Lithospheric thin zones, such as recently failed rifts, are generally assumed to be weak spots where magmatism and deformation can concentrate during rifting and large igneous province development1-3. Yet, the Turkana Depression in East Africa, the site of the failed 66-million-year-old Anza Rift, did not experience the widespread flood magmatism seen on the adjacent Ethiopian Plateau, despite being a lithospheric thin spot when the region encountered hot plume material around 45 million years ago4. Here we jointly invert surface-wave and receiver function data to constrain crustal and upper-mantle seismic structure below the Depression to evaluate lithospheric thermo-mechanical modification. Evidence for thick lower crustal intrusions, ubiquitous below the uplifted Ethiopian Plateau5,6, is comparatively lacking below the Depression's failed Anza Rift system, which ongoing East African rifting is circumnavigating, not exploiting. The mantle lithosphere below the Depression has also retained its cool, fast-wavespeed 'lid' character, contrasting the Ethiopian Plateau. Volatile depletion during failed Anza rifting probably rendered the thinned lithosphere refractory without later rejuvenation. Subsequent rifting and magmatism thus initiated away from the still-thin Anza Rift, in regions where fertile lithosphere enabled melting and the sufficient lowering of plate yield strength. Areas of thinned lithosphere are thus not necessarily persistent weak zones where significant extension and magmatic provinces will develop.

The ability to spatially map multiple layers of omics information across developmental timepoints enables exploration of the mechanisms driving brain development1, differentiation, arealization and disease-related alterations. Here we used spatial tri-omic sequencing, including spatial ATAC-RNA-protein sequencing and spatial CUT&Tag-RNA-protein sequencing, alongside multiplexed immunofluorescence imaging (co-detection by indexinng (CODEX)) to map dynamic spatial remodelling during brain development and neuroinflammation. We generated a spatiotemporal tri-omic atlas of the mouse brain from postnatal day 0 (P0) to P21 and compared corresponding regions with the human developing brain. In the cortex, we identified temporal persistence and spatial spreading of chromatin accessibility for a subset of layer-defining transcription factors. In the corpus callosum, we observed dynamic chromatin priming of myelin genes across subregions and identified a role for layer-specific projection neurons in coordinating axonogenesis and myelination. In a lysolecithin neuroinflammation mouse model, we detected molecular programs shared with developmental processes. Microglia exhibited both conserved and distinct programs for inflammation and resolution, with transient activation observed not only at the lesion core but also at distal locations. Overall, this study reveals common and differential mechanisms underlying brain development and neuroinflammation, providing a rich resource for investigating brain development, function and disease.

The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events1-3. Single-cell transcriptomics enables a systematic study of cell types across the entire timeline of cortical development. Here we present a comprehensive and high-resolution transcriptomic and epigenomic cell-type atlas of the developing mouse visual cortex. The atlas is built from a single-cell RNA sequencing dataset of 568,654 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 200,061 high-quality nuclei, which were densely sampled across the embryonic and postnatal developmental stages (from embryonic day 11.5 to postnatal day 56). We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory and non-neuronal cell types in the visual cortex. Branching points that mark the emergence of new cell types at specific developmental ages and molecular signatures of cellular diversification are identified. The trajectory map shows that neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage give rise to all cell classes and nearly all subclasses in a staggered parallel manner. Increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage and the onset of critical period, suggesting that there is continuous cell-type diversification at different stages of cortical development. Throughout development, there are cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types. We identify cell-type-specific and temporally resolved gene regulatory networks that link transcription factors and downstream target genes through accessible chromatin motifs. Collectively, our study provides a detailed dynamic molecular map directly associated with individual cell types and specific temporal events that can reveal the molecular logic underlying the complex and multifaceted cortical cell type and circuit development.

