Inhibition of gap junction intercellular communication is involved in silica nanoparticles-induced H9c2 cardiomyocytes apoptosis via the mitochondrial pathway.

Gap junction intercellular communication (GJIC) between cardiomyocytes is essential for synchronous heart contraction and relies on connexin-containing channels. Connexin 43 (Cx43) is a major component involved in GJIC in heart tissue, and its abnormal expression is closely associated with various cardiac diseases. Silica nanoparticles (SNPs) are known to induce cardiovascular toxicity.

Analysis of Blood Concentrations of Zinc, Germanium, and Lead and Relevant Environmental Factors in a Population Sample from Shandong Province, China.

Trace elements, including zinc (Zn) and germanium (Ge), are essential for health; deficiency or excess levels of trace elements results is harmful. As a result of industrial and agricultural production, Pb widely exists in people's living environment. It is absorbed mainly through the respiratory and digestive tracts, producing systemic harm.

[Influence of genetic polymorphisms of epoxide hydrolase 1 on metabolism of styrene in body].

Objective: To investigate the role of genetic polymorphisms of epoxide hydrolase 1 (EPHX1) in the metabolism of styrene in vivo.

Methods: Fifty-six styrene-exposed workers, who worked in the painting workshop of an enterprise for manufacturing glass fiber-reinforced plastic yachts in Shandong Province, China for over one year and were protected in approximately the same way, were selected as study subjects. The 8-hour time-weighted average concentration (8 h-TWA) of styrene and the concentrations of mandelic acid (MA) and phenyl glyoxylic acid (PGA) as urinary metabolites were measured.

[Meta-analysis of association of tumor necrosis factor alpha and transforming growth factor beta gene polymorphisms with pneumoconiosis].

Objective: To evaluate the relationship between tumor necrosis factor-alpha-238, transforming growth factor beta (509 and 869) gene polymorphisms and pneumoconiosis susceptibility.

Methods: We searched published full-text from foreign language databases including Elsevier, PubMed, Wiley Online Library, EMCC, Web of Science, chinese databases containing CNKI, VIP, Wanfang, CBM and Cochrane library to collect case-control or cohort study on gene gene polymorphisms said above with pneumoconiosis susceptibility from the year January1988 to August 2011. 28 relevant articles were selected and 20 of them met the criteria.

[The increase of micronuclei frequencies of peripheral blood lymphocyte in plywood workers exposed accumulatively to formaldehyde].

Objective: To investigate the effects of occupational exposure to formaldehyde on the micronuclei frequencies in peripheral blood lymphocytes of workers.

Methods: Two hundred thirty six plywood workers were divided into 3 exposure groups (low, middle and high) according to internal exposure biomarker (formaldehyde human serum albumin conjugate, FA-HSA), which was detected by ELISA. The concentrations of formaldehyde (FA) in air of two workshops were measure using the high performance liquid chromatography.

Proteomic analysis of pathways involved in estrogen-induced growth and apoptosis of breast cancer cells.

Background: Estrogen is a known growth promoter for estrogen receptor (ER)-positive breast cancer cells. Paradoxically, in breast cancer cells that have been chronically deprived of estrogen stimulation, re-introduction of the hormone can induce apoptosis.

Methodology/principal Findings: Here, we sought to identify signaling networks that are triggered by estradiol (E2) in isogenic MCF-7 breast cancer cells that undergo apoptosis (MCF-7:5C) versus cells that proliferate upon exposure to E2 (MCF-7).

dbOGAP - an integrated bioinformatics resource for protein O-GlcNAcylation.

Background: Protein O-GlcNAcylation (or O-GlcNAc-ylation) is an O-linked glycosylation involving the transfer of β-N-acetylglucosamine to the hydroxyl group of serine or threonine residues of proteins. Growing evidences suggest that protein O-GlcNAcylation is common and is analogous to phosphorylation in modulating broad ranges of biological processes. However, compared to phosphorylation, the amount of protein O-GlcNAcylation data is relatively limited and its annotation in databases is scarce.

Omics-based molecular target and biomarker identification.

Genomic, proteomic, and other omic-based approaches are now broadly used in biomedical research to facilitate the understanding of disease mechanisms and identification of molecular targets and biomarkers for therapeutic and diagnostic development. While the Omics technologies and bioinformatics tools for analyzing Omics data are rapidly advancing, the functional analysis and interpretation of the data remain challenging due to the inherent nature of the generally long workflows of Omics experiments. We adopt a strategy that emphasizes the use of curated knowledge resources coupled with expert-guided examination and interpretation of Omics data for the selection of potential molecular targets.

Support vector machine-based mucin-type o-linked glycosylation site prediction using enhanced sequence feature encoding.

Glycosylation is a common and complex protein post-translational modification (PTM). In particular, mucin-type O-linked glycosylation is abundant and plays important biological functions. The number of determined glycosylation sites is still small and there remains the need of accurate computational prediction for annotation and functional understanding of proteins.

