High-purity oxygen (O2) is vital for advanced applications in medicine, aerospace, and electronics, yet its sustainable production remains challenging. Pressure-swing adsorption (PSA) offers an energy-efficient alternative to cryogenic distillation, aligning with carbon-neutral objectives. However, achieving O2 purity above 99.99% is hampered by the removal of trace argon (Ar), whose kinetic diameter and polarizability are nearly identical to those of O2. Herein, we introduce a Ligand-Folding Modulation Strategy to tailor contractible ultra-micropores in Ni(II)-based metal-organic frameworks (MOFs), enabling precise Ar/O2 discrimination. Replacing rigid dicarboxylate linkers with a flexible, foldable analogue (trans-1,4-cyclohexanedicarboxylic acid, H2CDC) induces a zigzag pore contraction, narrowing the aperture from 7.5 Å to 5.0 Å. The resulting framework, Ni-TED-CDC (TED = 1,4-diazabicyclo[2.2.2]octane), exhibits an Ar uptake of 8.45 cm3/g at 298 K and 1 bar—49% higher than its large-pore analogue—and an Ar/O2 selectivity of 1.47, placing it at the forefront of O2 purification adsorbents. Breakthrough experiments confirm its capability to deliver ultra-high-purity O2 (>99.99%), highlighting its practical potential for PSA applications. Molecular simulations reveal that ligand foldability drives a confined, square-shaped pore geometry that optimally complements spherical Ar atoms, enhancing van der Waals interactions while excluding linear O2 molecules. This work establishes ligand-folding modulation as a versatile pore-engineering strategy for constructing responsive adsorption environments, providing a general design principle for inert-gas recognition and paving the way toward low-carbon, high-efficiency O2 purification technologies.
With the growing penetration of intermittent and fluctuating renewable energy sources, global and domestic energy systems are changing rapidly and traditional power grids are facing dramatic challenges. Under this scenario, the role of electricity should be reconsidered: it can not only directly meet the power demand of end users but also be converted into and stored as chemical energy. In this perspective, two routes of realizing this role transition of electricity are discussed, which are the electrified fuel conversion and the electrified fuel synthesis. Electricity can facilitate the traditional conversion of carbon-based fuels (e. g., the fuel reforming and gasification processes) by both electrified heating and electrochemical enhancement of reaction kinetics. For the fuel synthesis, the H2O and CO2 electrolysis, the direct and indirect electrochemical synthesis of both carbonaceous fuels and ammonia are highlighted for enabling diverse fuel options in the future. Finally, the importance of electricity in fuel separation and compression is also emphasized to achieve efficient interconnection between different energy networks.
Protein function is determined not only by its sequence, structure and partners, but also by the surrounding physicochemical environment comprising lipids, metabolites, ions and other macromolecules – hereby collectively referred to as the ‘periprotein environment’. Among these factors, the periprotein lipidome is emerging as an active functional matrix that shapes protein organization, conformational dynamics, assembly and activity. Here we summarize recent evidence demonstrating the functional crosstalk between the periprotein lipidome and the hosted proteins, focusing on hydrophobic proteins that are membrane-resident or are associated with lipid assemblies including vesicles, droplets and lipoproteins. We discuss examples ranging from defined lipid-binding pockets that allosterically regulate membrane-protein conformations to collective annular lipid environments that tune protein topology, multimerization and activity. These co-adaptations are driven by forces including hydrophobic compatibility, electrostatic attractions, hydrogen bonds, and van der Waals interactions, etc. Furthermore, we discuss current methods to profile the periprotein lipidomes, pinpoint the technical challenges, and posit alternative strategies to address this gap. As an under-explored link for understanding the principles underlying the lipid-central dogma crosstalk in life, we advocate for systematic characterizations of the periprotein lipidome for diverse target proteins and in various pathophysiological contexts.
