资源环境科技发展态势分析平台

Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful(1). Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives(2). Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.

The biosynthetic pathway that produces the secondary bile acids DCA and LCA in human gut microbes has been fully characterized, engineered into another bacterial host, and used to confer DCA production in germ-free mice-an important proof-of-principle for the engineering of gut microbial pathways.

Observations show robust near-surface trends in Southern Hemisphere tropospheric circulation towards the end of the twentieth century, including a poleward shift in the mid-latitude jet(1,2), a positive trend in the Southern Annular Mode(1,3-6) and an expansion of the Hadley cell(7,8). It has been established that these trends were driven by ozone depletion in the Antarctic stratosphere due to emissions of ozone-depleting substances(9-11). Here we show that these widely reported circulation trends paused, or slightly reversed, around the year 2000. Using a pattern-based detection and attribution analysis of atmospheric zonal wind, we show that the pause in circulation trends is forced by human activities, and has not occurred owing only to internal or natural variability of the climate system. Furthermore, we demonstrate that stratospheric ozone recovery, resulting from the Montreal Protocol, is the key driver of the pause. Because pre-2000 circulation trends have affected precipitation(12-14), and potentially ocean circulation and salinity(15-17), we anticipate that a pause in these trends will have wider impacts on the Earth system. Signatures of the effects of the Montreal Protocol and the associated stratospheric ozone recovery might therefore manifest, or have already manifested, in other aspects of the Earth system.