Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response

Identification of atypical flight patterns

Method and system for analyzing aircraft data, including multiple selected flight parameters for a selected phase of a selected flight, and for determining when the selected phase of the selected flight is atypical, when compared with corresponding data for the same phase for other similar flights. A flight signature is computed using continuous-valued and discrete-valued flight parameters for the selected flight parameters and is optionally compared with a statistical distribution of other observed flight signatures, yielding atypicality scores for the same phase for other similar flights. A cluster analysis is optionally applied to the flight signatures to define an optimal collection of clusters. A level of atypicality for a selected flight is estimated, based upon an index associated with the cluster analysis

Evaluation of SmartStax and SmartStax PRO Maize against Western Corn Rootworm and Northern Corn Rootworm: Efficacy and Resistance Management

Background: Cases of western corn rootworm (WCR) field-evolved resistance to Cry3Bb1 and other corn rootworm (CRW) control traits have been reported. Pyramid products expressing multiple CRW traits can delay resistance compared to single trait products. We used field studies to assess the pyramid CRW corn products, SmartStax (expressing Cry3Bb1 and Cry34Ab1/Cry35Ab1) and SmartStax PRO (expressing Cry3Bb1, Cry34Ab1/Cry35Ab1 and DvSnf7), at locations with high WCR densities and possible Cry3Bb1 resistance, and to assess the reduction in adult emergence attributable to DvSnf7 and other traits. Insect resistance models were used to assess durability of SmartStax and SmartStax PRO to WCR resistance. Results: SmartStax significantly reduced root injury compared to non-CRW-trait controls at all but one location with measurable WCR pressure, while SmartStax PRO significantly reduced root injury at all locations, despite evidence of Cry3Bb1 resistance at some locations. The advantage of SmartStax PRO over SmartStax in reducing root damage was positively correlated with root damage on non-CRW-trait controls. DvSnf7 was estimated to reduce WCR emergence by approximately 80–95%, which modeling indicated will improve durability of Cry3Bb1 and Cry34Ab1/Cry35Ab1 compared to SmartStax. Conclusion: The addition of DvSnf7 in SmartStax PRO can reduce root damage under high WCR densities and prolong Cry3Bb1 and Cry34Ab1/Cry35Ab1 durability

Genetically-Based Olfactory Signatures Persist Despite Dietary Variation

Individual mice have a unique odor, or odortype, that facilitates individual recognition. Odortypes, like other phenotypes, can be influenced by genetic and environmental variation. The genetic influence derives in part from genes of the major histocompatibility complex (MHC). A major environmental influence is diet, which could obscure the genetic contribution to odortype. Because odortype stability is a prerequisite for individual recognition under normal behavioral conditions, we investigated whether MHC-determined urinary odortypes of inbred mice can be identified in the face of large diet-induced variation. Mice trained to discriminate urines from panels of mice that differed both in diet and MHC type found the diet odor more salient in generalization trials. Nevertheless, when mice were trained to discriminate mice with only MHC differences (but on the same diet), they recognized the MHC difference when tested with urines from mice on a different diet. This indicates that MHC odor profiles remain despite large dietary variation. Chemical analyses of urinary volatile organic compounds (VOCs) extracted by solid phase microextraction (SPME) and analyzed by gas chromatography/mass spectrometry (GC/MS) are consistent with this inference. Although diet influenced VOC variation more than MHC, with algorithmic training (supervised classification) MHC types could be accurately discriminated across different diets. Thus, although there are clear diet effects on urinary volatile profiles, they do not obscure MHC effects

Information Display System for Atypical Flight Phase

Method and system for displaying information on one or more aircraft flights, where at least one flight is determined to have at least one atypical flight phase according to specified criteria. A flight parameter trace for an atypical phase is displayed and compared graphically with a group of traces, for the corresponding flight phase and corresponding flight parameter, for flights that do not manifest atypicality in that phase

Differentiation of Gram-Negative Bacterial Aerosol Exposure Using Detected Markers in Bronchial-Alveolar Lavage Fluid

