化学
辣根过氧化物酶
化学发光
免疫分析
鲁米诺
色谱法
可视化
纳米技术
模式识别(心理学)
人工智能
抗体
计算机科学
酶
生物化学
材料科学
生物
免疫学
作者
Linru Xu,Zhiyuan Cao,Rongliang Ma,Zizheng Wang,Qi Qin,Eryun Liu,Bin Su
出处
期刊:Analytical Chemistry
[American Chemical Society]
日期:2019-09-16
卷期号:91 (20): 12859-12865
被引量:28
标识
DOI:10.1021/acs.analchem.9b02631
摘要
Herein we report the combination of enzyme-linked immunoassay and pattern recognition analysis for extracting both chemical and spatial information from latent fingermarks (LFMs). The development approach basically involves two steps, namely, specific recognition of protein and polypeptide secretions present in the ridge residues of LFMs by horseradish peroxidase (HRP)-labeled antibodies and the HRP-catalyzed chemiluminescent (CL) reaction between luminol and H2O2. The emitted light can spatially resolve the ridges, generating a bright image against the dark object surface for visualization of an LFM. Meanwhile, thanks to the molecular specificity of the immunoassay step, the emission also provides us additional information on the existence of specific substances in LFMs. The developed LFMs are further processed by a set of digital image processing procedures. Quantitative analysis based on minutia features shows that even poorly developed fingermarks can be matched successfully. This work offers the promise of facilitating cross-disciplinary studies between data-processing approaches and fingermark development techniques, such as the extraction of more information from LFM evidence, as well as the establishment of evaluation criteria for an enhancement technique.
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