Kimberly Rose Clark

There is growing evidence of molecular differences in prostate tumors by race or ancestry, which may contribute to the disproportionate burden of aggressive prostate cancer for African American men. Here we investigated whether RNA expression of 310 genes or non-coding RNAs that have shown differential expression (p=7 vs. <=6). The Benjamini-Hochberg False Discovery Rate approach was used to adjust for multiple comparisons. Of the 310 genes/non-coding RNAs, 110 were significantly associated with GS (p=7: 4.3, 4.0-4.5; p=9.90E-05; q=0.01) and zinc finger homeobox 3 (ZFHX3; median and IQR for GS<=6: 4.0, 3.7-4.7 and GS>=7: 3.7, 3.5-4.0; p=1.30E-04; q=0.01). Notably, both genes were found to have lower expression in prostate tumor tissue in African American men compared to European American men in previous studies. Therefore, the direction of our findings with GS (lower expression for higher-grade tumors) is consistent with a potential role of these genes in prostate cancer disparities. The genes that had higher expression in higher- vs. lower-grade tumors in our study included several genes that have shown higher expression in tumor tissue from African American men than European American men in previous studies. These included splicing factor 1 (SF1; median and IQR for GS<=6: 3.5, 3.1-5.1 and GS>=7: 4.6, 3.3-7.4; p=5.60E-03; q=0.04), uroplakin 3B-like (UPK3BL; median and IQR for GS<=6: 6.1, 4.9-7.7 and GS>=7: 7.4, 5.5-9.3; p=7.20E-03; q= 0.04), and RNA binding motif protein 6 (RBM6; median and IQR for GS<=6: 9.6, 8.2-10.7 and GS>=7: 10.3, 8.9-12.1; p=0.01; q=0.05). While replication is needed, these findings add to growing evidence that RNA expression differences in prostate tumors by race or ancestry may contribute to prostate tumor aggressiveness and prostate cancer disparities. Citation Format: Jessica Yau, Ebuka Onyenobi, Yuji Zhang, Teklu B. Legesse, Gary Rose, Guangjing Zhu, Allen Burke, Ashley Cellini, Kimberly Clark, Nicholas Ambulos, Jing Yin, Søren M. Bentzen, Arif Hussain, Joanne Dorgan, Lorelei A. Mucci, Kathryn Hughes Barry. RNA expression markers with differential expression by race/ancestry are associated with prostate tumor aggressiveness among African American men [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1897.

This chapter summarizes the role that artificial intelligence and machine learning (AI/ML) are expected to play at every stage of advertising development, assessment, and execution. Together with advances in neuroscience for measuring attention, cognitive processing, emotional response, and memory, AI/ML have advanced to a point where analytics can be used to identify variables that drive more effective advertising and predict enhanced performance. In addition, the cost of computation has declined, making platforms to apply these tools much less expensive and within reach. The authors then offer recommendations for 1) understanding the clients/customers and users of the products and services that will be advertised, 2) aiding creativity in the process of designing advertisements, 3) testing the impact of advertisements, and 4) identifying the optimum placement of advertisements.

Consumer neuroscience is a quickly growing discipline that harnesses both theoretical principles and applied measures from the decision and affective neurosciences, along with psychophysiology and vision research, in order to explain and predict consumption behaviors. This discipline links several subfields, including neuroeconomics, social and affective neuroscience, and neuromarketing. This emerging field comprises both direct and peripheral measures of neural processing related to consumption behaviors. Consumer neuroscience complements traditional commercial research measures such as self-report, which can often be inaccurate and biased by anticipated or recalled, but not actual, consumption behaviors. All told, consumer neuroscience represents a unique field focusing on the consumer and the innumerable factors that affect individual preferences and consumption behavior. This chapter will provide a comprehensive overview of the field's history, key measures used, case examples of academic and commercial work, and a discussion of the field's continued bright trajectory.

This chapter examines the advent of the neuromarketing revolution, which over the past 10 years changed the way market research is conducted worldwide to include nonconscious measures in everyday studies. It required a form of technology transformation as traditional researchers and marketers came to accept that nonconscious response and emotion are critical in driving brand perceptions and behaviors. Moreover, it demanded a steep learning curve for understanding and adopting new types of scientifically driven methodologies such as EEG and Biometrics. Now with experience and extensive research by academics and practitioners, neurometrics are considered of high value for understanding consumer response and of great potential value for improving prediction leveraging AI and machine learning.