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Biotech / Medical : Ciphergen Biosystems(CIPH): -- Ignore unavailable to you. Want to Upgrade?

To: tuck who wrote (314)	3/7/2005 4:41:16 AM
From: tuck	Read Replies (1) \| Respond to of 510

[Classification of bacterial species with SELDI] >>Bioinformatics. 2005 Mar 3; [Epub ahead of print] Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis. Lancashire L, Schmid O, Shah H, Ball G. The Nottingham Trent University, Clifton Campus, Clifton Lane, Nottingham, NG11 8NS, UK; Loreus Ltd., School of Biomedical and Natural Sciences, Clifton Campus, Clifton Lane, Nottingham, NG11 8NS, UK. MOTIVATION: Robust computer algorithms are required to interpret the vast amounts of proteomic data currently being produced, and to generate generalised models which are applicable to "real world" scenarios. One such scenario is the classification of bacterial species. These vary immensely, some remaining remarkably stable whereas others are extremely labile showing rapid mutation and change. Such variation makes clinical diagnosis difficult and pathogens may be easily misidentified. RESULTS: We applied Artificial Neural Networks (Neuroshell 2) in parallel with cluster analysis and principal components analysis to SELDI-TOF Mass Spectrometry data with the aim of accurately identifying the bacterium Neisseria meningitidis from species within this genus and other closely related taxa. A subset of ions were identified that allowed for the consistent identification of species, classifying greater than 97% of a separate validation subset of samples into their respective groups. AVAILABILITY: Neuroshell 2 is commercially available from Ward Systems.<< Cheers, Tuck

To: tuck who wrote (314)	9/5/2007 1:05:56 PM
From: tuck	Respond to of 510

[SELDI versus FibroTest for the diagnosis of advanced fibrosis in patients with chronic hepatitis C] >>Aliment Pharmacol Ther. 2007 Sep 15;26(6):847-58. Diagnostic value of serum protein profiling by SELDI-TOF ProteinChip compared with a biochemical marker, FibroTest, for the diagnosis of advanced fibrosis in patients with chronic hepatitis C. Morra R, Munteanu M, Bedossa P, Dargere D, Janneau JL, Paradis V, Ratziu V, Charlotte F, Thibault V, Imbert-Bismut F, Poynard T. UMR CNRS 8149, Pharmacy Faculty, Paris 5 University, Paris, and Biopredictive, Paris, France. Background FibroTest has been validated for the diagnosis of liver fibrosis in patients with chronic hepatitis C. Aim To compare FibroTest with a new proteome-based model for the prediction of advanced liver fibrosis. Methods Sera from 191 consecutive patients with simultaneous liver biopsy and FibroTest on fresh sera were used for retrospective mass spectrometry analysis. A new fibrosis index was constructed combining proteomic peaks, selected on differential expression according to fibrosis stages in logistic regression analyses. The main end point was the diagnosis of advanced fibrosis on liver biopsy. Results Eight out of 1000 peaks were selected for the construction of the proteomic index. The area under the receiver operating curve (AUROC) of the proteomic index was 0.88 (95% CI: 0.82-0.92), significantly greater than the FibroTest AUROC of 0.81 (95% CI: 0.74-0.86; P = 0.04); the AUROC of the proteomic and FibroTest combination was 0.88 (95% CI: 0.83-0.92). Seven of the eight selected peaks were highly associated with the FibroTest score, with different patterns of association with the five components of FibroTest. Conclusions A proteomic index combining eight peaks had an excellent accuracy value for the diagnosis of advanced fibrosis in patients with chronic hepatitis C. However, despite a statistical significance, the small improvement delivered by proteomics impairs clinical applications because of its cost and its variability compared with the well validated FibroTest.<< Luckily for VRML, the current ovarian cancer tests aren't as good as the current liver fibrosis tests. So maybe it still has chance . . . Cheers, Tuck