University of Milano-Bicocca

About: University of Milano-Bicocca is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Population & Blood pressure. The organization has 8972 authors who have published 22322 publications receiving 620484 citations. The organization is also known as: Università degli Studi di Milano-Bicocca & Universita degli Studi di Milano-Bicocca.

Minimal residual disease-directed risk stratification using real-time quantitative PCR analysis of immunoglobulin and T-cell receptor gene rearrangements in the international multicenter trial AIEOP-BFM ALL 2000 for childhood acute lymphoblastic leukemia.

Abstract: Detection of minimal residual disease (MRD) is the most sensitive method to evaluate treatment response and one of the strongest predictors of outcome in childhood acute lymphoblastic leukemia (ALL). The 10-year update on the I-BFM-SG MRD study 91 demonstrates stable results (event-free survival), that is, standard risk group (MRD-SR) 93%, intermediate risk group (MRD-IR) 74%, and high risk group (MRD-HR) 16%. In multicenter trial AIEOP-BFM ALL 2000, patients were stratified by MRD detection using quantitative PCR after induction (TP1) and consolidation treatment (TP2). From 1 July 2000 to 31 October 2004, PCR target identification was performed in 3341 patients: 2365 (71%) patients had two or more sensitive targets ( or =10(-3) at TP2), and 52% as MRD-IR. The remaining 823 patients were stratified according to clinical risk features: HR (n=108) and IR (n=715). In conclusion, MRD-PCR-based stratification using stringent criteria is feasible in almost 80% of patients in an international multicenter trial.

Determination of the X(3872) meson quantum numbers

Abstract: The quantum numbers of the X(3872) meson are determined to be J(PC) = 1(++) based on angular correlations in B+ -> X(3872)K+ decays, where X(3872) -> pi(+) pi(-) j/psi and J/psi -> pi(+) mu(-). The data correspond to 1.0 fb(-1) of pp collisions collected by the LHCb detector. The only alternative assignment allowed by previous measurements J(PC) = 2(-+) is rejected with a confidence level equivalent to more than 8 Gaussian standard deviations using a likelihood-ratio test in the full angular phase space. This result favors exotic explanations of the X(3872) state.

Cross-presentation of glycoprotein 96-associated antigens on major histocompatibility complex class I molecules requires receptor-mediated endocytosis.

Abstract: Heat shock proteins (HSPs) like glycoprotein (gp)96 (glucose-regulated protein 94 [grp94]) are able to induce specific cytotoxic T lymphocyte (CTL) responses against cells from which they originate. Here, we demonstrate that for CTL activation by gp96-chaperoned peptides, specific receptor-mediated uptake of gp96 by antigen-presenting cells (APCs) is required. Moreover, we show that in both humans and mice, only professional APCs like dendritic cells (DCs), macrophages, and B cells, but not T cells, are able to bind gp96. The binding is saturable and can be inhibited using unlabeled gp96 molecules. Receptor binding by APCs leads to a rapid internalization of gp96, which colocalizes with endocytosed major histocompatibility complex (MHC) class I and class II molecules in endosomal compartments. Incubation of gp96 molecules isolated from cells expressing an adenovirus type 5 E1B epitope with the DC line D1 results in the activation of E1B-specific CTLs. This CTL activation can be specifically inhibited by the addition of irrelevant gp96 molecules not associated with E1B peptides. Our results demonstrate that only receptor-mediated endocytosis of gp96 molecules leads to MHC class I–restricted re-presentation of gp96-associated peptides and CTL activation; non–receptor-mediated, nonspecific endocytosis is not able to do so. Thus, we provide evidence on the mechanisms by which gp96 is participating in the cross-presentation of antigens from cellular origin.

A general framework for updating belief distributions.

Abstract: We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such as a mean or median, it is cumbersome to have to achieve this via a complete model for the whole data distribution. More importantly, there are settings where the parameter of interest does not directly index a family of density functions and thus the Bayesian approach to learning about such parameters is currently regarded as problematic. Our framework uses loss functions to connect information in the data to functionals of interest. The updating of beliefs then follows from a decision theoretic approach involving cumulative loss functions. Importantly, the procedure coincides with Bayesian updating when a true likelihood is known yet provides coherent subjective inference in much more general settings. Connections to other inference frameworks are highlighted.

Recombinant Protein Production in Yeasts

Abstract: Recombinant protein production is a multibillion-dollar market. The development of a new product begins with the choice of a production host. While one single perfect host for every protein does not exist, several expression systems ranging from bacterial hosts to mammalian cells have been established. Among them, yeast cell factories combine the advantages of being single cells, such as fast growth and easy genetic manipulation, as well as eukaryotic features including a secretory pathway leading to correct protein processing and post-translational modifications. In this respect, especially the engineering of yeast glycosylation to produce glycoproteins of human-like glycan structures is of great interest. Additionally, different attempts of cellular engineering as well as the design of different production processes that are leading to improved productivities are presented. With the advent of cheaper next-generation sequencing techniques, systems biotechnology approaches focusing on genome scale analyses will advance and accelerate yeast cell factories and thus recombinant protein production processes in the near future. In this review we summarize advantages and limitations of the main and most promising yeast hosts, including Saccharomyces cerevisiae, Pichia pastoris, and Hansenula polymorpha as those presently used in large scale production of heterologous proteins.