连续性血液净化对脓毒症急性肾损伤患者单核细胞CD14+HLA-DR表达的影响

Chinese Journal of Integrated Traditional and Western Nephrology（2020）

Cited 13|Views45

Abstract

目的:探讨脓毒症合并急性肾损伤(AKI)患者在经过CVVH治疗后促炎介质和单核细胞CD14+HLA-DR的表达与肾功能改善的关系.方法:对我科2016年06月～2018年06月共35例脓毒症合并AKI患者住院患者进行观察,分为肾功能改善组和未改善组,两组患者分别在CVVH治疗前和第5天、第15天抽取血,送检项目包括血肌酐、TNF-α、IL-6、外周血单核细胞CD14+HLA-DR的表达.记录患者肾功能改善及ICU死亡情况.结果:(1)CVVH治疗5 d后,肾功能改善组TNF-α水平在治疗后下降,与治疗前比较差异有统计学意义(P<0.05).与未改善组TNF-α组间比较差异有统计学意义.(2)两组患者CVVH治疗前单核细胞CD14+HLA-DR表达差异无统计学意义,治疗5 d后肾功能改善组单核细胞CD14+HLA-DR比治疗前表达增强,差异有统计学意义(P<0.05).而肾功能未改善组未显示出差异有统计学意义.结论:脓毒症AKI经过CVVH治疗后血浆TNF-α、单核细胞CD14+HLA-DR可能参与了细胞免疫调节的作用,并可能与脓毒症AKI肾功能恢复有关.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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