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The new era background and new social background put forward higher goals for the cultivation of innovative talents. The accurate prediction of the demand for innovation and entrepreneurship vocational ability of higher vocational students provides an important reference for higher vocational educators to formulate refined innovation and entrepreneurship education management strategies, more balanced allocation of limited innovation and entrepreneurship education resources, and make more scientific innovation and entrepreneurship education decisions. This paper studies the prediction of innovation and entrepreneurship vocational ability demand of higher vocational students under the background of digital informatization and theoretically discusses the demand for innovation and entrepreneurship vocational ability of higher vocational students and its connotation. It constructs the demand prediction framework of innovation and entrepreneurship vocational ability of higher vocational students for data identified on the Knowledge Retrieval Engine or High-quality Knowledge Q&A and Sharing Community, and develops the collection and use methods of students' innovation and entrepreneurship resource retrieval data. It makes the feature selection of the keyword sequence and the corresponding time lag sequence selected by the higher vocational students' innovation and entrepreneurship resource retrieval and builds the prediction model of the vocational ability demand for innovation and entrepreneurship of higher vocational students. Experimental results verify the effectiveness of the proposed model.

Different teaching and interaction methods applied by teachers in the virtual teaching environment will lead to certain differences in the characteristics of their teaching behaviors. An in-depth understanding of the teaching behavior characteristics of teachers in virtual digital graphic design teaching and the influencing factors to the teacher-student interaction effect can help different types of teachers cater to students’ extensive needs in learning digital graphic design skills. This paper studies the optimization of teachers’ teaching behaviors in the virtual teaching environment of digital graphic design. Firstly, the problems existing in the application of virtual reality technology in digital graphic design teaching were summarized, a structural model for the virtual teaching environment of digital graphic design was constructed, and the optimization of teachers’ teaching behaviors under the virtual teaching environment of digital graphic design was quantified based on the LDA model. An effect model for teachers’ teaching behaviors was constructed, and through analysis of the evaluation results of students on the virtual digital graphic design teaching effect of teachers, the effectiveness indicator of teachers’ teaching behavior decisions was obtained. The experimental results verified the effectiveness of the proposed model.

Purpose The paper aims to propose a virtual reality (VR) wisdom teaching model in open university English course from the perspective of “Metaverse”. The study aims to testify the stimulation for English learning and the effectiveness of English-expressing with VR tools for adult learners from the practice in a pilot reform project. Design/methodology/approach The paper opted for an exploratory study using ICARE Design Model as the framework, under the grounded theories of constructivism and multi-modal teaching. The study compared the evaluation data of one-semester English learning performance between the experimental class (67 students) with VR practice and the controlled class (67 students), including speaking test score, qualitative feedback and in-depth experience analysis. The data were complemented by reflection paper analysis, including manual evaluation (the criteria of semantics, pronunciation, fluency and completeness), questionnaire survey (in the form of five-point Likert scale) and semi-structured interview. Findings The paper provides empirical insights about the VR wisdom teaching model in English language teaching and learning in a Chinese Open University. The empirical results suggest that “3I” features of VR technology could make up for the shortcomings of traditional English classes in open universities in China, and VR resources designed with curriculum teaching materials could also be helpful for students’ command of knowledge points and language skills. What’s more, the sense of authentic experience in virtual could promote the teaching and learning effect in college English classes. Research limitations/implications The present study focuses on a wisdom mode of foreign language teaching and learning for adult learners in open education, so the research results may lack generalizability. Therefore, researchers are encouraged to further explore the deep integration of VR/artificial intelligence in foreign language teaching and learning. Originality/value This paper fulfills an identified need to study how VR tools provide an engaging, fun and immersive language learning environment, to enhance autonomous learning and learning engagement.

Purpose: To investigate the expression pattern and significance of DNA repair genes JWA and X-ray repair cross complement group 1 (XRCC1) in gastric cancer.Experimental Design: Expressions of JWA and XRCC1 were assessed by immunohistochemistry in a training cohort and they went into a second testing cohort and finally to a validating cohort. Prognostic and predictive role of JWA and XRCC1 expression status in cases treated with surgery alone or combined with adjuvant chemotherapy was evaluated, respectively.Results: JWA and XRCC1 protein levels were significantly downregulated in gastric cancer lesions compared with adjacent noncancerous tissues. Low tumoral JWA or XRCC1 expression significantly correlated with shorter overall survival (OS), as well as with clinicopathologic characteristics in patients without adjuvant treatment. Multivariate regression analysis showed that low JWA and XRCC1 expressions, separately and together, were independent negative markers of OS. Adjuvant fluorouracil-leucovorin-oxaliplatin (FLO) significantly improved OS compared with surgery alone (log-rank test, P = 0.01). However, this effect was evident only in the JWA or XRCC1 low expression group (HR = 0.44; 95% CI: 0.26–0.73; P = 0.002, and HR = 0.44, 95% CI: 0.26–0.75; P = 0.002, respectively); Adjuvant fluorouracil-leucovorin-platinol (FLP) did not improve OS, except in the patients with low JWA and XRCC1 expressions (P = 0.010 for JWA and 0.024 for XRCC1, respectively).Conclusions: JWA and XRCC1 protein expressions in tumor are novel candidate prognostic markers and predictive factors for benefit from adjuvant platinum-based chemotherapy (FLO or FLP) in resectable human gastric carcinoma. Clin Cancer Res; 18(10); 2987–96. ©2012 AACR.

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In the age of the Internet, the teaching of dynamic visual communication design (DVCD) is an irresistible trend for the innovation of visual art teaching. The DVCD teaching quality can be improved to a new level by providing feedbacks to applications with the data on students’ needs for practical perception (PPN). However, the current practical perception and service applications rarely tackle the feature extraction and application of high-level needs for practical perception in the context of digital media. To solve the problem, this paper explores the practical perception and quality evaluation for DVCD teaching in the context of digital media. Specifically, the students’ PPN feature extraction problem was described in the field of DVCD teaching, and fuzzy clustering was introduced to extract students’ PPN features. Then, the authors detailed the dynamic evolution of students’ PPN in the context of digital media, and selected multiple layers of evaluation indices for DVCD teaching quality. Finally, the evolution drivers and patterns of students’ PPN were demonstrated, and the distribution of teaching quality scores was obtained through experiments.

Background: The impact of PICC-related thrombosis is worth paying attention to, and it is important to predict the risk factors for thrombosis in patients with PICC catheterization， accurate scientific assessment tools are critical forpredictingand preventing thrombosis in patients with PICCs.The main objective is to develop and validate a machine learning model for predicting the risk of peripherally inserted central catheter-related venous thrombosis. Methods: Overall, 626 patients undergoing peripherally inserted central catheter placement from January 2016 to October 2020 were enrolled. The variables included patient demographic characteristics, clinical condition, laboratory examinations, treatment, and catheter-related factors. Support vector machine and genetic algorithm were used to develop and optimize the model, respectively. SHapley Additive exPlanations was used to interpret the model. Results: The model obtained an average area under the receiver operating characteristic curve of 0.95. The SHapley Additive exPlanations summary plot was used to illustrate the effects of the top 20 features from support vector machine. This study provides a visual way to illustrate the impact of input features on the result prediction. Conclusions: The machine learning model developed based on genetic algorithm shows good predictive ability in patients with a high risk of thrombosis-related peripherally inserted central catheter. Trial registration:retrospectively registered.

