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Fluorescent organic hybrid nanosheets were generated by crystallization of polymers capped with luminogenic molecules exhibiting aggregation-induced emission characteristics (AIE). During crystallization of polymers, AIE molecules were expelled out of lamellar crystals of polymers, and finally resided on the surface. The fluorescent nanosheets with dangling AIE molecules showed sensitive and specific response to explosives. Such polymer crystallization-induced fluorescent nanomaterials offers a unique avenue to fabricate functional nanomaterials with AIE molecule-enriched domains for potential applications in nanodevices, biological engineering, and so on.

Polymer/inorganic functional nanostructures are essential for the fabrication of high-performance nanodevices in the future. The synthesis of hybrid nanostructures is hindered by complicated synthetic protocols or harsh conditions. Herein, we report a facile and scalable method for the synthesis of organometallic polymer nanoribbons through crystallization of polymers capped with a ferrate complex. Nanoribbons consisted of a single crystalline polymer lamella coated with a redox-active ferrate complex on both sides. The nanoribbons had a width of approximately 70 nm and a thickness of 10 nm. With the merit of highly ordered crystalline structures of polymers and functional coating layers, as well as a highly anisotropic nature, the nanoribbons are useful in nanodevices and biosensors.

Background: AMP-activated protein kinase (AMPK) activators can improve inflammatory pain and neuropathic pain. Inflammation translocate signal transducers and activators of transcription 3 (STAT3) to the nuclei of activated macrophages, and STAT3 phosphorylation promotes the expression of inducible nitric oxide synthetase (iNOS). In this study, we determined whether AMPK activation alleviate inflammatory pain via STAT3 nuclear translocation and phosphorylation. Methods: Immunoblotting was used to measure the expression of p-AMPK, and iNOS. Immunoblotting and immunofluorescence were used to detect the nuclear translocation of p-STAT3(Ser727) and STAT3 in macrophages of local inflammatory tissues. Flow cytometry was used to measure reactive oxygen species (ROS) accumulation and mitochondrial damage.Results: AMPK activation with AICAR significantly alleviated pain hypersensitivity and inhibited the expression of iNOS in complete Freund's adjust (CFA)-induced inflamed skin tissues. CFA caused nuclear translocation of STAT3 and p-STAT3(Ser727) in macrophages of inflamed skin tissues. AICAR inhibited nuclear translocation of STAT3 and p-STAT3(Ser727) and promoted the phosphorylation of STAT3(Ser727) in the cytoplasm of macrophages. AICAR also inhibited the expression of iNOS and nuclear translocation of STAT3 and p-STAT3(Ser727), and promoted the phosphorylation of STAT3(Ser727) in NR8383 macrophages treated with CFA. AMPK activation also inhibited the ROS generation and the mitochondrial damage of NR8383 macrophages caused by CFA. In addition, transfection of STAT3 S727D decreased ROS and alleviated mitochondrial damage.Conclusions: Activation of AMPK attenuates inflammatory pain and suppresses STAT3 nuclear translocation and phosphorylation of STAT3(Ser727) in macrophages, resulting in reduced iNOS. Activation of AMPK also promotes phosphorylation of STAT3(Ser727) in the cytoplasm of macrophages to alleviate ROS accumulation and mitochondrial damage associated with inflammation.

A shaking table test of a three-story reinforced concrete (RC) building was conducted. The tested building is vertically irregular because of the first story’s elevated height and the third story’s added RC walls. In addition to far-field ground motions, near-fault ground motions were exerted on this building. A numerical model of the three-story building was constructed. Comparing with the test results indicates that the numerical model is satisfactory for simulating the seismic response of the three-story building. This validated numerical model was then further applied to look into two issues: the effective section rigidities of RC members and the effects of near-fault ground motions. The study results show the magnitude of the possible discrepancy between the actual seismic response and the estimated seismic response, when the effective section rigidities of the RC members are treated as in common practice. An incremental dynamic analysis of the three-story RC building subjected to one far-field and one near-fault ground motion, denoted as CHY047 and TCU052, respectively, was conducted. In comparison with the far-field ground motion, the near-fault ground motion is more destructive to this building. In addition, the effect of the selected near-fault ground motion (i.e. TCU052) on the building’s collapse is clearly identified.

