SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods

The Dynamical Mechanism of Auto-Inhibition of AMP-Activated Protein Kinase

We use a novel normal mode analysis of an elastic network model drawn from configurations generated during microsecond all-atom molecular dynamics simulations to analyze the mechanism of auto-inhibition of AMP-activated protein kinase (AMPK). A recent X-ray and mutagenesis experiment (Chen, et al Nature 2009, 459, 1146) of the AMPK homolog S. Pombe sucrose non-fermenting 1 (SNF1) has proposed a new conformational switch model involving the movement of the kinase domain (KD) between an inactive unphosphorylated open state and an active or semi-active phosphorylated closed state, mediated by the autoinhibitory domain (AID), and a similar mutagenesis study showed that rat AMPK has the same auto-inhibition mechanism. However, there is no direct dynamical evidence to support this model and it is not clear whether other functionally important local structural components are equally inhibited. By using the same SNF1 KD-AID fragment as that used in experiment, we show that AID inhibits the catalytic function by restraining the KD into an unproductive open conformation, thereby limiting local structural rearrangements, while mutations that disrupt the interactions between the KD and AID allow for both the local structural rearrangement and global interlobe conformational transition. Our calculations further show that the AID also greatly impacts the structuring and mobility of the activation loop

Structural analysis and corrosion studies on an ISO 5832-9 biomedical alloy with TiO2 sol–gel layers

The aim of this study was to demonstrate the relationship between the structural and corrosion properties of an ISO 5832-9 biomedical alloy modified with titanium dioxide (TiO2) layers. These layers were obtained via the sol–gel method by acid-catalyzed hydrolysis of titanium isopropoxide in isopropanol solution. To obtain TiO2 layers with different structural properties, the coated samples were annealed at temperatures of 200, 300, 400, 450, 500, 600 and 800 C for 2 h. For all the prepared samples, accelerated corrosion measurements were performed in Tyrode’s physiological solution using electrochemical methods. The most important corrosion parameters were determined: corrosion potential, polarization resistance, corrosion rate, breakdown and repassivation potentials. Corrosion damage was analyzed using scanning electron microscopy. Structural analysis was carried out for selected TiO2 coatings annealed at 200, 400, 600 and 800 C. In addition, the morphology, chemical composition, crystallinity, thickness and density of the deposited TiO2 layers were determined using suitable electron and X-ray measurement methods. It was shown that the structure and character of interactions between substrate and deposited TiO2 layers depended on annealing temperature. All the obtained TiO2 coatings exhibit anticorrosion properties, but these properties are related to the crystalline structure and character of substrate–layer interaction. From the point of view of corrosion, the best TiO2 sol–gel coatings for stainless steel intended for biomedical applications seem to be those obtained at 400 C.This study was supported by Grant No. N N507 501339 of the National Science Centre. The authors wish to express their thanks to J. Borowski (MEDGAL, Poland) for the Rex 734 alloy

Homing and Long-Term Engraftment of Long- and Short-Term Renewal Hematopoietic Stem Cells

Long-term hematopoietic stem cells (LT-HSC) and short-term hematopoietic stem cells (ST-HSC) have been characterized as having markedly different in vivo repopulation, but similar in vitro growth in liquid culture. These differences could be due to differences in marrow homing. We evaluated this by comparing results when purified ST-HSC and LT-HSC were administered to irradiated mice by three different routes: intravenous, intraperitoneal, and directly into the femur. Purified stem cells derived from B6.SJL mice were competed with marrow cells from C57BL/6J mice into lethally irradiated C57BL/6J mice. Serial transplants into secondary recipients were also carried out. We found no advantage for ST-HSC engraftment when the cells were administered intraperitoneally or directly into femur. However, to our surprise, we found that the purified ST-HSC were not short-term in nature but rather gave long-term multilineage engraftment out to 387 days, albeit at a lower level than the LT-HSC. The ST-HSC also gave secondary engraftment. These observations challenge current models of the stem cell hierarchy and suggest that stem cells are in a continuum of change

