@article{35c0e7588f624e169525991a86a04544,
title = "Investigating sex determination through MALDI MS analysis of peptides and proteins in natural fingermarks through comprehensive statistical modelling",
abstract = "In the last decade, Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS) has proven to be a valuable analytical tool in forensic research as it can detect and map molecular information of forensic relevance in trace evidence such as fingermarks and hair. The first published proof of concept demonstrating that it was possible to differentiate males and females from the peptide and protein content of their fingermarks was published in 2012. In that work, MALDI MS was used in Profiling mode (MALDI MSP) to quickly obtain spectral profiles of ungroomed marks. These were submitted to Partial Least Square Discriminant Analysis (PLS-DA) yielding sex discrimination with an accuracy between 67.5% and 74.4%, if harsh classification criteria were applied. Since then, this research has progressed to investigate the opportunity to increase the accuracy of prediction in natural marks (obtained with no preparation of the fingertip prior to deposition) either unenhanced or enhanced prior to matrix application and MALDI analysis. Extensive statistical modelling has been employed to determine the model with the highest sex predictive accuracy. Results show that in natural marks the presence of polymers (as external contaminants) in fingermarks affects the peptide/protein signals to various degrees and, only, by using one type of scoring system, a method has been identified to provide up to 86.1% predictive power in discriminating female from male marks.",
keywords = "Fingermark, Natural, MALDI MS, Sex, Machine learning, LASER-DESORPTION IONIZATION, MASS-SPECTROMETRY, LATENT FINGERMARKS, MOLECULES",
author = "Cameron Heaton and Bury, {Charles S.} and Ekta Patel and Robert Bradshaw and Florian Wulfert and Heeren, {Ron M.} and Laura Cole and Leeanna Marchant and Neil Denison and Richard McColm and Simona Francese",
note = "Funding Information: Data acquisition for Study 2 (172 natural marks) was carried out at the M4I Institute, Maastricht University, Maastricht, The Netherlands. This work was supported by (COST) Action CA16101 ?MULTI-modal Imaging of FOREnsic SciEnce Evidence - tools for Forensic Science? (MULTIFORESEE) supported by (COST) (European Cooperation in Science and Technology) via a Short-Term Scientific Mission (STSM). The overall work presented here has been supported by The Home Office Innovation Fund (funding Dr R, Bradshaw), BBSRC-GlaxoSmithKline PhD studentship (awarded to Dr E. Patel) and a VC PhD scholarship funded by DSTL and Sheffield Hallam University (awarded to Mr C. Heaton). Dr Benjamin Baluff is gratefully acknowledged for the training given to Mr Cameron Heaton. Miss Katie Kennedy is gratefully acknowledged for her assistance with the fingerprint collection. COST has provided funding for the first author to visit the MAaastricht laboratories. Funding Information: Data acquisition for Study 2 (172 natural marks) was carried out at the M4I Institute, Maastricht University, Maastricht, The Netherlands. This work was supported by (COST) Action CA16101 “MULTI-modal Imaging of FOREnsic SciEnce Evidence - tools for Forensic Science” (MULTIFORESEE) supported by (COST) (European Cooperation in Science and Technology) via a Short-Term Scientific Mission (STSM). The overall work presented here has been supported by The Home Office Innovation Fund (funding Dr R, Bradshaw), BBSRC - GlaxoSmithKline PhD studentship (awarded to Dr E. Patel) and a VC PhD scholarship funded by DSTL and Sheffield Hallam University (awarded to Mr C. Heaton). Dr Benjamin Baluff is gratefully acknowledged for the training given to Mr Cameron Heaton. Miss Katie Kennedy is gratefully acknowledged for her assistance with the fingerprint collection. COST has provided funding for the first author to visit the MAaastricht laboratories. Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",
year = "2020",
month = aug,
doi = "10.1016/j.forc.2020.100271",
language = "English",
volume = "20",
journal = "Forensic Chemistry",
issn = "2468-1709",
publisher = "Elsevier BV",
}