Scholarly Database

The Scholarly Database (SDB) aims to serve the needs of researchers and practitioners interested in the analysis, modeling, and visualization of large-scale scholarly datasets. The database currently provides access to 11 major datasets such as Medline, U.S. patents, National Science Foundation and National Institutes of Health funding awards - a total of about 20 million records. The books, journals, proceedings, patents, grants, technical reports, doctoral and master theses can be cross searched. Results can be downloaded as data dumps for further processing. The online interface at https://sdb.School of Library and Information Science.indiana.edu provides full-text search for four databases (MEDLINE, NSF, NIH, USPTO) using Solar. Specifically, it is able to search and filter the contents of these databases using many criteria and search fields, particularly those relevant for scientometric research and science policy practice

Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches

We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis. The few comparisons of clustering results from different similarity approaches have focused on small literature sets and have given conflicting results. Our study was designed to seek a robust answer to the question of which similarity approach would generate the most coherent clusters of a biomedical literature set of over two million documents.We used a corpus of 2.15 million recent (2004-2008) records from MEDLINE, and generated nine different document-document similarity matrices from information extracted from their bibliographic records, including titles, abstracts and subject headings. The nine approaches were comprised of five different analytical techniques with two data sources. The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models--BM25 and PMRA (PubMed Related Articles). The two data sources were a) MeSH subject headings, and b) words from titles and abstracts. Each similarity matrix was filtered to keep the top-n highest similarities per document and then clustered using a combination of graph layout and average-link clustering. Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE.PubMed's own related article approach (PMRA) generated the most coherent and most concentrated cluster solution of the nine text-based similarity approaches tested, followed closely by the BM25 approach using titles and abstracts. Approaches using only MeSH subject headings were not competitive with those based on titles and abstracts

CMU in Cross-Language Information Retrieval at NTCIR-3

We participated in the Cross-Language Information Retrieval evaluation at NTCIR-3 for the English-Chinese and English-Japanese tasks. We examined several approaches to query translation, including the use of a commercial machine translation system, a thesaurus that is automatically extracted from a parallel corpus, and a general-purpose online dictionary. The MT-based approach was most effective among these alternatives in our experiments for English-Chinese retrieval on the NTCIR-2 and 3 data. Combined use of machine translation and thesaurus extraction yielded further improvement. 1

Applying CLIR Techniques to Event Tracking

Cross-lingual event tracking from a very large number of information sources (thousands of Web sites, for example) is an open challenge. In this paper we investigate effective and scalable solutions for this problem, focusing on the use of cross-lingual information retrieval techniques to translate a small subset of the training documents, as an alternative to the conventional approach of translating all the multilingual test documents. In addition, we present a new variant of weighted pseudo-relevance feedback for adaptive event tracking

The RNA methyltransferase METTL16 enhances cholangiocarcinoma growth through PRDM15-mediated FGFR4 expression

Abstract Background RNA N6-Methyladenosine (m6A) modification is implicated in the progression of human cancers including cholangiocarcinoma (CCA). METTL16 is recently identified as a new RNA methyltransferase responsible for m6A modification, although the role of METTL16 in CCA has not yet been examined. The current study aims to investigate the effect and mechanism of the RNA methyltransferase METTL16 in CCA. Methods The expression of METTL16 in CCA was examined by analyzing publicly available datasets or by IHC staining on tumor samples. siRNA or CRISPR/Cas9-mediated loss of function studies were performed in vitro and in vivo to investigate the oncogenic role of METTL16 in CCA. MeRIP-Seq was carried out to identify the downstream target of METTL16. ChIP-qPCR, immunoprecipitation, and immunoblots were used to explore the regulation mechanisms for METTL16 expression in CCA. Results We observed that the expression of METTL16 was noticeably increased in human CCA tissues. Depletion of METTL16 significantly inhibited CCA cell proliferation and decreased tumor progression. PRDM15 was identified as a key target of METTL16 in CCA cells. Mechanistically, our data showed that METTL16 regulated PRDM15 protein expression via YTHDF1-dependent translation. Accordingly, we observed that restoration of PRDM15 expression could rescue the deficiency of CCA cell proliferation/colony formation induced by METTL16 depletion. Our subsequent analyses revealed that METTL16-PRDM15 signaling regulated the expression of FGFR4 in CCA cells. Specifically, we observed that PRDM15 protein was associated with the FGFR4 promoter to regulate its expression. Furthermore, we showed that the histone acetyltransferase p300 cooperated with the transcription factor YY1 to regulate METTL16 gene expression via histone H3 lysine 27 (H3K27) acetylation in CCA cells. Conclusions This study describes a novel METTL16-PRDM15-FGFR4 signaling axis which is crucial for CCA growth and may have important therapeutic implications. We showed that depletion of METTL16 significantly inhibited CCA cell proliferation and decreased tumor progression

The histone lysine acetyltransferase KAT2B inhibits cholangiocarcinoma growth: evidence for interaction with SP1 to regulate NF2-YAP signaling