Neurotized Free Muscle Flaps can Produce MRI Changes Mimicking Tumour Recurrence

Soft tissue sarcomas are investigated by magnetic resonance imaging (MRI) both for initial staging and follow-up. We describe the presence of increased signal on T2-weighted images caused by a neurotized muscle flap following reconstructive surgery. This raised concern about possible sarcoma recurrence that was not clinically evident. On post-operative imaging of sarcomas the presence of recurrent tumour is indicated by a mass and high signal intensity on T2-weighted images. However, high signal changes in skeletal muscle on T2-weighted images are not specific. In this case, the free functioning muscle transfer with neurotization of the flap mimicked recurrence on MR scan. High signal intensity on T2-weighted images in muscle is an indication of either a physiological change or a pathological condition and must be taken in context of the clinical picture

Building pathway clusters from Random Forests classification using class votes

<p>Abstract</p> <p>Background</p> <p>Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.</p> <p>Results</p> <p>We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These pathways may or may not share genes. As an illustration, our approach is applied to three human breast cancer microarray data sets. We found that our methods yielded consistent and interpretable results for these three data sets. We further investigated one of the pathway clusters found using PubMatrix. We found that informative genes in the pathway clusters do have more publications with keywords, like estrogen receptor, compared with informative genes in other top pathways. In addition, using the shortest path analysis in GeneGo's MetaCore and Human Protein Reference Database, we were able to identify the links which connect the pathways without shared genes within the pathway cluster.</p> <p>Conclusion</p> <p>Our proposed pathway clustering methods allow bioinformaticians and biologists to investigate how informative genes within pathways are related to each other and understand possible crosstalk between pathways in a cluster. Therefore, building pathway clusters may lead to a better understanding of molecular mechanisms affecting a trait of interest, and help generate further biological hypotheses from gene expression data.</p

Sentiment Analysis in Social Streams

In this chapter we review and discuss the state of the art on sentiment analysis in social streams –such as web forums, micro-blogging systems, and so- cial networks–, aiming to clarify how user opinions, affective states, and intended emotional effects are extracted from user generated content, how they are modeled, and how they could be finally exploited. We explain why sentiment analysis tasks are more difficult for social streams than for other textual sources, and entail going beyond classic text-based opinion mining techniques. We show, for example, that social streams may use vocabularies and expressions that exist outside the main- stream of standard, formal languages, and may reflect complex dynamics in the opinions and sentiments expressed by individuals and communities

Antisense epidermal growth factor receptor RNA transfection in human glioblastoma cells down-regulates telomerase activity and telomere length

Epidermal growth factor receptor is overexpressed and/or amplified in up to 50% of glioblastomas, suggesting an important role of this gene in glial tumorigenesis and progression. In the present study we demonstrated that epidermal growth factor receptor is involved in regulation of telomerase activity in glioblastoma. Antisense-epidermal growth factor receptor approach was used to inhibit epidermal growth factor receptor expression of glioblastoma U87MG cells. Telomerase activity in antisense-epidermal growth factor receptor cells decreased by up to 54 folds compared with control cells. Moreover, the telomere lengths of antisense-epidermal growth factor receptor cells were shortened. In addition, the tumorigenicity of antisense-epidermal growth factor receptor cells was significantly inhibited. Taken together, there were strong correlations between tumorigenicity and epidermal growth factor receptor expression levels, and between tumorigenicity and telomerase activity. These results provide evidence that epidermal growth factor receptor plays an important role in the regulation of telomerase activity of glioma cells. Our findings provide new insights into both the biological functions of epidermal growth factor receptor and the regulation of telomerase activity. The inhibition of telomerase activity triggered by antisense-epidermal growth factor receptor treatment may reflect yet another mechanism of antisense-epidermal growth factor receptor approach in tumour suppression

Glycobiology of cell death: when glycans and lectins govern cell fate

Although one typically thinks of carbohydrates as associated with cell growth and viability, glycosylation also has an integral role in many processes leading to cell death. Glycans, either alone or complexed with glycan-binding proteins, can deliver intracellular signals or control extracellular processes that promote initiation, execution and resolution of cell death programs. Herein, we review the role of glycans and glycan-binding proteins as essential components of the cell death machinery during physiologic and pathologic settings.Fil: Lichtenstein, Rachel. Ben-Gurion University of the Negev. Faculty of Engineering. Department of Biotechnology Engineering; IsraelFil: Rabinovich, Gabriel Adrian. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental (i); Argentina. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Quimica Biologica; Argentin