Inorganic Electrolyte Additive Promoting the Interfacial Stability for Durable Zn-Ion Batteries.

The development of Zn-ion batteries (ZIBs) is always hindered by the ruleless interface reactions between the solid electrode and liquid electrolyte, and seeking appropriate electrolyte additives is considered as a valid approach to stabilize the electrode/electrolyte interphases for high-performance ZIBs. Benefiting from the unique solubility of TiOSO4 in acidic solution, the composite electrolyte of 2 m ZnSO4+30 mm TiOSO4 (ZSO/TSO) is configured and its positive contribution to Zn//Zn cells, Zn//Cu cells, and Zn//NH4V4O10 batteries are comprehensively investigated by electrochemical tests and theoretical calculations. Based on the theoretical calculations, the introduction of TiOSO4 contributes to facilitating the desolvation kinetics of Zn2+ ions and guarantees the stable interface reactions of both zinc anode and NH4V4O10 cathode. As expected, Zn//Zn cells keep long-term cycling behavior for 3750 h under the test condition of 1 mA cm-2-1 mAh cm-2, Zn//Cu cells deliver high Coulombic efficiency of 99.9% for 1000 cycles under the test condition of 5 mA cm-2-1 mAh cm-2, and Zn//NH4V4O10 batteries maintain reversible specific capacity of 193.8 mAh g-1 after 1700 cycles at 5 A g-1 in ZSO/TSO electrolyte. These satisfactory results manifest that TiOSO4 additive holds great potential to improve the performances of ZIBs.

Alcohol promotes hepatocyte injury via ER stress sensor XBP1s mediated regulation of autophagy and lysosomal activity.

OBJECTIVE: Endoplasmic reticulum stress (ERS) plays an important role in the development of Alcoholic liver injury (ALI), but the exact mechanism needs further exploration. This study aims to investigate the role of ERS-XBP1s in ALI, and providing new target for the treatment of liver injury. METHOD: The ALI model was constructed using the NIAAA method and was validated by several methods. ERS was detected using western-blot, RT-PCR and immunohistochemistry. Apoptosis was measured by TUNEL staining, Hoechst staining, western-blot and Annexin V-FITC. Lysosomal function and autophagy were measured by Lyso-Tracker Green probe, western-blot and immunofluorescence, respectively. RESULTS: The ALI model was successfully constructed as demonstrated by increased liver steatosis, inflammation and oxidative stress, and higher levels of serum ALT, AST and TG. Alcohol significantly increased the expression of ERS-related molecules, such as PERK, IRE1α, GRP78 and XBP1s, and promoted the nuclear translocation of XBP1s. Moreover, alcohol significantly increased apoptosis and inhibition of XBP1s could reverse this effect in vivo and in vitro. Interestingly, we found that alcohol significantly elevated hepatocyte LC3-II/I levels and concomitantly accumulation of P62, and this phenomenon was reversed by inhibiting XBP1s both in vivo and in vitro. Mechanistically, we found that alcohol activation of ER stress sensor XBP1s which promoted liver injury via inhibiting lysosomal function and autophagy activity in hepatocytes, whereas inhibition of XBP1s reduces hepatocyte apoptosis by restoring lysosomal activity and activating of autophagy. CONCLUSION: Alcohol promotes hepatocytes injury via ER stress sensor XBP1s mediated inhibition of autophagy. Therefore, inhibition of XBP1 may protect the liver from alcohol-induced damage.

Individualized medication of venetoclax based on therapeutic drug monitoring in Chinese acute myeloid leukemia patients using an HPLC method.

