Splice-switching antisense oligonucleotides (ASOs) could be used to treat a subset of individuals with genetic diseases1, but the systematic identification of such individuals remains a challenge. Here we performed whole-genome sequencing analyses to characterize genetic variation in 235 individuals (from 209 families) with ataxia-telangiectasia, a severely debilitating and life-threatening recessive genetic disorder2,3, yielding a complete molecular diagnosis in almost all individuals. We developed a predictive taxonomy to assess the amenability of each individual to splice-switching ASO intervention; 9% and 6% of the individuals had variants that were ‘probably’ or ‘possibly’ amenable to ASO splice modulation, respectively. Most amenable variants were in deep intronic regions that are inaccessible to exon-targeted sequencing. We developed ASOs that successfully rescued mis-splicing and ATM cellular signalling in patient fibroblasts for two recurrent variants. In a pilot clinical study, one of these ASOs was used to treat a child who had been diagnosed with ataxia-telangiectasia soon after birth, and showed good tolerability without serious adverse events for three years. Our study provides a framework for the prospective identification of individuals with genetic diseases who might benefit from a therapeutic approach involving splice-switching ASOs.

Weather forecasting is important for science and society. At present, the most accurate forecast system is the numerical weather prediction (NWP) method, which represents atmospheric states as discretized grids and numerically solves partial differential equations that describe the transition between those states1. However, this procedure is computationally expensive. Recently, artificial-intelligence-based methods2 have shown potential in accelerating weather forecasting by orders of magnitude, but the forecast accuracy is still significantly lower than that of NWP methods. Here we introduce an artificial-intelligence-based method for accurate, medium-range global weather forecasting. We show that three-dimensional deep networks equipped with Earth-specific priors are effective at dealing with complex patterns in weather data, and that a hierarchical temporal aggregation strategy reduces accumulation errors in medium-range forecasting. Trained on 39 years of global data, our program, Pangu-Weather, obtains stronger deterministic forecast results on reanalysis data in all tested variables when compared with the world’s best NWP system, the operational integrated forecasting system of the European Centre for Medium-Range Weather Forecasts (ECMWF)3. Our method also works well with extreme weather forecasts and ensemble forecasts. When initialized with reanalysis data, the accuracy of tracking tropical cyclones is also higher than that of ECMWF-HRES.

Scalable generation of genuine multipartite entanglement with an increasing number of qubits is important for both fundamental interest and practical use in quantum-information technologies1,2. On the one hand, multipartite entanglement shows a strong contradiction between the prediction of quantum mechanics and local realization and can be used for the study of quantum-to-classical transition3,4. On the other hand, realizing large-scale entanglement is a benchmark for the quality and controllability of the quantum system and is essential for realizing universal quantum computing5,6,7,8. However, scalable generation of genuine multipartite entanglement on a state-of-the-art quantum device can be challenging, requiring accurate quantum gates and efficient verification protocols. Here we show a scalable approach for preparing and verifying intermediate-scale genuine entanglement on a 66-qubit superconducting quantum processor. We used high-fidelity parallel quantum gates and optimized the fidelitites of parallel single- and two-qubit gates to be 99.91% and 99.05%, respectively. With efficient randomized fidelity estimation9, we realized 51-qubit one-dimensional and 30-qubit two-dimensional cluster states and achieved fidelities of 0.637 ± 0.030 and 0.671 ± 0.006, respectively. On the basis of high-fidelity cluster states, we further show a proof-of-principle realization of measurement-based variational quantum eigensolver10 for perturbed planar codes. Our work provides a feasible approach for preparing and verifying entanglement with a few hundred qubits, enabling medium-scale quantum computing with superconducting quantum systems.

The paper-folding mechanism has been widely adopted in building of reconfigurable macroscale systems because of its unique capabilities and advantages in programming variable shapes and stiffness into a structure1,2,3,4,5. However, it has barely been exploited in the construction of molecular-level systems owing to the lack of a suitable design principle, even though various dynamic structures based on DNA self-assembly6,7,8,9 have been developed10,11,12,13,14,15,16,17,18,19,20,21,22,23. Here we propose a method to harness the paper-folding mechanism to create reconfigurable DNA origami structures. The main idea is to build a reference, planar wireframe structure24 whose edges follow a crease pattern in paper folding so that it can be folded into various target shapes. We realized several paper-like folding and unfolding patterns using DNA strand displacement25 with high yield. Orthogonal folding, repeatable folding and unfolding, folding-based microRNA detection and fluorescence signal control were demonstrated. Stimuli-responsive folding and unfolding triggered by pH or light-source change were also possible. Moreover, by employing hierarchical assembly26 we could expand the design space and complexity of the paper-folding mechanism in a highly programmable manner. Because of its high programmability and scalability, we expect that the proposed paper-folding-based reconfiguration method will advance the development of complex molecular systems.