The telencephalon of the mammalian brain contains multiple regions and circuits that have adaptive and integrative roles in a variety of brain functions. GABAergic neurons in the telencephalon are diverse; they have many circuit functions, and dysfunction of these neurons has been implicated in various brain disorders1-3. Here we conducted a systematic and in-depth analysis of the transcriptomic and spatial organization of GABAergic neuronal types in all regions of the mouse telencephalon and their developmental origins. This was accomplished using 611,423 young adult single-cell transcriptomes and 614,569 single-cell transcriptomes collected from multiple prenatal and postnatal developmental timepoints. We present a hierarchically organized adult telencephalic GABAergic neuronal cell-type taxonomy of 7 classes, 52 subclasses, 284 supertypes and 1,051 clusters, as well as a corresponding developmental taxonomy of 1,688 clusters across ages from embryonic day 7 to postnatal day 14. Detailed charting efforts reveal extraordinary complexity whereby relationships among cell types reflect both spatial locations and developmental origins. Transcriptomically and developmentally related cell types are often found in distant and diverse brain regions, indicating that long-distance migration and dispersion is a common characteristic of nearly all classes of telencephalic GABAergic neurons. Moreover, we find various spatial dimensions of both discrete and continuous variation among related cell types that are correlated with gene expression gradients. Lastly, we find that cortical, striatal and some pallidal GABAergic neurons undergo extensive postnatal diversification, whereas septal, preoptic and most pallidal GABAergic neuronal types emerge in a burst during the embryonic stage with limited postnatal diversification. Overall, the telencephalic GABAergic cell-type taxonomy will serve as a foundational reference for molecular, structural and functional studies of cell types and circuits by the entire community.

The human neocortex is composed of diverse cell types1 that are generated during development according to spatially and temporally organized programmes initiated by neural stem cells2-5. Despite the growing number of studies that have captured snapshots of gene expression of single cells along the axis of differentiation and maturation, the underlying map of lineage relationships that link individual progenitor cells to specific subtypes of neurons and glia remains unknown, especially in humans. Here we applied prospective lineage tracing to map the manifold of human neural stem and progenitor cell differentiation across the developmental window encompassing neurogenesis and gliogenesis in human primary tissue. By profiling the clonal output of 6,402 progenitor cells, we created a lineage-resolved map of human cortical development. Here we show that cortical progenitors switch from glutamatergic to GABAergic (involving γ-aminobutyric acid) neurogenesis around midgestation, which coincides with an onset of oligodendrocyte generation. Additionally, we find that truncated radial glia maintain a glutamatergic neurogenic potential for a protracted period during human cortical development. Unexpectedly, we find that late-born glutamatergic neurons derived from truncated radial glia exhibit molecular features of deep cortical layer neurons and may contribute to the expansion of the subplate region during midgestation.

Mammalian brains vary in size, structure and function, but the extent to which evolutionarily novel cell types contribute to this variation remains unresolved1-4. Previous studies suggest that there is a primate-specific population of striatal inhibitory interneurons-the TAC3 interneurons5. However, broader taxonomic and developmental characterization is required to address novelty in cell-type evolution. Here we examine gene expression in inhibitory neurons across 10 mammalian species, spanning 160 million years of divergence from primates. We find that the initial class of newborn TAC3 interneurons specified during development represents an ancestral, medial ganglionic eminence (MGE)-derived striatal population that is also present in pig and ferret cortex. This discovery prompted a re-examination of Glires, including mice, which are thought to lack the TAC3 type5,6. Targeted enrichment of MGE precursors in mice revealed conservation of the TAC3 initial class, camouflaged by reduced expression of Tac2 (the mouse orthologue of TAC3) and a gain of Th expression. Extending our analysis to the adult striatum further supported the homology of primate TAC3 and mouse Th striatal interneurons, and also uncovered a rare Tac2 subpopulation in the mouse ventromedial striatum. This study suggests that initial classes of telencephalic inhibitory neurons are largely conserved, and that during evolution, neuronal types in the mammalian brain change through redistribution and fate refinement, rather than by derivation of novel precursors early in development.

Post-traumatic stress (PTS) encompasses a range of psychological responses following trauma, which may lead to more severe outcomes such as post-traumatic stress disorder (PTSD). Identifying early neuroimaging biomarkers that link brain function to PTS outcomes is critical for understanding PTSD risk. This longitudinal study examines the association between brain dynamic functional network connectivity (dFNC) and current/future PTS symptom severity, and the impact of sex on this relationship. By analyzing 275 participants' dFNC data obtained ~2 weeks after trauma exposure, we noted that brain dynamics of an inter-network brain state link negatively with current (r=-0.197, pcorrected = 0.0079) and future (r=-0.176, pcorrected = 0.0176) PTS symptom severity. Also, dynamics of an intra-network brain state correlated with future symptom intensity (r = 0.205, pcorrected = 0.0079). We additionally observed that the association between the network dynamics of the inter-network and intra-network brain state with symptom severity is more pronounced in female group. Our findings highlight a potential link between brain network dynamics in the aftermath of trauma with current and future PTSD outcomes, with a stronger effect in female group, underscoring the importance of sex differences.

