The 100 most-cited articles in Nature Communications, 2022

This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations for molecular dynamics simulations. While most contemporary symmetry-aware models use invariant convolutions and only act on scalars, NequIP employs E(3)-equivariant convolutions for interactions of geometric tensors, resulting in a more information-rich and faithful representation of atomic environments. The method achieves state-of-the-art accuracy on a challenging and diverse set of molecules and materials while exhibiting remarkable data efficiency. NequIP outperforms existing models with up to three orders of magnitude fewer training data, challenging the widely held belief that deep neural networks require massive training sets. The high data efficiency of the method allows for the construction of accurate potentials using high-order quantum chemical level of theory as reference and enables high-fidelity molecular dynamics simulations over long time scales.

International challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI…

Multiple sequence alignments are widely used to infer evolutionary relationships, enabling inferences of structure, function, and phylogeny. Standard practice is to construct one alignment by some preferred method and use it in further analysis; however, undetected alignment bias can be problematic. I describe Muscle5, a novel algorithm which constructs an ensemble of high-accuracy alignment with diverse biases by perturbing a hidden Markov model and permuting its guide tree. Confidence in an inference is assessed as the fraction of the ensemble which supports it. Applied to phylogenetic tree estimation, I show that ensembles can confidently resolve topologies with low bootstrap according to standard methods, and conversely that some topologies with high bootstraps are incorrect. Applied to the phylogeny of RNA viruses, ensemble analysis shows that recently adopted taxonomic phyla are probably polyphyletic. Ensemble analysis can improve confidence assessment in any inference from an alignment.

Abstract Highly accurate protein structure predictions by deep neural networks such as AlphaFold2 and RoseTTAFold have tremendous impact on structural biology and beyond. Here, we show that, although these deep learning approaches have originally been developed for the in silico folding of protein monomers, AlphaFold2 also enables quick and accurate modeling of peptide–protein interactions. Our simple implementation of AlphaFold2 generates peptide–protein complex models without requiring multiple sequence alignment information for the peptide partner, and can handle binding-induced conformational changes of the receptor. We explore what AlphaFold2 has memorized and learned, and describe specific examples that highlight differences compared to state-of-the-art peptide docking protocol PIPER-FlexPepDock. These results show that AlphaFold2 holds great promise for providing structural insight into a wide range of peptide–protein complexes, serving as a starting point for the detailed characterization and manipulation of these interactions.

Microbial composition and functions in the rhizosphere-an important microbial hotspot-are among the most fascinating yet elusive topics in microbial ecology. We used 557 pairs of published 16S rDNA amplicon sequences from the bulk soils and rhizosphere in different ecosystems around the world to generalize bacterial characteristics with respect to community diversity, composition, and functions. The rhizosphere selects microorganisms from bulk soil to function as a seed bank, reducing microbial diversity. The rhizosphere is enriched in Bacteroidetes, Proteobacteria, and other copiotrophs. Highly modular but unstable bacterial networks in the rhizosphere (common for r-strategists) reflect the interactions and adaptations of microorganisms to dynamic conditions. Dormancy strategies in the rhizosphere are dominated by toxin-antitoxin systems, while sporulation is common in bulk soils. Functional predictions showed that genes involved in organic compound conversion, nitrogen fixation, and denitrification were strongly enriched in the rhizosphere (11-182%), while genes involved in…

Abstract Predicting the structure of interacting protein chains is fundamental for understanding the function of proteins. Here, we examine the use of AlphaFold2 (AF2) for predicting the structure of heterodimeric protein complexes. We find that using the default AF2 protocol, 44% of the models in a test set can be predicted accurately. However, by optimising the multiple sequence alignment, we can increase the accuracy to 59%. In comparison, the alternative fold-and-dock method RoseTTAFold is only successful in 10% of the cases on this set, template-based docking 35% and traditional docking methods 22%. We can distinguish acceptable (DockQ>0.23) from incorrect models with an AUC of 0.85 on the test set by analysing the predicted interfaces. The success is higher for bacterial protein pairs, pairs with large interaction areas consisting of helices or sheets, and many homologous sequences. Further, we test the possibility to distinguish interacting from non-interacting proteins and find that by analysing the predicted interfaces, we can separate truly interacting from non-interacting…

Although cellular senescence drives multiple age-related co-morbidities through the senescence-associated secretory phenotype, in vivo senescent cell identification remains challenging. Here, we generate a gene set (SenMayo) and validate its enrichment in bone biopsies from two aged human cohorts. We further demonstrate reductions in SenMayo in bone following genetic clearance of senescent cells in mice and in adipose tissue from humans following pharmacological senescent cell clearance. We next use SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from human and murine bone marrow/bone scRNA-seq data. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Using this senescence panel, we are able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways. SenMayo also represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

Abstract Identifying differentially abundant microbes is a common goal of microbiome studies. Multiple methods have been applied for this purpose, which are largely used interchangeably in the literature. Although it has been observed that these tools can produce different results, there have been very few large-scale comparisons to describe the scale and significance of these differences. In addition, it is challenging for microbiome researchers to know which differential abundance tools are appropriate for their study and how these tools compare to one another. Here, we have investigated these questions by analyzing 38 16S rRNA gene datasets with two sample groups for differential abundance testing. We tested for differences in amplicon sequence variants and operational taxonomic units (referred to as ASVs for simplicity) between these groups with 14 commonly used differential abundance tools. Our findings confirmed that these tools identified drastically different numbers and sets of significant ASVs, however, for many tools the number of features identified correlated with…

Flooding is among the most prevalent natural hazards, with particularly disastrous impacts in low-income countries. This study presents global estimates of the number of people exposed to high flood risks in interaction with poverty. It finds that 1.81 billion people (23% of world population) are directly exposed to 1-in-100-year floods. Of these, 1.24 billion are located in South and East Asia, where China (395 million) and India (390 million) account for over one-third of global exposure. Low- and middle-income countries are home to 89% of the world's flood-exposed people. Of the 170 million facing high flood risk and extreme poverty (living on under $1.90 per day), 44% are in Sub-Saharan Africa. Over 780 million of those living on under $5.50 per day face high flood risk. Using state-of-the-art poverty and flood data, our findings highlight the scale and priority regions for flood mitigation measures to support resilient development.

Antibiotic resistance genes (ARGs) have accelerated microbial threats to human health in the last decade. Many genes can confer resistance, but evaluating the relative health risks of ARGs is complex. Factors such as the abundance, propensity for lateral transmission and ability of ARGs to be expressed in pathogens are all important. Here, an analysis at the metagenomic level from various habitats (6 types of habitats, 4572 samples) detects 2561 ARGs that collectively conferred resistance to 24 classes of antibiotics. We quantitatively evaluate the health risk to humans, defined as the risk that ARGs will confound the clinical treatment for pathogens, of these 2561 ARGs by integrating human accessibility, mobility, pathogenicity and clinical availability. Our results demonstrate that 23.78% of the ARGs pose a health risk, especially those which confer multidrug resistance. We also calculate the antibiotic resistance risks of all samples in four main habitats, and with machine learning, successfully map the antibiotic resistance threats in global marine habitats with over 75%…

Abstract Colorectal cancer (CRC) is among the most common malignancies with limited treatments other than surgery. The tumor microenvironment (TME) profiling enables the discovery of potential therapeutic targets. Here, we profile 54,103 cells from tumor and adjacent tissues to characterize cellular composition and elucidate the potential origin and regulation of tumor-enriched cell types in CRC. We demonstrate that the tumor-specific FAP + fibroblasts and SPP1 + macrophages were positively correlated in 14 independent CRC cohorts containing 2550 samples and validate their close localization by immuno-fluorescent staining and spatial transcriptomics. This interaction might be regulated by chemerin, TGF-β, and interleukin-1, which would stimulate the formation of immune-excluded desmoplasic structure and limit the T cell infiltration. Furthermore, we find patients with high FAP or SPP1 expression achieved less therapeutic benefit from an anti-PD-L1 therapy cohort. Our results provide a potential therapeutic strategy by disrupting FAP + fibroblasts and SPP1 + macrophages interaction…

Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their…

Abstract Electrocatalytic recycling of waste nitrate (NO 3 − ) to valuable ammonia (NH 3 ) at ambient conditions is a green and appealing alternative to the Haber−Bosch process. However, the reaction requires multi-step electron and proton transfer, making it a grand challenge to drive high-rate NH 3 synthesis in an energy-efficient way. Herein, we present a design concept of tandem catalysts, which involves coupling intermediate phases of different transition metals, existing at low applied overpotentials, as cooperative active sites that enable cascade NO 3 − -to-NH 3 conversion, in turn avoiding the generally encountered scaling relations. We implement the concept by electrochemical transformation of Cu−Co binary sulfides into potential-dependent core−shell Cu/CuO x and Co/CoO phases. Electrochemical evaluation, kinetic studies, and in−situ Raman spectra reveal that the inner Cu/CuO x phases preferentially catalyze NO 3 − reduction to NO 2 − , which is rapidly reduced to NH 3 at the nearby Co/CoO shell. This unique tandem catalyst system leads to a NO 3 − -to-NH 3 Faradaic…

Abstract Electrochemical nitrate reduction to ammonia is a promising alternative strategy to the traditional Haber-Bosch process but suffers from a low Faradaic efficiency and limited ammonia yield due to the sluggish multi-electron/proton-involved steps. Herein, we report a typical hollow cobalt phosphide nanosphere electrocatalyst assembled on a self-supported carbon nanosheet array synthesized with a confinement strategy that exhibits an extremely high ammonia yield rate of 8.47 mmol h −1 cm −2 through nitrate reduction reaction, which is highly superior to previously reported values to our knowledge. In situ experiments and theoretical investigations reveal that the dynamic equilibrium between the generation of active hydrogen on cobalt phosphide and its timely consumption by nitrogen intermediates leads to a superior ammonia yield with a high Faradaic efficiency. This unique insight based on active hydrogen equilibrium provides new opportunities for large-scale ammonia production through electrochemical techniques and can be further used for carbon dioxide capture.

Long noncoding RNAs (lncRNAs) are recently implicated in modifying immunology in colorectal cancer (CRC). Nevertheless, the clinical significance of immune-related lncRNAs remains largely unexplored. In this study, we develope a machine learning-based integrative procedure for constructing a consensus immune-related lncRNA signature (IRLS). IRLS is an independent risk factor for overall survival and displays stable and powerful performance, but only demonstrates limited predictive value for relapse-free survival. Additionally, IRLS possesses distinctly superior accuracy than traditional clinical variables, molecular features, and 109 published signatures. Besides, the high-risk group is sensitive to fluorouracil-based adjuvant chemotherapy, while the low-risk group benefits more from bevacizumab. Notably, the low-risk group displays abundant lymphocyte infiltration, high expression of CD8A and PD-L1, and a response to pembrolizumab. Taken together, IRLS could serve as a robust and promising tool to improve clinical outcomes for individual CRC patients.

Abstract The development of electrocatalysts capable of efficient reduction of nitrate (NO 3 − ) to ammonia (NH 3 ) is drawing increasing interest for the sake of low carbon emission and environmental protection. Herein, we present a CuCo bimetallic catalyst able to imitate the bifunctional nature of copper-type nitrite reductase, which could easily remove NO 2 − via the collaboration of two active centers. Indeed, Co acts as an electron/proton donating center, while Cu facilitates NO x − adsorption/association. The bio-inspired CuCo nanosheet electrocatalyst delivers a 100 ± 1% Faradaic efficiency at an ampere-level current density of 1035 mA cm −2 at −0.2 V vs . Reversible Hydrogen Electrode. The NH 3 production rate reaches a high activity of 4.8 mmol cm −2 h −1 (960 mmol g cat −1 h −1 ). A mechanistic study, using electrochemical in situ Fourier transform infrared spectroscopy and shell-isolated nanoparticle enhanced Raman spectroscopy, reveals a strong synergy between Cu and Co, with Co sites promoting the hydrogenation of NO 3 − to NH 3 via adsorbed *H species. The…

Abstract Accurate capacity estimation is crucial for the reliable and safe operation of lithium-ion batteries. In particular, exploiting the relaxation voltage curve features could enable battery capacity estimation without additional cycling information. Here, we report the study of three datasets comprising 130 commercial lithium-ion cells cycled under various conditions to evaluate the capacity estimation approach. One dataset is collected for model building from batteries with LiNi 0.86 Co 0.11 Al 0.03 O 2 -based positive electrodes. The other two datasets, used for validation, are obtained from batteries with LiNi 0.83 Co 0.11 Mn 0.07 O 2 -based positive electrodes and batteries with the blend of Li(NiCoMn)O 2 - Li(NiCoAl)O 2 positive electrodes. Base models that use machine learning methods are employed to estimate the battery capacity using features derived from the relaxation voltage profiles. The best model achieves a root-mean-square error of 1.1% for the dataset used for the model building. A transfer learning model is then developed by adding a featured linear…

Abstract Protein design aims to build new proteins from scratch thereby holding the potential to tackle many environmental and biomedical problems. Recent progress in the field of natural language processing (NLP) has enabled the implementation of ever-growing language models capable of understanding and generating text with human-like capabilities. Given the many similarities between human languages and protein sequences, the use of NLP models offers itself for predictive tasks in protein research. Motivated by the evident success of generative Transformer-based language models such as the GPT-x series, we developed ProtGPT2, a language model trained on protein space that generates de novo protein sequences that follow the principles of natural ones. In particular, the generated proteins display amino acid propensities which resemble natural proteins. Disorder and secondary structure prediction indicate that 88% of ProtGPT2-generated proteins are globular, in line with natural sequences. Sensitive sequence searches in protein databases show that ProtGPT2 sequences are distantly…

Abstract Bacteria and archaea have developed multiple antiviral mechanisms, and genomic evidence indicates that several of these antiviral systems co-occur in the same strain. Here, we introduce DefenseFinder, a tool that automatically detects known antiviral systems in prokaryotic genomes. We use DefenseFinder to analyse 21000 fully sequenced prokaryotic genomes, and find that antiviral strategies vary drastically between phyla, species and strains. Variations in composition of antiviral systems correlate with genome size, viral threat, and lifestyle traits. DefenseFinder will facilitate large-scale genomic analysis of antiviral defense systems and the study of host-virus interactions in prokaryotes.

Identification of cell populations often relies on manual annotation of cell clusters using established marker genes. However, the selection of marker genes is a time-consuming process that may lead to sub-optimal annotations as the markers must be informative of both the individual cell clusters and various cell types present in the sample. Here, we developed a computational platform, ScType, which enables a fully-automated and ultra-fast cell-type identification based solely on a given scRNA-seq data, along with a comprehensive cell marker database as background information. Using six scRNA-seq datasets from various human and mouse tissues, we show how ScType provides unbiased and accurate cell type annotations by guaranteeing the specificity of positive and negative marker genes across cell clusters and cell types. We also demonstrate how ScType distinguishes between healthy and malignant cell populations, based on single-cell calling of single-nucleotide variants, making it a versatile tool for anticancer applications. The widely applicable method is deployed both as an…

Abstract High-entropy alloys have received considerable attention in the field of catalysis due to their exceptional properties. However, few studies hitherto focus on the origin of their outstanding performance and the accurate identification of active centers. Herein, we report a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) High-entropy alloys system with various active sites that have different adsorption capacities for multiple intermediates. The electronegativity differences between mixed elements in HEA induce significant charge redistribution and create highly active Co and Ru sites with optimized energy barriers for simultaneously stabilizing OH* and H* intermediates, which greatly enhances the efficiency of water dissociation in alkaline conditions. This work provides an in-depth understanding of the interactions between specific active sites and intermediates, which opens up a fascinating direction for breaking scaling relation issues for multistep reactions.

Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining the spatial context of the tissue microenvironment. Deciphering the spatial context of spots in a tissue needs to use their spatial information carefully. To this end, we develop a graph attention auto-encoder framework STAGATE to accurately identify spatial domains by learning low-dimensional latent embeddings via integrating spatial information and gene expression profiles. To better characterize the spatial similarity at the boundary of spatial domains, STAGATE adopts an attention mechanism to adaptively learn the similarity of neighboring spots, and an optional cell type-aware module through integrating the pre-clustering of gene expressions. We validate STAGATE on diverse spatial transcriptomics datasets generated by different platforms with different spatial resolutions. STAGATE could substantially improve the identification accuracy of spatial domains, and denoise the data while preserving spatial expression patterns. Importantly, STAGATE…

Abstract Subnanometric metal clusters usually have unique electronic structures and may display electrocatalytic performance distinctive from single atoms (SAs) and larger nanoparticles (NPs). However, the electrocatalytic performance of clusters, especially the size-activity relationship at the sub-nanoscale, is largely unexplored. Here, we synthesize a series of Ru nanocrystals from single atoms, subnanometric clusters to larger nanoparticles, aiming at investigating the size-dependent activity of hydrogen evolution in alkaline media. It is found that the d band center of Ru downshifts in a nearly linear relationship with the increase of diameter, and the subnanometric Ru clusters with d band center closer to Femi level display a stronger water dissociation ability and thus superior hydrogen evolution activity than SAs and larger nanoparticles. Benefiting from the high metal utilization and strong water dissociation ability, the Ru clusters manifest an ultrahigh turnover frequency of 43.3 s −1 at the overpotential of 100 mV, 36.1-fold larger than the commercial Pt/C.

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into relevant information. We argue that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could improve inputs for ecological models and lead to integrated hybrid modeling tools. This approach will require close interdisciplinary collaboration to ensure the quality of novel approaches and train a new generation of data scientists in ecology and conservation.

Abstract Reactive oxygen species (ROS) play vital roles in intestinal inflammation. Therefore, eliminating ROS in the inflammatory site by antioxidant enzymes such as catalase and superoxide dismutase may effectively curb inflammatory bowel disease (IBD). Here, Escherichia coli Nissle 1917 (ECN), a kind of oral probiotic, was genetically engineered to overexpress catalase and superoxide dismutase (ECN-pE) for the treatment of intestinal inflammation. To improve the bioavailability of ECN-pE in the gastrointestinal tract, chitosan and sodium alginate, effective biofilms, were used to coat ECN-pE via a layer-by-layer electrostatic self-assembly strategy. In a mouse IBD model induced by different chemical drugs, chitosan/sodium alginate coating ECN-pE (ECN-pE(C/A) 2 ) effectively relieved inflammation and repaired epithelial barriers in the colon. Unexpectedly, such engineered EcN-pE(C/A) 2 could also regulate the intestinal microbial communities and improve the abundance of Lachnospiraceae _NK4A136 and Odoribacter in the intestinal flora, which are important microbes to maintain…

Earth's forests face grave challenges in the Anthropocene, including hotter droughts increasingly associated with widespread forest die-off events. But despite the vital importance of forests to global ecosystem services, their fates in a warming world remain highly uncertain. Lacking is quantitative determination of commonality in climate anomalies associated with pulses of tree mortality-from published, field-documented mortality events-required for understanding the role of extreme climate events in overall global tree die-off patterns. Here we established a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970. Our analysis quantifies a global "hotter-drought fingerprint" from these tree-mortality sites-effectively a hotter and drier climate signal for tree mortality-across 675 locations encompassing 1,303 plots. Frequency of these observed mortality-year climate conditions strongly increases nonlinearly under projected warming. Our database also provides initial…

Abstract Transition metal oxides or (oxy)hydroxides have been intensively investigated as promising electrocatalysts for energy and environmental applications. Oxygen in the lattice was reported recently to actively participate in surface reactions. Herein, we report a sacrificial template-directed approach to synthesize Mo-doped NiFe (oxy)hydroxide with modulated oxygen activity as an enhanced electrocatalyst towards oxygen evolution reaction (OER). The obtained MoNiFe (oxy)hydroxide displays a high mass activity of 1910 A/g metal at the overpotential of 300 mV. The combination of density functional theory calculations and advanced spectroscopy techniques suggests that the Mo dopant upshifts the O 2 p band and weakens the metal-oxygen bond of NiFe (oxy)hydroxide, facilitating oxygen vacancy formation and shifting the reaction pathway for OER. Our results provide critical insights into the role of lattice oxygen in determining the activity of (oxy)hydroxides and demonstrate tuning oxygen activity as a promising approach for constructing highly active electrocatalysts.

Abstract Ultra-wide bandgap semiconductor Ga 2 O 3 based electronic devices are expected to perform beyond wide bandgap counterparts GaN and SiC. However, the reported power figure-of-merit hardly can exceed, which is far below the projected Ga 2 O 3 material limit. Major obstacles are high breakdown voltage requires low doping material and PN junction termination, contradicting with low specific on-resistance and simultaneous achieving of n- and p-type doping, respectively. In this work, we demonstrate that Ga 2 O 3 heterojunction PN diodes can overcome above challenges. By implementing the holes injection in the Ga 2 O 3 , bipolar transport can induce conductivity modulation and low resistance in a low doping Ga 2 O 3 material. Therefore, breakdown voltage of 8.32 kV, specific on-resistance of 5.24 mΩ⋅cm 2 , power figure-of-merit of 13.2 GW/cm 2 , and turn-on voltage of 1.8 V are achieved. The power figure-of-merit value surpasses the 1-D unipolar limit of GaN and SiC. Those Ga 2 O 3 power diodes demonstrate their great potential for next-generation power electronics applications.

Abstract The growing availability of single-cell data has sparked an increased interest in the inference of cell-cell communication from this data. Many tools have been developed for this purpose. Each of them consists of a resource of intercellular interactions prior knowledge and a method to predict potential cell-cell communication events. Yet the impact of the choice of resource and method on the resulting predictions is largely unknown. To shed light on this, we created a framework, available at https://github.com/saezlab/liana/tree/biorxiv-clean, to facilitate a comparative assessment of methods for inferring cell-cell communication from single cell transcriptomics data and then compared 15 resources and 6 methods. We found few unique interactions and a varying degree of overlap among the resources, and observed uneven coverage in terms of pathways and biological categories. We analysed a colorectal cancer single cell RNA-Seq dataset using all possible combinations of methods and resources. We found major differences among the highest ranked intercellular interactions inferred…

Federated learning is a privacy-preserving machine learning technique to train intelligent models from decentralized data, which enables exploiting private data by communicating local model updates in each iteration of model learning rather than the raw data. However, model updates can be extremely large if they contain numerous parameters, and many rounds of communication are needed for model training. The huge communication cost in federated learning leads to heavy overheads on clients and high environmental burdens. Here, we present a federated learning method named FedKD that is both communication-efficient and effective, based on adaptive mutual knowledge distillation and dynamic gradient compression techniques. FedKD is validated on three different scenarios that need privacy protection, showing that it maximally can reduce 94.89% of communication cost and achieve competitive results with centralized model learning. FedKD provides a potential to efficiently deploy privacy-preserving intelligent systems in many scenarios, such as intelligent healthcare and personalization.

Abstract Noble metal electrocatalysts (e.g., Pt, Ru, etc.) suffer from sluggish kinetics of water dissociation for the electrochemical reduction of water to molecular hydrogen in alkaline and neutral pH environments. Herein, we found that an integration of Ru nanoparticles (NPs) on oxygen-deficient WO 3-x manifested a 24.0-fold increase in hydrogen evolution reaction (HER) activity compared with commercial Ru/C electrocatalyst in neutral electrolyte. Oxygen-deficient WO 3-x is shown to possess large capacity for storing protons, which could be transferred to the Ru NPs under cathodic potential. This significantly increases the hydrogen coverage on the surface of Ru NPs in HER and thus changes the rate-determining step of HER on Ru from water dissociation to hydrogen recombination.

Abstract Single-atom Fe-N-C catalysts has attracted widespread attentions in the oxygen reduction reaction (ORR). However, the origin of ORR activity on Fe-N-C catalysts is still unclear, which hinder the further improvement of Fe-N-C catalysts. Herein, we provide a model to understand the ORR activity of Fe-N 4 site from the spatial structure and energy level of the frontier orbitals by density functional theory calculations. Taking the regulation of divacancy defects on Fe-N 4 site ORR activity as examples, we demonstrate that the hybridization between Fe 3 dz 2 , 3 dyz (3 dxz ) and O 2 π* orbitals is the origin of Fe-N 4 ORR activity. We found that the Fe–O bond length, the d-band center gap of spin states, the magnetic moment of Fe site and *O 2 as descriptors can accurately predict the ORR activity of Fe-N 4 site. Furthermore, these descriptors and ORR activity of Fe-N 4 site are mainly distributed in two regions with obvious difference, which greatly relate to the height of Fe 3 d projected orbital in the Z direction. This work provides a new insight into the ORR activity of…

Abstract Background The impact of long COVID is considerable, but risk factors are poorly characterised. We analysed symptom duration and risk factor from 10 longitudinal study (LS) samples and electronic healthcare records (EHR). Methods Samples: 6907 adults self-reporting COVID-19 infection from 48,901 participants in the UK LS, and 3,327 adults with COVID-19, were assigned a long COVID code from 1,199,812 individuals in primary care EHR. Outcomes for LS included symptom duration lasting 4+ weeks (long COVID) and 12+ weeks. Association with of age, sex, ethnicity, socioeconomic factors, smoking, general and mental health, overweight/obesity, diabetes, hypertension, hypercholesterolaemia, and asthma was assessed. Results In LS, symptoms impacted normal functioning for 12+ weeks in 1.2% (mean age 20 years) to 4.8% (mean age 63 y) of COVID-19 cases. Between 7.8% (mean age 28 y) and 17% (mean age 58 y) reported any symptoms for 12+ weeks, and greater proportions for 4+ weeks. Age was associated with a linear increased risk in long COVID between 20 and 70 years. Being female (LS:…

Abstract Developing highly active and durable electrocatalysts for acidic oxygen evolution reaction remains a great challenge due to the sluggish kinetics of the four-electron transfer reaction and severe catalyst dissolution. Here we report an electrochemical lithium intercalation method to improve both the activity and stability of RuO2 for acidic oxygen evolution reaction. The lithium intercalates into the lattice interstices of RuO2, donates electrons and distorts the local structure. Therefore, the Ru valence state is lowered with formation of stable Li-O-Ru local structure, and the Ru–O covalency is weakened, which suppresses the dissolution of Ru, resulting in greatly enhanced durability. Meanwhile, the inherent lattice strain results in the surface structural distortion of LixRuO2 and activates the dangling O atom near the Ru active site as a proton acceptor, which stabilizes the OOH* and dramatically enhances the activity. This work provides an effective strategy to develop highly efficient catalyst towards water splitting.

Abstract The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

Abstract Cancer-associated fibroblasts (CAFs) are the predominant components of the tumor microenvironment (TME) and influence cancer hallmarks, but without systematic investigation on their ubiquitous characteristics across different cancer types. Here, we perform pan-cancer analysis on 226 samples across 10 solid cancer types to profile the TME at single-cell resolution, illustrating the commonalities/plasticity of heterogenous CAFs. Activation trajectory of the major CAF types is divided into three states, exhibiting distinct interactions with other cell components, and relating to prognosis of immunotherapy. Moreover, minor CAF components represent the alternative origin from other TME components (e.g., endothelia and macrophages). Particularly, the ubiquitous presentation of endothelial-to-mesenchymal transition CAF, which may interact with proximal SPP 1 + tumor-associated macrophages, is implicated in endothelial-to-mesenchymal transition and survival stratifications. Our study comprehensively profiles the shared characteristics and dynamics of CAFs, and highlight their…

Abstract Electroreduction of carbon dioxide (CO 2 ) into multicarbon products provides possibility of large-scale chemicals production and is therefore of significant research and commercial interest. However, the production efficiency for ethanol (EtOH), a significant chemical feedstock, is impractically low because of limited selectivity, especially under high current operation. Here we report a new silver–modified copper–oxide catalyst (dCu 2 O/Ag 2.3% ) that exhibits a significant Faradaic efficiency of 40.8% and energy efficiency of 22.3% for boosted EtOH production. Importantly, it achieves CO 2 –to–ethanol conversion under high current operation with partial current density of 326.4 mA cm −2 at −0.87 V vs reversible hydrogen electrode to rank highly significantly amongst reported Cu–based catalysts. Based on in situ spectra studies we show that significantly boosted production results from tailored introduction of Ag to optimize the coordinated number and oxide state of surface Cu sites, in which the * CO adsorption is steered as both atop and bridge configuration to trigger…

Abstract Next-generation advanced high/pulsed power capacitors rely heavily on dielectric ceramics with high energy storage performance. However, thus far, the huge challenge of realizing ultrahigh recoverable energy storage density ( W rec ) accompanied by ultrahigh efficiency ( η ) still existed and has become a key bottleneck restricting the development of dielectric materials in cutting-edge energy storage applications. Here, we propose a high-entropy strategy to design “local polymorphic distortion” including rhombohedral-orthorhombic-tetragonal-cubic multiphase nanoclusters and random oxygen octahedral tilt, resulting in ultrasmall polar nanoregions, an enhanced breakdown electric field, and delayed polarization saturation. A giant W rec ~10.06 J cm −3 is realized in lead-free relaxor ferroelectrics, especially with an ultrahigh η ~90.8%, showing breakthrough progress in the comprehensive energy storage performance for lead-free bulk ceramics. This work opens up an effective avenue to design dielectric materials with ultrahigh comprehensive energy storage performance to meet…

Optical metasurfaces with high quality factors (Q-factors) of chiral resonances can boost substantially light-matter interaction for various applications of chiral response in ultrathin, active, and nonlinear metadevices. However, current approaches lack the flexibility to enhance and tune the chirality and Q-factor simultaneously. Here, we suggest a design of chiral metasurface supporting bound state in the continuum (BIC) and demonstrate experimentally chiroptical responses with ultra-high Q-factors and near-perfect circular dichroism (CD = 0.93) at optical frequencies. We employ the symmetry-reduced meta-atoms with high birefringence supporting winding elliptical eigenstate polarizations with opposite helicity. It provides a convenient way for achieving the maximal planar chirality tuned by either breaking in-plane structure symmetry or changing illumination angle. Beyond linear CD, we also achieved strong near-field enhancement CD and near-unitary nonlinear CD in the same planar chiral metasurface design with circular eigen-polarization. Sharply resonant chirality realized in…

Graphene and related two-dimensional (2D) materials have remained an active field of research in science and engineering for over fifteen years. Here, the authors investigate why the transition from laboratories to fabrication plants appears to lag behind expectations, and summarize the main challenges and opportunities that have thus far prevented the commercialisation of these materials.

Removal of organic micropollutants from water through advanced oxidation processes (AOPs) is hampered by the excessive input of energy and/or chemicals as well as the large amounts of residuals resulting from incomplete mineralization. Herein, we report a new water purification paradigm, the direct oxidative transfer process (DOTP), which enables complete, highly efficient decontamination at very low dosage of oxidants. DOTP differs fundamentally from AOPs and adsorption in its pollutant removal behavior and mechanisms. In DOTP, the nanocatalyst can interact with persulfate to activate the pollutants by lowering their reductive potential energy, which triggers a non-decomposing oxidative transfer of pollutants from the bulk solution to the nanocatalyst surface. By leveraging the activation, stabilization, and accumulation functions of the heterogeneous catalyst, the DOTP can occur spontaneously on the nanocatalyst surface to enable complete removal of pollutants. The process is found to occur for diverse pollutants, oxidants, and nanocatalysts, including various low-cost catalysts.…

Abstract A profound transformation of China’s energy system is required to achieve carbon neutrality. Here, we couple Monte Carlo analysis with a bottom-up energy-environment-economy model to generate 3,000 cases with different carbon peak times, technological evolution pathways and cumulative carbon budgets. The results show that if emissions peak in 2025, the carbon neutrality goal calls for a 45–62% electrification rate, 47–78% renewable energy in primary energy supply, 5.2–7.9 TW of solar and wind power, 1.5–2.7 PWh of energy storage usage and 64–1,649 MtCO 2 of negative emissions, and synergistically reducing approximately 80% of local air pollutants compared to the present level in 2050. The emission peak time and cumulative carbon budget have significant impacts on the decarbonization pathways, technology choices, and transition costs. Early peaking reduces welfare losses and prevents overreliance on carbon removal technologies. Technology breakthroughs, production and consumption pattern changes, and policy enhancement are urgently required to achieve carbon neutrality.

Abstract Single-site cocatalysts engineered on supports offer a cost-efficient pathway to utilize precious metals, yet improving the performance further with minimal catalyst loading is still highly desirable. Here we have conducted a photochemical reaction to stabilize ultralow Pt co-catalysts (0.26 wt%) onto the basal plane of hexagonal ZnIn 2 S 4 nanosheets (Pt SS -ZIS) to form a Pt-S 3 protrusion tetrahedron coordination structure. Compared with the traditional defect-trapped Pt single-site counterparts, the protruding Pt single-sites on h -ZIS photocatalyst enhance the H 2 evolution yield rate by a factor of 2.2, which could reach 17.5 mmol g −1 h −1 under visible light irradiation. Importantly, through simple drop-casting, a thin Pt SS -ZIS film is prepared, and large amount of observable H 2 bubbles are generated, providing great potential for practical solar-light-driven H 2 production. The protruding single Pt atoms in Pt SS -ZIS could inhibit the recombination of electron-hole pairs and cause a tip effect to optimize the adsorption/desorption behavior of H through…

Advancements of virtual reality technology pave the way for developing wearable devices to enable somatosensory sensation, which can bring more comprehensive perception and feedback in the metaverse-based virtual society. Here, we propose augmented tactile-perception and haptic-feedback rings with multimodal sensing and feedback capabilities. This highly integrated ring consists of triboelectric and pyroelectric sensors for tactile and temperature perception, and vibrators and nichrome heaters for vibro- and thermo-haptic feedback. All these components integrated on the ring can be directly driven by a custom wireless platform of low power consumption for wearable/portable scenarios. With voltage integration processing, high-resolution continuous finger motion tracking is achieved via the triboelectric tactile sensor, which also contributes to superior performance in gesture/object recognition with artificial intelligence analysis. By fusing the multimodal sensing and feedback functions, an interactive metaverse platform with cross-space perception capability is successfully…

Many luminescent stimuli responsive materials are based on fluorescence emission, while stimuli-responsive room temperature phosphorescent materials are less explored. Here, we show a kind of stimulus-responsive room temperature phosphorescence materials by the covalent linkage of phosphorescent chromophore of arylboronic acid and polymer matrix of poly(vinylalcohol). Attributed to the rigid environment offered from hydrogen bond and B-O covalent bond between arylboronic acid and poly(vinylalcohol), the yielded polymer film exhibits ultralong room temperature phosphorescence with lifetime of 2.43 s and phosphorescence quantum yield of 7.51%. Interestingly, the RTP property of this film is sensitive to the water and heat stimuli, because water could destroy the hydrogen bonds between adjacent poly(vinylalcohol) polymers, then changing the rigidity of this system. Furthermore, by introducing another two fluorescent dyes to this system, the color of afterglow with stimulus response effect could be adjusted from blue to green to orange through triplet-to-singlet Förster-resonance…

Abstract Long COVID remains a broadly defined syndrome, with estimates of prevalence and duration varying widely. We use data from rounds 3–5 of the REACT-2 study ( n = 508,707; September 2020 – February 2021), a representative community survey of adults in England, and replication data from round 6 ( n = 97,717; May 2021) to estimate the prevalence and identify predictors of persistent symptoms lasting 12 weeks or more; and unsupervised learning to cluster individuals by reported symptoms. At 12 weeks in rounds 3–5, 37.7% experienced at least one symptom, falling to 21.6% in round 6. Female sex, increasing age, obesity, smoking, vaping, hospitalisation with COVID-19, deprivation, and being a healthcare worker are associated with higher probability of persistent symptoms in rounds 3–5, and Asian ethnicity with lower probability. Clustering analysis identifies a subset of participants with predominantly respiratory symptoms. Managing the long-term sequelae of COVID-19 will remain a major challenge for affected individuals and their families and for health services.

Abstract Mimicking natural photosynthesis to convert CO 2 with H 2 O into value-added fuels achieving overall reaction is a promising way to reduce the atmospheric CO 2 level. Casting the catalyst of two or more catalytic sites with rapid electron transfer and interaction may be an effective strategy for coupling photocatalytic CO 2 reduction and H 2 O oxidation. Herein, based on the MOF ∪ COF collaboration, we have carefully designed and synthesized a crystalline hetero-metallic cluster catalyst denoted MCOF-Ti 6 Cu 3 with spatial separation and functional cooperation between oxidative and reductive clusters. It utilizes dynamic covalent bonds between clusters to promote photo-induced charge separation and transfer efficiency, to drive both the photocatalytic oxidative and reductive reactions. MCOF-Ti 6 Cu 3 exhibits fine activity in the conversion of CO 2 with water into HCOOH (169.8 μmol g −1 h −1 ). Remarkably, experiments and theoretical calculations reveal that photo-excited electrons are transferred from Ti to Cu, indicating that the Cu cluster is the catalytic reduction…

Rapid urban expansion has profound impacts on global biodiversity through habitat conversion, degradation, fragmentation, and species extinction. However, how future urban expansion will affect global biodiversity needs to be better understood. We contribute to filling this knowledge gap by combining spatially explicit projections of urban expansion under shared socioeconomic pathways (SSPs) with datasets on habitat and terrestrial biodiversity (amphibians, mammals, and birds). Overall, future urban expansion will lead to 11-33 million hectares of natural habitat loss by 2100 under the SSP scenarios and will disproportionately cause large natural habitat fragmentation. The urban expansion within the current key biodiversity priority areas is projected to be higher (e.g., 37-44% higher in the WWF's Global 200) than the global average. Moreover, the urban land conversion will reduce local within-site species richness by 34% and species abundance by 52% per 1 km grid cell, and 7-9 species may be lost per 10 km cell. Our study suggests an urgent need to develop a sustainable urban…

Aqueous zinc-ion batteries are realistic candidates as stationary storage systems for power-grid applications. However, to accelerate their commercialization, some important challenges must be specifically tackled, and appropriate experimental practices need to be embraced to align the academic research efforts with the realistic industrial working conditions for stationary storage. Within this commentary article, both the open challenges and the good experimental practices are discussed in relation to their impact on the future development of the aqueous Zn-ion technology. Aqueous Zn-based batteries represent a viable and cost-effective technology for electricity grid storage. Here, the authors discuss the most challenging aspects to bridge academic and industrial research and accelerate the adoption of this class of devices on a large scale.

Abstract Aqueous zinc batteries are appealing devices for cost-effective and environmentally sustainable energy storage. However, the zinc metal deposition at the anode strongly influences the battery cycle life and performance. To circumvent this issue, here we propose the use of lanthanum nitrate (La(NO 3 ) 3 ) as supporting salt for aqueous zinc sulfate (ZnSO 4 ) electrolyte solutions. Via physicochemical and electrochemical characterizations, we demonstrate that this peculiar electrolyte formulation weakens the electric double layer repulsive force, thus, favouring dense metallic zinc deposits and regulating the charge distribution at the zinc metal|electrolyte interface. When tested in Zn||VS 2 full coin cell configuration (with cathode mass loading of 16 mg cm −2 ), the electrolyte solution containing the lanthanum ions enables almost 1000 cycles at 1 A g −1 (after 5 activation cycles at 0.05 A g −1 ) with a stable discharge capacity of about 90 mAh g −1 and an average cell discharge voltage of ∼0.54 V.

