Linguistic Knowledge Can Enhance Encoder-Decoder Models (If You Let It)

In this paper, we explore the impact of augmenting pre-trained Encoder-Decoder models, specifically T5, with linguistic knowledge for the prediction of a target task. In particular, we investigate whether fine-tuning a T5 model on an intermediate task that predicts structural linguistic properties of sentences modifies its performance in the target task of predicting sentence-level complexity. Our study encompasses diverse experiments conducted on Italian and English datasets, employing both monolingual and multilingual T5 models at various sizes. Results obtained for both languages and in cross-lingual configurations show that linguistically motivated intermediate fine-tuning has generally a positive impact on target task performance, especially when applied to smaller models and in scenarios with limited data availability.Comment: Accepted to LREC-COLING 202

Low frequency follow up of radio halos and relics in the GMRT Radio Halo Cluster Survey

We performed GMRT low frequency observations of the radio halos, relics and new candidates belonging to the GMRT Radio Halo Cluster Sample first observed at 610 MHz. High sensitivity imaging was performed using the GMRT at 325 MHz and 240 MHz. The properties of the diffuse emission in each cluster were compared to our 610 MHz images and/or literature information available at other frequencies, in order to derive the integrated spectra over a wide frequency range.Beyond the classical radio halos, whose spectral index $\alpha$ is in the range $\sim1.2\div1.3$ (S$\propto\nu^{-\alpha}$), we found sources with $\alpha\sim1.6\div1.9$. This result supports the idea that the spectra of the radiating particles in radio halos is not universal, and that inefficient mechanisms of particle acceleration are responsible for their origin. We also found a variety of brightness distributions, i.e. centrally peaked as well as clumpy halos. Even though the thermal and relativistic plasma tend to occupy the same cluster volume, in some cases a positional shift between the radio and X-ray peaks of emission is evident. Our observations also revealed the existence of diffuse cluster sources which cannot be easily classified either as halos or relics. New candidate relics were found in A1300 and in A1682, and in some clusters "bridges" of radio emission have been detected, connecting the relic and radio halo emission. Combining our new data with literature information, we derived the LogL$_{\rm X}$-LogP$_{\rm 325 MHz}$ correlation for radio halos, and investigated the possible trend of the spectral index of radio halos with the temperature of the intracluster medium.Comment: 19 pages, 10 figures, 5 tables, accepted for publication on A&

READ-IT: assessing readability of Italian texts with a view to text simplification

In this paper, we propose a new approach to readability assessment with a specific view to the task of text simplification: the intended audience includes people with low literacy skills and/or with mild cognitive impairment. READ-IT represents the first advanced readability assessment tool for what concerns Italian, which combines traditional raw text features with lexical, morpho-syntactic and syntactic information. In READ-IT readability assessment is carried out with respect to both documents and sentences where the latter represents an important novelty of the proposed approach creating the prerequisites for aligning the readability assessment step with the text simplification process. READ-IT shows a high accuracy in the document classification task and promising results in the sentence classification scenario

ULISSE: an unsupervised algorithm for detecting reliable dependency parses

In this paper we present ULISSE, an unsupervised linguistically--driven algorithm to select reliable parses from the output of a dependency parser. Different experiments were devised to show that the algorithm is robust enough to deal with the output of different parsers and with different languages, as well as to be used across different domains. In all cases, ULISSE appears to outperform the baseline algorithms

The impact of ST6Gal-I in the progression of colorectal cancer

One of the hallmarks associated with cancer is an aberrant expression of glycans decorating the plasma membrane due to altered expression of glycosyltransferases. The elevation of sialyltransferase ST6Gal-I and of its cognate glycan structure Sia6LacNAc has been described in colon and other cancers and controversially associated with malignancy. In this study, we investigated the relationship between ST6Gal-I mRNA expression and clinical features in a cohort of over 600 colorectal cancer (CRC) cases on The Cancer Genome Atlas, finding that low ST6Gal-I expression was associated with a microsatellite unstable and mucinous phenotype, and with BRAF mutation, but not with clinical stage or survival. To investigate the effect of ST6Gal-I overexpression on CRC, we retrovirally transduced with the human ST6Gal-I cDNA or with an empty vector the cell lines SW48 (microsatellite unstable) and SW948 (chromosomal unstable), generating their ST and NC variants respectively. Transcriptomic analysis of the two cell lines revealed a higher number of modulated genes in SW948 ST compared with SW48 ST. SW948 ST (but not SW48 ST) displayed an accelerated apoptotic response compared to NC, while SW948 ST (but not SW48 ST) displayed increased ability to heal the wound than SW948 NC. In soft agar assay, SW948 ST (but not SW48 ST) cells generated fewer clones, although bigger, than SW948 NC. SW48 ST (but not SW948 ST) displayed a reduced capacity to invade Matrigel compared to NC. Treatment with HGF caused an increase of FAK phosphorylation in SW948 NC cells and a decrease in ST cells. Similar results were observed in SW48 NC and ST cells. With ALDH staining we observed a population of cancer stem cells in the two cell lines with no differences derived from ST6Gal-I overexpression. These results indicate a very cell type specific effect of ST6GAL1 and Sia6LacNAc on the phenotype of CRC cells

The mechanism of killing by the proline-rich peptide Bac7(1-35) against clinical strains of Pseudomonas aeruginosa differs from that against other gram-negative bacteria

Pseudomonas aeruginosa infections represent a serious threat to worldwide health. Proline-rich antimicrobial peptides (PR-AMPs), a particular group of peptide antibiotics, have demonstrated in vitro activity against P. aeruginosa strains. Here we show that the mammalian PR-AMP Bac7(1\u201335) is active against some multidrug-resistant cystic fibrosis isolates of P. aeruginosa. By confocal microscopy and cytometric analyses, we investigated the mechanism of killing against P. aeruginosa strain PAO1 and three selected isolates, and we observed that the peptide inactivated the target cells by disrupting their cellular membranes. This effect is deeply different from that previously described for PR-AMPs in Escherichia coli and Salmonella enterica serovar Typhimurium, where these peptides act intracellularly after having been internalized by means of the transporter SbmA without membranolytic effects. The heterologous expression of SbmA in PAO1 cells enhanced the internalization of Bac7(1\u201335) into the cytoplasm, making the bacteria more susceptible to the peptide but at the same time more resistant to the membrane lysis, similarly to what occurs in E. coli. The results evidenced a new mechanism of action for PRAMPs and indicate that Bac7 has multiple and variable modes of action that depend on the characteristics of the different target species and the possibility to be internalized by bacterial transporters. This feature broadens the spectrum of activity of the peptide and makes the development of peptide-resistant bacteria a more difficult process

Pulmonary embolism: yet another cause of hypoxaemic respiratory failure in COVID-19

Pulmonary embolism represents an overlooked cause of worsening respiratory failure in COVID-19. A regular bedside evaluation for atypical features like pleuritic chest pain or pleural effusion could help identify suspected cases for appropriate management

Mental health, work and care: the value of multidisciplinary collaboration in psychiatry and occupational medicine

Objectives To investigate the relation between work and mental health in a multidisciplinary fashion. Methods This overview is based on books and articles purposely extracted from national and international literature published in the fields of psychiatry, occupational medicine, economics and labor law, written in Italian and English, without time limits; it is part of the BUDAPEST-RP Project launched in 2010 to study the effects of the economic crisis on the Italian population. Results Some features of work and the labour market in the context of the Fourth Industrial Revolution (desynchronization of time, increased external control, need of orderliness in the work relationships-i.e., decreased tolerance of work-conflicts, e.g., between the employer and the Unions-, hypernomia and heteronomy) mirror some psychopathological aspects of the pre-morbid personality prone to develop depression, and may act as environmental risk factors. This, coupled with increased unemployment and precariousness, especially affecting the young, prompt to finding evidence-based strategies to promote employment of people affected by mental disorders, seriously hit by unemployment in the years following the Great Recession. Conclusions Work organization is the common denominator between the work environment conceived as a risk or protective factor for psychiatric disorders and the use of work in the field of psychiatric rehabilitation, by means of vocational rehabilitation programs. Given the intrinsic complexity of this common ground, networking is required between professionals of different backgrounds, to develop a multidisciplinary approach in the fields of care, research and education, and to foster a better integration between occupational health and psychiatry

Ontology learning from Italian legal texts

The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts. We use a fully-implemented ontology learning system (T2K) that includes a battery of tools for Natural Language Processing (NLP), statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP-powered incremental systems like T2K for accurate large-scale semi-automatic extraction of legal ontologies