InDEX: Indonesian Idiom and Expression Dataset for Cloze Test

We propose InDEX, an Indonesian Idiom and Expression dataset for cloze test. The dataset contains 10438 unique sentences for 289 idioms and expressions for which we generate 15 different types of distractors, resulting in a large cloze-style corpus. Many baseline models of cloze test reading comprehension apply BERT with random initialization to learn embedding representation. But idioms and fixed expressions are different such that the literal meaning of the phrases may or may not be consistent with their contextual meaning. Therefore, we explore different ways to combine static and contextual representations for a stronger baseline model. Experimentations show that combining definition and random initialization will better support cloze test model performance for idioms whether independently or mixed with fixed expressions. While for fixed expressions with no special meaning, static embedding with random initialization is sufficient for cloze test model.Comment: Accepted to "2022 International Conference on Asian Language Processing (IALP)

Tapping the Potential of Coherence and Syntactic Features in Neural Models for Automatic Essay Scoring

In the prompt-specific holistic score prediction task for Automatic Essay Scoring, the general approaches include pre-trained neural model, coherence model, and hybrid model that incorporate syntactic features with neural model. In this paper, we propose a novel approach to extract and represent essay coherence features with prompt-learning NSP that shows to match the state-of-the-art AES coherence model, and achieves the best performance for long essays. We apply syntactic feature dense embedding to augment BERT-based model and achieve the best performance for hybrid methodology for AES. In addition, we explore various ideas to combine coherence, syntactic information and semantic embeddings, which no previous study has done before. Our combined model also performs better than the SOTA available for combined model, even though it does not outperform our syntactic enhanced neural model. We further offer analyses that can be useful for future study.Comment: Accepted to "2022 International Conference on Asian Language Processing (IALP)

Immunization of Mice with Recombinant Protein CobB or AsnC Confers Protection against Brucella abortus Infection

Due to drawbacks of live attenuated vaccines, much more attention has been focused on screening of Brucella protective antigens as subunit vaccine candidates. Brucella is a facultative intracellular bacterium and cell mediated immunity plays essential roles for protection against Brucella infection. Identification of Brucella antigens that present T-cell epitopes to the host could enable development of such vaccines. In this study, 45 proven or putative pathogenesis-associated factors of Brucella were selected according to currently available data. After expressed and purified, 35 proteins were qualified for analysis of their abilities to stimulate T-cell responses in vitro. Then, an in vitro gamma interferon (IFN-γ) assay was used to identify potential T-cell antigens from B. abortus. In total, 7 individual proteins that stimulated strong IFN-γ responses in splenocytes from mice immunized with B. abortus live vaccine S19 were identified. The protective efficiencies of these 7 recombinant proteins were further evaluated. Mice given BAB1_1316 (CobB) or BAB1_1688 (AsnC) plus adjuvant could provide protection against virulent B. abortus infection, similarly with the known protective antigen Cu-Zn SOD and the license vaccine S19. In addition, CobB and AsnC could induce strong antibodies responses in BALB/c mice. Altogether, the present study showed that CobB or AsnC protein could be useful antigen candidates for the development of subunit vaccines against brucellosis with adequate immunogenicity and protection efficacy

A Prediction Model for Stock Market: A Comparison of The World’s Top Investors with Data Mining Method

Recently, many researches attempt to apply data mining methods to construct attractive decision support models for stock prediction. These models mainly focus on forecasting the price trend and providing advice for investors. According to the practical requirements, this paper proposes a model based on the combination of financial indicators and data mining methods to help fund managers make decision. Four industries were selected as our initial stock pool. One of the most popular data mining methods, support vector machine, was employed to construct a stock prediction model. The results indicate that our model is capable of selecting uptrend stocks. The predictive precision exceeds 60% for each industry in almost entire test period. The seven-year cumulative abnormal return exceeds 500%, much higher than the benchmark and even outperforms both Warren E. Buffett’s and William J. O’Neil’s investment methods. Although the return of our model is less than Richard Driehaus’ in some of test years, the Sharpe ratio of our model is much higher in the whole seven-year test period, which indicates that the return series that our model generated is more stable. Based on the above, a conclusion can be drawn that our model can provide sustained and effective guidance for fund managers on portfolio construction

Hyperoside Induces Breast Cancer Cells Apoptosis via ROS-Mediated NF-κB Signaling Pathway

