87 research outputs found

    MoS2 Nanosheets Assembled on Three-Way Nitrogen-Doped Carbon Tubes for Photocatalytic Water Splitting

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    In this work, a micron-sized three-way nitrogen-doped carbon tube covered with MoS2 nanosheets (TNCT@MoS2) was synthesized and applied in photocatalytic water splitting without any sacrificial agents for the first time. The micron-sized three-way nitrogen-doped carbon tube (TNCT) was facilely synthesized by the calcination of commercial sponge. The MoS2 nanosheets were assembled on the carbon tubes by a hydrothermal method. Compared with MoS2, the TNCT@MoS2 heterostructures showed higher H2 evolution rate, which was ascribed to the improved charge separation efficiency and the increased active sites afforded by the TNCT

    Luteolin inhibits GPVI-mediated platelet activation, oxidative stress, and thrombosis

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    Introduction: Luteolin inhibits platelet activation and thrombus formation, but the mechanisms are unclear. This study investigated the effects of luteolin on GPVI-mediated platelet activation in vitro and explored the effect of luteolin on thrombosis, coagulation, and platelet production in vivo.Methods: Washed human platelets were used for aggregation, membrane protein expression, ATP, Ca2+, and LDH release, platelet adhesion/spreading, and clot retraction experiments. Washed human platelets were used to detect collagen and convulxin-induced reactive oxygen species production and endogenous antioxidant effects. C57BL/6 male mice were used for ferric chloride-induced mesenteric thrombosis, collagen-epinephrine induced acute pulmonary embolism, tail bleeding, coagulation function, and luteolin toxicity experiments. The interaction between luteolin and GPVI was analyzed using solid phase binding assay and surface plasmon resonance (SPR).Results: Luteolin inhibited collagen- and convulxin-mediated platelet aggregation, adhesion, and release. Luteolin inhibited collagen- and convulxin-induced platelet ROS production and increased platelet endogenous antioxidant capacity. Luteolin reduced convulxin-induced activation of ITAM and MAPK signaling molecules. Molecular docking simulation showed that luteolin forms hydrogen bonds with GPVI. The solid phase binding assay showed that luteolin inhibited the interaction between collagen and GPVI. Surface plasmon resonance showed that luteolin bonded GPVI. Luteolin inhibited integrin αIIbÎČ3-mediated platelet activation. Luteolin inhibited mesenteric artery thrombosis and collagen- adrenergic-induced pulmonary thrombosis in mice. Luteolin decreased oxidative stress in vivo. Luteolin did not affect coagulation, hemostasis, or platelet production in mice.Discussion: Luteolin may be an effective and safe antiplatelet agent target for GPVI. A new mechanism (decreased oxidative stress) for the anti-platelet activity of luteolin has been identified