Plant response to drought stress involves fungi and bacteria that live on and in plants and in the rhizosphere, yet the stability of these myco- and micro-biomes remains poorly understood. We investigate the resistance and resilience of fungi and bacteria to drought in an agricultural system using both community composition and microbial associations. Here we show that tests of the fundamental hypotheses that fungi, as compared to bacteria, are (i) more resistant to drought stress but (ii) less resilient when rewetting relieves the stress, found robust support at the level of community composition. Results were more complex using all-correlations and co-occurrence networks. In general, drought disrupts microbial networks based on significant positive correlations among bacteria, among fungi, and between bacteria and fungi. Surprisingly, co-occurrence networks among functional guilds of rhizosphere fungi and leaf bacteria were strengthened by drought, and the same was seen for networks involving arbuscular mycorrhizal fungi in the rhizosphere. We also found support for the stress…

Abstract Designing efficient catalysts and understanding the underlying mechanisms for anodic nucleophile electrooxidation are central to the advancement of electrochemically-driven technologies. Here, a heterostructure of nickel boride/nickel catalyst is developed to enable methanol electrooxidation into formate with a Faradaic efficiency of nearly 100%. Operando electrochemical impedance spectroscopy and in situ Raman spectroscopy are applied to understand the influence of methanol concentration in the methanol oxidation reaction. High concentrations of methanol inhibit the phase transition of the electrocatalyst to high-valent electro-oxidation products, and electrophilic oxygen species (O* or OH*) formed on the electrocatalyst are considered to be the catalytically active species. Additional mechanistic investigation with density functional theory calculations reveals that the potential-determining step, the formation of *CH 2 O, occurs most favorably on the nickel boride/nickel heterostructure rather than on nickel boride and nickel. These results are highly instructive for the…

Ultrasonic neuromodulation has the unique potential to provide non-invasive control of neural activity in deep brain regions with high spatial precision and without chemical or genetic modification. However, the biomolecular and cellular mechanisms by which focused ultrasound excites mammalian neurons have remained unclear, posing significant challenges for the use of this technology in research and potential clinical applications. Here, we show that focused ultrasound excites primary murine cortical neurons in culture through a primarily mechanical mechanism mediated by specific calcium-selective mechanosensitive ion channels. The activation of these channels results in a gradual build-up of calcium, which is amplified by calcium- and voltage-gated channels, generating a burst firing response. Cavitation, temperature changes, large-scale deformation, and synaptic transmission are not required for this excitation to occur. Pharmacological and genetic inhibition of specific ion channels leads to reduced responses to ultrasound, while over-expressing these channels results in stronger…

Abstract As pioneering Fe3O4nanozymes, their explicit peroxidase (POD)-like catalytic mechanism remains elusive. Although many studies have proposed surface Fe2+-induced Fenton-like reactions accounting for their POD-like activity, few have focused on the internal atomic changes and their contribution to the catalytic reaction. Here we report that Fe2+within Fe3O4can transfer electrons to the surface via the Fe2+-O-Fe3+chain, regenerating the surface Fe2+and enabling a sustained POD-like catalytic reaction. This process usually occurs with the outward migration of excess oxidized Fe3+from the lattice, which is a rate-limiting step. After prolonged catalysis, Fe3O4nanozymes suffer the phase transformation to γ-Fe2O3with depletable POD-like activity. This self-depleting characteristic of nanozymes with internal atoms involved in electron transfer and ion migration is well validated on lithium iron phosphate nanoparticles. We reveal a neglected issue concerning the necessity of considering both surface and internal atoms when designing, modulating, and applying nanozymes.

Abstract The Chinese government has set long-term carbon neutrality and renewable energy (RE) development goals for the power sector. Despite a precipitous decline in the costs of RE technologies, the external costs of renewable intermittency and the massive investments in new RE capacities would increase electricity costs. Here, we develop a power system expansion model to comprehensively evaluate changes in the electricity supply costs over a 30-year transition to carbon neutrality. RE supply curves, operating security constraints, and the characteristics of various generation units are modelled in detail to assess the cost variations accurately. According to our results, approximately 5.8 TW of wind and solar photovoltaic capacity would be required to achieve carbon neutrality in the power system by 2050. The electricity supply costs would increase by 9.6 CNY¢/kWh. The major cost shift would result from the substantial investments in RE capacities, flexible generation resources, and network expansion.

Abstract Simultaneously increasing the activity and stability of the single-atom active sites of M–N–C catalysts is critical but remains a great challenge. Here, we report an Fe–N–C catalyst with nitrogen-coordinated iron clusters and closely surrounding Fe–N 4 active sites for oxygen reduction reaction in acidic fuel cells. A strong electronic interaction is built between iron clusters and satellite Fe–N 4 due to unblocked electron transfer pathways and very short interacting distances. The iron clusters optimize the adsorption strength of oxygen reduction intermediates on Fe–N 4 and also shorten the bond amplitude of Fe–N 4 with incoherent vibrations. As a result, both the activity and stability of Fe–N 4 sites are increased by about 60% in terms of turnover frequency and demetalation resistance. This work shows the great potential of strong electronic interactions between multiphase metal species for improvements of single-atom catalysts.

Abstract Single-atom catalysts anchoring offers a desirable pathway for efficiency maximization and cost-saving for photocatalytic hydrogen evolution. However, the single-atoms loading amount is always within 0.5% in most of the reported due to the agglomeration at higher loading concentrations. In this work, the highly dispersed and large loading amount (>1 wt%) of copper single-atoms were achieved on TiO 2 , exhibiting the H 2 evolution rate of 101.7 mmol g −1 h −1 under simulated solar light irradiation, which is higher than other photocatalysts reported, in addition to the excellent stability as proved after storing 380 days. More importantly, it exhibits an apparent quantum efficiency of 56% at 365 nm, a significant breakthrough in this field. The highly dispersed and large amount of Cu single-atoms incorporation on TiO 2 enables the efficient electron transfer via Cu 2+ -Cu + process. The present approach paves the way to design advanced materials for remarkable photocatalytic activity and durability.

Abstract Computational calculations and experimental studies reveal that the CoOOH phase and the intermediate-spin (IS) state are the key factors for realizing efficient Co-based electrocatalysts for the oxygen evolution reaction (OER). However, according to thermodynamics, general cobalt oxide converts to the CoO 2 phase under OER condition, retarding the OER kinetics. Herein, we demonstrate a simple and scalable strategy to fabricate electrodes with maintaining Fe-CoOOH phase and an IS state under the OER. The changes of phase and spin states were uncovered by combining in-situ /operando X-ray based absorption spectroscopy and Raman spectroscopy. Electrochemical reconstruction of chalcogenide treated Co foam affords a highly enlarged active surface that conferred excellent catalytic activity and stability in a large-scale water electrolyzer. Our findings are meaningful in that the calculated results were experimentally verified through the operando analyses. It also proposes a new strategy for electrode fabrication and confirms the importance of real active phases and spin states…

Persistent heat extremes can have severe impacts on ecosystems and societies, including excess mortality, wildfires, and harvest failures. Here we identify Europe as a heatwave hotspot, exhibiting upward trends that are three-to-four times faster compared to the rest of the northern midlatitudes over the past 42 years. This accelerated trend is linked to atmospheric dynamical changes via an increase in the frequency and persistence of double jet stream states over Eurasia. We find that double jet occurrences are particularly important for western European heatwaves, explaining up to 35% of temperature variability. The upward trend in the persistence of double jet events explains almost all of the accelerated heatwave trend in western Europe, and about 30% of it over the extended European region. Those findings provide evidence that in addition to thermodynamical drivers, atmospheric dynamical changes have contributed to the increased rate of European heatwaves, with implications for risk management and potential adaptation strategies.

Keyhole porosity is a key concern in laser powder-bed fusion (LPBF), potentially impacting component fatigue life. However, some keyhole porosity formation mechanisms, e.g., keyhole fluctuation, collapse and bubble growth and shrinkage, remain unclear. Using synchrotron X-ray imaging we reveal keyhole and bubble behaviour, quantifying their formation dynamics. The findings support the hypotheses that: (i) keyhole porosity can initiate not only in unstable, but also in the transition keyhole regimes created by high laser power-velocity conditions, causing fast radial keyhole fluctuations (2.5-10 kHz); (ii) transition regime collapse tends to occur part way up the rear-wall; and (iii) immediately after keyhole collapse, bubbles undergo rapid growth due to pressure equilibration, then shrink due to metal-vapour condensation. Concurrent with condensation, hydrogen diffusion into the bubble slows the shrinkage and stabilises the bubble size. The keyhole fluctuation and bubble evolution mechanisms revealed here may guide the development of control systems for minimising porosity.

Abstract Electrocatalytic urea synthesis emerged as the promising alternative of Haber–Bosch process and industrial urea synthetic protocol. Here, we report that a diatomic catalyst with bonded Fe–Ni pairs can significantly improve the efficiency of electrochemical urea synthesis. Compared with isolated diatomic and single-atom catalysts, the bonded Fe–Ni pairs act as the efficient sites for coordinated adsorption and activation of multiple reactants, enhancing the crucial C–N coupling thermodynamically and kinetically. The performance for urea synthesis up to an order of magnitude higher than those of single-atom and isolated diatomic electrocatalysts, a high urea yield rate of 20.2 mmol h −1 g −1 with corresponding Faradaic efficiency of 17.8% has been successfully achieved. A total Faradaic efficiency of about 100% for the formation of value-added urea, CO, and NH 3 was realized. This work presents an insight into synergistic catalysis towards sustainable urea synthesis via identifying and tailoring the atomic site configurations.

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as [Formula: see text]. When only K ≪ T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to [Formula: see text]. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning…

Nutrient scarcity is pervasive for natural microbial communities, affecting species reproduction and co-existence. However, it remains unclear whether there are general rules of how microbial species abundances are shaped by biotic and abiotic factors. Here we show that the ribosomal RNA gene operon (rrn) copy number, a genomic trait related to bacterial growth rate and nutrient demand, decreases from the abundant to the rare biosphere in the nutrient-rich coastal sediment but exhibits the opposite pattern in the nutrient-scarce pelagic zone of the global ocean. Both patterns are underlain by positive correlations between community-level rrn copy number and nutrients. Furthermore, inter-species co-exclusion inferred by negative network associations is observed more in coastal sediment than in ocean water samples. Nutrient manipulation experiments yield effects of nutrient availability on rrn copy numbers and network associations that are consistent with our field observations. Based on these results, we propose a "hunger games" hypothesis to define microbial species abundance rules…

Organic near-infrared room temperature phosphorescence materials have unparalleled advantages in bioimaging due to their excellent penetrability. However, limited by the energy gap law, the near-infrared phosphorescence materials (>650 nm) are very rare, moreover, the phosphorescence lifetimes of these materials are very short. In this work, we have obtained organic room temperature phosphorescence materials with long wavelengths (600/657-681/732 nm) and long lifetimes (102-324 ms) for the first time through the guest-host doped strategy. The guest molecule has sufficient conjugation to reduce the lowest triplet energy level and the host assists the guest in exciton transfer and inhibits the non-radiative transition of guest excitons. These materials exhibit good tissue penetration in bioimaging. Thanks to the characteristic of long lifetime and long wavelength emissive phosphorescence materials, the tumor imaging in living mice with a signal to background ratio value as high as 43 is successfully realized. This work provides a practical solution for the construction of organic…

Targeting ferroptosis, a unique cell death modality triggered by unrestricted lipid peroxidation, in cancer therapy is hindered by our incomplete understanding of ferroptosis mechanisms under specific cancer genetic contexts. KEAP1 (kelch-like ECH associated protein 1) is frequently mutated or inactivated in lung cancers, and KEAP1 mutant lung cancers are refractory to most therapies, including radiotherapy. In this study, we identify ferroptosis suppressor protein 1 (FSP1, also known as AIFM2) as a transcriptional target of nuclear factor erythroid 2-related factor 2 (NRF2) and reveal that the ubiquinone (CoQ)-FSP1 axis mediates ferroptosis- and radiation- resistance in KEAP1 deficient lung cancer cells. We further show that pharmacological inhibition of the CoQ-FSP1 axis sensitizes KEAP1 deficient lung cancer cells or patient-derived xenograft tumors to radiation through inducing ferroptosis. Together, our study identifies CoQ-FSP1 as a key downstream effector of KEAP1-NRF2 pathway and as a potential therapeutic target for treating KEAP1 mutant lung cancers.

