Functional Liver Imaging Score Derived from Gadoxetic Acid-enhanced MRI Predicts Cachexia and Prognosis in Hepatocellular Carcinoma Patients.

OBJECTIVE: Cachexia occurs in approximately half of hepatocellular carcinoma (HCC) patients as the disease progresses and is correlated with a poor prognosis. Therefore, early identification of HCC patients at risk of developing cachexia and their prognosis is crucial. This study investigated the functional liver imaging score (FLIS) derived from gadoxetic acid-enhanced magnetic resonance imaging (MRI) to identify cachexia in HCC patients and their prognosis. METHODS: Pretreatment clinical and MRI data from 339 HCC patients who underwent gadoxetic acid-enhanced MRI scans were retrospectively collected. Patient weights were recorded for 6 months following the MRI scan to diagnose cachexia. The FLIS was calculated as the sum of the enhancement quality score, the excretion quality score, and the portal vein sign quality score. A Cox proportional hazards model was used to determine the significant factors affecting overall survival (OS). Multivariable logistic regression was then conducted to identify variables predicting cachexia in HCC patients, which were subsequently used to predict OS. RESULTS: Cox regression analysis revealed a significant association between cachexia and worse OS. Both FLIS (0-4 vs. 5-6 points) (OR, 9.20; 95% CI: 4.68-18.10; P<0.001) and α-fetoprotein >100 ng/mL (OR, 4.08; 95% CI: 2.13-7.83; P<0.001) emerged as significant predictors of cachexia in patients with HCC. Furthermore, FLIS (0-4 vs. 5-6 points) (HR, 1.73; 95% CI: 1.19-2.51; P=0.004) was significantly associated with OS. Patients in the FLIS 0-4 points group had shorter OS than those in the FLIS 5-6 points group [20 months (95% CI, 14.7-25.3) vs. 43 months (95% CI, 27.7-58.3); P=0.001]. CONCLUSION: Cachexia was associated with worse OS. The functional liver imaging score emerged as a significant predictor of cachexia in HCC patients and their prognosis.

High-Entropy Materials for Application: Electricity, Magnetism, and Optics.

High-entropy materials (HEMs) have recently emerged as a prominent research focus in materials science, gaining considerable attention because of their complex composition and exceptional properties. These materials typically comprise five or more elements mixed approximately in equal atomic ratios. The resultant high-entropy effects, lattice distortions, slow diffusion, and cocktail effects contribute to their unique physical, chemical, and optical properties. This study reviews the electrical, magnetic, and optical properties of HEMs and explores their potential applications. Additionally, it discusses the theoretical calculation methods and preparation techniques for HEMs, thereby offering insights and prospects for their future development.

Rise of Metal-Organic Frameworks: From Synthesis to E-Skin and Artificial Intelligence.

Metal-organic frameworks (MOFs) have attained broad research attention in the areas of sensors, resistive memories, and optoelectronic synapses on the merits of their intriguing physical and chemical properties. In this review, recent progress on the synthesis of MOFs and their electronic applications is introduced and discussed. Initially, the crystal structures and properties of MOFs encompassing optical, electrical, and chemical properties are discussed in brief. Subsequently, advanced synthesis methods for MOFs are introduced, categorized into hydrothermal approach, microwave synthesis, mechanochemical synthesis, and electrochemical deposition. After that, the various roles of MOFs in widespread applications, including sensing, information storage, optoelectronic synapses, machine learning, and artificial intelligence, are discussed, highlighting their versatility and the innovative solutions they provide to long-standing challenges. Finally, an outlook on remaining challenges and a future perspective for MOFs are proposed.

Comprehensive exploration of a traditional Chinese medicinal plant of Magnolia officinalis based on high-coverage mass spectrometry and multidimensional chemical-biological analysis.

