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Abstract Transpiration (T) is pivotal in the global water cycle, responding to soil moisture, atmospheric stress, climate changes, and human impacts. Therefore, establishing a reliable global transpiration dataset is essential. Collocation analysis methods have been proven effective for assessing the errors in these products, which can subsequently be used for multisource fusion. However, previous results did not consider error cross-correlation, rendering the results less reliable. In this study, we employ collocation analysis, taking error cross-correlation into account, to effectively analyze the errors in multiple transpiration products and merge them to obtain a more reliable dataset. The results demonstrate its superior reliability. The outcome is a long-term daily global transpiration dataset at 0.1°from 2000 to 2020. Using the transpiration after partitioning at FLUXNET sites as a reference, we compare the performance of the merged product with inputs. The merged dataset performs well across various vegetation types and is validated against in-situ observations. Incorporating non-zero ECC considerations represents a significant theoretical and proven enhancement over previous methodologies that neglected such conditions, highlighting its reliability in enhancing our understanding of transpiration dynamics in a changing world.

Study region: The Tarim River Basin Study focus: Under the warming climate, understanding the impact of glacier storage changes on runoff is essential for maintaining ecosystems and freshwater supplies to lowland areas in cold regions. However, the lack of glacier data significantly hampers long-term analysis of this impact. To address this issue, we proposed a practical method within the Budyko framework to quantify the warming-induced changes in glacier storage. Based on this framework, we further developed a transparent elasticity approach to quantify how runoff responds to the glacier changes, with observations from 17 glacier-covered catchments in the Tarim River Basin, China. New hydrological insights for the region: Our results show that a 1℃ temperature rise in this region would lead to a 5–29 % increase in runoff attributable to warming-induced glacier storage change. On average, the glacier storage change contributes to approximately 25 % of runoff increases during 1960–2019. However, this positive trend may not be consistently sustained due to the non-linear and accelerated glacier loss in response to warming. The approach we present here provides efficient estimates for glacier-related hydrological changes in the Tarim River Basin and is transferable to other glacier-impacted regions due to its transparent methodology and low input requirements.

IntroductionMonitoring the leaf area index (LAI), which is directly related to the growth status of rice, helps to optimize and meet the crop’s fertilizer requirements for achieving high quality, high yield, and environmental sustainability. The remote sensing technology of the unmanned aerial vehicle (UAV) has great potential in precision monitoring applications in agriculture due to its efficient, nondestructive, and rapid characteristics. The spectral information currently widely used is susceptible to the influence of factors such as soil background and canopy structure, leading to low accuracy in estimating the LAI in rice.MethodsIn this paper, the RGB and multispectral images of the critical period were acquired through rice field experiments. Based on the remote sensing images above, the spectral indices and texture information of the rice canopy were extracted. Furthermore, the texture information of various images at multiple scales was acquired through resampling, which was utilized to assess the estimation capacity of LAI.Results and discussionThe results showed that the spectral indices (SI) based on RGB and multispectral imagery saturated in the middle and late stages of rice, leading to low accuracy in estimating LAI. Moreover, multiscale texture analysis revealed that the texture of multispectral images derived from the 680 nm band is less affected by resolution, whereas the texture of RGB images is resolution dependent. The fusion of spectral and texture features using random forest and multiple stepwise regression algorithms revealed that the highest accuracy in estimating LAI can be achieved based on SI and texture features (0.48 m) from multispectral imagery. This approach yielded excellent prediction results for both high and low LAI values. With the gradual improvement of satellite image resolution, the results of this study are expected to enable accurate monitoring of rice LAI on a large scale.

Crafting landslide susceptibility mapping is pivotal for the effective management of landslide risks. However, the influence of non-landslide sample selection on the modeling performance of landslide susceptibility assessment models remains a crucial challenge to overcome. This article employs Huize County as the research area and identifies 12 factors that exert influence. In this study, we utilized Extreme Gradient Boosting and Random Forest algorithms, and four methods (Whole-area random selection method, Buffer method, Frequency Ratio method, and Analysis Hierarchy Process) were employed to select non-landslide samples for constructing the landslide susceptibility assessment model. The findings revealed that the model performance derived from different non-landslide sample selections exhibited significant variations, and the models obtained using the buffer zone method, frequency ratio method, and AHP method performed better than the full-area random selection model. Among the evaluated models, the AHP method for non-landslide sample selection demonstrated the most optimal performance, with an AUC of 92.17% for XGBoost-AHP and 91.64% for RF-AHP. Based on the SHapley Additive explanation (SHAP), the main variables impacting landslide danger in the research area were elevation, NDVI, and peak seismic acceleration. This study provides theoretical support for the selection of non-landslide samples in landslide susceptibility assessments and interpretable AI research.

Producing low-carbon clinker-free engineering material is beneficial to environmental protection and energy conservation. This paper reports the utilization of natural Pisha sandstone (PS) as a new precursor to manufacture an environment-friendly engineering composite material in combination with solid waste (BFS, FA, and SF). The curing conditions of PSCM have been reported to a limited extent in a few studies. In this study, special attention was given to the mechanical properties and hydration progress of three different Pisha sandstone composite materials (PSCM) under different curing conditions. The prepared samples were subjected to different heat-curing temperatures (20 ℃, 40 ℃,60 ℃, and 80 ℃) for 24 h, different water curing time (1 day, 21 day, and 27 day), and aging effect (7–14-28–90 days). The results indicated that solid waste addition significantly increased the compressive strength under all curing conditions. However, high-temperature cure facilitated samples gained much of strength with less curing duration, whereas high-temperature caused shrinkage cracks at later age, which was detrimental to strength development. The satisfactory compressive strength was obtained under the combination of heating and water curing (80 ℃ for 24 h followed by water curing for 24 h) and especially containing 10% SF (22.38 MPa). The mineral crystallographic characterization and microstructure revealed that the development of strength depends on the amount of hydration products and high-temperature cure favors the formation of gels.

We report the controlled fabrication of nitrogen doped graphene (NG) nanoplates, which are uniformly decorated with iron nitride (Fe3N) nanoparticles, via ball milling of mixtures of graphite and iron nitrates and the following ammonia annealing. The obtained Fe3N@NG composites demonstrate excellent electrocatalytic activity and durability for oxygen evolution reaction, both of which outperform those of the state-of-the-art iridium oxide catalysts. This may be attributed to nitrogen doping as well as the synergistic effect between Fe3N and graphene nanoplates.

