Korean Grammatical Error Correction Based on Transformer with Copying Mechanisms and Grammatical Noise Implantation Methods.

Grammatical Error Correction (GEC) is the task of detecting and correcting various grammatical errors in texts. Many previous approaches to the GEC have used various mechanisms including rules, statistics, and their combinations. Recently, the performance of the GEC in English has been drastically enhanced due to the vigorous applications of deep neural networks and pretrained language models. Following the promising results of the English GEC tasks, we apply the Transformer with Copying Mechanism into the Korean GEC task by introducing novel and effective noising methods for constructing Korean GEC datasets. Our comparative experiments showed that the proposed system outperforms two commercial grammar check and other NMT-based models.

Exploring the Unexplored: Identifying Implicit and Indirect Descriptions of Biomedical Terminologies Based on Multifaceted Weighting Combinations.

In order to achieve relevant scholarly information from the biomedical databases, researchers generally use technical terms as queries such as proteins, genes, diseases, and other biomedical descriptors. However, the technical terms have limits as query terms because there are so many indirect and conceptual expressions denoting them in scientific literatures. Combinatorial weighting schemes are proposed as an initial approach to this problem, which utilize various indexing and weighting methods and their combinations. In the experiments based on the proposed system and previously constructed evaluation collection, this approach showed promising results in that one could continually locate new relevant expressions by combining the proposed weighting schemes. Furthermore, it could be ascertained that the most outperforming binary combinations of the weighting schemes, showing the inherent traits of the weighting schemes, could be complementary to each other and it is possible to find hidden relevant documents based on the proposed methods.

Overview of the Cancer Genetics and Pathway Curation tasks of BioNLP Shared Task 2013.

BACKGROUND: Since their introduction in 2009, the BioNLP Shared Task events have been instrumental in advancing the development of methods and resources for the automatic extraction of information from the biomedical literature. In this paper, we present the Cancer Genetics (CG) and Pathway Curation (PC) tasks, two event extraction tasks introduced in the BioNLP Shared Task 2013. The CG task focuses on cancer, emphasizing the extraction of physiological and pathological processes at various levels of biological organization, and the PC task targets reactions relevant to the development of biomolecular pathway models, defining its extraction targets on the basis of established pathway representations and ontologies. RESULTS: Six groups participated in the CG task and two groups in the PC task, together applying a wide range of extraction approaches including both established state-of-the-art systems and newly introduced extraction methods. The best-performing systems achieved F-scores of 55% on the CG task and 53% on the PC task, demonstrating a level of performance comparable to the best results achieved in similar previously proposed tasks. CONCLUSIONS: The results indicate that existing event extraction technology can generalize to meet the novel challenges represented by the CG and PC task settings, suggesting that extraction methods are capable of supporting the construction of knowledge bases on the molecular mechanisms of cancer and the curation of biomolecular pathway models. The CG and PC tasks continue as open challenges for all interested parties, with data, tools and resources available from the shared task homepage.

Design and synthesis of novel 2-(indol-5-yl)thiazole derivatives as xanthine oxidase inhibitors.

Xanthine oxidase (XO) inhibitors have been widely used for the treatment of gout. Indole rings are frequently used as active scaffold in designing inhibitors for enzymes. Herein, we describe the structure-activity relationship for novel xanthine oxidase inhibitors based on indole scaffold. A series of novel tri-substituted 2-(indol-5-yl)thiazole derivatives were synthesized, and their in vitro inhibitory activities against xanthine oxidase and in vivo efficacy lowering uric acid level in blood were measured. Among them, 2-(3-cyano-2-isopropylindol-5-yl)-4-methylthiazole-5-carboxylic acid exhibits the most potent XO inhibitory activity (IC50 value: 3.5nM) and the excellent plasma uric acid lowering activity. Study of structure activity relationship indicated that hydrophobic moiety (e.g., isopropyl) at 1-position and electron withdrawing group (e.g., CN) at 3-position of indole ring and small hydrophobic group (CH3) at 4-position of the thiazole ring enhanced the XO inhibitory activity. Hydrophobic substitution such as isopropyl at 1-position of the indole moiety without any substitution at 2-position has an essential role for enhancing bioavailability and therefore for high in vivo efficacy.

Effects of chronic alcohol consumption on expression levels of APP and Aß-producing enzymes.

Chronic alcohol consumption contributes to numerous diseases, including cancers, cardiovascular diseases, and liver cirrhosis. Epidemiological studies have shown that excessive alcohol consumption is a risk factor for dementia. Along this line, Alzheimer's disease (AD) is the most common form of dementia and is caused by the accumulation of amyloid-ß (Aß plaques in neurons. In this study, we hypothesized that chronic ethanol consumption is associated with pathological processing of APP in AD. To investigate the relationship between chronic alcohol consumption and Aß production, brain samples from rats fed an alcohol liquid diet for 5 weeks were analyzed. We show that the expression levels of APP, BACE1, and immature nicastrin were increased in the cerebellum, hippocampus, and striatum of the alcohol-fed group compared to the control group. Total nicastrin and PS1 levels were induced in the hippocampus of alcohol-fed rats. These data suggest that the altered expression of APP and Aß-producing enzymes possibly contributes to the chronic alcohol consumption-mediated pathogenesis of AD.

The small molecule phenamil is a modulator of adipocyte differentiation and PPARgamma expression.

We previously described the use of a cell-based screening approach to identify small molecules that regulate adipocyte differentiation. Here we identify the amiloride derivative phenamil as an adipogenic compound. Phenamil acutely induces expression of the key transcription factor of adipogenesis, peroxisome proliferator-activated receptor gamma (PPARgamma) and, consequently, promotes the differentiation of multiple preadipocyte cell lines, including 3T3-L1 and F442A. Interestingly, the adipogenic action of phenamil is distinct from and additive with both PPARgamma ligands and the previously identified adipogenic small molecule harmine. To identify signaling pathways mediating phenamil's effects, we performed transcriptional profiling of 3T3-F442A preadipocytes. ETS variant 4 (ETV4) was identified as a gene rapidly induced by phenamil but not by other adipogenic small molecules or PPARgamma agonists. Transient expression of ETV4 in preadipocytes enhances the expression of PPARgamma. Stable overexpression of ETV4 promotes expression of PPARgamma and its downstream target genes and enhances morphological differentiation. Finally, knockdown of PPARgamma expression by shRNA blocks the effects of phenamil on adipocyte differentiation and gene expression, but it does not block phenamil induction of ETV4, which suggests that ETV4 acts upstream of PPARgamma in differentiation processes. These results identify a phenamil as new small molecule tool for the probing of adipocyte differentiation that acts, at least in part, through induction of ETV4 expression.