Artemisinins ameliorate polycystic ovarian syndrome by mediating LONP1-CYP11A1 interaction.

Polycystic ovary syndrome (PCOS), a prevalent reproductive disorder in women of reproductive age, features androgen excess, ovulatory dysfunction, and polycystic ovaries. Despite its high prevalence, specific pharmacologic intervention for PCOS is challenging. In this study, we identified artemisinins as anti-PCOS agents. Our finding demonstrated the efficacy of artemisinin derivatives in alleviating PCOS symptoms in both rodent models and human patients, curbing hyperandrogenemia through suppression of ovarian androgen synthesis. Artemisinins promoted cytochrome P450 family 11 subfamily A member 1 (CYP11A1) protein degradation to block androgen overproduction. Mechanistically, artemisinins directly targeted lon peptidase 1 (LONP1), enhanced LONP1-CYP11A1 interaction, and facilitated LONP1-catalyzed CYP11A1 degradation. Overexpression of LONP1 replicated the androgen-lowering effect of artemisinins. Our data suggest that artemisinin application is a promising approach for treating PCOS and highlight the crucial role of the LONP1-CYP11A1 interaction in controlling hyperandrogenism and PCOS occurrence.

Development of an interpretable machine learning model associated with genetic indicators to identify Yin-deficiency constitution.

BACKGROUND: Traditional Chinese Medicine (TCM) defines constitutions which are relevant to corresponding diseases among people. As one of the common constitutions, Yin-deficiency constitution influences a number of Chinese population in the disease onset. Therefore, accurate Yin-deficiency constitution identification is significant for disease prevention and treatment. METHODS: In this study, we collected participants with Yin-deficiency constitution and balanced constitution, separately. The least absolute shrinkage and selection operator (LASSO) and logistic regression were used to analyze genetic predictors. Four machine learning models for Yin-deficiency constitution classification with multiple combined genetic indicators were integrated to analyze and identify the optimal model and features. The Shapley Additive exPlanations (SHAP) interpretation was developed for model explanation. RESULTS: The results showed that, NFKBIA, BCL2A1 and CCL4 were the most associated genetic indicators with Yin-deficiency constitution. Random forest with three genetic predictors including NFKBIA, BCL2A1 and CCL4 was the optimal model, area under curve (AUC): 0.937 (95% CI 0.844-1.000), sensitivity: 0.870, specificity: 0.900. The SHAP method provided an intuitive explanation of risk leading to individual predictions. CONCLUSION: We constructed a Yin-deficiency constitution classification model based on machine learning and explained it with the SHAP method, providing an objective Yin-deficiency constitution identification system in TCM and the guidance for clinicians.

A facile and intelligent detection method for diclazuril based on a stable dual emissive Eu3+-dopped metal-organic framework.

Diclazuril (DIC) is a broad-spectrum anti-coccidiosis drug of the triazine class, widely used in poultry farming. The overuse of DIC may lead to its accumulation in animal bodies, which may enter the food chain and threaten human health. In this work, we fabricated a stable Eu3+-doped UiO-66 fluorescence sensor (EuUHIPA-30) for the sensitive detection of DIC. Among 20 veterinary drugs, the fluorescence of EuUHIPA-30 selectively responds to DIC, with a low detection limit (0.19 µM) and fast response (10 s). EuUHIPA-30 is recyclable and can detect DIC in chicken and eggs with good recoveries. Moreover, a smartphone-integrated paper-based sensor enables the instrument-free, rapid, visual, and intelligent detection of DIC in chickens and eggs. This work provides a promising candidate for practical fluorescent DIC sensing in animal-derived food to promote food safety.

NR2F6 is essential for brown adipocyte differentiation and systemic metabolic homeostasis.

