TArC: Incrementally and semi-automatically collecting a Tunisian arabish corpus

This article describes the constitution process of the first morpho-syntactically annotated Tunisian Arabish Corpus (TArC). Arabish, also known as Arabizi, is a spontaneous coding of Arabic dialects in Latin characters and arithmographs (numbers used as letters). This code-system was developed by Arabic-speaking users of social media in order to facilitate the writing in the Computer-Mediated Communication (CMC) and text messaging informal frameworks. There is variety in the realization of Arabish amongst dialects, and each Arabish code-system is under-resourced, in the same way as most of the Arabic dialects. In the last few years, the focus on Arabic dialects in the NLP field has considerably increased. Taking this into consideration, TArC will be a useful support for different types of analyses, computational and linguistic, as well as for NLP tools training. In this article we will describe preliminary work on the TArC semi-automatic construction process and some of the first analyses we developed on TArC. In addition, in order to provide a complete overview of the challenges faced during the building process, we will present the main Tunisian dialect characteristics and their encoding in Tunisian Arabish

Label-Dependencies Aware Recurrent Neural Networks

In the last few years, Recurrent Neural Networks (RNNs) have proved effective on several NLP tasks. Despite such great success, their ability to model \emph{sequence labeling} is still limited. This lead research toward solutions where RNNs are combined with models which already proved effective in this domain, such as CRFs. In this work we propose a solution far simpler but very effective: an evolution of the simple Jordan RNN, where labels are re-injected as input into the network, and converted into embeddings, in the same way as words. We compare this RNN variant to all the other RNN models, Elman and Jordan RNN, LSTM and GRU, on two well-known tasks of Spoken Language Understanding (SLU). Thanks to label embeddings and their combination at the hidden layer, the proposed variant, which uses more parameters than Elman and Jordan RNNs, but far fewer than LSTM and GRU, is more effective than other RNNs, but also outperforms sophisticated CRF models.Comment: 22 pages, 3 figures. Accepted at CICling 2017 conference. Best Verifiability, Reproducibility, and Working Description awar

3D X-ray microscopy (XRM) investigation of exogenous materials inside mussels’ organs

The diffusion of pollutants in the marine environment is nowadays a well-recognized issue that is attracting growing interest from the scientific and social communities. One of the possible strategies to study the effect of pollutants is to quantify their presence inside marine organisms that are directly exposed for a certain period to the polluted environment. Among them, mussels, commonly considered as “biological water filters”, stand out as ideal candidates since they are stationary animals and their food intake comes only from the filtering of the surrounding water. Thus, the evaluation of the accumulation of exogenous pollutants, in particular high-density or metallic, inside the mussel's organs and specifically in its digestive glands, is of particular interest. In this paper we characterize the accumulation of exogenous materials in digestive glands of three different mussels by means of X-ray microscopy analysis. We provide evidence of how the unique capabilities of this technique allow reconstructing a full 3D image of an entire organ and how this image can provide valuable information to identify exogenous (non-biological) pollutants. Moreover, we take full advantage from the segmentation analysis of the images by discriminating different regions of the sample according to the density. With this experimental approach we measured the sizes of the exogenous pollutants and provided evidences that they accumulate preferentiality in the low-density regions of the organ, that are richer in ducts and secretive glands

One- and two-electron oxidations of β-amyloid25-35 by carbonate radical anion (CO3•-) and peroxymonocarbonate (HCO4-): role of sulfur in radical reactions and peptide aggregation

The β-amyloid (Aβ) peptide plays a key role in the pathogenesis of Alzheimer's disease. The methionine (Met) residue at position 35 in Aβ C-terminal domain is critical for neurotoxicity, aggregation, and free radical formation initiated by the peptide. The role of Met in modulating toxicological properties of Aβ most likely involves an oxidative event at the sulfur atom. We therefore investigated the one- or two-electron oxidation of the Met residue of Aβ25-35 fragment and the effect of such oxidation on the behavior of the peptide. Bicarbonate promotes two-electron oxidations mediated by hydrogen peroxide after generation of peroxymonocarbonate (HCO4-, PMC). The bicarbonate/carbon dioxide pair stimulates one-electron oxidations mediated by carbonate radical anion (CO3•-). PMC efficiently oxidizes thioether sulfur of the Met residue to sulfoxide. Interestingly, such oxidation hampers the tendency of Aβ to aggregate. Conversely, CO3•- causes the one-electron oxidation of methionine residue to sulfur radical cation (MetS•+). The formation of this transient reactive intermediate during Aβ oxidation may play an important role in the process underlying amyloid neurotoxicity and free radical generation

A rapid unravelling of mycobacterial activity and of their susceptibility to antibiotics

