Biomedical subjects

Gil Alterovitz

Publications and source records attributed to Gil Alterovitz.

6 recordsLinked to original sources

PubMed2007

Serum proteome profiling detects myelodysplastic syndromes and identifies CXC chemokine ligands 4 and 7 as markers for advanced disease.

Myelodysplastic syndromes (MDS) are among the most frequent hematologic malignancies. Patients have a short survival and often progress to acute myeloid leukemia. The diagnosis of MDS can be difficult; there is a paucity of molecular markers, and the pathophysiology is largely unknown. Therefore, we conducted a multicenter study investigating whether serum proteome profiling may serve as a noninvasive platform to discover novel molecular markers for MDS. We generated serum proteome profiles from 218 individuals by MS and identified a profile that distinguishes MDS from non-MDS cytopenias in a learning sample set. This profile was validated by testing its ability to predict MDS in a first independent validation set and a second, prospectively collected, independent validation set run 5 months apart. Accuracy was 80.5% in the first and 79.0% in the second validation set. Peptide mass fingerprinting and quadrupole TOF MS identified two differential proteins: CXC chemokine ligands 4 (CXCL4) and 7 (CXCL7), both of which had significantly decreased serum levels in MDS, as confirmed with independent antibody assays. Western blot analyses of platelet lysates for these two platelet-derived molecules revealed a lack of CXCL4 and CXCL7 in MDS. Subtype analyses revealed that these two proteins have decreased serum levels in advanced MDS, suggesting the possibility of a concerted disturbance of transcription or translation of these chemokines in advanced MDS.

Biomarkers↗

PubMed2006

GO PaD: the Gene Ontology Partition Database.

Gene Ontology (GO) has been widely used to infer functional significance associated with sets of genes in order to automate discoveries within large-scale genetic studies. A level in GO's direct acyclic graph structure is often assumed to be indicative of its terms' specificities, although other work has suggested this assumption does not hold. Unfortunately, quantitative analysis of biological functions based on nodes at the same level (as is common in gene enrichment analysis tools) can lead to incorrect conclusions as well as missed discoveries due to inefficient use of available information. This paper addresses these using an informational theoretic approach encoded in the GO Partition Database that guarantees to maximize information for gene enrichment analysis. The GO Partition Database was designed to feature ontology partitions with GO terms of similar specificity. The GO partitions comprise varying numbers of nodes and present relevant information theoretic statistics, so researchers can choose to analyze datasets at arbitrary levels of specificity. The GO Partition Database, featuring GO partition sets for functional analysis of genes from human and 10 other commonly studied organisms with a total of 131,972 genes, is available on the internet at: bcl.med.harvard.edu/proj/gopart. The site also includes an online tutorial.

Computer Graphics↗

PubMed2006

Automation, parallelism, and robotics for proteomics.

The speed of the human genome project (Lander, E. S., Linton, L. M., Birren, B., Nusbaum, C. et al., Nature 2001, 409, 860-921) was made possible, in part, by developments in automation of sequencing technologies. Before these technologies, sequencing was a laborious, expensive, and personnel-intensive task. Similarly, automation and robotics are changing the field of proteomics today. Proteomics is defined as the effort to understand and characterize proteins in the categories of structure, function and interaction (Englbrecht, C. C., Facius, A., Comb. Chem. High Throughput Screen. 2005, 8, 705-715). As such, this field nicely lends itself to automation technologies since these methods often require large economies of scale in order to achieve cost and time-saving benefits. This article describes some of the technologies and methods being applied in proteomics in order to facilitate automation within the field as well as in linking proteomics-based information with other related research areas.

Animals↗

PubMed2005

Optimization and evaluation of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) with reversed-phase protein arrays for protein profiling.

Surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry with protein arrays has facilitated the discovery of disease-specific protein profiles in serum. Such results raise hopes that protein profiles may become a powerful diagnostic tool. To this end, reliable and reproducible protein profiles need to be generated from many samples, accurate mass peak heights are necessary, and the experimental variation of the profiles must be known. We adapted the entire processing of protein arrays to a robotics system, thus improving the intra-assay coefficients of variation (CVs) from 45.1% to 27.8% (p<0.001). In addition, we assessed up to 16 technical replicates, and demonstrated that analysis of 2-4 replicates significantly increases the reliability of the protein profiles. A recent report on limited long-term reproducibility seemed to concord with our initial inter-assay CVs, which varied widely and reached up to 56.7%. However, we discovered that the inter-assay CV is strongly dependent on the drying time before application of the matrix molecule. Therefore, we devised a standardized drying process and demonstrated that our optimized SELDI procedure generates reliable and long-term reproducible protein profiles with CVs ranging from 25.7% to 32.6%, depending on the signal-to-noise ratio threshold used.

Lasers↗

PubMed2004

Electrical engineering and nontechnical design variables of multiple inductive loop systems for auditoriums.

This research analyzed both engineering and nontechnical issues involved in the use of Induction Loop Amplification (ILA) devices in auditoriums or large gathering places for hard-of-hearing individuals. A variety of parameters need to be taken into account to determine an optimal shape/configuration for the ILA device. In many cases, an optimal configuration is different from those proposed for classroom use (Ross, 1969; Hodgson, 1986; Clevenger, 1992). Experimental results were obtained for a double-loop configuration in such a setting (a university gymnasium/auditorium in this case). The results demonstrate that a double-loop configuration is a viable possibility for auditorium use. Several variables using this configuration were examined, and experimentation was done. Various implications, including consequent nontechnical issues specific to this application, are discussed as well. Technical and nontechnical aspects of the ILA configuration need to be examined together when designing an optimal system.

Acoustics↗

PubMed2002

Temporal patient state characterization using Iterative Order and Noise (ION) estimation: applications to anesthesia patient monitoring.

OBJECTIVE: As more sensors are added to increasingly technology-dependent operating rooms (OR), physicians such as anesthesiologists must sift through an ever-increasing number of patient parameters every few seconds as part of their OR duties. To the extent these many parameters are correlated and redundant, manually monitoring all of them may not be an optimal physician strategy for assessing patient state or predicting future changes to guide their actions. METHODS: The method is illustrated by application to seventy-six anesthetized patients for which thirty-two fundamental and derived variables were recorded at 20-second intervals. The Iterative Order and Noise estimation algorithm (ION) estimated the noise on each parameter. The performance of principal components analysis (PCA) was improved by normalizing the noise estimated by ION to unity. A linear regression of the resulting seven high signal-to-noise ratio principal components (PC's) predicted tachycardia 140 seconds in advance. RESULTS: ION estimated the noise on each parameter with sufficient accuracy to increase the number of significant PC's from two to seven, all of which had identifiable physiological correlates. The resulting receiver operating characteristic (ROC) suggested that a 70 percent prediction rate with 5 percent false alarms could be achieved. CONCLUSIONS: This paper illustrates the use of ION to improve significantly the performance of PCA in the efficient representation of patient state and in improving the performance of linear predictors of clinically significant parameters.

Algorithms↗