Understanding the spatiotemporal variations of the South Asian summer monsoon (SASM) is fundamental for predicting regional water resource availability. On interannual and decadal timescales, precipitation variations in the northeastern Indian Peninsula exhibit an antiphase pattern compared to other SASM-influenced regions, such as the central-western Indian Peninsula, southern Tibetan Plateau and Yunnan-Guizhou Plateau. However, it is unclear whether such heterogeneity existed on the sub-orbital timescale. We synthesized a new Holocene hydroclimatic dataset comprising 88 records from across the SASM region. Contrary to the traditional view of a uniform early Holocene maximum in monsoon precipitation, our results are the first to reveal a pattern of spatial heterogeneity: the northeastern Indian Peninsula experienced a wetting trend, whereas most other SASM regions showed an overall drying trend during the Holocene. This spatial contrast suggests that hydroclimatic variations in the northeastern Indian Peninsula do not represent overall SASM intensity. Notably, stalagmite δ18O records show a consistent pattern of the most negative values in the early Holocene followed by a gradual positive shift, contradicting the spatial heterogeneity revealed by moisture-sensitive records. This new finding suggests that not all stalagmite δ18O records in the SASM region can be simply interpreted as local precipitation, but rather that they may reflect an integrated signal of precipitation, water vapor sources and transport pathways. PMIP4 simulations corroborate the dipole pattern from hydroclimatic records, capturing the precipitation contrast between the northeastern Indian Peninsula and other SASM-influenced regions. PMIP4 simulations reveal a possible mechanism where the enhanced mid-Holocene land-sea thermal contrast triggered a summer anticyclonic anomaly. This anticyclonic anomaly induced atmospheric subsidence and was accompanied by a reduction in water vapor over the central-eastern Indian Peninsula, thereby suppressing precipitation and driving spatial heterogeneity. However, as simulations provide an atmospheric context rather than precise reconstructions, discrepancies persist between models and records, necessitating future model refinements.
A critical determinant of T cell anti-tumor function lies in their spatial interactions with adjacent cells, a dimension that remains largely elusive to conventional analytical approaches. Spatial multi-omics technologies are advancing our understanding of cancer immunity by resolving cellular interactions within intact tumor tissue contexts. Integrative profiling of spatial genomics, transcriptomics, proteomics and metabolomics enables multidimensional characterization of these biological processes, which respectively links clonal architecture to immune selection, delineates functional state transitions, quantifies cellular crosstalk and effector function, and identifies biochemical barriers. We propose an organizational framework where intratumoral immunity is governed by regions, which control immune cell access and retention under microenvironmental constraints, and functional niches, where proximity-dependent multicellular interactions drive immune activation, help, killing, or suppression. Translationally, we outline a paradigm in which discovery-grade spatial multi-omics define minimal architectural metrics measurable in clinical formalin-fixed, paraffin-embedded samples under robust quality control, with large-scale validation establishing reproducible biomarkers for patient stratification and companion diagnostics, potentially supporting mechanism-anchored intervention design and microstructural-guided immunotherapy.
Accurate deep-sea temperature observations are essential for understanding global climate change, sea-level rise, and marine ecosystem dynamics, yet conventional sensors rely on rigid titanium housings that prevent conformal integration on curved or moving surfaces. Herein, a miniaturized, ultrathin, and pressure-insensitive flexible temperature sensor is presented for deep ocean exploration. A composite system architecture incorporating a flexible printed circuit, stretchable interconnects, and pressure-robust soft encapsulation, combined with a ratiometric readout strategy, enables high accuracy temperature measurement of ≤±0.04 °C across 0–35 °C under abyssal ocean environments. A distributed-island layout is proposed to reduce the interfacial shear stress by 16.9% under hydrostatic pressure of 45 MPa. In parallel, a covalent bonding strategy and SiO2–fluorosilane composite surface coating improve the interfacial adhesion strength between the sensor and encapsulation by 36.8% and increase the surface water contact angle to 133°, enhancing corrosion resistance and long-term reliability. Field trials to a depth of 4300 m in the western Pacific using the submersible Shenhai Yongshi, together with a 4 × 4 conformal array demonstration, validate the scalability of this flexible-circuit design for distributed deep-sea temperature sensing.
Cynomolgus monkey blastoids are promising models for investigating early primate embryogenesis, yet previous generation systems have suffered from low efficiency and the presence of undefined cell clusters, limiting their broader application due to high costs, time consumption, and ethical concerns. In this study, we established an optimized protocol for efficiently inducing cynomolgus monkey blastoids by systematically modifying key parameters based on established human blastoid protocols. The resulting cyBlastoids consistently exhibited an induction efficiency exceeding 70%, with morphology and cell lineage allocation closely resembling those of natural blastocysts. Immunofluorescence staining and transcriptomic analyses revealed that the ICM-like and TE-like cells within cyBlastoids shared high molecular similarity to their counterparts in natural embryos and previously reported cynomolgus monkey blastoids. Extended in vitro culture further demonstrated that cyBlastoids displayed typical morphological and lineage characteristics of post-implantation embryos. Our stable and efficient protocol provides a robust alternative for primate embryo research, facilitating reproducible studies on early embryonic development in non-human primates.