Cell-free DNA (cfDNA) serves as a footprint of the nucleosome occupancy status of transcription start sites (TSSs), and has been subject to wide development for use in noninvasive health monitoring and disease detection. However, the requirement for high sequencing depth limits its clinical use. Here, we introduce a deep-learning pipeline designed for TSS coverage profiles generated from shallow cfDNA sequencing called the Autoencoder of cfDNA TSS (AECT) coverage profile. AECT outperformed existing single-cell sequencing imputation algorithms in terms of improvements to TSS coverage accuracy and the capture of latent biological features that distinguish sex or tumor status. We built classifiers for the detection of breast and rectal cancer using AECT-imputed shallow sequencing data, and their performance was close to that achieved by high-depth sequencing, suggesting that AECT could provide a broadly applicable noninvasive screening approach with high accuracy and at a moderate cost.

BackgroundElectroacupuncture (EA) produces analgesic effects on inflammatory pain partially via activating adenosine monophosphate (AMP)-activated protein kinase (AMPK) pathway in the spinal cord. However, it is unclear whether EA activates AMPK in peripheral tissues in inflammatory pain. This study was aimed at determining whether EA promotes autophagy by activating AMPK to inhibit the expression of inflammatory mediators IL-1β and iNOS in inflamed skin tissues. MethodsIn CFA-induced inflammatory pain in mice, mechanical allodynia and thermal hyperalgesia were tested 2 hours after EA treatment. The AMPK antagonist Compound C was injected intraperitoneally 30 minutes before EA treatment. The analgesic effects of AMPK activator 5-aminoimidazole-4-carboxyamide ribonucleoside (AICAR) were determined and its effects on autophagy, IL-1β and iNOS expression were detected. Also, the effects of the autophagy inhibitor 3-methyladenine (3-MA) on EA analgesia and iNOS/IL-1β expression in inflamed skin tissues were examined. The phosphorylation of AMPK (Thr172) and total AMPK proteins, LC3BII/I, autophagy substrate protein p62, IL-1β and iNOS were detected using Western blotting. Co-labeling of macrophages (CD68) with IL-1β and iNOS was detected using immunofluorescence. In addition, after NR8383 macrophages were treated with CFA, the effects of AICAR and Compound C on autophagy were determined using stubRFP-sensGFP-LC3 Lentivirus..ResultsEA reduced CFA-induced inflammatory pain, activated AMPK and autophagy, and inhibited iNOS and IL-1β expression in inflamed skin tissues. AICAR also attenuated CFA-induced hyperalgesia, promoted autophagy and inhibited iNOS and IL-1β expression in vivo and in vitro. In addition, the AMPK inhibitor Compound C reversed the effect of EA on autophagy. Pretreatment with 3-MA, an inhibitor of autophagy, inhibited the effect of EA on inflammatory pain and expression of iNOS and IL-1β in inflamed skin tissues. ConclusionsEA treatment alleviated inflammatory pain by activation of AMPK, enhancing autophagy, and inhibiting iNOS and IL-1β expression in the inflamed skin tissues.

As one of the most catastrophic natural disasters worldwide, earthquakes and their effect on structures are very important to structural health monitoring (SHM), particularly for the ones living around the Pacific ring of fire. In this regard, SHM techniques with real-time or online processing can be used to identify states of structures, track modal parameters, provide a warning message about damage, and help post-earthquake reconnaissance and rehabilitation. For instance, a recursive formulation based on subspace identification (SI) has been demonstrated that it is capable to track system changes. In this study, a recursive subspace identification (RSI) algorithm with a fixed window is proposed to investigate the time-varying dynamic characteristics under seismic excitations. Subsequently, some suggestion is described and discussed for practical implementation. For verifying the proposed algorithm, different datasets from full-scale experiments are applied to examine its applicability. In other words, the practicability of implementing RSI in real-time or online has been developed and examined in this paper.

We report controllable adjustment of the flow dynamics of polystyrene films supported by oxide-covered silicon by using a combination of ultraviolet ozone (UVO) treatment of the polymer and variable treatments of the substrate that adjust the contents of Si–OH and Si–H groups on the surface. The latter were achieved by submerging the substrates in a piranha solution and then in deionized water (leading to enrichment of Si–OH) or an aqueous hydrogen fluoride solution (leading to enrichment of Si–H) or both (leading to intermediate surface chemistry). X-ray photoelectron spectroscopic chemical analyses showed that the UVO treatment produced oxygenated functional groups in the polymer. Alongside, effective viscosity (ηeff) of the films became enhanced. However, the degree of enhancement increases (decreases) with the content of Si–OH (Si–H) groups on the substrate surface, ascribable to the resulting increases in the attractive interactions between the UVO-induced oxygenated groups in the polymer and Si–OH o...

The scalable growth of wafer-sized single-crystal graphene in an energy-efficient manner and compatible with wafer process is critical for the killer applications of graphene in high-performance electronics and optoelectronics. Here, ultrafast epitaxial growth of single-crystal graphene wafers is realized on single-crystal Cu90Ni10(1 1 1) thin films fabricated by a tailored two-step magnetron sputtering and recrystallization process. The minor nickel (Ni) content greatly enhances the catalytic activity of Cu, rendering the growth of a 4 in. single-crystal monolayer graphene wafer in 10 min on Cu90Ni10(1 1 1), 50 folds faster than graphene growth on Cu(1 1 1). Through the carbon isotope labeling experiments, graphene growth on Cu90Ni10(1 1 1) is proved to be exclusively surface-reaction dominated, which is ascribed to the Cu surface enrichment in the CuNi alloy, as indicated by element in-depth profile. One of the best benefits of our protocol is the compatibility with wafer process and excellent scalability. A pilot-scale chemical vapor deposition (CVD) system is designed and built for the mass production of single-crystal graphene wafers, with productivity of 25 pieces in one process cycle. Furthermore, we demonstrate the application of single-crystal graphene in electrically controlled liquid-crystal microlens arrays (LCMLA), which exhibit highly tunable focal lengths near 2 mm under small driving voltages. By integration of the graphene based LCMLA and a CMOS sensor, a prototype camera is proposed that is available for simultaneous light-field and light intensity imaging. The single-crystal graphene wafers could hold great promising for high-performance electronics and optoelectronics that are compatible with wafer process.

Recently, we found that a brief, 1 s exposure to ultraviolet ozone (UVO) can cause the effective viscosity, ηeff, of polystyrene films supported by oxide-coated silicon (PS-SiOx) to increase by mor...

Interferon-gamma (IFN-γ) is a major effector molecule of immunity and a common feature of tumors responding to immunotherapy. Active IFN-γ signaling can directly trigger apoptosis and cell cycle arrest in human cancer cells. However, the mechanisms underlying these actions remain unclear. Here, we report that IFN-γ rapidly increases protein synthesis and causes the unfolded protein response (UPR), as evidenced by the increased expression of glucose-regulated protein 78, activating transcription factor-4, and c/EBP homologous protein (CHOP) in cells treated with IFN-γ. The JAK1/2-STAT1 and AKT-mTOR signaling pathways are required for IFN-γ-induced UPR. Endoplasmic reticulum (ER) stress promotes autophagy and restores homeostasis. Surprisingly, in IFN-γ-treated cells, autophagy was impaired at the step of autophagosome-lysosomal fusion and caused by a significant decline in the expression of lysosomal membrane protein-1 and −2 (LAMP-1/LAMP-2). The ER stress inhibitor 4-PBA restored LAMP expression in IFN-γ-treated cells. IFN-γ stimulation activated the protein kinase-like ER kinase (PERK)-eukaryotic initiation factor 2a subunit (eIF2α) axis and caused a reduction in global protein synthesis. The PERK inhibitor, GSK2606414, partially restored global protein synthesis and LAMP expression in cells treated with IFN-γ. We further investigated the functional consequences of IFN-γ-induced ER stress. We show that inhibition of ER stress significantly prevents IFN-γ-triggered apoptosis. CHOP knockdown abrogated IFN-γ-mediated apoptosis. Inhibition of ER stress also restored cyclin D1 expression in IFN-γ-treated cells. Thus, ER stress and the UPR caused by IFN-γ represent novel mechanisms underlying IFN-γ-mediated anticancer effects. This study expands our understanding of IFN-γ-mediated signaling and its cellular actions in tumor cells.

In this paper, we propose an extraction method for landslide topographic features and based on these fine features, we trained a landslide stability classification model. Topographic factors have a huge impact on the stability of landslides, and our new feature extraction methods can provide more accurate portraits of landslides. Considering the factors affected landslide stability, this paper studied the factors used in traditional quantitative stability calculations and analyzed the factors affecting stability based on landslide data. So, the proposed method is a combination of theoretical method and numerical method. Based on support vector classification (SVC), random forest (RF), and extreme gradient boosting (XGBoost) models, this paper compares and analyzes the rationality and reliability of the landslide stability classification results output by three models. After adopting the new fine feature extraction method, the accuracy of the stable classification results has been improved by about 5% on average, and the interpretability of the classification results has also been greatly enhanced.

In landslide disaster prevention project, landslide profile is an important research object, which contains rich geological information of landslide. When we get the profile image of the landslide, if we can recommend several landslide cases with similar geological characteristics by the landslide profile image for research, the landslide disaster prevention project can be carried out quickly. In this paper, we propose a recommendation system based on similarity of landslide geological characteristics. The recommendation system is divided into two steps. Firstly, we construct a classification model to obtain the categories of landslide geological characteristics from the profile image by random forest algorithm and supervised machine learning approach. Then, according to the categories of landslide geological characteristics, the landslide case recommended model is constructed, and 5 landslide cases with similar geological characteristics are recommended for the landslide. According to the evaluation index of the recommendation system, the evaluation results show the effectiveness of the recommendation system.

House prices have received unusual attention in recent years, and evaluation of housing price has also become a research hotpot. Value of a house is considered as a mixture of various features, such as house type, orientation and location. Accurate assessment of houses thus faces a large number of challenges. Several methods have been applied to assess the value of a house, including geographically weighted regression and machine learning. However, every method has some limitations. The accuracy of traditional regression methods needs to be improved. Machine learning methods are weak in interpretability. In this paper, to analyze the housing price, we compared XBGoost, Random Forest, Support vector regression, back-propagation network and geographically weighted regression to model the second-hand housing price dataset, and analyzed the influenced of each feature. The result shows Random Forest reaches a lowest mean absolute error of 1517.29 and best r2 of 0.83. According to the constructed models, the importance values are given, and the area of house shows a strongest influence on housing price in the study area.

Electrodynamic suspension (EDS) system based on moving Halbach Array over a conducting plate has been verified to be poor in stability, but it is not clear whether the load could impact on it. This paper focuses on the effect of the load on the stability of the EDS system based on the Halbach array moving over a plate. Generalized energy was introduced by quantifying the Hamiltonian function. By Pade approximation, formulas to obtain both the amplitude and frequency were given. Load varied from 50kg to 64kg, keeping the generalized energy fixed to study the stability. Results show that the stability of electrodynamic suspension system could be improved by lager load, yet the oscillation frequency drifts.

Impervious surfaces have become the most intuitive indicator in the process of urbanization. Timely and accurate information on impervious surfaces from remote sensing images is essential. It not only helps us understand the process of land use/cover change, but also the influences on human society and the environment. In this study, convolutional neural network (CNN) was used to extract the impervious surface in Chengdu city, Sichuan province, China. The overall accuracy in 2009 and 2017 were 98.75% and 99.76% respectively. From the results for 2009 and 2017, the impervious surface increased by 51.24 km2, Growth rate is 13.8%. During the process of urban expansion, suburban farmland was replaced by impervious surfaces and the area of impervious surface gradually increased.