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

To: tuck who wrote (206)	2/27/2004 5:15:31 PM
From: tuck	Respond to of 510

Device or not, the potential is still being mined. This abstract describes another algorithm for analyzing pattern data. If memory serves, the 97% specificity, sensitivity, and predictive value, does indeed beat anything out there for ovarian, it certainly does for prostate. One wonders if CIPH might make deals with such folks for better algorithms. >>J Comput Biol. 2003;10(6):925-46. Probabilistic disease classification of expression-dependent proteomic data from mass spectrometry of human serum. Lilien RH, Farid H, Donald BR. Dartmouth Computer Science Department, Hanover, NH 03755, USA. We have developed an algorithm called Q5 for probabilistic classification of healthy versus disease whole serum samples using mass spectrometry. The algorithm employs principal components analysis (PCA) followed by linear discriminant analysis (LDA) on whole spectrum surface-enhanced laser desorption/ionization time of flight (SELDI-TOF) mass spectrometry (MS) data and is demonstrated on four real datasets from complete, complex SELDI spectra of human blood serum. Q5 is a closed-form, exact solution to the problem of classification of complete mass spectra of a complex protein mixture. Q5 employs a probabilistic classification algorithm built upon a dimension-reduced linear discriminant analysis. Our solution is computationally efficient; it is noniterative and computes the optimal linear discriminant using closed-form equations. The optimal discriminant is computed and verified for datasets of complete, complex SELDI spectra of human blood serum. Replicate experiments of different training/testing splits of each dataset are employed to verify robustness of the algorithm. The probabilistic classification method achieves excellent performance. We achieve sensitivity, specificity, and positive predictive values above 97% on three ovarian cancer datasets and one prostate cancer dataset. The Q5 method outperforms previous full-spectrum complex sample spectral classification techniques and can provide clues as to the molecular identities of differentially expressed proteins and peptides.<< And this one concerning a pattern for HAD. I do not know how big an indication HAD is. >>J Neurovirol. 2004;10 Suppl 1:74-81. Proteomic fingerprinting of human immunodeficiency virus type 1-associated dementia from patient monocyte-derived macrophages: A case study. Wojna V, Carlson KA, Luo X, Mayo R, Melendez LM, Kraiselburd E, Gendelman HE. The Departments of Microbiology and Specialized NeuroSciences Program, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico. The emergence of a subset of circulating monocytes during human immunodeficiency virus type 1 (HIV-1) disease has been shown to correlate with cognitive impairment. Thus, it is hypothesized that diagnostic protein profiles may be obtained from these cells from patients with or at risk for HIV-1-associated dementia (HAD). To address this possibility, we used ProteinChip assays to define a unique monocyte-derived macrophage (MDM) protein fingerprint during HAD and whether it is affected by highly active antiretroviral therapy (HAART). The study included five Hispanic women, one with HAD, two HIV-1-infected without cognitive impairment, and two seronegative controls. All patients were matched by age and immune status. Monocytes were recovered from the peripheral blood leukocytes by Percoll gradient centrifugation and allowed to differentiate in vitro for 7 days. Cell lysates and supernatants were collected from the MDM and analyzed by surface enhanced laser desorption/ionization-time of flight ProteinChip assays. Seven unique protein peaks between 3.0 and 20.0 kDa were found in the HAD MDM sample. Each of these proteins were abrogated after HAART. Additional studies extending this one time point determination would serve to confirm the general utility of MDM protein profiling for the diagnosis and monitoring of HAD.<< Cheers, Tuck