Identification and stability of synthetic cathinones in biological samples

Synthetic cathinones (“bath salts”) are a class of novel psychoactive substances abused for their psychostimulant and euphoric effects. However, these drugs have received international and national attention due to severe and life threatening adverse effects. In order to properly associate pharmacological, impairing, or toxic effects with synthetic cathinone use, toxicologists must be able to detect and reliably interpret results. The detection of these synthetic phenethylamines relies on validated analytical techniques. Quantitative assays determine the concentration of drug present in biological samples at the time of analysis, which may be significantly different from the concentration at the time of collection or time of death. Drug stability must be understood in order to determine the extent to which these changes influence analytical results. This research provides the forensic toxicology community with a comprehensive understanding of the stability of these compounds in biological matrices. A method for the detection of twenty-two synthetic cathinones, isolated from blood and urine using liquid chromatography quadrupole/time of flight mass spectrometry (LC-Q/TOF MS) was developed and validated. This method was used to assess synthetic cathinone stability in blood (pH 7) and urine (pH 4 and 8) stored at 32°C, 20°C, 4°C, and -20°C for six months. The selected synthetic cathinones were representative of the various structural analogs, including unsubstituted secondary amines (methcathinone, ethcathinone, buphedrone, and pentedrone); ring substituted secondary amines (3-FMC, 4-FMC, 4-MEC, 4-EMC, 3,4-DMMC, mephedrone, and methedrone); methylenedioxy-substituted secondary amines (methylone, ethylone, butylone, pentylone, eutylone); and tertiary amines (α-PVP, naphyrone, pyrovalerone, MPBP, MDPBP, and MDPV). The significance of analyte, storage temperature, storage time, concentration, and matrix pH were systematically assessed. Stability was influenced by structure, matrix pH, and storage temperature. Halogenated cathinones (3-FMC, 4-FMC) were the least stable and the tertiary cathinones bearing the methylenedioxy group (MDPBP, MDPV) were the most stable. The analysis of authentic urine samples from cathinone users supported these experimental findings. Matrix pH and cathinone structure had a more profound influence than prolonged storage. In addition to detecting synthetic cathinones from antemortem specimens to support experimental stability findings, synthetic cathinones were also identified in a series of fifty fatalities to determine postmortem distribution and redistribution. Drugs were identified in central and peripheral blood, urine, liver, vitreous humor, and stomach contents. Central to peripheral blood (C/P) and liver to peripheral blood (L/P) ratios were determined for seven synthetic cathinones to assess postmortem redistribution (PMR). While synthetic cathinones appear to exhibit low to moderate PMR, the highest C/P ratios were observed for cathinones bearing a secondary amine and a methylenedioxy group

PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model.

MotivationElectronic health records (EHRs) are quickly becoming omnipresent in healthcare, but interoperability issues and technical demands limit their use for biomedical and clinical research. Interactive and flexible software that interfaces directly with EHR data structured around a common data model (CDM) could accelerate more EHR-based research by making the data more accessible to researchers who lack computational expertise and/or domain knowledge.ResultsWe present PatientExploreR, an extensible application built on the R/Shiny framework that interfaces with a relational database of EHR data in the Observational Medical Outcomes Partnership CDM format. PatientExploreR produces patient-level interactive and dynamic reports and facilitates visualization of clinical data without any programming required. It allows researchers to easily construct and export patient cohorts from the EHR for analysis with other software. This application could enable easier exploration of patient-level data for physicians and researchers. PatientExploreR can incorporate EHR data from any institution that employs the CDM for users with approved access. The software code is free and open source under the MIT license, enabling institutions to install and users to expand and modify the application for their own purposes.Availability and implementationPatientExploreR can be freely obtained from GitHub: https://github.com/BenGlicksberg/PatientExploreR. We provide instructions for how researchers with approved access to their institutional EHR can use this package. We also release an open sandbox server of synthesized patient data for users without EHR access to explore: http://patientexplorer.ucsf.edu.Supplementary informationSupplementary data are available at Bioinformatics online

Quantum strategies

We consider game theory from the perspective of quantum algorithms. Strategies in classical game theory are either pure (deterministic) or mixed (probabilistic). We introduce these basic ideas in the context of a simple example, closely related to the traditional Matching Pennies game. While not every two-person zero-sum finite game has an equilibrium in the set of pure strategies, von Neumann showed that there is always an equilibrium at which each player follows a mixed strategy. A mixed strategy deviating from the equilibrium strategy cannot increase a player's expected payoff. We show, however, that in our example a player who implements a quantum strategy can increase his expected payoff, and explain the relation to efficient quantum algorithms. We prove that in general a quantum strategy is always at least as good as a classical one, and furthermore that when both players use quantum strategies there need not be any equilibrium, but if both are allowed mixed quantum strategies there must be.Comment: 8 pages, plain TeX, 1 figur

Artificial intelligence in gastroenterology: a state-of-the-art review

The development of artificial intelligence (AI) has increased dramatically in the last 20 years, with clinical applications progressively being explored for most of the medical specialties. The field of gastroenterology and hepatology, substantially reliant on vast amounts of imaging studies, is not an exception. The clinical applications of AI systems in this field include the identification of premalignant or malignant lesions (e.g., identification of dysplasia or esophageal adenocarcinoma in Barrett's esophagus, pancreatic malignancies), detection of lesions (e.g., polyp identification and classification, small-bowel bleeding lesion on capsule endoscopy, pancreatic cystic lesions), development of objective scoring systems for risk stratification, predicting disease prognosis or treatment response [e.g., determining survival in patients post-resection of hepatocellular carcinoma), determining which patients with inflammatory bowel disease (IBD) will benefit from biologic therapy], or evaluation of metrics such as bowel preparation score or quality of endoscopic examination. The objective of this comprehensive review is to analyze the available AI-related studies pertaining to the entirety of the gastrointestinal tract, including the upper, middle and lower tracts; IBD; the hepatobiliary system; and the pancreas, discussing the findings and clinical applications, as well as outlining the current limitations and future directions in this field.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Artificial Intelligence and Cardiovascular Genetics

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.</jats:p

Correction to: Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits

Erratum for Integrative analysis of loss-of-function variants in clinical and genomic data reveals novel genes associated with cardiovascular traits. [BMC Med Genomics. 2019

Nash Equilibria in Multi-Agent Motor Interactions

Social interactions in classic cognitive games like the ultimatum game or the prisoner's dilemma typically lead to Nash equilibria when multiple competitive decision makers with perfect knowledge select optimal strategies. However, in evolutionary game theory it has been shown that Nash equilibria can also arise as attractors in dynamical systems that can describe, for example, the population dynamics of microorganisms. Similar to such evolutionary dynamics, we find that Nash equilibria arise naturally in motor interactions in which players vie for control and try to minimize effort. When confronted with sensorimotor interaction tasks that correspond to the classical prisoner's dilemma and the rope-pulling game, two-player motor interactions led predominantly to Nash solutions. In contrast, when a single player took both roles, playing the sensorimotor game bimanually, cooperative solutions were found. Our methodology opens up a new avenue for the study of human motor interactions within a game theoretic framework, suggesting that the coupling of motor systems can lead to game theoretic solutions

N—Person Stochastic Games: Extensions of the Finite State Space Case and Correlation

In this chapter, we present a framework for m-person stochastic games with an infinite state space. Our main purpose is to present a correlated equilibrium theorem proved by Nowak and Raghavan [42] for discounted stochastic games with a measurable state space, where the correlation o