OBJECTIVE: The aim of this study was to establish a simple and sensitive high-performance liquid chromatography method for therapeutic drug monitoring of venetoclax (VEN) and optimize regimens. METHODS: The analysis required the extraction of a 50 µl plasma sample and the precipitation of proteins using acetonitrile extraction. The chromatographic method employed a mobile phase of acetonitrile: 0.5% KH 2 PO 4 (pH 3.5) (60/40, v/v) on a Diamond C 18 (4.6 mm × 250 mm, 5 µm) column at a flow rate of 1.0 ml/min. The quantitative method was validated based on standards described in 'Bioanalytical Method Validation: Guidance for Industry' published by the US Food and Drug Administration (FDA). RESULTS: The calibration curve was linear ( R2  = 0.9998) over the range of 75-4800 ng/ml, with limits of quantification of 25 ng/ml. The coefficients of intraday and interday validation, specificity, recovery, and stability all met the criteria of FDA guidance. The method was successfully applied to analyze VEN concentrations in 30 cases of acute myeloid leukemia patients. The peak concentration ( Cmax ) was 1881.19 ±â€…756.61 ng/ml, while the trough concentration ( Cmin ) was 1212.69 ±â€…767.92 ng/ml in acute myeloid leukemia patients. CONCLUSION: Our study establishes a simple, precise, and sensitive high-performance liquid chromatography method for monitoring VEN and confirms its applicability for therapeutic drug monitoring of VEN in hematological cancers.

Precise Synthesis of Dual-single-atom Electrocatalysts through Pre-coordination-directed in situ Confinement for CO2 Reduction.

Dual-single-atom catalysts (DSACs) are the next paradigm shift in single-atom catalysts because of the enhanced performance brought about by the synergistic effects between adjacent bimetallic pairs. However, there are few methods for synthesizing DSACs with precise bimetallic structures. Herein, a pre-coordination strategy is proposed to precisely synthesize a library of DSACs. This strategy ensures the selective and effective coordination of two metals via phthalocyanines with specific coordination sites, such as -F- and -OH-. Subsequently, in-situ confinement inhibits the migration of metal pairs during high-temperature pyrolysis, and obtains the DSACs with precisely constructed metal pairs. Despite changing synthetic parameters, including transition metal centers, metal pairs, and spatial geometry, the products exhibit similar atomic metal pairs dispersion properties, demonstrating the universality of the strategy. The pre-coordination strategy synthesized DSACs shows significant CO2 reduction reaction performance in both flow-cell and practical rechargeable Zn-CO2 batteries. This work not only provides new insights into the precise synthesis of DSACs, but also offers guidelines for the accelerated discovery of efficient catalysts.

Simultaneous Inhibition of Vanadium Dissolution and Zinc Dendrites by Mineral-Derived Solid-State Electrolyte for High-Performance Zinc Metal Batteries.

Designing solid electrolyte is deemed as an effective approach to suppress the side reaction of zinc anode and active material dissolution of cathodes in liquid electrolytes for zinc metal batteries (ZMBs). Herein, kaolin is comprehensively investigated as raw material to prepare solid electrolyte (KL-Zn) for ZMBs. As demonstrated, KL-Zn electrolyte is an excellent electronic insulator and zinc ionic conductor, which presents wide voltage window of 2.73 V, high ionic conductivity of 5.08 mS cm-1, and high Zn2+ transference number of 0.79. For the Zn//Zn cells, superior cyclic stability lasting for 2200 h can be achieved at 0.2 mA cm-2. For the Zn//NH4V4O10 batteries, stable capacity of 245.8 mAh g-1 can be maintained at 0.2 A g-1 after 200 cycles along with high retention ratio of 81%, manifesting KL-Zn electrolyte contributes to stabilize the crystal structure of NH4V4O10 cathode. These satisfying performances can be attributed to the enlarged interlayer spacing, zinc (de)solvation-free mechanism and fast diffusion kinetics of KL-Zn electrolyte, availably guaranteeing uniform zinc deposition for zinc anode and reversible zinc (de)intercalation for NH4V4O10 cathode. Additionally, this work also verifies the application possibility of KL-Zn electrolyte for Zn//MnO2 batteries and Zn//I2 batteries, suggesting the universality of mineral-based solid electrolyte.

Non-Fermi-Liquid Behavior from Cavity Electromagnetic Vacuum Fluctuations at the Superradiant Transition.

