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Abstract Purpose While asthma comorbidities are associated with higher health care utilisation, lower quality of life and poorer asthma control, the impact of asthma comorbidities on hospitalisation for asthma exacerbation (H-AX) remains less recognised. We aim to analyse the impact of asthma comorbidities on H-AX. Methods Based on a national survey on asthma control and disease perception (CARN 2015 study), we analysed the impact of comorbidities on annual incidence and frequency of H-AX in China. Information on demographic characteristics, asthma comorbidities and annual incidence and frequency of H-AX were presented in this study. Results Among 3875 ambulatory asthma patients, 75.9% (2941/3875) had comorbidities, and 26.4% (1017/3858) experienced H-AX during past year. After adjusting for confounding factors such as demographic data, smoking status and asthma control, COPD [OR = 2.189, 95% CI (1.673, 2.863)] and coronary heart disease [OR = 1.387, 95% CI (1.032, 1.864)] were associated with higher annual incidence, while allergic rhinitis [OR = 0.692, 95% CI (0.588, 0.815)] was associated with lower annual incidence, of H-AX. In terms of frequency, allergic rhinitis [OR = 1.630, 95% CI (1.214, 2.187)], COPD [OR = 1.472, 95% CI (1.021, 2.122)] and anxiety [OR = 2.609, 95% CI (1.051, 6.477)] showed statistically significant correlation with frequent H-AX. Conclusions COPD and coronary heart disease were associated with higher annual incidence, while allergic rhinitis was associated with lower annual incidence of H-AX. Allergic rhinitis, COPD and anxiety were associated with frequent H-AX. Comorbidities may have an important role in the risk and frequency of annual hospitalisations due to asthma exacerbation. The goal of asthma control should rely on a multi-disciplinary treatment protocol.

By connecting the symmetrical spiral inductive sensor to the oil return pipeline of the lubricating oil, a full flow online detection of the size, quantity and other parameters of the tiny metal debris particles in the lubricating oil solution is realised. Inductive sensors are used to excite symmetrical double helix coils, and alternating electromagnetic fields are generated. Changes in induced electromotive force are detected by the centre induction coil. In order to improve the detection accuracy of tiny metal debris particles, the degree of anti-jamming of the excitation signal, and the transmission distance, a method of stimulating using sinusoidal AC steady current signals was designed. The sinusoidal signal generator is designed based on FPGA, and the sinusoidal AC steady current excitation signal is realised through differential amplification, low-pass filtering, and AC steady current amplification, and experimental verification is performed to achieve better excitation and detection results.

Gear and its transmission are widely used in different transmission systems, and its complicated and changeable condition brings a series of problems to the fault feature extraction and diagnosis. In recent years, deep learning techniques have been gradually applied to feature extraction and pattern recognition, and the features of feature extraction and fault diagnosis in complex working environments have shown certain advantages. This study is based on stacked autoencoder under deep learning model, and improve training network performance by modified activation function. Through the network training before and after the experiment done, and to extract the fault feature data comparison in testing, improving network after activation function to extract fault features showed a greater advantage, can be a very good application in practical fault feature extraction.

Lubrication is one of the critical factors for the normal operation of wind turbine's gearbox, which carries abundant and various wear debris. Accordingly, these debris reflects the running state of the equipment and forecasts the early fault of wind turbine gearbox effectively. Thus, the authors can achieve predictive maintenance, even avoid the occurrence of safety accidents. In order to realise real-time online monitoring of lubrication, this article studied the principle of wear debris detection sensor, constructed approximate mathematical model of inductive wearing debris sensor, produced a prototype device, and carried out the monitoring test of metal wearing debris without oil. Experiment shown that the designed sensor can detect the signal of metal wear debris with the smallest diameter to 80μm, which can diagnose the early fault of the wind turbine.

Wear is the main influential reason for the reliability and service life of machinery and the inductive monitoring is the most research and application of online ferromagnetic debris detection for its unique characteristics. In the electromagnetic characteristics analysis of the wear debris, the numerical analysis method can directly solve the problem of electromagnetic field in the form of value, program instead of analytic form. Based on the current research on numerical analysis of electromagnetic characteristics for ferromagnetic debris, the solved problems of numerical analysis are analysed. The core and theoretical basis of numerical analysis of electromagnetic characteristics are studied and assumptions and boundary conditions are provided. Then the present problems and future development trend of the numerical analysis of electromagnetic characteristics for ferromagnetic wear debris are discussed.

Online oil monitoring technique is now an important development means to monitor wear condition and diagnose wear fault real time. Inductive wear debris monitoring is the research hotspot in the current online oil monitoring for its unique characteristics. Based on the current domestic and international online inductive wear debris monitoring, the relevant comments to the online inductive wear debris monitoring technology were given. Then, the positive and inverse problems of numerical analysis of inductive wear debris monitoring are analysed. Based on the above, the difficulties and shortages of online inductive wear debris monitoring are studied and the development trend and research focus of online inductive wear debris monitoring are discussion to provide for the oil online technology research.

