Table of Contents

Cover

Related Titles

Title Page

List of Contributors

Preface

Chapter 1: Forensic Science – Chemistry, Physics, Biology, and Engineering – Introduction

References

Chapter 2: Forensic Applications of Vibrational Spectroscopy¥

2.1 Introduction
2.2 Trace Evidence
2.3 Ink Analysis
2.4 Forensic Biology and Anthropology
2.5 Gunshot Residue
2.6 Controlled Substances
2.7 Counterterrorism and Homeland Security
2.8 Emerging Technologies
2.9 Conclusions
Acknowledgments
References

Chapter 3: Applications of Internal Reflection Spectroscopy in Forensic Analysis

3.1 Introduction
3.2 Principles and Theory
3.3 Accessories for ATR
3.4 Forensic Applications of ATR
3.5 Conclusion
References

Chapter 4: Applications of Mass Spectrometry in Forensic Science: A Brief Introduction

4.1 Introduction
4.2 Mass Spectrometry
4.3 Applications of MS in Forensic Science
4.4 Conclusions
Acknowledgments
References

Chapter 5: An Introduction to Forensic Electrochemistry

5.1 Introduction
5.2 Electrochemical Methods
5.3 Voltammetric Methods
5.4 Electrochemical Methods in Forensic Science
5.5 Outlook for Forensic Electrochemistry
References

Chapter 6: Electrochemical Detection of Gunshot Residue for Forensic Analysis

6.1 Overview of Gunshot Residue Detection
6.2 Electrochemical Detection of Inorganic GSR
6.3 Electrochemical Detection of Organic GSR
6.4 Next Steps in GSR Analysis: Chemometric Data Treatment and Complementary Orthogonal Methods
6.5 Future Prospects for Electroanalytical Detection of GSR
References

Chapter 7: From Optical to Hyperspectral Imaging Techniques in Forensic Sciences

7.1 Added Value of Imaging Techniques in Forensic Sciences
7.2 Optical Examination in Forensic Sciences: A Step Before Hyperspectral Imaging
7.3 Hyperspectral Imaging: A Flourishing Technique in Forensic Sciences
7.4 Conclusions and Future Prospects of Hyperspectral Imaging in Forensic Sciences
References

Chapter 8: Biochemical Analysis of Biomarkers for Forensic Applications

8.1 Introduction
8.2 Biocatalytic Analysis of Biomarkers for Forensic Identification of Ethnicity Between Caucasian and African American
8.3 Biocatalytic Analysis of Biomarkers for Forensic Identification of Sex
8.4 Biocatalytic Assay to Determine Age of Blood Sample
8.5 Conclusions
Acknowledgment
References

Chapter 9: Processing Skeletal Samples for Forensic DNA Analysis

9.1 Introduction
9.2 Bone Evidence in Forensic Investigations
9.3 The Sources of DNA from Skeletal Remains
9.4 Postmortem Taphonomic Effects of Skeletal Remains
9.5 Contamination of Challenged Bone Specimens
9.6 Sample Preparation and Processing of Bone Evidence for Forensic DNA Analysis
References

Chapter 10: DNA Damage and Repair in Forensic Science

10.1 Mechanisms of DNA Damage
10.2 DNA Damage in Forensic Samples
10.3 DNA Repair Mechanisms
10.4 DNA Repair in Forensic Science
References

Chapter 11: Biosensors in Forensic Analysis

11.1 Introduction
11.2 The Use of Biosensors in Forensic Toxicological Analysis
11.4 Conclusions and Future Perspectives
Acknowledgments
References

Chapter 12: Recent Advances in Bloodstain Pattern Analysis

12.1 Introduction
References

Chapter 13: Detection of Cocaine on Paper Currency

13.1 Cocaine
13.2 Cocaine on Banknotes as Forensic Evidence
13.3 Methods of Analysis
Acknowledgments
References

Chapter 14: The Forensic Analysis of Glass Evidence: Past, Present, and Future

14.1 Glass as Forensic Evidence
14.2 A Brief History of Forensic Glass Analysis
14.3 Current Methods of Forensic Glass Analysis
14.4 Future Directions of Forensic Glass Analysis
14.5 Conclusions
Acknowledgment
References

Chapter 15: Forensic Examination of Trace Evidence

15.1 What Is Trace Evidence?
15.2 Major Types of Trace Evidence
15.3 Limitations and Significance of Trace Evidence
References

Chapter 16: Fingerprint Spoofing and Liveness Detection

16.1 Introduction
16.2 Fingerprint Spoofing
16.3 Liveness Detection
16.4 Summary
References

Chapter 17: Engineering as a Forensic Science

17.1 Introduction
17.2 Accident Reconstruction
17.3 Biomechanics of Injuries
17.4 Products Liability
17.5 Conclusion
References
Further Reading

Chapter 18: Unmanned Systems Technology Use by Law Enforcement

18.1 Evolution and Anatomy of Unmanned Systems
18.2 Law Enforcement Applications
18.3 Legal Issues
18.4 Unmanned Systems Deployment
References