Electrochemical nitrate reduction to ammonia (NRA) can realize the green synthesis of ammonia (NH3) at ambient conditions, and also remove nitrate contamination in water. However, the current catalysts for NRA still face relatively low NH3 yield rate and poor stability. We present here a core–shell heterostructure comprising cobalt oxide anchored on copper oxide nanowire arrays (CuO NWAs@Co3O4) for efficient NRA. The CuO NWAs@Co3O4 demonstrates significantly enhanced NRA performance in alkaline media in comparison with plain CuO NWAs and Co3O4 flocs. Especially, at −0.23 V vs. RHE, NH3 yield rate of the CuO NWAs@Co3O4 reaches 1.915 mmol h−1 cm−2, much higher than those of CuO NWAs (1.472 mmol h−1 cm−2), Co3O4 flocs (1.222 mmol h−1 cm−2) and recent reported Cu-based catalysts. It is proposed that the synergetic effects of the heterostructure combing atom hydrogen adsorption and nitrate reduction lead to the enhanced NRA performance.

The origin of agricultural products significantly influences their quality and safety. Fluorescence spectroscopy was used to analyse Japonica rice 830, grown in different areas of Jilin Province, by examining rice seed, brown rice, and rice flour from 12 origins. Fluorescence spectra were pre-processed through normalisation and smoothing to remove noise. These processed spectra were input into decision trees, support vector machines (SVMs), K-nearest neighbour (KNN), and neural network models for classification. The analysis revealed that the combined four models achieved an average classification accuracy of 98.05% with a computation time of 180 s, while the reduced-scale models improved accuracy to 98.36% and reduced computation time to 11.25 s. Additionally, prediction models using standard rice starch content values across different states achieved R² values over 0.8. This method provides a rapid, precise approach for assessing rice quality and origin, demonstrating significant potential for application in rice analysis.

Dopamine (DA) is a widely present, calcium cholinergic neurotransmitter in the body, playing important roles in the central nervous system and cardiovascular system. Developing fast and sensitive DA detection methods is of great significance. Fluorescence-based methods have attracted much attention due to their advantages of easy operation, a fast response speed, and high sensitivity. This study prepared hydrophilic and high-performance CdS/ZnS quantum dots (QDs) for DA detection. The waterborne CdS/ZnS QDs were synthesized in one step using the amphiphilic polymer PEI-g-C14, obtained by grafting tetradecane (C14) to polyethyleneimine (PEI), as a template. The polyacrylonitrile nanofiber membrane (PAN-NFM) was prepared by electrospinning (e-spinning), and a metal organic frame (ZIF-8) was deposited in situ on the surface of the PAN-NFM. The CdS/ZnS QDs were loaded onto this substrate (ZIF-8@PAN-NFM). The results showed that after the deposition of ZIF-8, the water contact angle of the hydrophobic PAN-NFM decreased to within 40°. The nanofiber membrane loaded with QDs also exhibited significant changes in fluorescence in the presence of DA at different concentrations, which could be applied as a fast detection method of DA with high sensitivity. Meanwhile, the fluorescence on this PAN-NFM could be visually observed as it transitioned from a blue-green color to colorless, making it suitable for the real-time detection of DA.

The lower limb exoskeleton (LLE) plays an important role in production activities requiring assistance and load bearing. One of the challenges is to propose a control strategy that can meet the requirements of LLE trajectory tracking in different scenes. Therefore, this study proposes a control strategy (DBO–FPID) that combines the dung beetle optimizer (DBO) with feedforward proportional–integral–derivative controller (FPID) to improve the performance of LLE trajectory tracking in different scenes. The Lagrange method is used to establish the dynamic model of the LLE rod, and it is combined with the dynamic equations of the motor to obtain the LLE transfer function model. Based on the LLE model and target trajectory compensation, the feedforward controller is designed to achieve trajectory tracking in different scenes. To obtain the best performance of the controller, the DBO is utilized to perform offline parameter tuning of the feedforward controller and PID controller. The proposed control strategy is compared with the DBO tuning PID (DBO–PID), particle swarm optimizer (PSO) tuning FPID (PSO–FPID), and PSO tuning PID (PSO–PID) in simulation and joint module experiments. The results show that DBO–FPID has the best accuracy and robustness in trajectory tracking in different scenes, which has the smallest sum of absolute error (IAE), mean absolute error (MEAE), maximum absolute error (MAE), and root mean square error (RMSE). In addition, the MEAE of DBO–FPID is lower than 1.5 degrees in unloaded tests and lower than 3.6 degrees in the hip load tests, with only a few iterations, showing great practical potential.

Dolomite dust waste (DDW) has the potential to be used as an expansive agent for mortar due to its richness in magnesium and calcium. This paper reports the possibility of developing low-cost expansive agent for mortar using DDW through various activation methods. The changes in the physicochemical properties of the activated DDW and the shrinkage resistance, flexural strength, and compressive strength of the composite mortar prepared by partially replacing cement were systematically investigated. The hydration products and microstructure of DDW-composite mortar were investigated by XRD and SEM-EDS techniques. This study confirmed the feasibility of activated DDW as mortar expansion agents and the necessity of activation treatment for the resourceful use of DDW. The results showed that the activation treatment enhanced the activity of DDW, and the higher hydration reactivity significantly improved the shrinkage resistance and mechanical properties of composite mortar compared to raw DDW. The addition of 10% C800 DDW (thermal at 800 °C) showed a full-age compensatory effect on the volume shrinkage of the mortar. Substituting cement partially with 10% C900 DDW (thermal at 900 °C), the volume expansion rate of composite mortar after 28 d of standard curing exhibited 24.49% higher than normal, and its compressive strength (40.1 MPa) at 60 d exceeded 6.40% than normal mortar (37.7 MPa). The drying shrinkage of G30-10 (mechanically activated) and A0.1-10 (chemically activated) at 60 d resulted in 6.23% and 5.19% lower than normal mortar, respectively. Microanalysis revealed that the addition of DDW promoted the generation of C-M-S-H gels. The findings are instructive for the preparation of green and low-cost mortar expanders using DDW.