Close-in transiting sub-Neptunes are abundant in our Galaxy1. Planetary interior models based on their observed radius-mass relationship suggest that sub-Neptunes contain a discernible amount of either hydrogen (dry planets) or water (wet planets) blanketing a core composed of rocks and metal2. Water-rich sub-Neptunes have been believed to form farther from the star and then migrate inwards to their present orbits3. Here we report experimental evidence of reactions between warm, dense hydrogen fluid and silicate melt that release silicon from the magma to form alloys and hydrides at high pressures. We found that oxygen liberated from the silicate melt reacts with hydrogen, producing an appreciable amount of water up to a few tens of weight per cent, which is much greater than previously predicted based on low-pressure ideal gas extrapolation4,5. Consequently, these reactions can generate a spectrum of water contents in hydrogen-rich planets, with the potential to reach water-rich compositions for some sub-Neptunes, implying an evolutionary relationship between hydrogen-rich and water-rich planets. Therefore, detection of a large amount of water in exoplanet atmospheres may not be the optimal evidence for planet migration in the protoplanetary disk, calling into question the assumed link between composition and planet formation location.

Muscular systems1, the fundamental components of mobility in animals, have sparked innovations across technological and medical fields2,3. Yet artificial muscles suffer from dynamic programmability, scalability and responsiveness owing to complex actuation mechanisms and demanding material requirements. Here we introduce a design paradigm for artificial muscles, utilizing more than 10,000 microbubbles with targeted ultrasound activation. These microbubbles are engineered with precise dimensions that correspond to distinct resonance frequencies. When stimulated by a sweeping-frequency ultrasound, microbubble arrays in the artificial muscle undergo selective oscillations and generate distributed point thrusts, enabling the muscle to achieve programmable deformation with remarkable attributes: a high compactness of approximately 3,000 microbubbles per mm2, a low weight of 0.047 mg mm-2, a substantial force intensity of approximately 7.6 μN mm-2 and fast response (sub-100 ms during gripping). Moreover, they offer good scalability (from micrometre to centimetre scale), exceptional compliance and many degrees of freedom. We support our approach with a theoretical model and demonstrate applications spanning flexible organism manipulation, conformable robotic skins for adding mobility to static objects and conformally attaching to ex vivo porcine organs, and biomimetic stingraybots for propulsion within ex vivo biological environments. The customizable artificial muscles could offer both immediate and long-term impact on soft robotics, wearable technologies, haptics and biomedical instrumentation.

When electrons in metals act collectively, they enable emergent phenomena and electronic functionalities that transcend the behaviour of individual particles1. Coherent collective charge motion has so far been observed primarily in superconductors, in which it arises with the formation of Cooper pairs2,3. Here we report experimental evidence for coherent charge transport in the normal state of the kagome metal CsV3Sb5, indicative of a distinct collective electronic state. The signature is a set of magnetoresistance oscillations in mesoscopic crystalline pillars under in-plane magnetic fields, with a periodicity determined by the number of magnetic flux quanta h/e threading between adjacent kagome layers-effectively forming an interlayer Aharonov-Bohm interferometer. The cooperative nature of this phenomenon is evidenced by a non-analytic angular dependence characterized by abrupt transitions between discrete oscillation frequencies and its persistence over length scales that exceed the single-particle mean free path. Notably, the oscillation amplitude matches other anomalous electronic responses reported in CsV3Sb5, pointing to an underlying mechanism that establishes intrinsic coherence. These findings shed new light on the debated nature of correlated order in kagome metals and establish CsV3Sb5 as a platform for realizing long-range coherent charge transport in the absence of superconductivity-opening new directions for coherence in correlated electron systems beyond conventional models.

The iron and steel sector is central to national net-zero efforts but remains hard to abate1,2. Existing decarbonization roadmaps fail to guide technology choices for individual plants, given their heterogeneity and economic constraints3-5. Here, by integrating two global plant-level datasets and forecasted technology costs, we develop a model to identify the least-cost technology pathway for each plant worldwide in alignment with national carbon-neutrality targets. In the short term (pre-2030), energy efficiency improvements and scrap reuse are the cheapest decarbonization strategies, reducing cumulative global carbon dioxide (CO2) emissions by 7.8 Gt and 7.2 Gt at average costs of -US$8.5 tCO2-1 and US$0.3 tCO2-1, respectively. In the long term (after 2030), smelt reduction with carbon capture is expected to become technically mature and economically viable, achieving approximately 6.0 Gt of CO2 reductions at costs of US$7-15 tCO2-1 in Chinese plants and US$26-75 tCO2-1 in plants across Japan, Korea and Europe. After 2040, green-hydrogen-based steelmaking is estimated to contribute an additional 0.3 Gt of CO2 abatement in European plants at costs of US$27-44 tCO2-1. This study tailors plant-specific least-cost technology pathways that reconcile stakeholders' economic interests with climate objectives, enabling actionable decarbonization strategies and supporting global net-zero targets.