The development of antibiotic-resistant bacteria is a worldwide health-related emergency that calls for new tools to study the bacterial metabolism and to obtain fast diagnoses. Indeed, the conventional analysis timescale is too long and affects our ability to fight infections. Slowly growing bacteria represent a bigger challenge, since their analysis may require up to months. Among these bacteria, Mycobacterium tuberculosis, the causative agent of tuberculosis has caused, only in 2016 more than 10 million new cases and 1.7 million deaths. We employed a particularly powerful nanomechanical oscillator, the nanomotion sensor, to characterize rapidly and in real time a tuberculous and a non-tuberculous bacterial species, Bacillus Calmette-Guérin and Mycobacterium abscessus exposed to different antibiotics. Here, we show how high speed and high sensitivity detectors, the nanomotion sensors, can provide a rapid and reliable analysis of different mycobacterial species, obtaining qualitative and quantitative information on their response to different drugs.Consiglio Nazionale delle Ricerche and Swiss National Grants 200021-144321 and 407240-167137 The Gerbert Ruf Stiftung GRS-024/1

Nanotools and molecular techniques to rapidly identify and fight bacterial infections

Reducing the emergence and spread of antibiotic-resistant bacteria is one of the major healthcare issues of our century. In addition to the increased mortality, infections caused by multi-resistant bacteria drastically enhance the healthcare costs, mainly because of the longer duration of illness and treatment. While in the last 20 years, bacterial identification has been revolutionized by the introduction of new molecular techniques, the current phenotypic techniques to determine the susceptibilities of common Gram-positive and Gram-negative bacteria require at least two days from collection of clinical samples. Therefore, there is an urgent need for the development of new technologies to determine rapidly drug susceptibility in bacteria and to achieve faster diagnoses. These techniques would also lead to a better understanding of the mechanisms that lead to the insurgence of the resistance, greatly helping the quest for new antibacterial systems and drugs. In this review, we describe some of the tools most currently used in clinical and microbiological research to study bacteria and to address the challenge of infections. We discuss the most interesting advancements in the molecular susceptibility testing systems, with a particular focus on the many applications of the MALDI-TOF MS system. In the field of the phenotypic characterization protocols, we detail some of the most promising semi-automated commercial systems and we focus on some emerging developments in the field of nanomechanical sensors, which constitute a step towards the development of rapid and affordable point-of-care testing devices and techniques. While there is still no innovative technique that is capable of completely substituting for the conventional protocols and clinical practices, many exciting new experimental setups and tools could constitute the basis of the standard testing package of future microbiological tests. (C) 2016 Elsevier B.V. All rights reserved

Multivariate analysis of mean Raman spectra of erythrocytes for a fast analysis of the biochemical signature of ageing

Ageing of red blood cells (RBC) is a physiological process, fundamental to ensure a proper blood homeostasis that, in vivo, balances the production of new cells and the removal of senescent erythrocytes. A detailed characterization at the cellular level of the progression of the ageing phenomenon can reveal biological, biophysical and biochemical fingerprints for diseases related to misbalances of the cell turnover and for blood pathologies. We applied Principal Components Analysis (PCA) to mean Raman spectra of single cells at different ageing times to rapidly highlight subtle spectral differences associated with conformational and biochemical modifications. Our results demonstrate a two-step ageing process characterized by a first phase in which proteins plays a relevant role, followed by a further cellular evolution driven by alterations in the membrane lipid contribution. Moreover, we used the same approach to directly analyse relevant spectral effects associated to reduction in Haemoglobin oxygenation level and membrane fluidity induced by the ageing. The method is robust and effective, allowing to classify easily the studied cells based on their age and morphology, and consequently to evaluate the biological quality of a blood sample

Nanoscale characterization methods in plant disease management

Climate change, pests and disease are frequent causes of crop losses or severe yield potential reduction, while increasing food demand is calling for a more efficient management in agricultural systems. Identifying and correctly characterizing biotic or abiotic stress sources is a fundamental step for the improvement of agricultural practices. In particular, high resolution and high sensitivity techniques are needed in order to allow better analysis and quantification of pathogens and other stress causes. In this context, nanotechnologies are emerging as a set of viable tools and approaches to increase the level of knowledge and eventually allow a better management of plant diseases. The wide family of scanning probe microscopes (mainly for morphological, mechanical and chemical characterizations), scanning and transmission electron microscopy techniques, along with methods based on nanomaterials (quantum dots, nanobiosensors, carbon nanomaterials and other nanosized structures) have demonstrated higher sensitivity in many cases even with reduced investigation times, thus exploiting research possibilities. In this chapter an overview of the most recent and interesting nanoscale characterization methods is provided, along with some specific applicative examples and results from case studies