BACKGROUND The impact of PICC-related thrombosis is worth paying attention to, and it is important to predict the risk factors for thrombosis in patients with PICC catheterization，assessment tools are critical for predicting and preventing thrombosis in patients with PICCs.Predictive models would be helpful to estimate the risk of PICC-related thrombosis. OBJECTIVE To develop and validate a machine learning model for predicting the risk of peripherally inserted central catheter-related venous thrombosis. METHODS Overall, 626 patients undergoing peripherally inserted central catheter placement from January 2016 to October 2020 were enrolled. The variables included patient demographic characteristics, clinical condition, laboratory examinations, treatment, and catheter-related factors. Support vector machine and genetic algorithm were used to develop and optimize the model, respectively. SHapley Additive exPlanations was used to interpret the model. RESULTS The model obtained an average area under the receiver operating characteristic curve of 0.95. The SHapley Additive exPlanations summary plot was used to illustrate the effects of the top 20 features from support vector machine. This study provides a visual way to illustrate the impact of input features on the result prediction. CONCLUSIONS The machine learning model developed based on genetic algorithm shows good predictive ability in patients with a high risk of thrombosis-related peripherally inserted central catheter.

In knowledge graph reasoning, the existing graph attention mechanisms tend to distribute attention to certain high-frequency relations. In this work, we design a target relational attention-oriented reasoning model, which focuses more on the relations that match the target relation. We propose a hierarchical (node-level and relational subgraph-level) attention mechanism to aggregate the information of multi-hop neighbors, and to thereby obtain a better node-embedding representation, (with high-order propagation characteristics). The mechanism also relieves over-smoothing to a certain extent. Node-level information aggregation uses the classical graph-attention mechanism, and the distribution of attention in the subgraph-level information aggregation is determined according to the relation in the reasoning task. In other words, we must give these relations different attentions according to the reasoning relation in the task. Experiments show that our model significantly outperforms current state-of-the-art methods. We further study the influence of encoder parameters on the model performance; increasing the number of attention-heads, layers, or hidden out-dimensions can effectively improve the performance.

Objective To evaluate the safety and efficacy of stenting for symptomatic intracranial atherosclerotic severe stenosis or occlusion with Enterprise stents. Methods Fifty-three consecutive patients with symptomatic intracranial atherosclerotic severe (70%–99%) stenosis or occlusion who underwent endovascular treatment with Enterprise stents between September 2019 and March 2022 were retrospectively analyzed. Primary outcomes included technical stenting success rates, the incidence of complications within 30 days of the procedure, and the in-stent restenosis rates during the follow-up period. These outcomes were further categorized based on lesion location and operation time. Results Fifty-seven lesions in 53 patients aged 61.0 ± 10.0 years were treated with Enterprise stents with a technical success rate of 100%. Seven patients (12.3%) had severe complications within 30 days of the procedure: five had a symptomatic ischemic stroke, one had a symptomatic intracerebral hemorrhage, and one had a subarachnoid hemorrhage related to the procedure. No deaths were observed. The rate of in-stent restenosis was 18.2%, with a mean vascular imaging follow-up period of 6.7 months. The 30-day complication and in-stent restenosis rates did not differ significantly between patients with different lesion locations and operation times ( P > 0.05). Conclusion This retrospective study suggests that percutaneous transluminal angioplasty and stenting with Enterprise stents is an effective treatment for symptomatic intracranial arterial stenosis or occlusion with a high technical success rate. It also indicates that stenting during the early nonacute stage after stroke may not increase the incidence of perioperative complications for symptomatic intracranial atherosclerotic stenosis when following strict inclusion criteria.

Fangji Huangqi Decoction (FHD) is a classic prescription of traditional Chinese medicine which is recorded in “Jin Gui Yao Lue”. The purpose of this study is to develop a method for simultaneous determination multicomponent in FHD. The separation of the 19 compounds that included calycosin, calycosin-7-O-β-D-glucoside, formononetin, ononin, methylnissolin, methylnissolin-3-O-glucoside, isomucronulatol, tetrandrine, fangchinoline, atractylenolide-I, atractylenolide-III, liquiritigenin, liquiritin, isomucronulatol-7-O-β-D-glucoside, astragaloside-I, astragaloside-II, astragaloside-III, astragaloside-IV and glycyrrhetinic acid were achieved by linear gradient elution. The 19 components were identified by comparing the chromatographic peaks with the reference compounds and were quantitatively analyzed by multiple reaction monitoring. This method was strict validated with recovery (96.10–101.70%), precision [relative standard deviation (RSD), 1.34–3.34%], stability (RSD, 1.49–3.80%) and repeatability (RSD, 1.60–3.49%), respectively. All the compounds showed good linearities (R2 > 0.999). The limit of detection (LOD) and limit of quantitation (LOQ) for the 19 compounds were in the range of 0.03–0.27 μg/mL (LODs) and 0.05–1.23 μg/mL (LOQs). The correlation analysis indicated that astragalus flavonoids were negatively correlated with astragalosides, tetrandrine and their corresponding flavonoid glycosides, and atractylenolides were positively correlated with astragalosides and fangchinoline. This method proved to be reliable and effective, which would give a helpful basis for the quality control, pharmacological and pharmacokinetic of FHD.

