Speech in interaction: Mandarin particle Le as a marker of intersubjectivity

Adopting a discourse-analysis approach, we argue in line with van den Berg and Wu (2006) in showing that the particle le in Mandarin serves as a common ground coordination device, exhibiting a high degree of intersubjectivity, which is absent in the use of verbal -le. However, in view of the limit imposed by the data type of previous research, we observe the turn-taking behavior in natural, spontaneous, spoken data to further consolidate van den Berg and Wu‟s proposal. We argue that use of natural, spontaneous spoken data is essential in furthering our understanding of linguistic forms and their associated functions. Through this study, we hope we will be able to show and confirm the importance of data type in both the theoretical and pedagogical aspects of linguistic research

A Novel LMP1 Antibody Synergizes with Mitomycin C to Inhibit Nasopharyngeal Carcinoma Growth in Vivo Through Inducing Apoptosis and Downregulating Vascular Endothelial Growth Factor

Combined therapy emerges as an attractive strategy for cancer treatment. The aim of this study was to investigate the inhibitory effects of mitomycin C (MMC) combined with a novel antibody fragment (Fab) targeting latent membrane protein 1 (LMP1) on nasopharyngeal carcinoma (NPC) xenograft nude mice. The inhibitory rates of MMC (2 mg/kg), Fab (4 mg/kg), MMC (2 mg/kg) + Fab (4 mg/kg), and MMC (1 mg/kg) + Fab (4 mg/kg) were 20.1%, 7.3%, 42.5% and 40.5%, respectively. Flow cytometry analysis showed that the apoptotic rate of xenograft tumor cells in the MMC and Fab combination group was 28 ± 4.12%, significantly higher than the MMC (2 mg/kg) group (P < 0.01). Immunohistochemical staining showed that VEGF expression in NPC xenografts was significantly inhibited in the combination group compared to the Fab (4 mg/kg) group (P < 0.05). In conclusion, both MMC and Fab could inhibit NPC xenograft tumor growth in vivo and combination therapy showed apparent synergistic anti-tumor effects, which may be due to the induction of tumor cell apoptosis and the downregulation of VEGF expression. These results suggest that the novel combined therapy utilizing traditional chemotherapeutics and antibody-targeted therapy could be a promising strategy for the treatment of NPC

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

<p>Abstract</p> <p>Background</p> <p>There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights.</p> <p>Results</p> <p>In this paper we present a new method, which we refer to as indirect two-sided relative ranking, for comparing gene expression profiles that is robust to variations in experimental conditions. This method extends the current best approach, which is based on comparing the correlations of the up and down regulated genes, by introducing a comparison based on the correlations in rankings across the entire database. Because our method is robust to experimental variations, it allows a greater variety of gene expression data to be combined, which, as we show, leads to richer scientific discoveries.</p> <p>Conclusions</p> <p>We demonstrate the benefit of our proposed indirect method on several datasets. We first evaluate the ability of the indirect method to retrieve compounds with similar therapeutic effects across known experimental barriers, namely vehicle and batch effects, on two independent datasets (one private and one public). We show that our indirect method is able to significantly improve upon the previous state-of-the-art method with a substantial improvement in recall at rank 10 of 97.03% and 49.44%, on each dataset, respectively. Next, we demonstrate that our indirect method results in improved accuracy for classification in several additional datasets. These datasets demonstrate the use of our indirect method for classifying cancer subtypes, predicting drug sensitivity/resistance, and classifying (related) cell types. Even in the absence of a known (i.e., labeled) experimental barrier, the improvement of the indirect method in each of these datasets is statistically significant.</p

Prediction and Optimal Scheduling of Advertisements in Linear Television

Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue

Prediction and Optimal Scheduling of Advertisements in Linear Television

Advertising is a crucial component of marketing and an important way for companies to raise awareness of goods and services in the marketplace. Advertising campaigns are designed to convey a marketing image or message to an audience of potential consumers and television commercials can be an effective way of transmitting these messages to a large audience. In order to meet the requirements for a typical advertising order, television content providers must provide advertisers with a predetermined number of impressions in the target demographic. However, because the number of impressions for a given program is not known a priori and because there are a limited number of time slots available for commercials, scheduling advertisements efficiently can be a challenging computational problem. In this case study, we compare a variety of methods for estimating future viewership patterns in a target demographic from past data. We also present a method for using those predictions to generate an optimal advertising schedule that satisfies campaign requirements while maximizing advertising revenue

Capacitive energy storage from -50 to 100 °C using an ionic liquid electrolyte

Relying on redox reactions, most batteries are limited in their ability to operate at very low or very high temperatures. While performance of electrochemical capacitors is less dependent on the temperature, present-day devices still cannot cover the entire range needed for automotive and electronics applications under a variety of environmental conditions. We show that the right combination of the exohedral nanostructured carbon (nanotubes and onions) electrode and a eutectic mixture of ionic liquids can dramatically extend the temperature range of electrical energy storage, thus defying the conventional wisdom that ionic liquids can only be used as electrolytes above room temperature. We demonstrate electrical double layer capacitors able to operate from -50 to 100 °C over a wide voltage window (up to 3.7 V) and at very high charge/discharge rates of up to 20 V/s

Extensive microbial and functional diversity within the chicken cecal microbiome

Chickens are major source of food and protein worldwide. Feed conversion and the health of chickens relies on the largely unexplored complex microbial community that inhabits the chicken gut, including the ceca. We have carried out deep microbial community profiling of the microbiota in twenty cecal samples via 16S rRNA gene sequences and an in-depth metagenomics analysis of a single cecal microbiota. We recovered 699 phylotypes, over half of which appear to represent previously unknown species. We obtained 648,251 environmental gene tags (EGTs), the majority of which represent new species. These were binned into over two-dozen draft genomes, which included Campylobacter jejuni and Helicobacter pullorum. We found numerous polysaccharide- and oligosaccharide-degrading enzymes encoding within the metagenome, some of which appeared to be part of polysaccharide utilization systems with genetic evidence for the co-ordination of polysaccharide degradation with sugar transport and utilization. The cecal metagenome encodes several fermentation pathways leading to the production of short-chain fatty acids, including some with novel features. We found a dozen uptake hydrogenases encoded in the metagenome and speculate that these provide major hydrogen sinks within this microbial community and might explain the high abundance of several genera within this microbiome, including Campylobacter, Helicobacter and Megamonas

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts