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Poly(l-lactide) (PLLA) is a promising biodegradable alternative to petroleum-based plastics, but it exhibits slow crystallization kinetics. Understanding flow-induced crystallization under pressure (FICP) during practical polymer processing, such as injection molding, is important to tailor the crystallization and modulate the properties. Compared with the traditional “black-box” research on FICP, understanding the multistep FICP of PLLA during industrial-scale injection molding and the effect of external fields on crystallization viareal-time mode is crucial for revealing the underlying mechanism. This work first pays attention to the FICP process of PLLA during industrial-scale injection molding viaa homemade in situ investigation platform base-d on a highly brilliant synchrotron X-ray scattering. We find that an initial flash flow (shear time ∼0.1 s) with extremely intense flow (Weissenberg number Wi≫ 1) induces α/α′-form and β-form precursors in the PLLA melt, and subsequent crystallization around the oriented precursors occurs under quasi-isothermal and residual-pressure conditions. In particular, the elevated packing pressure observably promotes flow-induced oriented precursors and especially the β-form nucleates preferentially, while the segmental diffusion-dominant retardant crystal growth proceeds during the following quasi-isothermal crystallization. Being composed of thicker lamellae with a higher amount, the injection-molded PLLA bars under low pressure exhibit superior mechanical strength and thermomechanical performance. The outcome of this work points out that the pressure field is of great importance in flow-induced crystallization kinetics and the final crystalline morphology, which is valuable for guiding the development of a high-performance PLLA product and expanding its applications.

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Heterogeneous dual-atomic-site catalysts (DACs) hold great potential for diverse applications. However, to date, the synthesis of DACs primarily relies on different atoms freely colliding on the support during synthesis, principally leading to low yields. Herein, we report a general metal ion recognition (MIR) strategy for constructing a series of DACs, including but not limited to Fe1Sn1, Fe1Co1, Fe1Ni1, Fe1Cu1, Fe1Mn1, Co1Ni1, Co1Cu1, Co2, and Cu2. This strategy is achieved by coupling target inorganometallic cations and anions as ion pairs, which are sequentially adsorbed onto a nitrogen-doped carbon substrate as the precursor. Taking the oxygen reduction reaction as an example, we demonstrated that the Fe1Sn1-DAC synthesized through this strategy delivers a record peak power density of 1.218 W cm–2under 2.0 bar H2–O2conditions and enhanced stability compared to the single-atom-site FeN4. Further study revealed that the superior performance arises from the synergistic effect of Fe1Sn1dual vicinal sites, which effectively optimizes the adsorption of *OH and alleviates the troublesome Fenton-like reaction.

The analysis of 3D meshes with deep learning has become prevalent in computer graphics. As an essential structure, hierarchical representation is critical for mesh pooling in multiscale analysis. Existing clustering-based mesh hierarchy construction methods involve nonlinear discretization optimization operations, making them nondifferential and challenging to embed in other trainable networks for learning. Inspired by deep superpixel learning methods in image processing, we extend them from 2D images to 3D meshes by proposing a novel differentiable chart-based segmentation method named geodesic differential supervertex (GDSV). The key to the GDSV method is to ensure that the geodesic position updates are differentiable while satisfying the constraint that the renewed supervertices lie on the manifold surface. To this end, in addition to using the differential SLIC clustering algorithm to update the nonpositional features of the supervertices, a reparameterization trick, the Gumbel-Softmax trick, is employed to renew the geodesic positions of the supervertices. Therefore, the geodesic position update problem is converted into a linear matrix multiplication issue. The GDSV method can be an independent module for chart-based segmentation tasks. Meanwhile, it can be combined with the front-end feature learning network and the back-end task-specific network as a plug-in-plug-out module for training; and be applied to tasks such as shape classification, part segmentation, and 3D scene understanding. Experimental results show the excellent performance of our proposed algorithm on a range of datasets.

Garsorasib (D-1553; InventisBio, Shangai, China), a potent KRASG12Cinhibitor, has shown promising antitumour activity in patients with KRASG12C-mutated (ie, Gly12Cys) non-small-cell lung cancer (NSCLC) in a phase 1 study. We report results from a phase 2 study conducted to evaluate the efficacy and safety of garsorasib in patients with locally advanced or metastatic KRASG12C-mutated NSCLC.

Sine oculis homeobox homolog 1 (SIX1) is a new identified cancer driver in the development of prostate cancer (PC). However, the upstream regulatory mechanisms for SIX1 reactivation in cancer remains elusive. Here, we found that Ku70 robustly interacts with SIX1 in the nucleus of PC cells. The HD domain of SIX1 and the DBD domain of Ku70 are required for formation of Ku70-SIX1 complex. 20 groups of hydrogen bonds were identified in this complex by molecular dynamics simulation. Depletion of Ku70/SIX1 notably abrogates the proliferation and migration of PC. Further studies revealed that SIX1 is recruited to the promoter region on glutamate-pyruvate transaminase 2 (GPT2). Ku70 enhances the SIX1-mediated transcriptional activation on GPT2, thereby facilitating the generation of alpha-ketoglutarate (α-KG). In addition, formation of the Ku70-SIX1 complex promotes GPT2-dependent cell proliferation and migration in PC. Moreover, the expression of GPT2 is upregulated and strongly correlated with the expression of Ku70/SIX1 in PC tissues. In summary, our findings not only provide insight into the mechanistic interactions between Ku70 and SIX1, but also highlight the significance of the Ku70-SIX1-GPT2 axis for α-KG metabolism and PC carcinogenesis.

The development of catalysts with high NH3-selective catalytic reduction (SCR) activity in the presence of calcium (Ca) is urgently required for cement kiln flue gases at low-medium temperatures. Herein, a novel Ce–Mn/3DOM-m Ti–Zr (CMZT-3DOM-m) catalyst was synthesized for low-medium-temperature NH3-SCR. Over 90% NOxconversion can be obtained at 125–275 °C with over 95% N2selectivity, accompanied by the excellent wide-temperature NH3-SCR performance and superior resistance to Ca. Through scanning electron microscopy (SEM), Brunauer–Emmett–Teller (BET), X-ray diffraction (XRD), X-ray photoelectron spectra (XPS), temperature-programmed reduction with H2(H2-TPR), ammonia temperature-programmed desorption (NH3-TPD) and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) characterizations, the results demonstrated that Zr doping could effectively mitigate grain growth and enlarge the surface area of the CMZT-3DOM-m catalyst. Furthermore, the surface acidity, redox properties, concentration of surface Ce3+, Mn4+and chemisorbed oxygen were significantly improved. In situ DRIFTS experiments demonstrated that the adsorption and activation of NH3and NO are conducive to the excellent resistance to Ca poisoning. As a sacrificial site for Ca binding, Zr protected the active species, thereby enhancing the catalyst’s resistance to Ca poisoning and demonstrating excellent anti-Ca properties, which offered a novel approach to the design of catalysts for the prevention of Ca poisoning at low-medium temperatures.

