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A Bayesian age model suggests that human dispersal to the Americas probably began before the Last Glacial Maximum, overlapping with the last dates of appearance for several faunal genera.

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 stem cell niche and the size of the root meristem in plants are maintained by intercellular interactions and signalling networks involving a peptide hormone, root meristem growth factor 1 (RGF1)(1). Understanding how RGF1 regulates the development of the root meristem is essential for understanding stem cell function. Although five receptors for RGF1 have been identified(2-4), the downstream signalling mechanism remains unknown. Here we report a series of signalling events that follow RGF1 activity. We find that the RGF1-receptor pathway controls the distribution of reactive oxygen species (ROS) along the developmental zones of the Arabidopsis root. We identify a previously uncharacterized transcription factor, RGF1-INDUCIBLE TRANSCRIPTION FACTOR 1 (RITF1), that has a central role in mediating RGF1 signalling. Manipulating RITF1 expression leads to the redistribution of ROS along the root developmental zones. Changes in ROS distribution in turn enhance the stability of the PLETHORA2 protein, a master regulator of root stem cells. Our results thus clearly depict a signalling cascade that is initiated by RGF1, linking this peptide to mechanisms that regulate ROS.

Acute myeloid leukaemia (AML) is a heterogeneous disease characterized by transcriptional dysregulation that results in a block in differentiation and increased malignant self-renewal. Various epigenetic therapies aimed at reversing these hallmarks of AML have progressed into clinical trials, but most show only modest efficacy owing to an inability to effectively eradicate leukaemia stem cells (LSCs)(1). Here, to specifically identify novel dependencies in LSCs, we screened a bespoke library of small hairpin RNAs that target chromatin regulators in a unique ex vivo mouse model of LSCs. We identify the MYST acetyltransferase HBO1 (also known as KAT7 or MYST2) and several known members of the HBO1 protein complex as critical regulators of LSC maintenance. Using CRISPR domain screening and quantitative mass spectrometry, we identified the histone acetyltransferase domain of HBO1 as being essential in the acetylation of histone H3 at K14. H3 acetylated at K14 (H3K14ac) facilitates the processivity of RNA polymerase II to maintain the high expression of key genes (including Hoxa9 and Hoxa10) that help to sustain the functional properties of LSCs. To leverage this dependency therapeutically, we developed a highly potent small-molecule inhibitor of HBO1 and demonstrate its mode of activity as a competitive analogue of acetyl-CoA. Inhibition of HBO1 phenocopied our genetic data and showed efficacy in a broad range of human cell lines and primary AML cells from patients. These biological, structural and chemical insights into a therapeutic target in AML will enable the clinical translation of these findings.