Conductive MXene/Polymer Composites for Transparent Flexible Supercapacitors.

Transparent flexible energy storage devices are limited by the trade-off among flexibility, transparency, and charge storage capability of their electrode materials. Conductive polymers are intrinsically flexible, but limited by small capacitance. Pseudocapacitive MXene provides high capacitance, yet their opaque and brittle nature hinders their flexibility and transparency. Herein, the development of synergistically interacting conductive polymer Ti3C2Tx MXene/PEDOT:PSS composites is reported for transparent flexible all-solid-state supercapacitors, with an outstanding areal capacitance of 3.1 mF cm-2, a high optical transparency of 61.6%, and excellent flexibility and durability. The high capacitance and high transparency of the devices stem from the uniform and thorough blending of PEDOT:PSS and Ti3C2Tx, which is associated with the formation of O─H…O H-bonds in the composites. The conductive MXene/polymer composite electrodes demonstrate a rational means to achieve high-capacity, transparent and flexible supercapacitors in an easy and scalable manner.

The phosphate starvation response regulator PHR2 antagonizes arbuscule maintenance in Medicago.

Phosphate starvation response (PHR) transcription factors play essential roles in regulating phosphate uptake in plants through binding to the P1BS cis-element in the promoter of phosphate starvation response genes. Recently, PHRs were also shown to positively regulate arbuscular mycorrhizal colonization in rice and lotus by controlling the expression of many symbiotic genes. However, their role in arbuscule development has remained unclear. In Medicago, we previously showed that arbuscule degradation is controlled by two SPX proteins that are highly expressed in arbuscule-containing cells. Since SPX proteins bind to PHRs and repress their activity in a phosphate-dependent manner, we investigated whether arbuscule maintenance is also regulated by PHR. Here, we show that PHR2 is a major regulator of the phosphate starvation response in Medicago. Knockout of phr2 showed reduced phosphate starvation response, symbiotic gene expression, and fungal colonization levels. However, the arbuscules that formed showed less degradation, suggesting a negative role for PHR2 in arbuscule maintenance. This was supported by the observation that overexpression of PHR2 led to enhanced degradation of arbuscules. Although many arbuscule-induced genes contain P1BS elements in their promoters, we found that the P1BS cis-elements in the promoter of the symbiotic phosphate transporter PT4 are not required for arbuscule-containing cell expression. Since both PHR2 and SPX1/3 negatively affect arbuscule maintenance, our results indicate that they control arbuscule maintenance partly via different mechanisms. While PHR2 potentiates symbiotic gene expression and colonization, its activity in arbuscule-containing cells needs to be tightly controlled to maintain a successful symbiosis in Medicago.

Inhibition of MiR-106b-5p mediated by exosomes mitigates acute kidney injury by modulating transmissible endoplasmic reticulum stress and M1 macrophage polarization.

Acute kidney injury (AKI), mainly caused by Ischemia/reperfusion injury (IRI), is a common and severe life-threatening disease with high mortality. Accumulating evidence suggested a direct relationship between endoplasmic reticulum (ER) stress response and AKI progression. However, the role of the transmissible ER stress response, a new modulator of cell-to-cell communication, in influencing intercellular communication between renal tubular epithelial cells (TECs) and macrophages in the AKI microenvironment remains to be determined. To address this issue, we first demonstrate that TECs undergoing ER stress are able to transmit ER stress to macrophages via exosomes, promoting macrophage polarization towards the pro-inflammatory M1 phenotype in vitro and in vivo. Besides, the miR-106b-5p/ATL3 signalling axis plays a pivotal role in the transmission of ER stress in the intercellular crosstalk between TECs and macrophages. We observed an apparent increase in the expression of miR-106b-5p in ER-stressed TECs. Furthermore, we confirmed that ALT3 is a potential target protein of miR-106b-5p. Notably, the inhibition of miR-106b-5p expression in macrophages not only restores ATL3 protein level but also decreases transmissible ER stress and hinders M1 polarization, thus alleviating AKI progression. Additionally, our results suggest that the level of exosomal miR-106b-5p in urine is closely correlated with the severity of AKI patients. Taken together, our study sheds new light on the crucial role of transmissible ER stress in the treatment of AKI through the regulation of the miR-106b-5p/ATL3 axis, offering new ideas for treating AKI.

