Nature
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Research, news, and commentary from Nature, the international science journal. For daily science news, get Nature Briefing: https://go.nature.com/get-Nature-Briefing
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The genetic ancestry of domesticated barley has been mapped at high resolution, with each genome segment traced to its wild origins and the date estimated for when it entered the domesticated lineage.

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Tracing the ancestry of barley in time and space
Barley’s domestication history reveals the genetic legacy that shaped today’s crop.
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Close cooperation in flight between vertically stacked multirotor drones is widely regarded as dangerous – now research in Nature proposes a solution.

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Drones switch payloads in mid-air using a flying toolbox
Drones can exchange tools while in flight, enabling them to perform multiple tasks.
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Researchers who study trends in illicit drug use are concerned that sales of a potent class of synthetic opioids are on the rise globally.

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Dangerous ‘nitazene’ opioids are on the rise: researchers are worried
This class of synthetic opioids is more potent than heroin and morphine.
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How to pause and restart your science career: Funding crises, bereavement and a supervisor’s relocation can derail your career path, but you can overcome them.

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How to pause and restart your science career
Funding crises, bereavement and a supervisor’s relocation can derail your career path, but you can overcome them.
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Of the 202 Nobelists who have been awarded prizes in physics, chemistry and medicine this century, less than 70% hail from the country in which they were awarded their prize, a Nature analysis shows.

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More than 30% of this century’s science Nobel prizewinners immigrated: see their journeys
The most common destination for eventual Nobel laureates in physics, chemistry and medicine since 2000 is the United States, Nature has found.
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Nature research paper: Enzyme specificity prediction using cross attention graph neural networks

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Enzyme specificity prediction using cross attention graph neural networks - Nature
Enzymes are the molecular machines of life, and a key property that governs their function is substrate specificity—the ability of an enzyme to recognize and selectively act on particular substrates. This specificity originates from the three-dimensional (3D) structure of the enzyme active site and complicated transition state of the reaction1,2. Many enzymes can promiscuously catalyze reactions or act on substrates beyond those for which they were originally evolved1,3-5. However, millions of known enzymes still lack reliable substrate specificity information, impeding their practical applications and comprehensive understanding of the biocatalytic diversity in nature. Herein, we developed a cross-attention-empowered SE(3)-equivariant graph neural network architecture named EZSpecificity for predicting enzyme substrate specificity, which was trained on a comprehensive tailor-made database of enzyme-substrate interactions at sequence and structural levels. EZSpecificity outperformed the existing machine learning models for enzyme substrate specificity prediction, as demonstrated by both an unknown substrate and enzyme database and seven proof-of-concept protein families. Experimental validation with eight halogenases and 78 substrates revealed that EZSpecificity achieved a 91.7% accuracy in identifying the single potential reactive substrate, significantly higher than that of the state-of-the-art model ESP (58.3%). EZSpecificity represents a general machine learning model for accurate prediction of substrate specificity for enzymes related to fundamental and applied research in biology and medicine.
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The light frequency associated with changes in the energy state of atoms can be used to define the ticking of high-precision optical clocks. Experiments with ytterbium atoms have further enhanced the clocks’ precision by using a quantum amplification technique.

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A quantum boost for ultra-precise clocks
A new spectroscopic method takes advantage of quantum entanglement to improve the precision of optical-frequency measurement.
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