• Achieving structural modulation of nickel hydroxide modified graphene composites through the secondary reaction mechanism between ammonium ions and nickel ions. • Applying analytical methods like TEM and XPS to elucidate the reaction process and identify the suitable amounts of reactants. • Achieving full coverage of the Ku-band with maximum effective absorption bandwidth through the design of dielectric parameters. • Combining electromagnetic parameter analysis and simulation calculations to elucidate the multiple loss mechanisms in the electromagnetic dissipation process. Carbon-based materials exhibit excellent dielectric absorption properties, among which graphene has received particular attention in research of electromagnetic wave absorbing materials because of its high electrical conductivity and unique large-area, thin-layer two-dimensional structural features. However, the electromagnetic absorption performance of the material is hindered from further improvement due to its single component composition. It is influenced by the conductive network of graphene, making it challenging to achieve a balance in impedance matching and electromagnetic loss, thereby restricting its broader application. To address these challenges, we developed a series of nickel hydroxide-modified graphene composites. Through a structural composite design, we optimized overall impedance matching, introduced diverse loss mechanisms to enhance electromagnetic loss performance, and utilized a secondary reaction control method to precisely regulate the deposition of nickel hydroxide on the graphene surface, thereby achieving regulate of the composite material's electromagnetic parameters within a defined range. Under low sample filling ratios and a thin sample thickness of 1.8 mm, the effective absorption bandwidth reaches 6.5 GHz, demonstrating excellent electromagnetic absorption performance. This study provides a controllable design approach for modulating material electromagnetic parameters by influencing the reaction process. It also offers a design method for composites with an outstanding electromagnetic loss mechanism. [ABSTRACT FROM AUTHOR]

The selective oxidation of benzyl alcohol to benzaldehyde is currently difficult to achieve with high benzyl alcohol conversion and high benzaldehyde selectivity simultaneously under mild conditions. Herein, the Fe-based catalysts anchored on nitrogen-doped carbon (x-Fe/NC) were prepared by thermal decomposition of the iron-doped zeolitic imidazolate framework precursors (x-Fe-ZIF). Among the various catalysts with different iron contents (x-Fe/NC), the 2-Fe/NC catalyst showed the best balance of conversion and selectivity, achieving 96.0% conversion of benzyl alcohol and around 98.0% selectivity for benzaldehyde. A range of characterization methods combined with kinetic analysis demonstrated that the high catalytic activity was attributed to the formed Fe–Nxactive sites, which can accelerate the adsorption process of reactant molecules, facilitating the oxidation process while minimizing overoxidation to carboxylic acids. Moreover, the 2-Fe/NC catalyst showed excellent recyclability and substrate resistance, indicating its stability and potential for industrial application. This study offers fresh perspectives on the synthesis of effective transition metal-based catalysts and explores their potential applications in organic oxidation reactions.

Herein, the NOxremoval capability of SCRF based on the Cu/SSZ-13 catalyst and its influencing factors were comprehensively explored. The reaction characteristics of important reactions in SCRF including SCR, fast SCR, NH3oxidation, etc. under different soot contents were studied under quasi-steady-state experimental conditions, as well as the influence of reactant conditions on soot regeneration. The results indicated the following: Cu/SSZ-13 SCRF achieves NOxconversion efficiency exceeding 90% at 250 °C, comparable to through-flow SCR. Fast SCR performance is over 20% better than that of standard SCR at 200 °C, while NO2–SCR shows the lowest NOxremoval. A significant amount of N2O is generated, with NH4NO3formation impeding the SCR reaction. An NO2/NOxratio of 0.4 enhances NOxremoval. To limit NH4NO3formation at low temperatures, an NH3/NOxratio of 0.8 or lower is advised below 200 °C; above this temperature, the ratio should exceed 1 due to strong ammonia oxidation. Soot loading hinders NOxremoval at 200–500 °C but enhances it above 500 °C. NH3-TPD, NH3-TPO, and N2O generation experiments indicate that NH3adsorption sites exist on soot, covering the Cu-based catalyst surface. Quasi-steady state SCR tests show that while the SCR reaction does not actively regenerate soot, it strongly inhibits passive regeneration. Under NO2intake, the level of CO2from passive regeneration at 300 °C increased by 175 ppm, indicating competition with NO2.

Metal–organic frameworks (MOFs) hold enormous promise for treating bacterial infections to circumvent the threat of antibiotic resistance. However, positioning MOFs on wound dressings is hindered and remains a significant challenge. Herein, a facile heterointerfacial engineering strategy was developed to tailor the “MOF armor” that adaptively weaponized the poly(ε-caprolactone) electrospun dressing with excellent bacteria-killing efficacy. Hydrophilic epitaxial crystallization to enhance the interfacial wettability is the key to induce the uniform seeding of Cu2+and thus to generate a compact MOF layer on the electrospun dressing. The universality of the proposed strategy was demonstrated by the construction of different kinds of MOFs (HKUST-1, ZIF-8, and ZIF-67) on variously shaped substrates (nanofibers, pellets, plates, and 3D-printed porous scaffolds). By optimizing the Cu2+loading, the Cu-MOF armor exhibited sustained ion release behavior, strong antibacterial activity, and good biocompatibility. In vivorat model revealed that the Cu-MOF armor significantly promoted infected wound healing by inhibiting inflammatory factors, promoting collagen deposition, and angiogenesis. This unique MOF armor provides an appealing and effective solution for designing and fabricating advanced wound dressings.

Controlled high-order clustering of cell-surface proteins is an essential but unmatched regulatory mechanism in living systems for the modulation of cell behavior. Here, we present a strategy for generating extended and tunable one-dimensional clusters of death receptors on live cell surfaces by employing synthetic peptides to noncovalently bridging the proteins. The on-cell assembly process is validated through super-resolution fluorescence imaging and fluorescence lifetime imaging analyses. By adjusting the number of spacing peptides between the receptors before and even after the cluster formation, receptor separation can be precisely varied at nanoscale to drive cells into apoptotic or antiapoptotic states. Remarkably, this approach results in higher levels of cell apoptosis compared to the conventional practice of using preformed ligand-appended peptide coassemblies. These results demonstrate that in situfabrication of cell-interfacing materials with compositional control permits robust and effective manipulation of high-order clustering of cell-surface proteins, advancing our ability to regulate cell behavior.

