Nature Communications最新文献

Wheat stem rust is a disease of global importance caused by the fungal pathogen Puccinia graminis f. sp. tritici (Pgt). Here we generate chromosome-level, nuclear-phased genome references for Pgt isolates ETH2013-1 and ITA2018-1, representing races TKTTF and TTRTF respectively, that have caused major epidemics in Africa and Europe. The nuclear haplotypes of ETH2013-1 and ITA2018-1 are unique and unrelated to those of Ug99 and Pgt21. Pgt nuclear haplotypes show extensive variation in sequence and copy number of six known Avr genes and AvrSr33, which we identify through an effector gene library screen. Recognition properties of 22 novel Avr gene variants explain the race virulence phenotypes and the outbreak of TTRTF on durum cultivars containing Sr13b, since ITA2018-1 carries a homozygous deletion of AvrSr13. This work establishes an Avr gene atlas for Pgt that can inform wheat breeding and enable development of sequence-based virulence diagnostic tools for pathogen surveillance.

Local field potentials (LFPs) reflect coordination among neural populations, yet their exact relationship to neural computation remains unknown. One exception is the theta rhythm of the rodent hippocampus, which organizes sequential firing among place cells, enabling spike timing to track the animal's path through its environment. But when the animal stops, the theta rhythm becomes irregular, which is assumed to disrupt its ability to carry spatial information. Here we challenge this assumption by developing an artificial neural network that discovers position-tuned theta rhythms (pThetas) from LFPs even in the absence of strong theta oscillations. Using recordings from male rats, we provide evidence that pTheta is distinct from the dominant theta rhythm, while reflecting rhythmic coordination among place cell populations. Our work suggests that weak and intermittent oscillations, as seen in many brain regions and species, can convey information commensurate with population spike codes when decoded using information-based rather than variance-based principles.

Evidence supports the health benefits of physical activity, but the longitudinal patterns of physical activity associated with long-term health outcomes remain insufficiently understood. In 231,488 health professionals from three US cohorts with repeated physical activity assessments for 32 years, we prospectively examined the associations of long-term physical activity patterns (volume, consistency, and trajectories) with incidence of major chronic diseases, including type 2 diabetes, major cardiovascular disease, and cancer. We find that maintaining a volume at the recommended level throughout the follow-up is related to a greater risk reduction than engaging in sporadic high-volume activity in some periods mixed with inactivity. The trajectory analysis reveals that being physically active throughout middle adulthood is associated with a 10-28% lower incidence of major chronic diseases after age 60. This work demonstrates that maintaining physical activity over the long term provides added benefits beyond activity volume alone for chronic disease prevention.

The remaining carbon budget (RCB) of countries provides a benchmark for evaluating national mitigation efforts and was central to a recent European Court of Human Rights' ruling. However, estimates of national RCBs are inconsistent with CO₂ accounting in national greenhouse gas inventories (NGHGIs). Here, we align RCBs with NGHGI accounting standards. For 2024, NGHGI alignment reduces the 1.5 °C (50%) global RCB by  ~100 GtCO₂ ( ≈ 50%) and the 2 °C (66%) RCB by  ~200 GtCO₂ ( ≈ 20%). Thus, we estimate the 1.5 °C (50%) NGHGI-consistent global RCB to be depleted by 2027. We provide NGHGI-consistent national RCBs for common allocation methods and most countries. Following Paris Agreement equity principles, we find that by 2025, 64-85 countries could have exceeded their fair-share RCB for 1.5 °C (50%). While national RCBs depend on normative choices and are unlikely to directly drive negotiations, our framework enables more methodologically robust RCB calculations to track country-level mitigation progress.

Late diagnosis and the lack of effective early detection techniques contribute to the poor prognosis of pancreatic ductal adenocarcinoma (PDAC). To address this challenge, we develop ¹H NMR-based metabolomics-AI platforms employing customized multilayer support vector machine (SVM), AutoGluon, and Tabular Foundation Model (TabPFN) frameworks. These platforms integrate serum metabolomic profiles-including small-molecule metabolites and lipoproteins-with clinical/biochemical parameters (age, CA19-9) and Activin A, derived from 902 participants (424 high-risk controls and 478 PDAC cases). Our TabPFN-based algorithm, PanMETAI, outperform state-of-the-art models. In the Taiwanese training and validation cohort, the model achieved an impressive AUC of 0.99 (95% CI: 0.98-0.99). Its robustness is further confirmed in a Lithuanian external validation cohort (n = 322), which yields an AUC of 0.93 (0.90-0.95). Notably, it identifies key signature patterns that improve early-stage (I/II) PDAC diagnosis and perform well with small sample sizes (n = 50). TabPFN-PanMETAI offers a rapid, accurate, and non-invasive tool for early PDAC detection, with strong potential for clinical application.

Origami tessellations can transform flat sheets into curved yet inherently compliant surfaces that only approximate curvature and are unable to reconcile a fundamental trade-off among load-bearing capacity, curvature precision, and stiffness reprogrammability. We resolve this conflict by introducing a tileable crease pattern that folds into smooth, doubly curved shapes, enabling structural locking with minimal sagging under load. Solving an inverse problem, we compute fold patterns that match prescribed smooth surfaces with double, variable, and constant curvature. By strategically embedding tendons with varying pre-tension, we demonstrate reversible transformations from ultrasoft, formless states into rigid, load-bearing structures with in-situ tunable stiffness spanning orders of magnitude. This work unlocks a paradigm for folding doubly curved origami metamaterials, enabling flat-pack transport and scalable deployment of smooth, load-bearing shells.

Dielectric tunability induced by an external electric field in materials underpins radio frequency signal modulation devices such as phase shifters, which are critical components in wireless communication and sensing systems. However, the tunability and integrability of current devices have yet to be enhanced for emerging applications, particularly at millimeter-wave frequencies. Here, we demonstrate that topological polar structures formed in PbTiO₃/SrTiO₃ superlattices exhibit large tunable in-plane dielectric properties, as determined by their multiscale structural configurations and polarization switching behaviors. Under a moderate field of 30 kV cm^-1, the dipole wave structure maintains a tunability exceeding 15% at 70 GHz and above 8% over the measured range up to 110 GHz, contrasting with the weakly tunable flux closure structure. Based on in situ structural characterizations and molecular dynamics simulations, we delineate the polarization switching processes and elucidate the mechanisms underlying the observed tunable millimeter-wave dielectric responses. Our results provide new insights into the high-frequency dielectric properties of topological polar phases, potentially broadening the versatility of these materials in next-generation integrated electronic applications.

Genome-wide association studies (GWAS) have identified over 300 loci associated with the inflammatory bowel diseases (IBD), but putative causal genes for most loci are unknown. We conducted a disease-focused expression quantitative trait loci (eQTL) analysis using colon tissue from 252 IBD patients. We hypothesized IBD tissue could uncover IBD-associated regulatory variation undetectable in non-IBD cohorts. Here we show a total of 194 potential target genes for 108 IBD loci using eQTL from both IBD and non-IBD colon tissue. eQTL in IBD tissue were enriched for IBD GWAS colocalizations, provided evidence for genes such as ABO and TNFRSF14, and identified additional potential target genes compared to non-IBD tissue eQTL alone. Our results suggest disease state may alter the regulatory landscape and its characteristics, leading to increased effect sizes for some eQTL. These findings highlight the importance of diseased tissue eQTL studies for identifying potential consequences of IBD-associated variants.

Animals must constantly scan their environment for imminent threats to their safety. However, they must also integrate their past experiences across long timescales to assess the potential recurrence of new threats. Though visual inputs are critical for the detection of environmental danger, whether and how visual information shapes an animal's assessment of whether a new threat is likely to reappear in a given context is unknown. In this work, we developed a behavioral assessment of long-term threat avoidance behavior where animals will avoid a familiar location where they previously experienced a single threat exposure. This avoidance behavior is highly sensitive and lasts for multiple days. Intriguingly, we find that the melanopsin-expressing, intrinsically photosensitive retinal ganglion cells tune this behavior via a perihabenula-nucleus accumbens circuit distinct from canonical visual threat detection circuits in male mice. These findings define a long-term threat avoidance behavior that is shaped by a defined retinal cell type based on prior experience.