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CRISPR diagnostics are effective but suffer from low signal transduction efficiency, limited sensitivity, and poor stability due to their reliance on the trans-cleavage of single-stranded nucleic acid fluorescent reporters. Here, we present CrisprAIE, which integrates CRISPR/Cas reactions with "one to more" aggregation-induced emission luminogen (AIEgen) lighting-up fluorescence generated by the trans-cleavage of Cas proteins to AIEgen-incorporated double-stranded DNA labeled with single-stranded nucleic acid linkers and Black Hole Quencher groups at both ends (Q-dsDNA/AIEgens-Q). CrisprAIE demonstrates superior performance in the clinical nucleic acid detection of norovirus and SARS-CoV-2 regardless of amplification. Moreover, the diagnostic potential of CrisprAIE is further enhanced by integrating it with spherical nucleic acid-modified AIEgens (SNA/AIEgens) and a portable cellphone-based readout device. The improved CrisprAIE system, utilizing Q-dsDNA/AIEgen-Q and SNA/AIEgen reporters, exhibits approximately 80- and 270-fold improvements in sensitivity, respectively, compared to conventional CRISPR-based diagnostics. We believe CrisprAIE can be readily extended as a universal signal generation strategy to significantly enhance the detection efficiency of almost all existing CRISPR-based diagnostics., (© 2024. The Author(s).)

Internal combustion engine fueled by carbon-free hydrogen (H 2 -ICE) offers a promising alternative for sustainable transportation. Herein, we report a facile and universal strategy through the physical mixing of Pt catalyst with zeolites to significantly improve the catalytic performance in the selective catalytic reduction of nitrogen oxides (NO x ) with H 2 (H 2 -SCR), a process aiming at NO x removal from H 2 -ICE. Via the physical mixing of Pt/TiO 2 with Y zeolite (Pt/TiO 2  + Y), a remarkable enhancement of NO x reduction activity and N 2 selectivity was simultaneously achieved. The incorporation of Y zeolite effectively captured the in-situ generated water, fostering a water-rich environment surrounding the Pt active sites. This environment weakened the NO adsorption while concurrently promoting the H 2 activation, leading to the strikingly elevated H 2 -SCR activity and N 2 selectivity on Pt/TiO 2  + Y catalyst. This study provides a unique, easy and sustainable physical mixing approach to achieve proficient heterogeneous catalysis for environmental applications., (© 2024. The Author(s).)

In heterogeneous catalysis catalyst activation is often observed during the reaction process, which is mostly attributed to the induction by reactants. In this work we report that surface structure of molybdenum nitride (MoN x ) catalyst exhibits a high dependency on the partial pressure or concentration of reaction products i.e., CO and H 2 O in reverse water gas-shift reaction (RWGS) (CO 2 :H 2  = 1:3) but not reactants of CO 2 and H 2 . Molybdenum oxide (MoO x ) overlayers formed by oxidation with H 2 O are observed at reaction pressure below 10 mbar or with low partial pressure of CO/H 2 O products, while CO-induced surface carbonization happens at reaction pressure above 100 mbar and with high partial pressure of CO/H 2 O products. The reaction products induce restructuring of MoN x surface into more active molybdenum carbide (MoC x ) to increase the reaction rate and make for higher partial pressure CO, which in turn promote further surface carbonization of MoN x . We refer to this as the positive feedback between catalytic activity and catalyst activation in RWGS, which should be widely present in heterogeneous catalysis., (© 2024. The Author(s).)

