Exposure to the “Troubles” in Northern Ireland influences the clinical presentation of schizophrenia

Introduction: This study investigates the effect of exposure to "The Troubles" (the period of civil unrest from 1968 onwards) in Northern Ireland on symptomatology in people with schizophrenia.

Method: Eighty-two participants were assessed on a number of psychiatric rating scales and on measures of trauma, including an instrument designed to assess exposure to "Troubles"-related trauma.

Results: People with schizophrenia and a history of exposure to "The Troubles" had significantly higher levels of anxiety, depression, dissociative symptoms and number of admissions compared to those patients with no such exposure.

Discussion: "Troubles"-related trauma has a direct effect on the presentation of schizophrenia in Northern Ireland. Specific therapeutic intervention may be required in order to help patients come to terms with their experiences. © 2008 Elsevier B.V. All rights reserved.

Feasibility of a Clinical Chemical Analysis Approach to Predict Misuse of Growth Promoting Hormones in Cattle

A study was performed to determine if targeted metabolic profiling of cattle sera could be used to establish a predictive tool for identifying hormone misuse in cattle. Metabolites were assayed in heifers (n ) 5) treated with nortestosterone decanoate (0.85 mg/kg body weight), untreated heifers (n ) 5), steers (n ) 5) treated with oestradiol benzoate (0.15 mg/kg body weight) and untreated steers (n ) 5). Treatments were administered on days 0, 14, and 28 throughout a 42 day study period. Two support vector machines (SVMs) were trained, respectively, from heifer and steer data to identify hormonetreated animals. Performance of both SVM classifiers were evaluated by sensitivity and specificity of treatment prediction. The SVM trained on steer data achieved 97.33% sensitivity and 93.85% specificity while the one on heifer data achieved 94.67% sensitivity and 87.69% specificity. Solutions of SVM classifiers were further exploited to determine those days when classification accuracy of the SVM was most reliable. For heifers and steers, days 17-35 were determined to be the most selective. In summary, bioinformatics applied to targeted metabolic profiles generated from standard clinical chemistry analyses, has yielded an accurate, inexpensive, high-throughput test for predicting steroid abuse in cattle.