The identification of biosignatures of aerosol exposure to pathogens has the potential to provide useful diagnostic information. In particular, markers of exposure to different types of respiratory pathogens may yield diverse sets of markers that can be used to differentiate exposure. We examine a mouse model of aerosol exposure to known Gram negative bacterial pathogens, Francisella tularensis novicida and Pseudomonas aeruginosa. Mice were subjected to either a pathogen or control exposure and bronchial alveolar lavage fluid (BALF) was collected at four and twenty four hours post exposure. Small protein and peptide markers within the BALF were detected by matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) and analyzed using both exploratory and predictive data analysis methods; principle component analysis and degree of association. The markers detected were successfully used to accurately identify the four hour exposed samples from the control samples. This report demonstrates the potential for small protein and peptide marker profiles to identify aerosol exposure in a short post-exposure time frame

Statistical Detection of Atypical Aircraft Flights

A computational method and software to implement the method have been developed to sift through vast quantities of digital flight data to alert human analysts to aircraft flights that are statistically atypical in ways that signify that safety may be adversely affected. On a typical day, there are tens of thousands of flights in the United States and several times that number throughout the world. Depending on the specific aircraft design, the volume of data collected by sensors and flight recorders can range from a few dozen to several thousand parameters per second during a flight. Whereas these data have long been utilized in investigating crashes, the present method is oriented toward helping to prevent crashes by enabling routine monitoring of flight operations to identify portions of flights that may be of interest with respect to safety issues

Comparison of Fluorescence Microscopy and Solid-Phase Cytometry Methods for Counting Bacteria in Water

Total direct counts of bacterial abundance are central in assessing the biomass and bacteriological quality of water in ecological and industrial applications. Several factors have been identified that contribute to the variability in bacterial abundance counts when using fluorescent microscopy, the most significant of which is retaining an adequate number of cells per filter to ensure an acceptable level of statistical confidence in the resulting data. Previous studies that have assessed the components of total-direct-count methods that contribute to this variance have attempted to maintain a bacterial cell abundance value per filter of approximately 10(6) cells filter(−1). In this study we have established the lower limit for the number of bacterial cells per filter at which the statistical reliability of the abundance estimate is no longer acceptable. Our results indicate that when the numbers of bacterial cells per filter were progressively reduced below 10(5), the microscopic methods increasingly overestimated the true bacterial abundance (range, 15.0 to 99.3%). The solid-phase cytometer only slightly overestimated the true bacterial abundances and was more consistent over the same range of bacterial abundances per filter (range, 8.9 to 12.5%). The solid-phase cytometer method for conducting total direct counts of bacteria was less biased and performed significantly better than any of the microscope methods. It was also found that microscopic count data from counting 5 fields on three separate filters were statistically equivalent to data from counting 20 fields on a single filter

In search of the chemical basis for MHC odourtypes

Mice can discriminate between chemosignals of individuals based solely on genetic differences confined to the major histocompatibility complex (MHC). Two different sets of compounds have been suggested: volatile compounds and non-volatile peptides. Here, we focus on volatiles and review a number of publications that have identified MHC-regulated compounds in inbred laboratory mice. Surprisingly, there is little agreement among different studies as to the identity of these compounds. One recent approach to specifying MHC-regulated compounds is to study volatile urinary profiles in mouse strains with varying MHC types, genetic backgrounds and different diets. An unexpected finding from these studies is that the concentrations of numerous compounds are influenced by interactions among these variables. As a result, only a few compounds can be identified that are consistently regulated by MHC variation alone. Nevertheless, since trained animals are readily able to discriminate the MHC differences, it is apparent that chemical studies are somehow missing important information underlying mouse recognition of MHC odourtypes. To make progress in this area, we propose a focus on the search for behaviourally relevant odourants rather than a random search for volatiles that are regulated by MHC variation. Furthermore, there is a need to consider a ‘combinatorial odour recognition’ code whereby patterns of volatile metabolites (the basis for odours) specify MHC odourtypes