We study two-dimensional materials where electrons are coupled to the vacuum electromagnetic field of a cavity. We show that, at the onset of the superradiant phase transition towards a macroscopic photon occupation of the cavity, the critical electromagnetic fluctuations, consisting of photons strongly overdamped by their interaction with electrons, can in turn lead to the absence of electronic quasiparticles. Since transverse photons couple to the electronic current, the appearance of non-Fermi-Liquid behavior strongly depends on the lattice. In particular, we find that in a square lattice the phase space for electron-photon scattering is reduced in such a way to preserve the quasiparticles, while in a honeycomb lattice the latter are removed due to a nonanalytical frequency dependence of the damping ∝|ω|^{2/3}. Standard cavity probes could allow us to measure the characteristic frequency spectrum of the overdamped critical electromagnetic modes responsible for the non-Fermi-liquid behavior.

Mid-long wavelength infrared absorptance of hyperdoped silicon via femtosecond laser microstructuring.

Hyperdoped silicon (hSi) fabricated via femtosecond laser irradiation has emerged as a promising photoelectric material with strong broadband infrared (IR) absorption. In this work, we measured the optical absorptance of the hSi in the wavelength of 0.3-16.7 µm. Unlike the near to mid wavelength IR absorption, the mid-long wavelength IR (M-LWIR) absorption is heavily dependent on the surface morphology and the dopants. Furthermore, calculations based on coherent potential approximation (CPA) reveal the origin of free carrier absorption, which plays an important role in the M-LWIR absorption. As a result, a more comprehensive picture of the IR absorption mechanism is drawn for the optoelectronic applications of the hSi.

Local Spatial-Temporal Matching Method for Space-Based Infrared Aerial Target Detection.

The feature of a space-based infrared signal is that the intensity of clutter is much stronger than that of an aerial target. Such a feature poses a great challenge to aerial target detection since the existing infrared target detection methods are prone to enhance clutter but ignore the real target, which results in missed detection and false alarms. To tackle the challenge, we propose a concise method based on local spatial-temporal matching (LSM). Specifically, LSM mainly consists of local normalization, local direction matching, spatial-temporal joint model, and inverse matching. Local normalization aims to enhance the target to the same strength as the clutter, so that the weak target will not be ignored. After normalization, a direction-matching step is applied to estimate the moving direction of the background between the basic frame and referenced frame. Then the spatial-temporal joint model is constructed to enhance the target and suppress strong clutter. Similarly, inverse matching is conducted to further enhance the target. Finally, a salience map is obtained, on which the aerial target is extracted by the adaptive threshold segmentation. Experiments conducted on four space-based infrared datasets indicate that LSM handles the above challenge and outperforms seven state-of-the-art methods in space-based infrared aerial target detection.

A Dynamic Imaging Simulation Method of Infrared Aero-Optical Effect Based on Continuously Varying Gaussian Superposition Model.

Aero-optical effect correction has become a crucial issue in airborne infrared imaging. However, it is impractical to test the correction algorithm using flight tests and numerical simulation because of its high cost. This study proposes a dynamic imaging simulation method for the infrared aero-optical effect based on a continuously varying Gaussian superposition model. The influence of infrared image degradation under different high-speed aerodynamic flow fields was investigated in detail. A continuously varying Gaussian superposition model was established for flight speed, altitude, and attitude. A dynamic infrared scene simulation model was constructed. Experimental results show that the proposed method can realistically simulate actual aero-optical effects of any flight case. Moreover, it can simulate continuous frames of aerodynamically degraded infrared images. The method uses a simpler model than numerical simulation and provides more data for multitype tasks.

Robust PMBM Filter with Unknown Detection Probability Based on Feature Estimation.

