No abstract

Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.

This article illustrates the utility of using virtual environments to transform social interaction via behavior and context, with the goal of improving learning in digital environments. We first describe the technology and theories behind virtual environments and then report data from 4 empirical studies. In Experiment 1, we demonstrated that teachers with augmented social perception (i.e., receiving visual warnings alerting them to students not receiving enough teacher eye gaze) were able to We would like to thank Roy Pea, Byron Reeves, and the Stanford LIFE lab for helpful suggestions and Sandra Okita and Dan Schwartz for suggestions as well as for detailed comments on an earlier draft of this article. This work was supported in part by National Science Foundation Grant 0527377.Correspondence should be addressed to Jeremy N. Bailenson, Department of Communication, Stanford University, 450 Serra Mall, Stanford, CA 94305-2020. E-mail: bailenson@stanford.edu spread their attention more equally among students than teachers without augmented perception. In Experiments 2 and 3, we demonstrated that by breaking the rules of spatial proximity that exist in physical space, students can learn more by being in the center of the teacher's field of view (compared to the periphery) and by being closer to the teacher (compared to farther away). In Experiment 4, we demonstrated that inserting virtual co-learners who were either model students or distracting students changed the learning abilities of experiment participants who conformed to the virtual co-learners. Results suggest that virtual environments will have a unique ability to alter the social dynamics of learning environments via transformed social interaction.

Highlights d Pre-treatment ctDNA features are associated with checkpoint blockade response d Pre-treatment peripheral T cell levels are associated with checkpoint blockade response d Early on-treatment ctDNA dynamics are associated with checkpoint blockade response d Multiparameter noninvasive models can predict checkpoint blockade response in NSCLC

Background & Aims-Biomarkers are needed to identify patients at risk of tumor progression following chemoradiotherapy for localized esophageal cancer. These could improve identification of patients at risk for cancer progression and selection of therapy.