Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Harrington Bioengineering Program
- Creators: Materials Science and Engineering Program
- Creators: Loebenberg, Abby
Advances in cellular reprogramming, have enabled the generation of in vitro disease models that can be used to dissect disease mechanisms and evaluate potential therapeutics. To that end, efforts by many groups, including the Brafman laboratory, to generated patient-specific hiPSCs have demonstrated the promise of studying AD in a simplified and accessible system. However, neurons generated from these hiPSCs have shown some, but not all, of the early molecular and cellular hallmarks associated with the disease. Additionally, phenotypes and pathological hallmarks associated with later stages of the human disease have not been observed with current hiPSC-based systems. Further, disease relevant phenotypes in neurons generated from SAD hiPSCs have been highly variable or largely absent. Finally, the reprogramming process erases phenotypes associated with cellular aging and, as a result, iPSC-derived neurons more closely resemble fetal brain rather than adult brain.
It is well-established that in vivo cells reside within a complex 3-D microenvironment that plays a significant role in regulating cell behavior. Signaling and other cellular functions, such as gene expression and differentiation potential, differ in 3-D cultures compared with 2-D substrates. Nonetheless, previous studies using AD hiPSCs have relied on 2-D neuronal culture models that do not reflect the 3-D complexity of native brain tissue, and therefore, are unable to replicate all aspects of AD pathogenesis. Further, the reprogramming process erases cellular aging phenotypes. To address these limitations, this project aimed to develop bioengineering methods for the generation of 3-D organoid-based cultures that mimic in vivo cortical tissue, and to generate an inducible gene repression system to recapitulate cellular aging hallmarks.
We carried out secondary analyses on a subsample of sedentary, overweight/obese adults who participated in a 4-month, 2x2, randomized-controlled walking intervention examining the effects of goal setting (static v. adaptive goals) and rewards (immediate v. delayed) on steps/day (N=96). Fasting blood samples (n=58) were collected from participants before and after the intervention. Premenopausal females were in the follicular phase of their menstrual cycles. Lipid and glucose levels were measured using an automated chemistry analyzer, while insulin was measured using radio-immunoassay. Homeostatic model of insulin resistance (HOMA-IR) was calculated using the following formula (HOMA-IR=glucose x insulin / 405). We examined associations [partial correlations (adjusted for age)] between changes in blood biomarkers and VO2peak and cfPWV, irrespective of group, and we used linear mixed models to examine between-group differences in levels of and change in biomarker outcomes.
Groups did not differ in overall levels of, or degree of change in, biomarker outcomes (all p>0.05). Mean changes, irrespective of group, in biomarkers were as follows: glucose Δ= 0.74± 4.5mg/dl; insulin Δ= 0.09 ± 4.1 µU/ml; total cholesterol Δ= 0.24 ± 20.6 mg/dl; HDL-C Δ= 0.27 ± 5.1 mg/dl; LDL-C Δ= 1.3 ± 19.9 mg/dl; triglycerides Δ= 1.7 ± 27.2 mg/dl; HOMA-IR Δ = -.0548 ± 1.05). We found no significant associations between change in biomarker levels and change in VO2peak or change in cfPWV (all correlation coefficients < 0.15; p > 0.05).
A 4-month, behavioral economics-based mHealth intervention focused on increasing steps/day did not bring about favorable changes on markers of glycemia, insulin resistance and blood lipids.