Latent fingermarks are invisible to the naked eye and normally require the application of a chemical developer followed by an optical imaging step in order to visualize the ridge detail. If the finger deposition is poor, or the fingermark is aged, it can sometimes be difficult to produce an image of sufficient quality for identification. In this work, we show for the first time how mass spectrometry imaging (in this case time-of-flight secondary ion mass spectrometry, ToF-SIMS) can be used to enhance the quality of partially recovered fingermarks. We show three examples of how chemical imaging can be used to obtain enhanced images of fingermarks deposited on aluminium foil, glass and the handle of a hand grenade compared with conventional development techniques.

Fingermarks are trace evidence of great forensic importance, and their omnipresence makes them pivotal in crime investigation. Police and law enforcement authorities have exploited fingermarks primarily for personal identification, but crucial knowledge on when fingermarks were deposited is often lacking, thereby hindering crime reconstruction. Biomolecular constituents of fingermark residue, such as amino acids, lipids and proteins, may provide excellent means for fingermark age determination, however robust methodologies or detailed knowledge on molecular mechanisms in time are currently not available. Here, we address fingermark age assessment by: (i) drafting a first protein map of fingermark residue, (ii) differential studies of fresh and aged fingermarks and (iii), to mimic real-world scenarios, estimating the effects of donor contact with bodily fluids on the identification of potential age biomarkers. Using a high-resolution mass spectrometry-based proteomics approach, we drafted a characteristic fingermark proteome, of which five proteins were identified as promising candidates for fingermark age estimation. This study additionally demonstrates successful identification of both endogenous and contaminant proteins from donors that have been in contact with various bodily fluids. In summary, we introduce state-of-the-art proteomics as a sensitive tool to monitor fingermark aging on the protein level with sufficient selectivity to differentiate potential age markers from body fluid contaminants.

Fingermarks are highly relevant in criminal investigations for individualization purposes. In some cases, the question in court changes from 'Who is the source of the fingermarks?' to 'How did the fingermark end up on the surface?'. In this paper, we explore the evaluation of fingermarks given activity level propositions by using Bayesian networks. The variables that provide information on activity level questions for fingermarks are identified and their current state of knowledge with regards to fingermarks is discussed. We identified the variables transfer, persistency, recovery, background fingermarks, location of the fingermarks, direction of the fingermarks, the area of friction ridge skin that left the mark and pressure distortions as variables that may provide information on how a fingermark ended up on a surface. Using three case examples, we show how Bayesian networks can be used for the evaluation of fingermarks given activity level propositions.