The human genome functions as a three-dimensional chromatin polymer, driven by a complex collection of chromosome interactions1,2,3. Although the molecular rules governing these interactions are being quickly elucidated, relatively few proteins regulating this process have been identified. Here, to address this gap, we developed high-throughput DNA or RNA labelling with optimized Oligopaints (HiDRO)—an automated imaging pipeline that enables the quantitative measurement of chromatin interactions in single cells across thousands of samples. By screening the human druggable genome, we identified more than 300 factors that influence genome folding during interphase. Among these, 43 genes were validated as either increasing or decreasing interactions between topologically associating domains. Our findings show that genetic or chemical inhibition of the ubiquitous kinase GSK3A leads to increased long-range chromatin looping interactions in a genome-wide and cohesin-dependent manner. These results demonstrate the importance of GSK3A signalling in nuclear architecture and the use of HiDRO for identifying mechanisms of spatial genome organization.

The occurrence of superconductivity in proximity to various strongly correlated phases of matter has drawn extensive focus on their normal state properties, to develop an understanding of the state from which superconductivity emerges1,2,3,4. The recent finding of superconductivity in layered nickelates raises similar interests5,6,7,8. However, transport measurements of doped infinite-layer nickelate thin films have been hampered by materials limitations of these metastable compounds: in particular, a high density of extended defects9,10,11. Here, by moving to a substrate (LaAlO3)0.3(Sr2TaAlO6)0.7 that better stabilizes the growth and reduction conditions, we can synthesize the doping series of Nd1–xSrxNiO2 essentially free from extended defects. In their absence, the normal state resistivity shows a low-temperature upturn in the underdoped regime, linear behaviour near optimal doping and quadratic temperature dependence for overdoping. This is phenomenologically similar to the copper oxides2,12 despite key distinctions—namely, the absence of an insulating parent compound5,6,9,10, multiband electronic structure13,14 and a Mott–Hubbard orbital alignment rather than the charge-transfer insulator of the copper oxides15,16. We further observe an enhancement of superconductivity, both in terms of transition temperature and range of doping. These results indicate a convergence in the electronic properties of both superconducting families as the scale of disorder in the nickelates is reduced.

In mammalian cells, the decision to proliferate is thought to be irreversibly made at the restriction point of the cell cycle1,2, when mitogen signalling engages a positive feedback loop between cyclin A2/cyclin-dependent kinase 2 (CDK2) and the retinoblastoma protein3,4,5. Contrary to this textbook model, here we show that the decision to proliferate is actually fully reversible. Instead, we find that all cycling cells will exit the cell cycle in the absence of mitogens unless they make it to mitosis and divide first. This temporal competition between two fates, mitosis and cell cycle exit, arises because cyclin A2/CDK2 activity depends upon CDK4/6 activity throughout the cell cycle, not just in G1 phase. Without mitogens, mitosis is only observed when the half-life of cyclin A2 protein is long enough to sustain CDK2 activity throughout G2/M. Thus, cells are dependent on mitogens and CDK4/6 activity to maintain CDK2 activity and retinoblastoma protein phosphorylation throughout interphase. Consequently, even a 2-h delay in a cell’s progression towards mitosis can induce cell cycle exit if mitogen signalling is lost. Our results uncover the molecular mechanism underlying the restriction point phenomenon, reveal an unexpected role for CDK4/6 activity in S and G2 phases and explain the behaviour of all cells following loss of mitogen signalling.

In addition to its canonical function of protection from pathogens, the immune system can also alter behaviour1,2. The scope and mechanisms of behavioural modifications by the immune system is not yet well understood. Here, using mouse models of food allergy, we show that allergic sensitization drives antigen-specific avoidance behaviour. Allergen ingestion activates brain areas involved in the response to aversive stimuli, including the nucleus of tractus solitarius, parabrachial nucleus, and central amygdala. Allergen avoidance requires IgE antibodies and mast cells but precedes the development of gut allergic inflammation. The ability of allergen-specific IgE and mast cells to promote avoidance requires cysteinyl leukotrienes and growth and differentiation factor 15 (GDF15). Finally, a comparison of C57BL/6 and BALB/c mouse strains revealed a strong effect of the genetic background on the avoidance behaviour. These findings thus point to antigen-specific behavioural modifications that likely evolved to promote niche selection to avoid unfavourable environments.

