A study on text-score disagreement in online reviews

In this paper, we focus on online reviews and employ artificial intelligence tools, taken from the cognitive computing field, to help understanding the relationships between the textual part of the review and the assigned numerical score. We move from the intuitions that 1) a set of textual reviews expressing different sentiments may feature the same score (and vice-versa); and 2) detecting and analyzing the mismatches between the review content and the actual score may benefit both service providers and consumers, by highlighting specific factors of satisfaction (and dissatisfaction) in texts. To prove the intuitions, we adopt sentiment analysis techniques and we concentrate on hotel reviews, to find polarity mismatches therein. In particular, we first train a text classifier with a set of annotated hotel reviews, taken from the Booking website. Then, we analyze a large dataset, with around 160k hotel reviews collected from Tripadvisor, with the aim of detecting a polarity mismatch, indicating if the textual content of the review is in line, or not, with the associated score. Using well established artificial intelligence techniques and analyzing in depth the reviews featuring a mismatch between the text polarity and the score, we find that -on a scale of five stars- those reviews ranked with middle scores include a mixture of positive and negative aspects. The approach proposed here, beside acting as a polarity detector, provides an effective selection of reviews -on an initial very large dataset- that may allow both consumers and providers to focus directly on the review subset featuring a text/score disagreement, which conveniently convey to the user a summary of positive and negative features of the review target.Comment: This is the accepted version of the paper. The final version will be published in the Journal of Cognitive Computation, available at Springer via http://dx.doi.org/10.1007/s12559-017-9496-

The landscape of BRAF transcript and protein variants in human cancer

Background: The BRAF protein kinase is widely studied as a cancer driver and therapeutic target. However, the regulation of its expression is not completely understood. Results: Taking advantage of the RNA-seq data of more than 4800 patients belonging to 9 different cancer types, we show that BRAF mRNA exists as a pool of 3 isoforms (reference BRAF, BRAF-X1, and BRAF-X2) that differ in the last part of their coding sequences, as well as in the length (BRAF-ref: 76 nt; BRAF-X1 and BRAF-X2: up to 7 kb) and in the sequence of their 3'UTRs. The expression levels of BRAF-ref and BRAF-X1/X2 are inversely correlated, while the most prevalent among the three isoforms varies from cancer type to cancer type. In melanoma cells, the X1 isoform is expressed at the highest level in both therapy-naïve cells and cells with acquired resistance to vemurafenib driven by BRAF gene amplification or expression of the Δ[3-10] splicing variant. In addition to the BRAF-ref protein, the BRAF-X1 protein (the full length as well as the Δ[3-10] variant) is also translated. The expression levels of the BRAF-ref and BRAF-X1 proteins are similar, and together they account for BRAF functional activities. In contrast, the endogenous BRAF-X2 protein is hard to detect because the C-terminal domain is selectively recognized by the ubiquitin-proteasome pathway and targeted for degradation. Conclusions: By shedding light on the repertoire of BRAF mRNA and protein variants, and on the complex regulation of their expression, our work paves the way to a deeper understanding of a crucially important player in human cancer and to a more informed development of new therapeutic strategies

Clinically Relevant Interactions between Newer Antidepressants and Second-Generation Antipsychotics

INTRODUCTION: Combinations of newer antidepressants and second-generation antipsychotics (SGAs) are frequently used by clinicians. Pharmacokinetic drug interaction (PK DI) and poorly understood pharmacodynamic (PD) drug interaction (PD DI) can occur between them. AREAS COVERED: This paper comprehensively reviews PD DI and PK DI studies. EXPERT OPINION: More PK DI studies are needed to better establish dose correction factors after adding fluoxetine and paroxetine to aripiprazole, iloperidone and risperidone. Further PK DI studies and case reports are also needed to better establish the need for dose correction factors after adding i) fluoxetine to clozapine, lurasidone, quetiapine and olanzapine; ii) paroxetine to olanzapine; iii) fluvoxamine to asenapine, aripiprazole, iloperidone, lurasidone, olanzapine, quetiapine and risperidone; iv) high sertraline doses to aripiprazole, clozapine, iloperidone and risperidone: v) bupropion and duloxetine to aripiprazole, clozapine, iloperidone and risperidone; and vi) asenapine to paroxetine and venlafaxine. Possible beneficial PD DI effects occur after adding SGAs to newer antidepressants for treatment-resistant major depressive and obsessive-compulsive disorders. The lack of studies combining newer antidepressants and SGAs in psychotic depression is worrisome. PD DIs between newer antidepressants and SGAs may be more likely for mirtazapine and bupropion. Adding selective serotonin reuptake inhibitors and SGAs may increase QTc interval and may very rarely contribute to torsades de pointes