Abstract Background Cholangiocarcinoma (CCA) is a highly malignant cancer of the biliary tract with poor prognosis. Further mechanistic insights into the molecular mechanisms of CCA are needed to develop more effective target therapy. Methods The expression of the histone lysine acetyltransferase KAT2B in human CCA was analyzed in human CCA tissues. CCA xenograft was developed by inoculation of human CCA cells with or without KAT2B overexpression into SCID mice. Western blotting, ChIP-qPCR, qRT-PCR, protein immunoprecipitation, GST pull-down and RNA-seq were performed to delineate KAT2B mechanisms of action in CCA. Results We identified KAT2B as a frequently downregulated histone acetyltransferase in human CCA. Downregulation of KAT2B was significantly associated with CCA disease progression and poor prognosis of CCA patients. The reduction of KAT2B expression in human CCA was attributed to gene copy number loss. In experimental systems, we demonstrated that overexpression of KAT2B suppressed CCA cell proliferation and colony formation in vitro and inhibits CCA growth in mice. Mechanistically, forced overexpression of KAT2B enhanced the expression of the tumor suppressor gene NF2, which is independent of its histone acetyltransferase activity. We showed that KAT2B was recruited to the promoter region of the NF2 gene via interaction with the transcription factor SP1, which led to enhanced transcription of the NF2 gene. KAT2B-induced NF2 resulted in subsequent inhibition of YAP activity, as reflected by reduced nuclear accumulation of oncogenic YAP and inhibition of YAP downstream genes. Depletion of NF2 was able to reverse KAT2B-induced reduction of nuclear YAP and subvert KAT2B-induced inhibition of CCA cell growth. Conclusions This study provides the first evidence for an important tumor inhibitory effect of KAT2B in CCA through regulation of NF2-YAP signaling and suggests that this signaling cascade may be therapeutically targeted for CCA treatment

Additional file 1 of The RNA methyltransferase METTL16 enhances cholangiocarcinoma growth through PRDM15-mediated FGFR4 expression

Additional file 1: Supplementary Figure 1 (related to Fig. 4). PRDM15, NSD2, KMT2D, and SETD5 expression in cholangiocarcinoma and normal tissues from the TCGA database. Supplementary Figure 2 (related to Fig. 4). RT-qPCR analysis of PRDM15, NSD2, KMT2D and SETD5 expression in control and METTL16 knockdown cells. Supplementary Figure 3 (related to Fig. 4). SETD5, KMT2D, and NSD2 protein expression were determined by an immunoblotting assay in control and METTL16 knockdown cells. Supplementary Figure 4 (related to Fig. 4). A. MeRIP-qPCR assay was performed in METTL3 silencing (siMETTL3 #1) and control CCLP1 and HuCCT1 cells to detect the level of m6A-modified PRDM15 mRNA. B. PRDM15 protein expression was determined by an immunoblotting assay in control and METTL3 knockdown cells. Supplementary Figure 5 (related to Fig. 5) . The expression of PRDM15 and METTL16 is positively correlated in human CCA tissues. (A). Representative immunochemistry (IHC) staining for PRDM15 in normal bile duct and CCA tissues. Scale bar: 100 μm. (B). Quantitative result of the IHC data as represented in A. (C). Positive correlation between PRDM15 and METTL16 expression in CCA patient samples (Pearson correlation coefficient analysis based on the IHC scores). Supplementary Figure 6 (related to Fig. 6). The expression of FGFR4 is positively correlated with METTL16 in CCA tissues. (A). Representative immunochemistry (IHC) staining for FGFR4 expression in human CCA tissues and non-tumorous bile duct. Scale bar: 100 μm. (B). Quantitative result of the IHC data as represented in A. (C). Positive correlation between FGFR4 and METTL16 expression in CCA) patient samples (Pearson correlation coefficient analysis based on the IHC scores). Supplementary Figure 7 (related to Fig. 6). Forced overexpression of FGFR4 rescues the deficiency of CCA cell proliferation and colony formation induced by METTL16 depletion. V5-tagged FGFR4 expression construct was transfected in CCLP1 and HuCCT1 cells for 48 hours and FGFR4 protein expression was determined by immunoblotting (A). WST-1 cell proliferation (B) and colony formation (C) assay were performed in CCLP1 and HuCCT1 cells transfected with FGFR4 overexpression or control construct. (D, E) Phosphorylation of FGFR4 signaling pathway components ERK1/2 and AKT were determined in BLU-554 treated (D) or METTL16 depletion (E) CCA cells by western blotting assay. **P<0.01, ***P<0.001, ****P<0.0001. (B, C, E, F) Mean ± SD, One-way ANOVA test

Additional file 2 of The RNA methyltransferase METTL16 enhances cholangiocarcinoma growth through PRDM15-mediated FGFR4 expression

Additional file 2: Table S1. Primers used in this study