Chapter 19: Forensic Science – Conclusions and Perspectives

Index

End User License Agreement

List of Illustrations

Chapter 1: Forensic Science – Chemistry, Physics, Biology, and Engineering – Introduction

Figure 1.1 Application of vibrational spectroscopy for forensic analysis.
Figure 1.2 Forensic electrochemistry – the electroanalytical sensing of gunshot residues.
Figure 1.3 Schematic delineating voltammetry of microparticles on a wearable Forensic Finger. (a) The Forensic Finger shows the three electrode surfaces screen-printed onto a flexible nitrile finger cot (bottom left inset), as well as a solid, conductive ionogel immobilized on a similar substrate (top right inset). (b) “Swipe” method of sampling to collect the target powder directly onto the electrode. (c) Completion of the electrochemical cell by joining the index finger with electrodes to the thumb coated with the solid ionogel electrolyte.

Chapter 2: Forensic Applications of Vibrational Spectroscopy¥

Figure 2.1 Influence of the shaking time on the forensic analysis of Raman spectra of spray paints. The Raman spectra of an acrylic red spray paint, containing the pigment Naphthol red, after 0–5 min of shaking are shown. The peak intensities decrease over time. The inset shows the maximum counts calculated for the peak at 1350 cm⁻¹ for the 15 replicates of each condition plotted using boxplots. The time point of 1 min shows a higher pigment concentration, as indicated by the highest boxplot values
Figure 2.2 Determining the best excitation wavelength for Raman spectroscopy for the forensic analysis of black and color inkjet-printed documents. Comparison of Raman spectra obtained for yellow Canon and Hewlett-Packard sample A (HP A) with 785 nm (red dotted line) and 458 nm (solid blue line) excitation wavelengths. Differences between the two spectra from the same ink are explained by a resonance effect.
Figure 2.3 Discrimination of human and animal blood traces via Raman spectroscopy. (a) Comparison of the preprocessed and averaged Raman spectra from all human (blue trace, n = 10) spectra and all animal (red trace, n = 100) spectra. (b) Cross-validated prediction scores for human class using the binary PLS-DA model. Red line represents the default classification threshold.
Figure 2.4 Brain tissue from rats analyzed by FTIR spectroscopy to estimate the time since death. The spectra shown were acquired from brain tissue 0–144 h after death. Peak intensities at several frequencies were used to create calibration curves and estimate the postmortem interval with 93–97% accuracy.
Figure 2.5 ATR-FTIR imaging for detection of microscopic GSR. (a) Visual image of the mapped tape substrate area. (b–d) ATR images of mapped area: each pixel represents one raw ATR-FTIR spectrum. The pixels are colored by intensities of transmitted light at (b) 1415 cm⁻¹ (chemical marker for IGSR), (c) 1646 cm⁻¹ (a chemical marker for OGSR), and (d) 1728 cm⁻¹ (chemical marker for tape substrate). (e) Color scale determining the intensities of detected chemical signal. Blue colored areas indicate strong absorption (low %T) by the analyte, at that specific frequency, while red colored areas indicate little to no absorption (high %T) by the analyte, at that specific frequency. (f) FTIR spectra of organic GSR, inorganic GSR, cotton fiber, and tape, showing the unique peaks used during mapping to identify samples.
Figure 2.6 Quantifying cocaine in binary mixtures with adulterants. Raman spectra collected from binary mixtures of cocaine with (a) sodium carbonate, (b) caffeine, (c) benzocaine, and (d) lidocaine, each prepared in several concentrations. Quantitative analysis of spectral data resulted in calibration curves that could be used to estimate the concentration of cocaine.
Figure 2.7 Discrimination of 14 explosive compounds using Raman spectroscopy and principal component analysis. Key below Figure shows color coding of the explosives. (a) Three-dimensional scatter plot of 14 different explosives scored on the first 3 components showing separation. (b) Closer view of the three-dimensional feature space showing the separation of 10 of the explosives.

Chapter 4: Applications of Mass Spectrometry in Forensic Science: A Brief Introduction

Figure 4.1 Mass spectrometer schematic (MALDI: Matrix Assisted Laser Desorption Ionization; ESI: Electrospray Ionization; TOF: time-of-flight).
Figure 4.2 (a) MALDI-TOF mass spectrometer principle. An ion source, a mass analyzer, and a detector are present on the instrument. At the detector, the mass spectrum is detected/recorded. The mass analyzer is TOF-type and can be used in the linear or reflective mode. (b) ESI-MS of peptides. An ESI-MS spectrometer. In ESI-MS, the sample is a liquid under high temperature and high electric current. The sample dehydrates and becomes protonated for positive ionization.
Figure 4.3 LC-MS/MS experiment of a peptide mixture. In each LC-MS/MS experiment, with elution of peptides from the HPLC gradually, the mass spectrometer analyzes the corresponding ions via MS survey (recorded in an MS spectrum). Ions with highest intensity (typically 1–8 ions; 2 ions in this example) are selected for MS/MS fragmentation, fragmented, and then recorded as MS/MS #1 and MS/MS #2.