In the past decades, a band alignment theory has become a basis for designing different high-performance semiconductor devices, such as photocatalysis, photoelectrocatalysis, photoelectrostorage and third-generation photovoltaics. Recently, a faradaic junction model (coupled electron and ion transfer) has been proposed to explain charge transfer phenomena in these semiconductor heterojunctions. However, the classic band alignment theory cannot explain coupled electron and ion transfer processes because it only regulates electron transfer. Therefore, it is very significant to explore a suitable design concept for regulating coupled electron and ion transfer in order to improve the performance of semiconductor heterojunctions. Herein, we propose a potential window alignment theory for regulating ion transfer and remarkably improving the photoelectrocatalytic performance of a MoS 2 /Cd-Cu 2 ZnSnS 4 heterojunction photocathode. Moreover, we find that a faradaic potential window, rather than the band position of the intermediate layer, is a criterion for identifying interface charge transfer direction. This finding can offer different perspectives for designing high-performance semiconductor heterojunctions with suitable potential windows for solar energy conversion and storage., (© 2023. The Author(s).)

Post-translational modifications (PTMs) couple feed-fast cycles to diurnal rhythms. However, it remains largely uncharacterized whether and how meal timing organizes diurnal rhythms beyond the transcriptome. Here, we systematically profile the daily rhythms of the proteome, four PTMs (phosphorylation, ubiquitylation, succinylation and N-glycosylation) and the lipidome in the liver from young female mice subjected to either day/sleep time-restricted feeding (DRF) or night/wake time-restricted feeding (NRF). We detect robust daily rhythms among different layers of omics with phosphorylation the most nutrient-responsive and succinylation the least. Integrative analyses reveal that clock regulation of fatty acid metabolism represents a key diurnal feature that is reset by meal timing, as indicated by the rhythmic phosphorylation of the circadian repressor PERIOD2 at Ser971 (PER2-pSer971). We confirm that PER2-pSer971 is activated by nutrient availability in vivo. Together, this dataset represents a comprehensive resource detailing the proteomic and lipidomic responses by the liver to alterations in meal timing., (© 2023. Springer Nature Limited.)

Stereoselective ring-opening polymerization catalysts are used to produce degradable stereoregular poly(lactic acids) with thermal and mechanical properties that are superior to those of atactic polymers. However, the process of discovering highly stereoselective catalysts is still largely empirical. We aim to develop an integrated computational and experimental framework for efficient, predictive catalyst selection and optimization. As a proof of principle, we have developed a Bayesian optimization workflow on a subset of literature results for stereoselective lactide ring-opening polymerization, and using the algorithm, we identify multiple new Al complexes that catalyze either isoselective or heteroselective polymerization. In addition, feature attribution analysis uncovers mechanistically meaningful ligand descriptors, such as percent buried volume (%V bur ) and the highest occupied molecular orbital energy (E HOMO ), that can access quantitative and predictive models for catalyst development., (© 2023. The Author(s).)

The electrochemical ammonia oxidation to dinitrogen as a means for energy and environmental applications is a key technology toward the realization of a sustainable nitrogen cycle. The state-of-the-art metal catalysts including Pt and its bimetallics with Ir show promising activity, albeit suffering from high overpotentials for appreciable current densities and the soaring price of precious metals. Herein, the immense design space of ternary Pt alloy nanostructures is explored by graph neural networks trained on ab initio data for concurrently predicting site reactivity, surface stability, and catalyst synthesizability descriptors. Among a few Ir-free candidates that emerge from the active learning workflow, Pt 3 Ru-M (M: Fe, Co, or Ni) alloys were successfully synthesized and experimentally verified to be more active toward ammonia oxidation than Pt, Pt 3 Ir, and Pt 3 Ru. More importantly, feature attribution analyses using the machine-learned representation of site motifs provide fundamental insights into chemical bonding at metal surfaces and shed light on design strategies for high-performance catalytic systems beyond the d-band center metric of binding sites., (© 2023. The Author(s).)

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 provides machine-learned design rules besides the d-band center metrics, paving the path toward data-driven discovery of catalytic materials beyond linear scaling limitations., (© 2022. The Author(s).)

