Aside from movement initiation and control, the primary motor cortex (M1) has been implicated in pain modulation mechanisms. A large body of clinical data has demonstrated that stimulation and behavioral activation of M1 result in clinically important pain relief in patients with specific chronic pain syndromes. However, despite its clinical importance, the full range of circuits for motor cortex-related analgesia (MCRA) remains an enigma. This review draws on insights from experimental and clinical data and provides an overview of the neurobiological mechanisms of MCRA, with particular emphasis on its neurocircuitry basis. Based on structural and functional connections of the M1 within the pain connectome, neural circuits for MCRA are discussed at different levels of the neuroaxis, specifically, the endogenous pain modulation system, the thalamus, the extrapyramidal system, non-noxious somatosensory systems, and cortico-limbic pain signatures. We believe that novel insights from this review will expedite our understanding of M1-induced pain modulation and offer hope for successful mechanism-based refinements of this interventional approach in chronic pain management.

Hilbert space dimension is a key resource for quantum information processing1,2. Not only is a large overall Hilbert space an essential requirement for quantum error correction, but a large local Hilbert space can also be advantageous for realizing gates and algorithms more efficiently3-7. As a result, there has been considerable experimental effort in recent years to develop quantum computing platforms using qudits (d-dimensional quantum systems with d > 2) as the fundamental unit of quantum information8-19. Just as with qubits, quantum error correction of these qudits will be necessary in the long run, but so far, error correction of logical qudits has not been demonstrated experimentally. Here we report the experimental realization of an error-corrected logical qutrit (d = 3) and ququart (d = 4), which was achieved with the Gottesman-Kitaev-Preskill bosonic code20. Using a reinforcement learning agent21,22, we optimized the Gottesman-Kitaev-Preskill qutrit (ququart) as a ternary (quaternary) quantum memory and achieved beyond break-even error correction with a gain of 1.82 ± 0.03 (1.87 ± 0.03). This work represents a novel way of leveraging the large Hilbert space of a harmonic oscillator to realize hardware-efficient quantum error correction.

When two massive objects (black holes, neutron stars or stars) in our universe fly past each other, their gravitational interactions deflect their trajectories1,2. The gravitational waves emitted in the related bound-orbit system-the binary inspiral-are now routinely detected by gravitational-wave observatories3. Theoretical physics needs to provide high-precision templates to make use of unprecedented sensitivity and precision of the data from upcoming gravitational-wave observatories4. Motivated by this challenge, several analytical and numerical techniques have been developed to approximately solve this gravitational two-body problem. Although numerical relativity is accurate5-7, it is too time-consuming to rapidly produce large numbers of gravitational-wave templates. For this, approximate analytical results are also required8-15. Here we report on a new, highest-precision analytical result for the scattering angle, radiated energy and recoil of a black hole or neutron star scattering encounter at the fifth order in Newton's gravitational coupling G, assuming a hierarchy in the two masses. This is achieved by modifying state-of-the-art techniques for the scattering of elementary particles in colliders to this classical physics problem in our universe. Our results show that mathematical functions related to Calabi-Yau (CY) manifolds, 2n-dimensional generalizations of tori, appear in the solution to the radiated energy in these scatterings. We anticipate that our analytical results will allow the development of a new generation of gravitational-wave models, for which the transition to the bound-state problem through analytic continuation and strong-field resummation will need to be performed.

The pressures humanity has been placing on the environment have put Earth's stability at risk. The planetary boundaries framework serves as a method to define a 'safe operating space for humanity'1,2 and has so far been applied mostly to highlight the currently prevailing unsustainable environmental conditions. The ability to evaluate trends over time, however, can help us explore the consequences of alternative policy decisions and identify pathways for living within planetary boundaries3. Here we use the Integrated Model to Assess the Global Environment4 to project control variables for eight out of nine planetary boundaries under alternative scenarios to 2050, both with and without strong environmental policy measures. The results show that, with current trends and policies, the situation is projected to worsen to 2050 for all planetary boundaries, except for ozone depletion. Targeted interventions, such as implementing the Paris climate agreement, a shift to a healthier diet, improved food, and water- and nutrient-use efficiency, can effectively reduce the degree of transgression of the planetary boundaries, steering humanity towards a more sustainable trajectory (that is, if they can be implemented based on social and institutional feasibility considerations). However, even in this scenario, several planetary boundaries, including climate change, biogeochemical flows and biodiversity, will remain transgressed in 2050, partly as result of inertia. This means that more-effective policy measures will be needed to ensure we are living well within the planetary boundaries.

