Mean-value identities as an opportunity for Monte Carlo error reduction

In the Monte Carlo simulation of both lattice field theories and of models of statistical mechanics, identities verified by exact mean values, such as Schwinger-Dyson equations, Guerra relations, Callen identities, etc., provide well-known and sensitive tests of thermalization bias as well as checks of pseudo-random-number generators. We point out that they can be further exploited as control variates to reduce statistical errors. The strategy is general, very simple, and almost costless in CPU time. The method is demonstrated in the twodimensional Ising model at criticality, where the CPU gain factor lies between 2 and 4.

α-sarcin and RNase T1 based immunoconjugates: the role of intracellular trafficking in cytotoxic efficiency

Toxins have been thoroughly studied for their use as therapeutic agents in search of an improvement in toxic efficiency together with a minimization of their undesired side effects. Different studies have shown how toxins can follow different intracellular pathways which are connected with their cytotoxic action inside the cells. The work herein presented describes the different pathways followed by the ribotoxin a-sarcin and the fungal RNase T1,as toxic domains of immunoconjugates with identical binding domain, the single chain variable fragment of a monoclonal antibody raised against the glycoprotein A33. According to the results obtained both immunoconjugates enter the cells via early endosomes and, while a-sarcin can translocate directly into the cytosol to exert its deathly action, RNase T1 follows a pathway that involves lysosomes and the Golgi apparatus. These facts contribute to explaining the different cytotoxicity observed against their targeted cells, and reveal how the innate properties of the toxic domain, apart from its catalytic features, can be a key factor to be considered for immunotoxin optimization.