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We investigated adaptation of fire blight forecasting concepts to incorporate and optimize the use of biological agents for disease suppression. The effect of temperature on growth of the bacterial antagonists, Pseudomonas fluorescens A506 and Pantoea agglomerans C9-1S, and of the pathogen Erwinia amylovora 153N, on pear and apple blossoms was evaluated in growth chamber and screenhouse experiments. New blossoms were inoculated with the strains and subsequent growth was measured over 96 h. Bacterial growth rates on blossoms were described as functions of temperature. A degree hour-based "bacterial growth index" (96-h moving total of degree hours >10°C) was created to assess conduciveness of orchard environments for antagonist colonization. A comparison of this index to a disease risk index indicated that biocontrol treatments could be timed such that the antagonists could be expected to grow to an effective population size before the disease index shifted from "low" to "moderate" risk. For six pear- and apple-production areas of Oregon and Washington, regression of actual values of the bacterial growth and disease risk indices on index values derived from 4-day temperature forecasts resulted in coefficients of determination that averaged 0.75. The "bacterial growth index" and its estimation via temperature forecasts were incorporated into a decision matrix designed to guide optimal treatment timing. [ABSTRACT FROM AUTHOR]

Electronic health records (EHRs) have become increasingly relied upon as a source for biomedical research. Many different data types are available in EHR, including diagnoses, laboratory measurements, imaging and digital diagnostic data for identifying digital biomarkers, and clinical notes. There are challenges to consider when using EHR data, including potential bias in the availability of EHR data and the implications of missing data in EHR. Different modalities of longitudinal patient data can be used to investigate dynamic changes in health and inform biomarker discovery. There is a bright and opportunistic future of the EHR, including data capture, quality control, interoperability, governance, and utility. Electronic health records (EHRs) have become increasingly relied upon as a source for biomedical research. One important research application of EHRs is the identification of biomarkers associated with specific patient states, especially within complex conditions. However, using EHRs for biomarker identification can be challenging because the EHR was not designed with research as the primary focus. Despite this challenge, the EHR offers huge potential for biomarker discovery research to transform our understanding of disease etiology and treatment and generate biological insights informing precision medicine initiatives. This review paper provides an in-depth analysis of how EHR data is currently used for phenotyping and identifying molecular biomarkers, current challenges and limitations, and strategies we can take to mitigate challenges going forward. [ABSTRACT FROM AUTHOR]

Forty-four horses were used to determine if a learned stimulus could be used to increase acquisition of a response unrelated to the original learned task. Horses were paired by age, breed and sex. One randomly chosen horse from each pair served as the control while the remaining horse was trained to respond to a visual stimulus by pushing a lever to obtain a food reward. In Experiment I (n=28), the food reward was delivered in a feed box located equidistant between two levers located 2.7 m apart on one wall of the test stall. Trained horses were given 30 training trials daily until they achieved at least 85% correct responses in three nonconsecutive days. After each trained horse reached criterion, both horses in the pair were tested in 30 trials daily for five consecutive days in a modified Y maze. The stimulus that indicated the correct lever in the initial training task was used to signify the correct arm of the maze for both the control and trained horses. The correct arm of the maze was changed randomly during each daily session, and correct choices resulted in a food reward. In Experiment II (n=16), levers were located on opposite walls (11 m apart) of the test stall, and the stimulus and modified Y maze were simplified. Trained horses received 15 training trials daily until they reached at least 85% correct responses on three consecutive days. As each trained horse achieved this criterion, both horses in the pair were tested in a maze for 15 trials daily for 7 days. Again, the stimulus from initial lever-pressing task was used to signify the rewarded arm of the maze. Correct choices of trained and control horses in both experiments were compared using a paired t-test. In Experiment I, no differences (P>0.34) in mean correct responses were detected between trained and control horses on the first day in the maze (15.3 and 16.8, respectively) or after 5 days in the maze (84.0 and 82.1, respectively). Similarly, in Experiment II, trained and control horses did not differ (P>0.50) in mean correct responses on the first day (6.9 and 7.4, respectively) or after 7 days in the maze (63.6 and 61.6, respectively). These results indicate that the stimuli used to solve the lever-pressing task were not utilized by horses in the maze task, and that horses may have difficulty transferring learned visual stimuli to new tasks. [Copyright &y& Elsevier]

Explores results of studies about the green fluorescent protein (GFP) gene. Limitations and attributes of GFP as a reporter gene; Differentiation of wild-type and engineered GFP; Function in host-pathogen interactions, mycoparasitism and the phyllosphere; Cell dynamics; Vectors for GFP tagging of filamentous fungi; Role of GFP in the future of fungal biology.