The need for multidisciplinary research to address today's complex health and environmental challenges has never been greater. The One Health (OH) approach to research ensures that human, animal, and environmental health questions are evaluated in an integrated and holistic manner to provide a more comprehensive understanding of the problem and potential solutions than would be possible with siloed approaches. However, the OH approach is complex, and there is limited guidance available for investigators regarding the practical design and implementation of OH research. In this paper we provide a framework to guide researchers through conceptualizing and planning an OH study. We discuss key steps in designing an OH study, including conceptualization of hypotheses and study aims, identification of collaborators for a multi-disciplinary research team, study design options, data sources and collection methods, and analytical methods. We illustrate these concepts through the presentation of a case study of health impacts associated with land application of biosolids. Finally, we discuss opportunities for applying an OH approach to identify solutions to current global health issues, and the need for cross-disciplinary funding sources to foster an OH approach to research.

Quetiapine is an effective and well tolerated antipsychotic of comparable efficacy to haloperidol and lacks the latter compound's effect on prolactin and EPS.

Although wildlife intrusion and untreated manure have been associated with microbial contamination of produce, relatively few studies have examined the survival of Escherichia coli on produce under field conditions following contamination (e.g., via splash from wildlife feces). This experimental study was performed to estimate the die-off rate of E. coli on preharvest lettuce following contamination with a fecal slurry. During August 2015, field-grown lettuce was inoculated via pipette with a fecal slurry that was spiked with a three-strain cocktail of rifampin-resistant nonpathogenic E. coli. Ten lettuce heads were harvested at each of 13 time points following inoculation (0, 2.5, 5, and 24 h after inoculation and every 24 h thereafter until day 10). The most probable number (MPN) of E. coli on each lettuce head was determined, and die-off rates were estimated. The relationship between sample time and the log MPN of E. coli per head was modeled using a segmented linear model. This model had a breakpoint at 106 h (95% confidence interval = 69, 142 h) after inoculation, with a daily decrease of 0.70 and 0.19 log MPN for 0 to 106 h and 106 to 240 h following inoculation, respectively. These findings are consistent with die-off rates obtained in similar studies that assessed E. coli survival on produce following irrigation. Overall, these findings provide die-off rates for E. coli on lettuce that can be used in future quantitative risk assessments.

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