Simultaneous quantification of opiates, cocaine and cannabinoids in hair

The present paper describes a sensitive method developed in our laboratory for the simultaneous analysis of opiates (morphine, codeine and monoacetylmorphine), cocainics (cocaine and benzoylecgonine) and cannabinoids (Δ⁹-tetrahydrocannabinol and 11-nor-Δ⁹-tetrahydrocannabinol-9-carboxylic acid) in hair samples. After decontaminating the sample with dichloromethane, two consecutive hydrolyses were performed in order to achieve the best conditions for extracting the three kinds of drugs from the protein matrix. First the opiate and cocainic compounds were extracted by means of a soft acidic hydrolysis with 0.1 N HCl at 50 °C overnight and organic solvent extraction at pH 9.2. The cannabinoids need a stronger basic hydrolysis with 11.8 N KOH for 10 min at laboratory temperature. After adding maleic acid, the cannabinoids were extracted with an organic solvent. The derivatization was carried out with heptafluorobutyric anhydride and hexafluoropropanol. Calibration curves were linear between 0.5–100 ng/mg of hair. Recovery and reproducibility were assured. The quantification limits ranged between 0.04–0.26 ng/mg of hair. Seventy hair samples from known drug abusers were cut into 1-cm segments and analyzed by this method. The ranges of measured concentrations (ng/mg) were 0.31–89 for cocaine, 0.1–5.76 for benzoylecgonine, 0.34–45.79 for morphine, 0.45–39.59 for codeine, 0.09–48.18 for monoacetylmorphine, 0.06–7.63 for THC and 0.06–3.87 for THC---COOH. The results of sectional analyses agreed with the self reported drug histories. The usefulness of this method is in assessing earlier drug consumption, and also at the same time obtaining a chronological profile of the consumption of these three types of drugs.     

Multivariate Classification of Original and Fake Perfumes by Ion Analysis and Ethanol Content

The increased marketing of fake perfumes has encouraged us to investigate how to identify such products by their chemical characteristics and multivariate analysis. The aim of this study was to present an alternative approach to distinguish original from fake perfumes by means of the investigation of sodium, potassium, chloride ions, and ethanol contents by chemometric tools. For this, 50 perfumes were used (25 original and 25 counterfeit) for the analysis of ions (ion chromatography) and ethanol (gas chromatography). The results demonstrated that the fake perfume had low levels of ethanol and high levels of chloride compared to the original product. The data were treated by chemometric tools such as principal component analysis and linear discriminant analysis. This study proved that the analysis of ethanol is an effective method of distinguishing original from the fake products, and it may potentially be used to assist legal authorities in such cases.     

Ferocious Times: The IRA,the RIC,and Britain's Failure in 1919–1921

The 1916 Rising was, in military terms, a shambolic failure. Despite the fact that Britain was locked in a gruelling struggle with Germany, the Rising was still utterly crushed within a week. How then, in the aftermath of victory against Germany, did Britain fail to win the subsequent struggle with the Irish Republican Army (IRA) between 1919 and 1921? This article assesses some of the key factors that played out in the conflict, drawing particular attention to the IRA's focus on the Royal Irish Constabulary and the consequences of this, and then later, how distorted perceptions of the proximity of success ultimately undermined British commitment. One of the most remarkable features of the conflict was the widespread belief among many on the British side (and more than a few in the Republican camp) that the IRA was on the verge of total defeat when the truce was declared in 1921. The IRA had suffered heavy casualties and were running low on weapons and ammunition. Yet, somehow the movement prevailed. This article aims to shed light on how and why that happened.     

