International Transracial Adoption (ITRA) is something that became popular in the 1950’s and adoptions from Asia has accounted for approximately half. International adoption occurs when a child from one country is adopted into another. Transracial adoption is the phenomena of adoption across racial and ethnic identities. While popular, the effects of ITRA on racial and adoptee identity formation are still unknown. The study focuses on the Adoptee Mentorship Program (AMP) and AMP’Lified Program that teach International Transracial Adoptees (ITRAs) from Asia about racial and adoptee identity while building community. This study aims to understand how a mentorship program could affect the adoptee and racial identity formation process for other adoptees ages 5-18. The study used a series of program evaluation surveys to determine the effects of the mentorship program on adoptee and racial identity formation. It is hypothesized that the mentorship program will allow ITRAs to develop a stronger sense of their racial and adoptee identity. This was measured through several short answer and likert scale questions focusing on how the adoptee identifies themself as an Asian and as an adoptee. Questions measured self-esteem, knowledge around race and adoption, and whether or not the ITRAs felt a sense of community from the mentorship program. The pre and mid-way survey were conducted in November and March respectively. It is believed that data from these two surveys will show a positive correlation between the AMP and AMP’Lified Programs and the racial and adoptee identity formation for the youth. The final survey will be conducted at the end of the program in June and researchers hypothesize the program will continue to strengthen the racial and adoptee identity of ITRAs. Understanding the effects of mentorship programs on adoptee and racial identity formation for ITRAs will allow for better post-adoption resources and services for adoptees.

Anthropogenic nitrogen (N) emissions have caused an increase in global N deposition, and the northeastern United States is a N deposition hotspot. Nitrogen deposition could impact soil microbial abundance because most soil biota evolved under low N conditions. Soil microbes are key to many ecosystem processes such as organic matter decomposition, which makes nutrients available for plant growth. Therefore, understanding the factors controlling microbial abundance is critical for being able to predict ecosystem processes. We hypothesized that fungal and bacterial abundance and the fungi:bacteria ratio in soil would decrease along a natural N deposition gradient in the northeastern US, and be further reduced by fertilizer application. To address our hypothesis, we collected soil from eight different sites, six of which had experimental plots where N fertilizer had been added. At each site, we collected soil from four ambient or control plots and, if available, four fertilized plots (48 total plots). We measured microbial abundance using phospholipid fatty acid analysis (PLFA). We compared microbial abundance in fertilized to control plots using t-tests, and we analyzed changes in microbial abundance along the natural N gradient using regression analysis. We found that ambient N reduced bacterial abundance (p = 0.03, R² = 0.08), but it did not affect fungal abundance (p = 0.17, R² = 0.02). Fertilizer had no overall effect on fungal (p = 0.72, t = 0.36) or bacterial abundance (p = 0.91, t = -0.12). However, fertilizer did reduce bacterial (p = 0.02, F = 5.6) and fungal (p = 0.02, F = 5.8) abundance at high levels of ambient N deposition. In conclusion, our study showed that soil microbial responses to fertilizer in the northeastern US depend on the background levels of atmospheric N deposition. 

The ability to quantify rat and mice ultrasonic vocalizations (USVs) can provide ethological validity to animal models of affective disorders. Vocalization frequencies are key indicators of a rodent’s subjective state and are closely tied to their behavior. For example, 50-kHz calls in rats are emitted during positive events such as sucrose drinking, and are attributed to a positive affective state. In contrast, 22-kHz calls are ascribed to a negative affective state, and are emitted during negative events such as shock. Current methods for manually scoring vocalizations are slow and labor intensive, while automated programs lack the accuracy to produce satisfactory scoring under non-ideal recording conditions. In order to create a more precise program for detecting these USVs, we applied deep learning, which has revolutionized the field of bioacoustics through image detection and recognition of audio files. By converting soundwaves produced by mice and rats into spectrograms, we can train convolutional neural networks to distinguish between vocalizations and noise. Using these methods, we created the software DeepSqueak©, a Deep Learning Based System for Quantifying USVs and Extended Analysis Kit, which outperforms current state-of-the-art, commercially available software. Hundreds of rat calls from the 18-75kHz were manually isolated from spectrograms and used as training data for our neural network, allowing it to differentiate calls from noise. As a result, USV detections using DeepSqueak are far more rapid and accurate in comparison to existing software. The detected calls produced from the software were then reviewed and re-entered into the neural network as another training set to consolidate its precision and efficiency. With the speed and reliability of DeepSqueak, quantification of USVs can become more widespread and lead to a wealth of new knowledge relating to affective disorders.

Chlamydia trachomatis is a human urogenital pathogen that is the leading cause of sexually transmitted infection worldwide. A major aim of the Hybiske lab is to develop a functional genetic understanding for Chlamydia, with a particular emphasis on known and predicted secreted type II and type III effector proteins that are injected into a host cell by the bacterium and predicted to play important roles in pathogenesis. I am studying a set of newly generated C. trachomatis chimeric mutants that were generated from interspecies lateral gene transfer between C. trachomatis and the mouse adapted species C. muridarum. This series of recombinant strains contain a differing extent of genetic exchange surrounding the predicted inclusion membrane protein (Inc) CT147. CT147 is predicted to be secreted into the Chlamydia-containing vacuole (inclusion) membrane by type III secretion, and subsequently mediate molecular interactions with host proteins. Interestingly, in cultured cells, this strain prematurely ruptures its resident vacuole at 24 hours post infection (hpi), in stark contrast to wildtype C. trachomatis or control recombinant strains that grow normally inside host cells and do not rupture vacuoles at any stage of infection. We therefore hypothesize that the C. muridarum ortholog of Inc-CT147 (which is significantly divergent from the C. trachomatis gene) is incompatible with the series of ~30 Inc proteins normally secreted by C. trachomatis, in such a way that inclusion integrity is not properly maintained during this strain’s developmental growth. We anticipate that a detailed molecular characterization of the function of this Inc protein will reveal important new insight into the mechanisms by which Chlamydia manipulate host cell function to facilitate their infection. My immediate focus is on characterizing Inc-CT147’s role in inclusion formation through qRT-PCR to determine gene expression, immunofluorescence microscopy to characterize subcellular localization, and co-immunoprecipitation and mass spectrometry to identify CT147 interaction targets.