Utilizing diverse organic crosslinkers for cyclization has proven to be an effective approach to creating peptide libraries, enabling the rapid discovery of functional peptides. Existing crosslinkers usually provide a tiny and flexible molecular scaffold to constrain peptide conformations, leading to larger cyclic peptides retaining a high degree of flexibility. Moreover, the limited structural impact of the crosslinkers undermines the feasibility of diversifying cyclic peptide structures by varying the types of crosslinker scaffolds. These limitations hamper the robustness of various cyclic peptide libraries for ligands and drug discovery and development. Herein, we present a unique crosslinker featuring a bulky and rigid biphenyl-dihydrothiazole (BDT) scaffold for the rapid and biocompatible cyclization of linear peptides. This scaffold was used to construct phage display BDT-cyclic peptide libraries, enabling the effective identification of cyclic peptide binders with low-nanomolar binding affinity toward BCL-XL, a protein target with potential for cancer therapy. Thus, this study introduces a novel method for constructing cyclic peptide libraries with rigidly constrained and diverse structures, offering a promising avenue for the de novodiscovery of cyclic peptide ligands and drugs.

Ultra-high performance concrete (UHPC) has gained a lot of attention lately because of its remarkable properties, even if its high cost and high carbon emissions run counter to the current development trend. To lower the cost and carbon emissions of UHPC, this study develops a multi-objective optimization framework that combines the non-dominated sorting genetic algorithm and 6 different machine learning methods to handle this issue. The key features of UHPC are filtered using the recursive feature elimination approach, and Bayesian optimization and random grid search are employed to optimize the hyperparameters of the machine learning prediction model. The optimal mix ratios of UHPC are found by applying the multi-objective algorithm non-dominated sorting genetic algorithm-III and multi-objective evolutionary algorithm based on adaptive geometric estimation. The results are evaluated by technique for order preference by similarity to ideal solution and validated by experiments. The outcomes demonstrate that the compressive strength and slump flow of UHPC are correctly predicted by the machine learning models. The multi-objective optimization produces Pareto fronts, which illustrate the trade-off between the mix’s compressive strength, slump flow, cost, and environmental sustainability as well as the wide variety of possible solutions. The research contributes to the development of cost-effective and environmentally sustainable UHPC, and aids in robust, intelligent, and sustainable building practices.

The computational modeling of fracture in solids using damage mechanics faces challenges with complex crack topology. This can be addressed by using a variational framework to reformulate the damage mechanics. In this paper, we propose several mathematically elegant variational damage models (VDMs) for fracture mechanics without explicitly using damage variables. Based on the energy density ϕ, the fracture energy density is formulated as ϕ^=ϕ(1+ℓϕ/Gc)and the damage variable is expressed as s = ϕ/(ϕ + Gc/ℓ), which satisfy ϕ^∣ϕ→∞=Gc/ℓand s∣ϕ→∞= 1 as ϕapproaches infinity. These limits demonstrate that the new energy density converges to the Griffith energy release rate at full-damage state. The VDM profoundly modified the energy functional, implicitly incorporating the damage field. As a generalization of previous model, we propose a family of VDMs of varying orders. Additionally, we develop a multi-damage model to account for different types of energy densities, such as elastic thin plate and gradient elasticity. Using this functional, it is straightforward to deduce the governing equation for automatically evolving fractures. These formulations can be employed in conventional finite element method or other numerical methods with minimal modifications. Compared to the phase field method with the same mesh density, a sharper crack interface can be achieved. We demonstrate the capabilities of the proposed variational damage formulations using representative numerical examples.

Switched systems, as an exceptional modeling tool, may face threats to unexpected variations from the environment (e.g., external disturbances) or unreliable networks (e.g., desired controllers lagged to enabled subsystems or even controller disconnection). This article aims to study the robust model predictive control problem for a class of disturbed asynchronously switched systems with occasional controller disconnection. To mitigate the adverse effect of additive disturbances, a tube-based switched model predictive control strategy is designed by properly tightening original constraints. For the feasibility concern, the minimum mode-dependent dwell time is computed offline so as to ensure that reachable sets from an initial region are included in a common feasible set. Furthermore, a nonconservative stability condition is proposed for switched systems from a set-theoretic perspective. Based on this superior result, two stability strategies with distinct converging speeds are proposed to guarantee the closed-loop system to be uniformly asymptotically stable with constructed terminal constraints. Effectiveness of the theoretical results is validated via a simulation of time-varying communication networks.

Deformable image registration is one of the essential processes in analyzing medical images. In particular, when diagnosing abdominal diseases such as hepatic cancer and lymphoma, multi-domain images scanned from different modalities or different imaging protocols are often used. However, they are not aligned due to scanning times, patient breathing, movement, etc. Although recent learning-based approaches can provide deformations in real-time with high performance, multi-domain abdominal image registration using deep learning is still challenging since the images in different domains have different characteristics such as image contrast and intensity ranges. To address this, this paper proposes a novel unsupervised multi-domain image registration framework using neural optimal transport, dubbed OTMorph. When moving and fixed volumes are given as input, a transport module of our proposed model learns the optimal transport plan to map data distributions from the moving to the fixed volumes and estimates a domain-transported volume. Subsequently, a registration module taking the transported volume can effectively estimate the deformation field, leading to deformation performance improvement. Experimental results on multi-domain image registration using multi-modality and multi-parametric abdominal medical images demonstrate that the proposed method provides superior deformable registration via the domain-transported image that alleviates the domain gap between the input images. Also, we attain the improvement even on out-of-distribution data, which indicates the superior generalizability of our model for the registration of various medical images. Our source code is available at https://github.com/boahK/OTMorph.

Glecirasib (JAB-21822) is a new covalent oral KRAS-G12C inhibitor. This multicenter, single-arm phase 2b study assessed the efficacy and safety of glecirasib administered orally at 800 mg daily in patients with locally advanced or metastatic KRASG12C-mutated nonsmall-cell lung cancer. The primary endpoint was the objective response rate (ORR) assessed by an independent review committee (IRC). Between 15 September 2022 and 28 September 2023, 119 patients with a median age of 62 years were enrolled. As of the data cut-off date on 28 March 2024, the ORR assessed by IRC was 47.9% (56/117; 95% confidence interval: 38.5–57.3%). The incidence of treatment-related adverse events (TRAEs) of any grade was 97.5% (116/119). The incidence of grades 3 and 4 TRAEs was 38.7% (46/119). A total of 5.0% (6/119) of patients discontinued the treatment due to TRAEs. No treatment-related deaths occurred. Glecirasib exhibited promising clinical efficacy and manageable safety profiles in these patient populations. ClinicalTrials.gov identifier: NCT05009329.

