Category: 2022

Differences in the Morphology and Reproduction of Boltenia villosa Across a Latitudinal Gradient

Presenter: Carmen Sanchez-Reddick – Marine Biology

Faculty Mentor(s): Craig Young, Caitlin Plowman

Session: (Virtual) Poster Presentation

While the larval and early juvenile stages of Boltenia villosa are well documented in the literature, little is known about the adults. Early documentation of B. villosa describes a relationship between the body size and the stalk length as individuals with smaller bodies tend to have longer stalks and individuals with larger bodies tend to possess very short stalks. Anecdotal evidence suggests that larger individuals with short stalks make up the populations found in Washington, while Oregon populations consist of smaller individuals with longer stalks. The present study aimed to develop a qualitative understanding of the changes across the latitudinal gradient of Boltenia villosa. This was achieved by using a combination of morphometrics to determine any significant differences between different populations and histology to compare reproductive output. Preliminary results suggest a significant morphological difference between the two populations in body proportions and spine character despite their genetic similarities. Our understanding of the reproductive differences are continuing to be developed. These results indicate the possible existence of a subspecies of Boltenia villosa due to the distinct populations, but more research into each morphotype’s range is needed. This research also provides a broader understanding of how different marine environments can curate specific characteristics to appear in their inhabitants’ populations.

Economic and Political Aspects of Peruvian Immigration in the US during the Late 20th Century

Presenter: Kai Angel Augusto Sanchez-Pajuelo – Economics

Faculty Mentor(s): Iker Saitua

Session: (Virtual) Oral Panel—Read, Speak, and Act

“Not in Luxury, But to Get Along:” Economic and Political Aspects of Peruvian Immigration in the United States during the Late Twentieth Century”

The present paper studies Peruvian immigration to the United States during the late twentieth century. More specifically, it analyzes emigration from Peru caused by the sociopolitical and economic instability of the 1980s. In the 1970s and 1980s, the Peruvian economy went through a series of deep and prolonged economic crises that affected the country’s economic growth. The great depression of the Peruvian economy was mainly due to the negative effects of external shocks, political instability, limited national entrepreneurial capacity, and the lack of capacity to develop new export economic activities. Such depression pushed many Peruvians to emigrate to the United States to make a new start. Motivations of those immigrants were not limited to economic needs, but were framed in a wider context of lack of prospects in Peru. This wave of immigration into the United States was characterized by professional, qualified and semiqualified immigrants, remarkably working either in the service or clerical sectors. Educated people and skilled workers migrated from Peru to the United States during this period rather than unskilled labor force from rural areas. Furthermore, this immigration wave was characterized by family reunification and an occasional wave of refugees.

Coursed-Grained Approach for the Protein Dynamics of the SARS-CoV-2 Spike Protein Variants

Presenter: Ruben Sanchez – Biochemistry, Biology

Faculty Mentor(s): Marina Guenza

Session: (In-Person) Poster Presentation

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) utilizes a spike protein to recognize the receptor protein Angiotensin-converting enzyme 2 (ACE2) of human cells to initiate COVID-19. It is known that the spike protein adopts an active (open) conformation from an inactive (closed) conformation to initiate its infectious cycle. But it is unknown whether the different variants have mutations that affect the protein dynamics of the spike protein. It was hypothesized that the amino acid mutations of more transmissible variants will have increased protein dynamics leading to a dramatized Monod-Wyman-Changeux model. Identifying and targeting these dynamics may lead to the development of pharmaceuticals that may inhibit the infectivity of the SARS-CoV-2 virus. Therefore, two variants of the spike protein were analyzed using molecular dynamic simulations and the Langevin Equation for Protein Dynamics (LE4PD) to quantitively analyze residue fluctuation within their respective spike proteins. LE4PD quantified the protein dynamics and demonstrated that the more infectious variants have higher fluctuations in their protein dynamics.

