Nature Communications最新文献

The electronic structure of compensated antiferromagnets (CAF) creates large functional responses, reminiscent of ferromagnets and suitable for data storage and readout, despite (nearly) net-zero spontaneous magnetization. Many experimental signatures of CAF - such as giant thermoelectric Nernst effects - should be enhanced when two or more electronic bands are nearly degenerate in vicinity of the Fermi energy. Here, we report a zero-field, thermoelectric Nernst effect >1 μV/K in the CAF CoNb₃S₆ despite its tiny net magnetization ~2 milli − μ_B. As drivers of the functional Nernst and Hall effects, we identify near-degeneracies of electron bands at the upper and lower boundaries of the first Brillouin zone, which are vestiges of nodal planes enforced by a screw axis symmetry in the paramagnetic state. Hot spots of emergent, or fictitious, magnetic fields are formed at the slightly gapped nodal planes. Taking into account more than six hundred Wannier orbitals, our theoretical model reproduces the observed spontaneous Nernst effect, emphasizes the role of proximate spin-space group symmetries and nodal planes for the electronic structure of CAF, and demonstrates the promise of ab-initio search for functional responses in a wide class of materials with reconstructed unit cells (supercells) due to spin or charge order.

NF2-related Schwannomatosis (NF2 SWN) is a rare disease characterised by the growth of multiple nervous system neoplasms, including bilateral vestibular schwannoma (VS). VS tumours are characterised by extensive leucocyte infiltration. However, the immunological landscape in VS and the spatial determinants within the tumour microenvironment that shape the trajectory of disease are presently unknown. In this study, to elucidate the complex immunological networks across VS, we performed imaging mass cytometry (IMC) on clinically annotated VS samples from NF2 SWN patients. We reveal the heterogeneity in neoplastic cell, myeloid cell and T cell populations that co-exist within VS, and that distinct myeloid cell and Schwann cell populations reside within varied spatial contextures across characteristic Antoni A and B histomorphic niches. Interestingly, T-cell populations co-localise with tumour-associated macrophages (TAMs) in Antoni A regions, seemingly limiting their ability to interact with tumorigenic Schwann cells. This spatial landscape is altered in Antoni B regions, where T-cell populations appear to interact with PD-L1⁺ Schwann cells. We also demonstrate that prior bevacizumab treatment (VEGF-A antagonist) preferentially reduces alternatively activated-like TAMs, whilst enhancing CD44 expression, in bevacizumab-treated tumours. Together, we describe niche-dependent modes of T-cell regulation in NF2 SWN VS, indicating the potential for microenvironment-altering therapies for VS.

Sand ripples record interactions between planetary surfaces and environmental flows, providing paleoenvironmental archives when preserved into rocks. Two main ripple types form in sand: drag ripples, common in water, and impact ripples, exclusive to windblown surfaces. Enigmatic meter-scale aeolian ripples on Mars have been assumed to be impact ripples, though ground and orbiter-based observations suggest they may be drag ripples instead. Here, we report on low-pressure wind tunnel experiments in which large ripples formed and evolved from a flat bed. Observations demonstrate that impact and large ripples grow from distinct mechanisms. Large-ripple size aligns with predictions from drag-ripple theory, and associated sand fluxes are greater than predicted for impact ripples. These findings are inconsistent with an impact-ripple origin and instead suggest that large martian ripples are drag ripples. Windblown drag ripples constitute an untapped record of atmospheric evolution on planetary bodies with tenuous or ephemeral atmospheres across the Solar System.

Soil contamination by metals and metalloids (metal[loid]s) is a global issue with significant risks to human health, ecosystems, and food security. Accurate risk assessment depends on understanding metal(loid) mobility, which dictates bioavailability and environmental impact. Here we show a theory-guided machine learning model that predicts soil metal(loid) fractionation across the globe. Our model identifies total metal(loid) content and soil organic carbon as primary drivers of metal(loid) mobility. We find that 37% of the world’s land is at medium-to-high mobilization risk, with hotspots in Russia, Chile, Canada, and Namibia. Our analysis indicates that global efforts to enhance soil carbon sequestration may inadvertently increase metal(loid) mobility. Furthermore, in Europe, the divergence between spatial distributions of total and mobile metal(loid)s is uncovered. These findings offer crucial insights into global distributions and drivers of soil metal(loid) mobility, providing a robust tool for prioritizing metal(loid) mobility testing, raising awareness, and informing sustainable soil management practices.

A comprehensive assessment of combined modifiable risk factors with common complications of type 2 diabetes (T2D) is lacking, and the potential role of proteomics remains unclear. Here, we examine the associations of cardiovascular health (CVH) score and degree of risk factor control with common diabetic complications using data from the UK Biobank (n = 14,102). Furthermore, we explore the mediation effects of plasma proteomics in a subset with proteomic data (n = 1287). Over median follow-ups of 12.4–13.4 years, higher CVH score and higher degree of risk factor control are associated with lower risks of 30 and 22 of 45 adverse outcomes among individuals with T2D, respectively. Mediation analyses reveal that mortality and multiple vascular diseases share common mediators, such as uromodulin and pro-adrenomedullin. These findings highlight the importance of risk factors modification in reducing disease burden among people with T2D and facilitate the understanding of mediation effects of plasma proteins underlying these associations.

