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Based on mixed lubrication analysis, considering the influence of rough interface contact stiffness, contact damping, and interface friction on the gear transmission system, the relationship between interface contact and the overall performance of the gear transmission system has been established. First, the surface topography is characterized using statistical parameters of rough surfaces, and the contact stiffness and damping for tooth surfaces with different roughnesses are calculated. Subsequently, a six degree of freedom gear tribo-dynamics coupling model is developed. Finally, the established tribo-dynamics model is employed to investigate the relationship between surface roughness and the overall performance of the gear transmission system. This study provides a more intimate connection between the contact interface and the general behavior of the gear transmission system, enabling a better representation of real-world engineering problems. The research findings reveal that contact stiffness and damping decrease with increasing surface roughness. Higher roughness leads to greater gear vibration amplitude. Moreover, elevated surface roughness results in intensified meshing force and more significant energy loss. Surprisingly, when the roughness is appropriate, gears with rough surfaces lose less energy than those with smooth surfaces.

The effective utilization of charcoal and tar byproducts is a challenge for pyrolysis gasification of bamboo. Herein, the bamboo tar was modified via polymerization and acted as a new adhesive for the preparation of excellent bamboo-charcoal-derived molding activated carbon (MBAC). As compared with pristine tar and other adhesives, the aromatization of tar with phenol increased its molecular weight, oxygenic functional groups, and thermal stability, leading to the decreased blocking impact of charcoal pore and improved bonding and pyrolytic crosslinking effect between charcoal particles. These further contribute to the high mechanical strength, specific surface area, pore volume, and amount of oxygenic functional groups for fabricated MBAC. Owing to the high microporous volume of MBAC, it exhibited 385 mg·g−1 toluene and 75.2% tetrachloride gas adsorption performances. Moreover, the pseudo-first-order, pseudo-second-order, and Bangham models were used to evaluate the kinetic data. The toluene adsorption process conforms to the Bangham kinetic model, suggesting that the diffusion mechanism of toluene adsorption mainly followed intraparticle diffusion.

Inflammation of the fetal membranes is an indispensable event of parturition, with increasing prostaglandin E2 (PGE2) synthesis as one of the ultimate products that prime labor onset. In addition to PGE2, the fetal membranes also boast a large capacity for cortisol regeneration. It is intriguing how increased PGE2 synthesis is achieved in the presence of increasing amounts of classical anti-inflammatory glucocorticoids in the fetal membranes at parturition. 15(S)-hydroxyeicosatetraenoic acid (15(S)-HETE) synthesized by lipoxygenase 15/15B (ALOX15/15B) has been shown to enhance inflammation-induced PGE2 synthesis in amnion fibroblasts. Here, we examined whether glucocorticoids could induce ALOX15/15B expression and 15(S)-HETE production to promote PGE2 synthesis in amnion fibroblasts at parturition. We found that cortisol and 15(S)-HETE abundance increased parallelly in the amnion at parturition. Cortisol induced ALOX15/15B expression and 15(S)-HETE production paradoxically in amnion fibroblasts. Mechanism study revealed that this paradoxical induction was mediated by p300-mediated histone acetylation and interaction of glucocorticoid receptor with transcription factors CREB and STAT3. Conclusively, cortisol regenerated in the fetal membranes can paradoxically induce ALOX15/15B expression and 15(S)-HETE production in human amnion fibroblasts, which may further assist in the induction of PGE2 synthesis in the inflammatory responses of the fetal membranes for parturition.

