Extracting statistically dominant modes of a steel truss bridge from vehicle-induced vibrations

This study is intended to investigate the validity of the stability diagram (SD) aided multivariate autoregressive (MAR) analysis for identifying modal parameters of a real truss bridge. The MAR models are adopted to fit the time series of the dynamic accelerations recorded from a number of observation points on the bridge; then the modal parameters are extracted from the MAR model coefficient matrix. The SD is adopted to determine statistically dominant modes. In plotting the SD, a number of stability criteria are further adopted for filtering out those modes with unstable modal parameters. By the present method, the first five modal frequencies and mode shapes are identified with very high precision, while the damping ratios are identified with high precision for the 1st mode but with poorer precision for higher modes. Moreover, the ability of the SD in selecting structural modes without getting involved in any model-order optimization problem is highlighted through a comparison study.

CD4+ T Cells Targeting Dominant and Cryptic Epitopes from Bacillus anthracis Lethal Factor

Anthrax is an endemic infection in many countries, particularly in the developing world. The causative agent, Bacillus anthracis, mediates disease through the secretion of binary exotoxins. Until recently, research into adaptive immunity targeting this bacterial pathogen has largely focused on the humoral response to these toxins. There is, however, growing recognition that cellular immune responses involving IFNγ producing CD4+ T cells also contribute significantly to a protective memory response. An established concept in adaptive immunity to infection is that during infection of host cells, new microbial epitopes may be revealed, leading to immune recognition of so called 'cryptic' or 'subdominant' epitopes. We analyzed the response to both cryptic and immunodominant T cell epitopes derived from the toxin component lethal factor and presented by a range of HLA-DR alleles. Using IFNγ-ELISpot assays we characterized epitopes that elicited a response following immunization with synthetic peptide and the whole protein and tested their capacities to bind purified HLA-DR molecules in vitro. We found that DR1 transgenics demonstrated T cell responses to a greater number of domain III cryptic epitopes than other HLA-DR transgenics, and that this pattern was repeated with the immunodominant epitopes, as a greater proportion of these epitopes induced a T cell response when presented within the context of the whole protein. Immunodominant epitopes LF457-476 and LF467-487 were found to induce a T cell response to the peptide, as well as to the whole native LF protein in DR1 and DR15, but not in DR4 transgenics. The analysis of Domain I revealed the presence of several unique cryptic epitopes all of which showed a strong to moderate relative binding affinity to HLA-DR4 molecules. However, none of the cryptic epitopes from either domain III or I displayed notably high binding affinities across all HLA-DR alleles assayed. These responses were influenced by the specific HLA alleles presenting the peptide, and imply that construction of future epitope string vaccines which are immunogenic across a wide range of HLA alleles could benefit from a combination of both cryptic and immunodominant anthrax epitopes.

Quantification of HER2 heterogeneity in breast cancer-implications for identification of sub-dominant clones for personalised treatment

Breast cancer is a heterogeneous disease, at both an inter- and intra-tumoural level. Appreciating heterogeneity through the application of biomarkers and molecular signatures adds complexity to tumour taxonomy but is key to personalising diagnosis, treatment and prognosis. The extent to which heterogeneity exists, and its interpretation remains a challenge to pathologists. Using HER2 as an exemplar, we have developed a simple reproducible heterogeneity index. Cell-to-cell HER2 heterogeneity was extensive in a proportion of both reported 'amplified' and 'non-amplified' cases. The highest levels of heterogeneity objectively identified occurred in borderline categories and higher ratio non-amplified cases. A case with particularly striking heterogeneity was analysed further with an array of biomarkers in order to assign a molecular diagnosis. Broad biological complexity was evident. In essence, interpretation, depending on the area of tumour sampled, could have been one of three distinct phenotypes, each of which would infer different therapeutic interventions. Therefore, we recommend that heterogeneity is assessed and taken into account when determining treatment options.