| 绿原酸抑制LPS诱导的RAW264.7 细胞炎症及机制探索 |
| 投稿时间：2022-12-07 修订日期：2023-01-17 点此下载全文 |
| 引用本文：周云鑫,刘柯,丁军颖.绿原酸抑制LPS诱导的RAW264.7 细胞炎症及机制探索[J].医学研究杂志,2024,53(1):70-74, 79 |
| DOI：
10.11969/j.issn.1673-548X.2024.01.015 |
| 摘要点击次数: 2048 |
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| 基金项目:北京市自然科学基金资助项目(7182071)；北京市高层次公共卫生技术人才建设项目(学科骨干-01-009) |
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| 中文摘要:目的 明确绿原酸对脂多糖(lipopolysaccharide, LPS)诱导的巨噬细胞RAW264.7炎症的抗炎作用,揭示其可能的分子机制。方法 以CCK-8法检测不同浓度绿原酸干预后RAW264.7的细胞活性；采用LPS刺激巨噬细胞RAW264.7,预制细胞炎性状态,设置空白对照组(K组,n=3)、模型对照组(L组,n=3)和实验组(S组,n=3)分别给药,动态观察细胞形态；分别于24h及48h获取细胞沉淀及上清,以酶联免疫吸附(enzyme-linked immunosorbent assay, ELISA)法检测细胞上清中炎性细胞因子白细胞介素-1β(interleukin-1beta, IL-1β)、单核细胞趋化蛋白-1(monocyte chemoattractant protein-1, MCP-1)及精氨酸酶-1(arginase-1, Arg-1)的浓度；采用实时荧光定量PCR(quantitative real-time polymerase chain reaction, RT-qPCR)法检测前列腺素内过氧化物合酶2(prostaglandin-endoperoxide synthase 2, PTGS2)、转化生长因子β1(transforming growth factor-beta1, TGF-β1)、高迁移率族蛋白1(high mobility group box-1, HMGB1)及核转录因子-κB(nuclear transcription factor-kappaB, NF-κB)的mRNA表达。结果 1μg/ml的LPS成功预制RAW264.7细胞炎性状态；12.5~200.0μg/ml的绿原酸对RAW264.7无明显毒性,50μg/ml及200μg/ml的绿原酸对RAW264.7细胞有明显的增殖作用(P<0.05)；与模型对照组比较,实验组上清中IL-1β蛋白含量明显降低,Arg-1的含量明显升高(P<0.05)；与模型对照组比较,50μg/ml的绿原酸显著降低LPS诱导的炎性细胞中NF-κB、TGF-β1、PTGS2及HMGB1的mRNA表达(P<0.05)。结论 绿原酸对LPS诱导的RAW264.7炎性反应有明确抑制作用,可能与调控HMGB1介导的NF-κB相关通路分子表达有关。 |
| 中文关键词:绿原酸 脂多糖 RAW264.7 抗炎 |
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| Design and Application of an Artificial Intelligence Follow-up System for Gestational Hypertension |
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| Abstract:Purpose/Significance Gestational hypertension poses a serious threat to maternal health. Artificial intelligence(AI) follow-up and management systems contributes to the health of gestational hypertension. Method/Process The paper establishes an AI follow-up system for gestational hypertension based on big data technology and data platforms, including modules such as patient information management, follow-up data management, follow-up plan management, and patient course management. Result/Conclusion The follow-up system can assist doctors in understanding changes in patients’ diseases and meet the hospital’s follow-up management requirements for gestational hypertension in outpatient clinics. |
| keywords:gestational hypertension artificial intelligence follow-up system design |
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