The issue of bacterial resistance is an escalating problem due to the misuse of antibiotics worldwide. This study introduces a new antibacterial mechanism, the ferroptosis-like death (FLD) of bacteria, and an approach to creating green antibacterial nano-reactors. This innovative method leverages natural iron-containing ovotransferrin (OVT) assembled into an organic skeleton to encapsulate low-concentration adriamycin (ADM) for synthesizing eco-friendly nano-reactors. FLD utilizes the Fenton reaction of reactive oxygen species and ferrous ions to continuously produce ·OH, which can attack the bacterial cell membrane and destroy the cell structure to achieve bacteriostasis. The OVT@ADM nano-reactors are nearly spherical, with an average diameter of 247.23 nm and uniform particle sizing. Vitro simulations showed that Fe3+ in OVT@ADM was reduced to Fe2+ by glutathione in the bacterial periplasmic space, which made the structure of OVT loose, leading to a sustained slow release of ADM from OVT@ADM. The H2O2 continuously produced by ADM oxidized Fe2+ through the Fenton reaction to produce ·OH and Fe3+. The results of the antibacterial assay showed that OVT@ADM had a satisfactory antibacterial effect against S. aureus, and the inhibition rate was as high as 99.3%. The cytotoxicity results showed that the mitigation strategy significantly reduced the cytotoxicity caused by ADM. Based on the FLD mechanism, OVT@ADM nano-reactors were evaluated and applied to bacteriostasis. Therefore, the novel antibacterial mechanism and OVT@ADM by the green synthesis method have good application prospects.

The origin of agricultural products is crucial to their quality and safety. This study explored the differences in chemical composition and structure of rice from different origins using fluorescence detection technology. These differences are mainly affected by climate, environment, geology and other factors. By identifying the fluorescence characteristic absorption peaks of the same rice seed varieties from different origins, and comparing them with known or standard samples, this study aims to authenticate rice, protect brands, and achieve traceability. The study selected the same variety of rice seed planted in different regions of Jilin Province in the same year as samples. Fluorescence spectroscopy was used to collect spectral data, which was preprocessed by normalization, smoothing, and wavelet transformation to remove noise, scattering, and burrs. The processed spectral data was used as input for the long short-term memory (LSTM) model. The study focused on the processing and analysis of rice spectra based on NZ-WT-processed data. To simplify the model, uninformative variable elimination (UVE) and successive projections algorithm (SPA) were used to screen the best wavelengths. These wavelengths were used as input for the support vector machine (SVM) prediction model to achieve efficient and accurate predictions. Within the fluorescence spectral range of 475–525 nm and 665–690 nm, absorption peaks of nicotinamide adenine dinucleotide (NADPH), riboflavin (B2), starch, and protein were observed. The origin tracing prediction model established using SVM exhibited stable performance with a classification accuracy of up to 99.5%.The experiment demonstrated that fluorescence spectroscopy technology has high discrimination accuracy in tracing the origin of rice, providing a new method for rapid identification of rice origin.

Pisha sandstone (PS) is a special interbedded rock in the middle reaches of the Yellow River that experiences severe weathering and is loose and broken. Due to severe multiple erosion events, the Pisha sandstone region is called “the most severe water loss and soil erosion in the world” and “the ecological cancer of the earth”. As a special pozzolanic mineral, PS has the potential to be used as precursors for the synthesis of green and low-carbon geopolymer gel materials and applied in ecological restoration. This paper aims to undertake a phase review of the precursors for geopolymer gel materials. The genesis and distribution, physical and chemical characterization, erosion characteristics, and advances in the ecological restoration of PS are all summarized. Furthermore, current advances in the use of PS for the synthesis of geopolymer gel materials in terms of mechanical properties and durability are discussed. The production of Pisha sandstone geopolymer gels through the binder jetting technique and 3D printing techniques is prospected. Meanwhile, the prospects for the resource application of PS in mine rehabilitation and sustainable ecology are discussed. In the future, multifactor-driven comprehensive measures should be further investigated in order to achieve ecological restoration of the Pisha sandstone region and promote high-quality development of the Yellow River Basin.

ABSTRACT: Catalytic filters including catalytic bag filters and catalytic filter candles, which couple the filters with denitrification catalysts to obtain the ability to simultaneously remove SOx, NOx and dust, have become the promising applied technology for the integrated flue gas treatment because of their huge advantages in reducing the initial investment, floor occupancy and maintenance cost. In this review, we will summarize the recent advances in the development of catalytic filters in terms of their process principles, filter material, denitrification catalysts, structure-function relationships and industrial applications. Moreover, suggestions about the current challenges and future opportunities are also given from the viewpoints of catalysts and filter material design, catalytic filter preparation methods, and their poisoning and regeneration, etc. With the further development of theory and engineering research, the extensive industrial application of catalytic filters in the field of multiple pollutants flue gas treatment is highly anticipated in the future.

Abstract Dielectric capacitors play an important role in advanced electronic and power systems such as portable electronic devices, hybrid electric vehicles and electronic weapon systems, and the improvement of energy storage density will have a positive effect on reducing the volume and weight of equipment. Here, a series of single‐layer dielectrics with boron nitride nanosheets (BNNSs) uniformly dispersed and multilayer dielectrics with BNNSs showing a positive gradient distribution (PGD) and inverse gradient distribution (IGD) in the poly(vinylidene fluoride‐trifluoroethylene‐chlorotrifluoroethylene) (P[VDF‐TrFE‐CTFE]) matrix were prepared by high‐speed electrospinning and hot press technology. It is found that the best performance is observed inthe lowest interlayer gradient component in both PGD and IGD composite dielectrics. However, the performance of PGD is better than that of IGD, and the 3‐5‐3 multilayer dielectric in the positive gradient structure has the best electrical performance. Its maximum energy storage density of the 3‐5‐3 composite dielectrics is 12.93 J/cm3 at the applied electric field of 380 kV/mm. The above research results show that the gradient structure design plays an important role in optimising the breakdown strength and energy storage characteristics of composite dielectrics.

In recent years, the number of electronic devices and users has increased sharply with the rapid development and progress of electronic information technology. The motivation of this paper is to optimize the organization’s resource allocation strategy in the Internet of Things (IoT) environment. The optimal path planning and information processing efficiency are improved through Unmanned Aerial Vehicle (UAV) technology and migration optimization algorithm. The research method is migration optimization algorithm and UAV dynamic network. The information processing capability of traditional wireless communication systems has gradually been unable to meet the actual information processing needs. Therefore, a static network migration algorithm is constructed based on multiple-user multilateral edge computing servers. It migrates each user’s information processing task to the neighboring edge confidence processing server and uses the information processing server to perform auxiliary calculations. The simulation model adds a utility function that simulates energy consumption, delay weighting, and maximum extreme value, combined with the allocation strategy of optimizing each user’s information processing task to achieve the optimization goal. The static network migration algorithm established in this simulation has better results than other benchmark algorithms. Both scenario 1 and scenario 2 in the simulation show very close performance to the optimal solution. Meanwhile, a migration algorithm that can provide wireless charging for UAVs is built by a dynamic edge computing model based on the time associated with the UAV base station and multiple end users. Combined with completing the information processing tasks in each time slot, the energy arrival is also non-directional. The dynamic network migration algorithm can optimize the number of tasks absorbed by the end-user based on the current online status of the system without knowing the global information. The optimized target equation is related to the queue stability, and the parameter V has a linear relationship with the queue backlog length. Here, the problem of computing migration is studied in Mobile Edge Computing (MEC). The results show that the utility function of the weighted sum has an approximately linear relationship with the weights. As the value of the utility function increases, so does the weight function. The optimal data throughput of the proposed model is 70,000 bits, while the optimal data throughput of the state-of-the-art model is 68,000 bits. Therefore, the data transmission performance of the model presented here is better than that of other models. MEC can be significantly improved the efficiency of organizational resource allocation. Combining UAV and wireless charging technology, the computing and communication resource allocation issues of the UAV’s edge computing system are comprehensively discussed to improve the performance and efficiency of the network.

