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IMPORTANCE: The synergy of two oncogenic retroviruses is an essential phenomenon in nature. The synergistic replication of ALV-J and REV in poultry flocks increases immunosuppression and pathogenicity, extends the tumor spectrum, and accelerates viral evolution, causing substantial economic losses to the poultry industry. However, the mechanism of synergistic replication between ALV-J and REV is still incompletely elusive. We observed that microRNA-155 targets a dual pathway, PRKCI-MAPK8 and TIMP3-MMP2, interacting with the U3 region of ALV-J and REV, enabling synergistic replication. This work gives us new targets to modulate ALV-J and REV's synergistic replication, guiding future research on the mechanism.
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Vírus da Leucose Aviária , Leucose Aviária , MicroRNAs , Doenças das Aves Domésticas , Vírus da Reticuloendoteliose , Animais , Vírus da Reticuloendoteliose/genética , Vírus da Leucose Aviária/genética , Galinhas , MicroRNAs/genética , Replicação ViralRESUMO
Avian leukosis virus subgroup J (ALV-J) induces myelocytomas, which can metastasize to multiple organs in diseased chickens. Although metastasis is the primary cause of death in such cases, the mechanism for it remains unclear. Here, we found that interaction between ALV-J surface protein (SU) and doublecortin-like kinase 1 (DCLK1) promotes epithelial-mesenchymal transition (EMT) and cell proliferation. We found that ALV-J can activate EMT in infected cells. Subsequently, proteomics analysis revealed that DCLK1, a well-established putative tumor stem cell marker, which is highly expressed in ALV-J-infected DF-1 cells and chickens, might be a potential factor mediating EMT. Furthermore, using immunofluorescence and immunoprecipitation, we verified that SU interacts with DCLK1. Functional studies suggested that overexpression of DCLK1 increased viral replication and promoted cell proliferation by accelerating the progression of cells from the G0/G1 phase to the S phase of cell cycle, whereas RNA interference of DCLK1 reduced viral replication and arrested cell proliferation by retarding cell cycle progression from the late G1 phase into the S phase in ALV-J-infected cells. Moreover, we demonstrate that the increased accumulation of DCLK1 promotes EMT by increasing the expression of N-cadherin, vimentin, MMP2, and transcription factor Snail1 and decreasing the expression of epithelial marker E-cadherin. These results suggest that ALV-J SU interacts with DCLK1, and accelerates cell proliferation, leading to increased viral replication and ultimately activating EMT, which paves the way for tumor metastasis. IMPORTANCE Tumor metastasis is a major challenge in cancer research, because of its systemic nature and the resistance of disseminated tumor cells to existing therapeutic agents. It is estimated that >90% of mortality from cancer is attributable to metastases. We found that ALV-J can activate EMT, which plays a critical role in cancer metastasis. Subsequently, we identified a tumor stem cell marker, DCLK1, in ALV-J infected cells, which interacts with surface protein (SU) of ALV-J to promote virus replication, activate EMT, and accelerate cell proliferation enabling ALV-J to obtain metastatic ability. Understanding the process of participation of ALV-J in EMT and the route of metastasis will help elucidate the mechanism of virus-induced tumor metastasis and help identify promising molecular targets and key obstacles for ALV-J control and clinical technology development.
