Atmospheric and Oceanic Sciences

Abstract Covalent organic frameworks with three-dimensional networks and interconnected porous structures show promising advantages for hydrogen peroxide photocatalysis. However, 3D COFs are typically constructed from 3D-oriented knots with less conjugation and insufficient light absorption, which significantly inhibits their performance. Herein, we present a universal defect engineering approach by systematically replacing T d knots with trigonal planar ligands and modifying linear linkers with electron-withdrawing/donating groups to achieve simultaneous enhancement of light absorption and precise electronic tuning of 3D donor-acceptor structures. Experimental results and theoretical analysis reveal that the optimized 3D COF with planar ligands induced defects and fluorine functional groups (COF-300-D-F), which achieve an H 2 O 2 production rate of 19.09 mmol g −1 h −1 and apparent quantum yield of 11.95% at 400 nm with benzyl alcohol as sacrificial agent. Moreover, the material maintains long-term stability during continuous operation exceeding 96 hours and exhibits high activity in photocatalytic benzylamine coupling reactions.

Spatial multi-omics enables the exploration of tissue microenvironments and heterogeneity from the perspective of different omics modalities across distinct spatial domains within tissues. To jointly analyze the spatial multi-omics data, computational methods are desired to integrate multiple omics with spatial information into a unified space. Here, we present SMART (Spatial Multi-omic Aggregation using gRaph neural networks and meTric learning), a computational framework for spatial multi-omic integration. SMART leverages a modality-independent modular and stacking framework with spatial coordinates and adjusts the aggregation using triplet relationships. SMART excels at accurately identifying spatial regions of anatomical structures, compatible with spatial datasets of any type and number of omics layers, while demonstrating exceptional computational efficiency and scalability on large datasets. Moreover, a variant of SMART, SMART-MS, expands its capabilities to integrate spatial multi-omics data across multiple tissue sections. In summary, SMART provides a versatile, efficient, and scalable solution for integrating spatial multi-omics data. Du and colleagues present SMART, a scalable and computationally efficient framework for integrating spatial multi-omics data to identify tissue domains. The approach shows applicability to large and multi-section spatial profiling datasets.

Abstract Photosynthetic electron transfer relies on small soluble carriers that shuttle electrons between the cytochrome b ₆ f complex and Photosystem I (PSI). While copper-containing plastocyanin (Pc) serves this role in plants, the heme protein cytochrome c ₆ (Cyt c ₆) is also employed in algae and cyanobacteria. Here, we present a cryo–electron microscopy structure of a Cyt c ₆:PSI complex from Chlamydomonas reinhardtii . We observe that the heme group of Cyt c ₆ is positioned ~11 Å away from P700, stabilized by extensive contacts involving a N-terminal helix-loop-helix motif of PSAF, characteristic of eukaryotic PSI. Notably, the algal Cyt c ₆ also retains an arginine residue (R66) which is crucial for cyanobacterial donor:PSI reactions. Our structure reveals the previously uncharacterized interactions involving this residue; it can form a putative electrostatic contact with PsaB-D623 while also contributing to a tri-planar π(cation)-π interactions with adjacent residues. Our findings provide a structural framework for understanding the mechanism and evolution of donor:PSI interactions.