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Autophagy is the process of reusing the body's senescent and damaged cell components, which can be regarded as the cellular circulatory system. There are 3 distinct forms of autophagy: macroautophagy, microautophagy, and chaperone-mediated autophagy. In the heart, autophagy is regulated mainly through mitophagy because of the metabolic changes of cardiomyocytes caused by ischemia and hypoxia. Myocardial remodeling is characterized by gradual heart enlargement, cardiac dysfunction, and extraordinary molecular changes. Cardiac remodeling after myocardial infarction is almost inevitable, which is the leading cause of heart failure. Autophagy has a protective effect on myocardial remodeling improvement. Autophagy can minimize cardiac remodeling by preventing misfolded protein accumulation and oxidative stress. This review summarizes the nestest molecular mechanisms of autophagy and myocardial remodeling, the protective effects, and the new target of autophagy medicine in cardiac remodeling. The future development and challenges of autophagy in heart disease are also summarized.

The transcription factor STAT3 is a promising target for the treatment of non-small cell lung cancer (NSCLC). STAT3 activity is mainly dependent on phosphorylation at tyrosine 705 (pSTAT3-Y705), but the modulation on pSTAT3-Y705 is elusive. By screening a library of deubiquitinases (Dubs), we found that the Otub1 increases STAT3 transcriptional activity. As a Dub, Otub1 binds to pSTAT3-Y705 and specifically abolishes its K48-linked ubiquitination, therefore preventing its degradation and promoting NSCLC cell survival. The Otub1/pSTAT3-Y705 axis could be a potential target for the treatment of NSCLC. To explore this concept, we screen libraries of FDA-approved drugs and natural products based on STAT3-recognition element-driven luciferase assay, from which crizotinib is found to block pSTAT3-Y705 deubiquitination and promotes its degradation. Different from its known action to induce ALK positive NSCLC cell apoptosis, crizotinib suppresses ALK-intact NSCLC cell proliferation and colony formation but not apoptosis. Furthermore, crizotinib also suppresses NSCLC xenograft growth in mice. Taken together, these findings identify Otub1 as the first deubiquitinase of pSTAT3-Y705 and provide that the Otub1/pSTAT3-Y705 axis is a promising target for the treatment of NSCLC.

The traditional method for achieving misalignment tolerance using two detuned circuits depends on output sampling and communication between the primary and secondary sides. This article proposes a self-adaptive dual-channel detuned compensation topology to achieve a stable output for wireless charging of autonomous underwater vehicles (AUVs). In the low coupling coefficient interval, power is transferred through both channels; in the high coupling coefficient interval, power is transferred through only one channel. The mode switching process occurs naturally without additional switches or control. Two sets of arc-shaped coils are employed as the two channels, forming dual arc-shaped coil sets, without cross-coupling between them. Due to the symmetrical magnetic couplers, the mutual inductances of the two channels respond similarly to both rotational and axial misalignment. A 1.6-kW experimental prototype for the AUV wireless charging is built to validate the feasibility of the proposal. The output voltage fluctuation of the system is 8% within the coupling coefficient interval of [0.2, 0.6]. The system can still maintain over 89% transmission efficiency in the worst case.

Purpose: The pollution of soil with antibiotic resistance genes (ARGs) has become a significant concern. Biochar based fertilizer, as an effective soil amendment, can enhance soil fertility. However, the mechanisms underlying the effects of biochar based fertilizer on soil microbial community succession and ARGs remain unclear. Methods: Therefore, this study investigate the effect of two levels of swine manure biochar (SMB) addition on the soil microbial community and the distribution of antibiotic resistance genes (ARGs), using high-throughput qPCR, along with 16 S rRNA and ITS sequencing techniques. Results: The results indicated that SMB had no significant effects on the bacterial species diversity and species uniformity, but it significantly increased the soil fungal species diversity and species uniformity, such as Basidiomycota, Chytridiomycota, Mortierellomycota, Olpidiomycota, Monoblepharomycota, and Glomeromycota. Adding SMB decreased the abundance of ARGs and mobile genetic elements (MGEs), and adding 2% SMB inhibited ARGs better than 1% SMB. Actinobacteriota, MBNT15, Bacteroidota, and Nitrospirota were identified as potential phylum level hosts of ARGs because these bacteria were significantly positively correlated with ARGs and MGEs (p< 0.05). The correlations among the potential bacterial hosts of ARGs and fungal communities indicated that the influence of SMB on the soil fungal community structure indirectly affected the distribution of potential bacterial hosts of ARGs. Conclusion: In general, the application of biochar based fertilizer can control the transfer and spread of ARGs. The results obtained in this study provide theoretical support for applying SMB to fertilize soil and remediate pollution by ARGs.

Liver cirrhosis is prognostically associated with poor life expectancy owing to subsequent liver failure. Thus, understanding liver regeneration processes during cirrhotic injury is highly important. This study explored the role of macrophage heterogeneity in liver regeneration following splenectomy. We collected detailed clinical information from 54 patients with decompensated cirrhosis before and after splenectomy. Obvious liver regeneration was observed after splenectomy in cirrhotic patients. Single-cell RNA sequencing (scRNA-seq) was performed on three paired liver tissues from patients before and after surgery to explore the immune microenvironment map and the characteristics of liver regeneration-associated macrophages (RAMs). scRNA-seq analysis revealed that the composition of hepatic immune cells changed after splenectomy; among these changes, the proportion of CD300E+RAMs significantly increased after surgery, and high expression levels of functional genes associated with cell proliferation promoted liver regeneration. Moreover, a mouse model of carbon tetrachloride-induced cirrhosis and a coculture system consisting of primary bone marrow-derived macrophages and hepatocytes were established for validation. We observed a similar phenomenon of liver regeneration in cirrhotic mice and further confirmed that CD300E+monocyte-derived macrophages facilitated hepatocyte NAD+synthesis via the secretion of NAMPT, which subsequently promoted hepatocyte proliferation. This study characterized the hepatic immune microenvironment in patients with cirrhosis following splenectomy. Our findings demonstrated that CD300E+macrophages play a crucial role in remodeling the hepatic immune microenvironment after splenectomy, thereby promoting liver regeneration in patients with decompensated cirrhosis. CD300E+macrophages are anticipated to emerge as a novel therapeutic strategy for the treatment of liver cirrhosis.

In RGB-D semantic segmentation for indoor scenes, a key challenge is effectively integrating the rich color information from RGB images with the spatial distance information from depth images. However, most existing methods overlook the inherent differences in how RGB and depth images express information. Properly distinguishing the processing of RGB and depth images is essential to fully exploiting their unique and significant characteristics. To address this, we propose a novel heterogeneous dual-branch framework called HDBFormer, specifically designed to handle these modality differences. For RGB images, which contain rich detail, we employ both a basic and detail encoder to extract local and global features. For the simpler depth images, we propose LDFormer, a lightweight hierarchical encoder that efficiently extracts depth features with fewer parameters. Additionally, we introduce the Modality Information Interaction Module (MIIM), which combines transformers with large kernel convolutions to interact global and local information across modalities efficiently. Extensive experiments show that HDBFormer achieves state-of-the-art performance on the NYUDepthv2 and SUN-RGBD datasets.