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Vírus da Leucose Aviária , Leucose Aviária , Quinases Semelhantes a Duplacortina , Transição Epitelial-Mesenquimal , Proteínas de Membrana , Animais , Leucose Aviária/fisiopatologia , Vírus da Leucose Aviária/genética , Proliferação de Células , Galinhas , Quinases Semelhantes a Duplacortina/metabolismo , Proteínas de Membrana/metabolismoRESUMO
It is well-established that the genetic diversity, regional prevalence, and broad host range of astroviruses significantly impact the poultry industry. In July 2022, a small-scale commercial broiler farm in China reported cases of growth retardation and a 3% mortality rate. From chickens displaying proventriculitis and pancreatitis, three chicken astroviruses (CAstV) isolates were obtained and named SDAU2022-1-3. Complete genomic sequencing and analysis revealed the unique characteristics of these isolates from known CAstV strains in ORF1a, ORF1b, and ORF2 genes, characterized by an unusually high variability. Analysis of amino acid mutations in ORF1a, ORF1b, and ORF2 indicated that the accumulation of these mutations played a pivotal role in the emergence of the variant strain. Inoculation experiments demonstrated that affected chickens exhibited liver and kidney enlargement, localized proventricular hemorrhage, and a dark reddish-brown appearance in about two-thirds of the pancreas. Histopathological examination unveiled hepatic lymphocytic infiltration, renal tubular epithelial cell swelling, along with lymphocytic proventriculitis and pancreatitis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis indicated viremia and viral shedding at 3 days post-infection (dpi). The proventriculus displayed the highest viral loads, followed by the liver, kidney, duodenum, and pancreas. Liver parameters (AST and ALT) and kidney parameters (UA and UN) demonstrated mild damage consistent with earlier findings. While the possibility of new mutations in the ORF2 gene of CAstV causing proventriculitis and pancreatitis warrants further investigation, these findings deepen our comprehension of CAstV's pathogenicity in chickens. Additionally, they serve as valuable references for subsequent research endeavors.
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Infecções por Astroviridae , Avastrovirus , Pancreatite , Doenças das Aves Domésticas , Animais , Avastrovirus/genética , Galinhas , Virulência , Infecções por Astroviridae/veterinária , Infecções por Astroviridae/epidemiologia , Pancreatite/veterinária , FilogeniaRESUMO
Chiral pseudo[1]rotaxanes and [1]rotaxanes constructed from macrocyclic arenes still remain a big challenge mainly owing to the lack of such chiral macrocycles. In this work, a new system of chiral pseudo[1]rotaxanes formed by self-inclusion of helic[6]arene containing amide linked with the terminal tertiary amines was first discovered. Based on an atom-economic stopping strategy, a pair of chiral [1]rotaxanes were conveniently obtained in almost quantitative yields by blocking the pseudo[1]rotaxanes with monobenzyl bromide of tetraphenylethene. The structures of pseudo[1]rotaxanes and [1]rotaxanes were characterized by 2D NMR spectra in solution, combined with DFT calculations. The photophysical properties further revealed the efficient chirality transfer of helic[6]arene to the tetraphenylethene moiety, compared to their unthreaded chiral isomers. The discovery of the chiral pseudo[1]rotaxanes allows for a wide and available synthesis of chiral [1]rotaxanes, and also opening a new avenue to the design of chiral supramolecular materials.
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Outlier detection is an important research direction in the field of data mining. Aiming at the problem of unstable detection results and low efficiency caused by randomly dividing features of the data set in the Isolation Forest algorithm in outlier detection, an algorithm CIIF (Cluster-based Improved Isolation Forest) that combines clustering and Isolation Forest is proposed. CIIF first uses the k-means method to cluster the data set, selects a specific cluster to construct a selection matrix based on the results of the clustering, and implements the selection mechanism of the algorithm through the selection matrix; then builds multiple isolation trees. Finally, the outliers are calculated according to the average search length of each sample in different isolation trees, and the Top-n objects with the highest outlier scores are regarded as outliers. Through comparative experiments with six algorithms in eleven real data sets, the results show that the CIIF algorithm has better performance. Compared to the Isolation Forest algorithm, the average AUC (Area under the Curve of ROC) value of our proposed CIIF algorithm is improved by 7%.
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In most of the existing multi-task learning (MTL) models, multiple tasks' public information is learned by sharing parameters across hidden layers, such as hard sharing, soft sharing, and hierarchical sharing. One promising approach is to introduce model pruning into information learning, such as sparse sharing, which is regarded as being outstanding in knowledge transferring. However, the above method performs inefficiently in conflict tasks, with inadequate learning of tasks' private information, or through suffering from negative transferring. In this paper, we propose a multi-task learning model (Pruning-Based Feature Sharing, PBFS) that merges a soft parameter sharing structure with model pruning and adds a prunable shared network among different task-specific subnets. In this way, each task can select parameters in a shared subnet, according to its requirements. Experiments are conducted on three benchmark public datasets and one synthetic dataset; the impact of the different subnets' sparsity and tasks' correlations to the model performance is analyzed. Results show that the proposed model's information sharing strategy is helpful to transfer learning and superior to the several comparison models.
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The massive global consumption and discarded face masks drove by the ongoing spread of COVID-19. Meantime, incineration and landfill discarded face masks would result in severe environmental pollution and infectious hazards. Herein a suggestion to recycle polypropylene waste masks into CNTs by an environmentally friendly and high-added value disposal process was proposed, and which was prepared as supercapacitor electrode materials for energy storage attempting. The CNTs were prepared from waste masks by catalysis pyrolysis with Ni-Fe bimetallic catalysts. Especially, the bamboo-like structure CNT was obtained with Ni/Fe molar ratio is 3. This structure owned a high specific capacitance compared to other standard CNTs. Its specific capacitance could reach 56.04 F/g (1 A/g) and has excellent cycling stability with a capacitance retention rate of the material is 85.41% after 10,000 cycles. Besides, the assembled capacitor possesses a good energy density of 4.78 Wh/kg at a power density of 900 W/kg. Thus, this work provides a sustainable and cost-effective strategy for disposing waste masks into high-valuable CNT, and their potential application for supercapacitors was also studied and exploited. It would provide a new idea for recycling and utilizing other polypropylene wastes such as medical devices.
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An approach to the highly efficient synthesis of C(sp3)-bridged [6]cycloparaphenylenes (C[6]CPPs) from fluoren[3]arenes (F[3]As) was developed. Consequently, F[3]As as a new kind of macrocyclic arenes were synthesized. Followed by the demethylation, triflation and intramolecular aryl-aryl coupling reactions, C[6]CPPs were then conveniently obtained. Interestingly, C[6]CPPs could be selectively methylated to produce their fully outer-methyl-substituted derivatives. The crystal structures showed the hydroxyl-substituted F[3]As had bowl-shaped conformations, and the C[6]CPPs exhibited rigid belt-shaped structures with deep cavities. Moreover, C[6]CPPs exhibited high HOMO energies and narrow energy gaps. An unclosed belt was further obtained, and it not only showed a similar narrow energy gap to those of the aromatic belts, but also displayed strong fluorescence property, which can play a vital role in the design and synthesis of new aromatic belts.
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The design and synthesis of nitrogen-doped aromatic belts with conjugated structures still remain a challenge. Here, we report the first nitrogen-doped aromatic belt with a [6]cycloparaphenylene skeleton, which is conveniently synthesized from the easily available calix[3]carbazole. The aromatic belt has a rigid conjugated structure and deep cavity, and it can encapsulate one dichloromethane both in solution and in the solid state. Interestingly, the aromatic belt shows strong green fluorescence with a quantum yield of 0.39 and exhibits a narrow HOMO-LUMO energy gap of 2.02â eV. The belt-shaped conjugated structure composed of three carbazole subunits has specific optoelectronic properties that will promote wide applications in supramolecular chemistry and materials science.
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BACKGROUND: The pathogenesis of immunological tolerance caused by avian leukosis virus subgroup J (ALV-J), an oncogenic retrovirus, is largely unknown. RESULTS: In this study, the development, differentiation, and immunological capability of B cells and their progenitors infected with ALV-J were studied both morphologically and functionally by using a model of ALV-J congenital infection. Compared with posthatch infection, congenital infection of ALV-J resulted in severe immunological tolerance, which was identified as the absence of detectable specific antivirus antibodies. In congenitally infected chickens, immune organs, particularly the bursa of Fabricius, were poorly developed. Moreover, IgM-and IgG-positive cells and total immunoglobulin levels were significantly decreased in these chickens. Large numbers of bursa follicles with no differentiation into cortex and medulla indicated that B cell development was arrested at the early stage. Flow cytometry analysis further confirmed that ALV-J blocked the differentiation of CD117+chB6+ B cell progenitors in the bursa of Fabricius. Furthermore, both the humoral immunity and the immunological capability of B cells and their progenitors were significantly suppressed, as assessed by (a) the antibody titres against sheep red blood cells and the Marek's disease virus attenuated serotype 1 vaccine; (b) the proliferative response of B cells against thymus-independent antigen lipopolysaccharide (LPS) in the spleen germinal centres; and (c) the capacities for proliferation, differentiation and immunoglobulin gene class-switch recombination of B cell progenitors in response to LPS and interleukin-4(IL-4) in vitro. CONCLUSIONS: These findings suggested that the anergy of B cells in congenitally infected chickens is caused by the developmental arrest and dysfunction of B cell progenitors, which is an important factor for the immunological tolerance induced by ALV-J.
