Aberrant methylation of Polo-like kinase CpG islands in Plk4 heterozygous mice

<p>Abstract</p> <p>Background</p> <p>Hepatocellular carcinoma (HCC), one of the most common cancers world-wide occurs twice as often in men compared to women. Predisposing conditions such as alcoholism, chronic viral hepatitis, aflatoxin B1 ingestion, and cirrhosis all contribute to the development of HCC.</p> <p>Methods</p> <p>We used a combination of methylation specific PCR and bisulfite sequencing, qReal-Time PCR (qPCR), and Western blot analysis to examine epigenetic changes for the <it>Polo-like kinases </it>(<it>Plks</it>) during the development of hepatocellular carcinoma (HCC) in <it>Plk4 </it>heterozygous mice and murine embryonic fibroblasts (MEFs).</p> <p>Results</p> <p>Here we report that the promoter methylation of <it>Plk4 </it>CpG islands increases with age, was more prevalent in males and that <it>Plk4 </it>epigenetic modification and subsequent downregulation of expression was associated with the development of HCC in <it>Plk4 </it>mutant mice. Interestingly, the opposite occurs with another Plk family member, <it>Plk1 </it>which was typically hypermethylated in normal liver tissue but became hypomethylated and upregulated in liver tumours. Furthermore, upon alcohol exposure murine embryonic fibroblasts exhibited increased <it>Plk4 </it>hypermethylation and downregulation along with increased centrosome numbers and multinucleation.</p> <p>Conclusions</p> <p>These results suggest that aberrant <it>Plk </it>methylation is correlated with the development of HCC in mice.</p

Symbolic Logic meets Machine Learning: A Brief Survey in Infinite Domains

The tension between deduction and induction is perhaps the most fundamental issue in areas such as philosophy, cognition and artificial intelligence (AI). The deduction camp concerns itself with questions about the expressiveness of formal languages for capturing knowledge about the world, together with proof systems for reasoning from such knowledge bases. The learning camp attempts to generalize from examples about partial descriptions about the world. In AI, historically, these camps have loosely divided the development of the field, but advances in cross-over areas such as statistical relational learning, neuro-symbolic systems, and high-level control have illustrated that the dichotomy is not very constructive, and perhaps even ill-formed. In this article, we survey work that provides further evidence for the connections between logic and learning. Our narrative is structured in terms of three strands: logic versus learning, machine learning for logic, and logic for machine learning, but naturally, there is considerable overlap. We place an emphasis on the following "sore" point: there is a common misconception that logic is for discrete properties, whereas probability theory and machine learning, more generally, is for continuous properties. We report on results that challenge this view on the limitations of logic, and expose the role that logic can play for learning in infinite domains

c-Myc Regulates Self-Renewal in Bronchoalveolar Stem Cells

BACKGROUND: Bronchoalveolar stem cells (BASCs) located in the bronchoalveolar duct junction are thought to regenerate both bronchiolar and alveolar epithelium during homeostatic turnover and in response to injury. The mechanisms directing self-renewal in BASCs are poorly understood. METHODS: BASCs (Sca-1(+), CD34(+), CD31(-) and, CD45(-)) were isolated from adult mouse lung using FACS, and their capacity for self-renewal and differentiation were demonstrated by immunostaining. A transcription factor network of 53 genes required for pluripotency in embryonic stem cells was assessed in BASCs, Kras-initiated lung tumor tissue, and lung organogenesis by real-time PCR. c-Myc was knocked down in BASCs by infection with c-Myc shRNA lentivirus. Comprehensive miRNA and mRNA profiling for BASCs was performed, and significant miRNAs and mRNAs potentially regulated by c-Myc were identified. We explored a c-Myc regulatory network in BASCs using a number of statistical and computational approaches through two different strategies; 1) c-Myc/Max binding sites within individual gene promoters, and 2) miRNA-regulated target genes. RESULTS: c-Myc expression was upregulated in BASCs and downregulated over the time course of lung organogenesis in vivo. The depletion of c-Myc in BASCs resulted in decreased proliferation and cell death. Multiple mRNAs and miRNAs were dynamically regulated in c-Myc depleted BASCs. Among a total of 250 dynamically regulated genes in c-Myc depleted BASCs, 57 genes were identified as potential targets of miRNAs through miRBase and TargetScan-based computational mapping. A further 88 genes were identified as potential downstream targets through their c-Myc binding motif. CONCLUSION: c-Myc plays a critical role in maintaining the self-renewal capacity of lung bronchoalveolar stem cells through a combination of miRNA and transcription factor regulatory networks