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Herein, vermiculite clay is used as a reinforcement for epoxy resin, which is pretreated with HCl and functionalized with an organosilane. The functional vermiculite nanoparticles (0–10 mass %) are embedded into epoxy resin, and the mixture is subsequently cured with a diamine to yield highly crosslinked vermiculite-epoxy nanocomposites. These nanocomposites are characterized by Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). The curing of epoxy resin with diamine monomer and the inclusion of vermiculite nanoparticles are confirmed by FTIR spectra, SEM micrographs, and X-ray diffraction patterns. The surface morphology examined by SEM exhibits well exfoliation of VMT clay in the epoxy matrix. The extent of curing and glass transition temperatures (Tg) are measured from DSC scans. The functional vermiculite nanoparticles demonstrate the hindrance effect by impeding the curing process. However, Tg of vermiculite-epoxy nanocomposites is increased significantly as compared to the neat epoxy polymer.

Astragali Radix is the dry root of the leguminous plants

Background: Because of intratumor heterogeneity, most patients with solid tumor received limit benefits from the first line regimen. The intratumor heterogeneous molecules are known to drive tumor progression, therapeutic resistance, and disease relapse at late stage across many cancers. The strategy of precise identify the cancer recurrent drive-related heterogeneous molecules from residual tumor tissues is the urgent and unmet clinical need, and it will help clinicians to optimal match the approved cancer-cross-drugs.Methods: The potential cancer recurrent driven targets recognition algorithm was constructed based on proteomics data followed by signal network analysis of tumor tissues before and after treatment. The weight and ranking of the candidate targets were further determined according to advanced research progress and related network databases. Sequential therapies were conducted to confirm the role of cancer recurrent driven molecules in mice with lung metastasis of either BGC823 or B16F10 cells.Results: The algorithm system was established successfully for precise identifying the cancer driven targets from the metastatic lung tumor foci. Thirty-eight candidate targets were identified from residual metastatic foci of GC (gastric cancer) in mice model; and 5 of 38 targets including JWA, MDM2, FASN, USP9X, and PFN1 were sequentially treated with target-specific peptide or inhibitors in BALB/c nude mice; similarly, 5 of 54 candidate targets including JWA, MDM2, SMAD3, IDH1/2, and mTOR were identified from the metastatic lung foci of melanoma and treated sequentially in C57BL/6 mice. Data showed that each additional sequential therapy of new target significantly reduced GC lung metastasis and prolonged the survival in melanoma lung metastasis mice. Meanwhile, both JWA and MDM2 were identified as re-cyclable targets for treatment in both GC and melanoma models. Together, our results may make possible for real individual therapeutic regimens on metastatic GC and melanoma.Conclusions: The highlight of our study should be the tumor recurrent driven targets recognition approach which may pave the way for the rational design of improved therapies against resistant malignancies. More importantly, the recognition algorithm may get into translational significance, and make possible for real precise individual therapeutic regimen of every cancer cases.

Purpose: To investigate the protective effect of floroindole against cecal ligation and puncture (CLP)- induced sepsis, as well as the underlying mechanism of action. Methods: Thirty-five 10–week-old male Wistar rats weighing 190 - 210 g (mean: 200.00 ± 10.10 g) were used for this study. The rats were randomly assigned to seven groups of five rats each, viz, normal control group, and six CLP groups. The CLP groups were those subjected to cecal ligation and puncture (CLP). The first 5 CLP groups received 2, 4, 6, 8 or 10 mg/kg floroindole, respectively, 1 h after CLP, via intraperitoneal route (i.p.) while the 6th CLP group served as untreated control. Western blotting, enzyme-linked immunosorbent assay (ELISA) and real-time quantitative polymerase chain reaction (qRT-PCR) were used for the assessment of the expression levels of tumor necrosis factor-α (TNF- α), interleukn-6 (IL-6), nucleotide-binding oligomerization domain 2 (NOD2) and p-NF-κB p65. Results: Cecal ligation and puncture (CLP) significantly and time-dependently upregulated the expressions of TNF-α, IL-6 and NOD2 in intestinal tissues of rats (p < 0.05). However, treatment with floroindole significantly, and dose-dependently down-regulated CLP-induced expressions of these proteins (p < 0.05). Treatment of rats with floroindole also significantly and dose-dependently inhibited CLP-induced phosphorylation of NF-κB p65 in rat ileum (p < 0.05). Conclusion: The results obtained in this study demonstrate that floroindole confers some degree of protection against CLP-induced sepsis via inhibition of NF-κB p65 phosphorylation.

Knowledge graphs’ reasoning is of great significance for the further development of artificial intelligence and information retrieval, especially for reasoning over temporal knowledge graphs. The rotation-based method has been shown to be effective at modeling entities and relations on a knowledge graph. However, due to the lack of temporal information representation capability, existing approaches can only model partial relational patterns and they cannot handle temporal combination reasoning. In this regard, we propose HTTR: Householder Transformation-based Temporal knowledge graph Reasoning, which focuses on the characteristics of relations that evolve over time. HTTR first fuses the relation and temporal information in the knowledge graph, then uses the Householder transformation to obtain an orthogonal matrix about the fused information, and finally defines the orthogonal matrix as the rotation of the head-entity to the tail-entity and calculates the similarity between the rotated vector and the vector representation of the tail entity. In addition, we compare three methods for fusing relational and temporal information. We allow other fusion methods to replace the current one as long as the dimensionality satisfies the requirements. We show that HTTR is able to outperform state-of-the-art methods in temporal knowledge graph reasoning tasks and has the ability to learn and infer all of the four relational patterns over time: symmetric reasoning, antisymmetric reasoning, inversion reasoning, and temporal combination reasoning.

A novel salicylic acid (SA) molecularly imprinted polymer (MIP) has been synthesized successfully by a surface imprinting technique based on the SBA-15 nanoreactor. SBA-15, selected as the nanoreactor for immobilizing the monomers and template molecules, would be an option to develop a new SA imprinting strategy. The obtained imprinted materials were characterized by Fourier transmission infrared spectrometry (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and nitrogen adsorption–desorption isotherms. The results suggested that MIP possessed an excellent ordered hexagonal mesoporous structure, which preserved the highly ordered mesoporous structure of SBA-15. Experimental variables influencing the adsorption process, including the initial pH, initial concentration and temperature, were optimized by the three-level Box–Behnken experimental design with the three factors combining the response surface method (RSM) for the first time. The optimal adsorption conditions were obtained to achieve the maximum adsorption capacity of SA as follows: initial solution pH 4.62, initial SA concentration 52.38 mg L−1, and temperature 35.0 °C. Under these conditions, the experimental value of the adsorption capacity was 44.435 mg g−1, which was very close to the predicted value (43.429 mg g−1). Furthermore, the adsorption isotherm and selectivity towards SA onto MIP and non-imprinted polymer (NIP) were investigated, indicating that MIP had splendid recognizing ability and a superior specific adsorption capacity (145.19 mg g−1) compared to that of NIP (64.30 mg g−1) at 35 °C. Meanwhile, MIP was regenerated and found to be suitable for reuse in successive adsorption–desorption cycles five times without significant loss in the adsorption capacity. The results suggested that MIP could be used as an excellent adsorbent for the efficient removal of SA from aqueous solution.

Background: Cisplatin (DDP) is a highly effective chemotherapeutic agent to most solid tumors including gastric cancer (GC), however, its clinical value is limited due to severe toxic side effects and secondary drug resistance. JP3, a JWA protein based MMP2-targeted polypeptide, known to inhibit the growth of GC in vivo. However, the bidirectional effects of JP3 in DDP-resistant GC and normal cells have not been demonstrated. The present study aims to investigate the actions of JP3 on protecting normal cells from the toxicity of DDP while enhancing its anti-tumor effects on GC cells. Methods: Routine laboratory experimental methods including CCK-8 assay, Western blotting, Hoechst staining, immunofluorescence (IF) and qRT-PCR were used in mechanism investigation; protein docking analysis and coimmunoprecipitation (Co-IP) were used for prediction and confirmation of interactions between JP3 and CK2. Mouse xenograft model was used for screening the treatment of JP3 plus DDP on GC growth. Results: DDP showed similar toxicities to normal cells and DDP-resistant GC cells; JP3 competitively inhibited the binding of XRCC1 to CK2, reduced the DNA repair and anti-apoptosis capacity of DDP-resistant GC cells in combination with DDP treatment; meanwhile, JP3 protected normal cells from DDP-induced oxidative stress and DNA damage through ERK/Nrf2 signaling. JP3 combined with DDP showed similar bidirectional effects in vivo. Conclusions: JP3 enhanced the inhibitory effects of DDP on tumor growth while reduced toxic side effects of DDP on normal cells. The results of this study provide a new insight for the treatment of drug-resistant GC.

Multi-source knowledge fusion is one of the important research topics in the fields of artificial intelligence, natural language processing, and so on. The research results of multi-source knowledge fusion can help computer to better understand human intelligence, human language and human thinking, effectively promote the Big Search in Cyberspace, effectively promote the construction of domain knowledge graphs (KGs), and bring enormous social and economic benefits. Due to the uncertainty of knowledge acquisition, the reliability and confidence of KG based on entity recognition and relationship extraction technology need to be evaluated. On the one hand, the process of multi-source knowledge reasoning can detect conflicts and provide help for knowledge evaluation and verification; on the other hand, the new knowledge acquired by knowledge reasoning is also uncertain and needs to be evaluated and verified. Collaborative reasoning of multi-source knowledge includes not only inferring new knowledge from multi-source knowledge, but also conflict detection, i.e. identifying erroneous knowledge or conflicts between knowledges. Starting from several related concepts of multi-source knowledge fusion, this paper comprehensively introduces the latest research progress of open-source knowledge fusion, multi-knowledge graphs fusion, information fusion within KGs, multi-modal knowledge fusion and multi-source knowledge collaborative reasoning. On this basis, the challenges and future research directions of multi-source knowledge fusion in a large-scale knowledge base environment are discussed.

Background: JWA gene is known to down-regulate SP1 and reduces the expression level of Integrin αvβ3. Here, we identified a functional polypeptide (JP1) based on the active fragment of the JWA protein to suppress melanoma growth and metastasis by inhibiting the Integrin αvβ3. Methods: We conducted a series of melanoma growth and metastasis mouse models to evaluate anti-melanoma effect of JP1 peptide. 18F-labeled JP1 (18F-NFP-JP1) was detected by Micro-PET assay to demonstrate drug biodistribution. Toxicity test in cynomolgus monkeys and pharmacokinetic studies in rats were done to assess the druggability. The expression of MEK1/2, NEDD4L, SP1 and Integrin αvβ3 were detected in vitro and vivo models. Results: The peptide JP1 with the best anticancer effect was obtained. Micro-PET assay showed that JP1 specifically targeting to melanoma cells in vivo. JP1 inhibited melanoma growth, metastasis, and prolonged the survival of mouse. JP1 reduced the dosage and toxicity in combination with DTIC in melanoma xenograft and allograft mouse models. Cynomolgus monkey toxicity test showed no observed adverse effect level (NOAEL) of JP1 was 150 mg/kg. Mechanistically, JP1 was shown to activate p-MEK1/2 and triggered SP1 ubiquitination in melanoma cells. NEDD4L, an E3 ubiquitin ligase, was activated by p-MEK1/2 and to ubiquitinate SP1 at K685 site, resulting in subsequent degradation. Conclusions: JP1 was developed as a novel peptide that indicated therapeutic roles on proliferation and metastasis of melanoma through the NEDD4L-SP1-Integrin αvβ3 signaling.

In order to minimize energy consumption and running time while ensuring the smoothness of collaborative welding robot with multiple manipulators, a methodology for optimal trajectory planning is proposed. The trajectory is interpolated in each joint space by means of cubic B-spline and motion time nodes are optimized based on particle swarm optimization(PSO) algorithm. The simulation results show that the proposed trajectory planning method provides an ideal trajectory for the joint controller, so that the robot can smoothly complete the welding task with less energy and time consumption.