    Deep functional analysis of synII, a 770-kilobase synthetic yeast chromosome

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    INTRODUCTION Although much effort has been devoted to studying yeast in the past few decades, our understanding of this model organism is still limited. Rapidly developing DNA synthesis techniques have made a “build-to-understand” approach feasible to reengineer on the genome scale. Here, we report on the completion of a 770-kilobase synthetic yeast chromosome II (synII). SynII was characterized using extensive Trans-Omics tests. Despite considerable sequence alterations, synII is virtually indistinguishable from wild type. However, an up-regulation of translational machinery was observed and can be reversed by restoring the transfer RNA (tRNA) gene copy number. RATIONALE Following the “design-build-test-debug” working loop, synII was successfully designed and constructed in vivo. Extensive Trans-Omics tests were conducted, including phenomics, transcriptomics, proteomics, metabolomics, chromosome segregation, and replication analyses. By both complementation assays and SCRaMbLE (synthetic chromosome rearrangement and modification by loxP -mediated evolution), we targeted and debugged the origin of a growth defect at 37°C in glycerol medium. RESULTS To efficiently construct megabase-long chromosomes, we developed an I- Sce I–mediated strategy, which enables parallel integration of synthetic chromosome arms and reduced the overall integration time by 50% for synII. An I- Sce I site is introduced for generating a double-strand break to promote targeted homologous recombination during mitotic growth. Despite hundreds of modifications introduced, there are still regions sharing substantial sequence similarity that might lead to undesirable meiotic recombinations when intercrossing the two semisynthetic chromosome arm strains. Induction of the I- Sce I–mediated double-strand break is otherwise lethal and thus introduced a strong selective pressure for targeted homologous recombination. Since our strategy is designed to generate a markerless synII and leave the URA3 marker on the wild-type chromosome, we observed a tenfold increase in URA3 -deficient colonies upon I- Sce I induction, meaning that our strategy can greatly bias the crossover events toward the designated regions. By incorporating comprehensive phenotyping approaches at multiple levels, we demonstrated that synII was capable of powering the growth of yeast indistinguishably from wild-type cells (see the figure), showing highly consistent biological processes comparable to the native strain. Meanwhile, we also noticed modest but potentially significant up-regulation of the translational machinery. The main alteration underlying this change in expression is the deletion of 13 tRNA genes. A growth defect was observed in one very specific condition—high temperature (37°C) in medium with glycerol as a carbon source—where colony size was reduced significantly. We targeted and debugged this defect by two distinct approaches. The first approach involved phenotype screening of all intermediate strains followed by a complementation assay with wild-type sequences in the synthetic strain. By doing so, we identified a modification resulting from PCRTag recoding in TSC10 , which is involved in regulation of the yeast high-osmolarity glycerol (HOG) response pathway. After replacement with wild-type TSC10 , the defect was greatly mitigated. The other approach, debugging by SCRaMbLE, showed rearrangements in regions containing HOG regulation genes. Both approaches indicated that the defect is related to HOG response dysregulation. Thus, the phenotypic defect can be pinpointed and debugged through multiple alternative routes in the complex cellular interactome network. CONCLUSION We have demonstrated that synII segregates, replicates, and functions in a highly similar fashion compared with its wild-type counterpart. Furthermore, we believe that the iterative “design-build-test-debug” cycle methodology, established here, will facilitate progression of the Sc2.0 project in the face of the increasing synthetic genome complexity. SynII characterization. ( A ) Cell cycle comparison between synII and BY4741 revealed by the percentage of cells with separated CEN2-GFP dots, metaphase spindles, and anaphase spindles. ( B ) Replication profiling of synII (red) and BY4741 (black) expressed as relative copy number by deep sequencing. ( C ) RNA sequencing analysis revealed that the significant up-regulation of translational machinery in synII is induced by the deletion of tRNA genes in synII. </jats:sec

    MicroRNA-30c inhibits human breast tumour chemotherapy resistance by regulating TWF1 and IL-11

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    Chemotherapy resistance frequently drives tumour progression. However, the underlying molecular mechanisms are poorly characterized. Epithelial-to-mesenchymal transition (EMT) has been shown to correlate with therapy resistance, but the functional link and signalling pathways remain to be elucidated. We report here that miR-30c, a human breast tumour prognostic marker, plays a pivotal role in chemo-resistance by a direct targeting of TWF1, which encodes an actin-binding protein and promotes EMT. An IL-6 family member, IL-11 was identified as a secondary target of TWF1 in the miR-30c signalling pathway. Expression of miR-30c inversely correlated with TWF1 and IL-11 levels in primary breast tumours and low IL-11 correlated with relapse-free survival in breast cancer patients. Our study demonstrates that miR-30c is transcriptionally regulated by GATA3 in breast tumours. Identification of a novel miRNA-mediated pathway that regulates chemo-resistance in breast cancer will facilitate the development of novel therapeutic strategies

    Governance and Actions for Resilient Urban Food Systems in the Era of COVID-19: Lessons and Challenges in China

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    The COVID-19 pandemic has drastically challenged urban food systems, has hurt the resilience and fundamental function of urban food systems and also accelerated the trends of digitization and changing preferences of consumers in cities. This research conducted a qualitative analysis of the discourses, actions and interactions of different actors in the urban food systems in China during COVID-19 using an actor-oriented approach and discourse analysis. This research finds that stricter regulations and policies have been implemented by governments to regulate the food supply chain and ensure human health. Local community service personnel, volunteers, stakeholders along the food supply chain and consumers formulated collective actions during the pandemic yet chaos and discourse distortions also emerged at different stages. The pandemic is a preamble to changes in consumers’ preferences and food supply chains in urban communities. There were significant structural changes and a dual structure of urban and rural food systems, where unbalanced supply and demand existed. Collective actions with community governance and an innovative food business model to digitize flows and easily adapt to shocks in food systems are required