OBJECTIVE: Brown adipose tissue (BAT) development and function are essential for maintaining energy balance. However, the key factors that specifically regulate brown adipogenesis require further identification. Here, we demonstrated that the nuclear receptor subfamily 2 group F member 6 (NR2F6) played a pivotal role in brown adipogenesis and energy homeostasis. METHODS: We examined the differentiation of immortalized brown adipocytes and primary brown adipocytes when NR2F6 were deleted, and explored the mechanism through which NR2F6 regulated adipogenesis using ChIP-qPCR in vitro. Male wild type (WT) and Pdgfra-Cre-mediated deletion of Nr2f6 in preadipocytes (NR2F6-PKO) mice were fed with high fat diet (HFD) for 12 weeks, and adiposity, glucose intolerance, insulin resistance and inflammation were assessed. RESULTS: NR2F6 exhibited abundant expression in BAT, while its expression was minimal in white adipose tissue (WAT). Within BAT, NR2F6 was highly expressed in preadipocytes, experienced a transient increase in the early stage of brown adipocyte differentiation, and significantly decreased in the mature adipocytes. Depletion of NR2F6 in preadipocytes inhibited brown adipogenesis, caused hypertrophy of brown adipocytes, and impaired thermogenic function of BAT, but without affecting WAT development. NR2F6 transcriptionally regulated PPARγ expression to promote adipogenic process in brown adipocytes. Loss of NR2F6 in preadipocytes led to increased susceptibility to diet-induced metabolic disorders. CONCLUSIONS: Our findings unveiled NR2F6 as a novel key regulator of brown adipogenesis, potentially opening up new avenues for maintaining metabolic homeostasis by targeting NR2F6.

Motion-artifact-augmented pseudo-label network for semi-supervised brain tumor segmentation.

MRI image segmentation is widely used in clinical practice as a prerequisite and a key for diagnosing brain tumors. The quest for an accurate automated segmentation method for brain tumor images, aiming to ease clinical doctors' workload, has gained significant attention as a research focal point. Despite the success of fully supervised methods in brain tumor segmentation, challenges remain. Due to the high cost involved in annotating medical images, the dataset available for training fully supervised methods is very limited. Additionally, medical images are prone to noise and motion artifacts, negatively impacting quality. In this work, we propose MAPSS, a motion-artifact-augmented pseudo-label network for semi-supervised segmentation. Our method combines motion artifact data augmentation with the pseudo-label semi-supervised training framework. We conduct several experiments under different semi-supervised settings on a publicly available dataset BraTS2020 for brain tumor segmentation. The experimental results show that MAPSS achieves accurate brain tumor segmentation with only a small amount of labeled data and maintains robustness in motion-artifact-influenced images. We also assess the generalization performance of MAPSS using the Left Atrium dataset. Our algorithm is of great significance for assisting doctors in formulating treatment plans and improving treatment quality.

Dual-emissive Eu(III)-functionalized metal-organic frameworks for visual, rapid, and intelligent sensing of albendazole and albendazole sulfoxide in animal-origin food.

Albendazole (ABZ), a benzimidazole-based anthelmintic, is widely used to treat helminth infections. The extensive and improper use of ABZ may cause drug residues in animal-origin food and anthelmintics resistance, which potentially threaten human health. Meanwhile, albendazole sulfoxide (ABZSO), a metabolite of ABZ, also exhibits toxic effects. Therefore, the detection of ABZ and ABZSO in animal-derived food is significantly necessary. Herein, a dual-emission europium fluorescent sensor (EuUHC-30) was rationally designed and constructed. EuUHC-30 exhibits high selectivity and sensitivity towards ABZ and ABZSO with a detection limit of 0.10 and 0.13 µM, respectively. Furthermore, EuUHC-30 was successfully applied for quantification of ABZ and ABZSO in milk and pig kidney, which were verified by HPLC analysis. Moreover, a smartphone-assisted EuUHC-30 fluorescent paper sensor was fabricated for the practical determination of ABZ and ABZSO in real food. Overall, this work provides a visual, rapid, and intelligent method for the detection of ABZ and ABZSO in animal-origin food.

Transparent Self-Healing Anti-Freezing Ionogel for Monolayered Triboelectric Nanogenerator and Electromagnetic Energy-Based Touch Panel.

The advent of Internet of Things and artificial intelligence era necessitates the advancement of self-powered electronics. However, prevalent multifunctional electronics still face great challenges in rigid electrodes, stacked layers, and external power sources to restrict the development in flexible electronics. Here, a transparent, self-healing, anti-freezing (TSA) ionogel composed of fluorine-rich ionic liquid and fluorocarbon elastomer, which is engineered for monolayered triboelectric nanogenerators (M-TENG) and electromagnetic energy-based touch panels is developed. Notably, the TSA-ionogel exhibits remarkable features including outstanding transparency (90%), anti-freezing robustness (253 K), impressive stretchability (600%), and repetitive self-healing capacity. The resultant M-TENG achieves a significant output power density (200 mW m-2 ) and sustains operational stability beyond 1 year. Leveraging this remarkable performance, the M-TENG is adeptly harnessed for biomechanical energy harvesting, self-powered control interface, electroluminescent devices, and enabling wireless control over electrical appliances. Furthermore, harnessing Faraday's induction law and exploiting human body's intrinsic antenna properties, the TSA-ionogel seamlessly transforms into an autonomous multifunctional epidermal touch panel. This touch panel offers impeccable input capabilities through word inscription and participation in the Chinese game of Go. Consequently, the TSA-ionogel's innovation holds the potential to reshape the trajectory of next-generation electronics and profoundly revolutionize the paradigm of human-machine interaction.