Diabetic foot ulceration (DFU) is a devastating complication of diabetes whose pathogenesis remains incompletely understood. Here, we profile 174,962 single cells from the foot, forearm, and peripheral blood mononuclear cells using single-cell RNA sequencing. Our analysis shows enrichment of a unique population of fibroblasts overexpressing MMP1, MMP3, MMP11, HIF1A, CHI3L1, and TNFAIP6 and increased M1 macrophage polarization in the DFU patients with healing wounds. Further, analysis of spatially separated samples from the same patient and spatial transcriptomics reveal preferential localization of these healing associated fibroblasts toward the wound bed as compared to the wound edge or unwounded skin. Spatial transcriptomics also validates our findings of higher abundance of M1 macrophages in healers and M2 macrophages in non-healers. Our analysis provides deep insights into the wound healing microenvironment, identifying cell types that could be critical in promoting DFU healing, and may inform novel therapeutic approaches for DFU treatment.

The health of millions of people worldwide is negatively impacted by chronic exposure to elevated concentrations of geogenic fluoride in groundwater. Due to health effects including dental mottling and skeletal fluorosis, the World Health Organization maintains a maximum guideline of 1.5 mg/L in drinking water. As groundwater quality is not regularly tested in many areas, it is often unknown if the water in a given well or spring contains harmful levels of fluoride. Here we present a state-of-the-art global fluoride hazard map based on machine learning and over 400,000 fluoride measurements (10% of which >1.5 mg/L), which is then used to estimate the human population at risk. Hotspots indicated by the groundwater fluoride hazard map include parts of central Australia, western North America, eastern Brazil and many areas of Africa and Asia. Of the approximately 180 million people potentially affected worldwide, most reside in Asia (51-59% of total) and Africa (37-46% of total), with the latter representing 6.5% of the continent's population. Africa also contains 14 of the top 20…

Although urban greening is universally recognized as an essential part of sustainable and climate-responsive cities, a growing literature on green gentrification argues that new green infrastructure, and greenspace in particular, can contribute to gentrification, thus creating social and racial inequalities in access to the benefits of greenspace and further environmental and climate injustice. In response to limited quantitative evidence documenting the temporal relationship between new greenspaces and gentrification across entire cities, let alone across various international contexts, we employ a spatially weighted Bayesian model to test the green gentrification hypothesis across 28 cities in 9 countries in North America and Europe. Here we show a strong positive and relevant relationship for at least one decade between greening in the 1990s-2000s and gentrification that occurred between 2000-2016 in 17 of the 28 cities. Our results also determine whether greening plays a "lead", "integrated", or "subsidiary" role in explaining gentrification.

A major rate-limiting step in developing more effective immunotherapies for GBM is our inadequate understanding of the cellular complexity and the molecular heterogeneity of immune infiltrates in gliomas. Here, we report an integrated analysis of 201,986 human glioma, immune, and other stromal cells at the single cell level. In doing so, we discover extensive spatial and molecular heterogeneity in immune infiltrates. We identify molecular signatures for nine distinct myeloid cell subtypes, of which five are independent prognostic indicators of glioma patient survival. Furthermore, we identify S100A4 as a regulator of immune suppressive T and myeloid cells in GBM and demonstrate that deleting S100a4 in non-cancer cells is sufficient to reprogram the immune landscape and significantly improve survival. This study provides insights into spatial, molecular, and functional heterogeneity of glioma and glioma-associated immune cells and demonstrates the utility of this dataset for discovering therapeutic targets for this poorly immunogenic cancer.

Abstract The development of new solvents is imperative in lithium metal batteries due to the incompatibility of conventional carbonate and narrow electrochemical windows of ether-based electrolytes. Whereas the fluorinated ethers showed improved electrochemical stabilities, they can hardly solvate lithium ions. Thus, the challenge in electrolyte chemistry is to combine the high voltage stability of fluorinated ethers with high lithium ion solvation ability of ethers in a single molecule. Herein, we report a new solvent, 2,2-dimethoxy-4-(trifluoromethyl)-1,3-dioxolane (DTDL), combining a cyclic fluorinated ether with a linear ether segment to simultaneously achieve high voltage stability and tune lithium ion solvation ability and structure. High oxidation stability up to 5.5 V, large lithium ion transference number of 0.75 and stable Coulombic efficiency of 99.2% after 500 cycles proved the potential of DTDL in high-voltage lithium metal batteries. Furthermore, 20 μm thick lithium paired LiNi 0.8 Co 0.1 Mn 0.1 O 2 full cell incorporating 2 M LiFSI-DTDL electrolyte retained 84% of the…

Abstract Improving the catalytic efficiency of platinum (Pt) for hydrogen evolution reaction (HER) is crucial for water splitting technologies, and hydrogen spillover has emerged as a new frontier in designing the binary-component Pt/support HER electrocatalysts. However, such binary catalysts always suffer from long reaction pathway, undesirable interfacial barrier, and complicated synthesis processes. Here we report a single-phase complex oxide La2Sr2PtO7+δ as a high-performance HER electrocatalysts in acidic media via a unique atomic-scale hydrogen spillover effect between multifunctional catalytic sites. With insights from theoretical calculations, a possible synergistic mechanism involving the hydrogen spillover channel from OLa site→La-Pt bridge site→Pt site is proposed; namely, the OLa site enriches proton, the La-Pt bridge site with thermo-neutral H* adsorption facilitates the hydrogen spillover and H2 generation, and Pt site favors the final H2 desorption. Benefiting from such unusual phenomenon, the resulting La2Sr2PtO7+δ exhibits an exceptional HER electrode activity with…

Abstract For the practical use of synthetic hydrogels as artificial biological tissues, flexible electronics, and conductive membranes, achieving requirements for specific mechanical properties is one of the most prominent issues. Here, we demonstrate superstrong, superstiff, and conductive alginate hydrogels with densely interconnecting networks implemented via simple reconstructing processes, consisting of anisotropic densification of pre-gel and a subsequent ionic crosslinking with rehydration. The reconstructed hydrogel exhibits broad ranges of exceptional tensile strengths (8–57 MPa) and elastic moduli (94–1,290 MPa) depending on crosslinking ions. This hydrogel can hold sufficient cations (e.g., Li + ) within its gel matrix without compromising the mechanical performance and exhibits high ionic conductivity enough to be utilized as a gel electrolyte membrane. Further, this strategy can be applied to prepare mechanically outstanding, ionic-/electrical-conductive hydrogels by incorporating conducting polymer within the hydrogel matrix. Such hydrogels are easily laminated with…

Abstract Aerogel fibers have been recognized as the rising star in the fields of thermal insulation and wearable textiles. Yet, the lack of functionalization in aerogel fibers limits their applications. Herein, we report hygroscopic holey graphene aerogel fibers (LiCl@HGAFs) with integrated functionalities of highly efficient moisture capture, heat allocation, and microwave absorption. LiCl@HGAFs realize the water sorption capacity over 4.15 g g−1, due to the high surface area and high water uptake kinetics. Moreover, the sorbent can be regenerated through both photo-thermal and electro-thermal approaches. Along with the water sorption and desorption, LiCl@HGAFs experience an efficient heat transfer process, with a heat storage capacity of 6.93 kJ g−1. The coefficient of performance in the heating and cooling mode can reach 1.72 and 0.70, respectively. Notably, with the entrapped water, LiCl@HGAFs exhibit broad microwave absorption with a bandwidth of 9.69 GHz, good impedance matching, and a high attenuation constant of 585. In light of these findings, the multifunctional LiCl@HGAFs…

Abstract Electrochemical reduction of CO 2 to multi-carbon fuels and chemical feedstocks is an appealing approach to mitigate excessive CO 2 emissions. However, the reported catalysts always show either a low Faradaic efficiency of the C 2+ product or poor long-term stability. Herein, we report a facile and scalable anodic corrosion method to synthesize oxygen-rich ultrathin CuO nanoplate arrays, which form Cu/Cu 2 O heterogeneous interfaces through self-evolution during electrocatalysis. The catalyst exhibits a high C 2 H 4 Faradaic efficiency of 84.5%, stable electrolysis for ~55 h in a flow cell using a neutral KCl electrolyte, and a full-cell ethylene energy efficiency of 27.6% at 200 mA cm −2 in a membrane electrode assembly electrolyzer. Mechanism analyses reveal that the stable nanostructures, stable Cu/Cu 2 O interfaces, and enhanced adsorption of the *OCCOH intermediate preserve selective and prolonged C 2 H 4 production. The robust and scalable produced catalyst coupled with mild electrolytic conditions facilitates the practical application of electrochemical CO 2…

Abstract Development of the stable, lead-free inorganic perovskite material is of greatly importance on fabricating the third-generation solar cell. Until now, double perovskite, such as Cs2AgBiBr6, has been proved to be one of the most potential candidates to solve the toxicity and stability issues of traditional lead halide perovskite solar cells (PSCs). However, due to a wide and indirect bandgap of Cs2AgBiBr6 film, its light absorption ability is largely limited and the photoelectronic conversion efficiency (PCE) is normally lower than 2.5%. In this text, by using a hydrogenation method, the bandgap (Eg) of Cs2AgBiBr6 films could be tunable from 2.14 eV to 1.61 eV. At the same time, the highest PCE of hydrogenated Cs2AgBiBr6 perovskite solar cell has been improved more than 150% up to 6.27%. To the best of our knowledge, this is a record high efficiency of Cs2AgBiBr6-based perovskite solar cell. Further investigations confirmed that the interstitial doping of atomic hydrogen (H*) in Cs2AgBiBr6 lattice could not only adjust its valence and conduction band energy levels, but also…