In additive manufacturing (AM), inhomogeneous precipitates from variable thermal cycles degrade mechanical properties and fatigue life. We propose a novel large-small melt pool coupling strategy to fabricate NiTi shape memory alloy (SMA) with an architectured microstructure containing homogeneous coherent nanoprecipitates. This approach actively designs the spatiotemporal distribution of thermal cycles, where large melt pools ensure material forming while secondary low-energy lasers create smaller melt pools to enable precise in-situ heat treatment. Consequently, Ti4Ni2Ox nanoprecipitates transform from an initial intergranular network into a homogeneous distribution. The resulting NiTi SMA exhibits significantly enhanced low-cycle superelastic fatigue life, outperforming all reported AMed NiTi. This superior performance stems from synergistic effects of the architectured microstructure: during loading transfer between two characteristic zones governed by strain compatibility, the homogeneous nanoprecipitation strengthening in the in-situ heat-treated zones enhances superelastic recovery and delays microcracking, while cooperative deformation in the remelted zones minimizes damage accumulation. This methodology transforms the remelting process into a precise microstructural design tool, enabling the fabrication of high-performance complex engineering components.
The global deployment of high-speed railway (HSR) systems has revealed significant limitations in current 5G-Railway (5G-R) technologies, particularly under high-mobility conditions. This survey presents a systematic examination of how sixth-generation (6G) wireless technologies can transform HSR communications. The study analyzes eight interconnected domains: (1) architectural evolution from 5G-R to 6G-R systems, (2) advanced channel modeling for diverse HSR environments, (3) antenna designs for high-speed scenarios, (4) robust waveform development, (5) multidimensional network architectures, (6) AI-driven optimization, (7) IoT-enabled monitoring systems, and (8) high-capacity optical solutions. Drawing from extensive experimental studies and commercial trials, we demonstrate that 6G-R systems fundamentally differ through three paradigm shifts: the integration of communication and sensing functions, native AI implementation for operational efficiency, and hybrid satellite-terrestrial connectivity. The paper further identifies critical research challenges in deploying these technologies for next-generation intelligent railways.
Atomic comagnetometers based on hybrid spin ensembles are widely used in precision tests of fundamental physics and ultra-sensitive inertial sensing, but their performance can be limited by transverse magnetic noise whose impact depends on both power and direction. This work develops a unified framework for directional transverse-noise analysis and inference by combining a stochastic spin-noise model with an uncertainty-aware temporal convolutional network. The coupled alkali–noble-gas spin dynamics are formulated as a four-dimensional linear stochastic differential equation driven by directional transverse magnetic noise, from which angle-resolved covariance and power spectral density expressions are derived. These results reveal operating-point-dependent anisotropic spin-noise statistics and show that the hybrid spin resonance (HSR) vicinity provides particularly strong directional discriminability. To infer the noise direction from two-channel spin-noise time series, an Angle-aware Noise Estimation with Uncertainty based on temporal convolutional network (ANEU-TCN) is developed using double-angle circular regression and Monte Carlo Dropout. Validation on an experimentally acquired HSR dataset yields a mean absolute error of 0.524∘ and a root mean square error of 0.670∘, while the predicted uncertainty intervals remain conservative on the validation set. These results support accurate, uncertainty-aware directional-noise estimation and noise-aware self-calibration of atomic comagnetometers in complex magnetic environments.
Fingerprint authentication, as a mainstream biometric method, has become an indispensable component in consumer electronics and public safety. However, optical and capacitive scans are susceptible to deception by fake textures and interference in environmental contaminations. The scanning domain of ultrasonic methods is constrained by under-screen pulse-echo devices. Here we report a biometric texture imaging and authentication method using an ultrasonic array that occupies no space under the screen, with fingerprint authentication as an example. The method characterizes fingerprints with sub-millimeter minutiae by elaborating sound-field variations within the array induced by fingertip press. Although the sound field propagates along the plane, it can be used to reconstruct the 3D information of fingerprint ridges. Anti-counterfeit and highly robustness enables excellent texture imaging and authentication despite water or dirt on the fingertips. Demonstrations of any position on the developed fingerprint acquisition device prove that our method promises to advance large-screen identity authentication.
