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- All Subjects: Synthetic Biology
- All Subjects: Technology
- Creators: Harrington Bioengineering Program
Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.
For many, a long-distance hike on the 2,650+ mile Pacific Crest Trail (PCT) is the adventure of a lifetime. The federally designated National Scenic Trail passes through 48 Wilderness Areas in California, Washington, and Oregon on its way from Mexico to Canada. The trail experience on the PCT has been changing rapidly over the last 20 years due to two main factors: a four-fold increase in hikers attempting the whole trail each season; and hikers’ rapid adoption of digital technology like smartphones, GPS, and satellite messengers. Through a literature review and accompanying hiker survey, this study aimed to determine how these two factors have combined to alter the trail experience. Despite increased traffic on the trail, hikers appear to still be able to find ample solitude and a feeling of escape from society, and they reported being more likely to form lasting friendships as part of a “trail family”. However, increased traffic has altered many of the sensitive natural landscapes along the trail, contributed to the retirement of some iconic “trail angels” and led to increased conflict between subcultures within the community. Digital technology usage, particularly the use of smartphones and GPS-capable mapping apps, seems to be linked to decreased feelings of solitude, self-sufficiency, and escape. However, digital devices have helped democratize long-distance hiking by simplifying the logistics of long-distance hikes. Users of the devices also did not report reduced feelings of freedom or challenge from their hikes. Moreover, device users still felt that they were disconnecting with technology when hiking on the trail. Acknowledging both positive and negative effects of the changing trail experience, hikers can make more informed decisions about how to mitigate the negative impacts and maximize the positive impacts on the aspects of the trail experience they care the most about.
A variety of different genes have been associated with cell fate. For example, the Nanog/Oct-4/Sox2 network forms the core interaction of a gene network that maintains stem cell pluripotency, and Oct-4 and Sox2 also play a role in the tissue types that stem cells eventually differentiate into. Using the CRISPR/cas9 based homology independent targeted integration (HITI) method developed by Suzuki et al., we can integrate fluorescent tags behind genes with reasonable efficiency via the non-homologous end joining (NHEJ) DNA repair pathway. With human embryonic kidney (HEK) 293T cells, which can be transfected with high efficiencies, we aim to create a three-parameter reporter cell line with fluorescent tags for three different genes related to cell fate. This cell line would provide several advantages for the study of cell fate, including the ability to quantitatively measure cell state, observe expression heterogeneity among a population of genetically identical cells, and easily monitor fluctuations in expression patterns.
The project is partially complete at this time. This report discusses progress thus far, as well as the challenges faced and the future steps for completing the reporter line.