Coral reefs are losing the capacity to sustain their biological functions1. In addition to other well-known stressors, such as climatic change and overfishing1, plastic pollution is an emerging threat to coral reefs, spreading throughout reef food webs2, and increasing disease transmission and structural damage to reef organisms3. Although recognized as a global concern4, the distribution and quantity of plastics trapped in the world’s coral reefs remains uncertain3. Here we survey 84 shallow and deep coral ecosystems at 25 locations across the Pacific, Atlantic and Indian ocean basins for anthropogenic macrodebris (pollution by human-generated objects larger than 5 centimetres, including plastics), performing 1,231 transects. Our results show anthropogenic debris in 77 out of the 84 reefs surveyed, including in some of Earth’s most remote and near-pristine reefs, such as in uninhabited central Pacific atolls. Macroplastics represent 88% of the anthropogenic debris, and, like other debris types, peak in deeper reefs (mesophotic zones at 30–150 metres depth), with fishing activities as the main source of plastics in most areas. These findings contrast with the global pattern observed in other nearshore marine ecosystems, where macroplastic densities decrease with depth and are dominated by consumer items5. As the world moves towards a global treaty to tackle plastic pollution6, understanding its distribution and drivers provides key information to help to design the strategies needed to address this ubiquitous threat.

The Berry curvature and quantum metric are the imaginary part and real part, respectively, of the quantum geometric tensor which characterizes the topology of quantum states1. The former is known to generate a zoo of important discoveries such as quantum Hall effect and anomalous Hall effect (AHE)2,3, while the consequences of the quantum metric have rarely been probed by transport. Here we report the observation of quantum metric-induced nonlinear transport, including both nonlinear AHE and diode-like nonreciprocal longitudinal response, in thin films of a topological antiferromagnet, MnBi2Te4. Our observation reveals that the transverse and longitudinal nonlinear conductivities reverse signs when reversing the antiferromagnetic order, diminish above the Néel temperature, and are insensitive to disorder scattering, thus verifying their origin in the band structure topology. They also flip signs between electron and hole-doped regions, in agreement with theoretical calculations. Our work provides a pathway to probe the quantum metric through nonlinear transport and to design magnetic nonlinear devices.

Frustrated Lewis pairs (FLPs) are well documented for the activation of small molecules such as dihydrogen and carbon dioxide1,2,3,4. Although canonical FLP chemistry is heterolytic in nature, recent work has shown that certain FLPs can undergo single-electron transfer to afford radical pairs5. Owing to steric encumbrance and/or weak bonding association, these radicals do not annihilate one another, and they have thus been named frustrated radical pairs (FRPs). Notable preliminary results suggest that FRPs may be useful reagents in chemical synthesis6,7,8, although their applications remain limited. Here we demonstrate that the functionalization of C(sp3)–H bonds can be accomplished using a class of FRPs generated from disilazide donors and an N-oxoammonium acceptor. Together, these species undergo single-electron transfer to generate a transient and persistent radical pair capable of cleaving unactivated C–H bonds to furnish aminoxylated products. By tuning the structure of the donor, it is possible to control regioselectivity and tailor reactivity towards tertiary, secondary or primary C–H bonds. Mechanistic studies lend strong support for the formation and involvement of radical pairs in the target reaction.

Spectroscopy is a key analytical tool that provides valuable insight into molecular structure and is widely used to identify chemical samples. Tagging spectroscopy is a form of action spectroscopy in which the absorption of a single photon by a molecular ion is detected via the loss of a weakly attached, inert “tag” particle (e.g. He, Ne, N2).1–3 The absorption spectrum is derived from the tag loss rate as a function of incident radiation frequency. To date, all spectroscopy of gas phase polyatomic molecules has been restricted to large molecular ensembles, complicating spectral interpretation by the presence of multiple chemical and isomeric species. Here we present a novel tagging spectroscopic scheme to analyze the purest possible sample: a single gas phase molecule. We demonstrate this technique with the measurement of the infrared spectrum of a single tropylium (\({{\rm{C}}}_{7}{{{\rm{H}}}_{7}}^{+}\)) molecular ion; to our knowledge the first recorded spectrum of a single gas phase polyatomic molecule. Our method’s high sensitivity revealed spectral features previously unobserved using traditional tagging methods.4 Our approach in principle enables analysis of multi-component mixtures by identifying constituent molecules one at a time. Single molecule sensitivity extends action spectroscopy to rare samples, such as those of extraterrestrial origin,5,6 or to reactive reaction intermediates formed at number densities too low for traditional action methods.

