Small-molecule exhibits anti-tumor activity by targeting the RNA m6A reader IGF2BP3 in ovarian cancer.

Based on its absence in normal tissues and its role in tumorigenesis and tumor progression, insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), a reader of N6-methyladenosine (M6A) on RNA, represents a putative valuable and specific target for some cancer therapy. In this study, we performed bioinformatic analysis and immunohistochemistry (IHC) to find that IGF2BP3 was highly expressed in tumor epithelial cells and fibroblasts of ovarian cancer (OC), and was associated with poor prognosis, metastasis, and chemosensitivity in OC patients. In particular, we discovered that knockdown IGF2BP3 expression inhibited the malignant phenotype of OC cell lines by decreasing the protein levels of c-MYC, VEGF, CDK2, CDK6, and STAT1. To explore the feasibility of IGF2BP3 as a therapeutic target for OC, a small molecular AE-848 was designed and screened by molecular operating environment (MOE), which not only could duplicate the above results of knockdown assay but also reduced the expression of c-MYC in M2 macrophages and tumor-associated macrophages and promoted the cytokine IFN-γ and TNF-α secretion. The pharmacodynamic models of two kinds of OC bearing animals were suggested that systemic therapy with AE-848 significantly inhibited tumor growth by reducing the expression of tumor-associated antigen (c-MYC/VEGF/Ki67/CDK2) and improving the anti-tumor effect of macrophages. These results suggest that AE-848 can inhibit the growth and progression of OC cells by disrupting the stability of the targeted mRNAs of IGF2BP3 and may be a targeted drug for OC treatment.

Graph-Based Multi-Interaction Network for Video Question Answering.

Video question answering is an important task combining both Natural Language Processing and Computer Vision, which requires a machine to obtain a thorough understanding of the video. Most existing approaches simply capture spatio-temporal information in videos by using a combination of recurrent and convolutional neural networks. Nonetheless, most previous work focus on only salient frames or regions, which normally lacks some significant details, such as potential location and action relations. In this paper, we propose a new method called Graph-based Multi-interaction Network for video question answering. In our model, a new attention mechanism named multi-interaction is designed to capture both element-wise and segment-wise sequence interactions simultaneously, which can be found between and inside the multi-modal inputs. Moreover, we propose a graph-based relation-aware neural network to explore a more fine-grained visual representation, which could explore the relationships and dependencies between objects spatially and temporally. We evaluate our method on TGIF-QA and other two video QA datasets. The qualitative and quantitative experimental results show the effectiveness of our model, which achieves state-of-the-art performance.

Vitamin D receptor Bsm I polymorphism and osteoporosis risk in postmenopausal women: a meta-analysis from 42 studies.

OBJECTIVE: This study aimed to quantitatively summarize the evidence for VDR BsmI gene polymorphism and osteoporosis risk in postmenopausal women. MATERIALS AND METHODS: The PubMed, EMBASE, Weipu, CNKI, and Wanfang databases were searched for eligible studies. Case-control studies containing available genotype frequencies of B/b were chosen, and odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of this association. RESULTS: 4485 osteoporosis and 5490 controls were identified in our meta-analysis. In the stratified analysis, a significant association was observed between VDR BsmI gene polymorphism and osteoporosis susceptibility in Caucasians (additive model: OR = 0.809, 95% CI 0.678~0.965, p = 0.019; recessive model: OR = 0.736, 95% CI 0.568~0.955, p = 0.021; and co-dominant model: bb vs. BB OR = 0.701, 95% CI 0.511~0.962 p = 0.028), and we failed to find any significant relationship in Asians. CONCLUSION: The present meta-analysis suggests that VDR BsmI genotype is associated with increased risk of postmenopausal osteoporosis in Caucasians but not in Asians. To draw comprehensive and true conclusions, further prospective studies with larger numbers of participants worldwide are needed to examine associations between VDR BsmI polymorphism and osteoporosis in postmenopausal women.

Lack of association between interferon gamma +874 T/A polymorphism and cancer risk: an updated meta-analysis.

Interferon gamma (IFN-γ) is a potent proinflammatory cytokine which plays a pivotal role in the antiviral, antiproliferative, and antitumor activities. A T-to-A transition at the position +874 of human IFN-γ gene (IFNG) has been reported to influence the secretion of IFN-γ and affect cancer susceptibility. However, results from published studies on the association between IFNG +874 T/A polymorphism and cancer risk are inconclusive or even controversial. In order to derive a more precise estimation of the association, a meta-analysis of 38 eligible studies including 5,630 cases and 6,096 controls was conducted with odds ratio (OR) and its corresponding 95 % confidence interval (95 % CI). Overall, no significant association was detected in allelic model (A allele vs. T allele-OR = 0.96, 95 % CI, 0.86-1.08), homozygote comparison (AA vs. TT-OR = 0.97, 95 % CI, 0.79-1.21), heterozygote comparison (AT vs. TT-OR = 1.03, 95 % CI, 0.87-1.23), dominant model (AA + AT vs. TT-OR = 1.00, 95 % CI, 0.87-1.15), nor recessive model (AA vs. AT + TT-OR = 0.93, 95 % CI, 0.78-1.12). Further subgroup analyses based on ethnicity, cancer types, and Hardy-Weinberg equilibrium status failed to demonstrate any significant relationship except in African population under recessive model (AA vs. AT + TT-OR = 0.68, 95 % CI, 0.47-0.97). In conclusion, the current meta-analysis suggested that IFNG +874 T/A polymorphism may not contribute to cancer susceptibility, and further well-designed studies with large sample size are warranted to validate our conclusion.