Mus musculus Barrier-To-Autointegration Factor 2 (Banf2) is Not Essential for Spermatogenesis or Fertility.

The barrier-to-autointegration factor (BAF) is widely expressed in most human tissues and plays a critical role in chromatin organization, nuclear envelope assembly, gonadal development, and embryonic stem cell self-renewal. Complete loss of BAF has been shown to lead to embryonic lethality and gonadal defects. The BAF paralog, namely, barrier-to-autointegration factor 2 (BANF2), exhibits a testis-predominant expression pattern in both humans and mice. Unlike BAF, it may cause isolated male infertility. Therefore, we used the CRISPR/Cas9 system to generate Banf2-knockout mice to further study its function in spermatogenesis. Unexpectedly, knockout mice did not show any detectable abnormalities in histological structure of the testis, epididymis, ovary, and other tissues, and exhibited normal fertility, indicating that Banf2 is not essential for mouse spermatogenesis and fertility.

Discovery of breast cancer risk genes and establishment of a prediction model based on estrogen metabolism regulation.

BACKGROUND: Multiple common variants identified by genome-wide association studies have shown limited evidence of the risk of breast cancer in Chinese individuals. In this study, we aimed to uncover the relationship between estrogen levels and the genetic polymorphism of estrogen metabolism-related enzymes in breast cancer (BC) and establish a risk prediction model composed of estrogen-metabolizing enzyme genes and GWAS-identified breast cancer-related genes based on a polygenic risk score. METHODS: Unrelated BC patients and healthy subjects were recruited for analysis of estrogen levels and single nucleotide polymorphisms (SNPs) in genes encoding estrogen metabolism-related enzymes. The polygenic risk score (PRS) was used to explore the combined effect of multiple genes, which was calculated using a Bayesian approach. An independent sample t-test was used to evaluate the differences between PRS scores of BC and healthy subjects. The discriminatory accuracy of the models was compared using the area under the receiver operating characteristic (ROC) curve. RESULTS: The estrogen homeostasis profile was disturbed in BC patients, with parent estrogens (E1, E2) and carcinogenic catechol estrogens (2/4-OHE1, 2-OHE2, 4-OHE2) significantly accumulating in the serum of BC patients. We then established a PRS model to evaluate the role of SNPs in multiple genes. PRS model 1 (M1) was established from SNPs in 6 GWAS-identified high risk genes. On the basis of M1, we added SNPs from 7 estrogen metabolism enzyme genes to establish PRS model 2 (M2). The independent sample t-test results showed that there was no difference between BC and healthy subjects in M1 (P = 0.17); however, there was a significant difference between BC and healthy subjects in M2 (P = 4.9*10- 5). The ROC curve results showed that the accuracy of M2 (AUC = 62.18%) in breast cancer risk identification was better than that of M1 (AUC = 54.56%). CONCLUSION: Estrogen and related metabolic enzyme gene polymorphisms are closely related to BC. The model constructed by adding estrogen metabolic enzyme gene SNPs has a good predictive ability for breast cancer risk, and the accuracy is greatly improved compared with that of the PRS model that only includes GWAS-identified gene SNPs.

Expression of cellobiose dehydrogenase gene in Aspergillus niger C112 and its effect on lignocellulose degrading enzymes.

Cellobiose dehydrogenase (CDH) is one of the cellulase auxiliary proteins, which is widely used in the field of biomass degradation. However, how to efficiently and cheaply apply it in industrial production still needs further research. Aspergillus niger C112 is a significant producer of cellulase and has a relatively complete lignocellulose degradation system, but its CDH activity was only 3.92 U. To obtain a recombinant strain of A. niger C112 with high cellulases activity, the CDH from the readily available white-rot fungus Grifola frondose had been heterologously expressed in A. niger C112, under the control of the gpdA promoter. After cultivation in the medium with alkali-pretreated poplar fiber as substrate, the enzyme activity of recombinant CDH reached 36.63 U/L. Compared with the original A. niger C112, the recombinant A. niger transformed with Grifola frondosa CDH showed stronger lignocellulase activity, the activities of cellulases, ß-1, 4-glucosidase and manganese peroxidase increased by 28.57, 35.07 and 121.69%, respectively. The result showed that the expression of the gcdh gene in A. niger C112 could improve the activity of some lignocellulose degrading enzymes. This work provides a theoretical basis for the further application of gcdh gene in improving biomass conversion efficiency.

