, a wavelength that does not penetrate complex tissue. In order to expand the applications of these photodegradable hydrogels a new crosslinker is needed that cleaves in response to visible light. I am working to develop a new photodegradable crosslinker based on ruthenium polypyridyl linker complexes, which can be structurally tuned to respond to visible light irradiation, leading to exchange of a ligand with water and rapid hydrogel degradation. We have modified the complexes with a reactive azide handle for site-specific incorporation into hydrogel biomaterials that can be transplanted to or formulated within specific bodily locations. Our preliminary results suggest the Ruthenium polypyridyl complexes degrade in the visible spectrum, and previous experiments have concluded that click chemistry allows for PEG-hydrogel incorporation with azide-modified crosslinkers. In this poster, I will describe the synthesis and characterization of one model Ru-based linker, including its photolysis, stability, and applications of the complex in the development of dynamic biomaterials for drug delivery and cell growth in vivo.