Mental state terms refer to the narrator’s interpretation of a character’s cognitive state such as what the character says, wants, intends, or thinks (Altman et al., 2015). However, previous research on mental state terms has documented conflicting results regarding the frequency of mental state terms used across languages (Altman et al., 2015; Fichman et al., 2021). The current research examines children’s use of mental state terms by elementary school students (1st, 3rd, 5th, and 6th grade) enrolled in a Mandarin-English Dual Language Immersion (DLI) program in California. Children completed a story-telling task, and their narratives were based on the wordless picture book “Frog where are you?” in English, and “Frog goes to dinner” in Mandarin. Speech samples were collected and recorded over Zoom and then transcribed on Computerized Language Analysis (CLAN) software. Transcripts were coded for instances in which individuals of each grade level used mental state terms. Data collection is complete and analysis is in progress. In this study we will answer: (1) How often are children using mental state terms during a narrative production task in Mandarin and English? (2) What kind of emotional language use differences are seen across Mandarin-English and grade levels? We hypothesize that the frequency of mental state terms will be higher in English because English-speaking cultures place greater emphasis on conveying motivations or feelings involved (Sah & Torng, 2016). Across grade levels, we expect older children to use mental state terms at a higher frequency than their younger peers. Investigating how children make use of these devices in narrative production as they acquire two languages can provide insight into cultural priorities around storytelling.

The geologic record has become an increasingly important source of information for scientists to observe how plant communities of the past have responded to disturbance. Currently, there is a limited ability to recognize disturbance as a primary driver of plant community change, as there is limited evidence of how functional traits – plant traits that relate directly with plant function and ecological strategy – that can be measured in fossil leaves vary across succession. In this study I will measure a functional trait to help better identify disturbance in the fossil record, the carbon stable isotopic composition (δ13C) of bulk organic matter in leaves sampled across a successional gradient following a disturbance. This trait is often preserved during leaf fossilization and is representative of a plant's water use efficiency (WUE), or the amount of carbon dioxide used by the plant during photosynthesis for a given amount of water that is lost during transpiration. It is currently not known the extent to which carbon isotopes measured at the community-scale reflect the successional stage of a plant community. In an effort to develop this tool, I hypothesize that the WUE of plant species within a community will become more conservative in later successional stages. In support of this hypothesis, I predict that the abundance-weighted community average of leaf δ13Cwill increase through succession. In addition, I hypothesize that δ13C as a proxy for WUE will be most confounded in early succession, before a tree canopy forms, due to seedling utilizing water resources more rapidly without having established root systems and thus predict a higher variance of δ13Cvalues in this earliest stage of succession (Cernusak 2020). This research will help develop a method of identifying disturbances within geologic records which can give guidance on management decisions regarding modern ecosystems.

Trait-based plant ecology can serve as a means to better understand shifts in ecological strategies within plant communities and how that affects greater ecosystem processes, such as productivity, across a period of major climate change. The most recent major global warming event prior to modern anthropogenic influences was the Miocene Climatic Optimum (MCO) ca. 17-14 million years ago. This event was a short aberration to a long-term cooling trend of the last 53 million years, with global temperature averages up to 8°C warmer than preindustrial averages. Changing climate conditions during the MCO may have led to plant community reshuffling, with many ecosystems possibly restabilizing with notably different optimal trait distributions. Functional traits such as leaf shape, size, and toothedness can be indicative of a plant’s ecological strategy. These leaf morphology variables have been shown to closely correlate with climate, highlighting their role in plant function and strategy, and can thus be used to statistically analyze community diversity across the MCO. I hypothesize that the MCO caused an overall increase in functional trait diversity through an increase in favorable environments, allowing plant reshuffling or migration of plants with new ecological strategies into existing communities. We expect to see this through trait distributions in a community diversifying as the MCO progresses. This study uses leaf functional trait data measured digitally from a range of Miocene fossil sites to assess trends and variances from before, during, and after the MCO. Statistical analysis will make use of a previously developed R package to assess functional diversity. These results will be crucial information in understanding the ecological response to today’s far more rapid climate change, as well as humanity’s response to the possible need for human-assisted plant community reshuffling by providing an example of how global warming affected vegetation in Earth’s past.