    Effectiveness of blended learning on improving medical student’s learning initiative and performance in the physiology study

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    AbstractIn recent years, online learning has been widely used than before. However, it depends on student’s learning initiative and lacks of teacher-student interaction, which cannot bring desired learning performance. In our physiology teaching practice to “5 + 3” integration medical student, we tried to combine online and classroom learning to form the blended learning. This study assessed the effectiveness of the blended learning on students’ learning initiative and performance in the physiology study. It included 180 full-time students from clinical medical specialty across two academic years. These students were divided into the experimental classes receiving blended learning and the control classes receiving traditional learning. We carried out three classroom tests and one questionnaire survey. It found that the students of blended learning who mastered most of the content were as twice as the students of traditional learning. The average accuracy of classroom tests was above 90% from the students of the blended learning, which was higher than the approximate rate of 80% of from the students of the traditional learning. Both the times of preparing lessons and answering questions in class increased in the blended learning practice. In addition, students of blended learning were relatively unaffected by playing with the mobile phones in the class. It found that students acquired more knowledge, performed better in the classroom tests and their learning initiative was excited in the blended learning.This study provides the effect assessment and contributes to improve the teaching effect of the blended learning

    Genetic evidence supporting a causal role of Janus kinase 2 in prostate cancer: a Mendelian randomization study

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    AbstractBackground Janus kinase-2 (JAK2) inhibitors are now being tried in basic research and clinical practice in prostate cancer (PCa). However, the causal relationship between JAK2 and PCa has not been uniformly described. Here, we examined the cause-effect relation between JAK2 and PCa.Methods Two-sample Mendelian randomization (MR) analysis of genetic variation data of JAK2, PCa from IEU OpenGWAS Project was performed by inverse variance weighted, MR-Egger, and weighted median. Cochran’s Q heterogeneity test and MR-Egger multiplicity analysis were performed to normalize the MR analysis results to reduce the effect of bias on the results.Results Five instrumental variables were identified for further MR analysis. Specifically, combining the inverse variance-weighted (OR: 1.0009, 95% CI: 1.0001–1.0015, p = 0.02) and weighted median (OR: 1.0009, 95% CI: 1.0000–1.0017, p = 0.03). Sensitivity analysis showed that there was no heterogeneity (p = 0.448) and horizontal multiplicity (p = 0.770) among the instrumental variables.Conclusions We found JAK2 was associated with the development of PCa and was a risk factor for PCa, which might be instructive for the use of JAK2 inhibitors in PCa patients

    Protein-protein interactions prediction via multimodal deep polynomial network and regularized extreme learning machine

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    Predicting the protein-protein interactions (PPIs) has played an important role in many applications. Hence, a novel computational method for PPIs prediction is highly desirable. PPIs endow with protein amino acid mutation rate and two physicochemical properties of protein (e.g., hydrophobicity and hydrophilicity). Deep polynomial network (DPN) is well-suited to integrate these modalities since it can represent any function on a finite sample dataset via the supervised deep learning algorithm. We propose a multimodal DPN (MDPN) algorithm to effectively integrate these modalities to enhance prediction performance. MDPN consists of a two-stage DPN, the first stage feeds multiple protein features into DPN encoding to obtain high-level feature representation while the second stage fuses and learns features by cascading three types of high-level features in the DPN encoding. We employ a regularized extreme learning machine to predict PPIs. The proposed method is tested on the public dataset of H. pylori, Human, and Yeast and achieves average accuracies of 97.87%, 99.90%, and 98.11%, respectively. The proposed method also achieves good accuracies on other datasets. Furthermore, we test our method on three kinds of PPI networks and obtain superior prediction results.Accepted versio
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