In 100 primary colorectal carcinomas, we demonstrate by array comparative genomic hybridization (aCGH) that 33% show DNA copy number (DCN) loss involving PARK2, the gene encoding PARKIN, the E3 ubiquitin ligase whose deficiency is responsible for a form of autosomal recessive juvenile parkinsonism. PARK2 is located on chromosome 6 (at 6q25-27), a chromosome with one of the lowest overall frequencies of DNA copy number alterations recorded in colorectal cancers. The PARK2 deletions are mostly focal (31% ∼0.5 Mb on average), heterozygous, and show maximum incidence in exons 3 and 4. As PARK2 lies within FRA6E, a large common fragile site, it has been argued that the observed DCN losses in PARK2 in cancer may represent merely the result of enforced replication of locally vulnerable DNA. However, we show that deficiency in expression of PARK2 is significantly associated with adenomatous polyposis coli (APC) deficiency in human colorectal cancer. Evidence of some PARK2 mutations and promoter hypermethylation is described. PARK2 overexpression inhibits cell proliferation in vitro. Moreover, interbreeding of Park2 heterozygous knockout mice with Apc Min mice resulted in a dramatic acceleration of intestinal adenoma development and increased polyp multiplicity. We conclude that PARK2 is a tumor suppressor gene whose haploinsufficiency cooperates with mutant APC in colorectal carcinogenesis.array | comparative genomic hybridization | mouse model | PARKIN

Octacosanol has multiple biological functions. In this study, the anti-inflammatory effect and molecular mechanism of octacosanol were evaluated by using dextran sulfate sodium (DSS)-induced ulcerative colitis model in mice and lipopolysaccharide (LPS)-stimulated mouse macrophage RAW264.7 cells. The colitis mouse model was induced by 3.0% DSS in 8-week ICR mice and octacosanol orally administered with 100 mg/kg/day. The results showed that octacosanol significantly improved the health status of mice and reduced DSS-induced pathological damage in the colonic tissues. Octacosanol obviously inhibited the mRNA and protein expression levels of pro-inflammatory factors of colonic tissues. In vitro, octacosanol administration significantly reduced the expression of mRNA or protein of pro-inflammatory cytokines and the phosphorylation of c-Jun N-terminal kinase and p38, and it also partly prevented LPS-induced translocations of NF-κB and AP-1. Octacosanol has anti-inflammatory effect, and its molecular mechanism may be involved in downregulating the expression of inflammatory factors and blocking of MAPK/NF-κB/AP-1 signaling pathway.

Ulcerative colitis is a major inflammatory bowel disease (IBD), characterized by inflammation within the gastrointestinal tract through chronic or relapsing immune system activation. The aim of this study is to investigate the potential protective effect of oat β-glucan (βG) against colitis induced by DSS in mice. Eighty mice were randomly divided into the control group (no DSS, no βG), DSS group (DSS only), DSS + L-βG group (DSS plus 500 mg per kg βG), and DSS + H-βG group (DSS plus 1000 mg per kg βG). Compared with the DSS group, administration of βG significantly reduced clinical symptoms with less weight loss, diarrhea and shortening of the colon, the severity of colitis was significantly inhibited as evidenced by the reduced disease activity index (DAI) and degree of histological damage in colon. Moreover, treatment with βG not only decreased myeloperoxidase activity (MPO), and nitric oxide (NO) and malondialdehyde (MDA) levels, but also inhibited mRNA and protein expression of pro-inflammatory factors such as TNF-α, IL-1β, IL-6 and iNOS. This suggests that oat βG in diet might exhibit an anti-inflammatory function against colitis through inhibition of expression of pro-inflammatory factors.

Background With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline.ResultsHerein, the python library PyBioMed is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions. PyBioMed is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of PyBioMed could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use PyBioMed as an integral part of data analysis projects. By using PyBioMed, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently.ConclusionPyBioMed provides various user-friendly and highly customized APIs to calculate various features of biological molecules and complex interaction samples conveniently, which aims at building integrated analysis pipelines from data acquisition, data checking, and descriptor calculation to modeling. PyBioMed is freely available at http://projects.scbdd.com/pybiomed.html.