C2H4 and CH4 are essential for industrial applications. However, contamination with other natural gases is a challenge to their utilization. Although several sorbents have been investigated, their performance remains limited. This study introduces graphene-inspired, PPN-20, a porous polymer network (PPN) capable of separating C2H6/C2H4 and purifying CH4 from a C3H8/C2H6/CH4 mixture in a single step. The ultra-microporosity of PPN-20 enables preferential C-H···π interactions with C2H6 and C3H8. As a result, PPN-20 exhibits a C2H6 and C3H8 uptake of 3.93 mmol/g and 5.98 mmol/g, respectively, at 298 K and 1 bar, representing the highest reported for any PPN. It achieves ideal adsorbed solution theory (IAST) selectivities of 2.2 for C2H6/C2H4, 368.2 for C2H6/CH4, 40.14 for C3H8/C2H6, and 294,336 for C3H8/CH4. This selectivity, to the best of our knowledge, is the highest reported for any PPN in the case of C2H6/C2H4 separation and for any sorbent in the cases of C2H6/CH4, C3H8/C2H6, and C3H8/CH4 separation. Robustness tests, including breakthrough experiments, IAST calculations, etc., demonstrate the reliability of PPN-20. Its exceptional performance is attributed to precisely engineered pore sizes that enhance the trapping of guest molecules. These results will pave the way for the design of PPNs for short-chain hydrocarbon purification. A graphene-inspired porous polymer network acts as a molecular sieve, efficiently separating ethane from ethylene and purifying methane. Its finely tuned pores deliver record selectivity, offering a new path toward cleaner and energy-efficient natural gas processing.

Replacing the oxygen evolution reaction with more thermodynamically favourable organic oxidation reactions (OORs) can enable energy-efficient hydrogen evolution and hydrogenation. However, cathodic reduction rates are limited by sluggish OORs. Herein, we report a decoupled electrolysis strategy using a solid redox reservoir (RR) to realize an optimized hydrogen evolution reaction (HER) paired with valuable chemical synthesis. The decoupled system with a rechargeable capability features a HER coupled with RR oxidation for electricity storage, which is followed by the conversion of OORs (e.g., ethylene glycol, glycerol) into value-added chemicals coupled with the reduction of the oxidized RR to generate electricity. The fast kinetics of RR oxidation and membrane-free cell operation optimize the HER rate. The value-added chemicals and electricity are cocreated during the discharge process, offering more economic benefits. This decoupling design is universally applicable to other OORs-paired reduction systems (e.g., acetylene-to-ethylene semihydrogenation) to synthesize various chemicals for electricity storage and generation, paving a sustainable avenue for H2 production/hydrogenation and chemicals manufacturing. Using thermodynamically favourable organic oxidations instead of oxygen evolution enables energy-efficient cathodic reactions, but rates are limited by slow anodic kinetics. Here, the authors report decoupled charge‒discharge electrolysis using a solid redox reservoir to overcome this limitation.

Abstract This work presents a holistic integration of environmental sustainability and enhanced sensing performance throughout the full lifecycle of magnetoresistive sensors. Utilizing industry-scale screen-printing techniques combined with eco-friendly inks (formulated from engineered Fe/Fe 3 O 4 core-shell magnetic microparticles, bioderived polymeric binders, and water solvent), the fabrication process avoids harsh treatments and hazardous chemicals. The resulting sensors, constructed entirely from naturally sourced materials, inherently exhibit biocompatibility, biodegradability, and environmentally benign recyclability. These properties collectively demonstrate key attributes for a sustainable life cycle. Through rational engineering of the Fe/Fe 3 O 4 core-shell structure particles, two synergistic mechanisms are activated within the composite: spin-dependent hopping across Fe 3 O 4 shell grain boundaries and in situ magnetic flux concentration induced by Fe cores, thereby yielding an order-of-magnitude enhancement in low-field sensitivity relative to sputtered Fe film and printed Fe 3 O 4 particle-based counterparts, resulting in a higher magnetoresistance ratio at 10 mT relative to all printed magnetoresistive sensors reported previously. The convergence of eco-sustainability and high performance enables previously unattainable disposable magnetoelectronics, unlocking new opportunities for environmentally responsible and user-safe transient electronics and Internet of Things (IoT) applications.

Abstract Microtubule severing is essential for proper eukaryotic cell elongation and division. Here we show that the microtubule severing protein, KATANIN p60, is encoded by two genes in Zea mays L. (maize) called Discordia3a (Dcd3a) and Dcd3b . A semi-dominant mutant with short stature, poor fertility, and a clumped tassel was identified in Dcd3b called Clumped tassel1 ( Clt1 ). Genetic enhancers that further reduced stature and fertility were identified in inbred lines and mapped to the Dcd3a locus, identifying several dcd3a alleles. Loss-of-function p60 allele combinations reduce microtubule severing, fertility, and cell elongation. Cell elongation defects, in turn, contribute to G1 delay. KATANIN p60 is important for preprophase band (PPB) formation and positioning, and nuclear positioning in symmetric cell divisions. Misoriented PPBs lead to offset nuclei and rare misoriented symmetric divisions in mutants. A combination of these defects contributes to generating small mutant plants with fewer cells.

Amorphous materials, especially metallic glasses, are known for their exceptional mechanical properties, such as high yield strength and large yield strain. Understanding the microscopic mechanisms behind their failure, particularly the yielding transition, remains an active area of research. Previous studies have shown that yielding behaviour depends on the initial age of the sample. Through extensive computer simulations, we demonstrate that this age dependence varies across different materials and is influenced by the specific characteristics of the initial glass former, particularly its fragility. Both strong and fragile glass formers exhibit similar yielding behaviour in poorly annealed conditions with a critical yield strain, γc that does not depend on the initial conditions. However, below a critical degree of annealing, the yield point increases significantly with further annealing for fragile glasses, while it remains relatively constant for strong glasses. The results are found to be universal across a wide variety of model glassy systems with varying fragility, including metallic glasses, molecular glasses, model granular glasses, and network-forming glasses like Silica. We rationalise these findings by introducing a modified mean-field elastoplastic model that explicitly incorporates the crucial role of changing energy barrier with increasing annealing in the yielding process. This simple model reproduces all the simulation results and provides critical insights into how energy barriers influence the physics of the yielding transition including the critical yield strain under oscillatory shear deformation. Simulations show how glass fragility controls yielding under oscillatory shear. Strong and fragile glasses behave similarly when poorly annealed, but with annealing the yield point rises in fragile glasses only.

Non-ionic electronic skins offer intrinsic environmental stability, avoiding the leakage, volatility, and temperature sensitivity that limit ionic sensing systems. Yet, capacitive sensors based on electronic polarization typically exhibit low sensitivity because their dielectric modulation is confined to a single mode. Here, we introduce a dielectric-gradient, fully fiber-integrated non-ionic capacitive architecture that employs an impedance-driven enhancement mechanism. Controlled fiber deformation establishes a dual-variable dielectric network in which pressure-induced reduction of interfacial resistance and impedance releases suppressed polarization, yielding amplified capacitance far beyond that of conventional non-ionic sensors. The resulting device achieves ultrahigh sensitivity of 169.8 kPa−1 over a wide range of 20 Pa–8 MPa and maintains stable operation from −80 °C to 200 °C with less than 6% deviation. When integrated into a tactile-sensing glove and combined with machine learning, it attains 99.25% accuracy in recognizing multiple operational tools under both cryogenic and high-temperature conditions. These findings establish impedance engineering as a universal strategy for constructing high-gain, thermally robust, and reliable non-ionic electronic skins, enabling precision tactile sensing in environments previously inaccessible to flexible electronics. Capacitive sensors based on electronic polarization typically exhibit low sensitivity as their dielectric modulation is confined to a single mode. Here, the authors develop a dielectric-gradient all-fiber non-ionic electronic skin that converts interfacial impedance into signal amplification for tactile sensing.

Tandem duplications (TDs) are a common form of genomic rearrangements with both adaptive and pathogenic consequences. While prevalent in genomically unstable cancer genomes, TDs are rarely detected in normal tissues, suggesting the existence of robust protective mechanisms. Here, we identify the histone chaperone TONSL/TONSOKU (tnsl-1 in C. elegans) as a critical suppressor of TD formation. Loss of tnsl-1 results in the accumulation of TDs in two distinct size classes (~25 kb and ~300 kb), arising from different developmental contexts: small TDs emerge in rapidly dividing embryonic cells, whereas large TDs form in slower-dividing germline progenitors. Both classes depend on polymerase theta-mediated end joining (TMEJ), implicating DNA double-strand breaks in their genesis. Inhibition of break-induced replication (BIR) via Pif1 helicase loss reduces TD size, revealing a role for BIR in TD expansion. Remarkably, TONSL-deficient Arabidopsis thaliana exhibit an identical TD signature, highlighting the evolutionary conservation of this genome surveillance mechanism. These findings position TONSL as a cross-kingdom guardian of genome integrity through suppression of TD formation. Tandem duplications are a common class of structural variation in evolving genomes but are rare in healthy cells, and the DNA repair mechanisms that suppress their formation remain poorly defined. Here, the authors identify TONSL as a conserved factor that suppresses tandem duplications across species.