Deep learning for sex determination: Analyzing over 200,000 panoramic radiographs

The objective of this study is to assess the performance of an innovative AI-powered tool for sex determination using panoramic radiographs (PR) and to explore factors affecting the performance of the convolutional neural network (CNN). The study involved 207,946 panoramic dental X-rays and their corresponding reports from 15 clinical centers in São Paulo, Brazil. The PRs were acquired with four different devices, and 58% of the patients were female. Data preprocessing included anonymizing the exams, extracting pertinent information from the reports, such as sex, age, type of dentition, and number of missing teeth, and organizing the data into a PostgreSQL database. Two neural network architectures, a standard CNN and a ResNet, were utilized for sex classification, with both undergoing hyperparameter tuning and cross-validation to ensure optimal performance. The CNN model achieved 95.02% accuracy in sex estimation, with image resolution being a significant influencing factor. The ResNet model attained over 86% accuracy in subjects older than 6 years and over 96% in those over 16 years. The algorithm performed better on female images, and the area under the curve (AUC) exceeded 96% for most age groups, except the youngest. Accuracy values were also assessed for different dentition types (deciduous, mixed, and permanent) and missing teeth. This study demonstrates the effectiveness of an AI-driven tool for sex determination using PR and emphasizes the role of image resolution, age, and sex in determining the algorithm's performance.     

Genetic diversity and admixture data on 11 STRs (F13B, TPOX, CSF1PO, F13A01, D7S820, LPL, TH01, vWA, D13S317, FESFPS, and D16S539) in a sample of Rio de Janeiro European-descendants population, Brazil

Allelic frequencies, forensic parameters and admixture values for eleven STR loci (F13B, TPOX, CSF1PO, F13A01, D7S820, LPL, TH01, vWA, D13S317, FESFPS, and D16S539) were determined in a sample of unrelated individuals, European descendants from Rio de Janeiro area, Brazil.     

Comparative Analysis of Insect Succession Data from Victoria (Australia) Using Summary Statistics versus Preceding Mean Ambient Temperature Models

Minimum postmortem interval (mPMI) can be estimated with preceding mean ambient temperature models that predict carrion taxon pre‐appearance interval. But accuracy has not been compared with using summary statistics (mean ± SD of taxon arrival/departure day, range, 95% CI). This study collected succession data from ten experimental and five control (infrequently sampled) pig carcasses over two summers (n = 2 experimental, n = 1 control per placement date). Linear and exponential preceding mean ambient temperature models for appearance and departure times were constructed for 17 taxa/developmental stages. There was minimal difference in linear or exponential model success, although arrival models were more often significant: 65% of linear arrival (r² = 0.09–0.79) and exponential arrival models (r² = 0.05–81.0) were significant, and 35% of linear departure (r² = 0.0–0.71) and exponential departure models (r² = 0.0–0.72) were significant. Performance of models and summary statistics for estimating mPMI was compared in two forensic cases. Only summary statistics produced accurate mPMI estimates.     

Long Bone (Humerus,Femur, Tibia) Measuring Procedure in Cadavers

In this work, we present a measuring methodology for long bones of the limbs (humerus, femur, and tibia) of human corpses. Measurements of cadaveric height and long bone lengths were conducted on 72 corpses (20 females and 52 males) from the School of Medicine at the National Autonomous University of Mexico. Additionally, these measurements were compared with those taken from dry bones of a subsample of individuals. Our results show marginal differences (TEM% = 0.59) between cadaveric and dry bone measurements, resulting from different osteometric technical procedures. This note outlines the measuring methodology, which will be subsequently used to create regression formulas for stature estimation.     

The association between psychopathic personality traits and health-related outcomes

Purpose

Psychopathy and psychopathic personality traits (PPT) have been linked to a long list of negative life outcomes. To date, however, few studies have provided a systematic analysis of whether psychopathic personality traits contribute to increased health burden. The current study was designed to address this gap in the literature.

Method

This study analyzed data from the National Longitudinal Study of Adolescent Health and employed a measure of PPT derived from the five-factor model of personality. Analyses were conducted using OLS, logistic, and Poisson regression techniques.

Results

The results revealed that relatively higher scores on psychopathic personality traits were associated with a slight increase in a wide range of negative health outcomes. These significant associations were detected for both males and females.

Conclusions

We speak to the importance of these findings for the potential to reduce health burden among psychopaths and those who score relatively high on measures of psychopathic personality traits.