Low-Field-Driven Superior Energy Storage Effect with Excellent Thermal Stability by Constructing Coexistent Glasses.

In this work, we found that the defreezing coexistent glassy ferroelectric states hold significant potential for achieving superior energy storage performance, especially under low fields, by using phase field simulations and experimental approaches. A remarkable room-temperature energy recoverable storage density Wr exceeding 2.7 J/cm3 with a high efficiency η surpassing 80% under a low electric field of 170 kV/cm was obtained in the x = 6-12% compositions of x[Bi(Mg2/3Nb1/3)O3]-(1-x)[0.94(Bi0.5Na0.5)TiO3-0.06BaTiO3-1%MnO2] (BNBT-BMN) ceramics due to the combination of low Pr and high Pm of the coexistent ferroelectric glasses. Intriguingly, the superior Wr and η of the coexistent state of glasses can also be maintained in a wide temperature range of 293-430 K, indicating the excellent thermal stability of the energy storage behavior. Importantly, the Wr and η of this glass coexistent composition increase upon heating from room temperature to 360 K due to the defreezing process, leading to maximum Wr ∼ 2.9 J/cm3 with high efficiency η ∼ 90% of x = 10% at 360 K. When considering both energy storage behavior and thermal stability under low fields (<250 kV/cm), the BNBT-BMN ceramics outperform nearly all lead-free counterparts available today. Consequently, our work not only expands the research scope of ferroic glasses but also establishes a new paradigm for developing superior lead-free dielectrics suitable for high-temperature energy storage devices.

Ce-doped multi-phase NiMo-based phosphorus/sulfide heterostructure for efficient photo-enhanced overall water splitting at high current densities.

NiMo-based electrocatalysts are widely regarded as promising electrocatalysts for overall water splitting (OWS). However, to solve the problem of slow reaction kinetics and serious deactivation at high current density, the reasonable design of NiMo-based electrocatalysts is still a great challenge. In this work, NiMo-based phosphorus/sulfide heterostructure electrocatalysts with different Ce doping ratios (5%/10%/15%Ce-NiMo-PS@NF) have been designed using the combination of cation doping and heterostructure engineering. The doping of Ce not only changes the electronic environment of the heterostructure, accelerates the electron transport at the heterostructure interface, but also enhances the light absorption capacity of the heterostructure. The experimental results show that 10%Ce-NiMo-PS@NF has the best photo-enhanced electrocatalytic activity (hydrogen evolution reaction (HER): η1000 = 250 mV, oxygen evolution reaction (OER): η1000 = 242 mV, and OWS: E1000 = 1.864 V). In addition, its solar-to-hydrogen (STH) efficiency in a photoelectric coupled water splitting system is as high as 18.68%. This study not only provides a new method for the synthesis of new heterostructure electrocatalysts, but also provides a reference for the rational use of light energy to enhance electrocatalytic activity.

Jujuboside A ameliorates cognitive deficiency in delirium through promoting hippocampal E4BP4 in mice.

OBJECTIVE: Delirium (acute brain syndrome) is a common and serious neuropsychiatric disorder characterized by an acute decline in cognitive function. However, there is no effective treatment clinically. Here we investigated the potential effect of jujuboside A (JuA, a natural triterpenoid saponin) on cognitive impairment in delirium. METHODS: Delirium models of mice were established by injecting lipopolysaccharide (LPS) plus midazolam and implementing a jet lag protocol. Novel object recognition test and Y maze test were used to evaluate the effects of JuA on delirium-associated cognitive impairment. The mRNA and protein levels of relevant clock factors and inflammatory factors were measured by qPCR and Western blotting. Hippocampal Iba1+ intensity was determined by immunofluorescence staining. KEY FINDINGS: JuA ameliorated delirium (particularly delirium-associated cognitive impairment) in mice, which was proved by the behavioural tests, including a preference for new objects, an increase of spontaneous alternation and improvement of locomotor activity. Furthermore, JuA inhibited the expression of ERK1/2, p-p65, TNFα and IL-1ß in hippocampus, and repressed microglial activation in delirious mice. This was attributed to the increased expression of E4BP4 (a negative regulator of ERK1/2 cascade and microglial activation). Moreover, loss of E4bp4 in mice abrogated the effects of JuA on delirium as well as on ERK1/2 cascade and microglial activation in the hippocampus of delirious mice. Additionally, JuA treatment increased the expression of E4BP4 and decreased the expression of p-p65, TNFα and IL-1ß in LPS-stimulated BV2 cells, supporting a protective effect of JuA on delirium. CONCLUSIONS: JuA protects against delirium-associated cognitive impairment through promoting hippocampal E4BP4 in mice. Our findings are of great significance to the drug development of JuA against delirium and related disorders.

