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Abstract Background Paddy soil is a typical soil type affected by anthropogenic management and factors related to natural soil formation. The evolution from mudflats to typical paddy soils can significantly affect the soil microecology. Previous studies have reported the evolution of soil physicochemical properties, microbes, and related soil environmental factors in a millennium paddy soil chronosequence. However, the potential biological mechanisms of changes in metabolites and microbes–metabolites interaction are poorly understood. Therefore, a combination of high-throughput sequencing and environmental pseudotargeted metabolomics techniques was adopted to explore the effects of the millennium paddy soil chronosequence on microbial communities, metabolites, and their functions and interactions. Results The soil ecology changed greatly in the first 60 years of the transition from mudflat to paddy planting. Among the microbial communities, the response of the bacteria to the chronosequence was more sensitive than that of fungi. Among them, the bacterial communities of Proteobacteria, Bacteroidetes, Acidobacteria, and Nitrospirae exhibited regular succession over the chronosequence, but the fungal communities did not show regular changes. Bacterial function prediction revealed that the beginning of the critical stage of the evolution from mudflat to paddy soil involved the organic matter cycle and energy flow. In contrast, fungi were characterized mainly by pathogenic and saprophytic functions. The results of the principal component analysis of the metabolites revealed a similar pattern of change as that of the microbes. Seventy-five characteristic metabolites exhibited three trends of change during the development of the paddy soil chronosequence. Twenty-five differentially active metabolic pathways, including glyoxylate and dicarboxylate metabolism, starch and sucrose metabolism, and galactose metabolism, were enriched. In addition, correlation analysis revealed that long-chain fatty acids, short-chain fatty acids, phenolic acids, carbohydrates, and polyalcohols significantly regulate the microbial communities in paddy soil. Conclusions Combining metabolome and microbiome has expanded the overall understanding of the development of paddy soil under anthropogenic management. During the development of a paddy soil chronosequence, the synergistic regulation of soil physicochemical properties and metabolites in the microbial community results in increased productivity. This study provides a new perspective on microbes and metabolites interaction. Graphical Abstract

Imaging the wave velocity field surrounding a borehole while drilling is a promising and urgently needed approach for extending the exploration range of the borehole point. This paper develops a drilling process detection (DPD) system consisting of a multifunctional sensor and a pilot geophone installed at the top of the drilling rod, geophones at the tunnel face, a laser rangefinder, and an onsite computer. A weighted adjoint-state first arrival travel time tomography method is used to invert the P-wave velocity field of rock mass while borehole drilling. A field experiment in the ongoing construction of a deep buried tunnel in southwestern China demonstrated the DPD system and the tomography method. Time-frequency analysis of typical borehole drilling detection data shows that the impact drilling source is a pulse-like seismic exploration wavelet. A velocity field of the rock mass in a triangular area defined by the borehole trajectory and geophone receiving line can be obtained. Both the borehole core and optical image validate the inverted P-wave velocity field. A numerical simulation of a checkerboard benchmark model is used to test the tomography method. The rapid convergence of the misfits and consistent agreement between the inverted and observed travel times validate the P-wave velocity imaging.

Abstract Background Heavy metal contamination has been a severe worldwide environmental issue. For industrial pollutions, heavy metals rarely exist as singular entities. Hence, researches have increasingly focused on the detrimental effect of mixed heavy metal pollution. Genome analysis of Lampropedia strains predicted a repertoire of heavy metal resistance genes. However, we are still lack of experimental evidence regarding to heavy metal resistance of Lampropedia, and their potential in mixed heavy metal removal remain elusive. Results In this study, a Lampropedia aestuarii strain GYF-1 was isolated from soil samples near steel factory. Heavy metal tolerance assay indicated L. aestuarii GYF-1 possessed minimal inhibition values of 2 mM, 10 mM, 6 mM, 4 mM, 6 mM, 0.8 mM, and 4 mM for CdCl2, K2CrO4, CuCl2, NiCl2, Pb(CH3COO)2, ZnSO4, and FeCl2, respectively. The biosorption assay demonstrated its potential in soil remediation from mixed heavy metal pollution. Next the draft genome of L. aestuarii GYF-1 was obtained and annotated, which revealed strain GYF-1 are abundant in heavy metal resistance genes. Further evaluations on differential gene expressions suggested adaptive mechanisms including increased lipopolysaccharides level and enhanced biofilm formation. Conclusion In this study, we demonstrated a newly isolated L. aestuarii GYF-1 exhibited mixed heavy metal resistance, which proven its capability of being a potential candidate strain for industrial biosorption application. Further genome analysis and differential gene expression assay suggest enhanced LPS and biofilm formation contributed to the adaptation of mixed heavy metals.

Abstract Background Drug resistance limits the treatment effect of cisplatin-based chemotherapy in head and neck squamous cell carcinoma (HNSCC), and the underlying mechanism is not fully understood. The aim of this study was to explore the cause of cisplatin resistance in HNSCC. Methods We performed survival and gene set variation analyses based on HNSCC cohorts and identified the critical role of tumor necrosis factor alpha-induced protein 2 (TNFAIP2) in cisplatin-based chemotherapy resistance. Half-maximal inhibitory concentration (IC50) examination, colony formation assays and flow cytometry assays were conducted to examine the role of TNFAIP2 in vitro, while xenograft models in nude mice and 4-nitroquinoline N-oxide (4NQO)-induced HNSCC models in C57BL/6 mice were adopted to verify the effect of TNFAIP2 in vivo. Gene set enrichment analysis (GSEA) and coimmunoprecipitation coupled with mass spectrometry (Co-IP/MS) were performed to determine the mechanism by which TNFAIP2 promotes cisplatin resistance. Results High expression of TNFAIP2 is associated with a poor prognosis, cisplatin resistance, and low reactive oxygen species (ROS) levels in HNSCC. Specifically, it protects cancer cells from cisplatin-induced apoptosis by inhibiting ROS-mediated c-JUN N-terminal kinase (JNK) phosphorylation. Mechanistically, the DLG motif contained in TNFAIP2 competes with nuclear factor-erythroid 2-related factor 2 (NRF2) by directly binding to the Kelch domain of Kelch-like ECH-associated protein 1 (KEAP1), which prevents NRF2 from undergoing ubiquitin proteasome-mediated degradation. This results in the accumulation of NRF2 and confers cisplatin resistance. Positive correlations between TNFAIP2 protein levels and NRF2 as well as its downstream target genes were validated in HNSCC specimens. Moreover, the small interfering RNA (siRNA) targeting TNFAIP2 significantly enhanced the cisplatin treatment effect in a 4NQO-induced HNSCC mouse model. Conclusions Our results reveal the antioxidant and cisplatin resistance-regulating roles of the TNFAIP2/KEAP1/NRF2/JNK axis in HNSCC, suggesting that TNFAIP2 might be a potential target in improving the cisplatin treatment effect, particularly for patients with cisplatin resistance.

The mechanical properties and toughness of phase change materials are often weakened by defects which affect the application of matrix in tribology, and considering the hybridization of nanomaterials is able to increase the upper limit of materials’ performance. In this study, the in-situ polymerization of isopropylacrylamide was used on the surface of graphene and MXene to prepare a phase change two-dimensional composite with reversible phase change under specific temperatures. The composites were dispersed in epoxy resin matrix by KH550 (γ-Aminopropyl triethoxysilane) to realize phase change modulation of tribological properties. The results showed that the tribological properties of the modified epoxy resin coating realized friction reduction and anti-wear functions, and exhibited different tribological properties at different temperatures. The friction coefficient and wear rate of the composite coatings can be reduced to 0.1 % and 82.2 %, respectively, which is mainly attributed to the two-dimensional structure and physical characteristics of graphene and MXene, as well as the mechanical enhancement of the phase change homopolymer and their synergistic effects.

Intensive aquaculture in high-density hybrid snakehead [Channa maculata (♀) × Channa argus (♂)] fishponds can lead to toxic conditions for fish. This study investigated nitrogen migration and transformation in these fishponds during different cultivation periods. Using qPCR technology, we analyzed the abundance variation of nitrogen-cycling microorganisms in water and sediment to reveal the nitrogen metabolism characteristics of hybrid snakehead fishponds. The results showed that fish biomass significantly impacts suspended particulate matter (SPM) flux. At the sediment–water interface, inorganic nitrogen fluxes showed predominant NO3−-N absorption by sediments and NH4+-N and NO2−-N release, especially in later cultivation stages. Sediments were rich in nirS and AMX 16S rRNA genes (ranging from 4.04 × 109 to 1.01 × 1010 and 1.19 × 108 to 2.62 × 108 copies/g, respectively) with nirS-type denitrifiers potentially dominating the denitrification process. Ammonia-oxidizing bacteria (AOB) were found to dominate the ammonia oxidation process over ammonia-oxidizing archaea (AOA) in both water and sediment. Redundancy analysis revealed a positive correlation between SPM flux, Chlorophyll a (Chl-a), and denitrification genes in the water, and between nitrogen-cycling genes and NH4+/NO2− fluxes at the interface. These findings provide a scientific basis for nitrogen control in hybrid snakehead fishponds.

Mitochondrial dysfunction is associated with ototoxicity, which is caused by external factors. Mitophagy plays a key role in maintaining mitochondrial homeostasis and function and is regulated by a series of key mitophagy regulatory proteins and signaling pathways. The results of ototoxicity models indicate the importance of this process in the etiology of ototoxicity. A number of recent investigations of the control of cell fate by mitophagy have enhanced our understanding of the mechanisms by which mitophagy regulates ototoxicity and other hearing-related diseases, providing opportunities for targeting mitochondria to treat ototoxicity.

Abstract Background Eukaryotic translation initiation factor 6 (eIF6), also known as integrin β4 binding protein, is involved in ribosome formation and mRNA translation, acting as an anti-association factor. It is also essential for the growth and reproduction of cells, including tumor cells. Yet, its role in oral squamous cell carcinoma (OSCC) remains unclear. Methods The expression characteristics of eIF6 in 233 samples were comprehensively analyzed by immunohistochemical staining (IHC). Effects of eIF6 over-expression and knockdown on cell proliferation, migration and invasion were determined by CCK-8, wound healing and Transwell assays. Western blot, immunofluorescence (IF) and co-immunoprecipitation (co-IP) were performed for mechanical verification. Results We found that cytoplasmic eIF6 was abnormally highly expressed in OSCC tissues, and its expression was associated with tumor size and the clinical grade. Amplification of eIF6 promoted the growth, migration and invasion capabilities of OSCC cell lines in vitro and tumor growth in vivo. Through Western blot analysis, we further discovered that eIF6 significantly promotes epithelial-mesenchymal transformation (EMT) in OSCC cells, while depletion of eIF6 can reverse this process. Mechanistically, eIF6 promoted tumor progression by activating the AKT signaling pathway. By performing co-immunoprecipitation, we discovered a direct interaction between endogenous eIF6 and AKT protein in the cytoplasm. Conclusion These results demonstrated that eIF6 could be a new therapeutic target in OSCC, thus providing a new basis for the prognosis of OSCC patients in the future. Video abstract

Soil microorganism and their relationships with soil respiration in paddy systems in karst areas (KA) of southern China is important for understanding the mechanisms of greenhouse gas emission reduction. Soils were collected from the tillage layer (0–20 cm) during the rice growing season from KA and non-karst areas (NKA) (red soils) from the Guilin Karst Experimental Site in China. Community structures and inferred functionalities of bacteria and fungi were analyzed using the high-throughput sequencing techniques, FAPROTAX and FUNGuild. A bacterial–fungal co-occurrence network was constructed and soil respiration was measured using dark box-gas chromatography and built their relationships. The results indicated that soil respiration was significantly lower in KA than in NKA. Principal component analysis indicated that bacterial and fungal community structures significantly differed between KA and NKA. The OTU ratio of fungi to bacteria (F/B) was positively correlated with soil respiration (p = 0.044). Further, the key network microorganisms were OTU69 and OTU1133 and OTU1599 in the KA. Soil respiration negatively correlated with Acidobacteria Gp6, dung saprotroph-endophyte-litter saprotroph-undefined saprotroph, aerobic nitrite oxidizers and nitrifier in KA (p < 0.05). Overall, this study demonstrated that soil respiration was reduced when soil microorganisms shifted from bacterial to fungal dominance during the rice growing season in KA.

We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete Fourier transform (DFT) to extract fifteen features from vibration signals in the time and frequency domains of four bearing failure forms, which addresses the issue of ambiguous fault identification caused by their nonlinearity and nonstationarity. The extracted feature vectors are then divided into training and test sets as SVM inputs for fault diagnosis. To optimize the SVM, we construct a hybrid kernel SVM using a polynomial kernel function and radial basis kernel function. BO is used to optimize the extreme values of the objective function and determine their weight coefficients. We create an objective function for the Gaussian regression process of BO using training and test data as inputs, respectively. The optimized parameters are used to rebuild the SVM, which is then trained for network classification prediction. We tested the proposed diagnostic model using the bearing dataset of the Case Western Reserve University. The verification results show that the fault diagnosis accuracy is improved from 85% to 100% compared with the direct input of vibration signal into the SVM, and the effect is significant. Compared with other diagnostic models, our Bayesian-optimized hybrid kernel SVM model has the highest accuracy. In laboratory verification, we took sixty sets of sample values for each of the four failure forms measured in the experiment, and the verification process was repeated. The experimental results showed that the accuracy of the Bayesian-optimized hybrid kernel SVM reached 100%, and the accuracy of five replicates reached 96.7%. These results demonstrate the feasibility and superiority of our proposed method for fault diagnosis in rolling bearings.

Objective: BYSL, which encodes the Bystin protein in humans, is upregulated in reactive astrocytes following brain damage and/or inflammation. We aimed to determine the role and mechanism of BYSL in glioma cell growth and survival. Methods: BYSL expression in glioma tissues was measured by quantitative real-time PCR, Western blot, and immunohistochemistry. In vitro assays were performed to assess the role of BYSL in cell proliferation and apoptosis. Protein interactions and co-localization were determined by co-immunoprecipitation and double immunofluorescence. The expression and activity of the AKT/mTOR signaling molecules were determined by Western blot analysis, and the role of BYSL in glioma growth was confirmed in an orthotopic xenograft model. Results: The BYSL mRNA and protein levels were elevated in glioma tissues. Silencing BYSL inhibited glioma cell proliferation, impeded cell cycle progression, and induced apoptosis, whereas overexpressing BYSL protein led to the opposite effects. We identified a complex consisting of BYSL, RIOK2, and mTOR, and observed co-localization and positive correlations between BYSL and RIOK2 in glioma cells and tissues. Overexpressing BYSL or RIOK2 increased the expression and activity of AKT/mTOR signaling molecules, whereas downregulation of BYSL or RIOK2 decreased the activity of AKT/mTOR signaling molecules. Silencing BYSL or RIOK2 decreased the growth of the tumors and prolonged the lifespan of the animals in an orthotopic xenograft model. Conclusions: High expression of BYSL in gliomas promoted tumor cell growth and survival both in vitro and in vivo. These effects could be attributed to the association of BYSL with RIOK2 and mTOR, and the subsequent activation of AKT signaling.

To investigate the effect of catholyte shared by different membrane electrolytic cells on electrosynthesis of ammonium persulfate, the equivalent circuit models of two electrolytic cells with shared catholyte and separate catholyte were established and the pilot experiments were carried out with a cation exchange membrane (named PGN membrane) and the Al2O3 ceramic membrane. The model results showed that there appeared the bias ionic current from the low resistance electrolytic cell to the high resistance electrolytic cell with shared catholyte. The experimental results showed that the cathode current of the PGN membrane electrolytic cell was 56 A lower than its anode current with shared catholyte while the cathode current of the ceramic membrane electrolytic cell was 56 A higher than its anode current at the supply voltage of 5.3 V. And the current efficiency of PGN membrane and the ceramic membrane declined with their energy consumption increasing compared with those with separate catholyte. The model results showed a good agreement with those of the experiments. Therefore, it is necessary to consider the effect of shared catholyte by different membrane electrolytic cells on industrial electrosynthesis of ammonium persulfate.

This work introduces a one-step method for the preparation of layered oxide cathode materials utilizing pure Ni and Co mixed solution obtained from the waste hydrodesulfurization (HDS) catalyst. An efficient non-separation strategy with pyrometallurgical-hydrometallurgical (pyro-hydrometallurgical) process consisting of roasting and leaching is proposed. Most of the impurity metal elements such as Mo and V were removed by simple water leaching after the waste HDS catalyst was roasted with Na2CO3 at 650 °C for 2.5 h. Additionally, 93.9% Ni and 100.0% Co were recovered by H2SO4 leaching at 90 °C for 2.5 h. Then, LiNi0.533Co0.193Mn0.260V0.003Fe0.007Al0.004O2 (C–NCM) was successfully synthesized by hydroxide co-precipitation and high temperature solid phase methods using the above Ni and Co mixed solution. The final C–NCM material exhibits excellent electrochemical performance with a discharge specific capacity of 199.1 mAh g−1 at 0.1 C and a cycle retention rate of 79.7% after 200 cycles at 1 C. This novel process for the synthesis of cathode material can significantly improve production efficiency and realize the high added-value utilization of metal resources in a waste catalyst.

With the continuous development of hyperspectral image technology and deep learning methods in recent years, an increasing number of hyperspectral image classification models have been proposed. However, due to the numerous spectral dimensions of hyperspectral images, most classification models suffer from issues such as breaking spectral continuity and poor learning of spectral information. In this paper, we propose a new classification model called the enhanced spectral fusion network (ESFNet), which contains two parts: an optimized multi-scale fused spectral attention module (FsSE) and a 3D convolutional neural network (3D CNN) based on the fusion of different spectral strides (SSFCNN). Specifically, after sampling the hyperspectral images, our model first implements the weighting of the spectral information through the FsSE module to obtain spectral data with a higher degree of information richness. Then, the weighted spectral data are fed into the SSFCNN to realize the effective learning of spectral features. The new model can maximize the retention of spectral continuity and enhance the spectral information while being able to better utilize the enhanced information to improve the model’s ability to learn hyperspectral image features, thus improving the classification accuracy of the model. Experiment results on the Indian Pines and Pavia University datasets demonstrated that our method outperforms other relevant baselines in terms of classification accuracy and generalization performance.

The viscoelastic materials exhibit different tribological responses when compared to the stiff materials, due to the intermediate mechanical properties between viscous liquid and elastic solid. In this work, the effect of damping materials viscoelasticity on sliding friction under dry condition was investigated. However, it was difficult to change its damping properties only while other properties (strength or surface hardness) remain unchanged, since viscoelasticity was one of its intrinsic properties. Therefore, the attention of interactions between the material components was closely paid. To achieve this, the experimental groups of damping materials with various viscoelasticity were established by adding various fillers and adjusting their surface properties. Additionally, a viscoelastic property determined friction coefficient model was obtained and validated by the molecular dynamic method. The results show that the test model is in good agreement with the experimental results. Meanwhile, tribo-pairs with higher proportion of viscous character had greater oscillations in friction. They also exhibited higher friction coefficient due to the increased contribution of viscoelastic hysteresis losses to friction.

A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was proposed to solve the unclear fault characterization of rolling bearing vibration signal due to its nonlinear and nonstationary characteristics. A whale gray wolf optimization algorithm (WGWOA) was proposed by combining whale optimization algorithm (WOA) and gray wolf optimization (GWO), and the rolling bearing signal was decomposed by using variational mode decomposition (VMD). Each eigenvalue was extracted as eigenvector after VMD, and the training and test sets of the fault diagnosis model were divided accordingly. The support vector machine (SVM) was used as the fault diagnosis model and optimized by using WGWOA. The validity of this method was verified by two cases of Case Western Reserve University bearing data set and laboratory test. The test results show that in the bearing data set of Case Western Reserve University, compared with the existing VMD-SVM method, the fault diagnosis accuracy rate of the WGWOA-VMD-SVM method in five repeated tests reaches 100.00%, which preliminarily verifies the feasibility of this algorithm. In the laboratory test case, the diagnostic effect of the proposed fault diagnosis method is compared with backpropagation neural network, SVM, VMD-SVM, WOA-VMD-SVM, GWO-VMD-SVM, and WGWOA-VMD-SVM. Test results show that the accuracy rate of WGWOA-VMD-SVM fault diagnosis is the highest, the accuracy rate of a single test reaches 100.00%, and the accuracy rate of five repeated tests reaches 99.75%, which is the highest compared with the above six methods. WGWOA plays a good optimization role in optimizing VMD and SVM. The signal decomposed by VMD is optimized by using the WGWOA algorithm without mode overlap. WGWOA has the better convergence performance than WOA and GWO, which further verifies its superiority among the compared methods. The research results can provide an effective improvement method for the existing rolling bearing fault diagnosis technology.