Aging usually suppresses the renewal and regeneration of intestinal epithelium. The imbalance of intestinal epithelial homeostasis may also be a promoter for aging. JWA responds to oxidative stress and repairs damaged DNA; it participates in multiple cellular processes like cell proliferation and differentiation. Here we identified JWA as a new aging-associated gene, whose deletion-accelerated aging in mice was related to intestinal epithelium atrophy. We further knocked out intestinal epithelial JWA and found it disrupted intestinal epithelial homeostasis, thus promoting aging in mice. Mechanistically, we discovered that JWA deficiency promoted Notch1 ubiquitination degradation via ERK/Fbxw7 cascade and interfered with the PPARγ/Stat5 signal axis. This reduced the intestinal stem cell function and altered the intestinal epithelial cell lineage distribution, finally suppressing the renewal and regeneration of intestinal epithelium. Our results demonstrated that JWA is a new aging-associated gene essential for the renewal and regeneration of intestinal epithelium. We also provide a new idea that maintaining intestinal epithelial homeostasis may be a potential anti-aging strategy in humans or mammals.

Vegetation restoration is an effective method to improve the ecological environment of mine tailings, which has a profound impact on the potential ecological functions of soil fungal communities, yet little is known about its beneficial effect on soil ectomycorrhizal fungal community. In this study, the responses of soil characteristics and soil ectomycorrhizal fungal community diversity and structure to different revegetation, as well as the contribution of soil factors to soil ectomycorrhizal community were investigated in Liaoning Province, China. As we anticipated, the vegetation restoration significantly improved soil nutrients. What’s more, compared to PKSZ and PSC, RPL could better improve soil TC, TN, TP, and AP. In addition, soil ectomycorrhizal community diversity in RPL was greater than PKSZ and PSC. NMDS analyses indicated that soil ectomycorrhizal community significantly differed depending on different revegetation types. Thus, these results indicated that RPL could be a suitable species for the revegetation of iron mine tailings. The experiment provided theoretical basis for evidence for ecological restoration of iron mine tailings using local plant species.

Enhancing teachers' visual digital media design ability is conductive to improving the effectiveness of classroom teaching of art design major. Thoroughly exploring, discussing, and studying the correlation between teachers' visual digital media design ability and effective teaching is a requirement for the professional development of art design teachers, and it is a very meaningful job for cultivating high-quality art design professionals. To this end, this paper aims to study the correlation between teachers’ visual digital media design ability and effective teaching. At first, this paper constructed an Evaluation Index System (EIS) for evaluating teachers’ visual digital media design ability, and gave the calculation methods and steps of the evaluation model based on the entropy weight TOPSIS method; then, the paper employed a Bayesian Convolutional Neural Network (BCNN) and made predictions on the multi-dimensional contribution of teachers' visual digital media design ability to effective teaching through the fusion of evaluation elements. At last, the effectiveness of the constructed EISs and models was verified by experimental results.

Nephrotic syndrome (NS) is one of the leading causes of end-stage renal failure. Unfortunately, reliable surrogate markers for early diagnosing and monitoring the entire progression of NS are as yet absent. A method using UPLC-Q exactive HR-MS was established for the serum metabolomic study of adriamycin-induced nephropathy in rats. Two rat nephropathy models induced by adriamycin were adopted to reflect different degrees of renal damage of early and advanced stages. Then two MPC5 cell models were used to verify the role of proline in the progression of kidney injury. The results showed that seven metabolites such as 14S-HDHA, DPA, and DHA were associated with early renal injury, while 12 metabolites such as tryptophan, linoleyl carnitine, and LysoPC (18:3) reflected the advanced renal disease. At the same time, metabolites including LPE (22:6), LysoPC (22:5), and proline that changed during the whole process of NS were defined as progressive markers. Pathway analysis results showed that fatty acid metabolism, glycerophospholipid metabolism, and amino acids metabolism participated in the occurrence and development of NS. In addition, the change trend of intracellular proline content was consistent with that in serum, and the results were further supported by the detection of the crucial gene PYCRL. This study provides an important basis for searching for diagnostic markers of NS and also provides a methodological reference for early diagnosing and monitoring the pathogenesis of other progressive diseases.

Reconfigurable transfer lines (RTLs), which are highly responsive to demand fluctuations, have gained increasing attention. This research deals with the line configuration design and balancing prob...

