The ancient South Pole-Aitken impact basin provides a key data point for our understanding of the evolution of the Moon, as it formed during the earliest pre-Nectarian epoch of lunar history1, excavated more deeply than any other known impact basin2,3 and is found on the lunar far side, about which less is known than the well-explored near side. Here we show that the tapering of the basin outline and the more gradual topographic and crustal thickness transition towards the south support a southward impact trajectory, opposite of that commonly assumed. A broad thorium-rich and iron-rich ejecta deposit southwest of the basin is consistent with partial excavation of late-stage magma ocean liquids. These observations indicate that thorium-rich magma ocean liquids persisted only beneath the southwestern half of the basin at the time of impact, matching predictions for the transition from a global magma ocean to a local enrichment of potassium, rare-earth elements and phosphorus (KREEP) in the near-side Procellarum KREEP Terrane. These results have important implications for the upcoming human exploration of the lunar south pole by Artemis, as proposed landing sites are now recognized to sit on the downrange rim and thorium-rich impact ejecta of the basin.

Optical lattice clocks are at the forefront of precision metrology1-6, operating near a standard quantum limit set by quantum noise4,7. Harnessing quantum entanglement offers a promising route to surpass this limit8-15; however, there are practical difficulties in terms of scalability and measurement resolution requirements16,17. Here we adapt the holonomic quantum gate concept18 to develop a new Rabi-type 'global-phase spectroscopy' that uses the detuning-sensitive global Aharonov-Anandan phase19. With this approach, we can demonstrate quantum-amplified time-reversal spectroscopy on an optical clock transition that achieves directly measured 2.4(7) dB metrological gain and 4.0(8) dB improvement in laser noise sensitivity beyond the standard quantum limit. To this end, we introduce rotary echo to protect the dynamics from inhomogeneities in light-atom coupling and implement a laser-noise-cancelling differential measurement through symmetric phase encoding in two nuclear spin states. Our technique is not limited by measurement resolution, scales easily because of the global nature of entangling interaction and exhibits high resilience to typical experimental imperfections. We expect it to be broadly applicable to next-generation atomic clocks and other quantum sensors approaching the fundamental quantum precision limits20-22.

Even with the rapid development of renewable energy sources, improving the efficiency of energy conversion from fossil or synthetic fuels remains a challenge because, for example, combustion engines in long-range aircraft will still be needed in the upcoming decades1. Increasing their operating temperatures (1,050-1,150 °C (refs. 2-4)) is one option. This requires replacing single-crystalline Ni-based superalloys in the hottest sections of turbines by refractory-element-based materials, which exhibit much higher solidus temperatures beyond 2,000 °C (refs. 5-7). Here we introduce a single-phase Cr-36.1Mo-3Si (at.%) alloy that meets, for the first time, to our knowledge, the most important critical requirements for refractory-element-based materials: (1) relevant resistance against pesting, nitridation and scale spallation at elevated temperatures, minimum up to 1,100 °C, and (2) sufficient compression ductility at room temperature. Although strength and creep resistance in such alloys were already superior to Ni-based superalloys in several cases, oxidation/corrosion resistance, mandatory to withstand the combustion atmosphere, and ductility/toughness, needed for damage tolerance and device setting, still pose barriers for the development or application of refractory-element-based candidate materials. Any previous successful attempts to address the otherwise catastrophic oxidation of Mo and nitridation of Cr during oxidation suffered from a loss in ductility at ambient temperatures.