Magnolia bark is a traditional Chinese medicine used for hypoglycaemia. With the widespread use of Magnolia bark, its resources are facing a serious shortage. To address this issue, a strategy based on high-coverage mass spectrometry (HCMS) and multidimensional chemical-biological analysis (MCBA) was proposed for the comprehensive exploration of Magnolia officinalis which is the main source of Magnolia bark. The strategy is divided into three main steps. In the first step, the stem bark, stem xylem, root bark, root xylem, leaf and rootlet of Magnolia officinalis were comprehensively analyzed using high-coverage mass spectrometry. In the second step, multivariate statistical analysis was used to explore the heterogeneity of the six parts and detect differential chemical components. In the third step, a combination of experimental screening and molecular docking was used to explore α-glucosidase inhibitors from Magnolia officinalis. Multidimensional chemical-biological analysis (MCBA) of Magnolia officinalis was achieved by combining the last two steps. Finally, a total of 103 compounds were identified from the whole plant of Magnolia officinalis. Differential components of stem bark, stem xylem, leaf, root bark, root xylem and rootlet were systematically revealed. A pair of positional isomers, namely magnolol and honokiol, were found to be α-glucosidase inhibitors. The activity of their combination is superior to that of each single compound, indicating that magnolol and honokiol are in a synergistic relationship. This strategy contributes to comprehensive exploitation of functional plants and effective alleviation of resource shortage. This study also provides a research paradigm for other similar traditional Chinese medicinal plants.

Recent Progress on Flexible Self-Powered Tactile Sensing Platforms for Health Monitoring and Robotics.

Over the past decades, tactile sensing technology has made significant advances in the fields of health monitoring and robotics. Compared to conventional sensors, self-powered tactile sensors do not require an external power source to drive, which makes the entire system more flexible and lightweight. Therefore, they are excellent candidates for mimicking the tactile perception functions for wearable health monitoring and ideal electronic skin (e-skin) for intelligent robots. Herein, the working principles, materials, and device fabrication strategies of various self-powered tactile sensing platforms are introduced first. Then their applications in health monitoring and robotics are presented. Finally, the future prospects of self-powered tactile sensing systems are discussed.

Integration of High-Resolution LC-Q-TOF Mass Spectrometry and Multidimensional Chemical-Biological Analysis to Detect Nanomolar-Level Acetylcholinesterase Inhibitors from Different Parts of Zanthoxylum nitidum.

Zanthoxyli radix is a popular tea among the elderly, and it is believed to have a positive effect on Alzheimer's disease. In this study, a highly effective three-step strategy was proposed for comprehensive analysis of the active components and biological functions of Zanthoxylum nitidum (ZN), including high-resolution LC-Q-TOF mass spectrometry (HRMS), multivariate statistical analysis for heterogeneity (MSAH), and experimental and virtual screening for bioactivity analysis (EVBA). A total of 117 compounds were identified from the root, stem, and leaf of ZN through HRMS. Bioactivity assays showed that the order of acetylcholinesterase (AChE) inhibitory activity from strong to weak was root > stem > leaf. Nitidine, chelerythrine, and sanguinarine were found to be the main differential components of root, stem, and leaf by OPLS-DA. The IC50 values of the three compounds are 0.81 ± 0.02, 0.14 ± 0.01, and 0.48 ± 0.01 µM respectively, indicating that they are potent and high-quality AChE inhibitors. Molecular docking showed that pi-pi T-shaped interactions and pi-lone pairs played important roles in AChE inhibition. This study not only explains the biological function of Zanthoxyli radix in alleviating Alzheimer's disease to some extent, but also lays the foundation for the development of stem and leaf of ZN.

High energy-efficiency decomplexation of metal-complexes by H*-mediated electro-reduction on hydroxyphenyl Co-porphyrin catalysts.

Electrochemical reduction of metal-organic complex pollutants has been recognized as an environmental benign method that operates at mild condition. However, the selective reduction of metal complexes and energy consumption in cathodic process are still a big challenge. Herein, we found that hydroxyphenyl Co-porphyrin catalyst (CoTH@NG) realizes the highly selective decomplexation of metal-organic complexes by H* -mediated reduction, and simultaneously the impressive recovery efficiency of metal ions. Density functional theory (DFT) confirms the generation and capturing ability of H* on CoTH@NG, verifying the dominant role of H* -mediated reduction in the selective decomplexation of Cu-EDTA. CoTH@NG realizes the superior energy efficiency for Cu-EDTA removal (279.3 g kWh-1 of EEOCu-EDTA) and Cu recovery (48.6 g kWh-1 of EEOCu), which are remarkably 3.3 × 102 and 9.7 × 102 times higher than traditional carbon cloth electrode. Moreover, the recovered Cu0(s) nanowires on the electrode surface can be efficiently regenerated in HCOOH by a galvanic reaction through the electron channel of CoTH@NG, regenerating catalytic electrode. This is one of the pioneer studies on H* -mediated electro-reduction decomplexation of metal-complexes, metal recovery, and electrode regeneration on CoTH@NG, which providing a technical strategy for developing efficient electrocatalytic system for pollution control. Environmental Implication Metal complexes is a dramatic increase in the electroplating and mining industries, and seriously affect both public health and environmental sustainability. Our work reported a new hydroxyphenyl Co-porphyrin catalyst (CoTH@NG) which achieves the selective decomplexation of metal-organic complexes, and simultaneously the recovery of metal ions. CoTH@NG realizes the superior energy efficiency for Cu-EDTA removal (279.3 g kWh-1) and Cu0(s) recovery (48.6 g kWh-1), which are remarkably 3.3 × 102 and 9.7 × 102 times higher than traditional carbon cloth electrode. Moreover, the recovered Cu0(s) can be efficiently regenerated in HCOOH by a galvanic reaction through the electron channel of CoTH@NG, regenerating catalytic electrode.

