Ankle monitors are not the bright, kind alternative to incarceration that they are made to be. Advocates propose them as a solution to overcrowded carceral sites and excessive federal expenditure on public corrections agencies. Their logic being we can release certain incarcerated people to reduce prison, jail, and detention center populations and require them to pay for their monitoring to reduce prison expenditures. While there is potential for ankle monitors to achieve these aspirations, it is necessary to recognize how and where they can produce harm. Rather than being an alternative to incarceration, ankle monitors are a method of incarceration. They serve the same functions and hold the same power as prisons and jails with a more elusive form. In the current implementation of ankle monitors, we see individual bodies being transformed into sources of data to be capitalized upon by the government and private companies. Along with this, there is a shift of the financial burden of incarceration from prisons to the person being punished. This acts to further perpetuate the cycles of poverty and financial oppression that are seen within traditional forms of incarceration. Ankle monitor advocates also claim ankle monitors allow incarcerated people to enjoy freedom beyond prison walls and reintegrate into society. In reality, this is an oversimplification of freedom. Individuals with ankle monitors find themselves to be limited in their freedoms by restricted movement and stigmatization. They are unable to live a “normal” life because their ankle monitors prevent them from doing so. These people cannot move as they please, they cannot find and hold employment, and they cannot interact with people like they normally would. Ankle monitor usage must be critically examined and altered if it is to be considered a meaningful, gentle alternative to incarceration.

Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage their carbohydrate counting. This early model has a 68.3% accuracy of identifying 101 different food classes. A more refined model in future work could be deployed into a mobile application to identify food the user is about to consume and log it for easier carbohydrate counting.

The aim of this study was to explore cross-sectional and longitudinal aging differences in immediate and delayed visual and verbal memory abilities in individuals with Autism Spectrum Disorder (ASD) compared with neurotypicals (NTs). We measured hippocampal size, fornix fractional anisotropy (FA), and hippocampal and fornix freewater to understand how aging impacts memory structures. Longitudinal findings highlight vulnerabilities in immediate verbal memory and hippocampal volume, while cross-sectional findings indicate fornix freewater may increase at a faster rate in adults with ASD. Future research will examine cognitive and structural sex differences and will study how cognitive measures correlate with structural measures.

The distinctions between the neural resources supporting speech and music comprehension have long been studied using contexts like aphasia and amusia, and neuroimaging in control subjects. While many models have emerged to describe the different networks uniquely recruited in response to speech and music stimuli, there are still many questions, especially regarding left-hemispheric strokes that disrupt typical speech-processing brain networks, and how musical training might affect the brain networks recruited for speech after a stroke. Thus, our study aims to explore some questions related to the above topics. We collected task-based functional MRI data from 12 subjects who previously experienced a left-hemispheric stroke. Subjects listened to blocks of spoken sentences and novel piano melodies during scanning to examine the differences in brain activations in response to speech and music. We hypothesized that speech stimuli would activate right frontal regions, and music stimuli would activate the right superior temporal regions more than speech (both findings not seen in previous studies of control subjects), as a result of functional changes in the brain, following the left-hemispheric stroke and particularly the loss of functionality in the left temporal lobe. We also hypothesized that the music stimuli would cause a stronger activation in right temporal cortex for participants who have had musical training than those who have not. Our results indicate that speech stimuli compared to rest activated the anterior superior temporal gyrus bilaterally and activated the right inferior frontal lobe. Music stimuli compared to rest did not activate the brain bilaterally, but rather only activated the right middle temporal gyrus. When the group analysis was performed with music experience as a covariate, we found that musical training did not affect activations to music stimuli specifically, but there was greater right hemisphere activation in several regions in response to speech stimuli as a function of more years of musical training. The results of the study agree with our hypotheses regarding the functional changes in the brain, but they conflict with our hypothesis about musical expertise. Overall, the study has generated interesting starting points for further explorations of how musical neural resources may be recruited for speech processing after damage to typical language networks.

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.

