Using Artificial Neural Networks to Predict Disease Associations for Chemicals Present in Burn Pit Emissions

In June of 2015, 27,378 of the 28,000 returning Operation Iraqi Freedom/Operation Enduring Freedom (OIF/OEF) veterans report being exposed to burn pits. According to Barth et al. (2014), 9,660 returning OIF/OEF veterans were diagnosed with respiratory diseases, to include asthma, bronchitis, and sinusitis, thus strengthening the need to develop decision support tools that can be used to understand the relationships between chemical exposure and disease. In this study an Artificial Neural Network (ANN) was used to predict the chemical-disease associations for burn pit constituents. Ten burn pit constituents were tested using varying hidden layers, similar chemical structure relationships, and three Training, Validation, and Testing (TVT) ratios. The ANN predicted misidentification rates of 73% or greater when the hidden layer size varied between 1 and 5. Misidentification rates of 75% or greater were observed for ANN simulations when the TVT ratios ranged from 60/20/20 to 80/10/10. ANN-based screening of chemical groups containing chemicals with benzene rings and chemicals containing hydrocarbon chains produced misidentification rates of 73% or greater, and R2 values of 0.0762 and lower. Hidden Layer size, TVT ratios, and chemical structure had little effect on the model’s performance; additional training data is needed to improve the predictive capability of the ANN. The ANN-based screening of individual burn pit constituents produced several chemicals with R2 values greater than 0.8. These chemicals have been prioritized to further develop predictive ANN models for human health force support, resulting in the first research screening burn pit constituents with an ANN, and the first to prioritize burn pit emissions for future testing

A comparison of sex offenders and other types of offenders referred to intellectual disability forensic services

This study compared 131 sex offenders with ID and 346 other types of offenders with ID using case file records. All the females in the study were non sexual offenders. Significantly more sexual offenders were referred from court and criminal justice services while significantly fewer were referred from secondary healthcare. A higher percentage of sex offenders had some form of legal status at time of referral. Greater proportions of non sexual offenders were referred for aggression, damage to property, substance abuse and fire setting while only the sex offenders had an index sex offence. For previous offending, the non sexual offenders had higher rates of aggression, cruelty and neglect of children, property damage and substance abuse while the sexual offenders had higher rates of previous sexual offending. For psychiatric disturbance and adversity in childhood, only ADHD showed a significant difference between groups with the non sexual offenders recording higher rates

Addressing concerns about smoking cessation and mental health: theoretical review and practical guide for healthcare professionals

Smoking rates in people with depression and anxiety are twice as high as in the general population, even though people with depression and anxiety are motivated to stop smoking. Most healthcare professionals are aware that stopping smoking is one of the greatest changes that people can make to improve their health. However, smoking cessation can be a difficult topic to raise. Evidence suggests that smoking may cause some mental health problems, and that the tobacco withdrawal cycle partly contributes to worse mental health. By stopping smoking, a person's mental health may improve, and the size of this improvement might be equal to taking antidepressants. In this article we outline ways in which healthcare professionals can compassionately and respectfully raise the topic of smoking to encourage smoking cessation. We draw on evidence-based methods such as cognitive-behavioural therapy (CBT) and outline approaches that healthcare professionals can use to integrate these methods into routine care to help their patients stop smoking.</p

Addressing concerns about smoking cessation and mental health: theoretical review and practical guide for healthcare professionals

Smoking rates in people with depression and anxiety are twice as high as in the general population, even though people with depression and anxiety are motivated to stop smoking. Most healthcare professionals are aware that stopping smoking is one of the greatest changes that people can make to improve their health. However, smoking cessation can be a difficult topic to raise. Evidence suggests that smoking may cause some mental health problems, and that the tobacco withdrawal cycle partly contributes to worse mental health. By stopping smoking, a person's mental health may improve, and the size of this improvement might be equal to taking antidepressants. In this article we outline ways in which healthcare professionals can compassionately and respectfully raise the topic of smoking to encourage smoking cessation. We draw on evidence-based methods such as cognitive–behavioural therapy (CBT) and outline approaches that healthcare professionals can use to integrate these methods into routine care to help their patients stop smoking

Moral Disengagement Mechanisms Predict Cyber Aggression Among Emerging Adults

The Internet has given rise to many new communication tools (e.g., social media, text messaging), which, while beneficial in many respects, have become a means for aggressing against others. As evidence of the adverse correlates of cyber aggression mounts, improved understanding of the mechanisms that facilitate electronic aggression is needed. Moral disengagement (i.e., cognitive processes through which individuals disengage from their moral values) has been shown to predict cyber aggression when assessed as a unitary construct. The present study investigated the eight moral disengagement mechanisms measured by the Moral Disengagement Measure (Detert et al., 2008) and their relationships to four types of cyber aggression perpetration assessed with the Cyberbullying Experiences Survey (i.e., malice, public humiliation, deception, and unwanted contact; Doane et al., 2013). Emerging adults (N = 404, 58.67% women) aged 18 to 29 (M = 25.16, SD = 2.76) recruited through Amazon.com’s MTurk website completed measures online, and data were analyzed via path analysis. Each type of cyber aggression perpetration was predicted by different moral disengagement mechanisms. Advantageous comparison and dehumanization were the strongest predictors, and dehumanization was the only mechanism to predict all forms of cyber aggression. These findings provide support for the role of these mechanisms in cyber aggression and suggest that examining moral disengagement mechanisms individually may help to improve our understanding of cyber aggression among emerging adults. Further clinical and research implications are discussed

Neurofibromatosis Type 1 Implicates Ras Pathways in the Genetic Architecture of Neurodevelopmental Disorders

The genetic architecture of neurodevelopmental disorders is largely polygenic, non-specific, and pleiotropic. This complex genetic architecture makes the search for specific etiological mechanisms that contribute to neurodevelopmental risk more challenging. Monogenic disorders provide an opportunity to focus in on how well-articulated signaling pathways contribute to risk for neurodevelopmental outcomes. This paper will focus on neurofbromatosis type 1 (NF1), a rare monogenic disorder that is associated with varied neurodevelopmental outcomes. Specifically, this paper will provide a brief overview of NF1 and its phenotypic associations with autism spectrum disorder, attention-deficit/hyperactivity disorder, and specific learning disorders, describe how variation within the NF1 gene increases risk for neurodevelopmental disorders via altered Ras signaling, and provide future directions for NF1 research to help elucidate the genetic architecture of neurodevelopmental disorders in the general population

Differential Reinforcement of Alternative Behavior Increases Resistance to Extinction: Clinical Demonstration, Animal Modeling, and Clinical Test of One Solution

Basic research with pigeons on behavioral momentum suggests that differential reinforcement of alternative behavior (DRA) can increase the resistance of target behavior to change. This finding suggests that clinical applications of DRA may inadvertently increase the persistence of target behavior even as it decreases its frequency. We conducted three coordinated experiments to test whether DRA has persistence-strengthening effects on clinically significant target behavior and then tested the effectiveness of a possible solution to this problem in both a nonhuman and clinical study. Experiment 1 compared resistance to extinction following baseline rates of reinforcement versus higher DRA rates of reinforcement in a clinical study. Resistance to extinction was substantially greater following DRA. Experiment 2 tested a rat model of a possible solution to this problem. Training an alternative response in a context without reinforcement of the target response circumvented the persistence-strengthening effects of DRA. Experiment 3 translated the rat model into a novel clinical application of DRA. Training an alternative response with DRA in a separate context resulted in lower resistance to extinction than employing DRA in the context correlated with reinforcement of target behavior. The value of coordinated bidirectional translational research is discusse