Vaccines against toxoplasma gondii : challenges and opportunities

Development of vaccines against Toxoplasma gondii infection in humans is of high priority, given the high burden of disease in some areas of the world like South America, and the lack of effective drugs with few adverse effects. Rodent models have been used in research on vaccines against T. gondii over the past decades. However, regardless of the vaccine construct, the vaccines have not been able to induce protective immunity when the organism is challenged with T. gondii, either directly or via a vector. Only a few live, attenuated T. gondii strains used for immunization have been able to confer protective immunity, which is measured by a lack of tissue cysts after challenge. Furthermore, challenge with low virulence strains, especially strains with genotype II, will probably be insufficient to provide protection against the more virulent T. gondii strains, such as those with genotypes I or II, or those genotypes from South America not belonging to genotype I, II or III. Future studies should use animal models besides rodents, and challenges should be performed with at least one genotype II T. gondii and one of the more virulent genotypes. Endpoints like maternal-foetal transmission and prevention of eye disease are important in addition to the traditional endpoint of survival or reduction in numbers of brain cysts after challenge

Fast and robust common-reflection-surface parameter estimation

The common-reflection-surface (CRS) method offers a stack with higher signal-to-noise ratio at the cost of a time-consuming semblance search to obtain the stacking parameters. We have developed a fast method for extracting the CRS parameters using local slope and curvature. We estimate the slope and curvature with the gradient structure tensor and quadratic structure tensor on stacked data. This is done under the assumption that a stacking velocity is already available. Our method was compared with an existing slope-based method, in which the slope is extracted from prestack data. An experiment on synthetic data shows that our method has increased robustness against noise compared with the existing method. When applied to two real data sets, our method achieves accuracy comparable with the pragmatic and full semblance searches. Our method has the advantage of being approximately two and four orders of magnitude faster than the semblance searches. This research was originally published in Geophysics. © Society of Exploration Geophysicists. Redistribution subject to SEG license or copyright

Fast estimation of prestack common reflection surface parameters

We present a method for fast estimation of finite offset common reflection surface parameters. Firstly, the derivatives with respect to offset are derived from the velocity guide. Secondly, we apply structure tensors to extract the derivatives with respect to midpoint from stacked common offset sections. Finally, the mixed derivative is estimated using a one‐parametric semblance search. The proposed method is compared to the global five‐parametric semblance search and the pragmatic sequential two‐parametric semblance search on one synthetic and one real data set. The experiments show that the proposed method is more robust against noise than the pragmatic search and have comparable robustness with the global search. The proposed method smoothes parameter estimates in a local window, and the window size is set to give the best trade‐off between detail and robustness. Since the proposed method is dependent on a velocity guide, the quality of the other parameter estimates may be influenced by any inaccuracies in the guide. The main advantage of the proposed method is the computational efficiency. When compared with a gridded implementation of the semblance search, the proposed method is 10 and 400 times faster than the pragmatic and global search. Alternative search strategies significantly reduce the computational cost of the global search. However, since more than 99% of the computational cost of the proposed method comes from the semblance search to estimate the mixed derivative, it is expected that such techniques also reduce the computational cost for the proposed method67511631183The work was funded by the Norwegian Research Council, Grant 234019. This work was partly conducted while Anders U. Waldeland was visiting Martin Tygel's group of applied geophysics (GGA) at CEPETRO at the University of Campinas, Brazi