资源环境科技发展态势分析平台

A study of cancer-associated mutations in normal endometrial glands of the uterus has now been performed using whole-genome sequencing. The analysis sheds light on the early changes that lead to invasive disease.

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.

Precise protein sequencing and folding are believed to generate the structure and chemical diversity of natural channels(1,2), both of which are essential to synthetically achieve proton transport performance comparable to that seen in natural systems. Geometrically defined channels have been fabricated using peptides, DNAs, carbon nanotubes, sequence-defined polymers and organic frameworks(3-13). However, none of these channels rivals the performance observed in their natural counterparts. Here we show that without forming an atomically structured channel, four-monomer-based random heteropolymers (RHPs)(14) can mimic membrane proteins and exhibit selective proton transport across lipid bilayers at a rate similar to those of natural proton channels. Statistical control over the monomer distribution in an RHP leads to segmental heterogeneity in hydrophobicity, which facilitates the insertion of single RHPs into the lipid bilayers. It also results in bilayer-spanning segments containing polar monomers that promote the formation of hydrogen-bonded chains(15,16) for proton transport. Our study demonstrates the importance of the adaptability that is enabled by statistical similarity among RHP chains and of the modularity provided by the chemical diversity of monomers, to achieve uniform behaviour in heterogeneous systems. Our results also validate statistical randomness as an unexplored approach to realize protein-like behaviour at the single-polymer-chain level in a predictable manner.

Pyrethroid-impregnated bed nets have driven considerable reductions in malaria-associated morbidity and mortality in Africa since the beginning of the century(1). The intense selection pressure exerted by bed nets has precipitated widespread and escalating resistance to pyrethroids in African Anopheles populations, threatening to reverse the gains that been made by malaria control(2). Here we show that expression of a sensory appendage protein (SAP2), which is enriched in the legs, confers pyrethroid resistance to Anopheles gambiae. Expression of SAP2 is increased in insecticide-resistant populations and is further induced after the mosquito comes into contact with pyrethroids. SAP2 silencing fully restores mortality of the mosquitoes, whereas SAP2 overexpression results in increased resistance, probably owing to high-affinity binding of SAP2 to pyrethroid insecticides. Mining of genome sequence data reveals a selective sweep near the SAP2 locus in the mosquito populations of three West African countries (Cameroon, Guinea and Burkina Faso) with the observed increase in haplotype-associated single-nucleotide polymorphisms mirroring the increasing resistance of mosquitoes to pyrethroids reported in Burkina Faso. Our study identifies a previously undescribed mechanism of insecticide resistance that is likely to be highly relevant to malaria control efforts.