Time since last discharge of firearms and spent ammunition elements: state of the art and perspectives

The estimation of the time since last discharge of firearms or spent ammunition elements (e.g., casings) may provide crucial information in the investigation of a shooting incident and, eventually, the following trial. Herein, an exhaustive review of the methods described in the literature is reported, with the aim to evaluate their potential and limitations from a forensic perspective. This work, in particular, highlighted the fact that a number of investigations have been carried out in the field during the last century (with an especially high rate in the last 30 years), but the implementation of related procedures in forensic laboratories is still rare. The situation has been discussed and a series of propositions have been forwarded, in order to overcome challenges and facilitate the implementation of dating approaches in real casework

Plant Poisons in the Garden: A Human Risk Assessment

A study of the plants, and their associated poisons, in the Poison Garden at The Alnwick Garden was undertaken across a calendar year. By selecting 25 plants in the Poison Garden, we have been able to develop a single chromatographic method for the determination and quantification of 15 plant toxins by liquid chromatography mass spectrometry (LC-MS). Chromatographic separation was achieved on a C18 column (3.5 µm, 100 × 4.6 mm) with a gradient method using water +0.1 formic acid and methanol +0.1 formic acid. The developed method was validated for precision, linearity, limits of detection and quantification and extraction recoveries. The method showed good linearity with a R2 value of >0.995 for all 15 compounds with good precision of 10.7, 6.7 and 0.3 for the low, medium and high calibration points, respectively. The LC-MS method was used to analyse 25 plant species, as well as their respective parts (i.e., bulb, flower, fruit, leaf, pollen, seed, stem and root), to assess the human risk assessment to children (aged 1 to <2 years) in relation to the plant toxin and its respective LD50. The analysis found that the greatest potential health risks were due to the ingestion of Colchicum autumnale and Atropa belladonna. As a caution, all identified plants should be handled with care with additional precautionary steps to ensure nil contact by children because of the potential likelihood of hand-to-mouth ingestion

A study on contactless airborne transfer of textile fibres between different garments in small compact semi-enclosed spaces

Interpretation of fibre evidence at activity level requires extensive knowledge of all the possible transfer mechanisms that may explain the presence of fibres on a recipient surface of interest. Herein, we investigate a transfer method that has been largely understudied in previous literature: contactless transfer between garments through airborne travel. Volunteers were asked to wear UV-luminescent garments composed of different textile materials and situate themselves in a semi-enclosed space (elevator) for a pre-determined period of time with other participants, who wore non-luminescent recipient garments. The latter were then inspected for fibres using UV-luminescent photographic techniques. Results showed that contactless transfer between garments is possible. Indeed, a number of fibres were observed after most of the experiments. As many as 66 and 38 fibres were observed in the experiments involving cotton and polyester donor garments, compared to 2 and 1 fibres in those involving acrylic and wool donor garments, respectively. In this regard, the type of donor garment was found to be a significant factor. Multifactorial ANOVA supported these observations (p < 0.001) and further indicated a statistically significant influence of elevator door opening/closing (p < 0.001), people entering/exiting (p = 0.078) and the recipient garment (p = 0.030). Therefore, contactless transfer of fibres between garments can occur and can do so in (ostensibly) high numbers. This should be taken into consideration when interpreting fibre evidence at activity level and may have a major implication for the assignment of evidential values in some specific cases

Forensic profiling of smokeless powders (SLPs) by gas chromatography–mass spectrometry (GC-MS): a systematic investigation into injector conditions and their effect on the characterisation of samples

Smokeless powders (SLPs) are composed of a combination of thermolabile and non-thermolabile compounds. When analysed by GC-MS, injection conditions may therefore play a fundamental role on the characterisation of forensic samples. However, no systematic investigations have ever been carried out. This casts doubt on the optimal conditions that should be adopted in advanced profiling applications (e.g. class attribution and source association), especially when a traditional split/splitless (S/SL) injector is used. Herein, a study is reported that specifically focused on the evaluation of the liner type (L type) and inlet temperature (T inj). Results showed that both could affect the exhaustiveness and repeatability of the observed chemical profiles, with L type being particularly sensitive despite typically not being clarified in published works. Perhaps as expected, degradation effects were observed for the most thermolabile compounds (e.g. nitroglycerin) at conditions maximising the heat transfer rates (L type = packed and T inj ≥ 200 °C). However, these did not seem to be as influential as, perhaps, suggested in previous studies. Indeed, the harshest injection conditions in terms of heat transfer rate (L type = packed and T inj = 260 °C) were found to lead to better performances (including better overall %RSDs and LODs) compared to the mildest ones. This suggested that implementing conditions minimising heat-induced breakdowns during injection was not necessarily a good strategy for comparison purposes. The reported findings represent a concrete step forward in the field, providing a robust body of data for the development of the next generation of SLP profiling methods. Graphical abstract: (Figure presented.).</p

Comparison of four commercial solid phase micro-extraction (SPME) fibres for the headspace characterisation and profiling of gunshot exhausts in spent cartridge casings

Headspace solid phase micro-extraction (SPME) is a promising technique for the characterisation and profiling of gunshot exhausts in spent cartridge casings, especially for risk assessment and forensic purposes. To date, however, no comprehensive investigation has been carried out to objectively assess the kinds of compound released during a discharge that can be recovered by this approach, the selectivity of the main commercially available fibres, and their relative performances for the analysis of gunshot exhausts and the discrimination of different ammunition types. This study aimed to fill this gap. Gunshot exhausts in spent cartridge casings from four different ammunition types were analysed by GC-MS, after extraction with four different commercial fibres; 100 μm polydimethylsiloxane (PDMS), 85 μm polyacrylate (PA), 65 μm polydimethylsiloxane/divinylbenzene (DVB), and 85 μm carboxen/polydimethylsiloxane (CAR). Results showed that, overall, a total of 120 analytes could be observed across the cartridges, but the different tested fibres also displayed distinct performances, which were, to some extent, complementary for the characterisation of gunshot exhausts. DVB, in particular, recovered the most compounds simultaneously. On the other hand, the observed variability between measurements was also high, making it a poor candidate for (semi-)quantitative applications (e.g., estimation of time since discharge and/or source profiling). In this regard, PA demonstrated the highest potential for broad use and implementation in multi-purpose methods

From: Larry Roberts (enclosure)

Illegal trafficking of pharmaceutical products by criminal organisations is a global threat for public health. Drugs for erectile dysfunction such as phosphodiesterase type 5 inhibitors are the most commonly counterfeited medicines in Europe. The search of possible toxic chemical substances in seized products is needed to provide early warning for public health. Furthermore, the elemental profile of the seized products can be useful in criminal investigations. For the first time an ion beam analysis (IBA) procedure to characterise authentic Viagra® tablets and sildenafil-based illegal products is described. Moreover, results are compared with the ones obtained by instrumental neutron activation analysis (INAA) on authentic Viagra® tablets in two reactors. IBA results showed that a combination of particle-induced X-ray emission (PIXE) and secondary ion mass spectrometry using primary ions with energies in the range of several MeV (MeV-SIMS) is a powerful tool to characterise different products in a straightforward manner, allowing discrimination between legal and illegal products. INAA allowed accurate elemental quantification and also showed a great potential for the future implementation of an inter- laboratory classification system

Prevalence and characterisation of microfibres along the Kenyan and Tanzanian coast

Microplastic pollution is ubiquitous, with textiles being a major source of one of the dominant microplastic types—microfibres. Microfibres have been discovered in the aquatic environment and marine biota, demonstrating direct infiltration in the environment. However, the impact of non-plastic microfibres has been overlooked until recently despite their prevalence and the ecotoxicological risk posed by chemical dyes and finishes used during processing. During an expedition from Lamu to Zanzibar (East Africa), a citizen science strategy was employed to innovate, educate and influence microfibre pollution reform through the Flipflopi project, a circular economy effort to stop the use of single-use plastic. Simple sampling methods were developed to replace costly equipment, which local citizens could use to partake in the collection and sampling of surface water samples from the previously understudied Kenyan and Tanzanian coast. To maintain the reliability of samples and to minimise contamination, a forensic science strategy was embedded throughout the methodology of the study, collection and analysis of the samples. A total of 2,403 microfibres from 37 sites were recovered and fully characterised with 55% found to be of natural origin, 8% regenerated cellulosic and 37% synthetic microfibres. Natural microfibres were in higher abundance in 33 of the 37 sampled sites. Congruent with recent studies, these findings further support the need for greater understanding of the anthropogenic impact of natural microfibres

Prediction of bioconcentration factors in fish and invertebrates using machine learning

© 2018 The Authors The application of machine learning has recently gained interest from ecotoxicological fields for its ability to model and predict chemical and/or biological processes, such as the prediction of bioconcentration. However, comparison of different models and the prediction of bioconcentration in invertebrates has not been previously evaluated. A comparison of 24 linear and machine learning models is presented herein for the prediction of bioconcentration in fish and important factors that influenced accumulation identified. R2 and root mean square error (RMSE) for the test data (n = 110 cases) ranged from 0.23–0.73 and 0.34–1.20, respectively. Model performance was critically assessed with neural networks and tree-based learners showing the best performance. An optimised 4-layer multi-layer perceptron (14 descriptors) was selected for further testing. The model was applied for cross-species prediction of bioconcentration in a freshwater invertebrate, Gammarus pulex. The model for G. pulex showed good performance with R2 of 0.99 and 0.93 for the verification and test data, respectively. Important molecular descriptors determined to influence bioconcentration were molecular mass (MW), octanol-water distribution coefficient (logD), topological polar surface area (TPSA) and number of nitrogen atoms (nN) among others. Modelling of hazard criteria such as PBT, showed potential to replace the need for animal testing. However, the use of machine learning models in the regulatory context has been minimal to date and is critically discussed herein. The movement away from experimental estimations of accumulation to in silico modelling would enable rapid prioritisation of contaminants that may pose a risk to environmental health and the food chain.Biotechnology and Biological Sciences Research Council (BBSRC) CASE industrial scholarship scheme (Reference BB/K501177/1), iNVERTOX project (Reference BB/P005187/1) and AstraZeneca Global SHE research programme. This work was additionally supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001999), the UK Medical Research Council (FC001999), and the Wellcome Trust (FC001999)