在模拟犯罪环境中使用 ATR-FTIR 光谱和化学计量学估算人类血迹的沉积时间

IF 3.7 2区 化学 Q2 AUTOMATION & CONTROL SYSTEMS Chemometrics and Intelligent Laboratory Systems Pub Date : 2024-06-26 DOI:10.1016/j.chemolab.2024.105172
Miguel Mengual-Pujante , Antonio J. Perán , Antonio Ortiz , María Dolores Pérez-Cárceles
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引用次数: 0

摘要

血迹是犯罪现场最常见的液体之一。估计血液沉积时间(TSD)对于指导警方调查和澄清刑事犯罪具有重要意义。沉积后的时间通常是通过模拟血液生物大分子随时间推移而发生的物理化学降解来估算的。这项工作展示了一项 ATR-FTIR 光谱和化学计量学研究,用于估算不同表面和不同环境条件(室内和室外)下血迹的 TSD。在 0 至 212 天期间,共分析了 960 块污渍。所获得的 11 个偏最小二乘回归(PLSR)模型中的大多数都显示出良好的预测能力,残差预测偏差(RPD)值大于 3,R2 大于 0.90。非刚性支撑的模型比刚性支撑的模型显示出更好的预测能力。非刚性表面模型包括各种非刚性表面和环境条件,从犯罪学的角度来看,这可能是最有用的模型。这些结果表明,该技术可以成为犯罪现场血迹 TSD 原位测定的快速、可靠和可信的工具。
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Estimation of human bloodstains time since deposition using ATR-FTIR spectroscopy and chemometrics in simulated crime conditions

Blood in the form of stains is one of the most frequently encountered fluid in crime scene. Estimation of the time since deposition (TSD) is of great importance to guide the police investigation and the clarification of criminal offences. The time elapsed since deposition is usually estimated by modelling the physicochemical degradation of blood biomolecules over time. This work shows an ATR-FTIR spectroscopy and chemometrics study to estimate TSD of bloodstains on various surfaces and under different ambient conditions (indoor and outdoor). For a period from 0 to 212 days, a total of 960 stains were analyzed. Most of the eleven partial least squares regression (PLSR) models obtained showed a good prediction capacity, with a Residual Predictive Deviation (RPD) value higher than 3, and R2 higher than 0.90. Models for non-rigid supports showed better predictive capacity than those for rigid ones. A non-rigid surface model including the various non-rigid surfaces and ambient conditions was elaborated, which might be the most useful one from the criminalistic point of view. These results show that this technique can be a rapid, robust, and trustable tool for in situ determination of the TSD of bloodstains at crime scenes.

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来源期刊
CiteScore
7.50
自引率
7.70%
发文量
169
审稿时长
3.4 months
期刊介绍: Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.
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