Protein and gene circuit level synthetic bioengineering can require years to develop a single target. Phage assisted continuous evolution (PACE) is a powerful new tool for rapidly engineering new genes and proteins, but the method requires an automated cell culture system, making it inaccessible to non industrial research programs. Complex protein functions, like specific binding, require similarly dynamic PACE selection that can be alternatively induced or suppressed, with heat labile chemicals like tetracycline. Selection conditions must be controlled continuously over days, with adjustments made every few minutes. To make PACE experiments accessible to the broader community, we designed dedicated cell culture hardware and integrated optogenetically controlled plasmids. The low cost and open source platform allows a user to conduct PACE with continuous monitoring and precise control of evolution using light.

With millions of people living with a disease as restraining as migraines, there are no ways to diagnose them before they occur. In this study, a migraine model using nitroglycerin is used in rats to study the awake brain activity during the migraine state. In an attempt to search for a biomarker for the migraine state, we found multiple deviations in EEG brain activity across different bands. Firstly, there was a clear decrease in power in the delta, beta, alpha, and theta bands. A slight increase in power in the gamma and high frequency bands was also found, which is consistent with other pain-related studies12. Additionally, we searched for a decreased pain threshold in this deviation, in which we concluded that more data analysis is needed to eliminate the multiple potential noise influxes throughout each dataset. However, with this study we did find a clear change in brain activity, but a more detailed analysis will narrow down what this change could mean and how it impacts the migraine state.

The importance and prevalence of health literacy has emerged in part due to continuing changes in the delivery of health care services, creating new responsibilities for patients and their caregivers, which include finding and evaluating information, self-monitoring health status, and understanding financial constraints and obligations. Those with low health literacy are not able to access the same healthcare benefits, nor are they able to maintain a healthier life as they are not as informed about preventative care. Spanish speakers in the U.S. are subject to these outcomes due to their low levels of health literacy, in which they ultimately experience more severe health issues, late-stage diseases, and higher disease burden. This paper is a comprehensive examination of health literacy among Spanish speakers and makes recommendations on policies that could be implemented into the U.S. healthcare system to better accommodate Spanish speakers and help improve their health literacy for the ultimate goal of improving health outcomes and access to healthcare.

Objective: To determine if patients’ insurance status or the income level of their zip code of residence affect their quality of life or overall survival after enrollment in clinical trials for cancer treatment. Methods: Data were collected from cancer treatment trials conducted through the North Central Cancer Treatment Group and the Alliance for Clinical Trials in Oncology. 700 subjects with baseline quality of life scores were analyzed to explore potential differences in quality of life indicators by insurance group. 624 patients with valid US zip codes were also analyzed based on the median household income of their zip code to determine any associations with quality of life. Overall survival was also analyzed by insurance group and by income quartile. Results: 700 subjects (mean age 59 years, 53% male) were included. 49% had private insurance only, 30% had public insurance only, 8.9% had both private and public insurance, 1.4% had no insurance, and 10% had other insurance. 13% of patients came from zip codes in the bottom quartile by median income, 20% came from the second quartile, 25% from the third quartile and 42% from the top quartile. No significant differences were found in baseline quality of life scores between insurance groups or income quartiles. Patients with both private and public insurance had higher baseline fatigue scores compared to only private, only public, or other insurance. No significant difference was found in baseline fatigue scores by income quartile. No significant differences were found in overall survival by insurance group or income quartile. Conclusions: Patients with both private and public insurance may need more extensive interventions than patients with other insurance statuses due to their higher baseline fatigue scores. Future studies are needed to further investigate the effects of neighborhood advantage level on quality of life indicators.