In order to improve the operation reliability of high-grade computer numerical control (CNC) machine tools and reduce the maintenance time of failures, the remote state monitoring and intelligent maintenance system for CNC machine tools was proposed. Through collecting the basic information of equipment, maintenance information, and the information of the vibration, temperature, main current and power of the machine tool based on soft-bus technology, the system analysed the real-time state data, got the reliability parameters, extracted the fault features and established the maintenance knowledge base. Combining the dynamic monitoring data and static data, the system evaluated the key parts of machine tools. By the fault knowledge base, the system analysed the reason for failure and recommended the maintenance method. With the function modules, the system can improve the intelligent maintenance level of CNC machine tools and improve the using efficiency of machine tools.

In view of the stability and safe service of the transmission system of the wind turbine, the trend early warning method for the stability deterioration of the electromechanical system is proposed and the level of the predictive maintenance of the complex electromechanical system is improved. It includes: establishing the dynamic model of wind power transmission system, revealing the evolution law of the system stability deterioration, putting forward the signal processing method of the weak detection information, extracting the fault features decoupling with energy and constructing the early warning methods of the system stability deterioration trend. The research results can be applied to the safety monitoring and fault warning of the wind turbine. It is beneficial to ensure the safe and reliable operation of the equipment and realise the prediction maintenance, improve the operation and management level of the equipment, reduce the economic loss caused by the failure and promote the utilisation and development of green energy.

Wear is one of the common faults in the mechanical transmission system. Detection of wear particles in lubricating oil can detect and evaluate the wear degree of mechanical equipment. The electromagnetic sensor for metal wear particle detection can be connected in series with the oil circuit, which has the advantages of full liquid flow, simple structure, distinguishing metal properties, and not being influenced by bubbles and vibration. In view of the shortcomings of the existing electromagnetic sensor for wear particle detection, the detection principle and the induction electromotive force model were studied, and the magnetic field change of the metal particles through three coil differential solenoids was analysed. The optimisation design method was proposed here, which was about the related parameters, such as the wire diameter, the coil turns, the coil widths and so on. The experimental analysis of the sensor was carried out based on detection hardware system that could provide the phase-locked amplification function. The 10-mm inner diameter sensor could detect the minimum 100-μm ferromagnetic metal abrasive particles after optimisation. The developed sensor could provide data information for the abrasive particle detection, fault diagnosis and early warning of wear degree of mechanical equipment.

The aim of the present study was to investigate the influence of hypoxia and PI3K inhibition on angiogenic factors in A549 lung cancer cells. A549 cells were treated with the PI3K inhibitor LY294002 under normoxic and hypoxic conditions. Untreated cells were used as the control group and those treated by the inhibitor, as the suppression group. The cells were further divided based on normoxic or hypoxic conditions and named: Normoxic control group, normoxic suppression group, hypoxic control group and hypoxic suppression group. Expression levels of hypoxia-inducible factor (HIF)-1α and AKT1 mRNA in all groups were determined by reverse transcriptase-quantitative polymerase chain reaction and concentrations of vascular endothelial growth factor (VEGF), angiotensin II (ANG-II), transforming growth factor (TGF)-α/β1, and tumor necrosis factor (TNF)-α in the culture supernatant were measured by enzyme-linked immunosorbent assay. The expression levels of HIF-1α and AKT1 mRNA in the hypoxic control group were higher than those in the normoxic control group and the expression levels of HIF-1α and AKT1 mRNA in the hypoxic control group were higher than those in the hypoxic suppression group. Compared to the normoxic control and normoxic suppression groups, the concentrations of VEGF and TNF-α in supernatant were higher in the hypoxic control and hypoxic suppression groups, respectively. However, TGF-α and TGF-β1 demonstrated the opposite trend of the aforementioned factors. The concentration of ANG-II in the hypoxic suppression group was higher than that in the normoxic suppression group. In addition, compared to the normoxic control group and hypoxic control group, the concentrations of VEGF and TGF-β1 in supernatant were lower in the normoxic suppression group and in the hypoxic suppression group, respectively. In conclusion, the results of the present study suggest that hypoxia can stimulate A549 lung cancer cells to secrete VEGF and TNF-α and inhibit TGF-α and TGF-β1. The ability of A549 cells to secrete VEGF and TGF-β1 is regulated by PI3K/Akt, and ANG-II expression may be regulated by the PI3K/Akt pathway under hypoxic condition. [ABSTRACT FROM AUTHOR]