There is an emerging need for objective neural biomarkers of obsessive-compulsive disorder (OCD) to improve the efficacy of neuromodulatory interventions, most notably deep-brain stimulation (DBS), and develop closed-loop stimulation paradigms. Preliminary data suggest that such biomarkers may be derived from local field potentials (LFPs) recorded in individual patients implanted with sensing DBS devices. However, reliable LFP signatures that are generalizable across OCD patients have yet to be identified. Here, we relate LFPs recorded from sensing DBS electrodes in different basal-ganglia structures to core symptoms of OCD in 11 patients during personalized provocation of obsessions and compulsions. We identify two general markers of compulsion: delta and alpha LFP power was significantly increased during all compulsions in the external globus pallidus (GPe), nucleus accumbens, anterior limb of the internal capsule (ALIC) and anterior lateral anterior commissure. In mental compulsion subtypes, similar low-frequency increases were observed only in GPe (delta/alpha) and ALIC (alpha), suggesting that these signals possibly reflect more universal biomarkers of compulsivity unconfounded by motor function. GPe delta power correlated with OCD symptom severity, establishing a meaningful connection between subcortical sensing DBS readout and patient experience. ALIC alpha power was modulated by the phase of theta oscillations during compulsions, possibly reflecting pathological coupling of cortical networks in OCD. Our results demonstrate unique, group-level LFP correlates of core OCD symptoms across disease-relevant basal-ganglia structures. These electrophysiological signatures help pave the way toward the development of biomarker-targeted neuro-modulatory intervention for OCD. Netherlands Trial Register ID: NL7486.

Atmospheric particulate matter (PM), a public health concern worldwide, is at present regulated according to its mass concentration1. However, it is increasingly thought that mass concentration may not fully capture the physicochemical properties of PM linked to its health impact2. Consequently, it has been suggested to further investigate the adequacy of this metric as an unequivocal indicator of PM health effects3-5. The new European regulation on air quality introduced oxidative potential (OP) as a recommended parameter to be monitored at supersites1, to explore further deciphering information about PM reactivity and health impacts6,7. Here we use a database of almost 11,500 OP measurements from 43 locations across parts of Europe that were analysed with the two most commonly used OP assays8, OPAA and OPDTT, with a standardized protocol9,10. We find high spatial variability of OP across Europe, strongly influenced by site type, such as urban or rural. Accounting for OP alongside PM mass suggests that further improvements in urban air quality may require consideration, particularly near roads, where volumetric OP of PM10 exceeds background levels by a factor of 2.4 to 3.1, depending on the assay used. Analysis of mitigation strategies shows that traffic is a key source to target for effectively reducing OP in cities, whereas comprehensive reductions in PM from both traffic and biomass burning are required to also meet World Health Organization mass guidelines. Although the epidemiological evidence for OP health impacts is still evolving2,8, our findings may help inform the interpretation of future work.

As demand for immersive experiences grows, displays with smaller sizes and higher resolutions are being viewed increasingly closer to the human eye1. As the size of emitting pixels shrinks, the intensity and uniformity of their emission are degraded while colour cross-talk and fabrication complexity increase, making ultra-high-resolution imaging challenging2-4. By contrast, electronic paper, which uses ambient light for visibility, can maintain high optical contrast regardless of pixel size, but cannot achieve high resolution5,6. Here we demonstrate electronic paper with electrically tunable metapixels down to ~560 nm in size (>25,000 pixels per inch) consisting of WO3 nanodisks, which undergo a reversible insulator-to-metal transition on electrochemical reduction. This transition enables dynamic modulation of the refractive index and optical absorption, allowing precise control over reflectance and contrast at the nanoscale. By using this effect, the metapixels can achieve pixel densities approaching the visual resolution limit when the display size matches the pupil diameter, which we refer to as retina electronic paper. Our technology also demonstrates full-colour video capability (>25 Hz), high reflectance (~80%), strong optical contrast (~50%), low energy consumption (~0.5-1.7 mW cm-2) and support for anaglyph 3D display, highlighting its potential as a next-generation solution for immersive virtual reality systems.