Precision measurements using low-energy antiprotons, exclusively available at the antimatter factory (AMF) of CERN1, offer stringent tests of charge-parity-time (CPT) invariance, which is a fundamental symmetry in the Standard Model of particle physics2. These tests have been realized, for example, in antiprotonic helium3 and antihydrogen4. In our cryogenic Penning-trap experiments5, we measure the magnetic moments6,7 and charge-to-mass ratios of protons and antiprotons and now provide the most precise test of CPT invariance in the baryon sector8. Our experiments are limited by magnetic field fluctuations imposed by the decelerators in the AMF; therefore, we are advancing the relocation of antiprotons to dedicated precision laboratories. Here we present the successful transport of a trapped proton cloud from the AMF using BASE-STEP9-a transportable, superconducting, autonomous and open Penning-trap system that can distribute antiprotons into other experiments. We transferred the trapped protons from our experimental area at the AMF onto a truck and transported them across the Meyrin site of CERN, demonstrating autonomous operation without external power for 4 h and loss-free proton relocation. We thereby confirm the feasibility of transferring particles into low-noise laboratories in the vicinity of the AMF and of using a power generator on the truck10 to reach laboratories throughout Europe. This marks the potential start of a new era in precision antimatter research, enabling low-noise measurements of antiprotons, the charged antimatter ions H¯+11 and H¯2- (ref. 12), and other accelerator-produced ions, such as hydrogen-like lead or uranium ions13,14.

In quantum mechanics, empty space is not void but is characterized by vacuum-field fluctuations, which underlie phenomena such as the Lamb shift1, spontaneous emission, and the Casimir effect2. Due to their quantitatively small relative contributions in free-space atomic physics, they were traditionally overlooked in solid-state systems. Recently, however, the interplay between electronic correlations and quantum electrodynamical effects in low-dimensional systems has become a rapidly advancing area in condensed matter physics3-5, with substantial implications for quantum materials and device engineering. High-mobility two-dimensional electron gases in the quantum Hall regime6 offer an ideal platform to investigate how vacuum electromagnetic fields affect strongly correlated electronic states. Here we demonstrate that adjusting the coupling strength between a two-dimensional electron gas and the vacuum fields of a hovering split-ring resonator leads to a significant reduction in exchange splitting at odd-integer filling factors, along with an enhancement of fractional quantum Hall gaps at filling factors 4/3, 5/3 and 7/5. Theoretical analysis indicates that these effects stem from an effective long-range attractive interaction mediated by virtual cavity photons in regions with strong vacuum electric field gradients. Our findings uncover a new mechanism by which cavity vacuum fields can reshape electronic correlations in quantum Hall systems, establishing a new approach for manipulating correlated quantum phases in low-dimensional materials and paving the way for engineering tailored many-body interactions in compact devices.

Depression is characterized by diverse symptom combinations that can be represented as dynamic networks. While previous research has focused on central symptoms for targeted interventions, less attention has been given to whole-network properties. Here we show that 'network temperature', a novel measure of psychological network stability, captures symptom alignment across adolescence-a critical period for depression onset. Network temperature reflects system stability, with higher values indicating less symptom alignment and greater variability. In three large longitudinal adolescent cohorts (total N = 35,901), we found that network temperature decreases across adolescence, with the steepest decline during early adolescence, particularly in males. This suggests that depression symptom networks stabilize throughout development via increased symptom alignment, potentially explaining why adolescence is a crucial period for depression onset. These findings highlight early adolescence as a key intervention window and underscore the importance of sex-specific and personalized interventions.

Schizophrenia is associated with structural and functional changes in the central nervous system, including the most distal part of it, the retina. However, the question of whether retinal atrophy is present before individuals develop schizophrenia or is a secondary consequence of the disorder remains unanswered. Here we address this question by examining the association between polygenic risk scores for schizophrenia and retinal morphologies in individuals without a schizophrenia diagnosis. We used population data for 34,939 white British and Irish individuals from the UK Biobank. Our robust regression results show that higher polygenic risk scores for schizophrenia were associated with thinner overall maculae, while controlling for confounding factors (b = -0.17, P = 0.018). Similarly, we found that greater polygenic risk scores for schizophrenia specific to neuroinflammation gene sets were associated with thinner ganglion cell inner plexiform layers (b = -0.10, self-contained P = 0.014, competitive P = 0.02). These results provide new evidence for genetic factors that could predispose individuals to heightened neuroinflammatory responses. Over time, these responses could contribute to neurodegenerative processes such as retinal thinning.