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Vírus da Leucose Aviária/imunologia , Leucose Aviária/congênito , Subpopulações de Linfócitos B/patologia , Anergia Clonal , Doenças das Aves Domésticas/congênito , Células-Tronco/patologia , Animais , Anticorpos Antivirais/sangue , Leucose Aviária/patologia , Vírus da Leucose Aviária/patogenicidade , Subpopulações de Linfócitos B/química , Subpopulações de Linfócitos B/imunologia , Subpopulações de Linfócitos B/virologia , Bolsa de Fabricius/patologia , Diferenciação Celular , Proliferação de Células , Galinhas , Citometria de Fluxo , Imunoglobulina G/sangue , Imunoglobulina M/sangue , Doenças das Aves Domésticas/patologia , Proteínas Proto-Oncogênicas c-kit/análise , Células-Tronco/química , Células-Tronco/imunologia , Células-Tronco/virologiaRESUMO
BACKGROUND: Co-infection with avian leukosis virus subgroup J and reticuloendotheliosis virus induces synergistic pathogenic effects and increases mortality. However, the role of exosomal miRNAs in the molecular mechanism of the synergistic infection of the two viruses remains unknown. RESULTS: In this study, exosomal RNAs from CEF cells infected with ALV-J, REV or both at the optimal synergistic infection time were analysed by Illumina RNA deep sequencing. A total of 54 (23 upregulated and 31 downregulated) and 16 (7 upregulated and 9 downregulated) miRNAs were identified by comparing co-infection with two viruses, single-infected ALV-J and REV, respectively. Moreover, five key miRNAs, including miR-184-3p, miR-146a-3p, miR-146a-5p, miR-3538 and miR-155, were validated in both exosomes and CEF cells by qRT-PCR. GO annotation and KEGG pathway analysis of the miRNA target genes showed that the five differentially expressed miRNAs participated in virus-vector interaction, oxidative phosphorylation, energy metabolism and cell growth. CONCLUSIONS: We demonstrated that REV and ALV-J synergistically increased the accumulation of exosomal miRNAs, which sheds light on the synergistic molecular mechanism of ALV-J and REV.
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Vírus da Leucose Aviária/fisiologia , Coinfecção , Exossomos/genética , MicroRNAs/genética , Interações Microbianas , Vírus da Reticuloendoteliose/fisiologia , Infecções por Retroviridae/genética , Infecções por Retroviridae/virologia , Animais , Leucose Aviária/genética , Leucose Aviária/metabolismo , Leucose Aviária/virologia , Linhagem Celular , Exossomos/metabolismo , Exossomos/ultraestrutura , Regulação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Interações Hospedeiro-Patógeno , Interferência de RNA , Reprodutibilidade dos Testes , Infecções por Retroviridae/metabolismo , Replicação ViralRESUMO
We describe the first case of Stevens-Johnson syndrome (SJS) occurring 8 days after the first dose of a three-dose rabies vaccination series. She had no history of vaccine-related rash or other adverse drug reactions, nor had she received any other drug therapy. The temporal relationship between the development of SJS and the vaccination suggests that the rabies vaccination probably was the causal agent. This case serves as a warning of a distinct cutaneous reaction of rabies vaccination.
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Vacina Antirrábica/efeitos adversos , Síndrome de Stevens-Johnson/etiologia , Vacinação/efeitos adversos , Feminino , Humanos , Raiva/prevenção & controle , Vacina Antirrábica/administração & dosagem , Síndrome de Stevens-Johnson/fisiopatologia , Adulto JovemRESUMO
The research and application of bearing fault diagnosis techniques are crucial for enhancing equipment reliability, extending bearing lifespan, and reducing maintenance expenses. Nevertheless, most existing methods encounter challenges in discriminating between signals from machines operating under normal and faulty conditions, leading to unstable detection results. To tackle this issue, the present study proposes a novel approach for bearing fault detection based on graph neural networks and ensemble learning. Our key contribution is a novel stochasticity-based compositional method that transforms Euclidean-structured data into a graph format for processing by graph neural networks, with feature fusion and a newly proposed ensemble learning strategy for outlier detection specifically designed for bearing fault diagnosis. This approach marks a significant advancement in accurately identifying bearing faults, highlighting our study's pivotal role in enhancing diagnostic methodologies.