Historically, one’s social and geographical position can result in disproportionate levels of exposure to harmful environmental toxins and contaminants. The field of Environmental Justice aims at addressing this inequality by redistributing both the environmental burdens and benefits among all members of society. My research focuses on access to “blue spaces,” or public spaces built around bodies of water that confer health benefits and promote active lifestyles, as an environmental justice issue. Given that Minnesota prides itself with being the land of “10,000 lakes” on every license plate, my research aims to see if the state slogan may be misleading as these lakes may only be accessible to some members of my community. Exploratory in nature, my research intends to reveal possible inequalities regarding access to blue space—even if not clearly visible in the everyday landscape. Through the formulation of a Blue Space Equality Index, which includes several proxy variables for accessibility such as transportation routes, water quality, sidewalks and bench availability, and recreational usages, I will examine three blue space regions in Minneapolis. Using this index in conjunction with demographic and property values data, I intend to represent the local environment surrounding these spaces. A closer investigation of Minneapolis is relevant and timely considering the several high-profile cases of systematic racism in the city’s recent past which have made global headlines; Minneapolis is just a snapshot of what is occurring across the country and that closer examination of the environment is needed to better understand the forces underlying environmental and socioeconomic disparities in Minneapolis. My investigation of blue space accessibility will shed light on how the residents of Minneapolis connect with the environment around them and potentially expose the harsh realities for some community members who call the Twin Cities home.

In this study I investigate potential changes in plant community ecology in response to Earth’s most recent major global warming event, the Miocene Climatic Optimum (MCO). During the MCO (from 17-14 million years ago) global temperatures increased by approximately 8° C and CO2 levels increased by 300-400ppm. In assessing these ecological changes, I use minor leaf vein density (mLVD), a leaf functional trait correlated with photosynthetic rate, as a proxy for understanding plant community strategies. This trait corresponds with the spectrum of “fast” versus “slow” growing strategies described in plant physiology, with high mLVD in fast-growing plants facilitating higher photosynthetic rates, and low mLVD reflecting slow-growing persistence strategies with lower rates of photosynthesis. I hypothesize that global warming led to long growing seasons that enabled the dominance of ecological strategies that prioritize persistence over productivity (i.e., slow growing strategies), and more favorable climates increased the diversity of ecological strategies present within the community. Currently, I am measuring fossil leaf mLVD from specimens collected in the Pacific Northwest from sites representing before, during and after MCO. I examine the community-level distribution of this trait (mean, variance, kurtosis) and compare these values between sites, and thus across the MCO. I predict that plant community ecological diversity would increase during this global warming event; I also expect to see higher variance in distribution of mLVD values as warming temperatures opened new ecological niches, while mean mLVD would decrease due to an increase in persistence strategies correspondent with low mLVD. This work will help us not only to understand how plant communities responded to rising temperatures in the past but also how plant communities could potentially respond to changing climates in the future.

A high-throughput yeast two-hybrid method has recently been developed within the Seelig Lab at the University of Washington to measure thousands to millions of pairwise protein-proteins in a single tube. In each yeast cell, only one pair of proteins is expressed from the same single copy plasmid. Currently, the plasmid in each cell is assembled from 5 double stranded DNA fragments using yeast homologous recombination machinery upon yeast transformation. Particularly, 2 fragments encode for a pair of proteins and the other 3 fragments form the backbone of the single copy plasmid. To optimize the protocol and reduce the number of transformed DNA fragments, 3 of the aforementioned 4 fragments that form the backbone can first be assembled together into a separate accessory plasmid that is subsequently linearized using a restriction enzyme. This reduces the number of transformed fragments that assemble into the single copy plasmid to just 3, which increases the efficiency of the overall transformation. In my research with other members of the Seelig Lab, I have already assembled the accessory plasmid, and am now running the optimized version of the experimental protocol to confirm that this strategy leads to the same results as the established protocol when applied to a control set of coiled coil proteins. Upon completion of this optimization step, I will further try to optimize the protocol by investigating whether the two double stranded DNA fragments that encode for a pair of proteins as well as assemble the single copy plasmid, can be made from a pool of single stranded oligonucleotides rather than ordered as two separate fragments from a DNA synthesis company. This optimization should further reduce the labor and the cost of materials while performing the protocol, and will allow a broader range of individuals to successfully complete yeast transfections with limited resources.