Climate extremes are escalating under anthropogenic climate change1. Yet, how this translates into unprecedented cumulative extreme event exposure in a person's lifetime remains unclear. Here we use climate models, impact models and demographic data to project the number of people experiencing cumulative lifetime exposure to climate extremes above the 99.99th percentile of exposure expected in a pre-industrial climate. We project that the birth cohort fraction facing this unprecedented lifetime exposure to heatwaves, crop failures, river floods, droughts, wildfires and tropical cyclones will at least double from 1960 to 2020 under current mitigation policies aligned with a global warming pathway reaching 2.7 °C above pre-industrial temperatures by 2100. Under a 1.5 °C pathway, 52% of people born in 2020 will experience unprecedented lifetime exposure to heatwaves. If global warming reaches 3.5 °C by 2100, this fraction rises to 92% for heatwaves, 29% for crop failures and 14% for river floods. The chance of facing unprecedented lifetime exposure to heatwaves is substantially larger among population groups characterized by high socioeconomic vulnerabilities. Our results call for deep and sustained greenhouse gas emissions reductions to lower the burden of climate change on current young generations.

Methamphetamine is a growing health problem, as is mental health illness. However, no studies have investigated the combinatory effects of both diseases or characterized national trends over a period of time greater than 10 years. We evaluated US trends in mental health disorder-related hospital admissions (MHD-HAs) and compared them with those with concurrent methamphetamine use (MHD-HA-MUs), comparing the demographic characteristics from 2008 to 2020. Our findings reveal a significant increase in MHD-HA-MUs, increasing 10.5-fold, compared with a 1.4-fold increase in MHD-HAs. We also found a 1.53 times higher adjusted prevalence ratio of MHD-HA-MUs compared with MHD-HAs, even when adjusted for confounding factors. MHD-HA-MUs increased significantly among male patients (13-fold), non-Hispanic Black patients (39-fold), those aged 41-64 years (16-fold), and the South (24-fold). Overall, the data suggest that there are synergistic effects with methamphetamine use and mental health disorder, highlighting this patient group's unique needs, requiring distinct action.

Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies (GWASs) can provide new evidence regarding the aetiology of AUD. We report a multi-ancestry GWAS focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals [102,079 cases; European, 75,583; African, 20,689 (mostly African-American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent]. Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus, and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically-relevant comorbidities.

Addressing climate change requires accelerating the development of sustainable alternatives to energy- and water-intensive technologies, particularly for rapidly growing infrastructure such as data centres and cloud1. Here we present a life cycle assessment study examining the impacts of advanced cooling technologies on cloud infrastructure, from virtual machines to server architecture, data centre buildings and the grid. Life cycle assessment is important for early-stage design decisions, enhancing sustainability outcomes alongside feasibility and cost analysis2. We discuss constructing a life cycle assessment for a complex cloud ecosystem (including software, chips, servers and data centre buildings), analysing how different advanced cooling technologies interact with this ecosystem and evaluating each technology from a sustainability perspective to provide adoption guidelines. Life cycle assessment quantifies the benefits of advanced cooling methods, such as cold plates and immersion cooling, in reducing greenhouse gas emissions (15-21%), energy demand (15-20%) and blue water consumption (31-52%) in data centres. This comprehensive approach demonstrates the transformative potential of life cycle assessment in driving sustainable innovation across resource-intensive technologies.

