Close-Range Photogrammetric Measurement of Static Deflections for an Aeroelastic Supercritical Wing

Close range photogrammetric measurements were made for the lower wing surface of a full span aspect ratio 10.3 aeroelastic supercritical research wing. The measurements were made during wind tunnel tests for quasi-steady pressure distributions on the wing. The tests were conducted in the NASA Langley Transonic Dynamics Tunnel at Mach numbers up to 0.90 and dynamic pressures up to 300 pounds per square foot. Deflection data were obtained for 57 locations on the wing lower surface using dual non-metric cameras. Representative data are presented as graphical overview to show variations and trends of spar deflection with test variables. Comparative data are presented for photogrammetric and cathetometric results of measurements for the wing tip deflections. A tabulation of the basic measurements is presented in a supplement to this report

Interpreting Cancer Genomes Using Systematic Host Perturbations by Tumour Virus Proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations associated with cancer predisposition and large numbers of somatic genomic alterations. However, it remains challenging to distinguish between background, or “passenger” and causal, or “driver” cancer mutations in these datasets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. To test the hypothesis that genomic variations and tumour viruses may cause cancer via related mechanisms, we systematically examined host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways that go awry in cancer, such as Notch signalling and apoptosis. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches result in increased specificity for cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate prioritization of cancer-causing driver genes so as to advance understanding of the genetic basis of human cancer

NACA Technical Notes

Report presenting the results of a preliminary investigation of the effect of nonlinear structural terms on the flutter of a two-degree-of-freedom system. The three types of nonlinearities investigated were a flat spot, hysteresis, and a cubic spring. The results indicate that sometimes nonlinear effects can be large and destabilizing

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer