Chemiluminescence video assisted by chemometric modeling for forensic identification of blood at crime scenes†

IF 2.6 3区 化学 Q2 CHEMISTRY, ANALYTICAL
Thomas F. F. T. dos Santos, José R. S. Júnior, Licarion Pinto, Tadeu Morais Cruz, Jose Ailton M. Nascimento, Severino Carlos B. Oliveira and Vagner Bezerra dos Santos
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Abstract

The development of advanced chemiluminescent compounds and hematology methodologies has significant implications for forensic science, particularly for the detection of evidential residues at crime scenes. This study introduces a novel chemiluminescent (CL) method that utilizes a smartphone to produce digital videos of the chemiluminescent reaction between the luminol (5-amino-2,3-dihydrophthalazine-1,4-dione) reagent and blood. This innovative approach significantly reduces reagent consumption by 6 times, requiring less than 1 mL/0.01 g of sample/chemicals, which agrees with green chemistry principles. Blood samples used in this study were sourced from bovine liver and human subjects and were collected by the official forensic police at crime scenes. All samples were subsequently discarded by the criminal police. Frames from a 3-minutes video were processed using ImageJ software and the Color Grab app to generate RGB, HSV, and CMYK pattern recognition, combined with chemometric modeling. This enabled the differentiation of samples based on positive and negative patterns, effectively preventing false results. The pattern recognition models developed were able to distinguish bovine from human blood, even after dilution, which simulated attempts to hide traces at crime scenes through washing. The method demonstrated an accuracy of 90.30% with only four prediction errors and presented 100% sensitivity and specificity for the cotton + ceramics class, with 77.78% sensitivity and 93.10% specificity for both the wood and glass classes. Additionally, it was possible to estimate the age of the samples with a precision of 3.6 days. These results were obtained using a new data fusion strategy that facilitated the modeling of digital videos as a combination of frames to enhance model sensitivity and selectivity without increasing model complexity. These results indicate that the developed method is accurate, sensitive, and rapid. Supported by these results, this method represents a significant advancement in forensic science, offering a practical and efficient solution for crime scene investigations.

Abstract Image

化学发光视频辅助的化学计量模型在犯罪现场的血液法医鉴定。
先进化学发光化合物和血液学方法的发展对法医学,特别是对犯罪现场证据残留的检测具有重要意义。本研究介绍了一种新的化学发光(CL)方法,该方法利用智能手机生成鲁米诺(5-氨基-2,3-二氢酞嗪-1,4-二酮)试剂与血液之间化学发光反应的数字视频。这种创新的方法显着减少了6倍的试剂消耗,所需的样品/化学品少于1 mL/0.01 g,符合绿色化学原则。本研究中使用的血液样本来自牛肝脏和人类受试者,并由官方法医在犯罪现场收集。所有样本随后都被刑事警察丢弃。使用ImageJ软件和Color Grab应用程序对3分钟视频中的帧进行处理,生成RGB, HSV和CMYK模式识别,并结合化学计量学建模。这样可以根据阳性和阴性模式区分样品,有效地防止错误结果。开发的模式识别模型能够区分牛血和人血,即使经过稀释,这模拟了通过清洗来隐藏犯罪现场痕迹的尝试。该方法的预测精度为90.30%,预测误差仅为4个,对棉+陶瓷类的敏感性和特异性均为100%,对木材和玻璃类的敏感性和特异性均为77.78%和93.10%。此外,可以以3.6天的精度估计样本的年龄。这些结果是通过一种新的数据融合策略获得的,该策略有助于将数字视频作为帧的组合进行建模,从而在不增加模型复杂性的情况下提高模型的灵敏度和选择性。结果表明,该方法准确、灵敏、快速。在这些结果的支持下,该方法代表了法医学的重大进步,为犯罪现场调查提供了一种实用而高效的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Analytical Methods
Analytical Methods CHEMISTRY, ANALYTICAL-FOOD SCIENCE & TECHNOLOGY
CiteScore
5.10
自引率
3.20%
发文量
569
审稿时长
1.8 months
期刊介绍: Early applied demonstrations of new analytical methods with clear societal impact
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