The kinetochore is a protein complex responsible for transmitting force between microtubules and the centromeric region of DNA on chromosomes. The OA and Mif2 protein subunits of the kinetochore make direct attachments to the chromosome. They both bind to another subunit called MIND, which forms a bridge to the microtubule-binding elements of the kinetochore. Preliminary research shows that OA and Mif2 exhibit different binding preferences for the MIND complex. OA binds constitutively, regardless of whether MIND is in an open or closed conformation, whereas Mif2 strongly prefers the open conformation. However, the binding affinities for both OA and Mif2 for MIND have not yet been measured. This study developed the experimental methods for performing immunoprecipitation assays with OA, Mif2, and MIND. By performing phosphomimetic and truncation mutations to promote the MIND open conformation, the binding affinities of OA and Mif2 will be quantified. It is important to quantify the subunit binding affinities to gain a deeper understanding of kinetochore assembly and force transmission between microtubules and chromosomes. Ultimately, this research has applications in cellular division and cancer research.

During mitosis, the kinetochore plays a central role in ensuring the proper segregation of chromosomes in the parent cell. It does so by forming attachments to spindle microtubules, which facilitate the equal distribution of chromosomes to daughter cells. In budding yeast, the Dam1 and Ndc80 complexes are essential protein complexes that bind the kinetochore to spindle microtubules. The Ndc80 complex functions as the direct contact between the kinetochore and the dynamic microtubule tip and it is required for the Dam1 complex to associate with kinetochores. The Dam1 complex strengthens the kinetochore-microtubule attachment. In the presence of microtubules, Dam1complex oligomerizes into a sliding ring. This self assembly has been observed to occur with nanomolar concentrations of the complex in the presence of microtubules but in the absence of microtubules, appreciable oligomerization occurs at concentrations of the complex in the micromolar range. Dimers of the complex appear to predominate in high salt concentrations (500 mM NaCl) in comparison to monomers. This is thought to be due to electrostatic interactions between the monomers. When yeast histones were swapped for human histones, several mutations occurred in the Dam1 complex, and one mutation in the Ndc80 complex, that rescued the yeast cells from defects in mitosis. Preliminary characterization of the mutant Dam1 complexes lead to the hypothesis that the mutations that allow the yeast cells to adapt to the humanized histones changed the monomer-dimer equilibrium for the Dam1 complex. To measure the affinity of Dam1 complex monomers for each other, I will purify the protein complex and use size-exclusion chromatography and western blotting to quantify the relative abundance of the monomer and dimer at different concentrations of the complex. This will contribute to a greater understanding of mitosis and in turn cancer because it focuses on the dynamics that control proper chromosome segregation in cells.

