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Dysregulated extravillous trophoblast invasion and proliferation are known to increase the risk of recurrent spontaneous abortion (RSA); however, the underlying mechanism remains unclear. Herein, in our retrospective observational case-control study we show that villous samples from RSA patients, compared to healthy controls, display reduced succinate dehydrogenase complex iron sulfur subunit (SDHB) DNA methylation, elevated SDHB expression, and reduced succinate levels, indicating that low succinate levels correlate with RSA. Moreover, we find high succinate levels in early pregnant women are correlated with successful embryo implantation. SDHB promoter methylation recruited MBD1 and excluded c-Fos, inactivating SDHB expression and causing intracellular succinate accumulation which mimicked hypoxia in extravillous trophoblasts cell lines JEG3 and HTR8 via the PHD2-VHL-HIF-1α pathway; however, low succinate levels reversed this effect and increased the risk of abortion in mouse model. This study reveals that abnormal metabolite levels inhibit extravillous trophoblast function and highlights an approach for RSA intervention. Abnormal placentation is associated with recurrent spontaneous abortion (RSA) risk. Here the authors report that low embryonic villous succinate level associates with risk of RSA in patients, and increasing succinate levels is sufficient to reduce the incidence rate in a mouse model of spontaneous abortion.

The active sites for CO 2 electroreduction (CO 2 R) to multi-carbon (C 2+ ) products over oxide-derived copper (OD-Cu) catalysts are under long-term intense debate. This paper describes the atomic structure motifs for product-specific active sites on OD-Cu catalysts in CO 2 R. Herein, we describe realistic OD-Cu surface models by simulating the oxide-derived process via the molecular dynamic simulation with neural network (NN) potential. After the analysis of over 150 surface sites through NN potential based high-throughput testing, coupled with density functional theory calculations, three square-like sites for C–C coupling are identified. Among them, Σ3 grain boundary like planar-square sites and convex-square sites are responsible for ethylene production while step-square sites, i.e. n (111) × (100), favor alcohols generation, due to the geometric effect for stabilizing acetaldehyde intermediates and destabilizing Cu–O interactions, which are quantitatively demonstrated by combined theoretical and experimental results. This finding provides fundamental insights into the origin of activity and selectivity over Cu-based catalysts and illustrates the value of our research framework in identifying active sites for complex heterogeneous catalysts. The active sites over oxide-derived copper (OD-Cu) catalysts for CO 2 electroreduction are unclear. Here, the authors show atom-level product-specific active sites on OD-Cu surface models, where planar and convex square sites are responsible for ethylene while the step square site favours alcohols generation.

Noble-metal alloys are widely used as heterogeneous catalysts. However, due to the existence of scaling properties of adsorption energies on transition metal surfaces, the enhancement of catalytic activity is frequently accompanied by side reactions leading to a reduction in selectivity for the target product. Herein, we describe an approach to breaking the scaling relationship for propane dehydrogenation, an industrially important reaction, by assembling single atom alloys (SAAs), to achieve simultaneous enhancement of propylene selectivity and propane conversion. We synthesize γ-alumina-supported platinum/copper SAA catalysts by incipient wetness co-impregnation method with a high copper to platinum ratio. Single platinum atoms dispersed on copper nanoparticles dramatically enhance the desorption of surface-bounded propylene and prohibit its further dehydrogenation, resulting in high propylene selectivity (~90%). Unlike previous reported SAA applications at low temperatures (<400 °C), Pt/Cu SAA shows excellent stability of more than 120 h of operation under atmospheric pressure at 520 °C. Enhancing the catalytic activity of noble-metal alloys is frequently accompanied by side reactions. Here, the authors describe an approach to break the scaling relationship for propane dehydrogenation, by assembling single atom alloys, to achieve simultaneous enhancement of propylene selectivity and propane conversion.