Structural variants (SVs) represent a major source of genetic diversity and are related to numerous agronomic traits and evolutionary events; however, their comprehensive identification and characterization in cucumber (Cucumis sativus L.) have been hindered by the lack of a high-quality pan-genome. Here, we report a graph-based cucumber pan-genome by analyzing twelve chromosome-scale genome assemblies. Genotyping of seven large chromosomal rearrangements based on the pan-genome provides useful information for use of wild accessions in breeding and genetic studies. A total of ~4.3 million genetic variants including 56,214 SVs are identified leveraging the chromosome-level assemblies. The pan-genome graph integrating both variant information and reference genome sequences aids the identification of SVs associated with agronomic traits, including warty fruits, flowering times and root growth, and enhances the understanding of cucumber trait evolution. The graph-based cucumber pan-genome and the identified genetic variants provide rich resources for future biological research and genomics-assisted breeding., (© 2022. The Author(s).)

Despite recent advances of data acquisition and algorithms development, machine learning (ML) faces tremendous challenges to being adopted in practical catalyst design, largely due to its limited generalizability and poor explainability. Herein, we develop a theory-infused neural network (TinNet) approach that integrates deep learning algorithms with the well-established d-band theory of chemisorption for reactivity prediction of transition-metal surfaces. With simple adsorbates (e.g., *OH, *O, and *N) at active site ensembles as representative descriptor species, we demonstrate that the TinNet is on par with purely data-driven ML methods in prediction performance while being inherently interpretable. Incorporation of scientific knowledge of physical interactions into learning from data sheds further light on the nature of chemical bonding and opens up new avenues for ML discovery of novel motifs with desired catalytic properties., (© 2021. The Author(s).)

The gymnosperm Welwitschia mirabilis belongs to the ancient, enigmatic gnetophyte lineage. It is a unique desert plant with extreme longevity and two ever-elongating leaves. We present a chromosome-level assembly of its genome (6.8 Gb/1 C) together with methylome and transcriptome data to explore its astonishing biology. We also present a refined, high-quality assembly of Gnetum montanum to enhance our understanding of gnetophyte genome evolution. The Welwitschia genome has been shaped by a lineage-specific ancient, whole genome duplication (~86 million years ago) and more recently (1-2 million years) by bursts of retrotransposon activity. High levels of cytosine methylation (particularly at CHH motifs) are associated with retrotransposons, whilst long-term deamination has resulted in an exceptionally GC-poor genome. Changes in copy number and/or expression of gene families and transcription factors (e.g. R2R3MYB, SAUR) controlling cell growth, differentiation and metabolism underpin the plant's longevity and tolerance to temperature, nutrient and water stress., (© 2021. The Author(s).)

Peptides are widely used for surface modification to develop improved implants, such as cell adhesion RGD peptide and antimicrobial peptide (AMP). However, it is a daunting challenge to identify an optimized condition with the two peptides showing their intended activities and the parameters for reaching such a condition. Herein, we develop a high-throughput strategy, preparing titanium (Ti) surfaces with a gradient in peptide density by click reaction as a platform, to screen the positions with desired functions. Such positions are corresponding to optimized molecular parameters (peptide densities/ratios) and associated preparation parameters (reaction times/reactant concentrations). These parameters are then extracted to prepare nongradient mono- and dual-peptide functionalized Ti surfaces with desired biocompatibility or/and antimicrobial activity in vitro and in vivo. We also demonstrate this strategy could be extended to other materials. Here, we show that the high-throughput versatile strategy holds great promise for rational design and preparation of functional biomaterial surfaces.

Endothelial cell (EC) metabolism is thought to be one of the driving forces for angiogenesis. Here we report the identification of the hexosamine D-mannosamine (ManN) as an EC mitogen and survival factor for bovine and human microvascular EC, with an additivity with VEGF. ManN inhibits glycosylation in ECs and induces significant changes in N-glycan and O-glycan profiles. We further demonstrate that ManN and two N-glycosylation inhibitors stimulate EC proliferation via both JNK activation and the unfolded protein response caused by ER stress. ManN results in enhanced angiogenesis in a mouse skin injury model. ManN also promotes angiogenesis in a mouse hindlimb ischemia model, with accelerated limb blood flow recovery compared to controls. In addition, intraocular injection of ManN induces retinal neovascularization. Therefore, activation of stress pathways following inhibition of protein glycosylation can promote EC proliferation and angiogenesis and may represent a therapeutic strategy for treatment of ischemic disorders.

Building upon the d-band reactivity theory in surface chemistry and catalysis, we develop a Bayesian learning approach to probing chemisorption processes at atomically tailored metal sites. With representative species, e.g., *O and *OH, Bayesian models trained with ab initio adsorption properties of transition metals predict site reactivity at a diverse range of intermetallics and near-surface alloys while naturally providing uncertainty quantification from posterior sampling. More importantly, this conceptual framework sheds light on the orbitalwise nature of chemical bonding at adsorption sites with d-states characteristics ranging from bulk-like semi-elliptic bands to free-atom-like discrete energy levels, bridging the complexity of electronic descriptors for the prediction of novel catalytic materials.

Quantum biological electron transfer (ET) essentially involves in virtually all important biological processes such as photosynthesis, cellular respiration, DNA repair, cellular homeostasis, and cell death. However, there is no real-time imaging method to capture biological electron tunnelling in live cells to date. Here, we report a quantum biological electron tunnelling (QBET) junction and its application in real-time optical detection of QBET and the dynamics of ET in mitochondrial cytochrome c during cell life and death process. QBET junctions permit to see the behaviours of electron tunnelling through barrier molecules with different barrier widths. Using QBET spectroscopy, we optically capture real-time ET in cytochrome c redox dynamics during cellular apoptosis and necrosis in living cells. The non-invasive real-time QBET spectroscopic imaging of ET in live cell open a new era in life sciences and medicine by providing a way to capture spatiotemporal ET dynamics and to reveal the quantum biological mechanisms.

The recently developed droplet-based single-cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured for tens of thousands of single cells from multiple individuals. Despite the advances of many clustering methods, there are few tailored methods for population-scale scRNA-seq studies. Here, we develop a Bayesian mixture model for single-cell sequencing (BAMM-SC) method to cluster scRNA-seq data from multiple individuals simultaneously. BAMM-SC takes raw count data as input and accounts for data heterogeneity and batch effect among multiple individuals in a unified Bayesian hierarchical model framework. Results from extensive simulation studies and applications of BAMM-SC to in-house experimental scRNA-seq datasets using blood, lung and skin cells from humans or mice demonstrate that BAMM-SC outperformed existing clustering methods with considerable improved clustering accuracy, particularly in the presence of heterogeneity among individuals.

While common growth models assume a structure-less liquid composed of atomic flow units, structural ordering has been shown in liquid metals. Here, we conduct in situ transmission electron microscopy crystallization experiments on metallic glass nanorods, and show that structural ordering strongly affects crystal growth and is controlled by nanorod thermal history. Direct visualization reveals structural ordering as densely populated small clusters in a nanorod heated from the glass state, and similar behavior is found in molecular dynamics simulations of model metallic glasses. At the same growth temperature, the asymmetry in growth rate for rods that are heated versus cooled decreases with nanorod diameter and vanishes for very small rods. We hypothesize that structural ordering enhances crystal growth, in contrast to assumptions from common growth models. The asymmetric growth rate is attributed to the difference in the degree of the structural ordering, which is pronounced in the heated glass but sparse in the cooled liquid.

Supported nanoparticles are broadly employed in industrial catalytic processes, where the active sites can be tuned by metal-support interactions (MSIs). Although it is well accepted that supports can modify the chemistry of metal nanoparticles, systematic utilization of MSIs for achieving desired catalytic performance is still challenging. The developments of supports with appropriate chemical properties and identification of the resulting active sites are the main barriers. Here, we develop two-dimensional transition metal carbides (MXenes) supported platinum as efficient catalysts for light alkane dehydrogenations. Ordered Pt 3 Ti and surface Pt 3 Nb intermetallic compound nanoparticles are formed via reactive metal-support interactions on Pt/Ti 3 C 2 T x and Pt/Nb 2 CT x catalysts, respectively. MXene supports modulate the nature of the active sites, making them highly selective toward C-H activation. Such exploitation of the MSIs makes MXenes promising platforms with versatile chemical reactivity and tunability for facile design of supported intermetallic nanoparticles over a wide range of compositions and structures.