Predicting cachexia in hepatocellular carcinoma patients: a nomogram based on MRI features and body composition.

BACKGROUND: Approximately half of all patients with hepatocellular carcinoma (HCC) develop cachexia during the course of the disease. It is important to be able to predict which patients will develop cachexia at an early stage. PURPOSE: To develop and validate a nomogram based on the magnetic resonance imaging (MRI) features of HCC and body composition for potentially predicting cachexia in patients with HCC. MATERIAL AND METHODS: A retrospective two-center study recruited the pretreatment clinical and MRI data of 411 patients with HCC undergoing abdominal MRI. The data were divided into three cohorts for development, internal validation, and external validation. Patients were followed up for six months after the MRI scan to record each patient's weight to diagnose cachexia. Logistic regression analyses were performed to identify independent variables associated with cachexia in the development cohort used to build the nomogram. RESULTS: The multivariable analysis suggested that the MRI parameters of tumor size > 5 cm (P = 0.001), intratumoral artery (P = 0.004), skeletal muscle index (P < 0.001), and subcutaneous fat area (P = 0.004) were independent predictors of cachexia in patients with HCC. The nomogram derived from these parameters in predicting cachexia reached an area under receiver operating characteristic curve of 0.819, 0.783, and 0.814 in the development, and internal and external validation cohorts, respectively. CONCLUSION: The proposed multivariable nomogram suggested good performance in predicting the risk of cachexia in HCC patients.

Targeted Quantification of Glutathione/Arginine Redox Metabolism Based on a Novel Paired Mass Spectrometry Probe Approach for the Functional Assessment of Redox Status.

Glutathione (GSH) redox control and arginine metabolism are critical in regulating the physiological response to injury and oxidative stress. Quantification assessment of the GSH/arginine redox metabolism supports monitoring metabolic pathway shifts during pathological processes and their linkages to redox regulation. However, assessing the redox status of organisms with complex matrices is challenging, and single redox molecule analysis may not be accurate for interrogating the redox status in cells and in vivo. Herein, guided by a paired derivatization strategy, we present a new ultraperformance liquid chromatography tandem mass spectrometry (UPLC-MS/MS)-based approach for the functional assessment of biological redox status. Two structurally analogous probes, 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) and newly synthesized 2-methyl-6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (MeAQC), were set for paired derivatization. The developed approach was successfully applied to LPS-stimulated RAW 264.7 cells and HDM-induced asthma mice to obtain quantitative information on GSH/arginine redox metabolism. The results suggest that the redox status was remarkably altered upon LPS and HDM stimulation. We expect that this approach will be of good use in a clinical biomarker assay and potential drug screening associated with redox metabolism, oxidative damage, and redox signaling.

New-Style Logic Operation and Neuromorphic Computing Enabled by Optoelectronic Artificial Synapses in an MXene/Y:HfO2 Ferroelectric Memristor.

Today's computing systems, to meet the enormous demands of information processing, have driven the development of brain-inspired neuromorphic systems. However, there are relatively few optoelectronic devices in most brain-inspired neuromorphic systems that can simultaneously regulate the conductivity through both optical and electrical signals. In this work, the Au/MXene/Y:HfO2/FTO ferroelectric memristor as an optoelectronic artificial synaptic device exhibited both digital and analog resistance switching (RS) behaviors under different voltages with a good switching ratio (>103). Under optoelectronic conditions, optimal weight update parameters and an enhanced algorithm achieved 97.1% recognition accuracy in convolutional neural networks. A new logic gate circuit specifically designed for optoelectronic inputs was established. Furthermore, the device integrates the impact of relative humidity to develop an innovative three-person voting mechanism with a veto power. These results provide a feasible approach for integrating optoelectronic artificial synapses with logic-based computing devices.

Intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for predicting parametrial invasion in cervical cancer.

PURPOSE: This study aimed to assess the predictive efficacy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in parametrial invasion (PMI) in cervical cancer patients. METHODS: A total of 83 cervical cancer patients (32 PMI-positive and 51 PMI-negative) retrospectively underwent pretreatment IVIM-DWI and DCE-MRI scans. IVIM-DWI parameters included apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and perfusion fraction (f). DCE-MRI parameters included volume transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space volume (Ve). Logistic regression analyses were conducted to identify independent variables associated with PMI. Receiver operating characteristic curves were generated to assess the predictive performance of significant parameters. RESULTS: Multivariable analysis revealed that the MRI parameters D (odds ratio [OR]: 7.05; 95% CI 1.78-27.88; P = 0.005), D* (OR 6.58; 95% CI 1.49-29.10; P = 0.01), f (OR 5.12; 95% CI 1.23-21.37; P = 0.03), Ktrans (OR 4.60; 95% CI 1.19-17.81; P = 0.03), and Kep (OR 4.90; 95% CI 1.25-19.18; P = 0.02) were independent predictors of PMI in cervical cancer patients. The combined parameter incorporating these parameters demonstrated the highest performance in predicting PMI, yielding an area under the curve of 0.906, sensitivity of 84.4%, and specificity of 86.3%. CONCLUSION: The proposed combined parameter exhibited favorable performance in identifying PMI in cervical cancer patients.

Enzyme-Driven LC-HRMS Approach for Specific Recognition of 12α-Hydroxy Bile Acids.

The synthesis of 12α-hydroxylated bile acids (12HBAs) and non-12α-hydroxylated bile acids (non-12HBAs) occurs via classical and alternative pathways, respectively. The composition of these BAs is a crucial index for pathophysiologic assessment. However, accurately differentiating 12HBAs and non-12HBAs is highly challenging due to the limited standard substances. Here, we innovatively introduce 12α-hydroxysteroid dehydrogenase (12α-HSDH) as an enzymatic probe synthesized by heterologous expression in Escherichia coli, which can specifically and efficiently convert 12HBAs in vitro under mild conditions. Coupled to the conversion rate determined by liquid chromatography-high resolution mass spectrometry (LC-HRMS), this enzymatic probe allows for the straightforward distinguishing of 210 12HBAs and 312 non-12HBAs from complex biological matrices, resulting in a BAs profile with a well-defined hydroxyl feature at the C12 site. Notably, this enzyme-driven LC-HRMS approach can be extended to any molecule with explicit knowledge of enzymatic transformation. We demonstrate the practicality of this BAs profile in terms of both revealing cross-species BAs heterogeneity and monitoring the alterations of 12HBAs and non-12HBAs under asthma disease. We envisage that this work will provide a novel pattern to recognize the shift of BA metabolism from classical to alternative synthesis pathways in different pathophysiological states, thereby offering valuable insights into the management of related diseases.

miR-153 promotes neural differentiation by activating the cell adhesion/Ca2+ signaling pathway and targeting ion channel activity in HT-22 cells by bioinformatic analysis.

