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Anodic oxygen evolution reaction (OER) is recognized as kinetic bottleneck in water electrolysis. Transition metal sites with high valence states can accelerate the reaction kinetics to offer highly intrinsic activity, but suffer from thermodynamic formation barrier. Here, we show subtle engineering of highly oxidized Ni 4+ species in surface reconstructed (oxy)hydroxides on multicomponent FeCoCrNi alloy film through interatomically electronic interplay. Our spectroscopic investigations with theoretical studies uncover that Fe component enables the formation of Ni 4+ species, which is energetically favored by the multistep evolution of Ni 2+ →Ni 3+ →Ni 4+ . The dynamically constructed Ni 4+ species drives holes into oxygen ligands to facilitate intramolecular oxygen coupling, triggering lattice oxygen activation to form Fe-Ni dual-sites as ultimate catalytic center with highly intrinsic activity. As a result, the surface reconstructed FeCoCrNi OER catalyst delivers outstanding mass activity and turnover frequency of 3601 A g metal −1 and 0.483 s −1 at an overpotential of 300 mV in alkaline electrolyte, respectively. Electrocatalytic water oxidation is facilitated by high valence states, but these are challenging to achieve at low applied potentials. Here, authors report a multicomponent FeCoCrNi alloy with dynamically formed Ni 4+ species to offer high catalytic activity via lattice oxygen activation mechanism.

To compare non-pharmacological interventions in their ability to prevent delirium in critically ill patients, and find the optimal regimen for treatment. Literature searches were conducted using PubMed, Embase, CINAHL, and Cochrane Library databases until the end of June 2019. We estimated the risk ratios (RRs) for the incidence of delirium and in-hospital mortality and found the mean difference (MD) for delirium duration and the length of ICU stay. The probabilities of interventions were ranked based on clinical outcomes. The study was registered on PROSPERO (CRD42020160757). Twenty-six eligible studies were included in the network meta-analysis. Studies were grouped into seven intervention types: physical environment intervention (PEI), sedation reducing (SR), family participation (FP), exercise program (EP), cerebral hemodynamics improving (CHI), multi-component studies (MLT) and usual care (UC). In term of reducing the incidence of delirium, the two most effective interventions were FP (risk ratio (RR) 0.19, 95% confidence interval (CI) 0.08 to 0.44; surface under the cumulative ranking curve (SUCRA) = 94%) and MLT (RR 0.43, 95% CI 0.30 to 0.57; SUCRA = 68%) compared with observation. Although all interventions demonstrated nonsignificant efficacy in regards to delirium duration and the length of the patient's stay in the ICU, MLT (SUCRA = 78.6% and 71.2%, respectively) was found to be the most effective intervention strategy. In addition, EP (SUCRA = 97.2%) facilitated a significant reduction in hospital mortality, followed in efficacy by MLT (SUCRA = 73.2%), CHI (SUCRA = 35.8%), PEI (SUCRA = 34.8%), and SR (SUCRA = 31.8%). Multi-component strategies are overall the optimal intervention techniques for preventing delirium and reducing ICU length of stay in critically ill patients by way of utilizing several interventions simultaneously. Additionally, family participation as a method of patient-centered care resulted in better outcomes for reducing the incidence of delirium. •Systematic review of different preventive nonpharmacological interventions for ICU delirium.•Multi-component strategies are overall the optimal intervention for preventing delirium and reducing ICU length of stay.•Exercise program is recommended as the preferable intervention when considering feasibility and cost-effectiveness.•Family participation proved to be a promising intervention for reducing delirium incidence, but requires further research.

In recent years, a large number of studies have shown that the subcellular localization of long non-coding RNAs (lncRNAs) can bring crucial information to the recognition of lncRNAs function. Therefore, it is of great significance to establish a computational method to accurately predict the subcellular localization of lncRNA. Previous prediction models are based on low-level sequences information and are troubled by the few samples problem. In this study, we propose a new prediction model, GM-lncLoc, which is based on the initial information extracted from the lncRNA sequence, and also combines the graph structure information to extract high level features of lncRNA. In addition, the training mode of meta-learning is introduced to obtain meta-parameters by training a series of tasks. With the meta-parameters, the final parameters of other similar tasks can be learned quickly, so as to solve the problem of few samples in lncRNA subcellular localization. Compared with the previous methods, GM-lncLoc achieved the best results with an accuracy of 93.4 and 94.2% in the benchmark datasets of 5 and 4 subcellular compartments, respectively. Furthermore, the prediction performance of GM-lncLoc was also better on the independent dataset. It shows the effectiveness and great potential of our proposed method for lncRNA subcellular localization prediction. The datasets and source code are freely available at https://github.com/JunzheCai/GM-lncLoc .

