COVID-19 risk perceptions and their associations with related media consumption and personal experiences

Abstract

(XD) 22 23 IMPACT STATEMENT: Spot-On is an easy-to-use website that makes a rigorous and 24 bias-corrected modeling framework for analysis of single-molecule tracking 25 experiments available to all. ABSTRACT 27 Single-particle tracking (SPT) has become an important method to bridge 28 biochemistry and cell biology since it allows direct observation of protein binding and 29 diffusion dynamics in live cells. However, accurately inferring information from SPT studies 30 is challenging due to biases in both data analysis and experimental design. To address analysis 31 bias, we introduce "Spot-On", an intuitive web-interface. Spot-On implements a kinetic 32 modeling framework that accounts for known biases, including molecules moving out-of-33 focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule 34 trajectories. To minimize inherent experimental biases, we implement and validate 35 stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking 36 errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On 37 outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian 38 cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently 39 and robustly infers subpopulation fractions and diffusion constants. 40