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A new macrocyclic arene, dibenzofuran[3]arene, was synthesized, which could be conveniently transformed to an O-doped aromatic belt with a rigid ring-shaped structure and deep cavity. Moreover, the O-doped aromatic belt also showed a high HOMO energy and a narrow HOMO-LUMO gap experimentally and theoretically.
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A calix[3]carbazole-based cavitand was conveniently synthesized. It was found that the cavitand with adjustable conformation could show excellent complexation with fullerenes C60 and C70 in both solution and the solid state. Moreover, the crystal structures of the host-guest complexes show that the cavitand can stack into channel-like architectures, in which fullerenes are orderly arranged inside.
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Outlier detection is an important topic in machine learning and has been used in a wide range of applications. Outliers are objects that are few in number and deviate from the majority of objects. As a result of these two properties, we show that outliers are susceptible to a mechanism called fluctuation. This article proposes a method called fluctuation-based outlier detection (FBOD) that achieves a low linear time complexity and detects outliers purely based on the concept of fluctuation without employing any distance, density or isolation measure. Fundamentally different from all existing methods. FBOD first converts the Euclidean structure datasets into graphs by using random links, then propagates the feature value according to the connection of the graph. Finally, by comparing the difference between the fluctuation of an object and its neighbors, FBOD determines the object with a larger difference as an outlier. The results of experiments comparing FBOD with eight state-of-the-art algorithms on eight real-worlds tabular datasets and three video datasets show that FBOD outperforms its competitors in the majority of cases and that FBOD has only 5% of the execution time of the fastest algorithm. The experiment codes are available at: https://github.com/FluctuationOD/Fluctuation-based-Outlier-Detection .
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This study explores the analysis and modeling of energy consumption in the context of database workloads, aiming to develop an eco-friendly database management system (DBMS). It leverages vibration energy harvesting systems with self-sustaining wireless vibration sensors (WVSs) in combination with the least square support vector machine algorithm to establish an energy consumption model (ECM) for relational database workloads. Through experiments, the performance of self-sustaining WVS in providing power is validated, and the accuracy of the proposed ECM during the execution of Structured Query Language (SQL) statements is evaluated. The findings demonstrate that this approach can reliably predict the energy consumption of database workloads, with a maximum prediction error rate of 10% during SQL statement execution. Furthermore, the ECM developed for relational databases closely approximates actual energy consumption for query operations, with errors ranging from 1 to 4%. In most cases, the predictions are conservative, falling below the actual values. This finding underscores the high predictive accuracy of the ECM in anticipating relational database workloads and their associated energy consumption. Additionally, this paper delves into prediction accuracy under different types of operations and reveals that ECM excels in single-block read operations, outperforming multi-block read operations. ECM exhibits substantial accuracy in predicting energy consumption for SQL statements in sequential and random read modes, especially in specialized database management system environments, where the error rate for the sequential read model is lower. In comparison to alternative models, the proposed ECM offers superior precision. Furthermore, a noticeable correlation between model error and the volume of data processed by SQL statements is observed. In summary, the relational database ECM introduced in this paper provides accurate predictions of workload and database energy consumption, offering a theoretical foundation and practical guidance for the development of eco-friendly DBMS.