To overcome the poor mechanical performance of methyltrimethoxysilane (MTMS) aerogels and the low thermal stability of polyvinyl alcohol (PVA), the PVA/MTMS aerogel composites (PMAC) were successfully prepared through a facile impregnation process. It finds that the PVA concentration has a great influence on the physicochemical properties of the PMAC, which has been investigated in detail. It further turns out that the density (0.081 ~ 0.152 g/cm3) increases linearly along with the PVA concentration, while the thermal conductivity (32.9 ~ 51.7 mW/m/K) increases monotonously first and then keeps almost unchanged. The hydrophilicity of PMAC can be tailored by adjusting the PVA concentration. Compared with the pure MTMS aerogel and PVA, the thermal analysis reveals that the PMAC shows an improved thermal stability. Although the physical combination is verified between the MTMS aerogel and PVA, the mechanical performance of the PMAC is still significantly enhanced with the Young’s modulus and compressive strength reaching up to 20.35 MPa and 970.33 kPa, respectively. All these results suggest that the introduction of PVA into MTMS aerogel is feasible and effective for acquiring better performance for the aerogel composites, which contributes to extending their potential applications.

Limited by low tumor immunogenicity and the immunosuppressive tumor microenvironment (TME), triple-negative breast cancer (TNBC) has been poorly responsive to immunotherapy so far. Herein, a Ca & Mn dual-ion hybrid nanostimulator (CMS) is constructed to enhance anti-tumor immunity through ferroptosis inducing and innate immunity awakening, which can serve as a ferroptosis inducer and immunoadjuvant for TNBC concurrently. On one hand, glutathione (GSH) depletion and reactive oxygen species (ROS) generation can be achieved due to the mixed valence state of Mn in CMS. On the other hand, as an exotic Ca2+ supplier, CMS causes mitochondrial Ca2+ overload, which further amplifies the oxidative stress. Significantly, tumor cells undergo ferroptosis because of the inactivation of glutathione peroxidase 4 (GPX4) and accumulation of lipid peroxidation (LPO). More impressively, CMS can act as an immunoadjuvant to awaken innate immunity by alleviating intra-tumor hypoxia and Mn2+-induced activation of the STING signaling pathway, which promotes polarization of tumor-associated macrophages (TAMs) and activation of dendritic cells (DCs) for antigen presentation and subsequent infiltration of tumor-specific cytotoxic T lymphocytes (CTLs) into tumor tissues. Taken together, this work demonstrates a novel strategy of simultaneously inducing ferroptosis and awakening innate immunity, offering a new perspective for effective tumor immunotherapy of TNBC. [Display omitted] •CMS serves as a ferroptosis inducer and immunoadjuvant for TNBC concurrently.•Synergistic GSH depletion, ROS burst and Ca2+ overload effectively induce ferroptosis.•Alleviating tumor hypoxia and activating the STING pathway help to awaken innate immunity.•The Ca & Mn nanostimulator shows excellent inhibitory effect on distant tumor growth.

Climate warming leads to crop yield loss. Although investigations have shown the region-specific effect of climate warming on maize yield in China, the determinants of this region-specific effect are poorly known. Using county-level data from 1980 to 2010 for China, we investigated the dependence of yield change under climate warming on soil indigenous nutrients. Analysis of the data indicated an average decrease of 2.6% in maize yield for 1 °C warming. Warming-related yield loss occurred mostly in western China, the North China Plain, and the southwest region of Northeast China. By contrast, climate warming did not decline maize yield in the northern region of Northeast China, south, and southwest China. Summer maize is more sensitive to warming than spring maize. A 1 °C warming resulted in an average loss of 3.3% for summer maize and 1.8% for spring maize. The region-specific change in yield can be well quantified by a combination of soil indigenous total nitrogen (STN), available phosphorus (SAP), and available potassium (SAK). Under climate warming, maize yields in regions with high STN generally increased, while the risk of yield reduction appeared in regions with high SAK. Areas that were vulnerable (defined as a yield loss higher than 1% for a 1 °C increase) to climate warming accounted for 62%, while areas that showed resilience (defined as a yield increase higher than 1% for a 1 °C increase) to climate warming accounted for 27% of the planting area. An increase in nitrogen fertilizer application is expected to reduce the risk of yield reduction in regions with low STN. Our findings highlight soil resilience to climate warming and underline the practice of fertilizer management to mitigate yield loss due to climate warming.

