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trans-Resveratrol (resveratrol) has been shown to have various health benefits. As a consequence, there is an effort to determine plentiful sources of this molecule. Certain plants, such as grapes, synthesize resveratrol and therefore appear to be an excellent source of this chemical. Annual pruning of grapevine yields significant amounts of cane material that is normally mulched or simply burned. Previous studies have shown this grape cane to contain economically useful resveratrol. Texas is the seventh largest producer of grapes in the USA with over 162 ha currently under cultivation. As a result it is estimated that more than $3.2 million of resveratrol could be extracted from grape canes in Texas each year. In this study resveratrol was isolated by a non-optimized protocol from ten varieties of grape cane grown in central Texas, USA. HPLC analysis showed the cultivars Lenoir and Cabernet Sauvignon yielded the greatest relative amounts of resveratrol (52.3 and 49.6 mg/kgDW). A statistical grouping of the ten varieties suggests that Norton, Blanca du bois, Cabernet Sauvignon, and Lenoir are the best candidates to use for further resveratrol isolation. Keywords: HPLC, statistical groups, stilbenes, soxhlet extraction, Stilbenes are a diverse group of economically important chemicals some of which have been used for decades as optical brighteners in soaps, detergents, and fabric softeners (Smulders & Sung 2002). [...]

Health and health care inequities persist because the efforts to eliminate them have ignored structural racism, typically using a power neutral approach to diagnose and solve the problem. Critical theory can address many of the conceptual weaknesses of current approaches, help identify how racism operates in health care, and open the door for more effective individual employee and organizational actions to advance health equity. We apply Martín-Baró’s (1996) liberation psychology to lessons we learned through implementing a transdisciplinary national health and health care equity program. The program, which began in 2005, conducts equity-focused health services interventions and research, using the best available evidence to assist health and health care policymakers, payers, community-based organizations, care delivery organizations, and patients to transform and align their activities in order to advance health equity. It serves as a rare model to explore how misconceptions resulting from racist structures can hinder progress, even when everyone involved is highly motivated to address health and health care inequities. Liberation psychology guides our interpretation of the lessons learned and recommendations for the field of psychology. Psychologists advancing equity in health and health care should integrate liberation psychology and other critical theories into their own work. In addition, partnerships with other disciplines and communities outside of academia and professional health services are key to success. [ABSTRACT FROM AUTHOR]

Police, like other bureaucratic agencies, are responsible for collecting and disseminating policy-relevant data. Nonetheless, critical data, including killings by police, often go unreported. We argue that this is due in part to the limited oversight capacity of legislative bodies to whom police are accountable. Although many local assemblies lack the means for effective oversight, well-resourced state legislatures may induce transparency from state and substate agencies. This argument is evaluated in two studies of police transparency in the United States. First, we examine the compliance of 19,095 state, county, and municipal police agencies with official data requests over five decades, finding strong positive effects of state legislative capacity on transparency. Second, we examine the accuracy of transmitted data on killings by police, finding that lethality is systematically underreported in states with lower-capacity legislatures. Collectively, our study has implications for research on policing, legislatures, agency control, and analyses of government data. [ABSTRACT FROM AUTHOR]

Time-series cross-section (TSCS) data are prevalent in political science, yet many distinct challenges presented by TSCS data remain underaddressed. We focus on how dependence in both space and time complicates estimating either spatial or temporal dependence, dynamics, and effects. Little is known about how modeling one of temporal or cross-sectional dependence well while neglecting the other affects results in TSCS analysis. We demonstrate analytically and through simulations how misspecification of either temporal or spatial dependence inflates estimates of the other dimension's dependence and thereby induces biased estimates and tests of other covariate effects. Therefore, we recommend the spatiotemporal autoregressive distributed lag (STADL) model with distributed lags in both space and time as an effective general starting point for TSCS model specification. We illustrate with two example reanalyses and provide R code to facilitate researchers' implementation—from automation of common spatial-weights matrices (W) through estimated spatiotemporal effects/response calculations—for their own TSCS analyses. [ABSTRACT FROM AUTHOR]