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Miniaturized microarray-format digital ELISA enabled by lithographic protein patterning

delete2023-10-01
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OA
AI
A
Andrew Stephens
Y
Yujing Song
B
Brandon L. McClellan
S
Shiuan‐Haur Su
S
Sonnet Xu
K
K. Chen
M
María G. Castro
B
Benjamin H. Singer
K
Katsuo Kurabayashi *
DOI:10.1016/j.bios.2023.115536delete
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摘要

摘要

En 中文
The search for reliable protein biomarker candidates is critical for early disease detection and treatment. However, current immunoassay technologies are failing to meet increasing demands for sensitivity and multi-plexing. Here, the authors have created a highly sensitive protein microarray using the principle of singlemolecule counting for signal amplification, capable of simultaneously detecting a panel of cancer biomarkers at sub-pg/mL levels. To enable this amplification strategy, the authors introduce a novel method of protein patterning using photolithography to subdivide addressable arrays of capture antibody spots into hundreds of thousands of individual microwells. This allows for the total sensor area to be miniaturized, increasing the total possible multiplex capacity. With the immunoassay realized on a standard 75x25 mm form factor glass substrate, sample volume consumption is minimized to <10 mu L, making the technology highly efficient and cost-effective. Additionally, the authors demonstrate the power of their technology by measuring six secretory factors related to glioma tumor progression in a cohort of mice. This highly sensitive, sample-sparing multiplex immunoassay paves the way for researchers to track changes in protein profiles over time, leading to earlier disease detection and discovery of more effective treatment using animal models.
Keyword:
Biomarker discovery
Protein microarray
Protein patterning
Multiplex biomarker detection
Digital immunoassay
Glioma mouse model

期刊

Biosensors and Bioelectronics 封面图
Biosensors and Bioelectronics
IF:
10.5
论文数:
1.8W
被引数:
7.7W

机构

U
University of Michigan
学者数:
6.4W
论文数: 5.3W
被引数: 124
U
university of michigan system
学者数:
9.1W
论文数: 8.6W
被引数: 133
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