BYSL, which encodes the human bystin protein, is a sensitive marker for astrocyte proliferation during brain damage and inflammation. Previous studies have revealed that BYSL has important roles in embryo implantation and prostate cancer infiltration. However, the role and mechanism of BYSL in glioblastoma (GBM) cell migration and invasion remain unknown. We found that knockdown of BYSL inhibited cell migration and invasion, downregulated the expression of mesenchymal markers (e.g., β-catenin and N-cadherin), and upregulated the expression of epithelial marker E-cadherin in GBM cell lines. Overexpression of BYSL promoted GBM cell migration, invasion, and epithelial-mesenchymal transition (EMT). In addition, the role of BYSL in promoting EMT was further confirmed in a glioma stem cell line derived from a GBM patient. Mechanistically, overexpression of BYSL increased the phosphorylation of GSK-3β and the nuclear distribution of β-catenin. Inhibition of GSK-3β by 1-Azakenpaullone could partially reverse the effects of BYSL downregulation on the transcriptional activity of β-catenin, the expression of EMT markers, and GBM cell migration/invasion. Moreover, immunohistochemical analysis showed strong expression of BYSL in GBM tissues, which was positively correlated with markers of mesenchymal GBM. These results suggest that BYSL promotes GBM cell migration, invasion, and EMT through the GSK-3β/β-catenin signaling pathway.

MoS2/C nanocomposite coatings were deposited on a 304 stainless steel plate by unbalanced magnetron sputtering from carbon and molybdenum disulfide targets, and the target current of MoS2 was varied to prepare for coating with different carbon contents. The mechanical and tribological properties of the MoS2/C nanocomposite coating with different carbon contents were studied using a low-velocity impact wear machine based on kinetic energy control, and the substrate was used as the comparison material. The atomic content ratio of Mo to S in the MoS2/C coating prepared by unbalanced magnetron sputtering was approximately 1.3. The dynamic response and damage analysis revealed that the coating exhibited good impact wear resistance. Under the same experimental conditions, the wear depth of the MoS2/C coating was lower than that of the substrate, and the coating exhibited a different dynamic response process as the carbon content increased.

Abstract This paper investigates the self-loosening of threaded fasteners subjected to dynamic shear load. Three kinds of typical coatings, PTFE, MoS2, and TiN applied to bolts and nuts, are tested in this investigation. The study experimentally examines the loosening mechanisms of fasteners and assesses the anti-loosening performance of the three tested coatings based on their tightening characteristics, loosening curves, and the damage of thread surface. Additionally, the anti-loosening performance of the three coatings is compared under different load forms. The results indicate that the PTFE and MoS2 coatings have significant anti-loosening effect, whereas the anti-loosening performance of TiN coating is not satisfactory. It is also found that an appropriate increase of the initial tightening torque can significantly improve the anti-loosening effect. In addition, the microscopic analyses of PTFE and MoS2 coating reveal that a reduced initial tightening torque leads to fretting wear on the thread contact surfaces of fasteners, thereby aggravating the damage.

The chemical vapor deposition method is used to prepare CNT (carbon nanotube)/PCF (PAN-based carbon fiber felt) composite electrodes in this paper, with the surface morphology of CNT/PCF composites and electroadsorption desalination performance being studied. Results show such electrode materials with three-dimensional network nanostructures having a larger specific surface area and narrower micropore distribution, with a huge number of reactive groups covering the surface. Compared with PCF electrodes, CNT/PCF can allow for a higher adsorption and desorption rate but lower energy consumption; meanwhile, under the condition of the same voltage change, the CNT/PCF electrodes are provided with a better desalination effect. The study also found that the higher the original concentration of the solution, the greater the adsorption capacity and the lower the adsorption rate. At the same time, the higher the solution’s pH, the better the desalting; the smaller the ions’ radius, the greater the amount of adsorption.

Supercritical fluid extraction and expansion (SFEE) patented technology combines the advantages of both supercritical fluid extraction (SFE) and rapid expansion of supercritical solution (RESS) with on-line coupling, which makes the nanoparticle formation feasible directly from matrix such as Chinese herbal medicine. Supercritical fluid extraction is a green separation technology, which has been developed for decades and widely applied in traditional Chinese medicines or natural active components. In this paper, a SFEE patented instrument was firstly built up and controlled by LABVIEW work stations. Stearic acid was used to verify the SFEE process at optimized condition; via adjusting the preexpansion pressure and temperature one can get different sizes of particles. Furthermore, stearic acid was purified during the SFEE process with HPLC-ELSD detecting device; purity of stearic acid increased by 19%, and the device can purify stearic acid.