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The ocean is a vast three-dimensional space that is poorly explored and understood, and harbors unobserved life and processes that are vital to ecosystem function. To fully interrogate the space, novel algorithms and robotic platforms are required to scale up observations. Locating animals of interest and extended visual observations in the water column are particularly challenging objectives. Towards that end, we present a novel Machine Learning-integrated Tracking (or ML-Tracking) algorithm for underwater vehicle control that builds on the class of algorithms known as tracking-by-detection. By coupling a multi-object detector (trained on in situ underwater image data), a 3D stereo tracker, and a supervisor module to oversee the mission, we show how ML-Tracking can create robust tracks needed for long duration observations, as well as enable fully automated acquisition of objects for targeted sampling. Using a remotely operated vehicle as a proxy for an autonomous underwater vehicle, we demonstrate continuous input from the ML-Tracking algorithm to the vehicle controller during a record, 5+ hr continuous observation of a midwater gelatinous animal known as a siphonophore. These efforts clearly demonstrate the potential that tracking-by-detection algorithms can have on exploration in unexplored environments and discovery of undiscovered life in our ocean. 

Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.