AbstractA fire accident is one typical postulated accident in a nuclear fuel cycling facility. Safety-related data on a combustible fire are necessary to evaluate the safety of nuclear fuel cycling facilities under fire accident conditions quantitatively. Accurate and reliable data should be obtained by performing some demonstration tests.This study deals with the ignition and combustion characteristics of solvent involved at a nuclear fuel cycling facility and the fire behavior during a solvent fire. Small-scale and large-scale tests were conducted at the China Institute for Radiation Protection. The minimum ignition energy of the solvent under different temperatures was obtained. The test data were used to judge the possibility that the organic solvent ignited by a spark. Parameters such as combustion rate, smoke gas, aerosol release of solvent combustion, temperature distribution, and pressure change in the solvent fire cell were also obtained. The test results can be used as conservative estimates of the amount of aerosol release during a solvent fire. The experimental data also can be used to develop preventive and mitigation measures for solvent fire accidents. This paper puts forward information based on the experimental data and the recent international study.

AbstractIn industry, many highly reliable products possess multiple performance characteristics (PCs) and they typically degrade simultaneously. When such PCs are governed by a common failure mechanism or influenced by a shared operating environmental condition, interdependence between these PCs arises. To model such dependence, this article proposes a novel multivariate reparameterized inverse Gaussian (rIG) process model. It utilizes an additive structure; that is, the degradation of each marginal PC is considered as the result of the sum of two independent rIG processes, with one capturing the shared common effects across all PCs and the other describing the intrinsic randomness specific to that PC. The model has some nice statistical properties, and the system lifetime distribution can be conveniently approximated. An expectation-maximization algorithm is proposed for estimating the model parameters, and a parametric bootstrap method is designed to derive the confidence intervals. Comprehensive numerical simulations are conducted to validate the performance of the inference method. Two case studies are thoroughly investigated to demonstrate the applicability of the proposed methodology. Supplementary materialsfor this article are available online.

Under the background of China's "double carbon" goal, coal mining must become a systematic project that takes into account both economic strategy and environmental protection strategy. The destruction of groundwater artesian field caused by the development of overburden failure caused by large-scale coal mining activities is aggravating the ecological vulnerability of mining areas in China. In this paper, the high precision integrated prediction of the development height of overburden failure zone (HOF) under multiple sedimentary conditions is studied for the first time in a large regional background. In order to adapt to the complexity and disorder of geological source data, we optimize the ensemble learning process and meta-model training. Then, by coupling the data-driven model and the simulation-driven model, a dual-driven model is obtained which can automatically reduce the noise of abnormal bands that do not comply with the laws of physical geology. The results show that the D-S dual drive model has excellent stability and net income performance, which can effectively predict the development and termination height of HOF, ensure the safety of coal mining activities, and provide a reference for the isolation control of water and coal pollution in a wide area.

Ageing is associated with a decline in the number and fitness of adult stem cells1,2. Ageing-associated loss of stemness is posited to suppress tumorigenesis3,4, but this hypothesis has not been tested in vivo. Here we use physiologically aged autochthonous genetically engineered5,6mouse models and primary cells5,6to demonstrate that ageing suppresses lung cancer initiation and progression by degrading the stemness of the alveolar cell of origin. This phenotype is underpinned by the ageing-associated induction of the transcription factor NUPR1 and its downstream target lipocalin-2 in the cell of origin in mice and humans, which leads to functional iron insufficiency in the aged cells. Genetic inactivation of the NUPR1–lipocalin-2 axis or iron supplementation rescues stemness and promotes the tumorigenic potential of aged alveolar cells. Conversely, targeting the NUPR1–lipocalin-2 axis is detrimental to young alveolar cells through ferroptosis induction. Ageing-associated DNA hypomethylation at specific enhancer sites is associated with increased NUPR1 expression, which is recapitulated in young alveolar cells through DNA methylation inhibition. We uncover that ageing drives functional iron insufficiency that leads to loss of stemness and tumorigenesis but promotes resistance to ferroptosis. These findings have implications for the therapeutic modulation of cellular iron homeostasis in regenerative medicine and in cancer prevention. Furthermore, our findings are consistent with a model whereby most human cancers initiate at a young age, thereby highlighting the importance of directing cancer prevention efforts towards young individuals.

TiAl alloy, renowned for its high temperature resistance while maintaining lightweight properties, serves as a crucial structural material for hot-end components. However, the widespread application of additive manufacturing (AM) for TiAl alloys is constrained by their limited ductility. To enable the engineering-scale production of TiAl alloys with enhanced strength and ductility, this study introduces advancements in the heat source, material composition, and deposition processes. The characteristics of the cold-cathode electron beam heat source were used to manufacture low-cost in-situ alloyed TiAl alloys through wire-fed electron beam additive manufacturing. Mo, Zr, and Si elements were introduced into the TiAl alloy, and precise thermal control allowed the separated twin wires to simultaneously form a stable co-molten pool, and the specimens with good appearance and no internal microcracks and pores were obtained. Furthermore, a detailed comparison between Ti48Al alloy and Ti48Al1Mo0.45Zr0.3Si alloy was carried out, focusing on aspects such as grain morphology, chemical composition homogeneity, phase constitution, and mechanical properties. The influence of dual-wire synergistic control on process stability, microstructure evolution, and strengthening mechanisms was discussed. The results show that the cold-cathode electron beam heat source under low vacuum and the co-molten pool mode reduce aluminum evaporation and promote element mixing through layer-by-layer temperature control and remelting. Compared to the lamellar microstructure of Ti48Al alloy, the Ti48Al1Mo0.45Zr0.3Si alloy exhibits a dual-γ phase microstructure, consisting of fine lamellar colonies and equiaxed γ grains. This modification led to a 90% and 150% increase in elongation at room temperature and 650 °C, respectively. These findings offer important insights into enhancing the performance of TiAl alloys through cost-effective alloying strategies.