Protocol for induction of human kidney cell fibrosis.

Here, we present a protocol for inducing fibrosis in human kidney-2 (HK2) cells followed by quantitative real-time PCR analysis of fibrosis-related genes. We describe steps for growing and expanding cells, inducing HK2 fibrosis, and collecting cells for downstream applications. Given the limited cell quantity in culture flasks and the challenges of cell collection, we utilized 10-cm Petri dishes for cell harvesting, with each experimental group comprising five replicate samples. For complete details on the use and execution of this protocol, please refer to Zhang et al.1.

Developmental Dynamics of the Gut Virome in Tibetan Pigs at High Altitude: A Metagenomic Perspective across Age Groups.

Tibetan pig is a geographically isolated pig breed that inhabits high-altitude areas of the Qinghai-Tibetan plateau. At present, there is limited research on viral diseases in Tibetan pigs. This study provides a novel metagenomic exploration of the gut virome in Tibetan pigs (altitude ≈ 3000 m) across three critical developmental stages, including lactation, nursery, and fattening. The composition of viral communities in the Tibetan pig intestine, with a dominant presence of Microviridae phages observed across all stages of development, in combination with the previous literature, suggest that it may be associated with geographical locations with high altitude. Functional annotation of viral operational taxonomic units (vOTUs) highlights that, among the constantly increasing vOTUs groups, the adaptability of viruses to environmental stressors such as salt and heat indicates an evolutionary response to high-altitude conditions. It shows that the lactation group has more abundant viral auxiliary metabolic genes (vAMGs) than the nursery and fattening groups. During the nursery and fattening stages, this leaves only DNMT1 at a high level. which may be a contributing factor in promoting gut health. The study found that viruses preferentially adopt lytic lifestyles at all three developmental stages. These findings not only elucidate the dynamic interplay between the gut virome and host development, offering novel insights into the virome ecology of Tibetan pigs and their adaptation to high-altitude environments, but also provide a theoretical basis for further studies on pig production and epidemic prevention under extreme environmental conditions.

Network pharmacology combined with molecular docking and experimental validation to reveal the pharmacological mechanism of naringin against renal fibrosis.

To explore the pharmacological mechanism of naringin (NRG) in renal fibrosis (RF) based on network pharmacology combined with molecular docking and experimental validation. We used databases to screen for the targets of NRG and RF. The "drug-disease network" was established using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of targets were performed using Metascape, and molecular docking was performed using Schrödinger. We established an RF model in both mice and cells to validate the results of network pharmacology. After screening the database, we identified 222 common targets of NRG and RF and established a target network. Molecular docking showed that the target AKT had a good interaction with NRG. We found that the phosphatidylinositol 3-kinase (PI3K)/AKT signaling pathway was enriched by multiple targets and served as a target for experimental validation through GO and KEGG. The results revealed that NRG ameliorated renal dysfunction, reduced the release of inflammatory cytokines, decreased the expression of α-SMA, collagen I, and Fn, and recovered the expression of E-cad by inhibiting the PI3K/AKT signaling pathway. Our study used pharmacological analysis to predict the targets and mechanisms of NRG against RF. Furthermore, experiments proved that NRG inhibited RF effectively by targeting the PI3K/AKT signaling pathway.

Comprehensive analysis of the relationship between xanthine oxidoreductase activity and chronic kidney disease.

Chronic kidney disease (CKD) is a common disease that seriously endangers human health. However, the potential relationship between xanthine oxidoreductase (XOR) activity and CKD remains unclear. In this study, we used clinical data, CKD datasets from the Gene Expression Omnibus database, and untargeted metabolomics to explain the relationship between XOR activity and CKD. First, XOR activity showed high correlation with the biomarkers of CKD, such as serum creatinine, blood urea nitrogen, uric acid, and estimated glomerular filtration rate. Then, we used least absolute shrinkage and selection operator logical regression algorithm and random forest algorithm to screen CKD molecular markers from differentially expressed genes, and the results of qRT-PCR of XDH, KOX-1, and ROMO1 were in accordance with the results of bioinformatics analyses. In addition, untargeted metabolomics analysis revealed that the purine metabolism pathway was significantly enriched in CKD patients in the simulated models of kidney fibrosis.