Constant current (CC) and constant voltage (CV) charging of batteries is a crucial research area in the practical implementation of wireless power transfer (WPT) systems. The typical charging process of a battery starts from the constant current mode. As the battery’s voltage increases, the charging mode switches to the constant voltage mode. During charging, the equivalent load resistance of the battery will vary with the charging time, and the equivalent load resistance will affect the charging current or voltage and system’s efficiency. In this study, an adaptive wireless charging method of CC-CV is proposed based on sinusoidal pulse width modulation (SPWM) inverter control. The proposed WPT circuit detects the load variation by measuring the parameters of load voltage and load current, and accurately controls the system output current or voltage by adjusting the modulation depth of the SPWM inverter on the primary side. When there is relative motion between the transmitting coil and the receiving coil, the sharp change in coupling coefficient directly affects the system’s output voltage and output current, leading to output fluctuations and instability. To solve this problem, a method for estimating the coupling coefficient is proposed which estimates the coupling coefficient during the charging process by measuring system parameters. Then, the controller on the primary side adjusts the modulation depth of the SPWM inverter circuit based on the estimated new coupling coefficient, so that the system can still achieve constant current and constant voltage charging under displacement or distance changes. In this study, the CC mode output current during battery charging was set to 0.75 A, and the CV mode output voltage was set to 12 V. Simulation and experimental results demonstrate the validity and accuracy of the proposed control method.

Accurately predicting online ride-hailing demand can help operators allocate vehicle resources on demand, avoid idle time, and improve traffic conditions. However, due to the randomness and complexity of online ride-hailing demand data, which are affected by many factors and mostly time-series in nature, it is difficult to forecast accurately and effectively based on traditional forecasting models. Therefore, this study proposes an online ride-hailing demand forecasting model based on the attention mechanism of a random forest (RF) combined with a symmetric bidirectional long short-term memory (BiLSTM) neural network (Att-RF-BiLSTM). The model optimizes the inputs and can use past and future data to forecast, improving the forecasting precision of online ride-hailing demand. The model utilizes a random forest to filter and optimize the input variables to reduce the neural network complexity, and then an attention mechanism was incorporated into the BiLSTM neural network to construct a demand forecasting model and validate it using actual Uber pickup data from New York City. Compared with other forecasting models (Att-XGBoost-BiLSTM, Att-BiLSTM, and pure LSTM), the results show that the proposed symmetrical Att-RF-BiLSTM online ride-hailing demand forecasting model has a higher forecasting precision and fitting degree, which indicates that the proposed model can be satisfactorily applied to the area of online ride-hailing demand.

The cooperative lane change among several connected and automated vehicles (CAVs) provides ideas for enhancing the traffic safety and efficiency issues caused by lane changes. However, most of the existing studies mainly focus on the independent analysis of the lateral and longitudinal movements of the lane change without considering the impact of the lateral motion on the longitudinal motion. These works usually assume that the target tracking-preceding vehicles are determined for both the lane change vehicle and the following cooperative vehicle in the target lane. This work proposes a model predictive control (MPC)-based cooperative lane change (CLC) control strategy by considering the preceding vehicle switching and the correlation between the lateral and longitudinal motions. It builds the lateral movement based on the appropriate function curve and integrates this lateral movement in the construction of the coordinated longitudinal motion control strategy by using a set of linear piecewise functions in the design of constraints and objective function of the optimization model to provide smooth preceding vehicles switch. An advanced optimization solver is used to solve the optimization control problem step by step. The proposed strategy is validated based on numerical comparative experiments with two typical lane-changing scenarios. The results show that the proposed control strategy can smoothly complete the preceding vehicle switching during the lane change and quickly realize the stable tracking of the target lane vehicles after changing lanes.

Adopting an integrated strategy to realize efficient fractionation of lignocellulose into well-defined components for its valorization is challenging. Combinatorial pretreatments in this study decomposed hemicellulose of green bamboo during hydrothermal pretreatment (HP), and the hydrothermally pretreated bamboo was subsequently subjected to delignification using deep eutectic solvent (DES) consisting of choline chloride and lactic acid, finally facilitating enzymatic hydrolysis of cellulose residue. Upon hydrothermal treatment at 180 °C for 35 min, hemicellulose removal of 88.6% was achieved with xylo-oligosaccharide yield and purity of 50.9% and 81.6%, respectively. After DES treatment at 140 °C for 2 h, lignin removal was determined to be 79.1%. Notably, the regenerated lignin with high purity of 96.8% displayed superior antioxidant activity, and the decrease in the ratio of syringyl units to guaiacyl units led to a slight decrease in radical scavenging activity of lignin after five recycling runs of DES. Moreover, the two-step treated residue had much higher enzymatic digestibility than that of single HP residue and untreated green bamboo. Results show that synergistic pretreatment is a promising strategy to tackle the recalcitrance of lignocellulose towards high value-added utilization.

