Scatter plot for normalized intensity of 174marker antibody arrays.

<p>Panel A (left) shows strong intra-assay correlation (same sample assayed on the same glass slide, tested on the same day); Panel B (middle) shows strong inter-assay correlation (same sample assayed on different glass slides, tested on different days); Panel C (right) shows poor correlation between cancer and normal samples assayed on the same glass slides, tested on the same day.</p

Correlation analysis between ELISA and antibody array assays.

<p>Levels of two protein markers (MSP-alpha and TIMP-4) identified as being differentially expressed in ovarian cancer samples using antibody arrays were confirmed with ELISA. The antibody array data were completely concordant with the ELISA data in classifying sera from ovarian cancer patients and healthy controls. Antibody array data are shown as median array signal intensity (FI), and ELISA data are shown as mean protein concentration (ng/ml).</p

Split-Point Score Analysis of 5 serum markers in ovarian cancer and healthy controls.

<p>Panel A (top left): Dot histogram plot with 5-analyte split-point score classification of sera from healthy control (N) and ovarian cancer (CA). Correctly classified normal serum samples should have a score of 0 to 2, whereas samples from ovarian cancer patients should have a score of 3 to 5; Panel B (top right): The ROC curve for 5-marker panel of split-score analysis of ovarian cancer vs. healthy controls. The ROC is the curve plotted of sensitivity (true positive) against 1-specificity (false positive) values; Panel C (bottom right): Table using five-marker split-point score to classify ovarian cancer patients. A cut-off score of 3 was used.</p

Representative results for 174-marker antibody arrays.

<p>Panel A (left) shows representative fluorescent signal images for array G6; Panel B (middle) shows representative fluorescent signal images for array G7; Panel C (right) shows representative fluorescent signal images for array G8.</p

Hierarchical cluster analysis of 174-marker antibody arrays in ovarian cancers and healthy controls.

<p>Hierarchical cluster analysis of 174-marker antibody arrays in ovarian cancers and healthy controls.</p

Identification and Analysis of Flax Resistance Genes to <i>Septoria linicola</i> (Speg.) Garassini

In this study, the flax (Linum usitatissimum L.) genes associated with resistance to the disease pasmo (Septoria linicola (Speg.) Garassini) were mapped using genome resequencing and bulked segregant analysis (BSA) of genomic DNA of the pasmo-resistant parent y62–9, pasmo-susceptible parent y64–5, and F2 generation segregants. Pasmo resistance genes were identified using Gene Ontology (GO) functional prediction and gene annotation methods. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed the biological information and molecular mechanisms associated with the flax-pathogen interaction. The results of a quantitative real-time PCR analysis revealed that the levels of expression of the three genes Lus10003106, Lus10022077, and Lus10021999 differed between the y62–9 (pasmo-resistant) and y64–5 (pasmo-susceptible) parental flax lines after the inoculation of plants with the pasmo pathogen. Thus, these genes may play key roles in the resistance of flax to pasmo. The results of this study provide a foundation to support future studies of the pathogenesis of flax disease and the discovery and cloning of resistance genes and development of new molecular markers toward the development of pasmo-resistant flax varieties.</p