Biomedical subjects

Peter K Van de Water

Publications and source records attributed to Peter K Van de Water.

3 recordsLinked to original sources

PubMed2004

Evidence for landscape-level, pollen-mediated gene flow from genetically modified creeping bentgrass with CP4 EPSPS as a marker.

Sampling methods and results of a gene flow study are described that will be of interest to plant scientists, evolutionary biologists, ecologists, and stakeholders assessing the environmental safety of transgenic crops. This study documents gene flow on a landscape level from creeping bentgrass (Agrostis stolonifera L.), one of the first wind-pollinated, perennial, and highly outcrossing transgenic crops being developed for commercial use. Most of the gene flow occurred within 2 km in the direction of prevailing winds. The maximal gene flow distances observed were 21 km and 14 km in sentinel and resident plants, respectively, that were located in primarily nonagronomic habitats. The selectable marker used in these studies was the CP4 EPSPS gene derived from Agrobacterium spp. strain CP4 that encodes 5-enol-pyruvylshikimate-3-phosphate synthase and confers resistance to glyphosate herbicide. Evidence for gene flow to 75 of 138 sentinel plants of A. stolonifera and to 29 of 69 resident Agrostis plants was based on seedling progeny survival after spraying with glyphosate in greenhouse assays and positive TraitChek, PCR, and sequencing results. Additional studies are needed to determine whether introgression will occur and whether it will affect the ecological fitness of progeny or the structure of plant communities in which transgenic progeny may become established.

3-Phosphoshikimate 1-Carboxyvinyltransferase↗

PubMed2003

An assessment of predictive forecasting of Juniperus ashei pollen movement in the Southern Great Plains, USA.

Juniperus ashei pollen, a significant aeroallergen, has been recorded during December and January in Tulsa, Oklahoma, over the past 20 years. The nearest upwind source for this pollen is populations growing in southern Oklahoma and central Texas, at distances of 200 km and 600 km respectively. Long-distance dispersal of J. ashei pollen into the Tulsa area shows a strong correlation with the trajectories of wind blowing across southern populations before traveling north towards eastern Oklahoma. The strong tie between climatic conditions and the occurrence of this aeroallergen within the Tulsa, Oklahoma, atmosphere provided a unique opportunity to forecast the dispersal, entrainment, and downwind deposition of this significant aeroallergen. Forecasts of long-distance J. ashei pollen dispersal began during the winter of 1998/1999. Each forecast uses defined climatic parameters to signal pollination at each source site. Coupled to these estimates of pollen release, forecast weather conditions and modeled wind trajectories are used to determine the threat of dispersal to downwind communities. The accuracy of these forecasts was determined by comparing the forecast "threat" to aerobiological records for the same period collected in the "Tulsa region". Analysis of the two seasons revealed only a single occurrence of "high" or "very high" pollen concentrations in Tulsa not directly linked to "moderate" or "severe" forecast threats from the southern source areas.

Forecasting↗

PubMed2003

Pollen count forecasting.

Pollen forecasting is becoming increasingly important to allergists as an adjunct to effective patient care. Forecasts allow patients to avoid exposure to high pollen levels and prompt them to take prophylactic medication and to plan outdoor activities for periods of low pollen levels. Investigators are making progress in developing effective models for daily and seasonal forecasts for important pollen allergens; however, current models are limited to specific geographic areas. Models for the onset of the season for spring tree pollen are based on the chilling and heat units that are required before flowering can occur. Models for pollen season severity are based on regression analysis of preseason meteorologic conditions, and models for daily forecasts are based on the normal pollen curve and responses to day-to-day meteorologic conditions. When winds are favorable, long-distance transport can introduce allergenic pollen types into a local area. The Mountain Cedar Pollen Forecasting model, which combines day-to-day release forecasts at source areas and dispersion forecasts to downwind areas, has been reasonablly successful over the past 4 years. All pollen forecasting models are dependent on accurate meteorologic forecasts, and pollen forecasting will become more accurate as meteorologic forecasts improve.

Forecasting↗