Hawk tea (Litsea coreana Levl. var. lanuginosa) is a traditional herbal tea in southwestern China, and was found to possess hepatoprotective effects in our previous study. However, it is unclear whether hawk tea flavonoids (HTF) can alleviate alcoholic liver damage (ALD). Firstly, we extracted and identified the presence of 191 molecules categorized as HTFs, with reynoutrin, avicularin, guaijaverin, cynaroside, and kaempferol-7-O-glucoside being the most prevalent. After taking bioavailability into consideration and conducting comprehensive sorting, the contribution of guaijaverin was the highest (0.016 mg/mice). Then, by daily intragastric administration of HTF (100 mg/kg/day) to the ALD mice, we found that HTF alleviated liver lipid deposition (inhibition of TG, TC, LDL-C) by reducing liver oxidative-stress-mediated inflammation (up-regulation NRF2/HO-1 and down-regulation TLR4/MyD88/NF-κB pathway) and reshaping the gut microbiota (Lactobacillus, Bifidobacterium, Bacillus increased). Overall, we found HTF could be a potential protective natural compound for treating ALD via the gut–liver axis and guaijaverin might be the key substance involved.

The Chinese carbon dioxide measurement satellite (TanSat) has collected a large number of measurements in the solar calibration mode. To improve the accuracy of XCO2 retrieval, the Instrument Line Shape (ILS, also known as the slit function) must be accurately determined. In this study, we characterized the on-orbit ILS of TanSat by fitting measured solar irradiance from 2017 to 2018 with a well-calibrated high-spectral-resolution solar reference spectrum. We used various advanced analytical functions and the stretch/sharpen of the tabulated preflight ILS to represent the ILS for each wavelength window, footprint, and band. Using super Gaussian+P7 and the stretch/sharpen functions substantially reduced the fitting residual in O2 A-band and weak CO2 band compared with using the preflight ILS. We found that the difference between the derived ILS width and on-ground preflight ILS was up to −3.5% in the weak CO2 band, depending on footprint and wavelength. The large amplitude of the ILS wings, depending on the wavelength, footprint, and bands, indicated possible uncorrected stray light. Broadening ILS wings will cause additive offset (filling-in) on the deep absorption lines of the spectra, which we confirmed using offline bias correction of the solar-induced fluorescence retrieval. We estimated errors due to the imperfect ILS using simulated TanSat spectra. The results of the simulations showed that XCO2 retrieval is sensitive to errors in the ILS, and 4% uncertainty in the full width of half maximum (FWHM) or 20% uncertainty in the ILS wings can induce an error of up to 1 ppm in the XCO2 retrieval.

Like other proteins, the natural silk fibroin (SF) extracted from domesticated silkworms can adsorb at the air/water interface and stabilize foam due to its amphiphilic character and surface activity. At the interface, the adsorbed SF molecules experience structural reorganization and form water-insoluble viscoelastic films, which protect foam bubbles from coalescence and rupture. The solution conditions, such as protein concentration, pH, and additives, have significant influences on the molecular adsorption, layer thickness, interfacial mechanical strength, and, thus, on the foaming properties of SF. The understanding of the relationship between the interfacial adsorption, surface viscoelasticity, and foaming properties of SF is very important for the design, preparation, and application of SF foams in different fields.