Tens of thousands of metal–organic frameworks (MOFs) have been developed in the past two decades, and only ≈100 of them have been demonstrated as porous and hydrophobic. These hydrophobic MOFs feature not only a rich structural variety, highly crystalline frameworks, and uniform micropores, but also a low affinity toward water and superior hydrolytic stability, which make them promising adsorbents for diverse applications, including humid CO2 capture, alcohol/water separation, pollutant removal from air or water, substrate‐selective catalysis, energy storage, anticorrosion, and self‐cleaning. Herein, the recent research advancements in hydrophobic MOFs are presented. The existing techniques for qualitatively or quantitatively assessing the hydrophobicity of MOFs are first introduced. The reported experimental methods for the preparation of hydrophobic MOFs are then categorized. The concept that hydrophobic MOFs normally synthesized from predesigned organic ligands can also be prepared by the postsynthetic modification of the internal pore surface and/or external crystal surface of hydrophilic or less hydrophobic MOFs is highlighted. Finally, an overview of the recent studies on hydrophobic MOFs for various applications is provided and suggests the high versatility of this unique class of materials for practical use as either adsorbents or nanomaterials. The structural design, preparation strategies, characterization methods, and potential applications of hydrophobic metal–organic frameworks (MOFs), a class of unique materials with both microporosity and hydrophobicity, are overviewed herein. It is highlighted that hydrophobic MOFs can be prepared by some facile procedures, and this type of materials can act as either advanced adsorbents or nanomaterials.

Electrochemical CO 2 reduction in acidic electrolytes is a promising strategy to achieve high utilization efficiency of CO 2 . Although alkali cations in acidic electrolytes play a vital role in suppressing hydrogen evolution and promoting CO 2 reduction, they also cause precipitation of bicarbonate on the gas diffusion electrode (GDE), flooding of electrolyte through the GDE, and drift of the electrolyte pH. In this work, we realize the electroreduction of CO 2 in a metal cation-free acidic electrolyte by covering the catalyst with cross-linked poly-diallyldimethylammonium chloride. This polyelectrolyte provides a high density of cationic sites immobilized on the surface of the catalyst, which suppresses the mass transport of H + and modulates the interfacial field strength. By adopting this strategy, the Faradaic efficiency (FE) of CO reaches 95 ± 3% with the Ag catalyst and the FE of formic acid reaches 76 ± 3% with the In catalyst in a 1.0 pH electrolyte in a flow cell. More importantly, with the metal cation-free acidic electrolyte the amount of electrolyte flooding through the GDE is decreased to 2.5 ± 0.6% of that with alkali cation-containing acidic electrolyte, and the FE of CO maintains above 80% over 36 h of operation at −200 mA·cm −2 . Alkali bicarbonate precipitation hinders electrochemical CO 2 reduction in acidic electrolytes. Here, the authors report CO 2 reduction in a metal cation-free acidic electrolyte by covering the catalyst with crosslinked polyelectrolyte, achieving 36-hour stability in a flow cell.

Production of ammonia is currently realized by the Haber–Bosch process, while electrochemical N 2 fixation under ambient conditions is recognized as a promising green substitution in the near future. A lack of efficient electrocatalysts remains the primary hurdle for the initiation of potential electrocatalytic synthesis of ammonia. For cheaper metals, such as copper, limited progress has been made to date. In this work, we boost the N 2 reduction reaction catalytic activity of Cu nanoparticles, which originally exhibited negligible N 2 reduction reaction activity, via a local electron depletion effect. The electron-deficient Cu nanoparticles are brought in a Schottky rectifying contact with a polyimide support which retards the hydrogen evolution reaction process in basic electrolytes and facilitates the electrochemical N 2 reduction reaction process under ambient aqueous conditions. This strategy of inducing electron deficiency provides new insight into the rational design of inexpensive N 2 reduction reaction catalysts with high selectivity and activity. Electrocatalytic nitrogen reduction is promising for ammonia production, but electrocatalysts are limited by low efficiency and high cost. Here, the authors report electron-deficient copper nanoparticles, induced by rectifying contact with polyimide, for selective reduction of nitrogen to ammonia.

Mortality rates due to lung cancer are high worldwide. Although PD‐1 and PD‐L1 immune checkpoint inhibitors boost the survival of patients with non‐small‐cell lung cancer (NSCLC), resistance often arises. The Warburg Effect, which causes lactate build‐up and potential lysine‐lactylation (Kla), links immune dysfunction to tumor metabolism. The role of non‐histone Kla in tumor immune microenvironment and immunotherapy remains to be clarified. Here, global lactylome profiling and metabolomic analyses of samples from patients with NSCLC is conducted. By combining multi‐omics analysis with in vitro and in vivo validation, that intracellular lactate promotes extracellular lipolysis through lactyl‐APOC2 is revealed. Mechanistically, lactate enhances APOC2 lactylation at K70, stabilizing it and resulting in FFA release, regulatory T cell accumulation, immunotherapy resistance, and metastasis. Moreover, the anti‐APOC2K70‐lac antibody that sensitized anti‐PD‐1 therapy in vivo is developed. This findings highlight the potential of anti lactyl‐APOC2‐K70 approach as a new combination therapy for sensitizing immunotherapeutic responses. Although PD‐1/PD‐L1 immune‐checkpoint inhibitors boost the survival of patients with NSCLC, resistance often arises. Combining global lactylome profiling, metabolomics and mechanistic‐experiments, it is found that intracellular lactate promotes extracellular lipolysis through lactyl‐APOC2‐K70, inducing Tregs accumulation and immunotherapy resistance. An anti‐APOC2K70‐lac antibody that sensitized anti‐PD‐1 therapy in vivo is developed. This findings suggest that targeting lactylated APOC2‐K70 could improve the effectiveness of immunotherapy.