SUMMARY: A failed attempt to conduct a systematic review of disparities in racial inclusivity in stroke rehabilitation research: A call to action Group Members: Adeline Beeler & Mikayla McNally Faculty Mentor(s): Dr. Sydney Schaefer & Dr. Keith Lohse Topic Overview: Stroke is responsible for the death of an individual every four minutes in the United States. While all Americans are gravely affected by this statistic, Black Americans are at a significantly increased risk of first stroke incidence when compared to their white counterparts, majorly due to heightened prevalence of stroke risk factors. Not only does race contribute as a factor in stroke incidence, but it also has a considerable impact in the physical impairment of Black Americans following stroke occurrence. While it still remains unclear as to whether or not stroke plays a significant role in stroke rehabilitation efforts, there is a clearly demonstrated need for increased reporting or participation of Black Americans in stroke rehabilitation clinical trials to have the ability to conduct a systematic review of these racial disparities in the near future. In the analysis of 36 stroke rehabilitation-related clinical research studies, 80% of selected trials failed to report any participant racial demographics, with 77.3% of the NIH-funded trials not reporting, as well. Out of the 7 trials that did provide some sort of participant racial information, only 5 successfully provided statistically significant racial data compared to the remainder that simply categorized participants’ race as “white” or “other.” In order to fully investigate the effects of race on stroke rehabilitation, it is imperative that researchers collect and report equally distributed and diverse participant racial data when publishing clinical research. Potential methods of improvement for researchers to include more racially diverse subject populations include more comprehensive and in-depth advertising and recruitment strategies for their studies. Research Methods: In order to produce accurate analyses of the current state of the relationship between race and stroke rehabilitation efforts, 36 stroke rehabilitation clinical research trials from various locations across the United States were identified using the Centralized Open-Access Rehabilitation Database for Stroke (SCOAR). These trials were evaluated in order to extract relevant data, such as number of trial participants, average age of participants, if the research trial was funded by the National Institute of Health (NIH) or not, and any reported participant racial demographic details. Trends across these categories were compared between all trials to determine if any disparities existed in providing data sufficient to support the relationship between varying racial populations and stroke rehabilitation efforts. Future Project Efforts: Future efforts will include the completion of submitting a Point of View/Directions for Research article for publication to offer an opportunity for clinical and basic researchers to examine the discrepancies surrounding racial inclusivity in stroke rehabilitation clinical research. The aim is to improve the ability of clinicians to interpret the literature, translate research studies into practices, and better direct future experiments. Further identification of stroke rehabilitation clinical research trials will be necessary, as well as modifications to current written work content.

SUMMARY: A failed attempt to conduct a systematic review of disparities in racial inclusivity in stroke rehabilitation research: A call to action Group Members: Adeline Beeler & Mikayla McNally Faculty Mentor(s): Dr. Sydney Schaefer & Dr. Keith Lohse Topic Overview: Stroke is responsible for the death of an individual every four minutes in the United States. While all Americans are gravely affected by this statistic, Black Americans are at a significantly increased risk of first stroke incidence when compared to their white counterparts, majorly due to heightened prevalence of stroke risk factors. Not only does race contribute as a factor in stroke incidence, but it also has a considerable impact in the physical impairment of Black Americans following stroke occurrence. While it still remains unclear as to whether or not stroke plays a significant role in stroke rehabilitation efforts, there is a clearly demonstrated need for increased reporting or participation of Black Americans in stroke rehabilitation clinical trials to have the ability to conduct a systematic review of these racial disparities in the near future. In the analysis of 36 stroke rehabilitation-related clinical research studies, 80% of selected trials failed to report any participant racial demographics, with 77.3% of the NIH-funded trials not reporting, as well. Out of the 7 trials that did provide some sort of participant racial information, only 5 successfully provided statistically significant racial data compared to the remainder that simply categorized participants’ race as “white” or “other.” In order to fully investigate the effects of race on stroke rehabilitation, it is imperative that researchers collect and report equally distributed and diverse participant racial data when publishing clinical research. Potential methods of improvement for researchers to include more racially diverse subject populations include more comprehensive and in-depth advertising and recruitment strategies for their studies. Research Methods: In order to produce accurate analyses of the current state of the relationship between race and stroke rehabilitation efforts, 36 stroke rehabilitation clinical research trials from various locations across the United States were identified using the Centralized Open-Access Rehabilitation Database for Stroke (SCOAR). These trials were evaluated in order to extract relevant data, such as number of trial participants, average age of participants, if the research trial was funded by the National Institute of Health (NIH) or not, and any reported participant racial demographic details. Trends across these categories were compared between all trials to determine if any disparities existed in providing data sufficient to support the relationship between varying racial populations and stroke rehabilitation efforts. Future Project Efforts: Future efforts will include the completion of submitting a Point of View/Directions for Research article for publication to offer an opportunity for clinical and basic researchers to examine the discrepancies surrounding racial inclusivity in stroke rehabilitation clinical research. The aim is to improve the ability of clinicians to interpret the literature, translate research studies into practices, and better direct future experiments. Further identification of stroke rehabilitation clinical research trials will be necessary, as well as modifications to current written work content.

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.