Fangji Huangqi Tang (FHT) was first recorded in "Jin Gui Yao Lue," invented by the archaic Chinese medical doctor Zhongjing Zhang, and is a classic medicine that tonifies qi and expels wind, invigorates spleen for diuresis. A large number of literatures indicated that FHT showed a significant effect on Nephrotic Syndrome (NS). A comprehensive strategy was proposed to discover the potential effective compounds and therapeutic targets of FHT against NS as a case study. Serum metabolomics combined with multivariate statistical analysis was employed to analysis and screen the differential endogenous metabolites in serum samples of the control and model rats induced by Adriamycin. The correlation analysis between the efficacy biomarkers and different compounds absorbed in serum of FHT was conducted to explore the potential effective compounds of FHT against NS. With the help of network pharmacology, the therapeutic targets and the possible molecular mechanisms of FHT against NS were further investigated. Fifteen metabolites, including l-phenylalanine, 3-Hydroxybutyric acid and linolenic acid, were associated with renal damage based on the serum metabolomic results. Metabolic pathway analysis indicated that phenylalanine, tyrosine and tryptophan biosynthesis and linoleic acid metabolism were the key pathways associated with NS. Among them, 6 metabolites were defined as efficacy biomarkers such as uric acid, 2-methylbutyrylcarnitine and 10-HDA. The results of correlation analysis suggested that 14 constituents such as fanGhinoline, cycloastragenol, atractylenolide III, and glycyrrhetinic acid were recognized as potential effective compounds, whose potential protein targets participated in the MAPK signaling pathway, GnRH signaling pathway and aldoaterone-regulated sodium reabsorption. This study has clarified the potential effective compounds and therapeutic targets of FHT against NS. The results provided new evidence for the pharmacological mechanism of FHT on NS.

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.

Background: Triple negative breast cancer (TNBC) is a type of breast cancer with poor prognosis, and still has no adequate therapeutic target and ideal medicine. The public database and the relative studies have shown that low expression of JWA is closely related to the poor overall survival in many cancers including breast cancer. However, the precise biological functions and behind mechanisms of JWA in TNBC are still unclear.Methods: Both TCGA and GEO databases were used to confirm the relationship between expression levels of JWA and overall survival in TNBC cases. JAC1, an agonistic small compound of JWA gene, was used in TNBC models in vitro and in vivo. The routine cellular and molecular assays include CCK-8, colony formation, EdU incorporation, the flow cytometry, Western blot, immunohistochemistry, immune-fluorescence microscopy and reporter gene assays were conducted in this study.Results: Low expression of JWA was associated with poor prognosis in TNBC patients. JAC1 treatment inhibited TNBC cells proliferation and promoted apoptosis in vitro and in vivo. JAC1 specifically combined and targeted YY1 to eliminate its transcriptional inhibition on JWA gene. At the same time, JAC1 promoted ubiquitination and degradation of YY1. The rescued JWA induced G1 phase arrest and apoptosis in TNBC cells through the p38 MAPK signaling pathway. In addition, JAC1 disrupted the interaction between YY1 and HSF1, and suppressed the oncogenic role of HSF1 in TNBC through p-Akt signaling pathway.Conclusions: We discovered for the first time that JAC1 is a YY1 targeting compound and maybe a potential therapeutic agent for TNBC.

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.