The active sites of heterogeneous catalysts can be difficult to identify and understand, and, hence, the introduction of active sites into catalysts to tailor their function is challenging. During the past two decades, scaling relationships have been established for important heterogeneous catalytic reactions. More specifically, a physical or chemical property of the reaction system, termed as a reactivity descriptor, scales with another property often in a linear manner, which can describe and/or predict the catalytic performance. In this Review, we describe scaling relationships and reactivity descriptors for heterogeneous catalysis, including electronic descriptors represented by d -band theory, structural descriptors, which can be directly applied to catalyst design, and, ultimately, universal descriptors. The prediction of trends in catalytic performance using reactivity descriptors can enable the rational design of catalysts and the efficient screening of high-throughput catalysts. Finally, we outline methods to break scaling relationships and, hence, to break the constraint that active sites pose on the catalytic performance. Recently, scaling relationships have been established between certain physical or chemical properties of heterogeneous catalytic reactions. These properties, or reactivity descriptors, can describe and predict catalytic performance, and thus enable the rational design of new catalysts.

Low-cost, efficient catalyst high-throughput screening is crucial for future renewable energy technology. Interpretable machine learning is a powerful method for accelerating catalyst design by extracting physical meaning but faces huge challenges. This paper describes an interpretable descriptor model to unify activity and selectivity prediction for multiple electrocatalytic reactions (i.e., O 2 /CO 2 /N 2 reduction and O 2 evolution reactions), utilizing only easily accessible intrinsic properties. This descriptor, named ARSC, successfully decouples the atomic property (A), reactant (R), synergistic (S), and coordination effects (C) on the d -band shape of dual-atom sites, which is built upon our developed physically meaningful feature engineering and feature selection/sparsification (PFESS) method. Driven by this descriptor, we can rapidly locate optimal catalysts for various products instead of over 50,000 density functional theory calculations. The model’s universality has been validated by abundant reported works and subsequent experiments, where Co-Co/Ir-Qv3 are identified as optimal bifunctional oxygen reduction and evolution electrocatalysts. This work opens the avenue for intelligent catalyst design in high-dimensional systems linked with physical insights. Interpretable machine learning offers a powerful method for accelerating catalyst design. Here the authors report an interpretable descriptor model to unify activity and selectivity prediction for multiple electrocatalysis using only easily accessible intrinsic properties.

In this paper, we report that reversals of the large-scale circulation in two-dimensional Rayleigh–Bénard (RB) convection can be suppressed by imposing sinusoidally distributed heating to the bottom plate. We examine how the frequency of flow reversals depends on the dimensionless wavenumber $k$ of the spatial temperature modulation with various modulation amplitude $A$. For sufficiently large $k$, the flow reversal frequency is close to that in the standard RB convection under uniform heating. However, when $k$ decreases, the frequency of flow reversal gradually becomes lower and can even be largely reduced. Furthermore, we examine the growth of the corner roll and the global flow structure based on Fourier mode decomposition, and reveal that the size of the corner roll diminishes as the wavenumber decreases. The reason is that the regions occupied by the cold phase can absorb heat from the hot plumes and thus lower their temperature, which reduces the corner roll's kinetic energy input provided by the buoyancy force, and weakens the feeding process of the corner rolls. This results in the locking of the corner roll into a smaller region near the corner, making it harder for a reversal to occur. Using the concept of horizontal convection caused by non-uniform heating, we find a relevant parameter $k/A$ to describe briefly how the reversal frequency depends on wavenumber and modulation amplitude. The present work provides a new way to control the flow reversals in RB convection through modifying temperature boundary conditions.