At present, the types of pollutants in wastewater are more and more complicated, however, the multifunctional membrane materials are in short supply. To prepare a membrane with both high efficient oil-in-water emulsion separation performance and photocatalytic degradation performance of organic dyes, the bifunctional separation membrane was successfully prepared by electrostatic spinning technology of PVDF/PEMA and in situ deposition of anatase TiO2 nanoparticles containing Ti3+ and oxygen vacancies (Ov). The prepared composite membrane has excellent hydrophilic properties (WCA = 15.65), underwater oleophobic properties (UOCA = 156.69), and photocatalytic performance. These composite membranes have high separation efficiency and outstanding anti-fouling performance, the oil removal efficiency reaches 98.95%, and the flux recovery rate (FRR) reaches 99.19% for soybean oil-in-water emulsion. In addition, the composite membrane has outstanding photocatalytic degradation performance, with 97% and 90.2% degradation of RhB and AG-25 under UV conditions, respectively. Several oil-in-water separation and dye degradation experiments show that the PVDF composite membrane has excellent reuse performance. Based on these results, this study opens new avenues for the preparation of multifunctional reusable membranes for the water treatment field.

Physcion and chrysophanol induce defense responses against powdery mildew in cucumbers. The combination of these two compounds has synergistic interaction against the disease. We performed RNA-seq on cucumber leaf samples treated with physcion and chrysophanol alone and with their combination. We generated 17.6 Gb of high-quality sequencing data (∼2 Gb per sample) and catalogued the expressions profiles of 12,293 annotated cucumber genes in each sample. We identified numerous differentially expressed genes that exhibited distinct expression patterns among the three treatments. The gene expression patterns of the Chr and Phy treatments were more similar to each other than to the Phy × Chr treatment. The Phy × Chr treatment induced the highest number of differentially expressed genes. This dramatic transcriptional change after Phy × Chr treatment leaves reflects that physcion combined with chrysophanol treatment was most closely associated with induction of disease resistance. The analysis showed that the combination treatment caused expression changes of numerous defense-related genes. These genes have known or potential roles in structural, chemical and signaling defense responses and were enriched in functional gene categories potentially responsible for cucumber resistance. These results clearly demonstrated that disease resistance in cucumber leaves was significantly influenced by the combined physcion and chrysophanol treatment. Thus, physcion and chrysophanol are appealing candidates for further investigation of the gene expression and associated regulatory mechanisms related to the defense response.

Cistanche deserticola MA (C. deserticola) has been widely used as a laxative herbal in herbal medicine for the treatment of irritable bowel syndrome or constipation, and echinacoside (ECH) is one of the major bioactive ingredients in this herbal. Our aim was to investigate the effect of ECH on intestinal epithelial cell growth and death. MODE-K, an intestinal epithelial cell line, was used as an in vitro model of the intestine. Cell proliferation was measured by methylthiazol tetrazolium (MTT) assay. Cell apoptosis was determined with Annexin-V staining. Here we showed that in cultured MODE-K cells, ECH significantly stimulated cell proliferation and enhanced cell survival by reducing cell apoptosis in the presence of H2O2 or the mixture of pro-inflammatory cytokines, while transforming growth factor (TGF)-β1 expression was up-regulated in a dose-dependent manner. Knockdown of TGF-β1 expression disrupted both the proliferative and cytoprotective activities of ECH, which was further confirmed by neutralization of TGF-β1 activity using anti–TGF-β1 antibody. These data suggest that ECH as one of bioactive ingredients in herbal C. deserticola and others may improve mucosal tissue repair by stimulating intestinal epithelial cell proliferation and preventing cell death via up-regulation of TGF-β. Keywords:: Cistanche deserticola, intestinal epithelium, cell proliferation, cell apoptosis, transforming growth factor (TGF)-β

Quantitative determination of multiple effective components in a given plant usually requires a very large amount of authentic natural products. In this study, we proposed a rapid and non-destructive method for the simultaneous determination of echinacoside, verbascoside, mannitol, sucrose, glucose and fructose in Cistanche tubulosa by near infrared spectroscopy (NIRS). Near infrared diffuse reflectance spectroscopy (DRS) and high performance liquid chromatography (HPLC) were conducted on 116 batches of C. tubulosa samples. The DRS data were processed using standard normal variety (SNV) and multiplicative scatter correction (MSC) methods. Partial least squares regression (PLSR) was utilized to build calibration models for components-of-interest in C. tubulosa. All models were then assessed by calculating the root mean square error of calibration (RMSEC), correlation coefficient of calibration (r). The r values of all six calibration models were determined to be greater than 0.94, suggesting each model is reliable. Therefore, the quantitative NIR models reported in this study can be qualified to accurately quantify the contents of six medicinal components in C. tubulosa.