A recyclable Eu3+-functionalized dual-emissive metal-organic framework for portable, rapid detection and efficient removal of malachite green.

A europium-functionalized, dual-emissive, metal-organic framework-based fluorescence sensor (EuUCNDA) was constructed via post-synthetic modification of an UiO-66-type precursor through coordination interactions. EuUCNDA exhibited extremely high selectivity and sensitivity for malachite green (MG) with a low detection limit of 13.01 nM, a wide linear concentration range (0.05-50 µM), excellent anti-interference properties, a rapid response (<1 min), and the possibility of recycling. The good sensing performance of EuUCNDA enables the practical detection of MG in fish pond water and grass carp with good recoveries. Moreover, EuUCNDA can be reused for sensing MG and over 90% of fluorescence intensity can be restored after 7 cycles. Furthermore, EuUCNDA-embedded paper-based sensors combined with smartphone imaging afford portable and visual monitoring of MG in real samples. Notably, besides good sensing performance, EuUCNDA could efficiently remove MG from water. Hence, this work provides a recyclable and sensitive fluorescence sensor for portable, visual, rapid detection and efficient removal of MG.

Multifunctional Eu3+-MOF for simultaneous quantification of malachite green and leuco-malachite green and efficient adsorption of malachite green.

Multi-target detection combined with in-situ removal of contaminants is a challenging issue difficult to overcome. Herein, a dual-emissive Eu3+-metal organic framework (Eu3+-MOF) was constructed by pre-functionalization with a blue-emissive ligand and post-functionalization with red-emissive Eu3+ ions using a UiO-66 precursor. The fluorescence of the synthesized Eu3+-MOF is highly selective and sensitive toward malachite green (MG) and its metabolite leuco-malachite green (LMG), which are environmentally persistent and highly toxic to humans. The limit of detection of MG and LMG are 34.20 and 1.98 nM, respectively. Interestingly, the fluorescence of this Eu3+-MOF showed ratiometric but different responsive modes toward MG and LMG, which enabled the simultaneous quantification of MG and LMG. Furthermore, a paper-based sensor combined with the smartphone was fabricated, which facilitated not only the dual-channel detection of MG, but also its portable, visual, rapid, and intelligent determination. Furthermore, the high surface area of MOFs, together with the coordinate bonding interaction, π-π stacking, and electrostatic interaction sites, endows Eu3+-MOF with the efficient ability toward MG removal. This multifunctional Eu3+-MOF can be successfully used for trace detection, simultaneous determination of MG and LMG, as well as efficient removal of MG. Thus, it exhibits bright prospects for widespread applications in the field of food and environmental analysis.

CLCF1 signaling restrains thermogenesis and disrupts metabolic homeostasis by inhibiting mitochondrial biogenesis in brown adipocytes.

Great progress has been made in identifying positive regulators that activate adipocyte thermogenesis, but negative regulatory signaling of thermogenesis remains poorly understood. Here, we found that cardiotrophin-like cytokine factor 1 (CLCF1) signaling led to loss of brown fat identity, which impaired thermogenic capacity. CLCF1 levels decreased during thermogenic stimulation but were considerably increased in obesity. Adipocyte-specific CLCF1 transgenic (CLCF1-ATG) mice showed impaired energy expenditure and severe cold intolerance. Elevated CLCF1 triggered whitening of brown adipose tissue by suppressing mitochondrial biogenesis. Mechanistically, CLCF1 bound and activated ciliary neurotrophic factor receptor (CNTFR) and augmented signal transducer and activator of transcription 3 (STAT3) signaling. STAT3 transcriptionally inhibited both peroxisome proliferator-activated receptor-γ coactivator (PGC) 1α and 1ß, which thereafter restrained mitochondrial biogenesis in adipocytes. Inhibition of CNTFR or STAT3 could diminish the inhibitory effects of CLCF1 on mitochondrial biogenesis and thermogenesis. As a result, CLCF1-TG mice were predisposed to develop metabolic dysfunction even without external metabolic stress. Our findings revealed a brake signal on nonshivering thermogenesis and suggested that targeting this pathway could be used to restore brown fat activity and systemic metabolic homeostasis in obesity.