A Memristors-Based Dendritic Neuron for High-Efficiency Spatial-Temporal Information Processing.

Diverse microscopic ionic dynamics help mediate the ability of a biological neural network to handle complex tasks with low energy consumption. Thus, rich internal ionic dynamics in memristors based on transition metal oxide are expected to provide a unique and useful platform for implementing energy-efficient neuromorphic computing. To this end, a titanium oxide (TiOx )-based interface-type dynamic memristor and an niobium oxide (NbOx )-based Mott memristor are integrated as an artificial dendrite and spike-firing soma, respectively, to construct a dendritic neuron unit for realizing high-efficiency spatial-temporal information processing. Further, a dendritic neural network is hardware-implemented for spatial-temporal information processing to highlight the computational advantages achieved by incorporating dendritic functions in the network. Human motion recognition is demonstrated using the Nanyang Technological University-Red Green Blue (NTU-RGB) dataset as a benchmark spatial-temporal task; it shows a nearly 20% improvement in accuracy for the memristors-based hardware incorporating dendrites and a 1000× advantage in power efficiency compared to that of the graphics processing unit (GPU). The dendritic neuron developed in this study can be considered a critical building block for implementing more bio-plausible neural networks that can manage complex spatial-temporal tasks with high efficiency.

Voltage-Mode Ferroelectric Synapse for Neuromorphic Computing.

Ferroelectric materials with a modulable polarization extent hold promise for exploring voltage-driven neuromorphic hardware, in which direct current flow can be minimized. Utilizing a single active layer of an insulating ferroelectric polymer, we developed a voltage-mode ferroelectric synapse that can continuously and reversibly update its states. The device states are straightforwardly manifested in the form of variable output voltage, enabling large-scale direct cascading of multiple ferroelectric synapses to build a deep physical neural network. Such a neural network based on potential superposition rather than current flow is analogous to the biological counterpart driven by action potentials in the brain. A high accuracy of over 97% for the simulation of handwritten digit recognition is achieved using the voltage-mode neural network. The controlled ferroelectric polarization, revealed by piezoresponse force microscopy, turns out to be responsible for the synaptic weight updates in the ferroelectric synapses. The present work demonstrates an alternative strategy for the design and construction of emerging artificial neural networks.

Rotating neurons for all-analog implementation of cyclic reservoir computing.

Hardware implementation in resource-efficient reservoir computing is of great interest for neuromorphic engineering. Recently, various devices have been explored to implement hardware-based reservoirs. However, most studies were mainly focused on the reservoir layer, whereas an end-to-end reservoir architecture has yet to be developed. Here, we propose a versatile method for implementing cyclic reservoirs using rotating elements integrated with signal-driven dynamic neurons, whose equivalence to standard cyclic reservoir algorithm is mathematically proven. Simulations show that the rotating neuron reservoir achieves record-low errors in a nonlinear system approximation benchmark. Furthermore, a hardware prototype was developed for near-sensor computing, chaotic time-series prediction and handwriting classification. By integrating a memristor array as a fully-connected output layer, the all-analog reservoir computing system achieves 94.0% accuracy, while simulation shows >1000× lower system-level power than prior works. Therefore, our work demonstrates an elegant rotation-based architecture that explores hardware physics as computational resources for high-performance reservoir computing.

Optimization of alkali-treated poplar fiber saccharification using metal ions and surfactants.

In this study, contrary to untreated poplar fiber, processing of alkali-treated poplar fiber was optimized for the enzymatic saccharification. Considering reducing sugar content as the evaluation index, pH, temperature, time, amount of enzyme, and rotational speed of shaker were standardized to optimize the sugar production by enzymatic hydrolysis. Using response surface methodology, the optimum technological condition of enzymatic hydrolysis was found to be utilizing 43 mg cellulase at 46 °C for 50 h. At this, the sugar conversion amount of NaOH or H2O2-NaOH pretreated poplar was 164.62 mg/g and 218.82 mg/g respectively. It was a corresponding increase of 446.73% or 626.75% than that of poplar fiber without a pretreatment. At a low concentration, metal ions and surfactants promoted the conversion of reducing sugar. Especially, 0.01 g/L Mn2+ and 0.50 g/L hexadecyl trimethyl ammonium bromide (CTAB) produced the best effect and increased the conversion rate of reducing sugar by 23.62% and 21.44% respectively. Also, the effect of the combination of metal ions and surfactants was better than that of a single accelerator. By improving the enzymatic process, these findings could enhance the utilization of poplar fiber for the production of reducing sugar.

