Network Biology of Tumor Stem-like Cells Identified a Regulatory Role of CBX5 in Lung Cancer

Mounting evidence links cancers possessing stem-like properties with worse prognosis. Network biology with signal processing mechanics was explored here using expression profiles of a panel of tumor stem-like cells (TSLCs). The profiles were compared to their parental tumor cells (PTCs) and the human embryonic stem cells (hESCs), for the identification of gene chromobox homolog 5, CBX5, as a potential target for lung cancer. CBX5 was found to regulate the stem-like properties of lung TSLCs and was predictive of lung cancer prognosis. The investigation was facilitated by finding target genes based on modeling epistatic signaling mechanics via a predictive and scalable network-based survival model. Topologically-weighted measurements of CBX5 were synchronized with those of BIRC5, DNMT1, E2F1, ESR1, MLH1, MSH2, RB1, SMAD1 and TAF5. We validated our findings in another Taiwanese lung cancer cohort, as well as in knockdown experiments using sh-CBX5 RNAi both in vitro and in vivo.National Science Council (China) (NSC grant 100-2325-B-010-010-MY3/98-2314-B-010-024-MY2/97-3111-B075-001-MY3/ 96-2314-075-056-MY3)National Yang-Ming University (Ministry of Education, Aim for the Top University Plan: 96ADD122, 96ADD125, 96ADT191, 97ACD113, 97ACT302, 98ACT302, 98ACD107, 98ACT192 and Brain Research Center-3T-MRI project)))Taipei Veterans General Hospital (98-C1-099/E1-003/ER3-001)Taipei Veterans General Hospital (Joint Projects of VGHUST (98-G6-6/ 98-P1-01/99-P6-39)Chi Mei Medical Center (CMYM9801)Yen-Tjing-Ling Medical Foundation (96/97/98)Taipei City Hospital (96-002-62-092)Technology Development Program for Academia (TDPA; 98-EC-17-A-19-S2-0107)Taiwan. Department of Industrial Technology, Ministry of Economic AffairsNational Science Council (China) (NSC 101-2325-B-010 -009)Taiwan. Department of Health. Cancer Research Center of Excellence (DOH101-TD-C-111-007

DNA Sensor IFI204 Contributes to Host Defense Against Staphylococcus aureus Infection in Mice

Interferon-inducible protein (IFI204) (p204, the murine homolog of human IFI16) is known as a cytosolic DNA sensor to recognize DNA viruses and intracellular bacteria. However, little is known about its role during extracellular bacterial infection. Here we show that IFI204 is required for host defense against the infection of Staphylococcus aureus, an extracellular bacterial pathogen. IFI204 deficiency results in decreased survival, increased bacterial loads, severe organs damage, and decreased recruitment of neutrophils and macrophages. Production of several inflammatory cytokines/chemokines including IFN-β and KC is markedly decreased, as well as the related STING-IRF3 and NF-κB pathways are impaired. However, exogenous administration of recombinant KC or IFN-β is unable to rescue the susceptibility of IFI204-deficient mice, suggesting that other mechanisms rather than KC and IFN-β account for IFI204-mediated host defense. IFI204 deficiency leads to a defect in extracellular bacterial killing in macrophages and neutrophils, although bacterial engulf, and intracellular killing activity are normal. Moreover, the defect of bactericidal activity is mediated by decreased extracellular trap formation in the absence of IFI204. Adoptively transferred WT bone marrow cells significantly protect WT and IFI204-deficient recipients against Staphylococcus infection compared with transferred IFI204-deficient bone marrow cells. Hence, this study suggests that IFI204 is essential for the host defense against Staphylococcus infection

Human Streptococcus suis Outbreak, Sichuan, China

Streptococcus suis outbreak was associated with exposure to sick or dead pigs

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Segmentation of telecom customers based on customer value by decision tree model

The more the telecom services marketing paradigm evolves, the more important it becomes to retain high value customers. Traditional customer segmentation methods based on experience or ARPU (Average Revenue per User) consider neither customers' future revenue nor the cost of servicing customers of different types. Therefore, it is very difficult to effectively identify high-value customers. In this paper, we propose a novel customer segmentation method based on customer lifecycle, which includes five decision models, i.e. current value, historic value, prediction of long-term value, credit and loyalty. Due to the difficulty of quantitative computation of long-term value, credit and loyalty, a decision tree method is used to extract important parameters related to long-term value, credit and loyalty. Then a judgments matrix formulated on the basis of characteristics of data and the experience of business experts is presented. Finally a simple and practical customer value evaluation system is built. This model is applied to telecom operators in a province in China and good accuracy is achieved. (C) 2011 Elsevier Ltd. All rights reserved