Factors influencing aster leafhopper (Hemiptera: Cicadellidae) abundance and aster yellows phytoplasma infectivity in Wisconsin carrot fields.

In Wisconsin, vegetable crops are threatened annually by infection of the aster yellows phytoplasma (AYp), the causal agent of aster yellows (AY) disease, vectored by the aster leafhopper, Macrosteles quadrilineatus Forbes. Aster leafhopper abundance and infectivity are influenced by processes operating across different temporal and spatial scales. We applied a multilevel modeling approach to partition variance in multifield, multiyear, pest scouting data sets containing temporal and spatial covariates associated with aster leafhopper abundance and infectivity. Our intent was to evaluate the relative importance of temporal and spatial covariates to infer the relevant scale at which ecological processes are driving AY epidemics and identify periods of elevated risk for AYp spread. The relative amount of aster leafhopper variability among and within years (39%) exceeded estimates of variation among farm locations and fields (7%). Similarly, time covariates explained the largest amount of variation of aster leafhopper infectivity (50%). Leafhopper abundance has been decreasing since 2001 and reached its minimum in 2010. The average seasonal pattern indicated that periods of above average abundance occurred between 11 June and 1 August. Annual infectivity appears to oscillate around an average value of 2% and seasonal periods of above average infectivity occur between 19 May and 15 July. The coincidence of the expected periods of high leafhopper abundance and infectivity increases our knowledge of when the insect moves into susceptible crop fields and when it spreads the pathogen to susceptible crops, representing a seasonal interval during which management of the insect can be focused.

Seasonal patterns of aster leafhopper (Hemiptera: Cicadellidae) abundance and aster yellows phytoplasma infectivity in Wisconsin carrot fields.

In Wisconsin, vegetable crops are threatened annually by the aster yellows phytoplasma (AYp), which is obligately transmitted by the aster leafhopper. Using a multiyear, multilocation data set, seasonal patterns of leafhopper abundance and infectivity were modeled. A seasonal aster yellows index (AYI) was deduced from the model abundance and infectivity predictions to represent the expected seasonal risk of pathogen transmission by infectious aster leafhoppers. The primary goal of this study was to identify periods of time during the growing season when crop protection practices could be targeted to reduce the risk of AYp spread. Based on abundance and infectivity, the annual exposure of the carrot crop to infectious leafhoppers varied by 16- and 70-fold, respectively. Together, this corresponded to an estimated 1,000-fold difference in exposure to infectious leafhoppers. Within a season, exposure of the crop to infectious aster leafhoppers (Macrosteles quadrilineatus Forbes), varied threefold because of abundance and ninefold because of infectivity. Periods of above average aster leafhopper abundance occurred between 11 June and 2 August and above average infectivity occurred between 27 May and 13 July. A more comprehensive description of the temporal trends of aster leafhopper abundance and infectivity provides new information defining when the aster leafhopper moves into susceptible crop fields and when they transmit the pathogen to susceptible crops.

Systematic comparison of nonmelanoma skin cancer microarray datasets reveals lack of consensus genes.

BACKGROUND: DNA microarray technology has revealed vast numbers of gene expression alterations associated with human malignancies. Assigning validity and biological significance to these changes, however, remains a considerable hurdle. Recently, microarray analysis has been applied to the study of nonmelanoma skin cancer. OBJECTIVES: To compare experimental data rigorously in order to strengthen conclusions regarding the pathogenesis of basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), and to evaluate systematically the experimental and statistical parameters that may impact the degree of consensus among differentially expressed genes (DEGs) between studies. METHODS: We performed a systematic comparison of 10 studies that applied DNA microarray technology to study BCC/SCC. RESULTS: A total of 1133 DEGs collectively reported across the studies were compared, and 64 DEG overlaps were found: 18 DEG overlaps in SCC vs. SCC study comparisons, 18 DEG overlaps in BCC vs. BCC study comparisons and 28 DEG overlaps in BCC vs. SCC study comparisons. We documented differences in several experimental methods that may account for the relative lack of consensus between studies, including sample type, tissue procurement/handling, microarray chip and statistical analysis. The two most dysregulated biological pathways across all studies involved genes with enzymatic and structural/adhesion functions. CONCLUSIONS: DEGs that were found to overlap across two or more studies and biological pathways with the largest representation of DEGs across studies may be particularly relevant to disease pathogenesis and serve as targets for future therapy. In future work, more consistent experimental methods across laboratories may improve the validity of reported DEGs and strengthen conclusions drawn from microarray data.