Covid-19 as a breakdown in the texture of social practices

A lot of things need to be repaired and a lot of relationships are in need of a knowledgeable mending. Can we start to talk/write about them? This invitation - sent by one of the authors to the others - led us, as feminist women in academia, to join together in an experimental writing about the effects of COVID-19 on daily social practices and on potential (and innovative) ways for repairing work in different fields of social organization. By diffractively intertwining our embodied experiences of becoming together-with Others, we foreground a multiplicity of repair (care) practices COVID-19 is making visible. Echoing one another, we take a stand and say that we need to prevent the future from becoming the past. We are not going back to the past; our society has already changed and there is a need to cope with innovation and repairing practices that do not reproduce the past.Funding Agencies|European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programmeEuropean Research Council (ERC) [715950]</p

The STAR-RICH Detector

The STAR-RICH detector extends the particle idenfication capabilities of the STAR spectrometer for charged hadrons at mid-rapidity. It allows identification of pions and kaons up to ~3 GeV/c and protons up to ~5 GeV/c. The characteristics and performance of the device in the inaugural RHIC run are described

Identification of High p⊥\rm p_{\perp} Particles with the STAR-RICH Detector

The STAR-RICH detector extends the particle identification capapbilities of the STAR experiment for charged hadrons at mid-rapidity. This detector represents the first use of a proximity-focusing CsI-based RICH detector in a collider experiment. It provides identification of pions and kaons up to 3 GeV/c and protons up to 5 GeV/c. The characteristics and performance of the device in the inaugural RHIC run are described.Comment: 6 pages, 6 figure

Unbiased Functional Proteomics Strategy for Protein Kinase Inhibitor Validation and Identification of bona fide Protein Kinase Substrates: Application to Identification of EEF1D as a Substrate for CK2

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Ellagic Acid Derivatives from Rubus ulmifolius Inhibit Staphylococcus aureus Biofilm Formation and Improve Response to Antibiotics

Biofilms contribute to the pathogenesis of many forms of Staphylococcus aureus infection. Treatment of these infections is complicated by intrinsic resistance to conventional antibiotics, thus creating an urgent need for strategies that can be used for the prevention and treatment of biofilm-associated infections.This study demonstrates that a botanical natural product composition (220D-F2) rich in ellagic acid and its derivatives can limit S. aureus biofilm formation to a degree that can be correlated with increased antibiotic susceptibility. The source of this composition is Rubus ulmifolius Schott. (Rosaceae), a plant used in complementary and alternative medicine in southern Italy for the treatment of skin and soft tissue infections. All S. aureus clonal lineages tested exhibited a reduced capacity to form a biofilm at 220D-F2 concentrations ranging from 50-200 µg/mL, which were well below the concentrations required to limit bacterial growth (530-1040 µg/mL). This limitation was therapeutically relevant in that inclusion of 220D-F2 resulted in enhanced susceptibility to the functionally-distinct antibiotics daptomycin, clindamycin and oxacillin. Testing with kidney and liver cell lines also demonstrated a lack of host cell cytotoxicity at concentrations of 220D-F2 required to achieve these effects.These results demonstrate that extract 220D-F2 from the root of Rubus ulmifolius can be used to inhibit S. aureus biofilm formation to a degree that can be correlated with increased antibiotic susceptibility without toxic effects on normal mammalian cells. Hence, 220D-F2 is a strong candidate for development as a botanical drug for use in the prevention and treatment of S. aureus biofilm-associated infections