Utilizing real time strain to modulate patient-specific rehabilitation optimizing bone recovery

Presenter(s): Walker Rosenthal – Human Physiology

Co-Presenter(s): Alyssa Vongphachanh

Faculty Mentor(s): Kylie Nash

Session: (In-Person) Poster Presentation

Severe bone injuries often result in high complication rates and poor functional recovery. Mechanical loading through rehabilitation is a longstanding treatment for these injuries, but current practices are still challenged with variable healing, limiting this promising therapeutic [1,2]. Recent advancements in implantable strain sensors may promote better understanding of how rehabilitation induced loads contribute to healing outcomes [1]. Our lab uses this idea in a rat femoral segmental model stabilized with an internal fixation plate embedded with an implantable strain sensor to analyze the mechanical environment throughout healing for different loading conditions. Past work has found that load-sharing (compliant) fixation devices exhibited improved healing outcomes when compared to load-shielding (non-compliant) fixation plates [3]. We investigated the effects of rehabilitation on bone volume by using a wireless compliant fixation device capable of acquiring real-time micro-strain measurements on a segmental defect in the femur. We found that bone union occurred in 3/3 rehabilitated rats and only 2/4 in non-rehabilitated, sedentary counterparts. Rehabilitated rats experienced a higher mean strain amplitude and their bones bridged earlier than their sedentary counterparts. Our findings suggest a relationship between strain and bone healing outcomes. We hope to further explore the effects of rehabilitation intensity on local defect strain and thus bone healing outcomes.

Investigation of Individual Characteristics that Influence Parent Emotion Regulation in PCIT

Presenter: Sarah Romack – Psychology

Faculty Mentor(s): Elizabeth Skowron

Session: (In-Person) Poster Presentation

Child maltreatment is a substantial public health issue that creates emotional and psychological impacts on victims and is related to emotion regulation deficits in caregivers. Although Parent-Child Interaction Therapy (PCIT) is effective at reducing child-maltreating behavior and improving positive parenting strategies, little research has been conducted on how it strengthens parents’ emotion regulation skills in the process. To address this, the current study utilized a behavioral measure of parent emotion regulation (the Emotional Go/No-Go task) to identify subgroups of 88 child welfare- involved parents receiving PCIT whose emotion regulation skills changed the most across treatment. An exploratory analysis was then conducted to identify pre-treatment predictors of change in parent emotion regulation scores. Measures of parent stress, readiness for change, mental health (specifically depression and anxiety measures), and child behavioral scores were measured. Parent mental health and readiness for change were found to significantly predict high levels of change in parents’ emotion regulation skills. Analyzing the factors that differentiate at-risk parents’ response to PCIT treatment, particularly in terms of their emotion regulation skills, is vital in the current efforts to provide effective interventions and better understand how to match individual parents to effective treatments that will hinder child maltreatment.

Unremembered: The Misattributions of Clara Peeters and Judith Leyster

Presenter: Morning Glory Ritchie – Art History

Faculty Mentor(s): Maile Hutterer

Session: (In-Person) Oral Panel—Herstory Rediscovered, Poster Presentation

Clara Peeters and Judith Leyster were still-life painters prominent during the 17th-century. These still-life genre paintings were of a popular Dutch style which included painting of the interior domestic household and food items. During this era, women faced extreme challenges to receive an art education and to enter the market. Often, these women would have to have a male family member, such as husband or father, be the one to give the art education. These artists have all had a lack of recognition in art historical scholarship, with several of their works misattributed to other male artists of their time. Several 17th-century works created by women were often misattributed to men. Works by female painters were also attributed to their husbands or fathers, as was the case for several works by Judith Leyster who was unknown for almost three centuries. Many still-life works from this period also lack clarity and evidence for attribution leaving many works without name. Several women artists were extremely prominent and successful with their still-life compositions during the 17th-century. Therefore, it is time to start the search for women painters in order to better understand Early Modern culture and the impact of women in the arts. When not much is known about the life of a female artist due to restraints of the women’s role in the domestic household during the 17th-century, their legacy, reputation and contributions to the art world and history eventually fade away.