This paper provides a solution for multi-target tracking with unknown detection probability. For the standard Poisson Multi-Bernoulli Mixture (PMBM) filter, the detection probability is generally considered a priori. However, affected by sensors, the features used for detection, and other environmental factors, the detection probability is time-varying and unknown in most multi-target tracking scenarios. Therefore, the standard PMBM filter is not feasible in practical scenarios. In order to overcome these practical restrictions, we improve the PMBM filter with unknown detection probability using the feature used for detection. Specifically, the feature is modeled as an inverse gamma distribution and the target kinematic state is modeled as a Gaussian distribution; the feature is integrated into the target kinematic state to iteratively estimate the target detection probability with the motion state. Our experimental results show that the proposed method outperforms the standard PMBM filter and the robust PMBM filter based on Beta distribution in the scenarios with unknown and time-varying detection probability. Further, we apply the proposed filter to a simulated infrared image to confirm the effectiveness and robustness of the filter.

Low-SNR Infrared Point Target Detection and Tracking via Saliency-Guided Double-Stage Particle Filter.

Low signal-to-noise ratio (SNR) infrared point target detection and tracking is crucial to study regarding infrared remote sensing. In the low-SNR images, the intensive noise will submerge targets. In this letter, a saliency-guided double-stage particle filter (SGDS-PF) formed by the searching particle filter (PF) and tracking PF is proposed to detect and track targets. Before the searching PF, to suppress noise and enhance targets, the single-frame and multi-frame target accumulation methods are introduced. Besides, the likelihood estimation filter and image block segmentation are proposed to extract the likelihood saliency and obtain proper proposal density. Guided by this proposal density, the searching PF detects potential targets efficiently. Then, with the result of the searching PF, the tracking PF is adopted to track and confirm the potential targets. Finally, the path of the real targets will be output. Compared with the existing methods, the SGDS-PF optimizes the proposal density for low-SNR images. Using a few accurate particles, the searching PF detects potential targets quickly and accurately. In addition, initialized by the searching PF, the tracking PF can keep tracking targets using very few particles even under intensive noise. Furthermore, the parameters have been selected appropriately through experiments. Extensive experimental results show that the SGDS-PF has an outstanding performance in tracking precision, tracking reliability, and time consumption. The SGDS-PF outperforms the other advanced methods.

Parameter Design and Performance Evaluation of a Large-Swath and High-Resolution Space Camera.

A rotary-scan space camera with an area sensor can achieve large width and high-resolution imaging. Designing system parameters properly is important for the application of the rotary-scan space camera. We model the swath, resolution, and overlap rate between frames for such a camera. An optimum algorithm combining the linear weighting method and the Monte Carlo method for system parameter design is proposed based on the model. Then, the performance of the designed system is evaluated using the grid point method. The designed systems can achieve swaths of more than 1000 km and less than 1 m resolution without leakage during the imaging. In the evaluation, the designed system can cover 82.13% of the observation region at the height of 500 km in 6.5 min, and the average repeated observation frequency is 3.26 times per 118 s. The design method is simple and effective in the initial design of the rotary-scan space camera's system parameters. The system designed can provide "no-leakage and wide coverage by quick scan" and "high-frequency repeated observation over a long visibility period." This will greatly improve earth observation ability in wide-area search and rescue missions.

Understanding the improvement mechanism of plasma etching treatment on oxygen reduction reaction catalysts.

Plasma etching treatment is an effective strategy to improve the electrocatalytic activity, but the improvement mechanism is still unclear. In this work, a nitrogen-doped carbon nanotube-encased iron nanoparticles (Fe@NCNT) catalyst is synthesized as the model catalyst, followed by plasma etching treatment with different parameters. The electrocatalytic activity improvement mechanism of the plasma etching treatment is revealed by combining the physicochemical characterizations and electrochemical results. As a result, highly active metal-nitrogen species introduced by nitrogen plasma etching treatment are recognized as the main contribution to the improved electrocatalytic activity, and the defects induced by plasma etching treatment also contribute to the improvement of the electrocatalytic activity. In addition, the prepared catalyst also demonstrates superior ORR activity and stability than the commercial Pt/C catalyst.

