Search

Background Biliary tract cancers (BTC) are rare but highly aggressive tumours with poor prognosis, usually detected at advanced stages. Herein, we aimed at identifying BTC-specific DNA methylation alterations. Methods Study design included statistical power and sample size estimation. A genome-wide methylation study of an explorative cohort (50 BTC and ten matched non-tumoral tissue samples) has been performed. BTC-specific altered CpG islands were validated in over 180 samples (174 BTCs and 13 non-tumoral controls). The final biomarkers, selected by a machine-learning approach, were validated in independent tissue (18 BTCs, 14 matched non-tumoral samples) and bile (24 BTCs, five non-tumoral samples) replication series, using droplet digital PCR. Results We identified and successfully validated BTC-specific DNA methylation alterations in over 200 BTC samples. The two-biomarker panel, selected by an in-house algorithm, showed an AUC > 0.97. The best-performing biomarker (chr2:176993479-176995557), associated with HOXD8, a pivotal gene in cancer-related pathways, achieved 100% sensitivity and specificity in a new series of tissue and bile samples. Conclusions We identified a novel fully efficient BTC biomarker, associated with HOXD8 gene, detectable both in tissue and bile by a standardised assay ready-to-use in clinical trials also including samples from non-invasive matrices.

Colorectal cancer (CRC) develops through the accumulation of both genetic and epigenetic alterations. However, while the former are already used as prognostic and predictive biomarkers, the latter are less well characterized. Here, performing global methylation analysis on both CRCs and adenomas by Illumina Infinium HumanMethylation450 Bead Chips, we identified a panel of 74 altered CpG islands, demonstrating that the earliest methylation alterations affect genes coding for proteins involved in the crosstalk between cell and surrounding environment. The panel discriminates CRCs and adenomas from peritumoral and normal mucosa with very high specificity (100%) and sensitivity (99.9%). Interestingly, over 70% of the hypermethylated islands resulted in downregulation of gene expression. To establish the possible usefulness of these non-invasive markers for detection of colon cancer, we selected three biomarkers and identified the presence of altered methylation in stool DNA and plasma cell-free circulating DNA from CRC patients.

This paper considers online news censorship and it concentrates on censorship of identities. Obfuscating identities may occur for disparate reasons, from military to judiciary ones. In the majority of cases, this happens to protect individuals from being identified and persecuted by hostile people. However, being the collaborative web characterised by a redundancy of information, it is not unusual that the same fact is reported by multiple sources, which may not apply the same restriction policies in terms of censorship. Also, the proven aptitude of social network users to disclose personal information leads to the phenomenon that comments to news can reveal the data withheld in the news itself. This gives us a mean to figure out who the subject of the censored news is. We propose an adaptation of a text analysis approach to unveil censored identities. The approach is tested on a synthesised scenario, which however resembles a real use case. Leveraging a text analysis based on a context classifier trained over snippets from posts and comments of Facebook pages, we achieve promising results. Despite the quite constrained settings in which we operate -- such as considering only snippets of very short length -- our system successfully detects the censored name, choosing among 10 different candidate names, in more than 50\% of the investigated cases. This outperforms the results of two reference baselines. The findings reported in this paper, other than being supported by a thorough experimental methodology and interesting on their own, also pave the way for further investigation on the insidious issues of censorship on the web., Comment: Accepted for publication: Elsevier Online Social Networks and Media

Pilocytic astrocytoma (PA) is the most common glioma in pediatric patients and occurs in different locations. Chromosomal alterations are mostly located at chromosome 7q34 comprising the BRAF oncogene with consequent activation of the mitogen-activated protein kinase pathway. Although genetic and epigenetic alterations characterizing PA from different localizations have been reported, the role of epigenetic alterations in PA development is still not clear. The aim of this study was to investigate whether distinctive methylation patterns may define biologically relevant groups of PAs. Integrated DNA methylation analysis was performed on 20 PAs and 4 normal brain samples by Illumina Infinium HumanMethylation27 BeadChips. We identified distinct methylation profiles characterizing PAs from different locations (infratentorial vs supratentorial) and tumors with onset before and after 3 years of age. These results suggest that PA may be related to the specific brain site where the tumor arises from region-specific cells of origin. We identified and validated in silico the methylation alterations of some CpG islands. Furthermore, we evaluated the expression levels of selected differentially methylated genes and identified two biomarkers, one, IRX2, related to the tumor localization and the other, TOX2, as tumoral biomarker.

New Psychoactive Substances (NPS) are drugs that lay in a grey area of legislation, since they are not internationally and officially banned, possibly leading to their not prosecutable trade. The exacerbation of the phenomenon is that NPS can be easily sold and bought online. Here, we consider large corpora of textual posts, published on online forums specialized on drug discussions, plus a small set of known substances and associated effects, which we call seeds. We propose a semi-supervised approach to knowledge extraction, applied to the detection of drugs (comprising NPS) and effects from the corpora under investigation. Based on the very small set of initial seeds, the work highlights how a contrastive approach and context deduction are effective in detecting substances and effects from the corpora. Our promising results, which feature a F1 score close to 0.9, pave the way for shortening the detection time of new psychoactive substances, once these are discussed and advertised on the Internet.

Enormous advances in computing power and programming environments have obscured the importance of algorithms, one of the foundational pillars of software engineering. Today, even university curricula too often pay only lip service to the teaching of algorithmic fundamentals, reinforcing the popular belief that their place at the core of a software engineer's education is past. Yet even today, the importance of algorithms in software engineering has not diminished, and the effects of neglect are evident everywhere in needlessly inefficient industrial applications. The study of algorithms must regain its rightful place of central importance in the everyday work of today's practitioner.