The corrosion of steel caused by sulfate-reducing bacteria (SRB) has been a big trouble resulting in the service failure of engineering equipment, and SRB biofilm is the direct reason leading to the corrosion acceleration. In this work, SRB biofilms formed on N80 carbon steel in an artificial shale gas field produced water with different test conditions were characterized carefully by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), fluorescence microscope, and three-dimensional stereoscopic microscope. Results demonstrate that test time, temperature, and initial SRB cell concentration can influence the growth and surface morphology of biofilm, and test time and temperature are primary factors. There is a highest corrosion rate of 0.100 ± 0.005 mm/y on the seventh day due to the high biological activity, and then corrosion rates gradually decline with time. The formed biofilms at different time have a similar morphology and the contents of elemental S in biofilms are high also suggesting SRB corrosion. Temperature can influence the biological activity of SRB, and then affect the formation of SRB biofilms. SRB has a higher biological activity at 20 and 37 °C than that of at 60 and 80 °C. The influence of initial SRB cell count differences on biofilm is weak.

•Iron overloaded rat groups showed significantly higher hippocampal magnetic susceptibility values compared to the control group.•Rats with iron overload had longer escape latencies and fewer platform crossings in the morris water maze, indicating impaired spatial reference memory.•Quantitative susceptibility mapping (QSM) effectively quantified brain iron overload in vivo, highlighting its potential for assessing cognitive impairment in thalassemia patients. The aim of this study was to establish an iron overload rat model to simulate the elevated iron levels in patients with thalassemia and to investigate the potential association between hippocampal iron deposition and cognition. Two groups of iron overloaded rats and one group of control rats were used for this study. The Morris water maze (MWM) was used to test spatial reference memory indicated by escape latency time and number of MWM platform crossings. The magnetic susceptibility value of the hippocampal tissue, a measure of iron deposition, was assessed by quantitative susceptibility mapping (QSM) and was correlated with spatial reference memory performance. The iron content in hippocampal tissue sections of the rats were assessed using diaminobenzidine (DAB)-enhanced Perl's Prussian blue (PPB) staining. The rat groups with iron overload including the Group H and Group L had higher hippocampal magnetic susceptibility values than the control rat group, i.e., Group D. In addition, the iron overloaded groups had longer MWM escape latency than the control group, and reduced number of MWM platform crossings. There was a positive correlation between the mean escape latency and the mean hippocampal magnetic susceptibility value, a negative correlation between the number of platform crossings and the mean hippocampal magnetic susceptibility value, and a negative correlation between the number of platform crossings and the latent escape time in Group H and Group L. This rat model simulating iron overload in thalassemia showed hippocampal iron overload being associated with impairment of spatial reference memory. QSM could be used to quantify brain iron overload in vivo, highlighting its potential clinical application for assessing cognitive impairment in patients with thalassemia.

The detection and defense of malicious attacks are critical to the proper functioning of network security. Due to the diversity and rapid updates of the attack methods used by attackers, traditional defense mechanisms have been challenged. In this context, a more effective method to predict vulnerabilities in network systems is considered an urgent need to protect network security. In this paper, we propose a formal modeling and analysis approach based on Petri net vulnerability exploitation. We used the Common Vulnerabilities and Exposures (CVE)-2021-3711 vulnerability source code to build a model. A patch model was built to address the problems of this model. Finally, the time injected by the actual attacker and the time simulated by the software were calculated separately. The results showed that the simulation time was shorter than the actual attack time, and ultra-real-time simulation could be achieved. By modeling the network system with this method, the model can be found to arrive at an illegitimate state according to the structure of Petri nets themselves and thus discover unknown vulnerabilities. This method provides a reference method for exploring unknown vulnerabilities.

In this work, toppling failure of a jointed rock slope is studied by using the distinct lattice spring model (DLSM). The gravity increase method (GIM) with a sub-step loading scheme is implemented in the DLSM to mimic the loading conditions of a centrifuge test. A classical centrifuge test for a jointed rock slope, previously simulated by the finite element method and the discrete element model, is simulated by using the GIM-DLSM. Reasonable boundary conditions are obtained through detailed comparisons among existing numerical solutions with experimental records. With calibrated boundary conditions, the influences of the tensional strength of the rock block, cohesion and friction angles of the joints, as well as the spacing and inclination angles of the joints, on the flexural toppling failure of the jointed rock slope are investigated by using the GIM-DLSM, leading to some insight into evaluating the state of flexural toppling failure for a jointed slope and effectively preventing the flexural toppling failure of jointed rock slopes.