Chapter 5: An Introduction to Forensic Electrochemistry

Figure 5.1 Typical screen-printed setup (a) that allows a route to point-of-care electrochemistry, which is a development of a typical laboratory-based setup in (b). WE, solid working electrode; CE, counter electrode; and RE, reference electrode.
Figure 5.2 Potential–time profile (a) for a voltammetric experiment and a current–potential plot (b), better known as a voltammogram.
Figure 5.3 Schematic diagram of the general process that occurs when testing for atropine in a Coca-Cola™ sample.
Figure 5.4 Cyclic square-wave voltammogram at the bare GCE for a mixture of trace metals and explosives constituents of GSR: 3 ppm Pb, 10 ppm Sb, 50 ppm NG, and 10 ppm DNT. Square wave parameters: Estep, 4 mV; amplitude, 25 mV; frequency, 8 Hz; and teq, 5 s; (reduction) Estart, 1.15 V; and Estop, −0.95 V; (oxidation) Estart, accum, −0.95 V; Estop, 1.15 V; and taccum, 120 s. Electrolyte, acetate buffer (pH = 4.5).
Figure 5.5 Illustrative concept of the voltammetric determination of Rohypnol™.
Figure 5.6 Electrolysis-etched fingerprint on a bullet.
Figure 5.7 Schematic diagram of the hybridization process. (a) Magnetic beads harness DNA fragments; (b) DNA hybridization occurs with the target DNA; (c) a second hybridization occurs, that tags quantum dots to the DNA; and (d) dissolution of the quantum dots and electrochemical detection take place via adsorptive stripping voltammetry.

Chapter 6: Electrochemical Detection of Gunshot Residue for Forensic Analysis

Figure 6.1 Voltammograms of a sample, blank, and standard: (1) gunshot residue showing Pb, Cu, and Sb; (2) blank electrolyte; and (3) blank electrolyte spiked with 30 ng Sb.
Figure 6.2 Adaptation for batch-injection analysis (BIA) with a commercial HMDE stand and cell for ASV GSR analysis. (A) Detailed photograph of the outlet section of the J-adaptor, fitted to the glass capillary. (B) Schematic of the electrochemical cell showing (a) mercury reservoir and valve, (b) micropipettor, (c) mercury electrode capillary, (d) hanging mercury drop, (e) J-adaptor outlet, (f) sealing pipettor tip, and (g) modified 100 µl pipette tip.
Figure 6.3 Multicommuted flow system for determining Pb(II) in GSR. S, sample; SS, standard solution of Pb(II); CS, carrier solution (10 mg l⁻¹ of Bi(III) in 0.1 mol l⁻¹; acetate buffer solution, pH 4.5); D, detector; Sy, 10.0-ml syringe; W, waste; V1, V2, V3, three-way solenoid valves; and R1, R2, reaction coils (60 cm).
Figure 6.4 AbrSV of GSR samples from four subjects for three different conditions: in the laboratory, prior to any contact with GSR, named C1: first control; at the shooting lanes where others were discharging firearms, but without handling or discharging a firearm, named C2: second control; after discharging several rounds from the weapon (10 rounds for a Glock 40 and 8 rounds for a Sig Sauer 45) – F: Firing.
Figure 6.5 Use of “Forensic Fingers” for on-site analysis. Schematic delineates voltammetry of microparticles particles at a wearable Forensic Finger. (a) The Forensic Finger exhibiting the three-electrode surface screen-printed onto a flexible nitrile finger cot (bottom left inset), as well as a solid, conductive ionogel immobilized upon a similar substrate (top right inset). (b) “Swipe” method of sampling to collect the target powder directly onto the electrode. (c) Completion of the electrochemical cell by joining the index finger with electrodes to the thumb coated with the solid ionogel electrolyte.
Figure 6.6 Summary of cyclic voltammetric data for selected explosive compounds. Supporting electrolyte: 0.06 M monochloroacetic acid, 0.44 M sodium acetate, and 0.001 M EDTA, in 15% (v/v) l-propanol, pH 3.5. Scan rate, 300 mV s⁻¹. Concentrations of explosives were between 100 and 200 µg ml⁻¹.
Figure 6.7 Cyclic voltammograms of (a) diphenylamine and (b) centralite I, in acetonitrile. Sweep rate 100 mV s⁻¹, concentration 0.2 mM.
Figure 6.8 Simultaneous organic/inorganic electroanalysis and cyclic square-wave voltammogram for a mixture of trace metals and explosive constituents of GSR: 2 ppm Zn, 2 ppm Pb, 20 ppm Sb, and 200 ppm DPA. Square-wave parameters: E_step, 4 mV; amplitude, 25 mV; frequency, 25 Hz; and t_accum, 120 s; (reduction) E_start,accum 1.2 V and E_stop,−1.3 V; (oxidation) E_start,accum,−1.3 V; E_stop, 1.2 V; and t_accum, 120 s. Electrolyte, acetate buffer (pH = 4.5).
Figure 6.9 PCA score plots of current signals obtained with a gold microelectrode in a solution containing gunshot residues extracted from a 0.380 pistol with full jacketed (a) and normal ammunition (b), and from a 0.38 revolver with normal (c) and semi-jacketed ammunition (d).
Figure 6.10 (a) Example of the different cyclic square-wave stripping voltammetric signals obtained with “swiping” samples at a bare SPCE electrode. Score plot of the functions obtained after LDA analysis of the GSR samples according to (b) exposure level or (c) three-class response mode. Samples in (b) correspond to: N – no contact, S – secondary exposure, P – presence at discharge, L – load, F – fire, and W – wash. Samples in (c) correspond to free (N), witness (S and P), and involved (L, F, and W). See Section 2.3 for the electrochemical conditions.
Figure 6.11 Integration of the three orthogonal detection modes of SWV, SEM, and EDX. Comparison of (a) voltammetric, (b) SEM, and (c) EDX responses for samples from (A) a subject who has loaded a firearm and (B) a subject who has had no contact with GSR at SEM tape-modified electrode.