Integrated Bioinformatics for Radiation-Induced Pathway Analysis from Proteomics and Microarray Data.

Functional analysis and interpretation of large-scale proteomics and gene expression data require effective use of bioinformatics tools and public knowledge resources coupled with expert-guided examination. An integrated bioinformatics approach was used to analyze cellular pathways in response to ionizing radiation. ATM, or ataxia-telangiectasia mutated , a serine-threonine protein kinase, plays critical roles in radiation responses, including cell cycle arrest and DNA repair.

A comparison study on algorithms of detecting long forms for short forms in biomedical text.

Motivation: With more and more research dedicated to literature mining in the biomedical domain, more and more systems are available for people to choose from when building literature mining applications. In this study, we focus on one specific kind of literature mining task, i.e.

Integration of bioinformatics resources for functional analysis of gene expression and proteomic data.

In the post-genome era, researchers are systematically tackling gene functions and complex regulatory processes by studying organisms on a global scale; however, a major challenge lies in the voluminous, complex, and dynamic data being maintained in heterogeneous sources, especially from proteomics experiments. Advanced computational methods are needed for integration, mining, comparative analysis, and functional interpretation of high-throughput proteomic data. In the first part of this review, we discuss aspects of data integration important for capturing all data relevant to functional analysis.

Computational analysis and identification of amino acid sites in dengue E proteins relevant to development of diagnostics and vaccines.

We have identified 72 completely conserved amino acid residues in the E protein of major groups of the Flavivirus genus by computational analyses. In the dengue species we have identified 12 highly conserved sequence regions, 186 negatively selected sites, and many dengue serotype-specific negatively selected sites. The flavivirus-conserved sites included residues involved in forming six disulfide bonds crucial for the structural integrity of the protein, the fusion motif involved in viral infectivity, and the interface residues of the oligomers.

Comparative Bioinformatics Analyses and Profiling of Lysosome-Related Organelle Proteomes.

Complete and accurate profiling of cellular organelle proteomes, while challenging, is important for the understanding of detailed cellular processes at the organelle level. Mass spectrometry technologies coupled with bioinformatics analysis provide an effective approach for protein identification and functional interpretation of organelle proteomes. In this study, we have compiled human organelle reference datasets from large-scale proteomic studies and protein databases for 7 lysosome-related organelles (LROs), as well as the endoplasmic reticulum and mitochondria, for comparative organelle proteome analysis.

Proteomic and bioinformatic characterization of the biogenesis and function of melanosomes.

Melanin, which is responsible for virtually all visible skin, hair, and eye pigmentation in humans, is synthesized, deposited, and distributed in subcellular organelles termed melanosomes. A comprehensive determination of the protein composition of this organelle has been obstructed by the melanin present. Here, we report a novel method of removing melanin that includes in-solution digestion and immobilized metal affinity chromatography (IMAC).

Dependence network modeling for biomarker identification.

Motivation: Our purpose is to develop a statistical modeling approach for cancer biomarker discovery and provide new insights into early cancer detection. We propose the concept of dependence network, apply it for identifying cancer biomarkers, and study the difference between the protein or gene samples from cancer and non-cancer subjects based on mass-spectrometry (MS) and microarray data.

Results: Three MS and two gene microarray datasets are studied.

Substring selection for biomedical document classification.

Motivation: Attribute selection is a critical step in development of document classification systems. As a standard practice, words are stemmed and the most informative ones are used as attributes in classification. Owing to high complexity of biomedical terminology, general-purpose stemming algorithms are often conservative and could also remove informative stems.

Quantitative assessment of dictionary-based protein named entity tagging.

Objective: Natural language processing (NLP) approaches have been explored to manage and mine information recorded in biological literature. A critical step for biological literature mining is biological named entity tagging (BNET) that identifies names mentioned in text and normalizes them with entries in biological databases. The aim of this study was to provide quantitative assessment of the complexity of BNET on protein entities through BioThesaurus, a thesaurus of gene/protein names for UniProt knowledgebase (UniProtKB) entries that was acquired using online resources.

[caCORE: core architecture of bioinformation on cancer research in America].

A critical factor in the advancement of biomedical research is the ease with which data can be integrated, redistributed and analyzed both within and across domains. This paper summarizes the Biomedical Information Core Infrastructure built by National Cancer Institute Center for Bioinformatics in America (NCICB). The main product from the Core Infrastructure is caCORE--cancer Common Ontologic Reference Environment, which is the infrastructure backbone supporting data management and application development at NCICB.

BioThesaurus: a web-based thesaurus of protein and gene names.

Unlabelled: BioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to protein entries in the UniProt Knowledgebase. Currently covering more than two million proteins, BioThesaurus consists of over 2.8 million names extracted from multiple molecular biological databases according to the database cross-references in iProClass.