IntroductionPost-stroke aphasia (PSA) is a language disorder caused by left hemisphere stroke. Electroacupuncture (EA) is a minimally invasive therapeutic option for PSA treatment. Tongli (HT5) and Xuanzhong (GB39), two important language-associated acupoints, are frequently used in the rehabilitation of patients with PSA. Preliminary evidence indicated functional activation in distributed cortical areas upon HT5 and GB39 stimulation. However, research on the modulation of dynamic and static functional connectivity (FC) in the brain by EA in PSA is lacking.MethodThis study aimed to investigate the PSA-related effects of EA stimulation at HT5 and GB39 on neural processing. Thirty-five participants were recruited, including 19 patients with PSA and 16 healthy controls (HCs). The BOLD signal was analyzed by static independent component analysis, generalized psychophysiological interactions, and dynamic independent component analysis, considering variables such as age, sex, and years of education.ResultsThe results revealed that PSA showed activated clusters in the left putamen, left postcentral gyrus (PostCG), and left angular gyrus in the salience network (SN) compared to the HC group. The interaction effect on temporal properties of networks showed higher variability of SN (F = 2.23, positive false discovery rate [pFDR] = 0.017). The interaction effect on static FC showed increased functional coupling between the right calcarine and right lingual gyrus (F = 3.16, pFDR = 0.043). For the dynamic FC, at the region level, the interaction effect showed lower variability and higher frequencies of circuit 3, with the strongest connections between the supramarginal gyrus and posterior cingulum (F = 5.42, pFDR = 0.03), middle cingulum and PostCG (F = 5.27, pFDR = 0.036), and triangle inferior frontal and lingual gyrus (F = 5.57, pFDR = 0.026). At the network level, the interaction effect showed higher variability in occipital network–language network (LN) and cerebellar network (CN) coupling, with stronger connections between the LN and CN (F = 4.29, pFDR = 0.042). Dynamic FC values between the triangle inferior frontal and lingual gyri were anticorrelated with transcribing, describing, and dictating scores in the Chinese Rehabilitation Research Center for Chinese Standard Aphasia Examination.DiscussionThese findings suggest that EA stimulation may improve language function, as it significantly modulated the nodes of regions/networks involved in the LN, SN, CN, occipital cortex, somatosensory regions, and cerebral limbic system.

Room-temperature sodium-sulfur batteries are promising electrochemical energy storage systems. Here, the authors proposed a Fe3N/carbon composite to regulate the polysulfides chemistry and improve the performances of sodium-sulfur cells.

Abstract The maximum delivery pressure and the maximum rotational speed determine the power density of axial piston pumps. However, increasing the speed beyond the limit always accompanies cavitation, leading to the decrease of the volumetric efficiency. The pressure loss in the suction duct is considered a significant reason for the cavitation. Therefore, this paper proposes a methodology to optimize the shape of the suction duct aiming at reducing the intensity of cavitation and increasing the speed limit. At first, a computational fluid dynamics (CFD) model based on the full cavitation model (FCM) is developed to simulate the fluid field of the axial piston pump and a test rig is set to validate the model. Then the topology optimization is conducted for obtaining the minimum pressure loss in the suction duct. Comparing the original suction duct with the optimized one in the simulation model, the pressure loss in the suction duct gets considerable reduction, which eases the cavitation intensity a lot. The simulation results prove that the speed limit can increase under several different inlet pressures.

FPN (Feature Pyramid Network) and transformer-based target detectors are commonly employed in target detection tasks. However, these approaches suffer from design flaws that restrict their performance. To overcome these limitations, we proposed TIG-DETR (Texturized Instance Guidance DETR), a novel target detection model. TIG-DETR comprises a backbone network, TE-FPN (Texture-Enhanced FPN), and an enhanced DETR detector. TE-FPN addresses the issue of texture information loss in FPN by utilizing a bottom-up architecture, Lightweight Feature-wise Attention, and Feature-wise Attention. These components effectively compensate for texture information loss, mitigate the confounding effect of cross-scale fusion, and enhance the final output features. Additionally, we introduced the Instance Based Advanced Guidance Module in the DETR-based detector to tackle the weak detection of larger objects caused by the limitations of window interactions in Shifted Window-based Self-Attention. By incorporating TE-FPN instead of FPN in Faster RCNN and employing ResNet-50 as the backbone network, we observed an improvement of 1.9 AP in average accuracy. By introducing the Instance-Based Advanced Guidance Module, the average accuracy of the DETR-based target detector has been improved by 0.4 AP. TIG-DETR achieves an impressive average accuracy of 44.1% with ResNet-50 as the backbone network.

Polylactic acid (PLA) is a biodegradable polymer made from natural sources, and its electrospinning (e-spinning) nanofiber membrane doped with antibacterial ingredients is widely used in the field of medical dressings. In this research, 9 wt% of rosmarinic acid (RosA) and 0.04 wt% of graphite oxide (GO) with synergistic antibacterial activity were introduced into the e-spinning PLA precursor solution, and the obtained PLA nanofiber membrane showed good antibacterial properties and wound healing effects. At the same time, a nonionic amphiphilic polymer, polyethylene glycol (PEG), was also introduced into this system to improve the hydrophilicity of the e-spinning membrane for wound healing application. The morphological characterization showed the RosA/GO and PEG did not affect the e-spinning of PLA. The tests of mechanical performance and wettability demonstrated that PEG and RosA/GO incorporated in PLA have migrated easily to the surface of the fiber. The e-spun PLA/PEG/RosA/GO membrane showed good antibacterial activity and promoted initial wound healing quickly, which would be a promising application in wound dressing.

Waste Pisha sandstone (WPS) is the main damming material for the check dam in the Loss Plateau of northwest China. The dissolution characteristics of WPS in alkaline solutions were investigated as a basis for studying WPS modification materials and revealing the modification mechanism to further study the pozzolanic activity of WPS and the development of cementitious materials for concrete utilizing WPS. In this paper, WPS was milled and calcined at 600 °C, 700 °C, and 800 °C, respectively. After that, the activated WPS was immersed in 0.05, 0.1, 0.5, 1.0, 2.0, and 5.0 M NaOH solutions for leaching tests. The two curing temperatures of 20 °C and 80 °C were set, respectively. The ion concentration of Si, Al, and Ca in the alkaline solutions was determined using chemical titration, silicon–molybdenum blue colorimetric method, and graphite furnace atomic absorption spectrometry, respectively. After the leaching tests, the residues of WPS were characterized using XRD and SEM-EDS. The results show that the concentration of each ion in the leachate did not increase with leaching time but showed fluctuating variations with leaching time. Mechanochemical activation and thermal activation will promote the dissolution of minerals in alkaline solutions and increase the leaching efficiency of Si. However, the soluble Si in the leachate is not able to generate further gelling-like substances, limited by the total amount of available Ca in the mineral. WPS can dissolve more ions in higher concentrations of a NaOH solution, but the mineral crystallinity of its residue will be reduced. Higher curing temperatures can greatly increase the leaching efficiency of Si in a short time, which is better than thermal activation, and it can also promote the generation of newborn minerals and increase the crystallinity of minerals in WPS after leaching.

Red mud (RM) with the high alkalinity as a catalyst was evaluated for coal pyrolysis in a fixed bed as well as CO2 gasification of its resultant char in a thermogravimetric analyzer (TGA). The addition of RM into coal could improve the quality of tar during pyrolysis and enhance the reactivity of char during gasification. For catalytic pyrolysis with 12 wt% RM at 600 °C, the light fraction in tar was 72.0 wt%, which increased by 20.0%, compared with coal pyrolysis alone. The role of metal oxides in RM on coal pyrolysis was further clarified as well. After catalytic pyrolysis with RM, the specific surface area of resultant char increased, especially for mesoporous surface area, and meanwhile the sodium in RM was proved to migrate to the char surface. These positive factors contributed to the CO2 gasification activity of char. RM with the high alkalinity showed a promising catalyst candidate for coal pyrolysis and gasification in terms of its catalytic effects and low cost.

Two-dimensional materials (2DMs) have attracted substantial attention due to their abundant active sites and their ultrahigh surface area for different catalytic applications due to the high lateral-longitudinal ratio. Transition metal dichalcogenides (TMDs), especially MoS2, as one of the 2DMs most often studied, have shown superior activity in electrochemical applications. Recently, combinations of different 2DMs have been widely studied, and they appear to be the most promising strategy available to develop state of the art catalysts for different reactions.In this article, we review the interactions between MoS2 and other materials as well as the novel assembly induced phase transitions of TMDs and their underlying mechanisms. Several methods for inducing the phase transition of TMDs by building MoS2-based heterostructures have been introduced. The electronic coupling between these counterparts has significantly enhanced their conductivity and optimized the energy states of the materials, thus introducing enhanced activity as compared to their original counterparts. The ideas summarized in this article may shed new light on and help to develop next-generation green energy materials by designing and constructing highly active two-dimensional catalysts for efficient water splitting. Keywords: Molybdenum disulfide, Heterostructure, Phase transition, Interaction, Water splitting

The treatment of silted sediment in the river is a global problem. The accumulation of waste sediment will lead to an adverse impact on the environment. In this paper, the silted sediment was reused to produce geopolymer composite materials via alkali-activated gelling modification. The effects of the modifiers of sodium silicate solution, quicklime, and Na2SO4 admixture, and the dosage of the slag, fly ash, and silica fume admixture, and curing conditions and age, on the compressive strength and microstructure of the geopolymer-modified sediment materials were studied. The crystalline phase and hydration products of the modified sediment geopolymer composites were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), respectively. A compressive strength test was conducted to evaluate the mechanical properties of the composites. The results showed that the type and dosage of modifier, amount of mineral admixture additive, cure conditions, and cure age had significant effects on the mechanical properties of the composites. The effect of the addition of mineral admixture on the compressive strength of the modified sediment specimens was more noticeable than that of the modifier. The compressive strength of the geopolymer-modified specimens was greatly increased by the addition of mineral dopants. When 10 wt.% silica fume is added, the compressive strength reaches a maximum value of 33.25 MPa at 60 days. The SEM-EDS results show that the C-S-H gels and C-A-S-H gels were the main hydration products. The results indicate that river siltation sediment is an excellent raw material for geopolymer-modified materials. It is feasible to produce reliable and sustainable hydraulic engineering materials by using river sediment geopolymer-modified materials.

Electrocatalytic reduction of nitrate to ammonia is a promising approach to both green synthesis of ammonia and nitrate pollution disposal. However, current cathode catalysts display relatively low selectivity and Faradaic efficiency. We demonstrate here that nanocrystalline silver (nano-Ag) can achieve both high selectivity and high Faradaic efficiency. Nano-Ag at −0.33 V vs. RHE delivers a current density of −194.31 mA cm−2, exhibits a Faradaic efficiency of up to 96.4% and has selectivity of 89.6%. It also exhibits good stability, retaining 91.1% of the original selectivity and about 100% of the original Faradaic efficiency after 4 cycles, suggesting that nano-Ag is a highly efficient catalyst for reduction of nitrate to ammonia.