Chapter 7: From Optical to Hyperspectral Imaging Techniques in Forensic Sciences

Figure 7.1 Photographic image (a) and infrared image (b) of (A) a pair of black trousers stained with blood, (B) cloth samples with a name written on the inside of the collar, (C) burned document, (D) gunshot residues on a cloth sample, and (E) tire marks on a blue cloth sample.
Figure 7.2 Use of (a) normal light conditions and (b) luminescence conditions for the visual examination of three different gel pen inks.
Figure 7.3 Schematic representation of a hyperspectral system detailing the spectral camera setup.
Figure 7.4 Schematic representation of a three-dimensional hyperspectral data cube including the relationship between spectral and spatial dimensions and the resulting information obtained from a single pixel, a pixel line, and a single plane for one random wavelength.
Figure 7.5 Schematic representation of the three configurations for acquiring a hyperspectral image.
Figure 7.6 Steps to analyze a hyperspectral image.
Figure 7.7 Hyperspectral data unfolding process.
Figure 7.8 White-light photographs of all samples on the 12 different fabrics, and the results of the different hyperspectral imaging methods: band images, ratio images, PCA images, and SIMPLISMA images.
Figure 7.9 Spectra observed of a specific point identified as an explosive residue in the handprint NIR false color hyperspectral images: (a) ammonium nitrate residues; (b) dynamite residues; (c) single-base smokeless gunpowder residues; (d) double-base smokeless gunpowder residues; and (e) black powder residues.
Figure 7.10 Raman images of crossings using gel–liquid blue pen inks at different times separating the application of each ink line, where the horizontal line was applied first (green). The images were obtained using the MCR approach.