Magnesium alloys exhibit superior biocompatibility and biodegradability, which makes them an excellent candidate for artificial implants. However, these materials also suffer from lower corrosion resistance, which limits their clinical applicability. The corrosion mechanism of Mg alloys is complicated since the spontaneous occurrence is determined by means of loss of aspects, e.g., the basic feature of materials and various corrosive environments. As such, this study provides a review of the general degradation/precipitation process multifactorial corrosion behavior and proposes a reasonable method for modeling and preventing corrosion in metals. In addition, the composition design, the structural treatment, and the surface processing technique are involved as potential methods to control the degradation rate and improve the biological properties of Mg alloys. This systematic representation of corrosive mechanisms and the comprehensive discussion of various technologies for applications could lead to improved designs for Mg-based biomedical devices in the future.

Cartilage-derived stem/progenitor cells (CSPCs) are a potential choice for seed cells in osteal and chondral regeneration, and the outcomes of their survival and position distribution in vivo form the basis for the investigation of their mechanism. However, the current use of in vivo stem cell tracing techniques in laboratories is relatively limited, owing to their high operating costs and cytotoxicity. Herein, we performed tri-modal in vivo imaging of CSPCs during subcutaneous chondrogenesis using upconversion nanoparticles (UCNPs) for 28 days. Distinctive signals at accurate positions were acquired without signal noise from X-ray computed tomography, magnetic resonance imaging, and upconversion luminescence. The measured intensities were all significantly proportional to the cell numbers, thereby enabling real-time in vivo quantification of the implanted cells. However, limitations of the detectable range of cell numbers were also observed, owing to the imaging shortcomings of UCNPs, which requires further improvement of the nanoparticles. Our study explores the application value of upconversion nanomaterials in the tri-modal monitoring of implanted stem cells and provides new perspectives for future clinical translation.

The structure of Cu50Zr50 and Co56Ta35B9 metallic glass thin films (MGTF) was effectively tailored via various applied substrate temperatures by means of the magnetron sputtering technology. Obviously enhanced hardness and elastic modulus are achieved by different compositional MGTFs by increasing the substrate temperature. Compared with the CuZr MGTFs, the CoTaB MGTF deposited at 473 K displays the smaller strain-rate sensitivity exponent, m, and a weaker spectrum intensity based on the nanoindentation creep test, suggesting its better creep resistance. In addition, the STZ volume of the CoTaB MGTF significantly decreases after depositing at higher temperature. According to the nano-scratch analysis, the CoTaB MGTF at the substrate temperatures of 473 K performs the shallower scratch width and the larger H3/E2 value, indicating its better tribological property.

During the 2014 Asia-Pacific Economic Cooperation (APEC) Economic Leaders’ Meetings in Beijing, the Chinese government made significant efforts to clear Beijing’s sky. The emission control measures were very effective and the improved air quality during the APEC Meetings was called the “APEC Blue”. To monitor and estimate how these emission control measures affected air quality in Beijing and its five neighboring large cities (Tianjin, Shijiazhuang, Tangshan, Jinan, and Qingdao), we compared and analyzed the satellite-retrieved Aerosol Optical Thickness (AOT) products of the pre-APEC (18–31 October), APEC (1–11 November), and post-APEC periods (11–31 November) in 2002–2014 and daily PM2.5 measurements of the three periods in 2014 on the ground. Compared with the pre- and post-APEC periods, both ground and satellite observations indicated significantly reduced aerosol loading during the 2014 APEC period in Beijing and its surroundings, but with apparent spatial heterogeneity. For example, the peak value of PM2.5 in Beijing were around 100 µg∙m−3 during the APEC period, however, during the pre- and post-APEC periods, the peak values were up to 290 µg∙m−3. The following temporal correlation analysis of mean AOT values between Beijing and other five cities for the past thirteen years (2002–2014) indicated that the potential emission source regions strongly impacting air quality of Beijing were confined within central and southern Hebei as well as northern and southwestern Shandong, in correspondence with the spatial pattern of Digital Earth Model (DEM) of the study region. In addition to stringent emission control measures, back trajectory analysis indicated that the relatively favorable regional transport pattern might also have contributed to the “APEC Blue” in Beijing. These results suggest that the “APEC Blue” is a temporarily regional phenomenon; a long-term improvement of air quality in Beijing is still challenging and joint efforts of the whole region are needed.

Periodic narrowband signals and white noise are the main interferences in online detection and localization of cable partial discharge (PD), however, existing research has always focused on the white noise suppression only, which is not in line with the actual scene. A novel de-noising method for effectively extracting random PD pulse from complex and strong interferences is proposed in this paper and applied to PD localization. Firstly, an improved adaptive variational mode decomposition (AVMD) is used to decompose periodic narrowband interference, white noise, and PD signal into different intrinsic mode. According to the characteristic that the power of intrinsic mode component of periodic narrowband interference in the discrete Fourier transformation (DFT) power spectrum is much larger than that of PD and white noise, the periodic narrowband is removed out. In order to effectively filter out white noise, a scale adaptive wavelet packet decomposition method based on correlation coefficient is proposed, which decomposes the signal into high, middle, and low-frequency components. The components with low frequency, small amplitude are removed out as the white noise interference according to the threshold method, and the residual is the de-noising PD signal. Experimental results show that the proposed method can robustly suppress the interference of periodic narrowband signal and white noise, and effectively preserve the essential characteristics of the real PD signal. In the multi-sensor travelling wave based localization system of cable PD source using time-varying kurtosis, accurate estimation of first arrival time of PD pulse can be achieved by the de-noising results.

Since requirements of related applications for time series remotely-sensed images with high spatial resolution have been hard to be satisfied under current observation conditions of satellite sensors, it is key to reconstruct high-resolution images at specified dates. As an effective data reconstruction technique, spatiotemporal fusion can be used to generate time series land surface parameters with a clear geophysical significance. In this study, an improved fusion model based on the Sparse Representation-Based Spatiotemporal Reflectance Fusion Model (SPSTFM) is developed and assessed with reflectance data from Gaofen-2 Multi-Spectral (GF-2 MS) and Gaofen-1 Wide-Field-View (GF-1 WFV). By introducing a spatially enhanced training method to dictionary training and sparse coding processes, the developed fusion framework is expected to promote the description of high-resolution and low-resolution overcomplete dictionaries. Assessment indices including Average Absolute Deviation (AAD), Root-Mean-Square Error (RMSE), Peak Signal to Noise Ratio (PSNR), Correlation Coefficient (CC), spectral angle mapper (SAM), structure similarity (SSIM) and Erreur Relative Global Adimensionnelle de Synthèse (ERGAS) are then used to test employed fusion methods for a parallel comparison. The experimental results show that more accurate prediction of GF-2 MS reflectance than that from the SPSTFM can be obtained and furthermore comparable with popular two-pair based reflectance fusion models like the Spatial and Temporal Adaptive Fusion Model (STARFM) and the Enhanced-STARFM (ESTARFM).

Extracting surface water distribution with satellite imagery has been an important subject in remote sensing. Spectral indices of water only use information from a limited number of bands, thus they may have poor performance from pixels contaminated by ice/snow, clouds, etc. The detection algorithms using information from all spectral bands, such as constrained energy minimization (CEM), could avoid this problem to some extent. However, these are mostly designed for hyperspectral imagery, and may fail when applied to multispectral data. It has been proved that adding linearly irrelevant data to original data could improve the performance of CEM. In this study, two kinds of linearly irrelevant data are added for water extraction: the spectral indices and the spectral similarity metric data. CEM is designed for targets with low-probability distribution in an image, but water bodies do not always satisfy this condition. We thereby impose a sensible coefficient for each pixel to form the weighted autocorrelation matrix. In this study, the weight is based on the orthogonal subspace projection, so this new method is named Orthogonal subspace projection Weighted CEM (OWCEM). The newly launched Landsat 8 images over two lakes, the Hala Lake in China with ice/snow distributed in the north, and the Huron Lake in North America, a lake with a very large surface area, are selected to test the accuracy and robustness of our algorithm. The Kappa coefficient and the receiver operating characteristic (ROC) curve are calculated as an accuracy evaluation standard. For both lakes, our method can greatly suppress the background (including ice/snow and clouds) and extract the complete water surface with a high accuracy (Kappa coefficient > 0.96).

