Although no known asteroid poses a threat to Earth for at least the next century, the catalogue of near-Earth asteroids is incomplete for objects whose impacts would produce regional devastation1,2. Several approaches have been proposed to potentially prevent an asteroid impact with Earth by deflecting or disrupting an asteroid1–3. A test of kinetic impact technology was identified as the highest-priority space mission related to asteroid mitigation1. NASA’s Double Asteroid Redirection Test (DART) mission is a full-scale test of kinetic impact technology. The mission’s target asteroid was Dimorphos, the secondary member of the S-type binary near-Earth asteroid (65803) Didymos. This binary asteroid system was chosen to enable ground-based telescopes to quantify the asteroid deflection caused by the impact of the DART spacecraft4. Although past missions have utilized impactors to investigate the properties of small bodies5,6, those earlier missions were not intended to deflect their targets and did not achieve measurable deflections. Here we report the DART spacecraft’s autonomous kinetic impact into Dimorphos and reconstruct the impact event, including the timeline leading to impact, the location and nature of the DART impact site, and the size and shape of Dimorphos. The successful impact of the DART spacecraft with Dimorphos and the resulting change in the orbit of Dimorphos7 demonstrates that kinetic impactor technology is a viable technique to potentially defend Earth if necessary.

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Demonstration of a novel point mutation within the SLC12A3 gene in our cohort of Gypsy families with Gitelman syndrome is highly suggestive of a founder effect. This finding will facilitate the identification of the genetic defect in further cases of Gitelman syndrome among the Gypsy population. Our study represents the largest series ever published of patients with Gitelman syndrome having the same underlying mutation, and supports the lack of correlation between genotype and clinical phenotype in this disease.

Large volumetric neuroimaging datasets have grown in size over the past ten years from gigabytes to terabytes, with petascale data becoming available and more common over the next few years. Current approaches to store and analyze these emerging datasets are insufficient in their ability to scale in both cost-effectiveness and performance. Additionally, enabling large-scale processing and annotation is critical as these data grow too large for manual inspection. We propose a new cloud-native managed service for large and multi-modal experiments, providing support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API) and web-based user interface.Our project is open source and can be easily and costeffectively used for a variety of modalities and applications.