Electrochemical reduction of N 2 to NH 3 provides an alternative to the Haber-Bosch process for sustainable, distributed production of NH 3 when powered by renewable electricity. However, the development of such process has been impeded by the lack of efficient electrocatalysts for N 2 reduction. Here we report efficient electroreduction of N 2 to NH 3 on palladium nanoparticles in phosphate buffer solution under ambient conditions, which exhibits high activity and selectivity with an NH 3 yield rate of ~4.5 μg mg -1 h Pd h -1 and a Faradaic efficiency of 8.2% at 0.1 V vs. the reversible hydrogen electrode (corresponding to a low overpotential of 56 mV), outperforming other catalysts including gold and platinum. Density functional theory calculations suggest that the unique activity of palladium originates from its balanced hydrogen evolution activity and the Grotthuss-like hydride transfer mechanism on α-palladium hydride that lowers the free energy barrier of N 2 H, the rate-limiting step for NH 2 H, the rate-limiting step for NH 3 electrosynthesis.

Organization of spherical particles into lattices is typically driven by packing considerations. Although the addition of directional binding can significantly broaden structural diversity, nanoscale implementation remains challenging. Here we investigate the assembly of clusters and lattices in which anisotropic polyhedral blocks coordinate isotropic spherical nanoparticles via shape-induced directional interactions facilitated by DNA recognition. We show that these polyhedral blocks--cubes and octahedrons--when mixed with spheres, promote the assembly of clusters with architecture determined by polyhedron symmetry. Moreover, three-dimensional binary superlattices are formed when DNA shells accommodate the shape disparity between nanoparticle interfaces. The crystallographic symmetry of assembled lattices is determined by the spatial symmetry of the block's facets, while structural order depends on DNA-tuned interactions and particle size ratio. The presented lattice assembly strategy, exploiting shape for defining the global structure and DNA-mediation locally, opens novel possibilities for by-design fabrication of binary lattices.

Materials providing broadband light antireflection have applications as highly transparent window coatings, military camouflage, and coatings for efficiently coupling light into solar cells and out of light-emitting diodes. In this work, densely packed silicon nanotextures with feature sizes smaller than 50 nm enhance the broadband antireflection compared with that predicted by their geometry alone. A significant fraction of the nanotexture volume comprises a surface layer whose optical properties differ substantially from those of the bulk, providing the key to improved performance. The nanotexture reflectivity is quantitatively well-modelled after accounting for both its profile and changes in refractive index at the surface. We employ block copolymer self-assembly for precise and tunable nanotexture design in the range of ~10-70 nm across macroscopic solar cell areas. Implementing this efficient antireflection approach in crystalline silicon solar cells significantly betters the performance gain compared with an optimized, planar antireflection coating.

Artificial effective media are attractive because of the fantastic applications they may enable, such as super lensing and electromagnetic invisibility. However, the inevitable loss due to their strongly dispersive nature is one of the fundamental challenges preventing such applications from becoming a reality. In this study, we demonstrate an effective gain medium based on negative resistance, to overcompensate the loss of a conventional passive metamaterial, meanwhile keeping its original negative-index property. Energy conservation-based theory, full-wave simulation and experimental measurement show that a fabricated sample consisting of conventional sub-wavelength building blocks with embedded microwave tunnel diodes exhibits a band-limited Lorentzian dispersion simultaneously with a negative refractive index and a net gain. Our work provides experimental evidence to the assertion that a stable net gain in negative-index gain medium is achievable, proposing a potential solution for the critical challenge current metamateiral technology faces in practical applications.