Combining CD64 and CD123 Biomarkers for Sepsis Early Diagnosis and Severity Assessment via PD-L1 Antibody Affinity Microfluidic (PAAM) Chip in Trace Clinical Samples

化学 微流控芯片 CD64 微流控 跟踪(心理语言学) 抗体 色谱法 纳米技术 免疫学 受体 生物化学 语言学 生物 哲学 材料科学
作者
Haoni Yan,Yan Zhang,Yujie Shi,Jiahui Ding,Hengxing Su,Wenqiong Su,Yan Wang,Yanfei Mao,Tawfik A. Khattab,Salhah D. Al‐Qahtani,Aynur Abdulla,Lai Jiang,Xianting Ding
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:97 (14): 7928-7937 被引量:3
标识
DOI:10.1021/acs.analchem.4c07123
摘要

Sepsis, a lethal organ dysfunction caused by a dysregulated host response to infection, is the leading cause of worldwide in-hospital mortality. However, the early diagnostic methods for sepsis are still urgent for guiding accurate antibiotic usage and improving the survival rate of the patients. Herein, we constructed a PD-L1 antibody affinity microfluidic (PAAM) chip for early sepsis diagnosis and severity assessment. The chip was used to capture PD-L1-expressing leukocytes from whole blood samples obtained from healthy control (HC) volunteers (n = 15) and sepsis patients on day 1 (D1) and day 7 (D7) (n = 20), and there was a statistically significant difference between HC and sepsis patients (p < 0.0001), and the AUC was 0.96. However, there was no significant difference in the number of cells captured on-chip between sepsis patients on D1 and D7 (p = 0.16). Therefore, we performed immunofluorescence staining of PD-L1, CD64, and CD123 on the chip. The results showed that the combination of PD-L1, CD64, and CD123 for sepsis diagnosis had an AUC of 0.98, and there was a significant difference in PD-L1+/CD64+/CD123+ leukocytes between sepsis patients on D1 and on D7 (p < 0.0001). In conclusion, we found that the combination of multiple biomarkers was more precise and dependable for sepsis diagnosis and severity assessment.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
1秒前
molihuakai应助俭朴的乐巧采纳,获得10
1秒前
尙光完成签到,获得积分10
2秒前
凌慕完成签到,获得积分10
2秒前
2秒前
yj发布了新的文献求助10
2秒前
香蕉幻桃完成签到,获得积分20
3秒前
3秒前
3秒前
隐形曼青应助无忧的阳光采纳,获得10
3秒前
万能图书馆应助小车采纳,获得10
4秒前
思源应助小娄采纳,获得10
4秒前
王哈哈发布了新的文献求助20
5秒前
ttomatoooooo发布了新的文献求助10
5秒前
Lucas应助朴素蓝采纳,获得10
5秒前
6秒前
wsy123457发布了新的文献求助10
6秒前
笨笨听寒给光亮熠彤的求助进行了留言
7秒前
7秒前
坚定的蜗牛完成签到,获得积分10
7秒前
香蕉幻桃发布了新的文献求助10
7秒前
无花果应助hy采纳,获得10
7秒前
xinxin完成签到,获得积分10
7秒前
SciGPT应助houfei采纳,获得30
7秒前
7秒前
Burger完成签到,获得积分10
8秒前
Owen应助陈俊豪采纳,获得10
8秒前
33发布了新的文献求助10
8秒前
xingyan发布了新的文献求助30
8秒前
Hello应助love采纳,获得10
8秒前
岳博完成签到,获得积分10
9秒前
luyao完成签到 ,获得积分10
9秒前
10秒前
蜗牛杨y完成签到 ,获得积分10
10秒前
10秒前
领导范儿应助科研岗采纳,获得10
10秒前
初景应助番茄不加糖采纳,获得20
10秒前
11秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Mechanisms of Photosynthesis, 4th Edition 1000
Organic Reactions, Volume 116 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7255412
求助须知:如何正确求助?哪些是违规求助? 8877482
关于积分的说明 18747034
捐赠科研通 6935778
什么是DOI,文献DOI怎么找? 3200374
关于科研通互助平台的介绍 2374907
邀请新用户注册赠送积分活动 2175592