High-Ti (Ti/Y) flood basalts are widely distributed in the Late Permian Emeishan large igneous province (LIP), SW China, and their spatial distribution and genetic mechanism are important to reveal the role of plume-lithosphere interactions in the LIP origin. Western Guangxi is located on the eastern edge of Emeishan LIP. To explore the genesis of the high-Ti basalt in western Guangxi and any genetic link with the Emeishan LIP, we performed whole-rock geochemical and Sr-Nd isotope and zircon U-Pb-Hf isotope analyses on the Longlin basalts from western Guangxi. The results indicate that the Longlin basalt from Tongdeng area has relatively high SiO2 but low MgO and TFe2O3 contents. The rocks have zircon εHf(t) = −0.42 to 6.41, whole-rock (87Sr/86Sr)i = 0.707167–0.707345, and εNd(t) = −2.5 to −2.14. In contrast, the Longlin basalt from Zhoudong area has relatively low SiO2 but high MgO and TFe2O3 contents. The rocks have whole-rock (87Sr/86Sr)i = 0.706181–0.706191 and εNd(t) = −0.57 to 0.69. Four Longlin basalt samples display LREE enrichments and HREE depletions, and with indistinct δEu and δCe anomalies. LA-ICP-MS zircon U-Pb dating on three Longlin basalt samples (from different localities) yielded consistent weighted average age of 257.9 ± 2.6 Ma (MSWD = 0.55), 259.5 ± 0.75 Ma (MSWD = 3.0), and 256.7 ± 2.0 Ma (MSWD = 0.68), indicating a Late Permian emplacement. Considering the similar age and geochemical features between the Longlin basalt and Emeishan flood basalts, we interpret that the former is spatially, and temporally associated with the Emeishan LIP. Geochemical features show that the high-Ti basalts in western Guangxi resemble Deccan-type continental flood basalts (CFBs), which were derived by decompression melting of the mantle plume. Combined with previous geochemical studies, we suggest that the difference in Ti content and Ti/Y ratio in CFBs are related to the depth and melting degree of mantle source, in which high-Ti features may have been linked to low degree of partial melting in the deep mantle.

Gynecologic cancers are one of the main health concerns of women throughout the world, and the early diagnosis and effective therapy of gynecologic cancers will be particularly important for the survival of female patients. As a current hotspot, carbon nanomaterials have attracted tremendous interest in tumor theranostics, and their application in gynecologic cancers has also been developed rapidly with great achievements in recent years. This Overview Article summarizes the latest progress in the application of diverse carbon nanomaterials (e.g., graphenes, carbon nanotubes, mesoporous carbon, carbon dots, etc.) and their derivatives in the sensing, imaging, drug delivery, and therapy of different gynecologic cancers. Important research contributions are highlighted in terms of the relationships among the fabrication strategies, architectural features, and action mechanisms for the diagnosis and therapy of gynecologic cancers. The current challenges and future strategies are discussed from the viewpoint of the real clinical application of carbon-based nanomedicines in gynecologic cancers. It is anticipated that this review will attract more attention toward the development and application of carbon nanomaterials for the theranostics of gynecologic cancers.

Transition metal (TM) based electrocatalysts attract increasing attention in energy conversion reactions, and current effects focus on material engineering strategies to tailor physicochemical properties of TM based electrocatalysts for improved performance. This review provides a summary about the recent advances of engineering TM based nanomaterials for electrocatalytic reactions, which include hydrogen evolution reaction (HER), oxygen evolution reaction (OER), CO2 reduction reaction (CO2RR), and nitrate reduction reaction (NO3−RR). We highlight four engineering strategies, namely, size engineering, facet engineering, composition engineering, and crystal structure engineering for TM based electrocatalysts, and pay a special emphasis on exploring the relationship between their physicochemical properties and catalytic activities. We outline the opportunities in this research field, in particular, the strategy of rationally combining in-situ and operando techniques and theoretical predication to design efficient electrocatalysts. Finally, issues that deserve attention and consideration for practical applications are discussed.

Background. After myocardial infarction, anti-inflammatory macrophages perform key homeostatic functions that facilitate cardiac recovery and remodeling. Several studies have shown that lactate may serve as a modifier that influences phenotype of macrophage. However, the therapeutic role of sodium lactate in myocardial infarction (MI) is unclear. Methods. MI was established by permanent ligation of the left anterior descending coronary artery followed by injection of saline or sodium lactate. Cardiac function was assessed by echocardiography. The cardiac fibrosis area was assessed by Masson trichrome staining. Macrophage phenotype was detected via qPCR, flow cytometry, and immunofluorescence. Signaling proteins were measured by Western blotting. Results. Sodium lactate treatment following MI improved cardiac performance, enhanced anti-inflammatory macrophage proportion, reduced cardiac myocytes apoptosis, and increased neovascularization. Flow-cytometric analysis results reported that sodium lactate repressed the number of the IL-6+, IL-12+, and TNF-α+ macrophages among LPS-stimulated bone marrow-derived macrophages (BMDMs) and increased the mRNA levels of Arg-1, YM1, TGF-β, and IL-10. Mechanistic studies revealed that sodium lactate enhanced the expression of P-STAT3. Furthermore, a STAT3 inhibitor eliminated sodium lactate-mediated promotion macrophage polarization. Conclusion. Sodium lactate facilitates anti-inflammatory M2 macrophage polarization and protects against MI by regulating P-STAT3.

The Yellow River has the highest sediment concentration in the world, and the Yellow River coarse sediment mainly comes from a particular kind of argillaceous sandstone, Pisha sandstone. This paper reports an investigation of the possibility of development of low-cost engineering materials using Pisha sandstone via ion exchange modification. The effect of modifiers with different concentration on the inhibition of volume expansion and the strength enhancement of modified Pisha sandstone were studied via ion exchange solidification. The effects of the concentration of ten types of modifier solutions and curing age were considered. The hydration of the mineral components, particle surface potential and reaction products were studied, respectively, by XRD, zeta potential, TG/DTG and SEM. Expansion volume and shear strength tests were conducted to assess the volume stability and mechanical property of modified Pisha sandstone. It showed that the expansion of Pisha sandstone was controlled and that the volume stability and shear strength were improved via ion exchange modification. The results of XRD, TG/DTG and SEM showed that the spacing of the crystal layers of the Pisha sandstone clay mineral and the mass lost had decreased significantly. When the concentration of the modifier was 0.05 mol/L, the volume reduced by 54.55% maximum and the shear strength reached the peak of 138 kPa.

Laser polishing (LP) is an effective method to improve the surface quality of an additively manufactured nickel-based alloy. In this paper, the in-situ laser polishing (ILP) experiment is performed on the selective laser melting (SLM) IN718 samples. The white light interferometer is used to test the three-dimensional surface profile and surface roughness of samples. The results show that the surface quality of as-SLMed samples by ILP is improved. In particular, the surface roughness is decreased by 33.5%. To reveal the mechanism of ILP, a three-dimensional numerical model is established based on the finite volume method (FVM). The model can accurately simulate the mesoscopic scale physical phenomena when the laser interacts with the metal. The temperature field, the melt pool flow, and the evolution of the surface morphology during the ILP process are predicted using this model. The mechanism of ILP is revealed based on the dynamics of the molten pool. The contribution of capillary and thermocapillary forces to the reduction of bulge curvature at different stages is studied. Furthermore, the effect of ILP power on the surface quality is investigated, and the mechanism of bulges and depressions on the track surface during high-power ILP is revealed.

