Analysis of gut microbiota in rheumatoid arthritis patients. Disease-related dysbiosis and modifications induced by etanercept

A certain number of studies were carried out to address the question of how dysbiosis could affect the onset and development of rheumatoid arthritis (RA), but little is known about the reciprocal influence between microbiota composition and immunosuppressive drugs, and how this interaction may have an impact on the clinical outcome. The aim of this study was to characterize the intestinal microbiota in a groups of RA patients treatment-naïve, under methotrexate, and/or etanercept (ETN). Correlations between the gut microbiota composition and validated immunological and clinical parameters of disease activity were also evaluated. In the current study, a 16S analysis was employed to explore the gut microbiota of 42 patients affected by RA and 10 healthy controls. Disease activity score on 28 joints (DAS-28), erythrocyte sedimentation rate, C-reactive protein, rheumatoid factor, anti-cyclic citrullinated peptides, and dietary and smoking habits were assessed. The composition of the gut microbiota in RA patients free of therapy is characterized by several abnormalities compared to healthy controls. Gut dysbiosis in RA patients is associated with different serological and clinical parameters; in particular, the phylum of Euryarchaeota was directly correlated to DAS and emerged as an independent risk factor. Patients under treatment with ETN present a partial restoration of a beneficial microbiota. The results of our study confirm that gut dysbiosis is a hallmark of the disease, and shows, for the first time, that the anti-tumor necrosis factor alpha (TNF-α) ETN is able to modify microbial communities, at least partially restoring a beneficial microbiota

Amphiregulin activates human hepatic stellate cells and is upregulated in non alcoholic steatohepatitis

Amphiregulin (AR) involvement in liver fibrogenesis and hepatic stellate cells (HSC) regulation is under study. Non-alcoholic fatty liver disease (NAFLD) and its more severe form non-alcoholic steatohepatitis (NASH) may progress to cirrhosis and hepatocellular cancer (HCC). Our aim was to investigate ex vivo the effect of AR on human primary HSC (hHSC) and verify in vivo the relevance of AR in NAFLD fibrogenesis. hHSC isolated from healthy liver segments were analyzed for expression of AR and its activator, TNF- converting enzyme (TACE). AR induction of hHSC proliferation and matrix production was estimated in the presence of antagonists. AR involvement in fibrogenesis was also assessed in a mouse model of NASH and in humans with NASH. hHSC time dependently expressed AR and TACE. AR increased hHSC proliferation through several mitogenic signaling pathways such as EGFR, PI3K and p38. AR also induced marked upregulation of hHSC fibrogenic markers and reduced hHSC death. AR expression was enhanced in the HSC of a murine model of NASH and of severe human NASH. In conclusion, AR induces hHSC fibrogenic activity via multiple mitogenic signaling pathways, and is upregulated in murine and human NASH, suggesting that AR antagonists may be clinically useful anti-fibrotics in NAFLD

Bridging the demand and the offer in data science

During the last several years, we have observed an exponential increase in the demand for Data Scientists in the job market. As a result, a number of trainings, courses, books, and university educational programs (both at undergraduate, graduate and postgraduate levels) have been labeled as “Big data” or “Data Science”; the fil‐rouge of each of them is the aim at forming people with the right competencies and skills to satisfy the business sector needs. In this paper, we report on some of the exercises done in analyzing current Data Science education offer and matching with the needs of the job markets to propose a scalable matching service, ie, COmpetencies ClassificatiOn (E‐CO‐2), based on Data Science techniques. The E‐CO‐2 service can help to extract relevant information from Data Science–related documents (course descriptions, job Ads, blogs, or papers), which enable the comparison of the demand and offer in the field of Data Science Education and HR management, ultimately helping to establish the profession of Data Scientist.publishedVersio

Mutual Antagonism between Circadian Protein Period 2 and Hepatitis C Virus Replication in Hepatocytes.

Hepatitis C virus (HCV) infects approximately 3% of the world population and is the leading cause of liver disease, impacting hepatocyte metabolism, depending on virus genotype. Hepatic metabolic functions show rhythmic fluctuations with 24-h periodicity (circadian), driven by molecular clockworks ticking through translational-transcriptional feedback loops, operated by a set of genes, called clock genes, encoding circadian proteins. Disruption of biologic clocks is implicated in a variety of disorders including fatty liver disease, obesity and diabetes. The relation between HCV replication and the circadian clock is unknown. METHODS: We investigated the relationship between HCV core infection and viral replication and the expression of clock genes (Rev-Erbα, Rorα, ARNTL, ARNTL2, CLOCK, PER1, PER2, PER3, CRY1 and CRY2) in two cellular models, the Huh-7 cells transiently expressing the HCV core protein genotypes 1b or 3a, and the OR6 cells stably harboring the full-length hepatitis C genotype 1b replicon, and in human liver biopsies, using qRT-PCR, immunoblotting, luciferase assays and immunohistochemistry. RESULTS: In Huh-7 cells expressing the HCV core protein genotype 1b, but not 3a, and in OR6 cells, transcript and protein levels of PER2 and CRY2 were downregulated. Overexpression of PER2 led to a consistent decrease in HCV RNA replicating levels and restoration of altered expression pattern of a subset of interferon stimulated genes (ISGs) in OR6 cells. Furthermore, in liver biopsies from HCV genotype 1b infected patients, PER2 was markedly localized to the nucleus, consistent with an auto-inhibitory transcriptional feedback loop. CONCLUSIONS: HCV can modulate hepatic clock gene machinery, and the circadian protein PER2 counteracts viral replication. Further understanding of circadian regulation of HCV replication and rhythmic patterns of host-hosted relationship may improve the effectiveness of HCV antiviral therapy. This would extend to hepatic viral infections the current spectrum of chronotherapies, implemented to treat metabolic, immune related and neoplastic diseas

Early menopause is associated with lack of response to antiviral therapy in women with chronic hepatitis C.

BACKGROUND AND AIMS: Chronic hepatitis C (CHC) and liver fibrosis progress more rapidly in men and menopausal women than in women of reproductive age. We investigated the associations among menopause, sustained virologic response (SVR), and liver damage in patients with CHC. METHODS: We performed a prospective study of 1000 consecutive, treatment-naïve patients 18 years of age and older with compensated liver disease from CHC. Liver biopsy samples were analyzed (for fibrosis, inflammation, and steatosis) before patients received standard antiviral therapy. From women (n = 442), we collected data on the presence, type, and timing of menopause; associated hormone and metabolic features; serum levels of interleukin-6; and hepatic tumor necrosis factor (TNF)-α. RESULTS: Postmenopausal women achieved SVRs less frequently than women of reproductive age (46.0% vs 67.5%; P < .0001) but as frequently as men (51.1%; P = .283). By multivariate regression analysis, independent significant predictors for women to not achieve an SVR were early menopause (odds ratio [OR], 8.055; 95% confidence interval [CI], 1.834-25.350), levels of γ-glutamyl transpeptidase (OR, 2.165; 95% CI, 1.364-3.436), infection with hepatitis C virus genotype 1 or 4 (OR, 3.861; 95% CI, 2.433-6.134), and cholesterol levels (OR, 0.985; 95% CI, 0.971-0.998). Early menopause was the only independent factor that predicted lack of an SVR among women with genotype 1 hepatitis C virus infection (OR, 3.933; 95% CI, 1.274-12.142). Baseline levels of liver inflammation, fibrosis, steatosis, serum interleukin-6 (P = .04), and hepatic TNF-α (P = .007) were significantly higher among postmenopausal women than women of reproductive age. CONCLUSIONS: Among women with CHC, early menopause was associated with a low likelihood of SVR, probably because of inflammatory factors that change at menopause

Deficiency and haploinsufficiency of histone macroH2A1.1 in mice recapitulate hematopoietic defects of human myelodysplastic syndrome

Background: Epigenetic regulation is important in hematopoiesis, but the involvement of histone variants is poorly understood. Myelodysplastic syndromes (MDS) are heterogeneous clonal hematopoietic stem cell (HSC) disorders characterized by ineffective hematopoiesis. MacroH2A1.1 is a histone H2A variant that negatively correlates with the self-renewal capacity of embryonic, adult, and cancer stem cells. MacroH2A1.1 is a target of the frequent U2AF1 S34F mutation in MDS. The role of macroH2A1.1 in hematopoiesis is unclear. Results: MacroH2A1.1 mRNA levels are significantly decreased in patients with low-risk MDS presenting with chromosomal 5q deletion and myeloid cytopenias and tend to be decreased in MDS patients carrying the U2AF1 S34F mutation. Using an innovative mouse allele lacking the macroH2A1.1 alternatively spliced exon, we investigated whether macroH2A1.1 regulates HSC homeostasis and differentiation. The lack of macroH2A1.1 decreased while macroH2A1.1 haploinsufficiency increased HSC frequency upon irradiation. Moreover, bone marrow transplantation experiments showed that both deficiency and haploinsufficiency of macroH2A1.1 resulted in enhanced HSC differentiation along the myeloid lineage. Finally, RNA-sequencing analysis implicated macroH2A1.1-mediated regulation of ribosomal gene expression in HSC homeostasis. Conclusions: Together, our findings suggest a new epigenetic process contributing to hematopoiesis regulation. By combining clinical data with a discrete mutant mouse model and in vitro studies of human and mouse cells, we identify macroH2A1.1 as a key player in the cellular and molecular features of MDS. These data justify the exploration of macroH2A1.1 and associated proteins as therapeutic targets in hematological malignancies

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey