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本文引用的文献

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High expression levels of pyrimidine metabolic rate-limiting enzymes are adverse prognostic factors in lung adenocarcinoma: a study based on The Cancer Genome Atlas and Gene Expression Omnibus datasets.嘧啶代谢限速酶高表达是肺腺癌不良预后因素:基于癌症基因组图谱和基因表达综合数据集的研究。
Purinergic Signal. 2020 Sep;16(3):347-366. doi: 10.1007/s11302-020-09711-4. Epub 2020 Jul 8.
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Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the Global Burden of Disease Study.全球、地区和国家脓毒症发病率和死亡率,1990-2017 年:全球疾病负担研究分析。
Lancet. 2020 Jan 18;395(10219):200-211. doi: 10.1016/S0140-6736(19)32989-7.
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Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction.加权基因共表达网络分析确定急性心肌梗死后心力衰竭发展中的关键基因。
Front Genet. 2019 Nov 26;10:1214. doi: 10.3389/fgene.2019.01214. eCollection 2019.
4
TLR-stimulated IRAKM activates caspase-8 inflammasome in microglia and promotes neuroinflammation.TLR 刺激的 IRAKM 在小胶质细胞中激活 caspase-8 炎性小体并促进神经炎症。
J Clin Invest. 2018 Dec 3;128(12):5399-5412. doi: 10.1172/JCI121901. Epub 2018 Oct 29.
5
Identification of key genes in Gram‑positive and Gram‑negative sepsis using stochastic perturbation.利用随机扰动鉴定革兰氏阳性和革兰氏阴性败血症中的关键基因。
Mol Med Rep. 2017 Sep;16(3):3133-3146. doi: 10.3892/mmr.2017.7013. Epub 2017 Jul 15.
6
Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016.拯救脓毒症运动:脓毒症和脓毒性休克管理国际指南:2016 年版。
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7
The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).《脓毒症及脓毒性休克第三次国际共识定义(脓毒症-3)》
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8
Transcriptomic correlates of organ failure extent in sepsis.脓毒症器官衰竭程度的转录组学相关性。
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9
Interleukin-1 receptor-associated kinase M-deficient mice demonstrate an improved host defense during Gram-negative pneumonia.白介素-1 受体相关激酶 M 缺陷小鼠在革兰氏阴性菌肺炎中表现出改善的宿主防御。
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10
The impact of the types of microorganisms isolated from blood and wounds on the results of treatment in burn patients with sepsis.从血液和伤口分离出的微生物类型对烧伤合并脓毒症患者治疗结果的影响。
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[革兰氏阳性和革兰氏阴性脓毒症患者外周血单核细胞中的主控基因与共表达网络分析]

[Master genes and co-expression network analysis in peripheral blood mononuclear cells of patients with gram-positive and gram-negative sepsis].

作者信息

Li Lu, Fang Junjun, Li Zhitao, Shen Leixing, Wang Guobin, Fu Shuiqiao

机构信息

Department of Clinical Pharmacy, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.

Surgical Intensive Care Unit, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.

出版信息

Zhejiang Da Xue Xue Bao Yi Xue Ban. 2020 Dec 25;49(6):732-742. doi: 10.3785/j.issn.1008-9292.2020.12.08.

DOI:10.3785/j.issn.1008-9292.2020.12.08
PMID:33448176
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10412950/
Abstract

OBJECTIVE

To investigate the functional pathways enriched and differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) of patients with gram-positive and gram-negative sepsis.

METHODS

Dataset GSE9960 obtained from NCBI GEO database containing PBMC samples from 16 non-infectious systematic inflammatory response syndrome (SIRS) patients, 17 gram-positive septic patients and 18 gram-negative septic patients were included in the study. Functional pathway annotations were conducted by gene set enrichment analysis and weighted gene co-expression network analysis. DEGs were filtered and master DEGs were then validated in PBMCs of gram-positive septic, gram-negative septic and non-infectious SIRS patients.

RESULTS

The enriched gene sets in gram-positive sepsis and gram-negative sepsis were significantly different. The results indicated the opposite co-expression networks in SIRS and gram-negative sepsis, and the entirely different co-expression networks in gram-positive and gram-negative sepsis. Furthermore, we validated that was up-regulated in gram-positive sepsis (<0.05), was down-regulated in gram-negative sepsis (<0.01), while was up-regulated in gram-negative sepsis (<0.05).

CONCLUSIONS

The results indicate that there are differences in the mechanism and pathogenesis of gram-positive and gram-negative sepsis, which may provide potential markers for sepsis diagnosis and empirical antimicrobial therapy.

摘要

目的

研究革兰氏阳性菌和革兰氏阴性菌败血症患者外周血单核细胞(PBMC)中富集的功能通路及差异表达基因(DEG)。

方法

从NCBI GEO数据库获取数据集GSE9960,该数据集包含16例非感染性全身炎症反应综合征(SIRS)患者、17例革兰氏阳性菌败血症患者和18例革兰氏阴性菌败血症患者的PBMC样本。通过基因集富集分析和加权基因共表达网络分析进行功能通路注释。筛选DEG,然后在革兰氏阳性菌败血症、革兰氏阴性菌败血症和非感染性SIRS患者的PBMC中验证主要DEG。

结果

革兰氏阳性菌败血症和革兰氏阴性菌败血症中富集的基因集显著不同。结果表明SIRS和革兰氏阴性菌败血症中的共表达网络相反,而革兰氏阳性菌和革兰氏阴性菌败血症中的共表达网络完全不同。此外,我们验证了[具体基因名称1]在革兰氏阳性菌败血症中上调(<0.05),[具体基因名称2]在革兰氏阴性菌败血症中下调(<0.01),而[具体基因名称3]在革兰氏阴性菌败血症中上调(<0.05)。

结论

结果表明革兰氏阳性菌和革兰氏阴性菌败血症的机制和发病机制存在差异,这可能为败血症诊断和经验性抗菌治疗提供潜在标志物。