Nickel is a critical element in the shift to sustainable energy systems, with the demand for nickel projected to exceed 6 million tons annually by 20401-4, largely driven by the electrification of the transport sector. Primary nickel production uses acids and carbon-based reductants, emitting about 20 tons of carbon dioxide per ton of nickel produced5-7. Here we present a method using fossil-free hydrogen-plasma-based reduction to extract nickel from low-grade ore variants known as laterites. We bypass the traditional multistep process and combine calcination, smelting, reduction and refining into a single metallurgical step conducted in one furnace. This approach produces high-grade ferronickel alloys at fast reduction kinetics. Thermodynamic control of the atmosphere of the furnace enables selective nickel reduction, yielding an alloy with minimal impurities (<0.04 wt% silicon, approximately 0.01 wt% phosphorus and <0.09 wt% calcium), eliminating the need for further refining. The proposed method has the potential to be up to about 18% more energy efficient while cutting direct carbon dioxide emissions by up to 84% compared with current practice. Our work thus shows a sustainable approach to help resolve the contradiction between the beneficial use of nickel in sustainable energy technologies and the environmental harm caused by its production.

Hydrogen embrittlement (HE) impairs the durability of aluminium (Al) alloys and hinders their use in a hydrogen economy1-3. Intermetallic compound particles in Al alloys can trap hydrogen and mitigate HE4, but these particles usually form in a low number density compared with conventional strengthening nanoprecipitates. Here we report a size-sieved complex precipitation in Sc-added Al-Mg alloys to achieve a high-density dispersion of both fine Al3Sc nanoprecipitates and in situ formed core-shell Al3(Mg, Sc)2/Al3Sc nanophases with high hydrogen-trapping ability. The two-step heat treatment induces heterogeneous nucleation of the Samson-phase Al3(Mg, Sc)2 on the surface of Al3Sc nanoprecipitates that are only above 10 nm in size. The size dependence is associated with Al3Sc nanoprecipitate incoherency, which leads to local segregation of magnesium and triggers the formation of Al3(Mg, Sc)2. The tailored distribution of dual nanoprecipitates in our Al-Mg-Sc alloy provides about a 40% increase in strength and nearly five times improved HE resistance compared with the Sc-free alloy, reaching a record tensile uniform elongation in Al alloys charged with H up to 7 ppmw. We apply this strategy to other Al-Mg-based alloys, such as Al-Mg-Ti-Zr, Al-Mg-Cu-Sc and Al-Mg-Zn-Sc alloys. Our work showcases a possible route to increase hydrogen resistance in high-strength Al alloys and could be readily adapted to large-scale industrial production.

Marine plastic pollution is a global issue, with microplastics (1 µm-5 mm) dominating the measured plastic count1,2. Although microplastics can be found throughout the oceanic water column3,4, most studies collect microplastics from surface waters (less than about 50-cm depth) using net tows5. Consequently, our understanding of the microplastics distribution across ocean depths is more limited. Here we synthesize depth-profile data from 1,885 stations collected between 2014 and 2024 to provide insights into the distribution and potential transport mechanisms of subsurface (below about 50-cm depth, which is not usually sampled by traditional practices3,6) microplastics throughout the oceanic water column. We find that the abundances of microplastics range from 10-4 to 104 particles per cubic metre. Microplastic size affects their distribution; the abundance of small microplastics (1 µm to 100 µm) decreases gradually with depth, indicating a more even distribution and longer lifespan in the water column compared with larger microplastics (100 µm to 5,000 µm) that tend to concentrate at the stratified layers. Mid-gyre accumulation zones extend into the subsurface ocean but are concentrated in the top 100 m and predominantly consist of larger microplastics. Our analysis suggests that microplastics constitute a measurable fraction of the total particulate organic carbon, increasing from 0.1% at 30 m to 5% at 2,000 m. Although our study establishes a global benchmark, our findings underscore that the lack of standardization creates substantial uncertainties, making it challenging to advance our comprehension of the distribution of microplastics and its impact on the oceanic environment.

Acute myocardial infarction is a leading cause of morbidity and mortality worldwide1. Clinical studies have shown that the severity of cardiac injury after myocardial infarction exhibits a circadian pattern, with larger infarcts and poorer outcomes in patients experiencing morning-onset events2-7. However, the molecular mechanisms underlying these diurnal variations remain unclear. Here we show that the core circadian transcription factor BMAL17-11 regulates circadian-dependent myocardial injury by forming a transcriptionally active heterodimer with a non-canonical partner-hypoxia-inducible factor 2 alpha (HIF2A)12-16-in a diurnal manner. To substantiate this finding, we determined the cryo-EM structure of the BMAL1-HIF2A-DNA complex, revealing structural rearrangements within BMAL1 that enable cross-talk between circadian rhythms and hypoxia signalling. BMAL1 modulates the circadian hypoxic response by enhancing the transcriptional activity of HIF2A and stabilizing the HIF2A protein. We further identified amphiregulin (AREG)16,17 as a rhythmic target of the BMAL1-HIF2A complex, critical for regulating daytime variations of myocardial injury. Pharmacologically targeting the BMAL1-HIF2A-AREG pathway provides cardioprotection, with maximum efficacy when aligned with the pathway's circadian phase. These findings identify a mechanism governing circadian variations of myocardial injury and highlight the therapeutic potential of clock-based pharmacological interventions for treating ischaemic heart disease.

