The aim of this study to evaluate the expression Programmed cell death-1 (PD-1), TGF- ß, and IL-10 in placental tissue aborted women correlation with Toxoplasma.gondii (T. gondii) these cytokines each other toxoplasmosis, during an abortion. samples have been processed used for immunohistochemistry PDL-1, IL-10, TGF-β. There was increase TGF-β, infected T.gondii, results showed that residence p...

Background: Toxoplasma gondii is an obligate intracellular parasite, which affects a wide-range of mammals including human. Based on serological studies, T. gondii is one of the most prevalent protozoan parasites. Most cases of toxoplasmosis are asymptomatic or mild and influenza-like, but immunocompromised patients often develop fulminating life-threatening symptoms as pneumonia and encephalit...

Toxoplasma gondii is a globally distributed zoonotic protozoan parasite. Infection with T. can cause congenital toxoplasmosis in developing fetuses and acute outbreaks the general population, disease burden especially high South America. Prior studies found that environmental stage of gondii, oocysts, an important source infection Brazil; however, no have quantified this risk relative to other ...

Introduction: Toxoplasma gondii is a protozoan parasite with relatively high prevalence in human societies. Due to the lack of information on toxoplasmosis infection in school-aged children in Bojnord, the present study aimed to assess the prevalence of toxoplasmosis in school-age students and the level of vitamin D3 deficiency in them in Bojnurd, Northeast of Iran. Method: In this cross-secti...

Toxoplasmosis is a parasitic infection with public health importance. The aim of this study was to determine the seroprevalence toxoplasmosis and its risk factors among pregnant women consulted at Bamenda Regional Hospital.

This thesis explores approaches towards learning with kernel methods using prior knowledge. Invariant learning with kernel methods is considered in more details. In the first part of the thesis, kernels are developed which incorporate prior knowledge on invariant transformations. Next, algorithms which specifically include prior knowledge are considered. An algorithm which linearly classifies d...

The performance of a natural language system trained on one domain often drops significantly when testing on another domain. Therefore, the problem of domain adaptation remains one of the most important natural language processing challenges. While many different domain adaptation frameworks have been proposed, they have ignored one natural resource – the prior knowledge on the new domain. In t...

We study the problem of compressed sensing with asymmetric prior information, as motivated by networking applications. We focus on the scenario in which a resource-limited encoder needs to report a small subset S from a universe of N objects to a more powerful decoder. The distinguishing feature of our model is asymmetry: the subset S is an i.i.d. sample from a prior distribution μ, and μ is on...

Classical approaches to shape correspondence base their computation purely on the properties, in particular geometric similarity, of the shapes in question. Their performance still falls far short of that of humans in challenging cases where corresponding shape parts may differ significantly in geometry or even topology. We stipulate that in these cases, shape correspondence by humans involves ...