Reprogramming of rhythmic liver metabolism by intestinal clock.

BACKGROUND & AIMS: Temporal oscillations in intestinal nutrient processing and absorption are coordinated by the local clock, which leads to the hypothesis that the intestinal clock has major impacts on shaping peripheral rhythms via diurnal nutritional signals. Here, we investigate the role of the intestinal clock in controlling liver rhythmicity and metabolism. METHODS: Transcriptomic analysis, metabolomics, metabolic assays, histology, quantitative (q)PCR, and immunoblotting were performed with Bmal1-intestine-specific knockout (iKO), Rev-erba-iKO, and control mice. RESULTS: Bmal1 iKO caused large-scale reprogramming of the rhythmic transcriptome of mouse liver with a limited effect on its clock. In the absence of intestinal Bmal1, the liver clock was resistant to entrainment by inverted feeding and a high-fat diet. Importantly, Bmal1 iKO remodelled diurnal hepatic metabolism by shifting to gluconeogenesis from lipogenesis during the dark phase, leading to elevated glucose production (hyperglycaemia) and insulin insensitivity. Conversely, Rev-erba iKO caused a diversion to lipogenesis from gluconeogenesis during the light phase, resulting in enhanced lipogenesis and an increased susceptibility to alcohol-related liver injury. These temporal diversions were attributed to disruption of hepatic SREBP-1c rhythmicity, which was maintained via gut-derived polyunsaturated fatty acids produced by intestinal FADS1/2 under the control of a local clock. CONCLUSIONS: Our findings establish a pivotal role for the intestinal clock in dictating liver rhythmicity and diurnal metabolism, and suggest targeting intestinal rhythms as a new avenue for improving metabolic health. IMPACT AND IMPLICATIONS: Our findings establish the centrality of the intestinal clock among peripheral tissue clocks, and associate liver-related pathologies with its malfunction. Clock modifiers in the intestine are shown to modulate liver metabolism with improved metabolic parameters. Such knowledge will help clinicians improve the diagnosis and treatment of metabolic diseases by incorporating intestinal circadian factors.

Healthcare preferences of the general Chinese population in the hierarchical medical system: A discrete choice experiment.

Background: Chinese health insurance system faces resource distribution challenges. A patient-centric approach allows decision-makers to be keenly aware of optimized medical resource allocation. Objective: This study aims to use the discrete choice model to determine the main factors affecting the healthcare preferences of the general Chinese population and their weights in the three scenarios (chronic non-communicable diseases, acute infectious diseases, and major diseases). Methods: This study firstly identified the key factors affecting people's healthcare preferences through literature review and qualitative interviews, and then designed the DCE questionnaire. An online questionnaire produced by Lighthouse Studio (version 9.9.1) software was distributed to voluntary respondents recruited from mainland China's entire population from January 2021 to June 2021. Participants were required to answer a total of 21 questions of three scenarios in the questionnaire. The multinomial logit model and latent class model were used to analyze the collected data. Results: A total of 4,156 participants from mainland China were included in this study. The multinomial logit and latent class model analyses showed that medical insurance reimbursement is the most important attribute in all three disease scenarios. In the scenario of "non-communicable diseases," the attributes that participants valued were, from the most to the least, medical insurance reimbursement (45.0%), hospital-level (21.6%), distance (14.4%), cost (9.7%), waiting time (8.3%), and care provider (1.0%). As for willingness to pay (WTP), participants were willing to pay 204.5 yuan, or 1,743.8 yuan, to change from private hospitals or community hospitals to tertiary hospitals, respectively. Conclusions: This study explores the healthcare preferences of Chinese residents from a new perspective, which can provide theoretical reference for the refinement of many disease medical reimbursement policies, such as developing different reimbursement ratios for various common diseases and realizing rational configuration of medical resources.

Tangeretin prevents cognitive deficit in delirium through activating RORα/γ-E4BP4 axis in mice.