MicroRNAs have been studied extensively in neurodegenerative diseases. In a previous study, miR-153 promoted neural differentiation and projection formation in mouse hippocampal HT-22 cells. However, the pathways and molecular mechanism underlying miR-153-induced neural differentiation remain unclear. To explore the molecular mechanism of miR-153 on neural differentiation, we performed RNA sequencing on miR-153-overexpressed HT-22 cells. Based on RNA sequencing, differentially expressed genes (DEGs) and pathways in miR-153-overexpressed cells were identified. The Database for Annotation, Visualization and Integrated Discovery and Gene Set Enrichment Analysis were used to perform functional annotation and enrichment analysis of DEGs. Targetscan predicted the targets of miR-153. The Search Tool for the Retrieval of Interacting Genes and Cytoscape, were used to construct protein-protein interaction networks and identify hub genes. Q-PCR was used to detect mRNA expression of the identified genes. The expression profiles of the identified genes were compared between embryonic days 9.5 (E9.5) and E11.5 in the embryotic mouse brain of the GDS3442 dataset. Cell Counting Kit-8 assay was used to determine cell proliferation and cellular susceptibility to amyloid ß-protein (Aß) toxicity in miR-153-overexpressed cells. The results indicated that miR-153 increased cell adhesion/Ca2+ (Cdh5, Nrcam, and P2rx4) and Bdnf/Ntrk2 neurotrophic signaling pathway, and decreased ion channel activity (Kcnc3, Kcna4, Clcn5, and Scn5a). The changes in the expression of the identified genes in miR-153-overexpressed cells were consistent with the expression profile of GDS3442 during neural differentiation. In addition, miR-153 overexpression decreased cellular susceptibility to Aß toxicity in HT-22 cells. In conclusion, miR-153 overexpression may promote neural differentiation by inducing cell adhesion and the Bdnf/Ntrk2 pathway, and regulating electrophysiological maturity by targeting ion channels. MiR-153 may play an important role in neural differentiation; the findings provide a useful therapeutic direction for neurodegenerative diseases.

Porphyrin-based covalent organic frameworks from design, synthesis to biological applications.

Covalent organic frameworks (COFs) constitute a class of highly functional porous materials composed of lightweight elements interconnected by covalent bonds, characterized by structural order, high crystallinity, and large specific surface area. The integration of naturally occurring porphyrin molecules, renowned for their inherent rigidity and conjugate planarity, as building blocks in COFs has garnered significant attention. This strategic incorporation addresses the limitations associated with free-standing porphyrins, resulting in the creation of well-organized porous crystal structures with molecular-level directional arrangements. The unique optical, electrical, and biochemical properties inherent to porphyrin molecules endow these COFs with diversified applications, particularly in the realm of biology. This review comprehensively explores the synthesis and modulation strategies employed in the development of porphyrin-based COFs and delves into their multifaceted applications in biological contexts. A chronological depiction of the evolution from design to application is presented, accompanied by an analysis of the existing challenges. Furthermore, this review offers directional guidance for the structural design of porphyrin-based COFs and underscores their promising prospects in the field of biology.

Organellophagy regulates cell death:A potential therapeutic target for inflammatory diseases.

BACKGROUND: Dysregulated alterations in organelle structure and function have a significant connection with cell death, as well as the occurrence and development of inflammatory diseases. Maintaining cell viability and inhibiting the release of inflammatory cytokines are essential measures to treat inflammatory diseases. Recently, many studies have showed that autophagy selectively targets dysfunctional organelles, thereby sustaining the functional stability of organelles, alleviating the release of multiple cytokines, and maintaining organismal homeostasis. Organellophagy dysfunction is critically engaged in different kinds of cell death and inflammatory diseases. AIM OF REVIEW: We summarized the current knowledge of organellophagy (e.g., mitophagy, reticulophagy, golgiphagy, lysophagy, pexophagy, nucleophagy, and ribophagy) and the underlying mechanisms by which organellophagy regulates cell death. KEY SCIENTIFIC CONCEPTS OF REVIEW: We outlined the potential role of organellophagy in the modulation of cell fate during the inflammatory response to develop an intervention strategy for the organelle quality control in inflammatory diseases.

Synaptic Properties of a PbHfO3 Ferroelectric Memristor for Neuromorphic Computing.

The conventional von Neumann architecture has proven to be inadequate in keeping up with the rapid progress in artificial intelligence. Memristors have become the favored devices for simulating synaptic behavior and enabling neuromorphic computations to address challenges. An artificial synapse utilizing the perovskite structure PbHfO3 (PHO) has been created to tackle these concerns. By employing the sol-gel technique, a ferroelectric film composed of Au/PHO/FTO was created on FTO/glass for the purpose of this endeavor. The artificial synapse is composed of Au/PHO/FTO and exhibits learning and memory characteristics that are similar to those observed in biological neurons. The recognition accuracy for both MNIST and Fashion-MNIST data sets saw an increase, reaching 92.93% and 76.75%, respectively. This enhancement resulted from employing a convolutional neural network architecture and implementing an improved stochastic adaptive algorithm. The presented findings showcase a viable approach to achieve neuromorphic computation by employing artificial synapses fabricated with PHO.

