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The reliable identification of blood, as well as the determination of its origin (human or animal) is of great importance in a forensic investigation. Whilst presumptive tests are rapid and deployed in situ, their very nature requires confirmatory tests to be performed remotely. However, only serological tests can determine blood provenance. The present study improves on a previously devised Matrix Assisted Laser Desorption Ionisation Mass Spectrometry (MALDI MS)-proteomics based method for the reliable detection of blood by enabling the determination of blood provenance. The overall protocol was developed to be more specific than presumptive tests and faster/easier than the gold standard liquid chromatography (LC) MS/MS analysis. This is considered a pre-validation study that has investigated stains and fingermarks made in blood, other biofluids and substances that can elicit a false-positive response to colorimetric or presumptive tests, in a blind fashion. Stains and marks were either untreated or enhanced with a range of presumptive tests. Human and animal blood were correctly discriminated from other biofluids and non-biofluid related matrices; animal species determination was also possible within the system investigated. The procedure is compatible with the prior application of presumptive tests. The refined strategy resulting from iterative improvements through a trial and error study of 56 samples was applied to a final set of 13 blind samples. This final study yielded 12/13 correct identifications with the 13th sample being correctly identified as animal blood but with no species attribution. This body of work will contribute towards the validation of MALDI MS based methods and deployment in violent crimes involving bloodshed.

The determination of the type of deposition mechanism of blood within fingermarks at the scene of violent crimes is of great importance for the reconstruction of the bloodshed dynamics. However, to date, evaluation still relies on the subjective visual examination of experts. Practitioners encounter three types of scenarios in which blood may be found in fingermarks and they refer to the following three deposition mechanisms: (i) blood marks, originating from a bloodied fingertip; (ii) marks in blood, originating from a clean fingertip contacting a blood contaminated surface; (iii) coincidental deposition mechanisms, originating from a clean fingertip contacting a clean surface, leaving a latent fingermark, and subsequent contamination with blood. The authors hypothesised that, due to differences in distribution of blood in the furrows and on the ridges, the height of blood depositions on the ridges and furrows (and their relative proportions), will differ significantly across the three depositions mechanisms. A second hypothesis was made that the differences would be significant and consistent enough to exploit their measurement as a quantitative and objective way to differentiate the deposition mechanisms. In recent years, infinite focus microscopy (IFM) has been developed, allowing for the computational generation of a 3D image of the topology of a sample via acquisition of images on multiple focal planes. On these bases, it was finally hypothesised that the application of this technique would allow the distinction of deposition mechanisms (i) to (iii). A set of preliminary experiments were designed to test whether IFM was "fit for purpose" and, subsequently, to test if any of the three deposition mechanisms scenarios could be differentiated. Though IFM enabled the analysis of tape lifted samples with some success, for samples produced and analysed directly on the surface of deposition, the results show that the measurements from any scenario will be highly dependent on the original surface of deposition (both in terms of its nature and of the variable exposure to environment); as crime scenes exhibit a wide range of possible relevant surfaces of deposition, the technique showed to not have the desired wide appeal for inclusion into a standardised set of protocols within a routine crime scene workflow., (Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.)