Diminished medial prefrontal cortex activation during the recollection of stressful events is an acquired characteristic of PTSD.

BACKGROUND: Previous research has shown relatively diminished medial prefrontal cortex activation and heightened psychophysiological responses during the recollection of personal events in post-traumatic stress disorder (PTSD), but the origin of these abnormalities is unknown. Twin studies provide the opportunity to determine whether such abnormalities reflect familial vulnerabilities, result from trauma exposure, or are acquired characteristics of PTSD. METHODS: In this case-control twin study, 26 male identical twin pairs (12 PTSD; 14 non-PTSD) discordant for PTSD and combat exposure recalled and imagined trauma-unrelated stressful and neutral life events using a standard script-driven imagery paradigm during functional magnetic resonance imaging and concurrent skin conductance measurement. RESULTS: Diminished activation in the medial prefrontal cortex during Stressful v. Neutral script-driven imagery was observed in the individuals with PTSD, relative to other groups. CONCLUSIONS: Diminished medial prefrontal cortex activation during Stressful v. Neutral script-driven imagery may be an acquired characteristic of PTSD. If replicated, this finding could be used prospectively to inform diagnosis and the assessment of treatment response.

The impact of initiation: Early onset marijuana smokers demonstrate altered Stroop performance and brain activation.

Marijuana (MJ) use is on the rise, particularly among teens and emerging adults. This poses serious public health concern, given the potential deleterious effects of MJ on the developing brain. We examined 50 chronic MJ smokers divided into early onset (regular MJ use prior to age 16; n=24) and late onset (age 16 or later; n=26), and 34 healthy control participants (HCs). All completed a modified Stroop Color Word Test during fMRI. Results demonstrated that MJ smokers exhibited significantly poorer performance on the Interference subtest of the Stroop, as well as altered patterns of activation in the cingulate cortex relative to HCs. Further, early onset MJ smokers exhibited significantly poorer performance relative to both HCs and late onset smokers. Additionally, earlier age of MJ onset as well as increased frequency and magnitude (grams/week) of MJ use were predictive of poorer Stroop performance. fMRI results revealed that while late onset smokers demonstrated a more similar pattern of activation to the control group, a different pattern was evident in the early onset group. These findings underscore the importance of assessing age of onset and patterns of MJ use and support the need for widespread education and intervention efforts among youth.

Statistical molecular design of balanced compound libraries for QSAR modeling.

A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.