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.

Cancer treatments such as chemotherapy and radiation are expensive, painful, and often ineffective, as they compromise the patient’s immune system. Genetically-modified Salmonella Typhimurium (GMS) strains, however, have been proven to target tumors and suppress tumor growth. The GMS then undergo programmed lysis, optimally leaving no trace of Salmonella in the body. Additionally, constant culturing of S. Typhimurium changes the pH of the culture medium. The objective of this research is to investigate using Salmonella to induce changes in the typically acidic tumor microenvironment (TME) pH, ideally hindering tumor growth. Future studies involve utilizing Salmonella to treat a multitude of cancers.

Alginate microspheres have recently become increasingly popular in the realm of drug delivery for their biocompatibility, nontoxicity, inexpensiveness, among other factors. Recent strict regulations on microsphere size have drastically increased manufacturing cost and waste, even though the effect of size variance on drug delivery and subsequent performance is unclear. If sphere size variance does not significantly affect drug release profiles, it is possible that future ordinances may loosen tolerances in manufacturing to limit waste produced and expenditures. We use a mathematical model developed by Nickel et al. [12], to theoretically predict drug delivery profiles based on sphere size, and correlate the expected release with experimental data. This model considers diffusion as the key component for drug delivery, which is defined by Fick’s Laws of Diffusion. Alginate, chosen for its simple fabrication method and biocompatibility, was formed into microspheres with a modified extrusion technique and characterized by size. Size variance was introduced in batches and delivery patterns were compared to control groups of identical size. Release patterns for brilliant blue dye, the mock drug chosen, were examined for both groups via UV spectrometry. The absorbance values were then converted to concentration value using a calibration curve done prior to experimentation. The concentration values were then converted to mass values. These values then produced curves representing the mass of the drug released over time. Although the control and experimental values were statistically significantly different, the curves were rather similar to each other. However, when compared to the predicted release pattern, the curves were not the same. Unexpected degradation caused this dissimilarity between the curves. The predictive model was then adjusted to account for degradation by changing the diffusion coefficient in the code to a reciprocal first order exponent. The similarity between the control and experimental curves can insinuate the notion that size tolerances for microsphere production can be somewhat lenient, as a batch containing fifteen beads of the same size and one with three different sizes yields similar release patterns.