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• More than Ten CNVs were significantly associated with early-onset Cervical cancer. • The expression analysis showed that miR-182 was significantly upregulated in Cervical tumor compared to normal. • The results showed that mitogen associated protein 3 kinase 3 (MAP3K3) and FAM83H are direct targets of miR-182. • Suggesting that miR-182 has oncogenic properties in Cervical cancer. This study was to analyses the miRNAs role in cervical cancer and possibilities of microRNA-based markers as diagnostic tools. Genome wide analysis was performed for CNV detection using PennCNV and QuantiSNP. The associated mRNA qRT-PCR detection was used to measure quantities of microRNA gene expression. More than 10 CNV regions has a significant relationship with cervical cancer risk for both CNV detection algorithms. A total of 34 CNVs was detected by QuantiSNP while it was 27 in case of PennCNV, among which 22 CNVs was found to be overlapping between these two algorithms. the mRNA was analyzed for its expression on 36 carvical tumor normal tissue pairs of four targets i.e., MAP3K3 , RIPK2 , DIRAS3 and GAS7. These infers that there was a significant downregulation of all the four genes cervical tumor. Our results showed that miR-182 can modulate the expression of FAM83H, DIRAS3, RIPK2 and MAP3K3 in cervical cancer. Therefore, indicated that miR-182 can acts through these signaling pathway in proliferation of cervical cancer cells. The expression of tumor modulator miRNAs can be controlled by miRNA replacement therapy. Several miRNAs have been used for this purpose. The modulation of various signaling pathway and proteins in cervical cancer cells by miR-182 needs further clarification. [ABSTRACT FROM AUTHOR]

NPBS (Natural Products & Biological Sources) database is a chemical data resource with relational data between natural products and biological sources, manually curated from literatures of natural product researches. The relational data link a specific species and all the natural products derived from it and contrarily link a specific natural product and all the biological sources. The biological sources cover diverse species of plant, bacterial, fungal and marine organisms; the natural molecules have proper chemical structure data and computable molecular properties and all the relational data have corresponding references. NPBS database provides a wider choice of biological sources and can be used for dereplication to prevent re-isolation and re-characterization of already known natural products. Database URL : http://www.organchem.csdb.cn/scdb/NPBS [ABSTRACT FROM AUTHOR]

Aristolochic acids are known for nephrotoxicity, and implicated in multiple cancer types such as hepatocellular carcinomas demonstrated by recent studies. Natural products that are analogues to aristolochic acids have been constantly isolated from organisms; a larger chemical space of these compounds and a wider coverage of biological sources should be determined in consideration of the potential hazard of aristolochic acid analogues and the wide distribution of their biological sources in the nature. Therefore, we carried out an in silico research of naturally occurring aristolochic acid analogues and their biological sources, as a supplement to existing studies. The result shows a chemical space of 238 naturally occurring aristolochic acid analogues that are present in 175 species of biological sources including 44 traditional medicines. With the computational estimation for toxicity and the implication in hazard assessment of a biological source with the presence of aristolochic acid analogues, we propose that additional awareness should be raised to the public for avoidance of toxic species, especially those that are used as herbal medicines and easily accessible. [ABSTRACT FROM AUTHOR]

Chemically unstable natural products are prone to show their reactivity in the procedures of extraction, purification, or identification and turn into contaminants as so-called "artifacts". However, identification of artifacts requires considerable investments in technical equipment, time, and human resources. For revealing these reactive natural products and their artifacts by computational approaches, we set up a virtual screening system to seek cases in a biochemical database. The screening system is based on deep learning models of predicting the two main classifications of conversion reactions from natural products to artifacts, namely solvolysis and oxidation. A set of result data was reviewed for checking validity of the screening system, and we screened out a batch of reactive natural products and their probable artifacts. This work provides some insights into the formations of natural product artifacts, and the result data may act as warnings regarding the improper handling of biological matrixes in multicomponent extraction. [ABSTRACT FROM AUTHOR]

Machine translation of chemical nomenclature has considerable application prospect in chemical text data processing between languages. However, rule based machine translation tools have to face significant complication in rule sets building, especially in translation of chemical names between English and Chinese, which are the two most used languages of chemical nomenclature in the world. We applied two types of neural networks in the task of chemical nomenclature translation between English and Chinese, and made a comparison with an existing rule based machine translation tool. The result shows that deep learning based approaches have a great chance to precede rule based translation tools in machine translation of chemical nomenclature between English and Chinese. [ABSTRACT FROM AUTHOR]