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引用次数: 0
摘要
败血症是由感染引发的严重全身炎症综合征,是重症监护病房(ICU)发病率和死亡率的主要原因。免疫功能障碍是败血症的标志。在这项研究中,作者利用单细胞 RNA 测序(scRNA-seq)研究了淋巴源性白细胞之间的细胞-细胞通讯,以深入了解晚期败血症的潜在机制。作者的研究结果表明,与健康人相比,脓毒症患者细胞间相互作用的数量和强度都有所增加,其中有几种通路发生了显著变化,尤其是在传统树突状细胞(cDCs)和浆细胞树突状细胞(pDCs)中。值得注意的是,脓毒症患者的 CD6-ALCAM 等通路更为活化,这可能是由于 T 细胞抑制所致。这项研究为了解免疫抑制的机制提供了新的视角,并为脓毒症的临床干预提供了潜在的途径。
Inference and analysis of cell-cell communication of non-myeloid circulating cells in late sepsis based on single-cell RNA-seq.
Sepsis is a severe systemic inflammatory syndrome triggered by infection and is a leading cause of morbidity and mortality in intensive care units (ICUs). Immune dysfunction is a hallmark of sepsis. In this study, the authors investigated cell-cell communication among lymphoid-derived leucocytes using single-cell RNA sequencing (scRNA-seq) to gain a deeper understanding of the underlying mechanisms in late-stage sepsis. The authors' findings revealed that both the number and strength of cellular interactions were elevated in septic patients compared to healthy individuals, with several pathways showing significant alterations, particularly in conventional dendritic cells (cDCs) and plasmacytoid dendritic cells (pDCs). Notably, pathways such as CD6-ALCAM were more activated in sepsis, potentially due to T cell suppression. This study offers new insights into the mechanisms of immunosuppression and provides potential avenues for clinical intervention in sepsis.
期刊介绍:
IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells.
The scope includes the following topics:
Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.