Abstract The absence of two-dimensional (2D) van der Waals (vdW) ferromagnetic crystals with both above-room-temperature strong intrinsic ferromagnetism and large perpendicular magnetic anisotropy (PMA) severely hinders practical applications of 2D vdW crystals in next-generation low-power magnetoelectronic and spintronic devices. Here, we report a vdW intrinsic ferromagnetic crystal Fe 3 GaTe 2 that exhibits record-high above-room-temperature Curie temperature ( Tc , ~350-380 K) for known 2D vdW intrinsic ferromagnets, high saturation magnetic moment (40.11 emu/g), large PMA energy density (~4.79 × 10 5 J/m 3 ), and large anomalous Hall angle (3%) at room temperature. Such large room-temperature PMA is better than conventional widely-used ferromagnetic films like CoFeB, and one order of magnitude larger than known 2D vdW intrinsic ferromagnets. Room-temperature thickness and angle-dependent anomalous Hall devices and direct magnetic domains imaging based on Fe 3 GaTe 2 nanosheet have been realized. This work provides an avenue for room-temperature 2D ferromagnetism, electrical…

Abstract High-capacity Ni-rich layered oxides are promising cathode materials for secondary lithium-based battery systems. However, their structural instability detrimentally affects the battery performance during cell cycling. Here, we report an Al/Zr co-doped single-crystalline LiNi 0.88 Co 0.09 Mn 0.03 O 2 (SNCM) cathode material to circumvent the instability issue. We found that soluble Al ions are adequately incorporated in the SNCM lattice while the less soluble Zr ions are prone to aggregate in the outer SNCM surface layer. The synergistic effect of Al/Zr co-doping in SNCM lattice improve the Li-ion mobility, relief the internal strain, and suppress the Li/Ni cation mixing upon cycling at high cut-off voltage. These features improve the cathode rate capability and structural stabilization during prolonged cell cycling. In particular, the Zr-rich surface enables the formation of stable cathode-electrolyte interphase, which prevent SNCM from unwanted reactions with the non-aqueous fluorinated liquid electrolyte solution and avoid Ni dissolution. To prove the practical…

Abstract Ionic conductive hydrogels prepared from naturally abundant cellulose are ideal candidates for constructing flexible electronics from the perspective of commercialization and environmental sustainability. However, cellulosic hydrogels featuring both high mechanical strength and ionic conductivity remain extremely challenging to achieve because the ionic charge carriers tend to destroy the hydrogen-bonding network among cellulose. Here we propose a supramolecular engineering strategy to boost the mechanical performance and ionic conductivity of cellulosic hydrogels by incorporating bentonite (BT) via the strong cellulose-BT coordination interaction and the ion regulation capability of the nanoconfined cellulose-BT intercalated nanostructure. A strong (compressive strength up to 3.2 MPa), tough (fracture energy up to 0.45 MJ m −3 ), yet highly ionic conductive and freezing tolerant (high ionic conductivities of 89.9 and 25.8 mS cm −1 at 25 and −20 °C, respectively) all-natural cellulose-BT hydrogel is successfully realized. These findings open up new perspectives for the…

Abstract Electronic skins (e-skins) are devices that can respond to mechanical stimuli and enable robots to perceive their surroundings. A great challenge for existing e-skins is that they may easily fail under extreme mechanical conditions due to their multilayered architecture with mechanical mismatch and weak adhesion between the interlayers. Here we report a flexible pressure sensor with tough interfaces enabled by two strategies: quasi-homogeneous composition that ensures mechanical match of interlayers, and interlinked microconed interface that results in a high interfacial toughness of 390 J·m −2 . The tough interface endows the sensor with exceptional signal stability determined by performing 100,000 cycles of rubbing, and fixing the sensor on a car tread and driving 2.6 km on an asphalt road. The topological interlinks can be further extended to soft robot-sensor integration, enabling a seamless interface between the sensor and robot for highly stable sensing performance during manipulation tasks under complicated mechanical conditions.

The gut microbiome is an important determinant in various diseases. Here we perform a cross-sectional study of Japanese adults and identify the Blautia genus, especially B. wexlerae, as a commensal bacterium that is inversely correlated with obesity and type 2 diabetes mellitus. Oral administration of B. wexlerae to mice induce metabolic changes and anti-inflammatory effects that decrease both high-fat diet-induced obesity and diabetes. The beneficial effects of B. wexlerae are correlated with unique amino-acid metabolism to produce S-adenosylmethionine, acetylcholine, and L-ornithine and carbohydrate metabolism resulting in the accumulation of amylopectin and production of succinate, lactate, and acetate, with simultaneous modification of the gut bacterial composition. These findings reveal unique regulatory pathways of host and microbial metabolism that may provide novel strategies in preventive and therapeutic approaches for metabolic disorders.

The COVID-19 pandemic continues to impact daily life, including health system operations, despite the availability of vaccines that are effective in greatly reducing the risks of death and severe disease. Misperceptions of COVID-19 vaccine safety, efficacy, risks, and mistrust in institutions responsible for vaccination campaigns have been reported as factors contributing to vaccine hesitancy. This study investigated COVID-19 vaccine hesitancy globally in June 2021. Nationally representative samples of 1,000 individuals from 23 countries were surveyed. Data were analyzed descriptively, and weighted multivariable logistic regressions were used to explore associations with vaccine hesitancy. Here, we show that more than three-fourths (75.2%) of the 23,000 respondents report vaccine acceptance, up from 71.5% one year earlier. Across all countries, vaccine hesitancy is associated with a lack of trust in COVID-19 vaccine safety and science, and skepticism about its efficacy. Vaccine hesitant respondents are also highly resistant to required proof of vaccination; 31.7%, 20%, 15%, and…

Abstract Electrochemical alcohols oxidation offers a promising approach to produce valuable chemicals and facilitate coupled H2 production. However, the corresponding current density is very low at moderate cell potential that substantially limits the overall productivity. Here we report the electrooxidation of benzyl alcohol coupled with H2 production at high current density (540 mA cm−2 at 1.5 V vs. RHE) over a cooperative catalyst of Au nanoparticles supported on cobalt oxyhydroxide nanosheets (Au/CoOOH). The absolute current can further reach 4.8 A at 2.0 V in a more realistic two-electrode membrane-free flow electrolyzer. Experimental combined with theoretical results indicate that the benzyl alcohol can be enriched at Au/CoOOH interface and oxidized by the electrophilic oxygen species (OH*) generated on CoOOH, leading to higher activity than pure Au. Based on the finding that the catalyst can be reversibly oxidized/reduced at anodic potential/open circuit, we design an intermittent potential (IP) strategy for long-term alcohol electrooxidation that achieves high current…

Chiral discrimination is critical in environmental and life sciences. However, an ideal chiral discrimination strategy has not yet been developed because of the inevitable nonspecific binding entity of wrong enantiomers or insufficient intrinsic optical activities of chiral molecules. Here, we propose an "inspector" recognition mechanism (IRM), which is implemented on a chiral imprinted polydopamine (PDA) layer coated on surface-enhanced Raman scattering (SERS) tag layer. The IRM works based on the permeability change of the imprinted PDA after the chiral recognition and scrutiny of the permeability by an inspector molecule. Good enantiomer can specifically recognize and fully fill the chiral imprinted cavities, whereas the wrong cannot. Then a linear shape aminothiol molecule, as an inspector of the recognition status is introduced, which can only percolate through the vacant and nonspecifically occupied cavities, inducing the SERS signal to decrease. Accordingly, chirality information exclusively stems from good enantiomer specific binding, while nonspecific recognition of wrong…

The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.

Abstract Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be particularly effective in conducting atomistic simulations for such purposes. However, existing NNPs are generally designed for narrow target materials, making them unsuitable for broader applications in material discovery. Here we report a development of universal NNP called PreFerred Potential (PFP), which is able to handle any combination of 45 elements. Particular emphasis is placed on the datasets, which include a diverse set of virtual structures used to attain the universality. We demonstrated the applicability of PFP in selected domains: lithium diffusion in LiFeSO4F, molecular adsorption in metal-organic frameworks, an order–disorder transition of Cu-Au alloys, and material discovery for a Fischer–Tropsch catalyst. They showcase the power of PFP, and this technology provides a highly useful tool for material discovery.

Abstract Organic semiconductors offer a tunable platform for photocatalysis, yet the more difficult exciton dissociation, compared to that in inorganic semiconductors, lowers their photocatalytic activities. In this work, we report that the charge carrier lifetime is dramatically prolonged by incorporating a suitable donor-acceptor (β-ketene-cyano) pair into a covalent organic framework nanosheet. These nanosheets show an apparent quantum efficiency up to 82.6% at 450 nm using platinum as co-catalyst for photocatalytic H2 evolution. Charge carrier kinetic analysis and femtosecond transient absorption spectroscopy characterizations verify that these modified covalent organic framework nanosheets have intrinsically lower exciton binding energies and longer-lived charge carriers than the corresponding nanosheets without the donor-acceptor unit. This work provides a model for gaining insight into the nature of short-lived active species in polymeric organic photocatalysts.

Abstract Aqueous zinc ion batteries are receiving increasing attention for large-scale energy storage systems owing to their attractive features with respect to safety, cost, and scalability. Although vanadium oxides with various compositions have been demonstrated to store zinc ions reversibly, their limited cyclability especially at low current densities and their poor calendar life impede their widespread practical adoption. Herein, we reveal that the electrochemically inactive zinc pyrovanadate (ZVO) phase formed on the cathode surface is the main cause of the limited sustainability. Moreover, the formation of ZVO is closely related to the corrosion of the zinc metal counter electrode by perturbing the pH of the electrolyte. Thus, the dissolution of VO 2 (OH) 2 − , the source of the vanadium in the ZVO, is no longer prevented. The proposed amalgamated Zn anode improves the cyclability drastically by blocking the corrosion at the anode, verifying the importance of pH control and the interplay between both electrodes.

Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem…

Depression is one of the most poorly understood diseases due to its elusive pathogenesis. There is an urgency to identify molecular and biological mechanisms underlying depression and the gut microbiome is a novel area of interest. Here we investigate the relation of fecal microbiome diversity and composition with depressive symptoms in 1,054 participants from the Rotterdam Study cohort and validate these findings in the Amsterdam HELIUS cohort in 1,539 subjects. We identify association of thirteen microbial taxa, including genera Eggerthella, Subdoligranulum, Coprococcus, Sellimonas, Lachnoclostridium, Hungatella, Ruminococcaceae (UCG002, UCG003 and UCG005), LachnospiraceaeUCG001, Eubacterium ventriosum and Ruminococcusgauvreauiigroup, and family Ruminococcaceae with depressive symptoms. These bacteria are known to be involved in the synthesis of glutamate, butyrate, serotonin and gamma amino butyric acid (GABA), which are key neurotransmitters for depression. Our study suggests that the gut microbiome composition may play a key role in depression.

Immunogenic cell death significantly contributes to the success of anti-cancer therapies, but immunogenicity of different cell death modalities widely varies. Ferroptosis, a form of cell death that is characterized by iron accumulation and lipid peroxidation, has not yet been fully evaluated from this perspective. Here we present an inducible model of ferroptosis, distinguishing three phases in the process-'initial' associated with lipid peroxidation, 'intermediate' correlated with ATP release and 'terminal' recognized by HMGB1 release and loss of plasma membrane integrity-that serves as tool to study immune cell responses to ferroptotic cancer cells. Co-culturing ferroptotic cancer cells with dendritic cells (DC), reveals that 'initial' ferroptotic cells decrease maturation of DC, are poorly engulfed, and dampen antigen cross-presentation. DC loaded with ferroptotic, in contrast to necroptotic, cancer cells fail to protect against tumor growth. Adding ferroptotic cancer cells to immunogenic apoptotic cells dramatically reduces their prophylactic vaccination potential. Our study…

Abstract Bismuth vanadate (BiVO4) has been widely investigated as a photocatalyst or photoanode for solar water splitting, but its activity is hindered by inefficient cocatalysts and limited understanding of the underlying mechanism. Here we demonstrate significantly enhanced water oxidation on the particulate BiVO4 photocatalyst via in situ facet-selective photodeposition of dual-cocatalysts that exist separately as metallic Ir nanoparticles and nanocomposite of FeOOH and CoOOH (denoted as FeCoOx), as revealed by advanced techniques. The mechanism of water oxidation promoted by the dual-cocatalysts is experimentally and theoretically unraveled, and mainly ascribed to the synergistic effect of the spatially separated dual-cocatalysts (Ir, FeCoOx) on both interface charge separation and surface catalysis. Combined with the H2-evolving photocatalysts, we finally construct a Z-scheme overall water splitting system using [Fe(CN)6]3−/4− as the redox mediator, whose apparent quantum efficiency at 420 nm and solar-to-hydrogen conversion efficiency are optimized to be 12.3% and 0.6%,…

Abstract Polymer-ceramic piezoelectric composites, combining high piezoelectricity and mechanical flexibility, have attracted increasing interest in both academia and industry. However, their piezoelectric activity is largely limited by intrinsically low crystallinity and weak spontaneous polarization. Here, we propose a Ti 3 C 2 T x MXene anchoring method to manipulate the intermolecular interactions within the all- trans conformation of a polymer matrix. Employing phase-field simulation and molecular dynamics calculations, we show that OH surface terminations on the Ti 3 C 2 T x nanosheets offer hydrogen bonding with the fluoropolymer matrix, leading to dipole alignment and enhanced net spontaneous polarization of the polymer-ceramic composites. We then translated this interfacial bonding strategy into electrospinning to boost the piezoelectric response of samarium doped Pb (Mg 1/3 Nb 2/3 )O 3 -PbTiO 3 /polyvinylidene fluoride composite nanofibers by 160% via Ti 3 C 2 T x nanosheets inclusion. With excellent piezoelectric and mechanical attributes, the as-electrospun piezoelectric…

Abstract Population and development megatrends will drive growth in cement production, which is already one of the most challenging-to-mitigate sources of CO 2 emissions. However, availabilities of conventional secondary cementitious materials (CMs) like fly ash are declining. Here, we present detailed generation rates of secondary CMs worldwide between 2002 and 2018, showing the potential for 3.5 Gt to be generated in 2018. Maximal substitution of Portland cement clinker with these materials could have avoided up to 1.3 Gt CO 2 -eq. emissions (~44% of cement production and ~2.8% of anthropogenic CO 2 -eq. emissions) in 2018. We also show that nearly all of the highest cement producing nations can locally generate and use secondary CMs to substitute up to 50% domestic Portland cement clinker, with many countries able to potentially substitute 100% Portland cement clinker. Our results highlight the importance of pursuing regionally optimized CM mix designs and systemic approaches to decarbonizing the global CMs cycle.

Abstract Lactate is a key metabolite produced from glycolytic metabolism of glucose molecules, yet it also serves as a primary carbon fuel source for many cell types. In the tumor-immune microenvironment, effect of lactate on cancer and immune cells can be highly complex and hard to decipher, which is further confounded by acidic protons, a co-product of glycolysis. Here we show that lactate is able to increase stemness of CD8 + T cells and augments anti-tumor immunity. Subcutaneous administration of sodium lactate but not glucose to mice bearing transplanted MC38 tumors results in CD8 + T cell-dependent tumor growth inhibition. Single cell transcriptomics analysis reveals increased proportion of stem-like TCF-1-expressing CD8 + T cells among intra-tumoral CD3 + cells, a phenotype validated by in vitro lactate treatment of T cells. Mechanistically, lactate inhibits histone deacetylase activity, which results in increased acetylation at H3K27 of the Tcf7 super enhancer locus, leading to increased Tcf7 gene expression. CD8 + T cells in vitro pre-treated with lactate efficiently…

Abstract The electrochemical nitrate reduction reaction (NO 3 RR) to ammonia is an essential step toward restoring the globally disrupted nitrogen cycle. In search of highly efficient electrocatalysts, tailoring catalytic sites with ligand and strain effects in random alloys is a common approach but remains limited due to the ubiquitous energy-scaling relations. With interpretable machine learning, we unravel a mechanism of breaking adsorption-energy scaling relations through the site-specific Pauli repulsion interactions of the metal d -states with adsorbate frontier orbitals. The non-scaling behavior can be realized on (100)-type sites of ordered B2 intermetallics, in which the orbital overlap between the hollow *N and subsurface metal atoms is significant while the bridge-bidentate *NO 3 is not directly affected. Among those intermetallics predicted, we synthesize monodisperse ordered B2 CuPd nanocubes that demonstrate high performance for NO 3 RR to ammonia with a Faradaic efficiency of 92.5% at −0.5 V RHE and a yield rate of 6.25 mol h −1 g −1 at −0.6 V RHE . This study…

Both low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates.

Abstract Designing active and stable electrocatalysts with economic efficiency for acidic oxygen evolution reaction is essential for developing proton exchange membrane water electrolyzers. Herein, we report on a cobalt oxide incorporated with iridium single atoms (Ir-Co 3 O 4 ), prepared by a mechanochemical approach. Operando X-ray absorption spectroscopy reveals that Ir atoms are partially oxidized to active Ir >4+ during the reaction, meanwhile Ir and Co atoms with their bridged electrophilic O ligands acting as active sites, are jointly responsible for the enhanced performance. Theoretical calculations further disclose the isolated Ir atoms can effectively boost the electronic conductivity and optimize the energy barrier. As a result, Ir-Co 3 O 4 exhibits significantly higher mass activity and turnover frequency than those of benchmark IrO 2 in acidic conditions. Moreover, the catalyst preparation can be easily scaled up to gram-level per batch. The present approach highlights the concept of constructing single noble metal atoms incorporated cost-effective metal oxides…

Skin effect, experimentally discovered in one dimension, describes the physical phenomenon that on an open chain, an extensive number of eigenstates of a non-Hermitian Hamiltonian are localized at the end(s) of the chain. Here in two and higher dimensions, we establish a theorem that the skin effect exists, if and only if periodic-boundary spectrum of the Hamiltonian covers a finite area on the complex plane. This theorem establishes the universality of the effect, because the above condition is satisfied in almost every generic non-Hermitian Hamiltonian, and, unlike in one dimension, is compatible with all point-group symmetries. We propose two new types of skin effect in two and higher dimensions: the corner-skin effect where all eigenstates are localized at corners of the system, and the geometry-dependent-skin effect where skin modes disappear for systems of a particular shape, but appear on generic polygons. An immediate corollary of our theorem is that any non-Hermitian system having exceptional points (lines) in two (three) dimensions exhibits skin effect, making this…

Worldwide, there are nearly 10 million new cases of dementia annually, of which Alzheimer's disease (AD) is the most common. New measures are needed to improve the diagnosis of individuals with cognitive impairment due to various etiologies. Here, we report a deep learning framework that accomplishes multiple diagnostic steps in successive fashion to identify persons with normal cognition (NC), mild cognitive impairment (MCI), AD, and non-AD dementias (nADD). We demonstrate a range of models capable of accepting flexible combinations of routinely collected clinical information, including demographics, medical history, neuropsychological testing, neuroimaging, and functional assessments. We then show that these frameworks compare favorably with the diagnostic accuracy of practicing neurologists and neuroradiologists. Lastly, we apply interpretability methods in computer vision to show that disease-specific patterns detected by our models track distinct patterns of degenerative changes throughout the brain and correspond closely with the presence of neuropathological lesions on…

Reaction rates of common organic reactions have been reported to increase by one to six orders of magnitude in aqueous microdroplets compared to bulk solution, but the reasons for the rate acceleration are poorly understood. Using a coarse-grained electron model that describes structural organization and electron densities for water droplets without the expense of ab initio methods, we investigate the electric field distributions at the air-water interface to understand the origin of surface reactivity. We find that electric field alignments along free O-H bonds at the surface are ~16 MV/cm larger on average than that found for O-H bonds in the interior of the water droplet. Furthermore, electric field distributions can be an order of magnitude larger than the average due to non-linear coupling of intramolecular solvent polarization with intermolecular solvent modes which may contribute to even greater surface reactivity for weakening or breaking chemical bonds at the droplet surface.