Toward a novel framework for bloodstains dating by Raman spectroscopy: How to avoid sample photodamage and subsampling errors

Abstract

Answers to questions about the time of bloodstains formation are often essential to unravel the sequence of events behind criminal acts. Unfortunately, the relevance of preserved evidence to the committed offence usually cannot be verified, because forensic experts are still incapable of providing an accurate estimate of the bloodstains' age. An antidote to this impediment might be substituting the classical dating approach-founded on the application of calibration models-by the comparison problem addressed using likelihood ratio tests. The key aspect of this concept involves comparing the evidential data with results characterizing reference bloodstains, formed during the process of supervised ageing so as to reproduce the evidence. Since this comparison requires data that conveys information inherent to changes accompanying the process of blood decomposition, this study provided a Raman-based procedure, designated for probing into the chemistry of ageing bloodstains. To circumvent limitations experienced with single-point measurements-the risk of laser-induced degradation of hemoglobin and subsampling errors-the rotating mode of spectral acquisition was introduced. In order to verify the performance of this novel sampling method, obtained spectra were confronted with those acquired during conventional static measurements. The visual comparison was followed by analysis of data structure using regularized MANOVA, which boosted the variance between differently-aged samples while minimizing the variance observed for bloodstains deposited at the same time. Studies of relation between these variances demonstrated the superiority of novel procedure, as it provided Raman signatures that enabled a better distinction between differently-aged bloodstains.

Raman Spectroscopic Study of TiO2 Nanoparticles’ Effects on the Hemoglobin State in Individual Red Blood Cells

“…Additionally, using an excitation laser with 488 nm wavelength, we needed to consider the probability of laser effects directly on Hb [38], such as photodegradation of Hb (denaturation, hemichrome formation, and potential aggregation) in the process of Raman measurements. Some researchers suggest that the position of the ν 4 peak can indicate the iron ion transition to the ferric form [39], and this is considered as one of the markers of the Hb photodamage [40]. This effect is pronounced in the presence of both kinds of TiO 2 in comparison with control.…”

Analysis of the Ex-vivo transformation of Semen, Saliva and Urine as they dry out using ATR-FTIR spectroscopy and chemometric Approach

“…Both Principal Component Regression (PCR) Analysis and Partial Least Square Regression (PLSR) are strong chemometric tool for the estimation of TSD of body uids as reported in previous studies. 1,4,5,10,29 The calculated R 2 values for the calibration and prediction of both models are more than 0.9. While the root mean square error of cross validation (RMSECV) and prediction (RMSEP) values in both the models for all the three uids except diluted urine, showed low values ( 4.a and 4.b) respectively.…”

“…4 Despite the equal importance of semen, saliva, and urine as evidence in crime scene investigation, blood always received special attention in the research community. 3,4,9,29,30 All the three aforesaid uids including blood are consistently found in the broad range of homicides, suicide, rape, and other sexual assaults. 2,31,32 Although, it is not very frequent that an investigating team can reach the crime scene as early as the uid is still under drying process, but in several instances, investigators may come across a situation where the uid is still drying.…”

Analysis of the ex-vivo transformation of semen, saliva and urine as they dry out using ATR-FTIR spectroscopy and chemometric approach

“…The analytical technology gradually transformed into nondestructive from destructive methods 3 , 4 , 10 . A variety of techniques including Gas chromatography 11 , Liquid chromatography 12 – 14 , Oxygen electrode 3 , 15 , microRNA based assay 3 , 16 – 19 , Color transformation chart 20 , Electron paramagnetic resonance 21 – 23 , Reflectance spectroscopy in Ultraviolet, Visible and Infrared (IR) region 24 – 26 , smartphone imaging 27 , IR absorption 1 , 3 , 4 , 8 , 9 , 28 , 29 , Raman scattering 4 , 6 , 7 , 11 , 30 and fluorescence spectroscopy is explored around the world for the TSD estimation of blood (peripheral and menstrual) 31 and semen 8 . As an age prediction tool, most of these methods realistically depict promising results.…”