The Miocene Climatic Optimum was a period of rapid warming that occurred from 17 to 14 million years ago where temperatures rose 2-4°C above pre-warming estimates and CO2 concentrations increased to ~400-600 ppm. This event was coeval with the eruption of the Columbia River Basalts (16.6-15.9 Ma), a series of large flood basalts covering much of the Pacific Northwest. The combined forces of these events led to this period being characterized by tumultuous changes to Pacific Northwest plant communities. To quantify these changes, I am reconstructing canopy openness. Ranging from open deserts to closed rainforests, degree of canopy openness describes the amount of sunlight reaching the understory of a plant community. These differences in sunlight exposure affect the size and shape of leaf epidermal cells. Leaves grown in shaded conditions tend to have larger, more undulated epidermal cells when compared to those grown in full sunlight. In the fossil record, silica casts of those cells called phytoliths can be measured to reconstruct the canopy openness of ancient ecosystems. I am using samples from four fossil sites in Central Oregon: Hawk Rim (16.4-16.2 Ma), Mascall (15.1 Ma), Haystack Valley (23-18 Ma), and Picture Gorge Basalts (17.23-16.06 Ma). These sites range from immediately before the Miocene Climatic Optimum (MCO) through the first two million years of warming. They also include samples from sedimentary layers interbedded with basalts. Therefore, they will provide insight on changes that occurred within the plant community both as warming began and because of volcanic eruption. I hypothesize that increased temperature and CO2 concentrations resulted in longer growing seasons and a CO2 fertilization effect. These conditions promoted high vegetation productivity and therefore closed canopies. Additionally, I expect that areas impacted by eruption will exhibit open canopies due to repeated disturbance preventing the re-establishment of forests.

Corepressors are proteins that do not directly touch DNA but work with other proteins to keep the gene from being transcribed. TPL is a corepressor from the model plant Arabidopsis thaliana. While we understand a lot about how TPL works, there are still many mysteries remaining. The goal of my project is to identify other proteins that work with TPL to form a transcriptional repression complex at a single engineered promoter site. First, we created a synthetic repressor called dCas9-TPL that binds and represses the transcription of the RUBY reporter. The RUBY reporter is a visual marker expressed throughout the entire plant, turning the green plant a bright purple. Our engineered RUBY line also carries two guide RNAs in its promoter with sequences not found anywhere else in the Arabidopsis genome. This allows dCas9-TPL to bind to and repress this particular gene and not affect the transcription of other genes. We then crossed this transgenic plant line with plants expressing the dCas9-TPL repressor and the matching guide RNA. Visual screening of the Repressed RUBY line showed these plants turn faint whitish-pink instead of bright purple, signifying that the repression by TPL is working. I am currently on the next step which is identifying a homozygous line of Repressed RUBY to generate a mutagenesis population using the chemical EMS. Once I have these seeds, I will use visual screening to search for plants that have bright red or purple organs, which means that the repression by TPL is not working as well. By identifying regulators of corepressor function in plant biology, I hope to learn principles that can inform cellular engineering across many organisms and better understand why certain mutations associated with transcriptional repression cause developmental defects or diseases like cancer in humans.

Biological aging is the greatest risk factor for most major causes of mortality. Our lab operates under the hypothesis that slowing the rate of aging will also lower the risk of associated diseases. Unfortunately, biological aging research is often limited by the need for labor-intensive manual scoring of lifespan experiments. To solve this problem, we have created a pipeline using machine learning and robotics for the automated processing of lifespan experiments in Caenorhabditis elegans, a type of roundworm often used in biomedical research. Plates of C. elegans are first placed into a “WormBot” image capture robot, which takes images of the plates throughout the day. These photos are processed using YOLO, an object detection system that creates bounding boxes used to track general worm motion. I have implemented a semantic segmentation network that uses these bounding boxes to determine the general shape of the worm. This lets us gather morphological and behavioral data such as length, width, and position. This information is used to infer when the worm stops moving and can be called dead. The time of death this provides shows whether a treatment was successful in extending life. The morphological data can also be used to estimate whether or not the worm was healthier as it aged. This analysis lets us understand how effective various drugs, such as metformin, are at modulating the biological aging process and lessens the time required to run large numbers of trials. Our framework increases the rate at which experiments can be performed and also creates predictive models that provide suggestive data on the effectiveness of an intervention before the end of life. . By automating lifespan scoring, we accelerate the discovery rate of potential interventions that may eventually work in humans.