A facile and ingenious method to chemical etching-coordinating a metal-organic framework (MOF) followed by an annealing treatment was proposed to prepare Co3O4 nanoparticles uniformly dispersed in rational porous carbon nano-boxes (Co3O4@CNBs), which was further used to detect H2O2 released from living cells. The Co3O4@CNBs H2O2 sensor delivers much higher sensitivity than non-etching/coordinating Co3O4, offering a limit of detection of 2.32 nM. The wide working range covers 10 nM-359 μM H2O2, while possessing good selectivity and excellent reproducibility. Moreover, this biosensor was used to successfully real-time detect H2O2 released from living cells, including both healthy and tumor cells. The excellent performance holds great promise for Co3O4@CNBs’s applications in electrochemical biomimetic sensing, particularly real-time monitor H2O2 released from living cells.

Antibiotic-resistant bacteria (ARB) present a global public health problem. Microorganisms are the main cause of hospital-acquired infections, and the biological contamination of hospital environments can cause the outbreak of a series of infectious diseases. Therefore, it is very important to understand the spread of antibiotic-resistant bacteria in hospital environments. This study examines the concentrations of aerobic bacteria and E. coli in ward environments and the airborne transmission of bacterial drug resistance. The results show that the three wards examined have an average aerobic bacterial concentration of 132 CFU∙m−3 and an average inhalable aerobic bacterial concentration of 73 CFU∙m−3, with no significant difference (P > 0.05) among the three wards. All isolated E. coli showed multi-drug resistance to not only third-generation cephalosporin antibiotics, but also quinolones, aminoglycosides, and sulfonamides. Furthermore, 51 airborne E. coli strains isolated from the air in the three wards and the corridor were screened for ESBLs, and 12 (23.53%) were ESBL-positive. The drug-resistance gene of the 12 ESBL-positive strains was mainly TEM gene, and the detection rate was 66.67% (8/12). According to a homology analysis with PFGE, 100% homologous E. coli from the ward at 5 m and 10 m outside the ward in the corridor shared the same drug-resistance spectrum, which further proves that airborne E. coli carrying a drug-resistance gene spreads out of the ward through gas exchange. This leads to biological pollution inside, outside, and around the ward, which poses a direct threat to the health of patients, healthcare workers, and surrounding residents. It is also the main reason for the antibiotic resistance in the hospital environment. More attention should be paid to comprehensive hygiene management in the surrounding environment of hospitals. Keywords: Microbial aerosol, Escherichia coli, PFGE, Drug-resistant genes, Public health, Environmental biological pollution

A closed-loop modeling method was established here to evaluate the performance of new battery technology from lab research to scaled-up developed electric vehicle (EV) applications. As an emerging energy-storage device, the lithium–sulfur battery (LSB) is a very promising candidate for the next generation of rechargeable batteries. However, it has been difficult to commercialize the LSB up to now. In this work, we designed and built a battery, EV, and driver system loop model to study the key performance parameters of LSB operation in EVs, in which the tested data from the lab were introduced into the model followed by simulating driving cycles and fast charging. A comparison with the lithium-ion batteries used in real vehicles verified the high reliability of the model. Meanwhile, the simulation results showed that the LSB needs more improvements for EV application; in particular, developments are still highly needed to overcome the high power and energy loss and sharp voltage vibration for practical applications. The novelty of this work relies on the created closed-loop modeling method to simulate lab research results for evaluating new battery technology in scaled-up EV applications in order to not only vividly predict EV operation performance and commercialization feasibility, but also thoughtfully guide researchers and developers for further optimization and problem solutions. Therefore, this method holds great promise as a powerful tool for both lab research and the industrial development of new batteries for EV applications.

As a new way for the high-value utilization of red mud (RM) waste, we proposed an improved approach to prepare the RM-based sludge/powder via the sulfuric acid hydrothermal dissolution and NH3 aqueous precipitation route and then the RM-based industrial-sized honeycomb (150 × 150 × 600 mm) was successfully produced by the extrusion moulding method in pilot scale. The synthesized RM-based powdery/honeycomb catalyst exhibited more than 80% deNOx activity and good durability of H2O and SO2 above 350°C. But the decline of NO conversion was also observed above 350°C, which was confirmed to result from the increased oxygenation of NH3 at high temperature. To improve the NO conversion at high temperature, NH3 was shunted and injected into the catalyst bed at two different places (entrance and centre) to facilitate its uniform distribution, which relieved the oxidation of NH3 and increased deNOx efficiency with 98% NO conversion at 400°C. This work explored the industrial application feasibility for the RM-based honeycomb catalyst as well as the possible solution to decrease the oxygenation of NH3 at high temperature, which presented a valuable reference for the further pilot tests of RM catalyst in industry.

LRP6 is known for its role as a Wnt co-receptor essential for the canonical Wnt/β-catenin signaling. Here, Li et al. show that LRP6 exerts a Wnt-independent scaffold function and regulates connexin 43 gap junction formation and coupling of cardiomyocytes in mouse hearts.

The development of efficient materials and processes is a long-term goal for the integrated flue gas purification in industry. In this study, a large-size V-based catalytic filter (L3000 mm × Φ150 mm) was prepared by loading the catalyst emulsion into a blank filter, which demonstrated excellent performance for simultaneously removing NOx, SOx and dust. The laboratory investigation found that the small catalytic particles, high catalyst loading and low face velocity could improve the DeNOx efficiency, and above 80% NO conversion could be achieved in the temperature range of 250–400 °C on the condition of 7.41 wt % catalyst loading and 2/H2O was only observed below 300 °C, and the dust had little negative effects on DeNOx efficiency except for the increase of pressure drop. Moreover, a 90-day industrial test of 2380 catalytic filters over 100,000 Nm3/h of flue gas (0.50 Nm/min) from a glass kiln demonstrated that the removal efficiency of both NOx and SOx could be maintained above 95% with great stability at 320–350 °C, and 99% dust could be removed with a pressure drop of less than 1.40 KPa. The results reported herein indicate the promising application prospect of large-size V-based catalytic filters for integrated flue gas purification in industry.