With the increasing application numbers of radio frequency identification (RFID) multitags in recent years, the position distribution of RFID multitag has a significant impact on the reading performance of RFID system. The poor reading performance of RFID multitag will lead to the loss of important information stored in the tags. In this article, a novel synergistic topology graph construction strategy using graph attention transformer network (STGC-GATN) method is proposed to predict the reading performance of RFID multitag so as to optimize the RFID tags’ position distribution. First, considering increasingly complex electromagnetic environment, computer vision approach is involved to design and construct the RFID multitag reading performance analysis system. Then, scale-invariant SURF image matching method is adopted to effectively and accurately measure the multitags’ 3-D positions. After that, addressing the complex topology structure presented by the RFID multitag, a novel STGC-GATN method is proposed to construct the nonlinear relationship between the RFID multitag’s 3-D positions and corresponding reading distance. The proposed synergistic topology graph construction (STGC) strategy makes up for the insensitivity of graph attention transformer network (GATN) model to similar topology structures by fusing multiple distance functions, which can effectively improve the prediction accuracy of the reading distance of RFID multitag system. A large number of experiments are conducted to verify the effectiveness of the proposed methods. The experimental results show that compared with other benchmarks, the proposed STGC-GATN model can effectively forecast the reading distance of RFID multitag. The mean absolute error (MAE), mean absolute percent error (MAPE), root mean square error (RMSE), and $R^{2}$ of the prediction results of STGC-GATN are 0.0307, 1.96%, 0.0383, and 0.9898, respectively. By analyzing the predicted reading distance and the topology structure, the optimal multitag 3-D position structure can be found. The found optimal structure of RFID multitag can guide the position distribution of multitag so as to improve the reading performance of RFID system.

A novel anode with a homogeneous and dense structure was developed by n-butanol (BAT) additive. This H-Zn anode displayed modulated Zn2+-solvation structure, increased nucleation overpotential, therefore reducing the critical nucleation radius and promoting uniform Zn deposition.

Rice cultivation is one of the major anthropogenic methane sources in China and globally. However, accurately quantifying regional rice methane emissions is often challenging due to highly heterogeneous emission fluxes and limited measurement data. This study attempts to address this issue by quantifying regional methane emissions from rice cultivation with a high-resolution inversion of satellite methane observations from the Tropospheric Monitoring Instrument (TROPOMI). We apply the method to the largest rice-producing province (Heilongjiang) in China for 2021. Our satellite-based estimation finds a rice methane emission of 0.85 (0.69–1.03) Tg a–1from the province or an average emission factor of 22.0 (17.8–26.6) g m–2a–1when normalized by rice paddy areas. The satellite-based analysis reveals a 2 to 4 times lower bias in widely used global and national inventories, which lack up-to-date regional information. The inversion reduces the uncertainty of regional rice emissions by 73% relative to bottom-up estimates based on field flux measurements. The satellite inversion also shows that the highest rice methane emissions occur in June during the tillering stage of rice, decreasing toward ripening, indicating that the predominant water management practice in the region involves drainage and intermittent flooding after initial flooding. Process-based modeling further suggests that this practice can lead to a reduction of methane emissions by more than 50% compared to continuous flooding of rice paddies and natural wetlands.

ABSTRACTInteractions between double-stranded RNA (dsRNA) and proteins play an important role in cellular homeostasis by regulating the editing, stability, and splicing of intracellular RNA. The identification of dsRNA-binding proteins (dsRBPs) is key; however, it has long been challenging to purify dsRBPs from cells. In this study, we developed a novel method, dsRBPC (dsRNA-binding protein capture), to purify cellular dsRBPs based on classic phase separation purification procedures. A global dsRNA-binding proteome of LLC-PK1 cells was obtained, and we identified 1326 dsRBPs, including 1303 putative novel dsRBPs. Functional analyses suggested that these enriched dsRBPs are mainly associated with rRNA processing, RNA splicing, transcriptional regulation, and nucleocytoplasmic transport. We also found that the ARM (armadillo/beta-catenin-like repeats) motif is a previously unknown dsRNA-binding domain, as demonstrated by biochemical experiments. Collectively, this study provides a useful approach for dsRBP identification and the discovery of a global dsRNA-binding proteome to comprehensively map the dsRNA – protein interaction network.

ABSTRACTMost, if not all organisms exhibit robust rhythmicity of their biological functions, allowing a perpetual adaptation to external clues within the daily 24 hours-cycle. Studies on circadian rhythm regulation primarily focused on transcriptional level, considering mRNA levels to represent the primary determinant of oscillations of intracellular protein levels. However, a plethora of emerging evidence suggests that post-transcriptional regulation, particularly rhythmic mRNA translation, is not solely reliant on the oscillation of transcription. Instead, the circadian regulation of mRNA translation plays a critical role as well. A comprehensive understanding of these mechanisms underlying rhythmic translation and its regulation should bridge the gap in rhythm regulation beyond RNA fluctuations in research, and greatly enhance our comprehension of rhythm generation and maintenance. In this review, we summarize the major mechanisms of circadian regulation of translation, including regulation of translation initiation, elongation, and the alteration in rhythmic translation to external stresses, such as endoplasmic reticulum (ER) stress and ageing. We also illuminate the complex interplay between phase separation and mRNA translation. Together, we have summarized various facets of mRNA translation in circadian regulation, to set on forthcoming studies into the intricate regulatory mechanisms underpinning circadian rhythms and their implications for associated disorders.

Aims/BackgroundPulmonary hypertension (PH) is a severe progressive disease characterized by elevated blood pressure in the lungs. Medications are a critical form of treatment for patients with PH. This study aims to explore the experiences of patients with PH undergoing polypharmacy, thereby providing a more concrete foundation for formulating targeted intervention measures.MethodsA purposive sampling method was used to select 13 PH patients treated in a grade III hospital in Zhejiang Province from December 2023 to February 2024 as the research subjects. This study is a descriptive qualitative research design, where the patients were interviewed face-to-face in a semi-structured manner. The data were analyzed, summarized and extracted using the traditional content analysis method.ResultsThere were five themes and ten sub-themes surrounding the polypharmacy experiences of the PH patients: (1) Negative emotional experience of multidrug use, including lack of disease-related medication knowledge and insufficient ability to obtain medication information; (2) Complex physical testing of multiple drugs, including adverse reactions and complex dose titration; (3) Economic burden; (4) Coping difficulties, including insufficient drug safety, excessive reliance on medical personnel, and lack of opportunities for deep participation; (5) Desire for supports, including professional and social support, as well as those from family, colleagues and classmates.ConclusionDisease, treatment, psychological factors, and social customs affect PH patients’ drug use post-diagnosis, with varying experiences and degrees. Healthcare providers must offer tailored care and practical strategies for managing multiple drug use, considering patients’ unique experiences and needs.

Aims/BackgroundThe prevalence of postpartum fatigue among primipara is high in China, which seriously affects women’s subsequent physical and mental recovery. In order to deeply understand this phenomenon, domestic scholars began to conduct research on postpartum fatigue from the aspects of assessment tools and intervention measures. This study aims to investigate postpartum fatigue in primiparous women and its association with family functioning and social support, providing valuable insights for improving the condition in this population.MethodsPrimiparous women from February 2023 to March 2024 were selected as participants. Baseline demographic information was collected, and postpartum fatigue levels were assessed using Postpartum Fatigue Scale (PFS) at 7 days postpartum. Social support was evaluated with Postpartum Social Support Scale, and maternal role adaptation was assessed using Maternal Role Adaptation Questionnaire (MRAQ). Pearson correlation analysis was conducted to examine the relationship between postpartum fatigue levels, role adaptation, and social support.ResultsA total of 210 survey questionnaires were distributed; following which, 201 valid questionnaires were received. The total PFS score was 13.93 ± 4.53 points. Among the participants, 50 cases (24.87%) experienced no fatigue, 58 cases (28.86%) with mild fatigue, 78 cases (38.81%) with moderate fatigue, and 15 cases (7.46%) with severe fatigue. There were statistically significant differences in all dimensions and total scores of the Postpartum Social Support Level Scale for primiparas with different levels of postpartum fatigue (p< 0.001), with those facing severe fatigue reporting significantly lower level of social support. There were statistically significant differences in the comparison of each dimension and total score of the role adaptation scale for primiparas with different levels of postpartum fatigue (p< 0.001). The degree of role adaptation in patients with severe fatigue was significantly lower. The PFS score of primiparas was negatively correlated with the level of social support and role adaptation (r = –0.693, r = –0.735, p< 0.001).ConclusionThe majority of primiparous women experience varying degrees of postpartum fatigue at 7 days postpartum. Poor newborn health, artificial feeding, and nighttime feeding frequency ≥4 times per night can exacerbate postpartum fatigue. Good social support and role adaptation are beneficial in alleviating postpartum fatigue. Strengthening social support and role adaptation can help reduce postpartum fatigue levels in primiparous women.

The Jahn–Teller (JT) effect, as a spontaneous symmetry-breaking mechanism arising from the coupling between electronic and nuclear degrees of freedom, is a widespread phenomenon in molecular and condensed matter systems. Here, we investigate the influence of the JT effect on the photodissociation dynamics of CF3I molecules. Based on ab initio calculation, we obtain the three-dimensional potential energy surfaces for 3Q0+and 1Q1states and establish a diabatic Hamiltonian model to study the wavepacket dynamics in the CF3I photodissociation process. Using the wave function of the final state after dissociation, we calculate the rotational density matrix of the CF3fragment and analyze its rotational excitation under the JT effect, as well as its partial coherence property and selection rules. Our work paves the way to the experimental observation and quantification of the JT effect in molecular dissociation dynamics beyond the classical ball-and-stick model.

Predicting the properties for unseen materials exclusively on the basis of the chemical formula before synthesis and characterization has advantages for research and resource planning. This can be achieved using suitable structure-free encoding and machine learning methods, but additional processing decisions are required. In this study, we compare a variety of structure-free materials encodings and machine learning algorithms to predict the structure/property relationships of battery materials. It was found that the physical units used to measure the property labels have an important impact on the predictive ability of the models, regardless of the computational approach. Property labels with respect to weight give excellent performance, but property labels with respect to volume cannot be predicted with confidence using only chemical information, even when the underlying physical characteristics are the same. These results contrast with previous studies of unsupervised learning and classification, where structure-free encoding excelled, and highlight how the structural features or property labels of materials are represented plays an important role in the predictive ability of machine learning models.

Monitoring acetylcholinesterase (AChE) activity and its inhibitor is crucial yet challenging for the early diagnosis and treatment of neurological diseases. In this study, we present Au nanoparticle decorated CoAl layered double hydroxide monolayer (Au@CoAl-LDH-m) as a peroxidase-like (POD) nanozyme for the sensitive colorimetric detection of AChE and its inhibitor, thiamine pyrophosphate (TPP). Remarkably, the Au@CoAl-LDH-m nanozyme can catalyze the oxidation of chromogenic substrates through its POD-like activity, which is effectively inhibited by thiocholine (TCh, a catalytic product of AChE), thereby enabling detection of AChE and TPP through a visible colorimetric readout. The approach provides a highly sensitive and specificity assay with a broader linear response range (1–100 mU mL–1for AChE and 1–1000 ng mL–1for TPP) and a low detection limit (0.092 mU mL–1for AChE and 0.201 ng mL–1for TPP), respectively. These results highlight the significant potential of Au@CoAl-LDH-m for advancing colorimetric sensors in detecting small molecules across various biological applications.

Herein, the effects of support and the deposition-precipitation method on the Ru-based catalysts for NH3decomposition were studied. The results of the performance test, characterization, and DFT simulation show that the activity order of the catalysts with different supports is 5% Ru/MgO > 5% Ru/Al2O3> 5% Ru/Pr2O3> 5% Ru/La2O3. Ru/MgO exhibits the best ammonia decomposition performance (T80≈ 480 °C), because its suitable pore structure is conducive to ammonia adsorption, and abundant strong alkaline sites produce a strong metal–support interaction. The ammonia decomposition performance of 5% Ru/MgO (DP) prepared by the deposition-precipitation method is much higher than that of 5% Ru/MgO (IM) prepared by the impregnation method (T80decreases from 480 to 440 °C). On Ru/MgO (DP), the distribution of Ru particles is more uniform and the particle size is relatively consistent, and the Ru/MgO (DP) has more basic sites and a more reasonable ratio of lattice oxygen to defect oxygen. Calculated by DFT, the energy barrier of the first dehydrogenation of NH3and the combined desorption of N is 1.31 and 1.51 eV, respectively, and the latter is the rate-determining step of the ammonia decomposition reaction in Ru/MgO.

Aflatoxin B1 (AFB1) is one of the most toxic mycotoxins in food and feed, seriously jeopardizing the intestinal health, while the effects of AFB1 on intestinal damage remain to be well understood. This study aims to evaluate the effect of AFB1 on intestinal injury by regulating AMP-activated protein kinase (AMPK)-mediated pyroptosis in vitro. The present study showed that AFB1 led to the formation of large number of bubble-like protrusions on the cell membrane, releasing lactate dehydrogenase (LDH) and interleukin-1β (IL-1β). Stimulation with AFB1 resulted in the activation of the NOD-like receptor protein 3 (NLRP3) pathway, as indicated by the increased expression of pyroptosis-associated factor mRNAs and proteins, which ultimately led to a significant upregulation of the pyroptosis rate. Meanwhile, AFB1 caused dysfunction of mitochondrial dynamics by activating the AMPK signaling pathway as mainly evidenced by upregulating dynamin-1-like protein 1 (Drp1) mRNA and protein expression. Moreover, inhibition of NLRP3 and AMPK pathways by MCC950 and compound C, respectively, significantly alleviated AFB1-induced damage in IPEC-J2 cells, evidenced by suppressed NLRP3-mediated pyroptosis, and ameliorated AMPK-mediated mitochondrial dynamics imbalance. In conclusion, these results demonstrated that AFB1 promoted pyroptosis of IPEC-J2 cells by interfering with mitochondrial dynamics by activating the AMPK/NRLP3 pathway.