Neuromorphic Computing of Optoelectronic Artificial BFCO/AZO Heterostructure Memristors Synapses.

Compared with purely electrical neuromorphic devices, those stimulated by optical signals have gained increasing attention due to their realistic sensory simulation. In this work, an optoelectronic neuromorphic device based on a photoelectric memristor with a Bi2FeCrO6/Al-doped ZnO (BFCO/AZO) heterostructure is fabricated that can respond to both electrical and optical signals and successfully simulate a variety of synaptic behaviors, such as STP, LTP, and PPF. In addition, the photomemory mechanism was identified by analyzing the energy band structures of AZO and BFCO. A convolutional neural network (CNN) architecture for pattern classification at the Mixed National Institute of Standards and Technology (MNIST) was used and improved the recognition accuracy of the MNIST and Fashion-MNIST datasets to 95.21% and 74.19%, respectively, by implementing an improved stochastic adaptive algorithm. These results provide a feasible approach for future implementation of optoelectronic synapses.

An adjustable multistage resistance switching behavior of a photoelectric artificial synaptic device with a ferroelectric diode effect for neuromorphic computing.

Neuromorphic computing, which mimics biological neural networks, is widely regarded as the optimal solution for addressing the limitations of traditional von Neumann computing architecture. In this work, an adjustable multistage resistance switching ferroelectric Bi2FeCrO6 diode artificial synaptic device was fabricated using a sol-gel method with a simple process. The device exhibits nonlinearity in its electrical characteristics, demonstrating tunable multistage resistance switching behavior and a strong ferroelectric diode effect through the manipulation of ferroelectric polarization. One of its salient advantages resides in its capacity to dynamically regulate its polarization state in response to an external electric field, thereby facilitating the fine-tuning of synaptic connection strength while maintaining synaptic stability. The device is capable of accurately simulating the fundamental properties of biological synapses, including long/short-term plasticity, paired-pulse facilitation, and spike-timing-dependent plasticity. Additionally, the device exhibits a distinctive photoelectric response and is capable of inducing synaptic plasticity by light signal activation. The utilization of a femtosecond laser for the scrutiny of carrier transport mechanisms imparts profound insights into the intricate dynamics governing the optical memory effect. Furthermore, utilizing a convolutional neural network (CNN) architecture, the recognition accuracy of the MNIST and fashion MNIST datasets was improved to 95.6% and 78%, respectively, through the implementation of improved random adaptive algorithms. These findings present a new opportunity for utilizing Bi2FeCrO6 materials in the development of artificial synapses for neuromorphic computation.

Emerging ferroelectric materials ScAlN: applications and prospects in memristors.

The research found that after doping with rare earth elements, a large number of electrons and holes will be produced on the surface of AlN, which makes the material have the characteristics of spontaneous polarization. A new type of ferroelectric material has made a new breakthrough in the application of nitride-materials in the field of integrated devices. In this paper, the application prospects and development trends of ferroelectric material ScAlN in memristors are reviewed. Firstly, various fabrication processes and structures of the current ScAlN thin films are described in detail to explore the implementation of their applications in synaptic devices. Secondly, a series of electrical properties of ScAlN films, such as the current switching ratio and long-term cycle durability, were tested to explore whether their electrical properties could meet the basic needs of memristor device materials. Finally, a series of summaries on the current research studies of ScAlN thin films in the synaptic simulation are made, and the working state of ScAlN thin films as a synaptic device is observed. The results show that the ScAlN ferroelectric material has high residual polarization, no wake-up function, excellent stability and obvious STDP behavior, which indicates that the modified material has wide application prospects in the research and development of memristors.

Perspective into ion storage of pristine metal-organic frameworks in capacitive deionization.

Metal-organic frameworks (MOFs), featuring tunable conductivity, tailored pore/structure and high surface area, have emerged as promising electrode nanomaterials for ion storage in capacitive deionization (CDI) and garnered tremendous attention in recent years. Despite the many advantages, the perspective from which MOFs should be designed and prepared for use as CDI electrode materials still faces various challenges that hinder their practical application. This summary proposes design principles for the pore size, pore environment, structure and dimensions of MOFs to precisely tailor the surface area, selectivity, conductivity, and Faradaic activity of electrode materials based on the ion storage mechanism in the CDI process. The account provides a new perspective to deepen the understanding of the fundamental issues of MOFs electrode materials to further meet the practical applications of CDI.