In the following paper, I aim to form relationships between different patient factors and no-show rates. The culmination of these relationships will then be used in a logistic regression model. Data collected from a survey at 26 HonorHealth clinics were analyzed using odds ratios and relative risk methods. Of 310,307 visits collected, 22,280 of them were no shows (7.2%), an 11% decrease from national averages (18.8%). This fueled the study, along with a grant filed by HonorHealth looking at the impact of telehealth on the working poor. A binary logistic regression method was run over the data, and less than 1% of patients' no-shows were predicted correctly. By adding factors, and improving the diversity in the data collected, model accuracy can be improved.

In the US, underrepresented racial and ethnic minorities receive less than adequate health care in comparison to White Americans. This is attributed to multiple factors, including the long history of structural racism in the US and in the medical field in particular. A factor that is still prevalent today is the lack of diversity within the healthcare workforce. Racial and ethnic minorities are underrepresented in most healthcare occupations. Moreover, many physicians may continue to harbor implicit biases that may interfere with giving adequate care to patients of different backgrounds. We propose that diversity in healthcare should be increased through educational programs and a revamp of existing systems such as medical schools. The increased diversity would mitigate some of the health disparities that exist amongst minorities, as medical professionals are more likely to give adequate care to those who are members of the same community. Increased diversity would also help to increase the cultural competency of physicians as a whole.

Traumatic brain injury (TBI) is defined as an injury to the head that disrupts normal brain function. TBI has been described as a disease process that can lead to an increased risk for developing chronic neurodegenerative diseases, like frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). A pathological hallmark of FTLD and a hallmark of ALS is the nuclear mislocalization of TAR DNA Binding Protein 43 (TDP-43). This project aims to explore neurodegenerative effects of TBI on cortical lesion area using immunohistochemical markers of TDP-43 proteinopathies. We analyzed the total percent of NEUN positive cells displaying TDP-43 nuclear mislocalization. We found that the percent of NEUN positive cells displaying TDP-43 nuclear mislocalization was significantly higher in cortical tissue following TBI when compared to the age-matched control brains. The cortical lesion area was analyzed for each injured brain sample, with respect to days post-injury (DPI), and it was found that there were no statistically significant differences between cortical lesion areas across time points. The percent of NEUN positive cells displaying TDP-43 nuclear mislocalization was analyzed for each cortical tissue sample, with respect to cortical lesion area, and it was found that there were no statistically significant differences between the percent of NEUN positive cells displaying TDP-43 nuclear mislocalization, with respect to cortical lesion area. In conclusion, we found no correlation between the percent of cortical NEUN positive cells displaying TDP-43 nuclear mislocalization with respect to the size of the cortical lesion area.

Regenerative medicine utilizes living cells as therapeutics to replace or repair damaged or diseased tissue, but the manufacturing processes to produce cell-based tissue products require customized biounit operations that do not currently exist as conventional biochemical and biopharma manufacturing processes. Living cells are constantly changing and reacting to their environment, which in the case of cells isolated from their hosts, are utilized as living bioreactor components that, by themselves, are manipulated to biomanufacturer selected tissue products. Therefore, specialized technology is required to assure that cellular products produce the phenotypical tissue characteristics that the final product is designated to have, while also maintaining sterility of the culture. Because of this, FDA guidelines encourage the use of Process Analytical Technology (PAT – see Ref ) to be integrated into manufacturing systems of biologics to ensure quality and safety. To address the need for evaluation of sensor technologies for potential use in PAT, a literature review of both existing sensing technologies and biomarkers was conducted. After a thorough assessment of the sensor technologies that were most applicable to biomanufacturing, spectrophotometry was selected to monitor the metabolic components glucose and lactate of living cells in culture in real time. Initially, spectrophotometric measurements were taken of mock solutions of glucose and lactate solutions at concentrations relevant to human cell culture and physiology. With that data, a mathematical model was developed to predict a solution’s glucose and lactate concentration. This model was then integrated into a Matlab program that was used to continuously monitor and estimate solutions of glucose and lactate concentrations in real time. After testing the accuracy of this program in different solutions, it was determined that calibration curves and models must be made for each media type and estimates of glucose and lactate were found accurate only at higher concentrations. This program was successfully utilized to monitor in real time glucose and lactate production and consumption trends of Mesenchymal Stem Cells (MSCs) in culture, demonstrating proof-of-concept of the proposed bioprocess monitoring schema.