Identification of gunshot residue: a critical review.

A review of the scientific papers published on inorganic gunshot residue (GSR) analysis permits to study how the particle analysis has shown its capability in detection and identification of gunshot residue. The scanning electron microscope can be the most powerful tool for forensic scientists to determine the proximity to a discharging firearm and/or the contact with a surface exposed to GSR. Particle analysis can identify individual gunshot residue particles through both morphological and elemental characteristics. When particles are detected on the collected sample, the analytical results can be interpreted following rules of a formal general interpretative system, to determine whether they come from the explosion of a primer or from other possible sources. The particles on the sample are compared with an abstract idea of “unique” GSR particle produced by the sole source of the explosion of a primer. “Uniqueness” is not the only problem related to GSR detection and identification for a forensic scientist. With “not-unique” particles interpretation of results is extremely important. The evidential strength of “not-unique” particles can increase with a more fruitful interpretative framework based on Bayes rule. For the assessment of the value of a GSR in linking a suspect and a crime, it is important to compare two hypothesis: the first can be that of the evidence if the suspect has been shooting in a specific situation, the second that of the evidence if the suspect was not involved in this shooting. This case specific or case-by-case approach is closer to what the court is interested in. The authors consider that a “case-by-case” approach should be followed whenever possible. Research of models and data such as those developed in other trace evidence material (fibres, glass, etc.) using a Bayesian approach is suggested in the interpretation of GSR

Quantitative profile-profile relationship (QPPR) modelling: a novel machine learning approach to predict and associate chemical characteristics of unspent ammunition from gunshot residue (GSR)

Evidence association in forensic cases involving gunshot residue (GSR) remains very challenging. Herein, a new in silico approach, called quantitative profile-profile relationship (QPPR) modelling, is reported. This is based on the application of modern machine learning techniques to predict the pre-discharge chemical profiles of selected ammunition components from those of the respective post-discharge GSR. The obtained profiles can then be compared with one another and/or with other measured profiles to make evidential links during forensic investigations. In particular, the approach was optimised and successfully tested for the prediction of GC-MS profiles of smokeless powders (SLPs) from organic GSR in spent cases, for nine ammunition types. Results showed a high degree of similarity between predicted and experimentally measured profiles, after adequate combination and evaluation of fourteen machine learning techniques (median correlation of 0.982). Areas under the curve (AUCs) of 0.976 and 0.824 were observed after receiver operating characteristic (ROC) analysis of the results obtained in the comparisons between predicted-predicted and predicted-measured profiles, respectively, in the specific case that the ammunition types of interest were excluded from the training dataset (i.e., extrapolation). Furthermore, AUCs of 0.962 and 0.894 were observed in interpolation mode. These values were close to those of the comparison of the measured SLP profiles between themselves (AUC = 0.998), demonstrating excellent potential to correctly associate evidence in a number of different forensic scenarios. This work represents the first time that a quantitative approach has successfully been applied to associate a GSR to a specific ammunition

Accidental death involving professional fireworks

An interesting case of accidental death involving the explosion of professional fireworks in an apartment is described. The examination of the scene permitted to study several effects of the explosion on walls, ceiling, furniture and especially on a balcony where the victim was found. The external examination of the victim showed extensive thermal injuries, degloving injuries and extensive shrapnel wounds. The autopsy examination showed subarachnoid haemorrhage localized to the cerebellum, haemorrhage in the soft tissues of the neck and chest and fracture of one clavicle. Almost the entire surface of lungs showed blunt injuries and the liver showed tearing of parenchyma and multiple cavities. Histological analysis were carried out showing thickening of alveolar septae, enlargement of alveolar spaces and alveolar ruptures in lung sections while numerous, round, empty spaces were detected in the parenchyma of the liver. The examination of the scene and of the fragments found showed that at least eight pyrotechnical charges exploded on the balcony, in close proximity of the threshold with the living room of the apartment. According to the chemical findings, the charges were typical for professional use and were filled with a mixture of potassium perchlorate and aluminium. A conservative calculation results in more than 1.5 kg total mass of pyrotechnic composition exploding very close to the victim

