Billions in Tax Revenue Lost Due to Misuse of Opioids

MedicalResearch.com Interview with:

Joel Segel, Ph.D.Assistant ProfessorDepartment of Health Policy and AdministrationThe Pennsylvania State UniversityUniversity Park, PA 16802

Dr. Segel

Joel E. Segel, Ph.D.
Assistant Professor
Department of Health Policy and Administration
The Pennsylvania State University
University Park, PA 16802

MedicalResearch.com: What is the background for this study? What are the main findings? 

Response: Earlier research has shown that the societal costs of opioid misuse are high, including the impact on employment. However, previous work to understand the costs of opioid misuse borne by state and federal governments has largely focused on medical costs such as care related to overdoses and the cost of treating opioid use disorder.

Our main findings are that when individuals who misuse opioids are unable to work, state and federal governments may bear significant costs in the form of lost income and sales tax revenue. We estimate that between 2000 and 2016, state governments lost $11.8 billion in tax revenue and the federal government lost $26.0 billion.  Continue reading

Panel of Salivary RNA Biomarkers Could Identify Autism

MedicalResearch.com Interview with:

Steven D. Hicks, M.D.,Ph.D Department of Pediatrics Penn State College of Medicine Hershey, PA

Dr. Hicks

Steven D. Hicks, M.D.,Ph.D
Department of Pediatrics
Penn State College of Medicine
Hershey, PA

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Since autism has both genetic and environmental underpinnings, my colleagues and I suspected that transcriptional elements (e.g. regulatory RNA molecules) might be different in the saliva of children with autism compared to peers without autism. We used a non-biased approach to analyze saliva from 372 children, and allowed machine learning techniques to inform which RNA elements best predicted autism status. To our surprise, microbial RNA levels and human RNA levels were equally powerful in predicting which children had autism. This may be because some children with autism eat restricted diets, resist tooth brushing, or put foreign objects in their mouths. The end result was a panel of 32 RNAs (20 human and 12 bacterial) that identified autism with 87% accuracy. Interestingly, when we tested the panel in a completely separate set of 84 children (including children from a different geographic region) the accuracy remained 88%. 

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