Chapter 8: Biochemical Analysis of Biomarkers for Forensic Applications

Figure 8.1 (a) Biocatalytic cascade for the two-enzyme CK/LDH assay. (b) Biocatalytic cascade for the one-enzyme CK assay. The following abbreviations are used in the scheme: CK (creatine kinase), PK (pyruvate kinase), LDH (lactate dehydrogenase), Crt (creatine), Crt-P (creatine phosphate), ATP (adenosine 5′-triphosphate), ADP (adenosine 5′-diphosphate), NAD⁺ (β-nicotinamide adenine dinucleotide), NADH (β-nicotinamide adenine dinucleotide reduced), PEP (phospho(enol)pyruvic acid), Pyr (pyruvate), Lac (lactate), HK (hexokinase), G6PDH (glucose-6-phosphate dehydrogenase), NADP⁺ (β-nicotinamide adenine dinucleotide phosphate), NADPH (β-nicotinamide adenine dinucleotide phosphate reduced), Glc (glucose), Glc6P (glucose-6-phosphate), and 6-PGluc (6-phosphate gluconic acid).
Figure 8.2 Absorbance (λ = 340 nm) corresponding to the consumption of NADH upon operation of the CK/LDH assay. The bottom (red) and top (blue) traces correspond to the application of samples with CK and LDH concentrations mimicking AA and CA groups, respectively. Bold solid curves show the median responses for both groups. Inset: box and whisker plot of Abs in AA and CA groups. The median value for each group is noted with the horizontal line in a box, the boxes represent the range of values from 25% to 7%, the ends of the whiskers represent the 5% and 95% of values, and the dots are the mean, maximum, and minimum values.
Figure 8.3 Absorbance (λ = 340 nm) corresponding to the production of NADPH upon operation of the CK assay. The bottom (blue) and top (red) traces correspond to the application of samples with CK concentrations mimicking CA and AA groups, respectively. Bold solid curves show the median responses for both groups. Inset: box and whisker plot of Abs in AA and CA groups. The median value for each group is noted with the horizontal line in a box, the boxes represent the range of values from 25% to 75%, the ends of the whiskers represent the 5% and 95% of values, and the dots are the mean, maximum, and minimum values.
Figure 8.4 Density histograms of the output signal (absorbance) obtained for (a) CA group and (b) AA group using the CK/LDH assay (see the biocatalytic cascade shown in Figure 8.1a). The histograms were derived from the experimental data shown in Figure 8.2. Superimposed is the kernel density curve.
Figure 8.5 Density histograms of the output signal (absorbance) obtained for (a) CA group and (b) AA group using the CK assay (see the biocatalytic cascade shown in Figure 8.1b). The histograms were derived from the experimental data shown in Figure 8.3. Superimposed is the kernel density curve.
Figure 8.6 Absorbance changes (ΔAbs) obtained for the two-enzyme CK/LDH assay applied to the redissolved serum samples mimicking CA (circles b) and AA (squares a) groups after their drying and aging for different time intervals. Zero time interval corresponds to the analysis of the freshly prepared samples without drying. The data represent mean values of ΔAbs normalized to the maximum ΔAbs value characteristic of the fresh samples mimicking the AA group, and the error bars represent relative standard errors of ΔAbs measurements from five samples. Note that the samples were composed of mixed sera from different donors with added CK and LDH to mimic their concentration difference in the CA and AA groups.
Figure 8.7 Receiver operating characteristic (ROC) empirical (curve a) and smoothed (curve b) for the two-enzyme CK/LDH assay. Random choice is denoted by the diagonal line (line c). The highlighted point on the plot (curve a) corresponds to the best sensitivity–specificity pair (the best tradeoff between them) giving the most accurate cut-off point for discrimination between CA and AA serum samples. Note that samples were sera from individual donors with known ethnic origin.
Figure 8.8 Time-dependent absorbance changes (λ = 340 nm) obtained upon running the enzyme assays. (a) CK assay with the “female” CK concentration. (b) CK assay with the “male” CK concentration. (c) CK/ALT assay with the “female” CK and ALT concentrations. (d) CK/ALT assay with the “male” CK and ALT concentrations. Inset: Bar chart showing the absorbance changing after 10 min of the assay performance: (a) CK/ALT assay and (b) CK assay. “M” and “F” bars correspond to the “male” and “female” enzyme concentrations, respectively. The enzymatic assays were performed in a 50 mM glycylglycine buffer solution, pH 7.95.
Figure 8.9 (a) Biocatalytic cascade used for the CK/ALT assay where CK and ALT were applied jointly as two biomarkers. (b) Extension of the CK/ALT assay for the color production visible by a naked eye. The following abbreviations are used in the scheme: CK (creatine kinase), PK (pyruvate kinase), LDH (lactate dehydrogenase), ALT (alanine transaminase), Crt (creatine), Crt-P (creatine phosphate), ATP (adenosine triphosphate), ADP (adenosine diphosphate), NAD⁺ (ß-nicotinamide adenine dinucleotide), NADH (ß-nicotinamide adenine dinucleotide reduced), PEP (phospho(enol)pyruvic acid), Pyr (pyruvate), Lac (lactate), KTG (α-ketoglutaric acid), NBT (nitroblue tetrazolium), PMS (phenazine methosulfate).
Figure 8.10 Time-dependent absorbance changes (λ = 340 nm) obtained upon running the CK/ALT assay in human serum (50% v/v) solutions with (F) the “female” CK and ALT concentrations and (M) the “male” CK and ALT concentrations. Inset: The bar chart showing the absorbance changing after 10 min of the assay performance. “M” and “F” bars correspond to the “male” and “female” enzyme concentrations, respectively.
Figure 8.11 Bar chart showing absorbance changes (λ = 340 nm) obtained upon performing CK/ALT assay for 10 min on serum samples spiked with “male” (a) and “female” (b) CK and ALT concentrations and then after their drying, aging for different time intervals, and redissolving for the enzyme assay. Note that “0 h” experiment corresponds to the analysis of freshly prepared samples without drying/aging.
Figure 8.12 Time-dependent absorbance changes (λ = 580 nm) obtained upon performing chemical reaction of NBT and the residual NADH following the CK/ALT assay performed for 10 min for the serum (50% v/v) solutions spiked with “male” (M) and “female” (F) concentrations of CK and ALT. Inset: Photos of cuvettes with colored solutions obtained for the “male” and “female” samples after CK/ALT assay extended with the NBT reaction (note that the samples in this experiment were prepared in buffer solutions). Blue color in the left cuvette corresponds to the “female” sample.
Figure 8.13 Change in absorbance (λ = 340 nm) corresponding to the consumption of NADH upon operation of the CK-biocatalyzed reaction. The traces correspond to samples (n = 3) that mimic bloodstains, incubated at 40 °C from 0 to 120 h. Inset: Bar chart representing the change in absorbance at λ = 340 nm, after 30 min of assay completion.
Figure 8.14 Change in absorbance (λ = 340 nm) corresponding to the consumption of NADH upon operation of the ALT-biocatalyzed reaction. The traces correspond to samples (n = 3) that mimic bloodstains, incubated at 40 °C from 0 to 120 h. Inset: Bar chart representing the change in absorbance at λ = 340 nm, after 30 min of assay completion.
Figure 8.15 Change in absorbance (λ = 340 nm) corresponding to the consumption of NADH upon operation of the CK/ALT-biocatalyzed reactions operating in parallel. The traces correspond to samples (n = 3) that mimic bloodstains, incubated at 40 °C from 0 to 120 h. Inset: Bar chart representing the change in absorbance at λ = 340 nm, after 30 min of assay completion.
Figure 8.16 Absorbance change at λ = 340 nm, corresponding to the consumption of NADH after the analysis of the two different biocatalytic pathways (in the presence of CK or ALT) as well as the entire biocatalytic assay in the presence of both enzymes (CK and ALT). Time zero corresponds to the analysis of the freshly prepared samples without drying. The rest of the samples were resuspended in water after they underwent aging at 40 °C.
Figure 8.17 Absorbance change at λ = 340 nm, corresponding to the consumption of NADH after the analysis of the samples by the CK/ALT biocatalytic assay. Samples (n = 3) were resuspended after undergoing the aging process under different temperatures: 40, 25, and 18 °C, up to 120 h. Time zero corresponds to the freshly prepared samples without drying.

