Comprehensive ethological analysis of fear expression in rats using DeepLabCut and SimBA machine learning model.

Introduction: Defensive responses to threat-associated cues are commonly evaluated using conditioned freezing or suppression of operant responding. However, rats display a broad range of behaviors and shift their defensive behaviors based on immediacy of threats and context. This study aimed to systematically quantify the defensive behaviors that are triggered in response to threat-associated cues and assess whether they can accurately be identified using DeepLabCut in conjunction with SimBA.

Novel approach reveals genomic landscapes of single-strand DNA breaks with nucleotide resolution in human cells.

Single-strand breaks (SSBs) represent the major form of DNA damage, yet techniques to map these lesions genome-wide with nucleotide-level precision are limited. Here, we present a method, termed SSiNGLe, and demonstrate its utility to explore the distribution and dynamic changes in genome-wide SSBs in response to different biological and environmental stimuli. We validate SSiNGLe using two very distinct sequencing techniques and apply it to derive global profiles of SSBs in different biological states.