Oxytocin: A Pathway for the Intergenerational Impacts of Early Trauma

Presenter: Giovanni Ricci – Psychology

Faculty Mentor(s): Jennifer Ablow

Session: (In-Person) Poster Presentation

Oxytocin (OT) is a peptide hormone and neuropeptide that is produced by the hypothalamus and released by the pituitary gland. Research has shown OT is involved in regulating social behaviors such as pair bonding as well as facilitating maternal-child attachment. Research has also shown early childhood trauma may impair OT production later in life through negative feedback mechanisms. However, the relationship between OT and trauma has rarely been examined using both the Adverse Childhood Experiences (ACE) questionnaire and salivary OT measures. The aim of this study is to explore the association between salivary OT, ACE scores, and maternal-child bonding and attachment using a novel salivary OT measure. We hope to solidify previous findings and argue OT acts as an important factor in the transmission of intergenerational trauma. The study will include a sample of new mothers of infants who participated in a prenatal study. Maternal salivary OT and the MPAS and PBQ questionnaires will be collected at the outset of a postnatal visit, and ACE scores were collected as part of the prenatal study. Based on preliminary results, we expect maternal baseline OT will be positively associated with healthy maternal-child bonding and attachment, and negatively associated with ACE scores. Should results be as expected, implications for understanding the role early adversity plays in reduced OT production as a potential pathway for the intergenerational impacts of trauma are discussed.

The Effect of College Attendance on Personality Development Trajectories

Presenter: Sage Rezner – Psychology

Faculty Mentor(s): Sara Weston

Session: (In-Person) Poster Presentation

Personality traits develop throughout adolescence into emerging adulthood; however, it is unclear how college attendance affects the trajectory of development. Participants from the NLSY79 Child and Young Adult cohort provided personality data every two years from 2008 to 2016. The participants are the biological children of the mothers from the NLSY79 cohort, we used the personality data they provided when they were between the ages of fourteen and twenty-five. For each of the Big Five personality traits, we modeled development with both linear and quadratic growth models. College significantly predicted the development of Agreeableness, Neuroticism, and Openness. These findings suggest college attendance influences personality development.

Mapping Sequence-Function Landscapes in the Dihydrofolate Reductase Family Coauthors: Calin Plesa, Samuel Hint

Presenter: Carmen Resnick – Biochemistry

Faculty Mentor(s): Calin Plesa

Session: (In-Person) Poster Presentation

Dihydrofolate reductase (DHFR) is an essential enzyme in the folic acid synthesis pathway and has been the subject of intense study in the past few decades. Despite the wide diversity of homologs, research attention has primarily focused on particular DHFR proteins and as their mutants. In this study we explore DHFR expression through a knockout E. coli strain ER2566 ΔfolAΔthyA. We focus on the ability of DHFR to both rescue metabolic function and tolerate treatment against the antibiotic trimethoprim, which will allow us to understand how antibiotic resistance emerges given many evolutionarily divergent starting points. Changes in the mutational landscape of DHFR allows for varying survival rates in the presence of antibiotic inhibitors. We conduct a broad mutational scan using a library of 5,000 DHFR homologs synthesized using DropSynth gene synthesis. Variant fitness is determined in a multiplex survival assay in the knockout strain which allows supplementation- dependent conditional selection. We aim to collect quantitative fitness data on which mutations impact DHFR activity, both in the presence and absence of inhibitors, to elucidate sequence-function relationships and understand how the fitness landscapes vary as a function of the evolutionary distance between homologs. This data can be applied towards the development of narrow-spectrum and targeted antibiotics and mitigation of resistance through understanding the pathways from which antibiotic resistance arises.

Burn Notice: Using Changepoint Detection Algorithms to Improve Wildfire Tracking

Presenter: Sabrina Reis – Mathematics and Computer Science

Faculty Mentor(s): Weng-Keen Wong

Session: (In-Person) Oral Panel—Fuel, Fire, Grass and Compost

The ability to detect anomalous data is a critical component of any useful statistical analysis, but the process for identifying anomalies can prove time-consuming and arduous. To address these challenges, researchers often delegate data processing to an algorithm, which analyzes data with more speed, efficiency, and accuracy than manual calculations, enabling earlier detection of anomalies. The property of early detection is especially critical when monitoring spatio-temporal events such as wildfires. The critical impact of these events necessitate data sources that provide current and complete information. This need is often met by networks of sensors–for instance, air quality sensors–that collect real-time, localized data. When processed with an anomaly detection algorithm, the comprehensive data collected by sensor networks can reveal aberrations indicative of a spatio- temporal event. To explore how anomaly detection algorithms can facilitate early detection of events of interest using sensor data, we gathered historical data from open-source Purple Air sensors to build case studies of past wildfires. We then applied various types of changepoint detection algorithms to the data in hopes of identifying changes in the distribution of data that indicated a wildfire had broken out. The toolkit of detection methods produced by the project offer a cost-effective and portable way of enhancing our ability to monitor the formation and spread of wildfires.