Ultra-deepwater and shallow gas reservoirs, once regarded as hazards, are increasingly seen as valuable resources because of their vast reserves. Their stability depends critically on the integrity of the caprock, often a hydrate–sand composite that governs gas retention and prevents leakage, yet hydrate-bearing sediments (HBS) failure mechanisms remain poorly understood. Here we use a novel 4D in situ microstructural imaging method to provide the first direct visual evidence of a tensile strain-driven, chain-like hydrate damage process. This process follows a reproducible sequence of compressive stress concentration, crack propagation, free rotation, rotation limit, tensile stress redistribution, cementation network disintegration, and structural collapse. We show that tensile strain initiates this chain-like cementation failure, generating continuous weak layers that promote systematic sediment slippage and ultimately caprock failure. These insights establish a mechanistic basis for predicting caprock instability, guiding the design of sealing systems with improved damage tolerance, and enabling early warning frameworks in challenging subsea environments. Beyond gas hydrate systems, the findings have broader relevance for subsea infrastructure protection, continental slope stability, and the secure exploitation of unconventional offshore energy resources.
Point-of-care testing (POCT) faces challenges in robustly detecting trace analytes because of its limited ability to distinguish weak target signals from background noise, resulting in a risk of false-negative results. We present a deep learning (DL)-driven POCT assay based on commercial strips that allows for the robust detection of crudely extracted samples, and thus more reliable and quantitative detection compared with conventional intensity-based analysis. The assay leverages a target-responsive DNA hydrogel functionalized with recognition molecules and offers a general principle for the detection of diverse analytes. Rather than conventional intensity-based image analysis, the assay employs a DL tool as the signal readout to mitigate test variability and enhance subtle signals. Furthermore, a cloud-based smartphone application streamlines the user experience to provide intuitive and reliable detection results within seconds. We show that the DL-powered approach effectively distinguishes low-concentration positive signals and background, achieving over 90.0% accuracy, and demonstrating improved performance compared with traditional grayscale analysis. It significantly enhances sensitivity by 2- to 5-fold and expands the detection range by an order of magnitude for small-molecule mycotoxins. The platform enables the rapid and accurate quantification of mycotoxin in diverse contaminated food samples, with an average accuracy of 92.4%. This approach demonstrates strong agreement with standard laboratory methods in complex sample analysis and an improvement in POCT applicability compared with conventional readout methods.
Purely organic room-temperature phosphorescence (RTP) materials offer promising opportunities due to their metal-free composition, design flexibility, and ability to harness both singlet and triplet excitons. However, understanding their emission behaviors under diverse excitation modes remains limited. Here, we report a series of phenothiazine-based RTP luminogens with tunable sulfur oxidation states (–S–, –SO–, –SO₂–) and donor–acceptor architectures, enabling systematic control of electronic structures and molecular packing while preserving backbone consistency. These compounds provide a unified platform for multimodal luminescence, enabling stable phosphorescence emission under optical, electrical, and X-ray excitation. Notably, DOPTZ-SO₂ shows the highest RTP efficiency of 22.31% under photoluminescence excitation, while PTZ-SO₂ outperforms under electrical and X-ray excitation, showing over twice the external quantum efficiency in organic light-emitting diodes and a fivefold X-ray sensitivity enhancement. Comparative analyses across excitation conditions reveal distinct structure–property relationships. This work establishes a generalizable strategy combining oxidation-state modulation and excitation-mode adaptability for the development of efficient multimodal organic phosphors.
Mangrove ecosystems play a vital role in mitigating climate change by sequestering large amounts of blue carbon in both vegetation and sediments. Although recent studies have begun to address carbon accumulation associated with mangrove restoration, how the composition and stability of sediment carbon stocks change across successional stages remains poorly understood. Here, we investigated ecosystem carbon stocks, including plant biomass and sediment organic carbon to 1 m depth, as well as labile organic carbon fractions along a naturally expanding, single-species mangrove chronosequence in a rapidly growing estuarine zone of southern China. We found that total carbon stocks tended to increase with forest age, from 77.9 ± 11.1 Mg C ha–1 in young stands to 128.4 ± 14.7 Mg C ha–1 in old stands. Sediment carbon fractions in deeper sediment layers were positively associated with vegetation biomass. Labile organic carbon (LOC) concentrations also increased with stand age and showed strong vertical stratification within the upper 30 cm. Although LOC and total organic carbon (TOC) were closely correlated across depths, the LOC:TOC ratio declined with depth and varied among stand ages, indicating shifts in sediment carbon stability. These results suggest that mangrove development stage influences both the quantity and quality of sediment carbon. Our findings indicate that accounting for stand age and vertical carbon composition can improve assessments of carbon storage potential and vulnerability in mangrove ecosystems.