Food seeking and avoidance engage primary reward systems to drive behavior. It is nevertheless unclear whether innate or learned food biases interact with general reward processing to interfere with goal-directed choice. To this end, we recruited a large non-clinical sample of females with high eating-disorder symptoms (‘HED’) and a matched sample of females with low eating-disorder symptoms (‘LED’) to complete a reward-learning task where the calorie content of food stimuli was incidental to the goal of maximizing monetary reward. We find and replicate a low-calorie food bias in HED and a high-calorie food bias in LED, reflecting the strength of pre-experimental food-reward associations. An emotional arousal manipulation shifts this group-dependent bias across individual differences, with interoceptive awareness predicting this change. Reinforcement-learning models further identify distinct cognitive components supporting these group-specific food biases. Our results highlight the influence of reinforcement-based mechanisms and emotional arousal in eliciting potentially maladaptive food-reward associations.

Chromatin topology can impact gene regulation, but how evolutionary divergence in chromatin topology has shaped gene regulatory landscapes for distinctive human traits remains poorly understood. CTCF sites determine chromatin topology by forming domains and loops. Here, we show evolutionary divergence in CTCF-mediated chromatin topology at the domain and loop scales during primate evolution, elucidating distinct mechanisms for shaping regulatory landscapes. Human-specific divergent domains lead to a broad rewiring of transcriptional landscapes. Divergent CTCF loops concord with species-specific enhancer activity, influencing enhancer connectivity to target genes in a concordant yet constrained manner. Under this concordant mechanism, we establish the role of human-specific CTCF loops in shaping transcriptional isoform diversity, with functional implications for disease susceptibility. Furthermore, we validate the function of these human-specific CTCF loops using human forebrain organoids. This study advances our understanding of genetic evolution from the perspective of genome architecture.

Magnetically responsive soft materials with spatially-encoded magnetic and material properties enable versatile shape morphing for applications ranging from soft medical robots to biointerfaces. Although high-resolution encoding of 3D magnetic and material properties create a vast design space, their intrinsic coupling makes trial-and-error based design exploration infeasible. Here, we introduce a data-driven strategy that uses stochastic design alterations guided by a predictive neural network, combined with cost-efficient simulations, to optimize distributed magnetization profile and morphology of magnetic soft materials for desired shape-morphing and robotic behaviors. Our approach uncovers non-intuitive 2D designs that morph into complex 2D/3D structures and optimizes morphological behaviors, such as maximizing rotation or minimizing volume. We further demonstrate enhanced jumping performance over an intuitive reference design and showcase fabrication- and scale-agnostic, inherently 3D, multi-material soft structures for robotic tasks including traversing and jumping. This generic, data-driven framework enables efficient exploration of design space of stimuli-responsive soft materials, providing functional shape morphing and behavior for the next generation of soft robots and devices.

The coupled electron-nuclear spin system in an InGaAs semiconductor as testbed of nonlinear dynamics can develop auto-oscillations, resembling time-crystalline behavior, when continuously excited by a circularly polarized laser. We expose this system to deviations from continuous driving by periodic modulation of the excitation polarization, revealing a plethora of nonlinear phenomena that depend on modulation frequency and depth. We find ranges in which the system’s oscillations are entrained with the modulation frequency. The width of these ranges depends on the polarization modulation depth, resulting in an Arnold tongue pattern. Outside the tongue, the system shows a variety of fractional subharmonic responses connected through bifurcation jets when varying the modulation frequency. Here, each branch in the frequency spectrum forms a devil’s staircase. When an entrainment range is approached by going through an increasing order of bifurcations, chaotic behavior emerges. These findings can be described by an advanced model of the periodically pumped electron-nuclear spin system. We discuss the connection of the obtained results to different phases of time matter.

Modulating the physicochemical properties of oxides is crucial to achieve efficient and desirable reactions in heterogeneous catalysis. However, their catalytic role is not clearly identified because unevenly distributed interfaces and close conjugation with metal catalysts may hinder distinguishing their contribution in complex random structures. Here, we demonstrate a model platform composed of well-aligned CeO_x nanowire arrays on Pt catalysts to observe their catalytic role systematically. Independently modulating the crystallinity and oxygen vacancy concentration of oxide nanowires, while preserving heterogeneous interfaces, enables quantitative analysis of their individual effects on partial oxidation selectivity, resulting in hot electron generation during methanol oxidation reactions. CeO_x treated with vacuum annealing on Pt exhibits 1.47- and 2.12-times higher selectivity to methyl formate and chemicurrent yield than CeO_x without annealing on Pt. Density-functional theory calculations reveal that the promoted charge transfer from the electron-accumulated interface driven by oxygen vacancy acts as a key parameter in enhancing selectivity.