ECOLOGICAL EFFECTS OF TRANSGENIC CROPS AND THE ESCAPE OF TRANSGENES INTO WILD POPULATIONS

Ecological risks associated with the release of transgenic crops include nontarget effects of the crop and the escape of transgenes into wild populations. Nontarget effects can be of two sorts: (a) unintended negative effects on species that do not reduce yield and (b) greater persistence of the crop in feral populations. Conventional agricultural methods, such as herbicide and pesticide application, have large and well- documented nontarget effects. To the extent that transgenes have more specific target effects, transgenic crops may have fewer nontarget effects. The escape of transgenes into wild populations, via hybridization and introgression, could lead to increased weediness or to the invasion of new habitats by the wild population. In addition, native species with which the wild plant interacts (including herbivores, pathogens, and other plant species in the community) could be negatively affected by “transgenic-wild” plants. Conventional crop alleles have facilitated the evolution of increased weediness in several wild populations. Thus, some transgenes that allow plants to tolerate biotic and abiotic stress (e.g., insect resistance, drought tolerance) could have similar effects

VIRUS INFECTIONS IN WILD PLANT POPULATIONS ARE BOTH FREQUENT AND OFTEN UNAPPARENT

• Premise of the study: Pathogens are thought to regulate host populations. In agricultural crops, virus infection reduces yield. However, in wild plants little is known about the spatial and temporal patterns of virus prevalence. Thus, pathogen effects on plant population dynamics are unclear. Prevalence data provide necessary background for (1) evaluating the effects of virus infection on plant population size and dynamics and (2) improving risk assessment of virus-resistant transgenic crops. • Methods: We used ELISA and RT-PCR to survey wild Cucurbita pepo populations over 4 years for five viruses, aphid-transmitted viruses of the genus Potyvirus as a group and PCR to survey for virus-resistance transgenes. In addition, we surveyed the literature for reports of virus prevalence in wild populations. • Key results: In 21 C. pepo populations, virus prevalence (0–74%) varied greatly among populations, years, and virus species. In samples analyzed by both ELISA and RT-PCR, RT-PCR detected 6–44% more viruses than did ELISA. Eighty percent of these infections did not cause any visually apparent symptoms. In our samples, the virus-resistance transgene was not present. In 30 published studies, 92 of 146 tested species were infected with virus, and infection rates ranged from 0.01–100%. Most published studies used ELISA, suggesting virus prevalence is higher than reported. • Conclusions: In wild C. pepo , the demographic effects of virus are likely highly variable in space and time. Further, our literature survey suggests that such variation is probably common across plant species. Our results indicate that risk assessments for virus-resistant transgenic crops should not rely on visual symptoms or ELISA and should include data from multiple populations over multiple years

Implementing stakeholder engagement to explore alternative models of consent: An example from the PREP-IT trials

Introduction: Cluster randomized crossover trials are often faced with a dilemma when selecting an optimal model of consent, as the traditional model of obtaining informed consent from participant's before initiating any trial related activities may not be suitable. We describe our experience of engaging patient advisors to identify an optimal model of consent for the PREP-IT trials. This paper also examines surrogate measures of success for the selected model of consent. Methods: The PREP-IT program consists of two multi-center cluster randomized crossover trials that engaged patient advisors to determine an optimal model of consent. Patient advisors and stakeholders met regularly and reached consensus on decisions related to the trial design including the model for consent. Patient advisors provided valuable insight on how key decisions on trial design and conduct would be received by participants and the impact these decisions will have. Results: Patient advisors, together with stakeholders, reviewed the pros and cons and the requirements for the traditional model of consent, deferred consent, and waiver of consent. Collectively, they agreed upon a deferred consent model, in which patients may be approached for consent after their fracture surgery and prior to data collection. The consent rate in PREP-IT is 80.7%, and 0.67% of participants have withdrawn consent for participation. Discussion: Involvement of patient advisors in the development of an optimal model of consent has been successful. Engagement of patient advisors is recommended for other large trials where the traditional model of consent may not be optimal