Chapter 9: Processing Skeletal Samples for Forensic DNA Analysis

Figure 9.1 Section of the FDNY (Fire Department of New York City) memorial wall. Memorial, at FDNY Engine Co. 10 in the Liberty Street of New York, to the Fallen Firefighters of 9/11, by Rambusch Studios.
Figure 9.2 Diagram of a long bone. A long bone, such as an arm and a leg bone, consists of an outer cylinder of cortical bone surrounding a marrow cavity. Each end of a long bone is called an epiphysis, which is composed largely of cancellous bone. Flat bones have variable structures; for example, the skull consists mainly of cortical bone, whereas the spine consists mainly of cancellous bone.
Figure 9.3 (a) Cross-sectional view of cortical bone. The functional unit of cortical bones is a cylindrical structure known as osteon (circled). Haversian canals are shown in the center of the osteon. (b) Detailed view of an osteon. Osteocytes (arrows) are shown within osteons.
Figure 9.4 A bone fragment. Cortical and cancellous bones are shown. In Volkmann's and Haversian canals, blood vessels can be found.
Figure 9.5 Human burial rib bone fragments.
Figure 9.6 Tools for cutting bone samples. Osteotomes (a), a mallet (a) and a rotary device (b; Dremel, Racine, WI).
Figure 9.7 Effect of trypsin treatment on STR (short tandem repeat) profiles. STR profiles were obtained with the AmpFℓSTR® MiniFiler™ amplification kit. Overall, the allele calls of the trypsin method were similar to those of the sanding method. The electropherograms of (a) a sanded and (b) a trypsin-treated sample. (Reproduced from Li [3], with permission of Taylor & Francis Group.)

Chapter 10: DNA Damage and Repair in Forensic Science

Figure 10.1 Primary structure of DNA that can be damaged in a number of ways.
Figure 10.2 UV spectrum.
Figure 10.3 UV photoproducts. (a) Structure of a CPD, formed by the saturation of the 5,6 double bonds of adjacent pyrimidines and the formation of a cyclobutyl ring. (b) (6–4) photoproduct formed between adjacent pyrimidines when the C4 hydroxyl or amino group of the 3′ base is transferred to the C6 position of the 5′ base, forming a C6–C4 ∅ bond.
Figure 10.4 8-Oxoguanine. This hallmark of oxidative damage is a miscoding lesion, pairing with adenine instead of cytosine.
Figure 10.5 STR profiles generated from bloodstains exposed to UVC. (a) A full nine-locus profile (Profiler, Applied Biosystems) could be amplified after exposure for up to 8 h (∼50 J cm⁻² min⁻¹) and (b) only a partial nine-locus profile could be amplified after 12 h UVC (∼75 J cm⁻² min⁻¹).
Figure 10.6 DNA in physiological stains: strand breaks. The decrease in molecular weight is proportional to the increase in strand breaks. (a) UVA-irradiated DNA on an alkaline agarose gel to visualize single strand breaks. (b) UVB irradiated DNA on an alkaline agarose gel. (c) UVA-irradiated DNA on a native agarose gel to visualize double strand breaks. (d) UVB-irradiated DNA on a native agarose gel. Lengths of UV irradiation relative to natural sunlight exposure in a Washington, DC, in July at noon are listed above each lane, and the sizes of the molecular weight marker λ HindIII are shown in (a).
Figure 10.7 DNA in physiological stains: environmental exposure. DNA was digested with lesion-specific endonucleases, resulting in single strand gaps at the sites of damaged bases. The decrease in molecular weight was proportional to the increase in damage. T4 pyrimidine dimer glycosylase (T4PDG) removes CPDs, and formamidopyrimidine dimer DNA-glycosylase (FPG) excises oxidative lesions. (a) Bloodstains were exposed to a subtropical (Florida, USA) climate in the summertime. There was no significant difference in the “plus enzyme” and “no enzyme” treated samples, indicating that UV photoproducts were not predominant lesions. Bloodstains exposed to a continental climate in the summertime (Nebraska, USA) showed the formation of (b) CPDs and (c) oxidative lesions after 3 days outdoors. (Reproduced from Hall et al. [36], with permission of Springer.)
Figure 10.8 Base excision repair pathway. A modified base is detected by DNA glycosylase as distortions in the helical structure. The base is removed, and subsequent endonuclease activity generates an AP site. The gap is filled in by a repair-proficient polymerase and the nick is sealed by a DNA ligase.
Figure 10.9 SSBR of UV-damaged DNA. DNA damaged with UVC light was incubated with components of the SSBR pathway. (a) Combined actions of endonuclease IV, Polymerase β, and DNA ligase resulted in a nine-locus DNA profile (PowerPlex 1.2). (b) Endonuclease and DNA ligase alone did not have a similar effect. (Reproduced from Hall and Ballantyne [35], with permission of Springer.)