Regulating Au coverage for the direct oxidation of methane to methanol.

The direct oxidation of methane to methanol under mild conditions is challenging owing to its inadequate activity and low selectivity. A key objective is improving the selective oxidation of the first carbon-hydrogen bond of methane, while inhibiting the oxidation of the remaining carbon-hydrogen bonds to ensure high yield and selectivity of methanol. Here we design ultrathin PdxAuy nanosheets and revealed a volcano-type relationship between the binding strength of hydroxyl radical on the catalyst surface and catalytic performance using experimental and density functional theory results. Our investigations indicate a trade-off relationship between the reaction-triggering and reaction-conversion steps in the reaction process. The optimized Pd3Au1 nanosheets exhibits a methanol production rate of 147.8 millimoles per gram of Pd per hour, with a selectivity of 98% at 70 °C, representing one of the most efficient catalysts for the direct oxidation of methane to methanol.

Mullite Mineral-Derived Robust Solid Electrolyte Enables Polyiodide Shuttle-Free Zinc-Iodine Batteries.

Zinc dendrite, active iodine dissolution, and polyiodide shuttle caused by the strong interaction between liquid electrolyte and solid electrode are the chief culprits for the capacity attenuation of aqueous zinc-iodine batteries (ZIBs). Herein, mullite is adopted as raw material to prepare Zn-based solid-state electrolyte (Zn-ML) for ZIBs through zinc ion exchange strategy. Owing to the merits of low electronic conductivity, low zinc diffusion energy barrier, and strong polyiodide adsorption capability, Zn-ML electrolyte can effectively isolate the redox reactions of zinc anode and AC@I2 cathode, guide the reversible zinc deposition behavior, and inhibit the active iodine dissolution as well as polyiodide shuttle during cycling process. As expected, wide operating voltage window of 2.7 V (vs Zn2+/Zn), high Zn2+ transference number of 0.51, and low activation energy barrier of 29.7 kJ mol-1 can be achieved for the solid-state Zn//Zn cells. Meanwhile, high reversible capacity of 127.4 and 107.6 mAh g-1 can be maintained at 0.5 and 1 A g-1 after 3 000 and 2 100 cycles for the solid-state Zn//AC@I2 batteries, corresponding to high-capacity retention ratio of 85.2% and 80.7%, respectively. This study will inspire the development of mineral-derived solid electrolyte, and facilitate its application in Zn-based secondary batteries.

siRNA-loaded folic acid-modified TPGS alleviate MASH via targeting ER stress sensor XBP1 and reprogramming macrophages.

Macrophages show high plasticity and play a vital role in the progression of metabolic dysfunction-associated steatohepatitis (MASH). X-box binding protein 1 (XBP1), a key sensor of the unfolded protein response, can modulate macrophage-mediated pro-inflammatory responses in the pathogenesis of MASH. However, how XBP1 influences macrophage plasticity and promotes MASH progression remains unclear. Herein, we formulated an Xbp1 siRNA delivery system based on folic acid modified D-α-tocopheryl polyethylene glycol 1000 succinate nanoparticles (FT@XBP1) to explore the precise role of macrophage-specific Xbp1 deficiency in the progression of MASH. FT@XBP1 was specifically internalized into hepatic macrophages and subsequently inhibited the expression of spliced XBP1 both in vitro and in vivo. It promoted M1-phenotype macrophage repolarization to M2 macrophages, reduced the release of pro-inflammatory factors, and alleviated hepatic steatosis, liver injury, and fibrosis in mice with fat-, fructose- and cholesterol-rich diet-induced MASH. Mechanistically, FT@XBP1 promoted macrophage polarization toward the M2 phenotype and enhanced the release of exosomes that could inhibit the activation of hepatic stellate cells. A promising macrophage-targeted siRNA delivery system was revealed to pave a promising strategy in the treatment of MASH.

An artificial intelligence model for detecting pathological lymph node metastasis in prostate cancer using whole slide images: a retrospective, multicentre, diagnostic study.