All Resistive Pressure-Temperature Bimodal Sensing E-Skin for Object Classification.

Electronic skin (E-skin) with multimodal sensing ability demonstrates huge prospects in object classification by intelligent robots. However, realizing the object classification capability of E-skin faces severe challenges in multiple types of output signals. Herein, a hierarchical pressure-temperature bimodal sensing E-skin based on all resistive output signals is developed for accurate object classification, which consists of laser-induced graphene/silicone rubber (LIG/SR) pressure sensing layer and NiO temperature sensing layer. The highly conductive LIG is employed as pressure-sensitive material as well as the interdigital electrode. Benefiting from high conductivity of LIG, pressure perception exhibits an excellent sensitivity of -34.15 kPa-1 . Meanwhile, a high temperature coefficient of resistance of -3.84%°C-1 is obtained in the range of 24-40 °C. More importantly, based on only electrical resistance as the output signal, the bimodal sensing E-skin with negligible crosstalk can simultaneously achieve pressure and temperature perception. Furthermore, a smart glove based on this E-skin enables classifying various objects with different shapes, sizes, and surface temperatures, which achieves over 92% accuracy under assistance of deep learning. Consequently, the hierarchical pressure-temperature bimodal sensing E-skin demonstrates potential application in human-machine interfaces, intelligent robots, and smart prosthetics.

Efficacy and safety of medications for osteoporosis in kidney transplant recipients or patients with chronic kidney disease: A meta-analysis.

This study conducted a meta-analysis to analyze the efficacy and safety of osteoporosis medications in kidney transplant recipients and patients with chronic kidney disease (CKD). PubMed, Embase, the Cochrane Central Register of Controlled Trials were searched from the date of their inception through October 21, 2022. We performed a meta-analysis of the efficacy and safety of osteoporosis medications in adult patients with stage 3-5 CKD or kidney transplant recipients enrolled in randomized clinical trials (RCTs). We calculated the standard mean deviations with 95% confidence intervals (CI) for bone mineral density (BMD) and T scores after 6 and 12 months treatment, pooled odds ratio and 95% CI for fracture risk, and summarized adverse events. The inclusion criteria were met by 27 studies. Out of this, 19 studies were included for the meta-analysis. In stage 3-4 CKD patients, alendronate increased lumbar spine BMD. In patients at stage 5 CKD and undergoing hemodialysis, alendronate and raloxifene increased lumbar spine BMD. After 6 months, the BMD of kidney transplant recipients was seen to be significantly increased; however, there was no difference after 12 months, and the risk of fracture did not reduce. Thus, there is no evidence that these medications reduce the risk of fracture, and their effect on BMD and fracture remains unproven. These medications may increase the incidence of adverse events and their safety needs to be further evaluated. Therefore, we cannot draw a definitive conclusion about the efficacy and safety of osteoporosis medications in the above group of patients.

Association between myopia and anxiety: a cross-sectional study based on Chinese university freshmen.

Background: At least 1 billion people are affected by blindness or vision impairment worldwide, and in China, the proportion of myopia among college students is even higher. Anxiety and self-harm are becoming more and more common among college students, which indicates the importance of paying attention to their mental health. Previous studies have demonstrated that vision impairment has a negative impact on the mental health of adults. However, few studies have focused on the effects of myopia on college freshmen's mental health, and the association between the two factors in college students remained elusive. Methods: This is a large cross-sectional study. A total of 5,519 college freshman would be assessed for the eligibility of the present study, and the inclusion criteria of this study were as follows: (I) first-year college student; (II) diagnosed as myopia and emmetropia through vision test; (III) gave informed consent. Five questionnaires were utilized to collect anxiety data, which include the National Eye Institute Visual Function Questionnaire-25 (NEI-VFQ-25), the Self Esteem Scale (SES), the Self Rating Anxiety Scale (SAS), the Self Rating Depression Scale (SDS), and the Social Avoidance and Distress Scale (SAD), for data collection. In addition, a socio-demographic questionnaire was designed and utilized to collect corresponding information. All enrollees were required to complete the all the above questionnaires. Results: In total 4,984 college students were enrolled. The proportion of males is 60.43%, and the mean age was 19.8 years old. Both right and left vision had a statistically significant association with NEI-VFQ-25 score (P=0.006, r=0.070; and P=0.021, r=0.060, respectively; Pearson correlation analysis) and SAS score (P=0.003, r=0.075 and P=0.004, r=0.075, respectively; Pearson correlation analysis). However, the correlation coefficient was very low (all less than 0.1). No significant correlation was observed between eye vision and other questionnaire scores. Conclusions: Our data suggested that there is week correlation between myopia and anxiety. However, since this is a single-center study, the observed weak correlation may be caused by selection bias. Therefore, our results still need to be validated in further studies with a larger sample size.

