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Archive - Mar 28, 2013

New Technologies Used to Combat Aquatic Invasive Species

A new research paper by a team of researchers from the University of Notre Dame's Environmental Change Initiative (ECI) and collaborators demonstrates how two cutting-edge technologies can provide a sensitive and real-time solution to screening real-world water samples for invasive species before they get into our country or before they cause significant damage. The paper was published online on March 22, 2013 in Conservation Letters. "Aquatic invasive species cause ecological and economic damage worldwide, including the loss of native biodiversity and damage to the world's great fisheries," Dr. Scott Egan, a research assistant professor with Notre Dame's Advanced Diagnostics and Therapeutics Initiative and a member of the research team, said. "This research combines two new, but proven technologies, environmental DNA (eDNA) and Light Transmission Spectroscopy (LTS), to address the growing problem of aquatic invasive species by increasing our ability to detect dangerous species in samples before they arrive or when they are still rare in their environment and have not yet caused significant damage." Egan points out that eDNA is a species surveillance tool that recognizes a unique advantage of aquatic sampling: water often contains microscopic bits of tissue in suspension, including the scales of fish, the exoskeletons of insects, and the sloughed cells of and tissues of aquatic species. These tissue fragments can be filtered from water samples and then a standard DNA extraction is performed on the filtered matter. The new sampling method for invasive species was pioneered by members of the Notre Dame Environmental Change Initiative, including Dr. David Lodge and Dr. Chris Jerde, Central Michigan University's Dr. Andrew Mahon, and The Nature Conservancy's Dr. Lindsay Chadderton. Dr.

Study Shows Brain Scans Might Predict Future Criminal Behavior

A new study conducted by The Mind Research Network (MRN) in Albuquerque, New Mexico, together with collaborators at Duke University, the University of New Mexico, the University of Massachusetts Medical School, and the University of California-Santa Barbara, shows that neuroimaging data can predict the likelihood of whether a criminal will reoffend following release from prison. The paper, which was published online on March 27, 2013 in PNAS, studied impulsive and antisocial behavior and centered on the anterior cingulate cortex (ACC), a portion of the brain that deals with regulating behavior and impulsivity. The study demonstrated that inmates with relatively low anterior cingulate activity were twice as likely to reoffend than inmates with high-brain activity in this region. "These findings have incredibly significant ramifications for the future of how our society deals with criminal justice and offenders," said Dr. Kent A. Kiehl, who was senior author on the study and is director of mobile imaging at MRN and an associate professor of psychology at the University of New Mexico. "Not only does this study give us a tool to predict which criminals may reoffend and which ones will not reoffend, it also provides a path forward for steering offenders into more effective targeted therapies to reduce the risk of future criminal activity." The study looked at 96 adult male criminal offenders aged 20-52 who volunteered to participate in research studies. This study population was followed over a period of up to four years after inmates were released from prison. "These results point the way toward a promising method of neuroprediction with great practical potential in the legal system," said Dr.

Common Gene Variants Explain 42 Percent of Individual Variation in Antidepressant Response

Antidepressants are commonly prescribed for the treatment of depression, but many individuals do not experience symptom relief from treatment. The National Institute of Mental Health's STAR*D study, the largest and longest study ever conducted to evaluate depression treatment, found that only approximately one-third of patients responded within their initial medication trial and approximately one-third of patients did not have an adequate clinical response after being treated with several different medications. Thus, identifying predictors of antidepressant response could help to guide the treatment of this disorder. A new study, published online on December 12, 2012 in Biological Psychiatry and printed in the April 1, 2013 issue of that journal, now shares progress in identifying genomic predictors of antidepressant response. Many previous studies have searched for genetic markers that may predict antidepressant response, but have done so despite not knowing the contribution of genetic factors. Dr. Katherine Tansey of the Institute of Psychiatry at King's College London and colleagues resolved to answer that question. "Our study quantified, for the first time, how much is response to antidepressant medication influenced by an individual's genetic make-up," said Dr. Tansey. To perform this work, the researchers estimated the magnitude of the influence of common genetic variants on antidepressant response using a sample of 2,799 antidepressant-treated subjects with major depressive disorder and genome-wide genotyping data. They found that genetic variants explain 42% of individual differences, and therefore, significantly influence antidepressant response. "While we know that there are no genetic markers with strong effect, this means that there are many genetic markers involved.