Chapter 11: Biosensors in Forensic Analysis

Figure 11.1 Fundamentals of the bacterial reporter cell used for the electrochemical determination of arsenite. (a) Synthesis of the arsR repressor protein from the arsR gene under control of the ars promoter (Pars). (b) Binding of arsR to DNA. (c) Losing of arsR affinity for DNA binding sites in the presence of As(V) and increasing of the arsR and lacZ genes transcription, leading to β-Gal formation. (d) Diffusion of PAPG through the cell membrane and cleaving by β-Gal to form PAP detected electrochemically outside the cell.
Figure 11.2 Real image and schematic diagrams displaying the biodevice, the enzyme reactions, and the response to alcohol at the graphite–Teflon–AOx–HRP–ferrocene composite electrode.
Figure 11.3 (a) Aptasensor for cocaine determination, and (b) schematicoutline of the principle for cocaineelectrochemical aptasensor.
Figure 11.4 Configurations of SPR biosensors for the determination of testosterone: (a) Schematic of the SPR immunosensor assay binding process with nanogold label; (b) Scheme of SPR sensor setup with the PS – functionalized sensor chip.
Figure 11.5 Determination of E. coli O157:H7. (a) Capture onto MBs-pECAb followed by labeling with AuNPs/sECAb. (b) Detection of labeled E. coli O157:H7 through hydrogen evolution reaction at −1.0 V and chronoamperograms for 0 (top) to 10⁵ (bottom) cfu ml⁻¹. (c) Cyclic voltammograms in 1 M HCl for 0 (1) and 10⁵ (2) cfu ml⁻¹. (d) scanning electron microscopy (SEM) for heat-killed E. coli O157:H7 (A) and MBs-pECAb before (B) and after (C) incubation with 10⁵ cfu ml⁻¹ E. coli O157:H7 (bacteria pointed by white arrows).
Figure 11.6 Scheme of the protocol developed for the preparation of an electrochemical immunosensor for the determination of TNT. (1) Fabrication of an AET-SAM onto gold nanoparticles-modified GCE and covalent immobilization of PAMAM. (2) Covalent immobilization of TMB-OVA conjugate followed by sample loading and immobilization of anti-TNT antibody. (3) Immobilization of HRP-Ab.
Figure 11.7 Schematic diagram of the magnetosensing assay for DNA sequence-specific detection and quantification of V. cholera. (a) aPCR mix. (b) Hybridization reagent. (c) Tagging reagent. Steps: (1) Preparation of DNA sample followed by aPCR amplification of target ssDNA. (2) Hybridization. (3) Tagging of hybridization events. (4) DPASV detection.

Chapter 12: Recent Advances in Bloodstain Pattern Analysis

Figure 12.1 Viscosity measurements at different PCVs (15–75%) determined at two temperatures: room temperature (25 °C) and body temperature (37 °C).
Figure 12.2 Close-up of equine blood magnified by 2.5 × 0.07 using a Leica microscope, showing particle build-up on the edge of the blood drop.
Figure 12.3 Images depicting the drying of human blood at room temperature, acquired using a 2.5 × 0.07 magnification Leica microscope. (a) 15% PCV and (b) 75% PCV.
Figure 12.4 Bloodstain displaying visible spines on the periphery of the stain.
Figure 12.5 Typical boiling curve highlighting the boiling regimes for water. (a) Natural convection (around room temperature). (b) Nucleation boiling regime. (c) Transition boiling regime. (d) Film boiling regime.
Figure 12.6 Typical boiling curve highlighting the boiling regimes for blood. (a) Natural convection (around room temperature). (b) Nucleation boiling regime. (c) Transition boiling regime. (d) Film boiling regime.

Chapter 13: Detection of Cocaine on Paper Currency

Figure 13.1 Chemical structure of cocaine.
Figure 13.2 SEM image of cocaine crystals in the interstices between the fibers of a banknote.
Figure 13.3 Schematic representation of the cEIA for the detection of cocaine in extracts taken from banknotes.
Figure 13.4 Schematic representation of the in-gel immunodetection method for localization of cocaine on banknotes.