Ecosystem resilience is a key indicator of proximity to tipping points in terrestrial ecosystems, with declining resilience generally reflecting a heightened risk of abrupt transitions between ecosystem states. However, quantitative assessments of resilience change remain highly uncertain, owing to the inherently multidimensional nature of ecosystem resilience, as well as inconsistencies among assessment methodologies and ecosystem state variables used to infer resilience change. By synthesizing core ecosystem resilience concepts and evaluating multiple indicators and satellite-based vegetation state variables within established theoretical frameworks, we reveal substantial inconsistencies in inferred resilience trends: 59.6% and 42.8% of pixels show disagreement under the frameworks of critical slowing down and flickering, respectively, and 69.3% of show inconsistent trends across four satellite-based vegetation state variables (EVI, CSIF, LAI and kNDVI). Integrating dynamic global vegetation model simulations with observations further identifies climate change as the dominant driver of global ecosystem resilience changes, with temperature playing a key role. Together, these findings indicate that under ongoing global warming, neglecting conceptual differences in resilience and inconsistencies in representing critical transitions can lead to systematic misinterpretation of ecosystem stability and tipping-point risks, underscoring the urgent need for ecosystem-specific resilience assessment.
Chronic inflammation and epigenetic dysregulation contribute to hematopoietic stem cell (HSC) aging, yet the underlying mechanisms remain incompletely defined. Here, by integrating H3K4me3 ChIP-seq and RNA-seq datasets from young and aged human HSCs, we identify cholesterol 25-hydroxylase (CH25H) as an epigenetically upregulated gene in aged HSCs. CH25H is upregulated at both the transcript and protein levels in aged mouse and human HSCs, accompanied by increased production of its enzymatic product, 25-hydroxycholesterol (25-HC), a bioactive oxysterol implicated in inflammatory signaling. To interrogate the CH25H–25-HC axis, we perform structure-based virtual screening and identify Kukoamine A (KuA) as a candidate CH25H inhibitor, which we validate using a cellular thermal shift assay. Functionally, KuA reduces 25-HC production, attenuates inflammatory signaling, including NF-κB and IL-1β pathways, and partially restores a youthful transcriptional profile in aged HSCs. KuA also suppresses poly(I:C)-induced inflammatory activation and oxidative stress, and improves lymphoid differentiation potential and colony-forming capacity. Collectively, these findings identify CH25H as an epigenetically activated inflammatory regulator in aged HSCs and suggest that targeting the CH25H–25-HC axis may alleviate inflammatory stress and improve function of aged HSC.
The spread risk of non-indigenous species (NIS) is a major concern for coastal ecosystems, particularly via biofouling, as it is not mandatorily regulated in most regions. Trade policies can influence the NIS spread risk by changing shipping activities. The Belt and Road Initiative (BRI) trade facilitation policy aims to enhance trade activities, but its impact on biofouling-mediated NIS spread risk, primarily driven by reduced port residence times and changes in trade-driven shipping traffic, remains unclear. Here, we integrate a computable general equilibrium model with a higher-order NIS spread risk assessment model to evaluate how BRI trade facilitation influences biofouling-mediated NIS spread risk. Our findings show that trade facilitation does not necessarily increase NIS spread risk, as shorter port residence times generally exert a dominant mitigating effect. Consequently, overall NIS spread risk declines in most countries, with increases observed in only five cases. At the bilateral level, 85% of country pairs experience a net reduction in NIS spread risk. Importantly, changes in trade volumes and NIS spread risk do not align for most countries, with over 80% of countries decoupling risk changes from trade growth, leading to positive economic and environmental outcomes. These results highlight that trade facilitation does not necessarily exacerbate risks when accompanied by improvements in port operational efficiency. Policymakers should prioritize reducing port residence times as an effective risk mitigation strategy in the context of trade development. Countries experiencing increased risks should incorporate targeted measures, such as optimizing trade structures and strengthening vessel inspections, into their trade policies.
The selective oxidation of methane to methanol is a challenging yet highly promising process in catalysis, attracting significant attention for its potential to directly convert methane into high-value chemicals under mild conditions. This review provides a comprehensive overview of recent advancements in methane activation and selective oxidation, focusing on the regulatory mechanisms of reactive oxygen species (ROS) and their roles in catalytic reactions. By examining the generation pathways and reaction mechanisms of active species such as hydroxyl radicals (•OH), sulfate radicals (SO4-), chlorine radicals (Cl•), photogenerated holes (h+), and high-valent metals (e.g., FeIV=O, CuIII), we assess the performance and selectivity of various catalytic systems for methane oxidation. Furthermore, the advantages and limitations of different methane activation strategies are discussed. Despite significant progress in achieving high methanol selectivity (>90%) under mild conditions (<100°C), challenges like over-oxidation and product separation remain key obstacles. Future research should focus on catalyst design, reactor optimization, and improvements in catalytic efficiency to facilitate the industrial-scale application of efficient methane conversion.