• The grain size of multidirectional rotary forged (MRF) Al7075 sheets after T6 heat treatment exhibited near-parabolic evolution. • The abnormal grain growth mechanism in MRF20 %+T6 condition and fine grain inheriting mechanism in MRF70 %+T6 condition are investigated. • The strength-plasticity collaborative improvement is achieved of multidirectional rotary forged Al7075 sheets during T6 heat treatment. • The strength-plasticity collaborative improvement mechanism is discussed based on experimental data and crystal plasticity simulation. Al7075 sheets are widely used in aerospace industry and their higher strength-plasticity collaborative improvement requirement is urgent. In this study, the microstructure inheriting the evolution and mechanical properties of Al7075 sheets during multidirectional rotary forging (MRF) and T6 heat treatment are analyzed. The results show that the average grain size exhibits near-parabolic evolution with increasing MRF deformation amount. MRF20 %+T6 (20 % MRF deformation amount+T6) condition possesses the largest grain size of 72.6 μm, and its abnormal grain growth mechanism is that the medium deformation energy and high deformation heterogeneity in MRF20 % deformed grains could cause asynchronous recrystallization behavior during T6 heat treatment, and the grains with comparatively higher deformation energy get recrystallized firstly and devour adjacent grains along preferred 〈011〉 or 〈223〉 misorientation axis. MRF70 %+T6 condition possesses the finest grain size of 14.2 μm, and its fine grain inheriting mechanism is that the uniformly high deformation energy in MRF70 % deformed grains causes uniformly rapid recrystallization, and rapidly recrystallized grains effectively suppress grain boundary motion from adjacent grains. With increasing MRF deformation amount, tensile strength and elongation values both exhibit near-antiparabolic evolution. MRF70 %+T6 condition possesses the largest tensile strength (563 MPa) and elongation (17.73 %), which increases by 8.27 % and 80.55 % compared to as-annealed+T6 (MRF0 %+T6) condition (tensile strength is 520 MPa and elongation is 9.82 %), respectively. The strength-plasticity collaborative improvement is mainly because the combination of effectively inherited fine grains, refined inclusion particles, and uniformly distributed fine η' particles after T6 heat treatment could promote smooth dislocation movement and coordinated slip behavior in most matrix grains, which contributes to the delay of stress localization and strength-plasticity collaborative improvement. [ABSTRACT FROM AUTHOR]

• 2D Co(OH) 2 /Ti 3 C 2 (OH) x MXene composites with rapid reconstruction and self-healing behaviors are proposed as efficient and stable electrocatalysts during HzOR process. • The introduction of Ti 3 C 2 (OH) x MXene can significantly reduce the conductivity and hydrophilicity of the composite, and increase the intrinsic HzOR activity of the catalyst. • Co(OH)O/Ti 3 C 2 (OH) x MXene composites with metal-like conductivity not only present spontaneous adsorption capacity of N 2 H 4 , but also can modulate rate-determining step of dehydrogenation of *N 2 H 4 to *N 2 H 3. • The electrophilic oxygen of Co(OH)O/Ti 3 C 2 (OH) x can spontaneously obtain electrons and protons from N 2 H 4 , achieving the oxidation of N 2 H 4 while reducing Co(OH)O to Co(OH) 2 , thus completing the self-healing of the efficient catalyst. The development of efficient hydrazine oxidation reaction (HzOR) catalysts is important for the construction of remarkable energy storage and conversion systems. However, after a period of electrochemical reaction, the active site of the catalyst will be irreversibly reduced or inactivated, and how to recover the active site is a major challenge. Here, we report 2D Co(OH) 2 /Ti 3 C 2 (OH) x MXene composites with rapid reconstruction and self-healing behaviors as efficient and stable electrocatalysts during HzOR process. Both experimental and theoretical results indicate that the introduction of Ti 3 C 2 (OH) x MXene can effectively reduce the dehydrogenation barrier of Co(OH) 2 , from 0.584 eV to 0.481 eV to form the real catalytic active center Co(OH)O. Subsequently, Co(OH)O/Ti 3 C 2 (OH) x MXene composites with metal-like conductivity not only present spontaneous adsorption capacity of N 2 H 4 , but also can modulated rate-determining step of dehydrogenation of *N 2 H 4 to *N 2 H 3 (0.54 eV) compared with Co(OH)O. Finally, the electrophilic oxygen of Co(OH)O/Ti 3 C 2 (OH) x can spontaneously obtain electrons and protons from N 2 H 4 , achieving the oxidation of N 2 H 4 while reducing Co(OH)O to Co(OH) 2 , thus completing the self-healing of the efficient catalyst. Co(OH) 2 -coated Ti 3 C 2 (OH) x composites have been fabricated for electrocatalytic HzOR process. The addition of Ti 3 C 2 (OH) x can not only reduce the energy barrier of structural reconstruction, but also optimize the adsorption energy of the RDS at the active sites and finally improving the electrocatalytic performance, synchronously realize the oxidation of N 2 H 4 and the self-healing of the catalyst. [Display omitted] [ABSTRACT FROM AUTHOR]

The light-addressable electrochemical sensor (LAES) is a powerful tool for single-cell imaging due to its label-free and probe-free advantages. In this work, we report a photocurrent polarity-switchable LAES using a single-phase photoelectrode of a BiFeO3thin film for living cell imaging. The proposed BiFeO3could show both p- and n-type photocurrent behavior by simply altering the external bias voltage. LAES imaging of the same individual MCF-7 cells was performed in anodic and cathodic modes. Decreases in both photocurrents were observed due to the hindering effect of the adherent cells on local photoinduced Faraday currents. Furthermore, the dynamic photocurrent changes on cells after trypsin treatment were imaged and studied at anode and cathode polarities. Both polarities showed an increase in local photocurrents on cells as the cell–substrate junction weakened, and this change displayed heterogeneous characteristics. This is the first time that LAES cell imaging was achieved in a p-type mode. Meanwhile, our photocurrent polarity-switchable imaging approach overcomes the limitations of conventional photoelectrodes, which have been confined to single-polarity operation. We believe this work has the potential to significantly broaden the application scope of LAES in single-cell visualization and analysis, offering great insights into cellular behavior and function.