Leishmania donovani: Immunostimulatory Cellular Responses of Membrane and Soluble Protein Fractions of Splenic Amastigotes in Cured Patient and Hamsters

Visceral leishmaniasis (VL), caused by the intracellular parasite Leishmania donovani, L. chagasi and L. infantum is characterized by defective cell-mediated immunity (CMI) and is usually fatal if not treated properly. An estimated 350 million people worldwide are at risk of acquiring infection with Leishmania parasites with approximately 500,000 cases of VL being reported each year. In the absence of an efficient and cost-effective antileishmanial drug, development of an appropriate long-lasting vaccine against VL is the need of the day. In VL, the development of a CMI, capable of mounting Th1-type of immune responses, play an important role as it correlate with recovery from and resistance to disease. Resolution of infection results in lifelong immunity against the disease which indicates towards the feasibility of a vaccine against the disease. Most of the vaccination studies in Leishmaniasis have been focused on promastigote- an infective stage of parasite with less exploration of pathogenic amastigote form, due to the cumbersome process of its purified isolation. In the present study, we have isolated and purified splenic amastigotes of L. donovani, following the traditional protocol with slight modification. These were fractionated into five membranous and soluble subfractions each i.e MAF1-5 and SAF1-5 and were subjected for evaluation of their ability to induce cellular responses. Out of five sub-fractions from each of membrane and soluble, only four viz. MAF2, MAF3, SAF2 and SAF3 were observed to stimulate remarkable lymphoproliferative, IFN-γ, IL-12 responses and Nitric Oxide production, in Leishmania-infected cured/exposed patients and hamsters. Results suggest the presence of Th-1 type immunostimulatory molecules in these sub-fractions which may further be exploited for developing a successful subunit vaccine from the less explored pathogenic stage against VL

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Design des neuronalen Netzes als Prädiktor für die physikalischen Eigenschaften von Mandeln

In this study, an adaptive neuro fuzzy interface system (ANFIS) based predictor was designed to predict the physical properties of four almond types. Measurements of the dimensions, length, width and thickness were carried out for one hundred randomly selected samples of each type. With using these three major perpendicular dimensions, some physical parameters such as projected area, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, shape index and aspect ratio were estimated. In in a various Artificial Neural Network (ANN) structures, ANFIS structure which has given the best results was selected. The parameters analytically estimated and those predicted were given in the form of figures. The root mean-squared error (RMSE) was found to be 0.0001 which is quite low. ANFIS approach has given a superior outcome in the prediction of the Physical Properties of Almond Nuts