Delirium is a common and serious neuropsychiatric syndrome characterized with acute cognitive and attentional deficits, however, the effective therapies are lacking. Here, using mouse models of delirium, we investigated the effects of tangeretin (TAN, a natural flavonoid) on cognitive impairment by assessing object preference with novel object recognition (NOR) test and spontaneous alternation with Y maze test. We found that TAN, as a RORα/γ agonist, prevented cognitive decline in delirious mice as evidenced by a normal novel object preference and increased spontaneous alternation. This was accompanied by decreased expression of ERK1/2, TNFα and IL-1ß as well as diminished microglial activation in delirious mice. The protective effect of TAN on delirium was mainly attributed to increased hippocampal E4BP4 expression (a known target of RORs and a regulator of cognition in delirium through modulating the ERK1/2 cascade and microglial activation) via activation of RORα/γ. In addition, TAN treatment modulated the expression of RORα/γ target genes (such as E4bp4 and Bmal1) and inhibited the expression of TNFα and IL-1ß in lipopolysaccharide (LPS)-stimulated cells, supporting a beneficial effect of TAN on delirium. In conclusion, TAN is identified as a RORα/γ agonist which promotes E4BP4 expression to prevent cognitive decline in delirious mice. Our findings may have implications for drug development of TAN for prevention and treatment of various diseases associated with cognitive deficiency.

Interface-Driven Multiferroicity in Cubic BaTiO3-SrTiO3 Nanocomposites.

Perovskite multiferroics have drawn significant attention in the development of next-generation multifunctional electronic devices. However, the majority of existing multiferroics exhibit ferroelectric and ferromagnetic orderings only at low temperatures. Although interface engineering in complex oxide thin films has triggered many exotic room-temperature functionalities, the desired coupling of charge, spin, orbital and lattice degrees of freedom often imposes stringent requirements on deposition conditions, layer thickness and crystal orientation, greatly hindering their cost-effective large-scale applications. Herein, we report an interface-driven multiferroicity in low-cost and environmentally friendly bulk polycrystalline material, namely cubic BaTiO3-SrTiO3 nanocomposites which were fabricated through a simple, high-throughput solid-state reaction route. Interface reconstruction in the nanocomposites can be readily controlled by the processing conditions. Coexistence of room-temperature ferromagnetism and ferroelectricity, accompanying a robust magnetoelectric coupling in the nanocomposites, was confirmed both experimentally and theoretically. Our study explores the 'hidden treasure at the interface' by creating a playground in bulk perovskite oxides, enabling a broad range of applications that are challenging with thin films, such as low-power-consumption large-volume memory and magneto-optic spatial light modulator.

The nuclear receptor REV-ERBα regulates CYP2E1 expression and acetaminophen hepatotoxicity.

CYP2E1 plays an important role in drug metabolism and drug-induced hepatotoxicity. Here, we aimed to investigate a potential role for the nuclear receptor REV-ERBα in regulation of CYP2E1 expression and acetaminophen (APAP)-induced hepatotoxicity, and to determine the underlying mechanisms.Regulatory effects of REV-ERBα on CYP2E1 expression were assessed in vivo (using Rev-erbα-/- mice) and in vitro (using AML12 and HepG2 cells). In vitro microsomal CYP2E1 activity was probed using its specific substrate p-nitrophenol. Pharmacokinetic and acute toxicity studies were performed with Rev-erbα-/- and wild-type mice after APAP administration.We found that Rev-erbα ablation led to decreases in hepatic CYP2E1 expression and activity in mice. In line with this, APAP-induced hepatotoxicity was attenuated in Rev-erbα-deficient mice. The attenuated toxicity was due to down-regulation of APAP metabolism mediated by CYP2E1, which was evidenced by a decrease in formation of the toxic intermediate metabolite NAPQI (i.e. reduced APAP-cysteine and APAP-N-acetylcysteine levels). Furthermore, positive regulation of CYP2E1 expression by REV-ERBα was confirmed in both AML12 and HepG2 cells. Based on luciferase reporter assays, it was found that REV-ERBα regulated Cyp2e1 transcription and expression through repression of DEC2.In conclusion, REV-ERBα positively regulates CYP2E1 expression in mice, thereby affecting APAP metabolism and hepatotoxicity.

E4BP4 Coordinates Circadian Control of Cognition in Delirium.