Continuous glucose monitors (CGMs) provide detailed glucose profiles, but their relevance to health outcomes in individuals without diabetes remains unclear. Here we assess time in range (TIR3.9–5.6 and TITR3.9-7.8) and glycaemic variability in individuals (N = 3,634; age 46 ± 12 y; 83% female; BMI 27 ± 6 kg/m²) from PREDICT 1 (NCT03479866), PREDICT 2 (NCT03983733), and PREDICT 3 (NCT04735835) without diabetes or prediabetes, and explore associations with demographic, diet, lifestyle, cardiometabolic markers, and predicted cardiovascular risk. Outcomes are non-pre-defined exploratory analyses. Higher TIR3.9–5.6 is associated with lower HbA1c, OGTT glucose, carbohydrate intake, and higher protein intake. Sleep duration is inversely correlated with mean glucose. TIR3.9–5.6 provided moderate discrimination for predicted ASCVD 10-year risk (AUC = 0.75). While CGM metrics show potential to capture some components of glycaemic physiology, longer-term health outcomes are required to demonstrate whether CGM monitoring has utility for health management in euglycaemic individuals. Here, the authors show that continuous glucose metrics capture some components of glycaemic physiology in euglycaemic individuals. An evaluation of health outcomes longer-term would be required to assess whether continuous glucose monitoring has utility for health management in this population.

Spinal and bulbar muscular atrophy (SBMA) is an adult-onset neurodegenerative disorder caused by expansion of a polyglutamine tract in the androgen receptor (AR). Here, we show that polyglutamine-expanded AR accumulates in the nucleus of motor neurons and induces aberrant upregulation of glutamatergic synaptic genes through dysfunction of the master transcriptional repressor REST during early postnatal development in a mouse model of SBMA (AR-97Q mice). Reducing mutant AR or restoring REST function using antisense oligonucleotides during the neonatal period attenuated the upregulation of glutamatergic synaptic genes and ameliorated the disease phenotype and histopathology in AR-97Q mice. Furthermore, we observed increased calcium activity in induced pluripotent stem cell-derived motor neurons from SBMA patients compared to those from healthy controls, reflecting neuronal hyperexcitability. Late-onset neurodegeneration in SBMA is attributable to early synaptic defects and the resulting hyperexcitability of motor neurons, which may represent therapeutic targets. Early synaptic dysregulation underlies late-onset neurodegeneration in SBMA. Aberrant upregulation of REST target glutamatergic synaptic genes by polyglutamine-expanded AR induces motor neuron hyperexcitability, highlighting a therapeutic window.

Gamma-glutamyl carboxylase (GGCX) is the sole enzyme responsible for gamma carboxylation of glutamate in a vitamin K-dependent manner. This process is crucial for blood coagulation, bone metabolism, vascular calcification, and other biological processes because gamma carboxylation is essential for the maturation of clotting factors, anticoagulation factors, and some coagulation-unrelated factors. Despite these essential roles, the catalytic mechanism of GGCX remains incompletely understood. Here, we present the cryo-EM structures of human GGCX complexed with five typical substrates, including two clotting factors and three coagulation-unrelated factors. These structures not only elucidate the recognition mechanism for the propeptide but also reveal three distinct modes for substrate loading. Among them, the GGCX-MGP complex structure reveals a specific mode to load a substrate with an active glutamate residue at the N-terminus of the propeptide. Moreover, these structural observations are supported by our in vitro carboxylation and epoxidation assays.

