Critical aspects of Raman spectroscopy as ...
Document type :
Article dans une revue scientifique: Article original
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Title :
Critical aspects of Raman spectroscopy as a tool for postmortem interval estimation.
Author(s) :
Falgayrac, Guillaume [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Vitale, Raffaele [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Delannoy, Yann [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Behal, Helene [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Penel, Guillaume [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Colard, Thomas [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Vitale, Raffaele [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Delannoy, Yann [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Behal, Helene [Auteur]
Evaluation des technologies de santé et des pratiques médicales - ULR 2694 [METRICS]
Penel, Guillaume [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 [LASIRE]
Colard, Thomas [Auteur]
Marrow Adiposity & Bone Lab - Adiposité Médullaire et Os - ULR 4490 [MABLab]
Journal title :
Talanta Open
Abbreviated title :
Talanta
Volume number :
249
Pages :
123589
Publication date :
2022-06-15
ISSN :
1873-3573
English keyword(s) :
Raman spectroscopy
Chemometrics
Forensics
Bones
ANOVA-Simultaneous component analysis
Burial
Chemometrics
Forensics
Bones
ANOVA-Simultaneous component analysis
Burial
HAL domain(s) :
Sciences du Vivant [q-bio]
English abstract : [en]
The estimation of the postmortem interval (PMI) from skeletal remains represents a challenging task in forensic science. PMI is often influenced by extrinsic factors (humidity, dryness, scavengers, etc.) and intrinsic ...
Show more >The estimation of the postmortem interval (PMI) from skeletal remains represents a challenging task in forensic science. PMI is often influenced by extrinsic factors (humidity, dryness, scavengers, etc.) and intrinsic factors (age, sex, pathology, way of life, medical treatments, etc.). Raman spectroscopy combined with multivariate data analysis represents a promising tool for forensic anthropologists. Despite all the advantages of the technique, Raman spectra of skeletal remains are influenced by these extrinsic and intrinsic factors, which impairs precision and reproducibility. Both parameters have to reach a high level of confidence when such spectroscopy is used as a way to predict PMI. As a consequence, advanced multivariate data analysis is necessary to quantify the effect of all factors to improve the estimation of the PMI. The objective of this work is to evaluate the effect of intrinsic and extrinsic factors on the Raman spectra of skeletal remains. We designed a protocol close to a real-world scenario. We used ANOVA-simultaneous component analysis (ASCA) to unmix and quantify the effect of 1 intrinsic (source body) and 1 extrinsic (burial time) factors on the Raman spectra. In our model, the burial time was found to generate the highest variability after the source body. ASCA showed that the variability due to the burial time has 2 mixed contributions. Seasonal variations are the first contribution. The second contribution is attributed to diagenesis. A decrease in the mineral bands and an increase in the organic bands are observed. The source body was also found to contribute to the variability in Raman spectra. ASCA showed that the source body induces variability related to the composition of bones. This quantification cannot be assessed by basic chemometrics methods such as PCA. The results of this study highlighted the need to use an advanced chemometric data analysis tool (like ASCA) combined with Raman spectroscopy to estimate the postmortem interval.Show less >
Show more >The estimation of the postmortem interval (PMI) from skeletal remains represents a challenging task in forensic science. PMI is often influenced by extrinsic factors (humidity, dryness, scavengers, etc.) and intrinsic factors (age, sex, pathology, way of life, medical treatments, etc.). Raman spectroscopy combined with multivariate data analysis represents a promising tool for forensic anthropologists. Despite all the advantages of the technique, Raman spectra of skeletal remains are influenced by these extrinsic and intrinsic factors, which impairs precision and reproducibility. Both parameters have to reach a high level of confidence when such spectroscopy is used as a way to predict PMI. As a consequence, advanced multivariate data analysis is necessary to quantify the effect of all factors to improve the estimation of the PMI. The objective of this work is to evaluate the effect of intrinsic and extrinsic factors on the Raman spectra of skeletal remains. We designed a protocol close to a real-world scenario. We used ANOVA-simultaneous component analysis (ASCA) to unmix and quantify the effect of 1 intrinsic (source body) and 1 extrinsic (burial time) factors on the Raman spectra. In our model, the burial time was found to generate the highest variability after the source body. ASCA showed that the variability due to the burial time has 2 mixed contributions. Seasonal variations are the first contribution. The second contribution is attributed to diagenesis. A decrease in the mineral bands and an increase in the organic bands are observed. The source body was also found to contribute to the variability in Raman spectra. ASCA showed that the source body induces variability related to the composition of bones. This quantification cannot be assessed by basic chemometrics methods such as PCA. The results of this study highlighted the need to use an advanced chemometric data analysis tool (like ASCA) combined with Raman spectroscopy to estimate the postmortem interval.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
CHU Lille
CHU Lille
Collections :
Submission date :
2023-11-15T03:55:46Z
2024-01-10T15:37:20Z
2024-02-27T12:16:22Z
2024-01-10T15:37:20Z
2024-02-27T12:16:22Z