Improved understanding of the etiologies of delirium, a common and severe neuropsychiatric syndrome, would facilitate the disease prevention and treatment. Here, the authors invesitgate the role of circadian rhythms in the pathogenesis of delirium. They observe perturbance of circadian rhythms in mouse models of delirium and disrupted clock gene expression in patients with delirium. In turn, physiological and genetic circadian disruptions sensitize mice to delirium with aggravated cognitive impairment. Likewise, global deletion of E4bp4 (E4 promoter-binding protein), a clock gene markedly altered in delirium conditions, results in exacerbated delirium-associated cognitive decline. Cognitive decline in delirium models is attributed to microglial activation and impaired long-term potentiation in the hippocampus. Single-cell RNA-sequencing reveals microglia as the regulatory target of E4bp4. E4bp4 restrains microglial activation via inhibiting the ERK1/2 signaling pathway. Supporting this, mice lacking in microglial E4bp4 are delirious prone, whereas mice with E4bp4 specifically deleted in hippocampal CA1 neurons have a normal phenotype. Mechanistically, E4bp4 inhibits ERK1/2 signaling by trans-repressing Mapk1/3 (genes encoding ERK1/2) via direct binding to a D-box element in the promoter region. These findings define a causal role of clock dysfunction in delirium development and indicate E4bp4 as a regulator of cognition at the crosstalk between circadian clock and delirium.

Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching Study.

BACKGROUND: Artificial intelligence (AI) methods can potentially be used to relieve the pressure that the COVID-19 pandemic has exerted on public health. In cases of medical resource shortages caused by the pandemic, changes in people's preferences for AI clinicians and traditional clinicians are worth exploring. OBJECTIVE: We aimed to quantify and compare people's preferences for AI clinicians and traditional clinicians before and during the COVID-19 pandemic, and to assess whether people's preferences were affected by the pressure of pandemic. METHODS: We used the propensity score matching method to match two different groups of respondents with similar demographic characteristics. Respondents were recruited in 2017 and 2020. A total of 2048 respondents (2017: n=1520; 2020: n=528) completed the questionnaire and were included in the analysis. Multinomial logit models and latent class models were used to assess people's preferences for different diagnosis methods. RESULTS: In total, 84.7% (1115/1317) of respondents in the 2017 group and 91.3% (482/528) of respondents in the 2020 group were confident that AI diagnosis methods would outperform human clinician diagnosis methods in the future. Both groups of matched respondents believed that the most important attribute of diagnosis was accuracy, and they preferred to receive combined diagnoses from both AI and human clinicians (2017: odds ratio [OR] 1.645, 95% CI 1.535-1.763; P<.001; 2020: OR 1.513, 95% CI 1.413-1.621; P<.001; reference: clinician diagnoses). The latent class model identified three classes with different attribute priorities. In class 1, preferences for combined diagnoses and accuracy remained constant in 2017 and 2020, and high accuracy (eg, 100% accuracy in 2017: OR 1.357, 95% CI 1.164-1.581) was preferred. In class 2, the matched data from 2017 were similar to those from 2020; combined diagnoses from both AI and human clinicians (2017: OR 1.204, 95% CI 1.039-1.394; P=.011; 2020: OR 2.009, 95% CI 1.826-2.211; P<.001; reference: clinician diagnoses) and an outpatient waiting time of 20 minutes (2017: OR 1.349, 95% CI 1.065-1.708; P<.001; 2020: OR 1.488, 95% CI 1.287-1.721; P<.001; reference: 0 minutes) were consistently preferred. In class 3, the respondents in the 2017 and 2020 groups preferred different diagnosis methods; respondents in the 2017 group preferred clinician diagnoses, whereas respondents in the 2020 group preferred AI diagnoses. In the latent class, which was stratified according to sex, all male and female respondents in the 2017 and 2020 groups believed that accuracy was the most important attribute of diagnosis. CONCLUSIONS: Individuals' preferences for receiving clinical diagnoses from AI and human clinicians were generally unaffected by the pandemic. Respondents believed that accuracy and expense were the most important attributes of diagnosis. These findings can be used to guide policies that are relevant to the development of AI-based health care.

AFW extraction based on MCA.

This paper improves the learning dictionary construction method for morphological component analysis (MCA) to separate the atrial and ventricular signals. The incoherence is added into the objective function to reduce the sparsity ratio between the atrial and ventricular dictionaries. By using the dictionaries, atrial and ventricular activities are separated from the location of the coefficients. We test the methods on both the synthetic and real atrial data. While extracting AFW from synthetic data, we use the Poisson relation as the measure. The result shows that we can obtain greater relation value using the method this paper presents than using the methods of ABS and PCA. We also conduct spectral analysis on AFW extracted from real atrial data.