School bus safety - operator age in relation to school bus accidents. Final report.

National Highway Safety Bureau, Washington, D.C.Mode of access: Internet.COP: 2Author corporate affiliation: Dunlap and Associates, Inc., Darien, Conn.Subject code: DEDSSubject code: EABSubject code: JL

The tec kinase-regulated phosphoproteome reveals a mechanism for the regulation of inhibitory signals in murine macrophages

Previous work has shown conflicting roles for Tec family kinases in regulation of Toll-like receptor (TLR)-dependent signalling in myeloid cells. In the present study, we performed a detailed investigation of the role of Btk and Tec kinases in regulating TLR signalling in several types of primary murine macrophages. We demonstrate that primary resident peritoneal macrophages deficient for Btk and Tec secrete less pro-inflammatory cytokines in response to TLR stimulation than wild type cells. In contrast, we found that bone marrow-derived and thioglycollate-elicited peritoneal macrophages deficient for Btk and Tec secrete more pro-inflammatory cytokines than wild type cells. We then compared the phosphoproteome regulated by Tec kinases and lipopolysaccharide in primary peritoneal and bone marrow derived macrophages. From this analysis we determined that Tec kinases regulate different signalling programs in these cell types. In additional studies using bone marrow-derived macrophages, we find that Tec and Btk promote phosphorylation events necessary for immunoreceptor-mediated inhibition of TLR signalling. Taken together, our results are consistent with a model where Tec kinases (Btk, Tec, Bmx) are required for TLR-dependent signalling in many types of myeloid cells. However, our data also support a cell type-specific TLR-inhibitory role for Btk and Tec that is mediated by immunoreceptor activation and signalling via PI3K

Lung Cancer Staging in the Genomics Era

The search for clinically applicable biologic markers or tumor signatures sufficiently powered as prognosticators of tumor behaviors or responses to therapeutic interventions has significantly advanced in scope and sophistication in the last 10 years. The TNM system, examining of tumor tissues to identify histopathologic features that could be correlated with tumor biology and outcome, could be improved by the immunohistochemical assessment of individual marker proteins or painstaking sequencing of candidate genes (one at a time) from tumor tissues. Large-scale investigation of the gene or protein expression profiles using genomics or proteomics technology may further improve risk stratification and assessment of therapeutic response. Although the gene expression profiling studies summarized in this article are exciting and initially serve as proofs of concept that large-scale mining of the genome and the transcriptome yields clinically useful data, the technology is still evolving and standardization is still needed for large-scale studies and data validation. As a proof of principle, studies have been performed to demonstrate that it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study, and to demonstrate significant, albeit incomplete, agreement of gene expression patterns related to lung cancer biology and predictive of treatment outcomes via cross-study comparative analysis. Leading the concerted efforts of molecular characterization of lung cancer is the National Cancer Institute Director's Challenge Program: Toward A Molecular Classification of Cancer. The ultimate goal of molecular staging, envisioned as a combination of traditional TNM classification bolstered with gene/protein unique expression signatures, is to classify patients who have lung cancer on the basis of tumor biology, for better risk stratification and treatment using targeted patient-tailored therapeutics based on unique genotypes of individual tumors