While both periodic narrowband noise and white noise are significant sources of interference in the detection and localization of partial discharge (PD) signals in power cables, existing research has focused nearly exclusively on white noise suppression. This paper addresses this issue by proposing a new signal extraction method for effectively detecting random PD signals in power cables subject to complex noise environments involving both white noise and periodic narrowband noise. Firstly, the power cable signal was decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the periodic narrowband noise and frequency aliasing in the obtained signal components were suppressed using singular value decomposition. Then, signal components contributing significantly to the PD signal were determined according to the cross-correlation coefficient between each component and the original PD signal, and the PD signal was reconstructed solely from the obtained significant components. Finally, the wavelet packet threshold method was used to filter out residual white noise in the reconstructed PD signal. The performance of the proposed algorithm was demonstrated by its application to synthesized PD signals with complex noise environments composed of both Gaussian white noise and periodic narrowband noise. In addition, the time-varying kurtosis method was demonstrated to accurately determine the PD signal arrival time when applied to PD signals extracted by the proposed method from synthesized signals in complex noise environments with signal-to-noise ratio (SNR) values as low as −6 dB. When the SNR was reduced to −23 dB, the arrival time error of the PD signal was only one sampling point.

Melatonin is a biological hormone that plays crucial roles in stress tolerance. In this study, we investigated the effect of exogenous melatonin on abiotic stress in the tea plant. Under cold, salt and drought stress, increasing malondialdehyde levels and decreasing maximum photochemical efficiency of PSII were observed in tea leaves. Meanwhile, the levels of reactive oxygen species (ROS) increased significantly under abiotic stress. Interestingly, pretreatment with melatonin on leaves alleviated ROS burst, decreased malondialdehyde levels and maintain high photosynthetic efficiency. Moreover, 100 μM melatonin-pretreated tea plants showed high levels of glutathione and ascorbic acid and increased the activities of superoxide dismutase, peroxidase, catalase and ascorbate peroxidase under abiotic stress. Notably, melatonin treatments can positively up-regulate the genes (CsSOD, CsPOD, CsCAT and CsAPX) expression of antioxidant enzyme biosynthesis. Taken together, our results confirmed that melatonin protects tea plants against abiotic stress-induced damages through detoxifying ROS and regulating antioxidant systems.

We demonstrate compact, low power, lightweight laser-based sensors for measuring trace gas species in the atmosphere designed specifically for electronic unmanned aerial vehicle (UAV) platforms. The sensors utilize non-intrusive optical sensing techniques to measure atmospheric greenhouse gas concentrations with unprecedented vertical and horizontal resolution (~1 m) within the planetary boundary layer. The sensors are developed to measure greenhouse gas species including carbon dioxide, water vapor and methane in the atmosphere. Key innovations are the coupling of very low power vertical cavity surface emitting lasers (VCSELs) to low power drive electronics and sensitive multi-harmonic wavelength modulation spectroscopic techniques. The overall mass of each sensor is between 1–2 kg including batteries and each one consumes less than 2 W of electrical power. In the initial field testing, the sensors flew successfully onboard a T-Rex Align 700E robotic helicopter and showed a precision of 1% or less for all three trace gas species. The sensors are battery operated and capable of fully automated operation for long periods of time in diverse sensing environments. Laser-based trace gas sensors for UAVs allow for high spatial mapping of local greenhouse gas concentrations in the atmospheric boundary layer where land/atmosphere fluxes occur. The high-precision sensors, coupled to the ease-of-deployment and cost effectiveness of UAVs, provide unprecedented measurement capabilities that are not possible with existing satellite-based and suborbital aircraft platforms.

