“…- Donor profiling – The following studies aim at providing additional information from a fingermark, other than the ridge pattern: a new biometric identification tool built on an amino acid-based chemical assay [ 184 ]; donor-related information (i.e., gender, ethnicity, and donor age) obtained from secretion residue lipid profiling (technique: DESI-MSI) [ 185 ]; impact of gender and ethnicity on the lipid composition of residues present on an individual’s fingertips (technique: HPLC-ACPI-MS) [ 186 ]; donor gender determination using an amino acid-based chemical assay [ 187 ] or by specifically targeting the chromosomes X and Y contained in nucleated cells (technique: fluorescent in situ hybridization) [ 188 ]; donor characteristics and behavioural information (e.g., gender, ethnicity, diet, occupational activities, use of hand sanitizers) gained from bacterial profiling [ 189 ]; impact of donors and secretion types (i.e., eccrine, sebum-rich, and natural) on secretion residue composition (technique: MALDI-MSI-based metabolomics approach combined with chemometrics tools) [ 190 ].
- Evolution of secretion residue with time – Surface adhesion monitoring and topography variation (technique: PeakForce QNM AFM) [ 191 ]; molecular composition variation (e.g., carotenoids, squalene, unsaturated fatty acids and proteins – technique: Raman spectroscopy) [ 192 ]; migration imaging of endogenous fatty acids contained in sebum-rich fingermarks (technique: hyperspectral SRS) [ 193 ]; topological modifications (e.g., decrease of ridge height from 200 nm to 100 nm over three days – technique: AFM) [ 194 ]; thermal degradation of sebum-rich fingermarks (technique: FTIR microspectroscopy) [ 195 ]; intermolecular interactions between lipids (technique: FTIR microspectroscopy) [ 196 ], physical modifications of fingermarks left on metallic substrates (technique: EIS) [ 197 ], secretion residue composition variation (technique: SALDI-MS combined with MCF) [ 198 ] – caution: the last approach requires the dusting of nano-sized MCF (See section 3.2.6 for details).
- Age determination – Flatbed scanner combined with feature extraction was proposed to distinguish eccrine-rich and sebum-rich secretion residues as well as to estimate their age (i.e., 2-h-old, half-a-day-old and one-day-old) [ 199 ].
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