The continuous improvement in cancer care over the past decade has led to a gradual decrease in cancer-related deaths. This is largely attributed to improved treatment and disease management strategies. Early detection of recurrence using blood-based biomarkers such as circulating tumour DNA (ctDNA) is being increasingly used in clinical practice. Emerging real-world data shows the utility of ctDNA in detecting molecular residual disease and in treatment-response monitoring, helping clinicians to optimize treatment and surveillance strategies. Many studies have indicated ctDNA to be a sensitive and specific biomarker for recurrence. However, most of these studies are largely observational or anecdotal in nature, and peer-reviewed data regarding the use of ctDNA are mainly indication-specific. Here we provide general recommendations on the clinical utility of ctDNA and how to interpret ctDNA analysis in different treatment settings, especially in patients with solid tumours. Specifically, we provide an understanding around the implications, strengths and limitations of this novel biomarker and how to best apply the results in clinical practice.

Extreme precipitation is a considerable contributor to meteorological disasters and there is a great need to mitigate its socioeconomic effects through skilful nowcasting that has high resolution, long lead times and local details1,2,3. Current methods are subject to blur, dissipation, intensity or location errors, with physics-based numerical methods struggling to capture pivotal chaotic dynamics such as convective initiation4 and data-driven learning methods failing to obey intrinsic physical laws such as advective conservation5. We present NowcastNet, a nonlinear nowcasting model for extreme precipitation that unifies physical-evolution schemes and conditional-learning methods into a neural-network framework with end-to-end forecast error optimization. On the basis of radar observations from the USA and China, our model produces physically plausible precipitation nowcasts with sharp multiscale patterns over regions of 2,048 km × 2,048 km and with lead times of up to 3 h. In a systematic evaluation by 62 professional meteorologists from across China, our model ranks first in 71% of cases against the leading methods. NowcastNet provides skilful forecasts at light-to-heavy rain rates, particularly for extreme-precipitation events accompanied by advective or convective processes that were previously considered intractable.

Electron spin resonance spectroscopy is the method of choice for characterizing paramagnetic impurities, with applications ranging from chemistry to quantum computing1,2, but it gives access only to ensemble-averaged quantities owing to its limited signal-to-noise ratio. Single-electron spin sensitivity has, however, been reached using spin-dependent photoluminescence3,4,5, transport measurements6,7,8,9 and scanning-probe techniques10,11,12. These methods are system-specific or sensitive only in a small detection volume13,14, so that practical single-spin detection remains an open challenge. Here, we demonstrate single-electron magnetic resonance by spin fluorescence detection15, using a microwave photon counter at millikelvin temperatures16. We detect individual paramagnetic erbium ions in a scheelite crystal coupled to a high-quality-factor planar superconducting resonator to enhance their radiative decay rate17, with a signal-to-noise ratio of 1.9 in one second integration time. The fluorescence signal shows anti-bunching, proving that it comes from individual emitters. Coherence times up to 3 ms are measured, limited by the spin radiative lifetime. The method has the potential to be applied to arbitrary paramagnetic species with long enough non-radiative relaxation times, and allows single-spin detection in a volume as large as the resonator magnetic mode volume (approximately 10 μm3 in the present experiment), orders of magnitude larger than other single-spin detection techniques. As such, it may find applications in magnetic resonance and quantum computing.

Cancer cells evade T cell-mediated killing through tumour–immune interactions whose mechanisms are not well understood1,2. Dendritic cells (DCs), especially type-1 conventional DCs (cDC1s), mediate T cell priming and therapeutic efficacy against tumours3. DC functions are orchestrated by pattern recognition receptors3,4,5, although other signals involved remain incompletely defined. Nutrients are emerging mediators of adaptive immunity6,7,8, but whether nutrients affect DC function or communication between innate and adaptive immune cells is largely unresolved. Here we establish glutamine as an intercellular metabolic checkpoint that dictates tumour–cDC1 crosstalk and licenses cDC1 function in activating cytotoxic T cells. Intratumoral glutamine supplementation inhibits tumour growth by augmenting cDC1-mediated CD8+ T cell immunity, and overcomes therapeutic resistance to checkpoint blockade and T cell-mediated immunotherapies. Mechanistically, tumour cells and cDC1s compete for glutamine uptake via the transporter SLC38A2 to tune anti-tumour immunity. Nutrient screening and integrative analyses show that glutamine is the dominant amino acid in promoting cDC1 function. Further, glutamine signalling via FLCN impinges on TFEB function. Loss of FLCN in DCs selectively impairs cDC1 function in vivo in a TFEB-dependent manner and phenocopies SLC38A2 deficiency by eliminating the anti-tumour therapeutic effect of glutamine supplementation. Our findings establish glutamine-mediated intercellular metabolic crosstalk between tumour cells and cDC1s that underpins tumour immune evasion, and reveal glutamine acquisition and signalling in cDC1s as limiting events for DC activation and putative targets for cancer treatment.