Optical remote sensing of aquatic vegetation in shallow water is an essential aid to ecosystem protection, but it is difficult because the spectral characteristics of the vegetation are sensitive to external features such as water background effects, atmospheric effects, and the structural properties of the canopy. A global sensitivity analysis of an aquatic vegetation radiative transfer model provides invaluable background for algorithm development for use in optical remote sensing. Here, we use the extended Fourier Amplitude Sensitivity Test (EFAST) method for the modelling. Four different cases were identified by subdividing the ranges of water depth and leaf area index (LAI) involved. The results indicate that the reflectance of emergent vegetation is affected mainly by the concentrations of chlorophyll a + b in leaves (Cab), leaf inclination distribution function parameter (LIDFa) and LAI. The parameter LAI is influential in sparse vegetation cases whereas Cab and LIDFa are influential in dense vegetation cases. Canopy reflectance for submerged vegetation is dominated by water parameters. Relatively, LAI and Cab are highly sensitive vegetation parameters. The analysis is extended to vegetation index as well, which takes the Sentinel-2A as the reference sensor. It shows that NDAVI (Normalized Difference Aquatic Vegetation Index) is suitable for retrieving LAI in all cases except deep-sparse for emergent vegetation, whereas NDVI (Normalized Difference Vegetation Index) would be better in the deep-sparse case. NDVI, NDAVI and WAVI (Water Adjusted Vegetation Index), respectively, are suitable for retrieving Cab, Car and LIDFa in dense cases. For submerged vegetation, the sensitivity of LAI to NDAVI is relatively high only in the shallow-sparse case. The adjustment factor L in SAVI and WAVI fails to suppress the sensitivity to water constituent parameters. The sensitivity of LAI and Cab to NDVI in deep cases is relatively higher than that to the other indices, which may provide clues for the construction of inversion algorithms in macrophyte remote sensing in the aquatic environment using spectral signatures in the visible and near infrared regions.

We developed Cu-deficient, -sufficient and -super nutrition mice models by feeding them with diet containing 1.68, 11.72 or 51.69 mg of Cu/kg for 28 days, respectively. Then, the mice were treated to (−)-epigallocatechin-3-gallate (EGCG, 750 mg/kg BW) by oral in order to assess the acute toxicity of the drug. Following EGCG treatment, the survival rates were 12.5%, 50% and 100% in the Cu-deficient, -sufficient and Cu-super nutrition groups of mice, respectively. Cu level and ceruloplasmin activity in serum were significantly increased with the increase of dietary Cu. However, the Cu supplementation did not produce any obvious impact on serum superoxide dismutase activity. Furthermore, ceruloplasmin, in vitro, significantly promotes EGCG oxidation accompanied with increasing oxidation products and decreasing levels of reactive oxygen species. These results, therefore, suggest that Cu can relieve EGCG hepatotoxicity, possibly by up-regulating ceruloplasmin activity, which can be used to promote EGCG applications.

Saliva contains important personal physiological information that is related to some diseases, and it is a valuable source of biochemical information that can be collected rapidly, frequently, and without stress. In this article, we reported a new and simple localized surface plasmon resonance (LSPR) substrate composed of polyaniline (PANI)-gold hybrid nanostructures as an optical sensor for monitoring the pH of saliva samples. The overall appearance and topography of the substrates, the composition, and the wettability of the LSPR surfaces were characterized by optical and scanning electron microscope (SEM) images, infrared spectra, and contact angles measurement, respectively. The PANI-gold hybrid substrate readily responded to the pH. The response time was very short, which was 3.5 s when the pH switched from 2 to 7, and 4.5 s from 7 to 2. The changes of visible-near-infrared (NIR) spectra of this sensor upon varying pH in solution showed that—for the absorption at given wavelengths of 665 nm and 785 nm—the sensitivities were 0.0299 a.u./pH (a.u. = arbitrary unit) with a linear range of pH = 5–8 and 0.0234 a.u./pH with linear range of pH = 2–8, respectively. By using this new sensor, the pH of a real saliva sample was monitored and was consistent with the parallel measurements with a standard laboratory method. The results suggest that this novel LSPR sensor shows great potential in the field of mobile healthcare and home medical devices, and could also be modified by different sensitive materials to detect various molecules or ions in the future.