A Digital-Analog Bimodal Memristor Based on CsPbBr3 for Tactile Sensory Neuromorphic Computing.

Memristor with digital and analog bipolar bimodal resistive switching offers a promising opportunity for the information-processing component. However, it still remains a huge challenge that the memristor enables bimodal digital and analog types and fabrication of artificial sensory neural network system. Here, a proposed CsPbBr3 -based memristor demonstrates a high ON/OFF ratio (>103 ), long retention (>104 s), stable endurance (100 cycles), and multilevel resistance memory, which acts as an artificial synapse to realize fundamental biological synaptic functions and neuromorphic computing based on controllable resistance modulation. Moreover, a 5 × 5 spinosum-structured piezoresistive sensor array (sensitivity of 22.4 kPa-1 , durability of 1.5 × 104 cycles, and fast response time of 2.43 ms) is constructed as a tactile sensory receptor to transform mechanical stimuli into electrical signals, which can be further processed by the CsPbBr3 -based memristor with synaptic plasticity. More importantly, this artificial sensory neural network system combined the artificial synapse with 5 × 5 tactile sensing array based on piezoresistive sensors can recognize the handwritten patterns of different letters with high accuracy of 94.44% under assistance of supervised learning. Consequently, the digital-analog bimodal memristor would demonstrate potential application in human-machine interaction, prosthetics, and artificial intelligence.

Electrode Separators for the Next-Generation Alkaline Water Electrolyzers.

Multi-gigawatt-scale hydrogen production by water electrolysis is central in the green transition when it comes to storage of energy and forming the basis for sustainable fuels and materials. Alkaline water electrolysis plays a key role in this context, as the scale of implementation is not limited by the availability of scarce and expensive raw materials. Even though it is a mature technology, the new technological context of the renewable energy system demands more from the systems in terms of higher energy efficiency, enhanced rate capability, as well as dynamic, part-load, and differential pressure operation capability. New electrode separators that can support high currents at small ohmic losses, while effectively suppressing gas crossover, are essential to achieving this. This Focus Review compares the three main development paths that are currently being pursued in the field with the aim to identify the advantages and drawbacks of the different approaches in order to illuminate rational ways forward.

Ultrastretchable High-Conductivity MXene-Based Organohydrogels for Human Health Monitoring and Machine-Learning-Assisted Recognition.

Conductive hydrogels as promising candidates of wearable electronics have attracted considerable interest in health monitoring, multifunctional electronic skins, and human-machine interfaces. However, to simultaneously achieve excellent electrical properties, superior stretchability, and a low detection threshold of conductive hydrogels remains an extreme challenge. Herein, an ultrastretchable high-conductivity MXene-based organohydrogel (M-OH) is developed for human health monitoring and machine-learning-assisted object recognition, which is fabricated based on a Ti3C2Tx MXene/lithium salt (LS)/poly(acrylamide) (PAM)/poly(vinyl alcohol) (PVA) hydrogel through a facile immersion strategy in a glycerol/water binary solvent. The fabricated M-OH demonstrates remarkable stretchability (2000%) and high conductivity (4.5 S/m) due to the strong interaction between MXene and the dual-network PVA/PAM hydrogel matrix and the incorporation between MXene and LS, respectively. Meanwhile, M-OH as a wearable sensor enables human health monitoring with high sensitivity and a low detection limit (12 Pa). Furthermore, based on pressure mapping image recognition technology, an 8 × 8 pixelated M-OH-based sensing array can accurately identify different objects with a high accuracy of 97.54% under the assistance of a deep learning neural network (DNN). This work demonstrates excellent comprehensive performances of the ultrastretchable high-conductive M-OH in health monitoring and object recognition, which would further explore extensive potential application prospects in personal healthcare, human-machine interfaces, and artificial intelligence.

A multi-bioresponsive self-assembled nano drug delivery system based on hyaluronic acid and geraniol against liver cancer.