The dynamics of quantum many-body systems is characterized by quantum observables that are reconstructed from correlation functions at separate points in space and time1-3. In dynamics with fast entanglement generation, however, quantum observables generally become insensitive to the details of the underlying dynamics at long times due to the effects of scrambling. To circumvent this limitation and enable access to relevant dynamics in experimental systems, repeated time-reversal protocols have been successfully implemented4. Here we experimentally measure the second-order out-of-time-order correlators (OTOC(2))5-18 on a superconducting quantum processor and find that they remain sensitive to the underlying dynamics at long timescales. Furthermore, OTOC(2) manifests quantum correlations in a highly entangled quantum many-body system that are inaccessible without time-reversal techniques. This is demonstrated through an experimental protocol that randomizes the phases of Pauli strings in the Heisenberg picture by inserting Pauli operators during quantum evolution. The measured values of OTOC(2) are substantially changed by the protocol, thereby revealing constructive interference between Pauli strings that form large loops in the configuration space. The observed interference mechanism also endows OTOC(2) with high degrees of classical simulation complexity. These results, combined with the capability of OTOC(2) in unravelling useful details of quantum dynamics, as shown through an example of Hamiltonian learning, indicate a viable path to practical quantum advantage.

The unification of gravity and quantum mechanics remains one of the most profound open questions in science. With recent advances in quantum technology, an experimental idea first proposed by Richard Feynman1 is now regarded as a promising route to testing this unification for the first time. The experiment involves placing a massive object in a quantum superposition of two locations and letting it gravitationally interact with another mass. If the two objects subsequently become entangled, this is considered unambiguous evidence that gravity obeys the laws of quantum mechanics. This conclusion derives from theorems that treat a classical gravitational interaction as a local interaction capable of transmitting only classical, not quantum, information2-8. Here we extend the description of matter used in these theorems to the full framework of quantum field theory, finding that theories with classical gravity can then transmit quantum information and, thus, generate entanglement through physical, local processes. The effect scales differently to that predicted by theories of quantum gravity, and so it gives information on the parameters and form of the experiment required to robustly provide evidence for the quantum nature of gravity.

The landmark discovery that neutrinos have mass and can change type (or flavour) as they propagate-a process called neutrino oscillation1-6-has opened up a rich array of theoretical and experimental questions being actively pursued today. Neutrino oscillation remains the most powerful experimental tool for addressing many of these questions, including whether neutrinos violate charge-parity (CP) symmetry, which has possible connections to the unexplained preponderance of matter over antimatter in the Universe7-11. Oscillation measurements also probe the mass-squared differences between the different neutrino mass states (Δm2), whether there are two light states and a heavier one (normal ordering) or vice versa (inverted ordering), and the structure of neutrino mass and flavour mixing12. Here we carry out the first joint analysis of datasets from NOvA13 and T2K14, the two currently operating long-baseline neutrino oscillation experiments (hundreds of kilometres of neutrino travel distance), taking advantage of our complementary experimental designs and setting new constraints on several neutrino sector parameters. This analysis provides new precision on the Δm322 mass difference, finding 2.43-0.03+0.04×10-3eV2 in the normal ordering and -2.48-0.04+0.03×10-3eV2 in the inverted ordering, as well as a 3σ interval on δCP of [-1.38π, 0.30π] in the normal ordering and [-0.92π, -0.04π] in the inverted ordering. The data show no strong preference for either mass ordering, but notably, if inverted ordering were assumed true within the three-flavour mixing model, then our results would provide evidence of CP symmetry violation in the lepton sector.

Achieving superpolynomial speed-ups for optimization has long been a central goal for quantum algorithms1. Here we introduce decoded quantum interferometry (DQI), a quantum algorithm that uses the quantum Fourier transform to reduce optimization problems to decoding problems. When approximating optimal polynomial fits over finite fields, DQI achieves a superpolynomial speed-up over known classical algorithms. The speed-up arises because the algebraic structure of the problem is reflected in the decoding problem, which can be solved efficiently. We then investigate whether this approach can achieve a speed-up for optimization problems that lack an algebraic structure but have sparse clauses. These problems reduce to decoding low-density parity-check codes, for which powerful decoders are known2,3. To test this, we construct a max-XORSAT instance for which DQI finds an approximate optimum substantially faster than general-purpose classical heuristics, such as simulated annealing. Although a tailored classical solver can outperform DQI on this instance, our results establish that combining quantum Fourier transforms with powerful decoding primitives provides a promising new path towards quantum speed-ups for hard optimization problems.