Increasing evidence indicates that elevated expression of enhancer of zeste homolog 2 gene (EZH2) in many human malignant tumors acts a significant role in the oncogenic process. However, the underlying molecular mechanism is still unclarified. It is evident that apoptosis and autophagy of tumor cells is crucial for the tumorigenesis and progression of cancer, however, the exact role of EZH2 plays in apoptosis and autophagy has not been fully elucidated in colorectal cancer (CRC). Our previous study found that the expression level of EZH2 was higher in CRC tumor tissues than in the paired normal tissues using immunohistochemical analysis. We also recently found that the autophagy‐related gene‐related protein Ambra1 plays an important role in the autophagy pathway in CRC cells. In this study, mRNA and protein expression of EZH2 in four CRC cell lines were tested at first and RKO and HCT116 cells showed the highest levels among them. Here we transfected with EZH2‐shRNA, or added DZNep (an EZH2 inhibitor) to RKO and HCT116 cells in order to detect the effect of EZH2 on autophagy via determining the change of the protein expression of LC3 and Ambra1. The outcome indicated an obvious decrease of autophagy level in cells transfected with EZH2‐shRNA or DZNep. We also found the apoptotic rate of cells was elevated significantly after downregulation of EZH2. In addition, compared to control group, CRC cells transfected with EZH2‐shRNA or added DZNep revealed a significantly increased G1 cell cycle rate and an obvious decrease in the G2 cell cycle rate. Further analysis showed that knockdown of EZH2 induced cell-cycle arrest in CRC cells. Meanwhile, downregulation of EZH2 in CRC cells induces autophagy and apoptosis. Taken together, our results suggest that EZH2 plays a critical role in autophagy and apoptosis in the progression of CRC, which potentially facilitates the development of an ideal strategy for combating colorectal cancer.

Mechanical stress plays an important role in the initiation and progression of osteoarthritis. Studies show that excessive mechanical stress can directly damage the cartilage extracellular matrix and shift the balance in chondrocytes to favor catabolic activity over anabolism. However, the underlying mechanism remains unknown. MicroRNAs (miRNAs) are emerging as important regulators in osteoarthritis pathogenesis. We have found that mechanical loading up-regulated microRNA miR-365 in growth plate chondrocytes, which promotes chondrocyte differentiation. Here, we explored the role of the mechanical responsive microRNA miR-365 in pathogenesis of osteoarthritis (OA). We found that miR-365 was up-regulated by cyclic loading and IL-1β stimulation in articular chondrocytes through a mechanism that involved the transcription factor NF-κB. miR-365 expressed significant higher level in rat anterior cruciate ligament (ACL) surgery induced OA cartilage as well as human OA cartilage from primary OA patients and traumatic OA Patients. Overexpression of miR-365 in chondrocytes increases gene expression of matrix degrading enzyme matrix metallopeptidase 13 (MMP13) and collagen type X (Col X). The increase in miR-365 expression in OA cartilage and in response to IL-1 may contribute to the abnormal gene expression pattern characteristic of OA. Inhibition of miR-365 down-regulated IL-1β induced MMP13 and Col X gene expression. We further showed histone deacetylase 4 (HDAC4) is a direct target of miR-365, which mediates mechanical stress and inflammation in OA pathogenesis. Thus, miR-365 is a critical regulator of mechanical stress and pro-inflammatory responses, which contributes cartilage catabolism. Manipulation of the expression of miR-365 in articular chondrocytes by miR-365 inhibitor may be a potent therapeutic target for the prevention and treatment of osteoarthritis.