Chapter 14: The Forensic Analysis of Glass Evidence: Past, Present, and Future

Figure 14.1 Photograph of Wallner lines on the fractured edge of glass.
Figure 14.2 Photomicrograph of hackle marks on the fractured edge of glass.
Figure 14.3 (a–c) First three pages of the brochure for the original GRIM instrument from 1982.
Figure 14.4 Modern GRIM instrument.
Figure 14.5 Schematic of a LA-ICP-MS instrument.
Figure 14.6 Schematic of a LIBS instrument.
Figure 14.7 LIBS spectrum of glass.
Figure 14.8 LIBS spectra of three different types of glass (NIST SRM 621 Soda Lime, Pyrex, and NIST 1411 Borosilicate) showing the ability of LIBS for glass classification.
Figure 14.9 Schematic of a tandem-LA-LIBS instrument.
Figure 14.10 Transmission curves for double-pane architectural windows from Cardinal Corp. The top curve is the spectra for clear glass (2pClear) and shows greater transmission of UV and IR light as compared to original low-E glass (2pE180) and newer low-E glasses with increased spectral selectivity (2pE272, 2pE366, and 2pE340).
Figure 14.11 SiO₄ tetrahedral structures in crystalline and glassy silicates [144, 145]. The white circles represent silicon, and the black circles represent oxygen. A fourth oxygen would be located above or below each of the silicon atoms in the three-dimensional structure.
Figure 14.12 Photomicrographs of a glass sample in Nujol at 360× magnification using the diamond ATR objective, varied by increasing the contact pressure. (a) After initial contact. (b) After some contact. (c) After being crushed but not scattered. The length of the black bar measures 50 µm. (d) Mid-IR spectra of the glass shown in photomicrographs (a)–(c). As the contact pressure is increased, the glass peaks increase and the presence of the oil becomes insignificant.

Chapter 15: Forensic Examination of Trace Evidence

Figure 15.1 Linkages that can be established by the use of trace evidence.
Figure 15.2 Basic structure of a hair.
Figure 15.3 Human head hairs from the same individual collected at the same time. The variation in hairs is clearly seen.
Figure 15.4 Typical layers found in an OEM (original equipment manufacturer) paint system.
Figure 15.5 Automotive paint chip with 13 layers, showing internal clear layers, which appear as white in the photograph.
Figure 15.6 Physical match between several piece of automotive window glass.
Figure 15.7 Mud on a pickaxe used to dig a shallow grave. This mud was subsequently shown to have come from the bottom of the grave.
Figure 15.8 Generic layers of duct tape, showing all possible layers, although in reality not all may be present or detectable.
Figure 15.9 Bubbles from the manufacturing process located in duct tape adhesive.
Figure 15.10 Automotive headlight filaments showing (a) undamaged filament and (b) a distorted filament indicative of hot shock.
Figure 15.11 Physical match of a piece of automotive paint seized from the scene of a fatal accident to the body of the suspect vehicle.

Chapter 16: Fingerprint Spoofing and Liveness Detection

Figure 16.1 (a) Fingerprint mold made of dental material. (b) Finger fakes made of silicon. (c) Fingerprint mold made of etched PCB and the resultant fake.
Figure 16.2 (a) Fingerprint fake. (b) Fake overlaid on real finger. (c) Resulting imaged fake fingerprint.

List of Tables

Chapter 2: Forensic Applications of Vibrational Spectroscopy¥

Table 2.1 Most relevant ASTM and SWGMAT standards for various types of trace evidence [22–34]

Chapter 4: Applications of Mass Spectrometry in Forensic Science: A Brief Introduction

Table 4.1 Recent applications of mass spectroscopy in forensic science

Chapter 6: Electrochemical Detection of Gunshot Residue for Forensic Analysis

Table 6.1 Inorganic and organic compounds that may contribute to gunshot residue
Table 6.2 Summary of experimental conditions and target GSR analytes in the literature reviewed

Chapter 11: Biosensors in Forensic Analysis

Table 11.1 Biosensors employed for the determination of arsenic and cyanide
Table 11.2 Biosensors employed for the determination of illicit drugs
Table 11.3 Biosensors employed for the determination of toxins
Table 11.4 Biosensors employed for the determination of microorganisms
Table 11.5 Biosensors employed for the determination of chemical weapons
Table 11.6 Biosensors employed for the determination of explosives
Table 11.7 Biosensors employed for the determination of biological weapons

Chapter 12: Recent Advances in Bloodstain Pattern Analysis

Table 12.1 Reference Table depicting dry weight constants W_c^PCV derived for a range of PCVs

Chapter 13: Detection of Cocaine on Paper Currency

Table 13.1 Summary of the quantities of cocaine detected on banknotes of different currencies, and the analytical methods applied in each study
Table 13.2 Summary of recently reported analytical methods for the detection of cocaine on banknotes

Chapter 17: Engineering as a Forensic Science

Table 17.1 AIS severity code
Table 17.2 Safety hierarchy

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