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug–target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.

A viscosity jump of one to two orders of magnitude in the lower mantle of Earth at 800–1,200-km depth is inferred from geoid inversions and slab-subducting speeds. This jump is known as the mid-mantle viscosity jump1,2. The mid-mantle viscosity jump is a key component of lower-mantle dynamics and evolution because it decelerates slab subduction3, accelerates plume ascent4 and inhibits chemical mixing5. However, because phase transitions of the main lower-mantle minerals do not occur at this depth, the origin of the viscosity jump remains unknown. Here we show that bridgmanite-enriched rocks in the deep lower mantle have a grain size that is more than one order of magnitude larger and a viscosity that is at least one order of magnitude higher than those of the overlying pyrolitic rocks. This contrast is sufficient to explain the mid-mantle viscosity jump1,2. The rapid growth in bridgmanite-enriched rocks at the early stage of the history of Earth and the resulting high viscosity account for their preservation against mantle convection5,6,7. The high Mg:Si ratio of the upper mantle relative to chondrites8, the anomalous 142Nd:144Nd, 182W:184W and 3He:4He isotopic ratios in hot-spot magmas9,10, the plume deflection4 and slab stagnation in the mid-mantle3 as well as the sparse observations of seismic anisotropy11,12 can be explained by the long-term preservation of bridgmanite-enriched rocks in the deep lower mantle as promoted by their fast grain growth.

It is unclear how much carbon should be stored in temporary and risky offsets to compensate one ton of CO2 emissions. Here we cast the social value of an offset (SVO), measured in terms of economic damages avoided, as a well-defined fraction of the social cost of carbon reflecting offset duration, and risks of non-additionality and failure. The SVO reflects the value of temporary storage, and overcomes shortcomings in the climate science and economics of previous contributions1,2,3,4. The SVO is policy relevant. An efficient net-zero policy will consist of offsets if their SVO/cost ratio exceeds the benefit/cost ratio of alternatives. The SVO yields an indicator of the equivalence of offsets to permanent carbon storage measured by the ratio of the SVO to the social cost of carbon. We provide a matrix of equivalence factors for different risks, permanence and climate scenarios. Estimation yields a rule of thumb: one offset sequestering one ton for 50 years is equivalent to between 0.33 and 0.5 tons permanently locked away. Equivalence offers a means of replacing perpetual offset contracts by simpler, easy to monitor short-term contracts, has applications to carbon life cycle analysis5 and the valuation of carbon debts6, and can be the basis of comparing offsets of different qualities in the voluntary and compliance markets.

While eukaryotic Argonautes and long prokaryotic Argonautes (pAgos) cleave nucleic acids, some short pAgos lack nuclease activity and hydrolyze NAD(P)+ to induce bacterial cell death1. We present a hierarchical activation pathway for SPARTA, a short pAgo consisting of an Ago protein and an associated protein TIR-APAZ2. SPARTA progresses through distinct oligomeric forms, including a monomeric apo state, a monomeric RNA/DNA-bound state, two dimeric RNA/DNA-bound states, and a tetrameric RNA/DNA-bound active state. These snapshots together identify oligomerization as a mechanistic principle of SPARTA activation. Apo SPARTA is inactive, its RNA/DNA-binding channel occupied an auto-inhibitory motif in TIR-APAZ. Upon RNA/DNA binding, SPARTA transitions from a monomer to a symmetric and then an asymmetric dimer, in which two TIR domains interact via charge and shape complementarity. Next, two dimers assemble into a tetramer with a central TIR cluster responsible for hydrolyzing NAD(P)+. Additionally, we observed unique features of SPARTA-RNA/DNA interactions, including competition between the DNA 3’ end and the auto-inhibitory motif, interactions between the RNA G2 nucleotide and Ago, and splaying of the RNA-DNA duplex by two loops exclusive to short pAgos. Together, our findings contribute a mechanistic basis for the activation of short pAgos, a large section of the Ago superfamily.