In renewing tissues, mutations conferring selective advantage may result in clonal expansions1-4. In contrast to somatic tissues, mutations driving clonal expansions in spermatogonia (CES) are also transmitted to the next generation. This results in an effective increase of de novo mutation rate for CES drivers5-8. CES was originally discovered through extreme recurrence of de novo mutations causing Apert syndrome5. Here, we develop a systematic approach to discover CES drivers as hotspots of human de novo mutation. Our analysis of 54,715 trios ascertained for rare conditions9-13, 6,065 control trios12,14-19 and population variation from 807,162 mostly healthy individuals20 identifies genes manifesting rates of de novo mutations inconsistent with plausible models of disease ascertainment. We propose 23 genes hypermutable at loss-of-function (LoF) sites as candidate CES drivers. An extra 17 genes feature hypermutable missense mutations at individual positions, suggesting CES acting through gain of function. CES increases the average mutation rate roughly 17-fold for LoF genes in both control trios and sperm and roughly 500-fold for pooled gain-of-function sites in sperm21. Positive selection in the male germline elevates the prevalence of genetic disorders and increases polymorphism levels, masking the effect of negative selection in human populations. Despite the excess of mutations in disease cohorts for 19 LoF CES driver candidates, only 9 show clear evidence of disease causality22, suggesting that CES may lead to false-positive disease associations.

Long-term sustained pain following acute physical injury is a prominent feature of chronic pain conditions1. Populations of neurons that rapidly respond to noxious stimuli or tissue damage have been identified in the spinal cord and several nuclei in the brain2-4. Understanding the central mechanisms that signal ongoing sustained pain, including after tissue healing, remains a challenge5. Here we use spatial transcriptomics, neural manipulations, activity recordings and computational modelling to demonstrate that activity in an ensemble of anatomically and molecularly diverse parabrachial neurons that express the neuropeptide Y (NPY) receptor Y1 (Y1R neurons) is increased following injury and predicts functional coping behaviour. Hunger, thirst or predator cues suppressed sustained pain, regardless of the injury type, by inhibiting parabrachial Y1R neurons via the release of NPY. Together, our results demonstrate an endogenous analgesic hub at pain-responsive parabrachial Y1R neurons.

Men are at higher risk of several cancer types than women1. For bladder cancer the risk is four times higher for reasons that are not clear2. Smoking is also a principal risk factor for several tumour types, including bladder cancer3. As tumourigenesis is driven by somatic mutations, we wondered whether the landscape of clones in the normal bladder differs by sex and smoking history. Using ultradeep duplex DNA sequencing (approximately 5,000×), we identified thousands of clonal driver mutations in 16 genes across 79 normal bladder samples from 45 people. Men had significantly more truncating driver mutations in RBM10, CDKN1A and ARID1A than women, despite similar levels of non-protein-affecting mutations. This result indicates stronger positive selection on driver truncating mutations in these genes in the male urothelium. We also found activating TERT promoter mutations driving clonal expansions in the normal bladder that were associated strongly with age and smoking. These findings indicate that bladder cancer risk factors, such as sex and smoking, shape the clonal landscape of the normal urothelium. The high number of mutations identified by this approach offers a new strategy to study the functional effect of thousands of mutations in vivo-natural saturation mutagenesis-that can be extended to other human tissues.

As we age, many tissues become colonized by microscopic clones carrying somatic driver mutations1-7. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of this phenomenon remains limited due to the challenge of detecting mutations in small clones. Here we introduce a new version of nanorate sequencing (NanoSeq)8, a duplex sequencing method with an error rate lower than five errors per billion base pairs, which is compatible with whole-exome and targeted capture. Deep sequencing of polyclonal samples with single-molecule sensitivity simultaneously profiles large numbers of clones, providing accurate mutation rates, signatures and driver frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 blood samples from a twin cohort, we report an extremely rich selection landscape, with 46 genes under positive selection in oral epithelium, more than 62,000 driver mutations and evidence of negative selection in essential genes. High-resolution maps of selection across coding and non-coding sites are obtained for many genes: a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition or selection of somatic mutations. Accurate single-molecule sequencing provides a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

The amount of biological sequencing data available in public repositories is growing rapidly, forming a critical resource for biomedicine. However, making these data efficiently and accurately full-text searchable remains challenging. Here we build on efficient data structures and algorithms for representing large sequence sets1-6. We present MetaGraph, a methodological framework that enables us to scalably index large sets of DNA, RNA or protein sequences using annotated de Bruijn graphs. Integrating data from seven public sources7-13, we make 18.8 million unique DNA and RNA sequence sets and 210 billion amino acid residues across all clades of life-including viruses, bacteria, fungi, plants, animals and humans-full-text searchable. We demonstrate the feasibility of a cost-effective full-text search in large sequence repositories (67 petabase pairs (Pbp) of raw sequence) at an on-demand cost of around US$100 for small queries up to 1 megabase pairs (Mbp) and down to US$0.74 per queried Mbp for large queries. We show that the highly compressed representation of all public biological sequences could fit on a few consumer hard drives (total cost of around US$2,500), making it cost-effective to use and readily transportable for further analysis. We explore several practical use cases to mine existing archives for interesting associations, demonstrating the use of our indexes for integrative analyses, and illustrating that such capabilities are poised to catalyse advancements in biomedical research.