Background: The pathological examination of lymph node metastasis (LNM) is crucial for treating prostate cancer (PCa). However, the limitations with naked-eye detection and pathologist workload contribute to a high missed-diagnosis rate for nodal micrometastasis. We aimed to develop an artificial intelligence (AI)-based, time-efficient, and high-precision PCa LNM detector (ProCaLNMD) and evaluate its clinical application value. Methods: In this multicentre, retrospective, diagnostic study, consecutive patients with PCa who underwent radical prostatectomy and pelvic lymph node dissection at five centres between Sep 2, 2013 and Apr 28, 2023 were included, and histopathological slides of resected lymph nodes were collected and digitised as whole-slide images for model development and validation. ProCaLNMD was trained at a dataset from a single centre (the Sun Yat-sen Memorial Hospital of Sun Yat-sen University [SYSMH]), and externally validated in the other four centres. A bladder cancer dataset from SYSMH was used to further validate ProCaLNMD, and an additional validation (human-AI comparison and collaboration study) containing consecutive patients with PCa from SYSMH was implemented to evaluate the application value of integrating ProCaLNMD into the clinical workflow. The primary endpoint was the area under the receiver operating characteristic curve (AUROC) of ProCaLNMD. In addition, the performance measures for pathologists with ProCaLNMD assistance was also assessed. Findings: In total, 8225 slides from 1297 patients with PCa were collected and digitised. Overall, 8158 slides (18,761 lymph nodes) from 1297 patients with PCa (median age 68 years [interquartile range 64-73]; 331 [26%] with LNM) were used to train and validate ProCaLNMD. The AUROC of ProCaLNMD ranged from 0.975 (95% confidence interval 0.953-0.998) to 0.992 (0.982-1.000) in the training and validation datasets, with sensitivities > 0.955 and specificities > 0.921. ProCaLNMD also demonstrated an AUROC of 0.979 in the cross-cancer dataset. ProCaLNMD use triggered true reclassification in 43 (4.3%) slides in which micrometastatic tumour regions were initially missed by pathologists, thereby correcting 28 (8.5%) missed-diagnosed cases of previous routine pathological reports. In the human-AI comparison and collaboration study, the sensitivity of ProCaLNMD (0.983 [0.908-1.000]) surpassed that of two junior pathologists (0.862 [0.746-0.939], P = 0.023; 0.879 [0.767-0.950], P = 0.041) by 10-12% and showed no difference to that of two senior pathologists (both 0.983 [0.908-1.000], both P > 0.99). Furthermore, ProCaLNMD significantly boosted the diagnostic sensitivity of two junior pathologists (both P = 0.041) to the level of senior pathologists (both P > 0.99), and substantially reduced the four pathologists' slide reviewing time (-31%, P < 0.0001; -34%, P < 0.0001; -29%, P < 0.0001; and -27%, P = 0.00031). Interpretation: ProCaLNMD demonstrated high diagnostic capabilities for identifying LNM in prostate cancer, reducing the likelihood of missed diagnoses by pathologists and decreasing the slide reviewing time, highlighting its potential for clinical application. Funding: National Natural Science Foundation of China, the Science and Technology Planning Project of Guangdong Province, the National Key Research and Development Programme of China, the Guangdong Provincial Clinical Research Centre for Urological Diseases, and the Science and Technology Projects in Guangzhou.

Understanding the Bifunctional Trends of Fe-Based Binary Single-Atom Catalysts.