Multiclass analysis of illicit drugs in plasma and oral fluids by LC-MS/MS

An analytical procedure for the simultaneous determination in human plasma and oral fluids of several illicit drugs belonging to different chemical and toxicological classes is presented. Amphetamine, methamphetamine, morphine, 6-monoacetylmorphine, methylenedioxyamphetamine, methylenedioxyethylamphetamine, methylenedioxymethamphetamine, cocaine, benzoylecgonine, tetrahydrocannabinol, carboxytetrahydrocannabinol, ketamine, and phencyclidine have been quantified in real samples using a very rapid sample treatment, basically a protein precipitation. The quantitative analysis was performed by liquid chromatography-tandem mass spectrometry and has been fully validated. All the analytes were detected in positive ionization mode using a source, except carboxytetrahydrocannabinol, which was detected in negative ionization mode. The use of a diverter valve between the column and the mass spectrometer allows the preservation of the ion source performances for high-throughput analysis.[...

High-throughput screening for new psychoactive substances (NPS) in whole blood by DLLME extraction and UHPLC-MS/MS analysis

The increasing number of new psychoactive substances (NPS) present in the illicit market render their identification in biological fluids/tissues of great concern for clinical and forensic toxicology. Analytical methods able to detect the huge number of substances that can be used are sought, considering also that many NPS are not detected by the standard immunoassays generally used for routine drug screening. The aim of this work was to develop a method for the screening of different classes of NPS (a total of 78 analytes including cathinones, synthetic cannabinoids, phenethylamines, piperazines, ketamine and analogues, benzofurans, tryptamines) from blood samples. The simultaneous extraction of analytes was performed by Dispersive Liquid/Liquid Microextraction DLLME, a very rapid, cheap and efficient extraction technique that employs microliters amounts of organic solvents. Analyses were performed by a target Ultrahigh Performance Liquid Chromatography tandem Mass Spectrometry (UHPLC-MS/MS) method in multiple reaction monitoring (MRM). The method allowed the detection of the studied analytes with limits of detection (LODs) ranging from 0.2 to 2ng/mL. The proposed DLLME method can be used as an alternative to classical liquid/liquid or solid-phase extraction techniques due to its rapidity, necessity to use only microliters amounts of organic solvents, cheapness, and to its ability to extract simultaneously a huge number of analytes also from different chemical classes. The method was then applied to 60 authentic real samples from forensic cases, demonstrating its suitability for the screening of a wide number of NPS

Saliva and serum levetiracetam concentrations in patients with epilepsy

Although antiepileptic drug (AED) monitoring in saliva may have some clinical applicability, it has not yet come into routine use. The correlation between levetiracetam (LEV) saliva and serum concentrations also remains unclear. To confirm LEV saliva assay as a useful, noninvasive alternative to serum measurement, we investigated the possible correlation between saliva and serum LEV concentrations. Samples of saliva and blood were collected from 30 patients with epilepsy receiving chronic therapy with LEV as monotherapy or add-on therapy, and LEV concentrations were assayed in saliva and serum. Linear regression analyses showed a close correlation between saliva and serum LEV concentrations (r = 0.90; P < 0.001). LEV blood and saliva concentrations were linearly related to daily drug doses (r = 0.78 and 0.70; P < 0.01). When data were analyzed for subgroups (patients receiving LEV in monotherapy, as add-on therapy with enzyme-inducer AEDs, and as add-on therapy with noninducer or moderate-inducer AEDs), no significant difference was found between saliva and serum LEV concentrations among groups. These preliminary results indicate that LEV, like other AEDs, can be measured in saliva as an alternative to blood-based assays. Saliva LEV collection and assay is a valid noninvasive, more convenient alternative to serum measurement. © 2007 Lippincott Williams & Wilkins, Inc