Herein, a multi-bioresponsive self-assembled nano-drug delivery system (HSSG) was constructed by conjugating the anticancer drug Geraniol (GER) to hyaluronic acid (HA) via a disulfide bond. The HSSG NPs displayed a uniform spherical shape with an average diameter of ∼110 nm, maintained high stability, and realized controlled drug release in the tumor microenvironment (pH/glutathione/hyaluronidase). Results of fluorescence microscopy and flow cytometry verified that HSSG NPs were selectively uptaken by human hepatocellular carcinoma cell lines HepG2 and Huh7 via CD44 receptor-mediated internalization. Studies on H22 tumor-bearing mice demonstrate that HSSG NPs could effectively accumulate at the tumor site for a long period. In vitro and in vivo studies show that HSSG NPs significantly promoted the death of cancer cells while reducing the toxicity as compared to GER. Therefore, the HSSG NPs have great potential in the treatment of tumors.

Electrothermal sterilization and self-powered real-time respiratory monitoring of reusable mask based on Ag micro-mesh films.

Since the COVID-19 pandemic outbreaks, the utilization of medical masks plays a critical role in reducing the infected risk. However, constructing multifunctional masks to achieve simultaneously self-sterilization, reusability, and respiratory monitoring capability remains still a huge challenge. Herein, a reusable Ag micro-mesh film-based mask is proposed, which enables the capabilities of electrothermal sterilization and self-powered real-time respiratory monitoring. Highly conductive Ag micro-mesh films prepared by continuous draw spinning method demonstrate excellent electrothermal performances for thermal sterilization and serve as working electrode to fabricate triboelectric nanogenerator (TENG) for real-time respiratory monitoring, respectively. Under a low driving voltage of 3.0 V, the surface temperature of Ag micro-mesh film enables a quick increase to over 60 °C within 30 s, which endows thermal sterilization against S. aureus with antibacterial efficiency of 95.58 % within 20 min to achieve the self-sterilization of medical masks. Furthermore, a self-powered alarm system based on the fabricated TENG as respiratory monitor is developed for real-time respiratory monitoring to render a timely treatment for patients in danger of tachypnea and apnea. Consequently, this work has paved a new and practical avenue to achieve reusable multifunctional masks with capabilities of electrothermal sterilization and real-time respiratory monitoring in clinical medicine.

Site-Selective Assembly of Centimeter-Scale Arrays of Precisely Oriented Magnetic Nanoellipsoids.

The precise organization and orientation of anisotropic nanoparticles (NPs) on substrates over a large area is key to the application of NP assemblies in functional optical, electronic, and magnetic devices, but achieving such high-precision NP assembly still remains challenging. Here, we demonstrate the site-selective assembly of magnetic nanoellipsoids into large-area precisely positioned, orientationally controlled arrays via a combination of chemical patterning and magnetic manipulation. Magnetic ellipsoidal NPs are selectively positioned on predetermined chemical patterns with high fidelity through electrostatic interactions and aligned uniformly in line with an applied magnetic field. The position, orientation, and interparticle spacing of the ellipsoids can be precisely tuned by controlling the chemical patterns and magnetic field. This approach is simple to implement and can generate centimeter-scale arrays in high yield (up to 99%). The arrays exhibit collective magnetic responses that are dependent on the orientation of the ellipsoids. This work offers a tool for the fabrication of precisely engineered arrays of anisotropic NPs for applications such as metasurface and artificial spin ice.

Self-Healing, Thermadapt Triple-Shape Memory Ionomer Vitrimer for Shape Memory Triboelectric Nanogenerator.

Benefiting from the associative exchange reaction, vitrimers could be deformed to various shapes while maintaining the integrity of the network, thus being regarded as promising candidates for shape memory polymers. However, it is still a challenge to design the highly desired smart electronic devices with triple and multishape memory performances through a facile method. Here, a novel dual-cross-linked poly(acrylonitrile-co-butyl acrylate-co-hydroxyethyl methacrylate-co-zinc methacrylate) (Zn-PABHM) copolymer was developed via a facile and one-pot free radical polymerization strategy. Ionic cross-linking, the transcarbamoylation reaction, and glass transition were used to fix the permanent shape and two temporary shapes of the obtained ionomer vitrimer, respectively. The thermomechanical and stress relaxation performances of Zn-PABHM vitrimer can be customized by tuning the proportion of the chemical cross-linking and physical cross-linking knots. Furthermore, the Zn-PABHM was employed to construct a shape memory triboelectric nanogenerator, which demonstrates distinctive performance and tunable electrical outputs (37.4-96.0 V) due to variable contact areas enabled by triple shape memory effects. Consequently, the triple-shape memory ionomer vitrimer obtained via a facile and one-pot synthetic strategy has great potential in smart multifunctional electronic devices.