Generating Paired Transliterated-cognates Using Multiple Pronunciation Characteristics from Web corpora

A novel approach to automatically extracting paired transliterated-cognates from Web corpora is proposed in this paper. One of the most important issues addressed is that of taking multiple pronunciation characteristics into account. Terms from various languages may pronounce very differently. Incorporating the knowledge of word origin may improve the pronunciation accuracy of terms. The accuracy of generated phonetic information has an important impact on term transliteration and hence transliterated-term extraction. Transliterated-term extraction is a fundamental task in natural language processing to extract paired transliterated-terms in studying term transliteration. An experiment on transliterated-term extraction from two kinds of Web resources, Web pages and anchored texts, has been conducted and evaluated. The experimental results show that many transliterated-term pairs, which cannot be extracted using the approach only exploiting English pronunciation characteristics, have been successfully extracted using the proposed approach in this paper. By taking multiple language-specific pronunciation transformations into account may further improve the output of the transliterated-term extraction

Incorporating Pronunciation Variation into Different Strategies of Term Transliteration

Term transliteration addresses the problem of converting terms in one language into their phonetic equivalents in the other language via spoken form. It is especially concerned with proper nouns, such as personal names, place names and organization names. Pronunciation variation refers to pronunciation ambiguity frequently encountered in spoken language, which has a serious impact on term transliteration. More than one transliteration variants can be generated by an out-of-vocabulary term due to different kinds of pronunciation variations. It is important to take this issue into account when dealing with term transliteration. Several models, which take pronunciation variation into consideration, are proposed for term transliteration in this paper. They describe transliteration from various viewpoints and utilize the relationships trained from extracted transliterated-term pairs. An experiment in applying the proposed models to term transliteration was conducted and evaluated. The experimental results show promise. These proposed models are not only applicable to term transliteration, but also are helpful in indexing and retrieving spoken document retrieval

Tissue engineering: state of the art in oral rehabilitation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74998/1/j.1365-2842.2009.01939.x.pd

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival