Browse Articles

Serpentine’s wet breakdown path and enhanced water flux in cold subduction zones

Hydroxyl‑Mediated SO2 Promotion Enables Efficient NOx Reduction by CO over IrIn/Beta under Oxygen‑Rich Conditions

Microwave-field quantum metrology with inherent robustness against detection losses enabled by Rydberg interactions

Abstract Quantum sensing and metrology present one of the most promising near-term applications in the field of quantum technologies, with quantum sensors enabling unprecedented precision in measurements of electric, magnetic, or gravitational fields and displacements. Experimental loss at the detection stage remains one of the key obstacles to achieving a truly quantum advantage in many practical scenarios. Here, we combine the capabilities of Rydberg atoms to both sense external fields and be used for quantum information processing, thereby largely overcoming the issue of detection losses. While utilising the large dipole moments of Rydberg atoms in an ensemble to achieve single-shot precision of (217  ± 8) μ V cm −1 for a very short 160-ns-long microwave pulse, we employ inter-atomic dipolar interactions to take advantage of an error-prevention protocol that protects information against conventional losses at the detection stage. Counterintuitively, the protocol’s idea is based on introducing an additional non-linear, lossy quantum channel, which results in a threefold enhancement of Fisher information. The presented results pave the way for broader adoption of quantum-information-inspired enhancements enabled by intrinsic interactions present in a sensor system, and more broadly in practical quantum metrology and communication, without the need for a general-purpose quantum computer.

Field-to-forest fungal spillover is a biotic edge effect of coffee in Costa Rica

Abstract Agricultural expansion creates mosaic landscapes where managed land borders natural ecosystems, facilitating the movement of organisms between habitats. Ecological spillover from natural systems to crops has been previously examined, but the extent to which populations amplified by agriculture move into adjacent forests remains largely unexplored. We investigated whether Costa Rican coffee fields act as reservoirs for foliar fungi that, because of high crop density and phylogenetic signal in plant-fungal associations, may particularly affect close relatives of coffee (Rubiaceae) in the forest understory. Field surveys, airborne propagule sampling, and metabarcoding along transects at the coffee-forest border revealed declining leaf spot incidence with distance into the forest for Rubiaceae but not non-Rubiaceae hosts, in parallel with declines in the dominant fungal order on coffee leaves, Pleosporales, and 19 coffee-associated taxa. Ninety-three coffee-associated taxa, including many potential plant pathogens, showed higher modeled abundance on forest Rubiaceae than forest non-Rubiaceae hosts. Our findings suggest that crops can act as reservoirs for fungi colonizing adjacent forest plants, disproportionately affecting hosts more closely related to the crop. These plants may face increased disease pressure, leading to changes in forest understory composition near the crop-forest border. Phylogenetically structured spillover represents an underappreciated edge effect in fragmented landscapes.

Finite-temperature toroidal moment amenable to direct observation in an Fe10Dy10 molecular ring

Abstract Single-molecule toroics host closed magnetic vortices carrying toroidal moments τ , whose electric-dipole symmetry enables magnetoelectric spin control. Yet opposite toroidal chiralities are degenerate in conventional magnetic fields, making direct detection of τ challenging. Current approaches probe toroidal dynamics only indirectly through weak residual magnetism, while finite-temperature toroidal polarisation and realistic preparation/readout conditions remain unestablished. Here we show that the Fe 10 Dy 10 molecule hosts a 62-billion-dimensional low-energy manifold pervaded by toroidal character, rendered tractable by an ab initio-informed transfer-matrix framework that reproduces experimental data. The model reveals a large toroidal response robust to thermal fluctuations, quantified by a finite-temperature toroidal susceptibility ξ . We then propose a preparation-and-readout protocol in which a train of temporally asymmetric near-infrared pulses accumulates toroidal polarisation, converted through magnetoelectric response into a measurable electric-field-induced magnetic signal. These results establish Fe 10 Dy 10 as a molecular system where τ can be prepared, accumulated and read out under realistic conditions.

Two telomere-to-telomere Nelumbo genome assemblies reveal domestication history and empower precision breeding

Unit-level assessment of mitigation pathways for mercury emissions from the global coal power fleet

DirectContacts2: a wiring diagram of human physical protein interactions

Abstract Cellular function is driven by the activity of proteins in stable complexes. Protein complex assembly depends on the direct physical association of component proteins. Advances in macromolecular structure prediction with tools like AlphaFold and RoseTTAFold have greatly improved our ability to model these interactions in silico, but an all-by-all analysis of the human proteome’s ~200 M possible pairs remains computationally intractable. A comprehensive cellular map of direct protein interactions will therefore be an invaluable resource to direct screening efforts. Here, we present DirectContacts2 , a machine learning model that distinguishes direct from indirect protein interactions using features derived from over 25,000 mass spectrometry experiments. Applied to ~25 million human protein pairs, our model outperforms previous resources in identifying direct physical interactions and enriches for accurate structural models including ~2500 AlphaFold3 models. Our framework enables structural modeling of disease-relevant complexes (e.g. orofacial digital syndrome (OFDS) complex) offering insights into the molecular consequences of pathogenic mutations (OFD1) and broadly, establishes a highly accurate protein wiring diagram of the cell.

Evolving dynamics of H5Nx avian influenza in China revealed by long-term wild bird surveillance

Thermogenic methane beneath the North Greenland Ice Sheet revealed by isotopic and geological evidence

Abstract Glacial meltwater has been increasingly recognised as a potential source of atmospheric methane, yet its origin and variability in the High Arctic remain poorly constrained. In this study, we present measurements of methane concentration and carbon‑isotope composition in meltwater draining the northern Greenland Ice Sheet. Here we show that methane concentrations (12-20 nM) are significantly lower than those reported from other Greenland catchments, despite clear evidence of subglacial input. Isotopic signatures and regional geological context indicate that this methane is predominantly thermogenic, reflecting a geological source that is largely independent of subglacial microbial activity. These findings advance current understanding of methane sources beneath the Greenland Ice Sheet, revealing a thermogenic contribution alongside microbial methane in Arctic methane cycling. In this work we highlight the need to account for geological methane reservoirs when assessing present and future cryosphere–carbon feedbacks.

Carbohydrate-active enzymes of soil prophages enhance global carbon cycling potential

Place and behavioral modulation of hippocampal neurons during immobility

Abstract Behavioral state fluctuations profoundly impact episodic memory processing. To explore the underlying mechanisms, we recorded CA1 place cells in head-fixed male mice and focused on awake immobility to capture spontaneous behavioral state fluctuations by facial motion, pupillometry, and local field potential (LFP) analysis. We found that during awake immobility, the duration of spontaneous whisker-pad motion events correlated with ongoing levels of arousal and modulated both the frequency and the power of theta oscillations. CA1 place cells continued to encode location during immobility, with the spatial code being primarily driven by a subset of behaviorally-modulated place cells which increased their firing upon behavioral state transitions. Single-cell stimulation during immobility was sufficient for the induction of place fields, indicating that plasticity mechanisms can be engaged even in the absence of locomotion. Altogether, these data indicate that behavioral state fluctuations might contribute to episodic memory processing by modulating theta oscillatory dynamics and hippocampal gain via the engagement of a discrete place-cell ensemble.

Enzymatic activity-independent NANS stabilizes LATS2 to drive growth and therapeutic resistance in HR+/HER2- breast cancer

Patient-partnered multiomics reveals the molecular architecture of angiosarcoma

Sodium-glucose cotransporter 2 inhibitor tofogliflozin ameliorates insulin signaling by improving mitochondrial function in the podocytes in DKD

Genomic structural equation modeling reveals a common genetic dimension contributing to variation in growth‑related traits across multiple developmental stages

The link between diabetes and male infertility: mechanisms and implications

Abstract Diabetes mellitus (DM) is a growing global health crisis affecting male reproductive function, yet the enhanced combined effects of diabetes with pre-existing fertility abnormalities remain poorly understood. This study aims to investigate the individual and combined effects of diabetes and abnormal semen parameters on male reproductive function and the underlying apoptotic mechanisms. Thirty-nine men were enrolled and stratified into two phases: a validation cohort (nondiabetic vs. diabetic; fertile vs. abnormally infertile) and a four-group mechanistic study (normal nondiabetic ( n  = 10), abnormal nondiabetic ( n  = 11), normal diabetic ( n  = 10), and abnormal diabetic ( n  = 8)). We assessed HbA1c, FSH, LH, testosterone, semen parameters, sperm apoptosis (Annexin V/PI flow cytometry), DNA fragmentation (diphenylamine), and expression of apoptotic markers (caspase-3, cytochrome c, Bax, and Bcl-2) at gene and protein levels. Diabetic patients had significantly higher HbA1c (9.6 ± 2.31% vs. 5.49 ± 0.42%, p  < 0.001), elevated FSH and LH, and reduced testosterone. Abnormal infertile patients showed impaired motility and morphology. The abnormal diabetic group had the most severe dysfunction: lowest rapid progressive motility (11.3 ± 3.10%, p  < 0.001 vs. control) and highest early apoptosis (58.9 ± 8.79%, p  < 0.0001). Protein analysis showed a pro-apoptotic shift with an elevated Bax/Bcl-2 ratio (3.64), increased cytochrome-c, and caspase-3 activation exclusively in this group ( p  < 0.0001). Diabetes and abnormal semen parameters exert enhanced combined detrimental effects on male fertility via enhanced activation of the intrinsic mitochondrial apoptotic pathway. Diabetic men with pre-existing fertility abnormalities exhibit the most severe phenotype and require prioritized clinical intervention.

Enhanced HGF with increased receptor affinity and nitration-dysfunction resistance through interaction with lipoic acid trisulfide

Disulfidptosis-related genes stratify molecular subtypes and highlight MYH9 as a prognostic biomarker and candidate therapeutic target in pancreatic ductal adenocarcinoma

Topological indices and QSPR analysis of drug molecules from different therapeutic classes

Abstract Typically, Quantitative Structure–Property Relationship (QSPR) models are created for compounds related to a particular therapeutic use and might be restricted in scope. To explore the wider use of neighbourhood connectivity descriptors, ten drug molecules, encompassing a wide range of chemical and therapeutic classes, were chosen: anti-inflammatory, anti-bacterial, anti-viral, anti-hypertensive, anesthetic, anti-depressant and neuromuscular agents. The molecular structures were represented as graphs, with atoms represented by the vertices and chemical bonds represented by the edges, and various neighbourhood degree-based topological indices were calculated. Linear, quadratic and cubic QSPR regression models were used to correlate these descriptors with nine experimentally determined physicochemical properties such as boiling point, density, enthalpy of vaporization, flash point, refractive index, molar refractivity, polarizability, surface tension and molar volume. The coefficient of determination ( $$\textrm{R}^{\circ }$$ ) was used to evaluate the model performance. The results show that neighbourhood-based descriptors are able to capture molecular structural information and make reliable prediction of properties on structurally diverse drug molecules. The results provide good justification to use these descriptors in general for chemical graph theory and in QSPR studies without any particular disease or therapeutic indication.