Hyperoside (quercetin 3-o-β-d-galactopyranoside) is one of the flavonoid glycosides with anti-inflammatory, antidepressant, and anti-cancer effects. But it remains unknown whether it had effects on breast cancer. Here, different concentrations of hyperoside were used to explore its therapeutic potential in both breast cancer cells and subcutaneous homotransplant mouse model. CCK-8 and wound healing assays showed that the viability and migration capability of Michigan Cancer Foundation-7 (MCF-7) and 4T1 cells were inhibited by hyperoside, while the apoptosis of cells were increased. Real-time quantitative PCR (qRT-PCR) and western blot analysis were used to detect mRNA and the protein level, respectively, which showed decreased levels of B cell lymphoma-2 (Bcl-2) and X-linked inhibitor of apoptosis (XIAP), and increased levels of Bax and cleaved caspase-3. After exploration of the potential mechanism, we found that reactive oxygen species (ROS) production was reduced by the administration of hyperoside, which subsequently inhibited the activation of NF-κB signaling pathway. Tumor volume was significantly decreased in subcutaneous homotransplant mouse model in hyperoside-treated group, which was consistent with our study in vitro. These results indicated that hyperoside acted as an anticancer drug through ROS-related apoptosis and its mechanism included activation of the Bax–caspase-3 axis and the inhibition of the NF-κB signaling pathway

Detection of Salmonella DNA and drug-resistance mutation by PCR-based CRISPR-lbCas12a system

Abstract Salmonella is an important foodborne pathogen, which can cause serious public health problems. Rapid and accurate detection of Salmonella infection and drug resistance mutations in patients will provide timely guidance for clinical treatment and avoid disease progression and other related clinical problems. Here, we established a highly sensitive and quick method for Salmonella and drug resistance mutation detection based on polymerase chain reaction (PCR) and CRISPR-lbCas12a system and evaluated its practicability with clinical samples. Specific CRISPR RNAs (crRNAs) and primers are designed for Salmonella DNA and parC gene S80I mutation diagnosis. CrRNAs with and without phosphorylated modification and different crRNA preparation methods are used to assess the effect on the detection system. After optimization, we detected as low as one copy of Salmonella DNA and drug resistance mutation parC S80I with the Salmonella DNA standard. For 94 clinical samples, this method also showed high sensitivity (100%, 95% CI: 84.98–100%) and specificity (98.48%, 95% CI: 90.73–99.92%) with less time (3 h) than plate culture (16 h) and conventional antimicrobial susceptibility testing (over 16 h). Besides, one parC S80I mutant strain was detected, which is consistent with the result of DNA sequencing. Taken together, we established a highly sensitive and specific method for Salmonella infection and parC S80I drug resistance mutation detection with fewer reagents and ordinary instruments. This assay has wide application prospects for fast detection of pathogen (bacterium and virus) infection, drug resistance determination, and proper treatment guidance

circFBLIM1 act as a ceRNA to promote hepatocellular cancer progression by sponging miR-346

Abstract Backgroud Accumulating evidences indicate that circular RNAs (circRNAs), a class of non-coding RNAs, play important roles in tumorigenesis. However, the function of circRNAs in hepatocellular cancer (HCC) is largely unknown. Methods We performed circRNA microarrays to identify circRNAs that are aberrantly expressed in HCC tissues. Expression levels of a significantly upregulated circRNA, circFBLIM1, was detected by quantitative real-time PCR (qRT-PCR) in HCC cell lines and tissues. Then, we examined the functions of circFBLIM1 in HCC by cell proliferation, apoptosis, invasion and mouse xenograft assay. In addition, luciferase assay and RNA immunoprecipitation (RIP) assay were used to explore the miRNA sponge function of circFBLIM1 in HCC. Results Microarray analysis and qRT-PCR verified a circRNA termed circFBLIM1 that was upregulated in HCC tissues and cell lines. Knockdown of circFBLIM1 inhibited proliferation, invasion and promoted apoptosis in HCC. Via luciferase reporter assays, circFBLIM1 and FBLIM1 were observed to directly bind to miR-346. Subsequent experiments showed that circFBLIM1 and FBLIM1 regulated the expression of each other by sponging miR-346. Conclusions Taken together, we conclude that circFBLIM1 may function as a competing endogenous RNA (ceRNA) to regulate FBLIM1 expression through sponging miR-346 to exert regulatory functions in HCC. circFBLIM1 may be a diagnostic biomarker and potential target for HCC therapy

Regio- and Chemoselective Mono- and Bisnitration of 8‑Amino quinoline Amides with Fe(NO₃)₃·9H₂O as Promoter and Nitro Source

An efficient and regioselective remote C(5)–H nitration of 8-aminoquinoline amides by using the economical and nontoxic Fe­(NO₃)₃·9H₂O as promoter and nitro source has been developed. Furthermore, when CuCl₂·2H₂O was used as a catalyst, 8-aminoquinoline amides dominantly underwent bisnitration to give 5,7-dinitro-8-aminoquinoline amides. Notably, this is the first example in which Fe­(NO₃)₃·9H₂O plays a dual role as both chelating promoter and nitration reagent, and CuCl₂·2H₂O acts as an efficient catalyst for the bisnitration of quinolines