Dynamic memristor-based reservoir computing for high-efficiency temporal signal processing.

Reservoir computing is a highly efficient network for processing temporal signals due to its low training cost compared to standard recurrent neural networks, and generating rich reservoir states is critical in the hardware implementation. In this work, we report a parallel dynamic memristor-based reservoir computing system by applying a controllable mask process, in which the critical parameters, including state richness, feedback strength and input scaling, can be tuned by changing the mask length and the range of input signal. Our system achieves a low word error rate of 0.4% in the spoken-digit recognition and low normalized root mean square error of 0.046 in the time-series prediction of the Hénon map, which outperforms most existing hardware-based reservoir computing systems and also software-based one in the Hénon map prediction task. Our work could pave the road towards high-efficiency memristor-based reservoir computing systems to handle more complex temporal tasks in the future.

Testis-expressed protein 33 is not essential for spermiogenesis and fertility in mice.

Gene expression analyses have revealed that there are >2,300 testis-enriched genes in mice, and gene knockout models have shown that a number of them are responsible for male fertility. However, the functions of numerous genes have yet to be clarified. The aim of the present study was to identify the expression pattern of testis-expressed protein 33 (TEX33) in mice and explore the role of TEX33 in male reproduction. Reverse transcription-polymerase chain reaction and western blot assays were used to investigate the mRNA and protein levels of TEX33 in mouse testes during the first wave of spermatogenesis. Immunofluorescence analysis was also performed to identify the cellular and structural localization of TEX33 protein in the testes. Tex33 knockout mice were generated by CRISPR/Cas9 gene-editing. Histological analysis with hematoxylin and eosin or periodic acid-Schiff (PAS) staining, computer-assisted sperm analysis (CASA) and fertility testing, were also carried out to evaluate the effect of TEX33 on mouse spermiogenesis and male reproduction. The results showed that Tex33 mRNA and protein were exclusively expressed in mouse testes and were first detected on postnatal days 21-28 (spermiogenesis phase); their expression then remained into adulthood. Immunofluorescence analysis revealed that TEX33 protein was located in the spermatids and sperm within the seminiferous tubules of the mouse testes, and exhibited specific localization to the acrosome, flagellum and manchette during spermiogenesis. These results suggested that TEX33 may play a role in mouse spermiogenesis. However, Tex33 knockout mice presented no detectable difference in testis-to-body weight ratios when compared with wild-type mice. PAS staining and CASA revealed that spermatogenesis and sperm quality were normal in mice lacking Tex33. In addition, fertility testing suggested that the Tex33 knockout mice had normal reproductive functions. In summary, the findings of the present study indicate that TEX33 is associated with spermiogenesis but is not essential for sperm development and male fertility.

Analog memristive synapse based on topotactic phase transition for high-performance neuromorphic computing and neural network pruning.

Inspired by the human brain, nonvolatile memories (NVMs)-based neuromorphic computing emerges as a promising paradigm to build power-efficient computing hardware for artificial intelligence. However, existing NVMs still suffer from physically imperfect device characteristics. In this work, a topotactic phase transition random-access memory (TPT-RAM) with a unique diffusive nonvolatile dual mode based on SrCoO x is demonstrated. The reversible phase transition of SrCoO x is well controlled by oxygen ion migrations along the highly ordered oxygen vacancy channels, enabling reproducible analog switching characteristics with reduced variability. Combining density functional theory and kinetic Monte Carlo simulations, the orientation-dependent switching mechanism of TPT-RAM is investigated synergistically. Furthermore, the dual-mode TPT-RAM is used to mimic the selective stabilization of developing synapses and implement neural network pruning, reducing ~84.2% of redundant synapses while improving the image classification accuracy to 99%. Our work points out a new direction to design bioplausible memristive synapses for neuromorphic computing.

Type 2 diabetes mellitus facilitates endometrial hyperplasia progression by activating the proliferative function of mucin O-glycosylating enzyme GALNT2.

