A Multiantigenic DNA Vaccine That Induces Broad Hepatitis C Virus-Specific T-Cell Responses in Mice

There are 3 to 4 million new hepatitis C virus (HCV) infections annually around the world, but no vaccine is available. Robust T-cell mediated responses are necessary for effective clearance of the virus, and DNA vaccines result in a cell-mediated bias. Adjuvants are often required for effective vaccination, but during natural lytic viral infections damage-associated molecular patterns (DAMPs) are released, which act as natural adjuvants. Hence, a vaccine that induces cell necrosis and releases DAMPs will result in cell-mediated immunity (CMI), similar to that resulting from natural lytic viral infection. We have generated a DNA vaccine with the ability to elicit strong CMI against the HCV nonstructural (NS) proteins (3, 4A, 4B, and 5B) by encoding a cytolytic protein, perforin (PRF), and the antigens on a single plasmid. We examined the efficacy of the vaccines in C57BL/6 mice, as determined by gamma interferon enzyme-linked immunosorbent spot assay, cell proliferation studies, and intracellular cytokine production. Initially, we showed that encoding the NS4A protein in a vaccine which encoded only NS3 reduced the immunogenicity of NS3, whereas including PRF increased NS3 immunogenicity. In contrast, the inclusion of NS4A increased the immunogenicity of the NS3, NS4B, andNS5B proteins, when encoded in a DNA vaccine that also encoded PRF. Finally, vaccines that also encoded PRF elicited similar levels of CMI against each protein after vaccination with DNA encoding NS3, NS4A, NS4B, and NS5B compared to mice vaccinated with DNA encoding only NS3 or NS4B/5B. Thus, we have developed a promising ``multiantigen'' vaccine that elicits robust CMI. IMPORTANCE Since their development, vaccines have reduced the global burden of disease. One strategy for vaccine development is to use commercially viable DNA technology, which has the potential to generate robust immune responses. Hepatitis C virus causes chronic liver infection and is a leading cause of liver cancer. To date, no vaccine is currently available, and treatment is costly and often results in side effects, limiting the number of patients who are treated. Despite recent advances in treatment, prevention remains the key to efficient control and elimination of this virus. Here, we describe a novel DNA vaccine against hepatitis C virus that is capable of inducing robust cell-mediated immune responses in mice and is a promising vaccine candidate for humans.

A hybrid method for stochastic response analysis of a vibrating structure

Response analysis of a linear structure with uncertainties in both structural parameters and external excitation is considered here. When such an analysis is carried out using the spectral stochastic finite element method (SSFEM), often the computational cost tends to be prohibitive due to the rapid growth of the number of spectral bases with the number of random variables and the order of expansion. For instance, if the excitation contains a random frequency, or if it is a general random process, then a good approximation of these excitations using polynomial chaos expansion (PCE) involves a large number of terms, which leads to very high cost. To address this issue of high computational cost, a hybrid method is proposed in this work. In this method, first the random eigenvalue problem is solved using the weak formulation of SSFEM, which involves solving a system of deterministic nonlinear algebraic equations to estimate the PCE coefficients of the random eigenvalues and eigenvectors. Then the response is estimated using a Monte Carlo (MC) simulation, where the modal bases are sampled from the PCE of the random eigenvectors estimated in the previous step, followed by a numerical time integration. It is observed through numerical studies that this proposed method successfully reduces the computational burden compared with either a pure SSFEM of a pure MC simulation and more accurate than a perturbation method. The computational gain improves as the problem size in terms of degrees of freedom grows. It also improves as the timespan of interest reduces.

Ray tracing based path-length calculations for polarized light tomographic imaging

A ray tracing based path length calculation is investigated for polarized light transport in a pixel space. Tomographic imaging using polarized light transport is promising for applications in optical projection tomography of small animal imaging and turbid media with low scattering. Polarized light transport through a medium can have complex effects due to interactions such as optical rotation of linearly polarized light, birefringence, diattenuation and interior refraction. Here we investigate the effects of refraction of polarized light in a non-scattering medium. This step is used to obtain the initial absorption estimate. This estimate can be used as prior in Monte Carlo (MC) program that simulates the transport of polarized light through a scattering medium to assist in faster convergence of the final estimate. The reflectance for p-polarized (parallel) and s-polarized (perpendicular) are different and hence there is a difference in the intensities that reach the detector end. The algorithm computes the length of the ray in each pixel along the refracted path and this is used to build the weight matrix. This weight matrix with corrected ray path length and the resultant intensity reaching the detector for each ray is used in the algebraic reconstruction (ART) method. The proposed method is tested with numerical phantoms for various noise levels. The refraction errors due to regions of different refractive index are discussed, the difference in intensities with polarization is considered. The improvements in reconstruction using the correction so applied is presented. This is achieved by tracking the path of the ray as well as the intensity of the ray as it traverses through the medium.