Vegetation restoration is an effective method to improve the ecological environment of mine tailings, which has a profound impact on the potential ecological functions of soil fungal communities; yet, little is known about its beneficial effect on soil ectomycorrhizal fungal community. In this study, the responses of soil characteristics and soil ectomycorrhizal fungal community diversity and structure to different revegetation, as well as the contribution of soil factors to soil ectomycorrhizal community were investigated in Liaoning Province, China. As we anticipated, the presence of vegetation significantly improved most soil properties we studied. What’s more, compared to Korean pine (Pinus koraiensis Sieb. et Zucc.), Chinese poplar (Populus simonii Carr), and black locust (Robinia pseudoacacia L) could better improve soil total carbon, total nitrogen, total phosphorus, and available phosphorus. In addition, soil ectomycorrhizal fungal community diversity in black locust was greater than Korean pine and Populus simonii. Nonmetric multidimensional scaling analyses indicated that soil ectomycorrhizal community significantly differed depending on different revegetation types. Thus, these results indicated that black locust could be a suitable species for the revegetation of iron mine tailings. The study provided theoretical basis for ecological restoration of iron mine tailings using local plant species.

Industrial robotics is becoming increasingly popular in the field of manufacturing automation. Two-beam laser welding robot which is a proprietary industrial robot of great importance to improve the welding quality of stringer-skin T-shape structure. In the process of two-beam laser cooperative welding, the robot constantly adjusts its own posture, and the position and posture of each joint would change simultaneously, which leads to the change of the natural frequency, and other dynamic characteristics of the welding robot. Based on the finite element method (FEM), the modal analysis of the robot joints in the range of motion ability and the range of motion in the process of two beam laser welding are studied, which can provide the basis for the design and accurate control of the robot with high degree of freedom (DOF). The dynamic characteristics of the whole robot in different positions and attitudes is carried out, which includes two parts, one is importance ranking of 18 joints of the robot through orthogonal test according to the range of each joint movement. The other is obtaining a plurality of time points in one welding cycle, and performing a modal analysis of the robot at each time point on the basis of the robot joints in the range of motion during the process of two-beam laser welding, the optimal number of time nodes are attained and the test workload could be reduced. The approach described herein provides a theoretical basis for robotics design and control optimization.

Tumor heterogeneity limits the precision treatment of targeted drugs. It is important to find new tumor targets. JWA, also known as ADP ribosylation factor-like GTPase 6 interacting protein 5 (ARL6IP5, GenBank: AF070523, 1998), is a microtubule-associated protein and an environmental response gene. Substantial evidence shows that JWA is low expressed in a variety of malignancies and is correlated with overall survival. As a tumor suppressor, JWA inhibits tumor progression by suppressing multiple oncogenes or activating tumor suppressor genes. Low levels of JWA expression in tumors have been reported to be associated with multiple aspects of cancer progression, including angiogenesis, proliferation, apoptosis, metastasis, and chemotherapy resistance. In this review, we will discuss the structure and biological functions of JWA in tumors, examine the potential therapeutic strategies for targeting JWA and explore the directions for future investigation.

The females and males of dioecious plants have evolved sex-specific characteristics in terms of their morphological and physiological properties. However, the differentiation of phyllosphere microorganism of dioecious plants between parents and hybrid offspring remain largely unexplored. Here, the phyllosphere bacterial and fungal community diversity and composition of female (Populus nigra ‘DH5’ (PNDH5)), male (P. simonii ‘DH4’ (PSDH4)), and the hybrid offspring (P. simonii × P. nigra ‘DH1’ (PSPNDH1), P. simonii × P. nigra ‘DH2’ (PSPNDH2), P. simonii × P. nigra ‘DH3’ (PSPNDH3)) were investigated using 16S rDNA/ITS rDNA gene-based Illumina NovaSeq 6000 sequencing. There was considerable variation of plant height, diameter at breast height, leaf area, length of petioles, leaf moisture content, and starch among different samples, and PSDH2 owned the highest plant height, diameter at breast height, and length of petioles. No distinct differences of phyllosphere bacterial community diversity were observed among PSDH4, PNDH5, PSPNDH1, PSPNDH2, and PSPNDH3; while, PSPNDH2 owned the highest fungal Pielou_e index, Shannon index, and Simpson index. Firmicutes and Ascomycota were the predominant phyllosphere bacterial and fungal community at the phylum level, respectively. Bacilli and Gammaproteobacteria were the two most dominant bacterial classes regardless of parent and the hybrid offspring. The predominant phyllosphere fungal community was Dothideomycetes at the class level. The NMDS demonstrated that phyllosphere microbial community obviously differed between parents and offspring, while the phyllosphere microbial community presented some similarities under different hybrid progeny. Also, leaf characteristics contributed to the differentiation of phyllosphere bacterial and fungal communities between parents and hybrid offspring. These results highlighted the discrimination of phyllosphere microorganisms on parent and hybrid offspring, which provided clues to potential host-related species in the phyllosphere environment.