OBJECTIVE: Type 2 diabetes mellitus (T2DM) is thought to be a risk factor for endometrial hyperplasia, but potential links between the two diseases are unknown. This study aims to evaluate the role of T2DM in the progression of endometrial hyperplasia. METHODS: Female Sprague-Dawley rats were randomly divided into normal (N) group, endometrial hyperplasia (NH) group, T2DM (T) group, and endometrial hyperplasia with T2DM (TH) group. Proteomics analysis was performed to determine the protein profile of endometrial tissues. Proliferation, migration, and invasion of cells with/without GLANT2-knockdown were assessed. Immunohistochemical staining and ELISA were used to examine the expression of GALNT2 in endometrial tissues and serum of clinical samples. RESULTS: The highest uterus index and endometrial thickness were observed in TH group, with the expression of proliferation marker PCNA increased significantly, indicating that T2DM facilitates the progress of endometrial hyperplasia. Proteomics analysis showed that there were significant differences in protein profiles among groups and differential proteins were mainly enriched in metabolic pathways. Further verification by molecular biology analysis indicated that GALNT2 is the key target for T2DM facilitating endometrial hyperplasia. The expression of GALNT2 was significantly decreased in high glucose environment. T2DM could synergize the proliferative function of GALNT2 aberration by activating EGFR/AKT/ERK pathway. The decreased expressions of GALNT2 in clinical samples were associated with worse subtypes of endometrial hyperplasia. CONCLUSION: T2DM promoted the progression of endometrial hyperplasia by regulating the GALNT2-mediated phosphorylation of EGFR and enhancing cell proliferation. GALNT2 has the potential to be a novel biomarker in the treatment of endometrial hyperplasia.

Filter-Free Selective Light Monitoring by Organic Field-Effect Transistor Memories with a Tunable Blend Charge-Trapping Layer.

Integration of selective photodetection and signal storage in a single device, such as organic field-effect transistor (OFET) memories, meets the demands for radiation monitoring and protection. A new strategy is developed to achieve filter-free and selective light monitoring by adopting a solution-processed blend charge-trapping layer in OFET memories, where the charge-trapping layer is composed of phenyl-C61-butyric acid methyl ester (PCBM) dispersed in a polymer electret thin film. The OFET memory without PCBM shows response only to ultraviolet light, whereas the spectral response edges are extended to the visible and near-infrared regions in the corresponding devices with relatively low and high contents of PCBM in the charge-trapping layer, respectively. A set of OFET memories with different PCBM contents is used to qualitatively evaluate the light composition in an optical source. The tunable spectral response in the OFET memories is ascribed to the additional photoassisted charge-trapping paths depending on the blend ratio in the charge-trapping layer. This mechanism may inspire alternative approaches to organic-based optical sensing and monitoring in flexible and wearable electronics.

Ionic-liquid-assisted one-pot synthesis of Cu2O nanoparticles/multi-walled carbon nanotube nanocomposite for high-performance asymmetric supercapacitors.

Finding earth-abundant and high-performance electrode materials for supercapacitors is a demanding challenge in the energy storage field. Cuprous oxide (Cu2O) has attracted increasing attention due to its theoretically high specific capacitance, however, the development of Cu2O-based electrodes with superior capacitive performance is still challenging. We herein report a simple and effective ionic-liquid-assisted sputtering approach to synthesizing the Cu2O nanoparticles/multi-walled carbon nanotubes (Cu2O/MWCNTs) nanocomposite for high-performance asymmetric supercapacitors. The Cu2O/MWCNTs nanocomposite delivers a high specific capacitance of 357 F g-1, good rate capability and excellent capacitance retention of about 89% after 20 000 cycles at a current density of 10 A g-1. The high performance is attributed to the uniform dispersion of small-sized Cu2O nanoparticles on conductive MWCNTs, which offers plenty of redox active sites and thus improve the electron transfer efficiency. Oxygen vacancies are further introduced into Cu2O by the NaBH4 treatment, providing the oxygen-deficient Cu2O/MWCNTs (r-Cu2O/MWCNTs) nanocomposite with significantly improved specific capacitance (790 F g-1) and cycling stability (∼93% after 20 000 cycles). The assembled asymmetric supercapacitor based on the r-Cu2O/MWCNTs//activated carbon (AC) structure achieves a high energy density of 64.2 W h kg-1 at 825.3 W kg-1, and long cycling life. This work may form a foundation for the development of both high capacity and high energy density supercapacitors by showcasing the great potential of earth-abundant Cu-based electrode materials.