Coatings
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2025
·Vol. 15
·期 3
·271
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IF 2.8
Yong Yao,Weitao Huang,Mumin Rao,Yang Cao,Congshu Huang,Yu Liang,Canxing Tan,Yeqiang Mo
The main load-bearing structure of offshore wind power is mainly metal, and the corrosion of metal structures is particularly serious when exposed to corrosive environments, such as high salt and humidity for a long period of time and has attracted more and more attention from researchers at home and abroad. Epoxy resin is used as a matrix resin in both primer and middle coatings. In anti-corrosion coatings, when additives are added to the epoxy system, the affinity and hydrophobicity of the additives themselves affect the protective effect of the system. In this study, the effects of two additives, BIB (containing hydrophilic groups) and HFTC (containing both hydrophilic and hydrophobic groups), on the corrosion protection properties of epoxy adhesives were investigated. The impact of these additives on the contact angle, water absorption rate, salt spray resistance, and overall corrosion resistance was evaluated using various experimental methods. The results show that the BIB additive is not conducive to the enhancement of epoxy coatings’ anti-corrosive properties due to its good hydrophilicity. The addition of HFTC can effectively improve the protective performance of the coating, and when the addition of HFTC is 0.6%, the salt spray resistance of the composite coating is optimized. This study provides valuable insights into the optimization of epoxy systems for enhanced corrosion protection in marine environments.
研究领域:
材料科学
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腐蚀与防护
✓ 已验证
产品关联
DOI
高影响因子
BRIEFINGS IN BIOINFORMATICS
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2020
·Vol. 22
·期 4
·
IF 8.99
Zheng Shuangjia,Rao Jiahua,Song Ying,Zhang Jixian,Xiao Xianglu,Fang Evandro Fei,Yang Yuedong,Niu Zhangming
Biomedical knowledge graphs (KGs), which can help with the understanding of complex biological systems and pathologies, have begun to play a critical role in medical practice and research. However, challenges remain in their embedding and use due to their complex nature and the specific demands of their construction. Existing studies often suffer from problems such as sparse and noisy datasets, insufficient modeling methods and non-uniform evaluation metrics. In this work, we established a comprehensive KG system for the biomedical field in an attempt to bridge the gap. Here, we introduced PharmKG, a multi-relational, attributed biomedical KG, composed of more than 500 000 individual interconnections between genes, drugs and diseases, with 29 relation types over a vocabulary of ~8000 disambiguated entities. Each entity in PharmKG is attached with heterogeneous, domain-specific information obtained from multi-omics data, i.e. gene expression, chemical structure and disease word embedding, while preserving the semantic and biomedical features. For baselines, we offered nine state-of-the-art KG embedding (KGE) approaches and a new biological, intuitive, graph neural network-based KGE method that uses a combination of both global network structure and heterogeneous domain features. Based on the proposed benchmark, we conducted extensive experiments to assess these KGE models using multiple evaluation metrics. Finally, we discussed our observations across various downstream biological tasks and provide insights and guidelines for how to use a KG in biomedicine. We hope that the unprecedented quality and diversity of PharmKG will lead to advances in biomedical KG construction, embedding and application.
研究领域:
生物信息学
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医学信息学
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系统生物学
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DOI
高影响因子
BRIEFINGS IN BIOINFORMATICS
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2025
·Vol. 26
·期 3
·
IF 7.7
Wang Mingjuan,Chen Xuetong,Liu Mingxing,Luo Huiying,Zhang Shuangshuang,Guo Jie,Wang Jinghui,Zhou Li,Zhang Na,Li Hongyan,Wang Chao,Li Liang,Wang Zhenzhong,Wang Haiqing,Guo Zihu,Li Yan,Wang Yonghua
Traditional Chinese medicine (TCM) utilizes intricate herbal formulations that exemplify the principles of compatibility and synergy. However, the rapid proliferation of herbal data has resulted in redundant information, complicating the understanding of their potential mechanisms. To address this issue, we first established a comprehensive database that encompasses 992 herbs, 18 681 molecules, and 2168 targets. Consequently, we implemented a multi-network strategy based on a core information screening method to elucidate the highly intertwined relationships among the targets of various herbs and to refine herbal target information. Within a non-redundant network framework, separation and overlap analysis demonstrated that the networking of herbs preserves essential clinical information, including their properties, meridians, and therapeutic classifications. Furthermore, two notable trends emerged from the statistical analyses of classical TCM formulas: the separation of herbs and the overlap between herbs and diseases. This phenomenon is termed the herbal combination model (HCM), validated through statistical analyses of two representative case studies: the common cold and rheumatoid arthritis. Additionally, in vivo and in vitro experiments with the new formula YanChuanQin (YanHuSuo—Corydalis Rhizoma, ChuanWu—Aconiti Radix, and QinJiao—Gentianae Macrophyllae Radix) for acute gouty arthritis further support the HCM. Overall, this computational method provides a systematic network strategy for exploring herbal combinations in complex and poorly understood diseases from a non-redundant perspective.
研究领域:
生物信息学
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传统中医药学
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系统生物学
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产品关联
DOI
PubMed
高影响因子
BRIEFINGS IN BIOINFORMATICS
·
2021
·Vol. 22
·期 2
·1378-1386
·
IF 11.622
Li Shasha,Liu Wenli,Chen Yangzhen,Wang Liqin,An Wenlin,An Xiaoping,Song Lihua,Tong Yigang,Fan Huahao,Lu Chenyang
Antiviral therapies targeting the pandemic coronavirus disease 2019 (COVID-19) are urgently required. We studied an already-approved botanical drug cepharanthine (CEP) in a cell culture model of GX_P2V, a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related virus. RNA-sequencing results showed the virus perturbed the expression of multiple genes including those associated with cellular stress responses such as endoplasmic reticulum (ER) stress and heat shock factor 1 (HSF1)-mediated heat shock response, of which heat shock response-related genes and pathways were at the core. CEP was potent to reverse most dysregulated genes and pathways in infected cells including ER stress/unfolded protein response and HSF1-mediated heat shock response. Additionally, single-cell transcriptomes also confirmed that genes of cellular stress responses and autophagy pathways were enriched in several peripheral blood mononuclear cells populations from COVID-19 patients. In summary, this study uncovered the transcriptome of a SARS-CoV-2-related coronavirus infection model and anti-viral activities of CEP, providing evidence for CEP as a promising therapeutic option for SARS-CoV-2 infection.
研究领域:
病毒学
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分子生物学
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药理学
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转录组学
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传染病学
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DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）