For many individuals in industrialized nations, the widespread adoption of electric lighting has dramatically affected the circadian organization of physiology and behavior. Although initially assumed to be innocuous, exposure to artificial light at night (ALAN) is associated with several disorders, including increased incidence of cancer, metabolic disorders, and mood disorders. Within this review, we present a brief overview of the molecular circadian clock system and the importance of maintaining fidelity to bright days and dark nights. We describe the interrelation between core clock genes and the cell cycle, as well as the contribution of clock genes to oncogenesis. Next, we review the clinical implications of disrupted circadian rhythms on cancer, followed by a section on the foundational science literature on the effects of light at night and cancer. Finally, we provide some strategies for mitigation of disrupted circadian rhythms to improve health.

Life on earth has evolved during the past several billion years under relatively bright days and dark nights. Virtually all organisms on the planet display an internal representation of the solar days in the form of circadian rhythms driven by biological clocks. Nearly every aspect of physiology and behavior is mediated by these internal clocks. The widespread adoption of electric lights during the past century has exposed animals, including humans, to significant light at night (LAN) for the first time in our evolutionary history. Importantly, endogenous circadian clocks depend on light for synchronization with the external daily environment. Thus, LAN can derange temporal adaptations. Indeed, disruption of natural light–dark cycles results in several physiological and behavioral changes. In this review, we highlight recent evidence demonstrating how LAN exposure can have serious implications for adaptive physiology and behavior, including immune, endocrine, and metabolic function, as well as reproductive, foraging, and migratory behavior. Lastly, strategies to mitigate the consequences of LAN on behavior and physiology will be considered.

Vascular networks are fundamental components of biological systems. Quantitative analysis and observation of the features of these networks can improve our understanding of their roles in health and disease. Recent advancements in imaging technologies have enabled the generation of large-scale vasculature datasets, but barriers to analyzing these datasets remain. Modern analysis options are mainly limited to paid applications or open-source terminal-based software that requires programming knowledge with high learning curves. Here, we describe VesselVio, an open-source application developed to analyze and visualize pre-binarized vasculature datasets and pre-constructed vascular graphs. Vasculature datasets and graphs can be loaded with annotations and processed with custom parameters. Here, the program is tested on ground-truth datasets and is compared with current pipelines. The utility of VesselVio is demonstrated by the analysis of multiple formats of 2D and 3D datasets acquired with several imaging modalities, including annotated mouse whole-brain vasculature volumes.