In the last few years, the availability of temporal knowledge graphs has stimulated extensive research in temporal knowledge graph completion (TKGC) and temporal knowledge graph embedding (TKGE), where temporal information is added to static knowledge graphs that have been widely applied previously. However, most existing methods, such as current state-of-the-art DE-SimplE and TeRo, learn embeddings of temporal-evolving attributes, overlooking the inherent attributes inside entities, where some essential and inherent features are included. In this paper, we introduce a novel method utilizing Inherent Attributes with a Graph Attention network (IAGAT) for TKGC. Our IAGAT extracts inherent attributes from sufficient features corresponding to various facts at different time stamps, to obtain the inherent embeddings. And we take advantages of previous rotation based methods to obtain the temporal-evolving embed-dings. Through extensive experiments and sufficient comparisons, we demonstrate our model outperforms the current state-of-the-art models on link prediction task. Furthermore, we evaluate and prove the necessity of the inherent attributes in performance improvement, and study how our model functions in extracting inherent features.

Knowledge Graphs represent facts with triples containing head entity $h$ , tail entity $t$ and relation $r$ which facilitate applications of many scenarios, for example intelligent web search, community detection and question answering. Knowledge Graph Embedding (KGE) represents elements of triples in a low-dimensional continuous vector space. Though it has been widely studied by both academic and industry communities, most researches focus on learning embeddings of entities and relations separately rather than considering the interactive semantic information between them. However, neither relations nor entities exist lonely out of context. In this paper, we define an interactive semantic space to model the context of triples and propose a novel Bi-linear Semantic Matching Method using Convolutional networks (BiSC). Specifically, we use 1D convolutional neural networks to extract features of the interactive semantics and then compute the similarity scores in the bi-linear space. Compared to existing complex graph network methods, BiSC needs lower computational cost to reach competitive results on link prediction task. The consistent state-of-the-art performance through extensive experiments over two benchmarks demonstrates the advantages of the proposed BiSC model. Further analysis on convergence study and case study of interactive semantic space show the efficiency of our model.

Objective With the development of the society, the number of people who catch the nephrotic syndrome (NS) is going up roughly. As we all know, traditional Chinese medicine (TCM), especially Fangji Huangqi Decoction (FHD), has a long history with good curative effects on NS. However, the mechanism of FHD treating NS has not been clearly elucidated. Methods In this study, TCMSP platform was employed to screen active compounds of each herb of Fangji Huangqi Decoction combined with literatures. Furthermore, PharmMapper and SEA were used to predict and screen the active targets of FHD, and the HOME-NCBI-GENE, GeneCards and OMIM database were used to screen the active targets of NS. The GO and KEGG pathways involved in the targets were analyzed by ClueGO. Finally, contribution index was used to screen the active ingredients of FHD in the treatment of NS. Results After drug-likeness (DL) and bioavailability (OB) filtering, 43 compounds were selected from FHD, interacting with 85 NS-related targets. Systematic analysis of the constructed networks revealed that it was mainly involved in PI3K-Akt signaling pathway, MAPK signaling pathway, T cell receptor signaling pathway and TNF signaling pathway. The contribution index of every active ingredient also indicated five compounds, including astragaloside IV, quercetin, glycyrrhizic acid, glycyrrhizin and fangchinoline. Conclusions These results have successfully predicted the pharmacodynamic material basis and the mechanism efficiency of FHD in the treatment of NS.