Uncovering the Counterfeit: A study of whiskey authenticity through volatile organic compound fingerprinting, aroma and color sensory analysis.

This study presents a method employing gas chromatography coupled with mass spectrometry and headspace solid-phase microextraction (HS-SPME-GC-MS), supplemented with chemometrics (Soft independent modelling of class analogies - SIMCA), to analyze volatile organic compound (VOCs) profiles in suspect whiskey samples. Furthermore, a sensory analysis of aroma and color was conducted with a panel of 52 non-trained volunteers to evaluate their ability to discriminate and preference for counterfeit whiskeys. The HS-SPME-GC-MS method successfully distinguished 41 seized samples from authentic beverages. Interestingly, sensory analysis revealed that panelists could differentiate between counterfeit and authentic samples with a reference standard but did not consistently show a preference for aroma. In some cases, there was even a preference for the color of counterfeit whiskeys. The findings suggest that sensorial tests alone may not effectively distinguish counterfeit from authentic whiskeys, especially for non-expert consumers, highlighting the need for analytical instrumentation methods in fraud detection.

Can a spontaneous smile invalidate facial identification by photo-anthropometry?

PURPOSE: Using images in the facial image comparison process poses a challenge for forensic experts due to limitations such as the presence of facial expressions. The aims of this study were to analyze how morphometric changes in the face during a spontaneous smile influence the facial image comparison process and to evaluate the reproducibility of measurements obtained by digital stereophotogrammetry in these situations. MATERIALS AND METHODS: Three examiners used digital stereophotogrammetry to obtain 3-dimensional images of the faces of 10 female participants (aged between 23 and 45 years). Photographs of the participants' faces were captured with their faces at rest (group 1) and with a spontaneous smile (group 2), resulting in a total of 60 3-dimensional images. The digital stereophotogrammetry device obtained the images with a 3.5-ms capture time, which prevented undesirable movements of the participants. Linear measurements between facial landmarks were made, in units of millimeters, and the data were subjected to multivariate and univariate statistical analyses using Pirouette® version 4.5 (InfoMetrix Inc., Woodinville, WA, USA) and Microsoft Excel® (Microsoft Corp., Redmond, WA, USA), respectively. RESULTS: The measurements that most strongly influenced the separation of the groups were related to the labial/buccal region. In general, the data showed low standard deviations, which differed by less than 10% from the measured mean values, demonstrating that the digital stereophotogrammetry technique was reproducible. CONCLUSION: The impact of spontaneous smiles on the facial image comparison process should be considered, and digital stereophotogrammetry provided good reproducibility.

The effects of solubility of silver nanoparticles, accumulation, and toxicity to the aquatic plant Lemna minor.

The use of silver nanoparticles (AgNPs) in commercial products has increased due to their antibacterial properties and their impacts on the environment must be investigated. This scenario has motivated the conduction of this study, which relates different factors that affect the toxicity of AgNPs to the aquatic plant Lemna minor such as size, accumulation, concentration, and dissolution of AgNPs. To this end, synthesized AgNPs measuring 30, 85, and 110 nm were added into the culture medium to observe toxicity for 30 days. The mapping by SEM showed that the smallest AgNPs can translocate from roots to leaves due to its mobility and internalization. As predicted by the Ostwald equation, the solubility for 30-nm AgNPs increased almost 3 times at the end of 30 days, while for 85 and 110 nm size nanoparticles, after 7 days, the solubility decreased due to "Ostwald ripening" process. Plant mortality was assessed and, after 1 month, the size of 30 nm was the most toxic with negative growth in all studied concentrations, with 60% mortality in the worst case. The concentration of 50 µg mL-1 was toxic in all sizes with negative growth in the period. Therefore, the investigation of AgNPs' toxicity needs to consider a different factor to better understand their effects on aquatic plants and the environment.

In Silico Infrared Characterization of Synthetic Cannabinoids by Quantum Chemistry and Chemometrics.

