Lithium chloride therapy fails to improve motor function in a transgenic mouse model of Machado-Joseph disease

The accumulation of misfolded proteins in neurons, leading to the formation of cytoplasmic and nuclear aggregates, is a common theme in age-related neurodegenerative diseases, possibly due to disturbances of the proteostasis and insufficient activity of cellular protein clearance pathways. Lithium is a well-known autophagy inducer that exerts neuroprotective effects in different conditions and has been proposed as a promising therapeutic agent for several neurodegenerative diseases. We tested the efficacy of chronic lithium 10.4 mg/kg) treatment in a transgenic mouse model of Machado-Joseph disease, an inherited neurodegenerative disease, caused by an expansion of a polyglutamine tract within the protein ataxin-3. A battery of behavioral tests was used to assess disease progression. In spite of activating autophagy, as suggested by the increased levels of Beclin-1, Atg7, and LC3II, and a reduction in the p62 protein levels, lithium administration showed no overall beneficial effects in this model concerning motor performance, showing a positive impact only in the reduction of tremors at 24 weeks of age. Our results do not support lithiumchronic treatment as a promising strategy for the treatment of Machado-Joseph disease (MJD).FCT -Fundação para a Ciência e a Tecnologia(SFRH/BD/51059/2010

A Personalized Framework for Dynamic Modeling of Disease Trajectories in Chronic Lymphocytic Leukemia

Chronic Lymphocytic Leukemia (CLL) is the most common peripheral blood and bone marrow cancer in the developed world. This manuscript proposes mathematical model equations representing the disease dynamics of B-cell CLL. We interconnect delay differential cell cycle models in each of the tumor-involved disease centers using physiologically-relevant cell migration. We further introduce 5 hypothetical case studies representing CLL heterogeneity commonly seen in clinical practice and demonstrate how the proposed CLL model framework may capture disease pathophysiology across patient types. We conclude by exploring the capacity of the proposed temporally- and spatially-distributed model to capture the heterogeneity of CLL disease progression. By using Global Sensitivity Analysis, the critical parameters influencing disease trajectory over space and time are: (i) the initial number of CLL cells in peripheral blood, the number of involved lymph nodes, the presence and degree of splenomegaly; (ii) the migratory fraction of nonproliferating as well as proliferating CLL cells from bone marrow into blood and of proliferating CLL cells from blood into lymph nodes; (iii) the parameters inducing nonproliferative cells to proliferate. The proposed model offers a practical platform which may be explored in future personalized patient protocols once validated

System architecture for personalized automatic audio-visual content generation from Web feeds to an iTV platform

Fulfilling informational needs of seniors is vital for a successful development of active ageing and independent living initiatives, which contribute for an effective provision of welfare benefits tailored for these citizens. This paper aims to propose a system architecture for automated generation of audio-visual contents adapted from Web feeds of information about Assistance Services of General Interest for Elderly (ASGIE). These pieces of high-value generated content are tailored to the seniors’ requirements, needs and expectations, for further exhibition on an iTV platform. Also, this paper describes the technical choices leading to a prototype implementation developed in the context of +TV4E project, an ongoing research project of an iTV platform to enrich seniors television experience with the integration of informative content. Future work will involve submitting this prototype and the generated contents to field tests at seniors’ home environment

Evolution of control with learning classifier systems

Abstract In this paper we describe the application of a learning classifier system (LCS) variant known as the eXtended classifier system (XCS) to evolve a set of ‘control rules’ for a number of Boolean network instances. We show that (1) it is possible to take the system to an attractor, from any given state, by applying a set of ‘control rules’ consisting of ternary conditions strings (i.e. each condition component in the rule has three possible states; 0, 1 or #) with associated bit-flip actions, and (2) that it is possible to discover such rules using an evolutionary approach via the application of a learning classifier system. The proposed approach builds on learning (reinforcement learning) and discovery (a genetic algorithm) and therefore the series of interventions for controlling the network are determined but are not fixed. System control rules evolve in such a way that they mirror both the structure and dynamics of the system, without having ‘direct’ access to either

A Sentiment-Based Hotel Review Summarization Using Machine Learning Techniques

Part 2: 9th Mining Humanistic Data WorkshopInternational audienceWith the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. In this paper, we examine the problem of classifying hotel critiques using views expressed in users’ reviews. There is a massive development of opinions and reviews on the web, which invariably include assessments of products and services, and beliefs about events and persons. In this study, we aim to face the problem of the forever increasing amount of opinionated data that is published in a variety of data sources. The intuition is the extraction of meaningful services despite the lack of sufficient existing architectures. Another important aspect that needs to be taken into consideration when dealing with brand monitoring, relates to the rapid heterogeneous data processing, which is vital to be implemented in real-time in order for the business to react in a more immediate way