Nonlinear optics1 plays a central role in many photonic technologies, both classical2-5 and quantum6-8. However, the function of a nonlinear-optical device is typically determined during design and fixed during fabrication9, restricting the use of nonlinear optics to scenarios in which this inflexibility is tolerable. Here we present a photonic device with highly programmable nonlinear functionality: an optical slab waveguide with an arbitrarily reconfigurable two-dimensional distribution of χ(2) nonlinearity. The nonlinearity is realized using electric-field-induced χ(2) (refs. 10-16), and the programmability is engineered by massively parallel control of the electric-field distribution within the device using a photoconductive layer and optical programming with a spatial light pattern. To showcase the versatility of our device, we demonstrate spectral, spatial and spatio-spectral engineering of second-harmonic generation by tailoring arbitrary quasi-phase-matching grating structures1 in two dimensions. The programmability of the device makes it possible to perform inverse design of grating structures in situ, as well as real-time feedback to compensate for fluctuations in operating and environmental conditions. Our work shows that we can break from the conventional one-device-one-function paradigm, potentially expanding the applications of nonlinear optics to situations in which fast device reconfigurability is desirable-such as in programmable optical quantum gates and quantum light sources7,17-19, all-optical signal processing20, optical computation21 and adaptive structured light for sensing22-24.

Cognitive processes underlying behaviour are linked to specific spatiotemporal patterns of neural activity in the neocortex1-6. These patterns arise from synchronous synaptic activity7 and are often analysed as oscillations, but may also display aperiodic dynamics that are not well detected. Here we develop a novel analytical method decomposing patterned activity into discrete network events and use this approach to track gamma activity (30-80 Hz) in the mouse visual cortex (V1). We find that the gamma event rate varies with arousal and individual events can cluster in brief oscillatory bouts but also occur in isolation. Individual events synchronize neural firing across layers and promote enhanced visual encoding. V1 gamma events are evoked by patterned input from the dorsal lateral geniculate nucleus (dLGN) and suppressed by optogenetic modulation of the dLGN, suggesting that they support thalamocortical integration of visual information. In behaving mice, the gamma event rate increases steadily before visually cued behavioural responses, predicting trial-by-trial performance. Suppressing V1 gamma events impairs visual detection performance, whereas evoking them elicits a behavioural response. This relationship between gamma events and behaviour is sensory modality specific and rapidly modulated by changes in task objectives. Gamma events thus support a flexible encoding of visual information according to behavioural context.

During DNA replication, the replisome must remove barriers and roadblocks including the transcription machinery1,2. Transcription-replication conflicts (TRCs) occur when there are collisions between the replisome and transcription machinery, and are increasingly recognized as an important source of mammalian genome instability3. How cells facilitate replisome bypass at sites of TRCs is incompletely understood. Here we show that the CUL3-KCTD10 E3 ligase senses TRCs and promotes remodelling of the RNA polymerase complex to allow replisome bypass. We found that the substrate adaptor KCTD10 interacts with the replisome and the transcription machinery and regulates both in unstressed conditions. These bivalent interactions allow KCTD10 to detect co-directional TRCs and facilitate higher-order assembly of KCTD10 complexes that recruit CUL3 to induce the ubiquitination and removal of the RNA polymerase factor TCEA2. In the absence of KCTD10, there is increased retention of TCEA2 and the RNA polymerase complex, causing an accumulation of TRCs and increased DNA damage. Our results demonstrate how replication can proceed through transcriptionally active regions, utilizing a unique bridging function of the CUL3-KCTD10 complex. These findings provide a framework for how the coordination between transcription and replication may contribute to the maintenance of genome stability.

Two-dimensional (2D) materials have extended the device scalability1-3 of silicon (Si) technology and enabled fundamental innovations in device mechanisms4-6. Both industry7-9 and academia10-13, particularly in the field of integrated circuits, are pursuing integration breakthroughs to demonstrate the superiority of 2D electronics at the system level. Despite considerable integration progress on either 2D material integration11-13 or 2D-CMOS hybrid integration14, a system that can migrate the advantages of the device to the application is still lacking. Here we report a full-featured 2D NOR flash memory chip realized by an atomic device to chip (ATOM2CHIP) technology, which combines a superior 2D electronic device as a memory core and a powerful CMOS platform to support complex instruction control. The ATOM2CHIP blueprint includes a full-stack on-chip process and a cross-platform system design, providing a complete framework to bridge the gap from emerging device concept to an applicable chip. The full-stack on-chip process is a specially designed flow that incorporates planar integration, three-dimensional (3D) architecture and chip packaging, contributing to a high yield of 94.34% based on a full-chip test. The cross-platform system design handles both the 2D circuit design and the 2D-CMOS modules compatibility verification design, contributing to a highly complex, instruction-driven, full-featured chip with 8-bit commands and 32-bit parallelism. These results demonstrate an efficient system integration strategy that showcases the advantages of the 2D electronic system.

Mutations that occur in the cell lineages of sperm or eggs can be transmitted to offspring. In humans, positive selection of driver mutations during spermatogenesis can increase the birth prevalence of certain developmental disorders1-3. Until recently, characterizing the extent of this selection in sperm has been limited by the error rates of sequencing technologies. Here we used the duplex sequencing method NanoSeq4 to sequence 81 bulk sperm samples from individuals aged 24-75 years. Our findings revealed a linear accumulation of 1.67 (95% confidence interval of 1.41-1.92) mutations per year per haploid genome driven by two mutational signatures associated with human ageing. Deep targeted and exome NanoSeq5 of sperm samples identified more than 35,000 germline coding mutations. We detected 40 genes (31 newly identified) under significant positive selection in the male germline that have activating or loss-of-function mechanisms and are involved in diverse cellular pathways. Most of the positively selected genes are associated with developmental or cancer predisposition disorders in children, whereas four of the genes exhibited increased frequencies of protein-truncating variants in healthy populations. We show that positive selection during spermatogenesis drives a 2-3-fold increased risk of known disease-causing mutations, which results in 3-5% of sperm from middle-aged to older individuals with a pathogenic mutation across the exome. These findings shed light on germline selection dynamics and highlight a broader increased disease risk for children born to fathers of advanced age than previously appreciated.

Are widespread stereotypes accurate1-3 or socially distorted4-6? This continuing debate is limited by the lack of large-scale multimodal data on stereotypical associations and the inability to compare these to ground truth indicators. Here we overcame these challenges in the analysis of age-related gender bias7-9, for which age provides an objective anchor for evaluating stereotype accuracy. Despite there being no systematic age differences between women and men in the workforce according to the US Census, we found that women are represented as younger than men across occupations and social roles in nearly 1.4 million images and videos from Google, Wikipedia, IMDb, Flickr and YouTube, as well as in nine language models trained on billions of words from the internet. This age gap is the starkest for content depicting occupations with higher status and earnings. We demonstrate how mainstream algorithms amplify this bias. A nationally representative pre-registered experiment (n = 459) found that Googling images of occupations amplifies age-related gender bias in participants' beliefs and hiring preferences. Furthermore, when generating and evaluating resumes, ChatGPT assumes that women are younger and less experienced, rating older male applicants as of higher quality. Our study shows how gender and age are jointly distorted throughout the internet and its mediating algorithms, thereby revealing critical challenges and opportunities in the fight against inequality.

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 catalyse 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. Here 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 showed 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 enzyme substrate prediction (58.3%). EZSpecificity represents a general machine learning model for the accurate prediction of substrate specificity for enzymes related to fundamental and applied research in biology and medicine.