Binary single-atom catalysts (BSACs) have demonstrated fascinating activities compared to single atom catalysts (SACs) for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Notably, Fe SACs is one of the most promising ORR electrocatalysts, and further revealing the synergistic effects between Fe and other 3d transition metals (M) for FeM BSACs are very important to enhance bifunctional performance. Herein, density functional theory (DFT) calculations are first adapted to demonstrate the role of various transition metals on the bifunctional activity of Fe sites, and a notable volcano relationship is established through the generally accepted adsorption free energy that ΔG* OH for ORR, and ΔG* O -ΔG* OH for OER, respectively. Further, ten of the atomically dispersed FeM anchored on nitrogen-carbon support (FeM-NC) are successfully synthesized with typical atomic dispersion by a facile movable type printing method. The experimental data confirms the bifunctional activity diversity of FeM-NC between the early- and late- transition metals, agrees very well with the DFT results. More importantly, the optimal FeCu-NC shows the expected performance with high ORR and OER activity, thereby, the assembled rechargeable zinc-air battery delivers a high power density of 231 mW cm-2 , and an impressive stability that can be stably operated over 300 h.

Nanoparticles alleviate non-alcoholic steatohepatitis via ER stress sensor-mediated intestinal barrier damage and gut dysbiosis.

Introduction: The gut microbiota plays an important role in the development of non-alcoholic steatohepatitis (NASH), but the underlying mechanism is unclear. It has been found that the transcription factor XBP1s plays an important role in regulating inflammation and lipid metabolism and maintaining the integrity of intestinal barrier. However, whether XBP1s modulates the development of NASH by regulating the integrity of the intestinal barrier and altering the composition of the gut microbiota remains unknown. Methods: Mice fed with a fat-, fructose-, cholesterol-rich (FFC) diet for 24 weeks successfully established the NASH model, as demonstrated by significant hepatic steatosis, inflammation, hepatocyte injury and fibrosis. The profile of gut microbiota dynamically changed with the different stages of NAFLD via 16S rDNA sequencing the feces from mice fed with FFC diet for 0, 12, or 24 weeks or NASH mice treated with siRNA-loaded folic acid-modified TPGS (hereafter named FT@XBP1). Results: NASH mice had significantly higher abundance of Firmicutes, Blautia and Bacteroides, and lower abundance of Bifidobacterium and GCA-900066575. FT@XBP1 supplementation had a significantly attenuated effect on FFC diet-induced weight gain, hepatic fat accumulation, dyslipidemia, inflammatory cytokines, ER stress and fibrosis. In particularly, FT@XBP1 modulates the composition of the intestinal flora; for example, NASH mice demonstrated higher abundance of Blautia and Bacteroides, and lower abundance of Actinobacteriota, Muribaculaceae and Bifidobacterium, which were partially restored by FT@XBP1 treatment. Mechanistically, FT@XBP1 increased the expression of ZO-1 in the intestine and had the potential to restore intestinal barrier integrity and improve antimicrobial defense to alleviate enterogenic endotoxemia and activation of inflammatory signaling pathways. Discussion: Regulation of the key transcription factor XBP1s can partially restore the intestinal microbiota structure, maintain the integrity of intestinal mucosal barrier, and prevent the progression of NASH, providing new evidence for treating NASH.

Multimetallic Single-Atom Catalysts for Bifunctional Oxygen Electrocatalysis.

Multimetallic alloys have demonstrated promising performance for the application of metal-air batteries, while it remains a challenge to design multimetallic single-atom catalysts (MM-SACs). Herein, metal-C3N4 and nitrogen-doped carbon are employed as cornerstones to synthesize MM-SACs by a general two-step method, and the inherent features of atomic dispersion and the strong electronic reciprocity between the multimetallic sites have been verified. The trimetallic FeCoZn-SACs and quatermetallic FeCoCuZn-SACs are both found to deliver superior oxygen evolution reaction and oxygen reduction reaction activity, respectively, as well as outstanding bifunctional durability. Density functional theory calculations elucidate the crucial contribution of Co sites of FeCoCuZn-SACs to the efficient catalysis of both the ORR and the OER. More importantly, Zn-air batteries with FeCoCuZn-SACs as cathodic catalysts exhibit a high power density (252 mW cm-2), high specific capacity (817 mAh gZn-1), and considerable stability (over 225 h) for charging-discharging processes. This work provides a visual perspective for the advantages of MM-SACs toward oxygen electrocatalysis.