Latest Posters
Poster
EasyBeacons™ - new Probes Ideal for Realtime PCR Detection of Methylation Status of Single CpG Duplets and SNPs
The EasyBeacons™ presented here are based on the novel technology Intercalating Nucleic Acid, INA®, linked to a fluorophore and a quencher. INA® is composed of normal DNA nucleotides and Intercalating Pseudo Nucleotides (IPNs). The fact that the EasyBeacons™ are mostly composed of normal DNA nucleotides means that in many respects EasyBeacons™ behave like DNA based probes, allowing use of standard buffers, primers and enzymes and hence reduces the optimisation efforts.
Poster
Real-Time Multiplex Rt-PCR on Circulating Tumor Cells
Using the CTC kit (CellSearch™), cells that attached to anti-EpCAM Moab were immunomagnetically separated and used for analysis of a selected pilot set of 32 genes by real time RT-PCR. This study shows the feasibility of multiple gene expression analysis on RNA isolated from only one tumor cell. Most importantly, expression analysis of several tumor-specific genes in blood samples containing only 2 tumor cells is already possible.
Poster
Novel Fluidics Microbead Trap/Flow Cell Enhances Speed/Sensitivity of Bead-Based Bioassays Up to 5-Fold
Pacific Northwest National Laboratory (PNNL) has developed a micro/nano particle trap that allows surface-functionalized magnetic or non-magnetic particles to be trapped with subsequent perfusion of sample, reagents and wash solutions, yielding significant (up to 5-fold) improvements in assay speed and sensitivity, while significantly reducing sample matrix effects.
Poster
Combined Immune Parameters and X-ray data in Early Prediction of Anti-Tuberculosis Chemotherapy Response
20 tuberculosis (12 slow-responders and 8 fast responders) patients were treated with directly observed short course anti-tuberculosis chemotherapy. Chest X-ray was performed. sICAM-1 and suPAR were measured in serum by ELISA, TNFRs using the luminex technology. General discrimination analysis on selected analytes gave, 91.66% and 87,50% correctly classify fast responders and slow responder respectively. The support vector machine analysis gave 100% correct classification.
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