Environmental thermal challenges trigger the brain to coordinate both autonomic and behavioural responses to maintain optimal body temperature1-4. It is unknown how temperature information is precisely stored and retrieved in the brain and how it is converted into a physiological response. Here we investigated whether memories could control whole-body metabolism by training mice to remember a thermal challenge. Mice were conditioned to associate a context with a specific temperature by combining thermoregulatory Pavlovian conditioning with engram-labelling technology, optogenetics and chemogenetics. We report that if mice are returned to an environment in which they previously experienced a 4 °C cold challenge, they increase their metabolic rates regardless of the actual environmental temperature. Furthermore, we show that mice have increased hypothalamic activity when they are exposed to the cold, and that a specific network emerges between the hippocampus and the hypothalamus during the recall of a cold memory. Both natural retrieval and artificial reactivation of cold-sensitive memory engrams in the hippocampus mimic the physiological responses that are seen during a cold challenge. These ensembles are necessary for cold-memory retrieval. These findings show that retrieval of a cold memory causes whole-body autonomic and behavioural responses that enable mice to maintain thermal homeostasis.

The coupling between electrons and phonons is one of the fundamental interactions in solids, underpinning a wide range of phenomena, such as resistivity, heat conductivity and superconductivity. However, direct measurements of this coupling for individual phonon modes remain a substantial challenge. In this work, we introduce a new technique for mapping phonon dispersions and electron-phonon coupling (EPC) in van der Waals (vdW) materials. By generalizing the quantum twisting microscope1 (QTM) to cryogenic temperatures, we demonstrate its capability to map not only electronic dispersions through elastic momentum-conserving tunnelling but also phononic dispersions through inelastic momentum-conserving tunnelling. Crucially, the inelastic tunnelling strength provides a direct and quantitative measure of the momentum and mode-resolved EPC. We use this technique to measure the phonon spectrum and EPC of twisted bilayer graphene (TBG) with twist angles larger than 6°. Notably, we find that, unlike standard acoustic phonons, whose coupling to electrons diminishes as their momentum tends to zero, TBG exhibits a low-energy mode whose coupling increases with decreasing twist angle. We show that this unusual coupling arises from the modulation of the interlayer tunnelling by a layer-antisymmetric 'phason' mode of the moiré system. The technique demonstrated here opens the way for examining a large variety of other neutral collective modes that couple to electronic tunnelling, including plasmons2, magnons3 and spinons4 in quantum materials.

Beneath oceanic spreading centres, the lithosphere-asthenosphere boundary (LAB) acts as a permeability barrier that focuses the delivery of melt from deep within the mantle towards the spreading axis1. At intermediate-spreading to fast-spreading ridge crests, the multichannel seismic reflection technique has imaged a nearly flat, 1-2-km-wide axial magma lens (AML)2 that defines the uppermost section of the LAB3, but the nature of the LAB deeper into the crust has been more elusive, with some clues gained from tomographic images, providing only a diffuse view of a wider halo of lower-velocity material seated just beneath the AML4. Here we present 3D seismic reflection images of the LAB extending deep (5-6 km) into the crust beneath Axial volcano, located at the intersection of the Juan de Fuca Ridge and the Cobb-Eickelberg hotspot. The 3D shape of the LAB, which is coincident with a thermally controlled magma assimilation front, focuses hotspot-related and mid-ocean-spreading-centre-related magmatism towards the centre of the volcano, controlling both eruption and hydrothermal processes and the chemical composition of erupted lavas5. In this context, the LAB can be viewed as the upper surface of a 'magma domain', a volume within which melt bodies reside (replacing the concept of a single 'magma reservoir')6. Our discovery of a funnel-shaped, crustal LAB suggests that thermally controlled magma assimilation could be occurring along this surface at other volcanic systems, such as Iceland.