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To improve the corrosion inhibition of zinc-rich epoxy (ZRE) composite coatings and shed light on the influence of the spatial structure of graphene fillers on the coatings' performance, three-dimensional graphene (3DG) and a conventional graphene sheet (G) were used to modify the ZRE composite paint, respectively. The effect of introducing the 2D G fillers on the anti-corrosion behavior of ZRE was studied comprehensively, and its optimal content was determined to be 0.5 wt%. Interestingly, it was found that, comparing with 2D graphene sheets, the corrosion resistance of the ZRE coating could be enhanced more significantly with incorporating even less 3DG. With introducing only 0.1 wt% 3DG, the corrosion current intensity of the resulting 3DG/ZRE coating was reduced to be about 1/10 that of the G/ZRE coating with the same graphene content and 27% of that of the optimized G/ZRE. The corrosion products of the coating were analyzed with the XRD technique. The results indicated that, in contrast to neat ZRE coating, Zn5(CO3)2(OH)6 was absent from the corroded 3DG/ZRE coating, confirming its improved long-term anti-corrosion performance. The porous interconnected framework and high crystallinity of 3DG could contribute to not only its facilely mixing with epoxy resin, but also its effective incorporation into the conductive network of zinc micro-flakes, thus enhancing the corrosion resistance of its ZRE coating at a lower content. The innovative technology to improve the anti-corrosion performance of the ZRE coatings via using the 3D graphene fillers should be capable to be extended to other 2D fillers, such as MXenes.
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Serum amyloid A (SAA), an acute response phase protein (APP), is crucial for the innate immune response during pathogenic microorganisms' invasion. Marek's disease virus (MDV) is a highly oncogenic alphaherpesvirus that activates multiple innate immune molecules, including SAA, in the host during infection. However, the pathway through which SAA participates in MDV-induced host innate immunity remains unknown. The present study aimed to elucidate the pathway through which SAA exerts its anti-MDV function. We observed that MDV infection in vivo and in vitro significantly elevated SAA expression. Furthermore, through SAA overexpression and knockdown experiments, we demonstrated that SAA could inhibit MDV replication. Subsequently, we found that SAA activated Toll-Like Receptor 2/4 (TLR2/4) -mediated Interferon Beta (IFN-ß) promoter activity and IFN regulatory factor 7 (IRF7) promoter activity. During MDV infection, SAA enhanced TLR2/4-mediated IFN-ß signal transduction and messenger RNAs (mRNAs) expression of type I IFN (IFN-I) and interferon-stimulated genes (ISGs). Finally, TLR2/4 inhibitor OxPAPC inhibits the anti-MDV activity of SAA. These results demonstrated that SAA inhibits MDV replication and enhancing TLR2/4-mediated IFN-ß signal transduction to promote IFNs and ISGs expression. This finding is the first to demonstrate the signaling pathway by which SAA exerts its anti-MDV function. It also provides new insights into the control of oncogenic herpesviruses from the perspective of acute response phase proteins.
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Herpesvirus Galináceo 2 , Interferon Tipo I , Doença de Marek , Animais , Galinhas , Herpesvirus Galináceo 2/genética , Interferon Tipo I/metabolismo , Interferon beta/genética , Interferon beta/metabolismo , Doença de Marek/genética , Proteína Amiloide A Sérica/genética , Proteína Amiloide A Sérica/metabolismo , Transdução de Sinais , Receptor 2 Toll-Like/genética , Receptor 2 Toll-Like/metabolismo , Receptor 4 Toll-Like/metabolismoRESUMO
To promote the anticorrosion performance of epoxy/zinc (EP/Zn) coating, graphene oxide (GO) was directly incorporated into dual-component paint. Interestingly, it was found that the method of incorporating GO during the fabrication of the composite paints strongly influenced their performance. The samples were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and Raman spectroscopy. The results indicated that GO could be intercalated and modified with the polyamide curing agent while preparing component B of the paint, for which the interlayer spacing of the resulting polyamide modified GO (PGO) increased, and its dispersion in organic solvent was improved. The corrosion resistance of the coatings was studied through potentiodynamic polarization testing, electrochemical impedance spectroscopy (EIS), and immersion testing. Among the three types of as-prepared coatings, i.e., neat EP/Zn coating, GO modified EP/Zn coating (GO/EP/Zn), and PGO-modified EP/Zn coating (PGO/EP/Zn), the order of the corrosion resistance of the coatings was PGO/EP/Zn > GO/EP/Zn > neat EP/Zn. This work demonstrates that although the in situ modification of GO with a curing agent is a simple method, it evidently promotes the shielding effect of the coating and enhances its corrosion resistance.