Locating and identifying the components mounted on a printed circuit board (PCB) based on machine vision is an important and challenging problem for automated PCB inspection and automated PCB recycling. In this paper, we propose a PCB semantic segmentation method based on depth images that segments and recognizes components in the PCB through pixel classification. The image training set for the PCB was automatically synthesized with graphic rendering. Based on a series of concentric circles centered at the given depth pixel, we extracted the depth difference features from the depth images in the training set to train a random forest pixel classifier. By using the constructed random forest pixel classifier, we performed semantic segmentation for the PCB to segment and recognize components in the PCB through pixel classification. Experiments on both synthetic and real test sets were conducted to verify the effectiveness of the proposed method. The experimental results demonstrate that our method can segment and recognize most of the components from a real depth image of the PCB. Our method is immune to illumination changes and can be implemented in parallel on a GPU.

A new honeycomb production process was proposed with both filter cake (from hydrothermal treatment of metatitanic acid) and industrial titanium dioxide as Ti sources. The strength of the obtained pilot product was comparable with the current industrial honeycomb product from only filter cake, but its denitration (DeNOx) efficiency was elevated up to 15 percentage points. Multiple characterizations revealed the filter cake and industrial titanium dioxide to be composed of primary particles and secondary particles, respectively, and the introduced secondary particles from industrial titanium dioxide resulted in increased specific surface area and pore size/volume, facilitating the exposure of more active sites with improved activity. Moreover, a positive correlation property was found between the honeycomb strength and crystallinity for the samples from different titanium sources. The filter cake with rich hydroxyl groups and weak crystallinity could be fused more easily among these primary particles to have a higher strength than industrial titanium dioxide, and the primary particle of the filter cake could fill the pile pore of industrial titanium dioxide and act as a solid phase binder to acquire good strength for the honeycomb using both the filter cake and titanium dioxide as Ti sources. The improved honeycomb product with good activity and strength may have more widespread application for the purification of low temperature flue gas in industry.

Nipah disease is a highly fatal zoonosis which is caused by the Nipah virus. The Nipah virus is a BSL-4 virus with fruit bats being its natural host. It is mainly prevalent in Southeast Asia. The virus was first discovered in 1997 in Negeri Sembilan, Malaysia. Currently, it is mainly harmful to pigs and humans with a high mortality rate. This study describes the route of transmission of the Nipah virus in different countries and analyzes the possibility of the primary disease being in China and the method of its transmission to China. The risk factors are analyzed for different susceptible populations to Nipah disease. The aim is to improve people’s risk awareness and prevention and control of the disease and reduce its risk of occurring and spreading in China.

Cell migration is one of the key cell functions in physiological and pathological processes, especially in tumor metastasis. However, it is not feasible to monitor the important biochemical molecules produced during cell migrations in situ by conventional cell migration assays. Herein, for the first time a device containing both electrochemical sensing and trans-well cell migration modules was fabricated to sensitively quantify biochemical molecules released from the cell migration process in situ. The fully assembled device with a multi-wall carbon nanotube/graphene/MnO2 nanocomposite functionalized electrode was able to successfully characterize hydrogen peroxide (H2O2) production from melanoma A375 cells, larynx carcinoma HEp-2 cells and liver cancer Hep G2 under serum established chemotaxis. The maximum concentration of H2O2 produced from A375, HEp-2 and Hep G2 in chemotaxis was 130 ± 1.3 nM, 70 ± 0.7 nM and 63 ± 0.7 nM, respectively. While the time required reaching the summit of H2O2 production was 3.0, 4.0 and 1.5 h for A375, HEp-2 and Hep G2, respectively. By staining the polycarbonate micropore membrane disassembled from the device, we found that the average migration rate of the A375, HEp-2 and Hep G2 cells were 98 ± 6%, 38 ± 4% and 32 ± 3%, respectively. The novel bi-module cell migration platform enables in situ investigation of cell secretion and cell function simultaneously, highlighting its potential for characterizing cell motility through monitoring H2O2 production on rare samples and for identifying underlying mechanisms of cell migration.

The doping effect of graphene nanoplatelets (GNPs) on electrical insulation properties of polyethylene (PE) was studied by combining experimental and theoretical methods. The electric conduction properties and trap characteristics were tested for pure PE and PE/GNPs composites by using a direct measurement method and a thermal stimulated current (TSC) method. It was found that doping smaller GNPs is more beneficial to decrease the conductivity of PE/GNPs. The PE/GNPs composite with smaller size GNPs mainly introduces deep energy traps, while with increasing GNPs size, besides deep energy traps, shallow energy traps are also introduced. These results were also confirmed by density functional theory (DFT) and the non-equilibrium Green’s function (NEGF) method calculations. Therefore, doping small size GNPs is favorable for trapping charge carriers and enhancing insulation ability, which is suggested as an effective strategy in exploring powerful insulation materials.

BACKGROUND: The great advances of nanomaterials have brought out broad important applications, but their possible nanotoxicity and risks have not been fully understood. It is confirmed that exposure of environmental particulate matter (PM), especially ultrafine PM, are responsible for many lung function impairment and exacerbation of pre-existing lung diseases. However, the adverse effect of nanoparticles on allergic asthma is seldom investigated and the mechanism remains undefined. For the first time, this work investigates the relationship between allergic asthma and nanosized silicon dioxide (nano-SiO₂). METHODOLOGY/PRINCIPAL FINDINGS: Ovalbumin (OVA)-treated and saline-treated control rats were daily intratracheally administered 0.1 ml of 0, 40 and 80 µg/ml nano-SiO₂ solutions, respectively for 30 days. Increased nano-SiO₂ exposure results in adverse changes on inspiratory and expiratory resistance (Ri and Re), but shows insignificant effect on rat lung dynamic compliance (Cldyn). Lung histological observation reveals obvious airway remodeling in 80 µg/ml nano-SiO₂-introduced saline and OVA groups, but the latter is worse. Additionally, increased nano-SiO₂ exposure also leads to more severe inflammation. With increasing nano-SiO₂ exposure, IL-4 in lung homogenate increases and IFN-γ shows a reverse but insignificant change. Moreover, at a same nano-SiO₂ exposure concentration, OVA-treated rats exhibit higher (significant) IL-4 and lower (not significant) IFN-γ compared with the saline-treated rats. The percentages of eosinophil display an unexpected result, in which higher exposure results lower eosinophil percentages. CONCLUSIONS/SIGNIFICANCE: This was a preliminary study which for the first time involved the effect of nano-SiO₂ to OVA induced rat asthma model. The results suggested that intratracheal administration of nano-SiO₂ could lead to the airway hyperresponsiveness (AHR) and the airway remolding with or without OVA immunization. This occurrence may be due to the Th1/Th2 cytokine imbalance accelerated by the nano-SiO₂ through increasing the tissue IL-4 production.