Alzheimer’s disease (AD) is a neurodegenerative condition in which beta-amyloid protein accumulates into plaques, and tau protein forms neurofibrillary tangles. In the past, our laboratory has shown that repeated inflammatory events increase beta-amyloid in the hippocampus of male C57BL6/J mice. We sought to determine the effect of a second exposure to the bacterial mimetic lipopolysaccharide (LPS) on beta amyloid accumulation. An initial round of seven, once daily LPS or sterile saline injections, was administered to male C57BL6/J adult mice. Fourteen days after the last injection, a second round of LPS or saline injections was given, followed by tissue collection and quantification of beta-amyloid levels in the hippocampus. The results showed that animals injected with two rounds of LPS had significantly lower levels of beta-amyloid accumulation than those animals injected with just a single round of LPS, although both groups had significantly higher levels of beta-amyloid than the saline control animals. These results suggest a reduced inflammatory response following a secondary exposure to LPS. More specifically, animals exposed to LPS for a second time showed significantly less central and peripheral inflammation four hours after LPS administration than animals with no prior exposure. In addition, increased levels of IgM and IgG were discovered in the mice with prior LPS exposure. This could indicate possible antibody production against LPS or beta-amyloid rather than tolerance of the LPS as a mechanism for the reduced inflammatory response. In order to establish whether this results in a life-long effect, we are currently exploring the impact of LPS administration in old age for mice who were exposed to LPS earlier in life.

With the increasing student population trend at TCU, parking on campus is equally increasing
in difficulty. Due to the limited campus space, expanding parking availability is not a feasible
solution. Spark is a smart parking system that monitors the status of each space in parking lots,
indicating the space’s occupancy status on an aerial “Google Maps” view of the parking lot in a
smartphone application and, potentially, a website. The application could be linked to the TCU
Single-Sign-On for increased security and to make it easier for TCU students, faculty, and staff
to save their parking preferences. Spark can measure the fill rate of individual lots, recommend
a time-to-leave to procure a parking spot, and even provide update notifications on the status
of the user’s preferred lots.

Using the finite element method as a numerical approximation in solving for eigenvalues of the hyperbolic Laplacian, this research investigates the estimates of the first two eigenvalues with Dirichlet and Neumann boundary conditions on bounded domains in the upper half plane. Examples of finite element code using Matlab are presented to illustrate how to obtain these approximations for hyperbolic polygons. These values can further be used to shed light on the Selberg and Fundamental Gap conjectures.

In the past, Personality Psychologists have commonly applied clustering techniques on questionnaire data to analyze personality structure. The purpose of this research is to determine if techniques from topological data analysis can provide a greater understanding of personality. Specifically, persistent homology was used to determine clusters topologically and analyze the ‘shape’ of the data. Previous work we have done focused on seeing how persistent homology can provide insight on identifying the key (most persistent) clusters in the data. New analysis looks to see how the Big 5 Personality Factors cluster together as a function of age.

Background: To replace milk fats and eggs commonly found in ice cream, vegan varieties substitute with vegetable fats and/or pureed fruits. Vegan ingredient substitutions for ice cream must contain similar structural components to milk fat to preserve the expected texture/mouthfeel of the product. The purposes of this study were 1) to measure university students’ preferences and sensory ratings of vegan ice cream substitutions and 2) to identify which ingredients act as the best replacements.

Methods: 54 students enrolled in one of two TCU Nutritional Sciences (NTDT) courses participated in this single-blind, cross-sectional study. Subjects completed sensory evaluation of three homemade vegan ice creams containing different structural/flavor components. Sample A included coffee, cashews, and coconut cream; B used coconut cream and dates, and C contained coconut milk. Evaluations took place on two separate occasions in the NTDT Laboratory Kitchens. Flavor, sweetness, texture, mouthfeel, eye appeal, color, and overall rating of vegan ingredient substitutions for ice cream recipes were assessed. Sensory criteria responses were analyzed using SPSS XIX. Frequency distributions, ANOVAs, correlations, and descriptive statistics were determined to meet study objectives (p≤0.05). Protocol was approved by the TCU IRB.

Results: 53% of participants preferred the flavor of sample A, 42% of participants reported that sample B was the preferred flavor, and sample C received the lowest overall acceptability rating, with 73% of the participants disliking the flavor. More than 50% of participants stated sample A was most similar to traditionally-prepared non-vegan ice cream, and 78% of participants stated that they would consume these ice creams outside of the study.

Conclusions: Acceptable vegan ice cream fat substitutes are available. Cashew, coconut cream, dates, and coffee contributed to the rich flavors, creamy textures, and overall desirable sensory qualities in samples A and B. Coconut milk, utilized in sample C, contributed to an undesirable and unacceptable crystallized texture.