Irrigated agriculture enhances crop yields and climate resilience but also contributes to CO₂ emissions through energy use. Here, we apply energy system modeling to evaluate cost-emission trade-offs in electrified irrigation across the United States, integrating hourly energy production and historical water demand. We find that current practices are highly inefficient, leading to 23% (0.89 billion US dollar) higher costs and 39% (3.8 million metric tons of CO2) more CO2 emissions compared to the cost-optimal scenario, primarily due to reliance on diesel water pumps and limited solar photovoltaic adoption. Under cost-optimal conditions, 6.6 gigawatt of solar photovoltaic is deployed, and electric water pump installation capacity increase by 14% (11.3 106 m3h-1) relative to current levels. Emission reductions of 85% are achievable at marginal additional cost (+0.7%), whereas reaching net-zero roughly doubles system costs relative to business-as-usual. Renewable-powered electrified irrigation can thus deliver substantial, low-cost emission reductions but requires operational adaptation to solar-based systems. Irrigated agriculture is vital for food security but relies on energy- and carbon-intensive pumping. This study shows that switching to renewable-powered irrigation is not only environmentally compelling but also an economic opportunity.

The growing antibiotic resistance and high mortality rates associated with methicillin-resistant Staphylococcus aureus (MRSA) pose a global health threat, highlighting the urgent need for novel therapeutic strategies. Phenol-soluble modulin α3 (PSMα3) is a critical virulence factor in MRSA pathogenesis and immune evasion. However, its underlying mechanisms remain unclear. Here, we demonstrate that PSMα3 promotes both M1 macrophage polarization and necroptosis. These processes are mechanistically linked through an interaction between the interferon-stimulated gene factor 3 (ISGF3) and necrosome complexes, with formyl peptide receptor 2 (FPR2) serving as the key receptor. Based on this mechanism, we show that targeting signal transducer and activator of transcription 1 (STAT1), a key component of the ISGF3 complex, with the clinically approved drug fludarabine effectively mitigates MRSA infection in murine sepsis and pneumonia models. These findings reveal the mechanisms of MRSA pathogenesis and highlight the potential of anti-virulence strategies as innovative therapeutic approaches against MRSA infections. Methicillin-resistant Staphylococcus aureus (MRSA) is a key pathogenic bacterium and poses a significant therapeutic challenge due to its developing resistance to therapeutics. Here the authors establish a role for the MRSA virulence factor phenol-soluble modulin α3 in promoting macrophage M1 polarization and necroptosis via the host receptor FPR2 and the ISGF3 complex, and suggest the use of fludarabine to target the STAT1 component of this axis in models of MRSA infection.

Abstract Designing electrolyte materials for high-energy lithium metal batteries requires navigating vast, discrete chemical spaces, where intricate interphasial and electrolyte chemistries render component interactions largely unclear. Traditional trial-and-error methods struggle with discontinuous electrolyte-performance relationships and inefficient adaptation to new molecular candidates, hindering discovery. Here, we propose a two-stage deep active learning framework with knowledge transfer for rapid electrolyte design. In stage one, deep active learning with deep kernel learning selects informative experiments and models discontinuous relationships between formulation and performance, improving sample efficiency and reducing experimental cost. In stage two, target statistic coding quantifies what was learned and transfers it to new design settings, such as expanded formulation spaces and newly introduced components, using only a small number of additional measurements. Using this framework, we found electrolytes that increase the average lifetime of lithium metal symmetric cells by threefold after three learning iterations, and we rapidly identified improved formulations for Li 0 | |LiNi 0.8 Co 0.1 Mn 0.1 O 2 full cells in expanded chemical spaces. This work provides an experiment-driven, sample-efficient route to explore complex electrolyte formulation spaces and quantify inter-component correlations, as well as a realistic, high-cost, small-data benchmark for probabilistic surrogate modeling and sequential decision-making in discrete chemical spaces.