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Image Search Results
Journal: ACS Omega
Article Title: Differential Glycosylation Expression in Injured Rat Spinal Cord Treated with Immunosuppressive Drug Cyclosporin-A
doi: 10.1021/acsomega.8b02524
Figure Lengend Snippet: Intensity of primary astrocyte and Neu7 cell protein extracts binding to lectins on microarray. Bar chart representing the differences in binding of fluorescently labeled protein extracts to printed lectins on a microarray surface where Ast_Lys is the total lysate from primary astrocytes, Ast_Cyt is the cytosolic (hydrophilic) protein-enriched extract from primary astrocytes, Ast_Mem is the membrane (hydrophobic) protein-enriched extract from primary astrocytes, Neu7_Lys is the total lysate from Neu7 cells, Neu7_Cyt is the cytosolic (hydrophilic) protein-enriched extract from Neu7 cells, and Neu7_Mem is the membrane (hydrophobic) protein-enriched extract from Neu7 cells. Graph represents the mean of three replicate experiments (except for duplicate experiments for Neu7_Mem binding to MAL-II), with each experiment the median of six individual replicates. Error bars represent ±1 standard deviation of the mean of the three experiments.
Article Snippet: The lectins were printed at approximately 1 nL per feature on
Techniques: Binding Assay, Microarray, Labeling, Standard Deviation
Journal: The Journal of Molecular Diagnostics : JMD
Article Title: Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression
doi: 10.2353/jmoldx.2010.090187
Figure Lengend Snippet: Classification of kidney tumors using expression levels of six microRNAs (microarray data). A: Classification proceeds in two steps, following the cluster structure of the histological types (Figure 2). First, samples are classified into either the oncocytoma/chromophobe pair, or the conventional/papillary pair, using expression levels of hsa-miR-210 and hsa-miR-221 (B). In the second step, oncocytoma is differentiated from chromophobe using expression levels of hsa-miR-200c and hsa-miR-139-5p (C), and conventional is differentiated from papillary using expression levels of hsa-miR-31 and hsa-miR-126 (D). Independent test samples included oncocytoma samples (n = 19, red stars), chromophobe tumors (n = 14, black/yellow diamonds), conventional tumors (n = 17, blue squares), and papillary tumors (n = 6, green circles). The gray shaded regions indicate the thresholds for classification for each pair of microRNAs, indicating in each case the right branch in the binary classification tree (A). The 71 samples that were used for training the thresholds (see Methods and Figure 3) are shown in faded symbols in the background.
Article Snippet: 31 , 37 Briefly on
Techniques: Expressing, Microarray
Journal: The Journal of Molecular Diagnostics : JMD
Article Title: Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression
doi: 10.2353/jmoldx.2010.090187
Figure Lengend Snippet: Validation by qRT-PCR. The qRT-PCR validation set included 32 tumor samples: 8 oncocytoma tumors (red stars), 8 chromophobe tumors (yellow diamonds), 8 conventional tumors (blue squares), and 8 papillary tumors (green circles). For each decision point (Figure 4A), the plot on the left side (A, C, or E) shows the log2 expression ratio of the two microRNAs used at this node as measured by microarray (horizontal, calculated as the log2 ratio of the normalized fluorescence signal) and by qRT-PCR (vertical, calculated as the difference in normalized Ct values). In each plot, the vertical line demarcates the classification threshold trained on the microarray data, while the horizontal line indicates the classification threshold that was chosen for the qRT-PCR data, based on the microarray threshold (Methods). The plots on the right side (B, D, or F) show the qRT-PCR data (normalized Cts) of the two microRNAs in the samples of the relevant subtypes at each node. The gray shaded regions indicate the thresholds for classification for each pair of microRNAs, indicating in each case the right branch in the binary classification tree (Figure 4A). A: Log2 expression ratio of [hsa-miR-221/hsa-miR-210] in microarray and qRT-PCR. Correlation coefficient was 0.92. B: Normalized Cts of hsa-miR-221 and hsa-miR-210 in 32 samples. C: Log2 expression ratio of [hsa-miR-139-5p/hsa-miR-200c] in microarray and qRT-PCR. Correlation coefficient was 0.86. D: Normalized Cts of hsa-miR-139-5p and hsa-miR-200c in 16 oncocytoma and chromophobe samples. E: Log2 expression ratio of [hsa-miR-126/hsa-miR-31] in microarray and qRT-PCR. Correlation coefficient was 0.98. F: Normalized Cts of hsa-miR-126 and hsa-miR-31 in 16 conventional and papillary samples.
Article Snippet: 31 , 37 Briefly on
Techniques: Biomarker Discovery, Quantitative RT-PCR, Expressing, Microarray, Fluorescence
Journal: The Journal of Molecular Diagnostics : JMD
Article Title: Accurate Molecular Classification of Renal Tumors Using MicroRNA Expression
doi: 10.2353/jmoldx.2010.090187
Figure Lengend Snippet: Classification of Renal Tumors Using Expression Levels of 6 MicroRNAs
Article Snippet: 31 , 37 Briefly on
Techniques: Expressing, Biomarker Discovery, Microarray
Journal: Environmental Health Perspectives
Article Title: Human Pathogens Abundant in the Bacterial Metagenome of Cigarettes
doi: 10.1289/ehp.0901201
Figure Lengend Snippet: 16S PCR amplicons (1,500 bp) generated from metagenomic DNA extracted from cigarettes. Abbreviations: M, Marlboro Red samples; C, Camel samples; K, Kool Filter King samples; L, Lucky Strike Original Red samples; PC, positive control metagenomic DNA sample extracted from soil; NC, negative control. Lane 1, DNA ladder.
Article Snippet: The
Techniques: Generated, Positive Control, Negative Control
Journal: Environmental Health Perspectives
Article Title: Human Pathogens Abundant in the Bacterial Metagenome of Cigarettes
doi: 10.1289/ehp.0901201
Figure Lengend Snippet: Distribution of select bacteria of importance to human health detected in different cigarette brands using a 16S rRNA-based taxonomic microarray.
Article Snippet: The
Techniques: Bacteria, Microarray