The concept of forensic sciences as mere trace analysis has been modified by the idea of forensic intelligence, which entails applying data to make decisions within the investigative process. Many countries are engaged in combating drug trafficking and drug use because they are related to public health and safety issues. Prohibiting the consumption of traditional drugs has led new psychoactive substances (NPSs) to emerge. NPSs consist of compounds that resemble the initially banned substance and which aim to mimic the traditional drug recreational effects while circumventing drug legislation. For example, synthetic cannabinoids are sprayed on herbal products to reproduce the cannabis recreational effects. According to the United Nations Office on Drugs and Crime (UNODC), the toxic effects of synthetic cannabis types are unknown, and harm and fatalities associated with the use of these drugs have been reported. Information on the characterization related to these species is lacking. The rate at which NPSs appear poses a significant challenge because employing conventional methods to understand the characteristics of these compounds may require time and be costly. This work uses in silico practices as an alternative to understand how NPSs related to cannabis behave. We apply quantum chemistry methods to evaluate several synthetic cannabinoids recognized in forensic samples. More specifically, we generate infrared spectra that can be employed as a benchmark for NPSs. We apply a multivariate classification to evaluate the results. We conclude that in silico methods are an alternative that provide information about the spectra of undetected substances. This information can help to identify new drugs, to increase knowledge about them, and to feed information procedures.

In silico toxicity as a tool for harm reduction: A study of new psychoactive amphetamines and cathinones in the context of criminal science.

The emergence of new psychoactive substances (NPS) has raised many issues in the context of law enforcement and public drug policies. In this scenario, interdisciplinary studies are crucial to the decision-making process in the field of criminal science. Unfortunately, information about how NPS affect people's health is lacking even though knowledge about the toxic potential of these substances is essential: the more information about these drugs, the greater the possibility of avoiding damage within the scope of a harm reduction policy. Traditional analytical methods may be inaccessible in the field of forensic science because they are relatively expensive and time-consuming. In this sense, less costly and faster in silico methodologies can be useful strategies. In this work, we submitted computer-calculated toxicity values of various amphetamines and cathinones to an unsupervised multivariate analysis, namely Principal Component Analysis (PCA), and to the supervised techniques Soft Independent Modeling of Class Analogy and Partial Least Square-Discriminant Analysis (SIMCA and PLS-DA) to evaluate how these two NPS groups behave. We studied how theoretical and experimental values are correlated by PLS regression. Although experimental data was available for a small amount of molecules, correlation values reproduced literature values. The in silico method efficiently provided information about the drugs. On the basis of our findings, the technical information presented here can be used in decision-making regarding harm reduction policies and help to fulfill the objectives of criminal science.

Ketamine induces anxiolytic effects in adult zebrafish: A multivariate statistics approach.

Ketamine inappropriate use has been associated with serious consequences for human health. Anesthetic properties of ketamine are well-known, but its side effects are poorly described, including the effects on anxiety. In this context, animal models are a safe way to conduct this neurobehavioral research and zebrafish (Danio rerio) is an interesting model which has several advantages. The validation and interpretation of results of behavioral assays requires a suitable statistical approach, and the use of multivariate statistical methods has been little explored, especially in zebrafish behavioral models. Here, we investigated the anxiolytic-induced effects of ketamine in adult zebrafish, using Light-Dark Test and proposing the Multivariate Statistics methods (PCA, HCA and SIMCA) to analyze the results. In addition, we compared the processing of data to the one carried out by analysis of variance (ANOVA) ketamine produced significant concentration of exposure-dependent anxiolytic effects, increasing time in white area and number of crossings and decreasing latency to first access to white area. Average entry duration behavior resulted in a slight decrease from control to treatment groups, with an observed concentration-dependent increase among the exposed groups. PCA results indicated that two principal components represent 88.74% of all the system information. HCA and PCA results showed a higher similarity among control and treatment groups exposed to lower concentrations of ketamine and among treatment groups exposed to concentrations of 40 and 60 mg L(-1). In SIMCA results, interclasses distances were concentration of exposure-dependent increased and misclassifications and interclasses residues results also support these findings. These findings confirm the anxiolytic potential of ketamine and zebrafish sensibility to this drug. In summary, our study confirms that zebrafish and multivariate statistics data validation are an appropriate and viable behavioral model for the study of psychoactive substances, providing a detailed and reliable analysis.

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences.

Conformational analysis: a new approach by means of chemometrics.

In conformational analysis, the systematic search method completely maps the space but suffers from the combinatorial explosion problem because the number of conformations increases exponentially with the number of free rotation angles. This study introduces a new methodology of conformational analysis that controls the combinatorial explosion. It is based on a dimensional reduction of the system through the use of principal component analysis. The results are exactly the same as those obtained for the complete search but, in this case, the number of conformations increases only quadratically with the number of free rotation angles. The method is applied to a series of three drugs: omeprazole, pantoprazole, lansoprazole-benzimidazoles that suppress gastric-acid secretion by means of H+, K+-ATPase enzyme inhibition.