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Objectives:The current practice of prescribing psychotropic medication for the management of dementia-related behavioral disturbances is under substantial debate. Using Pearlin's stress process model as theoretical underpinning, the aim of this investigation is to identify caregiver and care recipient characteristics as predictors of anxiolytic, antipsychotic, and antidepressant use among community-dwelling dementia patients. We hypothesized that caregiving burden and patient characteristics, particularly behavior disturbances and pain, would be positively associated with psychotropic medication use. Methods:Data for this exploratory, cross-sectional study were drawn from the baseline assessment of the Resources for Enhancing Alzheimer's Caregiver Health II trial. Only participants with full baseline information were examined (N= 598). Caregiver characteristics, such as confidence managing problematic behaviors, and care recipient characteristics including pain, problem behaviors, cognitive impairment, and functional impairment, were examined in relation to care recipient psychotropic medication use. Results:Contrary to our hypothesis, behavioral disturbances and burden associated with these disturbances were not significantly associated with psychotropic use. Rather, caregiver characteristics such as race and overall vigilance, and care recipient characteristics such as cognitive status, functional status, and pain were significantly associated with the use of psychotropic medication. Findings differed by class of medication. Conclusion:These exploratory findings suggest the utility of a holistic approach to understanding the factors associated with pharmacotherapy among community-dwelling elders with dementia. Significant associations between caregiver characteristics and care recipient psychotropic medication use suggest that educating caregivers in non-pharmacologic strategies hold promise for a more balanced biopsychosocial approach to maintaining dementia patients in the community. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Biomass blend predictions from 10% (w/w) solid loading were applicable at 30%. • Impact analysis demonstrated the simultaneous application of LCF and predictive model. • Lignocellulosic sugars from biomass blends converted to ethanol at 100% (of theoretical) yield. • Techno-economic analysis validated industrial application of predictive model. Abstract Previously, a predictive model was developed to identify optimal blends of expensive high-quality and cheaper low-quality feedstocks for a given geographical location that can deliver high sugar yields. In this study, the optimal process conditions were tested for application at commercially-relevant higher biomass loadings. We observed lower sugar yields but 100% conversion to ethanol from a blend that contained only 20% high-quality feedstock. The impact of applying this predictive model simultaneously with least cost formulation model for a biorefinery location outside of the US Corn Belt in Lee County, Florida was investigated. A blend ratio of 0.30 EC, 0.45 SG, and 0.25 CS in Lee County was necessary to produce sugars at high yields and ethanol at a capacity of 50 MMGY. This work demonstrates utility in applying predictive model and LCF to reduce feedstock costs and supply chain risks while optimizing for product yields. [ABSTRACT FROM AUTHOR]

Although both genetic factors and features of the social environment are important predictors of posttraumatic stress disorder (PTSD), there are few data examining gene-social environment interactions in studies of PTSD. The authors examined whether features of the social environment (county-level crime rate and unemployment) modified the association between the serotonin protein gene (SLC6A4) promoter variant (5-HTTLPR) and risk of current PTSD in a sample of 590 participants from the 2004 Florida Hurricane Study. Interviews conducted in 2005 were used to obtain individual-level risk factor measures and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, PTSD diagnoses. DNA was extracted from salivary samples. County-level crime and unemployment rates were assessed from Federal Bureau of Investigation and US Census data, respectively. There was a significant interaction between 5-HTTLPR genotype and both crime rate (odds ratio = 2.68, 95% confidence interval: 1.09, 6.57) and unemployment rate (odds ratio = 3.67, 95% confidence interval: 1.42, 9.50) in logistic regression models predicting PTSD risk, after adjustment for individual-level determinants of PTSD. Stratified analyses indicated that the "s" allele of the 5-HTTLPR polymorphism was associated with decreased risk of PTSD in low-risk environments (low crime/unemployment rates) but increased risk of PTSD in high-risk environments. These results suggest that social environment modifies the effect of 5-HTTLPR genotype on PTSD risk.