|Usage of Low-Density Oligonucleotide Microarrays for Prognosis Prediction of Colorectal Cancer Patients|
Slabý O., Garajová I., Svoboda M., Fabian P., Svoboda M., Šmerdová T. and Vyzula R.
This study aimed to find individual up/down-regulated genes associated with progression and metastatic potential of colorectal cancers using low-density oligonucleotide microarrays spotted with genes known to be involved in process of metastasis development. We suppose that focusing on a particular biological pathway may be more useful than genome-wide screening for our purposes.
|Diagnosis of Aortic Aneurysm from Gene Expression Profiling of Peripheral Blood|
Catalin Barbacioru,Yulei Wang, Dov Shiffman, Olga Iakoubova, Sriram Balasubramanian, Julie Blake, John Elefteriades and Raymond Samaha
We report in this study that gene expression profiles of peripheral blood cells may allow early detection and diagnosis of aortic aneurysm. Gene expression profiles of peripheral blood samples collected from 58 individuals diagnosed with thoracic aortic aneurysm (cases) and 36 normal individuals (controls) were analyzed using the Applied Biosystems Expression Array Systems and Human Genome Survey Microarrays.
|New Platforms and Systems for DNA Microarrays|
B. Henze, B. Saal, D. Drutschmann, K. Wellesen and P. Schüßler
Operon has designed probes of different lengths to various positions in the Open Reading Frames (ORFs) and the results clearly show that 70mers offer the optimal combination of specificity and sensitivity.
|S&S® Serum Biomarker Chip Displays Specificity & Reproducibility for 120 Different Human Biomarker Profiles|
Christopher C. Zarozinski, Damon W. Pawlak, Brett A. Stillman, Michael A. Harvey and Breck O. Parker
We introduce a unique tool for the determination of relative abundances for human serum biomarkers. Conceptually similar to DNA microarrays, the S&S® Serum Biomarker Chip (SBC) is a single capture antibody array that was developed for comparative analysis of serum samples in order to identify differences or similarities in protein expression profiles.
|MicroRNA Profiling of Breast Cancer using miRCURY™ LNA Arrays|
Thomas Litman, Mikkel Nørholm, Christian Glue, Nina Stahlberg, Nana Jacobsen, Jens Eriksen, Inge M Svane, Henrik Flyger, Eva Balslev, Carsten Alsb and Søren Møller
MicroRNAs (miRNAs) comprise a recently identified class of small, non-protein-coding regulatory molecules that play important roles in many physiologic and pathologic processes, including differentiation, viral infection, and oncogenesis. In cancer, abnormal miRNA expression suggests that these molecules may serve as valuable diagnostic and prognostic molecular signatures.
|Biosensors using Surface Plasmon Resonance Dynamic Imaging|
J. Hottin, J. Spadavecchia, M. Canva, E. Maillart, M. Anger-Leroy and P. Kerourédan
We study the optical response of a SPRi detection system, characterizing temperature, stringency and time dependence of molecular interactions for the development of a DNA biochip. We are adapting this system and improve its robustness developing applications, as a 900 spots microarray identifying 65 mutations of the cystic fibrosis, for medical uses and industrial commercialization.
|Clinical Validation of a Protein Microarry Assay for Diagnostics of Autoimmune Disease|
S. Judice, D. Pawlak, H Appelhans, A. Frisse, M. Harvey and B. Stillman
We have developed an autoantigen microarray that will allow laboratories to measure the presence of autoantibobies associated with different collagenois and vasculitis-related autoimmune diseases for a single serum sample.
|Simplifying the Flow of Drug Discovery Data|
Dr. Jonathan M.R. Davies
Regardless of research disciplines, scientists need to easily reach the information pertinent to their research. Ideally this data access is easy. Researchers also need the ability to ‘move the data around’ to gain a better view or different perspective. This data manipulation needs to be straightforward. Incorporating the varying views and information required by different scientific disciplines is a considerable challenge.
|Combined Immune Parameters and X-ray data in Early Prediction of Anti-Tuberculosis Chemotherapy Response|
J.F. Djoba Siawaya, N.B. Bapela, H. Veenstra, M. Kidd, N. Beyers and P. van Helden
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.